Advanced Journal of Management, Humanity and Social Science

Abstract Attacks on critical infrastructure, whether kinetic or cyber, constitute one of the most pressing challenges in contemporary international law. The 2026 joint military strikes by the United States and Israel against Iran's nuclear facilities, energy infrastructure, bridges, and transportation networks, combined with concurrent cyber operations targeting communication systems, have reignited debate over the legal framework governing such attacks. This article examines the legal dimensions of the prohibition on infrastructure attacks under international law, analyzing the US-Israel strikes as a case study and exploring available legal avenues for Iran to seek recourse before international judicial bodies. Using a descriptive-analytical methodology grounded in treaty interpretation, customary international law analysis, and judicial precedent, this research finds that while international humanitarian law (IHL) provides a robust framework through the principles of distinction, proportionality, and precaution, the concept of "dual-use" objects—objects with both civilian and military applications—creates significant interpretive ambiguity . Despite this ambiguity, Article 56 of Additional Protocol I explicitly protects nuclear power plants from attack where such attacks may cause dangerous force release, and the International Criminal Court (ICC) has established precedent by issuing arrest warrants for attacks on Ukrainian critical infrastructure. The research identifies four principal legal avenues: proceedings before the International Court of Justice (ICJ), prosecution before the ICC, arbitration through bilateral dispute resolution mechanisms, and domestic litigation. However, significant obstacles persist, including the United States' withdrawal from the 1955 Treaty of Amity with Iran, non-membership in the Rome Statute, attribution challenges for cyber operations, and evidentiary difficulties. The article concludes that while international law prohibits attacks on critical infrastructure, enforcement mechanisms remain inadequate, and the most effective long-term strategy involves strengthening multilateral cooperation and developing a dedicated convention on critical infrastructure protection.

Abstract Sports injuries remain a major concern in both professional and recreational athletics, leading to significant physical, psychological, and economic consequences. Recent advances in biomechanics have provided a powerful framework for analyzing movement patterns, loading mechanisms, and tissue responses associated with sports-related injuries. This paper explores how biomechanical data analysis contributes to the understanding and prevention of sports injuries. Using motion capture systems, force plates, electromyography, and wearable sensors, researchers can quantify kinematic and kinetic variables that reveal underlying risk factors such as improper joint alignment, asymmetrical loading, or excessive repetitive forces. By integrating these biomechanical indicators with machine learning algorithms, predictive models can be developed to identify athletes at higher risk before injury occurs. The paper further reviews intervention strategies, including neuromuscular training, equipment design modifications, and individualized biomechanical feedback systems. Case studies from sports such as soccer, running, and basketball demonstrate how biomechanical insights have successfully reduced injury rates through targeted prevention programs. Ultimately, the synthesis of biomechanical data with modern computational tools represents a paradigm shift from reactive to proactive injury management. This approach not only enhances athletic performance but also promotes long-term musculoskeletal health. The findings underscore the need for interdisciplinary collaboration between biomechanists, sports scientists, medical professionals, and data analysts to create comprehensive injury-prevention ecosystems supported by empirical evidence.

Abstract The rise of algorithmic governance and data-driven decision-making represents a transformative shift in contemporary state administration, profoundly impacting democratic accountability. As governments increasingly integrate artificial intelligence (AI), machine learning, and big data analytics into policy formulation, public service delivery, and regulatory mechanisms, both opportunities and challenges emerge for traditional democratic practices. This study examines how algorithmic systems influence the three dimensions of democratic legitimacy: input, throughput, and output. Drawing on a comprehensive literature review and multi-dimensional analysis, five analytical frameworks are developed to explore the effects of algorithmic governance on citizen participation, procedural fairness, transparency, efficiency, and policy outcomes.

Findings indicate that algorithmic decision-making enhances operational efficiency, predictive capacity, and evidence-based policy interventions, enabling governments to respond more rapidly and effectively to complex societal challenges. Simultaneously, the reliance on automated systems introduces risks of bias, discrimination, opacity, and accountability gaps, which can undermine public trust and erode procedural and output legitimacy. Human-in-the-loop oversight, explainable AI (XAI), participatory design, algorithmic auditing, and multi-level governance emerge as critical strategies to reconcile technological efficiency with democratic norms.

