Search Results (3,451)

Background/Objectives: Cerebral palsy (CP) is a neurological disorder that affects movement and posture. Physical activity (PA) is safe and crucial for healthy development; however, this population faces barriers that hinder its implementation. Virtual reality (VR) is an emerging and promising technology that promotes PA in young people with CP. This work aims to compile and analyze the current scientific literature on physical exercise (PE) programs using VR in children and adolescents with CP through a PRISMA systematic review. Methods: A systematic review was conducted and reported based on the PRISMA (Preferred Reporting Items for Systematic Review and Meta-analyses) statement. The search was conducted through the Web of Science, PubMed, and Scopus databases on 1st September 2024. Studies based on PA interventions using VR in children and adolescents with CP were selected. Results: A total of 24 experimental research articles were selected for this review. The studies included comprise a total sample of 616 participants between 4 and 18 years old. The studies involved a diverse range of interventions, from brief sessions to intensive training. The results consistently demonstrated improvements in motor control, muscle strength, aerobic capacity, and overall participation in daily activities. Conclusions: The results highlight that the use of VR for PE programs has numerous benefits such as increased enjoyment, facilitation of motor learning, and acquisition of functional skills. PE through VR in children and adolescents with CP represents a promising tool; more scientific and practical evidence is needed to confirm its long-term effectiveness. Full article

Objective: Coronary atherosclerosis (CAD) is characterized by arterial intima lipid deposition, chronic inflammation, and fibrous tissue proliferation, leading to arterial wall thickening and lumen narrowing. As the primary cause of coronary heart disease and acute coronary syndrome, CAD significantly impacts global health. Recent genetic studies have demonstrated CAD’s polygenic and multifactorial nature, providing molecular insights for early diagnosis and risk assessment. This review analyzes recent advances in CAD-related genetic markers and evaluates their diagnostic potential, focusing on their applications in diagnosis and risk stratification within precision medicine. Methods: We conducted a systematic review of CAD genomic studies from PubMed and Web of Science databases, analyzing findings from genome-wide association studies (GWASs), gene sequencing, transcriptomics, and epigenomics research. Results: GWASs and sequencing studies have identified key genetic variations associated with CAD, including JCAD/KIAA1462, GUCY1A3, PCSK9, and SORT1, which regulate inflammation, lipid metabolism, and vascular function. Transcriptomic and epigenomic analyses have revealed disease-specific gene expression patterns, DNA methylation signatures, and regulatory non-coding RNAs (miRNAs and lncRNAs), providing new approaches for early detection. Conclusions: While genetic marker research in CAD has advanced significantly, clinical implementation faces challenges including marker dynamics, a lack of standardization, and integration with conventional diagnostics. Future research should prioritize developing standardized guidelines, conducting large-scale prospective studies, and enhancing multi-omics data integration to advance genomic diagnostics in CAD, ultimately improving patient outcomes through precision medicine. Full article

This manuscript presents the development and testing of a novel model designed to help organizations, particularly small and medium-sized enterprises (SMEs), address the challenges of integrating new technologies within the frameworks of Industry 4.0 and 5.0. The proposed model is a metamodel that evaluates organizational and contextual vulnerabilities concerning both existing technologies and potential external technologies under consideration for adoption. It synthesizes three foundational frameworks: the Viable System Model (VSM), the principles of viable and sustainable systems, and the Technology, Organization, and Environment (TOE) Model. The findings demonstrate the practical applicability of this model in an SME context, showcasing its ability to facilitate the gradual and sustainable adoption of new technologies. By aligning business needs with technological solutions and leveraging insights from computer science and organizational cybernetics, the model adapts to varying levels of technological adoption, integrating organizational dynamics and business evolution to support the implementation of emerging technologies. Full article

