Fair Resource Research Articles

The allocation and fairness of hospital pharmacist human resources in China: a time-series study

BackgroundTo address the rational use of medicines in healthcare institutions, the Chinese government enacted legislation for pharmacists in 2021, emphasizing the importance of pharmacists in medical services. The allocation and equity of pharmacist human resources in healthcare institutions directly affect people’s accessibility to pharmaceutical services. The study aims to analyze the supply and demand of pharmacist human resources in Chinese healthcare institutions and evaluate the equity of their distribution to provide a reference for the rational management of pharmacist resources.MethodsThis was a time-series study that was conducted using data obtained from Health and Health Statistical Yearbook that is performed every year by the National Health Commission of the People’s Republic of China. The study included 31 provinces, municipalities, and autonomous regions and 34,354 medical institutions in mainland China, which were classified into different economic regions based on their level of economic development. The study collected healthcare technicians and pharmacist data from national healthcare institutions between 2016 and 2020. The study evaluated the level of pharmacist human resource allocation using the health resource density index. The study explored the equity of pharmacist human resource allocation from two aspects: population and geographic area, using the Gini coefficient and Theil index.ResultsThe average annual growth rates of healthcare technical staff and pharmacists in Chinese medical institutions from 2016 to 2020 were 5.67% and 3.03%, respectively. The Gini coefficients of healthcare personnel resources based on population distribution were all below 0.119, while those based on geographical area were all above 0.655. The total Theil indexes of pharmacist human resources based on population distribution were all below 0.010, while those based on geographical area were all above 0.511. In addition, the contribution rates of the within-group Theil indexes of pharmacist human resources based on population and geographical area distributions to the total Theil index were all greater than or equal to 50%.ConclusionsThe allocation level of pharmacist human resources in China continues to improve, but there are differences in different economic development areas. Currently, allocation based on population shows equity, but allocation based on geographic area shows inequity. In the future, more attention should be paid to the geographic accessibility of pharmacist human resources, and resource allocation should consider both the population served and geographic area.

Optimized Architecture for Efficient OFDMA Network Design

This study presents a novel approach to enhancing the design and performance of OFDMA (Orthogonal Frequency Division Multiple Access) networks, with a particular focus on WiMAX (Worldwide Interoperability for Microwave Access) for Best Effort (BE) services. The proposed method integrates a robust Markovian analytical model with four advanced scheduling algorithms: throughput fairness, resource fairness, opportunistic scheduling, and throttling. A sophisticated simulator was developed, incorporating an ON/OFF traffic generator, user-specific wireless channels, and a dynamic central scheduler to validate the model’s accuracy and evaluate its robustness by dynamically allocating radio resources per frame. The validation study showed that the proposed model reduced simulation time by over 90%, completing analytical calculations in just 15 min, compared to nearly 2 days for simulations using conventional scheduling algorithms. Performance metrics such as the average number of active users and resource utilization closely matched those from the validation study, confirming the model’s accuracy. In the robustness study, the model consistently performed well across diverse traffic distributions (exponential and Pareto) and channel conditions. The proposed architecture increased network throughput by up to 25% and reduced latency under dynamic conditions, demonstrating its scalability, adaptability, and efficiency as a crucial solution for next-generation wireless communication systems.

2.C. Round table: A Pandemic Treaty to deliver global health equity: negotiating under a ticking clock

