Search Results (230)

Resettlement communities in Qinghai are located in cold, high-altitude regions with dry climates and strong solar radiation. Although not extremely cold, the moderate heating demand aligns well with high solar availability, making passive design highly effective for reducing energy use. This study investigates solar-optimized spatial configurations that enhance passive energy performance while addressing functional settlement needs. Through parametric modeling and climate-responsive simulations, four key spatial parameters are examined: building spacing, courtyard depth, density, and volumetric ratio. The findings highlight the dominant role of front–rear spacing in solar access, with optimal values at 3–4 m for single-story and 5–10 m for two-story buildings, balancing radiation gain and land use efficiency. Courtyard depths under 2.7 m significantly limit south façade exposure due to shading from the opposite courtyard wall under low-angle winter sun. This reduction results in the south façade attaining only 55.7–79.6% of the solar radiation acquisition by an unobstructed south façade (the baseline). Meanwhile, clustered orientations reduce inter-building shading losses by 38–42% compared to dispersed layouts. A three-tiered design framework is proposed: (1) macro-scale solar orientation zoning, (2) meso-scale spacing tailored to building height, and (3) micro-scale courtyard modulation for low-angle winter radiation. Together, these strategies provide practical, scalable guidelines for energy-efficient, climate-responsive settlement design in the alpine regions of Qinghai. Full article

While prior work has explored learner behavior using learning management systems (LMS) data, few studies provide week-level clustering validated against external engagement labels. To understand and assist students in online learning platforms and environments, this study presents a week-level engagement profiling framework for e-learning environments, utilizing K-means clustering and label-based validation. Leveraging log data from 127 students over a 13-week course, 44 activity-based features were engineered to classify student engagement into high, moderate, and low levels. The optimal number of clusters (k = 3) was identified using the elbow method and assessed through internal metrics, including a silhouette score of 0.493 and R² of 0.80. External validation confirmed strong alignment with pre-labeled engagement levels based on activity frequency and weighting. The clustering approach successfully revealed distinct behavioral patterns across engagement tiers, enabling a nuanced understanding of student interaction dynamics over time. Regression analysis further demonstrated a significant association between engagement levels and academic performance, underscoring the model’s potential as an early warning system for identifying at-risk learners. These findings suggest that clustering based on LMS behavior offers a scalable, data-driven strategy for improving learner support, personalizing instruction, and enhancing retention and academic outcomes in digital education settings such as MOOCs. Full article

The ecosystem services (ESs) of forests are the benefits that people derive from forest ecosystems. Their precise recognition is important for differentiating and determining the optimal principles of multifunctional forest management. The aim of this study is to identify some important ESs based on a site classification system at the lowest level—i.e., forest stands, at the forest owner level—as a tool for differentiated management. ESs were assessed within the Czech Republic and are expressed in units in accordance with the very sophisticated Forest Site Classification System. (1) Biomass production: The vertical differentiation of ecological conditions given by vegetation tiers, which reflect the influence of altitude, exposure, and climate, provides a basic overview of biomass production; the highest value is in the fourth vegetation tier, i.e., the Fageta abietis community. Forest stands are able to reach a stock of up to 900–1200 m³·ha⁻¹. The lowest production is found in the eighth vegetation tier, i.e., the Piceeta community, with a wood volume of 150–280 m³·ha⁻¹. (2) Soil conservation function: Geological bedrock, soil characteristics, and the geomorphological shape of the terrain determine which habitats serve a soil conservation function according to forest type sets. (3) The hydricity of the site, depending on the soil type, determines the hydric-water protection function of forest stands. Currently, protective forests occupy 53,629 ha in the Czech Republic; however, two subcategories of protective forests—exceptionally unfavorable locations and natural alpine spruce communities below the forest line—potentially account for 87,578 ha and 15,277 ha, respectively. Forests with an increased soil protection function—a subcategory of special-purpose forests—occupy 133,699 ha. The potential area of soil protection forests could be up to 188,997 ha. Water resource protection zones of the first degree—another subcategory of special-purpose forests—occupy 8092 ha, and there is potentially 289,973 ha of forests serving a water protection function (specifically, a water management function) in the Czech Republic. A separate subcategory of water protection with a bank protection function accounts for 80,529 ha. A completely new approach is presented for practical use by forest owners: based on the characteristics of the habitat, they can obtain information about the fulfillment of the habitat’s ecosystem services and, thus, have basic information for the determination of forest categories and the principles of differentiated management. Full article

