Search Results (1,841)

Digital chest tomosynthesis (DCT) has been clinically validated to offer significant advantages in diagnostic efficiency for pulmonary diseases and radiation dose reduction. Emerging stationary DCT (sDCT) systems can further shorten acquisition time and eliminate motion artifacts caused by X-ray source movement and patient respiration. This work focuses on the development of a multi-beam X-ray source for mobile sDCT systems by specification definition, source design, and experimental validation. The developed X-ray tube integrates 63 focal spots arranged linearly over a length of 816 mm. X-rays are emitted through seven segmented windows, achieving an angular span of 36° at a source image distance (SID) of 120 cm, with full coverage of a detector area of 35.6 cm × 43.2 cm. The tube operates at a maximum anode voltage of 140 kV, maximum anode current of 20 mA, and 24 mAs per scan, with a focal spot size of IEC 0.6. The developed multi-beam X-ray source achieves multiple key performance breakthroughs and provides an alternative source architecture for future sDCT implementation, with the potential to facilitate further system performance optimization and engineering development. Full article

Main engine load varies continuously, whereas onboard carbon capture columns are installed with fixed capacities. For liquefied natural gas (LNG)-fueled ships, this mismatch between design and operation makes off-design robustness, rather than nominal-point performance, the governing sizing criterion. This study developed a variable-load design window for onboard monoethanolamine CO₂ capture and evaluated a dual-loop organic Rankine cycle (ORC) as a secondary thermal integration option. A verified process model was applied to a 5 × 5 design–operating matrix (D50–D90/O50–O90). The mismatch was strongly asymmetric. When operating load did not exceed design load, capture rate remained near 90%; under overload, absorber treated only the design-point-equivalent exhaust-gas flow, causing capture performance to deteriorate rapidly. The mean CO₂ avoided rate increased from 57.4% at D50 to 70.4% at D90, while absorber diameter increased from 3.23 to 4.06 m. D70 emerged as the balanced option for low- to medium-load services, D80 marked the transition before full robustness, and D90 was robustness-oriented for frequent high-load operation. The ORC recovered 104–185 kW net power and supplied 231–410 kW LNG-side heating. Results support capacity selection before ORC application; CO₂ liquefaction and storage, voyage-weighted validation, and shipboard ORC feasibility remain outside the present scope. Full article

This paper studies quantitative forms of approximate recurrence for bounded linear operators on Banach spaces through the notion of uniformly $\delta$-almost periodic vectors. For a prescribed tolerance $\delta \ge 0$, this notion relaxes classical almost periodicity by requiring uniform orbit repetitions up to an error controlled by $\delta$, along relatively dense sets of approximate periods. The main purpose of the paper is to refine this qualitative recurrence condition by introducing return-time profiles. These profiles measure, for each accuracy level, the minimal size of recurrence windows needed to guarantee the existence of an approximate period. Thus, they provide a quantitative refinement of the usual relatively dense return condition. We prove that uniform $\delta$-almost periodicity is equivalent to the finiteness of the associated return-time profile at every positive accuracy level. We also establish basic structural properties of these profiles, including monotonicity with respect to the accuracy and tolerance parameters, behavior under scalar multiplication and forward iteration, and an elementary additive property of approximate periods. The final part of the paper applies the general framework to weighted backward shifts on ${\ell }^p$-spaces. In this setting, the explicit coordinate representation of the iterates allows us to identify several recurrence and obstruction mechanisms. We describe stable threshold recurrence, finite-support recurrence, exact recurrence generated by periodic vectors, and coordinate-level obstructions to $\delta$-almost periodicity. The results provide a rigorous framework for measuring approximate almost periodicity in linear dynamics and clarify how recurrence-window profiles complement the classical qualitative theory of relatively dense returns. Full article