Background: Nurses frequently face various sources of stress in the workplace, making self-compassion interventions crucial for promoting their mental well-being. This scoping review aims to: (a) identify self-compassion intervention programs implemented within the nursing population; and (b) analyze the content and outcome measures of these interventions. Methods: The study follows Arksey and O’Malley’s scoping review framework and adheres to the PRISMA-ScR guidelines. Relevant literature on self-compassion interventions for nurses published between January 2010 and May 2024 was systematically reviewed. Databases searched included PubMed, Web of Science, Scopus, ProQuest, and the Cochrane Library, using MeSH terms and free-text keywords such as “self-compassion”, “self-kindness”, “self-appreciation”, “self-worth”, “self-forgiveness”, “self-awareness”, “nurses”, and “nursing”. Results: Fifteen studies met the inclusion criteria and were included in the review. Self-compassion interventions were categorized into two types: (1) mindfulness-focused programs, such as Mindfulness-Based Stress Reduction (MBSR) and Mindful Self-Care and Resiliency (MSCR), which treat self-compassion as a potential outcome; and (2) self-compassion-focused programs, including Mindful Self-Compassion (MSC), Compassion Focused Therapy (CFT), and Loving-Kindness Meditation (LKM). Conclusions: The mental health challenges faced by nurses have drawn growing attention, underscoring the importance of self-compassion interventions. This review examines empirical studies within the nursing population, contributing to the development of more targeted and effective strategies to enhance the mental health and well-being of nursing professionals. Full article

Background: Myo-inositol plays a vital role in human health, functioning as a second messenger of FSH and facilitating the transport of glucose into the cell. Consequently, myo-inositol is regularly utilized in the treatment of polycystic ovary syndrome (PCOS), wherein it acts upon metabolic factors, improving insulin sensitivity and reducing total androgen levels. Patients with PCOS frequently suffer from infertility; thus, the use of myo-inositol has been explored in improving assistive reproductive technique (ART) procedures. This is by no means limited to patients with PCOS, as inositol has found applications in non-PCOS patient groups in addition to in male factor infertility. This joint statement from the Experts Group on Inositol in Basic and Clinical Research and on PCOS (EGOI-PCOS), the Polish Society of Andrology, and the International Scientific Association for the Support and Development of Medical Technologies discusses the latest evidence on this topic, with the aim of interrogating whether myo-inositol could be implemented in everyday ART patient care. Methods: The authors conducted a narrative review performed via an independent literature search between July and August 2024, using the search platforms PubMed, Web of Science, and Google Scholar. Results: In both non-PCOS and PCOS populations seeking IVF care, MI supplementation prior to ovarian stimulation may positively affect gonadotropin use and duration, oocyte and embryo quality, fertilization, and clinical pregnancy rates. Conclusions: This position statement recommends that myo-inositol be considered as a potential pretreatment strategy prior to ovarian hyperstimulation with gonadotropins. Full article

New data science and real-time modeling techniques facilitate better monitoring and control of manufacturing processes. By using real-time data models, industries can improve their processes and identify areas where resources are being wasted. Despite the challenges associated with implementing these data models in transient and multi-physical processes, they can significantly optimize operations, reduce trial and error, and minimize the overall environmental footprint. Implementing real-time data analytics allows industries to make quicker, informed decisions and immediate corrections to material processes. This ensures that manufacturing sustainability targets are regularly met and product quality is maintained. New concepts such as digital twins and digital shadows have been developed to bridge the gap between physical manufacturing processes and their virtual counterparts. These virtual models can be continuously updated with data from their physical counterparts, enabling real-time monitoring, control, and optimization of manufacturing processes. This paper demonstrates the predictive power of real-time reduced models within the digital twin framework to optimize process parameters using data-driven and hybrid techniques. Various reduced and real-time model-building techniques are investigated, with brief descriptions of their mathematical and analytical foundations. The role of machine learning (ML) and ML-assisted data schemes in enhancing predictions and corrections is also explored. Real-world applications of these reduced techniques for extrusion and additive manufacturing (AM) processes are presented as case studies. Full article

