The implementation of the Indonesia Case Base Groups (INA-CBG’s) payment system under the National Health Insurance scheme has fundamentally altered hospital financial and operational dynamics. This study aims to analyze hospitals’ strategic responses to the evolving challenges of the INA-CBG’s payment system within the BPJS Kesehatan era. A Systematic Literature Review (SLR) approach was employed by reviewing 42 national and international scientific articles published between 2014 and 2025, retrieved from Scopus, Web of Science, Google Scholar, and Sinta databases, following PRISMA guidelines. The synthesis of findings indicates that the prospective case-based payment system generates significant implications for hospital management, particularly in cost control, claim management, operational efficiency, and organizational adaptation. Hospitals’ strategic responses are reflected in strengthening financial governance, optimizing service processes, improving clinical documentation accuracy, enhancing information systems, and adjusting organizational policies. Key challenges identified include tariff adequacy, financial risk, administrative complexity, and potential tensions between efficiency and service quality. The findings highlight that hospitals with stronger managerial capacity and integrated information systems demonstrate better adaptability to payment system dynamics. This study underscores the importance of strategic and managerial readiness in sustaining hospital performance and service continuity within a prospective payment environment.

Purpose This study aims to introduce and empirically validate a novel moderated-mediation model to explain how integrating AI and blockchain as an intelligent information system for accounting transforms organizational knowledge into a strategic asset, ultimately enhancing sustainable value and competitive advantage within the ASEAN region. The authors propose a comprehensive framework where this technological system improves sustainability reporting quality (SRQ; a critical knowledge output), contingent upon the firm’s internal governance and the external environment. Specifically, the authors pioneer a contingent governance perspective, arguing that the amplifying role of internal governance is itself conditional on external pressures. Design/methodology/approach Adopting a quantitative approach, this study analyzes a panel data set of 3,300 firm-year observations from listed companies across major ASEAN economies. Structural equation modeling is used to test a sophisticated moderated-mediation framework. This methodology allows for a robust examination of the complex, conditional pathways linking AI and blockchain adoption to sustainable value while simultaneously assessing the contingent effects of enterprise risk management (ERM) and environmental uncertainty. Findings Results reveal that the AI and blockchain-powered system significantly improves the quality of sustainability reporting (a key knowledge output), which in turn drives sustainable value. Critically, the effectiveness of this system is amplified by robust ERM. However, the study uncovers a nuanced conditional effect: the strategic value of ERM is itself contingent on the level of external environmental uncertainty, highlighting how internal knowledge systems must adapt to external pressures to remain effective. Practical implications This research provides a practical roadmap for managers on how to build and govern information systems that translate technological investment into tangible, sustainable performance. It offers a new lens for investors to evaluate a firm’s knowledge management capabilities alongside its technological infrastructure. For policymakers, it underscores the need for policies that foster not just technology adoption but also the development of resilient organizational systems capable of navigating a highly interdependent world. Originality/value First, it is among the first study, to the best of the authors’ knowledge, to empirically model the complete pathway from a specific technological system to sustainable value via the mediating mechanism of SRQ. Second, and most significantly, it pioneers the concept of “contingent governance” by demonstrating that the moderating effect of ERM is not universal but is itself moderated by environmental uncertainty. This multi-level interaction offers a far more nuanced view than previously understood. Third, by situating this complex model within the under-researched, high-growth context of the ASEAN region, the authors provide crucial insights for emerging markets on leveraging information as a predominant asset.

The Monterrey Metropolitan Area (MMA), the largest urban and industrial center in northeastern Mexico, faces increasing groundwater stress driven by rapid urban expansion, recurrent drought, and limited surface-water availability. Since 2024, the San Juan River has been considered a potential source of treaty water under the 1944 U.S.–Mexico Water Treaty, further intensifying pressure on regional water resources. This study evaluates changes in groundwater recharge potential between 1990 and 2022 using an integrated Remote Sensing–Geographic Information System framework combined with the Analytic Hierarchy Process. Eight thematic layers—geology, structural lineaments, slope, geomorphology, precipitation, drainage density, Normalized Difference Vegetation Index, and soil type—were weighted to derive a Groundwater Potential Index and delineate recharge zones. Results show a pronounced redistribution of recharge capacity over 32 years. Very low recharge areas increased by 1021.3 km2, while very high recharge zones decreased by 100.4 km2. In total, more than 1100 km2 experienced degradation in recharge potential, mainly associated with urban growth and land-use change. These findings highlight the urgent need for sustainable groundwater management, stronger land-use planning, and protection of recharge areas. Coordinated action among stakeholders and robust regulatory enforcement will be essential as the region navigates future growth and international water obligations.

