Search Results (2,062)

Public concrete datasets often contain duplicate records, coupled variables, and cross-source distribution shifts, which may lead to overly optimistic model evaluation. Based on a deduplicated UCI high-performance concrete dataset (1005 samples), this study develops a leakage-controlled data-driven workflow with applicability-domain assessment. TabPFN, SHAP, and NSGA-II are used for compressive strength prediction, model-response attribution, and scenario-based candidate mix screening, respectively. Model evaluation follows a unified data split, inner training-set cross-validation, and an independent test-set protocol. In addition, 502 non-overlapping records from the Mendeley PCC dataset are used as an external benchmark to examine cross-source transferability and sensitivity to distribution shift. The results show that TabPFN achieves the highest R² and the lowest RMSE, MAE, and MAPE on the internal UCI test set, with values of 0.953, 3.744 MPa, 2.265 MPa, and 7.580%, respectively; however, its advantage over strong baselines such as CatBoost is limited. On the external Mendeley PCC dataset, TabPFN remains competitive, with R², RMSE, and MAE values of 0.490, 15.175 MPa, and 11.457 MPa, respectively, but its performance is close to that of random forest, XGBoost, and CatBoost. The 5NN applicability-domain stratification shows that external samples located within the 95% 5NN applicability domain achieve improved performance (R² = 0.634 and RMSE = 12.367 MPa), suggesting that external prediction errors are associated with the distance from the source-domain distribution. SHAP results indicate that cement, ground granulated blast-furnace slag, curing age, and water are the main attribution variables in the model output; their response directions should be interpreted as statistical attributions rather than material causal mechanisms. The Pareto candidate mixes generated by NSGA-II satisfy basic engineering constraints. Nevertheless, because the external benchmark reveals sensitivity to cross-source distribution shift, the resulting mix proportions should be treated as pre-experimental screening candidates rather than engineering-validated low-GWP concrete mix proportions. Full article

Canned motor pumps are widely utilized due to their distinct advantage of a completely leakage-free structure. Among them, an integrated impeller–rotor configuration is employed in the axial-flux canned motor pump, resulting in a shorter axial length and higher power density. This novel configuration allows for easy integration into space-constrained systems, such as electric vehicles, aerospace applications, and liquid-cooled servers. However, research on the internal flow characteristics of these pumps remains scarce. To address this gap, the present study investigates the internal flow across various flow rates. Numerical simulations are validated against experimental data. The average error remains below 2%. The pump achieves a peak efficiency of 68.6% at the design condition, but experiences efficiency drops of 15.0 and 25.2 percentage points under 0.5Q_d and 1.5Q_d, respectively. Results demonstrate that flow rates significantly govern internal characteristics. These include pressure, velocity, and entropy distributions, along with vortex structures and pressure fluctuations. Notably, operating at off-design conditions can intensify the internal pressure fluctuations by up to a factor of 29.4. Entropy analysis identifies major losses on blade suction sides and diffusers. These findings provide crucial hydrodynamic guidelines for low-noise thermal management systems in electric vehicles and ensuring high-reliability cooling loops in aerospace and liquid-cooled servers. Full article

Oxygen (O₂) leakage in macrophyte rhizospheres is an adaptive strategy for hypoxic environments, which is important in lake ecological restoration. In this investigation, the fluorescent planar optode (PO) technique is used for two-dimensional (2D) distribution of dissolved O₂ at a submillimeter scale in the rhizosphere of Vallisneria spiralis under various environmental conditions. The spatial heterogeneity in the distribution of oxic microniches is frequently verified in the rhizosphere. The radial oxygen loss (ROL) rate for root systems is characterized by the following sequence: basal root (20.6 ± 5.1–49.6 ± 9.5 nmol m⁻² s⁻¹, n = 7) > lateral root (14.1 ± 4.1–36.6 ± 8.3 nmol m⁻² s⁻¹, n = 7) > root tip (13.1 ± 4.6–28.8 ± 6.4 nmol m⁻² s⁻¹, n = 7). The O₂ maximum value on lines transecting each kind of root also obeys the sequence mentioned above. For one typical root, (1) O₂ decreases from 131.2 ± 2.4–147.4 ± 3.7 μmol L⁻¹ at the root center to 47.2 ± 1.4–75.9 ± 2.2 μmol L⁻¹ in the rhizosphere fringe due to O₂ supply from the root surface and O₂ consumption in rhizosphere sediment, and (2) the furthest distance from the aboveground part to the root tip leads to the lowest O₂ concentration at the root apex of that root. The light/dark transition and O₂ level in overlying water modulate the photosynthetic activity of leaves and the transfer of oxygen in the water column through aerenchyma tissue to the roots. The sequence of the oxygenated area (%), ROL rate, and O₂ concentration in rhizosphere sediment under various conditions is demonstrated as: high illumination/high O₂ > darkness/high O₂ > high illumination/low O₂ > darkness/low O₂. The effect of O₂ in water on the ROL of Vallisneria spiralis is more distinct than illumination. Oxygen storage in roots, and especially O₂ diffusion from overlying water, can supplement O₂ deficiency in the rhizosphere during the cessation of photosynthesis under darkness. This research advances the understanding of complex interrelationships among O₂ dynamics in different root parts, photosynthesis, O₂ in overlying water and O₂ transfer through plant aerenchyma to the rhizosphere. Full article

