Search Results (1,857,458)

The role of poverty, specifically the urban poor, in shaping the urban landscape is often solely linked to slums and informal settlements in urban centers. However, contrary to this common perception, this study aims to elucidate how urban poor residents contribute to shaping urban sprawl in developing countries. After identifying patterns of urban sprawl and poverty in the Jakarta Metropolitan Area (JMA) in Indonesia, the study used the Structural Equation Model (SEM) method to analyze survey data from 195 respondents with a per capita income of less than USD 2.15 (IDR 34,000) daily in Tangerang Regency, a western suburb of the JMA. This study shows that urban sprawl and poverty concentration overlap. The urban poor contribute to urban sprawl by purchasing affordable land on the urban periphery, traveling there with their motorized vehicles, and taking advantage of government subsidies. However, rather than gaining more land, they face increased public service costs, a lack of basic facilities, and habitat destruction. Most respondents own their own homes, but almost half of the respondents (41.54%) state that these homes are less than 48 m² in size. It can be concluded that economically vulnerable populations can contribute to urban sprawl when confronted with ineffective planning institutions. Full article

This study examines the association between the formal (de jure) adoption of renewable energy source (RES) support instruments and observed RES deployment outcomes across 36 European countries. We assess whether broader legislative adoption—measured by a transparent breadth/coverage index (SIC/OIL) based on binary coding and equal sector weights—correlates with higher RES shares. The empirical design comprises three complementary steps: (i) hierarchical clustering (Ward’s method; Euclidean distance on standardised indicators) to classify countries by legislative adoption profiles; (ii) parallel clustering of countries by RES utilisation profiles using 10 z-score-standardised outcome indicators (total and sectoral RES shares and per capita RES use by source); and (iii) an integrated comparison of both typologies, followed by a cross-sectional regression test of the OIL–RES association. Legislative and utilisation clusters do not systematically coincide, and the baseline regression shows a weak, statistically insignificant association with very low explanatory power (R² = ≈ 0.015), supporting heterogeneity (H1) rather than a universal positive average relationship (H₂). Interpretation is conservative because SIC/OIL captures policy-mix coverage (not budgets, enforcement, or design stringency) and because some low/zero policy entries may reflect limited source coverage. Overall, the findings suggest that observed RES performance is primarily shaped by country-specific structural conditions (resource endowments, economic capacity, and sustained long-term investment), implying that context-sensitive instruments and stronger implementation capacities should complement formal policy adoption. Full article

Terminal flight phases, particularly landing, are among the most critical, due to low altitude, low speed and the possible presence of crosswinds. Tools capable of accurately modeling and simulating these phases are essential for identifying potential issues and assessing airplane safety integrity. This work focuses on the development of a nonlinear flight simulator devised to handle terminal maneuvers, including ground effect and wind. Such a simulator incorporates the six-degree-of-freedom rigid body equations of motion coupled with a landing gear model and with a basic control that emulates the action of the pilot, while the aircraft aerodynamic characteristics are estimated through a dedicated semi-empirical procedure. The proposed simulator is employed to assess the effect of crosswind and approach speed on different performance indicators, considering a general aviation airplane (Ryan Navion). These indicators include ground roll distance, wing-tip clearance and lateral forces exerted on the landing gear. The results demonstrate that landings are achievable even beyond the demonstrated crosswind limits without encountering wing-tip strikes or rollover and that higher approach speeds could be advisable in strong crosswind conditions. Full article

Background: Nutrition is a fundamental factor in the healthy growth and development of young athletes, as well as in supporting optimal sports performance. This study aimed to explore associations between Mediterranean diet adherence score, BMI and selected physical performance measures in youth handball players, by identifying distinct player profiles through a clustering approach. Methods: Thirty-five male youth handball players participated in the study. Mediterranean diet adherence was evaluated by means of a 16-item KIDMED questionnaire and total score, and physical performance was assessed using the countermovement jump (CMJ) test, the 505-change of direction test, linear straight sprints and isometric handgrip strength. Results: Cluster 1 goes more than one day a week to a fast-food restaurant, skips breakfast on more occasions and consumes sweets and candy more often. In addition, Cluster 2 showed better sprint (p = 0.019–0.053, ES = 0.39–0.47) and CMJ (p = 0.042; ES = 0.40) performance than Cluster 1. Conclusions: These findings present associations between dietary adherence, BMI, and selected physical performance measures in this specific cohort. Given the cross-sectional design and the small sample size, these findings should be interpreted with caution and do not allow causal inferences. Full article