Biodiversity is declining in many parts of the world. Biological diversity measurement and monitoring are fundamental to the assessment of the causes and consequences of environmental changes, identification of key areas for the protection of biodiversity or ecosystem services, determining the effectiveness of actions, and the creation of decision-support tools critical to maintaining a sustainable planet. Biodiversity measurement is rapidly changing due to advances in citizen science, image recognition, acoustic monitoring, environmental DNA, genomics, remote sensing, and AI. In this perspective, we outline the exciting opportunities these developments offer but also consider the challenges. Our key recommendations are to 1) Capitalize on the ability of novel technology to integrate data sources 2) agree to standard methods for data collection 3) ensure new technologies are calibrated with existing data; 4) fill data gaps by using emerging technologies and increasing capacity, especially in the tropics; 5) create living safeguarded databases of trusted information to reduce the risk of poisoning by AI hallucinated, or false, information; 6) ensure data generation is valued; 7) ensure respectful incorporation of Indigenous Knowledge; 8) ensure measurements enable the quantification of effectiveness of actions, and 9) increase the resilience of global datasets to technical and societal change. Radical new collaborations are needed between computer scientists, engineers, molecular biologists, data scientists, field ecologists, citizen scientists, Indigenous peoples, policymakers, and local communities to create the rigorous, resilient, accessible biodiversity information systems required to underpin policies and practices that ensure the maintenance and restoration of ecological systems.

The article comprehensively examines the features of information-analytical support (IAS) in operational-investigative activities (OIA) aimed at countering youth crime, through the lens of legal, organizational-technological, and methodological aspects. The legal foundations of OIA and the application of operational-investigative tools are analyzed, along with modern technological solutions for the collection, processing, and analysis of operational information, and international experience in this area. Based on a review of current scientific studies and the specifics of the research problem, IAS in OIA is considered as a complex system of interrelated actions by authorized entities, aimed at collecting, accumulating, verifying, analytically processing, summarizing, and forecasting criminogenic processes in the youth environment. The role of modern digital technologies, social networks, online platforms, and automated information systems in the early identification of youth crime risks, the creation of «threat profiles,» and forecasting the dynamics of criminogenic processes is highlighted. It is substantiated that the effectiveness of OIA largely depends on the consolidation of operational information, its systematization, analytical processing, and transformation into reliable analytical conclusions for tactical and strategic decision-making. The need for an interdisciplinary approach combining criminal-legal, sociological, and technical factors is emphasized, and promising directions for the development of IAS in OIA are outlined in the context of socio-economic and digital transformations, the intensification of threats due to war, and the growth of youth deviance. The findings confirm the strategic role of IAS in ensuring systematic risk management of youth crime, underscore the need to modernize information infrastructure, create integrated analytical environments, improve legal regulation, implement advanced digital technologies, and train highly qualified analytical personnel to ensure the preventive effectiveness of operational measures.