Abstract Access to medical countermeasures (vaccines, therapeutics, diagnostics), fair resource allocation and a global health framework to counter future pandemics are to be provided for by the Pandemic Treaty, intensely debated in the Intergovernmental Negotiating Body (INB) over the past two years. The final negotiations round began under tremendous pressure (Apr 29, 2024), with dissonance on structural treaty elements and a ticking clock to finalise the text at the World Health Assembly (end of May 2024). At a time of shifting geopolitical powers, in a year of elections across the world, war in Europe and rising defence expenditure, countries are reluctant to commit; the draft postpones key decisions, proposing to establish two intergovernmental working groups for instruments on One Health and prevention, and on a Pathogen Access and Benefits (PABS), with technology transfer and capacity-building remain largely unaddressed, despite COVID-19 lessons. With EU and G7 countries holding to their positions on surveillance, financing, and intellectual property (IP), negotiations will continue. A more critical question remains: will the Treaty’s be adequate and timely enough to meet the challenges of inevitable future pandemics? Will it deliver the global framework of its foundational purpose of equity and justice? This RT aims to inform and involve the European public health community, continuing the series of activities embarked upon at the beginning of the pandemic, empowering its members for evidence-informed advocacy and concerted action. Following a brief presentation on the Treaty’s key provisions, each panel member will deliver a brief (2-3 min) intervention based on core expertise, with two rounds of panel questions/statements to follow, and with an interactive element to prioritise and submit questions. The first elaborating on the current provisions, linking them to the key expertise of panel members, i.e., international and EU law, public health law, One Health and infectious disease control, global health policies, technology transfer, fair pricing and access to countermeasures. The second examining what can be achieved via evidence-informed advocacy, and with a special focus on the role of the European public health community. Has it been well represented so far in negotiations? Should it be more involved? Is it well equipped to provide expert advice to Europe’s policymakers? Is there complementarity in relation to Europe’s Global Health Strategy (GHS) and national global health plans? Finally, the role of WHO will be briefly debated. How can sovereignty be safeguarded without compromising implementation? What is the role of transparency and sound governance to remain in line with national and EU laws and priorities? The last five minutes of this RT will be used to consolidate messages and share plans to inform future formal EUPHA positioning in negotiations. Key messages • Pandemic accord deliberation has have taken place under extreme urgency and geopolitical pressure. The European public health community must be informed and engaged for EU and country-level advocacy. • At a time of permacrisis, the adoption of a global framework for fair resouce allocation, access to medical countermeasures,and to strengthen health systems for future pandemics is urgently needed. Speakers/Panelists Sujitha Subramanian University of Liverpool, Liverpool, UK Dimitra Lingri European Healthcare Fraud and Corruption Network, Brussels, Belgium Debjani Muller HTAi, Edmonton, Canada Ricardo Mexia National Institute of Health Dr. Ricardo Jorge, Lisbon, Portugal Bettina Borisch WFPHA, Geneva, Switzerland

Contribution-Based Resource Allocation for Effective Federated Learning in UAV-Assisted Edge Networks.

This paper considers UAVs as edge computing nodes and investigates a novel network resource allocation method for federated learning within a three-layer wireless network architecture containing cloud, edges (UAVs), and clients. To address the issue of fair bandwidth resource allocation among clients participating in federated learning, a contribution calculation strategy based on the Shapley value (SV) used as the weight for model aggregation is proposed. On this basis, a client selection and wireless resource allocation method based on model contribution is further designed. By reducing the training and aggregation frequency of the low-contribution clients during the asynchronous aggregation phase, the limited bandwidth resources are allocated to high-contribution clients, thus improving the convergence speed and accuracy of the global model. Simulation experiments demonstrate that the proposed method can significantly reduce the system delay and total energy consumption with gains between 15% and 50% while also improving the final accuracy of the global model by 0.3% and 2% on both short-term and long-term perspectives, respectively.

A distributed end-to-end fair bandwidth allocation algorithm for multi-path networks

Multi-path transmission significantly improves network performance, yet it complicates the problem of fair resource allocation. While traditional fair bandwidth allocation schemes thrive in single-path settings, they often falter when applied to multi-path environments, highlighting the challenge of achieving fair bandwidth sharing in such networks. To tackle this issue, the concept of "max-min similarity" of queuing delays has been introduced based on insight into the intrinsic interactions between queuing packets, delays, and bandwidth allocation, which leads to a formal definition of max-min fair bandwidth allocation for multi-path environments. Theoretical analysis shows that the max-min similarity of queuing delays is a sufficient condition for max-min fair bandwidth allocation in single bottleneck environments. A novel distributed end-to-end fair bandwidth allocation algorithm, named DMFBA, is then proposed, which separates the control into flow-level and transmission path-level. In achieving max-min similarity in queuing delays by dynamically adjusting the distribution of flows’ queuing packet quotas across paths it achieves the goal of max-min fair bandwidth allocation. Two sets of numerical simulation experiments were conducted and the results show that DMFBA has less overhead and faster convergence than the traditional utility fair algorithms.

