Search Results (4,269)

Musaceae represent one of the main crops of economic and food importance worldwide. In Ecuador, the production and export of bananas, plantains, and abaca are fundamental pillars of the national economy. However, the presence of Fusarium oxysporum f. sp. cubense tropical race 4 (Foc TR4) in neighbouring countries increases the risk to production systems. In this study, information was collected through simple random probability sampling, using a semi-structured survey that included sociodemographic information, crop characteristics, phytosanitary problems, agronomic management practices, and biosecurity measures. To differentiate the profile of producers, a Multiple Correspondence Analysis (MCA) was performed, followed by a hierarchical cluster analysis to establish their types. Additionally, a vulnerability index—Iv (low, medium, high, and critical—is proposed, considering variables such as geographic location, cultivar diversity, and producer management. Among the producers surveyed, 83.3% were men and 16.7% were women; 64% identified as Mestizo, 31% as Montubio, and 1.7% as Afro-Ecuadorian. At the time of the interview, only 38.5% used some biosecurity measures on their farms. Multivariate analyses identified six groups of producers with distinct characteristics, including ethnicity, location, crop type, phytosanitary issues, and adoption of biosecurity measures. Iv ranged from −0.60 to 3.20, with an average of 0.59. Producer groups 1 to 3 presented low to medium vulnerability, while groups 4 to 6 exhibited critical levels. These results demonstrate the diversity of production systems and profiles of Musaceae producers in Ecuador, as well as the need to strengthen biosecurity measures and phytosanitary management to reduce vulnerability to threats such as Foc TR4. Full article

Windows play a crucial role in maintaining indoor thermal comfort, influenced by occupant behavior, passive design strategies, and advanced technologies that contribute to sustainable building practices. Despite advancements in adaptive and occupant-centric design, critical gaps remain unresolved in understanding of multi-climate adaptability, the complex interrelation between window operation and occupant behavior, and the integration of occupant roles into energy-related strategies under emerging technologies. This scoping review synthesizes peer-reviewed studies to assess the importance of window design (geometry, glazing, shading), operational strategies (manual control to AI-driven systems), and technological approaches (passive to smart systems) on thermal comfort, energy performance, and occupant behavior. Using bibliometric and scientometric analyses, the review focuses on four primary research clusters: thermal comfort and occupant behavior, window operation strategies, their impact on energy performance, and sustainability, with an emphasis on emerging trends. The findings highlight that glazing technologies, shading systems, and operational choices have a significant impact on both comfort and energy efficiency. The study develops a framework linking thermal comfort to window operation, occupant behavior, and climate context while conceptualizing a comprehensive design matrix and outlining future research directions aligned with the Sustainable Development Goals (SDG 3: health and well-being, SDG 7: clean energy, and SDG 11: sustainable cities and communities). Full article

Liuyang, the primary fireworks manufacturing base in the world, is demonstrating potential metals pollution risks. In this study, 163 soil samples were collected in Liuyang City, China, for source apportionment, pollution assessment and health risk evaluation using self-organizing map, positive matrix factorization and statistical methods. Geostatistical analysis confirmed high contamination risks from Hg, Cd, Pb, and As. Samples were classified into four groups based on contamination characteristics. Pollution sources included irrigation water, fireworks enterprises, and fireworks packaging material. Cluster 1 exhibited uniformly low metals concentrations, with sampling points widely distributed across the study area. Cluster 2 samples were concentrated in the central and northern regions. The average concentration of Cr was the highest, with irrigation water contributing the most to Cr at 74%. The contribution of fireworks companies and packaging materials was 14% and 12%, respectively. Cluster 3 displayed elevated Hg and Pb levels with distinct spatial banding, where fireworks enterprises contributed 49% (Hg) and 47% (Pb), while packaging materials accounted for 37% (Hg) and 39% (Pb). Cluster 4, gathered in the southeast, showed the highest Cd and As concentrations, with fireworks companies contributing the most with 73% and 82%, respectively. Risk assessment demonstrated that children experienced greater non-carcinogenic risks from oral and dermal exposure to As, Hg, Pb, Cr, and Cd, while adults faced higher inhalation risks for Cr and Cd. Carcinogenic risks exceeded safety thresholds, with children (4.1 × 10⁻⁹–2.0 × 10⁻⁴) more vulnerable than adults (2.9 × 10⁻¹²–1.4 × 10⁻⁴). Asdult carcinogenic risks via ingestion dominated, whereas Cr posed greater risks for children through inhalation. Full article

