ObjectiveThis study explores the reasons and methods by which medical students use Medical Educational Commercial Off-the-Shelf (MedED-COTS) learning platforms for exam preparation. It also compares student use of these platforms with institutional resources and identifies their benefits and limitations.MethodsA qualitative cross-sectional study was conducted at the University of Birmingham, UK, involving semi-structured focus groups with 5 medical students and 6 clinical teaching fellows (early career clinical instructors). Transcripts were analysed thematically using a deductive approach, with supplementary inductive coding to capture emerging themes.ResultsStudents reported that MedED-COTS were integral for exam preparation, often perceived as essential for success. Platforms were valued for accessibility, gamified features, and continuity with familiar strategies, such as working through past papers. Peer influence strongly shaped platform selection and use. Students highlighted the benefits of identifying knowledge gaps and flexible, self-directed learning opportunities. However, concerns were raised about subscription costs, equity of access, and the need to purchase multiple platforms. Clinical teaching fellows acknowledged the appeal of MedED-COTS but cautioned that oversimplification of complex topics risked undermining the development of deeper clinical reasoning skills.ConclusionMedED-COTS play a prominent role in student learning but require careful integration with institutional resources to ensure balance between exam preparation and clinical reasoning development. Medical schools should provide guidance on appropriate use, address barriers of cost and equity, and consider how validated elements of these platforms could be incorporated into curricula. Given the small, exploratory sample from a single institution, findings should be interpreted as preliminary but highlight important directions for future, larger-scale research on the role of commercial learning platforms in medical education.

Abstract: Innovations in the development and application of injectable hydrogels within biomed-ical engineering highlight their distinct characteristics and promising roles in tissue engineering and controlled release systems. Injectable hydrogels, distinguished by their three-dimensional network topologies, in-situ gelation process, and stimuli-responsive behaviour, have outstanding biocompatibility, mechanical properties, and the capacity to deliver therapeutic drugs to specific areas with little invasiveness. This review focuses on the advancements in hydrogel formulations, particularly natural and synthetic hydrogels, and their effectiveness in stimulating tissue regenera-tion. It specifically emphasizes cardiac applications following myocardial infarction. Hydrogels have received significant attention due to their exceptional porosity, mechanical behaviour, and biological compatibility, making them convenient for cancer therapy. Injectable hydrogels, known for their favourable physicochemical properties, have shown promising results in treating various conditions, including ocular diseases, cancer, wound healing, cardiovascular disorders, and rheumatoid arthritis. It highlights the diversity in study methodologies and the necessity for large-scale animal trials, which pose challenges for clinical translation. Furthermore, emphasizes the importance of enhancing hydrogel properties to improve therapeutic efficacy and calls for ad-ditional research to fully realize their potential in regenerative medicine. This study explores in-jectable hydrogels for cardiac tissue regeneration post-myocardial infarction (MI), a less-studied area compared to wound healing and drug delivery. It highlights their applications in ocular dis-eases, cancer therapy, rheumatoid arthritis, and personalized medicine, addressing challenges like clinical translation, biocompatibility, and mechanical property optimization. Emphasis is placed on improving hydrogel porosity, strength, and stimuli-responsiveness for enhanced outcomes. Unique insights include their role as targeted drug carriers for localized cancer therapy. Future di-rections involve biopolymer innovations, 3D bioprinting, and regenerative medicine advance-ments.

Abstract: Purpose; The purpose of this paper is to provide a state-of-art review on variation modeling and propagation in aircraft assembly based on process-oriented strategy. And the main focus is on classifying and delineating different approaches, methods, and techniques with critical appraisals of their theories, applications, and limitations, based on which future research directions and corresponding methodologies are proposed. Design/methodology/approach; To facilitate understanding of the background, this paper starts with a brief description of aircraft assembly. Afterwards, this paper presents a comprehensive review of practical solutions in aircraft variation modeling. Their characteristics are summarized, which serves as a basis for the discussion of deviation control strategies. Thereafter, the possible trends are discussed to facilitate assembly quality control in future research.

