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Digital design and virtual simulation of sports bras based on TG3D-Nuno knitted fabric simulation

In response to the key issues in the current digital design of sports underwear, such as fabric simulation distortion, disconnection between dynamic and static verification, and lagging functional evaluation, this study proposes a full-process digital development method for rib-knitted sports underwear based on the collaboration of TG3D-Nuno and CLO3D. Taking cotton/spandex (78%/22%) rib-knitted fabric as the research object, its multi-dimensional physical properties such as color, normal, roughness, and displacement are collected through the TG3D-Nuno 3D scanning system. After parameter mapping and calibration, the high-fidelity reproduction of the fabric’s visual texture and mechanical properties is achieved in the CLO3D virtual environment. Moreover, combined with a standard female human model (height 175.3 cm, bust 80.6 cm), the pattern of a functional sports underwear integrating a front-opening zipper, crossed shoulder strap structure, and elastic hem is designed using the “3D pen” tool. Furthermore, by constructing a dynamic simulation scenario in a running posture, a systematic verification of the underwear’s fit, support stability, and fabric collaborative deformation characteristics during exercise is carried out. The experimental results show that the digital process established in this study significantly improves the virtual restoration accuracy of knitted fabrics. Based on the evaluation of the size matching degree index, the 3D matching degree of the optimized pattern in key areas exceeds 98%. The dynamic simulation effectively identifies and corrects functional defects such as shoulder strap slippage and insufficient cup fit. This method realizes a complete technical closed-loop from fabric digitization to dynamic function verification, providing a feasible technical solution for the rapid development and precise design of sports underwear.

Mapping radiosensitivity in glioblastoma using MR elastography and biomechanical modeling

Unveiling the bactericidal effects of extracts and phytocompounds from Eichhornia crassipes (Mart.) Solms against methicillin-resistant Staphylococcus aureus (MRSA): An in vitro and in silico approach

Background Eichhornia crassipes (Mart.) Solms is used as a vegetable by the tribal communities of the Chittagong Hill Tracts in Bangladesh, where it has traditionally been employed to treat diarrhea, intestinal worms, digestive disorders, and hepatic conditions. However, its effects against methicillin-resistant Staphylococcus aureus (MRSA) remain unexplored. Purpose To assess the in vitro antibacterial potential of methanol, ethanol, and ethyl acetate extracts from the flowers and leaves of E. crassipes (MEECF, EEECF, EAEECF, MEECL, EEECL, and EAEECL) and to identify multi-target antibacterial phytocompounds in silico against MRSA. Methods Preliminary phytochemical screening (PPS), Fourier-transform infrared spectroscopy (FT-IR), and gas chromatography-mass spectrometry (GC-MS) were used for phytochemical profiling of MEECF, EEECF, EAEECF, MEECL, EEECL, and EAEECL. The antimicrobial activity of the extracts was evaluated using in vitro agar well diffusion, minimum inhibitory concentration (MIC), and minimum bactericidal concentration (MBC) assays. Computational approaches were applied to identify multi-targeting agents from GC-MS-annotated phytocompounds. Results In phytochemical profiling, PPS revealed the diverse nature of the plant’s compounds, while FT-IR identified various functional groups. GC-MS analysis metabolically annotated a total of 383 phytocompounds across all extracts. Molecular docking identified two key compounds: CID 4970 in MEECF and EEECF, and CID 615944 in MEECL. These hit phytocompounds exhibited strong multi-modal binding affinity toward β-lactamase and PBP2a. Further analysis demonstrated that CID 4970 and CID 615944 possessed favorable pharmacokinetic (PK) and drug-like properties without toxicity, making them promising candidates. Molecular dynamics simulation confirmed the binding stability and multi-modal inhibitory activity of CID 4970 and CID 615944 within the active sites of β-lactamase and PBP2a, reinforcing their potential as lead compounds for developing inhibitors against these proteins. All extracts demonstrated dose-dependent antibacterial activity in agar well diffusion, MIC, and MBC assays, supporting the in silico results. Conclusion This study provides scientific validation for the traditional use of E. crassipes in treating bacterial infections and suggests that CID 4970 and CID 615944 could serve as promising candidates for developing novel anti-MRSA agents.

