Search Results (48,598)

Yunnan Jiama (paper horse prints), a representative form of intangible cultural heritage in southwest China, is characterized by subtle inter-class differences, complex woodblock textures, and heterogeneous preservation conditions, which collectively pose significant challenges for digital preservation and automatic image classification. To address these challenges and improve the computational analysis of Jiama images, this study proposes an enhanced object detection framework based on YOLOv8 integrated with a Global Attention Mechanism (GAM), referred to as YOLOv8-GAM. In the proposed framework, the GAM module is embedded into the high-level semantic feature extraction and multi-scale feature fusion stages of YOLOv8, thereby strengthening global channel–spatial interactions and improving the representation of discriminative cultural visual features. In addition, image augmentation strategies, including brightness adjustment, salt-and-pepper noise, and Gaussian noise, are employed to simulate real-world image acquisition and degradation conditions, which enhances the robustness of the model. Experiments conducted on a manually annotated Yunnan Jiama image dataset demonstrate that the proposed model achieves a mean average precision (mAP) of 96.5% at an IoU threshold of 0.5 and 82.13% under the mAP@0.5:0.95 metric, with an F1-score of 94.0%, outperforming the baseline YOLOv8 model. These results indicate that incorporating global attention mechanisms into object detection networks can effectively enhance fine-grained classification performance for traditional folk print images, thereby providing a practical and scalable technical solution for the digital preservation and computational analysis of intangible cultural heritage. Full article

In this study, the bending behavior of beams is investigated using the fractional Euler–Bernoulli beam model. This model is developed based on fractional calculus, particularly employing the Riesz–Caputo derivatives, and is capable of accurately accounting for nonlocal and size-dependent effects in structural beams. Unlike classical models that rely on integer-order derivatives, the present model uses fractional-order derivatives, which offer greater precision in analyzing beam behavior at small scales such as micro and nano levels. In this work, various beams with different boundary conditions and loading types are analyzed. To solve the governing fractional equations, a numerical algorithm based on the finite difference method is developed, which also allows for the incorporation of a variable characteristic length function along the beam. The numerical simulation results demonstrate that the order of the fractional derivative and the characteristic length have a direct impact on the amount of beam deflection. These findings indicate that the Euler–Bernoulli model based on Riesz–Caputo derivatives has high potential for realistic simulation of beam bending behavior at small scales, making it an effective tool for accurate analysis of microscale structures. Full article

Anaerobic digestion under a Waste-to-Energy (WtE-AD) framework represents a sustainable alternative for managing organic waste and generating bioenergy in developing countries. However, most life cycle assessment (LCA) studies implicitly assume stable operation, overlooking the environmental implications of process instability. In practice, large-scale WtE-AD plants are frequently affected by methanogenic inhibition events that reduce methane production and compromise their technical, economic, and environmental performance. This study—Part 2 of a two-paper series—addresses this gap by quantifying, from a life cycle perspective, the environmental consequences of recurrent methanogenic inhibition events in large-scale WtE-AD systems, complementing the techno-economic analysis presented in Part 1. Large-scale WtE-AD plants were modeled using design equations based on treatment capacity (60–200 t d⁻¹), considering scenarios with up to ten inhibition events over a 25-year operational period. The LCA was conducted in accordance with ISO 14040:14044 standards, defining as the functional unit one ton of co-digested fruit and vegetable residues with meat industry wastes, under an attributional approach with system boundary expansion and evaluating midpoint indicators through the ReCiPe 2016 method. Results show that inhibition events increase greenhouse gas emissions by up to 400% (from 28.1 to 138.6 kg CO₂ eq t⁻¹ of waste treated), while plants with capacities above 125 t d⁻¹ exhibit environmental credits (negative emission balances), demonstrating greater environmental resilience. Electricity substitution from the Mexican grid generated savings of up to 0.624 kg CO₂ eq kWh⁻¹, although the magnitude of the benefits strongly depends on the regional electricity mix. This dependency was further explored through comparative electricity mix scenarios representative of different levels of power sector decarbonization, allowing the sensitivity of WtE-AD environmental performance to regional grid characteristics to be assessed. Compared to landfill disposal (1326 kg CO₂ eq t⁻¹), WtE-AD plants significantly reduce impacts across all assessed categories. By explicitly integrating operational instability into an industrial-scale LCA framework, this work highlights the importance of evaluating methanogenic inhibition events from a life cycle perspective, providing key insights for the design of more sustainable and resilient WtE-AD processes within a Latin American context. Full article

