Search Results (60,279)

Integrated circuits are the core of a cyber-physical system, where tens of billions of components are integrated into a tiny silicon chip to conduct complex functions. To maximize utilities, the design and manufacturing life cycle of integrated circuits rely on numerous untrustworthy third parties, forming a global supply chain model. At the same time, this model produces unpredictable and catastrophic issues, threatening the security of individuals and countries. As for guaranteeing the security of ultra-highly integrated chips, detecting slight abnormalities caused by malicious behavior in the current and voltage is challenging, as is achieving computability within a reasonable time and obtaining a golden reference chip; however, artificial intelligence can make everything possible. For the first time, this paper presents a systematic review of artificial-intelligence-based integrated circuit security approaches, focusing on the latest attack and defense strategies. First, the security threats of integrated circuits are analyzed. For one of several key threats to integrated circuits, hardware Trojans, existing attack models are divided into several categories and discussed in detail. Then, for summarizing and comparing the numerous existing artificial-intelligence-based defense strategies, traditional and advanced artificial-intelligence-based approaches are listed. Finally, open issues on artificial-intelligence-based integrated circuit security are discussed from three perspectives: in-depth exploration of hardware Trojans, combination of artificial intelligence, and security strategies involving the entire life cycle. Based on the rapid development of artificial intelligence and the initial successful combination with integrated circuit security, this paper offers a glimpse into their intriguing intersection, aiming to draw greater attention to these issues. Full article

With its unique climate and geographical advantages, Yunnan Province in China has become one of the country’s most important citrus-growing regions. However, the dense foliage and large fruit size of citrus trees often result in significant occlusion, and the fluctuating light intensity further complicates accurate assessment of fruit maturity. To address these challenges, this study proposes an improved model based on YOLOv8, named ORD-YOLO, for citrus fruit maturity detection. To enhance the model’s robustness in complex environments, several key improvements have been introduced. First, the standard convolution operations are replaced with Omni-Dimensional Dynamic Convolution (ODConv) to improve feature extraction capabilities. Second, the feature fusion process is optimized and inference speed is increased by integrating a Re-parameterizable Generalized Feature Pyramid Network (RepGFPN). Third, the detection head is redesigned using a Dynamic Head structure that leverages dynamic attention mechanisms to enhance key feature perception. Additionally, the loss function is optimized using InnerDIoU to improve object localization accuracy. Experimental results demonstrate that the enhanced ORD-YOLO model achieves a precision of 93.83%, a recall of 91.62%, and a mean Average Precision (mAP) of 96.92%, representing improvements of 4.66%, 3.3%, and 3%, respectively, over the original YOLOv8 model. ORD-YOLO not only maintains stable and accurate citrus fruit maturity recognition under complex backgrounds, but also significantly reduces misjudgment caused by manual assessments. Furthermore, the model enables real-time, non-destructive detection. When deployed on harvesting robots, it can substantially increase picking efficiency and reduce post-maturity fruit rot due to delayed harvesting. These advancements contribute meaningfully to the quality improvement, efficiency enhancement, and digital transformation of the citrus industry. Full article

