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                        "Value": "<p><span></span><span style=\"text-decoration:underline;\"></span></p><p>The Army National Guard is vital to the nation&rsquo;s security as the operations reserve of the Army. The Operations and Maintenance, National Guard (OMNG) budget request resources daily operations of all Army National Guard (ARNG) units across all 50 States, three Territories, and the District of Columbia. The budget supports trained, fit, disciplined, and cohesive teams of Soldiers prepared for large-scale conflicts and domestic response operations. The OMNG appropriation resources operations, training, logistics, engineering, administration, cybersecurity and cyberspace, and management support capabilities. Additionally, the appropriation funds installation capabilities that provide the training, facility, projection, and storage support that enables training, mobilization, and deployment of Army National Guard units and Soldiers. Budget Activity 1 (Operating Forces) consists of the following Activity Groups: Land Forces, Land Forces Readiness, Land Forces Readiness Support, and Cyber Activities. Budget Activity 4 (Administration and Servicewide Activities) consists of the following Activity Groups: Logistics Operations and Servicewide Support.</p><p>&nbsp;</p><p>The Army National Guard uses Operations and Maintenance to fund all training, readiness, and support for 331,300 Army National Guard Soldiers. Additionally, the OMNG&nbsp;Fiscal Year (FY) 2027 request includes funding for 25,754 civilian full-time equivalents (FTEs) that support operations across the States, Territories, and the District of Columbia.</p><p>&nbsp;</p><p>The FY 2027 OMNG budget request of $8,703.8 million includes $120.9 million in inflation-driven price increases, and a net program change of <span style=\"color:#000000;\">$19.6 million</span>. The increase includes implementation of a National Guard Quick Reaction Force (NGQRF) and the activation of the 260th Special Purpose Brigade in the District of Columbia National Guard. The FY 2027 OMNG budget request includes homeland security funds of $221,200 million.<span></span></p>"
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                        "Value": "<span style=\"background-color:#ffffff;\"></span><span style=\"background-color:#ff3366;\"></span><p><span style=\"background-color:#000000;\"></span><span style=\"color:#000033;\"></span></p><p><span style=\"color:#ff0000;\"></span>The FY 2027 OMNG budget request of $8,703.8 million includes $120.9 million in inflation-driven price increases, and an overall program change of $19.6 million. The budget request reflects training and support for an authorized end strength of 331,300 Soldiers to include 31,154 Active Guard and Reserve Soldiers. The budget supports 4,087 full-time and 1,050 part-time recruiters. Throughout the 50 States, three Territories, and the District of Columbia provides base support functions and facility sustainment, available to respond to Homeland Defense and large-scale operations. The ARNG has a physical presence in communities across the Nation and overseas.</p><p>&nbsp;</p><span style=\"text-decoration:underline;\"><strong>Functional Transfers:</strong></span>&nbsp;Within subactivity group 131 (Base Operations Support), OMNG plans to receive&nbsp;$+28.5 million for Child and Youth Services from Operation and Maintenance, Army (OMA). Within subactivity group 121 (Force Readiness Operations Support) OMNG plans to give&nbsp;$-24.8 million for Medical and Dental Readiness to the Defense Health Agency (DHA) in support of the Defense Health Program.<p>&nbsp;</p><p><span></span><span></span><span></span><span></span><strong><span style=\"text-decoration:underline;\"><span>People:</span></span><span>&nbsp;</span></strong><span>The FY 2027 budget request allocates resources for 25,754 Full-Time Equivalent (FTE) positions, which 20,037 are Dual Status Military Technicians (MILTECH) FTEs and 5,717 are Department of the Army Civilians (DAC)</span><span>&nbsp;</span><span>FTEs. MILTECHs are essential Full-Time Support personnel responsible for maintaining, training, and administering all Army National Guard (ARNG) units and organizations, ensuring that they remain trained and ready to support the Joint Force. DACs contribute to force generation capabilities and the continuity of operations across the 50 States, three Territories, and the District of Columbia. They develop and administer programs that enhance overall capability and capacity as part of the Total Army. The civilian pay budget includes an increase of 4% to strengthen the Army National Guard's ability to recognize and reward the civilian workforce critical to mission success.</span></p><p><span></span><span></span></p><p><strong><span style=\"text-decoration:underline;\"><span>Readiness and Modernization:</span></span></strong></p><p><span>&nbsp;</span></p><p>The FY 2027 budget supports readiness and lethality by providing trained, ready, and cost-effective forces for operational missions and capacity to support strategic surge requirements for Large-Scale Combat Operations (LSCO) in a Multidomain environment or other unanticipated national crises. The appropriation continues the implementation of the Army Continuous Transformation to optimize force structure, emphasizing speed and lethality, and converting Brigade Combat Teams to Mobile Brigade Combat Teams.&nbsp;<span><span>Funds Home Station Training at 100% supporting 781</span></span>&nbsp;Composite Miles and a Collective Training Event. <span style=\"color:#000033;\">This&nbsp;</span><span><span style=\"color:#000033;\">budget enables the Army&rsquo;s and the ARNG Continuous Transformation efforts. I</span><span>t supports </span></span><span><span>the Army's Force Structure Optimization by investing $24.5 million in establishing a National Guard quick reaction Force (NGQRF) training and equipment for approximately 24,000 National Guard Members and support the activation of the 260th Special Purpose Brigade by investing $32.6 million for&nbsp;</span></span>the District of Columbia National Guard. The&nbsp;FY 2027 budget request includes homeland security funds in the direct program of $221,200 million.</p><p><span><strong>&nbsp;</strong></span></p><p><span><strong><span style=\"text-decoration:underline;\">Operational Readiness:</span> </strong>The ARNG will conduct</span><span style=\"color:#ff6699;\"> </span><span style=\"color:#000033;\">four Combat Readiness Exercises (CRX) and two Combat Training Center (CTC) rotations</span><span> to build readiness that supports deterring adversaries around the globe and operate in a Multidomain environment as part of the Joint Force. The budget decreases funding for reduced flying proficiency hours but provides sufficient resources to train and sustain Combat Aviation Brigades at required readiness levels aligned with the </span>Continuous Transformation effort<span>.&nbsp;The budget supports the State Partnership Program to deter strategic attacks against our homeland and allies, promote regional stability, and shape international security.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</span></p><p><span><strong>&nbsp;</strong></span></p><p><span><span style=\"text-decoration:underline;\"><strong>Restoration and Modernization:</strong></span><strong> </strong></span>The increase in Restoration and Modernization funding addresses the deteriorating state of facilities by providing an enhanced level of sustainment, as well as specifically targeting the restoration and modernization of unaccompanied housing to provide serviceable, quality housing to all service members. This restores the warrior ethos by investing in the readiness of our facilities and improving the quality of life for ARNG Soldiers. Restoration funding provides the resources necessary to restore degraded facilities. Restoration consists of repair and replacement work to fix facilities damaged by previous inadequate sustainment, excessive age, natural disasters, fires, and accidents. Modernization funding provides resources necessary to upgrade facilities to meet new standards or fulfill new functions. Modernization alters facilities solely to implement new or advanced technologies, to accommodate new functions, or to replace building components that exceed the overall service life of the facilities.</p><p><span><span>&nbsp;</span></span></p><p><span><span><span style=\"text-decoration:underline;\"><strong>Facilities Sustainment:</strong></span>&nbsp;For discretionary resources,&nbsp;Sustainment is funded at </span></span>77 percent of the Department of War Facilities Sustainment Model (FSM) requirement<span><span>. Sustainment includes</span></span>&nbsp;repairs necessary to keep facilities in good working order and in accordance with industry standards. Activities include recurring maintenance checks, emergency repairs for plumbing, electrical, heating, and ventilation, air conditioning maintenance and repair, facility components repair, and replacement of roofs and furnaces. Sustainment funding is required to prevent deterioration and corrosion of existing facilities and to complement the Army's restoration and modernization efforts. In addition, these resources are necessary for the sustainment of facilities supporting medical readiness.</p><p><strong><span style=\"background-color:#ffffff;\">&nbsp;</span></strong></p><p><span style=\"text-decoration:underline;\"><strong><span style=\"background-color:#ffffff;\">Basic Operations Suppo</span></strong><span style=\"background-color:#ffffff;\"><strong>rt:</strong></span></span><span style=\"background-color:#ffffff;\">&nbsp;This subactivity group</span><span style=\"background-color:#ffffff;\">&nbsp;is funded at 97.8% of the requirements; a portion of this request is for DPW contracts and tails to in support of ARNG improvement of facilities by accelerating funds to repair poor and failing structure. A</span>dditional funding will improve ARNG facilities, providing Soldiers with safe, clean, and comfortable accommodations thereby<span style=\"background-color:#ffffff;\">&nbsp;increasing readiness and improving&nbsp;</span><span style=\"background-color:#ffffff;\">the resilience of the facilities.