The objective of this study was to assess the current usage, challenges, and specific needs regarding biomechanical data, with a focus on gait analysis, across a diverse field such as sports performance, clinical rehabilitation, and occupational health. We conducted a survey among more than 300 institutions in the DACH region (Germany, Austria, Switzerland). Of 49 individuals who began the survey, 24 submitted complete responses. Findings indicate that participants recognize the value of biomechanical data, yet adoption of publicly available datasets is hindered by inconsistent formats, limited metadata, and strict privacy regulations. Respondents emphasized standardized documentation and clearer guidelines to facilitate sharing and collaboration. Many institutions are overwhelmed by legal compliance, with data proception laws posing significant hurdles to effective usage. The results highlight the need to (1) establish standardized file formats, (2) improve metadata quality, (3) develop transparent, consistent data-sharing protocols, and (4) clarify legal frameworks for compliance.

Clinical forensic medical assessment insights from fitness for police interview consultations.

IMPACT This article offers practical lessons for international practitioners implementing Freedom of Information (FOI) regimes not only within defence and security, but also in large and decentralized organizations. By shifting the analytical focus from disclosure outcomes to the organizational processes that shape reactive disclosure, the study highlights how internal structures, workflows, and decision-making routines influence transparency in secrecy-sensitive institutions. The findings are particularly relevant for senior and mid-level public managers, FOI officers, legal advisers, and policy designers working in ministries of defence, armed forces, and security agencies, as well as for oversight bodies and supreme audit institutions. Beyond the Brazilian case, the article provides a process-oriented analytical lens that can be applied comparatively to other democratic contexts facing similar tensions between transparency and information control. It supports practitioners in diagnosing bottlenecks, anticipating disclosure risks, and designing FOI arrangements that balance legal compliance, organizational capacity, and legitimate secrecy requirements.

ABSTRACT Rapid digital transformation in the UAE has led to the rising reliance on third-party service providers, such as cloud platforms, IT contractors, and software vendors, by organizations. This dependency has expanded the cyber threat surface and has become an essential piece of the legal compliance and organizational resiliency puzzle in the world of cyber risk management. The study investigates third-party cyber risk management within the framework of the UAE Personal Data Protection Law (PDPL) and the Cybercrime Law, particularly the third-party data controllers and processors’ obligations. The study pertains to a qualitative literature review of the latest research and international standards, NIST SP 800–161 and ISO/IEC 27036 to provide a list of best practices for governance, risk assessment, contractual controls, monitoring, audit, incident response, and business continuity. The results show that a strong link exists between integrated IT governance, cybersecurity investment and operational resilience in minimizing risks of third-party data breaches. The research extends a framework for UAE organizations to meet the requirements of PDPL, protect personal data, and foster trust within the digital supply chain.

Relative to other global conflicts, the ongoing war in Sudan has exemplified a paradigmatic forgotten war, despite its varying ramifications for victims and the wider civilian population. In many ways, exploitation and its utilitarian value in hostility have often been rationalised by warring parties to justify their war aims. Although Sudan was plunged into its latest cycle of hostility in April 2023, the extent to which the conflict has induced vulnerability to exploitation, especially trafficking and slavery, remains largely uninterrogated in the academic literature. The scope of legal obligations and compliance by parties equally remain unclear. This paper therefore proceeds with two main objectives: firstly, it seeks to understand the relationship between war and exploitation in Sudanese conflicts (past and present), and, secondly, it investigates the implementation of applicable international law relating to trafficking and slavery, including compliance by parties. Given the collapse of many governance structures and widespread exploitation risks, the article further examines the roles of mutual aid networks at the community level and the impact of their work in mitigating exploitation.

ABSTRACT We develop and test an application-specific language model for supporting ethical decision-making in social work. The model is built using Gemini 2.5 pro with seven agents, six of which are responsible for information aggregation of possible actions, relevant ethical issues, principles, standards, laws and values while the seventh is responsible for summarising the information and recommending and justifying issue-related decisions. We further test the model via 70 simulated cases. In evaluating the appropriateness of social workers’ case-specific actions, the model’s judgements showed 80% alignment with the answers from the casebook. It also provided sufficient reasons or appropriate remedial plans in nearly half of the cases. Errors were due chiefly to inaccuracies in understanding legal compliance requirements, inadequate consideration of case-specific situations, and logical fallacies. Conversely, in some cases the model provided responses that were more appropriate than those from the casebook. Accordingly, we see considerable scope to apply artificial intelligence in supporting social work ethical decision-making.