Does corporate social responsibility influence corporate innovation in China? Combining innovation investment and dynamic capabilities theory

Purpose According to reputation theory, enterprises that adopt a proactive approach to corporate social responsibility (CSR) are known to actively invest in corporate innovation. However, this theory does not fully explain the mechanisms through which CSR influences corporate innovation, nor does it address how to effectively amplify CSR’s positive impact on innovation. To overcome these limitations, this research aims to incorporate the theories of innovation investment and dynamic capabilities. Innovation investment theory elucidates how CSR can attract additional financing, which can be directed toward innovation activities. Meanwhile, dynamic capabilities theory highlights how digital transformation in enterprises can enhance the positive effects of CSR on innovation, providing insights from both theoretical and empirical perspectives. Design/methodology/approach To demonstrate the mediating role of debt financing costs and the moderating role of enterprise digital transformation in the mechanism of CSR on corporate innovation, this research conducts fixes effects models by collecting 27,912 data points from 3,775A-share China-listed enterprises, ranging in period from 2010 to 2020. Empirical research once again proves that the theories of innovation investment and dynamic capabilities effectively compensates for the shortcomings of reputation theory. These three theories effectively explain that what is the effect of CSR on enterprise innovation? How does CSR influence corporate innovation? And through what mechanisms can CSR better enhance corporate innovation? Findings According to innovation investment theory, the cost of debt financing mediates the positive relationship between CSR and corporate innovation. This occurs because enterprises with robust CSR practices are more likely to secure external funding, thereby reducing their costs associated with external debt financing. Lower debt financing costs provide a stable source of funds for corporate innovation. Additionally, dynamic capability theory suggests that enterprise digital transformation moderates the positive relationship between CSR and corporate innovation. Building on these insights, it is recommended that enterprises, especially state-owned ones, should prioritize technological innovation to enhance their competitiveness. Research limitations/implications This research aims to address and narrow the knowledge gap regarding the relation between CSR and corporate innovation through theoretical and empirical analyses. With respect to the influence mechanism, this research solely based on innovation investment theory and dynamic capabilities theory, focuses on the influence mechanism of CSR on corporate innovation, with the debt financing costs as the mediating variable and digital transformation as the moderating variable. However, the influence mechanism turns out to be complicated and there is room for further exploring numerous mechanisms. For example, future research can focus on identifying additional channels through which CSR exerts an influence on corporate innovation based on TOE theoretical framework. Practical implications This research presents several strategies to enhance corporate innovation based on its conclusions: First, enterprises should promptly publish social responsibility reports to build a positive industry reputation. Moreover, by actively participating in CSR activities, they can strengthen their networks and enhance their industry standing. Second, the significant mediating role of debt financing costs should not be ignored. Enterprises are encouraged to seek diverse financing channels to reduce financial pressures, address financing challenges and facilitate the coordinated development of CSR and innovation. Third, enterprise digital transformation significantly affects the impact of CSR on innovation. Therefore, enterprises should advance digital transformation initiatives that incorporate technological innovation, organizational improvements and integration with supply chain partners. Finally, it has been noted that state-owned enterprises are often less responsive to technological innovation than their non-state counterparts. SOEs could redefine the scope and priorities of their social responsibilities to prevent excessive resource consumption that could hinder innovation. For instance, integrating some of their social responsibilities with innovation projects could promote both social and technological innovation objectives. Additionally, the government could ensure fair resource distribution among different types of enterprises and provide an equitable financing platform to mitigate financial challenges for both state-owned and non-state-owned enterprises. Originality/value Reputation theory does not fully elucidate the mechanisms by which CSR influences corporate innovation or how to effectively enhance CSR’s positive impact on innovation. This research integrates the theories of innovation investment and dynamic capabilities to address these gaps. According to innovation investment theory, debt financing costs mediate the positive relationship between CSR and corporate innovation. Meanwhile, dynamic capabilities theory posits that enterprise digital transformation moderates this positive relationship, further strengthening the impact of CSR on innovation.

Primary healthcare nurses' experiences in managing chronic diseases during COVID-19 in the North West province.

