Search Results (6,359)

Among workers performing hand-intensive tasks, musculoskeletal disorders in the upper extremities are more frequent in women than in men. However, risk assessments are generally not sex-specific, and it is not known whether exposures in regular work differ between females and males. The aim of this study was to compare measured wrist joint velocity and muscle activity between men and women performing identical tasks. Participants (28 female–male pairs) performed one of eighteen hand-intensive on-site tasks. Wrist velocity was measured using inertial units. Forearm muscle activity was measured via surface electromyography and normalized to maximal voluntary electrical activation (MVE). The 10th, 50th, and 90th percentiles and time in muscle recovery (< 0.5 %MVE) were computed. Between-sex differences were tested using the Wilcoxon signed-rank test. Wrist angular velocities did not significantly differ between sexes in any percentile (all p > 0.374). The muscle activity was significantly higher in female workers (p < 0.001–0.004), ranging from 1.3 to 2.8 times higher, and they spent less time in muscle recovery (p < 0.001). In hand-intensive tasks involving women and men, risk assessments should prioritize assessments of women to ensure protection against work-related musculoskeletal disorders for all workers. Full article

Tubular aggregate myopathy (TAM) is an inherited skeletal muscle disease associated with progressive muscle weakness, cramps, and myalgia. Tubular aggregates (TAs) are regular arrays of highly ordered and densely packed straight-tubules observed in muscle biopsies; the extensive presence of TAs represent a key histopathological hallmark of this disease in TAM patients. TAM is caused by gain-of-function mutations in proteins that coordinate store-operated Ca²⁺ entry (SOCE): STIM1 Ca²⁺ sensor proteins in the sarcoplasmic reticulum (SR) and Ca²⁺-permeable ORAI1 channels in the surface membrane. Here, we assessed the therapeutic potential of endurance exercise in the form of voluntary wheel running (VWR) in mitigating TAs and muscle weakness in Orai1^G100S/+ (GS) mice harboring a gain-of-function mutation in the ORAI1 pore. Six months of VWR exercise significantly increased specific force production, upregulated biosynthetic and protein translation pathways, and normalized both mitochondrial protein expression and morphology in the soleus of GS mice. VWR also restored Ca²⁺ store content, reduced the incidence of TAs, and normalized pathways involving the formation of supramolecular complexes in fast twitch muscles of GS mice. In summary, sustained voluntary endurance exercise improved multiple skeletal muscle phenotypes observed in the GS mouse model of TAM. Full article

This research provides a new systematic solution to the essential issue of self-noise interference in underwater acoustic sensing signals induced by unmanned surface vehicles (USVs) operating at sea. The self-noise pertains to the near-field interference noise generated by the growing diversity and volume of acoustic equipment utilized by USVs. The generating mechanism of self-noise is clarified, and a self-noise propagation model is developed to examine its three-dimensional coupling properties within spatiotemporal fluctuation environments in the time-frequency-space domain. On this premise, the YOLOv11 object identification framework is innovatively applied to the delay-Doppler (DD) feature maps of self-noise, thereby overcoming the constraints of traditional time-frequency spectral approaches in recognizing noise with delay spread and overlapping characteristics. A comprehensive comparison with traditional models like YOLOv8 and SSD reveals that the suggested delay-Doppler YOLO (DD-YOLO) algorithm attains an average accuracy of 87.0% in noise source identification. An enhanced denoising method, termed optimized time-frequency regularized overlapping group shrinkage (OTFROGS), is introduced, using structural sparsity alongside non-convex regularization techniques. Comparative experiments with traditional denoising methods, such as the normalized least mean square (NLMS) algorithm, wavelet threshold denoising (WTD), and the original time-frequency regularized overlapping group shrinkage (TFROGS), reveal that OTFROGS outperforms them in mitigating USV self-noise. This study offers a dependable technological approach for optimizing the performance of USV acoustic systems and proposes a theoretical framework and methodology applicable to different underwater acoustic sensing contexts. Full article