Background/Objectives: Aging involves a series of changes in non-pathological age-related conditions, some of which impact the cognitive functioning of older adults. Executive functions are cognitive skills that are often affected in this process, although they have been shown to improve after physical exercise interventions. This protocol aims to describe the procedures that will be carried out in a systematic literature review, including a meta-analysis of the effects of resistance interventions on the main dimensions of executive function in cognitively healthy older adults compared to active or passive control groups. Methods: The PRISMA-P guidelines will be followed. Eligibility criteria will be organized based on the PICOS strategy (older adults with normal cognition ≥60 years; chronic resistance interventions ≥4 weeks; active or passive control group; direct measures of executive function). The PubMed, EBSCO, Scopus, and Web of Science databases will be used. The risk of bias and quality of evidence will be measured using RoB2 and GRADE, respectively. The DerSimonian–Laird random effects model will be used for the meta-analysis. The effect size will be calculated using Hedges’ g with a 95% confidence interval and p < 0.05 to indicate statistical significance. Discussion: The results of the proposed review may be useful to justify the design and implementation of treatment plans based on resistance training for the prevention and management of cognitive changes typical of aging among older adults. PROSPERO registry: CRD42024571127. Full article

Background/Objective: Knee osteoarthritis (OA) is a common and debilitating condition affecting older adults, often progressing to advanced stages and requiring total joint replacement. Exercise therapy is widely recognized as the first-line approach for the prevention and initial management of OA. This systematic review assessed the effectiveness of home-based exercises (HBEs) compared to supervised exercises in alleviating pain and reducing disability among patients with knee OA. Methods: A systematic search of PubMed, Cochrane Library, and ScienceDirect identified randomized controlled trials (RCTs) published between January 2001 and October 2024. Methodological quality was evaluated using the Physiotherapy Evidence Database (PEDro) scale, and a meta-analysis was conducted to quantify the efficacy of these interventions. Results: Ten RCTs involving 917 patients were included, ranging in moderate to high methodological quality (PEDro score: 6.3 ± 1.2). Intervention durations ranged from 4 to 12 weeks. Both supervised and HBEs were found to be effective, but supervised exercises demonstrated statistically significant improvements in pain (SMD = −0.45 [95% CI −0.79; −0.11], p = 0.015) and disability (SMD = −0.28 [95% CI −0.42; −0.14], p < 0.001) compared to HBEs. Conclusions: Despite the superiority of supervised exercises over HBEs, considering the cost-effectiveness and ease of implementation of HBEs, we developed recommendations to create a hybrid rehabilitation program that combines both approaches to maximize clinical outcomes. Full article

This study explores the use of digital simulations in STEM education, addressing the gap in systematic reviews synthesizing recent advancements and their implications for teaching and learning by focusing on their impact on learning outcomes and student engagement across general and special education settings. The review includes 31 peer-reviewed empirical studies published in the last five years, sourced from ERIC, Scopus, and Web of Science, and adheres to the PRISMA methodology to ensure transparency and rigor. The findings reveal that interactive simulations are the most widely used type of digital tool, accounting for 25 of the 31 studies, followed by game-based simulations and virtual labs. Quasi-experimental designs dominate the research landscape, often employing pre- and post-tests to evaluate intervention effectiveness. While inquiry-based learning emerges as the most frequently implemented instructional strategy, hybrid and simulation-based approaches also feature prominently. Despite the evident benefits of digital simulations in enhancing conceptual understanding, engagement, and problem-solving skills, research gaps remain, particularly regarding their application in primary and special education contexts. This review underscores the need for diverse research methodologies and broader population studies to maximize the potential of digital simulations in STEM education. Full article