&nbsp;</span><span style=\"background-color:#ffffff;\">Other Significant components of&nbsp;</span><span style=\"background-color:#ffffff;\">Facilities Operations are: (1) pest control; (2) custodial service and refuse collection; (3) engineering services and real property maintenance (including public works management and real estate/real property administration); and (4) grounds maintenance and pavement clearing (including removal of snow and ice, grass cutting operations, and street sweeping.</span></p><p><span style=\"background-color:#ffffff;\">&nbsp;</span></p><p><span style=\"background-color:#ffffff;text-decoration:underline;\"><strong>Defending the Homeland:</strong></span><strong> </strong>The 2027 budget supports the President's mission to reduce crime and enhance public safety in Washington D.C. by assisting the D.C. Metropolitan Police Department through enhanced public safety operations.&nbsp;The National Guard is a community-based force, uniquely qualified to integrate with local law enforcement and build community trust.</p><p>&nbsp;</p><p><span>The Army National Guard continues to answer the call and meet the numerous demands at home and abroad, while taking care of its people, families, and civilians, maintaining readiness, and modernizing the Force. This budget request allows the Army National Guard to meet demands now and in the future.</span><span></span></p><br /><p>&nbsp;</p><p><br /></p><p>&nbsp;</p><p>&nbsp;</p><p>&nbsp;</p><p>&nbsp;</p><p>&nbsp;</p><p>&nbsp;</p><p>&nbsp;</p><p>&nbsp;</p><p>&nbsp;</p><p>&nbsp;</p><p>&nbsp;</p><p>&nbsp;</p><p>&nbsp;</p><p><br /></p><p><br /></p><p>&nbsp;</p>"
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                          }
                        ]
                      }
                    },
                    {
                      "Name": "Upload File",
                      "Type": "Toggle",
                      "Description": "",
                      "MissingExtraData": "This component has a generated word doc, but no json doc was found"
                    }
                  ]
                },
                {
                  "Name": "Mandatory Funding",
                  "Description": "",
                  "Type": "Tab",
                  "Children": [
                    {
                      "Name": "Funding Overview",
                      "Description": "",
                      "Type": "Grid",
                      "Code": "PBA19FundingOverview",
                      "Columns": [
                        {
                          "Code": "RowText",
                          "Text": "",
                          "Group": "",
                          "Level": 0,
                          "Order": 1.0,
                          "Type": "text"
                        },
                        {
                          "Code": "Py",
                          "Text": "FY 2025",
                          "Group": "",
                          "Level": 0,
                          "Order": 2.0,
                          "Type": "numeric"
                        },
                        {
                          "Code": "Cy",
                          "Text": "FY 2026",
                          "Group": "",
                          "Level": 0,
                          "Order": 3.0,
                          "Type": "numeric"
                        },
                        {
                          "Code": "By1",
                          "Text": "FY 2027",
                          "Group": "",
                          "Level": 0,
                          "Order": 4.0,
                          "Type": "numeric"
                        }
                      ],
                      "Rows": [
                        {
                          "Code": "BlnkRow",
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                        "Value": "<p><span style=\"color:#ff0000;\">The FY 2027 request for Operation and Maintenance, Army National Guard (OMNG) includes $8,703,824 thousand of discretionary and $2,025,315 thousand of mandatory for a total of $10,729,139 thousand. The mandatory funds support Facility Sustainment, Restoration, and Modernization (FSRM) to improve unaccompanied housing facilities across the 54 States, three Territories and the District of Columbia. It also supports engineering efforts to mitigate poor and failing infrastructure. Funding is essential to reducing the backlog of facility projects, bring facility sustainment up to 92% of Department of War Facilities Sustainment Model (FSM), and to contribute to quality of life and warrior ethos for Soldiers and their families.</span></p><p><span style=\"color:#ff0000;\"></span><span style=\"color:#ff0000;\"></span></p><p><span style=\"color:#ff0000;\">The FY 2026 spend plan for OMNG includes $8,563,267 thousand in discretionary and $385,000 thousand in mandatory for a total of $8,948,267 thousand.</span></p>"
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                        "Value": "<span style=\"background-color:#ff00ff;\"></span><p><strong><span></span></strong>The budget supports <span style=\"color:#000033;\">35</span>&nbsp;Brigade Combat Teams, and 2<span style=\"color:#ff0000;\">&nbsp;</span>Combat Aviation Brigades. Global Force Management allows for active and scalable&nbsp; Army National Guard Force employment to meet operational demand, whether it be <span style=\"color:#000000;\">competitive or contingency. The Army National Guard supports Combatant Commanders with predictable, task-organized, and responsive capabilities to achieve Global Employment of the Force end states and meet other requirements across the full range of military operations, to include: contingency response, operations support and military exercises.&nbsp;</span></p><p><span style=\"color:#000000;\"></span><strong><span style=\"color:#000033;\"></span></strong></p><p><strong><span style=\"color:#000000;\">Major Programmatic Increases:&nbsp;</span></strong><span style=\"color:#000000;\">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</span></p><p><span style=\"color:#000000;\"></span><span style=\"color:#000000;\"></span><span></span></p><p><span><span style=\"color:#000000;text-decoration:underline;\">Defend the Homeland:</span><span style=\"color:#000000;\">&nbsp;Increase funding to support the mobilization of 2,500 National Guard members to support missions in compliance with Executive Order 14333 \"Declaring a Crime Emergency in the District of Columbia.\"</span></span></p><p><span style=\"color:#000000;\"></span><span style=\"color:#000000;\"></span></p><p><span style=\"color:#000000;\"><span style=\"text-decoration:underline;\">Home Station Functional Support Brigade Structure:</span></span><span style=\"color:#000000;\">&nbsp;Increase funding for the activation of the 260th Special Purpose Brigade in the District of Columbia.&nbsp;</span></p><p><span style=\"color:#000000;\"></span><span style=\"color:#000000;\"></span></p><p><span style=\"color:#000000;\"><span style=\"text-decoration:underline;\">National Guard Quick Response Force:</span>&nbsp;&nbsp;</span><span style=\"color:#000000;\">Increase funding&nbsp; in support of the National Guard Response Element to establish a National Guard Quick Response Force to respond to public safety emergencies within 24 hours.</span></p><p><span style=\"color:#000000;\">&nbsp;</span></p><p><span style=\"color:#000000;text-decoration:underline;\">Enhanced Performance Award Pool for Department of War Civilian Employees:</span><span style=\"color:#000000;\">&nbsp;Strengthens the Department's ability to recognize and reward the civilian workforce.</span></p><p><span style=\"color:#000000;\">&nbsp;</span></p><p><span style=\"color:#000000;text-decoration:underline;\">Core Readiness:</span><span style=\"color:#000000;\">&nbsp;Funds the Force generating, Operating Tempo&nbsp;</span><span>(OPTEMPO)</span><span style=\"color:#000000;\">, and depot maintenance activities for the ARNG including Ground and Air operations, and Training exercises.&nbsp;The FY 2027 budget funds unit OPTEMPO at 781 composite miles for non-deployed units. The budget provides resources to train and sustain the Army National Guard combat forces at the highest training readiness levels consistent with mission requirements and supports the active component ground OPTEMPO metrics, encompassing actual miles driven for home station training and CTC rotations. This request funds 2 MBCT-level CTC rotations, which is an increase of 1 rotation from FY 2023.</span></p><p><span style=\"color:#000000;\">&nbsp;</span></p><p><span style=\"color:#000000;text-decoration:underline;\">Air Operations / Flying Hour Program</span><span style=\"color:#000000;\">: The FY 2027 budget funds 430,533 Flying Hours (7.3 hours per crew per month), an increase from FY 2026 (7.1 H/C/M) and provides the resources to train and sustain Combat Aviation Brigades at required readiness levels in accordance with safety standards.&nbsp;</span></p><p><span style=\"color:#000000;\">&nbsp;</span></p><p><span style=\"color:#000000;\"><span style=\"color:#000000;text-decoration:underline;\">Readiness Enablers:</span><span style=\"color:#000000;\">&nbsp;Provides logistics, engineering, cyber and medical support to the ARNG Soldier. Provide funding for physical examinations, medical contracts, immunization, health program and medical equipment. Provides funding for operational Support of the National Guard Chemical, Biological, Radiological, Nuclear (CBRN) response teams. Add funding for Organizational Clothing and Individual equipment in support of the increase in End Strength.&nbsp;</span></span></p><p><span style=\"color:#000000;\"></span><span style=\"color:#000000;\"></span></p><p><span style=\"color:#000000;\"><span style=\"color:#000000;\"><span style=\"text-decoration:underline;\">Army Security Program:</span>&nbsp;Increases funding for the physical security measure to protect Army National Guard Installations and standalone facilities from threats.