Adverse childhood experiences screening in healthcare settings: A focus on pediatric primary care

Art therapy, with painting as its central modality, has garnered substantial em-piri-cal support as an effective intervention for a spectrum of psychological dis-orders. This comprehensive paper delves into the multifaceted mechanisms through which the act of painting facilitates mental health recovery and pro-motes overall well-being. By synthesizing perspectives from clinical psychology, neuroscience, sensory integration theory, and aesthetics, we propose a novel integrated frame-work that elucidates how painting engages cognitive, emo-tional, sensory, and so-cial processes. A systematic and extensive review of em-pirical literature from 2000 to 2024 robustly supports the efficacy of structured and unstructured paint-ing interventions in significantly alleviating symptoms of depression, anxiety, post-traumatic stress disorder (PTSD), and enhancing emotional regulation, self-concept, and resilience. The paper argues that paint-ing serves as a powerful non-verbal medium for externalizing and processing complex emotions, facilitat-ing cognitive restructuring, accessing pre-verbal trauma memories, and fostering a profound sense of agency and accomplish-ment. Furthermore, it explores the neu-robiological underpinnings, including the role of the default mode network (DMN), stress hormone regulation, and neural plasticity. The conclusion empha-sizes the transformative potential of integrating painting into mainstream thera-peutic practices while acknowledg-ing limitations in current research methodolo-gies. The paper culminates with strong recommendations for future research direc-tions, including the stand-ardization of evidence-based protocols, longitudinal studies, the exploration of cross-cultural applications, and the investigation of digital painting's therapeu-tic efficacy.

This review summarizes the preparation methods of MOF-on-MOF materials and their application progress in the field of photocatalysis. It highlights the unique advantages of such materials in photocatalytic applications and discusses their application examples in areas including environmental remediation, energy conversion, photoelectrochemistry, and the development of antibacterial mate-rials. Finally, it outlines the main challenges currently facing MOF-on-MOF photocatalytic systems and provides an outlook on their future research direc-tions in the field of photocatalysis.

Background: When computerized numerical control (CNC) machine tools are working, the electric spindle generates serious heat, which can easily cause the thermal elongation of the spindle and generate thermal errors. Designing cooling devices to control the generation of thermal errors in the spindle and utilizing thermal error compensation techniques for error compensation are essential for improving machining quality and productivity. Objective: By summarizing the current status of research on cooling devices and compensation technology of electric spindles in recent years, some conclusions have been drawn in this work to propose the future research direction. Methods: By reviewing patents on cooling devices and thermal error compensation technology of high-speed electric spindles published in recent years, we have explored the ideas for the improvement of existing cooling devices and compensation technology. Results: Some problems of the patents on current cooling devices and thermal error compensation technology are analyzed, and future research directions are proposed, respectively. Conclusion: As spindle power and speed continue to increase, the existing spindle cooling device and compensation technology also need to be continuously improved. Designers use intelligent technology to monitor the temperature changes during the work of the spindle and fast and accurate control of the cooling system so that the high-speed spindle cooling device tends to be intelligent. Aiming at the thermal error generated in the spindle working process, the designer enhances the error compensation effect by continuously improving and upgrading the key steps in the thermal error compensation technology, which in turn improves the spindle machining accuracy.

This study takes agricultural landscapes as its research object and conducts a visual analysis of relevant domestic literature using keywords such as "agri-cul-tural landscape" and "farmland landscape." It reveals that research on agri-cul-tural landscapes has shown an upward trend from 1986 to 2025, reaching a peak in 2019 before slightly declining. The hotspots, trends, and future direc-tions of research are primarily concentrated in landscape design, rural land-scapes, and landscape ecology. This study aims to provide theoretical support and practical guidance for the sustainable development of agricultural land-scapes.

The investment decision-making for natural gas exploration projects is faced with numerous uncertain factors, such as market price fluctuations, technolo-gi-cal advancements, and policy changes. Traditional investment deci-sion-making methods struggle to effectively address these volatile risks and un-certainties. In recent years, the Geske model, as a multi-stage investment deci-sion-making tool based on option pricing theory, has gradually been applied to the field of natural gas exploration to help decision-makers make flexible and optimal investment choices in uncertain environments.Through a literature review, this paper ex-plores the current application status and optimization paths of the Geske model in natural gas exploration projects, and analyzes the advantages and limitations of its combination with option pricing theory. First, the application of the Geske model in multi-stage decision-making can effec-tively address the technological, market, and policy uncertainties in natural gas exploration projects, providing investors with flexible decision-making options. Second, this paper discusses issues such as practical application cases and com-putational complexity of the model, and proposes potential future research di-rections, including improving computational efficiency, accurately estimating parameters, and integrating big data and machine learning technologies. By sorting out existing research achievements, this paper provides a theoretical basis for the promotion of the Geske model in natural gas exploration and other high-risk industries, and offers new ideas for optimizing investment deci-sion-making.