Multifactorial modeling of nematode–soil interactions associated with citrus decline and implications for sustainable orchard management in southern Iran

Abstract Citrus decline, one of the major challenges in the orchards of Fars and Kohgiluyeh–Boyerahmad provinces, is a multifactorial disorder exacerbated by complex interactions between biotic and abiotic factors. This study aimed to model the interactions between the citrus nematode ( Tylenchulus semipenetrans ) and the physicochemical properties of the soil, and to evaluate their combined roles in the severity of tree decline. A total of 80 soil and root samples were collected between 2020 and 2022 using standard nematological methods. The data were analyzed using advanced statistical approaches, including ordinal logistic regression (OLR), generalized additive models (GAMs), and partial least squares–discriminant analysis (PLS-DA). The results revealed a significant relationship between nematode population density and decline severity, with soil texture, salinity, saturation percentage, pH, and lime content (Total Neutralizing Value, TNV) acting as moderating factors. The highest nematode densities were observed in light-textured soils with an electrical conductivity ranging from 2.5 to 3.5 dS m⁻¹. Moreover, a significant synergistic interaction was identified among alkaline pH, high TNV, and nematode population density in inducing micronutrient deficiencies. These findings emphasize the necessity of adopting integrated management strategies, including the use of tolerant rootstocks, nematode population regulation, and soil quality improvement, to mitigate citrus decline losses.

Association of anticoagulant and antiplatelet therapy with acute cerebral infarction in patients presenting with isolated vertigo or dizziness: A retrospective cohort study

Background Acute cerebral infarction (ACI) is a critical concern in patients presenting with isolated vertigo or dizziness (IVD). The use of antiplatelet or anticoagulant agents may influence the incidence of ACI in both protective and adverse directions, due to their preventive effects and associated comorbidities. This study aimed to determine the incidence of ACI among emergency department (ED) patients with IVD, stratified by the use of antiplatelet and anticoagulant medications. We also evaluated the association between antiplatelet and anticoagulant therapies and ACI incidence. Methods This was a retrospective cohort study. ED patients with IVD over four consecutive years were identified. The main outcome was ACI, which was determined by brain magnetic resonance imaging with diffusion-weighted imaging (bMRI-DWI). The primary independent variable was the use of antiplatelet or anticoagulant medications, which was categorized into two models. In Model 1, patients were divided into three groups: a no-medication group (patients who did not take any antiplatelet or anticoagulant agents), an antiplatelet group (patients who took aspirin or clopidogrel but no anticoagulants), and an anticoagulant group (patients who took warfarin or non–vitamin K antagonist oral anticoagulants [NOACs], regardless of concurrent antiplatelet use). Model 2 provided a more detailed classification of medication use: no-medication group, aspirin-only group, clopidogrel-only group, aspirin and clopidogrel group, and anticoagulant group. In addition, based on whether comorbidities were adjusted for, the multiple logistic regression models were categorized into Model A (without adjustment for comorbidities) and Model B (with adjustment for comorbidities). A total of four multivariable logistic regression models were developed for analysis. Results Among the 1,875 patients enrolled, 153 (8.2%) were diagnosed with ACI. The incidence of ACI was 6.7% (74/1,104) in the no-medication group, 8.8% (59/670) in the antiplatelet group, and 19.8% (20/101) in the anticoagulant group. In the more detailed classification, the incidence was 7.4% (28/377) in the aspirin-only group, 6.6% (10/152) in the clopidogrel-only group, and 14.9% (21/141) in the dual antiplatelet group (aspirin and clopidogrel). In all four multivariable models, the use of anticoagulants emerged as an independent predictor of ACI (adjusted odds ratio [AOR], 2.46; 95% confidence interval [CI], 1.20–5.08; p = 0.014 in Model 2B). The dual antiplatelet group was significantly associated with ACI in Model 2A (AOR, 1.74; 95% CI, 1.02–2.97; p = 0.044), but this association was no longer significant after adjusting for comorbidities in Model 2B (AOR, 1.34; 95% CI, 0.77–2.34; p = 0.297). The antiplatelet group, aspirin-only group, and clopidogrel-only group were not significantly associated with ACI occurrence in any model. Conclusion Nearly 20% of patients in the anticoagulant group and 15% in the dual antiplatelet group (aspirin and clopidogrel) experienced ACI among ED patients with IVD. The use of anticoagulants was a significant predictor of ACI occurrence. The association between dual antiplatelet therapy and ACI lost statistical significance after adjusting for comorbidities. These two medication groups may serve as clinical proxies for elevated ACI risk in ED patients presenting with IVD.