The immune status of dogs is shaped by continuous exposure to antigenic and various environmental stimuli, which together influence the development, regulation, and effectiveness of immune responses. Stress-related immune alterations may not be evident at the systemic level but can emerge at cellular and molecular scales. Therefore, this study aimed to comprehensively characterize the hematological and immunological profiles of dogs in different environments. We evaluated lymphocyte responses under basal conditions and following CD3/CD28-mediated in vitro activation, with subsequent long-term culture. Gene expression analyses targeted markers of early T cell activation, cytotoxic effector function, cytokine signaling, and inhibitory immune regulation. The memory phenotype of T lymphocytes was evaluated after blood collection and prolonged in vitro culture. In addition, hematological and biochemical profiles were assessed, including basic parameters, cortisol, and C-reactive protein. Our results revealed that client-owned dogs exhibited lower baseline expression of activation markers, especially in comparison with the short-term stay group, indicating an early immune activation state upon entry to the shelter environment. Furthermore, T lymphocytes from short- and long-term shelter dogs exhibited marked differences in the distribution of naïve and effector-memory subsets as well as different expansion capacity. These alterations persisted during prolonged in vitro culture, indicating that stress duration and environmental antigen exposure differentially shape immune responsiveness. In summary, chronic stress modulates canine immune status in a time-dependent manner, highlighting the importance of integrated cellular and molecular approaches in assessing the impact of environmental stressors on dogs’ health and welfare. Full article

The digital transformation of education demands a comprehensive understanding of how leadership orientations and digital competencies intersect among educators. This exploratory cross-sectional study examined associations between self-reported leadership orientations, digital skills, and organizational readiness for innovation among 71 primary school teachers in Western Attica, Greece. Using the Multifactor Leadership Questionnaire (MLQ Form-5x) adapted for respondents without administrative roles, we measured leadership self-concept—teachers’ preferences and tendencies regarding leadership—rather than enacted behaviors. This distinction is critical given that 94.4% of participants lacked principal experience; thus, responses reflect aspirational orientations rather than observed behavioral patterns. Descriptive profiling approaches, including K-means clustering and multinomial logistic regression, identified three tentative response pattern groupings: Passive-Moderate (53.5%), Balanced-Active (33.8%), and High-Engagement (12.7%), with observed multivariate differences. After reverse-coding the passive-avoidant items, transformational leadership showed the highest mean score (M = 4.33), followed by passive-avoidant (M = 4.15; reflecting low endorsement of avoidant behaviors) and transactional (M = 3.91). Transformational leadership demonstrated acceptable internal consistency (α = 0.783), while transactional (α = 0.583) and passive-avoidant (α = 0.617) scales showed lower reliability, warranting cautious interpretation. Critical competency gaps emerged in professional digital domains—particularly web development (22.5% deficit) and administrative systems (18.3% deficit)—despite a surplus in consumer technologies such as social media (−29.6%), revealing an ‘aspirational gap’ between leadership self-concept and digital readiness—technology familiarity does not automatically translate to digital leadership capability. Digital skills showed the strongest association with profile membership, with each additional skill associated with a 32–67% increase in the odds of membership in more engaged profiles. These findings suggest digital competency development may be associated with leadership orientation patterns, though the cross-sectional design precludes causal inference. Methodological limitations—including lower scale reliability, weak cluster separation (silhouette = 0.150), and modest sample size—require that findings be interpreted as hypothesis-generating rather than definitive. This work offers preliminary insights relevant to SDG4 (Quality Education) regarding heterogeneity in leadership orientation among primary educators, while highlighting the need for culturally validated instruments and for replication with larger samples. Full article

