Search Results (9,943)

Polymer-modified bituminous binders are widely used in road construction due to their enhanced mechanical performance; however, the effectiveness of these materials critically depends on the actual concentration of polymer modifiers, particularly styrene-butadiene-styrene (SBS). This study aims to develop and validate a rapid, reproducible Fourier Transform Infrared Spectroscopy—Attenuated Total Reflectance (FTIR-ATR) spectroscopy method for the quantitative determination of SBS content in polymer-modified bitumen (PMB). Since, to date, there is no clearly defined method for controlling the quantitative content of polymers in PMB, this creates difficulties in accepting the roadway into operation. Calibration PMB samples containing 1–4% SBS were prepared, tested for physical and mechanical properties, and analyzed spectroscopically to identify characteristic absorption bands at 966 cm⁻¹ and 699–760 cm⁻¹. A first-order calibration model was constructed to relate peak intensity to polymer concentration. The results demonstrate a clear linear correlation between SBS content and IR absorption features, confirming the suitability of FTIR as an instrumental method for routine laboratory control. Application of the model allowed determination of actual polymer mass fraction with high accuracy and reproducibility. The findings also showed that increased SBS levels improve softening point, elasticity, and low-temperature resistance, with 3–4% representing a performance-optimal range. Overall, the proposed FTIR-based approach provides an objective and efficient tool for quality control of polymer-modified binders and supports broader standardization efforts in the field. Full article

Background/Objectives: Food insecurity affects college students at nearly twice the rate of US households, with documented impacts on student academic performance, physical and mental health, and socialization. While frameworks exist to conceptualize general food insecurity and food insecurity in specific contexts, researchers and practitioners lack resources to guide system-level responses to food insecurity on college and university campuses and assess those responses. In this study, we aimed to develop and validate a simple yet comprehensive framework for assessing food insecurity responses within the context of higher education. Methods: We adapted an eight-phase process for framework development: (1) map selected data sources within the multidisciplinary literature, (2) read and categorize selected sources, (3) identify and name concepts, (4) deconstruct and categorize concepts based on their features, (5) group similar concepts together, (6) synthesize concepts into a framework, (7) validate the framework using expert panel review, and (8) revise as necessary. Results: The developed Campus Food Aid Self-assessment (CFAS) framework consists of six dimensions: Student Services and Supports; Involvement; Advocacy; Awareness and Culture Efforts; Education and Training; and Research, Scholarship, and Creative Works. Expert panelists (n = 7) reviewed the proposed framework and confirmed the clarity, comprehensiveness, and representativeness of the proposed dimensions, conceptual definitions, and operational variables. Conclusions: With a comprehensive yet accessible structure, the CFAS framework supports the development, coordination, and improvement of campus-based strategies to address food insecurity and support positive student outcomes. Full article

Autonomous driving in dense traffic demands policies that ensure safety, accurate path tracking, and ride comfort, yet reinforcement learning (RL) alone suffers from low sample efficiency and weak safety guarantees, while classical artificial potential field (APF) methods lack adaptability to dynamic scenarios. This paper proposes PIPF-TD3, which integrates APF theory with the Twin Delayed Deep Deterministic Policy Gradient (TD3) by embedding composite potential values and Doppler-weighted gradients as physics-informed features into the state vector. A Hybrid A* planner generates a reference path encoded as an attractive field; repulsive fields model nearby obstacles using real-time perception data; and a multi-objective reward function jointly optimizes path tracking, collision avoidance, and ride comfort. Experiments in CARLA 0.9.14 across two scenarios—a highway segment with mixed obstacles and a signalized intersection with conflicting turning movements—show that PIPF-TD3 achieves 100% task completion with zero collisions, whereas TD3 without potential field guidance suffers a 90% collision rate. PIPF-TD3 reduces mean cross-track error to 0.12 m (72.1% reduction over the rule-based FSM baseline), maintains 67.0% larger safety clearance, and yields RMS longitudinal and lateral accelerations of 1.12 and 0.75 m/s², outperforming the FSM by 37.1% and 42.7%. These results confirm that Doppler-weighted physical priors substantially enhance RL-based driving safety and quality in complex traffic conditions. Full article