The World Health Organization, stated that the coronavirus disease 2019 (COVID-19) pandemic not only affected the socioeconomic well-being of millions but also had adverse effects on public health, particularly in the management of chronic diseases at the primary healthcare (PHC) level. What remained unknown was the experiences of professional nurses(PNs) working in PHC regarding this issue. The study aimed to explore and describe the lived experiences of PHC nurses in managing chronic diseases during the COVID-19 pandemic. The study was conducted in the North West province, South Africa. A qualitative descriptive phenomenological design was employed to collect and analyse data. Face-to-face interviews were conducted and audio recorded with 16 PNs from five high-volume PHC facilities selected purposively. The study's findings reveal four themes: suboptimal care for patients with chronic disease, a lack of resources, mental health challenges experienced by PHC nurses, and stigma and discrimination from both family and community members. The neglect of PHC and its frontline healthcare staff has impeded the mental health of PHC workers and the management of chronic diseases thus any progress made in reducing the burden of chronic diseases is likely to have regressed during the COVID-19 pandemic.Contribution:Policymakers should prioritise strengthening PHC by implementing integrated disease management policies, ensuring ethical clinical standards, providing supportive supervision, fair resource allocation and capacity building for PHC staff. In addition, addressing stigma and discrimination, and raising awareness among families and communities is crucial for future pandemics to effectively manage both chronic and infectious diseases.

Differences Between the Chinese and American Higher Education Systems and Implications

Despite receiving considerable global attention, the higher education systems of China and the United States exhibit disparities and complementarities that highlight ongoing deficiencies in educational reform and development. This paper holds a comparative analysis of the strengths, weaknesses, and developmental trends within the higher education frameworks of both nations. It reveals that China's system is defined by its uniform policies and stringent teaching methodologies, characterized by fixed curricula and rigorous mechanisms for teacher training and student selection. In contrast, the US system is celebrated for its diversity, flexible policies, innovative teaching approaches, and diverse curricula. It places a strong emphasis on teacher autonomy and the individualization of student assessments. Based on these findings, this study offers a series of recommendations designed to advance the development of higher education in both countries. These include optimizing the admissions and examination systems, reforming educational philosophies, broadening international perspectives, and enhancing the allocation and fairness of educational resources.

Binary Particle Swarm Optimization for Fair User Association in Network Slicing-Enabled Heterogeneous O-RANs

The Open-Radio Access Network (O-RAN) alliance is leading the evolution of telecommunications towards a greater intelligence, openness, virtualization, and interoperability within mobile networks. The O-RAN standard incorporates of many components the Open-Central Unit (O-CU) and Open-Distributed Unit (O-DU), network slicing and heterogeneous base stations (BS). Together, these innovations have given rise to a three-tiered user association (UA) relationship in a type of network called heterogeneous network (HetNet) with network slicing-enabled. There is an absence of efficient UA schemes for achieving fair resource allocation in such network scenario. Hence, this study formulates the fairness-aware UA problem as a utility-based combinatorial optimization problem, which is computationally hard to solve. Hence, an efficient Binary Particle Swarm Optimization (BPSO)-based UA scheme is proposed to solve the problem. Through simulations of an O-RAN based HetNet with network slicing-enabled, performance of the proposed BPSO-UA scheme is compared against two other baseline UA schemes. Results demonstrate the effectiveness of the proposed BPSO-UA scheme in achieving high fairness through equitable network slicing resource allocation, thereby leading to higher user connectivity rate and comparable average spectral efficiency. This innovative approach sheds light on the potential of metaheuristic algorithms in tackling intricate UA challenges, offering valuable insights for the future design and optimization of mobile networks.

Ethical and legal aspects in anesthesiology, ethical and legal issues, an overview

Introduction: The practice of anesthesiology plays a crucial role in medicine, ensuring the comfort and safety of patients during medical and surgical procedures. However, this specialty faces a series of ethical and legal challenges. This article provides an overview of these issues, considering the importance of respecting patient autonomy and compliance with legal standards. Methods: To conduct this review, the following descriptors were used to search the PubMed and MEDLINE databases: "Anesthesiology", "Ethical", "Questions", "Aspects", "Legal". These descriptors were combined using the boolean operator AND to ensure search accuracy. Initially, 165 relevant studies were identified. After excluding duplicates, editorials, and incomplete articles, 122 articles were considered for analysis. The final selection included the full reading of 24 articles, of which 13 were considered relevant to compose this review. Results: Anesthesiologists face complex ethical dilemmas, from obtaining informed consent to making decisions in emergency situations. Additionally, there are concerns about fair resource allocation and balancing risks and benefits. In the legal realm, there are comprehensive regulations related to professional liability, documentation of procedures, and the use of medications and equipment. Conclusion: The practice of anesthesiology requires a solid understanding of the ethical and legal aspects involved. It is essential to respect patient autonomy by obtaining their informed consent. Constant ethical reflection and compliance with legal regulations are fundamental to ensuring the delivery of high-quality care.