Global warming has caused rice grains to ripen at high temperatures and become increasingly chalky, which also leads to a deterioration in the physicochemical and cooking properties of rice grains. In the present work, we first want to propose how to evaluate the palatability of rice from the high-temperature year 2022. We evaluated the qualities of 32 Japonica rice grains harvested in 2022. These showed no significant correlation with either amylose content or protein content, while the Mido score (=flavor score) showed a positive correlation with palmitic acid (r = 0.66, p < 0.01) and linoleic acid (r = 0.51, p < 0.01), in contrast to a negative correlation with oleic acid (r = −0.57, p < 0.01) and phosphorus content (r = −0.48, p < 0.01). And pasting temperatures (Pts) of polished rice flour showed significant positive correlation with the surface hardness of cooked rice grains (r = 0.53, p < 0.01) and significant negative correlation with their overall stickiness (r = −0.57, p < 0.01). In addition, Pts showed significant positive correlations with oleic acid and negative correlations with linoleic acid. Therefore, fatty acid composition could become one of the new indicators for evaluating the palatability of rice. Our second aim of this study was to determine the effects of high temperature on rice quality. It was found that oleic acid increased significantly and linoleic acid and palmitic acid decreased in 21 rice samples of the same varieties and growing regions in 2023, an abnormally hot year, compared to 2022, a normal hot year. In summary, both oleic acid content and pasting temperatures may lead to lower quality rice grains in 2023. Full article

AI-integrated robotics in Industry 5.0 demands advanced manufacturing systems capable of autonomously interpreting complex geometries and dynamically adjusting machining strategies in real time—particularly when dealing with aerospace components featuring large-curvature surfaces. Large-curvature aerospace components present significant challenges for precision drilling due to surface-normal deviations caused by curvature, roughness, and thin-wall deformation. This study presents a robotic drilling system that integrates adaptive PCA-based surface normal estimation with in-process pre-drilling correction and post-drilling verification. This system integrates a 660 nm wavelength linear laser projector and a 1.3-megapixel industrial camera arranged at a fixed 30° angle, which project and capture structured-light fringes. Based on triangulation, high-resolution point clouds are reconstructed for precise surface analysis. By adaptively selecting localized point-cloud regions during machining, the proposed algorithm converts raw measurements into precise normal vectors, thereby achieving an accurate solution of the normal direction of the surface of large curvature parts. Experimental validation on a 400 mm-diameter cylinder shows that using point clouds within a 100 mm radius yields deviations within an acceptable range of theoretical normals, demonstrating both high precision and reliability. Moreover, experiments on cylindrical aerospace-grade specimens demonstrate normal direction accuracy ≤ 0.2° and hole position error ≤ 0.25 mm, maintained across varying curvature radii and roughness levels. The research will make up for the shortcomings of existing manual drilling methods, improve the accuracy of hole-making positions, and meet the high fatigue service needs of aerospace and other industries. This system is significant in promoting the development of industrial automation and improving the productivity of enterprises by improving drilling precision and repeatability, enabling reliable assembly of high-curvature aerospace structures within stringent tolerance requirements. Full article

To address the insufficient adaptability of imported peanut harvesting equipment’s soil-engaging components to the specific soil conditions in Xinjiang, this study conducted Discrete Element Method (DEM)-based calibration of soil mechanical parameters using field soil samples with 1–20% moisture content from typical peanut cultivation areas in southern Xinjiang. Through the EDEM simulation platform, a comprehensive approach integrating the Hertz–Mindlin with the JKR adhesion model and Hertz–Mindlin with the Bonding model was employed to systematically calibrate nine key parameters: coefficient of restitution, static friction coefficient, rolling friction coefficient, JKR surface energy, normal/tangential stiffness per unit area, critical normal/tangential force, and soil bonding disk radius. Adopting static angle of repose (SAOR) and unconfined compressive force (UCF) as dual-response indicators, a hybrid experimental design strategy combining Central Composite Design (CCD), Plackett–Burman (PB) screening, and Box–Behnken Design (BBD) optimization was implemented. Regression models for SAOR and UCS were established, yielding six sets of soil parameters optimized for different moisture conditions through parameter optimization. Field validation demonstrated the following: ≤3.27% error in SAOR, ≤1.46% error in UCF, and ≤5.05% error in drawbar resistance validation for field digging shanks. Experimental results confirm that the model demonstrates strong prediction accuracy for soils in typical peanut harvesting regions of southern Xinjiang, thereby providing key parameter references for the future self-developed, highly adaptive soil-engaging components with drag reduction optimization in peanut harvesters for the Xinjiang region. Full article