Adsorptive removal of Cr(VI) ions using nitrogen-doping activated carbon: influence of pH, kinetics, isotherm models, optimization, and efficiency evaluation

Abstract Hexavalent chromium ion [Cr(VI)] poses serious environmental risks due to its high toxicity and ability to cross biological membranes, leading to organ damage and genetic mutations. This study presents a new practical method for removing Cr(VI) ions from wastewater using nitrogen-doped activated carbon (AC600) prepared by pyrolyzing sawdust with ZnCl 2 at 600 °C. Thereafter, batch experiments were conducted using different adsorbent doses (0.5–2.5 g L –1 ) and Cr(VI) ion concentrations (100–400 mg/L) at pH ranging from 1 to 12. Results revealed that Cr(VI) ions sorption on AC600 followed both linear and adsorption isotherm models at low sorbent doses (< 1.5 g/L). At higher doses, sorption shifted toward a hyperbolic adsorption pattern. Overall sorption data fitted well with both the Freundlich and Temkin isotherm models. Cr(VI) ions removal efficiency increased with contact time, following a sharp rise within the first 20–40 min of contact, while equilibrating within approximately 60–80 min. However, this efficiency decreased as pH increased. The highest efficiency (95–99%) was achieved using 2.5 g of AC600 to treat 1 L of water containing 100–150 mg/L of Cr(VI) ions within 2 h. For higher Cr(VI) ion concentration (200–250 mg/L), the efficiency decreased to 88–90%. The kinetics of Cr(VI) ion sorption on activated carbon followed the Pseudo-Second-Order model at low to moderate AC600 doses and low Cr(VI) ion concentrations. At higher doses and Cr(VI) levels, the power function and intraparticle diffusion models provided better fits. A maximum adsorption % could be achieved by using 2.5 g of AC600 and a Cr(VI) ion solution at 100 mg/L, according to results from an optimization of adsorption parameters using response surface methodology (RSM).

TL-DETR: Efficient transmission line defect detection for edge deployment

Visual inspection is critical for power system maintenance, yet deploying high-performance detection models on resource-constrained edge devices remains challenging due to complex background interference, extreme defect scale variations, and high computational overhead. This paper presents TL-DETR, a specialized detection framework that integrates multi-scale feature enhancement and dynamic sparse attention to achieve accurate and efficient transmission line defect detection for edge deployment. First, a ResNet-50-TL backbone network incorporating a multi-scale feature enhancement module is designed to preserve fine-grained features. Subsequently, the neck network integrates Attention-based Intra-scale Bi-level Routing and a channel shuffle mechanism to precisely focus on critical defects and reduce parameter count. Furthermore, a multi-scale attention mechanism is introduced to accomplish pixel-level recalibration through cross-spatial learning. Experiments on the CableInspect-ADs dataset demonstrate that the precision and mAP50 of TL-DETR reach 91.4% and 86.0%, respectively, representing improvements of 3.2% and 2.9% over the baseline RT-DETR. These results indicate that the model effectively balances accuracy and computational efficiency, demonstrating theoretical viability for practical edge deployment. Generalization experiments confirm that the model exhibits excellent generalization capabilities for detecting insulators, vibration dampers, and bolts, aligning closely with the engineering requirements for precise perception of minute defects.