The suckling phase is the critical window for rumen functional maturation, yet amino-acid-based interventions tailored to this stage remain scarce. L-citrulline (L-cit) bypasses hepatic first-pass metabolism, is converted to L-arginine peripherally, and resists ruminal microbial degradation, making it a candidate functional additive for early-life ruminants. This study evaluated whether dietary L-cit at 2 g·lamb⁻¹·d⁻¹ would improve rumen development and metabolic function in suckling Hu lambs. Twenty male Hu lambs were randomly assigned to a control (CON) or L-cit group (n = 10/group) and reared for 45 d (3 d adaptation + 42 d treatment). Growth and starter intake were assessed in all lambs; six lambs per group (n = 6) were subsequently slaughtered for rumen morphometry, gas chromatography–flame ionization detection (GC-FID) volatile fatty acid (VFA) quantification, 16S rRNA gene sequencing, and liquid chromatography–mass spectrometry (LC-MS) untargeted metabolomics. L-cit increased average daily starter intake by 25.96% (p = 0.036) and produced a 20.00% numerical but non-significant increase in average daily gain (ADG) (p = 0.203; Cohen’s d = 0.58). Rumen weight, volume, and papillary length, width, density, and epithelial thickness were all elevated (p < 0.05), whereas muscular thickness was unaffected (p = 0.162). Total VFA, acetate, propionate (+37.64%, p < 0.001), and butyrate were higher in the L-cit group; the molar proportion of propionate rose from 21.41% to 24.75%, and the acetate-to-propionate ratio declined from 2.90 to 2.44 (p = 0.005). Microbial richness (Chao1, Observed species) increased without altered evenness, and linear discriminant analysis effect size (LEfSe) identified L-cit-driven enrichment of propionate-generating and fiber-degrading genera, including Prevotellaceae_UCG-004, Ruminobacter, and the NK4A214_group. Of 539 differential metabolites (147 of which were annotated to the Kyoto Encyclopedia of Genes and Genomes (KEGG) database), KEGG enrichment highlighted linoleic acid metabolism and purine metabolism as the biologically interpretable targets. Microbiota–metabolite correlations linked L-cit-enriched genera to up-regulated metabolites such as adenine. Dietary L-cit at 2 g·lamb⁻¹·d⁻¹ enhances starter intake, promotes rumen epithelial development, promotes a shift toward enhanced propiogenic fermentation within an acetate-dominant profile, and remodels the microbiota–metabolome axis, supporting its application as a functional additive during the suckling phase of ruminants. Because epithelial barrier integrity, oxidative stress, and inflammatory markers were not directly measured, these findings should be interpreted as morphological and association-based evidence, and further functional validation is required. Full article

Respiratory disease remains a major challenge in pig production. This two-room pilot study evaluated whether room-level acoustic monitoring combined with physiological measurements could provide an early warning after an experimental Klebsiella pneumoniae challenge. Forty growing pigs balanced by sex and body weight were housed for 28 days in one control room and one challenged room (20 pigs/room; four pens/room). Challenged pigs were intranasally inoculated on days 8, 12, 16, and 20 with a culture whose dose was retrospectively verified by serial-dilution plating. Nasal and fecal samples were cultured on Klebsiella ChromoSelect agar, and colonies with expected morphology were enumerated as presumptive Klebsiella/K. pneumoniae colonies. A fine-tuned Audio Spectrogram Transformer (AST) classified five sound classes from facility-specific audio and was evaluated by group-blocked hold-out testing, five-fold group-blocked cross-validation, temporal deployment validation, and window-threshold sensitivity analysis. The model achieved hold-out macro-F1 of 0.947, five-fold macro-F1 of 0.928 ± 0.019, and 24 h deployment macro-F1 of 0.914. Presumptive nasal bacterial load was higher in challenged pigs at 1-week post-inoculation (log₁₀ 4.03 vs. 0.67). Group-size-standardized cough detections were also higher in the challenged room (54.84 vs. 36.80 detections/day), and daily coughing first exceeded the baseline threshold on day 8. Thresholds of 0.764 (control) and 1.115 (treatment) were obtained from an integrated score that included coughing, sneezing, ear temperatures, rectal temperature, and respiration rate; the treatment score and treatment–control contrast score first surpassed the threshold on day 8, and daily multimodal scores varied between groups (t = −6.636, p < 0.001). Integrated score improved discrimination of post-inoculation disturbance compared with cough detections alone (leave-one-day-out AUROC: 0.94 vs. 0.88). Because each condition was represented by one room, findings are exploratory temporal contrasts, not replicated treatment effects or a stand-alone diagnostic test. Full article

In the western Hunan region, the fire pit serves as the primary space for heating, receiving guests, and sacrificial ceremonies. However, the prolonged use of wood as the main fuel for the fire pit poses a significant threat to indoor air quality and the health of residents. This study conducts field monitoring and evaluation of indoor air quality in traditional earthen residences in Western Hunan during winter. It employs software simulation to analyze the concentration of indoor pollutants in typical earthen dwellings. Three passive mitigation strategies—adjusting window size, installing interior partitions, and setting up passive smoke exhaust systems—are proposed, and their effectiveness is validated through simulation. The results indicate that the best air circulation performance occurs when the window sill height is between 0.9 and 1.5 m, and the window sill length is between 1.5 and 2.1 m. Installing partitions increases the average concentration of indoor pollutants in the fire pit and master bedroom areas by 2.33 and 3.05 times, respectively. Installing smoke exhaust systems above the fireplace can decrease indoor pollutant concentrations by more than 70%. The findings provide effective strategies for controlling health risks caused by indoor pollutants in winter without affecting local residents’ living habits and traditional customs. Full article