Surgical treatment of high anal fistulas is challenging and associated with a relatively high rate of complications and failure. Stem cell therapy has shown promising results for fistulas associated with Crohn's disease but remains less studied in cryptoglandular fistulas. This clinical trial is being performed to evaluate the outcome of treating complex cryptoglandular perianal fistulas (PAFs) using minimal surgical debridement combined with either non-cultured (autologous) or cultured (allogeneic) adipose-derived regenerative cells (ADRCs). The primary outcome is the clinical healing rate after 12months. Secondary outcomes include functional outcomes regarding quality of life and anal continence (measured by the 36-Item Short Form Health Survey [SF-36] and the Wexner Fecal Incontinence Score), risk factors for fistula recurrence, radiological healing assessed by magnetic resonance imaging, and comparison of autologous versus allogeneic ADRCs with respect to cell characterization, immune responses, and efficacy. This is a double-blinded, randomized interventional non-inferiority, phase I-II clinical trial using two approved investigational medicinal products. The study will be conducted at the surgical department, Odense University Hospital OUH, in Odense, Denmark. Inclusion criterion is an adult patient (≥ 18years) with complex PAF (high transsphincteric or suprasphincteric), involving more than 30% of the anal sphincter. Key exclusion criteria are ongoing suppuration, simple anal fistula, ano- or rectovaginal fistula, inflammatory bowel disease, body mass index (BMI) of < 18.5kg/m2, known allergy to penicillin or streptomycin, pregnancy, and verified syphilis, human immunodeficiency virus (HIV), or hepatitis on screening test. The primary investigator (PI) is responsible for participants' recruitment. Eligible patients will undergo 1-day surgery, including debridement of the fistula tract and closure of the internal orifice, liposuction from the anterior abdominal wall, injection of 30-40mL of autologous microfat around the fistula tract, and injection of 30 million stem cells (either autologous ADRCs or allogeneic ADRC001) according to randomization (1:1 allocation ratio). Patients who receive treatment will attend follow-up visits at 3, 6, and 12months postoperatively. Serious adverse events will be reported including large abscess formation, wound dehiscence causing fecal incontinence, sepsis, major bleeding, and serious allergic reactions. The trial has been approved by the European Medicines Agency EMA and is monitored by the Good Clinical Practice (GCP) Unit at OUH. A total of 75 patients will be included. Recruitment began in October 2024, with a planned duration of 3years. The trial intervention is designed as a minimally invasive treatment with the potential to shorten and ease recovery, enable a quicker return to daily activities and work, and avoid sphincter damage, thereby preserving function. The trial is expected to provide evidence on whether allogeneic ADRCs combined with microfat are a viable alternative to autologous ADRCs with microfat for the treatment of PAF. Clinical Trials Information System (CTIS) EU CT 2022-502659-73-01. Registered on 18 November 2023. org NCT06303752. Registered on 25 February 2024.

The Lancet Commission on Global Surgery (LCoGS) defined six indicators with 2030 targets to track national surgical system performance. The aim of this systematic review was to evaluate national reporting and attainment of benchmarks for each indicator and to assess the quality of modelling studies used to fill data gaps. Seven bibliographic databases (1 April 2015-24 July 2024) and government domains of 48 countries committed to National Surgical, Obstetric, and Anaesthesia Plans were searched. Records providing national estimates of any LCoGS indicator were eligible. The primary outcome was the proportion of World Bank-classified countries meeting indicator benchmarks and the secondary outcome was the quality of modelled national estimates. This systematic review was prospectively registered in PROSPERO, the international prospective register of systematic reviews (CRD420250650890). Of 4245 records retrieved, 44 studies were included (35 research articles and 9 policy documents). Among 217 World Bank-classified countries, access to timely essential surgery (indicator 1) was reported for 94 countries (39% meeting benchmark), specialist surgical workforce density (indicator 2) was reported for 167 countries (50.3% meeting benchmark), surgical volume (indicator 3) was reported for 124 countries (31.5% meeting benchmark), perioperative mortality (indicator 4) was reported for 74 countries (no benchmark was set at country level), and financial risk protection indicators (indicators 5 and 6) were reported for five countries, with none meeting either benchmark. Across indicators, high-income countries were more likely to meet benchmarks. Most modelled studies lacked transparency in data sources, statistical methods, or model validation. Reporting of LCoGS indicators remains sparse and uneven, particularly in low- and middle-income countries. Without standardized, routine measurement and minimum quality standards for modelled estimates, progress towards 2030 cannot be credibly tracked. Integrating surgical metrics into national health information systems should be a policy priority.

ABSTRACT The growing complexity of spatial data management in Architecture, Engineering, and Construction requires integration of Building Information Modeling and Geospatial Information Systems. This study proposes a topological ontology that formally represents adjacency, intersection, and containment relationships to support spatial reasoning in built environments. Utilizing Semantic Web technologies, Industry Foundation Classes data are converted into Resource Description Framework to enhance interoperability and enable efficient spatial queries. A case study on a multi-story building demonstrates improved data management; RDF files are 12.8 times smaller than IFC files with sub-second performance for complex topological queries.

