Search Results (715)

Extreme heat poses growing health risks in tropical regions, yet public perception of this threat remains understudied in the Caribbean. This study examines how residents in Puerto Rico perceived heat-related health risks and how these perceptions relate to vulnerability and protective behaviors during the extreme heat events of the summer of 2020. We conducted a cross-sectional telephone survey of 500 adults across metropolitan and non-metropolitan areas of Puerto Rico, using stratified probability sampling. The questionnaire assessed heat risk perception, sociodemographic characteristics, health status, prior heat exposure, and heat-related behaviors. While most participants expressed concern about climate change and high temperatures, fewer than half perceived heat as a high level of personal health risk. Higher levels of risk perception were significantly associated with being male, aged 50–64, unemployed, and in fair health, having multiple chronic conditions, and prior experience with heat-related symptoms. Those with symptoms were nearly five times more likely to report high levels of risk perception (OR = 4.94, 95% CI: 2.93–8.34). In contrast, older adults (65+), despite their higher level of vulnerability, reported lower levels of risk perception and fewer symptoms. Nighttime heat exposure was widespread and strongly associated with heat-related symptoms. Common coping strategies included the use of fans and air conditioning, though economic constraints and infrastructure instability limited access. The findings highlight the disparity between actual and perceived vulnerability, particularly among older adults. Public health strategies should focus on risk communication tailored to vulnerable groups and address barriers to heat adaptation. Strengthening heat resilience in Puerto Rico requires improved infrastructure, equitable access to cooling, and targeted outreach. Full article

Extreme heat is a pressing public health threat. This study assesses and describes the interrelationships between beliefs about heat waves, individuals’ precautionary behaviors during heat waves, and demographic factors. In May 2022, we surveyed 1051 residents (aged 25–90 years) in Southern Spain, a region that experiences frequent heat waves. We found that many participants engaged in heat wave avoidance (80.5%, e.g., spending more time indoors), impact reduction (63.7%, e.g., drinking more water), or prosocial behavior (31.6%, e.g., helping others). However, one in four (25.9%) respondents also indicated that they personally do not need to worry about heat waves. Heat wave beliefs and behaviors were modestly correlated with demographic characteristics. Individuals who view themselves as less vulnerable to heat-related health risks (“impervious” beliefs) were less likely to report altering their behavior during heat waves. Public health efforts aiming to change behavior during heat waves may anticipate “impervious” beliefs and demographic differences in risk perception and heat-related behaviors. Full article

The growing integration of technology in education has heightened awareness of global risks, such as the spread of disinformation. This awareness is vital for fostering the well-being of individuals, especially teenagers, by promoting critical thinking and responsible digital practices. By cultivating these skills, sustainable education empowers individuals to identify potential threats, protect themselves, and advocate for informed, positive change. As part of a European project, this study aims to analyze the current level of awareness among secondary school students (12 to 17) and their teachers. Differences between both are analyzed in how they deal with disinformation in terms of (1) perceptions, (2) feelings and practices, and (3) knowledge and management. A quantitative approach was adopted for this study, which surveyed 1186 minors and 166 teachers. The analysis was based on non-parametric statistics; the Mann–Whitney U statistic was applied as the appropriate measure for comparing independent samples (teachers and students) with a non-normal distribution (p < 0.05). The results were surprising in that they highlighted that minors were more expert than expected in their use of technology and their awareness of the risks of disinformation. These conclusions make it clear that technological tools have the potential to raise awareness of the dangers of disinformation and improve the sustainability of education. Full article

Pesticide residues in fruits and vegetables pose a serious threat to food safety. Traditional detection methods have defects such as complex operation, high cost, and long detection time. Therefore, it is of great significance to develop rapid, non-destructive, and efficient detection technologies and equipment. In recent years, the combination of spectroscopic techniques and imaging technologies with machine learning algorithms has developed rapidly, providing a new attempt to solve this problem. This review focuses on the research progress of the combination of spectroscopic techniques (near-infrared spectroscopy (NIRS), hyperspectral imaging technology (HSI), surface-enhanced Raman scattering (SERS), laser-induced breakdown spectroscopy (LIBS), and imaging techniques (visible light (VIS) imaging, NIRS imaging, HSI technology, terahertz imaging) with machine learning algorithms in the detection of pesticide residues in fruits and vegetables. It also explores the huge challenges faced by the application of spectroscopic and imaging technologies combined with machine learning algorithms in the intelligent perception of pesticide residues in fruits and vegetables: the performance of machine learning models requires further enhancement, the fusion of imaging and spectral data presents technical difficulties, and the commercialization of hardware devices remains underdeveloped. This review has proposed an innovative method that integrates spectral and image data, enhancing the accuracy of pesticide residue detection through the construction of interpretable machine learning algorithms, and providing support for the intelligent sensing and analysis of agricultural and food products. Full article