Walking on compliant terrain presents a substantial challenge for individuals with lower-limb amputation, further elevating their already high risk of falling. While powered ankle–foot prostheses have demonstrated adaptability across speeds and rigid terrains, control strategies optimized for soft or compliant surfaces remain underexplored. This work experimentally validates an admittance-based control strategy that dynamically adjusts the quasi-stiffness of powered prostheses to enhance gait stability on compliant ground. Human subject experiments were conducted with three healthy individuals walking on two bilaterally compliant surfaces with ground stiffness values of 63 and $25{\displaystyle \frac{\mathrm{kN}}{\mathrm{m}}}$, representative of real-world soft environments. Controller performance was quantified using phase portraits and two walking stability metrics, offering a direct assessment of fall risk. Compared to a standard phase-variable controller developed for rigid terrain, the proposed admittance controller reduced short-term maximum Lyapunov exponents by an average of 7%, indicating improved local dynamic stability. These results support the potential of adaptive prostheses control to enhance gait stability on compliant surfaces, contributing to the development of more robust human–prosthesis interaction. Full article

Fairness-aware classification with respect to sensitive attributes, such as gender and race, is one of the most important topics in machine learning. Although numerous studies have made outstanding progress through various approaches, one key limitation is that they necessarily require additional labels of sensitive attributes for training. This poses a significant challenge since sensitive attributes typically correspond to personal information. To this end, we propose a novel reweighting method that dynamically gives more weights to underrepresented groups across potential sensitive attributes. Without auxiliary networks or strong assumptions about sensitive attributes, the proposed method significantly improves fairness under various scenarios on benchmark datasets, outperforming the existing state-of-the-art methods. Full article

Floccularia luteovirens is a rare and edible fungus endemic to the Qinghai–Tibet Plateau. Traditional viewpoints have inferred it to be a mycorrhizal fungus based on its spatial association with Kobresia, yet direct morphological evidence (e.g., Hartig net) and molecular evidence is lacking. Through a systematic review of the existing literature, this study found that all current evidence supporting a mycorrhizal relationship is merely indirect inference. In contrast, experiments conducted by our research team demonstrated that this fungus colonizes well on sawdust-based substrates , which is compatible with saprobic growth capacity and does not exclude the possibility of conditional mycorrhizal symbiosis in natural environments. Based on these findings, we propose that F. luteovirens may adopt a facultative nutritional mode to adapt to the alpine environment. Genomic analysis revealed that the CAZyme repertoire of F. luteovirens (including key enzyme families such as GH6, GH7, and AA1) shows high similarity to that of the saprobic fungus Agaricus bisporus and appears to be more comprehensive than that of the ectomycorrhizal fungus Boletus edulis, based on current annotation data. This pattern suggests its potential capacity for lignocellulose degradation. The successful cultivation of its closely related species Lepista sordida on various lignocellulosic substrates further supports this functional potential. This study proposes that F. luteovirens employs a ‘facultative nutrition’ strategy, which presents an alternative perspective to the traditional view of obligate dependence on mycorrhizal symbiosis. These findings contribute to our understanding of fungal adaptation in alpine environments and may inform strategies for artificial domestication of this valuable species. Full article

This article presents the concept of building a discrete event simulation model of a production system in terms of statistical and probabilistic models, which is based on a fragment of a broader production process in the furniture industry. The purpose of the study was to evaluate the efficiency of a single-shift production process during the start-up phase and to determine the impact of implementing two- and three-shift systems. The discrete event simulation model was developed using actual production data collected during a single-shift operation. Scenarios were then designed to identify and quantify the necessary process adjustments required for the successful implementation of two- and three-shift systems. The authors demonstrated that simulation modeling of production processes based on probabilistic distributions provides information that is essential for effective capacity planning. The proposed percentile grids enabled clear visualization and precise assessment of production resource utilization in various shift configurations, facilitating decision-making regarding capacity expansion based on previously assumed data. Full article