</span></span></p><p><span style=\"color:#000000;\">&nbsp;</span></p><p><span style=\"color:#000000;\"><span style=\"text-decoration:underline;\">Information Technology Services Management:</span></span><span style=\"color:#000000;\">&nbsp;Increases funding for</span> <span style=\"color:#000000;\">the Army National Guard (ARNG) Regional Cyber Center to provide operational and organizational support for Army IT, Signal, and Cyber organizations across the ARNG enterprise.</span></p><p><span style=\"color:#000000;\">&nbsp;</span></p><p><span style=\"color:#000000;text-decoration:underline;\">Environmental Management:</span><span style=\"color:#000000;\">&nbsp;Increases funding for environmental programs. Funding provides per-and polyfluoroalkyl substances (PFAS) mitigation for Army National Guard owned systems such as drinking water system upgrades and installation of granular activated carbon (GAC) filters at Army National Guard installations.</span></p><p><span><span>&nbsp;</span></span></p><p><span><span style=\"text-decoration:underline;\">Sexual Harassment/Assault Reponses and Prevention:</span><span>&nbsp;</span><span>Increase funding for 54 civilian Full time equivalent to support the Independent Review Commission of Sexual Assault in the Military Workforce to create a safe culture through prevention, education, and support for victims.&nbsp;</span><span>T</span></span><span>his program complies with Public Law 112-81 and provides support for the Army National Guard full time and collateral duty Sexual Assault Response Coordinators (SARCs) and Victim Advocate Coordinators (VACs) to receive qualification and refresher training. It also purchases </span>Sexual Harassment/Assault Response and Prevention (SHARP)<span> materials and training kits for distributive purposes.</span></p><p>&nbsp;</p><p><span style=\"color:#000000;\"></span><span style=\"color:#000000;\"></span></p><p><strong><span style=\"color:#000000;\">Major Programmatic Decreases:</span></strong><span style=\"color:#000000;\">&nbsp; &nbsp;&nbsp;</span></p><p><span style=\"color:#000000;\">&nbsp;</span></p><p><span style=\"color:#000000;\"><span style=\"color:#000000;text-decoration:underline;\">Federal Retirement System:</span><span style=\"color:#000000;\">&nbsp;Reduces funding to align with the adjusted </span></span>Federal Employees Retirement System&nbsp;<span style=\"color:#000000;\"><span style=\"color:#000000;\">(FERS) contribution rate</span></span><span style=\"color:#000000;\">. </span></p><p><span style=\"color:#000000;\">&nbsp;</span></p><p><span style=\"color:#000000;\"><span style=\"text-decoration:underline;color:#000033;\">Continuous Transformation:</span><span style=\"color:#000033;\">&nbsp;Decreases funding due to </span></span><span style=\"color:#000000;\"><span style=\"color:#000033;\">one Armored Brigade Combat Team converting to a Mobile Brigade Combat Team.</span></span></p><p><span style=\"color:#ff0000;\">&nbsp;</span></p><p><span style=\"color:#000000;\"></span><span style=\"text-decoration:underline;\"><span style=\"color:#000000;\">Restoration and Modernization - Facility Investment Strategy:</span></span><span style=\"color:#000000;\">&nbsp;Decreases funding for </span><span style=\"color:#000033;\">r</span><span style=\"color:#000000;\">estoration and modernization projects of deteriorating facilities to align with the Army Facility Investment Strategy.</span></p><p><span style=\"color:#000000;\">&nbsp;</span></p><p><span style=\"text-decoration:underline;\"><span style=\"color:#000000;\">Restoration and Modernization - Energy and Utility Program:</span></span><span style=\"color:#000000;\">&nbsp;</span><span>Decreases funding for energy and installation resilience, as well as water and utilities restoration and modernization. The discretionary funding decrease in contract services is offset by the mandatory funding increase.</span></p><p><span>&nbsp;</span></p><p><span style=\"text-decoration:underline;\">Efficiencies:</span>&nbsp;Efficiencies for BA-01 include contract services ($-11.9 million), travel budget ($-4.7 million), printing and reproduction ($-1.0 million) and workforce optimization ($-79.0 million).<br /></p>"
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                        "Value": "<span style=\"color:#000033;\"></span>The Administration and Servicewide Activities budget activity provides funds for service-wide communication and commercial transportation of Army National Guard equipment; staffing and operation of Army National Guard management activities to include providing support to civil authorities; planning and assistance for civil disturbances and emergencies; It provides support for the Soldier for Life Transition Assistance Program (SFL-TAP), to include pre-separation counseling and employment assistance; it has provisions for the Veterans Opportunity to Work (VOW) Act with mandated workshops and products; the VOW events include: Transition Overview, Military Occupational Classification (MOC) Crosswalk, Veteran Affairs (VA) Benefits Briefing I and II, Department of Labor (DOL) Employment Workshop, Financial Planning Seminar and CAPSTONE events.<p>&nbsp;</p><p><strong>Major Programmatic Increases:&nbsp;</strong>&nbsp;&nbsp;</p><p>&nbsp;</p><p><span><span style=\"text-decoration:underline;color:#000033;\">State Partnership Program:</span>&nbsp;</span>Increases funding for partnership engagements to maintain partnerships with partner nations.</p><p>&nbsp;</p><p><span style=\"text-decoration:underline;\">Information Technology Services Management- Network Modernization:</span> Increases funding to establish the Army National Guard (ARNG) National Capital Region- Network Enterprise Center as the primary information technology service and system provider supporting over 4,000 end users for the National Guard Bureau Headquarters.</p><p>&nbsp;</p><p><strong>Major Programmatic Decreases:</strong>&nbsp;&nbsp;</p><p>&nbsp;</p><p><span><span style=\"text-decoration:underline;\">Army Marketing Program</span>:</span>&nbsp;Decreases funding in marketing due to reduced requirements and projected success in meeting ARNG recruiting mission objectives.</p><p><span>&nbsp;</span></p><p><span><span style=\"text-decoration:underline;\">Automation and Information Systems</span>:</span>&nbsp;Decreases funding for the discontinuation of the Reserve Component Automation System (RCAS) as functionalities are subsumed by Army Enterprise Systems (ASMIS), Integrated Personnel and Pay system (IPPS-A), and Global Force Information Management (GFIM).</p><p>&nbsp;</p><p><span style=\"text-decoration:underline;\">Efficiencies:</span> Efficiencies for BA-04 include travel budget ($-4.4<span>&nbsp;</span>million), printing and reproduction ($-5.8 million) and workforce optimization ($-1.0 million).</p><p><span style=\"text-decoration:underline;\"><span><br /></span></span></p>&nbsp;"
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                        "Value": "<p><span>In FY 2027, the Army National Guard (ARNG) continues to implement force structure changes supporting the Continuous transformation by building a leaner and more lethal force, converting five Armored Brigade Combat Teams to Mobile Brigade Combat Teams, inactivating one Field Artillery Brigade and increasing Division Artillery (DIVARTY) lethality by adding High Mobility Artillery Rocket System (HIMARS) capability. Readiness funding supports </span><span style=\"color:#000033;\">two Combat Training Center (CTC) and four Combat Readiness Exercises (CRX)</span><span> rotations, maintenance for critical repair parts sustaining equipment operational levels, composite miles at 781 and the flying hour program at 7.3 hours/crew/month.</span></p><p><span></span><span style=\"text-decoration:underline;\"></span></p><p><span><span style=\"text-decoration:underline;\">Core Readiness:</span></span>&nbsp;Funds the Force generating, Operating Tempo, and depot maintenance activities for the ARNG including Ground and Air operations, and Training exercises.&nbsp;The FY 2027 budget funds unit Operating Tempo (OPTEMPO) at 781 composite miles for non-deployed units. The budget provides resources to train and sustain the Army National Guard combat forces at the highest training readiness levels consistent with mission requirements and supports the active component ground OPTEMPO metrics, encompassing actual miles driven for home station training and CTC rotations. This request funds<span style=\"color:#ff0000;\">&nbsp;</span><span style=\"color:#000033;\">2 BCT-level CTC rotations, which is an increase of one of the rotations from FY 2026.&nbsp;</span><span></span></p><p><span>&nbsp;</span></p><p><span style=\"text-decoration:underline;\">Air Operations / Flying Hour Program:</span> The FY 2027 budget funds 430,533 Flying Hours (7.3 hours per crew per month), an increase from FY 2026 (7.1 H/C/M) and provides the resources to train and sustain Combat Aviation Brigades at required readiness levels in accordance with safety standards.</p><p>&nbsp;</p><p><span style=\"text-decoration:underline;\">Readiness Enablers:</span> Provides logistics, engineering, cyber, and medical support to the ARNG Soldier. Provide funding for physical examinations, medical contracts, immunization, health program and medical equipment. Provides funding for the operational support of the National Guard Chemical, Biological, Radiological, Nuclear (CBRN) response teams. Increases funding for Organizational Clothing and Individual equipment due to the initial issues of the Vital Torso Protection, Modular Scalable Vests, and Extreme Cold Weather clothing and equipment.</p>"
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        "Metadata": {
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          "ServiceAgencyAcronym": "ARNG",
          "ServiceAgencyName": "ARNG Client Node",
          "BudgetYear": "2026",
          "BudgetCycle": "PB",
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          "AppropriationNumber": "2065"
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        "GeneratedOutput": {
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                "Value": "This exhibit includes FY 2027 costs for civilian and contractor FTEs accounted for in the Base Budget Estimate."