Newton–Raphson-Based Optimizer (NRBO) is a recently proposed metaheuristic that combines mathematical search rules with population-based optimization; however, it still suffers from an insufficient balance between global exploration and local exploitation, limited local refinement accuracy, and weak adaptability in complex optimization scenarios. To address these limitations, this paper proposes an Improved Newton–Raphson-Based Optimizer (INRBO), which enhances the original framework through a multi-strategy augmentation mechanism. Specifically, INRBO integrates three complementary strategies: (1) an adaptive differential operator with a linearly decaying scaling factor to dynamically regulate exploration and exploitation throughout the search process; (2) a quadratic interpolation strategy that exploits high-quality individuals to improve local search directionality and precision; and (3) an elitist population genetic strategy that preserves superior solution characteristics while maintaining population diversity and preventing premature convergence. The performance of INRBO is systematically evaluated on the CEC2017 benchmark suite under multiple dimensions and compared with several state-of-the-art metaheuristic algorithms. Experimental results demonstrate that INRBO achieves superior optimization accuracy, convergence efficiency, and robustness across unimodal, multimodal, hybrid, and composite functions, which is further confirmed by statistical significance tests. In addition, INRBO is applied to mobile robot path planning in grid-based environments of different scales, where it consistently generates shorter, smoother, and safer paths than competing algorithms. Overall, the proposed INRBO provides an effective and robust optimization framework for global continuous optimization problems and real-world engineering applications, demonstrating both strong theoretical value and practical applicability. Full article

Landslides in mountainous regions threaten infrastructure and human safety, making high-accuracy landslide inventories crucial for disaster management. However, fine-grained identification using high-resolution remote sensing imagery is hindered by low small-landslide detection accuracy and bare soil spectral interference. The aim of this study is to propose a lightweight UCTransNet with Triplet Attention and Pyramid Kernel Interaction (UCTransNet-TPKI) deep learning model for accurate multi-scale landslide extraction. The study area is located in Wushan County, Chongqing. GF-2 imagery from 2022 was collected, along with field sampling data and Mengdong dataset as validation data. The model proposed in this study, named UCTransNet-TPKI, is based on an improved UCTransNet architecture. Its key innovations include the introduction of two critical modules: the Pyramid Kernel Interaction module and the Triplet Attention mechanism. The PKI module captures multi-scale local contextual information in parallel under different receptive fields, significantly enhancing the network’s ability to extract landslide features. Concurrently, the Triplet Attention mechanism effectively refines feature representations by capturing the interaction dependencies across the three dimensions of a feature map. This enables the model to focus more precisely on key areas, such as the main body and edges of a landslide, while simultaneously suppressing interference from background noise. The experimental results show that UCTransNet-TPKI achieved the highest F1-score of 0.9008 and an IoU of 0.8252, outperforming MFFENet, TransLandSeg, and Segformer++. Ablation studies confirmed the contributions of each component, with the PKI module improving IoU by 0.72%, the Triplet Attention mechanism increasing IoU by 0.9%, and their combination yielding a clear synergistic enhancement of overall performance. Furthermore, UCTransNet-TPKI demonstrated strong generalization on the Mengdong dataset, achieving an F1-score of 0.9230 and an IoU of 0.8560. These results demonstrate that UCTransNet-TPKI provides an accurate automated landslide mapping solution, offering significant value for post-disaster emergency response and geological hazard management. Full article

Background: Sigmoid volvulus is a time-critical cause of large-bowel obstruction. While endoscopic detorsion (ED) is the primary intervention for rapid decompression and the assessment of mucosal viability, reported success, recurrence, and mortality rates vary significantly across the literature, complicating evidence-based clinical decision-making. Methods: A systematic review and meta-analysis were conducted following PRISMA guidelines (protocol submitted to PROSPERO). MEDLINE/PubMed and Embase were searched from inception to 20 October 2025, supplemented by manual reference screening. We included original prospective or retrospective studies (n ≥ 5) reporting outcomes after ED for sigmoid volvulus, specifically technical success, post-ED recurrence, or mortality. Pooled proportions were estimated using a DerSimonian–Laird random-effects model on the logit scale, with heterogeneity quantified using I² statistics. Administrative database studies were summarized descriptively and excluded from the quantitative synthesis to minimize selection bias. Results: Nineteen studies (2004–2025) met the inclusion criteria from an initial 890 records. Fifteen studies (n = 1738) contributed to the analysis of technical success, yielding a pooled estimate of 80.0% (95% CI: 75.0–83.0%; I² = 87.5%). Seventeen studies (n = 3285) reported recurrence following initially successful ED, with a pooled rate of 33.9% (95% CI: 19.5–52.1%; I² = 97.5%). Sixteen studies (n = 2790) reported mortality; the pooled estimate was 22.6% (95% CI: 18.7–26.4%; I² = 99.6%). This extreme heterogeneity likely reflects variations in patient comorbidities (case-mix) and differing outcome reporting windows rather than procedural risk in isolation. Conclusions: ED is an effective first-line stabilizing intervention for uncomplicated sigmoid volvulus; however, recurrence rates remain high, and outcome estimates exhibit significant heterogeneity. ED should be integrated within a structured clinical pathway that prioritizes standardized mucosal assessment, post-procedural decompression, and the timely planning of definitive management when feasible. Full article

