Introduction. The article is devoted to the systematization of the forms of studentsʼ involvement in the cultural and historical heritage, which is used in the educational activities of educational organizations and the cultural and educational activities of cultural institutions. Currently, there are no comprehensive scientific approaches and typologies that systematize the forms of working with the cultural and historical heritage in educational activities, despite the rich experience of educational organizations and cultural institutions, as well as the existing approaches and developments, which makes it difficult to create a high-quality methodological base for teachers and educators. Purpose of the study – to develop a typology of forms of studentsʼ involvement in the cultural and historical heritage used by educational organizations and cultural institutions to improve the effectiveness of educational and cultural activities aimed at forming civic identity. Methodology. Research methods: analysis of regulatory and legal documents, study of the experience of educational organizations and cultural institutions, typology of forms of work with cultural and historical heritage. Results. A typology of forms of studentsʼ involvement in cultural and historical heritage has been developed, which includes five types of forms: educational and upbringing, cultural and leisure, information and communication, artistic and aesthetic, and research and scientific-practical. The article demonstrates the variety of forms of working with cultural and historical heritage and their practical significance for teachers and parents, which will increase the latter's involvement in introducing the younger generation to cultural and historical heritage. Conclusions. The proposed typology will allow for the unification of approaches to the use of cultural and historical heritage in educational and cultural activities, and the creation of unified standards and recommendations for educational organizations and cultural institutions. An important advantage is that the typology can be used by both teachers to choose the most suitable form of work and by parents to plan joint leisure activities with their children.

This study explores the concept of mitigating circumstances in Jordanian legislation, with a particular focus on cybercrime. Mitigation is presented as a key mechanism for achieving individualized justice and ensuring proportionality between crime and punishment. It does not eliminate criminal responsibility but influences the severity or type of penalty imposed. The research finds that while the Jordanian legislator acknowledged mitigation in cybercrime, its application was narrowly confined to Article 29 of the Cybercrime Law, drafted in a limited and ambiguous manner. This undermined the legislative aim of encouraging offender cooperation with authorities. In contrast, the Penal Code provides broader grounds for mitigation, whether through statutory excuses or judicial discretion. Although this flexibility enhances fairness, it also risks inconsistency in judicial practice due to the absence of unified standards. The study concludes that Jordan’s criminal policy requires reform, particularly by clarifying cybercrime provisions and establishing coherent criteria for judicial discretion.

Sarcopenia is a growing concern as a geriatric syndrome associated with various adverse health outcomes. Determining its prevalence and identifying risk factors are essential for effective prevention. This systematic review and meta-analysis aimed to estimate the prevalence of sarcopenia and identify the factors associated with sarcopenia in community-dwelling older adults. Guided by the PICo framework, we systematically searched six databases for relevant literature. Two reviewers independently assessed the quality of included studies. We performed a meta-analysis to estimate the prevalence of sarcopenia in overall older adults and subgroups. For risk factor analysis, pooled odds ratios (ORs) with 95% CIs were calculated, employing either random or fixed-effects models as appropriate. A total of 52 eligible studies involving 70,202 older adults were included, among whom 7,488 were male and 9,054 were female. 40 studies were analyzed for both prevalence and related factors, while the remaining 12 were used for prevalence estimation only. The pooled analysis revealed a wide variation in the prevalence of sarcopenia among community-dwelling older adults, ranging from 5.2% to 50.0%, with an overall estimated prevalence of 18.8% (95% CI: 15.6%-22.4%) and substantial heterogeneity (I²=99.3%). Subgroup analyses showed that the highest rates were identified in studies using the EWGSOP 2018 definition (25.8%), Europe populations (23.4%), and using the anthropometric equations for muscle mass measurement (23.1%). Moreover, the factors significantly associated with sarcopenia in community-dwelling older adults were older age (OR = 3.3, 95% CI: 2.8-3.8), BMI (OR = 0.7, 95% CI: 0.6-0.9), malnutrition (OR = 3.4, 95% CI: 2.2-5.1), low physical activity (OR = 2.3, 95% CI: 1.8-2.8), current smoking (OR = 1.7, 95% CI: 1.3-2.2), and comorbidities such as osteoporosis (OR = 1.8, 95% CI: 1.3-2.4), osteoarthritis (OR = 1.4, 95% CI: 1.3-1.6), depression (OR = 3.0, 95% CI: 1.9-4.7), diabetes (OR = 2.8, 95% CI: 1.4-5.4), and cognitive impairment (OR = 2.5, 95% CI: 1.9-3.2). Our findings demonstrate a high prevalence of sarcopenia among community-dwelling older adults, with estimates significantly influenced by geographic region, diagnostic criteria and muscle mass measurement methods. The findings highlight heterogeneity due to non-standardized diagnostic methods and identify key risk factors including advanced age, low BMI, malnutrition, low physical activity, and comorbidities such as osteoporosis. These results underscore the need for unified diagnostic standards and early community-based interventions targeting modifiable risks.

