Search Results (1,363)

Artificial intelligence (AI) is now the computational core of smart building automation, acting across the entire cyber–physical stack. This review surveys peer-reviewed work on the integration of AI with indoor environmental quality (IEQ) and energy performance, distinguishing itself by presenting a holistic synthesis of the complete technological evolution from IoT sensors to generative AI. We uniquely frame this progression within a human-centric architecture that integrates digital twins of both the building (DT-B) and its occupants (DT-H), providing a forward-looking perspective on occupant comfort and energy management. We find that deep reinforcement learning (DRL) agents, often developed within physics-calibrated digital twins, reduce annual HVAC demand by 10–35% while maintaining an operative temperature within ±0.5 °C and CO₂ below 800 ppm. These comfort and IAQ targets are consistent with ASHRAE Standard 55 (thermal environmental conditions) and ASHRAE Standard 62.1 (ventilation for acceptable indoor air quality); keeping the operative temperature within ±0.5 °C of the setpoint and indoor CO₂ near or below ~800 ppm reflects commonly adopted control tolerances and per-person outdoor air supply objectives. Regarding energy impacts, simulation studies commonly report higher double-digit reductions, whereas real building deployments typically achieve single- to low-double-digit savings; we therefore report simulation and field results separately. Supervised learners, including gradient boosting and various neural networks, achieve 87–97% accuracy for short-term load, comfort, and fault forecasting. Furthermore, unsupervised models successfully mine large-scale telemetry for anomalies and occupancy patterns, enabling adaptive ventilation that can cut sick building complaints by 40%. Despite these gains, deployment is hindered by fragmented datasets, interoperability issues between legacy BAS and modern IoT devices, and the computer energy and privacy–security costs of large models. The key research priorities include (1) open, high-fidelity IEQ benchmarks; (2) energy-aware, on-device learning architectures; (3) privacy-preserving federated frameworks; (4) hybrid, physics-informed models to win operator trust. Addressing these challenges is pivotal for scaling AI from isolated pilots to trustworthy, human-centric building ecosystems. Full article

Scene text understanding, serving as a cornerstone technology for autonomous navigation, document digitization, and accessibility tools, has witnessed a paradigm shift from traditional methods relying on handcrafted features and multi-stage processing pipelines to contemporary deep learning frameworks capable of learning hierarchical representations directly from raw image inputs. This survey distinctly categorizes modern scene text recognition (STR) methodologies into three principal paradigms: two-stage detection frameworks that employ region proposal networks for precise text localization, single-stage detectors designed to optimize computational efficiency, and specialized architectures tailored to handle arbitrarily shaped text through geometric-aware modeling techniques. Concurrently, an in-depth analysis of text recognition paradigms elucidates the evolutionary trajectory from connectionist temporal classification (CTC) and sequence-to-sequence models to transformer-based architectures, which excel in contextual modeling and demonstrate superior performance. In contrast to prior surveys, this work uniquely emphasizes several key differences and contributions. Firstly, it provides a comprehensive and systematic taxonomy of STR methods, explicitly highlighting the trade-offs between detection accuracy, computational efficiency, and geometric adaptability across different paradigms. Secondly, it delves into the nuances of text recognition, illustrating how transformer-based models have revolutionized the field by capturing long-range dependencies and contextual information, thereby addressing challenges in recognizing complex text layouts and multilingual scripts. Furthermore, the survey pioneers the exploration of critical research frontiers, such as multilingual text adaptation, enhancing model robustness against environmental variations (e.g., lighting conditions, occlusions), and devising data-efficient learning strategies to mitigate the dependency on large-scale annotated datasets. By synthesizing insights from technical advancements across 28 benchmark datasets and standardized evaluation protocols, this study offers researchers a holistic perspective on the current state-of-the-art, persistent challenges, and promising avenues for future research, with the ultimate goal of achieving human-level scene text comprehension. Full article