Background: Artificial intelligence (AI) is being increasingly promoted as a means to enhance diagnostic accuracy, to streamline workflows, and to improve overall care quality in primary care. However, empirical evidence on how primary care physicians (PCPs) perceive, engage with, and emotionally respond to AI technologies in everyday clinical settings remains limited. Concerns persist regarding AI’s usability, transparency, and potential impact on professional identity, workload, and the physician–patient relationship. Methods: This qualitative study investigated the lived experiences and perceptions of 28 PCPs practicing in diverse outpatient settings across Germany. Participants were purposively sampled to ensure variation in age, practice characteristics, and digital proficiency. Data were collected through in-depth, semi-structured interviews, which were audio-recorded, transcribed verbatim, and subjected to rigorous thematic analysis employing Mayring’s qualitative content analysis framework. Results: Participants demonstrated a fundamentally ambivalent stance toward AI integration in primary care. Perceived advantages included enhanced diagnostic support, relief from administrative burdens, and facilitation of preventive care. Conversely, physicians reported concerns about workflow disruption due to excessive system prompts, lack of algorithmic transparency, increased cognitive and emotional strain, and perceived threats to clinical autonomy and accountability. The implications for the physician–patient relationship were seen as double-edged: while some believed AI could foster trust through transparent use, others feared depersonalization of care. Crucial prerequisites for successful implementation included transparent and explainable systems, structured training opportunities, clinician involvement in design processes, and seamless integration into clinical routines. Conclusions: Primary care physicians’ engagement with AI is marked by cautious optimism, shaped by both perceived utility and significant concerns. Effective and ethically sound implementation requires co-design approaches that embed clinical expertise, ensure algorithmic transparency, and align AI applications with the realities of primary care workflows. Moreover, foundational AI literacy should be incorporated into undergraduate health professional curricula to equip future clinicians with the competencies necessary for responsible and confident use. These strategies are essential to safeguard professional integrity, support clinician well-being, and maintain the humanistic core of primary care. Full article

This paper introduces the concept of degenerative affordances to explain how social media can unintentionally destabilise family-run influencer businesses. While affordance theory typically highlights the enabling features of technology, the researchers shift the focus to its unintended, risk-laden consequences, particularly within family enterprises where professional and personal identities are deeply entangled. Drawing on platform capitalism, family business research, and intersectional feminist critiques, the researchers develop a theoretical model to examine how social media affordances contribute to role confusion, privacy breaches, and trust erosion. Using a mixed-methods design, the researchers combine narrative interviews (n = 20) with partial least squares structural equation modelling (PLS-SEM) on survey data (n = 320) from family-based influencers. This study’s findings reveal a high explanatory power (R² = 0.934) for how digital platforms mediate entrepreneurial legitimacy through interpersonal trust and role dynamics. Notably, trust emerges as a key mediating mechanism linking social media engagement to perceptions of business legitimacy. This paper advances three core contributions: (1) introducing degenerative affordance as a novel extension of affordance theory; (2) unpacking how digitally mediated role confusion and privacy breaches function as internal threats to legitimacy in family businesses; and (3) problematising the epistemic assumptions embedded in entrepreneurial legitimacy itself. This study’s results call for a rethinking of how digital platforms, family roles, and entrepreneurial identities co-constitute each other under the pressures of visibility, intimacy, and algorithmic governance. The paper concludes with implications for influencer labour regulation, platform accountability, and the ethics of digital family entrepreneurship. Full article

Frequent corn leaf diseases and pests pose serious threats to agricultural production. Traditional manual detection methods suffer from significant limitations in both performance and efficiency. To address this, the present paper proposes a novel biotic condition screening (BCS) model for the detection of corn leaf diseases and pests, called BCS_YOLO, based on the You Only Look Once version 11n (YOLOv11n). The proposed model enables accurate detection and classification of various corn leaf pathologies and pest infestations under challenging agricultural field conditions. It achieves this thanks to three key newly designed modules—a Self-Perception Coordinated Global Attention (SPCGA) module, a High/Low-Frequency Feature Enhancement (HLFFE) module, and a Local Attention Enhancement (LAE) module. The SPCGA module improves the model’s ability to perceive fine-grained targets by fusing multiple attention mechanisms. The HLFFE module adopts a frequency domain separation strategy to strengthen edge delineation and structural detail representation in affected areas. The LAE module effectively improves the model’s discrimination ability between targets and backgrounds through local importance calculation and intensity adjustment mechanisms. Conducted experiments show that BCS_YOLO achieves 78.4%, 73.7%, 76.0%, and 82.0% in $precision$, recall, $F1score$, and $mAP@50$, respectively, representing corresponding improvements of 3.0%, 3.3%, 3.2%, and 4.6% compared to the baseline model (YOLOv11n), while also outperforming the mainstream object detection models. In summary, the proposed BCS_YOLO model provides a practical and scalable solution for efficient detection of corn leaf diseases and pests in complex smart-agriculture scenarios, demonstrating significant theoretical and application value. Full article