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              "Type": "Toggle",
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                }
              ]
            },
            {
              "Metadata": {
                "SourceSystem": "EAS",
                "ServiceAgencyAcronym": "ARNG",
                "ServiceAgencyName": "ARNG Client Node",
                "BudgetYear": "2026",
                "BudgetCycle": "PBR",
                "SubmissionDate": "September 2025",
                "AppropriationNumber": "2065"
              },
              "GeneratedOutput": {
                "Name": "Outyear Summary Grid",
                "Description": "",
                "Type": "Grid",
                "Code": "PB31ROutyearSummary",
                "Columns": [
                  {
                    "Code": "RowText",
                    "Text": "",
                    "Group": "",
                    "Level": 0,
                    "Order": 1.0,
                    "Type": "text"
                  },
                  {
                    "Code": "By2",
                    "Text": "FY 2028",
                    "Group": "",
                    "Level": 0,
                    "Order": 2.0,
                    "Type": "numeric"
                  },
                  {
                    "Code": "By3",
                    "Text": "FY 2029",
                    "Group": "",
                    "Level": 0,
                    "Order": 3.0,
                    "Type": "numeric"
                  },
                  {
                    "Code": "By4",
                    "Text": "FY 2030",
                    "Group": "",
                    "Level": 0,
                    "Order": 4.0,
                    "Type": "numeric"
                  },
                  {
                    "Code": "By5",
                    "Text": "FY 2031",
                    "Group": "",
                    "Level": 0,
                    "Order": 5.0,
                    "Type": "numeric"
                  }
                ],
                "Rows": [
                  {
                    "Code": "ARNG_BlnkRow",
                    "Type": "blank",
                    "Cells": []
                  },
                  {
                    "Code": "ARNG_ReseDrilEndStre",
                    "Type": "data",
                    "Cells": [
                      {
                        "ColumnCode": "RowText",
                        "Type": "text",
                        "Value": "Reserve Drill End Strength",
                        "NarrativeData": null
                      },
                      {
                        "ColumnCode": "By2",
                        "Type": "numeric",
                        "Value": "303,868",
                        "NarrativeData": null
                      },
                      {
                        "ColumnCode": "By3",
                        "Type": "numeric",
                        "Value": "303,662",
                        "NarrativeData": null
                      },
                      {
                        "ColumnCode": "By4",
                        "Type": "numeric",
                        "Value": "302,894",
                        "NarrativeData": null
                      },
                      {
                        "ColumnCode": "By5",
                        "Type": "numeric",
                        "Value": "302,894",
                        "NarrativeData": null
                      }
                    ]
                  },
                  {
                    "Code": "ARNG_ReseOnFullTimeActiDu",
                    "Type": "data",
                    "Cells": [
                      {
                        "ColumnCode": "RowText",
                        "Type": "text",
                        "Value": "Reservists on Full Time Active Duty (E/S)",
                        "NarrativeData": null
                      },
                      {
                        "ColumnCode": "By2",
                        "Type": "numeric",
                        "Value": "30,933",
                        "NarrativeData": null
                      },
                      {
                        "ColumnCode": "By3",
                        "Type": "numeric",
                        "Value": "30,933",
                        "NarrativeData": null
                      },
                      {
                        "ColumnCode": "By4",
                        "Type": "numeric",
                        "Value": "30,933",
                        "NarrativeData": null
                      },
                      {
                        "ColumnCode": "By5",
                        "Type": "numeric",
                        "Value": "30,933",
                        "NarrativeData": null
                      }
                    ]
                  },
                  {
                    "Code": "ARNG_CiviFtes",
                    "Type": "data",
                    "Cells": [
                      {
                        "ColumnCode": "RowText",
                        "Type": "text",
                        "Value": "Civilian FTEs",
                        "NarrativeData": null
                      },
                      {
                        "ColumnCode": "By2",
                        "Type": "numeric",
                        "Value": "25,803",
                        "NarrativeData": null
                      },
                      {
                        "ColumnCode": "By3",
                        "Type": "numeric",
                        "Value": "25,827",
                        "NarrativeData": null
                      },
                      {
                        "ColumnCode": "By4",
                        "Type": "numeric",
                        "Value": "25,859",
                        "NarrativeData": null
                      },
                      {
                        "ColumnCode": "By5",
                        "Type": "numeric",
                        "Value": "25,859",
                        "NarrativeData": null
                      }
                    ]
                  },
                  {
                    "Code": "ARNG_MiliTechInclMemo",
                    "Type": "data",
                    "Cells": [
                      {
                        "ColumnCode": "RowText",
                        "Type": "text",
                        "Value": "(Military Technician Included (Memo))",
                        "NarrativeData": null
                      },
                      {
                        "ColumnCode": "By2",
                        "Type": "numeric",
                        "Value": "0",
                        "NarrativeData": null
                      },
                      {
                        "ColumnCode": "By3",
                        "Type": "numeric",
                        "Value": "0",
                        "NarrativeData": null
                      },
                      {
                        "ColumnCode": "By4",
                        "Type": "numeric",
                        "Value": "0",
                        "NarrativeData": null
                      },
                      {
                        "ColumnCode": "By5",
                        "Type": "numeric",
                        "Value": "0",
                        "NarrativeData": null
                      }
                    ]
                  }
                ]
              }
            }
          ]
        }
      },
      {
        "Metadata": {
          "SourceSystem": "EAS",
          "ServiceAgencyAcronym": "ARNG",
          "ServiceAgencyName": "ARNG Client Node",
          "BudgetYear": "2026",
          "BudgetCycle": "PB",
          "SubmissionDate": "April 2026",
          "AppropriationNumber": "2065"
        },
        "GeneratedOutput": {
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          "ServiceAgencyName": "ARNG Client Node",
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                              "ColumnCode": "RowText",
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                        {
                          "Code": "ARNG_R5OtheObjeClas13Bene",
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                        {
                          "Code": "ARNG_R5aUsdhBeneOfFormEmpl",
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                        {
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                        },
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                                              },
                                              {
                                                "Metadata": {
                                                  "SourceSystem": "EAS",
                                                  "ServiceAgencyAcronym": "ARNG",
                                                  "ServiceAgencyName": "ARNG Client Node",
                                                  "BudgetYear": "2026",
                                                  "BudgetCycle": "PBR",
                                                  "SubmissionDate": "September 2025",
                                                  "AppropriationNumber": "2065"
                                                },
                                                "GeneratedOutput": {
                                                  "Name": "3B2 Grid",
                                                  "Description": "",
                                                  "Type": "Grid",
                                                  "Code": "Op5Part3b2",
                                                  "Columns": [
                                                    {
                                                      "Code": "RowText",
                                                      "Text": "B2. Summary of Operational Category",
                                                      "Group": "",
                                                      "Level": 0,
                                                      "Order": 1.0,
                                                      "Type": "text"
                                                    },
                                                    {
                                                      "Code": "Py",
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                                                      "Group": "",
                                                      "Level": 0,
                                                      "Order": 2.0,
                                                      "Type": "numeric"
                                                    },
                                                    {
                                                      "Code": "Cy",
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                                                      "Level": 0,
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                                                      "Type": "numeric"
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                                                      "Cells": []
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                                                          "Type": "text",
                                                          "Value": "Base Programs (BP)",
                                                          "NarrativeData": null
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                                                          "ColumnCode": "Py",
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                                                    },
                                                    {
                                                      "Code": "111_PaciDeteInitPdi",
                                                      "Type": "data",
                                                      "Cells": [
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                                                          "ColumnCode": "RowText",
                                                          "Type": "text",
                                                          "Value": "Pacific Deterrence Initiative (PDI)",
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                                                        },
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                                                          "ColumnCode": "Py",
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                                                          "Value": "0",
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                                                    },
                                                    {
                                                      "Code": "111_BlnkRow",
                                                      "Type": "blank",
                                                      "Cells": []
                                                    },
                                                    {
                                                      "Code": "111_OverOperCostOoc",
                                                      "Type": "subtotal",
                                                      "Cells": [
                                                        {
                                                          "ColumnCode": "RowText",
                                                          "Type": "text",
                                                          "Value": "Overseas Operations Costs (OOC)",
                                                          "NarrativeData": null
                                                        },
                                                        {
                                                          "ColumnCode": "Py",
                                                          "Type": "numeric",
                                                          "Value": "18,647",
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                                                        },
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                                                    },
                                                    {
                                                      "Code": "111_OperEnduSentOes",
                                                      "Type": "data",
                                                      "Cells": [
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                                          "Value": "<p><strong>Note</strong>: </p><p>&nbsp;</p><p>1. Composite Miles are calculated based on the Brigade Combat Team (BCT) force structure.&nbsp; BCTs are available for home station training and Force Generation training requirements.&nbsp; Composite Miles include the M1, and M2 in the Armored BCT; Up-Armored High Mobility Multipurpose Wheeled Vehicle in the Infantry BCT; and all Strykers in the Stryker Infantry.</p><p>&nbsp;</p><p>2.&nbsp;<span>Mobile Brigade Combat Teams (MBCT) converts from the ABCTs and IBCTs force structure to a leaner and more lethal design to bolster maintenance control capabilities and address emerging threats in the modern operational environment.</span></p><p>&nbsp;</p><p>3. Funds the Directed Readiness Table requirements in FY 2025-2027.</p>"
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                                            "Code": "By1",
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                                                    ]
                                                  },
                                                  {
                                                    "Code": "112_CongAdjuGenProv",
                                                    "Type": "data",
                                                    "Cells": [
                                                      {
                                                        "ColumnCode": "RowText",
                                                        "Type": "text",
                                                        "Value": "Congressional Adjustments (General Provisions)",
                                                        "NarrativeData": null
                                                      },
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                                                        "ColumnCode": "ChanFycy",
                                                        "Type": "numeric",
                                                        "Value": "0",
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                                                        "Type": "blank",
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                                                  },
                                                  {
                                                    "Code": "112_SubtEstiAmou",
                                                    "Type": "subtotal",
                                                    "Cells": [
                                                      {
                                                        "ColumnCode": "RowText",
                                                        "Type": "text",
                                                        "Value": "SUBTOTAL ESTIMATED AMOUNT",
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                                                      },
                                                      {
                                                        "ColumnCode": "ChanFycy",
                                                        "Type": "numeric",
                                                        "Value": "210,737",
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                                                      {
                                                        "ColumnCode": "ChanFyby1",
                                                        "Type": "blank",
                                                        "Value": "0",
                                                        "NarrativeData": null
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                                                  },
                                                  {
                                                    "Code": "112_WarRelaAndDisaSuppAppr",
                                                    "Type": "data",
                                                    "Cells": [
                                                      {
                                                        "ColumnCode": "RowText",
                                                        "Type": "text",
                                                        "Value": "War-Related and Disaster Supplemental Appropriation",
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                                                      {
                                                        "ColumnCode": "ChanFycy",
                                                        "Type": "numeric",
                                                        "Value": "0",
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                                                        "ColumnCode": "ChanFyby1",
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                                                        "Value": "0",
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                                                  },
                                                  {
                                                    "Code": "112_XyeCarr",
                                                    "Type": "data",
                                                    "Cells": [
                                                      {
                                                        "ColumnCode": "RowText",
                                                        "Type": "text",
                                                        "Value": "X-Year Carryover",
                                                        "NarrativeData": null
                                                      },
                                                      {
                                                        "ColumnCode": "ChanFycy",
                                                        "Type": "numeric",
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                                                        "Type": "blank",
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                                                  },
                                                  {
                                                    "Code": "112_FactChanCyToCyOnly",
                                                    "Type": "data",
                                                    "Cells": [
                                                      {
                                                        "ColumnCode": "RowText",
                                                        "Type": "text",
                                                        "Value": "Fact-of-Life Changes (2026 to 2026 Only)",