Different methodologies have been developed for the analysis and study of dynamical systems, including both theoretical models and natural systems. Examples span a wide range of applications, such as astronomy, financial and economic time series, biophysical systems, physiological phenomena, and Earth sciences, including seismicity and climatic processes. The study of these complex systems is commonly based on the analysis of the signals they generate, using mathematical tools to extract relevant information. A broad spectrum of mathematical disciplines converges in this context, including stochastic, probability and statistical theory, entropic and informational measures, fractal and multifractal analysis, natural time analysis, modeling of non-linearity and recurrence methods, generalized entropies, non-extensive systems, machine learning, and high-dimensional and multivariate complexity. Research in this area is largely focused on the characterization of complex systems, providing indicators of determinism or stochasticity, distinguishing between regularity, chaos, and noise, and identifying topological as well as disorder-regularity features. In addition, short- and long-term forecasting, together with the identification of short- and long-range correlations, play a central role in such characterization. To address these objectives, numerous mathematical tools have been developed for the analysis of time series and point processes, each designed to capture specific signal properties. In this work, many of the most important tools used in time series analysis are compiled and reviewed, highlighting their main characteristics and the different types of complex systems to which they have been applied. Full article

Objective: To develop and validate an artificial intelligence (AI) system for automated lens opacities classification system III (LOCS III)-based grading of all three major cataract subtypes using anterior segment optical coherence tomography (AS-OCT). Methods: This is a single-center cross-sectional study. AS-OCT images were collected and manually graded by ophthalmologists according to LOCS III. The dataset was randomly split into training, validation, and test sets. We propose a novel multi-granularity mask-guided network (MMNet) that jointly performs lens substructure segmentation and severity grading. The model’s performance was assessed on an independent test set for automatic grading of cortical cataract (CC), nuclear cataract (NC), and posterior subcapsular cataract (PSC) and the grading performance of the proposed method against ophthalmologists was also evaluated. The model’s interpretability was assessed via attention heatmaps and feature visualization. Results: The proposed MMNet exhibited high agreement with ground truth conducted through gold standard. The proportions of predictions with an absolute error < 1.0 for three subtypes range from 83.02% to 89.94%. The model’s grading accuracy for cataract subtypes was between 82.20 ± 1.41% and 89.76 ± 1.31% among the three subtypes, the Area Under the Curve (AUC) was between 0.954 (95% CI, 0.952–0.969; p < 0.001) and 0.973 (95% CI, 0.964–0.985; p < 0.001). The MMNet shows a satisfactory mean absolute error (MAE) of 0.14 ± 0.35 in CC, 0.10 ± 0.30 in NC, and 0.17 ± 0.38 in PSC grading. It also achieved a fast grading speed of 0.0178 s/image against manual grading. Conclusions: The proposed AI model presented advanced performance on AS-OCT images in automated LOCS III-based cataract grading for CC and NC, and also showed feasibility in PSC assessment. Full article

With the rapid development of applications such as smart cities and the industrial internet, the computation-intensive tasks generated by massive sensing devices pose significant challenges to traditional cloud computing paradigms. Unmanned aerial vehicle (UAV)-assisted edge computing systems, leveraging their high mobility and wide-area coverage capabilities, offer an innovative architecture for low-latency and highly reliable edge services. However, the practical deployment of such systems faces a highly complex multi-objective optimization problem featured by the tight coupling of task offloading decisions, UAV trajectory planning, and edge server resource allocation. Conventional optimization methods are difficult to adapt to the dynamic and high-dimensional characteristics of this problem, leading to suboptimal system performance. To address this critical challenge, this paper constructs an intelligent collaborative optimization framework for UAV-assisted edge computing systems and formulates the system quality of service (QoS) optimization problem as a mixed-integer non-convex programming problem with the dual objectives of minimizing task processing latency and reducing overall system energy consumption. A multi-agent joint task association and trajectory optimization (MA-JTATO) algorithm based on hybrid reinforcement learning is proposed to solve this intractable problem, which innovatively decouples the original coupled optimization problem into three interrelated subproblems and realizes their collaborative and efficient solution. Specifically, the Advantage Actor-Critic (A2C) algorithm is adopted to realize dynamic and optimal task association between UAVs and edge servers for discrete decision-making requirements; the multi-agent deep deterministic policy gradient (MADDPG) method is employed to achieve cooperative and energy-efficient trajectory planning for multiple UAVs to meet the needs of continuous control in dynamic environments; and convex optimization theory is applied to obtain a closed-form optimal solution for the efficient allocation of computational resources on edge servers. Simulation results demonstrate that the proposed MA-JTATO algorithm significantly outperforms traditional baseline algorithms in enhancing overall QoS, effectively validating the framework’s superior performance and robustness in dynamic and complex scenarios. Full article