The Role of Stakeholders In Achieving Surabaya Zero Child Marriage By 2024 to Realize Gender Equality

This study aims to analyze and describe the Role of Stakeholders in Realizing Surabaya Zero Child Marriage in 2024 to Achieve Gender Equality. This research uses a descriptive qualitative research design. A collaborative network involving the city government, private sector, NGOs, communities, and religious organizations such as Muslimat NU in the city of Surabaya has shown significant results in suppressing the rate of child marriage. Through effective coordination, fair resource distribution, transparent communication, and continuous program innovation, this network has made substantial progress towards the zero child marriage goal. However, there are still areas that require further attention, especially in terms of improving access to resources and strengthening coordination. By continuing to strengthen collaboration and applying lessons from experiences, Surabaya can achieve the goal of completely abolishing child marriage.

Equity and efficiency of health resource allocation in the Chengdu-Chongqing Economic Circle of China.

This study aimed to evaluate the fairness and efficiency of health resource allocation (HRAE) in Chengdu-Chongqing Economic Circle after the new healthcare reform. This study also aimed to identify existing problems, providing empirical evidence for the government to formulate regional health plans scientifically and reasonably. The fairness of health resource allocation was analyzed using the Gini coefficient, Theil index, and agglomeration degree from population and geographical area perspectives. The three-stage data envelopment analysis and the Malmquist productivity index were used to analyze HRAE from static and dynamic perspectives. The Gini coefficient for population allocation in Chengdu-Chongqing Economic Circle was 0.066-0.283, and the Gini coefficient for geographical area allocation was 0.297-0.469. The contribution rate within a region was greater than that between regions, and health resources were mainly concentrated in economically developed core areas. The overall fairness of Chengdu Economic Circle was relatively better than that of Chongqing Economic Circle. Moreover, the adjusted mean technical efficiency was 0.806, indicating room for HRAE improvement in Chengdu-Chongqing Economic Circle. Stochastic Frontier Analysis found that different environmental variables have varying degrees of impact on HRAE. The adjusted mean total factor productivity change (Tfpch) was 1.027, indicating an overall upward trend in HRAE since the new healthcare reform. However, scale efficiency change (Sech) (0.997) limited the improvement of Tfpch. The fairness of health resources allocated by population was better than that allocated by geographical area. The unfairness of health resources mainly stemmed from intra-regional differences, with considerable health resources concentrated in core areas. Over the past 13 years, HRAE has improved but exhibited spatial heterogeneity and Sech-hindered productivity improvement. The study recommends strengthening regional cooperation and sharing to promote the integrated and high-quality development of the health and well-being in Chengdu-Chongqing Economic Circle.

Regenerative Agriculture: Integrating Soil Health, Carbon Management and Socio-ecological Outcomes

Regenerative agriculture is a revolutionary farming method that aims to address the many issues raised by current agricultural practices by balancing soil health, carbon management, and socio-ecological results. This all-encompassing framework incorporates ideas to improve and restore soil ecosystem health, store carbon in the atmosphere, and build resilient rural communities. Regenerative agriculture prioritizes soil health by emphasizing techniques like cover crops, decreased tillage, and diverse cropping systems, which together strengthen soil structure, increase microbial activity, and accelerate nutrient cycling. Through their substantial contribution to carbon sequestration, these techniques help to stabilize the climate by reducing greenhouse gas emissions. Simultaneously, regenerative agriculture supports structures that foster socio-ecological resilience, such as fair resource distribution, farmer welfare, and community involvement. This strategy strives to improve ecological integrity and reconstruct rural livelihoods in addition to raising farm productivity and profitability. The combination of these components highlights a comprehensive vision in which agricultural methods are in line with social and ecological goals, offering a sustainable route forward for food systems in the future. In addition to providing insights into regenerative agriculture's potential to address global sustainability issues, this abstract highlights the fundamental concepts, advantages, and potential drawbacks of the practice. It also advances ecological and community health. Findings demonstrate convergence with respect to goals that improve the environment and emphasize the significance of socioeconomic factors that support food security.