ABSTRACT Reliable wood traceability is essential for sustainable forest management, legal compliance, and transparency in wood-value chains. Ink-based labelling using drop-on-demand inkjet printing enables direct application of two-dimensional matrix codes onto wood surfaces. However, the readability and robustness of codes depend on the printing quality, which is affected by the interaction between ink and wood surface. In this study, dots were printed on five hardwood species using ethanol-based ink at two different moisture levels on cross-sections cut by chainsaw and circular saw. A total of 960 dots were analysed using a 3D microscope and image analysis. Diffuse-porous species (alder, cherry and maple) exhibited smallest dot areas (about 3.1 mm²), lowest elongation (Feret ratio about 1.18) and highest circularity (about 0.45) compared to ring- and semi-ring-porous species (oak and walnut). Dot orientation tended to follow the radial anatomical direction, confirming that ink redistribution was governed by wood rays. Micro-scale surface roughness showed a moderate negative correlation with dot area (r = −0.36), whereas waviness exhibited no influence on dot morphology. Wood moisture content significantly amplified elongation of dots but had only a limited effect on spreading magnitude. The findings are relevant for identifying optimum printing parameter for respective wood species.

Reducing carbon emissions remains a major challenge for Lithuania under the European Green Deal, particularly due to the dominance of energy-related emissions and evolving economic dynamics. This study investigates the key drivers of CO₂ emissions, focusing on energy intensity, research and development (R&D), waste management, international legal compliance, economic growth, and trade openness over the period 1996Q1-2024Q4. To capture nonlinear, time-varying, and frequency-dependent relationships, the study employs advanced wavelet-based techniques, including Wavelet Power Spectrum, Wavelet Coherence, and Partial Wavelet Coherence. The findings reveal that energy intensity is the most dominant and persistent driver of emissions, exhibiting strong long-run effects, while economic growth also contributes positively, confirming the presence of scale effects. In contrast, R&D and institutional quality show conditional and time-dependent emission-reducing impacts, whereas waste management plays a relatively weak and indirect role. Based on these results, the study recommends prioritizing energy efficiency improvements, strengthening green innovation policies, enhancing institutional effectiveness, and accelerating the transition toward renewable energy systems to achieve sustainable emission reductions.

As dietitians actively engage in sectors beyond healthcare, practitioners are expected to uphold ethical standards that reflect both individual conduct and the profession's social identity. The growing influence of digital technologies, sustainability challenges, and interdisciplinary collaboration further underscores the need to understand current standards of ethical practice. However, global dialog on dietetic ethics remains limited and fragmented. To analyze how professional ethics are governed and enforced, and how ethical content domains are structured and expressed in dietetic codes worldwide. A qualitative document analysis was conducted on national or regional codes of ethics and conduct from 25 dietetic associations spanning North America, Europe, Asia-Pacific, and Africa. Documents were obtained from public repositories or through direct association outreach. Codes written in English or Chinese were analyzed directly; others were translated using artificial intelligence (AI) and verified by issuing organizations. Using a reflexive content analysis approach, we examined revision history, government and enforcement, and ethical content domains. Enactment of ethical guidelines ranged from 1982 to 2024, and only five documents reported revision practices, with update cycles varying from scheduled to ad hoc. Regional variation was observed across three dimensions of ethical guidelines: intended audience scope, aspirational enforcement approaches, and references to legal compliance in relation to local laws or legislation. All documents referenced bioethical principles, but only eight incorporated environmental ethics; ethical guidance addressed professional interactions outside patient-practitioner relationships. Conflicts of interest in these contexts included non-financial domains (e.g., media engagement), with advertising and marketing explicitly discussed in several recently updated guidelines. Findings highlight key opportunities to strengthen ethical guidance in dietetics, particularly in relation to environmental ethics, collaborative practice contexts, and conflicts of interest in digital settings.