Background: Women with gestational diabetes mellitus (GDM) are vulnerable to oxidative stress, yet limited data exist on the antioxidant potential of their breast milk. This study aimed to evaluate the antioxidant capacity and basic composition of colostrum in women with GDM compared to healthy controls, focusing on total antioxidant capacity (TAC) and enzymatic antioxidants: superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPx). Methods: The study included 77 lactating mothers: 56 with gestational diabetes (15 managed with diet/exercise—GDM G1; 41 required insulin—GDM G2) and 21 healthy controls. Colostrum samples were collected on days 3–5 postpartum and analyzed for macronutrients and antioxidant enzymes. To enable comparisons across study groups and to explore associations with maternal characteristics, a range of statistical methods was applied. A taxonomic (classification) analysis was then performed using the predictors that best fit the data: study group membership, maternal hypothyroidism history (from the medical interview), and gestational weight gain. Results: TAC was significantly lower in the GDM G2 group compared to GDM G1 and controls (p = 0.001), with no differences in enzymatic antioxidants. The control group had the highest energy (p = 0.048) and dry matter content (p = 0.015), while protein, fat, and carbohydrate levels did not differ significantly. After dividing the study group into four clusters, based on maternal health factors, including GDM status and thyroid function, TAC levels differed significantly between clusters, with the highest values observed in Cluster 3 (healthy controls without thyroid dysfunction) and the lowest in Cluster 2 (GDM and hypothyroidism). Analysis of colostrum composition revealed significant differences in energy content (p = 0.047) and dry matter concentration (p = 0.011), while no significant differences were found in other macronutrients. Conclusions: Our findings suggest that maternal metabolic and endocrine conditions, such as GDM and thyroid dysfunction, may differentially influence the nutritional and functional properties of colostrum—particularly its antioxidant potential. Full article

Intensive human interference has severely disrupted the natural and ecological environments of coastal areas, threatening ecosystem services (ESs). Meanwhile, the relationships between ESs exhibit certain variations across different spatial scales. Therefore, identifying the scale effects of interrelationships among ESs and their underlying driving mechanisms will better support scientific decision-making for the hierarchical and sustainable management of coastal ecosystems. Therefore, employing the Integrated Valuation of ESs and Tradeoffs (InVEST) model combined with GIS spatial visualization techniques, this investigation systematically examined the spatiotemporal distribution of four ESs across three scales (grid, county, and city) during 2000–2020. Complementary statistical approaches (Spearman’s correlation analysis and bivariate Moran’s I) were integrated to systematically quantify evolving ES trade-off/synergy patterns and reveal their spatial self-correlation characteristics. The geographical detector model (GeoDetector) was used to identify the main driving factors affecting ESs at different scales, and combined with bivariate Moran’s I to further visualize the spatial differentiation patterns of these key drivers. The results indicated that: (1) ESs (except for Water yield) generally increased from coastal regions to inland areas, and their spatial distribution tended to become more clustered as the scale increased. (2) Relationships between ESs became stronger at larger scales across all three study levels. These ESs connections showed stronger links at the middle scale (county). (3) Natural factors had the greatest impact on ESs than anthropogenic factors, with both demonstrating increased explanatory power as the scale enlarges. The interactions between factors of the same type generally yield stronger explanatory power than any single factor alone. (4) The spatial aggregation patterns of ESs with different driving factors varied significantly, while the spatial aggregation patterns of ESs with the same driving factor were highly similar across different spatial scales. These findings confirm that natural and social factors exhibit scale dependency and spatial heterogeneity, emphasizing the need for policies to be tailored to specific scales and adapted to local conditions. It provides a basis for future research on multi-scale and region-specific precision regulation of ecosystems. Full article

Accurate aircraft detection in remote sensing imagery is critical for aerospace surveillance, military reconnaissance, and aviation security but remains fundamentally challenged by extreme scale variations, arbitrary orientations, and dense spatial clustering in high-resolution scenes. This paper presents an adaptive attention-guided super-resolution network that integrates multi-scale feature learning with saliency-aware processing to address these challenges. Our architecture introduces three key innovations: (1) A hierarchical coarse-to-fine detection pipeline that first identifies potential regions in downsampled imagery before applying precision refinement, (2) A saliency-aware tile selection module employing learnable attention tokens to dynamically localize aircraft-dense regions without manual thresholds, and (3) A local tile refinement network combining transformer-based super-resolution for target regions with efficient upsampling for background areas. Extensive experiments on DIOR and FAIR1M benchmarks demonstrate state-of-the-art performance, achieving 93.1% AP₅₀ (DIOR) and 83.2% AP₅₀ (FAIR1M), significantly outperforming existing super-resolution-enhanced detectors. The proposed framework offers an adaptive sensing solution for satellite-based aircraft detection, effectively mitigating scale variations and background clutter in real-world operational environments. Full article

