Search Results (8,187)

Brownfield greening (BG) has become an important approach to addressing urban land scarcity, environmental remediation, and sustainable urban development. This scoping review analysed 116 English-language publications from the Web of Science and Scopus databases. The review identified five major research themes: pollution and remediation, regeneration design, brownfield characteristics and greening benefits, planning and decision-making, and stakeholder perceptions. Findings indicate a transition from contamination-focused studies towards integrated approaches emphasising ecological restoration, social values, and multifunctional green infrastructure. Research methods have evolved from qualitative case studies to interdisciplinary approaches involving spatial analysis, ecological modelling, scenario simulation, and participatory methods. Existing studies mainly focus on regenerated sites and site-scale analyses, while contamination and remediation processes are often insufficiently incorporated into planning, design, and ecosystem-service assessments. The review highlights the diverse ecological, social, economic, and cultural benefits generated by BG and identifies key research gaps, including the need to better integrate remediation into regeneration processes, to conduct long-term monitoring, to conduct comparative international studies, and to include evidence from underrepresented regions. Overall, BG is increasingly recognised as a multifunctional strategy for sustainable urban regeneration. Full article

Individual tree species classification is essential for detailed forest inventories, ecosystem monitoring, and biodiversity assessment. While UAV-acquired RGB and multispectral (MS) imagery have advanced tree species mapping, most studies focus on a single sensor type. In practice, UAV platforms carry diverse sensors with varying spatial resolutions, spectral bands, radiometric responses, and noise characteristics, introducing domain shifts that limit model generalization across datasets. To overcome these challenges, we propose a supervised cross-sensor transfer learning approach, leveraging a DenseNet-121 model pretrained on high-resolution UAV RGB imagery to improve classification on lower-resolution multispectral imagery with limited labelled data. The adapted model achieved 75% overall accuracy and a macro-F1 score of 0.706, significantly improving over models trained from scratch. Its performance was further evaluated on downsampled UAV MS imagery simulating conventional airborne multispectral photographs, demonstrating robustness and practical applicability for regional-scale forest inventories. This study highlights cross-domain transfer learning as a pathway toward sensor-independent, efficient, and operationally scalable tree species classification. Full article