Inventory management is one of the important aspects of theatrical performance execution, where several important elements support the needs of the show. Within the scope of Zone 3 Cirebon, there are various theater organizations or groups spread across various campuses. In this study, several campuses were selected as samples: Universitas Muhammadiyah Cirebon (through the "Roempoet" Theater Club), Swadaya Gunungjati University (through USB &amp; "Blue Chain Theater"), UNTAG 17 August (through the Department of Arts and Culture UNTAG 17), and IAIN Syekh Nurjati (through "Teater Awal") in Cirebon. The purpose of this research is to facilitate collaboration between theater organizations from various campuses, thereby facilitating the exchange of information about the borrowing of performance equipment between various organizations in Zone 3 Cirebon. This information system is web-based and developed using hardware such as the HP AMD RYZEN 5 laptop, powered by software including Visual Studio Code and Xampp. It uses the Laravel 8 Framework and the PHP programming language. The final result of this study is the Application of a Web-Based Theater Performance Inventory Borrowing System (Case Study: Campus Theater in Cirebon City). This Information System presents data about inventory, users, inventory types, administrators, loan records, and inventory borrowing and return processes.

The paper discusses the development and research of an information system for image generation based on modern generative artificial intelligence models with support for feder-ated learning and retraining mechanisms. The proposed system is focused on ensuring effec-tive generation of visual content while maintaining the confidentiality of user data, which is especially relevant in conditions of limited access to centralized data sets.The research analyzes the architecture of the information system, the principles of inte-gration of generative models, as well as approaches to organizing federated learning, in which model parameters are updated on local nodes without transmitting the output data to the central server. Particular attention is paid to methods of retraining models, which allow the system to adapt to new types of images, styles and user requirements during operation.The performance and efficiency of the proposed system are evaluated in terms of the quality of generated images, learning speed and resistance to changes in input data. The re-sults obtained confirm the feasibility of using a federated approach and further training of generative models to create scalable, adaptive, and secure image generation information sys-tems.In the future, it is planned to expand the functionality of the system, including adding full registration and authorization, the ability to use multiple LoRA adapters simultaneously, increasing the number of models available for training and generation, and implementing ad-ditional algorithms for federated learning.

Information systems are an important element in the business world that helps businesses increase work efficiency and reduce human error. In practice, many businesses still produce financial reports manually. Manual preparation of financial reports is inefficient and tends to have a higher potential for delays, lateness, or errors in data entry. This makes the financial reports presented inaccurate and unreliable as a basis for making decisions. To address this problem, a community service program was implemented by designing an accounting system using Microsoft Access, which provides various features that can help users in data processing. The method carried out starts with observation, system design, and evaluation by the partner. The result of implementing this program is that the system designed in Microsoft Access successfully accelerated the work process for partners, making the preparation of financial reports more efficient and timely. The financial reports presented also became more accurate and reliable.

Employee attendance plays a crucial role in human resource management; however, at Perumda Tirta Intan Garut, the attendance process is still conducted manually, leading to recording errors, delays in data recapitulation, and difficulties in monitoring employee discipline. This study aims to develop a web-based employee attendance information system using the Agile Development method to improve the efficiency, accuracy, and effectiveness of attendance management. The research employs a Research and Development (R&amp;D) approach combined with Agile Methodology, allowing iterative system development and continuous user feedback. System modeling is carried out using Unified Modeling Language (UML), including use case, activity, sequence, and class diagrams. The system is implemented using the Laravel framework and a MySQL database, while functional testing is conducted using Black Box Testing. The results indicate that the developed system enables real-time attendance recording, reduces data entry errors, accelerates attendance report generation, and improves user satisfaction. This study contributes practically by providing an adaptive and efficient web-based attendance system and methodologically by demonstrating the effectiveness of Agile Development in information system development within public service organizations.

