System Framework Research Articles

Multi scale analysis of social-ecological system of lobster (Panulirus spp.) fisheries in the Gunungkidul waters, Yogyakarta

Abstract Lobster is a high-value fisheries commodity in Gunungkidul Regency. Lobster resource management in the waters of Gunungkidul Regency has not been well identified in the social-ecological system (SES) framework. This study aims to describe and analyze the dynamics of interrelationships between the social-ecological system components of lobster fisheries in Gunungkidul Regency, which consists of the subsystem of resource systems (RS), resource units (RU), resource actors (RA), and resource governance (RG) and their interrelationships within and between subsystems to formulate a sustainable lobster management strategies in the waters of Gunungkidul Regency. This research was conducted from November 2022 until January 2023. The results of this study have indicated a dynamic interaction between the SES components of lobster fisheries. RS and RA are the SES components with the highest influence, so the slightest changes in RS and RA can cause co-evolutive changes to all the SES components of lobster fisheries in the waters of Gunungkidul Regency.

Optimizing safe and sustainable public transit for wellness tourism: Southeast Asian case studies

This study presents the development of the Reinforcement-Learning Multi-Objective Artificial Multiple Intelligence System (RL-MOAMIS) framework, aimed at optimizing public transport systems specifically designed for wellness tourism in Southeast Asia. The framework is tailored to enhance the safety, sustainability, and economic viability of bus routes that connect key wellness destinations across Thailand, Laos, and Vietnam. By integrating safety and environmental sustainability principles through a mixed-integer programming model, the RL-MOAMIS framework introduces two innovative improvement methods inspired by metaheuristic operators and employs a reinforcement-learning-based approach to dynamically select enhancement strategies. The empirical results demonstrate that the RL-MOAMIS framework significantly outperforms conventional methods, such as the Genetic Algorithm and Whale Optimization Algorithm, achieving a 27.45% increase in optimization efficiency, a 15% improvement in safety metrics, and a sustainability index enhancement ranging from 7.35% to 13.48% across all routes. The findings underscore the potential of RL-MOAMIS as a comprehensive and adaptable solution for optimizing public transport in wellness tourism. These improvements not only provide safer and more sustainable transportation options but also support economic development in rapidly urbanizing regions. The implications of this study are significant for policymakers, urban planners, and tourism developers, offering critical insights for the design and implementation of public transport systems that cater to the unique demands of wellness tourism.

Abstract P406: Transforming Clinical Practices for Blood Pressure Management in Community Health Centers through Timely Data and Technical Support

Introduction: Blood pressure (BP) control can prevent major adverse cardiac events and is monitored through various means, including the Centers for Medicare and Medicaid Services 165 metric for BP control - an annual reporting metric for community health centers (CHCs) within the Uniform Data System framework that becomes accessible 6 months after the conclusion of the reporting period. In pursuit of more immediate indicators related to BP management, the National Hypertension Control Initiative (NHCI) initiated collaboration with a population health platform to support select CHCs with rapidly available data on 19 BP-related metrics. Hypothesis: With technical support and regular access to data, CHCs can implement timely clinical practice and process changes. Methods: To support CHCs in using the population health platform, NHCI staff provided technical assistance in a rapid cycle performance improvement (RCPI) to 10 interested CHCs. This opportunity allowed CHCs to partner with NHCI staff to review BP related metrics in the population health platform and to identify opportunities for clinical process and practice changes. Over an 8-week period from October to December 2023, 7 CHCs were actively involved in a series of 5-6 structured 30–60-minute meetings with both NHCI registered nurse and quality improvement staff. These meetings reviewed BP metrics, mapped clinical workflows for improvement, and supported data analytics. CHCs often chose 1-2 BP metrics for focus, concentrating on incremental change and short-term improvement. Results: Among participating CHCs that reported, they revealed successful or anticipated adjustments in team responsibilities and clinical processes, including leadership involvement and new methods. Limitations included CHC staff engagement, time, concerns with data reliability, and familiarity with the population health platform. Most reporting CHCs shared that their goals were greatly impacted by access to readily available performance data and that they plan to continue using the population health platform to affect performance moving forward. Conclusions: For participating CHCs, individualized guidance based on timely data may have been helpful in analyzing workflows and procedures, assessing clinical care practices, and implementing quality improvement plans. Frequent data may allow CHCs to make clinical practice and process changes to efficiently measure impact and more quickly improve BP control than standard methods.