Burnout, characterized by emotional exhaustion and depersonalization, is increasingly recognized as a significant mental health concern with psychiatric implications. This cross-sectional study explored variables associated with current burnout levels among 2004 teachers in 19 Latin American countries and Spain, drawing on retrospective perceptions of COVID-19 pandemic-related changes in work conditions and student behavior. Using a comprehensive survey, researchers gathered demographic information, work-related characteristics, and burnout levels measured by the Maslach Burnout Inventory. Participants were recruited through social media platforms and teacher groups. Participants reported high emotional exhaustion, with 45.9% exceeding the clinical threshold. Moderate depersonalization levels were observed, with 30.2% scoring above the clinical cutoff. Hierarchical regressions indicated that emotional exhaustion was significantly predicted by individual (e.g., gender, age, socioeconomic status, pre-existing mental and chronic illnesses), school (e.g., school level, sector, and workload), and student factors (e.g., behavior and social adjustment problems), accounting for 17.4% of the variance. Depersonalization was similarly associated with individual (e.g., gender, age, education, and pre-existing mental illness), school (e.g., workload and school level), and student characteristics (e.g., educational, behavioral, and family adjustment problems), explaining 6.5% of the variance. These findings contribute to psychiatric and psychological research by identifying specific risk profiles for chronic stress syndromes in educators—an occupational group facing long-term psychological impacts from the COVID-19 crisis. This study underscores the need for interdisciplinary psychiatric approaches to diagnose and prevent burnout and promote teacher well-being through clinical and policy-level interventions. Full article

Digital transformation (DT) has become a strategic priority for public administrations, particularly due to the need to deliver more efficient and citizen-centered services and respond to societal expectations, ESG (Environmental, Social, and Governance) criteria, and the United Nations Sustainable Development Goals (UN SDGs). In this context, the main objective of this study is to propose an innovative methodology to automatically evaluate the level of digital transformation (DT) in public sector organizations. The proposed approach combines traditional assessment methods with Artificial Intelligence (AI) techniques. The methodology follows a dual approach: on the one hand, surveys are conducted using specialized staff from various public entities; on the other, AI-based models (including neural networks and transformer architectures) are used to estimate the DT level of the organizations automatically. Our approach has been applied to a real-world case study involving local public administrations in the Valencian Community (Spain) and shown effective performance in assessing DT. While the proposed methodology has been validated in a specific local context, its modular structure and dual-source data foundation support its international scalability, acknowledging that administrative, regulatory, and DT maturity factors may condition its broader applicability. The experiments carried out in this work include (i) the creation of a domain-specific corpus derived from the surveys and websites of several organizations, used to train the proposed models; (ii) the use and comparison of diverse AI methods; and (iii) the validation of our approach using real data. Based on the deficiencies identified, the study concludes that the integration of technologies such as the Internet of Things (IoT), sensor networks, and AI-based analytics can significantly support resilient, agile urban environments and the transition towards more effective and sustainable Smart City models. Full article

Background: The aim of this study was to explore the intention of Jordanian patients diagnosed with hyperlipidemia to engage in physical activity. This objective was achieved via an in-depth analysis of how patient attitudes, subjective norms, and perceived behavioral control can influence patient intentions to exercise. Additionally, this research examined how sociodemographic factors and perceived barriers can impact patient participation in physical activity. Methodology: This study employed a cross-sectional approach on a convenience sample of Jordanian patients diagnosed with hyperlipidemia. To gain the required data, a 15-item questionnaire (derived from the Theory of Planned Behavior) was presented to the participants in the form of an online survey (via several platforms, including WhatsApp, Facebook, and email). Results: The results indicate that perceived behavioral control had a significant correlation with the participants’ intentions to participate in physical activity. Additionally, the findings revealed that there were no significant correlations between demographic features (age, marital status, level of education, and monthly income) and intention to engage in physical activity. However, the results ascertained the existence of several facilitators to exercise (such as financial resource availability, self-interest, beneficial weather conditions, and supportive friends or exercise partners). The most commonly reported barriers to physical activity included time constraints, work commitments, and limitations imposed by existing health conditions. Conclusions: These findings provide valuable insights that can be employed to develop physical activity programs that address the cultural needs of Jordanian patients diagnosed with hyperlipidemia and enhance their levels of physical activity. Full article

Based on self-determination theory and the “environment–cognition–behavior” analysis framework, harmonious work passion is introduced into the research system to systematically explore the mechanism and internal path of inclusive leadership on employees’ creative territory behavior. Combined with work autonomy and status competition motivation, a three-way interaction model is constructed to reveal the boundary conditions under which inclusive leadership affects employees’ creative territory behavior. Through situational experiments (Study 1) and multi-time questionnaire surveys (Study 2), the results showed that harmonious work passion mediates the negative impact of inclusive leadership and creative territory behavior; when work autonomy is strong and employees’ status-competitive motivation is high, inclusive leadership has the most significant effect on creative territory behavior through harmonious work passion. The interaction among inclusive leadership, work autonomy, and status-competitive motivation is significant. The purpose of this study is to provide practical guidance for managers to reduce employees’ negative behaviors by optimizing the work environment and incentive strategies. Full article

