Search Results (3,551)

Pakistan’s construction sector exhibits a disproportionate safety burden, accounting for 19.7% of workplace accidents despite comprising only 9.5% of the industrial workforce. While prior studies have diagnosed safety culture deficiencies through qualitative assessments, behavioral interventions, and risk identification approaches, no research has provided quantitatively prioritized intervention recommendations integrating regulatory mechanisms across project lifecycle phases with role-specific training programs. Grounded in Hudson’s safety culture maturity model and Reason’s organizational accident theory, this study employed a quantitative survey methodology to prioritize regulatory and training interventions for safety culture improvement. A 43-item questionnaire was administered to 105 construction industry professionals across client organizations (21%), contractor firms (30%), and consulting companies (49%) using stratified purposive sampling. Data were analyzed using Relative Importance Index calculations, supplemented by Kruskal–Wallis tests and correlation analyses, with instrument reliability being confirmed through Cronbach’s alpha (α = 0.859). Key findings reveal that 75.2% of respondents reported absence of safety culture implementation at project sites. Stakeholder effectiveness analysis identified sponsoring agencies (RII = 0.869) and regulatory authorities (RII = 0.819) as primary safety culture drivers, with clients demonstrating the lowest influence (RII = 0.568). Training prioritization established personal protective equipment utilization (RII = 0.886) and basic induction protocols (RII = 0.850) as critical worker competencies, while managerial requirements emphasized site-specific briefings (RII = 0.821) and incident protection training (RII = 0.808). Regulatory intervention priorities included safety credit points for contractor licensing (RII = 0.737) and departmental safety manual integration into contracts (RII = 0.726). These findings provide quantitative prioritization to guide resource allocation for safety culture interventions, although the descriptive methodology constrains causal inference regarding intervention effectiveness. Full article

Understanding how cultivated xerophytic shrubs physiologically regulate canopy water loss under anomalously wet conditions is crucial for predicting ecohydrological responses and for providing practical guidance in landscape restoration under the ongoing warming–wetting trend on the northern Loess Plateau. This study tested hypotheses concerning the hierarchy of atmospheric and soil-water controls on canopy transpiration (E_c), stomatal conductance (g_s), the strength of canopy–atmosphere coupling, and species-specific soil-water sensitivities and water-use strategies in Caragana korshinskii and Salix psammophila. Concurrent measurements of branch-level sap flow, meteorological variables, and soil water content (SWC) at multiple depths were conducted in two adjacent stands during the wet season of a climatically wet year (July–September 2017). Meteorological factors, particularly vapor pressure deficit (VPD), were the dominant drivers of daily E_c and g_s, whereas SWC exerted secondary but species-specific influences. Both shrubs were strongly coupled to the atmosphere, with consistently low decoupling coefficients (Ω ≈ 0.11–0.15) on daily scales. C. korshinskii maintained stable water use through access to deeper soil, whereas S. psammophila responded sensitively to fluctuations in shallow SWC. These contrasting patterns indicate depth-partitioned water-use strategies and a context-dependent continuum between isohydric and anisohydric behavior rather than fixed species traits. The findings support improved parameterization of shrub water use in ecohydrological models, more effective water-use management, and informed species selection and nursery practices for landscape restoration in semi-arid regions experiencing warming–wetting climatic shifts. Full article

Schwanniomyces etchellsii is an unconventional, halotolerant microorganism. Like some other yeasts, it can efficiently perform various biocatalytic transformations of organic compounds in seawater more effectively than in freshwater. In seawater, conversion rates are higher, by-product production is minimized, greater substrate loading is possible, and cells can be recycled for further use. To identify the molecular features that explain this behavior, comparative proteomic and lipidomic studies were conducted on cells grown in seawater and freshwater at various growth stages. The results showed higher expression of proteins involved in the stress response, such as glycerol-3-phosphate dehydrogenase, the glycerol transporter Stl1 and the P-type ATPase sodium pump Ena1, and several phospholipid biosynthesis proteins, including inositol-3-phosphate synthase and phosphatidate cytidylyltransferase, in seawater. Changes in metabolic enzymes and other proteins involved in responding to stimuli were also observed between the two conditions. Overall, cells grown in a freshwater medium exhibited higher levels of enzymes involved in biosynthetic processes. Differences in lipid profiles were also observed between cells grown in the two media. Higher levels of monoacyl and diacylglycerols were found in seawater, while higher levels of phospholipids containing serine and ethanolamine were found in freshwater. Consistent with more permeable membranes, cells grown in seawater exhibited lower levels of ergosterol. Full article