Chemical leakage accidents in chemical industrial parks pose significant threats to personnel safety, particularly during evacuation processes, where individual behavior and evacuation strategies have a considerable impact on overall efficiency. This study takes a leakage incident at an alkylation unit as a case study. First, ALOHA5.4.7 software was used to simulate the influence of meteorological conditions across different seasons on the dispersion range of toxic gases, thereby generating an annual comprehensive risk zone distribution map. Subsequently, different evacuation scenarios were constructed in Pathfinder2024.1.0605, with the integration of trigger mechanisms to simulate individual behaviors during evacuation, such as variations in risk perception and peer influence. Furthermore, this study expanded the conventional application scope of Pathfinder—typically limited to small-scale building evacuations—by successfully adapting it for large-scale evacuation simulations in chemical industrial parks. The feasibility of such simulations was thereby demonstrated, highlighting the software’s potential. According to the simulation results, exit configuration, shelter placement, and individual behavior modeling significantly affect the total evacuation time. This study provides both theoretical insights and practical guidance for emergency response planning in chemical industrial parks. Full article

Children’s safety, well-being and inclusion in the school environment can be severely impacted by social isolation and bullying. This study examined these threats in a sample of 14 group-classes (291 students) from four different primary education schools. A total of 44 special educational needs (SEN) students and 44 students without SEN were selected. The social network structure of each group-class was analysed, as well as the number of friendship ties, the degree of emotional well-being and social participation (both inside and outside of the school), and the possible cases of bullying. The results show a significantly greater rate of social rejection, emotional distress and risk of exclusion in SEN students with respect to their peers, as well as a considerably higher perception of bullying (38.6% vs. 4.8%). The SEN students who reported bullying were mostly schooled in social networks with a more segregated and fragmented structure. Moreover, the mean value obtained in these groups was lower for all the analysed indicators, although the differences were not statistically significant. These data support the idea that the social capital of the group class could influence the prevention of violence and bullying towards SEN students. However, further studies with larger samples are needed to confirm this. Lastly, strategies to promote the social inclusion of SEN students in primary education schools are discussed. Full article

Coastal forests in Bangladesh provide various essential ecosystem services. However, these face severe threats from deforestation, land-use changes, and climate change. Understanding community perceptions of these services and their willingness to support restoration is crucial for effective conservation strategies. To analyze these, this study employs machine learning on survey data collected from Chakaria and Moheshkhali Upazilas of Cox’s Bazar District. Gradient Boosting Machine (GBM) model was used to identify key predictors of restoration willingness and compared with Random Forest (RF) and Generalized Linear Model (GLM). Proximity to forests shapes community priorities with stronger support for restoration among those living near the forest. Higher perception levels were linked to various ecosystem services provided by the forest, while forest dependence, age, and education also influenced perception with education and age showing strong negative correlations. The GBM model outperformed RF and the GLM in predicting restoration willingness due to its ability to capture complex relationships. The perceived importance of provisioning and supporting services and restoration awareness influenced willingness, accounting for 55.56% of the variation. Willingness was also shaped by income, forest dependency and awareness. Overall, this study leverages machine learning to align conservation efforts with socio-economic priorities, ensuring the resilience of Bangladesh’s coastal ecosystems. Full article

Background: Antimicrobial resistance (AMR) is a global threat that affects humans, animals, plants, the environment, societies, and economies—requiring urgent coordinated action. In May 2015, the World Health Assembly (WHA) adopted the Global Action Plan (GAP) on AMR, urging member states to develop and implement their own National Action Plans (NAPs) using a One Health approach. Objective: Both South Africa and Eswatini have developed NAPs and are currently in the implementation phase. However, no study has explored policymakers’ perceptions regarding NAP implementation particularly concerning coordination, accountability, resourcing, regulation and ownership. Methods: This qualitative study employed a narrative approach to explore these perceptions in South Africa and Eswatini. A total of 36 key informants were recruited using purposive and snowball sampling methods. Data was collected between November 2018 and March 2019 and transcribed verbatim. Results: Findings revealed that while governance structures for implementing NAPs exist in South Africa and Eswatini, several critical areas require urgent attention. These include limited accountability across One Health sectors, the absence of dedicated national budgets for NAP implementation, poor intra- and inter- ministerial coordination, weak medicine regulation and enforcement, and delayed multisectoral ownership of the NAPs. Conclusions: To address AMR effectively, both countries must allocate dedicated budgets, improve multisectoral integration, and strengthen regulatory frameworks regarding antimicrobial access and use across all One Health sectors. A firm commitment from all sectors is required—not just formal endorsement of the NAPs—to ensure sustainable implementation and ownership. Full article