TRUST-ME: Trust-Based Resource Allocation and Server Selection in Multi-Access Edge Computing

Multi-access edge computing (MEC) has attracted the interest of the research and industrial community to support Internet of things (IoT) applications by enabling efficient data processing and minimizing latency. This paper presents significant contributions toward optimizing the resource allocation and enhancing the decision-making process in edge computing environments. Specifically, the TRUST-ME model is introduced, which consists of multiple edge servers and IoT devices, i.e., users, with varied computing tasks offloaded to the MEC servers. A utility function was designed to quantify the benefits in terms of latency and cost for the IoT device while utilizing the MEC servers’ computing capacities. The core innovation of our work is a novel trust model that was designed to evaluate the IoT devices’ confidence in MEC servers. This model integrates both direct and indirect trust and reflects the trustworthiness of the servers based on the direct interactions and social feedback from other devices using the same servers. This dual trust approach helps with accurately gauging the reliability of MEC services and ensuring more informed decision making. A reinforcement learning framework based on the optimistic Q-learning with an upper confidence bounds action selection algorithm enables the IoT devices to autonomously select a MEC server to process their computing tasks. Also, a multilateral bargaining model is proposed for fair resource allocation of the MEC servers’ computing resources to the users while accounting for their computing demands. Numerical simulations demonstrated the operational effectiveness, convergence, and scalability of the TRUST-ME model, which was validated through real-world scenarios and comprehensive comparative evaluations against existing approaches.

The circular balancing problem

We propose a balancing problem with a minmax objective in a circular setting. This balancing problem involves the arrangement of an even number of items with different weights on a circle while minimizing the maximum total weight of items arranged on any half circle. Due to its generic structure, it may have applications in fair resource allocation schemes. We show the NP-hardness of the problem and develop polynomial-time algorithms when the number of distinct weights is a fixed constant. We propose for the general case a tight 7/6-approximation algorithm and show that it performs better than two existing algorithms designed for an equivalent problem in the literature. The worst-case performance ratio is derived through a linear combination of valid inequalities that are obtained from the problem definition, the properties of the proposed algorithm, and the optimal circular permutation structure. Furthermore, we formulate a more general problem of minimizing the maximum total weight of items on equally divided circular sectors and present its computational complexity and a tight approximation algorithm.

Foundations and Applications in Political Theory: An Analytical Study

This study explores the practical applications of political theory, focusing on how fundamental principles are translated into real political actions within governance and decision-making contexts. The first section addresses the identification of core principles such as democracy, justice, equality, sovereignty, legitimacy, and rights, which serve as a theoretical framework for political systems and policy formulation. Each principle is examined in depth, highlighting its significance in shaping governance and social order. For instance, democracy emphasizes citizen participation and accountability, while justice relates to fairness and equitable distribution of resources. Various political scenarios where these principles are applied are discussed, including legislative debates, policy-making processes, electoral campaigns, diplomatic negotiations, and judicial rulings. Each scenario illustrates the practical implications of political theories, demonstrating how lawmakers, policymakers, and diplomats engage with these concepts to address societal issues, Furthermore, the study emphasizes the necessity of considering stakeholders' perspectives, including government officials, political parties, civil society organizations, interest groups, and citizens, in evaluating the effectiveness of political actions. Through a critical analysis of these applications, the study assesses the outcomes of political decisions and governance practices, focusing on their alignment with democratic values and the protection of individual rights. It also addresses challenges such as institutional barriers, conflicting interests, and resource constraints that hinder the realization of political ideals. Ultimately, the study offers recommendations to enhance the significance of political theory in contemporary political discourse, advocating for collaborative efforts between theorists and practitioners to ensure that theoretical ideas inform practical policymaking. This study underscores the vital role of political theory in understanding and addressing current political challenges, contributing to enlightened governance and social progress.

The powerful influence of connections: exploring the effects of wasta informal networks on human resource development in Kuwait

ABSTRACT This research examines the consequences of engaging with wasta while practicing fair and ethical human resource management (HRM) in organizations in Kuwait. Weak ties have been established to be a powerful positive force for job seekers in the Western world, but in the Middle Eastern context, powerful close connections known as wasta exert a crucial impact on the pursuit of employment. We explore the relationship between wasta, HRM, and human resource development (HRD) in Kuwait using social exchange theory. Based on 24 semi-structured interviews, the study determines that the outcomes identified with wasta in businesses are considerable. Due to its disruption of standard HRM practices, wasta not only influences access to employment but also impacts employees’ professional development and their entire performance throughout their time with an organization. By unpacking this powerful but previously seldom explored phenomenon, this study expands conceptual frameworks on social influence and personal connections in the workplace, particularly regarding wasta. Additionally, it provides recommendations for lessening the undesirable outcomes of wasta and improving employee and organizational evolution in the fair practice of HRM.