Sustainable development has emerged as a critical priority for the global community, influencing all aspects of development worldwide. Within this context, the role of education and training in advancing sustainable development can contribute to this. This research aims to explore whether the integration of Information and Communication Technology educational tools into the curricula of engineering technicians helps trainees better understand the concepts of climate change and resource management, which are directly linked to the green transition and the green economy, compared to traditional educational methods. The study was conducted with trainees from Higher Vocational Training Schools (SAEKs) in the wider Athens area, Greece. According to the results, using educational technology to teach engineering courses aids students in developing the competencies needed to change production processes and business models in the direction of a greener future. This is especially crucial as future technicians will be able to use cutting-edge methods to lower emissions and boost resource use efficiency. The findings of the study could provide important information for all those involved in the design of educational curricula of engineering technicians. Concerns and thoughts on the effective use of educational technology in the educational process are also expressed.

With the continuous advancement of industrial automation, intelligent defect detection has become a crucial means of ensuring product quality. However, the cost and labor required to obtain high-quality labeled data limit the widespread practical application of traditional supervised learn-ing methods. Therefore, semi-supervised learning (SSL) and unsupervised learning (UL) methods have received extensive attention from researchers due to their superior performance in low-labeled or unlabeled scenarios. This paper provides a systematic survey of typical semi-supervised and unsupervised learning methods in the field of industrial defect detection, analyzes the core concepts and key technologies of unsupervised learning and semi-supervised learning, as well as compara-tive analysis on relevant datasets, and finally proposes future development direc-tions.

With the development of artificial intelligence technology, deep learning, as an advanced ma-chine learning method, has achieved remarkable results in various industries. English reading teaching, as an important part of language learning, how to use deep learning to improve stu-dents' reading comprehension ability has become an important topic in current educational re-search. This paper discusses the application of deep learning in high school English reading teaching. Firstly, it analyzes the basic principles and technical characteristics of deep learning, then combines the needs of high school English reading teaching to propose a deep learn-ing-based teaching model, and explores its feasibility and effectiveness. Through relevant teaching practice cases, this paper further elaborates on the advantages and challenges of deep learning in English reading teaching, and finally proposes effective teaching strategies and fu-ture development directions.

Role of polygenic risk scores in venous thromboembolism: current state and future direc tions.

Higher education institutions are the important chain in provision of the inter-connections between the workforce (school graduates, youth, or adults), representatives from different economic sectors, experts from research and innovation development organisations, and all the interested contributors. The research purpose is to build a new development model of sustainable communication for higher education institutions. This research is qualitative as it aims at constructing a new model. The research integrates the use of theoretical analysis, comparative analysis of existing models, theoretical modelling, model creation, summarising analysis. Very often the researchers think of the process of communication as a one-way process. The present work allowed for the establishment of the inter-connections between the development of the system of the external and internal perspectives, on the one hand, and the implementation of the process of sustainable communication, on the other hand. The novel contribution of this research is that the sender and the receiver of the information in the sustainable communication process act at the same time, their information meets and exchanges, thereby promoting information interaction or quasi-knowledge creation. Future research intends to include the empirical methods of research. Collection of quantitative data is a future research direction, too.

Driven by the profound transformation of global research paradigms through generative artificial intelligence (AI), this study explores how generative AI can enhance the research capabilities of graduate students. Addressing challenges such as inefficient literature reviews, insufficient innovation in experimental design, and the slow adaptation of training systems to new technologies, the research proposes a systematic application model. The study elaborates on em-pirical practices across the entire research workflow, including literature pro-cessing, experimental design, paper writing, and ethical education. It also pre-sents strategies to tackle challenges like excessive technical dependence, data security threats, and outdated ethical standards. The study concludes with fu-ture research directions, including cross-cultural comparisons of research capa-bilities, multi-technological synergy, long-term impact tracking, and dy-namic adaptation to emerging disciplines. It aims to provide theoretical support and practical references for the deep integration of "AI + education."

