Search Results (10,986)

This study examines the potential implications of the EU–Mercosur free trade agreement for the Polish horticultural sector, with particular emphasis on sustainability, trade competitiveness, and structural complementarities between the regions. Drawing on production, trade, and demographic data for the EU, Poland, and Mercosur countries, the analysis evaluates the alignment of horticultural supply and demand structures, the degree of intra-industry exchange, and the economic conditions shaping bilateral trade. The research applies the Grubel–Lloyd index and a Poisson Pseudo-Maximum Likelihood (PPML) gravity model to assess the determinants of Poland’s horticultural exports to Mercosur. The results indicate that trade remains predominantly inter-industry, reflecting substantial differences in agricultural specialisation and regulatory frameworks. At the same time, rising income levels in Mercosur, together with selected product-level complementarities, indicate emerging export opportunities for Poland. Poland’s trade with the Southern Common Market remains mainly as inter-industry, with the greatest export potential concentrated in high-value-added processed goods. Divergent sustainability standards, particularly in pesticide use, environmental regulation, and carbon-intensive transport, pose structural challenges that may affect the competitiveness and environmental footprint of expanded trade. Overall, the findings provide evidence that closer integration with Mercosur may support export diversification, but requires careful alignment with the EU’s sustainability objectives to ensure resilient and environmentally responsible development of the horticultural sector. Full article

Cerebrovascular diseases are a leading cause of global mortality, underscoring the need for objective and quantitative 3D visualization of cerebral vasculature from dynamic imaging modalities. Conventional analysis is often labor-intensive, subjective, and prone to errors due to image noise and subtraction artifacts. This study tackles the challenge of achieving fast and accurate volumetric reconstruction from angiography sequences. We propose a multi-stage pipeline that begins with image restoration to enhance input quality, followed by neural segmentation to extract vascular structures. Camera poses and sparse geometry are estimated through Structure-from-Motion, and these reconstructions are refined by leveraging the segmentation maps to isolate vessel-specific features. The resulting data are then used to initialize and optimize a 3D Gaussian Splatting model, enabling anatomically precise representation of cerebral vasculature. The integration of deep neural segmentation priors with explicit geometric initialization yields highly detailed 3D reconstructions of cerebral angiography. The resulting models leverage the computational efficiency of 3D Gaussian Splatting, achieving near-real-time rendering performance competitive with state-of-the-art reconstruction methods. The segmentation of brain vessels using nnU-Net and our trained model achieved an accuracy of 84.21%, highlighting the improvement in the performance of the proposed approach. Overall, our pipeline significantly improves both the efficiency and accuracy of volumetric cerebral vasculature reconstruction, providing a robust foundation for quantitative clinical analysis and enhanced guidance during endovascular procedures. Full article

We argue that a multidisciplinary approach is essential to identify deoxygenation impacts on marine ecosystems and fisheries, bridging across the traditionally separate fields of oceanography and economics. Oceanography reveals physical and chemical drivers of deoxygenation, and assesses potential biological impacts based on the physiological and ecological characteristics of organisms and communities. Economics identifies the consequences of human activities associated with the utilization of the changing ocean, particularly in relation to deoxygenation. Economic data, models and analysis can contribute to determining the future directions toward achieving a healthy ocean in the context of deoxygenation. However, differing perspectives on the value of the ocean may lead to conflicts between short-term economic gains and long-term sustainability. Uncertainties in fish populations and deoxygenation modeling add complexity. Despite the difficulties involved, the interdisciplinary view of economics and oceanography offers a more comprehensive understanding of the complexities of ocean deoxygenation and its impacts on both the ocean and people. In order to address the challenges posed by deoxygenation and its impacts, and to develop mitigation and adaptation strategies, it is essential to establish a strong collaboration between experts of oceanography and fisheries economics. Full article

