Search Results (11,073)

Background: Janus kinase (JAK) inhibitors have expanded the therapeutic landscape for moderate-to-severe atopic dermatitis (AD), yet real-world comparative data on upadacitinib and abrocitinib remain limited. Objective: We aimed to compare the 24-week real-world effectiveness and safety of upadacitinib 30 mg and abrocitinib 200 mg in adult patients with moderate-to-severe AD, using EASI-75 as the primary efficacy endpoint, and to explore potential clinical factors associated with treatment response. Methods: This retrospective single-center study included adult patients with moderate-to-severe AD treated with upadacitinib 30 mg or abrocitinib 200 mg and followed for 24 weeks in routine clinical practice. A small pediatric subgroup (n = 3) receiving abrocitinib 100 mg was analyzed separately for descriptive purposes only. Clinical outcomes included Eczema Area and Severity Index (EASI), Peak Pruritus Numerical Rating Scale (PP-NRS), EASI-50/75/90 response rates, and NRS-4 response. Safety was assessed using routinely documented adverse events. Exploratory analyses evaluated the possible influence of body mass index (BMI), baseline immunoglobulin E (IgE), and psychological stress on treatment response. Results: Both upadacitinib and abrocitinib were associated with rapid and sustained clinical improvement over 24 weeks. At month 6, EASI-75 response was 83.3% in the upadacitinib group versus 70.8% in the abrocitinib group (p = 0.27). EASI-50 response was significantly higher in the upadacitinib group (100% vs. 83.3%; p = 0.05). Exploratory findings suggested that higher BMI, elevated baseline IgE levels, and psychological stress may be associated with less favorable response trajectories. Both treatments demonstrated a generally favorable safety profile; however, one serious cerebrovascular thrombotic event occurred in a patient with pre-existing cardiovascular risk factors, highlighting the importance of individualized risk assessment when prescribing JAK inhibitors. Conclusions: In routine clinical practice, both upadacitinib and abrocitinib appeared effective for the management of moderate-to-severe AD over 24 weeks. Although upadacitinib 30 mg showed a numerically higher month-6 EASI-50 response, this finding should be interpreted cautiously given the modest sample size and the absence of broader between-group differences across other key efficacy outcomes. Larger prospective studies are needed to confirm comparative effectiveness and to clarify predictors of response and safety in real-world settings. Full article

This study addresses the growing need to integrate operational excellence with sustainability objectives in manufacturing systems. Despite extensive research on Lean Management and Quality Management Systems (QMSs), their combined impact on process performance and resource efficiency remains insufficiently explored, particularly in real industrial contexts. The aim of this study is to develop and apply an integrated Lean–QMS–SPC analytical framework linking process performance improvement with sustainability-related outcomes. A case study was conducted in a high-volume manufacturing environment. The study combined process analysis, system-level assessment, and root cause identification to support targeted improvement actions. The results indicate that the implementation of Lean-oriented practices and supporting methods was associated with improved process stability, reduced variability, and decreased occurrence of nonconformities. These improvements translate into enhanced operational performance and reduced resource consumption associated with rework and defects. A scenario-based estimation model, based on observed defect reduction, is used to assess the potential impact on energy consumption and CO₂ emissions. The study contributes to the literature by operationally integrating SPC analysis, QMS assessment, root cause analysis, and Lean-oriented improvement activities within an industrial manufacturing context. The findings highlight that quality-driven process improvements may support operational efficiency while contributing to resource-efficiency performance. Full article

Soil erosion is a serious problem threatening regional ecological security, particularly in the Loess Plateau of China. This study focuses on the Wuding River Basin on the Loess Plateau. Based on multi-source data from 2001 to 2024, the RUSLE model was used to estimate the soil erosion modulus. We used comprehensive methods, such as trend analysis, multiple regression, scenario simulation, partial least squares structural equation modeling (PLS-SEM), hot spot analysis, and Hurst exponent, to systematically analyze the spatiotemporal evolution characteristics of soil erosion, the contributions of driving factors, and the sustainability of trends. The results showed that over the 24-year period, the soil erosion modulus in the basin generally showed a decreasing trend, suggesting an improvement in soil erosion conditions. The area of mild and above erosion grades continued to shrink. Among the RUSLE factors, the vegetation cover factor (C) showed a significant downward trend (R² = 0.7721), with the decreasing area accounting for 95.8%; the rainfall erosivity factor (R) showed a slight upward trend, with the increasing area accounting for 92.7%; and the erosion control practice factor (P) remained stable in most areas (96.8%). Relative contribution analysis indicated that the R-factor dominated the largest area (46.85%), while absolute contribution analysis showed that the C-factor contributed most significantly to erosion reduction. PLS-SEM demonstrated that the influence pathways of natural factors and human activities on soil erosion differed significantly across spatial and temporal scales. On the temporal scale, the R-factor had the strongest direct positive effect on erosion; on the spatial scale, the topography factor (LS) had the strongest positive effect on erosion. Furthermore, we found that the disturbance of vegetation by human activities is being weakened with the continuous implementation of soil and water conservation projects. The cold and hot spots of erosion trends were concentrated in the southeastern part of the basin. Based on trend sustainability, the basin was divided into successfully treated areas (57.6%), potential rebound risk areas (29.4%), emergency treatment areas (11.2%), and monitoring priority areas (1.8%). Overall, this study advances the understanding of soil erosion evolution under long-term ecological restoration and provides a scientific basis for optimizing sustainable soil and water conservation management in the Wuding River Basin. Full article