This paper presents a consensus of Russian experts on ultrasound diagnosis of rotational vertebral artery (VA) compression. Rotational compression of the VA is highlighted as a significant cause of vertebrobasilar insufficiency, though it frequently leads to overdiagnosis due to the absence of unified standards and inadequate physician awareness. The article thoroughly discusses the indications, methodology of ultrasound examination using rotational head and neck maneuvers, evaluation criteria for interpreting results, and offers a diagnostic algorithm and a clinical example. The authors emphasize the importance of dynamically assessing hemodynamics in VA segments, basilar or posterior cerebral arteries to identify both the level and regional significance of compression. The proposed algorithm aims to standardize diagnostics and reduce clinical errors.

In recent years, artificial intelligence (AI) has made significant progress in the management of aortic dilatation diseases, including aortic dissection and aortic aneurysm, with applications spanning intelligent diagnosis, treatment decision support, and postoperative management. AI technologies, leveraging imaging analysis, multimodal data fusion, intelligent surgical assistance, and prognostic modeling, have improved early screening efficiency, personalized treatment precision, and long-term monitoring outcomes. However, current AI models face challenges such as poor interpretability, lack of standardized training data, and limited multicenter validation. Future efforts should focus on data sharing, the establishment of unified standards, and interdisciplinary collaboration to promote broader clinical adoption of AI in aortic dilatation diseases.

Public governance, as the core model of modern state governance, emphasizes that multiple entities, including government departments, social organizations, enterprises, and individual citizens, work together to address social problems and provide public services through the sharing of information and resources, the sharing of responsibilities, and the joint consultation of decisions, guided by common goals. With the accelerated advancement of globalization and informatization, as well as the profound transformation of government functions, cross-departmental collaborative governance has become a key strategy for improving government effectiveness and effectively addressing complex and changing social issues. As a key link in the collaborative governance framework, the cross-departmental standards collaboration mechanism is committed to promoting information sharing, resource integration, and collaborative decision-making among different departments through the formulation and implementation of a unified standards system, thereby enhancing the flexibility and effectiveness of government governance. This article first defines the relevant core concepts, then deeply analyzes the problems and challenges of the cross-departmental standards collaboration mechanism in current public governance practices, and then explores the basic principles and specific practical paths for building such a mechanism, aiming to provide useful reference and inspiration for improving the overall effectiveness of public governance.

The article is dedicated to analyzing the features of applying digital humanities (DH) in teaching humanities disciplines in higher education institutions, with an emphasis on comparing Western and Ukrainian experiences. The relevance of the topic is driven by the digital transformation of education, the need for adaptation to societal changes, and improving the quality of learning through innovative technologies. Analysis of recent studies shows that DH integrates cloud systems, open science, digital archives, and data analysis tools, promoting interdisciplinarity and interactivity in the educational environment, despite challenges of accessibility and faculty training. The theoretical foundations are based on the evolution of digital humanities from text digitization to methodology formation and integration into education with AI. Key implementation principles in Ukraine focus on interdisciplinarity, academic integrity, openness, practice-based learning, and continuity. Research results demonstrate a high level of DH implementation in EU and US countries. A crucial factor for effective DH integration is a methodological foundation that combines humanistic values with technological approaches. The Ukrainian experience shows gradual institutional integration of DH into curricula, development of digital educational courses, and student involvement in project-based research activities. Western and Ukrainian experiences reveal two different but complementary approaches: systematic implementation in EU and US countries and adaptive innovation under crisis conditions in Ukraine. The prospects for DH implementation in Ukrainian higher education include unified standards, a network of DH centers, interdisciplinary master’s programs, and methodological recommendations for instructors