Plastic waste presents a significant environmental and public health concern in Malawi, where rapid urban growth, limited waste collection services, and informal disposal practices contribute to persistent plastic waste hotspots. In Lilongwe City, the waste collection rate has been reported ranges from 10% to 30%. This means that out of the 500 to 600 tons of municipal solid waste produced each day, only about 50 to 150 tons are collected daily. These hotspots occur in settings such as drains, markets, settlement edges, riverbanks, and lakeshore environments. They intensify health-relevant exposure pathways by encouraging stagnant water, increasing flood risk, facilitating open burning, and supporting the formation of plastisphere biofilms that can contain pathogenic and antimicrobial resistant organisms. This research synthesises evidence on the main sources of plastic waste in Malawi, the mechanisms of leakage across different environments, and the associated health implications. It uses a scoping approach aligned with PRISMA-ScR guidance and is informed by the UK Research and Innovation (UKRI) funded Sustainable Plastic Attitudes to benefit Communities and their Environments (SPACES project), which highlights the influence of behavioural, governance, and environmental factors on plastic pollution. A two phase, risk-based decision framework to support targeted management of plastic waste hotspots is described. Phase 1 focuses on rapid harm reduction through the identification and ranking of hotspots according to risk severity, spatial extent, and feasibility, guiding timely interventions such as drain clearance, waste capture, and temporary stabilisation. Phase 2 addresses longer term prevention by tackling upstream drivers through policy measures, improved services, reuse and reduction schemes, and community engagement. The framework has been developed using evidence from Malawi; however, its methodology could be applied to other low- and middle-income countries that experience similar constraints and exposure pathways. The framework offers a transparent and practical tool for decision makers seeking to allocate limited resources effectively while reducing environmental and health risks associated with plastic waste. Full article

Background/Objectives: Spontaneous intracranial hypotension (SIH) is caused by spinal cerebrospinal fluid (CSF) leakage and is typically diagnosed by clinical presentation and characteristic MRI signs; however, objective tools for monitoring physiological changes and treatment response remain limited. Cine phase-contrast MRI (PC-MRI) enables noninvasive quantification of aqueductal CSF dynamics, yet reliable analysis is challenging since the cerebral aqueduct is extremely small and susceptible to low contrast, partial volume effects, and ROI-dependent measurement variability—particularly in SIH where CSF pulsatility is often reduced. Methods: We propose an end-to-end automated framework that integrates (1) a cascade localization–segmentation strategy, consisting of Tiny YOLOv4 detection followed by MultiResUNet segmentation on a YOLOv4-derived cropped ROI; (2) physiology-informed pulsatility-based segmentation (PUBS) to refine anatomical masks into functional flow ROIs; and (3) one-dimensional convolutional neural networks (1D-CNNs) to extract exploratory waveform morphology features from 32-phase cardiac-cycle velocity waveforms. The study includes 39 participants, yielding 59 cine PC-MRI examinations: 11 controls, 28 Pre-treatment SIH scans and 20 Post-treatment Recovery scans. Results: The cascade model significantly improves segmentation robustness compared with a full-image baseline, achieving higher Dice scores and markedly lower boundary errors across cohorts (e.g., Pre-treatment SIH HD95: 1.66 ± 0.74 px vs. 15.37 ± 44.98 px). PUBS refinement reduces quantification deviation from expert manual references in SIH (mean relative error: 7.4% to 5.6%) and improves diagnostic performance for multiple hemodynamic parameters (e.g., downward mean flow AUC: 0.747 to 0.792). For waveform morphology analysis, the end-to-end 1D-CNN classifier was evaluated using repeated-seed participant-level grouped LOOCV. The repeated-seed ensemble prediction showed modest out-of-sample discrimination between Normal controls and Pre-treatment SIH scans, with an AUC of 0.646, a bootstrap 95% confidence interval of 0.455–0.826, and a permutation-test p-value of 0.072. Separately, exploratory analysis of the final baseline-trained 1D-CNN latent space showed marked, apparent Normal-versus-SIH separability and an intermediate recovery distribution in PCA space, suggesting that aqueductal waveform morphology may encode SIH-related physiological information. Conclusions: These findings suggest that SIH-related information may be reflected not only in flow magnitude but also in aqueductal CSF waveform morphology. However, the modest and statistically non-significant out-of-sample performance of the end-to-end 1D-CNN classifier indicates that morphology-based AI features should currently be regarded as exploratory biomarker candidates rather than validated stand-alone diagnostic tools. Larger independent cohorts are required to confirm their reproducibility, physiological meaning, and clinical utility. Full article