The rapid integration of artificial intelligence in higher education positively affects student satisfaction, engagement, and learning outcomes. However, students frequently report ethical unease, guilt, and concerns about dependency. The current literature offers a limited explanation for their coexistence, as both have been treated as parallel or independent outcomes. Hence, this review extends and integrates existing theories by reconceptualising cognitive and moral dissonance as a central psychological process that explains how student satisfaction with AI-mediated learning is produced, negotiated, and sustained. Following PRISMA 2020 guidelines, we adopted a two-layer explanatory review design, synthesising 40 Scopus-indexed studies (Layer 1 = 15 studies; Layer 2 = 25 studies) from 2016 to 2025. Layer 1 studies explicitly define dissonance-related explanatory mechanisms that influence satisfaction and continued AI use across contexts such as dissertation writing, programming education, and problem-based learning. Layer 2 encompasses satisfaction-based studies that report ethical or affective concerns in parallel without theorising their interaction. The findings suggest a recurring satisfaction–dissonance paradox, in which students often experience genuine or conditional satisfaction from performance gains while simultaneously managing their psychological discomfort through one or more regulation mechanisms. Further, persistent and escalated dissonance leads to withdrawal or full or partial adaptive behaviour. We propose these dynamics as a testable Dual-Process Satisfaction–Dissonance Framework (DPSDF), which includes five dissonance triggers, five regulation strategies, three feedback loops, and four behavioural outcomes. Further, five domain experts’ suggestions have been taken to provide specific practical implications. This framework extends understanding of AI-mediated learning and provides foundations for future theory and policy development in higher education. Full article

Critical infrastructure restoration (CIR) is a disaster-management and sustainability challenge because prolonged disruption of energy, water, transport, communications, healthcare, and public-administration services can amplify social, economic, and environmental losses. This PRISMA 2020-reported systematic review synthesizes post-2016 scientific literature and official policy, legal, standards, and technical documents on CIR and AI decision support. The review identified 55 records, removed 1 duplicate, excluded 1 ineligible record, and retained 53 core sources for qualitative synthesis, including 31 scholarly publications and 22 official documents. Manual screening was used; no automated screening or AI-assisted exclusion tools were applied. The results are organized around four research questions covering regulatory frameworks, recovery practices, supporting systems, and AI model families. The synthesis shows that CIR is shaped by layered governance through NIS2, the CER Directive, the AI Act, and national measures; by operational recovery practices such as continuity planning, cyber crisis coordination, interdependency mapping, and model-supported restoration; by digital platforms including SCADA/ICS, IoT sensing, GIS/common operating pictures, decision-support systems, simulation environments, and digital twins; and by AI methods ranging from classical machine learning and computer vision to reinforcement learning and generative assistants. However, evidence maturity remains uneven, with many AI applications still simulation-based, sector-specific, or weakly validated in real restoration settings. The review contributes an integrated CIR-oriented framework showing that AI creates practical value when embedded in interoperable, human-supervised, regulation-aware, and empirically validated restoration architectures that support sustainable service continuity rather than isolated automation. Full article

The knowledge economy and green innovation are fundamental pillars for the transition towards sustainable production models. The objective of this study was to analyze the influence of intellectual capital, green knowledge management and environmental practices on green innovation in SMEs in Tena. A quantitative cross-sectional approach was developed, applying a structured questionnaire to a sample of 64 green enterprises. Data analysis was performed using a Partial Least Squares Structural Equation Model (PLS-SEM), after evaluating the psychometric properties of the measurement model. The results show that the model explains 40% of the variance in green innovation. It was confirmed that Environmental and Technological Practices (ETPs) have the strongest and most significant effect on innovation, followed to a lesser extent by Intellectual Capital, whose influence was positive but marginal. Green Knowledge Management did not show a statistically significant impact. It is concluded that green innovation in Amazonian enterprises depends primarily on the adoption of technological infrastructure and tangible practices, while the systematization of knowledge remains a pending challenge. Full article