Unexpected social change: The transformation of the Pati Regency’s coastal community due to the Indonesian government’s trawl restriction policy

Abstract Indonesia’s developmental endeavors, with a focal point on Java Island, presented an overarching concern for the excessive depletion of its coastal and maritime reservoirs. This fundamental notion laid the groundwork for Indonesian governmental actions in 2015 under the stewardship of Minister of Marine Affairs and Fisheries Susi Pujiastuti. During this period, a proactive measure was introduced, entailing the imposition of fishing limitations within the Northern Java Sea vicinity. Embodied within the Ministerial Regulation of Marine Affairs and Fisheries No. 2 of 2015, the restriction of Deploying Trawl and Seine Nets within Indonesian Fishery Management Zones became a tangible manifestation aimed at upholding the preservation of coastal and maritime resources. After an approximate span of eight years since the enforcement of this policy, noteworthy transformations have transpired within the northern Java capture fisheries sector. Comprehensive interviews, meticulous observations, and scrutiny of documents within the Pati Regency (particularly in the Juwana sub-district) within the Central Java province revealed discernible shifts within coastal communities in a relatively brief span. Employing the social-ecological system framework, an analytical lens was cast upon the repercussions of this governmental restriction policy on the circumstances of the Juwana sub-district’s coastal communities, notably the fishermen. The curtailment imposed on fishing apparatus compelled fishermen to modernize and enhance the efficiency of their equipment. The evolving working ethos of the community trended toward collective endeavors and opportunistic pursuit of commercial prospects. Nevertheless, simultaneous challenges surfaced, including societal disparities amidst coastal communities, the marginal involvement of local governance, and the plausible peril of ecosystem detriment beyond the initial boundaries.

Leader-follower formation control of nonholonomic mobile robots subject to robots failure

Over the years, control of autonomous vehicles in a defined formation has been the subject of much research. Albeit leader-follower approach being one of the most used in formation control, it suffers a major practical drawback of leader failure while cruising in formation. In this work, we aim to solve this problem by proposing a novel assignment algorithm that assigns a new leader from the follower robots to ensure robots complete their given task when their leader fails. This algorithm also assign role to new robots joining the group, as well as the failed robot when rescued back to the team. We drive robots towards their desired trajectories to achieve formation using a Lyapunov-based time-varying state tracking controller from the literature. Due to role switching amongst member robots, we propose a new variant of the limit-cycle obstacle avoidance algorithm to ensure smooth and collision free transition. Simulations and experiments are performed using the robot operating system framework due to its flexibility to verify the effectiveness and reliability of the proposed algorithms.

Digital Governance and Its Role in the Islamic Economy- Analytical Study

This study investigates the role of digital governance within the Islamic economy, aiming to explore how modern technological advancements can be integrated into Islamic financial institutions while adhering to Sharia law. The research employs an analytical and comparative approach to examine the intersection of digital governance and Islamic economics, focusing on its implications for economic management and institutional transparency. The results indicate that digital governance offers a framework of systems and mechanisms that enhance the efficiency, accountability, and transparency of Islamic institutions. These governance practices, while rooted in the principles of Islamic economics, are essential for the modern adaptation of these institutions, particularly in the global economy. The study concludes that adopting digital governance within Islamic finance can significantly improve the management and operational integrity of these institutions, ensuring their alignment with both religious and modern economic principles.

Suggested solutions to barriers in accessing healthcare by persons with disability in Uganda: a qualitative study