In an increasingly secular and pluralistic age marked by declining religious affiliation and rising individualized spiritual pursuits, accompanied by soaring mental health issues, the need for psychologically grounded perspectives on spiritual health is urgent. Drawing on developmental psychology, positive psychology, and psychology of religion and spirituality, this article introduces the Thrive Spiritual Health Framework. Spiritual health involves experiencing and responding to a loving source of transcendence in cognitive, affective, behavioral, and relational ways, and integrating those responses into narrative identities that inform who we are and who we belong to, shape our ethical ideals, inform virtues, and orient purpose—allowing us to sustain lives of love. The framework synthesizes six interrelated facets—transcendence, habits and rhythms, relationships and community, identity and narrative, vocation and purpose, and ethics and virtues (THRIVE)—through which spirituality nurtures thriving. Each facet is contextualizable across cultural and secular settings, highlighting both opportunities and vulnerabilities of contemporary spirituality. While individualized spiritual pathways may empower autonomy and innovation, they also risk fragmentation without relational and communal support. The framework provides an empirically grounded resource for research and practice, clarifying when spirituality promotes thriving and offering guidance for spiritual innovation in pluralistic contexts. Full article

The objective of this study is to investigate how two forms of engagement—job engagement and organization engagement—shape organizational citizenship behaviors directed at individuals (OCBI) and the organization (OCBO), and how these behaviors, in turn, influence employee burnout and intention to quit. This study also seeks to examine the impact of burnout on intention to quit. A paper-based survey was conducted among frontline bank employees from 21 financial institutions in Thailand. Data from 562 respondents, selected through convenience sampling, were analyzed using covariance-based structural equation modeling. Findings revealed that job engagement fosters OCBI, whereas organization engagement enhances OCBO. Job engagement also reduces burnout, while the adverse effect of organization engagement on burnout was small and insignificant. OCBI positively affects burnout and positively mediates the job engagement–burnout relationship. In contrast, OCBO negatively affects burnout and negatively mediates the organization engagement–burnout relationship. Finally, burnout increases employees’ intention to quit. These findings provide theoretical insights into the mechanisms linking engagement, citizenship behaviors, burnout, and intention to quit. Importantly, this study offers practical recommendations for promoting well-being and sustainable employee retention in the high-demand banking industry. Full article

Mental and behavioral healthcare (MBH) needs of youth have been increasingly recognized over the past decade. Youth living in rural areas of the United States face a particular challenge in accessing appropriate MBH services. However, the individual needs of communities vary. The current study recruited 32 caregivers, healthcare providers, and educators from four rural communities in one state in the Mountain West region of the United States. These participants responded to questions during a 45–60-min focus group. The goal of the focus groups was to understand (a) how caregivers, healthcare providers, and educators perceive the types of MBH services that are available in their community; (b) what barriers they perceive to accessing satisfactory MBH services; and (c) what strengths they perceive within their community’s MBH system. Results of a thematic analysis of focus group transcripts found common and conflicting themes that likely have an impact on the development of an effective MBH system for rural youth. Full article