Background: Free-word association (FWA) captures the most accessible lexical responses to a stimulus, providing a window into automatic cognitive representations of food categories that may differ across cultures and between sexes. Objectives: To examine whether the dominant cognitive associations evoked by the word “sweets” differ across three language groups (Hungarian, English, Spanish), whether they vary by sex, and whether they relate to body mass index (BMI) and self-reported eating disorder risk. Methods: A total of 1349 participants completed an online survey including a single FWA prompt. Responses were classified into 10 semantic categories and analyzed using chi-square tests. Effect sizes (Cramér’s V) were reported for all tests. Height and weight were converted to uniform metric units, and BMI was calculated. Results: The association profile differed significantly across language groups (χ²[18] = 210.05, p < 0.001, V = 0.28). Chocolate dominated Hungarian responses, while Baked goods/Desserts and Sugar/Candy dominated English, and Positive emotion and Baked goods/Desserts predominated among Spanish speakers. Sex differences were significant overall (χ²[9] = 43.72, p < 0.001, V = 0.18). BMI distributions differed markedly across nations (χ²[6] = 157.17, p < 0.001, V = 0.26), and sweets categories were significantly associated with eating disorder risk (χ²[27] = 48.04, p = 0.008, V = 0.11); however, this result should be interpreted with caution given the extreme skew toward the lowest-risk category [84.2%], with Negative/Health associations overrepresented among higher-risk participants. Conclusions: Cultural context plays a significant role in shaping automatic cognitive associations with sweet foods. The exploratory association between sweets categories and self-reported eating disorder risk warrants further investigation using validated instruments before any substantive conclusions can be drawn. Full article

Smartphone-holder use during motorcycling is increasingly common, but its task-dependent ergonomic effects remain insufficiently understood. This study examined visual, postural, and muscular responses during smartphone-holder use under a simulated riding-posture condition. Forty healthy adults completed five smartphone-use tasks: dynamic viewing, static viewing, texting, seated use, and standing use. Each riding-related task condition lasted one minute, with the final 30 s designated as the stable data collection window. For postural variables, instantaneous values were recorded at four time points (0, 10, 20, and 30 s from the onset of the stable window) and averaged. For electromyography (EMG), integrated EMG (IEMG) was computed over the same 30 s window using ten consecutive non-overlapping 3 s epochs, and averaged for normalization. The neck flexion (NF), upper thoracic angle (UTA), gaze angle (GA), viewing distance (VD), and electromyographic activities of the cervical erector spinae (CES) and upper trapezius (UTZ) were measured using integrated motion-analysis and EMG approaches. Two-way mixed ANOVA and repeated-measures correlation analyses were performed. The task condition significantly affected all measured variables, with effect sizes ranging from moderate to large (all ηp² ≥ 0.155), with texting producing the greatest NF, shortest VD, and highest muscle activation. Strong within-subject associations were identified among visual, postural, and muscular variables across riding-related tasks (VD–NF: r = −0.815, p < 0.001). Females exhibited higher CES and UTZ activation than males. These findings reveal a task-dependent visual–postural–muscular co-variation pattern during scooter-mounted smartphone-holder use and support the application of a sensor-based ergonomic assessment for characterizing task-dependent visual–postural–muscular responses during scooter-mounted smartphone-holder use. Full article

To address the problems of the limited feature extraction capability and insufficient training efficiency of the traditional Continuous Bag-of-Words (CBOW) model in Natural Language Processing (NLP), the Quantum Neural Network-enhanced CBOW model (QNN-CBOW) integrates Quantum Neural Networks (QNN) with the CBOW model, effectively enhancing training performance. This work aims to systematically investigate the sensitivity and influence patterns of key factors (activation function type, number of quantum feature extraction layers, context window size, and quantum gate noise level) on model behavior under controlled small-scale simulation conditions. Comparative experiments are carried out using the control variable method to clarify the influence mechanism of each factor. This paper presents a NISQ-era proof-of-concept study, which provides a theoretical basis and practical reference for the fusion and optimization of quantum neural networks and traditional NLP models. Full article