Community energy systems are expected to play an increasingly important role in the decarbonization of the residential sector, but their operation depends on how different electricity and heat storage technologies are configured and used. Existing studies typically examine storage options in isolation, limiting the comparability of their operational roles. This study addresses this gap by developing a decision-support framework that enables a consistent, operation-focused comparison of battery energy storage, hydrogen storage, and electric-vehicle-based storage within a unified community-scale hybrid energy system. The model represents electricity and heat balances in a hub formulation that couples photovoltaic and wind generation, a gas engine, an electric boiler, thermal and electrical storage units, hydrogen conversion and storage, and an aggregated fleet of electric vehicles. It is applied to a stylized Polish residential community using local demand, generation potential, and electricity price data. A set of single-technology and multi-technology scenarios is analyzed to compare how storage portfolios affect self-sufficiency, self-consumption, grid exchanges, and operating costs under current electricity market conditions. The results show that battery and electric vehicle storage primarily provide short-term flexibility and enable price-driven arbitrage, as reflected in the highest contribution of battery discharge to the electricity supply structure (5.6%) and systematic charging of BES and EVs during low-price hours, while hydrogen storage supports intertemporal shifting by charging in multi-hour surplus periods, reaching a supply share of 1.4% at the expense of substantial conversion losses. Moreover, the findings highlight fundamental trade-offs between cost-optimal, price-responsive operation and autonomy-oriented indicators such as self-sufficiency and self-consumption, showing how these depend on the composition of storage portfolios. The proposed framework, therefore, provides decision support for both technology selection and the planning and regulatory assessment of community energy systems under contemporary electricity market conditions. Full article

CPVG (Utility-scale photovoltaic generation) is expanding rapidly worldwide, yet its cumulative ecological effects remain insufficiently quantified. This review synthesizes current evidence to clarify how CPVG influences ecosystems through linked mechanisms of energy redistribution, biogeochemical cycling disturbance, and ecological responses. CPVG alters surface radiation balance, modifies microclimate, and disrupts carbon–nitrogen–water fluxes, thereby driving vegetation shifts, soil degradation, and biodiversity decline. These impacts accumulate across temporal scales—from short-term construction disturbances to long-term operational feedbacks—and propagate spatially from local to regional and watershed levels. Ecological outcomes differ substantially among deserts, grasslands, and agroecosystems due to contrasting resilience and limiting factors. Based on these mechanisms, we propose a multi-scale cumulative impact assessment framework integrating indicator development, multi-source monitoring, coupled modelling, and ecological risk tiering. A full-chain mitigation pathway is further outlined, emphasizing optimized siting, disturbance reduction, adaptive management, and targeted restoration. This study provides a systematic foundation for evaluating and regulating CPVG’s cumulative ecological impacts, supporting more sustainable solar deployment. Full article

