Search Results (1,010)

Organic fruit and vegetable production in the United States is increasingly popular, driven by consumer interest in foods associated with healthier lifestyles and environmentally friendly practices. This review synthesizes evidence on the production of this subsector from 1960 to 2021, using major literature databases (Agricola, ScienceDirect, and Google Scholar), to summarize health and environmental implications, economic importance, research trends, and persistent challenges. The production of fruits and vegetables is frequently reported to exhibit favorable quality and safety attributes, including higher antioxidant capacity and lower levels of cadmium, pesticides, and other chemical residues, supporting its relevance to nutrition and human health. This type of practice is also described as contributing to environmental restoration and preservation through improved soil conditions, reduced reliance on synthetic inputs, enhanced nutrient cycling, and climate-smart benefits such as increased soil organic matter and lower energy intensity. Nevertheless, it faces constraints that increase costs and limit scalability, including high labor demand, limited effectiveness and availability of some organic pest control tools, perishability, post-harvest losses, certification burdens, and market access regulations. Despite these barriers, data indicate growth: from 2007 to 2021, acreage increased by more than 100%, farm-gate value rose from $685 million to $1913 million, and the number of participating farms increased by more than 100%. Moreover, it accounts for 0.9% of the total value of the agricultural production in the U.S. Overall, the outlook for U.S. organic fruit and vegetables is encouraging, supported by expanding consumer demand, government support, and improved conditions for international trade. Full article

Sports drinks are becoming increasingly popular, especially among young, physically active individuals. The influence of acidic drinks on dental restorative materials, including composites and glass ionomers, is an important concern in conservative dentistry. Acidic conditions can cause material degradation, which may reduce their longevity and clinical performance. We aimed to examine the effect of sports drink exposure on the colour stability of composite and glass ionomer materials. This systematic review was conducted based on records published from 1 January 2005 to 31 December 2024, according to the PRISMA statement guidelines, using the databases PubMed, Scopus, Web of Science, and Embase. Based on the established inclusion and exclusion criteria, 17 studies were selected for this review, of which 12 were included in a meta-analysis. The meta-analysis demonstrated a statistically significant increase in colour change (ΔE) for microhybrid composites and nanocomposites after immersion in sports drinks for one month (SMD = 3.04; 95% CI: 0.67 to 5.41, and SMD = 3.00; 95% CI: 1.08 to 4.92, respectively). No such significant differences were observed for nanohybrid materials (SMD = 1.64; p-value = 0.579). Despite the findings of this systematic review, the extent of material degradation observed in in vitro studies cannot be directly translated to clinical oral conditions, as factors such as salivary buffering capacity and variable exposure to sports drinks influence outcomes. Full article

The rapid development of large language models (LLMs), including ChatGPT, Gemini, and Copilot, has led to their increasing use in health communication and patient education. However, their growing popularity raises important concerns about whether the language they generate aligns with recommended readability standards and patient health literacy levels. This review synthesizes evidence on the readability of medical information generated by chatbots using established linguistic readability indices. A comprehensive search of PubMed, Scopus, Web of Science, and Cochrane Library identified 4209 records, from which 140 studies met the eligibility criteria. Across the included publications, 21 chatbots and 14 readability scales were examined, with the Flesch–Kincaid Grade Level and Flesch Reading Ease being the most frequently applied metrics. The results demonstrated substantial variability in readability across chatbot models; however, most texts corresponded to a secondary or early tertiary reading level, exceeding the commonly recommended 8th-grade level for patient-facing materials. ChatGPT-4, Gemini, and Copilot exhibited more consistent readability patterns, whereas ChatGPT-3.5 and Perplexity produced more linguistically complex content. Notably, DeepSeek-V3 and DeepSeek-R1 generated the most accessible responses. The findings suggest that, despite technological advances, AI-generated medical content remains insufficiently readable for general audiences, posing a potential barrier to equitable health communication. These results underscore the need for readability-aware AI design, standardized evaluation frameworks, and future research integrating quantitative readability metrics with patient-level comprehension outcomes. Full article

