Search Results (28,576)

The use of multimodal data can effectively compensate for the lack of temporal resolution in streetscape imagery-based studies and achieve hourly refinement in the study of street walkability dynamics. Exploring the 24 h dynamic pattern of urban street walkability and its diurnal variation characteristics is a crucial step in understanding and responding to the accelerated urban metabolism. Aiming at the shortcomings of existing studies, which are mostly limited to static assessment or only at coarse time scales, this study integrates multimodal data such as streetscape images, remote sensing images of nighttime lights, and text-described crowd activity information and introduces a novel approach to enhance the simulation of pedestrian perception through a visual–textual multimodal deep learning model. A baseline model for dynamic assessment of walkability with street as a spatial unit and hour as a time granularity is generated. In order to deeply explore the dynamic regulation mechanism of street walkability under the influence of diurnal shift, the 24 h dynamic score of walkability is calculated, and the quantification system of walkability diurnal change characteristics is further proposed. The results of spatio-temporal cluster analysis and quantitative calculations show that the intensity of economic activities and pedestrian experience significantly shape the diurnal pattern of walkability, e.g., urban high-energy areas (e.g., along the riverside) show unique nocturnal activity characteristics and abnormal recovery speeds during the dawn transition. This study fills the gap in the study of hourly street dynamics at the micro-scale, and its multimodal assessment framework and dynamic quantitative index system provide important references for future urban spatial dynamics planning. Full article

Background: Soccer is a physically demanding sport characterized by frequent high-intensity efforts, which are particularly relevant in women’s competitions. Improving high-speed running and aerobic capacity has been linked to better on-field performance. Strength training has shown promise in enhancing these physical attributes, but its application in young female soccer players remains underexplored. This study aimed to investigate the effects of a 10-week in-season strength training program on physical performance and match running demands in young female soccer players. Methods: Thirty-two U18 Danish female professional soccer players from two comparable teams voluntarily participated in the study. Teams were allocated to either an experimental group, performing twice-weekly strength training (EG, n = 16) or a control group (CG, n = 16). Vertical jump performance and Yo-Yo IR2 performance as an estimation for maximal oxygen uptake (VO₂max) were assessed both pre and post intervention. Additionally, players’ match external demands (i.e., total distance, distance covered at speeds above 23 km·h⁻¹, and maximum velocity achieved) were monitored using Global Positioning System devices during four matches before and after the intervention. Results: Significant within-group differences were observed across all variables for the EG (p = 0.001; ES = 1.08 to 1.45, large), without differences in the CG (p > 0.01). Between-group analysis indicated significant differences favoring the EG in all variables (F = 27.40 to 47.17; p = 0.001). Conclusions: The application of a 10-week strength training program led to improvements in physical and match running performance among young female soccer players, underscoring the importance of incorporating strength training programs into female soccer periodization to enhance performance. Full article

Background: In a global panorama marked by a progressive rise in obesity, metabolic syndrome, and chronic non-communicable disease prevalence, nutrition education (NE) might play a pivotal role in restoring adoption and strengthening adherence to dietary patterns that protect human health. Therefore, the primary purpose of this work is to review the existing scientific literature studying NE programs aimed at schoolchildren in the decade 2014–2024 and evaluate the effectiveness of intervention tools. Methods: During the first phase of this research, a qualitative analysis was conducted to track similarity in intervention tools and strategies used in nutrition education programs. In the second phase, a quantitative analysis was carried out, extracting common parameters among studies and assessing their potential influence in improving adherence to the Mediterranean diet (MD). Results: A high degree of heterogeneity was observed in educational program designs and intervention tools, which were usually not properly described and justified. All studies that measured adherence to the MD registered an improvement after the intervention, in some cases even higher than 10%. However, this study found no relationship between common parameters (i.e., number of formal tools, number of non-formal tools, lesson duration, and program length) used in NE and the improvement in students’ adherence to MD. Conclusions: This research has contributed to outlining a general framework of NE and to promoting a systematic approach in this research field. Full article

