Search Results (56)

Background/Objective: The use of immersive virtual reality (VR) for cognitive training in older adults has shown promising results in recent years. However, the number of well-designed studies remains limited, and variability in methodologies makes it difficult to draw generalizable conclusions. This systematic review aims to examine the effects of VR-based cognitive training in older adults, describe the technological characteristics of these interventions, identify current gaps in the literature, and suggest future research directions. Methods: Following PRISMA guidelines, a search was conducted across major databases (PubMed, PsycINFO, Scopus, ProQuest, ACM, and Web of Science) from 2018 to 2025. The database search identified 156 studies, of which 12 met the inclusion criteria after screening and eligibility assessment. Across these studies, a total of 3202 older adult participants (aged 60 years or older) were included. Interventions varied in duration from 4 to 36 sessions, targeting domains such as memory, executive function, attention, and global cognition. Most interventions were based on cognitive training, with a few employing cognitive stimulation or cognitive rehabilitation approaches. Quality was assessed using the Effective Public Health Practice Project tool. Results: Most studies reported positive effects of VR interventions on cognitive domains such as attention, executive functions, and global cognition. Fewer studies showed improvements in memory. The majority used head-mounted displays connected to computers and custom-built software, often without public access. Sample sizes were generally small, and blinding procedures were often unclear. The average methodological quality was moderate. Conclusions: Immersive VR has potential as an effective tool for cognitive training in older adults. Future research should include larger randomized controlled trials, long-term follow-up, standardized intervention protocols, and the development of accessible software to enable replication and broader application in clinical and community settings. Full article

Spectroscopic observations of Earth-like exoplanets and ultra-faint galaxies–top scientific priorities for the coming decades–involve measuring broadband signals at rates of only a few photons per square meter per hour. This imposes exceptional requirements on the detector performance, necessitating dark currents below 1 e⁻/pixel/kilo second, read noise under 1 e⁻/pixel/frame, and the ability to handle large-format arrays–capabilities that are not yet met by most existing infrared detectors. In addition, spaceborne LiDAR systems require photodetectors with exceptional sensitivity, compact size, low power consumption, and multi-channel capability to facilitate long-range range finding, topographic mapping, and active spectroscopy without increasing the instrument burden. MCT Avalanche photodiodes arrays offer high internal gain, pixelation, and photon-counting performance across SW to MW wavelengths needed for multi-beam and multi-wavelength measurements, marking them as a critical enabling technology for next-generation planetary and Earth science LiDAR missions. This work reports the latest progress in developing Hg_1−xCd_xTe linear-mode e-APDs at premier industrial research institutions, including relevant experimental data, simulations and major project planning. Related studies are summarized to demonstrate the practical and iterative approach for device fabrication, which have a transformative impact on the evolution of this discipline. Full article

This research aims to develop a model for cultivating talents in sustainable food literacy education in Taiwan. The project adopts the professional and theoretical axes of the food industry, sustainable development, and food literacy. The research employs a mixed-method approach, combining qualitative and quantitative techniques, to construct sustainable food literacy assessment indicators for Taiwan. In the first year, through literature analysis and qualitative research, the core content of “sustainable food literacy” in Taiwan was extracted, resulting in four major dimensions with 24 indicator items. Then, using the Fuzzy Delphi method, the indicators were constructed, defining the core content and dimension indicators of sustainable food literacy, which include “sustainable agriculture and production”, “healthy diet and culture”, “green environmental protection and consumption”, and “food social responsibility and ethics”, encompassing a total of 20 indicators. In the second year, based on the dimensions identified in the first year, a sustainable food literacy curriculum was developed. A 10-week quasi-experimental teaching curriculum was conducted for students enrolled in the “Vegetable and Fruit Carving” elective course in two classes of the Department of Food and Beverage Management at Jingwen University of Science and Technology. By comparing the pre-test and post-test scores of students’ sustainable food literacy and their sustainable food works, as well as analyzing student learning portfolios and teacher reflections, it was shown that the curriculum developed in this research significantly enhanced students’ sustainable food literacy and their performance. The results of this two-year study can be used for the assessment of sustainable food literacy talents in Taiwan, contributing both academically and practically. Full article