To overcome low bioavailability and high trauma in inner ear therapies, targeted delivery across the round window membrane (RWM) via hollow microneedles (HMNs) offers a promising solution. However, the fabrication of high-aspect-ratio, small-size HMNs remains challenging. This study demonstrates the successful fabrication of small-outer-diameter HMNs using a 10 μm resolution digital light processing (DLP) system. Finite element analysis (FEA) identified a double tangent-arc transition as the optimal structural design for minimizing stress concentration. To manage the heightened parameter sensitivity at sub-feature-scale fabrication, a corrected curing index (CCI) model was established via a physics-informed regression approach incorporating polymerization kinetics and nonlinear spatial intensity distribution, achieving high fitting accuracy (R² > 0.96). Under optimized parameters, the fabricated HMNs possessed mean dimensions of 805.13 μm in height, 37.54 μm in inner diameter, and 79.36 μm in outer diameter. Compressive tests exhibited a robust structural strength of up to 141 mN per needle following post-curing. Combined in silico and in vitro experiments demonstrated excellent penetration performance. Furthermore, the HMNs achieved stable, pressure-dependent delivery with volumetric flow rates rising from 0.14 mL∙min⁻¹ to 0.39 mL∙min⁻¹ as driving pressure escalated from 50 kPa to 300 kPa, validating their functional capacity for controlled drug administration. Full article

Background: Low-dose aspirin (LDA) reduces preeclampsia (PE) risk by up to 40%, yet its molecular effects on chorion trophoblast cells (CTCs), a fetal membrane lineage at the feto-maternal interface, remain obscure. CTCs form a structural and immunoregulatory barrier whose dysfunction drives inflammation-associated membrane pathology in PE. Extracellular vesicles (EVs) released by CTCs may encode cellular stress and adaptation states, offering a molecular window into aspirin’s timing-dependent effects on PE risk modification. Methods: Human CTCs were challenged with cigarette smoke extract (CSE) to model oxidative stress-driven PE pathology. Two paradigms were tested: (1) prophylactic aspirin (4 and 40 µg/mL) before and/or flanking the CSE, and (2) therapeutic aspirin after the CSE challenge. The EVs were isolated via ultracentrifugation and size-exclusion chromatography, characterized by nanoparticle tracking and immunoblotting, and profiled by quantitative mass spectrometry. A network pathway analysis and machine learning biomarker selection defined the EV-encoded molecular states. Results: The CTC-derived EVs from the CSE-exposed cells carried a PE-like proteomic signature marked by suppressed VEGF/ECM remodeling, activated TNF-p53 apoptotic signaling, and heightened inflammation. Prophylactic low-dose aspirin shifted the EV cargo toward an EV-encoded signature consistent with preserved angiogenic potential (enrichment of VEGFA, COL1A1, and MMP14) and predicted attenuation of apoptotic and NF-κB pathway activity by an Ingenuity Pathway Analysis. High-dose aspirin produced broad transcriptional suppression without an accompanying pro-angiogenic EV signature. Therapeutic (post-injury) aspirin partially attenuated the injury-associated EV cargo but did not restore the angiogenic EV signature. An exploratory machine learning analysis of EV proteomes identified a candidate prophylactic biomarker panel anchored by HSPA8, SERPINF2, COL4A1, and PLOD1, mapped to the predicted angiogenic recovery and redox-balance pathways. These EV cargo readouts represent the predicted molecular states and require functional validation before clinical interpretation. Conclusions: The CTC-derived EV proteomic signatures capture the dose- and timing-dependent aspirin effects in this in vitro CTC model, positioning the chorion as a candidate pharmacological “secondary responder” favoring cellular resilience over classical anti-inflammatory suppression. As an exploratory hypothesis-generating study, EV-based molecular profiling could provide a foundation for future investigations aimed at stratifying aspirin responders from non-responders, although clinical validation in maternal plasma cohorts will be required before any translational application. Full article

Guttation plays an important role in increasing rice yield, preventing crop diseases and improving soil fertility, and is an important index to measure the water status in the field. However, the real-time detection of droplets generated by guttation is a difficult task. Droplets are small and dense targets. In the deep learning model, the detection of small objects in high-resolution images is a key problem to be solved. A Droplet-YOLO method is proposed, which combines the YOLOv8 model and multi-instance learning. The original image is divided into multiple sub-images using a sliding window and detected by YOLOv8. The detection of each sub-image is carried out by an independent repeated test, so multi-instance learning ensures 99.99% probability of detecting droplets. By comparing various models, Droplet-YOLO performs best in terms of precision, recall, and mean precision (mAP). In addition, through the hyper-parameter adjustment experiment, the configuration with a batch size of 32 and epoch of 200 was finally selected. The accuracy and recall rate of the model reached 96.8% and 95.7%, respectively, and the mAP reached 99.0%. Experiments show that this method has significant advantages for small object detection in high-resolution images, and the proposed Droplet-YOLO model is superior to the most advanced methods. Full article

