Search Results (4,658)

Concussions exert a massive cost on our economic and healthcare systems. Many of the most commonly employed neurocognitive measures in concussion assessment have been shown to be psychometrically problematic. Additionally, norms are established from largely male populations. The present study investigates the use of a validated and reliable measure of concussion sequelae, the mobile half-version of the Connors Continuous Performance Test 3rd Edition (CCPT-3), on a representative population to study the influence of sex and age on normative values collected at baseline. Baseline data were analyzed from 71,976 participants across a wide range of academic and athletic contexts, as well as healthcare settings. Multiple regressions examined the influence of sex as a function of age in different developmental groups: children, adolescents, young adults, adults, and older adults. Sex effects emerged during childhood, peaked during adolescence, and decreased in adulthood. Females showed better accuracy (fewer commission and omission errors), whereas males had faster response speeds (hit-rate RT). Effect sizes were generally in the small to very small range (sex effect sizes ranged from Cohen’s d = 0.02 to 0.39). The findings highlight the importance of accounting for sex and age in cognitive test performance and underscore the impact of correcting for even small effects when working with large samples. Full article

With ongoing urban warming and the increasing frequency of extreme heat events, thermal comfort at highly exposed public spaces like bus stops has attracted significant attention. However, existing studies largely rely on linear assumptions and limited environmental variables, leaving the complex, multidimensional mechanisms driving thermal perception unclear. This study investigates the nonlinear impacts of microclimate, urban morphology, and station design on passengers’ thermal perception during summer in Chongqing, China. Drawing on field measurements, questionnaire surveys, and spatial data, linear regression was first applied to estimate neutral temperatures and acceptable thermal ranges. Subsequently, an interpretable machine learning framework integrating XGBoost and SHAP analysis was developed to explore the nonlinear effects and interactions mechanisms among these variables. The results reveal a dual regulatory pattern. Mechanism variables exhibit distinct nonlinear thresholds, with wind speeds above 0.98 m/s showing cooling associations and PET values exceeding 34.70 °C corresponding to more rapid increases in thermal discomfort. Concurrently, urban morphology and station design factors contextually modify these direct effects by altering their magnitude and direction. Furthermore, significant spatial heterogeneity in thermal adaptation was observed, with neutral temperatures ranging from 23.19 to 31.01 °C. These findings provide a basis for developing adaptive and context-specific thermal environment management strategies for urban bus stops. Full article

Electric dipole antennas can be designed in a variety of geometries and applied across a wide range of configurations. Appropriately designed dipole antennas can provide deep tissue penetration and low radiofrequency (RF) power deposition in magnetic resonance imaging (MRI), making them attractive for applications requiring safe and effective RF transmission in deep regions. On clinical 3 T MRI systems, however, conventional dipoles are too large in size for practical imaging of the head. Inspired by telecommunications designs, the present work adapts meandered dipoles (where the conductor is folded to shorten the antenna) with the resonance frequency controlled through trace geometry. Additionally, multi-channel configurations are considered to improve RF power transmission. A straight dipole was progressively transformed into meandered geometries and characterized using benchtop measurements and electromagnetic simulations. Analyses evaluated frequency response, near-field behavior, power-flow directionality, and distributions of local tissue heating and transmitted RF magnetic field in multi-channel arrays. A four-channel parallel-transmit (pTx) prototype was also used to show the feasibility of dipole-based head imaging at 3 T. The present work demonstrates a practical implementation of compact, low-heating dipole arrays for head MRI, with potential for extension to ultra-high-field or multinuclear imaging. Full article

Background/Objectives: Tissue flossing (TF) with elastic bands (floss bands) is a therapeutic strategy to improve joint range of motion (ROM). While TF has demonstrated 3–7% ROM improvements in ankle and shoulder joints, its effects on knee flexion remain underexplored. Therefore, the objective of this study was to investigate the acute effects of TF on active and passive knee flexion range of motion in healthy adults. Methods: Sixty healthy participants (median age 23.0 [IQR 2.0] years; 30 male, 30 female) were randomized to an intervention group (IG; n = 30) receiving floss band (COMPRE Sanctband^®, Level 1; 50% tension, 50% overlap) application combined with knee mobilization (20 active/passive repetitions over 2 min), or a control group (CG; n = 30) performing the same mobilization without band application. Active (AROM) and passive (PROM) knee flexion were measured pre- (M0) and post-intervention (M1) using a validated smartphone goniometer (Goniometer Pro), by a blinded assessor. Results: Baseline characteristics (age, body mass index) did not differ between groups (p > 0.05); however, baseline AROM differed significantly between groups (p = 0.041). The IG showed significantly greater improvements than CG in AROM (Δ5.0° [4.0%] vs. Δ0.0°, p < 0.001) and PROM (Δ6.0° [4.5%] vs. Δ1.0° [0.8%], p < 0.001). Conclusions: TF combined with mobilization produced greater immediate increases in knee flexion ROM than mobilization alone, with large effect sizes. These findings support adequately powered, sham-controlled trials in clinical populations before clinical effectiveness can be inferred. Full article

We present a material distribution topology optimization (TO) framework that directly generates capacity-specific radial trims for severe-service control valves. The method uses an out-of-plane resistance modified two-dimensional turbulence model and objective functions that maximize directional change to create tortuous pressure-staging geometries at predefined channel depths. Four trims targeting non-dimensional capacities ($C_V$) of 0.672, 0.96 (two objectives), and 1.248 were optimized, MSLA-printed, and tested in a globe valve using IEC 60534 procedures. The measured capacities ranged from −13.7% to +4.8% of the targets for a fully 2D optimization process, dropping to a maximum of 7.8% when coupled with a hybrid 3D tuning step. Acoustic detection indicated incipient cavitation at a pressure drop ratios greater than $0.87$ for the most highly staged design and $0.73$ for the highest capacity design, which is consistent with our simulations of the flow field before fabrication. These results demonstrate that TO can deliver fit-to-service, capacity-tuned trims with excellent cavitation suppression, reducing reliance on large parametric design libraries. Full article