Background: Undifferentiated arthritis is characterized by synovitis that does not meet the criteria for any specific rheumatic disease. However, a subset of chronic occult infectious arthritis, owing to atypical or overlapping clinical features, is often misclassified as undifferentiated oligoarthritis, potentially leading to diagnostic delays and suboptimal management. This study aimed to compare the clinical, laboratory, and imaging characteristics of these two types of oligoarthritis and to evaluate potential discriminatory markers. Methods: Patients older than 16 years with synovitis involving ≤2 joints at Beijing Jishuitan Hospital from September 2023 to December 2024 were included. Ultrasound-guided joint aspiration or synovial biopsy samples were analyzed by culture and next-generation sequencing, classifying patients as pathogen-positive or -negative. Clinical, laboratory, and imaging data (ultrasound, MRI, CT, X-ray) were compared, and multivariable logistic regression and ROC analyses were performed to identify predictors of infectious arthritis. Results: A total of 57 patients were included, with 20 (35.1%) categorized as pathogen-positive and 37 (64.9%) as pathogen-negative. The mean age was 41.7 ± 14.3 years, and 61.4% of the patients were female, with no significant demographic differences between groups. Monoarthritis was more common in pathogen-positive patients, accounting for 95% of cases (p = 0.02). Although the distribution of affected joints was similar between groups, ultrasound revealed a significantly higher bone erosion grade in pathogen-positive patients (p = 0.02), and CT/X-ray demonstrated articular surface destruction in 58.8% of infectious cases compared to 6.2% in pathogen-negative cases (p < 0.001). Serum albumin levels were significantly lower in the pathogen-negative group (20.7 ± 8.5 g/L vs. 41.1 ± 3.9 g/L, p < 0.001). ROC analysis determined that an albumin threshold >35.4 g/L predicted microbiological positivity with 100% sensitivity and 69.7% specificity. Multivariable logistic regression identified normal serum albumin levels, severe ultrasound-detected bone erosion, and imaging evidence of joint surface destruction as significant predictors of chronic occult infectious arthritis. Conclusions: Our findings suggest that, despite overlapping clinical and laboratory features, serum albumin levels, severe bone erosion on ultrasound and articular surface destruction on CT/X-ray may help differentiate chronic occult infectious arthritis from undifferentiated oligoarthritis. Further studies with larger cohorts are needed to confirm these preliminary results. Full article

Purpose: The pulmonary function test holds significant clinical value in assessing the severity, prognosis, and treatment efficacy of respiratory diseases. However, the test is limited by patient compliance, thereby limiting its practical application. Moreover, it only reflects the current state of the patient and cannot directly indicate future health trends or prognosis. Computational fluid dynamics (CFD), combined with airway models built from medical image data, can assist in analyzing a patient’s ventilation function, thus addressing the aforementioned issues. However, current airway models have shortcomings in accurately representing the structural features of a patient’s airway. Additionally, these models exhibit geometric defects such as low smoothness, topological errors, and noise, which further reduce their usability. This study generates airway skeletons based on CT data and, in combination with convolutional surface technology, proposes an individualized airway modeling method to solve these deficiencies. This study also provides a method for predicting a patient’s lung function based on the constructed airway model and using CFD simulation technology. This study also explores the application of this method in preoperative prediction of the required extent of airway expansion for patients with large airway stenosis. Methods: Based on airway skeleton data extracted from patient CT images, a personalized airway model is constructed using convolutional surface technology. The airway model is simulated according to the patient’s clinical statistical values of pulmonary function to obtain airway simulation data. Finally, a regression equation is constructed between the patient’s measured pulmonary function values and the airway simulation data to predict the patient’s pulmonary function values based on the airway simulation data. Results: To preliminarily demonstrate the above method, this study used the prediction of FEV1 in patients with large airway stenosis as an example for a proof-of-concept study. A linear regression model was constructed between the outlet flow rate from the simulation of the stenosed airway and the patient’s measured FEV1 values. The linear regression model achieved a prediction result of RMSE = 0.0246 and R² = 0.9822 for the test set. Additionally, preoperative predictions were made for the degree of airway dilation needed for patients with large airway stenosis. According to the linear regression model, the proportion of airway radius expansion required at the stenotic position to achieve normal FEV1 was calculated as 72.86%. Conclusions: This study provides a method for predicting patient pulmonary function based on CFD simulation technology and convolutional surface technology. This approach addresses, to some extent, the limitations in pulmonary function testing and accuracy caused by patient compliance. Meanwhile, this study provides a method for preoperative evaluation of airway dilation therapy. Full article