Accurate Doppler frequency estimation for Low Earth Orbit (LEO)-based Signals of Opportunity (SoOP) positioning faces significant challenges from extreme dynamics (±40 kHz Doppler shift, 0.4 Hz/ms fluctuation) and severe SNR fluctuations induced by multi-beam switching. Empirical analysis reveals that phased-array beamforming generates three-tiered SNR fluctuation patterns during unpredictable beam handovers, rendering conventional single-algorithm solutions fundamentally inadequate. To address this limitation, we propose KDFE (KNN-Driven Fusion Estimator)—an adaptive framework integrating the Rife–Vincent algorithm and MLE via intelligent switching. Global FFT processing extracts real-time Doppler-SNR parameter pairs, while a KNN-based arbiter dynamically selects the optimal estimator by: (1) Projecting parameter pairs into historical performance space, (2) Identifying the accuracy-optimal algorithm for current beam conditions, and (3) Executing real-time switching to balance accuracy and robustness. This decision model overcomes the accuracy-robustness trade-off by matching algorithmic strengths to beam-specific dynamics, ensuring optimal performance during abrupt SNR transitions and high Doppler rates. Both simulations and field tests demonstrate KDFE’s dual superiority: Doppler estimation errors were reduced by 26.3% (vs. Rife–Vincent) and 67.9% (vs. MLE), and 3D positioning accuracy improved by 13.6% (vs. Rife–Vincent) and 49.7% (vs. MLE). The study establishes a pioneering framework for adaptive LEO-SoOP positioning, delivering a methodological breakthrough for LEO navigation. Full article

The intensifying global competition for cobalt resources and the increasing likelihood of trade decoupling and disruption are profoundly impacting the global energy transition. In a globalized trade environment, a decline in cobalt supply from exporting countries can spread through the trade network, negatively affecting demand countries. Quantitative analysis of the negative impacts of export supply declines in various countries can help identify early risks in the global supply chain, providing a scientific basis for energy security, industrial development, and policy responses. This study constructs a trade network using trade data on metal cobalt, cobalt powder, cobalt concentrate, and ore sand from the upstream (mining, selection, and smelting) stages of the cobalt industry chain across 155 countries and regions from 2000 to 2023. Based on this, an impact diffusion model is established, incorporating the trade volumes and production levels of cobalt resources in each country to measure their resilience to shocks and determine their direct or indirect dependencies. The study then simulates the impact on countries (regions) when each country’s supply is completely interrupted or reduced by 50%. The results show that: (1) The global cobalt trade network exhibits a ‘one superpower, multiple strong players’ characteristic. Congo (DRC) has a far greater destructive power than other countries, while South Africa, Zambia, Australia, Russia, and other countries have higher destructive power due to their strong storage and production capabilities, strong smelting capabilities, or as important trade transit countries. (2) The global cobalt trade network primarily consists of three major risk areas. The African continent, the Philippines and Indonesia in Southeast Asia, Australia in Oceania, and Russia, the United States, China, and the United Kingdom in Eurasia and North America form the primary risk zones for global cobalt trade. (3) When there is a complete disruption or a 50% reduction in export supply, China will suffer the greatest average demand loss, far exceeding the second-tier countries such as the United States, South Africa, and Zambia. In contrast, European countries and other regions worldwide will experience the smallest average demand loss. Full article