Solid waste management (SWM) is a major global challenge for environmental sustainability and public health. This study analyzed SWM perceptions and practices before and during the COVID-19 pandemic in Playa Boca Chica, Tecpan de Galeana, Guerrero, Mexico, using a descriptive and quantitative approach. Data was collected from 60 households between September and October 2022 and analyzed using SPSS statistical software version 26; reliability was confirmed with Cronbach’s Alpha; and the generation-associated greenhouse gas (GHG) emissions were estimated using the SWM-GHG climate calculator. This study explored socio-environmental dynamics in informal coastal settlements through a case study in the Global South. The results showed that waste generation remained stable during the pandemic (3.25 kg/day; p = 0.116), suggesting a pattern of behavioral rigidity in which entrenched waste management practices persisted despite the global health crisis, likely due to the absence of structural environmental interventions and policy-driven behavioral incentives. The climate calculator estimated GHG emissions of 92 and 99 tons of CO₂-eq/year before and during the pandemic, respectively. Residents highlighted the need for improved infrastructure, recycling, and composting, while 97% emphasized environmental education and waste separation. The absence of a local waste management policy contributes to persistent emissions, underscoring the need for integrated and sustainable SWM strategies. Full article

This paper presents a comprehensive review of artificial intelligence (AI) applications in photovoltaic-integrated buildings, focusing on energy forecasting, advanced control strategies, and pathways toward net-zero energy performance. Net-zero energy buildings are defined as systems that balance annual energy consumption with on-site renewable generation, requiring efficient and adaptive energy management. The review analyzes state-of-the-art AI-based forecasting methods for photovoltaic power generation and building energy demand, demonstrating the superior performance of machine learning and deep learning models in capturing nonlinear and time-dependent patterns. In parallel, advanced control strategies, including model predictive control (MPC), reinforcement learning (RL), and hybrid approaches, are evaluated in terms of their performance, limitations, and practical applicability. The results show that accurate forecasting alone is insufficient, and its integration with control strategies is essential for optimal system operation. Hybrid approaches combining model-based and data-driven methods emerge as the most effective solution for complex and dynamic environments. The role of real-time energy management systems in enabling adaptive and coordinated operation is also highlighted. Finally, key challenges related to data quality, model interpretability, and system integration are identified, along with future research directions. Overall, AI-driven energy management systems have strong potential to transform photovoltaic-integrated buildings into intelligent, flexible, and sustainable energy systems. Full article

This systematic review critically analysed the differences, intersections, and trends toward convergence between Human Resource Management (HRM) and People Management (PM), highlighting the evolution of these approaches in organizational contexts marked by digital transformation. Conducted in accordance with the PRISMA 2020 guidelines, the study utilized the Web of Science and SCOPUS databases. Fifty-eight studies were selected and analysed narratively, prioritizing evidence with a lower risk of bias. The results confirm that, although HRM and PM have distinct rationales, a progressive convergence between the two is observed, driven by technological, organizational, and sociocultural changes. In this process, immersive technologies play a central role as socio-technical mediators, shaping organisational practices through configurations that reflect institutional logics and generate paradoxes between efficiency and experience. The analysed literature demonstrates that these technologies enable the integration of practices traditionally oriented toward efficiency, measurement, and standardization—characteristics of HRM—with experiential, relational, and subjective dimensions, which are specific to PM. It is concluded that the strategic adoption of immersive technologies enhances hybrid management models, capable of articulating strategic alignment, personalization of practices, engagement, and well-being at work. Thus, rather than merely serving as support tools, immersive technologies are emerging as foundational elements of modern people management, challenging traditional models, and paving the way for more integrated, sustainable, and people-centred practices. Full article