Dynamic RIS partitioning in NOMA systems using deep reinforcement learning

The rapid evolution of wireless communication technologies necessitates innovative solutions to meet the increasing performance requirements of future networks, particularly in terms of spectral efficiency, energy efficiency, and computational efficiency. Reconfigurable Intelligent Surfaces (RIS) and Non-Orthogonal Multiple Access (NOMA) are emerging as promising technologies to enhance wireless communication systems. This paper explores the dynamic partitioning of RIS elements in NOMA systems using Deep Reinforcement Learning (DRL) to optimize resource allocation and overall system performance. We propose a novel DRL-based framework that dynamically adjusts the partitioning of RIS elements to maximize the achievable sum rate and ensure fair resource distribution among users. Our architecture leverages the flexibility of RIS to create an intelligent radio environment, while NOMA enhances spectral efficiency. The DRL model is trained online, adapting to real-time changes in the communication environment. Empirical results demonstrate that our approach closely approximates the performance of the optimal iterative algorithm (exhaustive search) while reducing computational time by up to 90 percent. Furthermore, our method eliminates the need for an offline training phase, providing a significant advantage in dynamic environments by removing the requirement for retraining with every environmental change. These findings highlight the potential of DRL-based dynamic partitioning as a viable solution for optimizing RIS-aided NOMA systems in future wireless networks.

Fair resource optimization for cooperative non-terrestrial vehicular networks

Non-terrestrial networks aim to extend wireless communications capabilities beyond traditional terrestrial infrastructure by utilizing various platforms such as satellites, high-altitude platform stations (HAPS), and unmanned aerial vehicles to provide global or localized coverage. However, improving data rates in non-terrestrial cooperative communications (NTCC) networks presents unique challenges, necessitating innovative solutions. This paper presents a novel approach to enhance the request–response ratio (RRR) of NTCC in time asynchrony. By leveraging the advantages of HAPS, such as wide coverage, high altitude, and flexible deployment, we aim to optimize the performance of NTCC networks. We formulate an optimization problem considering the simultaneous connection between the HAPS and ground users, power distribution, and decoding order. The joint optimization problem is formulated as non-convex-non-linear and is also NP-hard, making it very challenging to obtain a globally optimal solution. To reduce the complexity of the problem and make it more tractable, we decouple it into subproblems and achieve an efficient solution in two steps. In the first step, we use the Gale–Shapley algorithm to solve the many-to-many two-sided matching problem of HAPS user terminal association, given the fixed decoding and power allocation. Then, we solve the decoding order and power allocation problem using the Dinkeback-like algorithm, given the optimal association in the second step. Our proposed method iteratively updates the preference lists, mitigating interference among HAPS and enhancing overall system performance. Through extensive simulations, we demonstrate that implementing our proposed schemes achieves high RRR compared to benchmark schemes. Additionally, when temporal asynchrony is employed alongside our approach, there is an increase in the overall performance obtained from the process.

PERAN MASYARAKAT TERHADAP AKTIVITAS PENAMBANGAN MARMER DI KEC. BONTOCANI KAB. BONE PASCA PENGESAHAN UU NO. 3 TAHUN 2020 TENTANG MINERAL DAN BATUBARA

Natural Resources (SDA) managed by the State or individuals/corporations can certainly have consequences for 3 (three) aspects, namely, productivity, sustainability and fairness of the natural resources managed. Threats to these three aspects will hit the Bontocani area which is a mining area by PT. The Bukit Marmer Empire was not carried out properly or without supervision from other parties such as local people who live in the district. Bone in general, and Kec. Bontocani in particular. Community participation is very much needed in overseeing current natural resource management so that its sustainability is maintained and prevents more severe environmental damage. For this reason, researchers are interested in conducting research with the aim of knowing the role of the community in responding to mining activities in the district. Bontocani, and examine the legal protection for communities responding to marble mining businesses in the district. Bontocani, Kab. Bone after the ratification of Law no. 3 of 2020 using empirical research methods and normative research. The results of the research show that the community consisting of the anti-mining alliance in Kec. Bontocani believes that mining activities will have many negative impacts on the lives of the residents of the district. Bone in general and the people of Kec. Bontocani in particular. More deeply, the community's participatory efforts above can cause problems and risky consequences for the community itself. This is because there is no aspect of legal protection that can be provided by the revised Minerba Law which was only passed in 2020.