The study highlights the dual character of algorithmic governance: while it offers substantial opportunities for efficiency and policy optimization, it necessitates deliberate institutional, ethical, and participatory safeguards to preserve democratic accountability. By integrating human judgment, transparency measures, ethical constraints, and citizen engagement into algorithmic systems, states can enhance legitimacy across all dimensions of governance. The research contributes to the growing discourse on digital-era public administration by providing a structured framework to assess both the transformative potential and normative implications of AI-driven governance, offering practical insights for policymakers seeking to balance innovation with democratic accountability in contemporary states.

Abstract Perfectionism has become a salient construct in understanding students’ psychological functioning within academic settings. Defined as the pursuit of excessively high standards accompanied by critical self-evaluation, perfectionism manifests in both adaptive and maladaptive forms. This paper explores the psychological correlates of perfectionism among students, highlighting its influence on mental health, motivation, coping strategies, and social relationships. Research indicates that while adaptive perfectionism may foster organization, persistence, and academic success, maladaptive perfectionism is closely linked to heightened anxiety, depression, low self-esteem, and academic burnout. Perfectionistic students often struggle with cognitive distortions, such as all-or-nothing thinking, and rely on maladaptive coping strategies like avoidance and rumination, which exacerbate stress. Additionally, perfectionism affects interpersonal dynamics, where fear of failure and excessive competitiveness can hinder collaborative learning and peer support. Cultural and parental expectations also reinforce perfectionistic tendencies, intensifying psychological vulnerability in highly competitive educational environments. Mechanisms such as achievement motivation, self-worth contingencies, and distorted cognitive appraisals help explain the varying outcomes of perfectionism. Interventions including cognitive-behavioral therapy, mindfulness, self-compassion training, and growth-mindset educational practices are proposed as effective strategies to mitigate the negative impacts of maladaptive perfectionism while preserving the motivational benefits of adaptive forms. Understanding the psychological correlates of perfectionism is critical for educators, counselors, and policymakers aiming to promote academic excellence without compromising students’ well-being. Ultimately, fostering balanced forms of perfectionism may enable students to strive for high achievement while maintaining resilience, self-acceptance, and positive mental health in their educational journey.

Abstract Financial transparency and auditing are critical mechanisms for improving the efficiency and integrity of municipal financial management. In recent decades, the role of local governments in providing public services has expanded, making effective oversight and accountability increasingly essential. This study explores how financial transparency and systematic auditing practices influence municipal performance, focusing on their capacity to reduce corruption and enhance operational efficiency. By conducting an analytical review of literature from various international contexts, this research highlights patterns and correlations between transparent financial reporting, rigorous auditing processes, and improved municipal outcomes. The findings indicate that municipalities that adopt comprehensive transparency policies, such as public disclosure of budgets, expenditures, and procurement processes, are more likely to demonstrate accountable governance and reduced incidences of financial mismanagement. Similarly, the implementation of independent and consistent auditing practices reinforces internal controls, deters fraudulent activities, and fosters public trust. The study also examines challenges, including political interference, resource constraints, and varying legal frameworks, which may hinder the effectiveness of transparency and auditing measures. By integrating empirical evidence and theoretical perspectives, this research underscores that the synergy of transparency and auditing not only enhances operational efficiency but also acts as a critical deterrent against corruption in municipal finance. The paper concludes with policy recommendations for municipal authorities to strengthen financial oversight mechanisms, improve reporting standards, and institutionalize audit practices, ultimately contributing to sustainable urban governance. These insights provide valuable guidance for policymakers, municipal administrators, and researchers interested in promoting accountable and efficient local government financial management.