Objective: Solid pseudopapillary neoplasms (SPN) and pancreatoblastoma (PB) have a low overall incidence but represent the most common pancreatic tumors in childhood. Currently, there is a lack of systematic descriptions of contrast-enhanced ultrasound (CEUS) features for these two tumors in pediatric populations. This study aims to retrospectively analyze and compare the CEUS characteristics of SPN and PB to explore key imaging differentiation points. Methods: This retrospective study collected data on 22 patients with solid pseudopapillary neoplasms and pancreatic blastomas of the pancreas who were pathologically diagnosed at a children’s hospital between September 2019 and May 2025. The ultrasound contrast-enhanced imaging findings for both tumor types were summarized and analyzed. Two physicians with different levels of experience performed qualitative analysis of the contrast-enhanced images, while quantitative analysis was conducted using time–intensity curve (TIC) analysis software. Results: This study included a total of 22 pediatric patients (19 with SPN and 3 with PB). Significant differences existed between the two groups in age (13.51 years vs. 2.94 years) and Ki-67 index (5.00% vs. 30.00%). Qualitative analysis revealed high heterogeneity in SPN enhancement patterns, with capsular enhancement with cystic components being the most common (42.11%). All PBs (100%) consistently demonstrated the “disorganized nourishing vessels” sign. Quantitative analysis revealed that PBs exhibited numerically higher IMAX values (179.84% vs. 60.56%) and faster WoR trends (773.88 vs. 275.38). Inter-observer consistency analysis supported measurement reliability (key parameters ICC > 0.80). Conclusions: This preliminary study indicates differences in CEUS characteristics between pediatric SPN and PB; PB tends to exhibit rapid, high enhancement with chaotic feeding vessels and rapid washout, whereas SPN more commonly presents with moderate, slow enhancement patterns, often accompanied by features associated with cystic components. These findings provide new hemodynamic clues for their imaging differentiation. Given the extremely small sample size of PB cases, the above conclusions should be regarded as preliminary hypotheses awaiting validation in future large-scale studies. Full article

The present study extends the previous work which was concerned with the identification of damage in GFRP composite plates by damage detection algorithms such as the Normalized Curvature Damage Factor (NCDF), Strain Energy Difference (SED), and Damage Index (DI), using a novel damage (crack) modeling technique called the ‘Node-Releasing Technique’ (NRT) in Finite Element Analysis (FEA) for modeling and detecting perpendicular and slant partial-depth cracks in GFRP composite beams. This study explores the sensitivity of the damage modeling technique NRT in damage detection for composite beams using the NCDF algorithm, since it was concluded in the previous work that the NCDF performs better compared to the other methods when detecting both perpendicular and slant partial-depth cracks. This study also examines the variations in the Frequency Response Function (FRF) as another novel tool for identifying even small-scale damage. Most prior research in this domain has focused on variations in natural frequency, displacement mode shape, and damping as indicators for detecting and localizing structural damage through various experimental, theoretical, and computational approaches. However, these conventional parameters often lack the sensitivity required to detect small-scale damage and, still, there exists a gap in the use of the node-releasing technique in FEA to model the partial-depth perpendicular and slant crack damage in laminated composite structures, such as beam-like structures. To fill this gap, the present study attempts to use Curvature Mode Shapes (CMS)-based NCDF, obtained from numerical modal analysis, and variations in the Frequency Response Function (FRF), obtained through harmonic analysis, as more sensitive indicators for damage detection in laminated composite beams. FEA simulations are performed using the commercial FEA software package ANSYS 2021 R1 to obtain the first five flexural natural frequencies and the corresponding displacement mode shapes of both the intact and damaged composite beams. The curvature mode shapes are obtained from the displacement mode shapes data using the central difference approximation method to compute the NCDF. Simultaneously, GFRP composite beams were fabricated by the hand lay-up method, and Experimental Modal Analysis (EMA) was employed to substantiate the FE model and the validity of the numerical results. By combining both numerical and experimental methods, we proved that NCDF and FRF are reliable tools to determine and locate structural damage, even at a comparatively small scale. In general, the results indicate that NCDF is a stable and practically applicable parameter to locate cracks in laminated composite beams and provide meaningful information to be used as guidelines in applications of vibration-based structural health monitoring. Full article

Background and Objectives: Multiple sclerosis (MS) is a chronic neurological disorder causing physical, cognitive, and psychological impairments that affect daily functioning and quality of life (QoL). Psychological distress, cognitive deficits, and reduced physical activity often co-occur, yet their associations with QoL across disability levels are unclear. This study examined these relationships in people with relapsing–remitting MS, stratified by disability severity. Materials and Methods: This cross-sectional study included 149 adults with RRMS. Disability severity was classified as mild, moderate, or severe using the Patient-Determined Disease Steps (PDDS) scale. Psychological distress was assessed using the Depression, Anxiety, and Stress Scale–21 (DASS-21), cognitive function using the Montreal Cognitive Assessment (MoCA), and physical activity using the International Physical Activity Questionnaire (IPAQ). QoL was evaluated using the Multiple Sclerosis International Quality of Life (MusiQoL) questionnaire. Stratified comparative analyses were conducted to examine differences in overall and domain-specific QoL according to levels of psychological distress, cognitive function, and physical activity within disability categories. Results: In participants with mild and moderate disability, higher levels of depression, anxiety, and stress were associated with lower QoL scores, particularly in domains related to activities of daily living, psychological well-being, and symptoms. Higher cognitive function and greater physical activity were associated with more favorable QoL across several domains. In those with severe disability, associations between psychological distress and QoL were less consistent, although stress remained associated with selected QoL domains. Conclusions: Psychological distress, cognitive function, and physical activity show distinct patterns of association with daily functioning and QoL across disability levels in RRMS. Although causal inferences cannot be drawn from this cross-sectional design, disability-stratified analyses provide clinically relevant insights into how these factors co-vary with QoL at different stages of disease severity. Full article