Background/Objectives: Federated learning (FL) offers a way for healthcare institutions to collaboratively train machine learning models without sharing sensitive patient data. This systematic review aims to comprehensively synthesize the ethical dimensions of FL in healthcare, integrating privacy preservation, algorithmic fairness, governance, and equitable access into a unified analytical framework. The application of FL in healthcare between January 2020 and December 2024 is examined, with a focus on ethical issues such as algorithmic fairness, privacy preservation, governance, and equitable access. Methods: Following PRISMA guidelines, six databases (PubMed, IEEE Xplore, Web of Science, Scopus, ACM Digital Library, and arXiv) were searched. The PROSPERO registration is CRD420251274110. Studies were selected if they described FL implementations in healthcare settings and explicitly discussed ethical considerations. Key data extracted included FL architectures, privacy-preserving mechanisms, such as differential privacy, secure multiparty computation, and encryption, as well as fairness metrics, governance models, and clinical application domains. Results: Out of 3047 records, 38 met the inclusion criteria. The most popular applications were found in medical imaging and electronic health records, especially in radiology and oncology. Through thematic analysis, four key ethical themes emerged: algorithmic fairness, which addresses differences between clients and attributes; privacy protection through formal guarantees and cryptographic techniques; governance models, which emphasize accountability, transparency, and stakeholder engagement; and equitable distribution of computing resources for institutions with limited resources. Considerable variation was observed in how fairness and privacy trade-offs were evaluated, and only a few studies reported real-world clinical deployment. Conclusions: FL has significant potential to promote ethical AI in healthcare, but advancement will require the development of common fairness standards, workable governance plans, and systems to guarantee fair benefit sharing. Future studies should develop standardized fairness metrics, implement multi-stakeholder governance frameworks, and prioritize real-world clinical validation beyond proof-of-concept implementations. Full article

The emergent concept of the epigenetic inheritance of trauma across multiple generations has gained widespread attention in popular media, arguably at the cost of sufficient critical evaluation. This oversight risks distorting the complex and multifaceted nature of trauma transmission, with potential consequences for affected individuals and the broader society. Specifically, the prevalence of this oversimplified narrative in social work and healthcare settings underscores the need for a clearer and critical understanding of the science. To address this need, this work aims to support social workers and other healthcare workers that are interested in better understanding the biological basis of epigenetics as they integrate emerging research on trauma transmission into their daily practice. The paper first introduces fundamental concepts in epigenetics for a non-expert audience, clarifying key mechanisms that regulate gene activity. Building on this foundation, the authors examine sociocultural and biological models for trauma transmission, based on the current evidence, drawing on historic examples to highlight the strengths and limitations of each model. Ultimately, the authors encourage social workers to bridge both of these perspectives in trauma-informed care to enable social workers to challenge misconceptions about inherited trauma and foster patient empowerment through accurate education and advocacy, promoting more holistic and effective care. Full article

Artificial intelligence technology has increased in popularity in the domain of accounting. Previous studies have focused on analysing the impact of AI integration on accounting in general and on work performance, with few researchers analysing the impact of AI on accounting information. Our study aims to determine the impact of AI on accounting information, on the one hand, and earnings management, on the other, using a bibliometric analysis that examines trends in scientific output. Our analysis was based on the use of the Bibliometrix package of RStudio software. The information is obtained from the “Web of Science” database, which identified 98 articles published in 37 journals that are the subject of our bibliometric analysis for the period 2017–2025. Our study shows that integrating AI into accounting can resolve the problem of information asymmetry, increase the transparency of financial information, and both limit earnings management practices and promote more sophisticated forms of earnings management. The bibliometric results show an increase in scientific output on our topic from 2023 onwards, reaching its peak in 2025. Bibliometric analysis presents productivity over time, identifies the most developed topics and the most cited authors and articles, and reveals the most frequently used keywords. This study provides guidance for future research directions. Full article

Background: The Carnivore Diet (CD) is an almost exclusively animal-based dietary pattern that has gained increasing popularity on social media. Despite numerous health-related claims, a standardized definition is lacking, and scientific evidence regarding the long-term effects of this diet remains unclear. Methods: The literature search for this scoping review was conducted in accordance with PRISMA guidelines (PRISMA-ScR) using the databases PubMed, LIVIVO, Web of Science, and the Cochrane Library. Results: Nine human studies were included. Individual publications reported positive effects of the CD, such as weight reduction, increased satiety, and potential improvements in inflammatory or metabolic markers. At the same time, potential risks of nutrient deficiencies, particularly in vitamins C and D, calcium, magnesium, iodine, and dietary fiber, as well as elevated low-density-lipoprotein (LDL-) and total cholesterol (TC) levels, were identified, along with one case describing a deterioration in health status. Overall, the quality of evidence is very limited due to small sample sizes, short study durations, and the absence of control groups. Conclusions: The CD may offer short-term health benefits but carries substantial risks of nutrient deficiencies, reduced intake of health-promoting phytochemicals, and the development of cardiovascular disease. At this time, long-term adherence to a CD cannot be recommended. Full article

