<ROOT>
 <APPS_INITIALIZE_DATA>
  <USER_NAME>ENGINATICS</USER_NAME>
  <RESPONSIBILITY_KEY>SYSTEM_ADMINISTRATOR</RESPONSIBILITY_KEY>
  <APPLICATION_SHORT_NAME>SYSADMIN</APPLICATION_SHORT_NAME>
 </APPS_INITIALIZE_DATA>
<LOVS>
<!-- loader xml for Enginatics Blitz Report lov: INV Pegging -->
 <LOVS_ROW>
  <GUID>8E2FF36EDEFB79D2E0530100007F1FF2</GUID>
  <LOV_NAME>INV Pegging</LOV_NAME>
  <VALIDATE_FROM_LIST>Y</VALIDATE_FROM_LIST>
  <LOV_QUERY>select
flvv.meaning value,
null description
from
fnd_lookup_values_vl flvv
where
flvv.lookup_type=&apos;ASSEMBLY_PEGGING_CODE&apos; and
flvv.view_application_id=0 and
flvv.security_group_id=0
order by
decode(flvv.lookup_code,&apos;A&apos;,1,&apos;Y&apos;,2,&apos;B&apos;,3,&apos;I&apos;,4,&apos;X&apos;,5,&apos;N&apos;,6)</LOV_QUERY>
  <LOV_TRANSLATIONS>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>US</LANGUAGE>
   </LOV_TRANSLATIONS_ROW>
  </LOV_TRANSLATIONS>
 </LOVS_ROW>
<!-- loader xml for Enginatics Blitz Report lov: MFG Make or Buy -->
 <LOVS_ROW>
  <GUID>B0B5FC7B97ED64BCE0530100007F8BA8</GUID>
  <LOV_NAME>MFG Make or Buy</LOV_NAME>
  <VALIDATE_FROM_LIST>Y</VALIDATE_FROM_LIST>
  <LOV_QUERY>select
flvv.meaning value,
null description
from
fnd_lookup_values_vl flvv
where
flvv.lookup_type=&apos;MTL_PLANNING_MAKE_BUY&apos; and
flvv.view_application_id=700 and
flvv.security_group_id=0
order by
flvv.meaning</LOV_QUERY>
  <LOV_TRANSLATIONS>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>US</LANGUAGE>
   </LOV_TRANSLATIONS_ROW>
  </LOV_TRANSLATIONS>
 </LOVS_ROW>
<!-- loader xml for Enginatics Blitz Report lov: MSC Buyer Name -->
 <LOVS_ROW>
  <GUID>A8576D437D9C52DEE0530100007F5406</GUID>
  <LOV_NAME>MSC Buyer Name</LOV_NAME>
  <VALIDATE_FROM_LIST>Y</VALIDATE_FROM_LIST>
  <LOV_QUERY>select distinct
msi.buyer_name value,
null description
from 
msc_apps_instances@A2M_DBLINK mai,
msc_plans@A2M_DBLINK mp,
msc_plan_organizations@A2M_DBLINK mpo,
msc_system_items@A2M_DBLINK msi
where
mai.instance_code     = :$flex$.planning_instance and
mp.sr_instance_id     = mai.instance_id and
mp.compile_designator = :$flex$.plan and
mpo.sr_instance_id    = mp.sr_instance_id and
mpo.plan_id           = mp.plan_id and
(:$flex$.organization is null or
 xxen_util.contains(:$flex$.organization,mpo.organization_code) = &apos;Y&apos;
) and
msi.sr_instance_id    = mpo.sr_instance_id and 
msi.plan_id           = mpo.plan_id and 
msi.organization_id   = mpo.organization_id and 
msi.buyer_name     is not null 
order by lower(msi.buyer_name)</LOV_QUERY>
  <LOV_TRANSLATIONS>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>AR</LANGUAGE>
    <DESCRIPTION>إرجاع قائمة بأسماء المشتري ASCP
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>D</LANGUAGE>
    <DESCRIPTION>Gibt die Liste der ASCP-Käufernamen zurück
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>E</LANGUAGE>
    <DESCRIPTION>Devuelve la lista de nombres de compradores de ASCP
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>F</LANGUAGE>
    <DESCRIPTION>Renvoie la liste des noms d&apos;acheteurs de l&apos;ASCP
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>I</LANGUAGE>
    <DESCRIPTION>Restituisce l&apos;elenco dei nomi degli acquirenti ASCP
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>JA</LANGUAGE>
    <DESCRIPTION>ASCPバイヤー名のリストを返します
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>KO</LANGUAGE>
    <DESCRIPTION>ASCP 구매자 이름 목록을 반환합니다.
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>PTB</LANGUAGE>
    <DESCRIPTION>Retorna a lista de Nomes de Compradores ASCP
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>RU</LANGUAGE>
    <DESCRIPTION>Возвращает список ASCP имен покупателей
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>S</LANGUAGE>
    <DESCRIPTION>Returnerar listan över ASCP-köparnamn
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>TR</LANGUAGE>
    <DESCRIPTION>ASCP Alıcı Adlarının listesini verir
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>US</LANGUAGE>
    <DESCRIPTION>Returns the list of ASCP Buyer Names
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>ZHS</LANGUAGE>
    <DESCRIPTION>返回ASCP买方名称列表
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
  </LOV_TRANSLATIONS>
 </LOVS_ROW>
<!-- loader xml for Enginatics Blitz Report lov: MSC Category Set -->
 <LOVS_ROW>
  <GUID>A85770BE6AD052E2E0530100007F2871</GUID>
  <LOV_NAME>MSC Category Set</LOV_NAME>
  <VALIDATE_FROM_LIST>Y</VALIDATE_FROM_LIST>
  <LOV_QUERY>select
mcs.category_set_name value,
null description 
from 
msc_apps_instances@A2M_DBLINK mai,
msc_category_sets@A2M_DBLINK mcs
where 
mai.instance_code = :$flex$.planning_instance and
mai.instance_id = mcs.sr_instance_id and
exists
(select null
 from
 msc_item_categories@A2M_DBLINK mic
 where
 mic.sr_instance_id = mcs.sr_instance_id and
 mic.category_set_id = mcs.category_set_id
)  
order by 
lower(mcs.category_set_name)</LOV_QUERY>
  <LOV_TRANSLATIONS>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>AR</LANGUAGE>
    <DESCRIPTION>تُرجع قائمة مجموعات فئات ASCP</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>D</LANGUAGE>
    <DESCRIPTION>Liefert die Liste der ASCP-Kategoriesätze</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>E</LANGUAGE>
    <DESCRIPTION>Devuelve la lista de conjuntos de categorías ASCP</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>F</LANGUAGE>
    <DESCRIPTION>Retourne la liste des ensembles de catégories ASCP</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>I</LANGUAGE>
    <DESCRIPTION>Restituisce l&apos;elenco dei set di categorie ASCP</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>JA</LANGUAGE>
    <DESCRIPTION>ASCPカテゴリセットのリストを返します</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>KO</LANGUAGE>
    <DESCRIPTION>ASCP 범주 세트 목록을 반환합니다.</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>PTB</LANGUAGE>
    <DESCRIPTION>Devolve a lista dos conjuntos de categorias ASCP</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>RU</LANGUAGE>
    <DESCRIPTION>Возвращает список наборов категорий ASCP</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>S</LANGUAGE>
    <DESCRIPTION>Returnerar listan över ASCP-kategorisatser</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>TR</LANGUAGE>
    <DESCRIPTION>ASCP Kategori Kümelerinin listesini verir</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>US</LANGUAGE>
    <DESCRIPTION>Returns the list of ASCP Category Sets</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>ZHS</LANGUAGE>
    <DESCRIPTION>返回ASCP类别集的列表</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
  </LOV_TRANSLATIONS>
 </LOVS_ROW>
<!-- loader xml for Enginatics Blitz Report lov: MSC Category within a specified Category Set -->
 <LOVS_ROW>
  <GUID>A85776F7DF3D52E0E0530100007F6064</GUID>
  <LOV_NAME>MSC Category within a specified Category Set</LOV_NAME>
  <VALIDATE_FROM_LIST>Y</VALIDATE_FROM_LIST>
  <FILTER_BEFORE_DISPLAY>Y</FILTER_BEFORE_DISPLAY>
  <LOV_QUERY>select distinct
mic.category_name value,
null description
from 
msc_apps_instances@A2M_DBLINK mai,
msc_category_sets@A2M_DBLINK  mcs,
msc_item_categories@A2M_DBLINK  mic 
where 
mai.instance_code = :$flex$.planning_instance and
mai.instance_id = mcs.sr_instance_id and
mcs.category_set_name = :$flex$.category_set and
mcs.sr_instance_id = mcs.sr_instance_id and 
mcs.category_set_id = mcs.category_set_id 
order by 
lower(mic.category_name)</LOV_QUERY>
  <LOV_TRANSLATIONS>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>AR</LANGUAGE>
    <DESCRIPTION>تُرجع قائمة فئات ASCP ضمن مجموعة فئات محددة
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>D</LANGUAGE>
    <DESCRIPTION>Liefert die Liste der ASCP-Kategorien innerhalb eines angegebenen Kategorie-Sets
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>E</LANGUAGE>
    <DESCRIPTION>Devuelve la lista de categorías ASCP dentro de un conjunto de categorías especificado
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>F</LANGUAGE>
    <DESCRIPTION>Renvoie la liste des catégories ASCP dans un ensemble de catégories spécifié
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>I</LANGUAGE>
    <DESCRIPTION>Restituisce l&apos;elenco delle categorie ASCP all&apos;interno di un set di categorie specificato
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>JA</LANGUAGE>
    <DESCRIPTION>指定されたカテゴリセット内のASCPカテゴリのリストを返します。
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>KO</LANGUAGE>
    <DESCRIPTION>지정된 범주 집합 내의 ASCP 범주 목록을 반환합니다.
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>PTB</LANGUAGE>
    <DESCRIPTION>Retorna a lista de categorias ASCP dentro de um conjunto de categorias especificado
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>RU</LANGUAGE>
    <DESCRIPTION>Возвращает список категорий ASCP в пределах указанного набора категорий.
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>S</LANGUAGE>
    <DESCRIPTION>Returnerar listan över ASCP-kategorier inom en angiven kategorisats
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>TR</LANGUAGE>
    <DESCRIPTION>Belirli bir Kategori Kümesi içindeki ASCP Kategorilerinin listesini verir
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>US</LANGUAGE>
    <DESCRIPTION>Returns the list of ASCP Categories within a specified Category Set
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>ZHS</LANGUAGE>
    <DESCRIPTION>返回指定类别集中的ASCP类别列表。
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
  </LOV_TRANSLATIONS>
 </LOVS_ROW>
<!-- loader xml for Enginatics Blitz Report lov: MSC Demand Orgination Type -->
 <LOVS_ROW>
  <GUID>A8A49319B2344806E0530100007F204F</GUID>
  <LOV_NAME>MSC Demand Orgination Type</LOV_NAME>
  <VALIDATE_FROM_LIST>Y</VALIDATE_FROM_LIST>
  <LOV_QUERY>select distinct
 flv.meaning value,
 null description
from
 fnd_lookup_values@A2M_DBLINK flv
where
 flv.lookup_type IN (&apos;MSC_DEMAND_ORIGINATION&apos;) and
 flv.view_application_id = 700 and
 flv.security_group_id = 0 and
 flv.enabled_flag = &apos;Y&apos; and
 sysdate between nvl(flv.start_date_active,sysdate) and nvl(flv.end_date_active,sysdate) and
 flv.language = nvl((select fl.language_code from fnd_languages@A2M_DBLINK fl where fl.installed_flag in (&apos;B&apos;,&apos;I&apos;) and language_code = userenv(&apos;lang&apos;)),fnd_global.base_language@A2M_DBLINK)
order by
 value</LOV_QUERY>
  <LOV_TRANSLATIONS>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>AR</LANGUAGE>
    <DESCRIPTION>تُرجع قائمة أنواع إنشاء طلب ASCP
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>D</LANGUAGE>
    <DESCRIPTION>Gibt die Liste der ASCP Demand Origination Types zurück
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>E</LANGUAGE>
    <DESCRIPTION>Devuelve la lista de tipos de originación de demanda ASCP
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>F</LANGUAGE>
    <DESCRIPTION>Retourne la liste des types d&apos;origine de la demande ASCP
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>I</LANGUAGE>
    <DESCRIPTION>Restituisce l&apos;elenco dei tipi di origine della domanda ASCP
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>JA</LANGUAGE>
    <DESCRIPTION>ASCP Demand Origination Typesのリストを返します。
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>KO</LANGUAGE>
    <DESCRIPTION>ASCP 수요 발생 유형 목록을 반환합니다.
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>PTB</LANGUAGE>
    <DESCRIPTION>Devolve a lista de tipos de origem da demanda ASCP
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>RU</LANGUAGE>
    <DESCRIPTION>Возвращает список типов происхождения ASCP-требования
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>S</LANGUAGE>
    <DESCRIPTION>Returnerar listan över ASCP-behovstyper
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>TR</LANGUAGE>
    <DESCRIPTION>ASCP Talep Kaynak Türlerinin listesini verir
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>US</LANGUAGE>
    <DESCRIPTION>Returns the list of ASCP Demand Origination Types
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>ZHS</LANGUAGE>
    <DESCRIPTION>返回ASCP需求类型列表。
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
  </LOV_TRANSLATIONS>
 </LOVS_ROW>
<!-- loader xml for Enginatics Blitz Report lov: MSC Exception Type -->
 <LOVS_ROW>
  <GUID>A8619783803618A1E0530100007F1391</GUID>
  <LOV_NAME>MSC Exception Type</LOV_NAME>
  <VALIDATE_FROM_LIST>Y</VALIDATE_FROM_LIST>
  <LOV_QUERY>with q_excptn_group as
(
-- map the exception group from msc lang to local user lang
select
 flv2.meaning exception_group
from
 fnd_lookup_values@A2M_DBLINK flv1, -- in msc lang
 fnd_lookup_values flv2             -- in local user lang
where
 flv1.lookup_type = &apos;MSC_EXCEPTION_GROUP&apos; and
 flv1.meaning = :$flex$.exception_group and
 flv1.view_application_id = 700 and
 flv1.security_group_id = 0 and
 flv1.language = nvl((select fl.language_code from fnd_languages@A2M_DBLINK fl where fl.installed_flag in (&apos;B&apos;,&apos;I&apos;) and language_code = userenv(&apos;lang&apos;)),fnd_global.base_language@A2M_DBLINK) and
 flv2.lookup_type = flv1.lookup_type and
 flv2.lookup_code = flv1.lookup_code and
 flv2.view_application_id = flv1.view_application_id and
 flv2.security_group_id = flv1.security_group_id and
 flv2.language = userenv(&apos;lang&apos;)  
) 
select
 flv.meaning value
,null description
from
 fnd_lookup_values@A2M_DBLINK flv
where
 flv.lookup_type = &apos;MRP_EXCEPTION_CODE_TYPE&apos; and
 flv.view_application_id = 700 and
 flv.security_group_id = 0 and
 flv.enabled_flag = &apos;Y&apos; and
 sysdate between nvl(flv.start_date_active,sysdate) and nvl(flv.end_date_active,sysdate) and
 flv.language = nvl((select fl.language_code from fnd_languages@A2M_DBLINK fl where fl.installed_flag in (&apos;B&apos;,&apos;I&apos;) and language_code = userenv(&apos;lang&apos;)),fnd_global.base_language@A2M_DBLINK) and
 (:$flex$.exception_group is null or
  exists
  -- msc_phub_util.get_exception_group must run locally in case the user lang is not installed in the msc instance
  (select null from q_excptn_group where q_excptn_group.exception_group = msc_phub_util.get_exception_group(flv.lookup_code))
 )
order by
 lower(flv.meaning)</LOV_QUERY>
  <LOV_TRANSLATIONS>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>AR</LANGUAGE>
    <DESCRIPTION>تُرجع قائمة أنواع استثناءات ASCP</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>D</LANGUAGE>
    <DESCRIPTION>Gibt die Liste der ASCP-Exception-Typen zurück</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>E</LANGUAGE>
    <DESCRIPTION>Devuelve la lista de Tipos de Excepción ASCP</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>F</LANGUAGE>
    <DESCRIPTION>Renvoie la liste des types d&apos;exception de l&apos;ASCP</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>I</LANGUAGE>
    <DESCRIPTION>Restituisce l&apos;elenco dei tipi di eccezione ASCP</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>JA</LANGUAGE>
    <DESCRIPTION>ASCP例外タイプのリストを返します</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>KO</LANGUAGE>
    <DESCRIPTION>ASCP 예외 유형 목록을 반환합니다.</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>PTB</LANGUAGE>
    <DESCRIPTION>Retorna a lista de tipos de exceções ASCP</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>RU</LANGUAGE>
    <DESCRIPTION>Возвращает список типов исключений ASCP</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>S</LANGUAGE>
    <DESCRIPTION>Returnerar listan över ASCP-undantagstyper</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>TR</LANGUAGE>
    <DESCRIPTION>ASCP İstisna Türlerinin listesini verir</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>US</LANGUAGE>
    <DESCRIPTION>Returns the list of ASCP Exception Types</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>ZHS</LANGUAGE>
    <DESCRIPTION>返回ASCP异常类型的列表</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
  </LOV_TRANSLATIONS>
 </LOVS_ROW>
<!-- loader xml for Enginatics Blitz Report lov: MSC Excess/Safety Stock -->
 <LOVS_ROW>
  <GUID>A8A60BF8F1C24A0FE0530100007F5E32</GUID>
  <LOV_NAME>MSC Excess/Safety Stock</LOV_NAME>
  <VALIDATE_FROM_LIST>Y</VALIDATE_FROM_LIST>
  <LOV_QUERY>select
 flv.meaning value,
 null description
from
 fnd_lookup_values@A2M_DBLINK flv
where
 flv.lookup_type IN (&apos;MRP_FLP_SUPPLY_DEMAND_TYPE&apos;) and
 flv.security_group_id = 0 and
 flv.enabled_flag = &apos;Y&apos; and
 sysdate between nvl(flv.start_date_active,sysdate) and nvl(flv.end_date_active,sysdate) and
 flv.language = nvl((select fl.language_code from fnd_languages@A2M_DBLINK fl where fl.installed_flag in (&apos;B&apos;,&apos;I&apos;) and language_code = userenv(&apos;lang&apos;)),fnd_global.base_language@A2M_DBLINK) and
 to_number(flv.lookup_code) &lt; 0
order by
 value</LOV_QUERY>
  <LOV_TRANSLATIONS>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>AR</LANGUAGE>
    <DESCRIPTION>فائض / قيمة المخزون الآمن
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>D</LANGUAGE>
    <DESCRIPTION>Überschuss/Sicherheitsvorrat LOV
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>E</LANGUAGE>
    <DESCRIPTION>Exceso/Seguridad de existencias LOV
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>F</LANGUAGE>
    <DESCRIPTION>Excès / Stock de sécurité LOV
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>I</LANGUAGE>
    <DESCRIPTION>Eccesso/Scorta di sicurezza LOV
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>JA</LANGUAGE>
    <DESCRIPTION>余剰/安全在庫LOV
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>KO</LANGUAGE>
    <DESCRIPTION>초과 / 안전 재고 LOV
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>PTB</LANGUAGE>
    <DESCRIPTION>Excesso/Segurança LOV
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>RU</LANGUAGE>
    <DESCRIPTION>Избыток/Безопасный запас LOV
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>S</LANGUAGE>
    <DESCRIPTION>Överskott / säkerhet LOV
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>TR</LANGUAGE>
    <DESCRIPTION>Fazlalık / Güvenlik Stok Değer Listesi
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>US</LANGUAGE>
    <DESCRIPTION>Excess/Safety Stock LOV
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>ZHS</LANGUAGE>
    <DESCRIPTION>过剩/安全库存LOV
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
  </LOV_TRANSLATIONS>
 </LOVS_ROW>
<!-- loader xml for Enginatics Blitz Report lov: MSC Plan Name -->
 <LOVS_ROW>
  <GUID>A8452450392C6F2FE0530100007F6DF4</GUID>
  <LOV_NAME>MSC Plan Name</LOV_NAME>
  <VALIDATE_FROM_LIST>Y</VALIDATE_FROM_LIST>
  <LOV_QUERY>select 
 mp.compile_designator value
,null description
from 
 msc_plans@A2M_DBLINK mp,
 msc_apps_instances@A2M_DBLINK mai 
where mp.plan_id &gt; 0 
and mp.sr_instance_id = mai.instance_id
and mai.instance_code =:$flex$.planning_instance
order by lower(mp.compile_designator)</LOV_QUERY>
  <LOV_TRANSLATIONS>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>AR</LANGUAGE>
    <DESCRIPTION>إرجاع قائمة بأسماء خطة ASCP
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>D</LANGUAGE>
    <DESCRIPTION>Gibt die Liste der ASCP-Plan-Namen zurück
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>E</LANGUAGE>
    <DESCRIPTION>Devuelve la lista de nombres de planes ASCP
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>F</LANGUAGE>
    <DESCRIPTION>Retourne la liste des noms de plans ASCP
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>I</LANGUAGE>
    <DESCRIPTION>Restituisce l&apos;elenco dei nomi dei piani ASCP
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>JA</LANGUAGE>
    <DESCRIPTION>ASCPプラン名のリストを返します
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>KO</LANGUAGE>
    <DESCRIPTION>ASCP 계획 명 목록을 반환합니다.
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>PTB</LANGUAGE>
    <DESCRIPTION>Retorna a lista de nomes dos planos ASCP
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>RU</LANGUAGE>
    <DESCRIPTION>Возвращает список названий планов ASCP
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>S</LANGUAGE>
    <DESCRIPTION>Returnerar listan över ASCP-plannamn
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>TR</LANGUAGE>
    <DESCRIPTION>ASCP Plan Adlarının listesini verir
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>US</LANGUAGE>
    <DESCRIPTION>Returns the list of ASCP Plan Names
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>ZHS</LANGUAGE>
    <DESCRIPTION>返回ASCP计划名称的列表
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
  </LOV_TRANSLATIONS>
 </LOVS_ROW>
<!-- loader xml for Enginatics Blitz Report lov: MSC Plan Organization Codes -->
 <LOVS_ROW>
  <GUID>A84529F80CED6F4AE0530100007FD38E</GUID>
  <LOV_NAME>MSC Plan Organization Codes</LOV_NAME>
  <VALIDATE_FROM_LIST>Y</VALIDATE_FROM_LIST>
  <LOV_QUERY>select 
  mpo.organization_code value
, null description
from
  msc_trading_partners@A2M_DBLINK mtp, 
 msc_plan_organizations@A2M_DBLINK mpo,
 msc_plans@A2M_DBLINK mp,
 msc_apps_instances@A2M_DBLINK mai
where
     mp.sr_instance_id     = mpo.sr_instance_id 
and  mp.plan_id            = mpo.plan_id
and  mpo.sr_instance_id    = mai.instance_id
and  mp.compile_designator = nvl(:$flex$.plan,mp.compile_designator)
and mai.instance_code =:$flex$.planning_instance
and mtp.sr_instance_id = mpo.sr_instance_id
and mtp.partner_type = 3
and mtp.sr_tp_id = mpo.organization_id
and mtp.operating_unit_name = nvl(:$flex$.operating_unit,mtp.operating_unit_name)
order by lower(mpo.organization_code)</LOV_QUERY>
  <LOV_TRANSLATIONS>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>AR</LANGUAGE>
    <DESCRIPTION>تُرجع قائمة رموز المنظمة ضمن خطة ASCP المحددة
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>D</LANGUAGE>
    <DESCRIPTION>Gibt die Liste der Organization Codes innerhalb des angegebenen ASCP-Plans zurück
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>E</LANGUAGE>
    <DESCRIPTION>Devuelve la lista de Códigos de Organización dentro del Plan ASCP especificado
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>F</LANGUAGE>
    <DESCRIPTION>Renvoie la liste des codes d&apos;organisation dans le cadre du plan ASCP spécifié
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>I</LANGUAGE>
    <DESCRIPTION>Restituisce l&apos;elenco dei codici di organizzazione all&apos;interno del piano ASCP specificato
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>JA</LANGUAGE>
    <DESCRIPTION>指定されたASCPプラン内の組織コードのリストを返します
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>KO</LANGUAGE>
    <DESCRIPTION>지정된 ASCP 계획 내의 조직 코드 목록을 반환합니다.
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>PTB</LANGUAGE>
    <DESCRIPTION>Retorna a lista de Códigos de Organização dentro do Plano ASCP especificado
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>RU</LANGUAGE>
    <DESCRIPTION>Возвращает список организационных кодов в рамках указанного плана ППКП
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>S</LANGUAGE>
    <DESCRIPTION>Returnerar listan över organisationskoder inom den angivna ASCP-planen
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>TR</LANGUAGE>
    <DESCRIPTION>Belirtilen ASCP Planı dahilinde Organizasyon Kodlarının listesini verir
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>US</LANGUAGE>
    <DESCRIPTION>Returns the list of Organization Codes within the specified ASCP Plan
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>ZHS</LANGUAGE>
    <DESCRIPTION>返回指定ASCP计划中的组织代码列表。
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
  </LOV_TRANSLATIONS>
 </LOVS_ROW>
<!-- loader xml for Enginatics Blitz Report lov: MSC Planned Item -->
 <LOVS_ROW>
  <GUID>A844FAB91C4F7309E0530100007F496B</GUID>
  <LOV_NAME>MSC Planned Item</LOV_NAME>
  <VALIDATE_FROM_LIST>Y</VALIDATE_FROM_LIST>
  <FILTER_BEFORE_DISPLAY>Y</FILTER_BEFORE_DISPLAY>
  <LOV_QUERY>select 
msi.item_name value,
min(msi.description) description
from
msc_system_items@A2M_DBLINK msi,
msc_plans@A2M_DBLINK mp, 
msc_apps_instances@A2M_DBLINK mai 
where
msi.sr_instance_id = mai.instance_id and
msi.plan_id = mp.plan_id and
mp.sr_instance_id  = mai.instance_id and
mp.compile_designator = nvl(:$flex$.plan,mp.compile_designator) and
mai.instance_code =:$flex$.planning_instance
group by 
msi.item_name
order by
lower(msi.item_name)</LOV_QUERY>
  <LOV_TRANSLATIONS>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>AR</LANGUAGE>
    <DESCRIPTION>تُرجع قائمة عناصر ASCP المخططة</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>D</LANGUAGE>
    <DESCRIPTION>Liefert die Liste der ASCP Planned Items</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>E</LANGUAGE>
    <DESCRIPTION>Devuelve la lista de elementos planificados de ASCP</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>F</LANGUAGE>
    <DESCRIPTION>Renvoie la liste des articles prévus par l&apos;ASCP</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>I</LANGUAGE>
    <DESCRIPTION>Restituisce l&apos;elenco degli elementi pianificati ASCP</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>JA</LANGUAGE>
    <DESCRIPTION>ASCP 予定項目のリストを返します</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>KO</LANGUAGE>
    <DESCRIPTION>ASCP 계획 품목 목록을 반환합니다.</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>PTB</LANGUAGE>
    <DESCRIPTION>Retorna a lista de itens planejados da ASCP</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>RU</LANGUAGE>
    <DESCRIPTION>Возвращает список запланированных элементов ППКП</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>S</LANGUAGE>
    <DESCRIPTION>Returnerar listan över ASCP-planerade objekt</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>TR</LANGUAGE>
    <DESCRIPTION>ASCP Planlanan Öğelerin listesini döndürür</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>US</LANGUAGE>
    <DESCRIPTION>Returns the list of ASCP Planned Items</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>ZHS</LANGUAGE>
    <DESCRIPTION>返回ASCP计划项目的列表</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
  </LOV_TRANSLATIONS>
 </LOVS_ROW>
<!-- loader xml for Enginatics Blitz Report lov: MSC Planner Code -->
 <LOVS_ROW>
  <GUID>A85765FE708251D8E0530100007FCD1D</GUID>
  <LOV_NAME>MSC Planner Code</LOV_NAME>
  <VALIDATE_FROM_LIST>Y</VALIDATE_FROM_LIST>
  <LOV_QUERY>select distinct
mpl.planner_code value,
null description 
from 
msc_apps_instances@A2M_DBLINK mai, 
msc_plans@A2M_DBLINK mp, 
msc_plan_organizations@A2M_DBLINK mpo,
msc_planners@A2M_DBLINK mpl
where
mai.instance_code     = :$flex$.planning_instance and
mp.sr_instance_id     = mai.instance_id and
mp.compile_designator = :$flex$.plan and
mpo.sr_instance_id    = mp.sr_instance_id and
mpo.plan_id           = mp.plan_id and
(:$flex$.organization is null or
 xxen_util.contains(:$flex$.organization,mpo.organization_code) = &apos;Y&apos;
) and
mpl.sr_instance_id    = mpo.sr_instance_id and
mpl.organization_id   = mpo.organization_id
order by lower(mpl.planner_code)</LOV_QUERY>
  <LOV_TRANSLATIONS>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>AR</LANGUAGE>
    <DESCRIPTION>تُرجع قائمة رموز مخطط ASCP</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>D</LANGUAGE>
    <DESCRIPTION>Gibt die Liste der ASCP Planner Codes zurück</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>E</LANGUAGE>
    <DESCRIPTION>Devuelve la lista de los códigos de planificación ASCP</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>F</LANGUAGE>
    <DESCRIPTION>Renvoie la liste des codes de planificateurs de l&apos;ASCP</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>I</LANGUAGE>
    <DESCRIPTION>Restituisce l&apos;elenco dei codici ASCP Planner</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>JA</LANGUAGE>
    <DESCRIPTION>ASCPプランナーコードのリストを返します。</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>KO</LANGUAGE>
    <DESCRIPTION>ASCP 계획자 코드 목록을 반환합니다.</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>PTB</LANGUAGE>
    <DESCRIPTION>Retorna a lista de Códigos de Planejamento ASCP</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>RU</LANGUAGE>
    <DESCRIPTION>Возвращает список кодов Планировщика ASCP</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>S</LANGUAGE>
    <DESCRIPTION>Returnerar listan över ASCP-planeringskoder</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>TR</LANGUAGE>
    <DESCRIPTION>ASCP Planlayıcı Kodlarının listesini döndürür</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>US</LANGUAGE>
    <DESCRIPTION>Returns the list of ASCP Planner Codes</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>ZHS</LANGUAGE>
    <DESCRIPTION>返回ASCP规划师代码的列表。</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
  </LOV_TRANSLATIONS>
 </LOVS_ROW>
<!-- loader xml for Enginatics Blitz Report lov: MSC Planning Instance -->
 <LOVS_ROW>
  <GUID>A8454EC5D1EB6FE9E0530100007F0874</GUID>
  <LOV_NAME>MSC Planning Instance</LOV_NAME>
  <VALIDATE_FROM_LIST>Y</VALIDATE_FROM_LIST>
  <LOV_QUERY>select
 instance_code value
,null description 
from
 (
  select instance_code from msc_apps_instances
  union
  select instance_code from mrp_ap_apps_instances_all 
 )
order by instance_code</LOV_QUERY>
  <LOV_TRANSLATIONS>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>AR</LANGUAGE>
    <DESCRIPTION>تُرجع قائمة مثيلات تخطيط ASCP
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>D</LANGUAGE>
    <DESCRIPTION>Gibt die Liste der ASCP-Planungsinstanzen zurück
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>E</LANGUAGE>
    <DESCRIPTION>Devuelve la lista de instancias de planificación ASCP
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>F</LANGUAGE>
    <DESCRIPTION>Renvoie la liste des instances de planification de l&apos;ASCP
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>I</LANGUAGE>
    <DESCRIPTION>Restituisce l&apos;elenco delle istanze di pianificazione ASCP
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>JA</LANGUAGE>
    <DESCRIPTION>ASCPプランニングインスタンスのリストを返します
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>KO</LANGUAGE>
    <DESCRIPTION>ASCP 계획 인스턴스 목록을 반환합니다.