This study investigates how the gender of human resource (HR) managers and the presence of rationality culture (RC) in organizations jointly influence women employees’ workplace outcomes, including interpersonal affinity, job involvement, and organizational loyalty. Drawing on feminist organizational theory and social identity theory, the study examines whether women HR managers are associated with more positive outcomes for women employees and whether the dominance of RC moderates these effects. RC, rooted in bureaucratic logic and objectivity, may diminish the perceived value of relational and inclusive HR practices—especially in highly formalized work environments. The study employs a survey-based quantitative method using data from the Korean Women Managers Panel, which includes responses from over 346 women working in medium- and large-sized organizations in South Korea. Directional hypotheses are tested, proposing that women HR managers positively influence employee outcomes, but this effect may be weakened in organizations where RC is strongly embedded. The findings contribute to organizational behavior and the gender studies literature by clarifying how HR managers’ gender operates under varying cultural norms and revealing the conditional nature of its effectiveness. The study offers both theoretical and practical insights for organizations aiming to foster inclusive environments, with implications for HR strategy, organizational development, and gender Full article

This article aims to analyze the conditions that contribute to the sustainability of violence against women in Bulgaria, an EU member state with high rates of this phenomenon. The analysis is based on data obtained through qualitative and quantitative methods, including in-depth interviews and focus groups with experts from state institutions (the police, prosecutors, courts, and social services), politicians, journalists, and from non-governmental organizations working with victims, as well as a nationwide sample survey of the adult population of Bulgaria. The qualitative data were analyzed through thematic analysis. The article demonstrates that cultural, ideological, and structural conditions in Bulgarian society facilitate the sustainability of violence against women. These include patriarchal norms prevailing in the family, specific characteristics of the popular culture, the neoliberal ideology of extreme individualism, the withdrawal of the state from its obligations, and ineffective institutional response. These conclusions point to the need to enhance the state’s capacity to counteract the phenomenon as well as the need to address ingrained cultural norms of conduct. Full article

(1) Background: People living with spinal cord injury (SCI) face numerous challenges in their lives in terms of health conditions, everyday activity, and participation in society, which are not fully recognized. To address such issues, a community survey with 125 questions for people living with SCI was conducted and the response rates, population characteristics, health and functioning problems are reported. (2) Methods: The survey questionnaire comprised 125 questions on SCI characteristics, health conditions, activities, participation, and environmental and personal factors. The survey response rates were calculated, and demographics and health and functioning characteristics were analyzed. (3) Results: A total of 890 individuals responded to the survey. The median age of the participants was 48 years (interquartile range (IQR), 39–56), and 76% of the population were males. Paraplegia (60%) and complete injury (58%) were the most common injury type, and the cause was mostly traumatic (92%). More health problems and lower quality of life were more frequent with older age and in patients without paid work. (4) Conclusions: The Ko-InSCI study provides valuable information in terms of health needs and service gaps for people with SCI in the community. Full article

This study examines the relationships between job satisfaction, overtime hours, perceived stressors, and burnout symptoms among academic mid-level staff at German universities, with a particular focus on gender differences. Drawing on survey data from 1442 academics collected in April/May 2023, this study applies t-tests and regression analyses to examine the effects of structural and personal factors on job satisfaction. The findings suggest that job satisfaction is primarily shaped by psychosocial and institutional conditions. Negative predictors are perceived job insecurity, burnout symptoms, and excessive overtime, whereas a strong dedication to work buffers against these. Variables such as gender, age, parenthood, and participation in structured PhD programs did not show substantial effects. Notably, respondents who postponed having children for professional reasons reported lower job satisfaction, pointing to potential conflicts between career and personal life expectations. Full article

This paper develops empirical relationships to estimate FAA/EASA and MIL-3013B rules-compliant take-off field performance for single and multi-engine aircraft. Recent experience with modern aircraft flight manuals revealed that popular empirical legacy methods are no longer accurate; improvements in tires and brakes lead to significantly shorter certified distances. This work relies upon a survey of current operational aircraft and extensive numerical simulations of generic configurations to support the development of a collection of new equations to estimate take-off performance for single and multi-engine aircraft under dry and wet conditions. These relationships are individually tailored for civilian and U.S. Military rules; they account for the superior capability of modern braking systems and the implications of minimum-control speed on the certified distance. Full article