Habitat micromodification poses significant challenges to wildlife, necessitating adaptive responses. This study aimed to investigate how such habitat alterations affect the dietary intake and gut microbiota of Père David’s deer (Elaphurus davidianus). A total of 25 fresh fecal samples were collected from Père David’s deer through non-invasive sampling in Tianjin Qilihai Wetland across three distinct phases of habitat micromodification: pre-change (N = 10), under-change (N = 8), and post-change (N = 7). Dietary composition was analyzed via microscopic identification of plant residues, and gut microbiota structure was characterized using 16S rRNA high-throughput sequencing. Results showed that the diet shifted significantly across phases, with 33 plant species from 20 families identified. Meanwhile, the core gut microbiota remained structurally stable. The phyla Firmicutes and Bacteroidota consistently dominated, despite fluctuations in some specific bacterial genera. Functional prediction indicated minimal change in core microbial metabolic pathways. Correlation analysis suggested that key dietary plants were linked to the abundance of specific, functionally relevant microbial taxa. In conclusion, this study demonstrates that the gut microbiota of Père David’s deer exhibits marked resilience to dietary shifts induced by habitat micromodification. This stability is underpinned by functional redundancy within the microbial community and the consistent intake of fibrous plants, representing a key adaptive mechanism. Our findings highlight that integrating non-invasive monitoring of diet and microbiota can effectively assess the adaptive capacity of endangered ungulates to managed habitat change, thereby informing more resilient conservation strategies. Full article

Background: The global dissemination of multidrug-resistant (MDR) Salmonella poses a persistent and serious threat to food safety systems. As a leading poultry-exporting country, Thailand requires a comprehensive understanding of how resistance plasmids spread among Salmonella populations within its chicken production chain. Methods: Between March 2023 and February 2024, 223 Salmonella isolates were collected from chicken slaughterhouses and markets in northeastern Thailand. From these, 19 representative MDR Salmonella enterica isolates, selected based on distinct spatiotemporal distributions, underwent whole-genome sequencing. Genomic analyses included sequence typing, core-genome phylogenetics, and screening for antimicrobial resistance genes. Plasmid replicons were identified, and functional annotation was performed using the COG database. Results: Phylogenetic analysis revealed 11 distinct sequence types within the population. Among these, ST1541 and ST50 showed clear evidence of clonal transmission across different production stages, with a notable clustering pattern observed during the winter season. All sequenced isolates exhibited an MDR phenotype. Plasmids were detected in 78.9% of isolates, with conjugative plasmids being the most frequent type (57.9%). The β-lactamase gene bla_TEM-60 was the most prevalent (78.9%) and showed a strong correlation (r ≥ 0.7) with resistance to both ampicillin and cefotaxime. Functional annotation further revealed an abundance of genes involved in carbohydrate and amino acid metabolism across all isolates. Conclusions: These findings indicate that MDR Salmonella dissemination is driven by two synergistic mechanisms: the clonal expansion of fit lineages and the horizontal transfer of conjugative plasmids harboring β-lactamase genes. We identified IncI-gamma-K1 and Col-related plasmids as key vectors in this process. This study advocates for targeted interventions, guided by a One Health approach, that specifically aim to disrupt plasmid transmission at critical control points, such as slaughterhouses, to curb the spread of antimicrobial resistance. Full article

Biomimetic quadruped robots, inspired by the musculoskeletal systems of animals, employ pneumatic artificial muscles (PAMs) as compliant actuators to achieve flexible, efficient, and adaptive locomotion. This study focuses on a pneumatic artificial muscle (PAM)-driven biomimetic leg joints system. First, its kinematic and dynamic models are established. Next, to address the challenges posed by the strong nonlinearities and complex time-varying uncertainties inherent in PAMs, an adaptive robust control algorithm is proposed by employing the Udwadia controller. Rigorous theoretical analysis of the adaptive robust control algorithm is verified via the Lyapunov stability method. Finally, numerical simulations and hardware experiments are conducted on the PAM-driven biomimetic leg joints system under desired trajectories, where the adaptive robust control algorithm is systematically compared with three conventional control algorithm to evaluate its control performance. The experimental results show that the proposed controller achieves a maximum tracking error of within 0.05 rad for the hip joint and within 0.1 rad, highlighting its strong potential for practical deployment in real-world environments. Full article