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>PTB</LANGUAGE>
    <DESCRIPTION>Retorna a lista de Instâncias de Planejamento ASCP
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>RU</LANGUAGE>
    <DESCRIPTION>Возвращает список случаев планирования ASCP
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>S</LANGUAGE>
    <DESCRIPTION>Returnerar listan över ASCP-planeringsinstanser
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>TR</LANGUAGE>
    <DESCRIPTION>ASCP Planlama Örneklerinin listesini verir
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>US</LANGUAGE>
    <DESCRIPTION>Returns the list of ASCP Planning Instances
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>ZHS</LANGUAGE>
    <DESCRIPTION>返回ASCP规划实例的列表
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
  </LOV_TRANSLATIONS>
 </LOVS_ROW>
<!-- loader xml for Enginatics Blitz Report lov: MSC Supply Order Type -->
 <LOVS_ROW>
  <GUID>A8A48FF5451C47EBE0530100007F79A0</GUID>
  <LOV_NAME>MSC Supply Order Type</LOV_NAME>
  <VALIDATE_FROM_LIST>Y</VALIDATE_FROM_LIST>
  <LOV_QUERY>select
 flv.meaning value,
 null description
from
 fnd_lookup_values@A2M_DBLINK flv
where
 flv.lookup_type IN (&apos;MRP_ORDER_TYPE&apos;) and
 flv.security_group_id = 0 and
 flv.enabled_flag = &apos;Y&apos; and
 sysdate between nvl(flv.start_date_active,sysdate) and nvl(flv.end_date_active,sysdate) and
 flv.language = nvl((select fl.language_code from fnd_languages@A2M_DBLINK fl where fl.installed_flag in (&apos;B&apos;,&apos;I&apos;) and language_code = userenv(&apos;lang&apos;)),fnd_global.base_language@A2M_DBLINK)
order by
 value</LOV_QUERY>
  <LOV_TRANSLATIONS>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>AR</LANGUAGE>
    <DESCRIPTION>تُرجع قائمة أنواع أوامر التوريد ASCP
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>D</LANGUAGE>
    <DESCRIPTION>Gibt die Liste der ASCP Supply Order Types zurück
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>E</LANGUAGE>
    <DESCRIPTION>Devuelve la lista de tipos de pedidos de suministros ASCP
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>F</LANGUAGE>
    <DESCRIPTION>Renvoie la liste des types de commandes de fournitures de l&apos;ASCP
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>I</LANGUAGE>
    <DESCRIPTION>Restituisce l&apos;elenco dei tipi di ordine di fornitura ASCP
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>JA</LANGUAGE>
    <DESCRIPTION>ASCPサプライオーダータイプのリストを返します
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>KO</LANGUAGE>
    <DESCRIPTION>ASCP 공급 주문 유형 목록을 반환합니다.
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>PTB</LANGUAGE>
    <DESCRIPTION>Retorna a lista de tipos de pedidos de fornecimento ASCP
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>RU</LANGUAGE>
    <DESCRIPTION>Возвращает список типов заказов на поставку ASCP
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>S</LANGUAGE>
    <DESCRIPTION>Returnerar listan över ASCP-leveransbeställningstyper
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>TR</LANGUAGE>
    <DESCRIPTION>ASCP Tedarik Siparişi Türlerinin listesini verir
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>US</LANGUAGE>
    <DESCRIPTION>Returns the list of ASCP Supply Order Types
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>ZHS</LANGUAGE>
    <DESCRIPTION>返回ASCP供应订单类型的列表
</DESCRIPTION>
   </LOV_TRANSLATIONS_ROW>
  </LOV_TRANSLATIONS>
 </LOVS_ROW>
<!-- loader xml for Enginatics Blitz Report lov: Yes -->
 <LOVS_ROW>
  <GUID>8E2FF36EDEA679D2E0530100007F1FF2</GUID>
  <LOV_NAME>Yes</LOV_NAME>
  <VALIDATE_FROM_LIST>Y</VALIDATE_FROM_LIST>
  <LOV_QUERY>select &apos;Y&apos; id, xxen_util.meaning(&apos;Y&apos;,&apos;YES_NO&apos;,0) value, null description from dual</LOV_QUERY>
  <LOV_TRANSLATIONS>
   <LOV_TRANSLATIONS_ROW>
    <LANGUAGE>US</LANGUAGE>
   </LOV_TRANSLATIONS_ROW>
  </LOV_TRANSLATIONS>
 </LOVS_ROW>
</LOVS>
<REPORTS>
<!-- loader xml for Enginatics Blitz Report: MSC Pegging Hierarchy -->
 <REPORTS_ROW>
  <GUID>E0249A65F7E4438FE05362FB09052547</GUID>
  <SQL_TEXT>with
q_msc_full_pegging as
(
 select
  level-1 level_,
  rownum seq,
  substr(sys_connect_by_path(msi.item_name,&apos;-&gt; &apos;),4) item_path,
  substr(sys_connect_by_path(replace(msi.description,&apos;-&gt; &apos;,&apos;-&gt;&apos;),&apos;-&gt; &apos;),4) item_description_path,
  msi.item_name,
  msi.description item_description,
  msi.planner_code,
  msi.planning_make_buy_code,
  msi.buyer_name,
  msi.uom_code,
  msi.end_assembly_pegging_flag,
  msi.bom_item_type,
  decode(msi.min_minmax_quantity,0,to_number(null),msi.min_minmax_quantity) min_minmax_quantity,
  msi.preprocessing_lead_time,
  msi.cum_manufacturing_lead_time,
  msi.cumulative_total_lead_time,
  msi.postprocessing_lead_time,
  msi.base_item_id,
  msi.wip_supply_type,
  msi.planning_exception_set,
  msi.release_time_fence_code,
  msi.critical_component_flag,
  msi.mrp_planning_code,
  msi.lots_exist,
  msi.in_source_plan,
  msi.sr_inventory_item_id,
  mfp.*
 from
  (select
    mfp.*
   from
    msc_full_pegging&amp;a2m_dblink mfp
   where
     2=2
  ) mfp,
  msc_system_items&amp;a2m_dblink msi
 where
     mfp.sr_instance_id    = msi.sr_instance_id (+)
 and mfp.plan_id           = msi.plan_id (+)
 and mfp.organization_id   = msi.organization_id (+)
 and mfp.inventory_item_id = msi.inventory_item_id (+)
 connect by
  prior mfp.pegging_id=mfp.prev_pegging_id and
  prior mfp.sr_instance_id=mfp.sr_instance_id and
  prior mfp.plan_id=mfp.plan_id
  &amp;show_source_org_pegging
 start with
  3=3 and
  (   mfp.prev_pegging_id is null
   or not exists (select null
                  from   msc_full_pegging&amp;a2m_dblink mfp2
                  where  mfp2.sr_instance_id = mfp.sr_instance_id
                  and    mfp2.plan_id = mfp.plan_id
                  and    mfp2.pegging_id = mfp.prev_pegging_id
                  &amp;org_restriction
                 )
  )
)
----------------------------------------------------
-- Main Query Starts Here
----------------------------------------------------
select
y.*,
--
-- tree view columns
--
y.end_assembly || &apos;|&apos; || y.end_demand_origination || &apos;|&apos; || y.end_demand_order_number || &apos;|&apos; || to_char(y.end_peg_demand_date,&apos;YYYY/MM/DD&apos;) tv_eao_key,
case nvl(end_assembly_plan_ord_qoh_sts,&apos;N/A&apos;)
when &apos;Full&apos; then &apos;1 Full&apos;
when &apos;Partial&apos; then &apos;2 Partial&apos;
when &apos;None&apos; then &apos;3 None&apos;
else &apos;4 N/A&apos;
end tv_ea_po_qohs
from
(
select
 nvl(:p_instance_code,x.instance) instance,
 nvl(:p_plan_name,x.plan) plan,
 --
 -- end peg demand
 --
 x.end_assembly,
 x.end_peg_demand_organization,
 x.end_peg_demand_project,
 x.end_peg_demand_task,
 &amp;lp_custom_attributes
 --
 x.end_demand_origination || nvl2(x.end_peg_other_supply_type,&apos;/&apos;||x.end_peg_other_supply_type,null) end_peg_demand_origination,
 nvl(x.end_demand_order_number,nvl2(x.end_peg_other_supply_order,x.end_peg_other_supply_order,null)) end_peg_demand_order_number,
 --
 x.end_demand_origination,
 x.end_demand_order_number,
 --
 x.end_demand_order_qty,
 x.end_peg_demand_qty,
 --
 x.end_peg_demand_date,
 x.end_peg_supply_date,
 x.end_peg_days_late,
 --
 x.end_demand_priority,
 x.end_demand_due_date,
 x.end_demand_sugg_due_date,
 x.end_demand_req_ship_date,
 x.end_demand_days_late,
 --
 case
 when x.end_peg_demand_id &gt; 0 and x.end_assembly is not null
 then
  case
  when max(x.po_qoh_fulfillment) over (partition by x.end_demand_origination,end_demand_order_number,x.end_peg_demand_date,x.end_assembly) !=
       min(x.po_qoh_fulfillment) over (partition by x.end_demand_origination,end_demand_order_number,x.end_peg_demand_date,x.end_assembly)
  then &apos;Partial&apos;
  when max(x.po_qoh_fulfillment) over (partition by x.end_demand_origination,end_demand_order_number,x.end_peg_demand_date,x.end_assembly) = 1
  then &apos;Full&apos;
  else &apos;None&apos;
  end
 else
  null
 end end_assembly_plan_ord_qoh_sts,
 --
 case
 when max(x.po_qoh_fulfillment) over (partition by x.end_pegging_id) !=
      min(x.po_qoh_fulfillment) over (partition by x.end_pegging_id)
 then &apos;Partial&apos;
 when max(x.po_qoh_fulfillment) over (partition by x.end_pegging_id) = 1
 then &apos;Full&apos;
 else &apos;None&apos;
 end end_peg_plan_ord_qoh_sts,
 --
 x.demand_organization,
 x.source_organization,
 lpad(&apos; &apos;,2*(x.level_))||(x.level_) peg_level,
 lpad(&apos; &apos;,2*(x.level_))||x.item  pegged_item,
 x.item_path item_path,
 x.item_description item_description,
 x.uom uom,
 -- pegging info
 x.peg_days_late,
 x.peg_demand_origination_type || nvl2(x.peg_other_supply_type,&apos;/&apos;||x.peg_other_supply_type,null) peg_demand_origination,
 nvl(x.demand_order_number,nvl2(x.supply_order_number,/*&apos;/&apos;||*/x.supply_order_number,null)) peg_demand_order,
 x.peg_demand_date,
 x.peg_demand_qty,
 x.peg_pegged_qty,
 x.peg_supply_qty,
 x.peg_supply_type,
 x.supply_order_number peg_supply_order,
 x.peg_supply_date,
 case when x.peg_supply_type_id = 5
 then
  case max(nvl(x.supply_qoh_fulfillment,-1)) over (partition by x.peg_supply_type,x.supply_order_number,x.peg_supply_date)
  when -1 then null
  when min(x.supply_qoh_fulfillment) over (partition by x.peg_supply_type,x.supply_order_number,x.peg_supply_date)
  then case max(x.supply_qoh_fulfillment) over (partition by x.peg_supply_type,x.supply_order_number,x.peg_supply_date)
       when 1   then &apos;Full&apos;
       when 0.5 then &apos;Partial&apos;
                else &apos;None&apos;
       end
  else &apos;Partial&apos;
  end
 else
  null
 end supply_plan_ord_qoh_sts,
 x.supply_action,
 x.supply_reschedule_date,
 -- item details
 x.category_set_name,
 x.category_name,
 x.planner_code,
 x.buyer_name,
 x.make_buy,
 x.bom_item_type,
 x.is_bom,
 x.safety_stock,
 x.pegging_type,
 x.min_minmax_quantity,
 x.preprocessing_lead_time,
 x.cum_manufacturing_lead_time,
 x.cumulative_total_lead_time,
 x.postprocessing_lead_time,
 -- demand details
 x.demand_project,
 x.demand_task,
 nvl(x.demand_origination_type,x.peg_demand_origination_type || nvl2(x.peg_other_supply_type,&apos;/&apos;||x.peg_other_supply_type,null)) demand_origination,
 x.demand_order_number,
 x.demand_order_qty,
 x.demand_priority,
 x.demand_due_date,
 x.demand_days_late,
 x.demand_sugg_due_date,
 x.demand_need_by_date,
 x.demand_req_ship_date,
 x.demand_sch_ship_date,
 x.demand_customer,
 x.demand_customer_site,
 x.demand_ship_set,
 -- supply details
 x.supply_project,
 x.supply_task,
 x.supply_order_type,
 x.supply_order_number,
 x.supply_line_num,
 x.supply_order_qty,
 x.supply_firm_qty,
 x.supply_due_date,
 x.supply_days_late,
 x.supply_sugg_due_date,
 x.supply_firm_date,
 x.supply_old_need_by_date,
 x.supply_need_by_date,
 x.supply_promise_date,
 x.supply_wip_status,
 x.supply_vendor,
 x.supply_vendor_site,
 -- exceptions
 x.planning_exception_set,
 x.exceptions,
 -- item dff attributes
 &amp;lp_end_ass_dff_cols
 &amp;lp_item_dff_cols
 -- ids
 x.end_pegging_id,
 x.pegging_id,
 x.prev_pegging_id,
 x.demand_id,
 x.transaction_id,
 x.peg_supply_type_id,
 x.demand_origination_type_id,
 x.supply_order_type_id,
 x.peg_end_item_usage,
 --
 x.level_ &quot;Level&quot;,
 x.item item,
 x.item_description_path item_description_path,
 x.seq,
 x.is_end_peg,
 x.po_qoh_fulfillment,
 -- For Pivot to control the supply type ordering as 1.Onhand 2.Planned Supply 3.Existing Supply
 case
 when x.peg_supply_type_id = 18 then &apos;1 &apos;
 when x.peg_supply_type_id in (5,13,51,76,77,78,79) then &apos;2 &apos;
 else &apos;3 &apos; end || x.peg_supply_type peg_supply_type_label
from
-- start x
(select
  mfp.sr_instance_id,
  mfp.plan_id,
  mai.instance_code                                        instance,
  mp.compile_designator                                    plan,
  mfp.demand_id,
  mfp.transaction_id,
  mfp.pegging_id,
  mfp.prev_pegging_id,
  mfp.end_pegging_id,
  mfp.seq,
  mfp.organization_id,
  mfp.inventory_item_id,
  mfp.sr_inventory_item_id,
  --
  mfp.level_,
  mpo.organization_code                                    demand_organization,
  mfp.item_name                                            item,
  mfp.item_description                                     item_description,
  mfp.item_path                                            item_path,
  mfp.item_description_path                                item_description_path,
  mfp.uom_code                                             uom,
  xxen_util.meaning(mfp.end_assembly_pegging_flag,&apos;ASSEMBLY_PEGGING_CODE&apos;,0)
                                                           pegging_type,
  mfp.planner_code                                         planner_code,
  mfp.buyer_name                                           buyer_name,
  mcs.category_set_name                                    category_set_name,
  mic.category_name                                        category_name,
  msc_get_name.lookup_meaning&amp;a2m_dblink (&apos;MTL_PLANNING_MAKE_BUY&apos;,mfp.planning_make_buy_code)
                                                           make_buy,
  msc_get_name.lookup_meaning&amp;a2m_dblink (&apos;BOM_ITEM_TYPE&apos;,mfp.bom_item_type)
                                                           bom_item_type,
  mfp.min_minmax_quantity,
  mfp.preprocessing_lead_time,
  mfp.cum_manufacturing_lead_time,
  mfp.cumulative_total_lead_time,
  mfp.postprocessing_lead_time,
  nvl((select
        &apos;Y&apos;
       from
        msc_boms&amp;a2m_dblink mb
       where
           mb.sr_instance_id   = mfp.sr_instance_id
       and mb.plan_id          = mfp.plan_id
       and mb.organization_id  = mfp.organization_id
       and mb.assembly_item_id = nvl(md.using_assembly_item_id,mfp.inventory_item_id)
       and rownum=1
      ),&apos;N&apos;)                                               is_bom,
  (select distinct
    max(mss.safety_stock_quantity) keep (dense_rank last order by mss.period_start_date) over (partition by mss.organization_id,mss.inventory_item_id) safety_stock
   from
    msc_safety_stocks&amp;a2m_dblink mss
   where
       mss.sr_instance_id     = mfp.sr_instance_id
   and mss.plan_id            = mfp.plan_id
   and mss.organization_id    = mfp.organization_id
   and mss.inventory_item_id  = mfp.inventory_item_id
   and mss.period_start_date &lt;= sysdate
  ) safety_stock,
  -- pegginq types / quantities
  case when mfp.demand_id &lt; 0
  then msc_get_name.lookup_meaning&amp;a2m_dblink (&apos;MRP_FLP_SUPPLY_DEMAND_TYPE&apos;,mfp.demand_id)
  else msc_get_name.lookup_meaning&amp;a2m_dblink (&apos;MSC_DEMAND_ORIGINATION&apos;,decode(md.origination_type, 70, 50, 92, 50, md.origination_type))
  end                                                      peg_demand_origination_type,
  case
  when mfp.demand_id &lt; 0
  then msc_get_name.lookup_meaning&amp;a2m_dblink (&apos;MRP_FLP_SUPPLY_DEMAND_TYPE&apos;,mfp.demand_id)
  when mfp.end_origination_type &lt; 0
  then msc_get_name.lookup_meaning&amp;a2m_dblink (&apos;MRP_FLP_SUPPLY_DEMAND_TYPE&apos;,mfp.end_origination_type)
  else msc_get_name.lookup_meaning&amp;a2m_dblink (&apos;MSC_DEMAND_ORIGINATION&apos;,mfp.end_origination_type)
  end                                                      peg_demand_end_origination,
  mfp.supply_type                                          peg_supply_type_id,
  case
  when mfp.supply_type &lt; 0
  then msc_get_name.lookup_meaning&amp;a2m_dblink (&apos;MRP_FLP_SUPPLY_DEMAND_TYPE&apos;,mfp.demand_id)
  else msc_get_name.lookup_meaning&amp;a2m_dblink (&apos;MRP_ORDER_TYPE&apos;,mfp.supply_type)
  end                                                      peg_supply_type,
  case
  when mfp.demand_id &lt; 0 and mfp.prev_pegging_id is null and mfp.supply_type &lt; 0
  then msc_get_name.lookup_meaning&amp;a2m_dblink (&apos;MRP_FLP_SUPPLY_DEMAND_TYPE&apos;,mfp.supply_type)
  when mfp.demand_id &lt; 0 and mfp.prev_pegging_id is null and mfp.supply_type &gt; 0
  then msc_get_name.lookup_meaning&amp;a2m_dblink (&apos;MRP_ORDER_TYPE&apos;,mfp.supply_type)
  else null
  end                                                      peg_other_supply_type,
  case
  when mfp.demand_id = -1 and mfp.prev_pegging_id is null and mfp.supply_type &lt; 0
  then msc_get_name.lookup_meaning&amp;a2m_dblink (&apos;MRP_FLP_SUPPLY_DEMAND_TYPE&apos;,mfp.supply_type)
  when mfp.demand_id = -1 and mfp.prev_pegging_id is null and mfp.supply_type &gt; 0
  then msc_get_name.lookup_meaning&amp;a2m_dblink (&apos;MRP_ORDER_TYPE&apos;,mfp.supply_type)
  else null
  end                                                      peg_excess_supply_type,
  mfp.demand_quantity                                      peg_demand_qty,
  mfp.supply_quantity                                      peg_supply_qty,
  mfp.allocated_quantity                                   peg_pegged_qty,
  trunc(mfp.demand_date)                                   peg_demand_date,
  trunc(mfp.supply_date)                                   peg_supply_date,
  mfp.end_item_usage                                       peg_end_item_usage,
  case when trunc(mfp.supply_date) &lt;= trunc(mfp.demand_date)
  then to_number(null)
  else trunc(mfp.supply_date) - trunc(mfp.demand_date)
  end                                                      peg_days_late,
  --
  -- Planned Order QOH Fulfillment
  --
  case
  when mfp.supply_type = 18 -- onhand
  then 1
  when mfp.supply_type = 5 -- planned order
  then
    case
    when :show_source_org_pegging = &apos;N&apos;
    and  0 &lt; (select count(*) from msc_full_pegging&amp;a2m_dblink mfp2 where mfp2.sr_instance_id = mfp.sr_instance_id and mfp2.plan_id = mfp.plan_id and mfp2.prev_pegging_id = mfp.pegging_id and mfp2.organization_id != mfp.organization_id)
    then 0 -- planned order demand in a different source org and source org pegging is not being show =&gt; no visibility if planned order can be fullfilled from onhand in the soure org.
    when 0 = (select count(*) from msc_full_pegging&amp;a2m_dblink mfp2 where mfp2.sr_instance_id = mfp.sr_instance_id and mfp2.plan_id = mfp.plan_id and mfp2.prev_pegging_id = mfp.pegging_id)
    then 0 -- no planned order demand.
    else to_number(null) -- planned order with planned order demand. Ignore the Planned order and determine QOH fulfillment from the Planned Order Demand
    end
  else 0
  end                                                      po_qoh_fulfillment,
  --
  case when mfp.supply_type in (5) -- Planned Order
  then
   nvl(
   (select distinct
     case
     when max(
              case
              when mfp2.supply_type = 18 -- onhand
              then 1
              when mfp2.supply_type = 5 -- planned order
              then
                case
                when :show_source_org_pegging = &apos;N&apos;
                and  0 &lt; (select count(*) from msc_full_pegging&amp;a2m_dblink mfp3 where mfp3.sr_instance_id = mfp2.sr_instance_id and mfp3.plan_id = mfp2.plan_id and mfp3.prev_pegging_id = mfp2.pegging_id and mfp3.organization_id != mfp2.organization_id)
                then 0 -- planned order demand in a different source org and source org pegging is not being show =&gt; no visibility if planned order can be fullfilled from onhand in the soure org.
                when 0 = (select count(*) from msc_full_pegging&amp;a2m_dblink mfp3 where mfp3.sr_instance_id = mfp2.sr_instance_id and mfp3.plan_id = mfp2.plan_id and mfp3.prev_pegging_id = mfp2.pegging_id)
                then 0 -- no planned order demand.
                else to_number(null) -- planned order with planned order demand. Ignore the Planned order and determine QOH fulfillment from the Planned Order Demand
                end
              else 0
              end
             ) over () !=
          min(
              case
              when mfp2.supply_type = 18 -- onhand
              then 1
              when mfp2.supply_type = 5 -- planned order
              then
                case
                when :show_source_org_pegging = &apos;N&apos;
                and  0 &lt; (select count(*) from msc_full_pegging&amp;a2m_dblink mfp3 where mfp3.sr_instance_id = mfp2.sr_instance_id and mfp3.plan_id = mfp2.plan_id and mfp3.prev_pegging_id = mfp2.pegging_id and mfp3.organization_id != mfp2.organization_id)
                then 0 -- planned order demand in a different source org and source org pegging is not being show =&gt; no visibility if planned order can be fullfilled from onhand in the soure org.
                when 0 = (select count(*) from msc_full_pegging&amp;a2m_dblink mfp3 where mfp3.sr_instance_id = mfp2.sr_instance_id and mfp3.plan_id = mfp2.plan_id and mfp3.prev_pegging_id = mfp2.pegging_id)
                then 0 -- no planned order demand.
                else to_number(null) -- planned order with planned order demand. Ignore the Planned order and determine QOH fulfillment from the Planned Order Demand
                end
              else 0
              end
             ) over ()
     then 0.5 --Partial
     when max(
              case
              when mfp2.supply_type = 18 -- onhand
              then 1
              when mfp2.supply_type = 5 -- planned order
              then
                case
                when :show_source_org_pegging = &apos;N&apos;
                and  0 &lt; (select count(*) from msc_full_pegging&amp;a2m_dblink mfp3 where mfp3.sr_instance_id = mfp2.sr_instance_id and mfp3.plan_id = mfp2.plan_id and mfp3.prev_pegging_id = mfp2.pegging_id and mfp3.organization_id != mfp2.organization_id)
                then 0 -- planned order demand in a different source org and source org pegging is not being show =&gt; no visibility if planned order can be fullfilled from onhand in the soure org.
                when 0 = (select count(*) from msc_full_pegging&amp;a2m_dblink mfp3 where mfp3.sr_instance_id = mfp2.sr_instance_id and mfp3.plan_id = mfp2.plan_id and mfp3.prev_pegging_id = mfp2.pegging_id)
                then 0 -- no planned order demand.