Nahdlatul Ulama University, which manages multiple institutions, requires an integrated information system to coordinate academic and administrative processes efficiently. However, developing such a system faces challenges related to business process complexity and the need for diverse user role distribution. This study aims to design an integrated academic information system (SIUNU) by combining BPMN business process modeling and RACI matrix analysis to produce a modular, scalable, and accountable system architecture in a multi-campus environment. The research employs a qualitative-descriptive methodology with a case study approach. Business process modeling was conducted using Business Process Model and Notation (BPMN) 2.0 to visually represent workflows. The research produced business process models for five main modules: Authentication (login, forgot password, logout), Academic Dashboard (student data, lecturer data, GPA summaries, tracer studies), Evaluation and Reporting (teaching evaluation), Letter Management (drafting, verification, disposition, archiving), and the MBKM Module (program registration, credit conversion). RACI analysis generated structured role mapping, showing the Super Admin as the primary accountable party for system configuration, PTNU Admin as the operational implementer, Lecturers as academic consultants, and Students as active users of personal data. The integration of BPMN and RACI proved effective in producing an academic information system design framework that is not only technically robust but also organizationally accountable. This research contributes to the development of academic information system literature through an integrative approach and provides a ready-to-implement design for Nahdlatul Ulama University.

The theoretical and applied aspects of computer modeling are described, taking into account modern methods of constructing information, measurement and control systems (IIAs) of aircraft during their operation. The LA and IIiUS facilities are high‑tech and complex technical systems (CTC) that require combined approaches to their assessment. The ways of forming the main blocks of information models for obtaining the main indicators of aircraft reliability and safety are shown. Formulas are given for the use of adequate information technology processes and methods for assessing the technical level of created samples of both single‑level and multi‑level hierarchical systems in combination with known methods, operating algorithms and software, which are more complete in information content with probabilistic characteristics. The theoretical aspects of the work and the formulations are supported by a computational experiment, during which the aircraft cargo was delivered to a given area. The results of the work can be useful to developers of unmanned aircraft systems and specialists in the field of designing CTC facilities when predicting their technical condition with an assessment of functional safety and ensuring the desired efficiency.

The Aim of the paper is to analyse the state of the art of artificial intelligence application in Russia as regards technological dependability, as well as to propose new promising areas of research and development. Methods. The methods of contextual information search, system analysis, and dependability theory are used. Results . A review of domestic publications in the area of interest was conducted and showed the applicability of various artificial intelligence methods, in particular machine learning, to improve the dependability of various technological items. Two main t asks are identified to be solved: identification of pre failures in order to prevent failures by conducting preventive maintenance or repair; rapid detection of failures that have already occurred and their localisation. Examples of existing similar solutions are provided. The possible ways to overcome the absence of initial learning data associated with rare failures, are analysed. For more accurate prediction of failures, it is proposed to collect and use not only the parameters that characterise an examined item itself, but also environmental parameters that can also affect the condition of the item. The paper shows the relevance of studies aimed at generalized and systematic results to serve as guidelines for preferred application of certain artificial intelligence methods. New promising areas of artificial intelligence application are indicated, i.e., identifying possible common causes in cases of multiple failures, which will help reduce recovery time, and analysing the root causes of failures in order to take measures to eliminate them or reduce their future impact. Conclusion . The conducted analysis and the propose recommendations will contribute to the cross‑industry exchange of experience, the expansion and deepening of work on the use of artificial intelligence for dependability assurance and make them more practical.

Background: Hospital administrative processes including billing, scheduling, and medical records management—are critical to health system performance but are often characterized by inefficiencies, high operational costs, and workforce burden. Artificial intelligence (AI) and automation technologies, including robotic process automation (RPA) and natural language processing (NLP), have emerged as potential solutions to streamline these processes and enhance productivity. Objective: This scoping review aimed to synthesize existing evidence on the use of AI and automation in hospital administrative functions, focusing on efficiency gains, cost savings, implementation barriers, and ethical and regulatory considerations. Methods: A scoping search of peer-reviewed literature was conducted across major electronic databases including PubMed, Scopus, Web of Science, and Google Scholar. Studies published between 2015 and 2025 that examined AI-based or automation-driven interventions in hospital administrative settings were included. Eligible studies addressed applications in billing, scheduling, records management, hospital information systems, or workflow optimization. Data was extracted and synthesized narratively due to heterogeneity in study designs and outcome measures. Results: The review identified substantial evidence that AI and automation improve administrative efficiency through reduction of processing time, minimization of manual errors, and optimization of resource allocation. RPA demonstrated significant benefits in billing and claims processing, while NLP enhanced documentation accuracy and records retrieval. Several studies reported measurable cost savings and productivity improvements following implementation. However, common barriers included integration challenges with legacy systems, limited interoperability, data quality concerns, staff resistance, insufficient training, high upfront costs, and uncertain short-term return on investment. Regulatory and governance challenges, particularly data protection compliance and algorithm transparency were also frequently highlighted. Conclusion: AI and automation technologies show considerable promise in transforming hospital administrative processes by improving efficiency and reducing operational costs. Nevertheless, successful implementation requires strong governance frameworks, workforce capacity building, financial planning, and ethical oversight. Future research should focus on longitudinal cost-effectiveness evaluations and context-specific implementation strategies, particularly in resource-limited health systems.