BackgroundThere are 1.3 billion people with disabilities globally, and they frequently face barriers to accessing healthcare, contributing to their worse health and higher mortality. However, little research has explored patient-reported approaches to improve healthcare for persons with disabilities. Consequently, this study aimed to explore possible solutions and recommendations to address the existing barriers to access to healthcare for persons with disabilities in rural Uganda.MethodsWe conducted 27 semi-structured interviews with individuals with various disabilities in rural Luuka district, Eastern Uganda, between September and November 2022. The participants included individuals with visual impairment (n = 5), physical impairment (n = 5), hearing impairment (n = 6), multiple impairments (n = 5), intellectual/cognitive impairment (n = 5), and albinism (n = 1). Interviews were recorded, transcribed verbatim, and thematically analysed. We categorized the solutions using the Missing Billion disability-inclusive health systems framework.ResultsOur findings, framed within the health systems framework, revealed several critical themes. On the demand side, suggested solutions emphasized advocacy and sensitization for persons with disabilities, their communities, and caregivers about healthcare needs. Socio-economic empowerment and community-based health services were also highlighted as essential. On the supply side, participants stressed the importance of training healthcare workers on disability, facilitating dialogue and experience-sharing sessions, and employing health workers with disabilities. Additional recommendations included improving accessibility and reasonable accommodation, organizing inclusive services like special clinic days and outreaches, ensuring representation in health facility management, and establishing comprehensive rehabilitation services with affordable assistive devices.ConclusionThe multifaceted solutions proposed by persons with disabilities highlight the complex challenges they face in accessing healthcare services and highlight the necessity for comprehensive, sustainable interventions. The call to action for policymakers and healthcare providers is to prioritise the incorporation of disability-inclusive practices and explore multi-dimensional approaches that foster a more inclusive healthcare environment that adequately meets the needs of persons with disabilities.

Developing a robust security framework for inter-bank data transfer systems in the financial service sector

This paper explores the critical need for a robust security framework in inter-bank data transfer systems within the financial services sector. It reviews current security measures, identifies key vulnerabilities, and examines existing standards and protocols such as SWIFT and ISO 20022. Major security threats, including cyber-attacks and insider risks, are analyzed alongside technological, operational, and regulatory challenges. The impact of emerging technologies like blockchain and AI on security is discussed. Recommendations are provided for financial institutions to enhance security practices and for regulators to strengthen policy frameworks. The paper also highlights future research directions to address evolving security challenges in the financial sector.

Resilience optimization of bus-metro double-layer network against extreme weather events

The resilience of bus and metro systems to extreme weather events is a critical concern in urban planning, given their growing complexity and interconnectivity. Traditional studies often simplify or overlook the interdependency between different transportation modes, focusing on recovery strategies for a single mode to enhance system resilience. This study proposes an integrated resilience assessment framework for bus and metro systems, conceptualized as a Bus-Metro Double-Layer Network (B-M DLN). The framework considers both network structure and system function to accurately evaluate the B-M DLN resilience. A resilience optimization model for B-M DLN based on Genetic Algorithm (GA) is established to suggest the optimal recovery sequence of damaged stations, emphasizing the importance of station repair time, node strength, and node degree in recovery prioritization. Through a case analysis of Xi’an City, China, the B-M DLN shows significantly enhanced resilience when applying the optimal recovery strategy, especially in large-scale failure scenarios.

Zawiłości wynalazku biotechnologicznego w świetle prawa cywilnego, podatkowego i bilansowego

The main research problem of the article is the juridical assessment of a biotechnological invention in the light of civil, tax and accounting law. The aim is to present the issue of biotechnological invention from the perspective of various areas of law, the process of shaping current legislation in this field, as well as a review of Polish and EU case law. The work presents a broader analysis of biotechnological inventions in three branches of law: civil, tax and accounting. In the context of civil law, the principles of legal protection of this type of inventions were analyzed, as well as their impact on civil law relations. The main aspects of the regulation of biotechnological inventions in Polish civil law are presented, including the criteria for granting patents, as well as issues related to intellectual property. The importance of a balance between the protection of innovation and social interests and the need to constantly adapt the law to dynamically developing biomedical technologies were emphasized. Legal analysis based on tax law showed how complex the subject of the biotechnological invention is. All theses were supported by literature, legislation and case law. Tax law shows the potential of the invention and the possibilities associated with it. The accounting law segment of the study determines the categorization of biotechnological inventions within the appropriate framework of the legal system by identifying the relevant legal provisions.