                                                        "NarrativeData": null
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                                                        "ColumnCode": "ChanFycy",
                                                        "Type": "numeric",
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                                                        "ColumnCode": "ChanFyby1",
                                                        "Type": "blank",
                                                        "Value": "0",
                                                        "NarrativeData": null
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                                                  },
                                                  {
                                                    "Code": "112_SubtBaseFund",
                                                    "Type": "subtotal",
                                                    "Cells": [
                                                      {
                                                        "ColumnCode": "RowText",
                                                        "Type": "text",
                                                        "Value": "SUBTOTAL BASELINE FUNDING",
                                                        "NarrativeData": null
                                                      },
                                                      {
                                                        "ColumnCode": "ChanFycy",
                                                        "Type": "numeric",
                                                        "Value": "210,737",
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                                                        "Type": "blank",
                                                        "Value": "0",
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                                                    ]
                                                  },
                                                  {
                                                    "Code": "112_AntiReprReq1415Acti",
                                                    "Type": "data",
                                                    "Cells": [
                                                      {
                                                        "ColumnCode": "RowText",
                                                        "Type": "text",
                                                        "Value": "Anticipated Reprogramming (Requiring 1415 Actions)",
                                                        "NarrativeData": null
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                                                      {
                                                        "ColumnCode": "ChanFycy",
                                                        "Type": "numeric",
                                                        "Value": "0",
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                                                        "Type": "blank",
                                                        "Value": "0",
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                                                  },
                                                  {
                                                    "Code": "112_LessWarRelaAndDisaSuppAppr",
                                                    "Type": "data",
                                                    "Cells": [
                                                      {
                                                        "ColumnCode": "RowText",
                                                        "Type": "text",
                                                        "Value": "Less: War-Related and Disaster Supplemental Appropriation",
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                                                        "ColumnCode": "ChanFycy",
                                                        "Type": "numeric",
                                                        "Value": "0",
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                                                        "Type": "blank",
                                                        "Value": "0",
                                                        "NarrativeData": null
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                                                  },
                                                  {
                                                    "Code": "112_LessXyeCarr",
                                                    "Type": "data",
                                                    "Cells": [
                                                      {
                                                        "ColumnCode": "RowText",
                                                        "Type": "text",
                                                        "Value": "Less: X-Year Carryover",
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                                                        "ColumnCode": "ChanFycy",
                                                        "Type": "numeric",
                                                        "Value": "0",
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                                                        "Type": "blank",
                                                        "Value": "0",
                                                        "NarrativeData": null
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                                                    ]
                                                  },
                                                  {
                                                    "Code": "112_PricChan",
                                                    "Type": "data",
                                                    "Cells": [
                                                      {
                                                        "ColumnCode": "RowText",
                                                        "Type": "text",
                                                        "Value": "Price Change",
                                                        "NarrativeData": null
                                                      },
                                                      {
                                                        "ColumnCode": "ChanFycy",
                                                        "Type": "blank",
                                                        "Value": "0",
                                                        "NarrativeData": null
                                                      },
                                                      {
                                                        "ColumnCode": "ChanFyby1",
                                                        "Type": "numeric",
                                                        "Value": "4,595",
                                                        "NarrativeData": null
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                                                    ]
                                                  },
                                                  {
                                                    "Code": "112_FuncTran",
                                                    "Type": "data",
                                                    "Cells": [
                                                      {
                                                        "ColumnCode": "RowText",
                                                        "Type": "text",
                                                        "Value": "Functional Transfers",
                                                        "NarrativeData": null
                                                      },
                                                      {
                                                        "ColumnCode": "ChanFycy",
                                                        "Type": "blank",
                                                        "Value": "0",
                                                        "NarrativeData": null
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                                                        "ColumnCode": "ChanFyby1",
                                                        "Type": "numeric",
                                                        "Value": "0",
                                                        "NarrativeData": null
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                                                    ]
                                                  },
                                                  {
                                                    "Code": "112_ProgChan",
                                                    "Type": "data",
                                                    "Cells": [
                                                      {
                                                        "ColumnCode": "RowText",
                                                        "Type": "text",
                                                        "Value": "Program Changes",
                                                        "NarrativeData": null
                                                      },
                                                      {
                                                        "ColumnCode": "ChanFycy",
                                                        "Type": "blank",
                                                        "Value": "0",
                                                        "NarrativeData": null
                                                      },
                                                      {
                                                        "ColumnCode": "ChanFyby1",
                                                        "Type": "numeric",
                                                        "Value": "17,782",
                                                        "NarrativeData": null
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                                                    ]
                                                  },
                                                  {
                                                    "Code": "112_NormCurrEsti",
                                                    "Type": "total",
                                                    "Cells": [
                                                      {
                                                        "ColumnCode": "RowText",
                                                        "Type": "text",
                                                        "Value": "NORMALIZED CURRENT ESTIMATE",
                                                        "NarrativeData": null
                                                      },
                                                      {
                                                        "ColumnCode": "ChanFycy",
                                                        "Type": "dollar",
                                                        "Value": "210,737",
                                                        "NarrativeData": null
                                                      },
                                                      {
                                                        "ColumnCode": "ChanFyby1",
                                                        "Type": "dollar",
                                                        "Value": "233,114",
                                                        "NarrativeData": null
                                                      }
                                                    ]
                                                  }
                                                ]
                                              },
                                              {
                                                "Name": "Mandatory Funding ",
                                                "Description": "",
                                                "Type": "Toggle",
                                                "ToggleOrder": "upload",
                                                "Text": {
                                                  "Enccoding": "",
                                                  "Value": ""
                                                },
                                                "Uploads": []
                                              },
                                              {
                                                "Metadata": {
                                                  "SourceSystem": "EAS",
                                                  "ServiceAgencyAcronym": "ARNG",
                                                  "ServiceAgencyName": "ARNG Client Node",
                                                  "BudgetYear": "2025",
                                                  "BudgetCycle": "PBR",
                                                  "SubmissionDate": "September  2024",
                                                  "AppropriationNumber": "2065"
                                                },
                                                "GeneratedOutput": {
                                                  "Name": "SAG Funding by Operation",
                                                  "Description": "",
                                                  "Type": "Toggle",
                                                  "ToggleOrder": "upload",
                                                  "Text": {
                                                    "Enccoding": "",
                                                    "Value": ""
                                                  },
                                                  "Uploads": [
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                                                      "Filename": "ARNG_112_3_PBR26.xlsx",
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                                              },
                                              {
                                                "Metadata": {
                                                  "SourceSystem": "EAS",
                                                  "ServiceAgencyAcronym": "ARNG",
                                                  "ServiceAgencyName": "ARNG Client Node",
                                                  "BudgetYear": "2026",
                                                  "BudgetCycle": "PBR",
                                                  "SubmissionDate": "September 2025",
                                                  "AppropriationNumber": "2065"
                                                },
                                                "GeneratedOutput": {
                                                  "Name": "3B2 Grid",
                                                  "Description": "",
                                                  "Type": "Grid",
                                                  "Code": "Op5Part3b2",
                                                  "Columns": [
                                                    {
                                                      "Code": "RowText",
                                                      "Text": "B2. Summary of Operational Category",
                                                      "Group": "",
                                                      "Level": 0,
                                                      "Order": 1.0,
                                                      "Type": "text"
                                                    },
                                                    {
                                                      "Code": "Py",
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                                                      "Group": "",
                                                      "Level": 0,
                                                      "Order": 2.0,
                                                      "Type": "numeric"
                                                    },
                                                    {
                                                      "Code": "Cy",
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                                                      "Group": "",
                                                      "Level": 0,
                                                      "Order": 3.0,
                                                      "Type": "numeric"
                                                    },
                                                    {
                                                      "Code": "By1",
                                                      "Text": "FY 2027 \\n Estimate",
                                                      "Group": "",
                                                      "Level": 0,
                                                      "Order": 4.0,
                                                      "Type": "numeric"
                                                    }
                                                  ],
                                                  "Rows": [
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                                                      "Code": "112_BlnkRow_2",
                                                      "Type": "blank",
                                                      "Cells": []
                                                    },
                                                    {
                                                      "Code": "112_BaseProgBp",
                                                      "Type": "data",
                                                      "Cells": [
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                                                          "ColumnCode": "RowText",
                                                          "Type": "text",
                                                          "Value": "Base Programs (BP)",
                                                          "NarrativeData": null
                                                        },
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                                                          "ColumnCode": "Py",
                                                          "Type": "numeric",
                                                          "Value": "195,116",
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                                                          "ColumnCode": "Cy",
                                                          "Type": "numeric",
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                                                          "ColumnCode": "By1",
                                                          "Type": "numeric",
                                                          "Value": "203,789",
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                                                        }
                                                      ]
                                                    },
                                                    {
                                                      "Code": "112_PaciDeteInitPdi",
                                                      "Type": "data",
                                                      "Cells": [
                                                        {
                                                          "ColumnCode": "RowText",
                                                          "Type": "text",
                                                          "Value": "Pacific Deterrence Initiative (PDI)",
                                                          "NarrativeData": null
                                                        },
                                                        {
                                                          "ColumnCode": "Py",
                                                          "Type": "numeric",
                                                          "Value": "0",
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                                                        },
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                                                          "ColumnCode": "Cy",
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                                                        }
                                                      ]
                                                    },