To address the modeling complexity and multi-objective collaborative optimization challenges in multi-depot and multiple unmanned aerial vehicle (UAV) delivery task planning, this paper proposes a bi-layer planning framework, which comprehensively considers resource constraints, multi-depot coordination, and the coupling characteristics of path execution. The novelty of this work lies in the seamless integration of an enhanced genetic algorithm and tailored swarm optimization within a unified two-tier architecture. The upper layer tackles the task assignment problem by formulating a multi-objective optimization model aimed at minimizing economic costs, delivery delays, and the number of UAVs deployed. The Enhanced Non-Dominated Sorting Genetic Algorithm II (ENSGA-II) is developed, incorporating heuristic initialization, goal-oriented search operators, an adaptive mutation mechanism, and a staged evolution control strategy to improve solution feasibility and distribution quality. The main contributions are threefold: (1) a novel ENSGA-II design for efficient and well-distributed task allocation; (2) an improved PSO-based path planner with chaotic initialization and adaptive parameters; and (3) comprehensive validation demonstrating substantial gains over baseline methods. The lower layer addresses the path planning problem by establishing a multi-objective model that considers path length, flight risk, and altitude variation. An improved particle swarm optimization (PSO) algorithm is proposed by integrating chaotic initialization, linearly adjusted acceleration coefficients and maximum velocity, a stochastic disturbance-based position update mechanism, and an adaptively tuned inertia weight to enhance algorithmic performance and path generation quality. Simulation results under typical task scenarios demonstrate that the proposed model achieves an average reduction of 47.8% in economic costs and 71.4% in UAV deployment quantity while significantly reducing delivery window violations. The framework exhibits excellent capability in multi-objective collaborative optimization. The ENSGA-II algorithm outperforms baseline algorithms significantly across performance metrics, achieving a hypervolume (HV) value of 1.0771 (improving by 72.35% to 109.82%) and an average inverted generational distance (IGD) of 0.0295, markedly better than those of comparison algorithms (ranging from 0.0893 to 0.2714). The algorithm also demonstrates overwhelming superiority in the C-metric, indicating outstanding global optimization capability in terms of distribution, convergence, and the diversity of the solution set. Moreover, the proposed framework and algorithm are both effective and feasible, offering a novel approach to low-altitude urban logistics delivery problems. Full article

Background: Greater tuberosity fracture–dislocations (GTFDs) represent a distinct subset of proximal humerus fractures, occurring in up to 57% of anterior glenohumeral dislocations. Malreduction may result in impingement, instability, and functional limitation. Treatment is influenced by the displacement magnitude and direction, bone quality, and patient activity level. Methods: This narrative review was based on a comprehensive search of PubMed, Scopus, and Web of Science for English-language articles published between January 2000 and March 2025. Studies on pathomechanics, classification, diagnosis, treatment, and outcomes of GTFDs in adult and pediatric populations were included. Data were analyzed to summarize the current evidence and identify clinical trends. Results: A displacement ≥ 5 mm is the standard surgical threshold, though superior or posterosuperior displacement ≥ 3 mm—and ≥2 mm in overhead athletes—may justify surgery. Conservative treatment remains appropriate for minimally displaced fractures but is associated with up to 48% subacromial impingement and 11% delayed surgery. Surgical options include arthroscopic repair for small or comminuted fragments and open reduction and internal fixation (ORIF) with screws or plates for larger, split-type fractures. Locking plates and double-row suture constructs demonstrate superior biomechanical performance compared with transosseous sutures. Reverse shoulder arthroplasty (RSA) is reserved for elderly patients with poor bone stock, cuff insufficiency, or severe comminution. Pediatric cases require physeal-sparing strategies. Conclusions: GTFDs management demands an individualized approach based on fragment displacement and direction, patient age and activity level, and bone quality. While 5 mm remains the common threshold, lower cutoffs are increasingly adopted in active patients. A tiered treatment algorithm integrating displacement thresholds, fracture morphology, and patient factors is proposed to support surgical decision making. The incorporation of fracture morphologic classifications further refines fixation strategy. Further prospective and pediatric-specific studies are needed to refine treatment algorithms and validate outcomes. Full article