Identifying patterns and mechanisms of AI integration in blockchain for e-voting network security

The study focuses on the enhancement of e-voting blockchain network security through the integration of artificial intelligence. The critical problem addressed is the existing limitations in real-time threat detection and anomaly detection within blockchain transactions. These limitations can compromise the integrity and security of blockchain networks, making them vulnerable to attacks and fraudulent activities. The core results of the research include the development and implementation of sophisticated AI algorithms designed to enhance the monitoring of blockchain transactions and the auditing of smart contracts. These AI-driven advancements introduce unique features, such as the capability to detect and respond to security threats and anomalies in real-time. This significantly strengthens and optimizes the security frameworks of blockchain systems in e-voting. These results are explained by the strategic application of machine learning and natural language processing methodologies. By employing these advanced AI techniques, the study has achieved more accurate and efficient threat detection, thereby addressing the security challenges previously mentioned. The practical applications of these findings are extensive and diverse. Enhanced security mechanisms can be utilized in financial transactions, supply chain management, and decentralized applications, providing a robust framework for improved blockchain-based e-voting security. In conclusion, integrating AI into blockchain security mechanisms addresses current limitations in threat detection and offers a scalable and effective solution for future security challenges

Ecology and conservation of cavity-nesting birds in the Neotropics: Recent advances, future directions, and contributions to ornithology

ABSTRACT About 35% of tree-cavity-nesting bird species inhabit the Neotropics, a region crucial to understanding their breeding ecology, conservation, and roles in social-ecological systems. Sixteen years ago, Cornelius et al. (2008) reviewed published knowledge and identified research priorities for Neotropical cavity-nesting birds. Advances since 2008 have not been synthesized and many remain excluded from dominant ornithology because of barriers that disproportionately affect people and ideas from the Global South. Here, we review recent advances in knowledge about Neotropical cavity-nesting birds, introduce the Special Feature series “Ecology and conservation of cavity nesters in the Neotropics,” and outline possible directions for future research. Research in the Neotropics has advanced knowledge of breeding biology, demonstrated that nest sites are limited and birds compete for cavities (mainly in humid forests), identified non-excavated cavities (formed by wood decay) as the main source of cavities and demonstrated the importance of understanding Indigenous and local community relationships to birds. With field studies across the Neotropics, the Special Feature series shows how environment, people’s common imaginaries, vegetation management, and behavior of avian excavators can interact to influence cavity availability, with ecological consequences for many cavity-using organisms. In the future, researchers should center ethno-knowledge and natural history to create an accurate list of cavity-nesting birds in the Neotropics, and integrate this knowledge into studies of population and community ecology. It is also important to study factors that influence cavity dynamics, especially using a social-ecological systems framework and especially in arid and semi-arid regions. We recommend expanding the concept of nest webs (ecological networks of cavity nesters) to incorporate additional cavity substrates (e.g., termitaria, cliffs), cavity alternatives (e.g., bulky enclosed stick nests of many Furnariidae), and cavity-using taxa beyond birds and mammals (e.g., social insects, snakes), which abound in the Neotropics but were not contemplated in the original nest web formulation. Translated versions of this article are available in Supplementary Material 1 (Spanish) and Supplementary Material 2 (Portuguese).

AR/VR assisted integrated framework of autonomous disassembly system for industrial products

An immersive Augmented Reality (AR) technology enhances productivity and flexibility in manufacturing by providing real-time instructions within workers’ field of view, aiding in complex tasks. According to cognitive load and attention-based theories, AR guidance can reduce cognitive strain, enhancing task performance. The affordance of AR in industrial processes like assembly or disassembly for repair/maintenance has been exploited broadly. However, the prevailing studies on automated user interfaces for AR instruction development, specifically virtual scene creation and target generation for object mapping rendering, still need to be explored. Notably, production industries currently rely on outsourcing skilled professionals to create AR overlaying instructions using manufacturer input. However, the exactness of the disassembly repository is substantial to avoid defects in AR guidance particulars. This underscores the significance of generalized automated AR instruction development and emphasizes the demands for further research. In this work, the autonomous AR-integrated framework is developed for the disassembly context, empowering manufacturers to acquire desired outcomes across various modules. These modules include the validation of the manual user disassembly sequence repository during the prefatory phase of AR instruction creation and the provision of Disassembly Sequence Planning (DSP) input. Additionally, the framework supports the simulation/rendering of disassembly efforts in a virtual platform and the generation of rendering virtual display scenes for appropriate AR-guided object mapping. Furthermore, it enables the generation of essential model targets for registering the AR scenes. Subsequently, the extracted repositories (virtual scenes and model targets) are input into the Unity AR tool to create AR mapping guidance for disassembly operations. The performance of the autonomous disassembly module is evaluated through three case studies with different AR visualizations. Furthermore, the potential of the proposed framework is exploited by extracting feedback from experts regarding flexibility, compatibility, completion time, and cognitive level.