Industrial Symbiosis (IS) represents a key strategy within the Circular Economy (CE) paradigm, enabling firms located near enhance competitiveness through the collective exchange and valorisation of resources. By fostering the reuse of water, energy, and materials, IS contributes to the sustainable optimization of manufacturing processes. Nevertheless, the implementation of IS, as a distinct business model, requires the active collaboration of heterogeneous stakeholders, which often generates critical challenges in aligning interests and achieving equitable benefits. This study explores an innovative approach to agri-food symbiosis by evaluating the incorporation of Olive Oil Mill Wastewater (OOMW), a by-product of olive oil production, into bread formulations. This strategy not only mitigates the environmental burden associated with OOMW disposal but also promotes resource efficiency within the olive oil supply chain. Bread samples were produced by varying the concentration of OOMW, and each formulation was assessed according to quality characteristics, consumer acceptability parameters, and sustainability aspects. The selection of the best-performing formulation was conducted through a Multi-Criteria Decision-Making (MCDM) framework, specifically applying the VIKOR method. The findings highlight how the integration of OOMW into bread production can generate a dual benefit, improving food quality while advancing sustainable practices in both the olive oil and bakery sectors. Full article

During the Joseon Dynasty, Korean Buddhism intentionally negotiated its survival and ongoing relevance in response to the predominance of Neo-Confucian state ideology by aligning Buddhist teaching with Confucian ethical ideals, especially filial piety. This process can be clearly observed in two well-known apocryphal texts—the Bulseol daebo bumo eunjung gyeong (佛說大報父母恩重經, Eunjung gyeong) and the Bulseol jangsu myeoljoe hojedongja darani gyeong (佛說長壽滅罪護諸童子陀羅尼經, Jangsu gyeong)—whose acceptance in Joseon Korea was largely dependent on their Confucian-inspired ethical substance. This article explores how the material aspects of these texts—such as woodblock printing methods, visual programs, book formats, and meticulous colophons—operated as means for integrating Buddhist doctrinal themes with Confucian moral standards. By focusing on the 1452 woodblock editions produced at Wŏnamsa Temple, this research highlights materiality as an influential factor in enabling the visual and ritual spread of Buddhist filial ethics and thereby supporting Buddhism’s cultural legitimacy in a Confucian-dominated environment. Using a material culture lens, this study addresses a notable gap in the current research—which has typically emphasized textual interpretation at the expense of material dimensions—and offers insight into how religious groups strategically utilized materiality to adapt within changing socio-cultural contexts. Full article

As a highly representative traditional plant dye, the pigment composition of Cotinus coggygria Scop. (CCS) and its dyeing mechanisms require further study. In this work, pigments were extracted from the trunk of CCS using environmentally friendly solvents, namely ethanol and water. A systematic analysis of the components in the CCS extract and the stripping solutions from dyed cotton fabrics was conducted using LC-MS and UV-Vis spectroscopy, enabling an exploration of how different solvents influence the dissolution of CCS pigments and their dyeing effects on cotton fibers. The results indicated that water is more effective for extracting flavonoid glycosides and proanthocyanidins, whereas ethanol demonstrated superior efficacy in extracting flavonols and flavonol glycosides. Additionally, the dyed samples exhibited significant antibacterial activity against Staphylococcus aureus. The water–ethanol extraction and dyeing technology developed in this study aligns with the principles of sustainable development in green chemistry, providing an environmentally friendly solution for the industrial application of CCS and offering substantial ecological and economic value. Full article

Background: Assessing image quality is critical in medical imaging to ensure diagnostic reliability. Traditional no-reference image quality assessment (IQA) metrics designed for natural images often fail to address the complexities of medical images. This study proposes DermaIQA, a novel no-reference metric for dermoscopic images that aligns quality scores with clinical perception. Methods: We developed a degradation pipeline simulating realistic artifacts without requiring extensive manual labeling. From 812 expert-classified images, we generated a comprehensive dataset (>125,000 images) using controlled blur and compression techniques. An iterative ranking procedure converted these degradations into a continuous quality scale, which was used to train a vision transformer model. Results: The proposed IQA metric outperformed both heuristic and deep learning techniques, achieving 92% accuracy in distinguishing high-quality vs. low-quality images. The approach demonstrated robust generalization when tested on external datasets with different acquisition characteristics, confirming its relevance across varied imaging conditions. Conclusions: DermaIQA represents the first dermatology-specific quality metric that minimizes expert annotation requirements while maintaining clinical relevance. This tool enhances workflows through real-time acquisition feedback and acts as a gatekeeper for AI diagnostic systems, ensuring only high-quality images are processed. The trained model and inference scripts are publicly available. Full article