Urban regeneration, as a key strategy for promoting sustainable development of urban areas, requires innovative digital technologies to address increasingly complex urban challenges in its implementation. With the fast advancement of digital technologies such as artificial intelligence (AI), Internet of Things (IoT), and big data, these technologies have extensively penetrated various dimensions of urban regeneration, from planning and design to implementation and post-operation management, providing new possibilities for improving urban regeneration efficiency and quality. However, the existing literature lacks a systematic evaluation of technology application patterns across different project scales and phases, comprehensive analysis of stakeholder–technology interactions, and quantitative assessment of technology distribution throughout the urban regeneration lifecycle. This research gap limits the in-depth understanding of how digital technologies can better support urban regeneration practices. This study aims to identify and quantify digital technology application patterns across urban regeneration stages, scales, and stakeholder configurations through systematic analysis of 56 high-quality articles from the Scopus and Web of Science databases. Using a mixed-methods approach combining a systematic literature review, bibliometric analysis, and meta-analysis, we categorized seven major digital technology types and analyzed their distribution patterns. Key findings reveal distinct temporal patterns: GIS and BIM/CIM technologies dominate in the pre-urban regeneration (Pre-UR) stage (10% and 12% application proportions, respectively). GIS applications increase significantly to 14% in post-urban regeneration (Post-UR) stage, while AI technology remains underutilized across all phases (2% in Pre-UR, decreasing to 1% in Post-UR). Meta-analysis reveals scale-dependent technology adoption patterns, with different technologies showing varying effectiveness at building-level, district-level, and city-level implementations. Research challenges include stakeholder digital divides, scale-dependent adoption barriers, and phase-specific implementation gaps. This study constructs a multi-dimensional analytical framework for digital technology support in urban regeneration, providing quantitative evidence for optimizing technology selection strategies. The framework offers practical guidance for policymakers and practitioners in developing context-appropriate digital technology deployment strategies for urban regeneration projects. Full article

This study aims to create a reference framework to evaluate the technological capabilities (TCs) of public research centers in Mexico through their characterization, measurement, and statistical analysis for decision making on technological strengthening. Additionally, the study seeks to understand the context in which innovation and linkage activities occur within the research system and highlight the importance of integrating such studies into academic institutions. Using this generic framework, public research centers (PRCs), in addition to identifying weaknesses in the development of capabilities at the organizational level, could determine the level of development at which their TCs are located to address social demands and promote collaboration models between university and industry. To achieve this objective, 228 surveys were carried out per stage among researchers from the PRCs in Mexico. Each stage was composed of one questionnaire. Questionnaire 1 considered aspects of investment capabilities, assimilation, modification, support, and linkage. Questionnaire 2 was used to collect data on scientific productivity based on evaluation criteria established by the National Council of Humanities, Sciences and Technologies (CONAHCyT). The aspects covered included infrastructure, scientific publications, intellectual property, postgraduate programs, and collaborative projects. The results indicate that the majority of Mexican PRCs have developed basic and intermediate TCs, with 77% involved in applied research and technological development, but from the total research projects, only 8% present higher levels of technological maturity. The originality of the study lies in the quantitative measurement of TCs within the Mexican PRCs for the benefit of innovative and high-performance work systems, addressing a gap in the existing literature, and could be extrapolated to other universities of developing countries. Full article