The food and agriculture sector is a cornerstone of critical infrastructure (CI), underpinning global food security, public health, and economic stability. However, the increasing digitalization and connectivity of operational technologies (OTs) in this sector expose it to significant cybersecurity risks. Blockchain technology (BT) has emerged as a transformative solution for addressing these challenges by enhancing network security, traceability, and system resilience. This study presents a comprehensive review of BT applications in OT security for food and agriculture CI, employing bibliometric and content analysis methods. A total of 124 relevant articles were identified from six databases, including the Web of Science Core Collection and MEDLINE^®. Bibliometric analysis was conducted across five dimensions: publication year, literature type, journal distribution, country contributions, and keyword trends. The findings are meticulously organized through tables, charts, and graphs. The year 2018 marked a surge in research within this domain, with the IEEE Internet of Things Journal and IEEE ACESS emerging as the most prolific journals, each boasting nine publications. The United States, China, and India are at the forefront in terms of journal citation counts. Our analysis determined that a reference count of 37 serves as an appropriate threshold. Otoum Safa stands out as the author with the highest number of published articles, totaling four. Keywords such as “blockchain”, “internet of things”, “smart contract”, “security”, and “critical infrastructure” appear with significant frequency. The statistics, trends, and insights gleaned from this bibliometric analysis can guide researchers in the OTCI field to forge a coherent and logical research trajectory. Content analysis further identified six key research areas within this domain: identity authentication and data verification, secure access control, attack detection and perception, data security and protection, data backup and recovery, and attack assessment and attribution. Based on these insights, a general framework is proposed to guide future research and practical applications of BT in securing OT within food and agriculture CI. This study systematically analyzes the current research landscape, challenges, and opportunities for BT in securing the OT critical to food and agriculture CI. By bridging the gap between blockchain innovations and the operational needs of the food and agriculture sector, this work contributes to advancing strategic implementation and improving the security of CI systems. Full article

Existential threats, including threats to the self, society, and the planet, are present throughout the lifespan and form a core element of the human experience. To consolidate knowledge and constructs about how people can adequately respond to existential threats, we convened an interdisciplinary working group, which consisted of eight researchers from the fields of psychology, systemic theology, practical theology, religious studies, cognitive science, palliative care, and sustainability science. The group met one day per week for 9 months to engage in an interactive co-creative process of data collection and analyses, discussion, iterative presentations, and writing. The process resulted in the development of an interdisciplinary model that pulls together the key themes of how people, societies, and systems can foster existential resilience and transformation. The model consists of three axes across which we (individuals, groups, systems) have to strengthen or stretch our “inner muscles”: connectedness, agency, and time. All axes contribute to the development of our inner capacities and, ultimately, meaning and purpose, which are crucial to support resilience and transformation. Our interdisciplinary overarching model provides a common conceptualization for existential resilience and transformation that can bridge existing research to support individual, collective, and large-scale system-change work. Its relevance and potential implementation are illustrated and presented from different disciplinary angles. Full article

The convergence of IT and OT networks has gained significant attention in recent years, facilitated by the increase in distributed computing capabilities, the widespread deployment of Internet of Things devices, and the adoption of Industrial Internet of Things. This convergence has led to a drastic increase in external access capabilities to previously air-gapped industrial systems for process control and monitoring. To meet the need for remote access to system information, protocols designed for the OT space were extended to allow IT networked communications. However, OT protocols often lack the rigor of cybersecurity capabilities that have become a critical characteristic of IT protocols. Furthermore, OT protocol implementations on individual devices can vary in performance, requiring the comprehensive evaluation of a device’s reliability and capabilities before installation into a critical infrastructure production network. In this paper, the authors define a framework for identifying vulnerabilities within these protocols and their on-device implementations, utilizing formal modeling, hardware in the loop-driven network emulation, and fully virtual network scenario simulation. Initially, protocol specifications are modeled to identify any vulnerable states within the protocol, leveraging the Construction and Analysis of Distributed Processes (CADP) software (version 2022-d “Kista”, which was created by Inria, the French Institute for Research in Computer Science and Automation, in France). Device characteristics are then extracted through automated real-time network emulation tests built on the OMNET++ framework, and all measured device characteristics are then used as a virtual device representation for network simulation tests within the OMNET++ software (version 6.0.1., a public-soucre, open-architecture software, initially developed by OpenSim Limited in Budapest, Hungary), to verify the presence of any potential vulnerabilities identified in the formal modeling stage. With this framework, the authors have thus defined an end-to-end process to identify and verify the presence and impact of potential vulnerabilities within a protocol, as shown by the presented results. Furthermore, this framework can test protocol compliance, performance, and security in a controlled environment before deploying devices in live production networks and addressing cybersecurity concerns. Full article