Accurate short-term wind power forecasting plays a critical role in maintaining grid stability due to the inherently irregular and fluctuating nature of wind resources. Deep learning models such as LSTM, GRU, and CNN are widely used to learn temporal dynamics; however, their ability to capture or adapt to the underlying symmetries and asymmetries inherent in real-world wind energy data remains insufficiently explored. In this study, we evaluate and compare these models using authentic production and meteorological data from the Tokat Wind Farm in Türkiye. The forecasting scenarios were designed to reflect the temporal structure of the dataset, including seasonal patterns, recurrent behaviors, and the symmetry-breaking effects caused by abrupt changes in wind speed and operational variability. The results demonstrate that the LSTM model most effectively captures the temporal relationships and partial symmetries within the data, yielding the lowest error metrics (RMSE = 0.2355, MAE = 0.1249, MAPE = 25.16%, R² = 0.8199). GRU and CNN offer moderate performance but show reduced sensitivity to asymmetric fluctuations, particularly during periods of high variability. The comparative findings highlight how symmetry-informed model behavior—specifically the ability to learn repeating temporal structures and respond to symmetry-breaking events—can significantly influence forecasting accuracy. This study provides practical insights into the interplay between data symmetries and model performance, supporting the development of more robust deep learning approaches for real-world wind energy forecasting. Full article

Background/Objectives: Facial expressions are central to nonverbal communication and social cognition, and their recognition is shaped not only by facial features but also by contextual cues and prior experience. In high-threat contexts, rapid and accurate decoding of others’ emotions is adaptively advantageous. Grounded in neurocognitive models of face processing and vigilance, we tested whether brief perceptual adaptation to emotionally salient scenes, real-world disaster exposure, and pre-traumatic stress reactions enhance facial-emotion categorization. Methods: Fifty healthy adults reported prior direct exposure to catastrophic events (present/absent) and completed the Pre-Traumatic Stress Reactions Checklist (Pre-Cl; low/high). In a computerized task, participants viewed a single adaptor image for 5 s—negative (disaster), positive (pleasant environment), or neutral (phase-scrambled)—and then categorized a target face as emotional (fearful, angry, happy) or neutral as quickly and accurately as possible. Performance was compared across adaptation conditions and target emotions and examined as a function of disaster exposure and Pre-Cl. Results: Emotional adaptation (negative or positive) yielded better performance than neutral adaptation. Higher-order interactions among adaptation condition, target emotion, disaster exposure, and Pre-Cl indicated that the magnitude of facilitation varied across specific facial emotions and was modulated by both experiential (exposed vs. non-exposed) and dispositional (low vs. high Pre-Cl) factors. These effects support a combined influence of short-term contextual tuning and longer-term experience on facial-emotion categorization. Conclusions: Brief exposure to emotionally salient scenes facilitates subsequent categorization of facial emotions relative to neutral baselines, and this benefit is differentially shaped by prior disaster exposure and pre-traumatic stress. The findings provide behavioral evidence that short-term perceptual adaptation and longer-term experiential predispositions jointly modulate a fundamental communicative behavior, consistent with neurocognitive accounts in which context-sensitive visual pathways and salience systems dynamically adjust to support adaptive responding under threat. Full article

Citizens increasingly engage in private politics—market-based actions such as boycotts and buycotts—alongside or instead of public politics aimed at government institutions. This study examines how perceptions of efficacy and institutional trust, shaped by digital media environments, influence individuals’ choice between these modes of participation. A laboratory experiment tested how efficacy cues and governance frames affect engagement preferences in the United States (N = 395). Participants were asked to sign an e-petition directed at either a government agency (NOAA) or a private corporation (BP). Experimental treatments varied by portraying government as either pluralist or business-like and by emphasizing governmental versus corporate efficacy. Results show that efficacy cues, rather than ideological beliefs about how government should operate, primarily drive behavior. Messages enhancing perceived governmental efficacy increased public political action, while messages emphasizing business efficacy shifted respondents toward private politics. These findings indicate that perceptions of efficacy, as filtered through digital and algorithmic environments, shape how citizens direct their participation. Understanding how these cues operate is essential for anticipating whether civic engagement will gravitate toward public institutions or market channels in an increasingly mediated political landscape. Full article