Leakage detection in water distribution networks is a core component of smart water management. Addressing the limitations of traditional acoustic detection methods, which heavily rely on manual expertise, and the inadequate feature extraction and low recognition rates for minor leaks of existing deep learning models in complex noise environments, this study proposes a novel hybrid architecture CNN model named Incep-ResNet. The model innovatively integrates multi-scale feature extraction and deep residual learning, incorporating an SE attention mechanism to achieve adaptive recalibration of feature channels. Experimental results demonstrate that the model achieves a leakage identification accuracy of 96.6%, representing improvements of 6.7% and 7% compared to ResNet18 and GoogLeNet, respectively. It exhibits excellent noise resistance and feature extraction capabilities, providing a new technical solution for intelligent leakage detection. Full article

To address the application bottlenecks of organic phase change materials characterized by low thermal conductivity and susceptibility to liquid leakage, this study utilized natural poplar wood as a raw material to construct a three-dimensional carbon/silver heterogeneous porous skeleton via delignification, gradient carbonization, and in situ electroless silver plating. Polyethylene glycol (PEG) was then vacuum-encapsulated within this structure to prepare form-stable composite phase change materials (CPCMs). The regulatory effects of carbonization temperature and metal interface modification on the microscopic morphology and thermophysical properties of the materials were systematically investigated. The results indicate that the skeleton carbonized at 800 °C achieves an optimal balance between pore distribution and skeleton rigidity, ensuring the uniform conformal growth of silver nanoparticles and endowing the material with excellent anti-leakage performance. The thermal conductivity of the optimal sample reaches as high as 0.683 W/(m·K), with the melting latent heat maintained at 133.9 J/g, while also demonstrating an agile and stable photothermal conversion response. Non-equilibrium molecular dynamics (NEMD) simulations further confirm that the silver nanoparticle modification layer smooths the phonon vibration frequency mismatch between the carbon substrate and organic segments, significantly reducing the interfacial thermal resistance. This research provides an important reference for the structural design and microscopic heat transfer mechanism analysis of high-performance phase change energy storage materials. Full article