Purpose: Mental health care is limited worldwide, especially for children and adolescents. Moreover, there are barriers to using mental health services for children and adolescents, including a shortage of standardized training programs and the subsequent workforce. To solve this problem, Japan adopted problem-based learning (PBL) to enhance standardized medical education about child and adolescent psychiatry (CAP). This preliminary study aimed to evaluate online CAP studies at Nagoya University (NU), Japan, with a focus on PBL materials. Design and methods: A descriptive cross-sectional preliminary study was carried out at NU with a questionnaire developed under the Trondheim–Nagoya (TroNA) project by NU and the Norwegian University of Science and Technology (NTNU). The questionnaire, measuring students’ perceptions and understanding of the PBL curriculum and PBL in the CAP, consisted of 15 questions answered on a three-point Likert scale. To compare the PBL CAP delivered online (2021) with the established PBL CAP carried out in person (2019) at NU, an identical questionnaire was used both in 2019 and 2021. Results: The majority of medical students in both in-person (82.5%) and online (91.2%) classes agreed that PBL helped them develop clinical problem-solving skills. In addition, 53.6% of the students in the in-person class and 75.8% of the students in the online class thought PBL enhanced their understanding of CAP. In terms of specific case scenarios, the majority of students in the in-person class (59.8%) and online class (74.7%) agreed that the PBL case helped them understand the importance of a multidisciplinary approach in CAP. Conclusions: Most of the NU medical students were generally satisfied with CAP’s online PBL curriculum. The online PBL CAP curriculum with specific case scenarios can provide medical students with suitable educational means. This preliminary study can to a certain extent provide information relevant for the development of online PBL education in CAP patients and for planning to attract more future doctors to CAP. Full article

Science, technology, engineering, and math (STEM) education is challenged by industries to incorporate business, engineering, and communication experiences to prepare students for workplace success. In this study, we outline an approach—the STEM Oriented Alliance for Research (SOAR)—to enhance student experience by offering interdisciplinary project-based learning (IPBL) for undergraduate students majoring in electrical engineering, communications, and marketing. We examined how students’ disciplinary and cooperative orientations toward learning shifted in response to their experiences in a semester-long interdisciplinary project-based learning experience with authentic industry outputs. Using a multi-method approach, we explored how interdisciplinary projects influenced student experiences in terms of five collaboration abilities: positive interdependence, accountability, promotive interaction, group processing, and social skills. Further, we observed a shift from fixed- to more growth-oriented mindsets, and from a primarily disciplinary to interdisciplinary focus for their future professional work. The outcomes of the SOAR project make clear that providing structure for professional cooperation on interdisciplinary projects can have profound effects on how students learn to cooperate and position themselves as learners. For most SOAR participants, the experience was deeply formative and contributed to their readiness to cooperate and learn within the interdisciplinary and STEM-oriented workforce. Full article

Conducting a literature review is a mandatory initial stage in scientific research on a specific topic. However, this task is becoming much more complicated in certain areas (such as food science and technology) due to the huge increase in the number of scientific publications. Different tools based on artificial intelligence could be very useful for this purpose. This paper addresses this challenge by developing and checking different tools applicated to an emerging topic in food science and technology: “hybrid meat products”. The first tool to be applied was based on Natural Language Processing and was used to select and reduce the initial number of papers obtained from a traditional bibliographic search (using common scientific databases such as Web Science and Scopus) from 938 to 178 (a 87% reduction). The second tool was a project based on the interplay between Retrieval-Augmented Generation (RAG) and LLAMA 3, which was used to answer key questions relating to the topic under review (“hybrid meat products”) but limiting the context to the scientific review obtained after applying the first AI tool. This new strategy for reviewing scientific literature could be a major advance on from the traditional literature review procedure, making it faster, more open, more accessible to everyone, more effective, more objective, and more efficient—all of which help to fulfill the principles of open science. Full article

Peer-led Team Learning (PLTL) is a model of instruction and learning that has been used to address low success rates in various science, technology, engineering, and mathematics (STEM) courses and other fields in higher education. (1) While research conveying the efficacy of this model of instruction remains mixed, this project sought to add to the body of knowledge communicating the benefits of PLTL for STEM achievement. This study examined the experiences of STEM community college transfer students’ engagement in PLTL within their major course of study when a suite of supports was provided. (2) Specifically, study participants were enrolled in degree programs at a four-year rural, regional university in the engineering, computer science, and mathematics (ECSM) fields and were provided social, financial, and academic assistance. Qualitative analysis of the data revealed that with a PLTL component, community college transfer students were more likely to participate, engage, and perform better in coursework given the additional supports. (3) Study participants indicated the community of learners created through PLTL was a primary motivator for continued engagement and progress towards ECSM degree attainment. (4) Implications for practice extend to engagement and retention efforts of STEM students from the community college population Full article