Background: Riboflavin transporter deficiency type 2 is an ultra-rare, yet treatable, inborn error of metabolism. This autosomal recessive disorder is caused by pathogenic mutations in the SLC52A2 gene leading to progressive ataxia, polyneuropathy, and hearing and visual impairment. The early initiation of riboflavin therapy can prevent or mitigate the complications. To date, only 200 cases have been reported, mostly in consanguineous populations. The p.Gly306Arg founder mutation, identified in patients of Lebanese descent, is the most frequently reported worldwide. It was described in a homozygous state in a total of 21 patients. Therefore, studies characterizing the phenotypic spectrum of this mutation remain scarce. Methods: A retrospective review of charts of patients diagnosed with riboflavin transporter deficiency type 2 at a tertiary-care reference center in Lebanon was performed. Clinical, biochemical, and molecular profiles were analyzed and compared to reported cases in the literature. Results: A total of six patients from three unrelated families were diagnosed between 2018 and 2023. All patients exhibited the homozygous founder mutation, p.Gly306Arg, with variable phenotypes, even among family members. The median age of onset was 3 years. Diagnosis was achieved by exome sequencing at a median age of 5 years, as clinical and biochemical profiles were inconsistently suggestive. The response to riboflavin was variable. One patient treated with high-dose riboflavin recovered his motor function, while the others were stabilized. Conclusions: This study expands the current knowledge of the phenotypic spectrum associated with the p.Gly306Arg mutation in the SLC52A2 gene. Increased awareness among physicians of the common manifestations of this rare disorder is crucial for early diagnosis and treatment. In the absence of a consistent clinical or biochemical phenotype, the use of next-generation sequencing as a first-tier diagnostic test may be considered. Full article

(1) Background: The provision of monofunctional or inadequately distributed services in urban park green spaces often constrains residents’ opportunities and diversity for outdoor activities, particularly limiting access and participation for specific age groups or activity preferences. However, functional nodes with temporal and spatial flexibility demonstrate high-quality characteristics of resilient and shared services through integrated development. Accurately identifying user demand provides a solid basis for optimizing the functional configuration of urban parks. (2) Methods: This study took the old city area of Zhengzhou, Henan Province, China, as a case study. By collecting and integrating various types of data, such as geographic spatial data, field investigation data, and behavioral observations, we developed a population demand quantification method and a modular analysis approach for park service functions. This framework enabled correlation analysis between diverse user needs and park services. The study further classified and combined park functions into modular units, quantifying their elastic and shared service capabilities—namely, the adaptive flexibility and shared utilization capacity of park services. Additionally, we established a demand-responsive evaluation system for identifying and diagnosing problem areas in park services based on multi-source data. (3) Results: The demand response index and diagnostic results indicate that the supply of fitness facilities—particularly equipment-based installations—is insufficient within the old urban district of Zhengzhou. Among the three user groups—children, young and middle-aged adults, and the elderly—the elderly population exhibited the lowest demand response index, revealing a significant gap in meeting their specific needs. (4) Conclusions: Based on the research findings, a three-tier optimization strategy is proposed: A. improve green space connectivity to expand the service coverage of parks; B. implement multifunctional overlay and coordinated integration in spatial design based on site characteristics and demand diagnostics; and C. increase the total supply of facilities to enhance spatial efficiency in parks. By integrating the demand assessment data and diagnostic results, this approach enabled a data-driven reorganization of service types and targeted allocation of resources within existing park infrastructure, offering a practical tool and reference for the planning of urban outdoor activity spaces. Full article