                else to_number(null) -- planned order with planned order demand. Ignore the Planned order and determine QOH fulfillment from the Planned Order Demand
                end
              else 0
              end
             ) over () = 1
     then 1 -- Full
     else 0 -- None
     end
   from
    msc_full_pegging&amp;a2m_dblink mfp2
   connect by
    prior decode(mfp2.supply_type,5,mfp2.pegging_id,0)=mfp2.prev_pegging_id and
    prior mfp2.sr_instance_id=mfp2.sr_instance_id and
    prior mfp2.plan_id=mfp2.plan_id
    &amp;show_source_org_pegging2
   start with
    mfp2.sr_instance_id=mfp.sr_instance_id and
    mfp2.plan_id=mfp.plan_id and
    mfp2.prev_pegging_id=mfp.pegging_id
   ),0)
  else
   -1 -- ignore
  end                                                      supply_qoh_fulfillment,
  --
  nvl2(mfp.prev_pegging_id,null,&apos;Y&apos;)                       is_end_peg,
  --
  -- demand
  --
  case
  when mfp.demand_id &lt; 0 then msc_get_name.project&amp;a2m_dblink (mfp.project_id, mfp.organization_id, mfp.plan_id, mfp.sr_instance_id)
  else msc_get_name.project&amp;a2m_dblink (md.project_id, md.organization_id, md.plan_id, md.sr_instance_id)
  end                                                      demand_project,
  case
  when mfp.demand_id &lt; 0 then msc_get_name.task&amp;a2m_dblink (mfp.task_id, mfp.project_id, mfp.organization_id, mfp.plan_id, mfp.sr_instance_id)
  else msc_get_name.task&amp;a2m_dblink (md.task_id, md.project_id, md.organization_id, md.plan_id, md.sr_instance_id)
  end                                                      demand_task,
  msc_get_name.item_name&amp;a2m_dblink (md.using_assembly_item_id,null,null,null)
                                                           using_assembly_segments,
  decode(md.origination_type,92,50,md.origination_type)    demand_origination_type_id,
  msc_get_name.lookup_meaning&amp;a2m_dblink (&apos;MSC_DEMAND_ORIGINATION&apos;,decode(md.origination_type, 70, 50, 92, 50, md.origination_type))
                                                           demand_origination_type,
  --md.order_number
  nvl(md.order_number
     ,decode(md.origination_type
            , 1 , to_char(md.disposition_id)
            , 3 , msc_get_name.job_name&amp;a2m_dblink (md.disposition_id, md.plan_id, md.sr_instance_id)
            , 22, to_char(md.disposition_id)
            , 50, msc_get_name.maintenance_plan&amp;a2m_dblink (md.schedule_designator_id)
            , 70, msc_get_name.maintenance_plan&amp;a2m_dblink (md.schedule_designator_id)
            , 92, msc_get_name.maintenance_plan&amp;a2m_dblink (md.schedule_designator_id )
            , 29, decode(md.plan_id
                        ,-11, msc_get_name.designator&amp;a2m_dblink (md.schedule_designator_id)
                            , decode(mfp.in_source_plan
                                    ,1,msc_get_name.designator&amp;a2m_dblink (md.schedule_designator_id, md.forecast_set_id )
                                    , msc_get_name.scenario_designator&amp;a2m_dblink (md.forecast_set_id, md.plan_id, md.organization_id, md.sr_instance_id)
                                      || decode(msc_get_name.designator&amp;a2m_dblink (md.schedule_designator_id,md.forecast_set_id )
                                               , null, null
                                                     , &apos;/&apos;||msc_get_name.designator&amp;a2m_dblink (md.schedule_designator_id,md.forecast_set_id )
                                               )
                                    )
                        )
            , 78, to_char(md.disposition_id)
                , msc_get_name.designator&amp;a2m_dblink (md.schedule_designator_id)
            )
     )                                                     demand_order_number,
  --
  -(nvl(md.daily_demand_rate,md.using_requirement_quantity)) * nvl(md.probability, 1)
                                                           demand_order_qty,
  md.demand_priority                                       demand_priority,
  trunc(md.old_demand_date)                                demand_due_date,
  trunc(md.using_assembly_demand_date)                     demand_sugg_due_date,
  trunc(to_date(null))                                     demand_need_by_date,
  trunc(md.request_ship_date)                              demand_req_ship_date,
  trunc(md.schedule_ship_date)                             demand_sch_ship_date,
  --md.late_days
  round(decode
   (
    sign(md.dmd_satisfied_date - md.using_assembly_demand_date)
   ,-1,least(md.dmd_satisfied_date - md.using_assembly_demand_date,-0.01)
   , 1,greatest(md.dmd_satisfied_date - md.using_assembly_demand_date,0.01)
      , 0
   ),2)                                                    demand_days_late,
  decode(md.customer_id
        , null,msc_get_name.get_other_customers&amp;a2m_dblink (md.plan_id,md.schedule_designator_id)
              ,msc_get_name.customer&amp;a2m_dblink (md.customer_id)
        )                                                  demand_customer,
  decode(md.customer_site_id
        ,null,msc_get_name.get_other_customers&amp;a2m_dblink (md.plan_id,md.schedule_designator_id)
             ,msc_get_name.customer_site&amp;a2m_dblink (md.customer_site_id)
        )                                                  demand_customer_site,
  md.ship_set_name                                         demand_ship_set,
  -- supply
  -- ms.order_type id
  msc_get_name.project&amp;a2m_dblink (ms.project_id, ms.organization_id, ms.plan_id, ms.sr_instance_id) supply_project,
  msc_get_name.task&amp;a2m_dblink (ms.task_id, ms.project_id, ms.organization_id, ms.plan_id, ms.sr_instance_id) supply_task,
  decode(ms.order_type,92,70,ms.order_type)                supply_order_type_id,
  --  ms.order_type_text
  case
  when mp.plan_type = 8
  then case when ms.order_type = 1  then msc_get_name.lookup_meaning&amp;a2m_dblink (&apos;SRP_CHANGED_ORDER_TYPE&apos;, ms.order_type)
            when ms.order_type = 2  and ms.source_organization_id is null then msc_get_name.lookup_meaning&amp;a2m_dblink (&apos;SRP_CHANGED_ORDER_TYPE&apos;, ms.order_type)
            when ms.order_type = 2  and ms.source_organization_id is not null then msc_get_name.lookup_meaning&amp;a2m_dblink (&apos;MRP_ORDER_TYPE&apos;,53)
            when ms.order_type = 53 then msc_get_name.lookup_meaning&amp;a2m_dblink (&apos;SRP_CHANGED_ORDER_TYPE&apos;, ms.order_type)
            else msc_get_name.lookup_meaning&amp;a2m_dblink (&apos;MRP_ORDER_TYPE&apos;,case ms.order_type when 92 then 70 else ms.order_type end)
            end
  else msc_get_name.lookup_meaning&amp;a2m_dblink (&apos;MRP_ORDER_TYPE&apos;,case ms.order_type when 92 then 70 else ms.order_type end)
  end                                                      supply_order_type,
  --ms.order_number
  msc_get_name.supply_order_number&amp;a2m_dblink
   (ms.order_type
   ,ms.order_number
   ,ms.plan_id
   ,ms.sr_instance_id
   ,ms.transaction_id
   ,ms.disposition_id
   )                                                       supply_order_number,
  --
  ms.purch_line_num                                        supply_line_num,
  nvl(ms.daily_rate,ms.new_order_quantity)                 supply_order_qty,
  ms.firm_quantity                                         supply_firm_qty,
  --ms.action
  msc_get_name.action&amp;a2m_dblink
   (&apos;MSC_SUPPLIES&apos;
   ,mfp.bom_item_type
   ,mfp.base_item_id
   ,mfp.wip_supply_type
   ,ms.order_type
   ,ms.reschedule_flag
   ,ms.disposition_status_type
   ,ms.new_schedule_date
   ,ms.old_schedule_date
   ,ms.implemented_quantity
   ,ms.quantity_in_process
   ,ms.new_order_quantity
   ,mfp.release_time_fence_code
   ,ms.reschedule_days
   ,ms.firm_quantity
   ,ms.plan_id
   ,mfp.critical_component_flag
   ,mfp.mrp_planning_code
   ,mfp.lots_exist
   ,ms.item_type_value
   ,ms.transaction_id
   )                                                       supply_action,
  --
  case when ms.old_schedule_date &lt;&gt; ms.new_schedule_date
  then trunc(ms.new_schedule_date) else null end           supply_reschedule_date,
  trunc(ms.old_schedule_date)                              supply_due_date,
  trunc(ms.new_schedule_date)                              supply_sugg_due_date,
  trunc(ms.firm_date)                                      supply_firm_date,
  trunc(ms.old_need_by_date)                               supply_old_need_by_date,
  trunc(ms.need_by_date)                                   supply_need_by_date,
  trunc(ms.promised_date)                                  supply_promise_date,
  round(nvl(ms.earliest_completion_date-ms.need_by_date,0),2)
                                                           supply_days_late,
  msc_get_name.lookup_meaning&amp;a2m_dblink (&apos;WIP_JOB_STATUS&apos;,ms.wip_status_code)
                                                           supply_wip_status,
  msc_get_name.org_code&amp;a2m_dblink (ms.source_organization_id,ms.source_sr_instance_id)
                                                           source_organization,
  msc_get_name.supplier&amp;a2m_dblink (ms.supplier_id)                    supply_vendor,
  msc_get_name.supplier_site&amp;a2m_dblink (ms.supplier_site_id)          supply_vendor_site,
  --
  -- end peg demand
  --
  case when mfpe.demand_id &gt; 0
  then mfpe.demand_id
  else mfpe.transaction_id
  end                                                      end_peg_partition_id,
  mfpe.organization_id                                     end_peg_org_id,
  mfpe.inventory_item_id                                   end_peg_item_id,
  msie.sr_inventory_item_id                                end_peg_sr_item_id,
  mfpe.demand_id                                           end_peg_demand_id,
  mfpe.transaction_id                                      end_peg_transaction_id,
  msie.item_name                                           end_assembly,
  -- project
  case
  when mfpe.demand_id &lt; 0 then msc_get_name.project&amp;a2m_dblink (mfpe.project_id, mfpe.organization_id, mfpe.plan_id, mfpe.sr_instance_id)
  else msc_get_name.project&amp;a2m_dblink (mde.project_id, mde.organization_id, mde.plan_id, mde.sr_instance_id)
  end                                                      end_peg_demand_project,
  case
  when mfpe.demand_id &lt; 0 then msc_get_name.task&amp;a2m_dblink (mfpe.task_id, mfpe.project_id, mfpe.organization_id, mfpe.plan_id, mfpe.sr_instance_id)
  else msc_get_name.task&amp;a2m_dblink (mde.task_id, mde.project_id, mde.organization_id, mde.plan_id, mde.sr_instance_id)
  end                                                      end_peg_demand_task,
  mpoe.organization_code                                   end_peg_demand_organization,
  case when mfpe.demand_id &lt; 0
  then msc_get_name.lookup_meaning&amp;a2m_dblink (&apos;MRP_FLP_SUPPLY_DEMAND_TYPE&apos;,mfpe.demand_id)
  else msc_get_name.lookup_meaning&amp;a2m_dblink (&apos;MSC_DEMAND_ORIGINATION&apos;,decode(mde.origination_type, 70, 50, 92, 50, mde.origination_type))
  end                                                      end_demand_origination,
  case
  when mfp.supply_type &lt; 0
  then msc_get_name.lookup_meaning&amp;a2m_dblink (&apos;MRP_FLP_SUPPLY_DEMAND_TYPE&apos;,mfpe.demand_id)
  else msc_get_name.lookup_meaning&amp;a2m_dblink (&apos;MRP_ORDER_TYPE&apos;,mfpe.supply_type)
  end                                                      end_peg_supply_type,
  case
  when mfpe.demand_id &lt; 0 and mfpe.supply_type &lt; 0
  then msc_get_name.lookup_meaning&amp;a2m_dblink (&apos;MRP_FLP_SUPPLY_DEMAND_TYPE&apos;,mfpe.supply_type)
  when mfpe.demand_id &lt; 0 and mfpe.supply_type &gt; 0
  then msc_get_name.lookup_meaning&amp;a2m_dblink (&apos;MRP_ORDER_TYPE&apos;,mfpe.supply_type)
  else null
  end                                                      end_peg_other_supply_type,
  case
  when mfpe.demand_id = -1 and mfpe.supply_type &lt; 0
  then msc_get_name.lookup_meaning&amp;a2m_dblink (&apos;MRP_FLP_SUPPLY_DEMAND_TYPE&apos;,mfpe.supply_type)
  when mfpe.demand_id = -1 and mfpe.supply_type &gt; 0
  then msc_get_name.lookup_meaning&amp;a2m_dblink (&apos;MRP_ORDER_TYPE&apos;,mfpe.supply_type)
  else null
  end                                                      end_peg_excess_supply_type,
  nvl(mde.order_number
     ,decode(mde.origination_type
            , 1 , to_char(mde.disposition_id)
            , 3 , msc_get_name.job_name&amp;a2m_dblink (mde.disposition_id, mde.plan_id, mde.sr_instance_id)
            , 22, to_char(mde.disposition_id)
            , 50, msc_get_name.maintenance_plan&amp;a2m_dblink (mde.schedule_designator_id)
            , 70, msc_get_name.maintenance_plan&amp;a2m_dblink (mde.schedule_designator_id)
            , 92, msc_get_name.maintenance_plan&amp;a2m_dblink (mde.schedule_designator_id )
            , 29, decode(mde.plan_id
                        ,-11, msc_get_name.designator&amp;a2m_dblink (mde.schedule_designator_id)
                            , decode(msie.in_source_plan
                                    ,1,msc_get_name.designator&amp;a2m_dblink (mde.schedule_designator_id, mde.forecast_set_id )
                                    , msc_get_name.scenario_designator&amp;a2m_dblink (mde.forecast_set_id, mde.plan_id, mde.organization_id, mde.sr_instance_id)
                                      || decode(msc_get_name.designator&amp;a2m_dblink (mde.schedule_designator_id,mde.forecast_set_id )
                                               , null, null
                                                     , &apos;/&apos;||msc_get_name.designator&amp;a2m_dblink (mde.schedule_designator_id,mde.forecast_set_id )
                                               )
                                    )
                        )
            , 78, to_char(mde.disposition_id)
                , msc_get_name.designator&amp;a2m_dblink (mde.schedule_designator_id)
            )
     )                                                     end_demand_order_number,
  case when mfpe.demand_id &lt; 0
  then
   (select
     msc_get_name.supply_order_number&amp;a2m_dblink
      (mse.order_type
      ,mse.order_number
      ,mse.plan_id
      ,mse.sr_instance_id
      ,mse.transaction_id
      ,mse.disposition_id
      )
    from
     msc_supplies&amp;a2m_dblink mse
    where
        mse.sr_instance_id = mfpe.sr_instance_id
    and mse.plan_id = mfpe.plan_id
    and mse.transaction_id = mfpe.transaction_id
   )
  else
   null
  end                                                      end_peg_other_supply_order,
  mde.demand_priority                                      end_demand_priority,
  trunc(mfpe.demand_date)                                  end_peg_demand_date,
  trunc(mfpe.supply_date)                                  end_peg_supply_date,
  case when trunc(mfpe.supply_date) &lt;= trunc(mfpe.demand_date)
  then to_number(null)
  else trunc(mfpe.supply_date) - trunc(mfpe.demand_date)
  end                                                      end_peg_days_late,
  trunc(mde.old_demand_date)                               end_demand_due_date,
  trunc(mde.using_assembly_demand_date)                    end_demand_sugg_due_date,
  trunc(mde.request_ship_date)                             end_demand_req_ship_date,
  -(nvl(mde.daily_demand_rate,mde.using_requirement_quantity)) * nvl(mde.probability, 1)
                                                           end_demand_order_qty,
  mfpe.demand_quantity                                     end_peg_demand_qty,
  round(decode
   (
    sign(mde.dmd_satisfied_date - mde.using_assembly_demand_date)
   ,-1,least(mde.dmd_satisfied_date - mde.using_assembly_demand_date,-0.01)
   , 1,greatest(mde.dmd_satisfied_date - mde.using_assembly_demand_date,0.01)
      , 0
   ),2)                                                    end_demand_days_late,
  -- exceptions
  mfp.planning_exception_set,
  (select /*+ ordered index(med msc_exception_details_n1) */
    distinct listagg(med.exception_type_meaning,&apos;, &apos;) within group (order by med.exception_type_meaning) over ()
   from
    (select distinct
      med.number1,
      med.sr_instance_id,
      med.plan_id,
      med.organization_id,
      med.inventory_item_id,
      flvv.meaning exception_type_meaning
     from
      msc_exception_details&amp;a2m_dblink med,
      fnd_lookup_values_vl&amp;a2m_dblink flvv
     where
         med.exception_type      in (1,2,3,4,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29)
     and flvv.lookup_type         = &apos;MRP_EXCEPTION_CODE_TYPE&apos;
     and flvv.view_application_id = 700
     and flvv.lookup_code         = med.exception_type
    ) med
   where
       med.sr_instance_id       = mfp.sr_instance_id
   and med.plan_id              = mfp.plan_id
   and med.number1              = mfp.transaction_id
   and med.organization_id      = mfp.organization_id
   and med.inventory_item_id    = mfp.inventory_item_id
  ) exceptions
 from
  q_msc_full_pegging                mfp,
  msc_apps_instances&amp;a2m_dblink     mai,
  msc_plans&amp;a2m_dblink              mp,
  msc_plan_organizations&amp;a2m_dblink mpo,
  msc_item_categories&amp;a2m_dblink    mic,
  msc_category_sets&amp;a2m_dblink      mcs,
  msc_supplies&amp;a2m_dblink           ms,
  msc_demands&amp;a2m_dblink            md,
  msc_full_pegging&amp;a2m_dblink       mfpe,
  msc_plan_organizations&amp;a2m_dblink mpoe,
  msc_system_items&amp;a2m_dblink       msie,
  msc_demands&amp;a2m_dblink            mde
  --
 where
     mfp.sr_instance_id       = mai.instance_id
 --
 and mfp.sr_instance_id       = mp.sr_instance_id
 and mfp.plan_id              = mp.plan_id
 --
 and mfp.sr_instance_id       = mpo.sr_instance_id
 and mfp.plan_id              = mpo.plan_id
 and mfp.organization_id      = mpo.organization_id
 --
 and mfp.sr_instance_id       = mic.sr_instance_id
 and mfp.organization_id      = mic.organization_id
 and mfp.inventory_item_id    = mic.inventory_item_id
 and mic.category_set_id      = mcs.category_set_id
 and (   mcs.category_set_name = :p_category_set_name
      or (:p_category_set_name is null and mcs.default_flag = 1)
     )
 --
 --
 and mfp.sr_instance_id       = ms.sr_instance_id (+)
 and mfp.plan_id              = ms.plan_id (+)
 and mfp.transaction_id       = ms.transaction_id (+)
 --
 and mfp.sr_instance_id       = md.sr_instance_id (+)
 and mfp.plan_id              = md.plan_id (+)
 and mfp.demand_id            = md.demand_id (+)
 --
 and mfp.sr_instance_id       = mfpe.sr_instance_id (+)
 and mfp.plan_id              = mfpe.plan_id (+)
 and mfp.end_pegging_id       = mfpe.pegging_id (+)
 and mfpe.sr_instance_id      = mpoe.sr_instance_id (+)
 and mfpe.plan_id             = mpoe.plan_id (+)
 and mfpe.organization_id     = mpoe.organization_id (+)
 and mfpe.sr_instance_id      = msie.sr_instance_id (+)
 and mfpe.plan_id             = msie.plan_id (+)
 and mfpe.organization_id     = msie.organization_id (+)
 and mfpe.inventory_item_id   = msie.inventory_item_id (+)
 and mfpe.sr_instance_id      = mde.sr_instance_id (+)
 and mfpe.plan_id             = mde.plan_id (+)
 and mfpe.demand_id           = mde.demand_id (+)
 --
 and 1=1
) x
) y
where
 4=4
order by
 instance,
 plan,
 demand_organization,
 is_bom desc,
 end_peg_demand_date         nulls last,
 end_peg_demand_origination  nulls last,
 end_peg_demand_order_number nulls last,
 end_pegging_id,
 seq</SQL_TEXT>
  <ENABLED>Y</ENABLED>
  <DB_PACKAGE>XXEN_MSC</DB_PACKAGE>
  <REPORT_TRANSLATIONS>
   <REPORT_TRANSLATIONS_ROW>
    <LANGUAGE>US</LANGUAGE>
    <REPORT_NAME>MSC Pegging Hierarchy</REPORT_NAME>
    <DESCRIPTION>ASCP Pegging Hierarchy. This reports shows the pegging hierarchy from the Top Level Demand.</DESCRIPTION>
   </REPORT_TRANSLATIONS_ROW>
  </REPORT_TRANSLATIONS>
  <CATEGORY_ASSIGNMENTS>
   <CATEGORY_ASSIGNMENTS_ROW>
    <CATEGORY>Enginatics</CATEGORY>
   </CATEGORY_ASSIGNMENTS_ROW>
   <CATEGORY_ASSIGNMENTS_ROW>
    <CATEGORY>R12 only</CATEGORY>
   </CATEGORY_ASSIGNMENTS_ROW>
  </CATEGORY_ASSIGNMENTS>
  <ANCHORS>
   <ANCHORS_ROW>
    <ANCHOR>&amp;a2m_dblink</ANCHOR>
   </ANCHORS_ROW>
   <ANCHORS_ROW>
    <ANCHOR>&amp;lp_custom_attributes</ANCHOR>
   </ANCHORS_ROW>
   <ANCHORS_ROW>
    <ANCHOR>&amp;lp_end_ass_dff_cols</ANCHOR>
   </ANCHORS_ROW>
   <ANCHORS_ROW>
    <ANCHOR>&amp;lp_item_dff_cols</ANCHOR>
   </ANCHORS_ROW>
   <ANCHORS_ROW>
    <ANCHOR>&amp;org_restriction</ANCHOR>
   </ANCHORS_ROW>
   <ANCHORS_ROW>
    <ANCHOR>&amp;show_source_org_pegging</ANCHOR>
   </ANCHORS_ROW>
   <ANCHORS_ROW>
    <ANCHOR>&amp;show_source_org_pegging2</ANCHOR>
   </ANCHORS_ROW>
   <ANCHORS_ROW>
    <ANCHOR>1=1</ANCHOR>
   </ANCHORS_ROW>
   <ANCHORS_ROW>
    <ANCHOR>2=2</ANCHOR>
   </ANCHORS_ROW>
   <ANCHORS_ROW>
    <ANCHOR>3=3</ANCHOR>
   </ANCHORS_ROW>
   <ANCHORS_ROW>
    <ANCHOR>4=4</ANCHOR>
   </ANCHORS_ROW>
   <ANCHORS_ROW>
    <ANCHOR>:p_category_set_name</ANCHOR>
   </ANCHORS_ROW>
   <ANCHORS_ROW>
    <ANCHOR>:p_instance_code</ANCHOR>
   </ANCHORS_ROW>
   <ANCHORS_ROW>
    <ANCHOR>:p_plan_name</ANCHOR>
   </ANCHORS_ROW>
   <ANCHORS_ROW>
    <ANCHOR>:show_source_org_pegging</ANCHOR>
   </ANCHORS_ROW>
  </ANCHORS>
  <PARAMETERS>
   <PARAMETERS_ROW>
    <SORT_ORDER>1</SORT_ORDER>
    <DISPLAY_SEQUENCE>-30</DISPLAY_SEQUENCE>
    <ANCHOR>3=3</ANCHOR>
    <SQL_TEXT>mfp.sr_instance_id=:p_instance_id</SQL_TEXT>
    <PARAMETER_TYPE_DSP>Number</PARAMETER_TYPE_DSP>
    <DEFAULT_VALUE>select
 x.instance_id
from
 (
  select instance_id,instance_code from msc_apps_instances
  union
  select instance_id,instance_code from mrp_ap_apps_instances_all
 ) x
where
 x.instance_code = :$flex$.planning_instance