The impact of sewage discharge on water quality in reversing rivers has rarely received attention. This study simulated water quality changes in Maoergang River (a water body with counter flow conditions) affected by effluent discharge from Yangjiabu Sewage Treatment Plant. The results revealed that the diffusion patterns of COD, NH₄⁺-N, and TP in the study area were largely consistent; however, different hydrological conditions and discharge scenarios resulted in obvious differences in pollutant distribution. During the dry season, regardless of normal or counter folow conditions, the Maoergang and Xitiaoxi downstream were the primary affected segments. Regulated by hydrodynamic forces, under normal flow conditions, the Xitiaoxi downstream received a higher pollutant load while the Xitiaoxi upstream received minimal inputs. In the wet season, pollutant concentrations were generally lower due to the dilution effect of increased runoff; notably, the primary affected segments shifted to the downstream reaches of Maoergang and Huanchenghe. Under accidental discharge scenarios, excessive sewage release expanded the scope of pollution impacts, with elevated pollutant concentrations causing water quality non-compliance in parts of the upstream and downstream Xitiaoxi—both of which are within the germplasm resource protection zone. Predictive analysis indicated that when the sewage treatment plant’s discharge was reduced to 1.0 × 10⁴ t·d⁻¹, the receiving water bodies could still meet local water quality standards, even under the counter flow hydrological conditions, which pose the greatest threat to water quality during the dry season. Full article

This paper provides a systematic review of the progress in encoded microsphere suspension array technology and its application in the multiplex detection of mycotoxins. Mycotoxins are diverse and frequently coexist in food matrices, leading to synergistic toxic effects. This poses significant challenges to existing risk assessment systems. Current multiplex detection methods still face technical bottlenecks such as target loss, matrix interference, and reliance on large-scale instruments. Suspension array technology based on encoded microspheres, combined with efficient signal amplification strategies, offers an ideal platform for achieving highly sensitive and high-throughput analysis of mycotoxins. This paper systematically reviews the core aspects of this technology, including encoding strategies such as physical, optical, and multi-dimensional approaches, along with new encoding materials like aggregation-induced emission materials and fluorescent proteins. It further covers matrix materials and preparation methods with an emphasis on green, biocompatible options and integrated fabrication techniques, as well as signal amplification mechanisms based on nucleic acid amplification, enzyme catalysis, and nanomaterials. The integration of magnetic separation techniques and the combination with portable, smartphone-based platforms for intelligent on-site detection are also highlighted. Finally, this review outlines future development trends such as the incorporation of artificial intelligence, 3D printing, and smart algorithms, aiming to provide theoretical references and technical support for research and applications in related fields. Full article

Drought poses a severe threat to grassland biodiversity and ecosystem function. However, quantitative frameworks that capture the interactive effects of drought intensity and duration on productivity remain scarce, limiting impact assessment accuracy. To bridge this gap, we developed and validated a novel hybrid modeling framework to quantify drought impacts on net primary productivity (NPP) across Inner Mongolia’s major grasslands (1961–2012). Drought was characterized using the Standardized Precipitation Index (SPI), and ecosystem productivity was simulated with the Biome-BGC model. Our core innovation is the hybrid model, which integrates linear and nonlinear components to explicitly capture the compounded, nonlinear influence of combined drought intensity and duration. This represents a significant advance over conventional single-perspective approaches. Key results demonstrate that the hybrid model substantially outperforms linear and nonlinear models alone, yielding highly significant regression equations for all grassland types (meadow, typical, desert; all p < 0.001). Independent validation confirmed its robustness and high predictive skill (NSE ≈ 0.868, RMSE = 20.09 gC/m²/yr). The analysis reveals two critical findings: (1) drought duration is a stronger driver of productivity decline than instantaneous intensity, and (2) desert grasslands are the most vulnerable, followed by typical and meadow grasslands. The hybrid model serves as a practical tool for estimating site-specific productivity loss, directly informing grassland management priorities, adaptive grazing strategies, and early-warning system design. Beyond immediate applications, this framework provides a transferable methodology for assessing drought-induced vulnerability in biodiverse ecosystems, supporting conservation and climate-adaptive management. Full article