Extreme weather events have led to widespread yield losses and significant global economic damage in recent decades. African agriculture is particularly vulnerable due to its harsh environments and limited adaptation capacity. This systematic review analyzes 96 articles from Web of Science, Science Direct, and Google Scholar, focusing on biophysical studies related to maize in Africa and worldwide. We investigated the observed and projected extreme weather events in Africa, their impacts on maize production, and the approaches used to assess these effects. Our analysis reveals that drought, heatwaves, and floods are major threats to African maize production, impacting yields, suitable cultivation areas, and farmers’ livelihoods. While studies have employed various methods, including field experiments, statistical models, and process-based modeling, African research is often limited by data gaps and technological constraints. We identify three main gaps: (i) lack of reliable long-term experimental and empirical data, (ii) limited access to advanced climate change adaptation technologies, and (iii) insufficient knowledge about specific extreme weather patterns and their interactions with management regimes. This review highlights the urgent need for targeted research in Africa to improve understanding of extreme weather impacts and formulate effective adaptation strategies. We advocate for focused research on data collection, technology transfer, and integration of local knowledge with new technologies to bolster maize resilience and food security in Africa. Full article

In industry 4.0, where the automation and digitalization of entities and processes are fundamental, artificial intelligence (AI) is increasingly becoming a pivotal tool offering innovative solutions in various domains. In this context, nutrition, a critical aspect of public health, is no exception to the fields influenced by the integration of AI technology. This study aims to comprehensively investigate the current landscape of AI in nutrition, providing a deep understanding of the potential of AI, machine learning (ML), and deep learning (DL) in nutrition sciences and highlighting eventual challenges and futuristic directions. A hybrid approach from the systematic literature review (SLR) guidelines and the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines was adopted to systematically analyze the scientific literature from a search of major databases on artificial intelligence in nutrition sciences. A rigorous study selection was conducted using the most appropriate eligibility criteria, followed by a methodological quality assessment ensuring the robustness of the included studies. This review identifies several AI applications in nutrition, spanning smart and personalized nutrition, dietary assessment, food recognition and tracking, predictive modeling for disease prevention, and disease diagnosis and monitoring. The selected studies demonstrated the versatility of machine learning and deep learning techniques in handling complex relationships within nutritional datasets. This study provides a comprehensive overview of the current state of AI applications in nutrition sciences and identifies challenges and opportunities. With the rapid advancement in AI, its integration into nutrition holds significant promise to enhance individual nutritional outcomes and optimize dietary recommendations. Researchers, policymakers, and healthcare professionals can utilize this research to design future projects and support evidence-based decision-making in AI for nutrition and dietary guidance. Full article

The Single-cell Assay for Transposase-Accessible Chromatin with high throughput sequencing (scATAC-seq) has gained increasing popularity in recent years, allowing for chromatin accessibility to be deciphered and gene regulatory networks (GRNs) to be inferred at single-cell resolution. This cutting-edge technology now enables the genome-wide profiling of chromatin accessibility at the cellular level and the capturing of cell-type-specific cis-regulatory elements (CREs) that are masked by cellular heterogeneity in bulk assays. Additionally, it can also facilitate the identification of rare and new cell types based on differences in chromatin accessibility and the charting of cellular developmental trajectories within lineage-related cell clusters. Due to technical challenges and limitations, the data generated from scATAC-seq exhibit unique features, often characterized by high sparsity and noise, even within the same cell type. To address these challenges, various bioinformatic tools have been developed. Furthermore, the application of scATAC-seq in plant science is still in its infancy, with most research focusing on root tissues and model plant species. In this review, we provide an overview of recent progress in scATAC-seq and its application across various fields. We first conduct scATAC-seq in plant science. Next, we highlight the current challenges of scATAC-seq in plant science and major strategies for cell type annotation. Finally, we outline several future directions to exploit scATAC-seq technologies to address critical challenges in plant science, ranging from plant ENCODE(The Encyclopedia of DNA Elements) project construction to GRN inference, to deepen our understanding of the roles of CREs in plant biology. Full article