The accelerating global urbanization process has posed new challenges to urban planning. With the rapid advancement of artificial intelligence (AI) technology, the application of AI in urban planning has gradually emerged as a prominent research focus. This study systematically reviews the current state, development trends, and challenges of AI applications in urban planning through a combination of bibliometric analysis using Citespace, AI-assisted reading based on generative models, and predictive analysis via support vector machine (SVM) algorithms. The findings reveal the following: (1) The application of AI in urban planning has undergone three stages—namely, the budding stage (January 1984 to January 2017), the rapid development stage (January 2017 to January 2023), and the explosive growth stage (January 2023 to January 2025). (2) Research hotspots have shifted from early-stage basic data integration and fundamental technology exploration to a continuous fusion and iteration of foundational and emerging technologies. (3) Globally, China, the United States, and India are the leading contributors to research in this field, with inter-country collaborations demonstrating regional clustering. (4) High-frequency keywords such as “deep learning,” “machine learning,” and “smart city” are prevalent in the literature, reflecting the application of AI technologies across both macro and micro urban planning scenarios. (5) Based on current research and predictive analysis, the application scenarios of technologies like deep learning and machine learning are expected to continue expanding. At the same time, emerging technologies, including generative AI and explainable AI, are also projected to become focal points of future research. This study offers a technical application guide for urban planning, promotes the scientific integration of AI technologies within the field, and provides both theoretical support and practical guidance for achieving efficient and sustainable urban development. Full article

Objectives: To explore the genetic basis of phage resistance in sequentially generated capsular mutants of phage-resistant Klebsiella pneumoniae using an established phage library. Methods: Sequential induction strategies were employed to obtain phage-resistant K. pneumoniae capsular mutants by exposing ST11-K64 K. pneumoniae Kp2325 to different single phages. Whole genome sequencing and bioinformatic analysis were used to elucidate the capsular-related genetic changes in phage-resistant mutants. Phenotypic changes were assessed through gene complementation, growth assays, phage cleavage spectrum analysis, TEM for phage morphology, CPS analysis, biofilm formation, and virulence assays. Results: Three sequentially generated phage-resistant K. pneumoniae capsular mutants were obtained, designated R1, R2 and R3. The narrowing of the phage cleavage spectrum and the evolutionary trade-offs of biological phenotypes were observed. Key genetic changes included: (1) ISKpn26 insertion disrupting wcaJ in R1; (2) combined wcaJ insertion and 9-bp deletion in waaH in R2; and (3) CPS gene cluster deletion in R3 were identified as key mechanisms of phage resistance in K. pneumoniae mutants R1, R2 and R3, respectively. Conclusions: Sequential exposure to different single phages led to rapid evolution of phage resistance in K. pneumoniae via genetic mutations that disrupt capsular synthesis. These findings highlight the critical role of bacterial capsule in phage–host interactions and emphasize the need to use phage cocktails targeting different types of receptors to counteract the evolution of bacterial defense mechanisms in phage therapy. Full article

The H7N9 influenza viruses, which are capable of causing severe respiratory syndrome in humans, were first discovered to infect humans in 2013 and continue to pose a persistent public health threat. Quail has been proposed as a potential intermediate host that may facilitate the emergence of novel reassorted influenza A viruses with the capacity to infect humans across species barriers; however, information on the biological characterization of quail H7N9 remains limited. In this study, we isolated and identified an avian H7N9 influenza virus from quails, designated as A/quail/Hebei/CH06-07/2018 (H7N9) and abbreviated as CH06-07, in Hebei, China. Phylogenetic analyses revealed that both the HA gene and the NA gene of CH06-07 were clustered in the Eurasian lineage. Furthermore, CH06-07 exhibited binding affinity for both α2,3-linked and α2,6-linked sialic acid receptors and demonstrated high pathogenicity in both quails and mice. Notably, transmission studies revealed that CH06-07 not only exhibited efficient inter-quail transmission and inter-guinea pig transmission but also demonstrated effective cross-species transmission. Importantly, infected quails and guinea pigs generated significant quantities of viral aerosols (≥18,998 ± 1672 copies per liter of air at 3 days post-infection), and infectious viruses were successfully recovered from environmental aerosols. These findings highlight the necessity for continuous surveillance of the prevalence of quail-origin H7N9 influenza A viruses in poultry populations due to their potential threat to human health. Full article

