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Opis: The growing trend of aging populations globally has increased the interest in nature-based virtual reality (NBVR) as a non-pharmacological intervention with potential support for the emotional and cognitive health of older adults. The review summarized nine studies identified through searching in PubMed and Web of Science. NBVR, delivered via head-mounted display (HMD) to simulate natural environments (e.g., forests/gardens) and studies consistently found NBVR was experienced with lower levels of stress and anxiety, improved mood, and greater cognitive engagement, particularly in individuals who have limited access to ‘real’ nature. Participants described the NBVR as calming or having some emotional restoration, before emphasizing possible social or motivational benefits. Despite the positive emotional outcomes, we do not adequately understand the mechanisms of NBVR on stress, anxiety, mood, and cognition. Most studies also used small, relatively homogenous samples, based heavily on self-report data, with a limited use of physiological measures. Regardless of the limitations, NBVR is compelling and appears to have the potential for a replicable, low cost intervention. Future research should examine larger and more diverse groups of older adults, including some based on cultural, socioeconomic, cognitive, and physical variations and experience with digital technology and nature, to support greater generalizability of the research. NBVR use should not be perceived as a substitute for real nature, but rather a supportive option for people who have lower access to outdoor nature environments.
Ključne besede: simulated natural environments, cognitive engagement, stress reduction, immersive technology, non-pharmacological interventions, nature connectedness, gerontechnology
Objavljeno v ReVIS: 15.01.2026; Ogledov: 499; Prenosov: 4
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Opis: Central and Eastern Europe continue to generate incremental innovations, slow rates of technology commercialization, and exhibit limited public-private collaboration in research and development. This paper examines the role of cluster organizations as intermediaries, particularly in bridging the knowledge transfer gap between industry and research. Employing qualitative comparative analysis methodology, this exploratory paper highlights the conditions that foster industry-driven collaboration. As a mixed research method that is novel to cluster research, it provides a fresh perspective on how companies establish and maintain connections with research centers. The analysis investigates the associations between the hindering and facilitating factors of cooperation within cluster organizations (conditions) and the prevalence of business-initiated collaboration with research organizations (outcome). The results indicate that structural, socio-behavioral and power dynamics factors influence the patterns of cooperation between these two types of actors. However, to contribute to the advancement and continuity of these relationships, intermediary actors should prioritize addressing the power imbalances to secure strategic cooperation that can lead to regional structural and systemic transformations. The results provide evidence for policy implications, emphasizing the importance of simplifying early-stage technology transfer procedures and reducing administrative obstacles to enhance clusters’ mediator role in an innovation system.
Ključne besede: cluster organizations, industry, research organizations, fuzzy set, qualitative comparative analysis, innovation collaboration
Objavljeno v ReVIS: 15.01.2026; Ogledov: 591; Prenosov: 3
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Opis: Abstract: This paper explores the key challenges and enabling factors in the implementation of telemedicine services in rural and low-resource settings, with particular focus on older adults, focusing particularly on how best practices can be adapted to overcome the digital divide. Drawing from a structured literature review using the Semantic Scholar corpus, this study synthesizes findings from 25 empirical studies selected from a total of 920 unique records, based on clear inclusion criteria, narrowing the scope for deeper qualitative and thematic insights across multiple countries and healthcare contexts. The findings highlight infrastructural barriers, provider and patient-related challenges, and resource constraints, while also identifying technological solutions, capacity-building initiatives, and community engagement strategies as critical enablers. Recommendations are made for future development of telemedicine systems tailored to the specific needs of underserved rural populations.
Ključne besede: telemedicine, healthcare informatics, digital inclusion, social systems, technology adoption
Objavljeno v ReVIS: 15.01.2026; Ogledov: 641; Prenosov: 4
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Opis: In this article, models for prediction of surface hardness for SLM specimens are presented. In experiments, EOS Maraging Steel MS1 was processed using EOS M 290 3D printer via selective laser melting (SLM). To predict hardness of SLM specimens, several machine learning methods were applied, including genetic programming, neural network, multiple regression, k-nearest neighbors, support vector machine, logistic regression, and random forest. In the research, fractal geometry was used to characterize the complexity of SLM-shaped microstructures. It was found that fractal geometry combined with machine learning techniques together greatly improved our comprehension of the intricacies of surface analysis and provided highly efficient predictions. All the applied algorithms exhibited predictability above 90%, with the best average result of 98.7% for genetic programming.
Ključne besede: additive manufacturing, SLM, machine learning, hardness prediction, fractal geometry
Objavljeno v ReVIS: 15.01.2026; Ogledov: 489; Prenosov: 4
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Opis: Aging is a complex and dynamic process that, despite its naturalness, represents one of the greatest challenges of modern medicine. With advancing age, factors for the development of numerous chronic diseases appear, such as cardiovascular diseases, diabetes, cancer and dementia. Understanding, monitoring and potentially slowing down these processes is becoming a key task of longevity science. Early detection of changes with aging plays a key role in this, as it allows for timely intervention, more effective treatment, improvement of quality of life and reduction of costs for the healthcare system. An important element of early diagnostics is individualized approaches based on the use of advanced technologies for monitoring biomarkers of aging. In the last decade, we have witnessed the rapid development of systems that use automated, invasive or non-invasive , and often continuous monitoring of various biomarkers . These include wearable devices, microfluidic and " lab -on-a- chip " systems, optical sensors and artificial intelligence that analyze biological data in real time. Such technologies are used to shift from classical reactive medicine to a proactive, personalized approach to health and longevity. The article presents known molecular, cellular and physiological biomarkers of aging, an overview of selected technologies for monitoring biomarkers of aging. We will focus on analyzing their reliability, clinical utility, and the difference between technologies that offer evidence-based value to the user and those that may lead to incorrect interpretations or decisions due to unreliable or misleading data.
Ključne besede: biomarkers of aging, monitoring technologies, preventive medicine, artificial intelligence in healthcare, longevity, personalized health interventions
Objavljeno v ReVIS: 15.01.2026; Ogledov: 599; Prenosov: 2
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