Compared to other multi-source image fusion tasks, visible and SAR image fusion faces a lack of training data in deep learning-based methods. Introducing structural priors to design fusion networks is a viable solution. We incorporated the feature hierarchy concept from computer vision, dividing deep features into low-, mid-, and high-level tiers. Based on the complementary modal characteristics of SAR and visible, we designed a fusion architecture that fully analyze and utilize the difference of hierarchical features. Specifically, our framework has two stages. In the cross-modal enhancement stage, a CycleGAN generator-based method for cross-modal interaction and input data enhancement is employed to generate pseudo-modal images. In the fusion stage, we have three innovations: (1) We designed feature extraction branches and fusion strategies differently for each level based on the features of different levels and the complementary modal features of SAR and visible to fully utilize cross-modal complementary features. (2) We proposed the Layered Strictly Nested Framework (LSNF), which emphasizes hierarchical differences and uses hierarchical characteristics, to reduce feature redundancy. (3) Based on visual saliency theory, we proposed a Gradient-weighted Pixel Loss (GWPL), which dynamically assigns higher weights to regions with significant gradient magnitudes, emphasizing high-frequency detail preservation during fusion. Experiments on the YYX-OPT-SAR and WHU-OPT-SAR datasets show that our method outperforms 11 state-of-the-art methods. Ablation studies confirm each component’s contribution. This framework effectively meets remote sensing applications’ high-precision image fusion needs. Full article

Aminoglycoside antibiotics are critical in clinical use for treating severe infections, but they can occasionally cause irreversible sensorineural hearing loss. To establish a rational pathway for otoprotectant discovery, we provide an integrated, three-tier methodology—comprising cell-model selection, transcriptomic analysis, and a gentamicin–Texas Red (GTTR) uptake assay—to guide the development of otoprotective strategies. We first utilized two murine auditory cell lines—UB/OC-2 and HEI-OC1. We focused on TMC1 and OCT2 and further explored the underlying mechanisms of ototoxicity. UB/OC-2 exhibited a higher sensitivity to gentamicin, which correlated with elevated OCT2 expression confirmed via RT-PCR and Western blot. Transcriptomic analysis revealed upregulation of PI3K-Akt, calcium, and GPCR-related stress pathways in gentamicin-treated HEI-OC1 cells. Protein-level analysis further confirmed that gentamicin suppressed phosphorylated Akt while upregulating ER stress markers (GRP78, CHOP) and apoptotic proteins (cleaved caspase 3, PARP). Co-treatment with PI3K inhibitors (LY294002, wortmannin) further suppressed Akt phosphorylation, supporting the role of PI3K-Akt signaling in auditory cells. To visualize drug entry, we used GTTR to evaluate its applicability as a fluorescence-based uptake assay in these cell lines, which were previously employed mainly in cochlear explants. Sodium thiosulfate (STS) and N-acetylcysteine (NAC) significantly decreased GTTR uptake, suggesting a protective effect against gentamicin-induced hair cell damage. In conclusion, our findings showed a complex ototoxic cascade involving OCT2- and TMC1-mediated drug uptake, calcium imbalance, ER stress, and disruption of PI3K-Akt survival signaling. We believe that UB/OC-2 cells serve as a practical in vitro model for mechanistic investigations and screening of otoprotective compounds. Additionally, GTTR may be a simple, effective method for evaluating protective interventions in auditory cell lines. Overall, this study provides molecular-level insights into aminoglycoside-induced ototoxicity and introduces a platform for protective strategies. Full article

Driven by the urgent need to mitigate climate change and achieve net-zero emissions, carbon pricing has emerged as a critical policy tool in major economies worldwide. This study compares carbon pricing in the EU, China, Canada, and Singapore, evaluating effectiveness in emission reductions, with the EU ranking first with high carbon prices, road market coverage, and strict penalties, based on carbon price per capita. Conversely, Singapore’s position as fourth in carbon price per capita among these four most mature carbon markets, Singapore has a high GDP per capita and lower carbon prices. Canada’s fragmented provincial policies and China’s limited market coverage, despite being the top global emitter. Our analysis reveals three critical success factors: (1) higher carbon prices per capita are essential for carbon reduction, (2) the necessity of penalties on carbon price per capita from EUR 20–EUR 100, and (3) expanded market coverage maximizes impact. To address global disparities, we propose a Uniform Carbon Pricing Mechanism under the Global Carbon Resilience Framework (GCRF), based on carbon price per capita tiered pricing: EUR 100/t (developed), EUR 30–50 (developing), and EUR 5–15 (least-developed countries). This balanced system supports vulnerable regions while cutting emissions, proving that fair carbon pricing is crucial for climate goals and economic stability. Full article