                                                    {
                                                      "Code": "112_BlnkRow",
                                                      "Type": "blank",
                                                      "Cells": []
                                                    },
                                                    {
                                                      "Code": "112_OverOperCostOoc",
                                                      "Type": "subtotal",
                                                      "Cells": [
                                                        {
                                                          "ColumnCode": "RowText",
                                                          "Type": "text",
                                                          "Value": "Overseas Operations Costs (OOC)",
                                                          "NarrativeData": null
                                                        },
                                                        {
                                                          "ColumnCode": "Py",
                                                          "Type": "numeric",
                                                          "Value": "25",
                                                          "NarrativeData": null
                                                        },
                                                        {
                                                          "ColumnCode": "Cy",
                                                          "Type": "numeric",
                                                          "Value": "0",
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                                                        {
                                                          "ColumnCode": "By1",
                                                          "Type": "numeric",
                                                          "Value": "0",
                                                          "NarrativeData": null
                                                        }
                                                      ]
                                                    },
                                                    {
                                                      "Code": "112_OperEnduSentOes",
                                                      "Type": "data",
                                                      "Cells": [
                                                        {
                                                          "ColumnCode": "RowText",
                                                          "Type": "text",
                                                          "Value": "Operation ENDURING SENTINEL (OES)",
                                                          "NarrativeData": null
                                                        },
                                                        {
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                                                          "ColumnCode": "RowText",
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                            "ServiceAgencyAcronym": "ARNG",
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                                                        "Value": "10,772",
                                                        "NarrativeData": null
                                                      }
                                                    ]
                                                  },
                                                  {
                                                    "Code": "113_FuncTran",
                                                    "Type": "data",
                                                    "Cells": [
                                                      {
                                                        "ColumnCode": "RowText",
                                                        "Type": "text",
                                                        "Value": "Functional Transfers",
                                                        "NarrativeData": null
                                                      },
                                                      {
                                                        "ColumnCode": "ChanFycy",
                                                        "Type": "blank",
                                                        "Value": "0",
                                                        "NarrativeData": null
                                                      },
                                                      {
                                                        "ColumnCode": "ChanFyby1",
                                                        "Type": "numeric",
                                                        "Value": "0",
                                                        "NarrativeData": null
                                                      }
                                                    ]
                                                  },
                                                  {
                                                    "Code": "113_ProgChan",
                                                    "Type": "data",
                                                    "Cells": [
                                                      {
                                                        "ColumnCode": "RowText",
                                                        "Type": "text",
                                                        "Value": "Program Changes",
                                                        "NarrativeData": null
                                                      },
                                                      {
                                                        "ColumnCode": "ChanFycy",
                                                        "Type": "blank",
                                                        "Value": "0",
                                                        "NarrativeData": null
                                                      },
                                                      {
                                                        "ColumnCode": "ChanFyby1",
                                                        "Type": "numeric",
                                                        "Value": "282,321",
                                                        "NarrativeData": null
                                                      }
                                                    ]
                                                  },
                                                  {
                                                    "Code": "113_NormCurrEsti",
                                                    "Type": "total",
                                                    "Cells": [
                                                      {
                                                        "ColumnCode": "RowText",
                                                        "Type": "text",
                                                        "Value": "NORMALIZED CURRENT ESTIMATE",
                                                        "NarrativeData": null
                                                      },
                                                      {
                                                        "ColumnCode": "ChanFycy",
                                                        "Type": "dollar",
                                                        "Value": "850,330",
                                                        "NarrativeData": null
                                                      },
                                                      {
                                                        "ColumnCode": "ChanFyby1",
                                                        "Type": "dollar",
                                                        "Value": "1,143,423",
                                                        "NarrativeData": null
                                                      }
                                                    ]
                                                  }
                                                ]
                                              },
                                              {
                                                "Name": "Mandatory Funding ",
                                                "Description": "",
                                                "Type": "Toggle",
                                                "ToggleOrder": "upload",
                                                "Text": {
                                                  "Enccoding": "",
                                                  "Value": ""
                                                },
                                                "Uploads": []
                                              },
                                              {
                                                "Metadata": {
                                                  "SourceSystem": "EAS",
                                                  "ServiceAgencyAcronym": "ARNG",
                                                  "ServiceAgencyName": "ARNG Client Node",
                                                  "BudgetYear": "2025",
                                                  "BudgetCycle": "PBR",
                                                  "SubmissionDate": "September  2024",
                                                  "AppropriationNumber": "2065"
                                                },
                                                "GeneratedOutput": {
                                                  "Name": "SAG Funding by Operation",
                                                  "Description": "",
                                                  "Type": "Toggle",
                                                  "ToggleOrder": "upload",
                                                  "Text": {
                                                    "Enccoding": "",
                                                    "Value": ""
                                                  },
                                                  "Uploads": [
                                                    {
                                                      "Filename": "ARNG_113_3_PB25.xlsx",
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                                              {
                                                "Metadata": {
                                                  "SourceSystem": "EAS",
                                                  "ServiceAgencyAcronym": "ARNG",
                                                  "ServiceAgencyName": "ARNG Client Node",
                                                  "BudgetYear": "2026",
                                                  "BudgetCycle": "PBR",
                                                  "SubmissionDate": "September 2025",
                                                  "AppropriationNumber": "2065"
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                                                  },
                                                  {
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                                                          "UserText": "Increases funding in support of the National Guard Response Element to establish a National Guard Quick Response Force (NGQRF) available to respond to public safety emergencies within 24 hours, operating within a civil assistance support element structure. The NGQRF will provide 1,500 Army Guard members trained in Civil Disobedience operations.",
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                                                          "UserText": "Reduces funding to align with the adjusted Federal Employees Retirement System (FERS) contribution rates. These adjustments incorporate updated actuarial assumptions, workforce demographics shifts, and revised projections of retirement liabilities.",
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                                                        "ColumnCode": "RowText",
                                                        "Type": "text",
                                                        "Value": "Price Change",
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                                                        "Type": "text",
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                                                    "Code": "114_NormCurrEsti",
                                                    "Type": "total",
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                                                        "Type": "text",
                                                        "Value": "NORMALIZED CURRENT ESTIMATE",
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                                              {
                                                "Metadata": {
                                                  "SourceSystem": "EAS",
                                                  "ServiceAgencyAcronym": "ARNG",
                                                  "ServiceAgencyName": "ARNG Client Node",
                                                  "BudgetYear": "2025",
                                                  "BudgetCycle": "PBR",
                                                  "SubmissionDate": "September  2024",
                                                  "AppropriationNumber": "2065"
                                                },
                                                "GeneratedOutput": {
                                                  "Name": "SAG Funding by Operation ",
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                                              },
                                              {
                                                "Metadata": {
                                                  "SourceSystem": "EAS",
                                                  "ServiceAgencyAcronym": "ARNG",
                                                  "ServiceAgencyName": "ARNG Client Node",
                                                  "BudgetYear": "2026",
                                                  "BudgetCycle": "PBR",
                                                  "SubmissionDate": "September 2025",
                                                  "AppropriationNumber": "2065"
                                                },
                                                "GeneratedOutput": {
                                                  "Name": "3B2 Grid",
                                                  "Description": "",
                                                  "Type": "Grid",
                                                  "Code": "Op5Part3b2",
                                                  "Columns": [
                                                    {
                                                      "Code": "RowText",
                                                      "Text": "B2. Summary of Operational Category",
                                                      "Group": "",
                                                      "Level": 0,
                                                      "Order": 1.0,
                                                      "Type": "text"
                                                    },
                                                    {
                                                      "Code": "Py",
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                                                      "Group": "",
                                                      "Level": 0,
                                                      "Order": 2.0,
                                                      "Type": "numeric"
                                                    },
                                                    {
                                                      "Code": "Cy",
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                                                      "Group": "",
                                                      "Level": 0,
                                                      "Order": 3.0,
                                                      "Type": "numeric"
                                                    },
                                                    {
                                                      "Code": "By1",
                                                      "Text": "FY 2027 \\n Estimate",
                                                      "Group": "",
                                                      "Level": 0,
                                                      "Order": 4.0,
                                                      "Type": "numeric"
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                                                  ],
                                                  "Rows": [
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                                                      "Code": "114_BlnkRow_2",
                                                      "Type": "blank",
                                                      "Cells": []
                                                    },
                                                    {
                                                      "Code": "114_BaseProgBp",
                                                      "Type": "data",
                                                      "Cells": [
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                                                          "ColumnCode": "RowText",
                                                          "Type": "text",
                                                          "Value": "Base Programs (BP)",
                                                          "NarrativeData": null
                                                        },
                                                        {
                                                          "ColumnCode": "Py",
                                                          "Type": "numeric",
                                                          "Value": "82,142",
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                                                          "ColumnCode": "Cy",
                                                          "Type": "numeric",
                                                          "Value": "88,001",
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                                                          "ColumnCode": "By1",
                                                          "Type": "numeric",
                                                          "Value": "73,011",
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                                                      ]
                                                    },
                                                    {
                                                      "Code": "114_PaciDeteInitPdi",
                                                      "Type": "data",
                                                      "Cells": [
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                                                          "ColumnCode": "RowText",
                                                          "Type": "text",
                                                          "Value": "Pacific Deterrence Initiative (PDI)",
                                                          "NarrativeData": null
                                                        },
                                                        {
                                                          "ColumnCode": "Py",
                                                          "Type": "numeric",
                                                          "Value": "0",
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                                                        },
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                                                          "ColumnCode": "Cy",
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                                                        }
                                                      ]
                                                    },
                                                    {
                                                      "Code": "114_BlnkRow",
                                                      "Type": "blank",
                                                      "Cells": []