With the deep integration of artificial intelligence (AI) technology in the field of education, public English teaching in vocational colleges is undergoing unprec-edented changes. This paper systematically explores the pathways for the role transformation of English teachers in the AI era. Through literature analysis, case studies, and questionnaire surveys, it reveals a multidimensional shift in teachers' roles—from traditional knowledge transmitters to learning facilita-tors, curriculum designers, technology collaborators, and emotional supporters. The study finds that AI technology not only alters teaching methods and teach-er-student relationships but also poses new demands on teachers' professional competencies. Finally, the paper proposes practical strategies and future direc-tions for this role transformation, providing theoretical references and practical guidance for the reform of English teaching in vocational colleges.

The logistics industry is one of the major contributors to carbon emissions. Low-carbon logistics is crucial for achieving the goals of "carbon peak" and "carbon neutrality". This article employs bibliometric analysis, utilizing Excel and CiteSpace software, to analyze 964 Chinese academic journal articles on low-carbon logistics published on the China National Knowledge Infrastructure (CNKI) database between 2008 and 2024. The study investigates publication volume trends, core authors and institutions,high-frequency keywords, keyword clustering, and the evolution of research within the low-carbon logistics field.The research findings indicate that studies on low-carbon logistics have undergone a shift from macro-level to micro-level explorations, and from local-ized to systemic perspectives. The results demonstrate that, with the advance-ment of technologies such as artificial intelligence and big data, digital logistics has emerged as a new research hotspot. Furthermore, decarbonization and sys-tematization of logistics activities represent significant future research direc-tions.

Elections are a concrete manifestation of the implementation of democracy in Indonesia, where the participation of the younger generation, especially the millennial generation, is a crucial aspect in determining the direction of the nation's future. However, the emergence of a tendency towards apathy and pessimism towards politics among millennials raises concerns about the quality of democracy in the future. This study aims to understand how the political idealism of the millennial generation, both optimistic and pessimistic, affects their level of political participation. This study highlights the importance of political education as a means to increase awareness and sensitivity of the younger generation to social and political issues. This study uses a qualitative approach with a descriptive type of research, where data is collected through an in-depth understanding of a phenomenon with interviews, online participant observation and analysis of social media upload documents, this study seeks to explore millennial perceptions of politics and the role of social media in shaping their political culture. The results of the study show that millennial attitudes towards politics are greatly influenced by educational factors, personal experience, and trust in the political system. In addition, social media plays a significant role in influencing their views and levels of political participation, both positively and negatively. More effective political education is needed to encourage active participation of millennials in Indonesian democracy.

Nonalcoholic fatty liver disease (NAFLD) is of global concern due to its high prevalence worldwide. NAFLD, as one of the most common causes of liver function abnormalities, is associated with obesity, insulin resistance, and type 2 diabetes mellitus, and there are no medications available to treat NAFLD. Extracellular vesicles (EVs) are nanosized, membrane-bound vesicles that deliver biomolecules between cells. Exosomes are a subtype of EVs that mediate intercellular communication by delivering proteins and RNAs. MicroRNAs (miRNAs) are a highly conserved class of small tissue-specific non-coding RNAs that influence the expression of many functionally interacting genes. Hepatic-derived exosomal miRNAs are tightly associated with NAFLD occurrence and progression through multiple mechanisms. In addition, the characterization of miRNAs suggests that they may serve as multifunctional biomarkers for NAFLD, be used as clinical therapeutic targets for NAFLD, and be significant predictors of patient prognosis. Here, we review recent advances in the regulation and function of exosome- derived miRNAs in NAFLD, focusing on miRNAs specifically expressed or enriched in hepatocytes (HCs), hepatic macrophages, hepatic stellate cells (HSCs), and other immune cells in the liver. Finally, we discuss future research directions on exosomal miRNAs as biomarkers for NAFLD's diagnosis and clinical therapeutic targets.

Hydrogen sensing towards palladium-based nanocomposites: A review