Identification of key candidate genes for body weight traits in male Dongfeng sika deer based on genome-wide association analysis

ZIF-8-coated 3D-printed PCL/ion-doped BCP scaffolds for enhanced bone regeneration

Large bone defects require bioactive, mechanically robust scaffolds for regeneration. This study developed 3D-printed polycaprolactone/biphasic calcium phosphate (PCL/BCP) composite scaffolds (35−45 wt% ion-doped BCP with Sr 2+ , Mg 2+ , and Si 4+ ) via fused deposition modeling (FDM), followed by in situ ZIF-8 coating. The optimal PCL + 40 wt.% ion-doped BCP formulation exhibited superior compressive strength (~30 MPa) and modulus (~ 0.4 GPa). Degradation in Phosphate-buffered saline (PBS) showed ~8% mass loss over 28 days with stable pH. Immersion in simulated body fluid (SBF) revealed rapid apatite formation and sustained release of Ca 2+ , P, Mg 2+ , Si 4+ , and Sr 2+  ions. SEM confirmed uniform nanoscale ZIF-8 deposition, enriching surfaces with Zn 2+ . In vitro assays with MG-63 cells and hBMSCs demonstrated that ZIF-8-coated scaffolds significantly enhanced cell adhesion, proliferation (MTT), cytoskeletal organization (DAPI/phalloidin), and mineralization (Alizarin Red S) compared to uncoated controls (p < 0.05). The synergistic integration of ion-doped BCP, 3D printing, and ZIF-8 coating yields a bioactive, biodegradable platform with excellent osteogenic potential for advanced bone tissue engineering.

Synthesis of thiol-functionalized metal phthalocyanines-silver nanoparticles assemblies and their photophysics

Conformational Isomerization of Imide Anions Governs Solvation and Transport in Water-in-Salt Electrolytes

Quality of life domains revised by people with multiple sclerosis and healthcare professionals for adaptive measure development

Background Multiple sclerosis (MS) significantly affects individuals’ health-related quality of life (HRQoL). Ideally, HRQoL assessment tools for MS should be patient-centered, ensuring that each item meaningfully contributes to measurement precision. The present study has three main objectives: (1) a review of the literature to identify key HRQoL domains by examining existing instruments; (2) confirmation and integration of HRQoL domains based on stakeholders’ input; (3) systematic comparison of the categories and subcategories identified by the stakeholders with the domains identified in the literature review. Methods Findings from the literature review were discussed in four focus group meetings (FGMs) with key stakeholders, including people with MS (PwMS) and healthcare professionals (HPs). Participants were purposively sampled to ensure diversity in geographic location, gender, education, and (for PwMS) disease severity. FGMs were audio-recorded, transcribed verbatim, and analyzed using qualitative content analysis by two independent researchers. The categories and subcategories generated from the qualitative analysis were then systematically compared with the items of the MS-specific HRQoL instruments identified in the literature review, by two independent researchers. Results Out of 5190 references, 308 records related to 9 instruments were included in the literature review. The main HRQoL domains were then extracted and discussed with the steering committee, and informed the FGM grids. The results validated the HRQoL domains identified in literature and provided deeper insights into their complexity. Conclusion This study confirmed and added granularity to the existing HRQoL domains relevant to PwMS, identifying key areas for inclusion in future research. The findings contribute to the development of a more comprehensive, patient-centered HRQoL assessment tool, which could inform targeted interventions to enhance quality of life in PwMS.