Background/Objectives: Traditional dietary screeners face significant limitations: they rely on subjective self-reporting, average intake estimates, and are influenced by a participant’s awareness of being observed—each of which can distort results. These factors reduce both accuracy and reproducibility. The Guide Against Age-Related Disease (GARD) addresses these issues by applying Assembly Theory to objectively quantify food and food behavior (FFB) complexity. This study aims to validate the GARD as a structured, bias-resistant tool for dietary assessment in clinical and research settings. Methods: The GARD survey was administered in an internal medicine clinic within a suburban hospital system in the southeastern U.S. The tool assessed six daily eating windows, scoring high-complexity FFBs (e.g., fresh plants, social eating, fasting) as +1 and low-complexity FFBs (e.g., ultra-processed foods, refined ingredients, distracted eating) as –1. To minimize bias, patients were unaware of scoring criteria and reported only what they ate the previous day, avoiding broad averages. A computer algorithm then scored responses based on complexity, independent of dietary guidelines. Internal (face, convergent, and discriminant) validity was assessed using Spearman rho correlations. Results: Face validation showed high inter-rater agreement using predefined Assembly Index (A_i) and Copy Number (N_i) thresholds. Positive correlations were found between high-complexity diets and behaviors (rho = 0.533–0.565, p < 0.001), while opposing constructs showed moderate negative correlations (rho = –0.363 to −0.425, p < 0.05). GARD scores aligned with established diet patterns: Mediterranean diets averaged +22; Standard American Diet averaged −10. 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 assessment of the state of health (SOH) of lithium-ion batteries (LIBs) is fundamental to ensuring safe operation. However, due to the complex electrochemical processes during battery operation and the limited availability of training data, accurate estimation of the state of health remains challenging. To address this, this paper proposes a prediction framework based on dual-view voltage signal features and an improved Long Short-Term Memory (LSTM) neural network. By relying solely on readily obtainable voltage signals, the data requirement is greatly reduced; dual-view features, comprising kinetic and aggregated aspects, are extracted based on the underlying reaction mechanisms. To fully leverage the extracted feature information, Scaled Dot-Product Attention (SDPA) is employed to dynamically score all hidden states of the long short-term memory network, adaptively capturing key temporal information. The experimental results based on the NASA PCoE battery dataset indicate that, under various operating conditions, the proposed method achieves an average absolute error below 0.51% and a root mean square error not exceeding 0.58% in state-of-health estimation, demonstrating high predictive accuracy. Full article

Background: Protein kinase R (PKR) inhibits general mRNA translation by phosphorylating the alpha subunit of eukaryotic translation initiation factor 2 (eIF2). PKR also modulates NF-κB signaling during viral infections, but comparative studies of PKR-mediated NF-κB responses across mammalian species and their regulation by viral inhibitors remain largely unexplored. This study aimed to characterize the conserved antiviral and inflammatory roles of mammalian PKR orthologs and investigate their modulation by poxviral inhibitors. Methods: Using reporter gene assays and quantitative RT-PCR, we assessed the impact of 17 mammalian PKR orthologs on general translation inhibition, stress-responsive translation, and NF-κB-dependent induction of target genes. Congenic human and rabbit cell lines infected with a myxoma virus strain lacking PKR inhibitors were used to compare the effects of human and rabbit PKR on viral replication and inflammatory responses. Site-directed mutagenesis was employed to determine key residues responsible for differential sensitivity to the viral inhibitor M156. Results: All 17 mammalian PKR orthologs significantly inhibited general translation, strongly activated stress-responsive ATF4 translation, and robustly induced NF-κB target genes. Inhibition of these responses was specifically mediated by poxviral K3 orthologs that effectively suppressed PKR activation. Comparative analyses showed human and rabbit PKRs similarly inhibited virus replication and induced cytokine transcripts. Amino acid swaps between rabbit PKRs reversed their sensitivity to viral inhibitor M156 and NF-κB activation. Conclusions: Our data show that the tested PKR orthologs exhibit conserved dual antiviral and inflammatory regulatory roles, which can be antagonized by poxviral K3 orthologs that exploit eIF2α mimicry to modulate the PKR-NF-κB axis. Full article