To examine how federal appellate courts evaluate constitutional claims concerning custodial dental care and to characterize the clinical and procedural features of these cases. Decisions of the U.S. courts of appeals issued between 1980 and 2025 were identified through structured database searches. Cases substantively evaluating dental care were coded for severe pain, infection, abscess (coded separately), functional impairment, delay, custody type, representation status, defendant level, and appellate outcome. Descriptive statistics summarized case characteristics, and logistic regression evaluated associations between selected variables and appellate outcomes. A total of 182 appellate decisions met inclusion criteria, of which 174 evaluated adequacy of care. Severe pain was described in 86% of coded cases and functional impairment in 62%. Infection was documented in 41% of cases, with an abscess specifically identified in 16%. Delay was alleged in 73% of cases. Overall, 35% of decisions resulted in reversal or remand. Among cases with documented delay duration, the median delay was substantially longer in plaintiff-favorable cases, and delays exceeding 90 days were associated with higher odds of reversal or remand. Appellate review emphasizes documented awareness and response rather than equivalence to community standards. This legal threshold does not ensure timely clinical resolution. Public health evaluation of custodial dental systems should consider disease progression and access to definitive treatment in addition to legal compliance. Improvements are likely to depend on system-level monitoring of access and timeliness of care rather than litigation alone, reflecting the distinction between legal sufficiency and clinical adequacy.

Evaluating driver proficiency remains a fundamental determinant of road safety, regulatory adherence, and public confidence in licensing systems. This paper presents the Smart Driving Test System (SDTS), a fully integrated, sensor-based, microcontroller-driven framework designed to automate and standardize the assessment of driving skills. A functional prototype demonstrates SDTS capability to replace subjective human judgment with objective, repeatable, and data-centric performance metrics. The work includes a comprehensive feasibility analysis encompassing technological maturity, economic viability, operational deployment, and legal compliance, further supported by a detailed cost estimation model and implementation strategy. A comparative assessment with established international smart driving evaluation platforms underscores SDTS's distinctive contributions in communication architecture, modular hardware configuration, graphical user interface functionalities, and scalable system design. The paper also outlines prospective enhancements, including the incorporation of machine learning for predictive performance analysis, adoption of low-power wireless communication protocols such as ZigBee and LoRa to simplify installation, utilization of cloud-based analytics for centralized monitoring, and employment of multimodal sensor fusion to improve environmental perception. By bridging the gap between conventional manual testing procedures and next-generation automated evaluation, SDTS significantly enhances the transparency, consistency, and reliability of driver certification processes. Furthermore, it lays the groundwork for the digital transformation of transportation licensing infrastructure and aligns with broader advancements toward intelligent transportation ecosystems, promoting safer roads, harmonized assessment standards, and strengthened public trust in driver qualification frameworks.

This study explored operating theatre nurses' experiences of receiving feedback on intraoperatively acquired positioning-related injuries and organisational factors influencing these processes. A descriptive cross-sectional web-based survey was completed by 57 Swedish operating theatre nurses using a study-specific questionnaire grounded in patient-safety frameworks. Most respondents had encountered positioning-related injuries, yet structured feedback was uncommon: over half received feedback only occasionally, and one-third never received any. When incidents were reported, feedback was often infrequent or absent. Although feedback was rated highly important for clinical practice, reporting, and positioning safety, responsibility for providing it was perceived as unclear. Barriers included limited interdepartmental collaboration, unclear routines, and time constraints, whereas facilitators included cross-unit collaboration, defined feedback responsibilities, and leadership support. Some nurses reported resorting to impermissible access to patient records to obtain outcome information. The findings indicate a need for systematic, leadership-supported feedback structures that strengthen organisational learning, ensure legal compliance, and enhance perioperative patient safety.

ABSTRACT This study aims to investigate the use of Artificial Intelligence Applications in Managing Arbitration Sessions with a particular emphasis on traits of IT governance, legal compliance, and regulatory issues in the United Arab Emirates. It explores the legal and institutional dimensions of the contribution of AI in adjudication processes and the preparedness of the UAE to move toward the development of smart arbitration processes based on automation and algorithmic decision-making support. The study also underscores the importance that Federal Arbitration Law No. (6) of 2018 and the UAE National Strategy for Artificial Intelligence 2031 have played and will continue to play in the context of promoting digital transformation in dispute resolution mechanisms. It also explores practical measures, like the Smart Arbitration File and the Digital Judge. The findings emphasize the importance of establishing and maintaining a balanced governance system on AI-assisted arbitration processes in the UAE legal system that confirms transparency, accountability, cybersecurity, data protection, and neutrality.