Octachlorinated metal phthalocyanines (MPcCl₈, M = Co, Zn, VO) represent an underexplored class of functional materials with promising potential for chemiresistive sensing applications. This work is the first to determine the structure of single crystals of CoPcCl₈, revealing a triclinic (P-1) packing motif with cofacial molecular stacks and an interplanar distance of 3.381 Å. Powder XRD, vibrational spectroscopy, and elemental analysis confirm phase purity and isostructurality between CoPcCl₈ and ZnPcCl₈, while VOPcCl₈ adopts a tetragonal arrangement similar to its tetrachlorinated analogue. Thin films were fabricated via physical vapor deposition (PVD) and spin-coating (SC), with SC yielding highly crystalline films and PVD resulting in poorly crystalline or amorphous layers. Electrical measurements demonstrate that SC films exhibit n-type semiconducting behavior with conductivities 2–3 orders of magnitude higher than PVD films. Density functional theory (DFT) calculations corroborate the experimental findings, predicting band gaps of 1.19 eV (Co), 1.11 eV (Zn), and 0.78 eV (VO), with Fermi levels positioned near the conduction band, which is consistent with n-type character. Chemiresistive sensing tests reveal that SC-deposited MPcCl₈ films respond reversibly and selectively to ammonia (NH₃) and hydrogen sulfide (H₂S) at room temperature. ZnPcCl₈ shows the highest NH₃ response (45.3% to 10 ppm), while CoPcCl₈ exhibits superior sensitivity to H₂S (LOD = 0.3 ppm). These results suggest that the films of octachlorinated phthalocyanines produced by the SC method are highly sensitive materials for gas sensors designed to detect toxic and corrosive gases. Full article

Background/Objectives: Anxiety disorders are highly prevalent and impairing psychiatric conditions. Conventional diagnostic approaches based on symptom checklists lack biological specificity and often fail to guide treatment decisions effectively. This study protocol outlines a multidimensional, prospective investigation designed to identify behavioral and neurobiological biomarkers predictive of treatment response in individuals with anxiety-related symptoms, grounded in the Research Domain Criteria framework. Methods: This observational, longitudinal study (NCT06773585) will include a transdiagnostic sample of clinical anxiety group alongside a healthy control group (185 participants, including 145 patients with anxiety disorders and 40 healthy controls). Participants will undergo comprehensive baseline assessments, including clinical interviews, self-report questionnaires, a virtual reality (VR)-based behavioral task, electroencephalography (EEG), electrocardiography (ECG), and structural and functional brain magnetic resonance imaging. Follow-up assessments will be conducted at 2, 6, and 12 months, with recruitment and data collection planned from 2024 to 2029. These complementary modalities are integrated to capture behavioral, physiological, and neural indicators of anxiety and its treatment response. Multimodal baseline features will be used to construct machine-learning models predicting treatment response, defined as ≥40% reduction in anxiety severity scores. Longitudinal analyses will examine symptom trajectories and neural mechanisms associated with response. Neurobiological comparisons will be made across timepoints and between responders, non-responders, and healthy controls. Conclusions: By identifying objective, biologically grounded markers of anxiety and treatment response, our findings will contribute to the development of personalized assessment tools and scalable digital interventions for psychiatric care. Full article

The rapid development of the Internet of Things (IoT), a network of interconnected devices and sensors, has improved operational efficiency, comfort, and sustainability in smart buildings. However, relying on interconnected systems also introduces cybersecurity vulnerabilities. For instance, attackers can exploit zero-day vulnerabilities (previously unknown security flaws), launch Distributed Denial of Service (DDoS) attacks (overwhelming network resources with traffic), or access sensitive Building Management Systems (BMS, centralized platforms for controlling building operations). By targeting critical assets such as Heating, Ventilation, and Air Conditioning (HVAC) systems, security cameras, and access control networks, they may compromise the safety and functionality of the entire building. To address these threats, this paper presents a cybersecure intelligent sensor framework to protect smart buildings from various IoT-related cyberattacks. The main component is an automated Intrusion Detection System (IDS, software that monitors network activity for suspicious actions), which uses machine learning algorithms to rapidly identify, classify, and respond to potential threats. Furthermore, the framework integrates intelligent sensor networks with AI-based analytics, enabling continuous monitoring of environmental and system data for behaviors that might indicate security breaches. By using predictive modeling (forecasting attacks based on prior data) and automated responses, the proposed system enhances resilience against attacks such as denial of service, unauthorized access, and data manipulation. Simulation and testing results show high detection rates, low false alarm frequencies, and fast response times, thereby supporting the cybersecurity of smart building infrastructures and minimizing downtime. Overall, the findings suggest that AI-enhanced cybersecurity systems offer promise for IoT-based smart building security. Full article