This article studies the application of deep neural networks for automatic building detection in aerial RGB images. Special focus is put on accuracy robustness in both well-structured and poorly planned urban scenarios, which pose significant challenges due to occlusions, irregular building layouts, and limited contextual cues. The applied methodology considers several CNNs using only RBG images as input, and both validation and transfer capabilities are studied. U-Net-based models achieve the highest single-model accuracy, with an Intersection over Union ($IoU$) of 0.9101. A soft-voting ensemble of the best U-Net models further increases performance, reaching a best ensemble $IoU$ of 0.9665, improving over state-of-the-art building detection methods on standard benchmarks. The approach demonstrates strong generalization using only RGB imagery, supporting scalable, low-cost applications in urban planning and geospatial analysis. Full article

This paper proposes a method for improving machine tool linear feed system accuracy by considering the geometric error shape of the guideway. First, a mathematical model relating guideway errors to worktable pose errors is established using static force equilibrium principles and deformation coordination equations. The impact of different guideway geometric error-shape combinations of linear feed system accuracy is analyzed. It is determined under which combination of guideway error shapes the linear feed system achieves the highest accuracy. Second, a finite element analysis model of the machine tool linear feed system is developed to examine how guideway geometric error shapes affect the error-averaging effect. This is compared with conventional design methods that disregard error shapes. Finally, experimental verification confirms both the effectiveness and broader applicability of the guideway error-shape design methodology. The results show that controlling the error shape of guideways can relax the requirement for guideway amplitude, thereby reducing machining difficulty and production costs. Full article

Additive manufacturing (AM) has emerged as a pivotal technology in component fabrication, renowned for its capabilities in freeform fabrication, material efficiency, and integrated design-to-manufacturing processes. As a critical branch of AM, metal additive manufacturing (MAM) has garnered significant attention for producing metal parts. However, process anomalies during MAM can pose safety risks, while internal defects in as-built parts detrimentally affect their service performance. These concerns underscore the necessity for robust in-process monitoring of both the MAM process and the quality of the resulting components. This review first delineates common MAM techniques and popular in-process monitoring methods. It then elaborates on the fundamental principles of acoustic emission (AE), including the configuration of AE systems and methods for extracting characteristic AE parameters. The core of the review synthesizes applications of AE technology in MAM, categorizing them into three key aspects: (1) hardware setup, which involves a comparative analysis of sensor selection, mounting strategies, and noise suppression techniques; (2) parametric characterization, which establishes correlations between AE features and process dynamics (e.g., process parameter deviations, spattering, melting/pool stability) as well as defect formation (e.g., porosity and cracking); and (3) intelligent monitoring, which focuses on the development of classification models and the integration of feedback control systems. By providing a systematic overview, this review aims to highlight the potential of AE as a powerful tool for real-time quality assurance in MAM. Full article