Objectives: The impact of renal ischemia during partial nephrectomy (PN) on postoperative renal function remains controversial. On-clamp PN provides improved surgical exposure and haemostasis but induces warm ischemia, which may impair renal function. Off-clamp PN avoids ischemia-related injury and may better preserve renal function, although concerns persist regarding blood loss and oncological safety. We systematically compared perioperative and functional outcomes, as well as surgical margin status between on-clamp and off-clamp PN. Methods: We performed a systematic search of PubMed, Embase, Cochrane, Web of Science, and Scopus to identify randomized controlled trials (RCTs) and observational studies comparing on-clamp versus off-clamp PN with no publication time limitations. Outcomes included estimated glomerular filtration rate (eGFR), percentage eGFR change, estimated blood loss (EBL), transfusion rates, positive surgical margins (PSMs), operative time, and complications. Results: Thirty-nine studies (four RCTs) including 10,154 patients were analysed. Off-clamp PN was associated with a smaller decline in eGFR (mean difference [MD] −4 mL/min/1.73 m², 95% CI −5.7 to −2.8) and lower percentage eGFR loss (MD −1.7%, 95% CI −2.8 to −0.7). On-clamp PN was associated with lower EBL (MD −48 mL, 95% CI −72 to −25). Transfusion rates favored on-clamp PN but were not statistically significant (OR 0.7, 95% CI 0.5–1.0). On-clamp PN was associated with a higher risk of PSM (OR 1.3, 95% CI 1.0–1.7) and postoperative complications (OR 1.3, 95% CI 1.1–1.6). Between-study heterogeneity and predominance of observational data were key limitations. Conclusions: Off-clamp PN provides superior renal functional preservation and lower risks of PSMs and complications, at the cost of increased blood loss. These findings support individualized surgical decision-making based on patient and tumor characteristics. What does the study add?: This study provides an extensive and detailed comparison of off-clamp versus on-clamp partial nephrectomy, encompassing more than 10,000 patients from 39 studies. By integrating the available evidence up to late 2024, it delivers comprehensive estimates of the renal functional benefits associated with ischemia-free surgery. Our findings delineate the trade-offs between renal preservation, blood loss, and surgical margin status, thereby informing individualised decision-making in nephron-sparing surgery and refining current understanding of when ischemia avoidance is most clinically advantageous. Patient summary: Our study suggests that performing partial nephrectomy without temporarily clamping the kidney blood vessels may better preserve kidney function and reduce cancer-related surgical risks, but can lead to increased blood loss during surgery. These findings indicate that the choice of surgical technique should be individualised, taking into account tumour features and patient-specific factors. Full article

Background/Objectives: Non-invasive hemodynamic monitoring technologies are being developed to support clinical decisions while reducing risks from invasive procedures. Usability evaluation is essential to assess safety and effectiveness before commercial release. This study examined the usability of a novel patch-type ultrasound-based system (CW10) designed for continuous monitoring in perioperative settings. Methods: A summative evaluation was conducted following IEC 62366-1 with 15 anesthesiologists. Potential hazards were identified via the FDA MAUDE database (Code: DQK) to inform test scenarios. Participants were stratified by clinical experience (1–<5, 5–<10, and ≥10 years) to observe potential variations in operation. In a simulated operating room, users performed 9 clinical scenarios (49 tasks). Metrics included task success rates, subjective satisfaction (5-point Likert scale), and the System Usability Scale (SUS). Results: The overall task success rate was 98.2%. No statistically significant differences were observed across groups in performance, subjective ratings, or SUS scores (p > 0.05). The mean SUS score was 78.5, corresponding to a “Good” usability level. While some use errors occurred in tasks like probe orientation, root cause analysis suggested these were likely due to negative transfer from prior device experience rather than interface complexity. Conclusions: The results suggest the system demonstrates acceptable usability and consistent operation across experience levels. Integrated automated features and the patch design may contribute to reducing inter-user variability for continuous monitoring. This study provides usability evidence that may inform the development of similar non-invasive technologies. Full article