Chilling injury is a major problem limiting the postharvest storage and marketability of mango fruit at low temperature. The present study investigated the individual and combined effects of sodium nitroprusside (SNP), L-arginine (Arg) and salicylic acid (SA) on chilling tolerance, regulation of oxidative stress and the postharvest quality of ‘Keitt’ mango fruit stored at 5 ± 1 °C for 28 days followed by 4 days of shelf life at 23 °C. Fruits were pre-treated with 1 mM SNP, 1 mM Arg, 2 mM SA or their binary combinations before storage. The chilling injury, membrane damage, lipid peroxidation, protein oxidation and fruit softening were greatly enhanced by cold storage in untreated fruits. In contrast, all the treatments significantly ameliorated these deteriorative changes, and the combined treatments were superiorly effective. Among these, SNP + Arg was the most effective treatment, which reduced the chilling injury index from 4.05 in control fruits to 1.00 after shelf life, completely inhibiting the incidence of decay and reducing electrolyte leakage and malondialdehyde accumulation by 47.4 and 48.2%, respectively. The same treatment also maintained higher firmness, titratable acidity, visual appearance and ascorbic acid content than untreated fruits. The enhanced chilling tolerance was accompanied by increased antioxidant defense, as SNP + Arg significantly stimulated the activities of superoxide dismutase, catalase and peroxidase, but suppressed the activity of pectin methylesterase. Multivariate analyses, such as PCA, clustered heatmap and integrated stress index, demonstrated a strong negative relationship between oxidative stress markers and antioxidant metabolism. The results showed that combined SNP and Arg treatments enhanced chilling tolerance through increasing antioxidant capacity, preserving membrane integrity, and retarding ripening-related metabolism, which provides an effective way to maintain the postharvest quality of cold-stored mango fruit. Full article

One of the keys to improving feed conversion rates in Precision Livestock Farming (PLF) is the early identification of growth impediments. However, the swine farming data collected by Electronic Feeding Station (EFS) are often disorganized and lack effective labeling. Data from healthy pigs are frequently intermixed with that from sick pigs, leading to label leakage and survivor bias in models, particularly when age is included as a feature. To address these known issues, this study breaks away from traditional modeling methods. First, we clean and classify the time-series data from electronic feeding stations, using age-cohort baselines as one of the criteria for determining high and low productivity, thereby avoiding problems such as label leakage. Next, we construct a high-dimensional feature matrix that captures dynamic derivatives such as feeding acceleration and weight gain acceleration, which together serve as behavioral feature fingerprints. To test the system, we optimized the mixed-model algorithm and evaluated the model based on behavioral deviations among individual pigs after removing all absolute age labels. Our results indicate that the full-feature model achieved an ROC-AUC of 0.778 and an F1-score of 0.4137 at the optimal threshold. Interestingly, SHAP attribution analysis revealed that “intake peer deviation,” “Cumulative Intake and Lifetime Avg Intake,” and “feeding acceleration” served as precursors to low productivity and growth retardation in this dataset, with these factors proving more significant than absolute feed intake or age. Our ablation experiments confirmed that a model based solely on behavioral features (excluding age labels) maintained an ROC-AUC of 0.773, successfully decoupling pig growth performance from growth stage. Our model can detect changes in feeding dynamic signatures at an average of 12.3 days, thereby providing insights for pig growth assessment, health monitoring, or more informed culling decisions. Full article

Introduction: The 3 Rs principle advocates developing alternative, biologically relevant models. Thus, 3D fish liver in vitro models have been increasingly used for ecotoxicological studies. We previously optimized spheroids from the rainbow trout non-tumoral liver cell line RTL-W1 and employed them to assess the effects of aquatic pollutants. Although they demonstrated potential for assessing ecotoxicological effects, further optimization is warranted to enhance their physiological relevance. Incorporating an extracellular matrix (ECM), such as collagen, has been shown to be a promising strategy to improve spheroids’ structural organization and functionality. Objective: This study aimed to optimize 3D culturing conditions of RTL-W1 spheroids by evaluating the effects of collagen supplementation on viability, morphology, and functional response. Methodology: Spheroids from the RTL-W1 cell line (60,000 cells per well) were cultured in 96-well ultra-low attachment (ULA) plates at 18 °C. After spheroids’ formation, rat tail collagen was supplemented at concentrations of 15 (C15), 30 (C30), and 60 (C60) µg/mL at culture days 7, 8, and 9. Spheroids were collected at two sampling days (10 and 14). Viability was assessed using alamarBlue and lactate dehydrogenase (LDH) assays, while morphology was assessed by optical microscopy. Collagen penetration was evaluated using Masson’s trichrome staining technique. Protein expression of cytochrome P450(CYP)1A was assessed by quantifying immunocytochemistry staining using an anti-CYP1A antibody. Results: On day 10, LDH leakage decreased in C15 and C60, compared with the control, whilst C15 spheroids showed lower absorbance levels in the alamarBlue assay. On day 14, LDH showed no significant differences; however, C30 and C60 had higher alamarBlue absorbance, indicating greater metabolic capacity. Spheroid morphology appeared intact in all conditions. Masson trichrome revealed collagen fibrils at the periphery of the spheroids, especially in C30 and C60, indicating that spheroids incorporated collagen. CYP1A immunostain was present in all conditions, localized in the spheroids’ border, and tended to be higher when supplementation occurred in earlier days. Conclusions: Our results suggest that RTL-W1 spheroids interacted with the collagen matrix and appeared to functionally improve. Data suggest that incorporating ECM may increase the complexity and physiological relevance of RTL-W1 spheroids, thereby better supporting mechanistic and ecotoxicological applications. Full article