order by instance_code</DEFAULT_VALUE>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Instance Id</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>2</SORT_ORDER>
    <DISPLAY_SEQUENCE>-20</DISPLAY_SEQUENCE>
    <ANCHOR>3=3</ANCHOR>
    <SQL_TEXT>mfp.plan_id=:p_plan_id</SQL_TEXT>
    <PARAMETER_TYPE_DSP>Number</PARAMETER_TYPE_DSP>
    <DEFAULT_VALUE>select
 mp.plan_id
from 
 msc_plans  mp,
 msc_apps_instances  mai 
where 
    mp.sr_instance_id = mai.instance_id
and mai.instance_code =:$flex$.planning_instance
and mp.compile_designator = :$flex$.plan</DEFAULT_VALUE>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Plan Id</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>3</SORT_ORDER>
    <DISPLAY_SEQUENCE>-10</DISPLAY_SEQUENCE>
    <ANCHOR>3=3</ANCHOR>
    <SQL_TEXT>mfp.end_pegging_id in
(
select /*+ ordered */ distinct
mfp2.end_pegging_id
from
msc_form_query&amp;a2m_dblink mfq,
msc_full_pegging&amp;a2m_dblink mfp2
where
mfp2.sr_instance_id = mfq.number1 and
mfp2.plan_id = mfq.number2 and
mfp2.organization_id = mfq.number3 and
mfp2.inventory_item_id = mfq.number4
)</SQL_TEXT>
    <PARAMETER_TYPE_DSP>Char</PARAMETER_TYPE_DSP>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>instance_id|plan_id|organization_id|inventory_item_id</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>4</SORT_ORDER>
    <DISPLAY_SEQUENCE>10</DISPLAY_SEQUENCE>
    <ANCHOR>:p_instance_code</ANCHOR>
    <PARAMETER_TYPE_DSP>LOV</PARAMETER_TYPE_DSP>
    <LOV_NAME>MSC Planning Instance</LOV_NAME>
    <LOV_GUID>A8454EC5D1EB6FE9E0530100007F0874</LOV_GUID>
    <VALIDATE_FROM_LIST_DSP>Y</VALIDATE_FROM_LIST_DSP>
    <LOV_QUERY_DSP>select
 instance_code value
,null description 
from
 (
  select instance_code from msc_apps_instances
  union
  select instance_code from mrp_ap_apps_instances_all 
 )
order by instance_code</LOV_QUERY_DSP>
    <REQUIRED>Y</REQUIRED>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Planning Instance</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>5</SORT_ORDER>
    <ANCHOR>&amp;a2m_dblink</ANCHOR>
    <SQL_TEXT>select mai.a2m_dblink
from
(
select nvl2(maaia.a2m_dblink,&apos;@&apos;||maaia.a2m_dblink,null) a2m_dblink from mrp_ap_apps_instances_all maaia where maaia.instance_code = :p_instance_code
) mai</SQL_TEXT>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Planning Instance</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>6</SORT_ORDER>
    <ANCHOR>&amp;lp_custom_attributes</ANCHOR>
    <SQL_TEXT>select
 replace(replace(replace(replace(replace(flvv.description,
  &apos;&lt;INSTID&gt;&apos;, &apos;x.sr_instance_id&apos;),
  &apos;&lt;PLANID&gt;&apos;, &apos;x.plan_id&apos;),
  &apos;&lt;SD&gt;&apos;    , &apos;&apos;&apos;D&apos;&apos;&apos;),
  &apos;&lt;WHSID&gt;&apos; , &apos;x.end_peg_org_id&apos;),
  &apos;&lt;TRXID&gt;&apos; , &apos;x.end_peg_demand_id&apos;
  ) 
  || &apos; &apos; 
  || &apos;&quot;&apos; || substrb(rtrim(ltrim(rtrim(ltrim(translate(flvv.meaning,&apos;A.+-/\=?#,;:&apos;&apos;&quot;&apos;,&apos;A_____________&apos;))),&apos;_&apos;),&apos;_&apos;),1,xxen_report.max_column_length) || &apos;&quot;&apos;
  || &apos;,&apos;
from
fnd_lookup_values_vl flvv
where
flvv.lookup_type = &apos;XXEN_MSC_CUSTOM_ATTRIBUTES&apos; and
flvv.view_application_id = 0 and
flvv.enabled_flag = &apos;Y&apos; and
trunc(sysdate) between nvl(flvv.start_date_active,trunc(sysdate)) and nvl(flvv.end_date_active,trunc(sysdate))
order by
flvv.meaning</SQL_TEXT>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Planning Instance</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>7</SORT_ORDER>
    <DISPLAY_SEQUENCE>20</DISPLAY_SEQUENCE>
    <ANCHOR>:p_plan_name</ANCHOR>
    <PARAMETER_TYPE_DSP>LOV</PARAMETER_TYPE_DSP>
    <LOV_NAME>MSC Plan Name</LOV_NAME>
    <LOV_GUID>A8452450392C6F2FE0530100007F6DF4</LOV_GUID>
    <VALIDATE_FROM_LIST_DSP>Y</VALIDATE_FROM_LIST_DSP>
    <LOV_QUERY_DSP>select 
 mp.compile_designator value
,null description
from 
 msc_plans@A2M_DBLINK mp,
 msc_apps_instances@A2M_DBLINK mai 
where mp.plan_id &gt; 0 
and mp.sr_instance_id = mai.instance_id
and mai.instance_code =:$flex$.planning_instance
order by lower(mp.compile_designator)</LOV_QUERY_DSP>
    <REQUIRED>Y</REQUIRED>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Plan</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>8</SORT_ORDER>
    <DISPLAY_SEQUENCE>30</DISPLAY_SEQUENCE>
    <ANCHOR>3=3</ANCHOR>
    <SQL_TEXT>mfp.organization_id in (select mpo.organization_id from msc_plan_organizations&amp;a2m_dblink  mpo where mpo.organization_code=:p_organization_code and mpo.sr_instance_id = :p_instance_id and mpo.plan_id = :p_plan_id)</SQL_TEXT>
    <PARAMETER_TYPE_DSP>LOV</PARAMETER_TYPE_DSP>
    <LOV_NAME>MSC Plan Organization Codes</LOV_NAME>
    <LOV_GUID>A84529F80CED6F4AE0530100007FD38E</LOV_GUID>
    <VALIDATE_FROM_LIST_DSP>Y</VALIDATE_FROM_LIST_DSP>
    <LOV_QUERY_DSP>select 
  mpo.organization_code value
, null description
from
  msc_trading_partners@A2M_DBLINK mtp, 
 msc_plan_organizations@A2M_DBLINK mpo,
 msc_plans@A2M_DBLINK mp,
 msc_apps_instances@A2M_DBLINK mai
where
     mp.sr_instance_id     = mpo.sr_instance_id 
and  mp.plan_id            = mpo.plan_id
and  mpo.sr_instance_id    = mai.instance_id
and  mp.compile_designator = nvl(:$flex$.plan,mp.compile_designator)
and mai.instance_code =:$flex$.planning_instance
and mtp.sr_instance_id = mpo.sr_instance_id
and mtp.partner_type = 3
and mtp.sr_tp_id = mpo.organization_id
and mtp.operating_unit_name = nvl(:$flex$.operating_unit,mtp.operating_unit_name)
order by lower(mpo.organization_code)</LOV_QUERY_DSP>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Organization</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>9</SORT_ORDER>
    <ANCHOR>&amp;org_restriction</ANCHOR>
    <SQL_TEXT>and mfp2.organization_id in (select mpo.organization_id from msc_plan_organizations&amp;a2m_dblink  mpo where mpo.organization_code=:p_organization_code and mpo.sr_instance_id = :p_instance_id and mpo.plan_id = :p_plan_id)</SQL_TEXT>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Organization</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>10</SORT_ORDER>
    <DISPLAY_SEQUENCE>40</DISPLAY_SEQUENCE>
    <ANCHOR>:show_source_org_pegging</ANCHOR>
    <PARAMETER_TYPE_DSP>LOV Oracle</PARAMETER_TYPE_DSP>
    <LOV_NAME>Yes_No</LOV_NAME>
    <VALIDATE_FROM_LIST_DSP>Y</VALIDATE_FROM_LIST_DSP>
    <LOV_QUERY_DSP>select
lookup_code id,
meaning value,
null description
from
fnd_lookups
where fnd_lookups.lookup_type=&apos;YES_NO&apos;
order by value,description</LOV_QUERY_DSP>
    <DEFAULT_VALUE>Y</DEFAULT_VALUE>
    <REQUIRED>Y</REQUIRED>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Show Source Org. Pegging</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>11</SORT_ORDER>
    <ANCHOR>&amp;show_source_org_pegging</ANCHOR>
    <SQL_TEXT>  and prior mfp.organization_id=mfp.organization_id</SQL_TEXT>
    <MATCHING_VALUE>N</MATCHING_VALUE>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Show Source Org. Pegging</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>12</SORT_ORDER>
    <ANCHOR>&amp;show_source_org_pegging</ANCHOR>
    <SQL_TEXT>  and 9=9</SQL_TEXT>
    <MATCHING_VALUE>Y</MATCHING_VALUE>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Show Source Org. Pegging</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>13</SORT_ORDER>
    <ANCHOR>&amp;show_source_org_pegging2</ANCHOR>
    <SQL_TEXT>  and prior mfp2.organization_id=mfp2.organization_id</SQL_TEXT>
    <MATCHING_VALUE>N</MATCHING_VALUE>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Show Source Org. Pegging</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>14</SORT_ORDER>
    <ANCHOR>&amp;show_source_org_pegging2</ANCHOR>
    <SQL_TEXT>  and 9=9</SQL_TEXT>
    <MATCHING_VALUE>Y</MATCHING_VALUE>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Show Source Org. Pegging</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>15</SORT_ORDER>
    <DISPLAY_SEQUENCE>50</DISPLAY_SEQUENCE>
    <ANCHOR>:p_category_set_name</ANCHOR>
    <PARAMETER_TYPE_DSP>LOV</PARAMETER_TYPE_DSP>
    <LOV_NAME>MSC Category Set</LOV_NAME>
    <LOV_GUID>A85770BE6AD052E2E0530100007F2871</LOV_GUID>
    <VALIDATE_FROM_LIST_DSP>Y</VALIDATE_FROM_LIST_DSP>
    <LOV_QUERY_DSP>select
mcs.category_set_name value,
null description 
from 
msc_apps_instances@A2M_DBLINK mai,
msc_category_sets@A2M_DBLINK mcs
where 
mai.instance_code = :$flex$.planning_instance and
mai.instance_id = mcs.sr_instance_id and
exists
(select null
 from
 msc_item_categories@A2M_DBLINK mic
 where
 mic.sr_instance_id = mcs.sr_instance_id and
 mic.category_set_id = mcs.category_set_id
)  
order by 
lower(mcs.category_set_name)</LOV_QUERY_DSP>
    <DEFAULT_VALUE>select 
mcs.category_set_name value
from 
msc_category_sets@A2M_DBLINK   mcs
where 
exists
(select null
 from 
 msc_apps_instances@A2M_DBLINK  mai,
 msc_item_categories@A2M_DBLINK mic
 where 
 mai.instance_code =:$flex$.planning_instance and
 mic.sr_instance_id = mai.instance_id and
 mic.category_set_id = mcs.category_set_id
)  and
mcs.default_flag = 1 and
rownum=1</DEFAULT_VALUE>
    <REQUIRED>Y</REQUIRED>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Category Set</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>16</SORT_ORDER>
    <DISPLAY_SEQUENCE>60</DISPLAY_SEQUENCE>
    <ANCHOR>3=3</ANCHOR>
    <SQL_TEXT>(mfp.sr_instance_id,mfp.plan_id,mfp.pegging_id) in
(
select distinct
mfp2.sr_instance_id,mfp2.plan_id,mfp2.end_pegging_id
from
msc_item_categories&amp;a2m_dblink mic2,
msc_category_sets&amp;a2m_dblink mcs2,
msc_full_pegging&amp;a2m_dblink mfp2
where
mic2.category_name=:p_category and
mic2.sr_instance_id=:p_instance_id and
mcs2.sr_instance_id=mic2.sr_instance_id and
mcs2.category_set_id=mic2.category_set_id and
mcs2.category_set_name=:p_category_set_name and
mic2.sr_instance_id=mfp2.sr_instance_id and
mic2.inventory_item_id=mfp2.inventory_item_id and
mic2.organization_id=mfp2.organization_id and
mfp2.plan_id=:p_plan_id
)</SQL_TEXT>
    <PARAMETER_TYPE_DSP>LOV</PARAMETER_TYPE_DSP>
    <LOV_NAME>MSC Category within a specified Category Set</LOV_NAME>
    <LOV_GUID>A85776F7DF3D52E0E0530100007F6064</LOV_GUID>
    <VALIDATE_FROM_LIST_DSP>Y</VALIDATE_FROM_LIST_DSP>
    <FILTER_BEFORE_DISPLAY_DSP>Y</FILTER_BEFORE_DISPLAY_DSP>
    <LOV_QUERY_DSP>select distinct
mic.category_name value,
null description
from 
msc_apps_instances@A2M_DBLINK mai,
msc_category_sets@A2M_DBLINK  mcs,
msc_item_categories@A2M_DBLINK  mic 
where 
mai.instance_code = :$flex$.planning_instance and
mai.instance_id = mcs.sr_instance_id and
mcs.category_set_name = :$flex$.category_set and
mcs.sr_instance_id = mcs.sr_instance_id and 
mcs.category_set_id = mcs.category_set_id 
order by 
lower(mic.category_name)</LOV_QUERY_DSP>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Category</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>17</SORT_ORDER>
    <DISPLAY_SEQUENCE>70</DISPLAY_SEQUENCE>
    <ANCHOR>3=3</ANCHOR>
    <SQL_TEXT>msi.item_name=:p_end_ass_item</SQL_TEXT>
    <PARAMETER_TYPE_DSP>LOV</PARAMETER_TYPE_DSP>
    <LOV_NAME>MSC Planned Item</LOV_NAME>
    <LOV_GUID>A844FAB91C4F7309E0530100007F496B</LOV_GUID>
    <VALIDATE_FROM_LIST_DSP>Y</VALIDATE_FROM_LIST_DSP>
    <FILTER_BEFORE_DISPLAY_DSP>Y</FILTER_BEFORE_DISPLAY_DSP>
    <LOV_QUERY_DSP>select 
msi.item_name value,
min(msi.description) description
from
msc_system_items@A2M_DBLINK msi,
msc_plans@A2M_DBLINK mp, 
msc_apps_instances@A2M_DBLINK mai 
where
msi.sr_instance_id = mai.instance_id and
msi.plan_id = mp.plan_id and
mp.sr_instance_id  = mai.instance_id and
mp.compile_designator = nvl(:$flex$.plan,mp.compile_designator) and
mai.instance_code =:$flex$.planning_instance
group by 
msi.item_name
order by
lower(msi.item_name)</LOV_QUERY_DSP>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>End Assembly</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>18</SORT_ORDER>
    <DISPLAY_SEQUENCE>80</DISPLAY_SEQUENCE>
    <ANCHOR>3=3</ANCHOR>
    <SQL_TEXT>(mfp.sr_instance_id,mfp.plan_id,mfp.pegging_id) in
(
select distinct
mfp2.sr_instance_id,mfp2.plan_id,mfp2.end_pegging_id
from
msc_system_items&amp;a2m_dblink msi2,
msc_full_pegging&amp;a2m_dblink mfp2
where
msi2.item_name=:p_item and
msi2.sr_instance_id=:p_instance_id and
msi2.plan_id=:p_plan_id and
msi2.sr_instance_id=mfp2.sr_instance_id and
msi2.plan_id=mfp2.plan_id and
msi2.inventory_item_id=mfp2.inventory_item_id and
msi2.organization_id=mfp2.organization_id
)</SQL_TEXT>
    <PARAMETER_TYPE_DSP>LOV</PARAMETER_TYPE_DSP>
    <LOV_NAME>MSC Planned Item</LOV_NAME>
    <LOV_GUID>A844FAB91C4F7309E0530100007F496B</LOV_GUID>
    <VALIDATE_FROM_LIST_DSP>Y</VALIDATE_FROM_LIST_DSP>
    <FILTER_BEFORE_DISPLAY_DSP>Y</FILTER_BEFORE_DISPLAY_DSP>
    <LOV_QUERY_DSP>select 
msi.item_name value,
min(msi.description) description
from
msc_system_items@A2M_DBLINK msi,
msc_plans@A2M_DBLINK mp, 
msc_apps_instances@A2M_DBLINK mai 
where
msi.sr_instance_id = mai.instance_id and
msi.plan_id = mp.plan_id and
mp.sr_instance_id  = mai.instance_id and
mp.compile_designator = nvl(:$flex$.plan,mp.compile_designator) and
mai.instance_code =:$flex$.planning_instance
group by 
msi.item_name
order by
lower(msi.item_name)</LOV_QUERY_DSP>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Item</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>19</SORT_ORDER>
    <DISPLAY_SEQUENCE>90</DISPLAY_SEQUENCE>
    <ANCHOR>4=4</ANCHOR>
    <SQL_TEXT>(
y.end_peg_demand_project=:p_project or
y.demand_project=:p_project or
y.supply_project=:p_project
)</SQL_TEXT>
    <PARAMETER_TYPE_DSP>LOV custom</PARAMETER_TYPE_DSP>
    <VALIDATE_FROM_LIST_DSP>Y</VALIDATE_FROM_LIST_DSP>
    <LOV_QUERY_DSP>select distinct
mp.project_number value,
mp.project_description description
from
msc_projects@A2M_DBLINK mp
where 
mp.plan_id=-1 and  
sr_instance_id=:$flex$.Instance_ID and
(
:$flex$.organization is null or
mp.organization_id in 
(select 
 mpo.organization_id 
 from msc_plan_organizations@A2M_DBLINK  mpo 
 where 
 xxen_util.contains(:$flex$.organization,mpo.organization_code)=&apos;Y&apos; and
 mpo.sr_instance_id=:$flex$.Instance_Id and 
 mpo.plan_id=:$flex$.plan_id
)
)
order by
mp.project_number</LOV_QUERY_DSP>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Project</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>20</SORT_ORDER>
    <DISPLAY_SEQUENCE>100</DISPLAY_SEQUENCE>
    <ANCHOR>3=3</ANCHOR>
    <SQL_TEXT>(mfp.sr_instance_id,mfp.plan_id,mfp.pegging_id) in
(
select distinct
mfp2.sr_instance_id,mfp2.plan_id,mfp2.end_pegging_id
from
msc_system_items&amp;a2m_dblink msi2,
msc_full_pegging&amp;a2m_dblink mfp2
where
msi2.planner_code=:p_planner_code and
msi2.sr_instance_id=:p_instance_id and
msi2.plan_id=:p_plan_id and
msi2.sr_instance_id=mfp2.sr_instance_id and
msi2.plan_id=mfp2.plan_id and
msi2.inventory_item_id=mfp2.inventory_item_id and
msi2.organization_id=mfp2.organization_id
)</SQL_TEXT>
    <PARAMETER_TYPE_DSP>LOV</PARAMETER_TYPE_DSP>
    <LOV_NAME>MSC Planner Code</LOV_NAME>
    <LOV_GUID>A85765FE708251D8E0530100007FCD1D</LOV_GUID>
    <VALIDATE_FROM_LIST_DSP>Y</VALIDATE_FROM_LIST_DSP>
    <LOV_QUERY_DSP>select distinct
mpl.planner_code value,
null description 
from 
msc_apps_instances@A2M_DBLINK mai, 
msc_plans@A2M_DBLINK mp, 
msc_plan_organizations@A2M_DBLINK mpo,
msc_planners@A2M_DBLINK mpl
where
mai.instance_code     = :$flex$.planning_instance and
mp.sr_instance_id     = mai.instance_id and
mp.compile_designator = :$flex$.plan and
mpo.sr_instance_id    = mp.sr_instance_id and
mpo.plan_id           = mp.plan_id and
(:$flex$.organization is null or
 xxen_util.contains(:$flex$.organization,mpo.organization_code) = &apos;Y&apos;
) and
mpl.sr_instance_id    = mpo.sr_instance_id and
mpl.organization_id   = mpo.organization_id
order by lower(mpl.planner_code)</LOV_QUERY_DSP>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Planner</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>21</SORT_ORDER>
    <DISPLAY_SEQUENCE>110</DISPLAY_SEQUENCE>
    <ANCHOR>3=3</ANCHOR>
    <SQL_TEXT>(mfp.sr_instance_id,mfp.plan_id,mfp.pegging_id) in
(
select distinct
mfp2.sr_instance_id,mfp2.plan_id,mfp2.end_pegging_id
from
msc_system_items&amp;a2m_dblink msi2,
msc_full_pegging&amp;a2m_dblink mfp2
where
msi2.buyer_name = :p_buyer_name and
msi2.sr_instance_id=:p_instance_id and
msi2.plan_id=:p_plan_id and
msi2.sr_instance_id=mfp2.sr_instance_id and
msi2.plan_id=mfp2.plan_id and
msi2.inventory_item_id=mfp2.inventory_item_id and
msi2.organization_id=mfp2.organization_id
)</SQL_TEXT>
    <PARAMETER_TYPE_DSP>LOV</PARAMETER_TYPE_DSP>
    <LOV_NAME>MSC Buyer Name</LOV_NAME>
    <LOV_GUID>A8576D437D9C52DEE0530100007F5406</LOV_GUID>
    <VALIDATE_FROM_LIST_DSP>Y</VALIDATE_FROM_LIST_DSP>
    <LOV_QUERY_DSP>select distinct
msi.buyer_name value,
null description
from 
msc_apps_instances@A2M_DBLINK mai,
msc_plans@A2M_DBLINK mp,
msc_plan_organizations@A2M_DBLINK mpo,
msc_system_items@A2M_DBLINK msi
where
mai.instance_code     = :$flex$.planning_instance and
mp.sr_instance_id     = mai.instance_id and
mp.compile_designator = :$flex$.plan and
mpo.sr_instance_id    = mp.sr_instance_id and
mpo.plan_id           = mp.plan_id and
(:$flex$.organization is null or
 xxen_util.contains(:$flex$.organization,mpo.organization_code) = &apos;Y&apos;
) and
msi.sr_instance_id    = mpo.sr_instance_id and 
msi.plan_id           = mpo.plan_id and 
msi.organization_id   = mpo.organization_id and 
msi.buyer_name     is not null 
order by lower(msi.buyer_name)</LOV_QUERY_DSP>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Buyer</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>22</SORT_ORDER>
    <DISPLAY_SEQUENCE>120</DISPLAY_SEQUENCE>
    <ANCHOR>3=3</ANCHOR>
    <SQL_TEXT>(mfp.sr_instance_id,mfp.plan_id,mfp.pegging_id) in
(
select distinct
mfp2.sr_instance_id,mfp2.plan_id,mfp2.end_pegging_id
from
msc_system_items&amp;a2m_dblink msi2,
msc_full_pegging&amp;a2m_dblink mfp2
where
msi2.planning_make_buy_code=xxen_util.lookup_code&amp;a2m_dblink(:p_make_or_buy,&apos;MTL_PLANNING_MAKE_BUY&apos;,700) and
msi2.sr_instance_id=:p_instance_id and
msi2.plan_id=:p_plan_id and
msi2.sr_instance_id=mfp2.sr_instance_id and
msi2.plan_id=mfp2.plan_id and
msi2.inventory_item_id=mfp2.inventory_item_id and
msi2.organization_id=mfp2.organization_id
)</SQL_TEXT>
    <PARAMETER_TYPE_DSP>LOV</PARAMETER_TYPE_DSP>
    <LOV_NAME>MFG Make or Buy</LOV_NAME>
    <LOV_GUID>B0B5FC7B97ED64BCE0530100007F8BA8</LOV_GUID>
    <VALIDATE_FROM_LIST_DSP>Y</VALIDATE_FROM_LIST_DSP>
    <LOV_QUERY_DSP>select
flvv.meaning value,
null description
from
fnd_lookup_values_vl flvv
where
flvv.lookup_type=&apos;MTL_PLANNING_MAKE_BUY&apos; and
flvv.view_application_id=700 and
flvv.security_group_id=0
order by
flvv.meaning</LOV_QUERY_DSP>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Make / Buy</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>23</SORT_ORDER>
    <DISPLAY_SEQUENCE>130</DISPLAY_SEQUENCE>
    <ANCHOR>1=1</ANCHOR>
    <SQL_TEXT>msc_get_name.lookup_meaning&amp;a2m_dblink (&apos;MRP_ORDER_TYPE&apos;,mfp.supply_type) = :p_supply_type</SQL_TEXT>
    <PARAMETER_TYPE_DSP>LOV</PARAMETER_TYPE_DSP>
    <LOV_NAME>MSC Supply Order Type</LOV_NAME>
    <LOV_GUID>A8A48FF5451C47EBE0530100007F79A0</LOV_GUID>
    <VALIDATE_FROM_LIST_DSP>Y</VALIDATE_FROM_LIST_DSP>
    <LOV_QUERY_DSP>select
 flv.meaning value,
 null description
from
 fnd_lookup_values@A2M_DBLINK flv
where
 flv.lookup_type IN (&apos;MRP_ORDER_TYPE&apos;) and
 flv.security_group_id = 0 and
 flv.enabled_flag = &apos;Y&apos; and
 sysdate between nvl(flv.start_date_active,sysdate) and nvl(flv.end_date_active,sysdate) and
 flv.language = nvl((select fl.language_code from fnd_languages@A2M_DBLINK fl where fl.installed_flag in (&apos;B&apos;,&apos;I&apos;) and language_code = userenv(&apos;lang&apos;)),fnd_global.base_language@A2M_DBLINK)
order by
 value</LOV_QUERY_DSP>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Supply Type</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>24</SORT_ORDER>
    <DISPLAY_SEQUENCE>140</DISPLAY_SEQUENCE>
    <ANCHOR>3=3</ANCHOR>
    <SQL_TEXT>(mfp.sr_instance_id,mfp.plan_id,mfp.pegging_id) in
(
select distinct
mfp2.sr_instance_id,mfp2.plan_id,mfp2.end_pegging_id
from
msc_supplies&amp;a2m_dblink ms2,
msc_full_pegging&amp;a2m_dblink mfp2
where
msc_get_name.supplier(ms2.supplier_id) = :p_supplier and
ms2.sr_instance_id=:p_instance_id and
ms2.plan_id=:p_plan_id and
ms2.sr_instance_id=mfp2.sr_instance_id and
ms2.plan_id=mfp2.plan_id and
ms2.transaction_id=mfp2.transaction_id
)</SQL_TEXT>
    <PARAMETER_TYPE_DSP>LOV custom</PARAMETER_TYPE_DSP>
    <VALIDATE_FROM_LIST_DSP>Y</VALIDATE_FROM_LIST_DSP>
    <FILTER_BEFORE_DISPLAY_DSP>Y</FILTER_BEFORE_DISPLAY_DSP>
    <LOV_QUERY_DSP>select distinct
mtp.partner_name value,
partner_number   description
from
msc_trading_partners@A2M_DBLINK mtp
where
mtp.sr_instance_id=:$flex$.instance_id and
mtp.partner_type = 1
order by
value</LOV_QUERY_DSP>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Supplier</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>25</SORT_ORDER>
    <DISPLAY_SEQUENCE>150</DISPLAY_SEQUENCE>
    <ANCHOR>1=1</ANCHOR>
    <SQL_TEXT>ms.new_schedule_date &gt;= :p_supdatefr</SQL_TEXT>
    <PARAMETER_TYPE_DSP>Date</PARAMETER_TYPE_DSP>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Supply Date From</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>26</SORT_ORDER>
    <DISPLAY_SEQUENCE>160</DISPLAY_SEQUENCE>
    <ANCHOR>1=1</ANCHOR>
    <SQL_TEXT>ms.new_schedule_date &lt; :p_supdateto + 1</SQL_TEXT>
    <PARAMETER_TYPE_DSP>Date</PARAMETER_TYPE_DSP>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Supply Date To</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>27</SORT_ORDER>