Background: Wearable sensors have gained increasing popularity as an objective method for remotely monitoring infant movement in naturalistic settings. Over the first year of life, infants generate a wide range of motions, from goal-directed to spontaneous movement. These include linear movements, such as kicks, and orientation changes, such as postural transitions. Many sensor processing pipelines emphasize capturing linear movements through movement-generated acceleration while focusing less on information about orientation embedded in the gravitational part of the data. Here, we introduce a complementary gravity-referenced approach that extracts the gravitational component of accelerometer signals to estimate limb orientation, extending the reliable quantification of rich and detailed aspects of infant movement. Infant orientation has demonstrated clinical relevance, including associations with later neuromotor outcomes, and it can be used to chart infant motor development, motivating the development of objective methods to quantify orientation from sensor data. Methods: Wearable sensors (Opal APDM) were used to longitudinally evaluate infant motor activity recorded in sessions conducted at 3, 6, 9, and 12 months of age. We extracted data from a 5 min segment that has simultaneous video recordings. From these datasets, applying the gravity-referenced method, we computed pitch, roll, and yaw, angles that collectively describe limb orientation. We then quantified orientation variability using axis-specific circular standard deviations (SDs) for pitch, roll, and yaw and a multi-axis composite measure based on generalized variance. Results: Axis-specific circular SDs for pitch, roll, and yaw, as well as the composite generalized variance, increased significantly from 3 to 12 months (p ≤ 0.01 for each metric). Composite variability was strongly associated with Mullen gross motor outcomes at 9 and 12 months of age (r = 0.55, p < 0.001). Conclusions: Overall, gravity-referenced pitch, roll, and yaw provide rich orientation features that increased as infants develop more postural transitions. Furthermore, the orientation features correlated with standardized measures of infant motor function. These orientation metrics can complement traditional linear kinematic measures and improve our ability to granularly track infant motor development in the first year of life. Full article

Background/Objectives: Compounded vaginal creams are widely used for conditions such as hormone replacement therapy, vaginal dryness, low libido, vaginal infections, etc. Recent research highlights the potential of using anhydrous bases to extend shelf life, particularly when combined with self-emulsifying and mucoadhesive properties that improve mucosal retention and enhance drug bioavailability. This study provides in vitro and ex vivo evaluation of an anhydrous vaginal base. Methods: Key quality indicators such as irritation potential, leakage potential, pH compatibility, mucoadhesion, and self-emulsification were assessed using the chorioallantoic membrane Hen’s Egg Test, MTT assay, texture analysis, and fluorescence microscopy. Results: The anhydrous vaginal base demonstrated high cell viability (>78%) and non-irritant potential (IS = 2.5) in in vitro assays. It maintained physiological vaginal pH (4.56 ± 0.05), showed strong mucoadhesive properties comparable to commercial products, and exhibited minimal leakage. Ex vivo studies confirmed its prolonged retention on vaginal tissues. The anhydrous vaginal base formed stable emulsions upon contact with vaginal fluid simulant, effectively distributing both lipophilic and hydrophilic compounds. Conclusions: Compared to water-containing bases, an anhydrous vaginal base shows advantages: longer retention time and lower leakage; adaptability to varying vaginal fluid levels; and efficient dispersion of both hydrophilic and lipophilic active pharmaceutical ingredients. These features support its potential use in compounded vaginal products, minimizing stability risks and enhancing patient compliance and therapeutic outcomes. Full article