Background/Objectives: The “Land of Fires” (LF) in the Campania Region has attracted considerable attention due to massive environmental contamination deriving from decades of illegal disposal, burial, and burning of urban, industrial, and toxic waste. Cadmium (Cd) has been repeatedly proven to affect male reproductive function by a plethora of endocrine and non-endocrine mechanisms. The scientific literature is almost devoid of large studies addressing semen quality in this area, particularly by directly correlating seminal parameters to objectively measured pollutant burden in biological samples. Therefore, the aim of the current study was to comprehensively evaluate semen quality of males of reproductive age living in the LF, by correlating seminal parameters to cumulative local male reproductive tract Cd burden objectively quantified in whole semen samples. Methods: The current single-center, observational, cross-sectional study evaluated semen quality in 493 males aged 14–50 (29.07 ± 7.17) years living in three LF municipalities. Moreover, the association of semen quality with whole semen Cd (sCd) levels measured by inductively coupled plasma mass spectrometry (ICP-MS) was addressed in a subgroup of participants; semen samples suitable for semen Cd measurements were available from 383/493 (77.7%) participants of the total cohort, and all analyses involving semen Cd were performed within the measured subset. Results: In the total cohort, seminal parameters were as follows: semen pH 8.32 ± 0.3, semen volume 3.13 ± 1.67 mL, sperm concentration 37.58 ± 30.18 × 10⁶/mL, total count 111.2 ± 104 × 10⁶/ejaculate, total motility 56.83 ± 16.09%, progressive motility 50.22 ± 16.63%, in situ motility 6.72 ± 3.43%, immotile spermatozoa 43.07 ± 15.88%, normal morphology 7.97 ± 4.02%, and viability 64.75 ± 15.34%. Prevalence of normozoospermia and pathological seminal parameters was as follows: normozoospermia 66.5% (328/493), pathological seminal parameters 33.5% (165/493), specifically, oligozoospermia 14% (69/493), cryptozoospermia 0.8% (4/493), azoospermia 2.2% (11/493), asthenozoospermia 3% (15/493), teratozoospermia 0.6% (3/493), oligo-astheno-teratozoospermia 6.1% (30/493), necrozoospermia 5.7% (28/493), and different combined seminal parameters alterations 7.1% (35/493). Whole semen Cd was below (undetectable) or above (detectable) the limit of detection (LoD) (0.2 μg/L) in 66.6% (255/383) and 33.4% (128/383) whole semen samples, respectively. In samples with detectable sCd, sCd level was below or above the median value (0.76 μg/L; min–max 0.1–5.95 μg/L) in 23.4% (30/128) and 76.6% (98/128) whole semen samples, respectively. Participants with detectable sCd levels had a significantly reduced sperm total count (93.28 ± 84.88 × 10⁶/ejaculate vs. 113.2 ± 101.5 × 10⁶/ejaculate; p = 0.037), and normal morphology (7.29 ± 3.71% vs. 8.23 ± 3.91%; p = 0.034), and a significantly lower prevalence of normozoospermia (60.2% vs. 72.2%; p = 0.02) and significantly higher prevalence of pathological seminal parameters (39.8% vs. 27.8%; p = 0.02), specifically, a significantly higher prevalence of oligozoospermia (21.1% vs. 12.6%; p = 0.036) than those with undetectable sCd levels. Whole semen Cd levels were significantly higher in participants with pathological seminal parameters (1.08 ± 0.84 μg/L vs. 0.93 ± 0.74 μg/L; p = 0.037) than those with normozoospermia. Participants with sCd levels above the median value (N = 98) had a significantly reduced sperm concentration (29.12 ± 24.84 × 10⁶/mL vs. 43.62 ± 29.55 × 10⁶/mL; p = 0.015) and displayed a trend towards reduced sperm normal morphology (6.92 ± 3.38% vs. 8.55 ± 4.49%; p = 0.057) than those with sCd levels below the median value (N = 30). Moreover, participants with sCd levels above the median value (N = 98) had a significantly reduced sperm concentration (29.12 ± 24.84 × 10⁶/mL vs. 35.3 ± 26.29 × 10⁶/mL; p = 0.03), total count (85.77 ± 80.52 × 10⁶/ejaculate vs. 113.2 ± 101.5 × 10⁶/ejaculate; p = 0.008) and normal morphology (6.92 ± 3.38% vs. 8.23 ± 3.91%; p = 0.006), and a significantly lower prevalence of normozoospermia (57.1% vs. 72.2%; p = 0.008) and significantly higher prevalence of pathological seminal (42.9% vs. 27.8%; p = 0.008), specifically, a significantly higher prevalence of oligozoospermia (23.5% vs. 12.6%; p = 0.014) than those with undetectable sCd levels. Conclusions: The results of the current study demonstrate an association between the environmental Cd exposure and the impairment of seminal parameters, with a significantly poorer semen quality in participants with detectable sCd, and, more markedly, in those with sCd level above the median value, compared to participants with undetectable sCd, although subgroups comparisons highlighted a homogeneous profile in major confounders including age, BMI, and smoking habits among subgroups of participants with different sCd burden. Full article

Western Guangxi is one of the principal bauxite-producing regions in China; however, its metallogenic model remains unclear. Building on previous studies, this paper systematically examines the ore-forming materials, sedimentary setting, ore genesis, mineral assemblages, diaspore formation, and pisoid (ooid) development of sedimentary bauxite deposits in western Guangxi. Based on this synthesis, a comprehensive metallogenic model is proposed to clarify the formation processes of these deposits. Metallogenic evolution is interpreted to involve five successive stages: weathering, leaching and alteration, deposition, post-depositional modification, and capping–sealing. Ore-forming materials are derived from volcanic ash supplied by the Emeishan Large Igneous Province and the Permian magmatic arc of the Paleo-Tethys. These materials are transported to isolated carbonate platforms and subsequently subjected to intense chemical weathering. During the early stages of ore formation, bauxite undergoes leaching and alteration, and variations in leaching intensity lead to the development of distinct ore types. Future work should focus on the genesis of diaspores, the formation of pisoids (ooids), and ore-forming mechanisms, while also addressing the coupling relationships among deep-time paleoclimate, major geological events, and sedimentary bauxite formation. Such efforts are essential for advancing a comprehensive metallogenic framework for sedimentary bauxites. Full article

