Search Results (10,395)

Aligned with circular bioeconomy principles, which aim to establish closed-loop systems that maximize resource utilization and renewal while minimizing waste, this study developed and characterized innovative catalysts derived from waste almond shells. These shells were carbonized and functionalized to create active surfaces containing Lewis and Brønsted acid sites. Modification was achieved through treatment with ZnCl₂ to introduce Lewis acid (LA) sites and with sulfuric acid to generate Brønsted acid (BA) sites. Detailed instrumental analyses enabled assessment of catalyst morphology, textural parameters, and surface functional groups. A physical mixture of the two catalysts was used to convert glucose into 5-hydroxymethylfurfural (HMF), yielding a maximum HMF yield of 76.8%. The results indicate that the collaborative action of Lewis and Brønsted acid sites, along with oxygen-containing surface groups, contributes to catalyst efficiency. These insights facilitate targeted catalyst optimization by adjusting surface texture and functional groups. Full article

This study formulates and verifies a network-based evaluation methodology for appraising the sustainable competitiveness of community enterprises. Based on Social Capital Theory, the Resource-Based View (RBV), and Network Theory, the model defines high-quality networks as structural relational circumstances that facilitate resource sharing and knowledge sharing, serving as mediating mechanisms that improve competitive outcomes. A quantitative study approach was utilized, gathering survey data from 451 representatives of community enterprises around Thailand, and Structural Equation Modeling (SEM) was applied to assess both measurement features and structural relationships. The model demonstrates satisfactory internal reliability, convergent validity, and discriminant validity, affirming measurement adequacy. Empirical evidence indicates that high-quality networks are positively correlated with sustainable competitiveness, both directly and indirectly, with 49.2% of the overall effect conveyed through resource and knowledge exchange, emphasizing the practical value of network-based processes. The suggested model offers practical utility for policymakers and development agencies in search of evidence-based instruments to enhance competitiveness, network capacity, and long-term resilience in community enterprises. The cross-sectional methodology and lack of contextual control variables restrict causal inference and external generalizability, highlighting the necessity for longitudinal or quasi-experimental expansions. By emphasizing model creation and empirical validation, this study develops a systematic and reproducible methodological framework for assessment. Full article

Background: Intimate partner violence (IPV) represents a major public health problem in Europe, with significant physical, psychological, and social consequences. Nurses are often the first professionals capable of detecting early signs of IPV, yet they lack validated instruments to assess their clinical competency in detection, evaluation, documentation, and intervention. This study aimed to develop and validate the Intimate Partner Violence Nursing Competency Scale (IPVNCS), aligned with the Nursing Intervention Classification (NIC 6403). Methods: A cross-sectional psychometric study was conducted among registered nurses in the Community of Madrid. A 30-item Likert-type self-administered instrument (1–5 scale) was developed based on NANDA, NIC 6403, and NOC frameworks. A total of 202 nurses participated. Reliability was assessed through Cronbach’s alpha. Construct validity was examined using exploratory factor analysis (EFA) with Promax rotation and confirmatory factor analysis (CFA) using AMOS 26. Ethical approval was obtained (CEU San Pablo, code 843/24/104). Results: After item refinement, 26 items remained across four dimensions: (1) Intervention and Referral, (2) Detection and Assessment, (3) Documentation and Recording-keeping, (4) Psychosocial Support. The instrument showed excellent reliability ($\alpha$ = 0.97). KMO was 0.947 and Bartlett’s test was significant (p < 0.001). CFA demonstrated satisfactory fit: ${\chi }^2$/df = 2.066, RMSEA = 0.073, CFI = 0.92, TLI = 0.91, NFI = 0.86. The final model adequately represented the latent structure. After debugging, its psychometric properties were significantly improved. Four redundant items were eliminated, achieving internal consistency ($\alpha$ = 0.97), a KMO value of 0.947 and a significant Bartlett’s test of sphericity. It showed a better fit, according to ${\chi }^2$/df = (2.066); Parsimony = (720.736); RMR (0.0529; RMSEA (0.073); NFI (0.860); TLI (0.910) and CFI (0.920). The final model provides an adequate representation of the latent structure of the data. This study provides initial evidence of construct validity and internal consistency reliability of the IPVNCS. Conclusions: The IPVNCS is a valid and reliable tool to assess nursing competencies for clinical management of IPV. It supports structured evaluation across four core nursing domains, enabling improved educational planning, clinical decision-making, and quality of care for victims. The scale fills a gap in clinical nursing assessment tools and can support protocol development in emergency, primary care, and hospital settings. Full article