In the context of urban distribution, given the complexity of express delivery and the variability of distribution conditions, vehicle routing problems with time-dependent characteristics have received increasing attention. This study incorporates a cross-period travel time estimation method for road segments that accounts for temporal and weather-dependent variations in vehicle speed. Building upon this foundation, this study establishes an multi-objective optimization model for the green vehicle routing problem that systematically incorporates intricate constraints, including time-varing vehicle speed, fuel consumption, carbon emissions, and customer servive time windows. This model aims to achieve three primary objectives: (1) minimizing the fleet size, (2) minimizing the overall delivery expenses, which include fuel consumption and carbon emissions, and (3) maximizing the average customer satisfaction. To solve this model, we develop an improved Non-Dominated Sorting Genetic Algorithm III (INSGA-III). To effectively prevent the algorithm from becoming trapped in local optima, we propose a dual-criteria selection mechanism. Meanwhile, we introduce a destroy-and-repair variable neighborhood search strategy to enhance the algorithm’s optimization capability under complex constraints. Experimental evaluations conducted on Solomon benchmark instances as well as real-world case studies indicate that the proposed INSGA-III algorithm surpasses widely utilized multi-objective optimization methods across all assessed performance metrics. This highlights the significant potential of the presented INSGA-III algorithm for practical applications in urban delivery scenarios, which is closely linked to the sustainable development of cities. Full article

Automatic video anomaly detection remains challenging because abnormal events are infrequent, visually heterogeneous, and weakly bounded in time. This study proposes an unsupervised framework trained only with normal video segments. The framework integrates sliding-window segment construction, dual-view perturbation, a two-branch spatio-temporal encoder, exponential moving-average prototype updating, prototype-guided contrastive optimization, and a robust anomaly score composed of prototype deviation, second-order temporal residual, and local-neighborhood sparsity. Experiments were conducted on UCSD Ped2, CUHK Avenue, and ShanghaiTech under the same input size, segment length, optimizer, and threshold protocol. The proposed model achieved AUC values of 97.4%, 91.8%, and 83.7% on the three datasets, respectively, with an average AUC of 91.0% and an average F1 score of 88.1%. Relative to the baseline contrastive model, the average AUC increased by 2.4 percentage points, and the average F1 score increased by 2.8 percentage points. Across three independent runs, the improvement over the contrastive baseline was statistically significant (paired two-sided t-test, p = 0.018). Ablation and sensitivity analyses indicate that the performance gain is mainly attributable to spatio-temporal joint encoding, prototype traction, temporal residual scoring, and local-neighborhood support. These results show that contrastive representation learning, explicit prototype updating, and temporal-aware scoring can jointly produce a stable representation of normal behavior without using abnormal samples during training. Full article

Arthritis (RA) is characterized by immune-mediated chronic inflammation and endothelial dysfunction, ultimately resulting in clinically overt cardiovascular complications. As a prototypical disease of microvascular dysfunction, RA represents an ideal model to study microvascular alterations. The dermal capillary network offers an easily accessible window to the peripheral microcirculation, whose function can be easily assessed using Nailfold videocapillaroscopy (NVC) or laser techniques. Whereas the clinical significance of structural alterations is not always clear, functional abnormalities may provide more direct insight into the dynamic status of the microvasculature and endothelial integrity. The present narrative review aims to provide an integrative overview of available studies evaluating functional abnormalities of the dermal microcirculation in RA, with particular emphasis on the emerging role of NVC as a dynamic vascular assessment tool. Several studies in RA have assessed the structure and morphology of the peripheral microvasculature using NVC, but far fewer data exist on functional alterations assessed with this method. The study of functional alterations of the dermal microvascular network in RA has largely been based on laser techniques, which consistently point towards altered microvascular reactivity. By contrast, functional NVC-related approaches remain limited, despite their potential ability to simultaneously assess structural and dynamic capillary abnormalities in vivo. Available evidence supports that NVC may be reframed as a promising functional vascular biomarker in RA. However, the available literature is characterized by small sample sizes, predominantly cross-sectional designs, and methodological heterogeneity, highlighting the need for standardized prospective studies. Full article