The karst inorganic carbon sink is crucial for carbon neutrality, but its trends and drivers in subtropical humid zones remain unclear. This study selected subtropical humid zones in China with significant forest greening, quantified the carbonate rock weathering carbon sink (CCS) using a thermodynamic dissolution model, and explored the effects of climate, vegetation, hydrology, and radiation energy on CCS through importance analysis. The results showed that from 1982 to 2020, the CCS flux was 12.40 t C km⁻² yr⁻¹, and the total carbon sink was 1188.54 × 10⁴ t C yr⁻¹. Normalized difference vegetation index, leaf area index, and CCS exhibited an increasing trend, with growth rates of 0.002, 0.01 m² m⁻², and 0.05 t C km⁻² yr⁻¹, respectively. Surface available water, precipitation, and evapotranspiration were the dominant factors affecting CCS. This study found that forest greening caused precipitation to increase faster than evapotranspiration, driving an increase in available surface water and ultimately promoting the karst carbon sink in subtropical humid zones. Our findings highlight forest greening as a vital strategy for carbon neutrality. Full article

The assessment of microplastics (MPs) in terrestrial ecosystems has garnered increasing global attention due to their accumulation and migration in soils, which may have potential impacts on soil health, biodiversity, and agricultural productivity. However, research on their distribution and interactions in soil remains limited, especially in tropical regions. This study aimed to characterize MPs extracted from tropical soil samples and relate their abundance to soil and terrain attributes under different land uses (forest, grassland, and agriculture). Soil samples were collected from an experimental farm in Lavras, Minas Gerais, Southeastern Brazil, to determine soil physical and chemical attributes and MP abundance in a micro-watershed. These locations were also used to obtain terrain attributes from a digital elevation model and the normalized difference vegetation index (NDVI). The majority of microplastics found in all samples were identified as polypropylene (PP), polyethylene (PE), polyethylene terephthalate (PET), and vinyl polychloride (PVC). The spatial distribution of MP was rather heterogeneous, with average abundances of 3826, 2553, and 3406 pieces kg⁻¹ under forest, grassland, and agriculture, respectively. MP abundance was positively related to macroporosity and sand content and negatively related to clay content and most chemical attributes. Regarding terrain attributes, MP abundance was negatively correlated with plan curvature, convergence index, and vertical distance to channel network, and positively related to topographic wetness index. These findings indicate that continuous water fluxes at both the landscape and soil surface scales play a key role, suggesting a tendency for higher MP accumulation in lower-lying areas and soils with greater porosity. These conditions promote MP transport and accumulation through surface runoff and facilitate their entry into the soil. Full article

The evaluation of the interfacial shear strength between sand and steel materials plays a fundamental role in the design of geotechnical foundations and structures. However, testing equipment cannot consider the dual effects of particle size and steel roughness on a uniform stress state. In this study, a novel torsion shear apparatus was designed that can measure arbitrary displacement within the interface. On this basis, the influence of the sand particle size and contact surface roughness on interface shear behavior was studied, and the sand–steel interface mechanical responses, including stress state, sample deformation, and friction properties, were evaluated. The results of the torsional interface shear test (TIST) were compared with those of the conventional direct interface shear test (DIST). The results indicate that the shear strength of rough interfaces exceeds that of smooth interfaces but remains below the shear strength observed in pure soil shear tests. Moreover, a critical value of relative roughness exists, beyond which the peak shear stress or friction angle does not significantly increase. Despite variations in the sand grain sizes used in the tests, the corresponding friction angles were approximately equal. In pure soil shear tests, the friction angle was positively correlated with grain size, indicating that grain size directly affects the friction angle in pure soil shear. Additionally, the normalized interface friction angles obtained from the torsional interface shear tests showed good agreement with those derived from interface direct shear tests. Full article