Collegiate student-athletes are particularly vulnerable to food insecurity (FI). Prevalence rates range from 9.9% to 65%, although research is limited among this population. Background/Objectives: The challenge of balancing academic and degree progression requirements with training and competition demands can increase the risk for FI among student-athletes. Furthermore, insufficient funds for food has been reported for student-athletes living both on campus and off campus. Methods: This qualitative study employed a phenomenological design and constructivist theoretical framework to explore the experiences of athletic trainers, sports dietitians/nutritionists, and other professionals working with student-athletes in identifying and addressing FI among student-athletes via a series of online focus groups. Results: Participants (n = 27, 12 public colleges) had ≥7 years of collegiate athletics work experience, and most had been in their current position for <3 years. Five approaches to FI screening emerged; specifically, no screening, screening varies by team/sport, informal screening, dietitian screening, and formal screening. Emerging social determinants of FI included financial challenges, competing priorities, cultural/societal impacts, limited life skills, and the food environment. All these factors precipitated on a systems level, including individual, team/athletic department, and university/societal tiers. Conclusions: Athletic department and university policies and budgetary decisions emerged as potential antagonists of food security among student-athletes. FI mitigation strategies for student-athletes must go beyond simply addressing individual factors. Obtainment of food security among collegiate student-athletes requires system changes at the team/athletic department and university tiers. Full article

To address the issue of excessive pessimism caused by demand and supply uncertainties in the green hydrogen supply chain, this study develops a two-tier green hydrogen supply chain model comprising upstream hydrogen production stations and downstream hydrogen refueling stations. This research work investigates optimal ordering and production strategies under stochastic demand and supply conditions. Additionally, option contracts are introduced to share the risks associated with the stochastic output of green hydrogen. This study shows the following: (1) Under decentralized decision-making, the optimal ordering quantity when the hydrogen refueling station is excessively pessimistic is not necessarily lower than the optimal ordering quantity when it is in a rational state, and hydrogen production stations will only operate when the degree of excessive pessimism is relatively low. (2) The initial option ordering quantity is always larger than the minimum execution quantity under the option contract; higher first-order option prices and lower second-order option prices can help to increase the initial option ordering quantity. (3) The option contract is effective in circumventing the negative impact of excessive pessimism at hydrogen production stations on planned production quantities. This study addresses the gap in the existing research regarding excessively pessimistic behaviors and the application of option contracts within the green hydrogen supply chain, providing both theoretical insights and practical guidance for decision-making optimization. This advancement further promotes the sustainable development of the green hydrogen industry. Full article

Traditional villages possess considerable heritage values. Tourism provides an effective way to protect and revitalize the traditional village heritages. Current research has insufficient consideration of tourism potential when constructing the spatial utilization pattern of traditional villages. This study aims to build a spatial utilization pattern of traditional villages within the Yellow River Basin by assessing the tourism potential of each traditional village via the Combined Weight Method and identifying cultural heritage corridors through the application of the Minimum Cumulative Resistance model. The results indicate the following: (1) The traditional villages situated within the Yellow River Basin demonstrate an uneven spatial distribution, with a notable concentration in the middle and lower reaches. (2) The traditional villages located in the middle and lower reaches possess greater tourism potential compared to those found in the upstream, and they are primarily situated in Shanxi and Henan provinces. (3) In light of the cultural attributes, this study proposes a spatial utilization pattern characterized by “four core areas, seven cultural zones, and a three–tiered corridor system”. These findings promote the development of traditional villages while preserving their heritage values, strengthen the communication and integration of regional cultures, and offer practical guidance towards regional coordination and enduring development. Full article