GMMA as delivery system for Klebsiella pneumoniae O-antigens and K-antigens

Integrating multi-session transcranial direct current stimulation with routine physical therapy to improve quadriceps strength and activation in athletes during subacute recovery following ACL reconstruction: A double-blind RCT

Objective Anterior cruciate ligament reconstruction (ACLR) is often associated with persistent quadriceps weakness and impaired voluntary activation. Integrating active anodal transcranial direct current stimulation (a-tDCS) with routine physical therapy (RPT) may offer additional neuromodulatory benefits during the subacute phase of rehabilitation in nonprofessional male athletes. Methods Twenty male nonprofessional athletes (mean age: 27.50 ± 7.24 years, BMI: 25.83 ± 3.49) were randomly assigned to two groups: active M1 a-tDCS + RPT (n = 10) and sham M1 a-tDCS + RPT (n = 10). Both groups received 10 sessions of a-tDCS during RPT. The active group received 2 mA stimulation for 20 minutes per session, while the sham group received 2 mA for 30 seconds, followed by ramp-down and discontinuation. Quadriceps strength was measured using an isokinetic dynamometer, voluntary activation was assessed using the superimposed burst technique (Central Activation Ration (CAR) method) Baseline measurements were taken after 10 weeks of RPT, prior to the combined intervention phase. Results The active a-tDCS group demonstrated a significant improvement in CAR compared to the sham group (mean difference: 6.85%; 95% CI: 1.92–11.77; p = 0.01), while the sham group showed a slight, non-significant decrease (2.54%; p = 0/80). Within-group analysis revealed significant voluntary activation improvements in the active group (p = 0.005), with no significant changes in the sham group (p = 0.59). No significant between-group differences in quadriceps strength were observed (p = 0.4), although both groups showed significant within-group improvements (active: 21.8%, P ≤ 0.001; sham: 14.8%, p = 0.02), likely due to the effects of RPT. Conclusion The integration of multi-session a-tDCS with RPT during the subacute phase of ACLR recovery significantly enhanced voluntary activation and knee-specific function, as measured by the International Knee Documentation Committee (IKDC) score. These findings suggested that multiple-channel a-tDCS may facilitate neural activation and functional recovery, with clinically meaningful improvements in IKDC scores observed in the active group. Trial Registration: Iranian Registry of Clinical Trials (IRCT) Registration Number: IRCT20231113060048N1; Registered on December 28, 2023. URL: https://irct.behdasht.gov.ir/search/result?query=IRCT20231113060048N1

Adaptive error compensation in CNC turning based on deep reinforcement learning and genetic algorithm fusion

Abstract Precision manufacturing in CNC turning operations faces persistent challenges from complex, time-varying error sources, encompassing thermal deformation, progressive tool wear, and force-induced deflections. In this work we propose an adaptive error compensation framework that brings deep reinforcement learning (DRL) and genetic algorithms (GA) into a coupled, bidirectional loop, rather than treating them as standalone tools. GA performs global hyperparameter and reward-weight optimisation, while DRL handles real-time adaptive control through continuous interaction with the cutting environment. Validation on aerospace-grade Ti-6Al-4 V turning yields a mean absolute error of 2.6 μm—an 86.3% compensation effectiveness—together with 38% faster convergence than standalone DRL and a process capability index of 1.67 that comfortably clears the six-sigma threshold. Beyond ablation against DRL-only and GA-only configurations, we benchmark the fusion algorithm against three mainstream predictive-compensation baselines (BPNN-based, LSTM-based, and PSO-based) under identical machining conditions, and the proposed approach retains a clear margin across MAE, RMSE, recovery time, and convergence. The limits of the method are also reported: compensation accuracy degrades once cutting parameters drift more than 30% beyond the training envelope or when the workpiece material differs substantially from the training distribution, a constraint that motivates the transfer-learning extensions discussed later in the paper.