Driver emotion recognition is vital for intelligent driver assistance systems, where the accurate detection of emotional states enhances both safety and user experience. Current approaches, however, require extensive labeled datasets, perform poorly under real-world conditions, and degrade with class imbalance. To overcome these challenges, we propose the Active Learning and Deep Attention Mechanism (ALDAM) framework. ALDAM introduces three key innovations: (1) an active learning cycle that reduces labeling effort by ~40%; (2) a weighted-cluster loss that mitigates class imbalance; and (3) a deep attention mechanism that strengthens feature selection under occlusion, pose variation, and illumination changes. Evaluated on four benchmark datasets (FER-2013, AffectNet, CK+, and EMOTIC), ALDAM achieves an average accuracy of 97.58%, F1-score of 98.64%, and AUC of 98.76% surpassing CNN-based models and advanced baselines such as SE-ResNet-50. These results establish ALDAM as a robust and efficient solution for real-time driver emotion recognition. Full article

Compassion fatigue is a widely recognized phenomenon in human care settings, but it has been little explored in the veterinary field, despite sharing many of the same determinants. This study aimed to (1) identify distinct emotional risk profiles in veterinarians based on their levels of compassion fatigue and satisfaction; (2) estimate the relative prevalence of compassion fatigue in each of these profiles; and (3) analyze the predictive value of sociodemographic variables (gender, age, cohabitation) on belonging to these profiles. A cross-sectional study was conducted with 135 practising veterinarians. An abbreviated version of the ProQOL scale, adapted to the animal context, was used. Its two-dimensional structure (compassion fatigue and satisfaction) was validated using confirmatory factor analysis. Hierarchical cluster and k-means analyses were performed on the factor scores, which identified four emotional profiles: (1) intense emotional involvement, (2) emotional detachment, (3) functional distancing, and (4) high emotional risk. The latter grouped 23% of the sample, while 50.4% presented significant levels of emotional exhaustion. Finally, an ordinal regression was applied, which showed that being over 44 years of age (OR = 2.11) and living with a partner (OR = 1.94) increase perceived emotional risk, with no significant effects of gender. The findings highlight the need for training initiatives that enhance emotional regulation and communication with animal guardians or owners, while promoting sustainable, ethically responsible, and emotionally healthy professional practice. Full article

Welding-based manufacturing and joining processes are extensively used in various areas of industrial production. While welding has been used as a primary method of joining in many applications, its capability to fabricate metal components such as the Wire Arc Additive Manufacturing (WAAM) method should not be undermined. WAAM is a promising method for producing large metal parts, but it is still prone to defects such as porosity that can reduce structural reliability. To ensure these defects are found and measured in a consistent way, inspection methods must be tied directly to code-based acceptance limits. In this work, a three-pass WAAM joint specimen was made in a welded-joint configuration using robotic GMAW-based deposition. This setup provided a stable surface for Phased Array Ultrasonic Testing (PAUT) while still preserving WAAM process conditions. The specimen, which was intentionally seeded with porosity, was divided into five zones and inspected using the 6 dB drop method for defect length and amplitude-based classification, with AWS D1.5 serving as the reference code. The results showed that porosity was not uniform across the bead. Zones 1 and 3 contained the longest clusters (15 mm and 16.5 mm in length) and exceeded AWS length thresholds, while amplitude-based classification suggested they were less critical than other regions. This difference shows the risk of relying on only one criterion. By embedding these results in a DMAIC (Define–Measure–Analyze–Improve–Control) workflow, the inspection outcomes were linked to likely causes such as unstable shielding and cooling effects. Overall, the study demonstrates a code-referenced, dual-criteria approach that can strengthen quality control for WAAM. Full article