The high-fidelity 3D digitization of small, detailed cultural heritage objects, such as Oracle Bones, presents significant challenges for which existing reconstruction workflows are often inadequate. Methods based on Structure-from-Motion (SfM) often lack the geometric density required to capture fine inscription details, while Light Detection and Ranging and RGB-Depth approaches may introduce high data overhead and unstable color mapping. Recent specialized studies have utilized multi-shading-based techniques to extract such hidden surface textures, yet integrating these results into a cohesive mesh remains difficult. To address these limitations, we propose a digitization framework specifically designed for object-level archaeological artifacts. Our method combines semi-automatic alignment with ICP-based refinement for robust camera pose estimation, reducing misalignment issues associated with feature-only registration. Furthermore, we employ an efficient mesh-based representation with vertex-level coloring, enabling detailed geometry and consistent texturing while maintaining compact storage requirements. Our contributions include: (1) a high-quality mesh reconstruction framework that preserves fine inscription geometry; (2) a hybrid camera pose estimation strategy that improves alignment robustness; and (3) an integrated hardware-assisted workflow tailored for digitizing small archaeological artifacts under controlled acquisition conditions. Experimental results on physical Oracle Bone artifacts demonstrate that the proposed method achieves a mean geometric reconstruction error of approximately 0.075 mm with a Hausdorff distance of 1 mm. These results demonstrate the effectiveness of the proposed workflow for digitization of oracle bone artifacts. Full article

Background/Objectives: Poly(ADP-ribose) polymerase 1 (PARP1) is an important therapeutic target in DNA repair-deficient cancers, but discovery of new inhibitors remains constrained by scaffold convergence, tolerability limits, and acquired resistance. This study aimed to develop an interpretable, reliability-stratified cheminformatics workflow for PARP1 potency prioritization and structure-based follow-up. Methods: A curated ChEMBL dataset of 3339 PARP1 inhibitors was encoded using RDKit 2D descriptors and Avalon fingerprints (1143 initial features), then reduced to 132 informative variables by Random Forest-based feature selection. Five regression models were optimized, including a stacked ensemble. Model interpretation was performed using permutation feature importance and SHAP. External near-domain corroboration was assessed using a stringent PubChem similarity expansion (Tanimoto > 0.90) around sub-10 nM seed compounds, followed by comparison with retrievable experimental PARP1 activity values. Top scaffold-diverse candidates were further evaluated by complementary docking against PARP1 (PDB: 4R6E) using AutoDock Vina and cavity-guided docking through the SwissDock platform. Results: The stacked ensemble achieved the best held-out performance (test R² = 0.723; RMSE = 0.610 pIC₅₀ units), with 83.7% of test predictions within ≤0.75 pIC₅₀ units and only 2.7% exceeding 1.5 pIC₅₀ units. PubChem similarity expansion retrieved approximately 32,450 analogs, of which 3349 were predicted to have IC₅₀ ≤ 10 nM. Among 366 compounds with retrievable experimental PARP1 activity values, predicted versus experimental pIC₅₀ showed a positive association (R² = 0.124; Pearson r = 0.479), with RMSE = 0.491 and MAE = 0.330 pIC₅₀ units. Three ligands—CID 168873053, CID 175154210, and CID 172894737—showed the strongest complementary docking support and pocket-consistent poses relative to niraparib. Conclusions: This workflow provides a transparent and practically useful framework for near-domain PARP1 inhibitor prioritization. The combined QSAR, explainability, external corroboration, and docking strategy supports shortlist generation for experimental follow-up. Full article

Background/Objectives: Castanopsis tibetana Hance (C. tibetana) is a valuable timber species in southern China. Its chloroplast and nuclear genomes have been characterized, but its mitochondrial genome (mitogenome) remains unknown. This study assembles and characterizes the first complete mitogenome of C. tibetana, elucidating its structural and evolutionary features. Methods: A hybrid approach combining Oxford Nanopore long reads and Illumina short reads was used. The mitogenome was assembled via iterative seed-based mapping and annotated via GeSeq and tRNAscan-SE. Repeats were identified via MISA, TRF, and REPuter. The RNA editing sites were predicted with the PREP suite. Phylogenetic analysis was performed on 14 conserved protein-coding genes from 13 species via maximum likelihood and Bayesian inference. Results: The mitogenome is a 554,078 bp circular molecule (GC 45.27%) encoding 51 genes (32 PCGs, 16 tRNAs, 3 rRNAs). It contains 202 simple sequence repeats (37.1% tetrameric). We predicted 53 C-to-U RNA editing sites, most frequently in nad7 and nad5. Codon usage showed bias, with 28 codons having RSCU > 1. Twenty fragments (6001 bp, 1.08% of the mitogenome) were transferred from the chloroplast. Phylogenomic analysis placed C. tibetana within Fagaceae, close to other Castanopsis species. Conclusions: This study provides the first comprehensive characterization of the C. tibetana mitogenome, revealing its structural architecture, repetitive landscape, RNA editing profile, and phylogenetic placement. These findings offer valuable genomic resources for understanding mitogenome evolution in Fagaceae and support future research on the conservation genetics and molecular breeding of this important tree species. Full article