To address the bottlenecks of conventional valve-controlled marine steering systems—characterized by high throttling losses, low efficiency, and high leakage risk—as well as the insufficient power density and impact resistance of electro-mechanical actuators (EMAs) for high-load steering of large vessels, this paper proposes and validates a high-performance integrated solution for an electro-hydrostatic actuator (EHA) for ship steering. First, a fifth-order electro–hydraulic–mechanical coupled dynamic model comprising a permanent magnet synchronous motor, hydraulic pump, hydraulic cylinder, and load is established. The validity and applicability boundaries of three simplifying assumptions—neglecting leakage, pipeline pressure losses, and steady-state fluid compressibility effects—are quantitatively analysed, with a total introduced error ≤3%. These assumptions are justified under medium-pressure, short-pipeline, and well-sealed conditions typical of marine EHA systems. Second, a composite control architecture combining outer-loop sliding mode control with inner-loop motor PID dual-loop control is proposed. Parameter tuning is performed using pole placement for the sliding surface and the Ziegler–Nichols critical ratio method for the inner loops, effectively suppressing hydraulic system parameter perturbations and random wave-induced load disturbances. Quantitative comparisons show that the proposed method reduces overshoot by 11.63% and improves sinusoidal tracking accuracy by 90.13% compared to conventional single-loop PID control. An integrated drive-control structure is designed, and a three-phase full-bridge inverter main circuit with wide-voltage input capability—including EMI filtering, soft-start, and LC filtering—is developed to accommodate the ±20% voltage fluctuations typical of ship power grids, thereby enhancing system integration and grid adaptability. Phased bench tests demonstrate that the settling time from no-load start-up to 200 r/min is only 0.01 s. When a sudden 20 N·m load is applied, the speed drop is less than 3%, and the recovery time is less than 0.025 s. The steady-state steering angle error does not exceed 0.12°, the maximum average steering rate reaches 3.33°/s, and the steering response time is within 0.3 s. All core performance indicators exceed the general technical standards for marine steering systems, with a 65.7% improvement in steady-state accuracy and a 62.5% improvement in response speed over conventional PID control. The research findings provide an effective general technical solution and experimental data support for the performance optimization and engineering application of marine EHA systems. Full article

Orthohantavirus infections are classically associated with hemorrhagic fever with renal syndrome (HFRS) in Eurasia and hantavirus cardiopulmonary syndrome (HCPS) in the Americas. However, accumulating evidence indicates that the clinical spectrum is considerably broader, with frequent involvement of organ systems beyond the kidney and lung. Hepatic manifestations, in particular, may mimic acute viral hepatitis, leading to diagnostic challenges and underrecognition. This paper synthesizes published evidence on hepatic involvement in orthohantavirus infection, with a focus on clinical presentation, pathogenic mechanisms, differential diagnosis, biomarkers, and public health implications. Relevant literature was identified through searches of peer-reviewed articles, with emphasis on studies reporting hypertransaminasemia, hepatitis-like illness, and liver injury in confirmed hantavirus infections. Mild to moderate elevations in aminotransferases are common during acute orthohantavirus infection, and in some patients the clinical picture may be dominated by fever, thrombocytopenia, and hepatitis-like abnormalities, closely resembling dengue, leptospirosis, or classical viral hepatitis. Hepatic injury appears to result primarily from systemic endothelial dysfunction, immune-mediated inflammation, and microvascular leakage rather than direct hepatocytopathic effects. Emerging biomarkers of severity, including thrombocytopenia, neutrophil-to-lymphocyte ratio, soluble thrombomodulin, and IL-6 trans-signaling, reflect widespread vascular and inflammatory activation. Diagnostic delays are frequent, particularly in non-endemic regions, due to low clinical awareness and overlapping features with more common febrile hepatotropic syndromes. Orthohantavirus infection should be considered in the differential diagnosis of acute febrile illness with unexplained hypertransaminasemia and thrombocytopenia, especially when epidemiological clues suggest rodent exposure or compatible environmental contexts. Recognizing hepatic involvement as part of a systemic endothelial syndrome may improve diagnostic accuracy, reduce underreporting, and facilitate earlier supportive management. Increased awareness among hepatologists, infectious disease specialists, and emergency physicians is warranted. Full article