Education Stakeholders’ Experience in the Use of Public Employee’s Performance Management Information System (PEPMIS) in Monitoring Teachers' Job Performance in Public Secondary Schools in Dar-es salaam, Tanzania

This study investigates the critical role of management accounting systems (MAS) in facilitating entrepreneurial decision-making within the Cambodian business context. As entrepreneurship emerges as a pivotal strategy for economic development and employment generation in developing economies, understanding the informational infrastructure that supports entrepreneurial ventures becomes increasingly essential. Management accounting systems serve as fundamental suppliers of economic information that enable entrepreneurs to make informed decisions regarding business operations, resource allocation, and strategic planning. This research synthesizes existing literature on accounting information systems and their influence on entrepreneurial behavior, examining how the integration of financial and managerial accounting components provides comprehensive decision-support mechanisms. The findings reveal that accounting information systems significantly and positively influence entrepreneurial decision-making by providing reliable information management capabilities, enhancing business operation oversight, and supporting strategic resource deployment. Furthermore, the study demonstrates that the quality of accounting information systems, when combined with digital technologies such as e-commerce platforms, creates synergistic effects that amplify entrepreneurial confidence and decision-making efficacy. The implications for Cambodia's developing entrepreneurial ecosystem suggest that strengthening management accounting education and system implementation could substantially enhance the nation's entrepreneurial capacity and economic growth trajectory.

Abstract. The combined use of independent soil moisture data from radar and radiometer measurements in data assimilation (DA) systems is expected to yield synergistic performance gains due to their complementary strengths. This study evaluates the impact of simultaneously assimilating soil moisture retrievals from ASCAT (Advanced SCATterometer) and SMAP (Soil Moisture Active Passive) into the Korean Integrated Model (KIM) using a weakly coupled DA framework based on the National Aeronautics and Space Administration's Land Information System (LIS). The Noah land surface model (LSM) within LIS, which is the same as that used in KIM, is used to simulate land surface states and assimilate soil moisture retrievals. The impact of soil moisture DA is evaluated using independent reference datasets, assessing its influence on soil moisture analysis and numerical weather prediction performance. Overall, assimilating single-sensor soil moisture data, ASCAT or SMAP, into the LSM improves global soil moisture analysis accuracy by 4.0 % and 10.5 %, respectively, compared to the control case without soil moisture DA, achieving the most significant enhancements in croplands. Relative to single-sensor soil moisture DA, multi-sensor soil moisture DA yields more balanced skill enhancements for both specific humidity and air temperature analyses and forecasts. The most pronounced synergistic improvements by simultaneously assimilating both soil moisture products are observed in the 2 m air temperature analysis and forecast, especially when both soil moisture products have a positive impact. Precipitation forecast skill also improves with multi-sensor soil moisture DA, although the improvements are not consistent across regions and events. This paper discusses remaining issues for future studies to further improve the weather prediction performance of the KIM-LIS multi-sensor soil moisture DA system.

Modern optical systems are able to send and receive ultra-short temporal pulses (USP). At the same time, pulse broadening, as a result of antenna dispersion, limits USP applications in the microwave. Here, we set out to increase the coherent bandwidth of loop antennas. Through simulation and experiments, we show that by increasing the loop thickness, one may achieve USP attributes – 260 ps upon transmitting and 380 ps upon receiving (which is equivalent to a coherent channel exceeding 2.5 GHz). Finally, the bandwidth of most parametric oscillators and amplifiers is narrow, and we look at ways to increase it. A loop inside a loop system, coupled by a nonlinear impedance element, exhibits a line-narrowing and signal amplification. In all, these elements could be advantageous for applications such as ultra-wide bandwidth communication and nonlinear quantum information systems.