This paper presents a two-stage explainable recommendation system for reciprocal affiliate–seller matching that uses machine learning and data science to handle voluminous data and generate personalized ranking lists for each user. In the first stage, a representation learning model was trained to create dense embeddings for affiliates and sellers, ensuring efficient identification of relevant pairs. In the second stage, a learning-to-rank approach was applied to refine the recommendation list based on user suitability and relevance. Diversity-enhancing reranking (maximal marginal relevance/explicit query aspect diversification) and popularity penalties were also implemented, and their effects on accuracy and provider-side diversity were quantified. Model interpretability techniques were used to identify which features affect a recommendation. The system was evaluated on a fully synthetic dataset that mimics the high-level statistics generated by affiliate platforms, and the results were compared against classical baselines (ALS, Bayesian personalized ranking) and ablated variants of the proposed model. While the reported ranking metrics (e.g., normalized discounted cumulative gain at 10 (NDCG@10)) are close to 1.0 under controlled conditions, potential overfitting, synthetic data limitations, and the need for further validation on real-world datasets are addressed. Attributions based on Shapley additive explanations were computed offline for the ranking model and excluded from the online latency budget, which was dominated by approximate nearest neighbors-based retrieval and listwise ranking. Our work demonstrates that high top-K accuracy, diversity-aware reranking, and post hoc explainability can be integrated within a single recommendation pipeline. While initially validated under synthetic evaluation, the pipeline was further assessed on a public real-world behavioral dataset, highlighting deployment challenges in affiliate–seller platforms and revealing practical constraints related to incomplete metadata. Full article

Game-based learning has become an increasingly popular educational methodology due to its ability to enhance student interest and engagement. The aim of this study was to analyze the effect of game-based learning on motivation, self-efficacy, and academic performance in Natural Sciences learning. A systematic review and meta-analytic methodology was employed, following PRISMA guidelines. For this purpose, the databases consulted were Web of Science and Scopus, from which a total of 234 documents were retrieved and reduced to 15 studies after rigorously applying the established eligibility criteria. These studies were included in the systematic review and meta-analysis to ensure the validity and relevance of the meta-analytic findings. The meta-analytic results revealed a very strong and highly significant positive effect across all subgroups, benefiting the experimental groups (Z = 6.29; p < 0.00001). In conclusion, the implementation of game-based learning has a positive impact on motivation, self-efficacy, and academic performance in the teaching and learning of Natural Sciences content. Therefore, its incorporation into pedagogical practices represents an opportunity to strengthen student engagement and promote more meaningful learning. Full article

With the growing popularity of DevOps culture among companies and the corresponding increase in Microservices architecture development—both known to boost productivity and efficiency in software development—an increasing number of organizations are aiming to integrate them. Implementing DevOps culture and best practices can be challenging, but it is increasingly important as software applications become more robust and complex, and performance is considered essential by end users. By following the Design Science Research methodology, this paper proposes an iterative framework that closely follows the recommended DevOps practices, validated with the assistance of expert interviews, for implementing DevOps practices into Microservices architecture software development, while also offering a series of tools that serve as a base guideline for anyone following this framework, in the form of a theoretical use case. Therefore, this paper provides organizations with a guideline for adapting DevOps and offers organizations already using this methodology a framework to potentially enhance their established practices. Full article

With the advancement of digital technology, serious games have become an essential tool for disseminating and educating individuals about cultural heritage. However, systematic empirical research remains limited with respect to how visual elements influence users’ cognitive and emotional engagement through interactive behaviors. Using the “Macau Historic Centre Science Popularization System” as a case study, this mixed-methods study investigates the mechanisms by which visual elements affect user experience and learning outcomes in digital interactive environments. Eye-tracking data, behavioral logs, questionnaires, and semi-structured interviews from 30 participants were collected to examine the impact of visual elements on cognitive resource allocation and emotional engagement. The results indicate that the game intervention significantly enhanced participants’ retention and comprehension of cultural knowledge. Eye-tracking data showed that props, text boxes, historic buildings, and the architectural light and shadow shows (as incentive feedback elements) had the highest total fixation duration (TFD) and fixation count (FC). Active-interaction visual elements showed a stronger association with emotional arousal and were more likely to elicit high-arousal experiences than passive-interaction elements. The FC of architectural light and shadow shows a positive correlation with positive emotions, immersion, and a sense of accomplishment. Interview findings revealed users’ subjective experiences regarding visual design and narrative immersion. This study proposes an integrated analytical framework linking “visual elements–interaction behaviors–cognition–emotion.” By combining eye-tracking and information dynamics analysis, it enables multidimensional measurement of users’ cognitive processes and emotional responses, providing empirical evidence to inform visual design, interaction mechanisms, and incentive strategies in serious games for cultural heritage. Full article