Managing Change in Healthcare Systems Policy and Healthcare Service Delivery System in India

Health is not just the absence of disease; it is a state of total physical, mental, and social well-being." The purposeful arrangement of individuals, organizations, and resources that provides healthcare services to the target population in need is known as the healthcare system. Around the world, there are as many different types of healthcare systems as there are civilizations, cultures, societies, and histories. This implies that a country must create its own healthcare system based on its requirements and available resources. An examination of the Indian health sector reveals the labour, difficulties, supply, demand, and necessary future research. In addition to the excellent work that is readily apparent, there are other areas that require development and attention. It is imperative that research of this kind be conducted to address the uncharted territory. The goal of this study is to examine potential workable remedies for the health-related problems. Additionally, the study attempts to solve the issues and create some framework for the health care system.

DeepOpt: a deep learning optimized privacy preservation framework for cyber-physical systems

Privacy preservation and security enhancement are the key components of any network architecture due to advanced attack procedures. Cyber-Physical Systems (CPS) also need a mitigation and prevention strategy to deal with cyber threats. The existing approaches majorly deal with attack detection and focus on one or two attacks at a time. With this focus and demand of the CPS, this work proposes a deep learning optimized privacy preservation framework called DeepOpt. This proposed framework prevents the network from attackers and maintains security by classifying multiple attackers simultaneously using deep learning architecture. The proposed framework initializes privacy preservation using the trust-based approach and a hybrid optimization algorithm. In this, the network is divided into different zones, and each zone is secured using trust parameters with additional verification by secure hash function. The hybrid optimization selects the communication path using trust and energy that returns the attack-free path. This proposed architecture is simulated over different network scenarios with or without attacker nodes, and their traces are labeled to train the proposed deep convolutional neural network architecture. Finally, these models are integrated, and their performance is analyzed in different network scenarios and the presence of five different attackers such as blackhole, wormhole, man-in-the-middle attack, spoofing, and distributed denial of service. The simulation results, with improvement in detection accuracy, packet delivery ratio, and other performance factors, indicate the effectiveness of the proposed framework for both prevention and mitigation. Hence, this overall architecture preserves the privacy of CPS even in multifarious dynamic network scenarios.

Understanding Socio-Ecological Complexity of Mangrove-Crocodile-Fisher System of Bugsuk Island, Balabac, Palawan, the Philippines

The mangrove forest in Palawan has the most extensive distribution in the Philippines. The fisher community's perception of the mangrove forest as a known habitat for saltwater crocodiles (Crocodylus porosus) and its fishery benefits in Bugsuk Island were gathered using a participatory systems mental modeling framework for the coastal social-ecological system. From the causal loop diagram, six reinforcing and one balancing feedback loop were derived. The respondents observed a positive growth in the interaction between mangroves and crocodiles in Bugsuk Island, with both populations expanding and providing support to fishery resources. Bugsuk Island represents a unique diversity with great potential for resource conservation and economic benefit.

Using a sustainable food systems framework to examine gender equality and women’s empowerment in aquatic food systems

This article aims to generate novel insights by examining gender dynamics within aquaculture and small-scale fisheries, employing a gendered agrifood systems conceptual framework to comprehensively analyze gender equality and women’s empowerment in aquatic food systems. To do this, it evaluates 202 articles using a scoping review methodology. Though additional literature from 19 articles was pulled in to provide the context. The findings are that aquatic foods value chains and food environment are negatively impacted by gender disparities in terms of women’s agency, access to and control over resources, gendered social norms, and policies and governance. This hampers the ability of women to engage in and benefit from aquatic food systems. This results in gendered disparities in dietary outcomes, low achievements in relation to gender equality and women’s empowerment, and less adaptive capacity in relation to developing resilient livelihoods. The article acknowledges the importance of developing and leveraging women’s agency and bargaining power, strengthening their access to and control over key aquatic food systems resources, tackling harmful gender norms, developing gender-sensitive data collection and analysis to inform evidence-based policymaking, and implementing gender-responsive and gender-transformative policies and strategies to create an enabling environment for these interventions to succeed. Investment in multi-level, and multi-layered, gender-responsive and gender-transformative approaches are needed to co-develop – with women and their organizations – positive, gender-equitable norms to strengthen women’s agency and decision-making at a variety of levels, ranging from individual to policy level.