    <DISPLAY_SEQUENCE>170</DISPLAY_SEQUENCE>
    <ANCHOR>3=3</ANCHOR>
    <SQL_TEXT>(mfp.sr_instance_id,mfp.plan_id,mfp.pegging_id) in
(
select distinct
mfp2.sr_instance_id,mfp2.plan_id,mfp2.end_pegging_id
from
msc_exception_details&amp;a2m_dblink med2,
msc_full_pegging&amp;a2m_dblink mfp2
where
med2.exception_type=xxen_util.lookup_code&amp;a2m_dblink(:exception_message,&apos;MRP_EXCEPTION_CODE_TYPE&apos;,700) and
med2.sr_instance_id=:p_instance_id and
med2.plan_id=:p_plan_id and
med2.sr_instance_id=mfp2.sr_instance_id and
med2.plan_id=mfp2.plan_id and
med2.number1=mfp2.transaction_id
)</SQL_TEXT>
    <PARAMETER_TYPE_DSP>LOV</PARAMETER_TYPE_DSP>
    <LOV_NAME>MSC Exception Type</LOV_NAME>
    <LOV_GUID>A8619783803618A1E0530100007F1391</LOV_GUID>
    <VALIDATE_FROM_LIST_DSP>Y</VALIDATE_FROM_LIST_DSP>
    <LOV_QUERY_DSP>with q_excptn_group as
(
-- map the exception group from msc lang to local user lang
select
 flv2.meaning exception_group
from
 fnd_lookup_values@A2M_DBLINK flv1, -- in msc lang
 fnd_lookup_values flv2             -- in local user lang
where
 flv1.lookup_type = &apos;MSC_EXCEPTION_GROUP&apos; and
 flv1.meaning = :$flex$.exception_group and
 flv1.view_application_id = 700 and
 flv1.security_group_id = 0 and
 flv1.language = nvl((select fl.language_code from fnd_languages@A2M_DBLINK fl where fl.installed_flag in (&apos;B&apos;,&apos;I&apos;) and language_code = userenv(&apos;lang&apos;)),fnd_global.base_language@A2M_DBLINK) and
 flv2.lookup_type = flv1.lookup_type and
 flv2.lookup_code = flv1.lookup_code and
 flv2.view_application_id = flv1.view_application_id and
 flv2.security_group_id = flv1.security_group_id and
 flv2.language = userenv(&apos;lang&apos;)  
) 
select
 flv.meaning value
,null description
from
 fnd_lookup_values@A2M_DBLINK flv
where
 flv.lookup_type = &apos;MRP_EXCEPTION_CODE_TYPE&apos; and
 flv.view_application_id = 700 and
 flv.security_group_id = 0 and
 flv.enabled_flag = &apos;Y&apos; and
 sysdate between nvl(flv.start_date_active,sysdate) and nvl(flv.end_date_active,sysdate) and
 flv.language = nvl((select fl.language_code from fnd_languages@A2M_DBLINK fl where fl.installed_flag in (&apos;B&apos;,&apos;I&apos;) and language_code = userenv(&apos;lang&apos;)),fnd_global.base_language@A2M_DBLINK) and
 (:$flex$.exception_group is null or
  exists
  -- msc_phub_util.get_exception_group must run locally in case the user lang is not installed in the msc instance
  (select null from q_excptn_group where q_excptn_group.exception_group = msc_phub_util.get_exception_group(flv.lookup_code))
 )
order by
 lower(flv.meaning)</LOV_QUERY_DSP>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Exception</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>28</SORT_ORDER>
    <DISPLAY_SEQUENCE>180</DISPLAY_SEQUENCE>
    <ANCHOR>1=1</ANCHOR>
    <SQL_TEXT>msc_get_name.lookup_meaning&amp;a2m_dblink (&apos;MSC_DEMAND_ORIGINATION&apos;,md.origination_type) = :p_peg_type</SQL_TEXT>
    <PARAMETER_TYPE_DSP>LOV</PARAMETER_TYPE_DSP>
    <LOV_NAME>MSC Demand Orgination Type</LOV_NAME>
    <LOV_GUID>A8A49319B2344806E0530100007F204F</LOV_GUID>
    <VALIDATE_FROM_LIST_DSP>Y</VALIDATE_FROM_LIST_DSP>
    <LOV_QUERY_DSP>select distinct
 flv.meaning value,
 null description
from
 fnd_lookup_values@A2M_DBLINK flv
where
 flv.lookup_type IN (&apos;MSC_DEMAND_ORIGINATION&apos;) and
 flv.view_application_id = 700 and
 flv.security_group_id = 0 and
 flv.enabled_flag = &apos;Y&apos; and
 sysdate between nvl(flv.start_date_active,sysdate) and nvl(flv.end_date_active,sysdate) and
 flv.language = nvl((select fl.language_code from fnd_languages@A2M_DBLINK fl where fl.installed_flag in (&apos;B&apos;,&apos;I&apos;) and language_code = userenv(&apos;lang&apos;)),fnd_global.base_language@A2M_DBLINK)
order by
 value</LOV_QUERY_DSP>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Demand Origination</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>29</SORT_ORDER>
    <DISPLAY_SEQUENCE>185</DISPLAY_SEQUENCE>
    <ANCHOR>3=3</ANCHOR>
    <SQL_TEXT>(mfp.demand_id, mfp.plan_id, mfp.sr_instance_id) in
(select mde.demand_id, mde.plan_id, mde.sr_instance_id
 from msc_demands&amp;a2m_dblink  mde,
      msc_system_items&amp;a2m_dblink msie
 where 
 msie.sr_instance_id = mde.sr_instance_id and
 msie.plan_id = mde.plan_id and
 msie.organization_id = mde.organization_id and
 msie.inventory_item_id = mde.inventory_item_id and
 nvl(regexp_replace(mde.order_number, &apos;*\(.*\)&apos;)
   ,decode(mde.origination_type
          , 1 , to_char(mde.disposition_id)
          , 3 , msc_get_name.job_name&amp;a2m_dblink (mde.disposition_id, mde.plan_id, mde.sr_instance_id)
          , 22, to_char(mde.disposition_id)
          , 50, msc_get_name.maintenance_plan&amp;a2m_dblink (mde.schedule_designator_id)
          , 70, msc_get_name.maintenance_plan&amp;a2m_dblink (mde.schedule_designator_id)
          , 92, msc_get_name.maintenance_plan&amp;a2m_dblink (mde.schedule_designator_id )
          , 29, decode(mde.plan_id
                      ,-11, msc_get_name.designator&amp;a2m_dblink (mde.schedule_designator_id)
                          , decode(msie.in_source_plan
                                  ,1,msc_get_name.designator&amp;a2m_dblink (mde.schedule_designator_id, mde.forecast_set_id )
                                  , msc_get_name.scenario_designator&amp;a2m_dblink (mde.forecast_set_id, mde.plan_id, mde.organization_id, mde.sr_instance_id)
                                    || decode(msc_get_name.designator&amp;a2m_dblink (mde.schedule_designator_id,mde.forecast_set_id )
                                             , null, null
                                                   , &apos;/&apos;||msc_get_name.designator&amp;a2m_dblink (mde.schedule_designator_id,mde.forecast_set_id )
                                             )
                                  )
                      )
          , 78, to_char(mde.disposition_id)
              , msc_get_name.designator&amp;a2m_dblink (mde.schedule_designator_id)
          )
   ) = :p_end_demand_order and
   mde.sr_instance_id = :p_instance_id and
   mde.plan_id = :p_plan_id
  )</SQL_TEXT>
    <PARAMETER_TYPE_DSP>LOV custom</PARAMETER_TYPE_DSP>
    <VALIDATE_FROM_LIST_DSP>Y</VALIDATE_FROM_LIST_DSP>
    <LOV_QUERY_DSP>select distinct
 nvl(regexp_replace(mde.order_number, &apos;*\(.*\)&apos;)
   ,decode(mde.origination_type
          , 1 , to_char(mde.disposition_id)
          , 3 , msc_get_name.job_name@A2M_DBLINK (mde.disposition_id, mde.plan_id, mde.sr_instance_id)
          , 22, to_char(mde.disposition_id)
          , 50, msc_get_name.maintenance_plan@A2M_DBLINK (mde.schedule_designator_id)
          , 70, msc_get_name.maintenance_plan@A2M_DBLINK (mde.schedule_designator_id)
          , 92, msc_get_name.maintenance_plan@A2M_DBLINK (mde.schedule_designator_id )
          , 29, decode(mde.plan_id
                      ,-11, msc_get_name.designator@A2M_DBLINK (mde.schedule_designator_id)
                          , decode(msie.in_source_plan
                                  ,1,msc_get_name.designator@A2M_DBLINK (mde.schedule_designator_id, mde.forecast_set_id )
                                  , msc_get_name.scenario_designator@A2M_DBLINK (mde.forecast_set_id, mde.plan_id, mde.organization_id, mde.sr_instance_id)
                                    || decode(msc_get_name.designator@A2M_DBLINK (mde.schedule_designator_id,mde.forecast_set_id )
                                             , null, null
                                                   , &apos;/&apos;||msc_get_name.designator@A2M_DBLINK (mde.schedule_designator_id,mde.forecast_set_id )
                                             )
                                  )
                      )
          , 78, to_char(mde.disposition_id)
              , msc_get_name.designator@A2M_DBLINK (mde.schedule_designator_id)
          )
 ) value,
 msc_get_name.lookup_meaning@A2M_DBLINK (&apos;MSC_DEMAND_ORIGINATION&apos;,decode(mde.origination_type, 70, 50, 92, 50, mde.origination_type)) description
from
 msc_full_pegging@A2M_DBLINK mfp,
 msc_demands@A2M_DBLINK mde,
 msc_system_items@A2M_DBLINK msie
where
 mde.sr_instance_id = mfp.sr_instance_id and
 mde.plan_id = mfp.plan_id and
 mde.demand_id = mfp.demand_id and
 msie.sr_instance_id = mde.sr_instance_id and
 msie.plan_id = mde.plan_id and
 msie.organization_id = mde.organization_id and
 msie.inventory_item_id = mde.inventory_item_id and
 mfp.sr_instance_id = :$flex$.instance_id and
 mfp.plan_id = :$flex$.plan_id and
 mfp.prev_pegging_id is null and
 (:$flex$.Demand_Origination is null or
  msc_get_name.lookup_meaning@A2M_DBLINK (&apos;MSC_DEMAND_ORIGINATION&apos;,decode(mde.origination_type, 70, 50, 92, 50, mde.origination_type)) = :$flex$.Demand_Origination
 )
order by
 value</LOV_QUERY_DSP>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Demand Order</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>30</SORT_ORDER>
    <DISPLAY_SEQUENCE>190</DISPLAY_SEQUENCE>
    <ANCHOR>3=3</ANCHOR>
    <SQL_TEXT>mfp.demand_id = xxen_util.lookup_code&amp;a2m_dblink(:p_peg_other,&apos;MRP_FLP_SUPPLY_DEMAND_TYPE&apos;,700)</SQL_TEXT>
    <PARAMETER_TYPE_DSP>LOV</PARAMETER_TYPE_DSP>
    <LOV_NAME>MSC Excess/Safety Stock</LOV_NAME>
    <LOV_GUID>A8A60BF8F1C24A0FE0530100007F5E32</LOV_GUID>
    <VALIDATE_FROM_LIST_DSP>Y</VALIDATE_FROM_LIST_DSP>
    <LOV_QUERY_DSP>select
 flv.meaning value,
 null description
from
 fnd_lookup_values@A2M_DBLINK flv
where
 flv.lookup_type IN (&apos;MRP_FLP_SUPPLY_DEMAND_TYPE&apos;) and
 flv.security_group_id = 0 and
 flv.enabled_flag = &apos;Y&apos; and
 sysdate between nvl(flv.start_date_active,sysdate) and nvl(flv.end_date_active,sysdate) and
 flv.language = nvl((select fl.language_code from fnd_languages@A2M_DBLINK fl where fl.installed_flag in (&apos;B&apos;,&apos;I&apos;) and language_code = userenv(&apos;lang&apos;)),fnd_global.base_language@A2M_DBLINK) and
 to_number(flv.lookup_code) &lt; 0
order by
 value</LOV_QUERY_DSP>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Other Demand Origination</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>31</SORT_ORDER>
    <DISPLAY_SEQUENCE>200</DISPLAY_SEQUENCE>
    <ANCHOR>3=3</ANCHOR>
    <SQL_TEXT>(mfp.end_origination_type&gt;0 and mfp.demand_id &gt; 0)</SQL_TEXT>
    <PARAMETER_TYPE_DSP>LOV</PARAMETER_TYPE_DSP>
    <LOV_NAME>Yes</LOV_NAME>
    <LOV_GUID>8E2FF36EDEA679D2E0530100007F1FF2</LOV_GUID>
    <VALIDATE_FROM_LIST_DSP>Y</VALIDATE_FROM_LIST_DSP>
    <LOV_QUERY_DSP>select &apos;Y&apos; id, xxen_util.meaning(&apos;Y&apos;,&apos;YES_NO&apos;,0) value, null description from dual</LOV_QUERY_DSP>
    <DEFAULT_VALUE>Y</DEFAULT_VALUE>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Exclude Other Demand</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>32</SORT_ORDER>
    <DISPLAY_SEQUENCE>210</DISPLAY_SEQUENCE>
    <ANCHOR>1=1</ANCHOR>
    <SQL_TEXT>nvl(md.using_assembly_demand_date, mfp.demand_date)  &gt;= :dmddatefr</SQL_TEXT>
    <PARAMETER_TYPE_DSP>Date</PARAMETER_TYPE_DSP>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Demand Date From</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>33</SORT_ORDER>
    <DISPLAY_SEQUENCE>220</DISPLAY_SEQUENCE>
    <ANCHOR>1=1</ANCHOR>
    <SQL_TEXT>nvl(md.using_assembly_demand_date, mfp.demand_date) &lt; :dmddateto + 1</SQL_TEXT>
    <PARAMETER_TYPE_DSP>Date</PARAMETER_TYPE_DSP>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Demand Date To</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>34</SORT_ORDER>
    <DISPLAY_SEQUENCE>230</DISPLAY_SEQUENCE>
    <ANCHOR>3=3</ANCHOR>
    <SQL_TEXT>(mfp.sr_instance_id,mfp.plan_id,mfp.pegging_id) in
(
select distinct
mfp2.sr_instance_id,mfp2.plan_id,mfp2.end_pegging_id
from
msc_system_items&amp;a2m_dblink msi2,
msc_full_pegging&amp;a2m_dblink mfp2
where
msi2.end_assembly_pegging_flag=xxen_util.lookup_code&amp;a2m_dblink(:p_pegging,&apos;ASSEMBLY_PEGGING_CODE&apos;,0) and
msi2.sr_instance_id=:p_instance_id and
msi2.plan_id=:p_plan_id and
msi2.sr_instance_id=mfp2.sr_instance_id and
msi2.plan_id=mfp2.plan_id and
msi2.inventory_item_id=mfp2.inventory_item_id and
msi2.organization_id=mfp2.organization_id
)</SQL_TEXT>
    <PARAMETER_TYPE_DSP>LOV</PARAMETER_TYPE_DSP>
    <LOV_NAME>INV Pegging</LOV_NAME>
    <LOV_GUID>8E2FF36EDEFB79D2E0530100007F1FF2</LOV_GUID>
    <VALIDATE_FROM_LIST_DSP>Y</VALIDATE_FROM_LIST_DSP>
    <LOV_QUERY_DSP>select
flvv.meaning value,
null description
from
fnd_lookup_values_vl flvv
where
flvv.lookup_type=&apos;ASSEMBLY_PEGGING_CODE&apos; and
flvv.view_application_id=0 and
flvv.security_group_id=0
order by
decode(flvv.lookup_code,&apos;A&apos;,1,&apos;Y&apos;,2,&apos;B&apos;,3,&apos;I&apos;,4,&apos;X&apos;,5,&apos;N&apos;,6)</LOV_QUERY_DSP>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Pegging</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>35</SORT_ORDER>
    <DISPLAY_SEQUENCE>240</DISPLAY_SEQUENCE>
    <ANCHOR>4=4</ANCHOR>
    <SQL_TEXT>y.is_end_peg=&apos;Y&apos;</SQL_TEXT>
    <PARAMETER_TYPE_DSP>LOV</PARAMETER_TYPE_DSP>
    <LOV_NAME>Yes</LOV_NAME>
    <LOV_GUID>8E2FF36EDEA679D2E0530100007F1FF2</LOV_GUID>
    <VALIDATE_FROM_LIST_DSP>Y</VALIDATE_FROM_LIST_DSP>
    <LOV_QUERY_DSP>select &apos;Y&apos; id, xxen_util.meaning(&apos;Y&apos;,&apos;YES_NO&apos;,0) value, null description from dual</LOV_QUERY_DSP>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Show End Pegs Only</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>36</SORT_ORDER>
    <DISPLAY_SEQUENCE>250</DISPLAY_SEQUENCE>
    <ANCHOR>&amp;lp_end_ass_dff_cols</ANCHOR>
    <SQL_TEXT>select 
xxen_msc.get_item_dff_lexicals(mai.instance_id,&apos;x.end_peg_sr_item_id&apos;,&apos;x.end_peg_org_id&apos;,&apos;EA: &apos;)
from
(
select maaia.instance_id from mrp_ap_apps_instances_all maaia where maaia.instance_code = :p_instance_code union
select mai.instance_id from msc_apps_instances mai where mai.instance_code = :p_instance_code and not exists (select null from  mrp_ap_apps_instances_all maaia where maaia.instance_code = :p_instance_code)
) mai</SQL_TEXT>
    <PARAMETER_TYPE_DSP>LOV</PARAMETER_TYPE_DSP>
    <LOV_NAME>Yes</LOV_NAME>
    <LOV_GUID>8E2FF36EDEA679D2E0530100007F1FF2</LOV_GUID>
    <VALIDATE_FROM_LIST_DSP>Y</VALIDATE_FROM_LIST_DSP>
    <LOV_QUERY_DSP>select &apos;Y&apos; id, xxen_util.meaning(&apos;Y&apos;,&apos;YES_NO&apos;,0) value, null description from dual</LOV_QUERY_DSP>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Show Item Descriptive Attributes</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
   <PARAMETERS_ROW>
    <SORT_ORDER>37</SORT_ORDER>
    <ANCHOR>&amp;lp_item_dff_cols</ANCHOR>
    <SQL_TEXT>select 
xxen_msc.get_item_dff_lexicals(mai.instance_id,&apos;x.sr_inventory_item_id&apos;,&apos;x.organization_id&apos;)
from
(
select maaia.instance_id from mrp_ap_apps_instances_all maaia where maaia.instance_code = :p_instance_code union
select mai.instance_id from msc_apps_instances mai where mai.instance_code = :p_instance_code and not exists (select null from  mrp_ap_apps_instances_all maaia where maaia.instance_code = :p_instance_code)
) mai</SQL_TEXT>
    <PARAMETER_TRANSLATIONS>
     <PARAMETER_TRANSLATIONS_ROW>
      <LANGUAGE>US</LANGUAGE>
      <PARAMETER_NAME>Show Item Descriptive Attributes</PARAMETER_NAME>
     </PARAMETER_TRANSLATIONS_ROW>
    </PARAMETER_TRANSLATIONS>
   </PARAMETERS_ROW>
  </PARAMETERS>
  <PARAMETER_DEPENDENCIES>
   <PARAMETER_DEPENDENCIES_ROW>
    <FLEX_BIND>:$flex$.Demand_Origination</FLEX_BIND>
    <PARAMETER_NAME>Demand Origination</PARAMETER_NAME>
    <DEPENDENT_PARAMETER_NAME>Demand Order</DEPENDENT_PARAMETER_NAME>
   </PARAMETER_DEPENDENCIES_ROW>
   <PARAMETER_DEPENDENCIES_ROW>
    <FLEX_BIND>:$flex$.Instance_ID</FLEX_BIND>
    <PARAMETER_NAME>Instance Id</PARAMETER_NAME>
    <DEPENDENT_PARAMETER_NAME>Project</DEPENDENT_PARAMETER_NAME>
   </PARAMETER_DEPENDENCIES_ROW>
   <PARAMETER_DEPENDENCIES_ROW>
    <FLEX_BIND>:$flex$.Instance_Id</FLEX_BIND>
    <PARAMETER_NAME>Instance Id</PARAMETER_NAME>
    <DEPENDENT_PARAMETER_NAME>Project</DEPENDENT_PARAMETER_NAME>
   </PARAMETER_DEPENDENCIES_ROW>
   <PARAMETER_DEPENDENCIES_ROW>
    <FLEX_BIND>:$flex$.category_set</FLEX_BIND>
    <PARAMETER_NAME>Category Set</PARAMETER_NAME>
    <DEPENDENT_PARAMETER_NAME>Category</DEPENDENT_PARAMETER_NAME>
   </PARAMETER_DEPENDENCIES_ROW>
   <PARAMETER_DEPENDENCIES_ROW>
    <FLEX_BIND>:$flex$.instance_id</FLEX_BIND>
    <PARAMETER_NAME>Instance Id</PARAMETER_NAME>
    <DEPENDENT_PARAMETER_NAME>Demand Order</DEPENDENT_PARAMETER_NAME>
   </PARAMETER_DEPENDENCIES_ROW>
   <PARAMETER_DEPENDENCIES_ROW>
    <FLEX_BIND>:$flex$.instance_id</FLEX_BIND>
    <PARAMETER_NAME>Instance Id</PARAMETER_NAME>
    <DEPENDENT_PARAMETER_NAME>Supplier</DEPENDENT_PARAMETER_NAME>
   </PARAMETER_DEPENDENCIES_ROW>
   <PARAMETER_DEPENDENCIES_ROW>
    <FLEX_BIND>:$flex$.organization</FLEX_BIND>
    <PARAMETER_NAME>Organization</PARAMETER_NAME>
    <DEPENDENT_PARAMETER_NAME>Buyer</DEPENDENT_PARAMETER_NAME>
   </PARAMETER_DEPENDENCIES_ROW>
   <PARAMETER_DEPENDENCIES_ROW>
    <FLEX_BIND>:$flex$.organization</FLEX_BIND>
    <PARAMETER_NAME>Organization</PARAMETER_NAME>
    <DEPENDENT_PARAMETER_NAME>Planner</DEPENDENT_PARAMETER_NAME>
   </PARAMETER_DEPENDENCIES_ROW>
   <PARAMETER_DEPENDENCIES_ROW>
    <FLEX_BIND>:$flex$.organization</FLEX_BIND>
    <PARAMETER_NAME>Organization</PARAMETER_NAME>
    <DEPENDENT_PARAMETER_NAME>Project</DEPENDENT_PARAMETER_NAME>
   </PARAMETER_DEPENDENCIES_ROW>
   <PARAMETER_DEPENDENCIES_ROW>
    <FLEX_BIND>:$flex$.plan</FLEX_BIND>
    <PARAMETER_NAME>Plan</PARAMETER_NAME>
    <DEPENDENT_PARAMETER_NAME>Buyer</DEPENDENT_PARAMETER_NAME>
   </PARAMETER_DEPENDENCIES_ROW>
   <PARAMETER_DEPENDENCIES_ROW>
    <FLEX_BIND>:$flex$.plan</FLEX_BIND>
    <PARAMETER_NAME>Plan</PARAMETER_NAME>
    <DEPENDENT_PARAMETER_NAME>End Assembly</DEPENDENT_PARAMETER_NAME>
   </PARAMETER_DEPENDENCIES_ROW>
   <PARAMETER_DEPENDENCIES_ROW>
    <FLEX_BIND>:$flex$.plan</FLEX_BIND>
    <PARAMETER_NAME>Plan</PARAMETER_NAME>
    <DEPENDENT_PARAMETER_NAME>Item</DEPENDENT_PARAMETER_NAME>
   </PARAMETER_DEPENDENCIES_ROW>
   <PARAMETER_DEPENDENCIES_ROW>
    <FLEX_BIND>:$flex$.plan</FLEX_BIND>
    <PARAMETER_NAME>Plan</PARAMETER_NAME>
    <DEPENDENT_PARAMETER_NAME>Organization</DEPENDENT_PARAMETER_NAME>
   </PARAMETER_DEPENDENCIES_ROW>
   <PARAMETER_DEPENDENCIES_ROW>
    <FLEX_BIND>:$flex$.plan</FLEX_BIND>
    <PARAMETER_NAME>Plan</PARAMETER_NAME>
    <DEPENDENT_PARAMETER_NAME>Plan Id</DEPENDENT_PARAMETER_NAME>
   </PARAMETER_DEPENDENCIES_ROW>
   <PARAMETER_DEPENDENCIES_ROW>
    <FLEX_BIND>:$flex$.plan</FLEX_BIND>
    <PARAMETER_NAME>Plan</PARAMETER_NAME>
    <DEPENDENT_PARAMETER_NAME>Planner</DEPENDENT_PARAMETER_NAME>
   </PARAMETER_DEPENDENCIES_ROW>
   <PARAMETER_DEPENDENCIES_ROW>
    <FLEX_BIND>:$flex$.plan_id</FLEX_BIND>
    <PARAMETER_NAME>Plan Id</PARAMETER_NAME>
    <DEPENDENT_PARAMETER_NAME>Demand Order</DEPENDENT_PARAMETER_NAME>
   </PARAMETER_DEPENDENCIES_ROW>
   <PARAMETER_DEPENDENCIES_ROW>
    <FLEX_BIND>:$flex$.plan_id</FLEX_BIND>
    <PARAMETER_NAME>Plan Id</PARAMETER_NAME>
    <DEPENDENT_PARAMETER_NAME>Project</DEPENDENT_PARAMETER_NAME>
   </PARAMETER_DEPENDENCIES_ROW>
   <PARAMETER_DEPENDENCIES_ROW>
    <FLEX_BIND>:$flex$.planning_instance</FLEX_BIND>
    <PARAMETER_NAME>Planning Instance</PARAMETER_NAME>
    <DEPENDENT_PARAMETER_NAME>Buyer</DEPENDENT_PARAMETER_NAME>
   </PARAMETER_DEPENDENCIES_ROW>
   <PARAMETER_DEPENDENCIES_ROW>
    <FLEX_BIND>:$flex$.planning_instance</FLEX_BIND>
    <PARAMETER_NAME>Planning Instance</PARAMETER_NAME>
    <DEPENDENT_PARAMETER_NAME>Category</DEPENDENT_PARAMETER_NAME>
   </PARAMETER_DEPENDENCIES_ROW>
   <PARAMETER_DEPENDENCIES_ROW>
    <FLEX_BIND>:$flex$.planning_instance</FLEX_BIND>
    <PARAMETER_NAME>Planning Instance</PARAMETER_NAME>
    <DEPENDENT_PARAMETER_NAME>Category Set</DEPENDENT_PARAMETER_NAME>
   </PARAMETER_DEPENDENCIES_ROW>
   <PARAMETER_DEPENDENCIES_ROW>
    <FLEX_BIND>:$flex$.planning_instance</FLEX_BIND>
    <PARAMETER_NAME>Planning Instance</PARAMETER_NAME>
    <DEPENDENT_PARAMETER_NAME>End Assembly</DEPENDENT_PARAMETER_NAME>
   </PARAMETER_DEPENDENCIES_ROW>
   <PARAMETER_DEPENDENCIES_ROW>
    <FLEX_BIND>:$flex$.planning_instance</FLEX_BIND>
    <PARAMETER_NAME>Planning Instance</PARAMETER_NAME>
    <DEPENDENT_PARAMETER_NAME>Instance Id</DEPENDENT_PARAMETER_NAME>
   </PARAMETER_DEPENDENCIES_ROW>
   <PARAMETER_DEPENDENCIES_ROW>
    <FLEX_BIND>:$flex$.planning_instance</FLEX_BIND>
    <PARAMETER_NAME>Planning Instance</PARAMETER_NAME>
    <DEPENDENT_PARAMETER_NAME>Item</DEPENDENT_PARAMETER_NAME>
   </PARAMETER_DEPENDENCIES_ROW>
   <PARAMETER_DEPENDENCIES_ROW>
    <FLEX_BIND>:$flex$.planning_instance</FLEX_BIND>
    <PARAMETER_NAME>Planning Instance</PARAMETER_NAME>
    <DEPENDENT_PARAMETER_NAME>Organization</DEPENDENT_PARAMETER_NAME>
   </PARAMETER_DEPENDENCIES_ROW>
   <PARAMETER_DEPENDENCIES_ROW>
    <FLEX_BIND>:$flex$.planning_instance</FLEX_BIND>
    <PARAMETER_NAME>Planning Instance</PARAMETER_NAME>
    <DEPENDENT_PARAMETER_NAME>Plan</DEPENDENT_PARAMETER_NAME>
   </PARAMETER_DEPENDENCIES_ROW>
   <PARAMETER_DEPENDENCIES_ROW>
    <FLEX_BIND>:$flex$.planning_instance</FLEX_BIND>
    <PARAMETER_NAME>Planning Instance</PARAMETER_NAME>
    <DEPENDENT_PARAMETER_NAME>Plan Id</DEPENDENT_PARAMETER_NAME>
   </PARAMETER_DEPENDENCIES_ROW>
   <PARAMETER_DEPENDENCIES_ROW>
    <FLEX_BIND>:$flex$.planning_instance</FLEX_BIND>
    <PARAMETER_NAME>Planning Instance</PARAMETER_NAME>
    <DEPENDENT_PARAMETER_NAME>Planner</DEPENDENT_PARAMETER_NAME>