The structural application of Fiber-Reinforced Polymers (FRP) is significantly hindered by their inherent thermal sensitivity. This paper presents a comprehensive review of the fire performance of FRP materials and FRP-concrete systems, spanning from material-scale degradation to structural-scale response. Distinct from previous studies, this review explicitly distinguishes between the fire behavior of internally reinforced FRP-reinforced concrete members and externally applied systems, including Externally Bonded Reinforcement (EBR) and Near-Surface Mounted (NSM) techniques. The thermal and mechanical degradation mechanisms of FRP constituents—specifically reinforcing fibers and polymer matrices—are first analyzed, with a focused discussion on the critical role of the glass transition temperature T_g. A detailed comparative analysis of the pros and cons of organic (epoxy-based) and inorganic (cementitious) binders is provided, elaborating on their respective bonding mechanisms and thermal stability under fire conditions. Furthermore, the effectiveness of various fire-protection strategies, such as external insulation systems, is evaluated. Synthesis of existing research indicates that while insulation thickness remains the dominant factor governing the fire survival time of EBR/NSM systems, the irreversible thermal degradation of polymer matrices poses a primary challenge for the post-fire recovery of FRP-reinforced structures. This review identifies critical research gaps and provides practical insights for the fire-safe design of FRP-concrete composite structures. Full article

Wind and sand pose a significant threat to operational safety along the route of the Golmud-Korla Railway. To combat the adverse effects of these hazards, numerous sand retaining dikes and sand intercepting ditches have been constructed along the railway corridor. However, the deposition and erosion mechanisms of sand particles in close proximity to these structures have yet to be fully investigated. Therefore, it uses numerical simulations to study the structure of the wind-sand flow field around the sand retaining dike and the sand intercepting ditch, under varying spacing conditions, with an analysis of sand deposition and erosion laws. The results indicate that vortices form on the leeward side and within the sand intercepting ditch. Among these, the vortex flow occurring on the downstream side of the sand retaining dike exhibits a flow reattachment phenomenon at specific locations (i.e., attachment points). As the spacing increases, clockwise vortices Rd1 and Rd2, develop on the leeward side and inside the ditch, respectively. The leeward side of the spacing range of 0–8H is characterized by reverse erosion and deposition processes. When the spacing is 10–15H, a forward erosion zone emerges and expands progressively with the increase in spacing. When the spacing exceeds 10H, i.e., as the sand intercepting ditch is positioned downstream of the vortex reattachment point of the sand retaining dike, its sand interception efficiency is markedly enhanced. It not only elucidates the wind-sand flow and deposition patterns surrounding sand retaining dike and sand intercepting ditch under various spacing configurations but also offers valuable insights for the future design and implementation of protective structures for railways in wind-sand affected regions. Full article

Tan sheep are a characteristic and economically important local breed in the Ningxia Hui Autonomous Region of China, where respiratory diseases continue to pose challenges to animal health and production. In this study, a Pasteurella multocida strain (P6) was isolated from the lung tissue of a single Tan sheep presenting with severe and fatal respiratory disease, and subjected to case-based genomic and pathogenic characterization. The isolate was identified as capsular serotype A based on biochemical profiling, 16S rRNA gene sequencing, kmt-1 PCR, and capsular typing. To provide supportive evidence of virulence potential, a murine infection model was employed, in which P6 induced acute clinical signs and severe pulmonary lesions, including congestion, edema, hemorrhage, and fibrinous inflammatory exudation. Whole-genome sequencing revealed that strain P6 possesses a 2,289,251 bp genome with a GC content of 40.2%, encoding 2155 predicted genes and multiple mobile genetic elements, including genomic islands, prophages, transposons, and a CRISPR locus. Phylogenetic analysis based on seven housekeeping genes placed P6 in close relationship with strains 166CV and 103220, distinct from several rodent- and avian-derived isolates. Functional genomic analyses identified numerous genes associated with carbohydrate metabolism, secondary metabolite biosynthesis, host–pathogen interaction, virulence-related functions, and antimicrobial resistance. Comparative genomic analysis with the reference strain PM70 indicated a largely conserved functional framework, accompanied by a significant enrichment of mobilome-associated genes, suggesting enhanced genomic plasticity. Overall, this study provides a descriptive genomic overview of a P. multocida isolate associated with respiratory disease in Tan sheep and highlights its genetic features and potential adaptive capacity, while acknowledging the limitations inherent to a single-case investigation. Full article