Study of quantum decoherence at the Protvino to ORCA experiment

Protvino to ORCA (oscillation research with cosmics in the abyss) (P2O) is an upcoming neutrino oscillation experiment with a very long baseline of 2595 km. Because of the substantial baseline, this experiment provides a unique opportunity to study the Earth matter effects over very large distances. This makes it a suitable experiment to investigate the environmental decoherence in neutrino oscillations, where the neutrino system could interact with a stochastic environment and lead to a loss in the coherence of neutrino states. In this work, we consider an open quantum system framework to simulate the neutrino oscillations in the P2O experiment and obtain bounds on the decoherence parameters in different phenomenological models. Here, we also consider that the decoherence parameter Γ depends on neutrino energy Eν as Γjk(Eν)=Γ0(EνE0)n. Furthermore, assuming the presence of decoherence in nature, we study the effect of it on the determination of neutrino mass hierarchy and CP violation at the P2O experiment. Published by the American Physical Society 2024

A high resolution hydrodynamic-biogeochemical-oyster-filtration model predicts that the presence of oysters (Crassostrea virginica) can improve, or reduce, water quality depending upon oyster abundance and location

The eastern oyster (Crassostrea virginica) provides numerous ecosystem services such as building reef habitat, clarifying the water by filtering seston, and reducing excess nitrogen when their biodeposits are denitrified. Some of these ecosystem services have been extensively studied using two-dimensional and three-dimensional (3D) models. Yet, the relationship between oyster abundance, their filtration and biodeposition rates, and associated water quality metrics has not been estimated with high-resolution models that include biodeposit resuspension as well as simulation of 3D processes in the sub-tributaries where oysters are abundant. To undertake these estimates, a 3D Regional Ocean Modeling System (ROMS) framework, comprised of a coupled hydrodynamic-water quality model with an oyster filtration and biodeposition sub-model, was implemented over a fine-resolution model grid (120–150 m) of the Choptank River on the eastern shore of Chesapeake Bay, U.S.A. After validation with data from 20 cruises between May and September 2010, the model was used to predict seven variables associated with water quality in simulations with zero, recent, and 50x recent abundances of oysters. Results indicated that improvement in the seven water quality variables differed in response to the abundance of oysters and between regions in the Choptank River. In line with expectations, the water quality metrics improved with increasing oyster abundance in the shallow and retentive sub-tributaries of Broad and Harris Creeks. In contrast, in the deeper and more flushed mainstem of the Choptank River, some water quality metrics deteriorated when recent abundances of oysters were added to the model compared to the simulation with zero oysters and the same metrics improved when oyster abundances were increased by 50x. Overall, model results indicated that the many complex physical and biogeochemical processes that influence the effect of oysters on water quality resulted in differing responses to oysters across different systems. In addition, this study introduces a high-resolution, predictive tool that could be used to estimate the number of oysters needed to meet water quality thresholds in specific systems in support of ecosystem management.

Equity in practice: Integrating cross cultural health brokers for culturally safe primary care for immigrants and refugees in British Columbia.

Umbrella Multicultural Health Co-op is a community health centre serving cultural communities of immigrants/refugees in British Columbia. It uses Cross Cultural Health Brokers (CCHBs), multicultural workers bridging patients and the healthcare system, to better meet the primary care needs of immigrant/refugee populations. Through the Team Primary Care initiative, Umbrella Co-op: (1) added new CCHBs alongside allied health practitioners; and (2) implemented team workshops and evaluation for quality improvement. The learning health system framework guided project activities. Comprehensive, culturally responsive primary care for immigrants and refugees benefits from a team-based approach that includes the integration of CCHBs. Team development activities improved team function. Co-developing evaluation with the interprofessional team enabled meaningful participation. Health system design for equity-oriented team-based primary care for immigrants and refugees should include resources for CCHBs and team development infrastructure.