Background/Objectives: Prior studies suggest that rates of Helicobacter pylori colonization are higher among Hispanic immigrants compared to U.S.-born Hispanics. It is unknown whether differences in H. pylori colonization rates among Hispanics are related to immigration status or to cultural factors such as diet. Methods: This was a survey study, conducted among self-identified Hispanics who had an endoscopy for symptoms of gastroesophageal reflux disease (GERD). Qualifying patients completed a telephone survey which included questions about immigration status and the 12-item Short Acculturation Scale for Hispanics (SASH), a validated instrument which measures cultural factors such as language preference and diet. We examined the relationship between SASH factors and H. pylori status, classified based on endoscopic biopsy results. Results: We called 400 patients and 186 completed the survey. Median age was 65 (interquartile range 21 to 82) and 81% were female. Thirty of 186 (16%) respondents were born in the U.S. while 156/186 (84%) were immigrants, primarily from the Dominican Republic. Among immigrants, 69% had immigrated before 1990. Rates of H. pylori were 8/30 (27%) among U.S. born Hispanics compared to 51/156 (33%) among Hispanic immigrants (p = 0.67). Rates of H. pylori were 51/147 (35%) among those with a mostly Latino diet vs. 8/39 (21%) among those with a U.S or mixed diet (p = 0.05). In a multivariable model predicting H. pylori status, a mostly Latino diet was the only cultural predictor which approached statistical significance (p = 0.05) (aOR 2.61, 95% CI 0.94–7.20). Conclusions: Rates of H. pylori colonization were modestly higher among Hispanic immigrants compared to U.S.-born Hispanics. A novel preliminary finding was that higher rates of H. pylori colonization were observed among those who ate a predominantly Latino diet. Full article

Lignin, an abundant and renewable biopolymer, holds significant potential for asphalt modification owing to its unique aromatic structure and reactive functional groups. This review summarizes the main lignin preparation routes and key physicochemical attributes and assesses its applicability for enhancing asphalt performance. The physical incorporation of lignin strengthens the asphalt matrix, improving its viscoelastic properties and resistance to oxidative degradation. These enhancements are mainly attributed to the cross-linking effect of lignin’s polymer chains and the antioxidant capacity of its phenolic hydroxyl groups, which act as free-radical scavengers. At the mixture level, lignin-modified asphalt (LMA) exhibits improved aggregate bonding, leading to enhanced dynamic stability, fatigue resistance, and moisture resilience. Nevertheless, excessive lignin content can have a negative impact on low-temperature ductility and fatigue resistance at intermediate temperatures. This necessitates careful dosage optimization or composite modification with softeners or flexible fibers. Mechanistically, lignin disperses within the asphalt, where its polar groups adsorb onto lighter components to boost high-temperature performance, while its strong interaction with asphaltenes alleviates water-induced damage. Furthermore, life cycle assessment (LCA) studies indicate that lignin integration can substantially reduce or even offset greenhouse gas emissions through bio-based carbon storage. However, the magnitude of the benefit is highly sensitive to lignin production routes, allocation rules, and recycling scenarios. Although the laboratory research results are encouraging, there is a lack of large-scale road tests on LMA. There is also a lack of systematic research on the specific mechanism of how it interacts with asphalt components and changes the asphalt structure at the molecular level. In the future, long-term service-road engineering tests can be designed and implemented to verify the comprehensive performance of LMA under different climates and traffic grades. By using molecular dynamics simulation technology, a complex molecular model containing the four major components of asphalt and lignin can be constructed to study their interaction mechanism at the microscopic level. Full article