The study examines the evolution, knowledge structure, and trends in snowmelt runoff prediction models. It identifies research hotspots, future directions, and offers a theoretical basis for accurate simulation and prediction. Utilizing CiteSpace software, 556 core Chinese and English publications from 2010 to 2025 were visually analyzed. Research on snowmelt runoff simulation shows: (1) Chinese publications are prominent in core journals like “Journal of Glaciology and Geocryology,” while English publications appear in high-impact journals like “Water Resources Research.” (2) Institutions like the University of Chinese Academy of Sciences, the Northwest Institute of Eco-Environment and Resources, and the University of California have formed a cross-regional research network. (3) International collaboration involves 42 countries, with a focus on China, the United States, and India. However, domestic institutional cooperation needs improvement. (4) Research trends in snowmelt runoff simulation have progressed from empirical statistics to remote sensing and model-driven physical mechanisms, and now to the integration of artificial intelligence with physical models. (5) The Chinese literature focuses on cold regions, while the English literature emphasizes intelligent modeling. This shift indicates a move towards “physical–intelligent” hybrid modeling. Future research should address challenges like model applicability in data-scarce areas, improving interpretability of complex models, quantifying uncertainties, and developing physically constrained deep learning models. Collaboration among institutions is crucial for enhancing water resource management and disaster warning systems in cold regions. Full article

Tomato harvesting still relies heavily on manual labor, while factors such as clustered fruit growth, inconsistent ripening stages, occlusion, and complex cultivation environments pose significant challenges to automated harvesting systems and place higher demands on target detection accuracy. To address these issues, a tomato detection method based on the Mamba state space model was proposed, and an improved model termed YOLO-VCW was developed based on YOLOv8n. Specifically, the original C2f module in the backbone network was replaced with the C2f-VSS module to enhance global contextual feature extraction. A Coordinate Attention mechanism was introduced into the feature fusion stage to improve the model’s ability to focus on tomato target regions under complex background and occlusion conditions. In addition, the WIoUv3 loss function was adopted in the detection head to improve localization accuracy and training stability in overlapping fruit scenarios. Experimental results showed that YOLO-VCW achieved a precision of 91.33%, a recall of 86.79%, and an F1-score of 89.00% on the tomato dataset. Compared with YOLOv8n, the proposed model improved precision, recall, F1-score, and mAP₅₀ by 1.90%, 4.43%, 3.25%, and 4.44%, respectively, with only a slight increase in Parameters to 3.9 M. These results demonstrate that YOLO-VCW provides effective and robust performance for tomato target detection in complex environments. Full article

This article reconsiders the emergence of the “military martyr” figure in late antique Christianity, not through the hagiographical narratives alone, but along the axes of cult formation, ritual practice, relic circulation, and public space. Modern scholarship has tended to focus either on whether early Christians served in the Roman army or on the later development of military saint iconography. This study reframes the question, asking instead through what processes the military martyr became a distinct cultic category. At the center of the analysis are two key figures in the fourth-century preaching tradition of Cappadocia: Theodore the Recruit and the Forty Martyrs of Sebaste. The texts attributed to Basil of Caesarea and Gregory of Nyssa construct these figures not merely as witnesses of faith, but as agents who protect communities and intercede and whose sacred power circulates through relics, martyrial spaces, and liturgical practices. When epigraphic evidence, transitional spaces, networks of mobility and lodging, and early visual transformations are considered together, the “military martyr” emerges not as a fixed identity, but as a model of sanctity that intensifies across different regional contexts. Military identity thus becomes embedded within a late antique Christian discourse shaped around protection, mobility, and belonging. Full article