Despite the emergence of eco-friendly solvents and scalable methods for polymeric membrane fabrication, studies on the impacts of solvent synthesis and manufacturing scale-up have not been conducted. To this end, a life cycle assessment (LCA) was developed with the goal of determining the global environmental and health impacts of producing polysulfone (PSf) membranes with the solvents PolarClean and γ-valerolactone (GVL) via doctor blade extrusion (DBE) and slot die coating (SDC). Along with PolarClean and GVL, dimethylacetamide (DMAc) and N-methyl-2-pyyrolidone (NMP) were included in the LCA as conventional solvents for comparison. The dope solution viscosity had a major influence on the material inventories; to produce a normalized membrane unit on a surface area basis, a larger quantity of PSf-PolarClean-GVL materials was required due to its high viscosity. The life cycle impact assessment found electricity and PolarClean to be major contributing parameters to multiple impact categories during membrane fabrication. The commercial synthesis route of PolarClean selected in this study required hazardous materials derived from petrochemicals, which increased its impact on membrane fabrication. Due to more materials being required to fabricate membranes via SDC to account for tool fluid priming, the PSf-PolarClean-GVL membrane fabricated via SDC exhibited the highest impacts. The amount of electricity and concentration of PolarClean were the most sensitive parameters according to Spearman’s rank coefficient analysis. A scenario analysis in which the regional energy grid was substituted found that using the Swedish grid, which comprises far more renewable technologies than the global and US energy grids, significantly lowered impacts in most categories. Despite the reported eco-friendly benefits of using PolarClean and GVL as alternatives to conventional organic solvents, the results in this study provide a wider perspective of membrane fabrication process impacts, highlighting that upstream impacts can counterbalance the beneficial properties of alternative materials. Full article

Submarine pipelines are highly susceptible to lateral buckling failure under service conditions of high temperature and pressure. While existing bearing capacity evaluation methods mainly focus on flat seabeds, research on the ultimate bearing capacity of pipelines buried in sloping seabeds is limited. This study applies the FELA method to analyze the ultimate bearing capacity of pipelines buried in inclined sandy seabeds under various loading directions. The results reveal that in sloping seabeds, the minimum ultimate bearing capacity (P_u,b) does not occur in the vertical direction, but rather deviates toward the outward normal direction of the seabed surface, moving toward the foot of the slope. The P_u,b is only 57% of the uplift bearing capacity in the extreme case. A predictive model was proposed to accurately determine the direction of P_u,b. The results also indicated that increasing the seabed slope angle leads to a significant reduction of bearing capacity, while increases in the internal friction angle of the seabed and the pipeline–soil interface friction angle enhance the bearing capacity. Moreover, the design code of DNV (2017) was identified as unsafe due to its omission of seabed inclination effects, and the P_u,b is only 75% of the best estimate of DNV (2017) in the extreme case. A reduction factor model was developed to mitigate this gap, offering a more reliable framework for evaluating the bearing capacity of pipelines. Full article

Reservoir storage is critical for climate resilience and water security, yet many reservoirs are failing to reach their normal capacity due to intensified droughts—an underexplored global challenge. This study provides the first comprehensive global assessment of reservoir-filling dynamics, leveraging a gap-free monthly surface area time series (2001–2023) generated by a U-Net deep learning framework that fuses MODIS and Landsat data. After analyzing 6754 reservoirs worldwide, in this study, we introduce the reservoir area index (RAI) to characterize the anomalies and severity of filling problems, validated against 131 in situ storage records. The results reveal a clear wetting trend from 2001 to 2011, followed by increasing levels of underfilling after 2012, peaking during the 2021–2023 droughts. Both small and large reservoirs, especially in arid regions, show heightened vulnerability. Compared to previous altimetry-based studies limited to around 500 large reservoirs and in shorter periods after 2011, our findings uncover decadal trends and size-dependent disparities in reservoir filling. Despite some uncertainties, this dataset offers valuable insights to inform adaptive water management and supports its future refinement through improved area–volume relationships. Full article

Aluminium metal matrix composites (AMMCs) incorporate aluminium alloys reinforced with fibres (continuous/discontinuous), whiskers, or particulate. These materials were engineered as advanced solutions for demanding sectors including construction, aerospace, automotive, and marine. Micro- and nano-scale reinforcing particles typically enable attainment of exceptional combined properties, including reduced density with ultra-high strength, enhanced fatigue strength, superior creep resistance, high specific strength, and specific stiffness. Microstructural, mechanical, and tribological characterizations were performed, evaluating input parameters like reinforcement weight percentage, applied normal load, sliding speed, and sliding distance. Fabricated nanocomposites underwent tribometer testing to quantify abrasive and erosive wear behaviour. Multiple investigations employed the Taguchi technique with regression modelling. Analysis of variance (ANOVA) assessed the influence of varied test constraints. Applied load constituted the most significant factor affecting the physical/statistical attributes of nanocomposites. Sliding velocity critically governed the coefficient of friction (COF), becoming highly significant for minimizing COF and wear loss. In this review, the reinforcement homogeneity, fractural behaviour, and worn surface morphology of AMMCswere examined. Full article