Female soccer is rapidly becoming a widely practiced sport at different levels: this opens up a new demand for systems meant to protect athletes from head impacts or to monitor their effects. The market is offering some solutions in similar sports, but the specificity and high relevance of soccer encourage the development of a dedicated solution. From market analysis, technology scouting, and ethnographic research a set of functional and technical requirements have been defined and proposed. The designed instrumented head band is equipped with one Inertial Measurement Unit (IMU) in the occipital area and four contact pressure sensors on the sides. The concept design is low-cost and open-architecture, prioritizing accessibility over complexity. The modularity also ensures that each component (sensing, battery, communication) can be replaced or upgraded independently, enabling iterative refinement and integration into future sports safety systems. In addition to safety monitoring for injury prevention or detection of the traumatic impact, the system is relevant for supporting performance monitoring, rehabilitation or post-injury recovery and other important applications. System engineering has started and the next step is building the prototypes for testing and validation. Full article

On 7 January 2025, an Mw7.1 earthquake struck Dingri County, Tibet, causing severe damage in a high-altitude, sparsely instrumented region where traditional damage assessment methods are limited. To address this, we developed an integrated "source simulation–nighttime light validation" framework. First, a kinematic source model (constrained by InSAR and teleseismic data) and the Unified Seismic Tomography models for continental China lithosphere 2.0 (USTClitho2.0) velocity model were used with the curved-grid finite difference method to simulate high-resolution ground motion and intensity fields. Second, NASA Black Marble (VNP46A2) nighttime light data, processed with the Block-Matching and 3D filtering (BM3D) algorithm, were analyzed to compute pixel-level radiance changes and township-level total nighttime light loss rates (TNLR). The results reveal a high spatial consistency between simulated high-intensity zones and areas of significant light loss. For instance, Mangpu Township, within a simulated high-intensity zone, exhibited a TNLR of 44.7%. This demonstrates that nighttime light remote sensing can effectively validate physical simulations in areas lacking dense seismic networks. Our framework provides a novel, complementary methodology for rapid and reliable post-earthquake damage assessment in high-mountain, data-sparse regions. Full article

The integration of artificial intelligence into education has driven growing interest in predicting student learning styles and developing recommendation systems that personalize learning pathways. While previous reviews examined these domains, most focus on pre-2023 research, overlooking recent methodological shifts. We conduct a systematic literature review of 40 studies published between 2017 and 2025, with emphasis on publications from 2023 to 2025 (70% of reviewed studies). Our analysis identifies three qualitative shifts: adoption of ensemble and deep learning methods over single classifiers, emergence of multimodal inputs including physiological signals, and evolution from isolated prediction to integrated adaptive systems. Beyond methodological synthesis, this review critically examines factors underlying observed trends and barriers to deployment. The Felder-Silverman Learning Style Model dominates research (58.3%) due to historical path dependency and instrument availability rather than demonstrated pedagogical superiority. While ensemble methods achieve high reported accuracy (87–98%), methodological concerns emerge: 65% of studies employ random rather than temporal validation, potentially inflating performance, and only 23% address production-level requirements, including privacy, scalability, and integration. We systematically analyze implementation barriers spanning computational requirements, LMS integration, educator acceptance, ethical considerations, and scalability—revealing that the gap between research prototypes and deployable systems remains substantial. Our contributions include a stakeholder impact framework, evaluation metrics taxonomy, critical analysis of reported performance claims, and identification of five research gaps with actionable recommendations. This review offers researchers and practitioners both a comprehensive synthesis of advances and a critical roadmap for bridging the implementation gap in AI-powered personalized education. Full article