This study examines the impact of personal remittances on housing prices in European Union (EU) countries, while also accounting for a broader set of macroeconomic, demographic, and structural variables. Using annual data for 27 EU countries from 2007 to 2022, we employ a comprehensive panel econometric approach, including cross-sectional dependence tests, second-generation unit root tests, pooled mean group–autoregressive distributed lag (PMG-ARDL) estimation, and panel causality tests, to capture both short- and long-term dynamics. Our findings confirm that remittances significantly and positively influence long-term housing price levels, underscoring their relevance as a demand-side driver. Other key variables such as net migration, GDP, travel credit to GDP, economic freedom, and real effective exchange rates also contribute to housing price movements, while supply-side indicators, including production in construction and building permits, exert moderating effects. Moreover, real interest rates are shown to have a significant long-term negative effect on property prices. The analysis reveals key causal links from remittances, FDI, and net migration to housing prices, highlighting their structural and predictive roles. Bidirectional causality between economic freedom, housing output, and prices indicates reinforcing feedback effects. These findings position remittances as both a development tool and a key indicator of real estate dynamics. The study highlights complex interactions between international financial flows, demographic pressures, and domestic economic conditions and the need for policymakers to consider remittances and migrant investments in real estate strategies. These findings offer important implications for policymakers seeking to balance housing affordability, investment, and economic resilience in the EU context and key insights into the complexity of economic factors and real estate prices. Importantly, the analysis identifies several causal relationships, notably from remittances, FDI, and net migration toward housing prices, underscoring their predictive and structural importance. Bidirectional causality between economic freedom and house prices, as well as between housing output and pricing, reflects feedback mechanisms that further reinforce market dynamics. These results position remittances not only as a developmental instrument but also as a key signal for real estate market performance in recipient economies. Full article

The use of remote sensing technologies for mapping forest fires has experienced significant growth in recent decades, driven by advancements in remote sensors, processing platforms, and artificial intelligence algorithms. This study presents a review of 192 scientific articles published between 1990 and 2024, selected using PRISMA criteria from the Scopus database. Trends in the use of active and passive sensors, spectral indices, software, and processing platforms as well as machine learning and deep learning approaches are analyzed. Bibliometric analysis reveals a concentration of publications in Northern Hemisphere countries such as the United States, Spain, and China as well as in Brazil in the Southern Hemisphere, with sustained growth since 2015. Additionally, the publishers, journals, and authors with the highest scientific output are identified. The normalized burn ratio (NBR) and the normalized difference vegetation index (NDVI) were the most frequently used indices in fire mapping, while random forest (RF) and convolutional neural networks (CNN) were prominent among the applied algorithms. Finally, the main technological and methodological limitations as well as emerging opportunities to enhance fire detection, monitoring, and prediction in various regions are discussed. This review provides a foundation for future research in remote sensing applied to fire management. Full article

Obstructive sleep apnea syndrome (OSAS) is a prevalent disorder with significant systemic and oral health consequences. This narrative review synthesizes the current knowledge on the interplay between dental health and sleep apnea, highlighting the expanding role of dentists in the screening, early detection, and management of OSAS. Validated questionnaires, anatomical assessments, and anthropometric measurements have enhanced dentists’ capacity for early screening. However, knowledge and training gaps remain, particularly in low- and middle-income countries. Dentists are uniquely positioned to identify anatomical and oral risk factors, facilitate referrals for diagnosis, and provide therapeutic interventions such as oral appliance therapy. Interdisciplinary collaboration between dental and medical professionals is essential to improve early detection, treatment outcomes, and patient quality of life. Enhancing education, standardizing protocols, and integrating dentists into multidisciplinary care pathways are critical steps for advancing the management of sleep apnea. Full article

The COVID-19 pandemic exacerbated mental illness, accelerated cognitive decline, and deepened social inequalities. In low and middle-income countries (LMIC) such as Panama, it is unclear as to whether, and to what extent, the pandemic lockdowns affected cognitive, mental, and physical health of older adults. This study investigated changes in cognitive function, mental health, and physical health in a sample of Panamanian older adults assessed before and during the pandemic, and examined whether sociodemographic variables were associated with cognition and mental health. Participants completed in-person interviews between 2018 and early 2020 and a follow-up telephone interview between February and May 2021. Repeated measures analyses showed no significant changes in cognitive function or depression; however, participants reported fewer chronic illnesses. Linear regression analysis indicated that higher cognitive function during the pandemic was associated with younger age, higher education, and having sufficient income. An attrition analysis compared participants who completed both interviews to those who were lost to follow-up, revealing that participants who dropped out of the study had lower socioeconomic status and greater impairment at baseline. These findings highlight the need for targeted support for vulnerable older adults during public health crises. Full article