This paper shifts the research perspective from “Buddhist monasteries” to “monastic Buddhism,” using Nālandā Mahāvihāra as a micro-level case to illuminate the broader support mechanism of Indian Buddhist monasteries, with particular focus on the concept of “non-exhaustible endowment”. Drawing on epigraphic evidence, Vinaya texts, and Chinese pilgrims’ records, it finds that major donors supported monasteries through religious rituals, land grants, and cash investments, primarily in the form of landed property and gold and silver currency, which were designated as non-exhaustible endowments. Monasteries then engaged in agriculture, handicrafts, building industry, commerce, and lending, transforming static assets into a non-exhaustible cycle of capital that benefited both monastics and laity. Systems such as Yizhi (robe funds) and Gongfu zhi Zhuang (robe-providing estates) reveal mature financial services that not only liberated monks from economic constraints but also stimulated the cotton textile trade between India and China. The wealth possessed by monasteries was not static but perpetually engaged in a dynamic cycle of capital. Major Buddhist monasteries thus emerged as regional economic engines, which became the core value for continuous royal patronage, as well as the key incentive for their violent destruction by Turkic Muslims. However, the transformation of the religious landscape and economic network in late medieval Bihār was not a simplistic process. Faced with a changing political and religious environment over time, Sufi saints, Jain followers, Shaiva ascetics and other religious communities, each grounded in their own faiths, landholdings, commercial networks and educational systems, gradually displaced, restructured and undermined the Buddhist monastery-centered endowment mechanism, causing Buddhism to progressively lose its regional dominance as an institutionalized religion. Full article

Background/Objectives: Evidence on the role of muscle mechanical (myotonic) properties in athletic performance remains limited in young adult and sub-elite populations, particularly in American football, and sex-specific patterns of association are not well understood. This study aimed to investigate the associations between lower extremity myotonic properties and performance outcomes (strength and balance) in American football athletes, with a specific focus on sex-related differences and candidate predictors. Methods: A cross-sectional design was implemented involving 35 American football athletes (17 female, 18 male). Lower extremity muscle tone, stiffness, and elasticity were assessed using MyotonPRO. Strength parameters (lower limb, handgrip, back, and shoulder internal rotation) and balance performance (static and dynamic under eyes-open and eyes-closed conditions) were evaluated using standardized measurement protocols. Pearson correlation analysis was conducted to examine bivariate associations, followed by Least Absolute Shrinkage and Selection Operator (LASSO) regression to determine candidate predictors while addressing multicollinearity. Results: Male athletes exhibited significantly greater height, body mass, and BMI (p < 0.001), alongside elevated myotonic values compared to females. Correlation analyses indicated distinct sex-specific association patterns between myotonic properties and performance metrics. LASSO regression revealed a distinct sex-specific divergence in strength prediction: female strength was predominantly driven by proximal musculature (quadriceps and hamstring elasticity/stiffness), whereas male strength was anchored by distal musculature (gastrocnemius tone/stiffness). Furthermore, rigorous penalization shrunk nearly all balance coefficients to zero in both sexes, indicating that resting myotonic properties do not independently predict dynamic or static postural control. Conclusions: While lower extremity myotonic properties are candidate predictors of multi-regional strength via sex-specific proximal and distal strategies, they do not independently predict balance performance, suggesting postural control relies primarily on active motor recruitment rather than passive resting mechanics. Given the cross-sectional design of this study, causal inferences cannot be drawn, and these findings should be interpreted accordingly. The observed sex-specific differences may support consideration of individualized, sex-informed training strategies in American football athletes. Full article

Information disorders condition electoral processes, becoming a major institutional concern. In response, the European Union and various fact-checking organisations co-organised the Elections24Check project to curb disinformation in the 2024 European elections. This research analyses the activities, strategies, and editorial behaviour of the five Spanish fact-checking agencies that are integrated into the initiative. Through a content analysis applied to 3256 publications, the findings demonstrate the maturity of the Spanish ecosystem, which led the project by contributing 32.8% of the total content. Strategically, reactive action predominated, except for Newtral, which prioritised prebunking (62.6%). Political scrutiny was minor (6.6%), focusing on major coalitions and far-right leaders. Thematically, highlights included war conflicts, migration, and national/regional frameworks utilised for emotional polarisation, displacing the focus from the strictly European debate. In conclusion, Spain consolidates itself as a cornerstone of European fact-checking. However, the results reveal inefficiencies in the project’s extended timeframe, suggesting more constrained and effective frameworks for election campaigns. Furthermore, the persistence of narratives anchored to local agendas evidences a strategic fragmentation that hinders the construction of a fully pan-European public space. Full article