Bisphenol A (BPA) is an endocrine-disrupting chemical with estrogen-like activity, known to impair immune function. BPA may act as a pro-inflammatory agent, reducing immune response efficacy, increasing bacterial load in E. coli infections, and altering immune responses in parasitic infections (Leishmania major, Nippostrongylus brasiliensis, Toxocara canis) through cytokine and regulatory T-cell modulation. Following its ban in food contact materials in Europe, several analogs have been introduced. This study assessed the immunotoxicity of BPA and six analogs, namely BPAP, BPE, BPP, BPS-MAE, BPZ, and TCBPA, by evaluating in vitro the antibody production. Peripheral blood mononuclear cells from healthy male and female donors were exposed to increasing concentrations of each compound for 24 h. After stimulation with rhIL-2 and ODN2006, IgM and IgG secretion were measured on day six. All compounds suppressed antibody production in a concentration-dependent manner, with some sex-related differences. IC₅₀ values showed BPP as the most potent suppressor, and BPE as the weakest. Similarly, IC₂₀ values confirmed these differences in potency, except for BPA being the weakest for IgM in males. Overall, te results do not support the idea that BPA analogs are safer than BPA. Full article

Modern vehicles are rapidly transforming into interconnected cyber–physical systems that rely on advanced sensor technologies and pervasive connectivity to support autonomous functionality. Yet, despite this evolution, standardized methods for quantifying cybersecurity vulnerabilities across critical automotive components remain scarce. This paper introduces a novel hybrid model that integrates expert-driven insights with generative AI tools to adapt and extend the Common Vulnerability Scoring System (CVSS) specifically for autonomous vehicle sensor systems. Following a three-phase methodology, the study conducted a systematic review of 16 peer-reviewed sources (2018–2024), applied CVSS version 4.0 scoring to 15 representative attack types, and evaluated four free source generative AI models—ChatGPT, DeepSeek, Gemini, and Copilot—on a dataset of 117 annotated automotive-related vulnerabilities. Expert validation from 10 domain professionals reveals that Light Detection and Ranging (LiDAR) sensors are the most vulnerable (9 distinct attack types), followed by Radio Detection And Ranging (radar) (8) and ultrasonic (6). Network-based attacks dominate (104 of 117 cases), with 92.3% of the dataset exhibiting low attack complexity and 82.9% requiring no user interaction. The most severe attack vectors, as scored by experts using CVSS, include eavesdropping (7.19), Sybil attacks (6.76), and replay attacks (6.35). Evaluation of large language models (LLMs) showed that DeepSeek achieved an F1 score of 99.07% on network-based attacks, while all models struggled with minority classes such as high complexity (e.g., ChatGPT F1 = 0%, Gemini F1 = 15.38%). The findings highlight the potential of integrating expert insight with AI efficiency to deliver more scalable and accurate vulnerability assessments for modern vehicular systems.This study offers actionable insights for vehicle manufacturers and cybersecurity practitioners, aiming to inform strategic efforts to fortify sensor integrity, optimize network resilience, and ultimately enhance the cybersecurity posture of next-generation autonomous vehicles. Full article

The exponential increase in electronic waste (e-waste) from end-of-life electrical and electronic equipment presents a growing environmental challenge. E-waste contains high concentrations of rare earth elements (REEs), which are classified as critical raw materials (CRMs). Their removal and recovery from contaminated systems not only mitigate pollution but also support resource sustainability within a circular economy framework. The present study proposed the use of hazelnut shells as a biosorbent to reduce water contamination and recover REEs. The sorption capabilities of this lignocellulosic material were assessed and optimized using the response surface methodology (RSM) combined with a Box–Behnken Design (three factors, three levels). Factors such as pH (4 to 8), salinity (0 to 30), and biosorbent dose (0.25 to 0.75 g/L) were evaluated in a complex mixture containing 9 REEs (Y, La, Ce, Pr, Nd, Eu, Gd, Tb and Dy; equimolar concentration of 1 µmol/L). Salinity was found to be the factor with greater significance for REEs sorption efficiency, followed by water pH and biosorbent dose. At a pH of 7, salinity of 0, biosorbent dose of 0.75 g/L, and a contact time of 48 h, optimal conditions were observed, achieving removals of 100% for Gd and Eu and between 81 and 99% for other REEs. Optimized conditions were also predicted to maximize the REEs concentration in the biosorbent, which allowed us to obtain values (total REEs content of 2.69 mg/g) higher than those in some ores. These results underscore the high potential of this agricultural waste with no relevant commercial value to improve water quality while providing an alternative source of elements of interest for reuse (circular economy). Full article