Background: Plant-based protein supplementation in supporting muscle recovery following resistance exercise remains an area of growing interest, particularly among vegan athletes, as a potential alternative to animal-based proteins. This systematic review aimed to evaluate the effectiveness of plant-based proteins on recovery from resistance exercise-induced muscle damage in healthy young adults. Methods: A systematic and comprehensive search was administered in eight databases up to 1 May 2025, identifying 1407 articles. Following deduplication and screening, 24 studies met the eligibility criteria, including 22 randomized controlled trials and 2 non-randomized studies, with the majority from high income western countries. Results: Interventions primarily involved soy, pea, rice, hemp, potato, and blended plant protein sources, with doses ranging from 15 to 50 g, typically administered post resistance exercise. Outcomes assessed included muscle protein synthesis (MPS), delayed-onset muscle soreness (DOMS), inflammatory biomarkers, muscle function, and fatigue. The review findings reaffirm that single-source plant proteins generally offer limited benefits compared to animal proteins such as whey, particularly in acute recovery settings, a limitation well-documented consistently in the literature. However, our synthesis highlights that well-formulated plant protein blends (e.g., combinations of pea, rice, and canola) can stimulate MPS at levels comparable to whey when consumed at adequate doses (≥30 g with ~2.5 g leucine). Some studies also reported improvements in subjective recovery outcomes and reductions in muscle damage biomarkers with soy or pea protein. However, overall evidence remains limited by small sample sizes, moderate to high risk of bias, and heterogeneity in intervention protocols, protein formulations, and outcome measures. Risk of bias assessments revealed concerns related to detection and reporting bias in nearly half the studies. Due to clinical and methodological variability, a meta-analysis was not conducted. Conclusion: plant-based proteins particularly in the form of protein blends and when dosed appropriately, may support muscle recovery in resistance-trained individuals and offer a viable alternative to animal-based proteins. However, further high-quality, long-term trials in vegan populations are needed to establish definitive recommendations for plant protein use in sports nutrition. Full article

Digitalization is rapidly reshaping the global construction industry; however, its adoption in developing countries, such as Pakistan, remains limited and uneven. Hence, this study investigates and evaluates the current status of digital technology integration in Pakistan’s construction industry, with a primary focus on key tools, implementation challenges, and necessary policy interventions. Using a three-phase mixed-method approach involving a literature review, expert interviews, and a nationwide survey, this research identifies Building Information Modeling, Geographic Information Systems, and E-Procurement as essential technologies with strong potential to improve transparency, efficiency, and collaboration. However, adoption is hindered by a lack of awareness, limited technical expertise, and the absence of a cohesive national policy. This study also highlights that the private sector shows greater readiness compared to the public sector; however, systemic barriers persist across both sectors. Based on stakeholder insights, a three-part policy strategy was also proposed. This includes establishing a national regulatory framework, investing in capacity-building programs, and providing financial or institutional incentives to encourage the adoption of these measures. The findings emphasize that digitalization is not just a technical upgrade; it represents a pathway to improved governance and more efficient infrastructure delivery. With timely and coordinated policy action, the construction industry in Pakistan can align itself with global innovation trends and move toward a more sustainable and digitally empowered future. Full article