                                                    },
                                                    {
                                                      "Code": "114_OverOperCostOoc",
                                                      "Type": "subtotal",
                                                      "Cells": [
                                                        {
                                                          "ColumnCode": "RowText",
                                                          "Type": "text",
                                                          "Value": "Overseas Operations Costs (OOC)",
                                                          "NarrativeData": null
                                                        },
                                                        {
                                                          "ColumnCode": "Py",
                                                          "Type": "numeric",
                                                          "Value": "14",
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                                                        },
                                                        {
                                                          "ColumnCode": "Cy",
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                                                          "Value": "0",
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                                                        {
                                                          "ColumnCode": "By1",
                                                          "Type": "numeric",
                                                          "Value": "0",
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                                                        }
                                                      ]
                                                    },
                                                    {
                                                      "Code": "114_OperEnduSentOes",
                                                      "Type": "data",
                                                      "Cells": [
                                                        {
                                                          "ColumnCode": "RowText",
                                                          "Type": "text",
                                                          "Value": "Operation ENDURING SENTINEL (OES)",
                                                          "NarrativeData": null
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                                                          "UserText": "Increases funding for Home Station Training which focuses on warfighting readiness as the Army continues to restore core capabilities with all units achieving the highest levels of training readiness attainable. Increases funding for Brigade Combat Teams' operation and maintenance costs for repair parts, fuel, supplies, and other home station training support costs commensurate with increased training.",
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                                                        "NarrativeData": null
                                                      }
                                                    ]
                                                  },
                                                  {
                                                    "Code": "115_PricChan",
                                                    "Type": "data",
                                                    "Cells": [
                                                      {
                                                        "ColumnCode": "RowText",
                                                        "Type": "text",
                                                        "Value": "Price Change",
                                                        "NarrativeData": null
                                                      },
                                                      {
                                                        "ColumnCode": "ChanFycy",
                                                        "Type": "blank",
                                                        "Value": "",
                                                        "NarrativeData": null
                                                      },
                                                      {
                                                        "ColumnCode": "ChanFyby1",
                                                        "Type": "numeric",
                                                        "Value": "1,857",
                                                        "NarrativeData": null
                                                      }
                                                    ]
                                                  },
                                                  {
                                                    "Code": "115_FuncTran",
                                                    "Type": "data",
                                                    "Cells": [
                                                      {
                                                        "ColumnCode": "RowText",
                                                        "Type": "text",
                                                        "Value": "Functional Transfers",
                                                        "NarrativeData": null
                                                      },
                                                      {
                                                        "ColumnCode": "ChanFycy",
                                                        "Type": "blank",
                                                        "Value": "",
                                                        "NarrativeData": null
                                                      },
                                                      {
                                                        "ColumnCode": "ChanFyby1",
                                                        "Type": "numeric",
                                                        "Value": "0",
                                                        "NarrativeData": null
                                                      }
                                                    ]
                                                  },
                                                  {
                                                    "Code": "115_ProgChan",
                                                    "Type": "data",
                                                    "Cells": [
                                                      {
                                                        "ColumnCode": "RowText",
                                                        "Type": "text",
                                                        "Value": "Program Changes",
                                                        "NarrativeData": null
                                                      },
                                                      {
                                                        "ColumnCode": "ChanFycy",
                                                        "Type": "blank",
                                                        "Value": "",
                                                        "NarrativeData": null
                                                      },
                                                      {
                                                        "ColumnCode": "ChanFyby1",
                                                        "Type": "numeric",
                                                        "Value": "-2,957",
                                                        "NarrativeData": null
                                                      }
                                                    ]
                                                  },
                                                  {
                                                    "Code": "115_NormCurrEsti",
                                                    "Type": "total",
                                                    "Cells": [
                                                      {
                                                        "ColumnCode": "RowText",
                                                        "Type": "text",
                                                        "Value": "NORMALIZED CURRENT ESTIMATE",
                                                        "NarrativeData": null
                                                      },
                                                      {
                                                        "ColumnCode": "ChanFycy",
                                                        "Type": "dollar",
                                                        "Value": "345,261",
                                                        "NarrativeData": null
                                                      },
                                                      {
                                                        "ColumnCode": "ChanFyby1",
                                                        "Type": "dollar",
                                                        "Value": "344,161",
                                                        "NarrativeData": null
                                                      }
                                                    ]
                                                  }
                                                ]
                                              },
                                              {
                                                "Name": "Mandatory Funding",
                                                "Description": "",
                                                "Type": "Toggle",
                                                "ToggleOrder": "upload",
                                                "Text": {
                                                  "Enccoding": "",
                                                  "Value": ""
                                                },
                                                "Uploads": []
                                              },
                                              {
                                                "Metadata": {
                                                  "SourceSystem": "EAS",
                                                  "ServiceAgencyAcronym": "ARNG",
                                                  "ServiceAgencyName": "ARNG Client Node",
                                                  "BudgetYear": "2025",
                                                  "BudgetCycle": "PBR",
                                                  "SubmissionDate": "September  2024",
                                                  "AppropriationNumber": "2065"
                                                },
                                                "GeneratedOutput": {
                                                  "Name": "SAG Funding by Operation ",
                                                  "Description": "",
                                                  "Type": "Toggle",
                                                  "ToggleOrder": "upload",
                                                  "Text": {
                                                    "Enccoding": "",
                                                    "Value": ""
                                                  },
                                                  "Uploads": [
                                                    {
                                                      "Filename": "ARNG_115_3_PBR26.xlsx",
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                                              },
                                              {
                                                "Metadata": {
                                                  "SourceSystem": "EAS",
                                                  "ServiceAgencyAcronym": "ARNG",
                                                  "ServiceAgencyName": "ARNG Client Node",
                                                  "BudgetYear": "2026",
                                                  "BudgetCycle": "PBR",
                                                  "SubmissionDate": "September 2025",
                                                  "AppropriationNumber": "2065"
                                                },
                                                "GeneratedOutput": {
                                                  "Name": "3B2 Grid",
                                                  "Description": "",
                                                  "Type": "Grid",
                                                  "Code": "Op5Part3b2",
                                                  "Columns": [
                                                    {
                                                      "Code": "RowText",
                                                      "Text": "B2. Summary of Operational Category",
                                                      "Group": "",
                                                      "Level": 0,
                                                      "Order": 1.0,
                                                      "Type": "text"
                                                    },
                                                    {
                                                      "Code": "Py",
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                                                      "Group": "",
                                                      "Level": 0,
                                                      "Order": 2.0,
                                                      "Type": "numeric"
                                                    },
                                                    {
                                                      "Code": "Cy",
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                                                      "Level": 0,
                                                      "Order": 3.0,
                                                      "Type": "numeric"
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                                                      "Code": "By1",
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                                                      "Group": "",
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                                                  ],
                                                  "Rows": [
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                                                      "Code": "115_BlnkRow_2",
                                                      "Type": "blank",
                                                      "Cells": []
                                                    },
                                                    {
                                                      "Code": "115_BaseProgBp",
                                                      "Type": "data",
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                                                          "ColumnCode": "RowText",
                                                          "Type": "text",
                                                          "Value": "Base Programs (BP)",
                                                          "NarrativeData": null
                                                        },
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                                                          "ColumnCode": "Py",
                                                          "Type": "numeric",
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                                                          "ColumnCode": "Cy",
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                                                    {
                                                      "Code": "115_PaciDeteInitPdi",
                                                      "Type": "data",
                                                      "Cells": [
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                                                          "ColumnCode": "RowText",
                                                          "Type": "text",
                                                          "Value": "Pacific Deterrence Initiative (PDI)",
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                                                        },
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                                                          "ColumnCode": "Py",
                                                          "Type": "numeric",
                                                          "Value": "0",
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                                                          "ColumnCode": "Cy",
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                                                      ]
                                                    },
                                                    {
                                                      "Code": "115_BlnkRow",
                                                      "Type": "blank",
                                                      "Cells": []
                                                    },
                                                    {
                                                      "Code": "115_OverOperCostOoc",
                                                      "Type": "subtotal",
                                                      "Cells": [
                                                        {
                                                          "ColumnCode": "RowText",
                                                          "Type": "text",
                                                          "Value": "Overseas Operations Costs (OOC)",
                                                          "NarrativeData": null
                                                        },
                                                        {
                                                          "ColumnCode": "Py",
                                                          "Type": "numeric",
                                                          "Value": "0",
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                                                          "ColumnCode": "Cy",
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                                                        {
                                                          "ColumnCode": "By1",
                                                          "Type": "numeric",
                                                          "Value": "0",
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                                                        }
                                                      ]
                                                    },
                                                    {
                                                      "Code": "115_OperEnduSentOes",
                                                      "Type": "data",
                                                      "Cells": [
                                                        {
                                                          "ColumnCode": "RowText",
                                                          "Type": "text",
                                                          "Value": "Operation ENDURING SENTINEL (OES)",
                                                          "NarrativeData": null
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                                                          "UserText": "Increases funding for Home Station Training which focuses on warfighting readiness as the Army continues to restore core capabilities with all units achieving the highest levels of training readiness attainable. Increases funding for Brigade Combat Teams' operation and maintenance costs for repair parts, fuel, supplies, and other home station training support costs commensurate with increased training.",
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                                                        "ColumnCode": "RowText",
                                                        "Type": "text",
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                                                  {
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                                                        "ColumnCode": "RowText",