The Swedish Twin Registry (STR), established in the late 1950s, is one of the world's most comprehensive twin registries and a cornerstone for research on genetic and environmental determinants of health. STR includes data on Swedish-born twins since 1886, complemented by longitudinal questionnaires, clinical measures, and biobank samples. In 2019, STR became a national research infrastructure with a mission to provide broader data sharing, while in 2025, STR further transitioned into a legally defined role as a 'certain research database' under the new Swedish Act on Certain Research Databases. The new legislation provides a framework for collecting and storing personal data with broad consent for future research projects, without requiring ethical approval for the data collection per se. Instead, ethical review is conducted separately for each research project seeking to use STR data. This article aims to describe STR's current role, governance, and legal context, highlighting implications for data access and biobank integration. The registry currently holds data on more than 160,000 twins, with ongoing ascertainment at 9 months and 9 years with follow-ups at ages 15, 18, and 24. Annual linkages to national health registers enrich longitudinal analyses of disease outcomes. A variable search engine is openly available via STR's web portal while higher level metadata is provided through Swedish research data services. STR's evolution illustrates both opportunities and challenges in balancing open science practices, legal compliance, and participant integrity within large-scale research infrastructures.

ABSTRACT Explainability of AI systems is branded as a solution to the black box problem. The EU AI Act introduces AI explainability as a requirement for high-risk AI systems, including a right to explanation. However, understanding the wording of the requirements and the related provider and deployer obligations is complicated. This paper takes a legal-evolution research approach by analysing legal literature and the wording of the AI HLEG Guidelines, the OECD AI Principles, the AI Act, and the Council of Europe’s AI Convention, contributing to understanding the AI Act’s explainability requirements. First, this paper finds that explanations can take different forms while fulfilling various functions. It finds that, in the AI Act, the central functions of AI explanations are to understand the AI system’s inner workings and outputs, to enable contestation of decisions by affected persons, to facilitate usability by the deployer and to achieve legal compliance. Second, this research maps the explanations required under the AI Act onto the AI lifecycle phases. Resultantly, this research finds that the AI Act expects the provider and deployer to engage in continuous and iterative explainability by design, development and deployment throughout the AI lifecycle, following the evolution of their AI system.

Background The integration of artificial intelligence (AI) algorithms in military targeting systems represents one of the most significant technological shifts in modern warfare, fundamentally altering the speed, precision, and scale of military operations. In the context of the Iranian-Israeli conflict, both nations have emerged as early adopters of AI-enhanced military technologies, albeit through markedly different strategic approaches and technological implementations. Method This study employs a mixed-method analytical approach that combines technical system assessment, comparative case study analysis, and evaluation of the international legal framework. Data collection utilized cross-checking methodology across multiple source types, including investigative journalism, open-source intelligence (OSINT) platforms, military data, and peer-reviewed studies to address three core research questions regarding technical architecture differences, operational effectiveness metrics, and compliance with International Humanitarian Law. Results The analysis reveals substantial differences in both approach and capability. Israeli systems exhibit advanced data integration and surveillance architectures, emphasizing precision and human machine collaboration through platforms such as the Iron Dome, Lavender, and various targeting support technologies. In contrast, Iranian systems prioritize cost-effectiveness and asymmetric capabilities, focusing on autonomous drone operations and cyber warfare integration, albeit with limited independently verified performance metrics. Notable divergences exist in operational doctrine, human oversight mechanisms, and legal compliance frameworks. While field results reveal that the use of artificial intelligence technologies in warfare must be subject to international law to avoid significant civilian casualties. Conclusion While both countries have incorporated AI technologies into military operations, critical gaps in international governance underscore the urgent need for robust regulatory mechanisms to oversee autonomous weapon systems. These findings contribute to academic understanding of military AI implementation patterns and inform policy debates on the ethical and legal dimensions of algorithmic warfare