With the rise in experience economy and the popularization of digital technology, user-generated content (UGC) has become a core data source for understanding tourist needs and evaluating the service quality of venues. As a landmark venue that combines science education, interactive experience, and landscape viewing, the service quality of the Macau Science Center directly affects tourists’ travel experience and word-of-mouth dissemination. However, existing studies mostly rely on traditional questionnaire surveys and lack multi-technology collaborative analysis. In order to accurately identify the factors affecting satisfaction, this study uses 788 valid UGC data from five major platforms, namely Google Maps reviews, TripAdvisor, Sina Weibo, Xiaohongshu (Rednote), and Ctrip, from January 2023 to November 2025. It integrates word frequency analysis, semantic network analysis, latent Dirichlet allocation (LDA) topic modeling, and Valence Aware Dictionary and sEntiment Reasoner (VADER) sentiment computing to construct a systematic research framework. The study found that (1) the core attention dimensions of users cover the needs of parent–child and family visits, exhibitions and interactive experiences, ticketing and consumption services, surrounding environment and landscape, emotional evaluation, and recommendation intention. (2) The keyword association network has gradually developed from a loose network in the early stage to a comprehensive experience-dense network. (3) LDA analysis identified five main potential demand themes: comprehensive visiting experience and scenario integration, parent–child interaction and characteristic scenario experience, core venue facilities and ticketing services, visiting value and emotional evaluation, and transportation and surrounding landscapes. (4) User emotions were predominantly positive, accounting for 82.7%, while negative emotions were concentrated in local service details, and the emotional scores showed a fluctuating upward trend. This study provides targeted suggestions for the service optimization of the Macau Science Center and also provides a methodological reference for UGC-driven research in similar cultural venues. Full article

Lead climbing and bouldering have witnessed a surge in popularity, particularly highlighted by their inclusion in prestigious events like the 2020 Summer Olympic Games in Tokyo. This systematic review aims to comprehensively assess existing literature on injury risk factors and prevention programs specific to these disciplines. We systematically searched PubMed, Web of Science, and SPORTDiscus up to November 2023. Methodological quality was appraised using the Joanna Briggs Institute (JBI) critical appraisal tools. Data synthesis involved qualitative analysis. Of 463 screened records, 7 studies were included, encompassing data from over 4000 climbers. The literature consistently indicates that overuse injuries—particularly to the fingers and shoulders—are more prevalent than acute injuries in adult population. However, evidence for specific risk factors is inconclusive and contradictory. Reported associations for higher skill level, age, and use of preventive measures (e.g., taping) were inconsistent across studies. Further research employing rigorous methodologies and long-term follow-up is warranted to elucidate injury mechanisms in lead climbing and bouldering. These investigations are crucial for informing clinical practice and developing sport-specific injury prevention strategies aimed at ensuring the safety and well-being of athletes in these disciplines. Future studies should focus on standardizing injury definitions and assessment methods and explore targeted preventive measures to address the unique risks associated with these sports. Full article

Citizen science approaches for monitoring, and even restoring, coral reefs have grown in popularity though tend to be restricted to those who have taken courses that expose them to the relevant methodologies. Now that cheap (~10 USD), waterproof pouches for smart phones are widely available, there is the potential for mass acquisition of coral reef images by non-scientists. Furthermore, with the emergence of better machine-learning-based image classification approaches, high-quality data can be extracted from low-resolution images (provided that key benthic organisms, namely corals, other invertebrates, & algae, can be distinguished). To determine whether informally captured images could yield comparable ecological data to point-intercept + photo-quadrat surveys conducted by highly proficient research divers, we trained an artificial intelligence (AI), CoralNet, with images taken before and during a bleaching event in 2015 in Chagos (Indian Ocean). The overall percent coral covers of the formal, “gold standard” method and the informal, “tourist diver” approach of 38.7 and 35.1%, respectively, were within ~10% of one another; coral bleaching percentages of 30.5 and 31.8%, respectively, were statistically comparable. Although the AI was prone to classifying bleached corals as healthy in ~one-third of cases, the fact that these data could be collected by someone with no knowledge of coral reef ecology might justify this approach in areas where divers or snorkelers have access to waterproof cameras and are keen to document coral reef condition. Full article

Design science research (DSR) has become a popular method in information systems research and has been warmly welcomed in other disciplines as well. The importance of DSR is evident, in terms of its contribution to knowledge, as well as the creation of artefacts to solve problems of common interest. While it has demonstrated a clear methodology for achieving research goals, the philosophical underpinnings are not widely synthesised. There are inconsistencies and voids related to the philosophical aspects of DSR. For example, there is an inconsistent argument among researchers regarding the definition of design science research in the first place. This study analysed six key texts published within the last fifteen years in design science research along with a critical discussion, with the help of the existing literature. Accordingly, the study presents suggestions for the philosophical aspects of DSR. Namely, the definitions related to DSR terms (design, design science, design science research, and research), philosophical aspects (ontology, epistemology, and axiology), and theory development approaches (inductive, deductive, abductive, and retroductive), as well as research strategies were discussed. This is recommended to take as a starting point for a formative discussion of the topic, fine-tuning ideas with a critical eye. Full article