In intelligent excavator applications, traditional excavator posture recognition methods face two major challenges: limited recognition accuracy and insufficient computing resources on edge devices. To address these issues, this study proposes an excavator posture recognition method based on an improved Real-Time Detection Transformer (RT-DETR). First, a new backbone network is designed based on the Reparameterized Vision Transformer to improve feature utilization efficiency while reducing computational demands. Next, the overall architecture is optimized by introducing lightweight Dynamic Upsamplers, which reduce information loss during upsampling and enhance multi-scale feature fusion. In addition, a Cross-Attention Fusion Module is adopted to strengthen local feature extraction while retaining the global modeling capability of the Transformer, thereby improving the discrimination between foreground and background. Finally, a Multi-Scale Fusion Network is introduced to further enhance the multi-scale feature representation ability of RT-DETR. Experimental results show that the proposed method achieves a mean average precision (mAP) of 94.29% for small object detection, which is 7.96% higher than that of the baseline RT-DETR, while reducing the number of model parameters by 34.95%. Compared with YOLO-series models, the proposed method improves mAP by 8.62% to 12.75%. These results indicate that the proposed method outperforms existing methods in both detection accuracy and computational efficiency and provides an efficient and feasible solution for real-time excavator posture recognition. Full article

Background/Objective: Sex-based disparities in cancer outcomes have gained increasing attention in women’s health research. We examined the relationship between sex and overall survival (OS) among patients with non-small-cell lung cancer (NSCLC), with particular emphasis on the survival advantage observed in women across different clinical stages and treatment settings. Sex-related differences in cancer outcomes have become an important focus in oncology and women’s health research. This study aimed to investigate the association between sex and overall survival (OS) in patients with non-small-cell lung cancer (NSCLC), with particular attention to the observed survival advantage in women across clinical stages and treatment contexts. Methods: A total of 129,864 patients diagnosed with NSCLC were identified, including 78,460 men and 51,404 women. Demographic characteristics, socioeconomic status, tumor features, treatment modalities, and survival outcomes were compared between sexes. Kaplan–Meier survival analyses and stage-stratified Cox proportional hazards models were used to evaluate overall survival differences between female and male patients. Results: Women demonstrated significantly superior OS compared with men across all stages of NSCLC (all p < 0.001). This survival advantage persisted regardless of receipt of chemotherapy. Among patients receiving chemotherapy, survival improvements were observed in both sexes; however, women consistently exhibited longer median OS at each stage. From stage IB to IV, median OS in women was 52.0, 30.0, 13.0, and 5.0 months, respectively, compared with 33.0, 23.0, 11.0, and 4.0 months in men. Notably, the magnitude of sex-related survival differences was more pronounced in earlier stages (IB/II) than in advanced stages (III/IV), suggesting potential biological or treatment response differences favoring women. Age-stratified analyses further demonstrated that women older than 45 years experienced a consistent survival advantage across all stages. Multivariable Cox regression confirmed that female sex was independently associated with reduced mortality risk at every stage (HRs ranging from 0.766 to 0.857; all p < 0.001). Conclusions: Women with NSCLC exhibit a significant and independent survival advantage over men across clinical stages, regardless of chemotherapy status, particularly among patients older than 45 years. These findings highlight the importance of considering sex in prognostic assessment and support further investigation into factors contributing to survival differences in NSCLC. Full article