This study aims to explore the relationship between the digital financial literacy of homestay business owners and economic sustainability. A conceptual model is developed by integrating three primary constructs—performance expectancy, effort expectancy, and facilitating conditions—from the unified theory of acceptance and use of technology (UTAUT) with digital financial literacy and FinTech use by homestay business owners. Further, the effect of FinTech use on economic sustainability is examined through the interaction between facilitating conditions and financial inclusion. Data were collected from Southern India, and hypothesized relationships were tested after checking the measurement properties of the survey instrument. The findings indicate that (i) the digital financial literacy of homestay business owners is a precursor to FinTech use, which, in turn, is positively associated with economic sustainability; (ii) digital financial literacy interacting with performance expectancy (first moderator) and effort expectancy (second moderator) significantly influenced FinTech use; and (iii) FinTech use interacting with facilitating conditions (first moderator) and financial inclusion (second moderator) increased economic sustainability. The three-way interactions in this study provide insights into the boundary conditions that increase FinTech use and economic sustainability, particularly in the context of homestay businesses. The proposed digital financial literacy and FinTech adoption model contributes to the information technology adoption research by extending the UTAUT, in which performance expectancy and effort expectancy play a vital role in FinTech adoption by homestay business owners. The three-way model developed and tested, to the best of our knowledge, is the first of its kind in the Indian context and hence makes a pivotal contribution to the advancement of the UTAUT model through its application to homestay business owners. The implications for theory and practice are discussed. Full article

This paper analyzes the implementation of the Geoportal SIG FESBAL–UPM, a Participatory Geographic Information System (PGIS) developed within the Master’s and Doctorate programs in Rural Development Project Planning and Sustainable Management at UPM. The study introduces a model integrated with Project-Based Learning (PBL), the Working With People (WWP) framework, and the CFS-RAI principles to address challenges in responsible food systems. The geoportal designed to be applied at the Food Bank–UPM Chair–FESBAL, acts as an innovative instrument for participation among the different stakeholders enabling the spatialization and analysis of data across social, environmental, and governance dimensions. Functionally, it offers a robust foundation for evidence-based decision-making, systematizes geographic information, and visualizes data via the web, supporting research, training, and community engagement actions. Furthermore, this study details the specific projects and activities developed under the three involved action lines: research, training, and community engagement, identifying strengths and weaknesses in each. The findings affirm that this participatory approach ensures that the proposed solutions are aligned with local needs and priorities, increasing the sustainability and long-term success of the projects implemented through the geoportal. Full article

This paper outlines the design, development, and practical implementation of a rubber belt-driven dual cone continuously variable transmission (CVT) model. This model enables a demonstration of stepless changes in the transmission ratio between input and output shafts. Although the model can be operated manually via a control panel, enhanced functionality, such as automated measurement, proportional-integral-derivative (PID) speed control, and data measurement and storage, is achieved through a control application created within the LabVIEW virtual instrument environment. This work also includes a partial comparison between the practical implementation and its simulation model created in MATLAB-Simulink. Full article

Cross-border e-commerce, as an emerging trade format, offers new chances for optimizing industrial chains’ layout, enhancing economic resilience, and attaining high-quality development at the city level. In this context, treating the execution of the cross-border e-commerce comprehensive pilot zone (CBEC) as a quasi-natural experiment, this study subtly attests to how the CBEC affects urban entrepreneurship by using a difference-in-differences (DID) technique. The results exhibit that the CBEC greatly promotes urban entrepreneurship, which is supported by some robustness tests, including instrumental variable testing and placebo testing. Heterogeneity analysis reveals that in cities with more developed economies, stronger digitalization, richer cultures, sounder law rules, and better business environments, the benefit for the CBEC on entrepreneurship is more significant. Mechanism testing argues that the CBEC promotes urban entrepreneurship through talent aggregation and industrial upgrading. Precisely, the more concentrated high-quality talents are and the more advanced the industrial structure is, the higher the urban entrepreneurship. More importantly, the CBEC exhibits a spatial spillover effect on entrepreneurship, promoting local entrepreneurship while stimulating the motivation to imitate and learn in neighboring areas, thereby driving their entrepreneurship. The findings offer a viable decision-making guide for building a unified factor market and achieving regional coordinated development. Full article