This study examines the spatial distribution and evolutionary trends of strategic emerging industries (SEIs) in the Beijing–Tianjin–Hebei (BTH) region using the registration information of industrial and commercial enterprises from 2000 to 2020. At the county level, panel data and spatial econometric models were established to empirically test the impact of the development of SEIs on carbon emissions and its spatial spillover effects. The findings point to pronounced imbalances in SEIs development within the BTH, with Tianjin and Hebei registering markedly lower SEI shares than Beijing. In terms of spatial distribution, SEIs in the region have transitioned from a dispersed pattern to a dual-cluster structure and are further evolving into a polycentric structure. The empirical results indicate that SEI development has a notable inhibitory effect on local carbon emissions and demonstrates significant spatial spillover effects. For every 1 percentage point increase in the share of SEIs, the carbon emission intensity at the county level decreases significantly by approximately 0.0204 units. The estimation results for all three weight matrices indicate that the indirect effects are greater than the direct effects. This indicates that the SEI development in neighboring counties has a strong spillover effect on local carbon emissions reductions, and that the spillover effect far exceeds the local effect. Therefore, the development of SEIs in the BTH Region should focus on leveraging local comparative advantages to promote reduction in regional carbon emissions. Full article

Understanding the impact of neighborhood-level factors on stroke prevalence is crucial for addressing existing disparities. However, there is a distinct lack of ecological studies at the census tract level that investigate the social determinants of health (SDOH) influencing stroke prevalence within the U.S. Health and Human Services Region 3 (HHS Region 3: Delaware, Maryland, Pennsylvania, Virginia, West Virginia, and the District of Columbia). This study adopted a multivariate modeling approach to investigate the association between the 13 indicators of the Health Opportunity Index (HOI) and stroke prevalence at the census tract level in HHS Region 3 using four HOI indicator profiles and to highlight the specific SDOHs that are most associated with stroke prevalence. The four HOI indicator profiles include: (a) neighborhood and built environment profile, (b) social and community context profile, (c) resource profile, and (d) economic profile. The methodological approach was quantitative, using secondary data. The sample size was 8021 census tracts. The HOI was estimated for each census tract in the study area. Ordinary least squares regression (OLS) analysis and spatial lag model (SLM) were run to examine whether the 13 indicators of the HOI (categorized into four profiles) reliably predict stroke prevalence and to determine the most appropriate model that best identifies the strongest predictors of stroke prevalence. The results show that affordability, education, spatial segregation, and income inequality indicators were the strongest predictors of stroke prevalence in HHS Region 3. This granular research identifies the neighborhood-level SDOH most strongly linked to stroke prevalence, which can be leveraged to guide the development of targeted public health programs, quality improvement initiatives, resource allocation, and policy creation to combat stroke-related morbidity and mortality across census tracts in HHS Region 3. For example, the built environment, encompassing factors like employment access, affordable housing, and walkability, profoundly influences stroke prevalence and provides urban planners with practical insights for developing healthier, more equitable communities, such as creating neighborhood parks to encourage physical activity, a key factor in stroke prevention. This study also provides neighborhood organizations with the evidence needed to pursue grant funding and raise awareness about the socio-structural influences on stroke outcomes in their respective neighborhoods. Lastly, the insights generated from our study can facilitate collaborative decision-making processes with communities in HHS Region 3 regarding the prioritization of neighborhood-level SDOH for targeted public health interventions. This prioritization should focus on addressing predictors of stroke prevalence that are congruent with the community’s established priorities, thereby maximizing cost savings. Full article