Background: Artificial intelligence (AI) has emerged as a transformative technology in healthcare, with its integration into cardiac surgery offering significant advancements in precision, efficiency, and patient outcomes. However, a comprehensive understanding of AI’s applications, benefits, challenges, and future directions in cardiac surgery is needed to inform its safe and effective implementation. Methods: A systematic review was conducted following PRISMA guidelines. Literature searches were performed in PubMed, Scopus, Cochrane Library, Google Scholar, and Web of Science, covering publications from January 2000 to November 2024. Studies focusing on AI applications in cardiac surgery, including risk stratification, surgical planning, intraoperative guidance, and postoperative management, were included. Data extraction and quality assessment were conducted using standardized tools, and findings were synthesized narratively. Results: A total of 121 studies were included in this review. AI demonstrated superior predictive capabilities in risk stratification, with machine learning models outperforming traditional scoring systems in mortality and complication prediction. Robotic-assisted systems enhanced surgical precision and minimized trauma, while computer vision and augmented cognition improved intraoperative guidance. Postoperative AI applications showed potential in predicting complications, supporting patient monitoring, and reducing healthcare costs. However, challenges such as data quality, validation, ethical considerations, and integration into clinical workflows remain significant barriers to widespread adoption. Conclusions: AI has the potential to revolutionize cardiac surgery by enhancing decision making, surgical accuracy, and patient outcomes. Addressing limitations related to data quality, bias, validation, and regulatory frameworks is essential for its safe and effective implementation. Future research should focus on interdisciplinary collaboration, robust testing, and the development of ethical and transparent AI systems to ensure equitable and sustainable advancements in cardiac surgery. Full article

Specifications grading is an alternative grading system that has been used with increasing frequency in higher education. Since first introduced by Linda Nilson in 2014, more than 90 publications on the design and implementation of specifications grading systems have been published. This work presents a systematic review of the current literature to analyze the variety of ways specifications grading systems are executed, including the diverse design and implementation considerations, as well as to present and discuss emergent themes. We analyzed 90 publications and present their relevant findings in the results. The following databases were last searched on 5 October 2024 for publications: IEEE Xplore, ACS Publications, ASEE PEER, PER, Scopus, ERIC, ACM, ScienceDirect, and Web of Science. All peer-reviewed journal articles, conference proceedings, and book chapters that implemented at least two structural features of specifications grading in an undergraduate or graduate course were included in this review. Theses, dissertations, conference abstracts, posters, workshops, blogs, opinion pieces, social media exchanges, and content provided on websites were not included. Additionally, reports of specifications grading systems in K-12 courses or those that only presented the design and/or implementation of less than two structural features of the grading system were similarly excluded. Our findings from the literature reveal that the following themes emerge from educators who use specifications grading: instructor commentary on time investment, academic performance, and student reactions to specifications grading. This review provides a resource for those interested in exploring this alternative grading system, and the emergent themes indicate that there are ripe opportunities for future study. Full article

This experimental study evaluated the effectiveness of an innovative motor science teaching program aimed at promoting the inclusion and involvement of students with Attention Deficit/Hyperactivity Disorder (ADHD) in secondary school. Sixty students (30 in the sample group and 30 in the control group) participated in the program, while 10 specially trained motor education teachers implemented the activities. The quantitative analysis showed a significant improvement in school inclusion scores (as measured by the Ainscow Inclusion Scale) and school engagement scores (Student Engagement Scale), with a strong positive correlation between the two parameters (r = 0.62, p < 0.01). The qualitative analysis, based on interviews with teachers, revealed positive perceptions of the program and emphasized the importance of training to address behavioral difficulties and ensure an inclusive school environment. The results suggest that customized motor education programs, combined with targeted training for teachers, can foster greater inclusion of students with ADHD in the school setting. Full article