Background/Objectives: Colorectal cancer (CRC) is the leading cancer-related death in Puerto Rico (PR). Yet CRC screening (CRCS) rates remain low. We developed ¡Salud!, por la Vida, an educational intervention aiming to increase CRCS among age-eligible adults living in PR. Methods: We conducted a cluster randomized controlled trial among adults 50–75 years old at Federally Qualified Health Clinics in PR. Participants could not have a history of CRC nor be currently adherent to CRCS guidelines for a fecal occult blood test (FOBT) or fecal immunochemical test (FIT) (within last year) or colonoscopy (within last 5–10 years). Out of 445 randomized participants, 355 completed the study procedures (Control: 277; Intervention: 78) and were included in the main analysis. Participants in the intervention arm completed baseline and follow-up questionnaires alongside the educational intervention (at baseline) and two reminder calls (before follow-up) within a four-month period. Control arm participants only completed baseline and follow-up questionnaires within the same period. All participants were followed up to assess CRCS completion. Results: Post-trial screening rates were significantly higher in the intervention group: FOBT/FIT (55% vs. 39%, p = 0.02), colonoscopy (10% vs. 3%, p = 0.02), and any CRCS (60% vs. 41%, p < 0.01). Compared to controls, those in the intervention group showed a 48% higher probability of undergoing any CRCS (RR = 1.48, 95%CI: 1.17, 1.86), were 1.4 times more likely to complete a FOBT/FIT (RR = 1.40, 95%CI: 1.09, 1.80), and were over 3 times more likely to undergo a colonoscopy (RR = 3.16, 95%CI: 1.26, 7.91). Conclusions: The findings underscore the efficacy of the intervention in increasing CRCS uptake, potentially preventing late-stage detection and reducing CRC mortality in PR. Full article

Population mobility is increasingly crucial for regional development. However, current studies often neglect the impact of rapid digitalization. This study adopts a three-stage analytical framework derived from the Techno-Economic Paradigm across its incubation, penetration, and maturity phases to examine how digital technology evolution has reshaped China’s population mobility patterns. Through ERGM and social network analysis, we found the following: (1) During the incubation period (1980s–2000), digital technology enhanced economies of scale, leading to a siphoning effect of the population from inland to coastal areas. (2) In the penetration phase (2000–2017), digital technology had a dual effect. Automation weakened coastal agglomeration by replacing labor, while the digital industry created new inland clusters of employment, ultimately reshaping population mobility into a multi-center structure. (3) In the maturity phase (2018–present), the concentration of skilled workers in technology hubs and the dispersal of displaced labor to less digitally advanced areas formed a multi-centered and networked population mobility pattern, thereby enhancing the sustainability and spatial balance of the urban system through functional specialization and the matching of skill profiles to city roles. Full article

Rhizoctonia solani (Rs) and Sclerotinia sclerotiorum (Ss) are devastating pathogens of rice and rapeseed, contributing 20–69% and 10–50% of yield losses, respectively. These pathogens develop resistant overwintering and/or oversummering sclerotia, which serve as inocula for infection in the subsequent season under favorable conditions. The present study was designed to investigate the month-wise variation in microbial diversity by mixing Rs and Ss sclerotia separately in rice-rapeseed rotation field soil, thereby identifying key microbial players associated with specific sclerotia and their implications for subsequent crops. Therefore, we incubated 2.5 g of Rs and Ss sclerotia in 100 g of soil for 3 months to mimic the field conditions and subjected month-wise soil samples to 16S rRNA and ITS2 sequencing. Data analysis of bacterial communities revealed diversity, richness, and evenness in Ss treated soil samples compared to the control, while fungal communities exhibited less diversity. These results were also evident in PCoA and hierarchical clustering, where control and treated samples were scattered in 16S rRNA and ITS sequencing. Genus level diversity exhibited enrichment of bacterial genera with known beneficial potential, notably Acidibacter, Stenotrophobacter, Sphingomonas, Flavisolibacter, Gaiella, and Neobacillus in control. Beneficial bacterial genera such as Ramlibacter, Geomonas, Kofleria, Nitrospira, and Paraflavitalea were enriched in Ss treated soil samples. The addition of Ss and Rs sclerotia activated several beneficial fungi, notably Trichoderma, Talaromyces, Clonostachys in Ss treated samples, and Vermispora, Hyalorbilia, Mortierella, Lecanicillium in Rs treated samples. Additionally, Rs treated soil samples also activated pathogenic genera, including Typhula, Fusarium, and Rhizoctonia. Sclerotia in soil modulates the microbiome and activates beneficial and pathogenic microbes. During the off-season, the Sclerotinia inoculum pressure in the soil reduces, and it is safe to grow crops next season. Whereas, in the case of Rhizoctonia infected soil, it is suggested to avoid growing crops susceptible to wilt, root rot, and blight. However, field experiments to understand the pathogen–pathogen interactions around the sclerotiosphere require further exploration. Full article