Ducted propulsion fans are widely recognized for their ability to enhance aerodynamic efficiency and operational safety by utilizing a surrounding shroud to contain the flow and mitigate blade tip losses. However, maximizing thrust and optimizing internal flow dynamics remain critical challenges in further improving their aerodynamic performance. This study investigates the aerodynamic characteristics of a ducted propulsion fan configured with a secondary air intake channel designed to enhance mass flow ingestion. Utilizing Reynolds-Averaged Navier–Stokes (RANS) simulations coupled with the Shear Stress Transport (SST) k-omega turbulence model, the internal flow dynamics and aerodynamic efficiency of configurations both with and without the secondary air intake channel are examined. The secondary air intake, strategically located adjacent to the rotor blade tip, increases the mass flow rate and, consequently, enhances thrust. Physically, this configuration successfully reinjects bypass flow to mitigate tip leakage vortices, significantly reducing the low-velocity wake regions adjacent to the rotor tip. Several configurations were evaluated by systematically varying the intake channel’s position, curvature, and the dimensions of its inlet and outlet ports under static conditions at 6000 rpm. Numerical results demonstrate that the optimal design improves thrust by an additional 2.2% compared to the baseline ducted fan without the auxiliary intake port due to the mitigated tip vortices and stabilized flow field. Full article

Triethylamine (TEA), a widely used volatile organic compound (VOC), poses severe threats to environmental safety and human health upon accidental leakage, making the development of high-performance TEA detection techniques urgently needed. Herein, we report a Sn-based metal–organic framework (Sn-MOF) constructed from 4,5-dichloroimidazole ligands synthesized via a solvothermal approach. The resulting MOF-derived SnO₂ materials were obtained by calcination at 400–600 °C, yielding SnO₂ with tunable specific surface area and surface defect-site density. Structural and surface characterizations revealed that the materials consist of primary nanoparticles in the range of 10–50 nm, forming aggregated particles of 1–2 µm. The gas sensing performance toward TEA was systematically evaluated. The SnO₂-400 °C sensor exhibited the highest response (S = 85.0) to 100 ppm TEA at 190 °C, with a low detection limit of 1 ppm, superior selectivity, good repeatability, and excellent long-term stability. The observed performance variation was attributed to the combined effects of specific surface area, abundant defect-associated surface sites, and suitable mesoporous structure. This work not only provides a high-performance TEA sensor for industrial and food safety monitoring but also offers a rational strategy for designing MOF-derived metal oxide gas sensors with tailored microstructures and surface defect chemistry. Full article

Water-soil gushing caused by tunnel leakage can induce severe ground disturbance and threaten the safety of shield tunnels, yet rapid prediction remains difficult because high-fidelity numerical simulations are computationally expensive. This study develops an interpretable machine-learning framework for predicting gushing-induced ground disturbance around shield tunnels based on a validated two-phase Material Point Method database. Six governing variables are considered, including the tunnel depth ratio, gushing location, soil friction angle, Young’s modulus, intrinsic permeability, and soil gushing mass. Three representative response variables were selected, namely the maximum ground settlement, flow-zone width, and flow-zone centroid angle. Five algorithms, including MLP, RF, XGBoost, SVR, and Ridge, were established and compared, with hyperparameters optimised using Optuna. The results show that nonlinear models consistently outperform the linear baseline, among which MLP, RF, and XGBoost achieve the best overall accuracy and robustness. Error-distribution analysis further indicates that MLP and RF yield the highest proportion of low-error predictions. SHAP interpretation shows that SGM is the dominant factor governing maximum settlement and flow-zone width, whereas gushing location primarily controls the flow-zone centroid angle. The proposed framework provides an efficient and physically interpretable surrogate for rapid hazard assessment of gushing-induced ground disturbance in shield tunnelling. Full article