Public governance, as the core model of modern state governance, emphasizes that multiple entities, including government departments, social organizations, enterprises, and individual citizens, work together to address social problems and provide public services through the sharing of information and resources, the sharing of responsibilities, and the joint consultation of decisions, guided by common goals. With the accelerated advancement of globalization and informatization, as well as the profound transformation of government functions, cross-departmental collaborative governance has become a key strategy for improving government effectiveness and effectively addressing complex and changing social issues. As a key link in the collaborative governance framework, the cross-departmental standards collaboration mechanism is committed to promoting information sharing, resource integration, and collaborative decision-making among different departments through the formulation and implementation of a unified standards system, thereby enhancing the flexibility and effectiveness of government governance. This article first defines the relevant core concepts, then deeply analyzes the problems and challenges of the cross-departmental standards collaboration mechanism in current public governance practices, and then explores the basic principles and specific practical paths for building such a mechanism, aiming to provide useful reference and inspiration for improving the overall effectiveness of public governance.

BackgroundThe apolipoprotein E ε4 allele (APOE ε4) is a genetic risk factor for neurodegenerative diseases. The potential of lipid metabolism as a biomarker in conjunction with APOE ε4 for the evaluation of dementia with Lewy bodies (DLB) warrants further investigation.ObjectiveThe study aimed to investigate the association between APOE ε4 and lipid metabolism in DLB.MethodsThis was a cross-sectional observational study that included a total of 171 DLB patients diagnosed based on established clinical consensus criteria. Strict inclusion and exclusion criteria were used in this study. APOE genotypes and blood lipid levels were determined using unified standards. IBM SPSS Statistics software was used for statistical analysis.ResultsIn patients with mild and moderate CDR, APOE ε4 carriers had significantly higher CHOL and LDL-C levels compared to non-carriers. In the 70-79 age group, APOE ε4 carriers demonstrated higher LDL-C (2.94 ± 0.83 mmol/L versus 2.47 ± 0.97 mmol/L, q = 0.0480) and CHOL (4.88 ± 1.05 mmol/L versus 4.25 ± 1.18 mmol/L, q = 0.0453) levels compared to non-carriers. In the 70-79 age group, ROC curve analysis showed that TG (AUC = 0.65, 95%CI = 0.514-0.785, p = 0.046), LDL-C (AUC = 0.663, 95%CI = 0.526-0.801, p = 0.03) and CHOL (AUC = 0.692, 95%CI = 0.557-0.827, p = 0.011) had certain reference value for diagnosis. Among patients presenting with rapid eye movement sleep behavior disorder, fluctuating cognition, and parkinsonism, APOE ε4 carriers exhibited higher levels of APO B, CHOL, and LDL-C compared to non-carriers.ConclusionsPeripheral blood lipid level as a metabolic biomarker, combined with APOE ε4 gene detection, has potential value for disease monitoring and prognosis evaluation.

With China’s low-altitude economy becoming a strategic emerging industry, the rapid growth of UAV applications demands higher efficiency in low-altitude airspace utilization and safety management. However, existing studies lack unified grid division standards and refined methods to evaluate capacity for complex urban low-altitude airspace. This study is devoted to developing a methodology for determining safe distances and assessing the throughput capacity of transport systems. The work is based on a multi-criteria assessment that takes into account four significant indicators. The application of the Pareto optimization principle made it possible to identify the most effective compromise solutions. A collision probability model with random UAV(Unmanned Aerial Vehicle) headings was proposed to determine safety separations, and a grid capacity simulation model with saturation judgment and convergence verification was established. The optimal grid granularity was identified as 20 m. Safety separations for DJI M300RTK, Mavic 3Pro, and Air 3S were 104 m, 86 m, and 47 m, respectively. Saturated capacity stabilized within 106–116 s, with stable values of 1.022, 0.961, and 1.023 drones/min for the three UAV models. The results of the study contain key conclusions about traffic capacity and suggest ways to optimize it. Conclusions: This study provides a theoretical framework for airspace resource optimization and UAV path planning, offering quantifiable benchmarks to evaluate and manage urban low-altitude airspace.