ABSTRACT Biodiversity surveys are essential in Environmental Impact Assessment (EIA), providing baseline information for impact prediction and decision-making. Brazilian legislation requires the identification of scientific, economic, rare, or endangered value, but does not specify methodologies. We evaluated the floristic survey conducted for the EIA of an iron ore mining project in the Serra de Ouro Preto, at the entrance of Ouro Preto, a UNESCO World Heritage Site. We conducted a pioneering counter-assessment based on a one-day field survey in Campos Rupestres vegetation, depositing vouchers in herbarium, and identifying specimens with taxonomic rigor; additional records were retrieved from virtual herbaria. We documented 93 species, 79 recorded in the field and 14 from herbaria. Of the field-recorded species, 56 (71%) were absent from the EIA report, including four endangered species and one microendemic species (new status at species rank). We also identified 23 medicinal species and seven ruderal species. Herbarium records revealed another microendemic species restricted to the affected area and absent from the EIA report. These findings indicate incomplete legal compliance and inadequate biodiversity characterization, highlighting the need for clearer regulations and stronger technical guidance. Despite the limitations of the case study approach, findings have clear implications to EIA theory and practice.

With the rapid development of generative artificial intelligence (AI) technologies and large AI models, these technologies are expected to play an important role in multiple aspects of medical workflows in ophthalmology. However, their rapid and widespread adoption has also introduced multiple challenges regarding application specifications, ethical constraints, and legal compliance. To ensure the safe, effective, and compliant application of generative AI large models in ophthalmology, the Intelligent Ophthalmology Subcommittee (China) of Technical Committee on Smart Medical Digitalization of IEEE Technology and Engineering Management Society convened domestic experts in the field. Drawing upon relevant Chinese laws and regulations governing medical practice, data security, and privacy protection, and incorporating the latest research advances, the expert panel held multiple online and offline seminars nationwide. Using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system, Good Practice Statements, and the Delphi method, the panel developed a consensus framework addressing the ethical, technical, and legal issues associated with the application of generative AI large models in ophthalmology. Designed to be continuously updated as technology advances, this framework aims to provide evidence-based support for clinical practice.

This paper examines digital privacy protection among Albanian children through an educational technology perspective, focusing on how rapid technology adoption increases young people’s exposure to online risks. The study is designed as a mixed-method secondary-data case study that combines descriptive quantitative evidence from national and institutional sources with qualitative analysis of legal, policy, and institutional documents.)The findings indicate that children in Albania are increasingly exposed to a range of digital risks, including privacy violations, harmful content, and unsafe online interactions, while levels of formal reporting remain limited. At the same time, the analysis shows that the Albanian policy framework related to children’s digital protection has progressed primarily in legal and strategic terms, with comparatively weaker and uneven implementation in practice. Evidence from educational settings suggests that digital education initiatives and school based digital literacy programs may play a positive and potentially protective role; however, the available data do not support definitive conclusions regarding their relative effectiveness compared to regulatory or technical interventions. Against this background, the article argues that children’s digital privacy in contexts such as Albania should not be addressed solely as a matter of cybersecurity or legal compliance, but rather as a multidimensional governance issue encompassing educational practice, institutional coordination, and rights based digital governance. The Albanian case illustrates a dual dynamic: on the one hand, measurable progress through the development of multi stakeholder policies and strategies, and on the other hand, a persistent gap between formal protection frameworks and their effective implementation in everyday institutional and educational contexts. Received: 20 December 2025 / Accepted: 05 April 2026 / Published: May 2026

This study examines the influence of legal compliance on the financial performance of Micro, Small, and Medium Enterprises (MSMEs) in Indonesia, with a particular focus on financial stability, profitability, and competitiveness. Employing a descriptive-analytical design with a conceptual approach, this research synthesizes legal and financial theories through an extensive review of secondary data, including academic literature, regulatory frameworks, and governance studies. Legal compliance is operationalized across four key dimensions: business licensing, taxation, employment, and consumer protection. The findings indicate that legal compliance plays a strategic role in enhancing financial stability by reducing regulatory risks, minimizing unexpected costs, and improving cash flow management. Furthermore, compliance contributes to profitability through cost efficiency and improved access to financing with more competitive capital costs. In terms of competitiveness, legally compliant MSMEs demonstrate stronger reputational capital, greater market access, and higher adaptability within digital and global markets. The study also highlights that compliance should not be perceived merely as a regulatory obligation but as a financial strategy that strengthens governance quality and long-term business sustainability. However, the effectiveness of compliance is contingent upon regulatory simplification and MSME capacity, including legal literacy and administrative readiness. This study contributes to the integration of business law and financial performance perspectives in the MSME context and offers policy-relevant insights for strengthening MSME resilience.