Classical thermodynamics omits rigidity, which property distinguishes solids from gases and liquids. By accounting for rigidity (i.e., Young’s elastic modulus, ϒ), we recently amended historical formulae and moreover linked heat capacity, thermal expansivity, and ϒ. Further exploration is motivation by the importance of classical thermodynamics to various applied sciences. Based on heat performing work, we show here, theoretically, that density times sublimation enthalpy divided by the molar mass (ρΔH_sub/M, energy per volume), depends linearly on ϒ (1 GPa = 10⁹ J m⁻³). Data on diverse metals, non-metallic elements, chalcogenides, simple oxides, alkali halides, and fluorides with cubic structures validate this relationship at ambient conditions. Furthermore, data on hcp metals and molecular solids show that ρΔH_sub/M is proportional to ϒ for anisotropic materials. Proportionality constants vary only from 0.1 to 0.7 among these different material types (>100 substances), which shows that the elastic energy reservoir of solids is large. Proportionality constants depend on whether molecules or atoms are sublimated and are somewhat affected by structure. We show that ductility of refractory, high-ϒ metals affect high-temperature determinations of their ΔH_sub. Our results provide information on sublimation processes and subsequent gas phase reactions, while showing that elasticity of solids is the key parameter needed to assessing their energetics. Implications are highlighted. Full article

Background/objectives: This study evaluated the immunoenhancing effects of Agastache rugosa extract in a cyclophosphamide-induced immunosuppressed mouse model. Methods: Jeju A. rugosa was processed via hot water extraction and 20% ethanol extraction. For immunosuppression induction, 7-week-old male BALB/c mice received intraperitoneal CPA injections (150 mg/kg, day −3; 110 mg/kg, day −1), followed by oral administration of hot water extract (ARE-W) and ethanol extract (ARE-E) at 100 and 300 mg/kg for 14 days. Oral administration of ARE-W and ARE-E was started on day 0, immediately following the final CPA injection on day −1. Immune function was assessed through body weight changes, spleen weight, NK cell activity, IFN-γ production, and splenic lymphocyte proliferation. Results: Results demonstrated that CPA treatment induced comprehensive immune dysfunction, while A. rugosa extracts significantly ameliorated these immunosuppressive conditions. Notably, ARE-W (300 mg/kg) significantly enhanced NK cell cytotoxicity against tumor cells and IFN-γ production compared to the CPA group, and effectively restored spleen weight and lymphocyte proliferation. ARE-E also exhibited dose-dependent immune function recovery; however, ARE-W showed superior efficacy across most immune parameters. Conclusions: These findings suggest that A. rugosa extract, particularly ARE-W, effectively restores immune function in immunosuppressed conditions, indicating potential application as a natural functional material for ameliorating immunosuppression caused by cancer treatment or immune diseases. Full article