True slime molds (Eumycetozoa) remain under-explored globally, particularly in water-logged forest habitats. Despite evidence suggesting a high biodiversity potential in the Knyszyn Forest of north-eastern Poland, no systematic effort had previously been undertaken there. In the present survey, plant substrates from eight swampy sub-compartments were incubated for over four months, resulting in the detection of fifteen slime mold species. Four of these taxa are newly reported for northern and north-eastern Poland, while several have been recorded only a handful of times in the global literature. These findings underscore how damp, nutrient-rich conditions foster Eumycetozoa and demonstrate the effectiveness of moist-chamber culturing in revealing rare or overlooked taxa. Current evidence shows that, although slime molds may occasionally colonize living plant or fungal tissues, their influence on crop productivity and tree vitality is negligible; they are therefore better regarded as biodiversity indicators than as pathogens or pests. By establishing a replicable framework for studying water-logged environments worldwide, this work highlights the ecological importance of swamp forests in sustaining microbial and slime mold diversity. Full article

Chiral liquid chromatography (cLC) using chiral stationary phases (CSPs) has become a crucial technique for separating enantiomers. Understanding enantiomeric discrimination is essential for improving chromatographic conditions and elucidating chiral molecular recognition; the computational methods are extremely helpful for this. To assess the relevance of the association of these two approaches and to analyze the current trends, in this review, a systematic analysis of the scientific literature was performed, covering recently published works (from 2015 to January 2025) on enantioseparation by cLC using CSPs and computational studies. CSPs based on polysaccharides and Pirkle-type were the most described (accounting for 52% and 14% of the studies, respectively). Regarding the computational methods, molecular docking and molecular dynamics (MD) were the most reported (accounting for 50% and 25% of the studies, respectively). In the articles surveyed, a significant growth in research concerning both cLC enantioseparation and computational studies is evident, emphasizing the benefit of the synergy between these two approaches. Full article

Background: This study investigated the relationship between problematic media use (PMU) and working memory in preschoolers. Methods: Parents of children aged 3 to 7 (260 boys, 257 girls; M_age = 5.57, SD = 0.73) in Jinan, China, completed questionnaires assessing children’s PMU and working memory. Subsequently, High (n_high = 32, M_age = 4.53, SD = 0.67) and Low (n_low = 30, M_age = 4.67, SD = 0.66) PMU groups, based on the survey data, complete a dual 1-back task during functional near-infrared spectroscopy (fNIRS) recording. Results: Behavioral accuracy and reaction time showed no significant group differences. However, a significant interaction between the PMU group and gender on prefrontal activation was observed, F(1, 60) = 5.88–7.59, ps < 0.05, ηp² = 0.09–0.12. High-PMU boys exhibited greater left prefrontal activation than low-PMU boys, while low-PMU girls showed greater activation in these same areas compared to low-PMU boys. A three-way interaction of group, task condition, and gender on prefrontal activation was also found, F(2, 60) = 5.81–6.42, p < 0.01, ηp² = 0.10–0.19, suggesting that neural responses varied by task and participant characteristics. Conclusions: These findings indicate that PMU may be associated with altered prefrontal activation during working memory tasks in preschoolers, with gender playing a moderating role. Full article

The aim of this article is to identify key factors shaping organizational agility as a determinant of the sustainable development of an organization in the conditions of Economy 5.0. The research used the survey method conducted in 2024 on a sample of 312 respondents. It analyzed the impact of decision-making processes, identification with the goals of the organization, tolerance of rapid changes, internal communication, internal motivation and implementation of the idea of work–life balance. Based on the results, an original mathematical model was constructed presenting the relationships between the analyzed variables. The research results confirmed a significant relationship between the level of organizational agility and the ability of the organization to implement the sustainable development strategy. It was identified that factors such as quick and accurate decision-making, strong identification of employees with the goals of the organization and efficient communication have the greatest impact on strengthening this ability. The limitation of the research was the homogeneity of the sample and the inability to fully take into account variables related to the industry and cultural context. The research highlights that enhancing organizational agility is crucial for achieving sustainable development and building lasting competitive advantage in the dynamic context of the Economy 5.0. Full article