Background: Three-dimensional (3D) cell cultures are increasingly recognized as effective models for studying diseases and developing cell therapies. In the endocrine pancreas field, organoids/spheroids derived from human islet cells enable advances in diabetes research, drug screening, and tissue engineering. While various 3D culture methods exist, approaches such as magnetic bead-assisted aggregation remain underexplored for endocrine pancreatic cells. Additionally, the use of biological scaffolds, especially those derived from decellularized pancreatic extracellular matrix, provides a biomimetic environment that promotes adhesion, proliferation, and functionality of pancreatic cells. This study presents a protocol for magnetic bead-guided 3D culture of human islet cells within decellularized pancreatic scaffolds. Methods: Human pancreas from adult brain-dead donors was harvested for both islets’ isolation processing and decellularization to generate an acellular pancreatic bioscaffold. Primary human pancreatic islets were first grown in two-dimensional adherent cultures, then enzymatically harvested from the surface and reassembled into three-dimensional clusters using different initial cell amounts (small clusters 0.5 × 10⁴–1 × 10⁴ and larger clusters 2.5 × 10⁴–5 × 10⁴ cells) and then placed within acellular pancreatic slices of different thickness, namely 50 and 90 μm. Optic microscopic examination, scanning electron microscopy analysis, and assessment of insulin and lactate dehydrogenase (LDH) levels were used to evaluate these 3D islet-like cluster cultures. Results: We report the establishment of 3D cultures derived from primary pancreatic islet cells using a magnetic approach in a remarkable 18 h period for the complete formation of 3D clusters. The small clusters (0.5 × 10⁴–1 × 10⁴ cells) exhibited a faster attachment to the acellular matrix, with cells visibly spreading outside the cluster interacting with the bioscaffold slice, when compared to the larger clusters (2.5 × 10⁴–5 × 10⁴ cells). These cells continued to produce insulin, and no statistically significant differences in LDH levels were found under these different conditions. Conclusions: Here, we demonstrate that a magnetic bead-based protocol can be successfully applied to endocrine pancreatic cells, enabling the rapid formation of compact, viable, and functional 3D structures. Despite limitations such as higher cost and prolonged retention of magnetic particles, the approach supports size-dependent interactions with decellularized pancreatic scaffolds. These findings are valuable for researchers designing experiments tailored to specific objectives and underscore the potential of this platform for advancing diabetes research and pancreatic tissue engineering. Full article

Training load monitoring in women’s volleyball is a challenge for optimizing performance and mitigating injury risk. Non-invasive monitoring technologies and machine learning (ML) can support decision-making, but the evidence remains heterogeneous. This scoping review mapped and integrated the evidence on training load management, fatigue, and performance in women’s volleyball and identified gaps. The PRISMA Extension for Scoping Reviews (PRISMA-ScR) and the Joanna Briggs Institute (JBI) framework were followed. A systematic search was conducted in Scopus, Web of Science, and PubMed, covering January 2020 to September 2025. We included studies in female players at any competitive level, including mixed-sex studies meeting a minimum threshold of female participation, that evaluated external and/or internal load, neuromuscular or perceptual fatigue, and/or performance, using standardized data extraction and narrative/thematic synthesis. Fifty-three studies were included. Inertial measurement units (IMUs), force platforms, heart rate (HR) and heart rate variability (HRV), wellness questionnaires, and global/local positioning systems (GPSs/LPSs) were most prevalent. External-load intensity indicators (e.g., high-intensity jumps and accelerations) were reported as more sensitive to fatigue-related changes than accumulated volume. Machine learning models were less frequent and were mainly applied to multi-source integration and fatigue/readiness prediction, with recurring limitations in external validation and interpretability. Women-specific biological moderators, such as the menstrual cycle, were rarely addressed. Full article