Abstract. The article examines the impact of artificial intelligence (AI) technologies on the processes of detecting, preventing, and suppressing illegal drug trafficking. It analyzes key areas of AI application — from big data analytics and digital platform monitoring to predictive modeling and automation of forensic processes. The paper outlines the achievements and limitations of existing systems and discusses ethical, legal, and international aspects. It concludes that integrating AI into law enforcement operations can significantly enhance the effectiveness of anti-drug efforts, but requires the development of unified regulatory standards and interagency cooperation.

Gene editing technologies are undergoing breakthrough advancements, with next-generation tools such as base editing and prime editing demonstrating significant advantages. Base editors, which combine a Cas9 nickase with a deaminase, enable precise single-base conversions (e.g., CT or AG) without inducing double-strand DNA breaks, showing great promise for treating diseases caused by point mutations. In terms of clinical applications, there are now over 300 global clinical trials in gene therapy, primarily focused on hematological disorders and solid tumors. Innovations in delivery systemssuch as lipid nanoparticles (LNPs) and adeno-associated virus (AAV) vectorshave improved tissue targeting, although long-term safety monitoring remains to be further refined. Regulatory policies vary significantly across countries; therefore, future efforts should prioritize the establishment of unified safety standards, tiered risk assessment frameworks, and comprehensive, lifecycle-oriented ethical review mechanisms. Such measures are essential to facilitate the safe translation of these technologies and unlock their vast potential in precision medicine, agriculture, and beyond.

Gait analysis is an important method for studying the laws and characteristics of human motion. With the wide application of Artificial Neural Networks (ANN) in various fields, their value in gait analysis has become increasingly prominent. This paper systematically reviews the application of ANN in the analysis of gait kinematics, dynamics, and spatiotemporal parameters, and deeply discusses the main existing problems, such as model construction, training data, and limitations of single perspective. It also looks forward to the future development directions. Future research should focus on developing more accurate network models, integrating multimodal training methods, and constructing datasets with unified standards to promote the wide application of this technology in clinical practice and sports science.

Introduction: Teleradiology has become an integral component of modern health care, enabling remote access to radiological expertise but introducing new challenges related to communication, technology, and legal accountability. This study evaluates radiologists' perceptions of malpractice risks in teleradiology within the United Arab Emirates (UAE) and explores their implications for patient safety. Methods: A descriptive cross-sectional survey was administered to radiologists across public and private health care institutions in the UAE between August and November 2024. The survey examined participants' demographic profiles, teleradiology experience, awareness of malpractice claims, communication practices, and perceived challenges. Quantitative data were analyzed using descriptive and inferential statistics to identify risk patterns and contributing factors. Results: Teleradiology was widely adopted among respondents, reflecting its essential role in current radiology practice. However, respondents identified several malpractice-related risks, most notably limited patient information, inconsistent communication protocols, and technical disruptions affecting image quality and transmission reliability. Many radiologists expressed uncertainty regarding the legal frameworks governing teleradiology and highlighted the need for clear national policies and institutional guidance. Conclusion: While teleradiology enhances accessibility and continuity of care, its safe implementation requires stronger governance, reliable technological infrastructure, and effective interdisciplinary communication. The study underscores the need for unified legal standards and targeted training to strengthen patient safety and minimize malpractice exposure.