Despite their known influence in science, technology, engineering, and mathematics (STEM) fields, spatial abilities remain an underassessed aspect of cognition, particularly in educational settings. One explanation could be a lack of affordable, valid instruments for measuring various aspects of spatial ability. We evaluate the validity of a set of public-domain, algorithmically generated two-dimensional rotation items using a sample from the Synthetic Aperture Personality Assessment (SAPA) Project (N = 1,020,195). We examine the psychometric properties of the items and their relationship with various other cognitive abilities and personality traits. In addition, we identify the highest performing college majors and occupations on the 2D rotation items and on a set of 3D rotation items. Findings suggest strong unidimensionality for the 2D rotation items and the presence of lower-order factors which reflect differences across items in mental rotation demands. The highest scoring majors and occupations were similar—but not identical—across the 2D and 3D rotation measures and point to potentially meaningful differences across areas of expertise. Full article

The science of taxonomy, albeit being fundamental for all organismic research, has been underfunded and undervalued for about two generations. We analyze how this could happen, particularly in times of a biodiversity crisis, when we have increased awareness amongst the population and decision makers that knowledge about species we share the planet with is indispensable for finding solutions. We identify five major issues: the habit of holding taxonomy in low esteem; the focus on inappropriate publication metrics in evaluating scientific output; the excessive focus on innovative technology in evaluating scientific relevance; shifting priorities in natural history museums away from their traditional strengths; and changing attitudes towards specimen collecting and increasing legislation regulating collecting and international exchange of specimens. To transform taxonomy into a thriving science again, we urgently suggest significantly increasing baseline funding for permanent positions in taxonomy, particularly in natural history museums; reviving taxonomic research and teaching in universities at the tenured professor level; strongly increasing soft money for integrative taxonomy projects; refraining using journal-based metrics for evaluating individual researchers and scientific output and instead focusing on quality; installing governmental support for open access publishing; focusing digitizing efforts to the most useful parts of collections, freeing resources for improving data quality by improving identifications; requiring natural history museums to focus on collection-based research; and ending the trend of prohibitive legislation towards scientific collecting and international exchange of taxonomic specimens, and instead building legal frameworks supportive of biodiversity research. Full article

The growing concept of Industry 5.0 (IR 5.0) has enhanced the study horizon of the technology-centered Industry 4.0 (IR 4.0) to an intelligent and balanced socioeconomic change powered mutually by people and technologies. The role of humans in the technological revolution is largely focused on IR 5.0, which is already a future trend. IR 4.0’s cyber–physical systems revolution has evolved into IR 5.0, or in other words, from machine-to-machine integration to human-to-machine integration, which is radically altering how people live, work, and interact with one another. Therefore, the current study aims to comprehensively review transformation through industrial revolutions and provide a way forward in the construction industry with the incorporation of IR 5.0. This study has used a narrative-based research methodology in which multiple databases such as Scopus, Web of Sciences, Google Scholar, and Science Direct have been utilized for extracting articles related to the subject area of the current study. Moreover, through narrative-based methodology, which is a generic-based review technique, the information gathered from multiple sources has been summarized and synthesized. The findings of the review indicate that resilience, human-centricity, economic efficiency, and sustainable development are the key characteristics of IR 5.0. Moreover, the adoption of IR 5.0 in the construction industry also faces some major challenges such as a shortage of IR 5.0-related technical skills, investment-hesitancy among investors, security, and cultural concerns for human-to-machine integration, and an unavailability of data for effective decision-making for governments and stakeholders. The study results also highlight that with selective technology adoption, project teams embracing IR 5.0 for improved collaboration and coordination, more environmentally friendly technology adoption through human-to-machine collaboration, and stakeholders leveraging the power of human knowledge and innovative proficiency through machines, reforms can be brought into the construction industry through the incorporation of IR 5.0. It is also important to keep in mind that adopting IR 4.0 is still difficult in some areas and it may seem like achieving IR 5.0 will require years of effort and significant cultural change; however, it needs to be considered right away. The effects of disruptive technologies on Industry 4.0 are covered in several studies; however, IR 5.0 is a novel idea that is still in its early stages, thus its consequences have not been well examined in the construction industry. Therefore, the current study has expanded the body of knowledge on this important subject in detail and has comprehensively explained the transformation by providing a way forward for the adoption of IR 5.0 in the construction industry. Full article