   </PARAMETER_DEPENDENCIES_ROW>
  </PARAMETER_DEPENDENCIES>
  <TEMPLATES>
   <TEMPLATES_ROW>
    <TEMPLATE_NAME>Pivot: Full Hierarchy (Default)</TEMPLATE_NAME>
    <DESCRIPTION>Pivot: Full Hierarchy (Default)</DESCRIPTION>
    <OWNER>SYSADMIN</OWNER>
    <TEMPLATE_COLUMNS>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>48</DISPLAY_SEQUENCE>
      <COLUMN_NAME>BOM_ITEM_TYPE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-93.0094</DISPLAY_SEQUENCE>
      <COLUMN_NAME>BOM_LEVEL</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-11.0012</DISPLAY_SEQUENCE>
      <COLUMN_NAME>BOM_LEVEL_</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>46</DISPLAY_SEQUENCE>
      <COLUMN_NAME>BUYER_NAME</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>44</DISPLAY_SEQUENCE>
      <COLUMN_NAME>CATEGORY_NAME</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>43</DISPLAY_SEQUENCE>
      <COLUMN_NAME>CATEGORY_SET_NAME</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>55</DISPLAY_SEQUENCE>
      <COLUMN_NAME>CUMULATIVE_TOTAL_LEAD_TIME</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>54</DISPLAY_SEQUENCE>
      <COLUMN_NAME>CUM_MANUFACTURING_LEAD_TIME</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-90.0104</DISPLAY_SEQUENCE>
      <COLUMN_NAME>Charge_Description_Master</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>69</DISPLAY_SEQUENCE>
      <COLUMN_NAME>DEMAND_CUSTOMER</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>70</DISPLAY_SEQUENCE>
      <COLUMN_NAME>DEMAND_CUSTOMER_SITE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>64</DISPLAY_SEQUENCE>
      <COLUMN_NAME>DEMAND_DAYS_LATE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>63</DISPLAY_SEQUENCE>
      <COLUMN_NAME>DEMAND_DUE_DATE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>94</DISPLAY_SEQUENCE>
      <COLUMN_NAME>DEMAND_ID</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>66</DISPLAY_SEQUENCE>
      <COLUMN_NAME>DEMAND_NEED_BY_DATE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>60</DISPLAY_SEQUENCE>
      <COLUMN_NAME>DEMAND_ORDER_NUMBER</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>61</DISPLAY_SEQUENCE>
      <COLUMN_NAME>DEMAND_ORDER_QTY</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>23</DISPLAY_SEQUENCE>
      <COLUMN_NAME>DEMAND_ORGANIZATION</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>59</DISPLAY_SEQUENCE>
      <COLUMN_NAME>DEMAND_ORIGINATION</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-48.0049</DISPLAY_SEQUENCE>
      <COLUMN_NAME>DEMAND_ORIGINATION_PATH</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-46.0047</DISPLAY_SEQUENCE>
      <COLUMN_NAME>DEMAND_ORIGINATION_TYPE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-46.0048</DISPLAY_SEQUENCE>
      <COLUMN_NAME>DEMAND_ORIGINATION_TYPE_</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>97</DISPLAY_SEQUENCE>
      <COLUMN_NAME>DEMAND_ORIGINATION_TYPE_ID</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>62</DISPLAY_SEQUENCE>
      <COLUMN_NAME>DEMAND_PRIORITY</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>57</DISPLAY_SEQUENCE>
      <COLUMN_NAME>DEMAND_PROJECT</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>67</DISPLAY_SEQUENCE>
      <COLUMN_NAME>DEMAND_REQ_SHIP_DATE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>68</DISPLAY_SEQUENCE>
      <COLUMN_NAME>DEMAND_SCH_SHIP_DATE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>71</DISPLAY_SEQUENCE>
      <COLUMN_NAME>DEMAND_SHIP_SET</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>65</DISPLAY_SEQUENCE>
      <COLUMN_NAME>DEMAND_SUGG_DUE_DATE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>58</DISPLAY_SEQUENCE>
      <COLUMN_NAME>DEMAND_TASK</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-90.0097</DISPLAY_SEQUENCE>
      <COLUMN_NAME>EA__Charge_Description_Master</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-90.0093</DISPLAY_SEQUENCE>
      <COLUMN_NAME>EA__Graphical_Link_for_Web_Reqs</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-90.0092</DISPLAY_SEQUENCE>
      <COLUMN_NAME>EA__Invoice_UOM</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-90.0095</DISPLAY_SEQUENCE>
      <COLUMN_NAME>EA__Item_Model</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-90.0091</DISPLAY_SEQUENCE>
      <COLUMN_NAME>EA__Late_Demands_Penalty</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-90.0094</DISPLAY_SEQUENCE>
      <COLUMN_NAME>EA__Material_Over_Capacity_Penalty</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-90.0096</DISPLAY_SEQUENCE>
      <COLUMN_NAME>EA__Tax_Denomination</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>3</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_ASSEMBLY</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>21</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_ASSEMBLY_PLAN_ORD_QOH_STS</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>20</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_DEMAND_DAYS_LATE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>17</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_DEMAND_DUE_DATE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>10</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_DEMAND_ORDER_NUMBER</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>11</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_DEMAND_ORDER_QTY</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>9</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_DEMAND_ORIGINATION</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>16</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_DEMAND_PRIORITY</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>19</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_DEMAND_REQ_SHIP_DATE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>18</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_DEMAND_SUGG_DUE_DATE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-10.0011</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_ORDER_PLAN_ORD_QOH_STS</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>91</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_PEGGING_ID</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>15</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_PEG_DAYS_LATE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>13</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_PEG_DEMAND_DATE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-82.0083</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_PEG_DEMAND_DAYS_LATE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-77.0079</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_PEG_DEMAND_DUE_DATE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>8</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_PEG_DEMAND_ORDER_NUMBER</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-8.0009</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_PEG_DEMAND_ORDER_QOH</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>4</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_PEG_DEMAND_ORGANIZATION</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>7</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_PEG_DEMAND_ORIGINATION</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-77.0078</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_PEG_DEMAND_PRIORITY</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>5</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_PEG_DEMAND_PROJECT</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-8.001</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_PEG_DEMAND_QOH</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-8.001</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_PEG_DEMAND_QOH_STATUS</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>12</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_PEG_DEMAND_QTY</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-77.0081</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_PEG_DEMAND_REQ_SHIP_DATE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-77.008</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_PEG_DEMAND_SUGG_DUE_DATE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>6</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_PEG_DEMAND_TASK</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-8.0011</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_PEG_ORDER_ITEM_QOH_STATUS</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-8.0009</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_PEG_ORDER_QOH</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-8.0009</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_PEG_ORDER_QOH_STATUS</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-3.0004</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_PEG_ORGANIZATION</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>22</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_PEG_PLAN_ORD_QOH_STS</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-4.0005</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_PEG_PROJECT</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-8.001</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_PEG_QOH</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-8.0012</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_PEG_QOH_FULLFILL_STATUS</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>14</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_PEG_SUPPLY_DATE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-4.0006</DISPLAY_SEQUENCE>
      <COLUMN_NAME>END_PEG_TASK</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>90</DISPLAY_SEQUENCE>
      <COLUMN_NAME>EXCEPTIONS</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-90.01</DISPLAY_SEQUENCE>
      <COLUMN_NAME>Graphical_Link_for_Web_Reqs</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-11.0012</DISPLAY_SEQUENCE>
      <COLUMN_NAME>INDENT</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>1</DISPLAY_SEQUENCE>
      <COLUMN_NAME>INSTANCE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>49</DISPLAY_SEQUENCE>
      <COLUMN_NAME>IS_BOM</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>104</DISPLAY_SEQUENCE>
      <COLUMN_NAME>IS_END_PEG</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>102</DISPLAY_SEQUENCE>
      <COLUMN_NAME>ITEM</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-11.0013</DISPLAY_SEQUENCE>
      <COLUMN_NAME>ITEM_</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>28</DISPLAY_SEQUENCE>
      <COLUMN_NAME>ITEM_DESCRIPTION</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>100</DISPLAY_SEQUENCE>
      <COLUMN_NAME>ITEM_DESCRIPTION_PATH</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-93.0094</DISPLAY_SEQUENCE>
      <COLUMN_NAME>ITEM_NAME</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>27</DISPLAY_SEQUENCE>
      <COLUMN_NAME>ITEM_PATH</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-90.0099</DISPLAY_SEQUENCE>
      <COLUMN_NAME>Invoice_UOM</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-90.0102</DISPLAY_SEQUENCE>
      <COLUMN_NAME>Item_Model</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-91.0092</DISPLAY_SEQUENCE>
      <COLUMN_NAME>LEVEL_</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-90.0098</DISPLAY_SEQUENCE>
      <COLUMN_NAME>Late_Demands_Penalty</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>101</DISPLAY_SEQUENCE>
      <COLUMN_NAME>Level</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>47</DISPLAY_SEQUENCE>
      <COLUMN_NAME>MAKE_BUY</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>52</DISPLAY_SEQUENCE>
      <COLUMN_NAME>MIN_MINMAX_QUANTITY</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-90.0101</DISPLAY_SEQUENCE>
      <COLUMN_NAME>Material_Over_Capacity_Penalty</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>26</DISPLAY_SEQUENCE>
      <COLUMN_NAME>PEGGED_ITEM</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>92</DISPLAY_SEQUENCE>
      <COLUMN_NAME>PEGGING_ID</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>51</DISPLAY_SEQUENCE>
      <COLUMN_NAME>PEGGING_TYPE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>30</DISPLAY_SEQUENCE>
      <COLUMN_NAME>PEG_DAYS_LATE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>33</DISPLAY_SEQUENCE>
      <COLUMN_NAME>PEG_DEMAND_DATE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>32</DISPLAY_SEQUENCE>
      <COLUMN_NAME>PEG_DEMAND_ORDER</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>31</DISPLAY_SEQUENCE>
      <COLUMN_NAME>PEG_DEMAND_ORIGINATION</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-19.002</DISPLAY_SEQUENCE>
      <COLUMN_NAME>PEG_DEMAND_ORIGINATION_TYPE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>34</DISPLAY_SEQUENCE>
      <COLUMN_NAME>PEG_DEMAND_QTY</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>99</DISPLAY_SEQUENCE>
      <COLUMN_NAME>PEG_END_ITEM_USAGE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>25</DISPLAY_SEQUENCE>
      <COLUMN_NAME>PEG_LEVEL</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>35</DISPLAY_SEQUENCE>
      <COLUMN_NAME>PEG_PEGGED_QTY</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-27.0028</DISPLAY_SEQUENCE>
      <COLUMN_NAME>PEG_RESERVED_QTY</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>39</DISPLAY_SEQUENCE>
      <COLUMN_NAME>PEG_SUPPLY_DATE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>38</DISPLAY_SEQUENCE>
      <COLUMN_NAME>PEG_SUPPLY_ORDER</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>36</DISPLAY_SEQUENCE>
      <COLUMN_NAME>PEG_SUPPLY_QTY</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>37</DISPLAY_SEQUENCE>
      <COLUMN_NAME>PEG_SUPPLY_TYPE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>96</DISPLAY_SEQUENCE>
      <COLUMN_NAME>PEG_SUPPLY_TYPE_ID</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>105</DISPLAY_SEQUENCE>
      <COLUMN_NAME>PEG_SUPPLY_TYPE_LABEL</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>2</DISPLAY_SEQUENCE>
      <COLUMN_NAME>PLAN</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>45</DISPLAY_SEQUENCE>
      <COLUMN_NAME>PLANNER_CODE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>89</DISPLAY_SEQUENCE>
      <COLUMN_NAME>PLANNING_EXCEPTION_SET</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>56</DISPLAY_SEQUENCE>
      <COLUMN_NAME>POSTPROCESSING_LEAD_TIME</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>53</DISPLAY_SEQUENCE>
      <COLUMN_NAME>PREPROCESSING_LEAD_TIME</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>93</DISPLAY_SEQUENCE>
      <COLUMN_NAME>PREV_PEGGING_ID</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-27.0028</DISPLAY_SEQUENCE>
      <COLUMN_NAME>PROJECT</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-97.0098</DISPLAY_SEQUENCE>
      <COLUMN_NAME>QOH_FULFILLMENT</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>50</DISPLAY_SEQUENCE>
      <COLUMN_NAME>SAFETY_STOCK</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>103</DISPLAY_SEQUENCE>
      <COLUMN_NAME>SEQ</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>24</DISPLAY_SEQUENCE>
      <COLUMN_NAME>SOURCE_ORGANIZATION</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>41</DISPLAY_SEQUENCE>
      <COLUMN_NAME>SUPPLY_ACTION</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>80</DISPLAY_SEQUENCE>
      <COLUMN_NAME>SUPPLY_DAYS_LATE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>79</DISPLAY_SEQUENCE>
      <COLUMN_NAME>SUPPLY_DUE_DATE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>82</DISPLAY_SEQUENCE>
      <COLUMN_NAME>SUPPLY_FIRM_DATE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>78</DISPLAY_SEQUENCE>
      <COLUMN_NAME>SUPPLY_FIRM_QTY</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>76</DISPLAY_SEQUENCE>
      <COLUMN_NAME>SUPPLY_LINE_NUM</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>84</DISPLAY_SEQUENCE>
      <COLUMN_NAME>SUPPLY_NEED_BY_DATE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>83</DISPLAY_SEQUENCE>
      <COLUMN_NAME>SUPPLY_OLD_NEED_BY_DATE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>75</DISPLAY_SEQUENCE>
      <COLUMN_NAME>SUPPLY_ORDER_NUMBER</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>77</DISPLAY_SEQUENCE>
      <COLUMN_NAME>SUPPLY_ORDER_QTY</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>74</DISPLAY_SEQUENCE>
      <COLUMN_NAME>SUPPLY_ORDER_TYPE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-61.0062</DISPLAY_SEQUENCE>
      <COLUMN_NAME>SUPPLY_ORDER_TYPE_</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>98</DISPLAY_SEQUENCE>
      <COLUMN_NAME>SUPPLY_ORDER_TYPE_ID</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-62.0063</DISPLAY_SEQUENCE>
      <COLUMN_NAME>SUPPLY_ORDER_TYPE_PATH</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-100.0101</DISPLAY_SEQUENCE>
      <COLUMN_NAME>SUPPLY_PATH</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>40</DISPLAY_SEQUENCE>
      <COLUMN_NAME>SUPPLY_PLAN_ORD_QOH_STS</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>72</DISPLAY_SEQUENCE>
      <COLUMN_NAME>SUPPLY_PROJECT</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>85</DISPLAY_SEQUENCE>
      <COLUMN_NAME>SUPPLY_PROMISE_DATE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-30.0031</DISPLAY_SEQUENCE>
      <COLUMN_NAME>SUPPLY_QOH_FULFILL</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>42</DISPLAY_SEQUENCE>
      <COLUMN_NAME>SUPPLY_RESCHEDULE_DATE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>81</DISPLAY_SEQUENCE>
      <COLUMN_NAME>SUPPLY_SUGG_DUE_DATE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>73</DISPLAY_SEQUENCE>
      <COLUMN_NAME>SUPPLY_TASK</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>87</DISPLAY_SEQUENCE>
      <COLUMN_NAME>SUPPLY_VENDOR</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>88</DISPLAY_SEQUENCE>
      <COLUMN_NAME>SUPPLY_VENDOR_SITE</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>86</DISPLAY_SEQUENCE>
      <COLUMN_NAME>SUPPLY_WIP_STATUS</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-27.0029</DISPLAY_SEQUENCE>
      <COLUMN_NAME>TASK</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>95</DISPLAY_SEQUENCE>
      <COLUMN_NAME>TRANSACTION_ID</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>106</DISPLAY_SEQUENCE>
      <COLUMN_NAME>TV_EAO_KEY</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>107</DISPLAY_SEQUENCE>
      <COLUMN_NAME>TV_EA_PO_QOHS</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-90.0103</DISPLAY_SEQUENCE>
      <COLUMN_NAME>Tax_Denomination</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>29</DISPLAY_SEQUENCE>
      <COLUMN_NAME>UOM</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
     <TEMPLATE_COLUMNS_ROW>
      <DISPLAY_SEQUENCE>-92.0093</DISPLAY_SEQUENCE>
      <COLUMN_NAME>level</COLUMN_NAME>
     </TEMPLATE_COLUMNS_ROW>
    </TEMPLATE_COLUMNS>
    <TEMPLATE_PIVOT>
     <TEMPLATE_PIVOT_ROW>
      <COLUMN_NAME>END_ASSEMBLY</COLUMN_NAME>
      <FIELD_TYPE>ROW</FIELD_TYPE>
      <DISPLAY_SEQUENCE>1</DISPLAY_SEQUENCE>
     </TEMPLATE_PIVOT_ROW>
     <TEMPLATE_PIVOT_ROW>
      <COLUMN_NAME>END_PEGGING_ID</COLUMN_NAME>
      <FIELD_TYPE>VALUE</FIELD_TYPE>
      <DISPLAY_SEQUENCE>1</DISPLAY_SEQUENCE>
      <AGGREGATION>COUNT</AGGREGATION>
     </TEMPLATE_PIVOT_ROW>
     <TEMPLATE_PIVOT_ROW>
      <COLUMN_NAME>END_PEG_ORDER_QOH</COLUMN_NAME>
      <FIELD_TYPE>ROW</FIELD_TYPE>
      <DISPLAY_SEQUENCE>6</DISPLAY_SEQUENCE>
     </TEMPLATE_PIVOT_ROW>
     <TEMPLATE_PIVOT_ROW>
      <COLUMN_NAME>END_PEG_QOH</COLUMN_NAME>
      <FIELD_TYPE>ROW</FIELD_TYPE>
      <DISPLAY_SEQUENCE>7</DISPLAY_SEQUENCE>
     </TEMPLATE_PIVOT_ROW>
     <TEMPLATE_PIVOT_ROW>
      <COLUMN_NAME>END_PEG_QOH_FULLFILL_STATUS</COLUMN_NAME>
      <FIELD_TYPE>ROW</FIELD_TYPE>
      <DISPLAY_SEQUENCE>6</DISPLAY_SEQUENCE>
     </TEMPLATE_PIVOT_ROW>
     <TEMPLATE_PIVOT_ROW>
      <COLUMN_NAME>INSTANCE</COLUMN_NAME>
      <FIELD_TYPE>ROW</FIELD_TYPE>
      <DISPLAY_SEQUENCE>2</DISPLAY_SEQUENCE>
     </TEMPLATE_PIVOT_ROW>
     <TEMPLATE_PIVOT_ROW>
      <COLUMN_NAME>PEG_DEMAND_ORIGINATION_TYPE</COLUMN_NAME>
      <FIELD_TYPE>ROW</FIELD_TYPE>
      <DISPLAY_SEQUENCE>13</DISPLAY_SEQUENCE>
     </TEMPLATE_PIVOT_ROW>
     <TEMPLATE_PIVOT_ROW>
      <COLUMN_NAME>PLAN</COLUMN_NAME>
      <FIELD_TYPE>ROW</FIELD_TYPE>
      <DISPLAY_SEQUENCE>3</DISPLAY_SEQUENCE>
     </TEMPLATE_PIVOT_ROW>
     <TEMPLATE_PIVOT_ROW>
      <COLUMN_NAME>level</COLUMN_NAME>
      <FIELD_TYPE>ROW</FIELD_TYPE>
      <DISPLAY_SEQUENCE>9</DISPLAY_SEQUENCE>
     </TEMPLATE_PIVOT_ROW>
    </TEMPLATE_PIVOT>
    <FILE_NAME>MSC Pegging Hierarchy - Enginatics Dashboard.xlsm</FILE_NAME>
    <FILE_LANGUAGE>US</FILE_LANGUAGE>
    <FILE_DATA>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