Satellite maps of sinking coastlines face scrutiny

Radar studies produce contradictory results, raising questions about efforts to identify areas vulnerable to rising seas

Knowledge of breast cancer and practice of breast self-examination among adolescent girls in semi-urban area – Savar, Dhaka, Bangladesh: A school-based cross-sectional study

Breast cancer is a leading cause of cancer-related deaths worldwide, with most cases in Bangladesh diagnosed at advanced stages due to limited awareness and late detection. While breast self-examination (BSE) is a simple, cost-free method for early detection, its practice among adolescents remains poorly understood. This study aims to explore breast cancer knowledge, BSE practices, and barriers among adolescent girls in a semi-urban area, addressing a critical gap in early prevention efforts. A cross-sectional study was carried out with 384 adolescent girls from four renowned schools in a semi-urban area of Dhaka, Bangladesh. Participants were sampled at school from January to April 2025. Proportionate stratified random sampling was conducted to determine the study sample from each school. A validated semi-structured self-reported questionnaire was employed to collect data from participants during the survey period. Among the participants, only 45.3% had heard of BSE and just 4.6% reported ever practicing it. Overall, breast cancer knowledge was low, with a mean score of 9.49 out of 31 (30.6%). Regression analyses indicated that higher breast cancer knowledge scores were significantly associated with having a science academic background (β = 1.82, p < 0.01), higher family income (β = 1.14, p < 0.05), and prior BSE practice (β = 2.36, p < 0.001). A strong positive correlation was observed between overall knowledge and BSE practice (r = 0.54, p = 0.001). Students from the science section were significantly more likely to practice BSE than those from the humanities section (OR = 9.47, 95% CI: 1.21–73.89, p = 0.032). Participants who received BSE information from health workers were approximately nine times more likely to practice BSE than those who did not (OR = 9.62, 95% CI: 2.30–40.20, p = 0.002). The study demonstrates critically low levels of breast cancer knowledge and BSE practice among adolescent girls, with knowledge strongly influencing practice. These findings underscore the need for culturally appropriate, school-based educational interventions to improve awareness, promote early detection behaviors, and potentially reduce future breast cancer morbidity and mortality in Bangladesh.

Tribological performance of Al5052/B₄C/Granite hybrid composites: machine learning prediction and multi-response optimization

Fast cell wall softening causes Venus flytrap closure

Plants can move rapidly without muscles, as seen in the Venus flytrap’s snapping lobes—a long-standing puzzle in plant biomechanics. Trap closure involves an elastic instability, but the active mechanical driver has remained elusive. Using in situ hydraulic and mechanical measurements, we identified the motor driving this transition. Closure occurs too quickly to be explained by water transport, revealing a distinct, nonhydraulic mechanism: a rapid (about one second) softening of the epidermal cell wall, releasing elastic energy stored in the trap. This represents the fastest modulation of wall mechanics reported in plants. Our finding reveals a mode of plant motility based on dynamic tuning of material properties, suggesting principles for muscle-free, bioinspired actuation.

Multilayer perceptron neural network approach for power quality improvement in a grid integrated PV and electric vehicle systems

Recently, there has been an increase in the grid integration of electric vehicles (EVs) and solar photovoltaic (PV) systems, primarily driven by two goals: lowering energy costs and decreasing emissions. Numerous research studies have concentrated on the separate effects of integrating PVs and EVs into the grid. Nevertheless, it is important to recognize that as the adoption of PVs and EVs continues to grow, the supply grid will face the cumulative effects of PV and EV integration on power quality (PQ) challenges. To provide a comprehensive understanding, this study examines the joint impact of PVs and EVs on PQ aspects in detail. This study has indicated that EVs and PVs alone can adversely impact grid reliability and PQ because of the variable character of PV source and the unpredictability of EV demand. But multiple research efforts have shown that coordination between PVs and EVs can help to alleviate certain problems that arise from their individual integration. This study demonstrates PQ enhancement in a grid system integrated with PV and EV using a multilayer perceptron neural network (MLPNN) approach. In the system with PV integration, the GWO-ANFIS, MPPT technique is employed for optimizing power extraction. Under balanced non-linear loading conditions, simulation results show that the THD is initially 25.97% without compensation, then decreases to 12.57% with a shunt passive filter (SPF), 3.37% with the application of recursive least squares (RLS), and 1.37% with MLPNN. With much lower THD and quicker convergence, the suggested MLPNN-based controller exhibits improved harmonic mitigation. A comparison between the proposed and existing methods are drawn using the MATLAB/Simulink platform.