Wild mushroom harvesting is an activity practiced throughout the United States (U.S.) and holds a place of both cultural and economic importance. Mushroom harvesting on public lands in the U.S. takes two primary forms: (1) commercial harvest (for sale) or (2) personal harvest (for one’s own consumption or for sharing to others). As mushroom harvesting has grown in popularity, particularly in urban and suburban areas, ready access to information surrounding harvests on public lands has become increasingly important to the mushroom harvesting community, and ultimately to fungal conservation and sustainable exploitation. In this study, documents pertaining to harvesting on state and federal public lands in the U.S. were analyzed for their accessibility for personal and commercial harvesters. Scores were assigned based on access (ranked 0–5), with higher scores indicating greater access to the public. Overall, personal harvest (Min = 1, Max = 5, Average = 2.96) was permitted to some extent in every state, with the greatest access provided in Oregon, Nebraska, Wisconsin, and Michigan. Permits were often not required (Min = 0, Max = 3, Average = 0.7), with Montana and South Dakota having the most permitting requirements. Commercial harvest was associated with more limited access, and had greater associated regulation (Min = 0, Max = 4, Average = 1.02). Seventeen states that allowed for personal harvest did not allow for commercial harvest. Permitting was almost always required for commercial harvest (Min = 0, Max = 4, Average = 1.06), with Oregon having the most developed commercial permitting requirements. Access to public lands was found to be highly variable in the U.S. and is governed by a variety of local, state, and federal regulations. Information, depending on its source, was at times easy to access through a website, pamphlet, or phone call. However, in many cases information was out of date or difficult to find, and studies on the impacts of commercial and personal mushroom harvesting are limited. As a result, it is important that land managers develop communication mechanisms with the public for information sharing, to provide open and frequent communication, and for building long-term trust and relationships with harvesters. We offer some example mechanisms to land/resource managers and university/public educational partners as a starting point. Full article

Urban river networks face significant ecological challenges due to intensive urbanization. Traditional assessment methods focus mainly on individual rivers and overlook cross-scale connections. To fill this research gap, the study refined the Urban Riverscape Conditions-based Assessment for Management Needs (URBAN) framework and developed a dual-scale assessment system covering the entire river network and individual rivers. It evaluates hydrology, geomorphology, ecology, and the waterfront public service dimension. Taking the Qingxi area of Shanghai as a case study, this study integrated multi-source data and adopted field investigations, the analytic hierarchy process (AHP) and principal component analysis (PCA) to collect field data, calculate indicator weights, and extract dominant functional factors. The results show that the overall comprehensive health score of the study area is 59.39, classified as average; the river network scale scores 58.34, and the 21 monitored rivers achieve an average score of 61.80. The assessment identifies clear advantages in hydrological and geomorphological conditions, whereas waterfront public services and river morphological diversity are still deficient. Overall, this system demonstrates good operability and scientific validity, providing practical technical approaches for sustainable urban river network management and supporting refined watershed governance. Full article

This study addresses second-home ownership not merely as a form of tourism accommodation or real estate investment, but as a home-building process intersecting with local life, belonging, daily practices, and sustainable destination governance. While the economic, environmental, and community impacts of second-homes have been extensively discussed in the literature, how individuals perceive their primary and secondary homes differently in terms of the bodily, material, vibrant, imaginary, and emotional dimensions of home has been examined in a limited number of studies. This research analyzes paired data obtained through a two-stage online questionnaire from 223 British participants who own a secondary home in the Mugla–Ortaca region and a primary home in the United Kingdom. The 18-item Home Scale was used as the measurement tool. Confirmatory factor analysis, reliability–validity analyses, measurement invariance, and paired-samples t-tests were applied. The findings show that the bodily home difference was not statistically significant at the conventional 0.05 threshold, whereas primary-home scores were significantly higher in the material, vibrant, imaginary, and emotional home dimensions. The small to small-medium effect sizes suggest that the results should be interpreted cautiously as an asymmetrical home-building process rather than as evidence of a hierarchical superiority of the primary home. The study proposes a planning approach that does not view second home owners as merely transient consumers in sustainable coastal–rural destinations, but rather considers social sustainability, service planning, seasonality management, and local community engagement channels together. Full article