Introduction. The article considers the development of the theoretical model for the implementation of digital twins of highways and assesses their effectiveness within the traffic management system, adapting their construction principles to the specifics of Russia’s transport infrastructure. Materials and Methods. The integration of digital twins into traffic management demonstrates its effectiveness through a close relationship with intelligent transport systems. The research is based on modern method and system analysis to the creation and application of digital twins. The authors propose a mathematical model for formalizing and evaluating the effectiveness, which integrates key factors such as: road maintenance costs, reduction of vehicle idle time, fuel savings, and improved safety. Digital twins generate economic benefits through more accurate forecasting of repair and preventive maintenance work, diminishing operational expenses, and decreased need for constant personnel presence at sites. Furthermore, they also serve as a key tool for long-term planning, providing the capability to model future scenarios for the development of the transport network with minimal financial investment. Results. The study encompassed methods of predictive analytics, data from pilot projects, and approaches to creating digital twins that utilize data collected by sensor networks, video cameras, and drones. Processing and integrating this information into the unified digital platform enables real-time monitoring of changes on the roads, forecasting situation development, and making informed management decisions using tools of predictive analytics. A theoretical and economic model has been developed and formalized to assess the effectiveness of digital twins, providing quantitative justification for investment decisions. Several specific problems related to scaling these technologies in the Russian Federation were identified, including an insufficient regulatory framework, the need to develop unified data standards, and a shortage of skilled personnel. A structured table outlining the development of digital twins and their key directions is presented. Discussion and Conclusion. The research has showed that combining digital twins with intelligent transport systems opens sufficient opportunities for optimizing traffic flow management, improving road safety, and increasing transport capacity. Comprehensive traffic optimization is impossible without demonstrating the practical significance of digital twins. The proposed model can serve as a basis for planning and justifying investments in the digitalization of transport infrastructure at various state and municipal levels. However, successful implementation depends on many factors and requires a complex approach, including serious personnel training at all levels, development of the regulatory framework, and creation of the unified digital ecosystem.

With the growing demand for sustainable finance and investment decision-making, the role of artificial intelligence (AI) in environmental, social, and governance (ESG) data collection and analysis has attracted increasing scholarly attention. Nevertheless, challenges such as fragmented data sources and inconsistent standards continue to limit its application. Against this backdrop, this study reviews prior research to outline recent progress in ESG data collection, risk identification, and financial analysis, while also evaluating AIs role in improving data reliability, guiding investment strategies, and strengthening risk control. The results reveal that techniques such as natural language processing (NLP), machine learning, and generative AI can strengthen ESG data collection and analytical capacity, with practical applications in risk identification, portfolio optimization, and asset pricing. Yet, practical applications are constrained by issues such as inconsistent data standards, algorithmic bias, and the lack of model interpretability. Future research should prioritize the establishment of unified data standards, the enhancement of algorithmic fairness and interpretability, and the advancement of multimodal data integration and cross-regional comparisons to develop a more intelligent and reliable ESG analytical framework.

ESG has now been established as a standard for evaluating whether a company is in a favorable state of development. However, ensuring the transparency of corporate ESG information remains a persistent challenge. In today's corporate ESG regulatory practices, the lack of unified mandatory standards coupled with lagging legal frameworks makes it extremely challenging to supervise corporate ESG information. In response to this, based on the mutual needs of corporations and stakeholders, this study integrates responsive regulation theory, agenda-Melding theory, and stakeholder theory to construct a theoretical framework: public pressure from media exposure formation of industry practices judicial rulings citing these practices development of statutory law. This establishes a novel supervisory reinforcement mechanism grounded in media exposure. This study will call the above mechanism the media disclosure mechanism and apply it to explore new approaches for corporate ESG oversight, demonstrating its ultimate role in hardening soft law. However, the widespread popularization of this mechanism may simultaneously expose corporations to legal risks such as damaged reputation and interference of public opinion in the judicial process.

Introduction. Ensuring the financial security of banks in the digital environment is a key factor in maintaining the stability of the banking sector and overall macro-financial balance in the context of intensive digitalization. The rapid growth of electronic transaction volumes, the introduction of innovative financial technologies (FinTech), and the expansion of virtual ecosystems are transforming traditional approaches to managing banking processes, assets, and information infrastructure. This necessitates a rethinking of the paradigms of asset, data, and operational process protection, as a result of which financial security is viewed not only as a key indicator of the stability of individual banking institutions, but also as a systemic task that determines macrofinancial stability. There is an urgent need for a scientific rethinking of approaches to financial security in the digital space. This involves developing integrated strategies that combine technological solutions, adaptive financial instruments, effective risk management, and regulatory innovations (RegTech, SupTech). Systematic construction of cyber defense architecture, development of analytical platforms based on big data, and strengthening cryptographic information protection mechanisms are key vectors that will contribute to the consolidation of financial security and ensure the sustainable development of banks in a dynamic digital landscape. Problem Statement. The transition to a dominant role of the digital space in the banking sector is accompanied by an escalation of multi-vector threats – both technical and regulatory. On the one hand, the intensification of the use of cloud computing, artificial intelligence and distributed ledger technologies increases vulnerability to cyber risks, including sophisticated phishing attacks, ransomware and targeted cyberattacks on critical infrastructure. On the other hand, the integration of financial and digital technologies (DeFi, Open Banking) generates new forms of interaction between market entities that do not always fit into the existing regulatory framework. Regulatory lags, the lack of unified cybersecurity standards, and fragmented supervision create the prerequisites for the accumulation of systemic risks. Purpose. The purpose of the study is a comprehensive analysis of mechanisms for ensuring the financial security of banks in the digital space, taking into account modern challenges and the need to adapt financial instruments in the context of global digital transformation.