Against the backdrop of evolving global climate patterns, the frequency and intensity of extreme weather events have increased significantly, posing unprecedented threats to agricultural production. This change has particularly profound impacts on agricultural systems in developing countries, making the enhancement of farmers’ capacity to withstand extreme weather events a crucial component for achieving sustainable agricultural development. As an essential safeguard for agricultural production, agricultural insurance plays an indispensable role in risk management. However, a pronounced gap persists between policy aspirations and actual adoption rates among farmers in developing economies. This study employs the integrated theory of planned behavior (TPB) and protection motivation theory (PMT) to construct an analytical framework incorporating psychological, socio-cultural, and risk-perception factors. Using Jiangsu Province—a representative high-risk agricultural region in China—as a case study, we administered 608 structured questionnaires to farmers. Structural equation modeling was applied to identify determinants influencing insurance adoption decisions. The findings reveal that farmers’ agricultural insurance purchase decisions are influenced by multiple factors. At the individual level, risk perception promotes purchase intention by activating protection motivation, while cost–benefit assessment enables farmers to make rational evaluations. At the social level, subjective norms can significantly enhance farmers’ purchase intention. Further analysis indicates that perceived severity indirectly enhances purchase intention by positively influencing attitude, while response costs negatively affect purchase intention by weakening perceived behavior control. Although challenges such as cognitive gaps and product mismatch exist in the intention-behavior transition, institutional trust can effectively mitigate these issues. It not only strengthens the positive impact of psychological factors on purchase intention, but also significantly facilitates the transformation of purchase intention into actual behavior. To promote targeted policy interventions for agricultural insurance, we propose corresponding policy recommendations from the perspective of public intervention based on the research findings. Full article

This study examines how employees perceive technology-based demands during the digital transformation process and how these perceptions affect job performance. The research utilized data obtained from 388 experts in the accounting and financial reporting profession, a knowledge-intensive field that heavily employs new technologies (e.g., ERP systems, digital audit tools). The data collected through a convenience sampling method was analyzed using SPSS 27 and SmartPLS 4 software. The findings reveal that the direct effect of technostress on job performance is not significant; however, this stress indirectly contributes to performance through techno-eustress. In this study, techno-eustress refers to the cognitive appraisal of technology-related demands as development-enhancing challenges rather than threats. This concept is theoretically grounded in the broader eustress framework, which views stressors as potentially motivating and growth-promoting when positively interpreted. The model is based on Cognitive Evaluation Theory, the Job Demands–Resources Model, and Self-Determination Theory. This study demonstrates that digital transformation can promote not only operational improvements but also organizational resilience by enhancing employees’ psychological resources and adaptive capacities. By highlighting the mediating role of techno-eustress, this research offers a nuanced perspective on how human-centered cognitive mechanisms can strategically support performance and sustainability in the face of technological disruption—an increasingly relevant area for organizations striving to thrive amid uncertainty. Full article

Global warming is leading to an increase in extreme-temperature events, posing a significant threat to crop productivity and global food security. Plants have evolved sophisticated mechanisms to perceive and respond to both heat and cold stress. While these mechanisms share certain similarities, they also exhibit distinct differences, enabling plants to effectively cope with extreme temperatures. This review summarizes recent findings on the mechanisms underlying plant perception and response to extreme temperature stresses. Additionally, we compare the signaling pathways for heat and cold stress in plants and discuss the remaining challenges in the field. Finally, we address unresolved issues and propose future directions. Full article

Global biodiversity losses continue despite intensive conservation efforts. Many mammal species are understudied due to their specialized ecological niches. One such species is the Philippine colugo (Cynocephalus volans), a nocturnal endemic species in the Philippines. In this study, we utilized Local Ecological Knowledge (LEK) to obtain baseline information on species knowledge, attitudes, population status, and threats. Between June and September 2023, we interviewed 471 residents across all villages in Anda, Bohol. The majority of local people recognized the species and had witnessed it in Anda, occasionally near households. Residents have limited knowledge of colugo diet and distribution, which they get primarily through word-of-mouth and personal experience. The species is perceived as neutral, but the willingness to conserve it is high. Although the Philippine colugo population seems to be present in several villages in Anda, one-fourth of the respondents believe it is declining. We identified hunting for consumption as the main threat to the colugo population in Anda, which, together with other threats, may corroborate this result. We recommend actively involving male farmers in colugo population monitoring and behavioral observations, as well as investigating the drivers and importance of colugo meat consumption among residents to design a proper conservation strategy. Full article