Background: Mobile health has been increasingly integrated into tuberculosis care to support patient education, communication, and treatment engagement. However, evidence remains limited regarding whether positive engagement with mHealth is associated with knowledge, attitudes, and practices among patients with multidrug-resistant tuberculosis. This study aimed to examine the association between positive mHealth engagement and knowledge, attitude, practice, and total KAP among patients with multidrug-resistant tuberculosis, and to evaluate the psychometric properties of the engagement score used as the primary exposure variable. Methods: A cross-sectional study was conducted among patients with multidrug-resistant tuberculosis. A positive mHealth engagement score was constructed from 12 mHealth-related items after harmonizing item directionality so that higher scores indicated more favorable engagement. The 12 items reflected five behavioural domains: intensity of use, ease and acceptability of use, functional engagement (communication with providers, access to health information, and perceived benefit for disease self-management), continuity of use, and barriers to sustained engagement. The composite score was computed as the mean of the 12 standardised items, with higher values indicating more positive engagement. Internal consistency was assessed using Cronbach’s alpha and corrected item–total correlations, and structural validity was explored using principal component analysis. Adjusted linear regression models were used to examine associations between the engagement score and Knowledge, Attitude, Practice, and total KAP scores, controlling for age, sex, and occupation. Sensitivity analyses were performed after excluding a poorly performing item, and tertile analyses were used to assess dose–response patterns. Results: The positive mHealth engagement score showed good internal consistency, with a Cronbach’s alpha of 0.852. One item demonstrated poor psychometric performance, and Cronbach’s alpha increased to 0.864 after its exclusion. The data were suitable for dimensionality assessment, with a Kaiser–Meyer–Olkin value of 0.870 and a significant Bartlett’s test. Principal component analysis identified a dominant first component explaining 43.29% of the total variance. Using the refined score, higher positive mHealth engagement was significantly associated with higher Knowledge scores (β = 2.06; 95% CI: 1.28–2.85; p < 0.001), higher Attitude scores (β = 4.68; 95% CI: 3.30–6.06; p < 0.001), and higher total KAP scores (β = 6.68; 95% CI: 4.62–8.74; p < 0.001), whereas no significant association was observed for the Practice score (β = −0.07; 95% CI: −0.63 to 0.49; p = 0.804). In tertile analyses, Knowledge, Attitude, and total KAP scores increased significantly across engagement levels, while Practice scores did not. Conclusions: Positive mHealth engagement was associated with better knowledge, attitudes, and overall KAP among patients with multidrug-resistant tuberculosis, but not with practice. These findings are associative; the cross-sectional design does not permit causal conclusions. The engagement score demonstrated good reliability and acceptable structural validity and may be a useful summary measure for evaluating patient interaction with mHealth interventions in tuberculosis care. Integrated strategies combining mHealth with clinical follow-up, adherence counseling, and structural support may be needed to translate informational and attitudinal gains into practice change. Full article

The agricultural sector, particularly animal production, faces numerous unprecedented challenges driven by climate change, resource depletion, and an ever-growing global demand for quality food. These challenges are further compounded by the increasing environmental impact of livestock farming, including greenhouse gas emissions, overuse of water and land resources, and the destruction of vital ecosystems. Ensuring the sustainability of animal production systems while mitigating the negative environmental impacts of these factors is essential for future global food security. As the demand for animal-derived products continues to rise, there is a pressing need for innovations that can enhance productivity without compromising environmental integrity or animal welfare. Artificial intelligence (AI) has emerged as a transformative technology with the potential to revolutionize the animal production industry. AI-driven solutions offer promising avenues for optimizing production efficiency, enhancing animal health and welfare, and reducing the environmental footprint of livestock farming. Machine learning, sensor technologies, and advanced data analytics are being increasingly utilized to monitor and predict various aspects of animal farming, such as feed efficiency, disease prevention, and climate resilience. These technologies enable farmers to make data-driven decisions, fostering more sustainable and environmentally responsible practices. This review examines the integration of AI into animal production systems, emphasizing its applications in climate change mitigation, resource management, and advancing sustainability. The discussion addresses how AI technologies can be utilized to improve productivity while minimizing environmental impact and enhancing animal welfare. Additionally, the paper outlines future opportunities, challenges, and potential barriers to integrating AI technologies into livestock farming, thereby ensuring long-term sustainability amid global challenges. Full article

The utilization of unconventional feed resources offers a sustainable strategy to mitigate feed shortages particularly in tropical and subtropical regions where access to conventional feeds is often limited. Among these, water hyacinth (Eichhornia crassipes) is one of the world’s most aggressive aquatic weeds, which has drawn attention due to its dual role as a problematic invasive species and a potential livestock feed. This plant reduces water quality, contributes to biodiversity loss and causes economic damage in farming systems. At the same time, its high capacity for nutrient absorption makes it a viable source of protein and energy for ruminants when properly harvested and processed into forms such as hay, dried leaves, and silage. However, its utilization requires caution, as the plant can accumulate toxins and heavy metals from polluted water, which may harm animal health if unprocessed. This review focuses on the potential of water hyacinth to improve ruminant growth performance, nutrient digestibility and rumen fermentation. Including water hyacinth in ruminant diet safely can possibly improve animal productivity, contribute to sustainable weed management and also provide a practical strategy to alleviate feed shortage in dry seasons, thereby encouraging resilience and sustainable ruminant production. Full article