Abstract The rapid evolution of artificial intelligence (AI) has transformed strategic decision-making processes in organizations, enabling faster insights, predictive analytics, and automation. However, the integration of AI systems also raises critical challenges concerning data governance, ethics, and regulatory compliance. Effective data governance ensures that data used in AI-driven decisions is accurate, secure, transparent, and aligned with corporate objectives. Ethical frameworks are essential to mitigate biases, prevent discrimination, and maintain trust among stakeholders. Moreover, the establishment of AI guidelines, including accountability, explainability, and fairness, plays a pivotal role in guiding organizations toward responsible innovation. This paper explores how robust data governance structures and ethical AI guidelines can enhance strategic decision-making and corporate integrity. It analyzes current models of governance frameworks, including ISO/IEC 38505 and OECD AI Principles, and their implications for business strategy. The discussion emphasizes that organizations adopting transparent and ethical data practices not only comply with regulations but also gain a competitive advantage through enhanced reputation and stakeholder confidence. Ultimately, the study concludes that integrating governance and ethics into AI decision systems is no longer optional—it is a strategic necessity for sustainable, fair, and accountable business practices in the era of intelligent automation.

Abstract Family law serves as a fundamental legal framework regulating relationships within families, including marriage, divorce, child custody, inheritance, and domestic obligations. This comparative study examines the divergent and convergent features of family law systems in Eastern and Western jurisdictions, highlighting the influence of cultural, religious, and social factors. Western legal systems, including common law and civil law traditions, emphasize individual autonomy, gender equality, and codified procedural safeguards. In contrast, Eastern systems, particularly those influenced by Islamic law and traditional Asian customs, prioritize family cohesion, social harmony, and religious or cultural norms. The study analyzes marriage and divorce regulations, child custody and protection mechanisms, inheritance rules, and contemporary reforms in both regions. It also addresses emerging trends such as recognition of same-sex marriages, assisted reproductive technologies, and cross-border legal issues. Comparative findings reveal key differences in the balance between individual rights and collective responsibilities, the role of religion in legal formulation, gender equality, and procedural approaches. Despite these differences, globalization and international human rights standards have prompted reforms in both regions, fostering convergence in areas such as child welfare, protection of vulnerable family members, and legal modernization. The study concludes that understanding the underlying social, religious, and cultural values of family law systems is essential for policymakers, legal scholars, and practitioners to promote effective, equitable, and culturally sensitive legal frameworks. Comparative analysis not only enhances cross-cultural legal understanding but also provides opportunities for harmonization, mutual learning, and informed reform in globalized contexts.

Abstract Urban infrastructure projects are essential for enhancing the quality of life, supporting economic growth, and ensuring sustainable development in cities. However, the planning and execution of these projects involve substantial financial commitments, which necessitate rigorous evaluation to ensure efficient resource allocation. This study explores the cost-benefit analysis (CBA) of urban infrastructure projects from the perspective of municipal financial management. The research emphasizes the role of CBA in identifying the economic, social, and environmental impacts of urban projects, providing a systematic framework for decision-making and prioritization. Using a combination of qualitative and quantitative methodologies, this study examines multiple case studies of urban infrastructure projects, including transportation networks, water supply systems, and public facilities. The analysis incorporates direct and indirect costs, projected revenues, long-term social benefits, and environmental considerations, while also addressing risk factors and uncertainties inherent in project execution. The findings indicate that projects with high initial costs can yield significant long-term social and economic returns if carefully managed and evaluated. Additionally, the research highlights the critical role of financial management practices within municipalities, including budgeting, fiscal monitoring, and risk mitigation, in optimizing project outcomes. Policymakers and municipal managers can leverage these insights to make informed decisions that balance short-term financial constraints with long-term urban development goals. Ultimately, the study demonstrates that rigorous cost-benefit analysis, coupled with sound municipal financial management, serves as a key instrument in promoting sustainable, economically viable, and socially beneficial urban infrastructure projects. The paper concludes with practical recommendations for improving CBA methodologies, integrating environmental and social metrics, and enhancing municipal financial governance to ensure successful implementation and maximization of public value.