Background/Objectives: Older adults (65+) are the fastest growing age group in Canada, comprising 18.8% of the country’s population. During the COVID-19 pandemic, use of virtual care, including telehealth and tele-medicine, increased dramatically among older adults in Canada who often face higher health risks, mobility limitations, and many barriers to accessing healthcare. Despite the rapid expansion in virtual care, no systematic review has focused specifically on virtual care among older adults in Canada. This review aims to explore the factors influencing virtual care adoption and the experiences of older Canadians during the pandemic through a systematic review. Methods: Conducted in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, the review involved a comprehensive search of PubMed, Scopus, ESCBOHost, and Web of Science on 2 May 2025, yielding 281 unique citations. After screening and applying eligibility criteria, 15 studies employing quantitative, qualitative, or mixed-methods designs, with sample sizes ranging from 15 to 2,282,798, were included and appraised using the Mixed Methods Appraisal Tool (MMAT). Results: The review identified three domains of factors and the ways in which each factor shapes older adults’ virtual care experiences: (1) personal factors influencing virtual care use and demand (e.g., age, education, language, income, immigration status, community sizes), (2) resource factors impacting virtual care adoption (e.g., technology access, support), and (3) varying virtual care experiences among older adults (e.g., in assessment and communication efficacy, privacy, care quality, convenience, safety, and costs). Conclusions: This review highlights the complexities of virtual care engagement among older adults and underscores the need for inclusive, tailored strategies to improve the accessibility and effectiveness of virtual care delivery in both pandemic and post-pandemic contexts. Full article

To address the new challenges of sustainable international trade under the digital transformation, this study aims to explore the relevance and mechanism of the relationship between technological specialization and the sustainable development of digital service trade (focusing on economic sustainability). Based on panel data from 50 economies from 2006 to 2022, the core hypothesis of “whether technological specialization can enhance the sustainable competitiveness of digital service trade by optimizing the global value chain and industrial structure” is verified. An improved index of technological specialization is proposed, breaking through the limitations of traditional indicators, and for the first time introducing the dimension of “knowledge breadth,” reinterpreting the “Leontief Paradox” in the context of digital trade. The study finds that technological specialization significantly enhances the export of digital services, and the effect is more significant in countries with strict intellectual property protection, latecomers in technology, and the European region. Mechanically, this is achieved through improving the position in the global value chain and upgrading the industrial structure. This provides a theoretical breakthrough to solve the technology–trade paradox in the digital age and offers a path for latecomer economies to reconstruct competitive advantages and achieve sustainable development through technological specialization. Full article

Background: Patient safety culture is critical for enhancing the quality and safety of healthcare. Studies in low- and middle-income countries have reported challenges in developing patient safety culture, especially in implementing nonpunitive responses to errors and event reporting. However, evidence from Laos remains limited. Objectives: This study aimed to assess patient safety culture in hospitals in southern Laos, using a validated survey tool to identify strengths and areas of improvement. Methods: A cross-sectional study using purposive sampling was conducted in four provincial and twenty-three district hospitals in southern Laos. Healthcare workers on patient safety committees responded to the Hospital Survey on Patient Safety Culture. The positive response rate was analyzed. Bivariate tests (chi-square/Fisher’s exact) were applied to compare positive response rates between hospital types and professions. Results: A total of 253 valid responses (75.5%) were analyzed. “Organizational Learning–Continuous Improvement” scored over 75% in both provincial and district hospitals. In contrast, “Nonpunitive Response to Error” and “Frequency of Events Reported” were scored <20% on average. Provincial hospitals scored significantly higher than district hospitals in supervisory support and handoffs. Conclusions: This study illustrated strengths in organizational learning while identifying nonpunitive responses and event reporting as critical areas of improvement for hospitals in Laos. To improve patient safety, hospitals in Laos must promote a culture in which errors can be reported without fear of blame. Strengthening leadership support and reporting systems is essential. These findings can inform strategies to enhance patient safety in other low-resource healthcare settings. Full article