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                                                        "ColumnCode": "RowText",
                                                        "Type": "text",
                                                        "Value": "X-Year Carryover",
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                                                        "Type": "text",
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                                                    "Code": "116_SubtBaseFund",
                                                    "Type": "subtotal",
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                                                        "ColumnCode": "RowText",
                                                        "Type": "text",
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                                                    "Code": "116_AntiReprReq1415Acti",
                                                    "Type": "data",
                                                    "Cells": [
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                                                        "ColumnCode": "RowText",
                                                        "Type": "text",
                                                        "Value": "Anticipated Reprogramming (Requiring 1415 Actions)",
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                                                    "Type": "data",
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                                                        "ColumnCode": "RowText",
                                                        "Type": "text",
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                                                        "Type": "text",
                                                        "Value": "Less: X-Year Carryover",
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                                                  {
                                                    "Code": "116_PricChan",
                                                    "Type": "data",
                                                    "Cells": [
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                                                        "ColumnCode": "RowText",
                                                        "Type": "text",
                                                        "Value": "Price Change",
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                                                  },
                                                  {
                                                    "Code": "116_FuncTran",
                                                    "Type": "data",
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                                                        "ColumnCode": "RowText",
                                                        "Type": "text",
                                                        "Value": "Functional Transfers",
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                                                  },
                                                  {
                                                    "Code": "116_ProgChan",
                                                    "Type": "data",
                                                    "Cells": [
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                                                        "ColumnCode": "RowText",
                                                        "Type": "text",
                                                        "Value": "Program Changes",
                                                        "NarrativeData": null
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                                                        "ColumnCode": "ChanFycy",
                                                        "Type": "blank",
                                                        "Value": "0",
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                                                  },
                                                  {
                                                    "Code": "116_NormCurrEsti",
                                                    "Type": "total",
                                                    "Cells": [
                                                      {
                                                        "ColumnCode": "RowText",
                                                        "Type": "text",
                                                        "Value": "NORMALIZED CURRENT ESTIMATE",
                                                        "NarrativeData": null
                                                      },
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                                                        "Type": "dollar",
                                                        "Value": "1,114,864",
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                                                      },
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                                                        "ColumnCode": "ChanFyby1",
                                                        "Type": "dollar",
                                                        "Value": "1,096,948",
                                                        "NarrativeData": null
                                                      }
                                                    ]
                                                  }
                                                ]
                                              },
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                                                "Name": "Mandatory Funding ",
                                                "Description": "",
                                                "Type": "Toggle",
                                                "ToggleOrder": "upload",
                                                "Text": {
                                                  "Enccoding": "",
                                                  "Value": ""
                                                },
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                                              },
                                              {
                                                "Metadata": {
                                                  "SourceSystem": "EAS",
                                                  "ServiceAgencyAcronym": "ARNG",
                                                  "ServiceAgencyName": "ARNG Client Node",
                                                  "BudgetYear": "2025",
                                                  "BudgetCycle": "PBR",
                                                  "SubmissionDate": "September  2024",
                                                  "AppropriationNumber": "2065"
                                                },
                                                "GeneratedOutput": {
                                                  "Name": "SAG Funding by Operation ",
                                                  "Description": "",
                                                  "Type": "Toggle",
                                                  "ToggleOrder": "upload",
                                                  "Text": {
                                                    "Enccoding": "",
                                                    "Value": ""
                                                  },
                                                  "Uploads": [
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                                                      "Filename": "ARNG_116_3_PBR26.xlsx",
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                                              },
                                              {
                                                "Metadata": {
                                                  "SourceSystem": "EAS",
                                                  "ServiceAgencyAcronym": "ARNG",
                                                  "ServiceAgencyName": "ARNG Client Node",
                                                  "BudgetYear": "2026",
                                                  "BudgetCycle": "PBR",
                                                  "SubmissionDate": "September 2025",
                                                  "AppropriationNumber": "2065"
                                                },
                                                "GeneratedOutput": {
                                                  "Name": "3B2 Grid",
                                                  "Description": "",
                                                  "Type": "Grid",
                                                  "Code": "Op5Part3b2",
                                                  "Columns": [
                                                    {
                                                      "Code": "RowText",
                                                      "Text": "B2. Summary of Operational Category",
                                                      "Group": "",
                                                      "Level": 0,
                                                      "Order": 1.0,
                                                      "Type": "text"
                                                    },
                                                    {
                                                      "Code": "Py",
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                                                      "Group": "",
                                                      "Level": 0,
                                                      "Order": 2.0,
                                                      "Type": "numeric"
                                                    },
                                                    {
                                                      "Code": "Cy",
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                                                      "Group": "",
                                                      "Level": 0,
                                                      "Order": 3.0,
                                                      "Type": "numeric"
                                                    },
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                                                      "Group": "",
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                                                      "Type": "numeric"
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                                                  "Rows": [
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                                                      "Code": "116_BlnkRow_2",
                                                      "Type": "blank",
                                                      "Cells": []
                                                    },
                                                    {
                                                      "Code": "116_BaseProgBp",
                                                      "Type": "data",
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                                                          "ColumnCode": "RowText",
                                                          "Type": "text",
                                                          "Value": "Base Programs (BP)",
                                                          "NarrativeData": null
                                                        },
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                                                          "ColumnCode": "Py",
                                                          "Type": "numeric",
                                                          "Value": "1,126,690",
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                                                          "ColumnCode": "Cy",
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                                                        }
                                                      ]
                                                    },
                                                    {
                                                      "Code": "116_PaciDeteInitPdi",
                                                      "Type": "data",
                                                      "Cells": [
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                                                          "ColumnCode": "RowText",
                                                          "Type": "text",
                                                          "Value": "Pacific Deterrence Initiative (PDI)",
                                                          "NarrativeData": null
                                                        },
                                                        {
                                                          "ColumnCode": "Py",
                                                          "Type": "numeric",
                                                          "Value": "0",
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                                                    },
                                                    {
                                                      "Code": "116_BlnkRow",
                                                      "Type": "blank",
                                                      "Cells": []
                                                    },
                                                    {
                                                      "Code": "116_OverOperCostOoc",
                                                      "Type": "subtotal",
                                                      "Cells": [
                                                        {
                                                          "ColumnCode": "RowText",
                                                          "Type": "text",
                                                          "Value": "Overseas Operations Costs (OOC)",
                                                          "NarrativeData": null
                                                        },
                                                        {
                                                          "ColumnCode": "Py",
                                                          "Type": "numeric",
                                                          "Value": "1,719",
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                                                        },
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                                                          "ColumnCode": "Cy",
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                                                          "ColumnCode": "By1",
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                                                          "Value": "0",
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                                                        }
                                                      ]
                                                    },
                                                    {
                                                      "Code": "116_OperEnduSentOes",
                                                      "Type": "data",
                                                      "Cells": [
                                                        {
                                                          "ColumnCode": "RowText",
                                                          "Type": "text",
                                                          "Value": "Operation ENDURING SENTINEL (OES)",
                                                          "NarrativeData": null
                                                        },
                                                        {
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                                                  {
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                                                          "UserText": "Increases funding for Home Station Training which focuses on warfighting readiness as the Army continues to restore core capabilities with all units achieving the highest levels of training readiness attainable. Increases funding for Brigade Combat Teams' operation and maintenance costs for repair parts, fuel, supplies, and other home station training support costs commensurate with increased training.",
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Typical mission capabilities include rescuing casualties trapped in rubble, decontamination, and performing medical triage and initial treatment to stabilize for transport to a medical facility.</p><p>&nbsp;</p><p>&nbsp; &nbsp; &nbsp;The Homeland Response Force (HRF), directed by the Secretary of War,&nbsp;transforms the&nbsp;Department of War CBRNE Consequence Management capability into a faster more flexible response capability. The HRFs combine with the CBRNE Homeland Response Force and CSTs to form&nbsp;an integral part of an overall CBRNE Consequence Enterprise with the overall objective to save lives during a major or catastrophic&nbsp;CBRNE&nbsp;event. These units provide additional regional capability (one in each of the ten Federal Emergency Management Agency Regions) to enhance lifesaving capabilities, maximize flexibility, and reduce response time.</p><p>&nbsp;</p><p>&nbsp; &nbsp; &nbsp;Command and Control Chemical, Biological, Radiological, Nuclear Response Element funding supports COTS durable and non-durable equipment and supplies to include chemical and biological protective response suits, self-contained breathing apparatus, and a mix of highly specialized chemical, biological, and radiological sensors and identification equipment.</p><p>&nbsp;</p><p><strong></strong><strong>Organizational Clothing Individual Equipment Sustainment&nbsp;(OCIE)</strong><strong> -</strong><strong>&nbsp;</strong>Provides resources for the inventory, distribution, diagnostic services, repair, replacements, warehousing, and automated accountability of OCIE.</p><p><strong>&nbsp;</strong></p><p><strong>Privatized Army Lodging</strong><strong> -</strong><strong>&nbsp;</strong>Provides resources and travel for ARNG personnel performing Basic Training, One Station Unit Training, and Advance Individual Training, Initial Entry Training, and Basic Officer Leader Course for ARNG officers (Reserve Officers' Training Corps only).</p><p>&nbsp;</p><p><strong>Range Operations</strong><strong> -</strong><strong>&nbsp;</strong>Provides resources for (1)&nbsp;the Integrated Training Area Management Program; and (2) resources range operations. Funds day-to-day range operations expenses to include consumable supplies on ranges (e.g. target materials), local range operations, target/instrumentation maintenance contracts, operational unexploded ordnance clearance, miscellaneous services, and personnel training and travel.<strong></strong><strong></strong></p><p><br /></p><p><strong>Training (Professional Development)</strong><strong> -</strong><strong>&nbsp;</strong>Provides resources for (1) the Army Training Information Infrastructure program that includes the hardware, software, communications, classrooms, facilities, and services necessary to develop, store, retrieve, deliver, and manage training information and content; (2) Reserve Component Training Support; and (3) operating costs to support the One Army School System which include the mission of augmenting United States Army Training and Doctrine Command Initial Entry Training and Reserve Officers' Training Corps instructor support.</p><p>&nbsp;</p><p><strong>Training Support Centers (TSC)</strong><strong> -</strong><strong>&nbsp;</strong>Provides resources for the training support operations and the sustainment/maintenance, and training support systems to support live, virtual, constructive, and gaming capabilities. TSC includes the following: Training Support Centers, Flight training, Maneuver and Close Combat Non-System, Live training and synthetic training facilities, Installation Preparedness programs, and Training Aids Devices Simulators and Simulations Contractor Logistics Support.</p><p><strong>&nbsp;</strong></p><p><strong><span style=\"color:#ff0000;\">MANDATORY FUNDING JUSTIFICATION:</span></strong></p><p><span style=\"color:#ff0000;\"><strong></strong></span><strong></strong></p><p><span style=\"color:#ff0000;\">The FY 2026 spend plan amount for Force Readiness Operations Support includes $800,413 thousand of discretionary and $20,688 thousand of mandatory for a total of $821,101 thousand.</span></p>"
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