The triply periodic minimal surface (TPMS) structures hold significant promise for enhancing thermal-hydraulic performance in compact heat exchangers. However, a systematic comparison of various TPMS types and optimization strategies under unified standards is lacking, hindering rational selection for engineering applications. This study experimentally and numerically investigates the performance of seven TPMS structures, encompassing basic types (Diamond, IWP, Gyroid, and Primitive), structural strategies (sheet vs solid networks), hybridization, and cell density enhancement. A key finding is the significant deviation of additively manufactured samples from their designs, with an average pressure drop of the realized Primitive-sheet structure being 22.96% higher than its ideal counterpart. More importantly, the results reveal a fundamental performance trade-off: solid-network TPMS structures (exemplified by IWP-solid-1) excel in flow efficiency, reducing pressure drop by an order of magnitude compared to their sheet-network counterparts, while sheet-network structures (particularly the Diamond-sheet) achieve superior heat transfer coefficients, up to 104.42% higher than the Primitive-sheet. Hybridization of the Gyroid and Primitive sheets demonstrated a potential pathway for pressure drop reduction. Crucially, evaluation based on the area goodness factor (j/f) identified the Diamond-sheet and IWP-solid-1 as the top performers for overall thermal-hydraulic efficiency among sheet and solid networks, respectively. This study provides direct guidance and critical data for selecting and optimizing the TPMS structures in thermal management systems.

The subject of the study is the international legal mechanisms for regulating climate change and their interaction with national legal regimes, particularly the legal practices of the Russian Federation. A systematic analysis of international climate law has been conducted, revealing key gaps: fragmentation of enforcement and accountability mechanisms, challenges in fairly distributing burdens between developed and developing countries, insufficient coherence between international and national legal regimes, limited accessibility to procedures for compensating transboundary climate damage, and difficulties in proving causal links in climate disputes. The achievements in secondary and strategic acts (strategies, "roadmaps" for the Paris Agreement, carbon accounting methodologies) in the Russian Federation are noted, but there is a lack of coordination, absence of unified climate legislation, and not always effective integration of "hard" and "soft" law. A synthetic interdisciplinary approach has been applied, combining systemic-legal, comparative-legal, and doctrinal analyses, institutional and functional-legal approaches with elements of climatology, political science, and economics. Methods of analyzing the treaty framework, monitoring and financial mechanisms, comparing national practices (Russia, EU: Germany, France), and studying judicial precedents have been used. The work combines a comprehensive legal and institutional analysis of international climate norms with a detailed assessment of their implementation practices in Russia and comparable jurisdictions, proposing unified approaches to standardizing the evidentiary basis in climate disputes and formulating specific mechanisms for translating elements of "soft" law into national legislation. New practical and legal tools have been identified: centralized scientific-legal commissions for unifying expertise, methodological standards for establishing causation, and hybrid funding models for adaptation measures. Based on the conducted research, eight priority measures are proposed to enhance the effectiveness of climate regulation: from creating national climate councils and formalizing "soft law" standards to developing unified standards of proof in climate disputes, expanding access to justice, harmonizing extraterritorial regulation, and strengthening international financial mechanisms. The necessity of a comprehensive, multi-level approach is emphasized, combining legal harmonization, institutional reform, civil society participation, and fair distribution of resources and responsibilities. Such an approach is viewed as a prerequisite for forming a sustainable and legitimate global climate legal order that responds to the challenges of the 21st century.