An ongoing challenge in pelagic oceanography and limnology is to quantify and understand the distribution of suspended particles and particle aggregates with sufficient temporal and spatial fidelity to understand their dynamics. These particles include biotic (mesoplankton, organic fragments, fecal pellets, etc.) and abiotic (dusts, precipitates, sediments and flocks, anthropogenic materials, etc.) matter and their aggregates (i.e., marine snow), which form a large part of the total particulate matter > 200 μm in size in the ocean. The transport of organic material from surface waters to the deep-sea floor is of particular interest, as it is recognized as a key factor controlling the global carbon cycle and hence, a critical process influencing the sequestration of carbon dioxide from the atmosphere. Here we describe the development of an oceanographic instrument, the Pelagic Laser Tomographer (PLT), that uses high-resolution optical technology, coupled with post-processing analysis, to scan the 3D content of the water column to detect and quantify 3D distributions of small particles. Existing optical instruments typically trade sampling volume for spatial resolution or require large, complex platforms. The PLT addresses this gap by combining high-resolution laser-sheet imaging with large effective sampling volumes in a compact, deployable system. The PLT can generate spatial distributions of small particles (~100 µm and larger) across large water volumes (order 100–1000 m³) during a typical deployment, and allow measurements of particle patchiness over spatial scales to less than 1 mm. The instrument’s small size (6 kg), high resolution (~100 µm in each 3000 cm² tomographic image slice), and analysis software provide a tool for pelagic studies that have typically been limited by high cost, data storage, resolution, and mechanical constraints, all usually necessitating bulky instrumentation and infrequent deployment, typically requiring a large research vessel. Full article

The thermosphere serves as a pivotal region for Sun–Earth interactions, and thermospheric winds are of great scientific importance for deepening insights into atmospheric dynamics, climate formation mechanisms, and space environment evolution. This study designed and developed a Ground-based Doppler Asymmetric Spatial Heterodyne Interferometer (GDASHI). Targeting the nightglow of the oxygen atomic red line (OI 630.0 nm), this instrument enables high-precision observation of thermospheric winds. The GDASHI was deployed at Gemini Astronomical Manor (26.7°N, 100.0°E), and has obtained one year of nighttime meridional and zonal wind data. To verify the reliability of GDASHI-derived winds, a collocated observation comparison was performed against the Dual-Channel Optical Interferometer stationed at Binchuan Station (25.6°N, 100.6°E), Yunnan. The winds of the two instruments are basically consistent in both their diurnal variation trends and amplitudes. Further Deming regression and correlation analysis were conducted for the two datasets, with the meridional and zonal winds yielding fitting slopes of 0.808 and 0.875 and correlation coefficients of 0.754 and 0.771, respectively. An uncertainty analysis of the inter-instrument comparison was also carried out, incorporating instrumental measurement uncertainties, instrumental parameter errors, and small-scale perturbations induced by observational site differences; the synthesized total uncertainties of zonal and meridional winds are determined to be 20.24 m/s and 20.77 m/s, respectively. This study not only verifies the feasibility and reliability of GDASHI for ground-based thermospheric wind detection but also provides critical observational support for analyzing the spatiotemporal variation characteristics of mid-low latitude thermospheric wind fields and exploring their underlying physical mechanisms. Full article

Ophiocordyceps sinensis is a precious medicinal material with significant pharmacological and economic value. However, the visual similarity between its wild and cultivated forms poses a challenge for authentication. This study investigates the influence of specimen orientation on the accuracy of hyperspectral identification. Hyperspectral data were systematically acquired from four standard specimen orientations (left lateral, right lateral, dorsal, and ventral) for each sample. Random Forest (RF), Support Vector Machine (SVM), Logistic Regression (LR), and Fully Connected Neural Network (FCNN) models were trained and evaluated using both single-orientation and multi-orientation fused data. Results indicate that the LR model achieved superior and stable performance, with an average identification accuracy exceeding 98%. Crucially, for all tested models, no statistically significant difference in identification accuracy was observed across the different specimen orientations. This finding demonstrates that specimen orientation does not significantly influence identification accuracy. The conclusion was further corroborated in experiments using randomly orientation-fused datasets, in which model performance remained consistent and reliable. It is therefore concluded that precise specimen orientation control is unnecessary for the hyperspectral identification of Ophiocordyceps sinensis. This insight substantially simplifies the hardware design of dedicated identification devices by eliminating the need for complex orientation-fixing mechanisms and facilitating the standardization of operational protocols. The study provides a practical theoretical foundation for developing cost-effective, user-friendly, and widely applicable identification instruments for Ophiocordyceps sinensis and offers a reference for similar non-destructive testing applications involving anisotropic medicinal materials. Full article