Spain is among the European countries with the greatest number of preserved castles and defensive structures—some estimates place the total at around 10,000, the majority of which date back to the medieval period. Yet, surprisingly, many of these fortifications remain uncatalogued and in an advanced state of ruin. This study focuses on a small fortress that has been overlooked by historiography and neglected by public authorities, yet which still stands after seven centuries: the Tower of Lopera, a castle belonging to the so-called Banda Morisca (the frontier of Al-Andalus in the 14th century). Using a combination of digital documentation techniques—namely, portable laser scanning, photogrammetry (via drone and camera), and digital image processing software—we have been able to digitize, geometrize, and document both the surviving architectural remains and their immediate physical environment. Rather than pursuing the latest technological innovations, this methodology prioritizes practical and realistic solutions based on the resources typically available to cultural heritage administrations. Our work serves two main objectives: to demonstrate the viability of applying such tools to this typology of architectural heritage and to conduct a detailed graphic and geometric analysis of the structure. Given the abundance of similar abandoned fortresses in Spain, the findings presented here could inform future heritage documentation strategies on a broader, potentially national, scale. Full article

Research regarding airborne laser scanning (ALS) point cloud semantic segmentation typically revolves around supervised machine learning, which requires time-consuming generation of training data. Therefore, the models are usually trained using one of the benchmarking datasets that cover a small area. Recently, many European countries published classified ALS data, which can be potentially used for training models. However, a review of the classification schemes of these datasets revealed that these schemes vary substantially, therefore limiting their applicability. Thus, our goal was three-fold. First, to develop a common classification scheme that can be applied for the semantic segmentation of various ALS datasets. Second, to unify the classification scheme of existing ALS datasets. Third, to employ them for the training of a classifier that will be able to classify data from different sources and will not require additional training. We propose a classification scheme of four classes: ground and water, vegetation, buildings and bridges, and ‘other’. The developed classifier is trained jointly using ALS data from Austria, Switzerland, and Poland. A test on unseen datasets demonstrates that the achieved intersection over union accuracy varies between 90.0–97.3% for ground and water, 68.0–95.9% for vegetation, 77.6–94.8% for buildings and bridges, and 13.5–52.7% for ‘other’. As a result, we conclude that the developed method generalizes well to previously unseen data. Full article

Sjögren’s Disease (SjD) is an autoimmune disorder characterized by sicca symptoms arising from impaired salivary and lacrimal gland function and accompanying extraglandular involvement. SjD is recognized as an illness of female dominance for which the 2002 American–European Consensus Group Classification Criteria and the American College of Rheumatology/European Alliance of Associations for Rheumatology 2016 classification criteria are utilized for inclusion in clinical trials, and treatment recommendations from countries belonging to the American College of Rheumatology or the European Alliance of Associations for Rheumatology are globally recognized. It is presumed that there are geographical differences among female sufferers, and unique diagnostic criteria and recommendations are used in clinical practice in Japan. In addition to the items included in the classification criteria, several methods to measure saliva secretion, serum biomarkers, and artificial intelligence tools have recently been reported to be useful for the assessment of SjD. While symptomatic therapies including tear drops, artificial saliva, and muscarinic agonists are still the mainstay for treating SjD, several kinds of molecular targeted drugs, such as biological drugs and Janus kinase inhibitors, that are expected to improve the prognosis of SjD have been tested in recent clinical trials. Full article

Turbot Scophthalmus maximus (Linnaeus, 1758) is one of the most valuable and economically important species for the Black Sea countries. In Bulgaria, their numbers are limited and stocks are depleted; therefore, monitoring development and health status is extremely important. Internal helminths are widespread among turbots on the Bulgarian Black Sea coast. However, description of this infection is relatively limited, and they have not been reported in scientific papers. For this purpose, a total of 36 hauls were made at depths from 15 to 90 m, and 65 turbots were examined for intestinal parasites. The present study represents the first report of internal helminths in turbot from Bulgarian marine waters through the spawning season, characterized morphologically based on a microscope observation and molecular identification. Evaluation of laboratory analyses revealed that two different parasites were determined: Bothriocephalus sp. (Müller, 1776) and Hysterothylacium aduncum (Rudolphi, 1802) and that 73.85% of the turbot were infected with one or more parasites. Based on the results, control measures and treatment for the wild population are unrealistic but should be considered for the containment and spread of diseases in aquaculture facilities. Full article