tO6+OIKY+xUwHNEztSu6LYq7hkQPXFFNdGQ7w2WxD1HHLyf7ZvW2vo7M1rJJd+RKhgJ59qfAyUqRg7ShqkXKx5oXcy/w6qKtVX1+oDUEsDBBQAAAAIAJJ1oVzHbYMjuAAAADQBAAAjAAAAeGwvd29ya3NoZWV0cy9fcmVscy9zaGVldDQueG1sLnJlbHOFj8EKwjAQRO+C/xD2blIVRKRpLyJ4lfoBa7ptg20SslH0782xguBtdod9s1PWr2kUT4psvdOwlgUIcsa31vUars1ptQfBCV2Lo3ek4U0MdbVclBcaMeUjHmxgkSmONQwphYNSbAaakKUP5LLT+ThhymPsVUBzx57Upih2Ks4ZUH0xxbnVEM/tGkTzDjn5P9t3nTV09OYxkUs/IlSwT58avI2UqRh7ShqknK15prcy/w6qKtVX1+oDUEsDBBQAAAAIAJJ1oVywWpsSuAAAADQBAAAjAAAAeGwvd29ya3NoZWV0cy9fcmVscy9zaGVldDUueG1sLnJlbHOFj8EKwjAQRO+C/xD2blJFRKRpLyJ4lfoBa7ptg20SslH0782xguBtdod9s1PWr2kUT4psvdOwlgUIcsa31vUars1ptQfBCV2Lo3ek4U0MdbVclBcaMeUjHmxgkSmONQwphYNSbAaakKUP5LLT+ThhymPsVUBzx57Upih2Ks4ZUH0xxbnVEM/tGkTzDjn5P9t3nTV09OYxkUs/IlSwT58avI2UqRh7ShqknK15prcy/w6qKtVX1+oDUEsDBBQAAAAIAJJ1oVyXP76TuAAAADQBAAAjAAAAeGwvd29ya3NoZWV0cy9fcmVscy9zaGVldDYueG1sLnJlbHOFj8EKwjAQRO+C/xD2blIFRaRpLyJ4lfoBa7ptg20SslH0782xguBtdod9s1PWr2kUT4psvdOwlgUIcsa31vUars1ptQfBCV2Lo3ek4U0MdbVclBcaMeUjHmxgkSmONQwphYNSbAaakKUP5LLT+ThhymPsVUBzx57Upih2Ks4ZUH0xxbnVEM/tGkTzDjn5P9t3nTV09OYxkUs/IlSwT58avI2UqRh7ShqknK15prcy/w6qKtVX1+oDUEsDBBQAAAAIAJJ1oVyZdEQnSgEAAHoEAAAjAAAAeGwvd29ya3NoZWV0cy9fcmVscy9zaGVldDcueG1sLnJlbHOtlE9LAzEQxe+C32HJ3cxu1Vak216K0KtW8Bqzs9tg/izJWO23N7q1NKVbEfYUMi95+eUNyXT+aXS2QR+UsyUreM4ytNJVyjYle149XN2xLJCwldDOYsm2GNh8dnkxfUQtKG4Ka9WGLLrYULI1UXsPEOQajQjctWijUjtvBMWpb6AV8k00CKM8H4M/9GCzxDNbViXzy+qaZattG0/+29vVtZK4cPLdoKUTR8DG6IUXH/Fy0VX4BqlknEPV1cKBXvC4lsFppkkPk1HSu+Bq4tIZ6HAiRlGkNwVSBrWymED8FsNeLngMr49hNGQuuwBOh7ITz9IUQ9K0XllC/4RE311JqI40OJqP+KuyfZGN/9e2fHLUtqBjP32C05UCdOPZiG6HjEiZ+IgSEoOVEvBTLziaui+EmyExpLPknU5AhCS1wRfYjftMIPkxZl9QSwMEFAAAAAgAknWhXAig0rzFBgAAdCMAABgAAAB4bC93b3Jrc2hlZXRzL3NoZWV0MS54bWylml1vnEYUhu8r9T8gLnqXheGb7a6ral0rkZoqqvuRXmKY3UUBZgs4tlP1v/cc4DBj2ZU4JHLM62V5OTM8c2bgsPvhsa6sz7LtStXsbbFxbUs2uSrK5rS3f//t5k1iW12fNUVWqUbu7SfZ2T9cffvN7kG1n7qzlL0FDk23t899f9k6TpefZZ11G3WRDew5qrbOevizPTndpZVZMRxUV47nupFTZ2Vjjw7bdomHOh7LXF6r/L6WTT+atLLKeoi/O5eXjtzqfIldnbWf7i9vclVfwOKurMr+aTC1rTrfvjs1qs3uKmj3owiy3Hps4ceD/z6dZvj8xZnqMm9Vp479BpydMeaXzU+d1Mny2ell+xfZiAA64HOJF1BbeetCEuHs5Wkzf6UZXpkxMOyudntfFnv7H3f69wa2An+5+hft+9e+2g2cfGgtgFH+ktVwDW7xExHaztWuKOHyo7PVyuPe/lFsrw/DjuGoP0r50BnaQljvlPqEO95BEC74X7JGWk+3F7jkAL5t9eryszz2B1lVYAjNz/K+/Cw/wNf29p3qe1Xj/mE49PDRsVVfZDOcU1YSvgvBoOfzL48m2rT7ewzYwwOdOVpTU+Q3w9CBHijkMbuv+oOq/iyL/gzRik3ghXEivNCmvb+qh7eyPJ2xMd4mhh0Dmtvi6Vp2OYwVaPVmOGuuKjgF/LbqEsc8oJ49DtuH0T7dJGEYRAma3Mmuv5l6KL/voBMohslqNIHuGkxgO5lERogLTYCSwQS2k4kINiJwI2zmQo9g8oDt5OHFGy8JRchxgfMNkcCWXKBPhZv6jD7BHIImsCUTdxPGrj9ctoXtiScT2JJJxO0TSOFDILCdPHxI8wsDSKeDYbu+KwScb4QMBD8GMTOqIfUEn1JBmKKYr8nirhAEKAo6HCLq+iecIpZfVEGUoiDUU2PA8B2JWEiPs2PMpk0Qsyh0YFxoBVGLYu4oYxjy20cMCw2xF+r28Q2Ja2GADX3HNvIIbRS6rTo/LxxnHjGOgnwSfury5lRsMO7zk7FHsKNYn788Qh2FJoqZ1TFhjvOLgTc/mXqENwoKxl/Rx8S3p/n2DRqXXnKC2jMyM/T20sMJYU8jvGKuw7lgnHY1wPx51yd8UayfKHyiFwV/ovDnJYSxhjDSIHt0+4QvCiImYudVn/hFQTYhe0XhE78otA1zMPlEr6+xw0S9EDufsEMxd8mKzBkQeCg0MuzMGRB6KPSoZq9hA2IPxdfEQxAGBoQJPwMH81rWWMx6bPYCYg+F7h7uajYg9lDokcDvZaIv0LkT13cL6QsoZ6LQQ4APDVEcaIoTdt+GhDAKioZ/pxASwSg0eey+DYlgFHrO5l7qkABG8TXhEMDhs7sx9rUK59sx434s5N4FhQQwCmqVz87BIfGLwkh/C/kNiV8U60djSPii0Msq9o1uRACj4M+3EYGLgsJYkeoiAheFTi7MiS0iblGQS2zcJrKn/4gIRjG3b3GyighcFHogUbP44cyPFAyEzWdBCyGMiGEU+p5lzhP8wIjqyLg9E/MI5fsR3pGBd8Id8THBjeKVZi7srZggR6Hh5GbVmBhHQTYBf1kQE+Uo9JzDHvoxsY3itdGytHsIcnw0picd7jODmNhGoXuZPVnE8xMzIz8vX93GRDIKvb5gT8UxEYziteawx0RCNKPQjtx+TohmFK9cLn5cxHXyLHevTyYJAY5CT9QacH6IhHpiLESgF/lGxHpirKVTvYbgGxL1iUF9zE8KCVGP4uVMs3AoJ/OTYgP+Fc+gEoIfhU68zOk8JeBR0NqEPQmkxDsKnXa52TslylGQjeA/OkoJbhQ6v7DTXEpIo9DxsPNUSkSj0N3Dnk1SAhmFXglyLzlhnBoY85+TpMQxijnHLV62pXPNw1xcLz5cuLraocmNXPathnDnugeqqSExdxkk3LnsgWqygaYtzArCneseqKbjwxXlF3eue6DS1DIpEe5c7UClJzHuoBZDnX+sS2ls4Uqxh6Nw55IHKv5Acsaq7FAQvs76jArCo87ue3VTVr1sjXo3VuhfK6qn/1tUx1q1avtbLGBPRh4UznWpv2qLtW8OxE5b5ucCwvWweA+nOaimKIey+FDyPvw11bwpAizBn+T7rD2VTWdVUFvHEjX0XjuWsQcNVflBYXFtqMHTX2d4lUTCKxPuBpg8KgV9M/4BjUTfW9nfX6Agf5HtbfkFynMAvGpLKIQP74rs7Qpeauly2A8n3OKbCe27QuDRo/PNYHm1U0Xxdvjg6rusvnx/+Pjxp8PWen97sD7IE0R+st6Wss3a/Py0c/SXd85zG2d+X+bqP1BLAwQUAAAACACSdaFcI5Cr10gGAAB6FwAAGAAAAHhsL3dvcmtzaGVldHMvc2hlZXQyLnhtbKVYbXOiSBD+flX3Hyg+3X1QGQRFK2aLxGSTfc0m+/6NwBipIOMCGlNX99/vmcEZcaRYyW1tQjvT89DT/XTb6ZNXm0VirGmWxyydmKRrmQZNQxbF6cPE/PL5suOZRl4EaRQkLKUT85nm5qvTP/84eWLZYz6ntDCAkOYTc14Uy3Gvl4dzugjyLlvSFDszli2CAh+zh16+zGgQiUOLpGdb1qC3COLULBHG2TEYbDaLQzpl4WpB06IEyWgSFLA/n8fLXKItwmPgFkH2uFp2QrZYAuI+TuLiWYCaxiIcXz+kLAvuE9x7Q5wgNDYZ/tv46cvXiPWDNy3iMGM5mxVdIPdKmw+vP+qNekGokA7vfxQMceCAdcwDuIOyX2YScRWWvQPrvxCMR6Y0jLsrG6/iaGL+Mzy/OCPO2UVnarvTjjPsWx2P+F7HvRh5nj8c4Gf0r3l6InhykxkgI/0QLBCDO77imL3TkyhG9DmwkdHZxPT7Y/+LyzfEoa8xfcorssG5es/YI9+4hg0Wh6cJDTlrjACPNT2nSQIkF3T/VYK6hn/ujv2pAF7Ga1bcqTPLgCfDPSsKtriNH+YFjs3Z0xX4TRFHgizaFBRZI8iDj8EmRo7w37fsCeQKNuWyeDeWJqZjGsiPdcxWXEV8zsbcY9l1RGCwsMBHBhlRUAQf0+SZX8RgqyKJuTGQZzFNohuWx/xe5TVxFZoho2kOR67Sgr+1sloemZj2yKzub4w1P457I4RbgKoM7/aUPVJW3sGCikNVljG5FDUBoY3oLFglBa57RbkTYZzdHSIEIqvG0fOU5iHSHLZ0bW5NyBKA4LexiHm52jnyKY6KOe5hdx3bHXrEBso9zYvLWFzZCFc5QvWt1CJbrBIFTBfhwHOL0n8BCiguUPDcoRDHGrSwBCEXGHhuMQjicuQ1cGFxGE95eNhtaQAvexwDT4nhdT3XdQYeD8uRlgy3KHhKFKfrDq1+m6jge0eYgqcE6XeHxBr1W1gC7wkQPCXIoHKfBlIQpFOZpBAkuay2/iSKoRDqLDjSo0RylAtbHNxpHkcRLfOg6SqSmmTHTbfihSNRJDnJjp2t+UUkSbkg0wQOPtYNkp+kQlC7PUGJZCgXdpXD9lzitslXIknKBZWx7SsQz/KSbDuiopK1tseWpOXC/6hltqQtF3a0bW+PKq072pIXFBRbMtiuVEavdTXglbis9JUa6bbNaVuSkAvSOXbr+mZLDnJBwljtYSQF7QoFrfaukQzkjYC0plokjszQvmQgF9Stjk7wviSeU/Gt2/o2jvQtF7ZWeEenU6/sMkQLM0WrhXaJPRno6sDCHI0f+jgy5si1XQraE67rc2XxTY7+I0fLtT61TnprtEOh1Dg/VCFKpYd3qhcDZe/FAEa0y5JfNlPiO4A3UC6ejXZxrH277H27zkoNBEBZ3t/XOD/UcPY1poca7r7GxaHGYF/j8lBjuK/x+lDD29e4OtQY7Wtclxr8e1Vdl2iRenOIQnaREuF+W6Oi+fVdjYrm2Pc1KppnP9SoaK79eBhiovn2pgZFc+6nGhXNu7c1Kpp77w5VbM27n2tUNO9+qVHRvPu1RkXz7rcaFc2732tUNO/+qFHRvPuzRkXzru/X6Gju9Wsy0db8629zcSgqTH/g2pot/jYVUS926axXIiQj/+NK1C2knZKRYEpGKikZSaNkJIeSkQVKBt2VDF4rGQRWMpiqZFBSyeCekkEyJYNNSgZtlAx+iD9VKyWT/x1/dK2G8s45GvfOmjbPmzYxOOClxRWhcfpeX0O+qO7XhO5yD1zj++vfHL5qsuy6tEkvc01H3jZtvivxOtoF35fL2uqH2pd/bMK/adr81LR52+TDu6aTn5s2MWyqceDX2tVvTUDfm+z70bT58zcE8Pkoa8dqrRb6jbTG3EtQd1Tbt2x5rW+W6VdOfsq2KWRpJEZRQVJ2KQWmymq8hpnda8fwiedyiVj8n+G7459YsfHicHa7SqhRPC8x3AoxnbvGbDfazPgAb4Dua5nFLMO4VrQ+mDZnQcFQwOivVZDgOB88r5Lg1PzrPgnSx7/Nk55cQg8msHkzVmciZm3BA30fZA9xmhsJnYkBFF6ZlUMqIRdsKSQ+FhFjQPlpvp0BWl30dzPGCj4Q5B94iVJT89P/AFBLAwQUAAAACACSdaFcE/dambcEAAC5DwAAGAAAAHhsL3dvcmtzaGVldHMvc2hlZXQzLnhtbKVXXXPiNhR970z/g8dP7QO2JdnGeIAdAsuGZJPuJtls2zdhBHhiW17bJGR2+t97JSObD5cBmiHoYF0fXekeXV11P6zjSHtlWR7ypKcjw9I1lgR8FiaLnv7tadzydC0vaDKjEU9YT39nuf6h/+sv3TeeveRLxgoNGJK8py+LIvVNMw+WLKa5wVOWQM+cZzEt4Ge2MPM0Y3QmX4ojE1uWa8Y0TPSSwc9O4eDzeRiwEQ9WMUuKkiRjES3A/3wZprlii4NT6GKavazSVsDjFCimYRQW75JU1+LAnywSntFpBPNeI5sG2jqDD4Z/ooaRzw9GisMg4zmfFwYwm6XPh9PvmB2TBhXT4fxPokE2LMBrKAJYU+HLXEJOxYVrMnIhmYhM6ZhYrsxfhbOe/tNC7nBso1GL2BZp2W1y1eq0PbflDQcjB7WviDUc/KP3u1InXzINxMjuaQwxeBRPHN3sd2chRF8Qaxmb9/QB8QefZId86Tlkb/kW1oRWp5y/iI4J+GAJehaxQKhGo9C8siGLImByQO4/SlJJaFaM21ixj6W6wckZm9NVVDzwt2sWLpYFbCVstIFM6sOfvY9YHoBgYWwDC96AR0AC31ocio0HeqNr2b6Fs2LZ07FjtJHVIYJkyvJiHApSXQtWecHj76UR2lCVJBAySQKtIsGGjZ22h/DpLBAryQKtYrEMp22Rc0jsDQm0GxJygSvgtHQF2g0L8gzPcWzXO2NZxF4WLNAqFnw+S3vDAq1iIWdHCJKpdAXa/+FKZ8MCbR0hZFvuGVFGkOhLxQFQLJ5xLkul21q46LhIkVKpAJuB3fPDgZRMBbhcp0gJVQAVEliRE3ccUgpFtSywdf6eQ0oYAlzghlIEroOJQO4nzgKrKApw/ui4yjtb+/SC7KX2KamFIcR54iRIlbdqQXgG9hzknLAvzDIfy2Q/ogXtdzP+psGJDGR5SkV9g3wxRGM+h0QubAfCuKeDkiBV53DGvPatrvkKB0ewsbg7tCB2ZWLCmNXAwLIzMBCDNsrsXx478jgQRw2Bef7XUaNcE3S7ruFd165KCwhC5Xxn12J4aEF2LUaHFvXs5BJ9bOBwdknGhybersWnQwu0t9DXDSZol2XS4Iq7a3LTwLK3bLeHC4vauyyfG0z2Brrb1gzZc/S+fB+iX0WG7E33D1sWAmKFv9Twaw0favhYw6cafqvhcw2/1/DPGv5Vw79rOBhsYVCTcmgAuqkwKKTCoIUKQ9ArDOEVhdf2ZhBV2cm7EIzrhdpby6tjncNjnaNjnR+Fg6JOEXveJt5+CMfb/cR18F78oXhtyBbXx4acNL5yc+yV22Odn4913pX+d5q8vG/uK+NXls9lRg14MgtFxU2jMoEVcMmsqm1RwhNtYFsYALLEn/ZsA7bhof8Vvh1/gqHBjn/jOtojtmz/CSNLG7iuf2tbCB4hJF6wEPgZzB9WEdOK9xRuDgEU9xO4Gs7Wc1H/E8hyaRbyDG57MovCZTWjBYftw36saASvi3vrKqJ9/bdpRJOX3/WuqR5BOpfcIq83TanfTemC3dFsESa5FrG5rPqhQMjKm4HEBU8lEnU5LyCnq19LuCIzcMQy4KyYc16oH2JPVJfu/r9QSwMEFAAAAAgAknWhXP0T5ZMdBAAAvAsAABgAAAB4bC93b3Jrc2hlZXRzL3NoZWV0NC54bWydVtty2zYQfe9M/4HDp/ZBJMGbJI6kDGVZidMmTRzHafsGUZDEMUkwJHTxZPLvPQBFQbKdRrbHNg5J4Oxi9+wCg1e7PDM2rKpTXgxNYjmmwYqEz9NiOTQ/30w7PdOoBS3mNOMFG5r3rDZfjX79ZbDl1V29YkwYYCjqobkSooxsu05WLKe1xUtW4MuCVzkVeKyWdl1WjM7VojyzXccJ7ZymhdkwRNU5HHyxSBM24ck6Z4VoSCqWUQH/61Va1i1bnpxDl9Pqbl12Ep6XoJilWSruFalp5El0tSx4RWcZ9r0jPk2MXYVfF39ea0a9f2QpT5OK13whLDDbjc+Pt9+3+zZNDkyP938WDfERgE0qE6ip3Je5RIIDl6vJvBeSycw0jslwVdE6nQ/Nb73peOJ404uON56Sjn95GXfiCQk6oT8NemE3di5C57s5GiidfKgMiJG9pzly8Em+CU17NJinyL4kNiq2GJqxF8Wvu/KDWnSbsm19hA2p1Rnnd/LDFXxwJD3LWCJVY1AMG3bBsmxojn3I/asiBQShfWA8xi37VKkbTs7Zgq4zcc23b1i6XAmUkmt1A2xb6iOa309YnUCwsG25kjfhGUjw38hTWXjQG92pcZvOxQrIs3pB4Ic9yTJjtZimktU0knUteP5lP2vP1bAgZ4oFY8sCeOZi5Egtxtgu7ltB1/GIe74HCJ8iQf3sSVzH8t2g23sOS3fPgrF1BX3pzH2gYTWh1LF8iQ+kDSYB4fO9IP02F/C8XY6onLkJtxWEBM+37h6UgNS1ywOrS5y+9xw9yTaoNHGkqPMz4R0kpTXVs9xeQILw55qymxJR9Tehgo4GFd8aaJIgq0sqjxwSSROy2tzA+lGxocrkqlguG5oQKKbXaACbkdcd2BuUdbKfMm6mIN96Su8wxYb5gw+yTRz70CxrSrNpCqpWn6z+1qETV/oPXJEGQBEqR8npxwvVmdSuJhpeajjV8LWGbzS80vCthn9o+KeG7zR8r+FfGn7Q8KOG1xp+0vBGw88a3mr4RcO/NfxHw381jOMj3LTrJtVHAYqPIhQfhSg+ilHcBOkkwVDTSYL/N5OYfFCM7zzIpGR6IpMn1lBn51vDZG3tgTTGkuln1tBWz7eGydqa+2BvkumH1pqjsyndhBfzVJ62NGvKQ+CC2Z606vj2jNglBIA48gdPjh/duMQxbn289Y2YhN3o2nUwMQyjjyQMAZzoIgww143GQd+IMdMlxsSPIEQYXVyvM2aI+xKXhwTn+xVuh/PdQl4BZIcsq5RXuPCpUsV9taKCQz7s65pmWC6vruuMjszfZhkt7n43B3b7Cj1Dccvm8dTORoOSLtk7Wi3TojYytlAHP6JVNZcDhQUvFZKnKxdoHO3TCrdkBkccCw1pwbloH6RID/fu0X9QSwMEFAAAAAgAknWhXDxcjZIcBAAAxAsAABgAAAB4bC93b3Jrc2hlZXRzL3NoZWV0NS54bWydVl1T4zYUfe9M/4PHT+1DYkv+SOJJshMSstB2t7ssy7Z9E46SeLAtr60QmE7/e49kbOWD0gAD+Nj33qOrq3MlDd89ZKl1z8sqEfnIJl3Xtngei0WSr0b21+t5p29blWT5gqUi5yP7kVf2u/GPPwy3oryr1pxLCwx5NbLXUhaR41Txmmes6oqC57AsRZkxiddy5VRFydlCB2WpQ103dDKW5HbNEJWncIjlMon5TMSbjOeyJil5yiTyr9ZJUTVsWXwKXcbKu03RiUVWgOI2SRP5qEltK4ujy1UuSnabYt4PxGex9VDil+LPa4bR349GypK4FJVYyi6YnTrn4+kPnIHD4pbpeP4n0RAfBbhP1AIaKvq2lEjQclFD5r2RTK1MnZgqVxltksXI/nvuefMw9M473hmZdnwy9Tv9M592pu75dEDIJHTD6T/2eKh18qm0IEb+kWVYgy/qS892xsNFgtVXxFbJlyN74kWT94Ey6KCbhG+rHWwprd4KcacMl8jBVfQ85bFSjcXwuOdTnqZgCiD37zWpJnRaxl3csM+1upHkgi/ZJpVXYnvBk9VaopVotwcyrY9o8TjjVQzBYuwuVbyxSEGC/1aWqMaD3tiDfm6ThVyPbIqa3fJKzhNFZlvxppIi+1YbyRNFHYyl0sF4NsFhtx8EfthXKZzIgvE0C54NS+/kYP8pGBFPwcR7fQrYa3QKeDYs2I9OzH/QlHCnhm7Xp0GvT+jpZSBNNcmbsiBNGhSZN5PAbnLiJGgjBAVeXwPaSgETbsKDbo+4A+8VUqBq+9NaMJIip6+E10rJaKnfpf2ABOH/r4RTt4buuxmTbDwsxdbC5giyqmDqqCGRGuLZ1kJPKd+Jch7ZkCW6p0K734+9/tC5RxPHTy6zZ1x6rYuDQduRQbM3Mpghjroj6y1At+iLCSmO/YQG+/mcHXt4+x7TYw9CDia1O2Of7hvP94wHkfM9o7sf+X6vkAeJX9RpoSKm1gfxl77esNTK/GLgrwb+ZuAHAz8a+LuBnwz8bOCVgV8MvDbwq4E3Bn4z8A8D/zTwLwMnkx2M5WqmNMHCtHi2g1Hw9jvq22KUUx0tuxJT587J4oazKfWhAhQT5Bhq0R8Yz18yzl8y4nj9b9qLPaN/0ET1EVq3cizyRaJOXZbWjSNx0WxPXHWMe9aEEgJAXPWDN9ePrilxrRsfX31rQsJedEVdOIZh9JmEIYAbTcMAvjQ6CwbWBJ6UWDM/gkAw6PJqk3JLPha4RMQ45y9xS1w8LNVVgCD1okxEiYufbmLcW0smBZTKv29YinB1hd2kbGz/dJuy/O5ne+g0n7CbaG61rTw3s/GwYCv+gZWrJK+slC/1BQCHZFlfEjSWotBInVFCYktp3ta4LXMk4naxVS2FkM2LEk97/x7/C1BLAwQUAAAACACSdaFcTWEm8UwEAACNDAAAGAAAAHhsL3dvcmtzaGVldHMvc2hlZXQ2LnhtbJ1XW3ObRhR+70z/ww5P7YOAXS6SGEkZLFmx0iZNHMdp+7aClcQYWAKri6fT/96zi2GF7KSSNZb44Jz99uy5cTx6c8hStGNllfB8bGDTNhDLIx4n+XpsfLmb9wYGqgTNY5rynI2NR1YZbyY//zTa8/Kh2jAmEDDk1djYCFEEllVFG5bRyuQFy0Gy4mVGBdyWa6sqSkZjtShLLWLbvpXRJDdqhqA8h4OvVknEZjzaZiwXNUnJUirA/mqTFFXDlkXn0GW0fNgWvYhnBVAskzQRj4rUQFkULNY5L+kyhXMfsEsjdCjhj8DXabZRz5/tlCVRySu+EiYwW7XNz48/tIYWjVqm5+c/iwa74IBdIgOoqcjrTMJey0U0mfNKMhmZ2jDprjLYJvHY+Gcw9Z0+uSa9K9sZ9lyHzHvDsO/3HP/auxrY09D2Z/8ak5HKk48lgmRkH2gGMfgsn2DbsCajOIHwS2ZUstXYCJ0gfOtJgVp1n7B9dYSRTNYl5w9SsAAjbMnPUhbJtEEULjs2ZWk6NqYuhoT/plglBkqr5TzGDf9cJTjYGbMV3abilu9vWLLeCKgmYvY9OLlMkSB+nLEqgpyF3U0ieSOeAgn8oiyRtQcpRw/quk9isRkbBNy2ZJWYJ5LMQNG2Ejz7WguVae1iiJZaDCuaxb458DzXH0gTzmRxn1jg2rB4Zh/bQ+cCEthOmQJXTXKxKbIAJcuwZcHO5QeCZHlyKoAna+SzM/2B25gcBcU2XeL1B5ic71fchAdDN32FGeAE5QxydApw0JmnIM0pJLh8d9IYLw/cLL88LUgTUQf4LrfCgcyuM1yn+MAkAw97/v9HwqprTRXyjAo6GZV8j6DhAllVUPn6woFkfrFWoc6kbiiVxwYUB5RjBR1kN3EGI2sHXSF6Upm/oNJvVSzYtN0ZaDo7AzMkR13idU9RNS/7CPHM77WRxjTJ1jXNdbqmXb2g4nZVprUKBKo94Mn5Zs9Jhl2O6+caJ4bMjx3oku7ytx0h7gpvOkK7K1x04nJi1bvaKnCwDt3J+t9c1VBloH/X8L2GHzT8Q8OPGn7S8FbDzxreafhFw3sNv2r4p4Z/afi3hmF4hCG4jfEhRLHFEK8WQ2RaDDFoMbhcvuSOcxOy7fyqAOXWqa53knQdoX+SbnIb+Z5QleR75EQ+r+XYVwonuQBv++8Lb34kXPxI+K4j1PVRu6eeBOoGEvE8TuT4QNO6XAWMzM3koOYRB4UEYwDYlh+4s93gjmAb3bvw1EUh9vvBLbFB0feDT9j3AdjB1PdAlwRX3hCFoEkwmrkBZBdsurrdpgyJxwLGoQgGlgXMu/FhJWeavoGKMuElTLCqc8AAXlLBIZ/Zty1NYbWcxbcpnRi/LFOaP/xqjKzmEbQwRS172UsHm4wKumbvablO8gqlbKXGGNiyrEcdhQUvFJIvRi6gjzV3Gxj7GRhim9AfV5yL5kYmXvuPxOQ/UEsDBBQAAAAIAJJ1oVyBHpmunQUAAIYOAAAYAAAAeGwvd29ya3NoZWV0cy9zaGVldDcueG1srVdbb9pIFH5faf+D5Xfj+w0BFZiwGyntVk03fR7sAUaxPd7xEJJW/e/7zdgYkqgt262UwPEZn+/czxkmbx6r0nigomW8npruyDENWue8YPV2av79cWUlptFKUhek5DWdmk+0Nd/Mfv9tcuDivt1RKg0g1O3U3EnZjG27zXe0Iu2IN7TGyYaLikg8iq3dNoKSQgtVpe05TmRXhNVmhzAWl2DwzYbldMnzfUVr2YEIWhIJ+9sda9oj2mNxEV4hyAG+Hu05M3HZnQx4bvDKvorlgrd8I0c5r+zOtNdepnb6zM8qv8TRioj7fWMBuIFza1Yy+aTdNY0qH19vay7IukRGHt2A5MajwJ+Hf//MYPJa0+Umk3xAeh3Ji2DcAKl5YKq0TlDez0XRDQcs7wTm/ySYqpnOMBUuMd6zYmp+WaVZvFy5c2sRXaVWsIpW1jzKFpYX+pkXOKkbpt5XczbRFfxeGGgT+o5UyMGt4rimPZsUDHWpgA1BN1PzLvDH8ywJ1ZEWu2P00J7RRrvjhz8EK25YTdFF6D9J1re0pLmkMMo1jc+cV7c5UblOcTw8vlOtVXZM1Y1rzu8V/DXEHGWmBlGmEHw90IyWeHueALL9R1unaBhmD5ad00crV7qD4W5BN2Rfyg/88Cdl252Ecd4oDhFAVYHj4mlJ2xxNCe0jT+HmvAQIPo2KYbh4SFxFHjviwAq5A0I08pLQDSMPOPm+lbz61J/0CL0s8tTJguhlvXQUeGGcuD+SDY6yIE563cD5oVYY1WkFcZS8VKtqVC0bD7Lp6BKlmLidIIijUmeUhGEQJSrc3wtTepQFcQyT990w2V2WdAksiSSzieAHAx0fINJtQ9Ro99KxB0Cd8m/kO0TB5UpsnmlBvBno2gLaABmiUo+Q/lil8iLIT1pO636JiM4aEL2xKqyLEO+0HBD9E2LXBV0I+g7nsm+grpVueH5PC9VGStQ0GvbA5Uc1hXXjqu6H9B0pGb7VPsKE2Kt+8BCc50eGfGrQz4cdL6lpkLLkh0VJ6nuNq0bCdd3s5VvatmSL93rmlRBcnDOpYnxkUs0GfYjtrb6m5vuSkpYiNjRnmyeDGA+k3FNjTeWB0tpwDKx0w8c+UaHtp4HO3DAN09i9ipdxYLneaoFpuEysNF6mVhwkvhf5vpcsEzUN1Ybfl8SdORN7oI9cb6Z1DCceKuJ5JL4RmZK18hcF5rqG76wwriWtkDSBjSr7mHWs3n9dZoP7bhbNF1dJYi1cP7GCMEmt1MdaSNx0FWVBEs2vsmfuK6wbWH0ehVe+vmCg8Rok+C0RW4ZyKelGT09MDNFNWE1L3mgKNbvmEiPy+LTDdYoi2c4IidtwlGv/gFJUuLdU7hujIQ0Vt+yz2h+mwQXDjNb1OTUbLqQgDJHegf+Z46BcNkyvIVwKJcPaOT6LsVqS4rro9lx3OzIGrp74Jd2S/Km/OZ3OdJflQBd61uD+Mi9ha00kzcCFPf0V8P9ejTR2tuO4hxkf6D97JlRrYj+p6dTpR3chHmpH+k6KGT04gOVQ62V+Q9a0dE8Sp9XXBRGxIXvJ1cLWDwOCmoGkzhFKo+IP9BOTu2FYoE9QeLMJrqVjTNyZ507sI31k/rXZzIIYS2k4Uhx9qqZokHZ8PVF7Qr3gJ67qsDMOSlArk/zHCpMoiuNvaAxPsM80wsZXGpUuu/MeRB/s92c0uENydJ5WGHtrkt//99SoLfAMQD29LKmTFSg5+ihvWqm/jb1AgX+ZJ3EULua454XR3AoKsrYWwcq35tkq8ZPM9dzl1ddfePlHAN1g3JYoTaHGxPnzqYQivY9evmnD7HPb4yvHX6ZpZi0zJ7CCtFCzyQ3x4XhOMI/V/fXM9vAnb8mO7brdLxdlbDiWuNuWqPoPdIOQvuCcfIh7H14KdF6oT50Ke/gFOfsXUEsBAhQAFAAAAAgAknWhXJ54jAWVAwAAFiMAABMAAAAAAAAAAAAgALaBAAAAAFtDb250ZW50X1R5cGVzXS54bWxQSwECFAAUAAAACACSdaFctVUwI+4AAABMAgAACwAAAAAAAAAAACAAtoHGAwAAX3JlbHMvLnJlbHNQSwECFAAUAAAACACSdaFcdD85erwAAAAoAQAAHgAAAAAAAAAAACAAtoHdBAAAY3VzdG9tWG1sL19yZWxzL2l0ZW0xLnhtbC5yZWxzUEsBAhQAFAAAAAgAknWhXB/QP6u9AAAAKQEAAB8AAAAAAAAAAAAgALaB1QUAAGN1c3RvbVhtbC9fcmVscy9pdGVtMTAueG1sLnJlbHNQSwECFAAUAAAACACSdaFcOLUaKr0AAAApAQAAHwAAAAAAAAAAACAAtoHPBgAAY3VzdG9tWG1sL19yZWxzL2l0ZW0xMS54bWwucmVsc1BLAQIUABQAAAAIAJJ1oVwQHARyvQAAACkBAAAfAAAAAAAAAAAAIAC2gckHAABjdXN0b21YbWwvX3JlbHMvaXRlbTEyLnhtbC5yZWxzUEsBAhQAFAAAAAgAknWhXDd5IfO+AAAAKQEAAB8AAAAAAAAAAAAgALaBwwgAAGN1c3RvbVhtbC9fcmVscy9pdGVtMTMueG1sLnJlbHNQSwECFAAUAAAACACSdaFcQE45wr4AAAApAQAAHwAAAAAAAAAAACAAtoG+CQAAY3VzdG9tWG1sL19yZWxzL2l0ZW0xNC54bWwucmVsc1BLAQIUABQAAAAIAJJ1oVxnKxxDvgAAACkBAAAfAAAAAAAAAAAAIAC2gbkKAABjdXN0b21YbWwvX3JlbHMvaXRlbTE1LnhtbC5yZWxzUEsBAhQAFAAAAAgAknWhXE+CAhu9AAAAKQEAAB8AAAAAAAAAAAAgALaBtAsAAGN1c3RvbVhtbC9fcmVscy9pdGVtMTYueG1sLnJlbHNQSwECFAAUAAAACACSdaFcXJYnIr0AAAAoAQAAHgAAAAAAAAAAACAAtoGuDAAAY3VzdG9tWG1sL19yZWxzL2l0ZW0yLnhtbC5yZWxzUEsBAhQAFAAAAAgAknWhXHvzAqO9AAAAKAEAAB4AAAAAAAAAAAAgALaBpw0AAGN1c3RvbVhtbC9fcmVscy9pdGVtMy54bWwucmVsc1BLAQIUABQAAAAIAJJ1oVwMxBqSvQAAACgBAAAeAAAAAAAAAAAAIAC2gaAOAABjdXN0b21YbWwvX3JlbHMvaXRlbTQueG1sLnJlbHNQSwECFAAUAAAACACSdaFcK6E/E70AAAAoAQAAHgAAAAAAAAAAACAAtoGZDwAAY3VzdG9tWG1sL19yZWxzL2l0ZW01LnhtbC5yZWxzUEsBAhQAFAAAAAgAknWhXAMIIUu9AAAAKAEAAB4AAAAAAAAAAAAgALaBkhAAAGN1c3RvbVhtbC9fcmVscy9pdGVtNi54bWwucmVsc1BLAQIUABQAAAAIAJJ1oVwkbQTKvQAAACgBAAAeAAAAAAAAAAAAIAC2gYsRAABjdXN0b21YbWwvX3JlbHMvaXRlbTcueG1sLnJlbHNQSwECFAAUAAAACACSdaFc7WYRKb0AAAAoAQAAHgAAAAAAAAAAACAAtoGEEgAAY3VzdG9tWG1sL19yZWxzL2l0ZW04LnhtbC5yZWxzUEsBAhQAFAAAAAgAknWhXMoDNKi9AAAAKAEAAB4AAAAAAAAAAAAgALaBfRMAAGN1c3RvbVhtbC9fcmVscy9pdGVtOS54bWwucmVsc1BLAQIUABQAAAAIAJJ1oVxSI/I5bBUAAA6fAQATAAAAAAAAAAAAIAC2gXYUAABjdXN0b21YbWwvaXRlbTEueG1sUEsBAhQAFAAAAAgAknWhXGHt4mNEAQAA6gIAABQAAAAAAAAAAAAgALaBEyoAAGN1c3RvbVhtbC9pdGVtMTAueG1sUEsBAhQAFAAAAAgAknWhXBmRH/zjAQAArgUAABQAAAAAAAAAAAAgALaBiSsAAGN1c3RvbVhtbC9pdGVtMTEueG1sUEsBAhQAFAAAAAgAknWhXKaTImO8AAAAZAEAABQAAAAAAAAAAAAgALaBni0AAGN1c3RvbVhtbC9pdGVtMTIueG1sUEsBAhQAFAAAAAgAknWhXGoy1EeqAAAAOAEAABQAAAAAAAAAAAAgALaBjC4AAGN1c3RvbVhtbC9pdGVtMTMueG1sUEsBAhQAFAAAAAgAknWhXC6d9hK5AAAATgEAABQAAAAAAAAAAAAgALaBaC8AAGN1c3RvbVhtbC9pdGVtMTQueG1sUEsBAhQAFAAAAAgAknWhXCecf7W3AAAATgEAABQAAAAAAAAAAAAgALaBUzAAAGN1c3RvbVhtbC9pdGVtMTUueG1sUEsBAhQAFAAAAAgAknWhXAjMxC+uAAAAPAEAABQAAAAAAAAAAAAgALaBPDEAAGN1c3RvbVhtbC9pdGVtMTYueG1sUEsBAhQAFAAAAAgAknWhXOWKP5qvAAAAQgEAABMAAAAAAAAAAAAgALaBHDIAAGN1c3RvbVhtbC9pdGVtMi54bWxQSwECFAAUAAAACACSdaFc8q/D0rkAAABgAQAAEwAAAAAAAAAAACAAtoH8MgAAY3VzdG9tWG1sL2l0ZW0zLnhtbFBLAQIUABQAAAAIAJJ1oVxX7pBjsgAAAEQBAAATAAAAAAAAAAAAIAC2geYzAABjdXN0b21YbWwvaXRlbTQueG1sUEsBAhQAFAAAAAgAknWhXGXTT3nnCwAATqsAABMAAAAAAAAAAAAgALaByTQAAGN1c3RvbVhtbC9pdGVtNS54bWxQSwECFAAUAAAACACSdaFclIXQ2VkKAAAq3QAAEwAAAAAAAAAAACAAtoHhQAAAY3VzdG9tWG1sL2l0ZW02LnhtbFBLAQIUABQAAAAIAJJ1oVwB1wfhugAAAE4BAAATAAAAAAAAAAAAIAC2gWtLAABjdXN0b21YbWwvaXRlbTcueG1sUEsBAhQAFAAAAAgAknWhXCeP9GOsAQAASgQAABMAAAAAAAAAAAAgALaBVkwAAGN1c3RvbVhtbC9pdGVtOC54bWxQSwECFAAUAAAACACSdaFcOv7UybIAAABEAQAAEwAAAAAAAAAAACAAtoEzTgAAY3VzdG9tWG1sL2l0ZW05LnhtbFBLAQIUABQAAAAIAJJ1oVzuL0AYwQAAAOsAAAAYAAAAAAAAAAAAIAC2gRZPAABjdXN0b21YbWwvaXRlbVByb3BzMS54bWxQSwECFAAUAAAACACSdaFckJj/+cEAAADrAAAAGQAAAAAAAAAAACAAtoENUAAAY3VzdG9tWG1sL2l0ZW1Qcm9wczEwLnhtbFBLAQIUABQAAAAIAJJ1oVyVqbfVwQAAAOsAAAAZAAAAAAAAAAAAIAC2gQVRAABjdXN0b21YbWwvaXRlbVByb3BzMTEueG1sUEsBAhQAFAAAAAgAknWhXMPViR/CAAAA6wAAABkAAAAAAAAAAAAgALaB/VEAAGN1c3RvbVhtbC9pdGVtUHJvcHMxMi54bWxQSwECFAAUAAAACACSdaFcqvgRxMAAAADrAAAAGQAAAAAAAAAAACAAtoH2UgAAY3VzdG9tWG1sL2l0ZW1Qcm9wczEzLnhtbFBLAQIUABQAAAAIAJJ1oVxvRT4WwgAAAOsAAAAZAAAAAAAAAAAAIAC2ge1TAABjdXN0b21YbWwvaXRlbVByb3BzMTQueG1sUEsBAhQAFAAAAAgAknWhXOTtD0LBAAAA6wAAABkAAAAAAAAAAAAgALaB5lQAAGN1c3RvbVhtbC9pdGVtUHJvcHMxNS54bWxQSwECFAAUAAAACACSdaFcbsDH3sEAAADrAAAAGQAAAAAAAAAAACAAtoHeVQAAY3VzdG9tWG1sL2l0ZW1Qcm9wczE2LnhtbFBLAQIUABQAAAAIAJJ1oVweSX7KwQAAAOsAAAAYAAAAAAAAAAAAIAC2gdZWAABjdXN0b21YbWwvaXRlbVByb3BzMi54bWxQSwECFAAUAAAACACSdaFcEdP758IAAADrAAAAGAAAAAAAAAAAACAAtoHNVwAAY3VzdG9tWG1sL2l0ZW1Qcm9wczMueG1sUEsBAhQAFAAAAAgAknWhXBD8+77AAAAA6wAAABgAAAAAAAAAAAAgALaBxVgAAGN1c3RvbVhtbC9pdGVtUHJvcHM0LnhtbFBLAQIUABQAAAAIAJJ1oVzcC0EewgAAAOsAAAAYAAAAAAAAAAAAIAC2gbtZAABjdXN0b21YbWwvaXRlbVByb3BzNS54bWxQSwECFAAUAAAACACSdaFcnRKJ+cEAAADrAAAAGAAAAAAAAAAAACAAtoGzWgAAY3VzdG9tWG1sL2l0ZW1Qcm9wczYueG1sUEsBAhQAFAAAAAgAknWhXIZWJITBAAAA6wAAABgAAAAAAAAAAAAgALaBqlsAAGN1c3RvbVhtbC9pdGVtUHJvcHM3LnhtbFBLAQIUABQAAAAIAJJ1oVwH7hlAwAAAAOsAAAAYAAAAAAAAAAAAIAC2gaFcAABjdXN0b21YbWwvaXRlbVByb3BzOC54bWxQSwECFAAUAAAACACSdaFcMb8oRcEAAADrAAAAGAAAAAAAAAAAACAAtoGXXQAAY3VzdG9tWG1sL2l0ZW1Qcm9wczkueG1sUEsBAhQAFAAAAAgAknWhXM4C44O/AQAAvwMAABAAAAAAAAAAAAAgALaBjl4AAGRvY1Byb3BzL2FwcC54bWxQSwECFAAUAAAACACSdaFcF6s+8TwBAABRAgAAEQAAAAAAAAAAACAAtoF7YAAAZG9jUHJvcHMvY29yZS54bWxQSwECFAAUAAAACACSdaFcK1BKEcECAACLGQAAGgAAAAAAAAAAACAAtoHmYQAAeGwvX3JlbHMvd29ya2Jvb2sueG1sLnJlbHNQSwECFAAUAAAACACSdaFcUycvuMAAAAAfAQAAIgAAAAAAAAAAACAAtoHfZAAAeGwvYWN0aXZlWC9fcmVscy9hY3RpdmVYMS54bWwucmVsc1BLAQIUABQAAAAIAJJ1oVxNChNuRgAAAEwAAAAXAAAAAAAAAAAAIAC2gd9lAAB4bC9hY3RpdmVYL2FjdGl2ZVgxLmJpblBLAQIUABQAAAAIAJJ1oVw1jjge5AAAAC4BAAAXAAAAAAAAAAAAIAC2gVpmAAB4bC9hY3RpdmVYL2FjdGl2ZVgxLnhtbFBLAQIUABQAAAAIAJJ1oVyAG9yBzAAAAI8BAAAfAAAAAAAAAAAAIAC2gXNnAAB4bC9jaGFydHMvX3JlbHMvY2hhcnQxLnhtbC5yZWxzUEsBAhQAFAAAAAgAknWhXBHKeiHMAAAAjwEAAB8AAAAAAAAAAAAgALaBfGgAAHhsL2NoYXJ0cy9fcmVscy9jaGFydDIueG1sLnJlbHNQSwECFAAUAAAACACSdaFcoXjI980AAACPAQAAHwAAAAAAAAAAACAAtoGFaQAAeGwvY2hhcnRzL19yZWxzL2NoYXJ0My54bWwucmVsc1BLAQIUABQAAAAIAJJ1oVyoJFjaJg0AAKWEAAAUAAAAAAAAAAAAIAC2gY9qAAB4bC9jaGFydHMvY2hhcnQxLnhtbFBLAQIUABQAAAAIAJJ1oVww5naoPAoAAPg3AAAUAAAAAAAAAAAAIAC2ged3AAB4bC9jaGFydHMvY2hhcnQyLnhtbFBLAQIUABQAAAAIAJJ1oVxL+a4T5wwAAJB4AAAUAAAAAAAAAAAAIAC2gVWCAAB4bC9jaGFydHMvY2hhcnQzLnhtbFBLAQIUABQAAAAIAJJ1oVwcFKeo9gAAAG4DAAAVAAAAAAAAAAAAIAC2gW6PAAB4bC9jaGFydHMvY29sb3JzMS54bWxQSwECFAAUAAAACACSdaFcHBSnqPYAAABuAwAAFQAAAAAAAAAAACAAtoGXkAAAeGwvY2hhcnRzL2NvbG9yczIueG1sUEsBAhQAFAAAAAgAknWhXBwUp6j2AAAAbgMAABUAAAAAAAAAAAAgALaBwJEAAHhsL2NoYXJ0cy9jb2xvcnMzLnhtbFBLAQIUABQAAAAIAJJ1oVxf9EpbiQQAAJ8lAAAUAAAAAAAAAAAAIAC2gemSAAB4bC9jaGFydHMvc3R5bGUxLnhtbFBLAQIUABQAAAAIAJJ1oVyFxSgirQQAAF4mAAAUAAAAAAAAAAAAIAC2gaSXAAB4bC9jaGFydHMvc3R5bGUyLnhtbFBLAQIUABQAAAAIAJJ1oVxf9EpbiQQAAJ8lAAAUAAAAAAAAAAAAIAC2gYOcAAB4bC9jaGFydHMvc3R5bGUzLnhtbFBLAQIUABQAAAAIAJJ1oVwu+XQQfQIAAFgFAAASAAAAAAAAAAAAIAC2gT6hAAB4bC9jb25uZWN0aW9ucy54bWxQSwECFAAUAAAACACSdaFcoZLUJ+oAAABDAwAAIwAAAAAAAAAAACAAtoHrowAAeGwvZHJhd2luZ3MvX3JlbHMvZHJhd2luZzEueG1sLnJlbHNQSwECFAAUAAAACACSdaFcCyj0NLgAAAAkAQAAJgAAAAAAAAAAACAAtoEWpQAAeGwvZHJhd2luZ3MvX3JlbHMvdm1sRHJhd2luZzEudm1sLnJlbHNQSwECFAAUAAAACACSdaFceMAM2zYNAAB5XgAAGAAAAAAAAAAAACAAtoESpgAAeGwvZHJhd2luZ3MvZHJhd2luZzEueG1sUEsBAhQAFAAAAAgAknWhXIotjzEvAgAAJQQAABsAAAAAAAAAAAAgALaBfrMAAHhsL2RyYXdpbmdzL3ZtbERyYXdpbmcxLnZtbFBLAQIUABQAAAAIAJJ1oVw7+igwUAIAABAFAAATAAAAAAAAAAAAIAC2gea1AAB4bC9tZWRpYS9pbWFnZTEuZW1mUEsBAhQAFAAAAAgAknWhXKJFbmy8AAAAzQEAABMAAAAAAAAAAAAgALaBZ7gAAHhsL21lZGlhL2ltYWdlMi5wbmdQSwECFAAUAAAACACSdaFcLmBVm+kqAAD8KwAAEwAAAAAAAAAAACAAtoFUuQAAeGwvbWVkaWEvaW1hZ2UzLnBuZ1BLAQIUABQAAAAIAJJ1oVzqAclpjaYDAABQFAASAAAAAAAAAAAAIAC2gW7kAAB4bC9tb2RlbC9pdGVtLmRhdGFQSwECFAAUAAAACACSdaFcDDGZkYcUAABY3QAAJwAAAAAAAAAAACAAtoEriwQAeGwvcGl2b3RDYWNoZS9waXZvdENhY2hlRGVmaW5pdGlvbjEueG1sUEsBAhQAFAAAAAgAknWhXAXH5uBLEgAAxL4AACcAAAAAAAAAAAAgALaB958EAHhsL3Bpdm90Q2FjaGUvcGl2b3RDYWNoZURlZmluaXRpb24yLnhtbFBLAQIUABQAAAAIAJJ1oVwPcaNEHRMAACnGAAAnAAAAAAAAAAAAIAC2gYeyBAB4bC9waXZvdENhY2hlL3Bpdm90Q2FjaGVEZWZpbml0aW9uMy54bWxQSwECFAAUAAAACACSdaFc8/0BCJESAADFwAAAJwAAAAAAAAAAACAAtoHpxQQAeGwvcGl2b3RDYWNoZS9waXZvdENhY2hlRGVmaW5pdGlvbjQueG1sUEsBAhQAFAAAAAgAknWhXHNXoIRUEgAAj74AACcAAAAAAAAAAAAgALaBv9gEAHhsL3Bpdm90Q2FjaGUvcGl2b3RDYWNoZURlZmluaXRpb241LnhtbFBLAQIUABQAAAAIAJJ1oVxmjl50Yw8AADGuAAAnAAAAAAAAAAAAIAC2gVjrBAB4bC9waXZvdENhY2hlL3Bpdm90Q2FjaGVEZWZpbml0aW9uNi54bWxQSwECFAAUAAAACACSdaFc7GNLT5cPAAD2rgAAJwAAAAAAAAAAACAAtoEA+wQAeGwvcGl2b3RDYWNoZS9waXZvdENhY2hlRGVmaW5pdGlvbjcueG1sUEsBAhQAFAAAAAgAknWhXApBDOq9AAAARwEAACkAAAAAAAAAAAAgALaB3AoFAHhsL3Bpdm90VGFibGVzL19yZWxzL3Bpdm90VGFibGUxLnhtbC5yZWxzUEsBAhQAFAAAAAgAknWhXAWNNzO9AAAARwEAACkAAAAAAAAAAAAgALaB4AsFAHhsL3Bpdm90VGFibGVzL19yZWxzL3Bpdm90VGFibGUyLnhtbC5yZWxzUEsBAhQAFAAAAAgAknWhXCLoErK9AAAARwEAACkAAAAAAAAAAAAgALaB5AwFAHhsL3Bpdm90VGFibGVzL19yZWxzL3Bpdm90VGFibGUzLnhtbC5yZWxzUEsBAhQAFAAAAAgAknWhXFXfCoO9AAAARwEAACkAAAAAAAAAAAAgALaB6A0FAHhsL3Bpdm90VGFibGVzL19yZWxzL3Bpdm90VGFibGU0LnhtbC5yZWxzUEsBAhQAFAAAAAgAknWhXHK6LwK9AAAARwEAACkAAAAAAAAAAAAgALaB7A4FAHhsL3Bpdm90VGFibGVzL19yZWxzL3Bpdm90VGFibGU1LnhtbC5yZWxzUEsBAhQAFAAAAAgAknWhXP6TT0n8CQAA/2IAAB4AAAAAAAAAAAAgALaB8A8FAHhsL3Bpdm90VGFibGVzL3Bpdm90VGFibGUxLnhtbFBLAQIUABQAAAAIAJJ1oVyu9U1GxQcAABQzAAAeAAAAAAAAAAAAIAC2gSgaBQB4bC9waXZvdFRhYmxlcy9waXZvdFRhYmxlMi54bWxQSwECFAAUAAAACACSdaFc4qNbCLkHAADJLgAAHgAAAAAAAAAAACAAtoEpIgUAeGwvcGl2b3RUYWJsZXMvcGl2b3RUYWJsZTMueG1sUEsBAhQAFAAAAAgAknWhXPrxc80HCAAAZTAAAB4AAAAAAAAAAAAgALaBHioFAHhsL3Bpdm90VGFibGVzL3Bpdm90VGFibGU0LnhtbFBLAQIUABQAAAAIAJJ1oVyOYnbVRAgAABwyAAAeAAAAAAAAAAAAIAC2gWEyBQB4bC9waXZvdFRhYmxlcy9waXZvdFRhYmxlNS54bWxQSwECFAAUAAAACACSdaFc7wZEWUcAAADcAAAAJwAAAAAAAAAAACAAtoHhOgUAeGwvcHJpbnRlclNldHRpbmdzL3ByaW50ZXJTZXR0aW5nczEuYmluUEsBAhQAFAAAAAgAknWhXPUrfDM0AAAA3AAAACcAAAAAAAAAAAAgALaBbTsFAHhsL3ByaW50ZXJTZXR0aW5ncy9wcmludGVyU2V0dGluZ3MyLmJpblBLAQIUABQAAAAIAJJ1oVxFJ3WTMAIAAHEFAAAgAAAAAAAAAAAAIAC2geY7BQB4bC9zbGljZXJDYWNoZXMvc2xpY2VyQ2FjaGUxLnhtbFBLAQIUABQAAAAIAJJ1oVzajbBCJQIAAFkFAAAgAAAAAAAAAAAAIAC2gVQ+BQB4bC9zbGljZXJDYWNoZXMvc2xpY2VyQ2FjaGUyLnhtbFBLAQIUABQAAAAIAJJ1oVxHJluOKAIAAGEFAAAgAAAAAAAAAAAAIAC2gbdABQB4bC9zbGljZXJDYWNoZXMvc2xpY2VyQ2FjaGUzLnhtbFBLAQIUABQAAAAIAJJ1oVxXcMVmGAIAAEsFAAAgAAAAAAAAAAAAIAC2gR1DBQB4bC9zbGljZXJDYWNoZXMvc2xpY2VyQ2FjaGU0LnhtbFBLAQIUABQAAAAIAJJ1oVyQLc0IBgIAANMEAAAgAAAAAAAAAAAAIAC2gXNFBQB4bC9zbGljZXJDYWNoZXMvc2xpY2VyQ2FjaGU1LnhtbFBLAQIUABQAAAAIAJJ1oVy65t4yFAIAACMFAAAgAAAAAAAAAAAAIAC2gbdHBQB4bC9zbGljZXJDYWNoZXMvc2xpY2VyQ2FjaGU2LnhtbFBLAQIUABQAAAAIAJJ1oVwGnPRwdwIAAEYGAAAWAAAAAAAAAAAAIAC2gQlKBQB4bC9zbGljZXJzL3NsaWNlcjEueG1sUEsBAhQAFAAAAAgAknWhXKsqme42BQAAHBwAAA0AAAAAAAAAAAAgALaBtEwFAHhsL3N0eWxlcy54bWxQSwECFAAUAAAACACSdaFcwofb8lEGAADXGwAAEwAAAAAAAAAAACAAtoEVUgUAeGwvdGhlbWUvdGhlbWUxLnhtbFBLAQIUABQAAAAIAJJ1oVwDW5puzQEAAN0DAAAkAAAAAAAAAAAAIAC2gZdYBQB4bC90aW1lbGluZUNhY2hlcy90aW1lbGluZUNhY2hlMS54bWxQSwECFAAUAAAACACSdaFcyJrkAGQBAAB4AgAAGgAAAAAAAAAAACAAtoGmWgUAeGwvdGltZWxpbmVzL3RpbWVsaW5lMS54bWxQSwECFAAUAAAACACSdaFcWfd2JAo2AAAA0AAAEQAAAAAAAAAAACAAtoFCXAUAeGwvdmJhUHJvamVjdC5iaW5QSwECFAAUAAAACACSdaFcvH0HZwMIAADPIAAADwAAAAAAAAAAACAAtoF7kgUAeGwvd29ya2Jvb2sueG1sUEsBAhQAFAAAAAgAknWhXDttMku7AAAAQgEAACMAAAAAAAAAAAAgALaBq5oFAHhsL3dvcmtzaGVldHMvX3JlbHMvc2hlZXQxLnhtbC5yZWxzUEsBAhQAFAAAAAgAknWhXMihuPq4AAAANAEAACMAAAAAAAAAAAAgALaBp5sFAHhsL3dvcmtzaGVldHMvX3JlbHMvc2hlZXQyLnhtbC5yZWxzUEsBAhQAFAAAAAgAknWhXOAIpqK4AAAANAEAACMAAAAAAAAAAAAgALaBoJwFAHhsL3dvcmtzaGVldHMvX3JlbHMvc2hlZXQzLnhtbC5yZWxzUEsBAhQAFAAAAAgAknWhXMdtgyO4AAAANAEAACMAAAAAAAAAAAAgALaBmZ0FAHhsL3dvcmtzaGVldHMvX3JlbHMvc2hlZXQ0LnhtbC5yZWxzUEsBAhQAFAAAAAgAknWhXLBamxK4AAAANAEAACMAAAAAAAAAAAAgALaBkp4FAHhsL3dvcmtzaGVldHMvX3JlbHMvc2hlZXQ1LnhtbC5yZWxzUEsBAhQAFAAAAAgAknWhXJc/vpO4AAAANAEAACMAAAAAAAAAAAAgALaBi58FAHhsL3dvcmtzaGVldHMvX3JlbHMvc2hlZXQ2LnhtbC5yZWxzUEsBAhQAFAAAAAgAknWhXJl0RCdKAQAAegQAACMAAAAAAAAAAAAgALaBhKAFAHhsL3dvcmtzaGVldHMvX3JlbHMvc2hlZXQ3LnhtbC5yZWxzUEsBAhQAFAAAAAgAknWhXAig0rzFBgAAdCMAABgAAAAAAAAAAAAgALaBD6IFAHhsL3dvcmtzaGVldHMvc2hlZXQxLnhtbFBLAQIUABQAAAAIAJJ1oVwjkKvXSAYAAHoXAAAYAAAAAAAAAAAAIAC2gQqpBQB4bC93b3Jrc2hlZXRzL3NoZWV0Mi54bWxQSwECFAAUAAAACACSdaFcE/dambcEAAC5DwAAGAAAAAAAAAAAACAAtoGIrwUAeGwvd29ya3NoZWV0cy9zaGVldDMueG1sUEsBAhQAFAAAAAgAknWhXP0T5ZMdBAAAvAsAABgAAAAAAAAAAAAgALaBdbQFAHhsL3dvcmtzaGVldHMvc2hlZXQ0LnhtbFBLAQIUABQAAAAIAJJ1oVw8XI2SHAQAAMQLAAAYAAAAAAAAAAAAIAC2gci4BQB4bC93b3Jrc2hlZXRzL3NoZWV0NS54bWxQSwECFAAUAAAACACSdaFcTWEm8UwEAACNDAAAGAAAAAAAAAAAACAAtoEavQUAeGwvd29ya3NoZWV0cy9zaGVldDYueG1sUEsBAhQAFAAAAAgAknWhXIEema6dBQAAhg4AABgAAAAAAAAAAAAgALaBnMEFAHhsL3dvcmtzaGVldHMvc2hlZXQ3LnhtbFBLBQYAAAAAewB7AAgjAABvxwUAAAA=
</FILE_DATA>
    <DATA_SHEET_FILE_NAME>xl/worksheets/sheet1.xml</DATA_SHEET_FILE_NAME>
    <PARAMETER_SHEET_FILE_NAME>xl/worksheets/sheet8.xml</PARAMETER_SHEET_FILE_NAME>
    <COLUMN_HEADER_ROW_NUM>1</COLUMN_HEADER_ROW_NUM>
    <TEMPLATE_SHARED_STRINGS>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>0</STRING_ID>
      <STRING>Sum of Peg Pegged Qty</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>1</STRING_ID>
      <STRING>Peg Supply Date</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>2</STRING_ID>
      <STRING>End Peg Demand Project</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>3</STRING_ID>
      <STRING>End Peg Demand Origination</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>4</STRING_ID>
      <STRING>End Peg Demand Order</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>5</STRING_ID>
      <STRING>End Peg Demand 
Date</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>6</STRING_ID>
      <STRING>End Peg Supply 
Date</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>7</STRING_ID>
      <STRING>End Peg Days 
Late</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>8</STRING_ID>
      <STRING>End Demand Suggested Due Date</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>9</STRING_ID>
      <STRING>End Assembly</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>10</STRING_ID>
      <STRING>End Demand Order Qty</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>11</STRING_ID>
      <STRING>End Peg Demand Organization</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>12</STRING_ID>
      <STRING>End Assembly Order - Planned Order QOH Fulfillment Status</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>13</STRING_ID>
      <STRING>End Pegging Id</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>14</STRING_ID>
      <STRING>Seq</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>15</STRING_ID>
      <STRING>Level</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>16</STRING_ID>
      <STRING>Item</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>17</STRING_ID>
      <STRING>Item Path</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>18</STRING_ID>
      <STRING>Demand Organization</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>19</STRING_ID>
      <STRING>Source Organization</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>20</STRING_ID>
      <STRING>Peg Demand Origination</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>21</STRING_ID>
      <STRING>Peg Demand Order</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>22</STRING_ID>
      <STRING>Peg Demand 
Qty</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>23</STRING_ID>
      <STRING>Peg Supply 
Qty</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>24</STRING_ID>
      <STRING>Peg Supply Type</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>25</STRING_ID>
      <STRING>Peg Supply Order</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>26</STRING_ID>
      <STRING>Planned Order QOH Fulfillment Status</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>27</STRING_ID>
      <STRING>Supply Suggested Due Date</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>28</STRING_ID>
      <STRING>Supply Action</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>29</STRING_ID>
      <STRING>Make Buy</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>30</STRING_ID>
      <STRING>Grand Total</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>31</STRING_ID>
      <STRING>N/A</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>32</STRING_ID>
      <STRING>(blank)</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>33</STRING_ID>
      <STRING>None</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>34</STRING_ID>
      <STRING>Peg Supply Type Label</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>35</STRING_ID>
      <STRING>End Peg Demand Date</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>36</STRING_ID>
      <STRING>End Peg Demand Qty</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>37</STRING_ID>
      <STRING>Tv Ea Po Qohs</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>38</STRING_ID>
      <STRING>Distinct Count of Tv Eao Key</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>39</STRING_ID>
      <STRING>4 N/A</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>40</STRING_ID>
      <STRING>3 None</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>41</STRING_ID>
      <STRING>2 Partial</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>42</STRING_ID>
      <STRING>1 Full</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>43</STRING_ID>
      <STRING>End Demand Sugg Due Date (Year)</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>44</STRING_ID>
      <STRING>End Demand Sugg Due Date (Month)</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>45</STRING_ID>
      <STRING>2000</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
     <TEMPLATE_SHARED_STRINGS_ROW>
      <STRING_ID>46</STRING_ID>
      <STRING>Jan</STRING>
     </TEMPLATE_SHARED_STRINGS_ROW>
    </TEMPLATE_SHARED_STRINGS>
    <TEMPLATE_PARAMETER_DEFAULTS>
     <TEMPLATE_PARAMETER_DEFAULTS_ROW>
      <PARAMETER_NAME>Planning Instance</PARAMETER_NAME>
      <DEFAULT_VALUE>TST</DEFAULT_VALUE>
     </TEMPLATE_PARAMETER_DEFAULTS_ROW>
    </TEMPLATE_PARAMETER_DEFAULTS>
    <TEMPLATE_STYLES>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>A1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>AA1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>AB1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>AC1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>AD1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>AE1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>AF1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>AG</CELL_IDENTIFIER>
      <STYLE_ID>5</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>AG1</CELL_IDENTIFIER>
      <STYLE_ID>10</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>AH</CELL_IDENTIFIER>
      <STYLE_ID>9</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>AH1</CELL_IDENTIFIER>
      <STYLE_ID>11</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>AI</CELL_IDENTIFIER>
      <STYLE_ID>9</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>AI1</CELL_IDENTIFIER>
      <STYLE_ID>11</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>AJ</CELL_IDENTIFIER>
      <STYLE_ID>9</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>AJ1</CELL_IDENTIFIER>
      <STYLE_ID>11</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>AK1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>AL1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>AM</CELL_IDENTIFIER>
      <STYLE_ID>5</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>AM1</CELL_IDENTIFIER>
      <STYLE_ID>10</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>AN1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>AO1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>AP</CELL_IDENTIFIER>
      <STYLE_ID>5</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>AP1</CELL_IDENTIFIER>
      <STYLE_ID>10</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>AQ1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>AR1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>AS1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>AT1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>AU1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>AV1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>AW1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>AX1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>AY1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>AZ1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>B1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BA1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BB1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BC1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BD1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BE1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BF1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BG</CELL_IDENTIFIER>
      <STYLE_ID>3</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BG1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BH1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BI</CELL_IDENTIFIER>
      <STYLE_ID>9</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BI1</CELL_IDENTIFIER>
      <STYLE_ID>11</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BJ1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BK</CELL_IDENTIFIER>
      <STYLE_ID>5</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BK1</CELL_IDENTIFIER>
      <STYLE_ID>10</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BL1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BM</CELL_IDENTIFIER>
      <STYLE_ID>5</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BM1</CELL_IDENTIFIER>
      <STYLE_ID>10</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BN</CELL_IDENTIFIER>
      <STYLE_ID>5</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BN1</CELL_IDENTIFIER>
      <STYLE_ID>10</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BO</CELL_IDENTIFIER>
      <STYLE_ID>5</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BO1</CELL_IDENTIFIER>
      <STYLE_ID>10</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BP</CELL_IDENTIFIER>
      <STYLE_ID>5</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BP1</CELL_IDENTIFIER>
      <STYLE_ID>10</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BQ1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BR1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BS1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BT1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BU1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BV1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BW1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BX1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BY</CELL_IDENTIFIER>
      <STYLE_ID>9</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BY1</CELL_IDENTIFIER>
      <STYLE_ID>11</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BZ</CELL_IDENTIFIER>
      <STYLE_ID>9</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>BZ1</CELL_IDENTIFIER>
      <STYLE_ID>11</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>C1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>CA</CELL_IDENTIFIER>
      <STYLE_ID>5</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>CA1</CELL_IDENTIFIER>
      <STYLE_ID>10</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>CB1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>CC</CELL_IDENTIFIER>
      <STYLE_ID>5</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>CC1</CELL_IDENTIFIER>
      <STYLE_ID>10</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>CD1</CELL_IDENTIFIER>
      <STYLE_ID>10</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>CE1</CELL_IDENTIFIER>
      <STYLE_ID>10</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>CF1</CELL_IDENTIFIER>
      <STYLE_ID>10</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>CG1</CELL_IDENTIFIER>
      <STYLE_ID>10</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>CH1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>CI1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>CJ1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>CK1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>CL1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>CM1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>CN1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>CO1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>CP1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>CQ1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>CR1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>CS1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>CT1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>CU1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>CV1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>CW1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>CX1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>CY1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>CZ1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>D1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>DA1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>DB1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>DC1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>E1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>F1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>G1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>H1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>I</CELL_IDENTIFIER>
      <STYLE_ID>3</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>I1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>J</CELL_IDENTIFIER>
      <STYLE_ID>3</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>J1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>K</CELL_IDENTIFIER>
      <STYLE_ID>9</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>K1</CELL_IDENTIFIER>
      <STYLE_ID>11</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>L</CELL_IDENTIFIER>
      <STYLE_ID>9</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>L1</CELL_IDENTIFIER>
      <STYLE_ID>11</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>M</CELL_IDENTIFIER>
      <STYLE_ID>5</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>M1</CELL_IDENTIFIER>
      <STYLE_ID>10</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>N</CELL_IDENTIFIER>
      <STYLE_ID>5</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>N1</CELL_IDENTIFIER>
      <STYLE_ID>10</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>O1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>P</CELL_IDENTIFIER>
      <STYLE_ID>5</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>P1</CELL_IDENTIFIER>
      <STYLE_ID>10</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>Q</CELL_IDENTIFIER>
      <STYLE_ID>5</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>Q1</CELL_IDENTIFIER>
      <STYLE_ID>10</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>R</CELL_IDENTIFIER>
      <STYLE_ID>5</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>R1</CELL_IDENTIFIER>
      <STYLE_ID>10</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>S</CELL_IDENTIFIER>
      <STYLE_ID>5</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>S1</CELL_IDENTIFIER>
      <STYLE_ID>10</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>T1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>U1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>V1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>W1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>X1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>Y1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>data</SHEET_TYPE>
      <CELL_IDENTIFIER>Z1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>parameter</SHEET_TYPE>
      <CELL_IDENTIFIER>A1</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>parameter</SHEET_TYPE>
      <CELL_IDENTIFIER>A10</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>parameter</SHEET_TYPE>
      <CELL_IDENTIFIER>A11</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>parameter</SHEET_TYPE>
      <CELL_IDENTIFIER>A12</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>parameter</SHEET_TYPE>
      <CELL_IDENTIFIER>A13</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>parameter</SHEET_TYPE>
      <CELL_IDENTIFIER>A14</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>parameter</SHEET_TYPE>
      <CELL_IDENTIFIER>A15</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>parameter</SHEET_TYPE>
      <CELL_IDENTIFIER>A16</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>parameter</SHEET_TYPE>
      <CELL_IDENTIFIER>A2</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>parameter</SHEET_TYPE>
      <CELL_IDENTIFIER>A3</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>parameter</SHEET_TYPE>
      <CELL_IDENTIFIER>A4</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>parameter</SHEET_TYPE>
      <CELL_IDENTIFIER>A5</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>parameter</SHEET_TYPE>
      <CELL_IDENTIFIER>A6</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>parameter</SHEET_TYPE>
      <CELL_IDENTIFIER>A7</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>parameter</SHEET_TYPE>
      <CELL_IDENTIFIER>A8</CELL_IDENTIFIER>
      <STYLE_ID>1</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
     <TEMPLATE_STYLES_ROW>
      <SHEET_TYPE>parameter</SHEET_TYPE>
      <CELL_IDENTIFIER>B3</CELL_IDENTIFIER>
      <STYLE_ID>2</STYLE_ID>
     </TEMPLATE_STYLES_ROW>
    </TEMPLATE_STYLES>
    <TEMPLATE_SHARING>
     <TEMPLATE_SHARING_ROW>
      <SHARING_LEVEL>S</SHARING_LEVEL>
      <LEVEL_VALUE>Site</LEVEL_VALUE>
     </TEMPLATE_SHARING_ROW>
    </TEMPLATE_SHARING>
    <PARAMETER_EXCLUSION>
    </PARAMETER_EXCLUSION>
   </TEMPLATES_ROW>
  </TEMPLATES>
  <DEFAULT_TEMPLATES>
   <DEFAULT_TEMPLATES_ROW>
    <TEMPLATE_NAME>Pivot: Full Hierarchy (Default)</TEMPLATE_NAME>
   </DEFAULT_TEMPLATES_ROW>
  </DEFAULT_TEMPLATES>
  <UPLOAD_COLUMNS>
  </UPLOAD_COLUMNS>
  <UPLOAD_PARAMETERS>
  </UPLOAD_PARAMETERS>
  <UPLOAD_SQLS>
  </UPLOAD_SQLS>
  <UPLOAD_DEPENDENCIES>
  </UPLOAD_DEPENDENCIES>
 </REPORTS_ROW>
</REPORTS>
</ROOT>