There is growing interest in the use of herbicide for the silvicultural practice of tree thinning (i.e., chemical thinning or e-thinning) in New Zealand. Potential benefits of this approach include improved stability of the standing crop in high winds, and safer and lower-cost operations, particularly in steep or remote terrain. As uptake grows, tools for monitoring treatment effectiveness, particularly during the early stages of stress, will become increasingly important. This study evaluated the use of UAV-based multispectral and hyperspectral imagery to detect early herbicide-induced stress in a nine-year-old radiata pine (Pinus radiata D. Don) plantation, based on temporal changes in crown spectral signatures following treatment with metsulfuron-methyl. A staggered-treatment design was used, in which herbicide was applied to a subset of trees in six blocks over several weeks. This staggered design allowed a single UAV acquisition to capture imagery of trees at varying stages of herbicide response, with treated trees ranging from 13 to 47 days after treatment (DAT). Visual canopy assessments were carried out to validate the onset of visible symptoms. Spectral changes either preceded or coincided with the development of significant visible canopy symptoms, which started at 25 DAT. Classification models developed using narrow band hyperspectral indices (NBHI) allowed robust discrimination of treated and non-treated trees as early as 13 DAT (F1 score = 0.73), with stronger results observed at 18 DAT (F1 score = 0.78). Models that used multispectral indices were able to classify treatments with a similar accuracy from 18 DAT (F1 score = 0.78). Across both sensors, pigment-sensitive indices, particularly variants of the Photochemical Reflectance Index, consistently featured among the top predictors at all time points. These findings address a key knowledge gap by demonstrating practical, remote sensing-based solutions for monitoring and characterising herbicide-induced stress in field-grown radiata pine. The 13-to-18 DAT early detection window provides an operational baseline and a target for future research seeking to refine UAV-based detection of chemical thinning. Full article

This study evaluates the feasibility and visibility of electric vehicles (EVs) in Egypt, addressing critical research gaps and proposing actionable strategies to drive adoption. Employing a systematic review of academic, governmental, and industry sources, the paper identifies underexplored areas such as rural–urban adoption disparities, lifecycle assessments of EV batteries, and sociocultural barriers, including gender dynamics and entrenched consumer preferences. Its primary contribution is an interdisciplinary framework that integrates technical aspects, such as grid resilience and climate-related battery degradation, with socioeconomic dimensions, providing a holistic overview of EV feasibility in Egypt tailored to Egypt’s context. Key findings reveal infrastructure limitations, inconsistent policy frameworks, and behavioral skepticism as major hurdles, and highlight the untapped potential of renewable energy integration, particularly through synergies between solar PV generation (e.g., Benban Solar Park) and EV charging infrastructure. Recommendations prioritize policy reforms (e.g., tax incentives, streamlined tariffs), solar-powered charging infrastructure expansion, public awareness campaigns, and local EV manufacturing to stimulate economic growth. The study underscores the urgency of stakeholder collaboration to transform EVs into a mainstream solution, positioning Egypt as a regional leader in sustainable mobility and equitable development. Full article

Ensuring a sustainable and healthy human environment in university dormitories is essential for students’ learning, living, and overall health and well-being. To address this need, we carried out a series of systematic field measurements of the noise levels at 30 dormitories in three representative major urban universities in a major provincial capital city in China and designed and implemented a comprehensive questionnaire and surveyed 1005 students about their perceptions of their acoustic environment. We proposed and applied a sustainability–health-oriented, multidimensional assessment framework to assess the acoustic environment of the dormitories and student responses to natural sound, technological sounds, and human-made sounds. Using the Structural Equation Modeling (SEM) approach combined with the field measurements and student surveys, we identified three categories and six factors on student health and well-being for assessing the acoustic environment of university dormitories. The field data indicated that noise levels at most of the measurement points exceeded the recommended or regulatory thresholds. Higher noise impacts were observed in early mornings and evenings, primarily due to traffic noise and indoor activities. Natural sounds (e.g., wind, birdsong, water flow) were highly valued by students for their positive effect on the students’ pleasantness and satisfaction. Conversely, human and technological sounds (traffic noise, construction noise, and indoor noise from student activities) were deemed highly disturbing. Gender differences were evident in the assessment of the acoustic environment, with male students generally reporting higher levels of the pleasantness and preference for natural sounds compared to female students. Educational backgrounds showed no significant influence on sound perceptions. The findings highlight the need for providing actionable guidelines for dormitory ecological design, such as integrating vertical greening in dormitory design, water features, and biodiversity planting to introduce natural soundscapes, in parallel with developing campus activity standards and lifestyle during noise-sensitive periods. The multidimensional assessment framework will drive a sustainable human–ecology–sound symbiosis in university dormitories, and the category and factor scales to be employed and actions to improve the level of student health and well-being, thus, providing a reference for both research and practice for sustainable cities and communities. Full article