Purpose: This study aimed to map publication trends, topical focus, study designs, and institutional concentration in otology research in Saudi Arabia from 1978 to 2024 to deduce any topical, regional, institutional, or funding disparities in the field of otology in the country. Methods: We conducted a scoping review of studies on human ear diseases in Saudi Arabia, searching PubMed and the Cochrane Library from inception to 31 December 2024. Bibliometric characteristics were charted, topics were mapped to ICD-11 chapters, and temporal trends were modelled using negative binomial regression with a single data-driven breakpoint. Results: Of 2227 records identified, 510 studies were included. Annual output increased by 9.28% (95% CI 7.05–11.55). An inflection occurred around 2017, with slower growth before 2017 (7.2%/year, 95% CI 5.3–9.1) and faster growth from 2018 onward (23.9%/year, 95% CI 18.6–29.4). The institutional affiliation of first authors was concentrated in a small number of organizations, led by King Saud University. Observational studies predominated (441/510), whereas experimental studies were limited (16/510). ICD-11 mapping showed the greatest concentration in “Ear and mastoid” (189/510, 37.1%) and “Factors influencing health status or contact with health services” (179/510, 35.1%) chapters. Funding was reported in 75 studies. Conclusions: PubMed- and Cochrane-indexed otology and hearing health research output in Saudi Arabia has grown substantially, particularly since 2017, but remains concentrated by institution, region, study design, and topic. The dominance of cochlear implant and hearing impairment research, together with limited multicenter, experimental, vestibular, tinnitus, and rehabilitation-focused studies, identifies priorities for future audiology and neurotology research planning. Full article

Edible insects are increasingly recognized as a viable alternative protein source, offering a potentially sustainable approach to addressing global food security challenges. This narrative review critically examines the nutritional composition, environmental advantages, techno-functional attributes, and potential applications of insect-based proteins within human food systems. Edible insects are characterized by high protein content, favourable essential amino acid profiles, and appreciable levels of key micronutrients, rendering them nutritionally comparable to conventional livestock-derived proteins. Moreover, insect production systems generally require substantially lower inputs of land, water, and feed, resulting in comparatively lower greenhouse gas emissions and reduced overall environmental burden. Despite these advantages, broader adoption remains constrained by challenges related to regulatory heterogeneity, food safety concerns, and limited consumer acceptance. Overall, the available evidence suggests that edible insects can function as a nutritionally adequate and environmentally sustainable complementary protein source; however, significant variability in nutrient composition, limitations in standardized safety assessment, and socio-cultural barriers currently restrict their large-scale integration into mainstream food systems. In addition, inconsistencies in analytical methodologies and reliance on in vitro data further complicate cross-study comparisons and translational relevance. Future research should focus on standardization of rearing and processing conditions, harmonization of evaluation frameworks (e.g., protein quality indices), comprehensive safety assessments, and well-designed clinical studies to validate nutritional and functional benefits, alongside the development of effective strategies to improve consumer acceptance and support regulatory alignment across regions. Full article

The rapid proliferation of image editing tools poses unprecedented challenges to information sustainability and social trust, as malicious digital forgeries can easily contaminate public discourse, news reporting, and legal forensics. Advanced image editing techniques make image tampering increasingly difficult for the naked eye to recognize, which requires highly accurate methods for detecting and localizing image tampering. In this paper, an end-to-end network model named AEM-Net is proposed. AEM-Net combines RGB and SRM features to enhance the model’s sensitivity to image details and potentially tampered regions through multi-scale feature extraction and fusion. AEM-Net consists of the HRNet-based Multiscale Feature Extraction Module and the Context-Aggregated Pyramid Localization Module (CAPLM). The multi-scale feature extraction module utilizes the Attentional Perceptual Feature Fusion Module to adaptively focus on the anomalous regions. In contrast, the CAPLM utilizes the Expanded Convolutional Feedback Enhancement Module to effectively exploit contextual feature information for achieving pixel-level localization of tampered regions. Experimental results on public benchmark datasets demonstrate that AEM-Net achieves superior performance compared with existing state-of-the-art methods. In particular, AEM-Net achieves an AUC/F1 score of 95.36%/67.19% on CasiaV1, 93.25%/79.75% on Coverage, and 87.36%/66.24% on NIST16, while requiring only 0.09 s to process a single image, demonstrating both high localization accuracy and computational efficiency. Full article