22q11.2 deletion syndrome (22q11.2DS) is the most common recurrent microdeletion in humans and a prototypical high-risk neurogenetic copy number variant (CNV) associated with a broad spectrum of neurodevelopmental and psychiatric disorders, including intellectual disability (ID), autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), anxiety, and psychotic symptoms. This hemizygous deletion encompasses multiple genes involved in brain development and neural circuit function, contributing to marked phenotypic variability and multisystem involvement. In pediatric populations, deficits in adaptive functioning are frequently reported and may occur independently of global intellectual impairment, reflecting broader behavioral vulnerabilities within this genetic risk architecture. Background/Objectives: This study aimed to characterize the sociodemographic, clinical, and intellectual profiles of children and adolescents with 22q11.2DS and to examine adaptive functioning and its associations with behavioral difficulties. Methods: Thirty-four patients aged 1–17 years with a confirmed molecular diagnosis of 22q11.2DS were assessed. Standardized instruments were used to evaluate cognitive performance, adaptive functioning, and behavioral outcomes. Results: Intellectual disability was highly prevalent, with most participants showing combined cognitive and adaptive impairments. Adaptive functioning was compromised across domains, with relatively higher socialization scores compared to other areas, such as daily living skills. Multivariate analyses indicated associations between sociodemographic factors and behavioral difficulties, as well as between social problems and lower global adaptive functioning. Conclusions: Together, these findings contribute to the characterization of the adaptive and behavioral phenotype associated with a high-risk neurogenetic CNV and highlight the relevance of adaptive functioning as a key outcome for early evaluation and intervention in pediatric 22q11.2DS. Full article

Background/Objectives: Primary health care (PHC) is the cornerstone of any high-quality healthcare system. For PHC to work well, healthcare professionals need to be skilled in critical thinking, self-reflection, and patient-centered care. However, few studies have explored the potential interplays between these factors. Therefore, this cross-sectional study evaluated the critical thinking disposition and training needs of PHC professionals, alongside patient experiences and satisfaction with PHC services. Methods: The study involved 54 PHC professionals and 100 patients from sixteen PHC facilities in Crete, Greece. Professionals completed the Critical Thinking Disposition Scale (CTDS) and Training Needs Assessment (TNA) questionnaires, while patients filled out the Quality-of-Life Instrument of Chronic Conditions in Primary Health Care (QUALICOPC) questionnaire. Results: Our findings indicated that PHC professionals exhibited high critical thinking levels (CTDS, mean score of 46.46 ± 4.24). However, TNA scores suggested moderate training needs, particularly in relationships/investigations [median: 0.50 (0, 1.50)], communication/patient-centered [median: 0.30 (0, 1.1)], and flexibility and application of knowledge [median: 0.40 (0, 1.0)]. Nevertheless, no significant correlation was found between CTDS and TNA (ρ = 0.08, p > 0.05). Patients mostly rated their health as poor (40%), and 26% lacked a family physician. Although patients were highly satisfied with communication and patient-centered care (>95% reporting positive experiences), continuity and empowerment had room for improvement. Only 37% felt their GP knew their living conditions, and 26% lacked a personal physician. Patients with chronic conditions reported significantly different experiences. Specifically, patients with chronic conditions had better continuity of care (84% vs. 59%, p = 0.01) and more comprehensive care (70% vs. 43%, p = 0.01) compared to controls. Conclusions: Our findings suggest that targeted training is needed for PHC professionals to address skill gaps. These initial findings could guide the creation of customized professional development initiatives and point to areas where PHC services could be structurally improved. Additional studies, including longitudinal ones, are required to further validate these associations. Full article