Public attitudes toward renewable energy sources (RES) have been widely studied at the household level. However, less is known about how citizens differ in their broader perceptions, knowledge, and behavioral orientations toward renewable energy. This study explores such heterogeneity within Polish society using survey data from a representative sample of 974 respondents. An exploratory factor analysis identified six dimensions of renewable energy attitudes: environmental concern, knowledge and awareness, social and economic support, perceived ease of use, perceived benefits, and behavioral intentions. Using these attitudinal dimensions, cluster analysis revealed two distinct consumer segments that differ in their overall level of engagement with renewable energy. The first cluster comprises pro-green and engaged individuals who express strong concern for environmental issues, have a greater awareness of the benefits of renewable energy, and are more ready to adopt such technologies. The second cluster represents respondents who are less engaged or skeptical, with weaker environmental and behavioral commitment. The comparison of sociodemographic characteristics across clusters showed no statistically significant differences in gender, age, education, or place of residence, and only a marginal effect for income. The findings suggest that support for renewable energy in Poland is not driven by demographics but somewhat shaped by cognitive and value-based factors, offering valuable insights for policymakers and communication strategists promoting the energy transition. Full article

Recycling education is important for promoting pro-environmental sustainable behavior, yet traditional approaches often lack engagement and impact, particularly among younger audiences. This study presents a digital, turn-based card strategy game designed to teach recycling principles and concepts through interactive city-building mechanics. Set in an augmented reality environment, the game challenges players to balance population growth, resource use, and waste management to maintain a high well-being score for their city. Players construct digital buildings (houses, recycling facilities, resource infrastructures), each influencing waste production, recycling efficiency, and overall well-being. The game integrates educational content with engaging decision-making, aiming to foster system thinking and eco-conscious behavior. Unlike prior AR approaches, this game focuses on digital interaction, leveraging immersive game-based learning. Usability and engagement were evaluated using the in-game version of the Game Experience Questionnaire (GEQ). Findings support that users responded positively to the prototype’s game experience, suggesting that the digital game is promising. The study contributes to the growing field of digital pro-environmental education, providing insights into how interactive gameplay can support environmental awareness and laying groundwork for future evaluation of its educational impact. Full article

Objective: This study aimed to identify caregivers’ perceptions, preferences, and intentions regarding the use of digital articulation therapy applications for children with DLD. Methods: A cross-sectional online survey was conducted between August and September 2025 among 197 caregivers of children diagnosed with DLD. A 43-item questionnaire was structured into five domains addressing demographics, therapy experience, digital-therapy exposure, and preferences for application-based articulation therapy. Constructs from the Unified Theory of Acceptance and Use of Technology 2, including performance expectancy (PE), social influence (SI), price value (PV), facilitating conditions (FC), and behavioral intention, were analyzed. Results: Most respondents were mothers (96%), and 78.7% of them resided in urban areas. Among them, 84.3% had prior speech therapy experience. Only 15.7% had used educational or therapeutic applications; the main dissatisfaction factors were lack of fun (51.6%) and feedback (19.3%). Caregivers preferred short, engaging sessions (20–40 min per day), video-based (75%) or game-based (64%) content, and feedback every 2 months, with a reasonable monthly cost (20,000–30,000 KRW). Regression analysis revealed that sex (β = −0.451, p = 0.013), PE (β = 0.381, p < 0.001), and PV (β = 0.212, p = 0.034) significantly associated with behavioral intention to use an articulation-therapy application, whereas SI and FC were not significant. Conclusions: Caregivers of children with DLD demonstrated strong willingness to adopt digital articulation therapy applications, particularly when these tools provide meaningful therapeutic outcomes at moderate cost and include motivating, interactive content. Future application design should prioritize treatment functionality, user engagement, and accessibility to enhance adoption and continuity of digital speech-language interventions. Full article