Peeling behavior of soft materials is important in a wide range of applications, e.g., electronics, healthcare, etc. When applied on soft substrates, soft adhesives demonstrate unique mechanical behaviors compared to adhesives applied on rigid substrates. Adhesive properties can be conveniently measured by “peel testing”. The focus of this work is characterization of commercial glues on fabric substrates using commonly used peel tests. We investigate energy dissipation on textile substrates. For practical applications, we aim to develop a systematic approach for selecting adhesives for soft, flexible substrates. Here, we developed a multi-criteria framework for evaluating adhesives using data from peel tests. The criteria used here consider the shape and stability of the T-peel trace. The results of the multi-criteria evaluation were compared to traditionally used peel strength and fracture energy. Although E6000 produced the highest peel force ($1.82\pm 0.27 \mathrm{N} \mathrm{m}{\mathrm{m}}^{-1}$) and the largest apparent fracture energy, ${\mathrm{G}}_{\mathrm{c}}$ ($8673\pm 1545 \mathrm{J} {\mathrm{m}}^{-2}$), it showed large force oscillation ($\mathrm{S}\mathrm{S}\mathrm{A}=4.05\pm 0.83 \mathrm{N}$). Fabri-Fuse was selected based on its low oscillation ($\mathrm{S}\mathrm{S}\mathrm{A}=0.69\pm 0.29 \mathrm{N}$), lowest $\mathrm{C}\mathrm{o}{\mathrm{V}}_{{\mathrm{F}}_{\mathrm{c}\mathrm{i}}}$(4.0%), high peel stability index (PSI), and high displacement at break. Functional evaluation showed that Fabri-Fuse increased strain-to-electrical-failure to $34.95\pm 2.43\mathrm{\%},$ higher than direct printing on fabric or printing on E6000 (highest peel strength). These results suggest that metrics that consider the shape of the peel trace and inter-sample repeatability provide a useful alternative for selecting adhesives other than highest peel strength. Full article

Background: Return to play (RTP) after total hip arthroplasty (THA) is increasingly expected by younger and more physically active patients. Current activity recommendations remain heterogeneous and are largely derived from expert opinion and indirect biomechanical modelling approaches, rather than direct in vivo biomechanical evidence. The aim of this article is to systematically map and synthesize the evidence from instrumented hip implant studies and to clarify how direct in vivo telemetry data can inform RTP counselling after THA. Methods: A scoping review was conducted according to a predefined Open Science Framework protocol and reported following PRISMA-ScR guidelines. MEDLINE (PubMed) and Scopus were searched from inception. Peer-reviewed clinical studies reporting direct in vivo biomechanical measurements obtained from instrumented hip implants were included. Conference proceedings, technical notes, reviews, and in vitro or computational-only studies were excluded. Data were extracted and synthesized descriptively according to activity domain, biomechanical variables, and implant technology. Results: Fifty studies met the inclusion criteria. Early investigations established feasibility and evolved from wired strain-gauge systems to fully implantable telemetric prostheses capable of measuring three-dimensional forces, moments, and friction-related parameters. Across cohorts, level walking consistently produced peak hip contact forces of approximately 2–3 times body weight, serving as a clinically meaningful reference loading envelope. Several recreational activities—including cycling, aquatic exercise, Nordic walking, and most gym-machine exercises—generally remained within or close to this range when performed with controlled technique. In contrast, certain rehabilitation tasks, forward-bent postures, lifting maneuvers, and perturbation events generated loads equal to or exceeding those observed during walking. Importantly, frictional moments and load direction showed substantial variability and may be more relevant to implant fixation than peak force magnitude alone. Conclusions: Instrumented hip implants provide objective biomechanical benchmarks that support principle-based and individualized RTP counselling, grounded in directly measured mechanical exposure rather than sport classification alone. Full article

Objective: Despite increasing use of behavioural interventions in paediatric swallowing and feeding care, the evidence base remains limited and difficult to interpret due to small sample sizes, heterogeneous interventions, diverse outcome measures, and variability in study populations. This review and meta-analysis, therefore, aimed to evaluate the effects of behavioural interventions and botulinum toxin injections on drooling, swallowing, feeding, and oral-motor outcomes in children, based exclusively on randomised controlled trials (RCTs). Methods: Systematic searches were conducted in CINAHL, Embase, and PubMed to identify RCTs. Pharmacological and surgical interventions were excluded, except for botulinum toxin injections, which were analysed as a distinct intervention category given their widespread clinical use in paediatric drooling management. Methodological quality was assessed using the Revised Cochrane Risk of Bias tool (RoB 2). Random-effects meta-analyses were performed, with prediction intervals calculated to account for between-study heterogeneity and to assess the expected range of effects in comparable future studies. Results: Twenty-eight studies were included. Behavioural interventions demonstrated moderate-to-large effects on oral-motor outcomes, whereas botulinum toxin injections demonstrated the strongest effects on drooling. Outcomes measured using multi-item caregiver-reported tools showed larger effects. No significant effects were observed for swallowing or feeding outcomes. Effect sizes varied by age, outcome measure, and respondent type, indicating systematic sources of variation in intervention effects. Prediction intervals indicated substantial clinical and methodological variability, suggesting that intervention effects are context-dependent and not consistently generalisable across populations and settings. Conclusions: Intervention effectiveness in paediatric swallowing and feeding is domain-specific, with consistent benefits observed for drooling and oral-motor outcomes but not for swallowing or feeding. Outcomes are strongly influenced by the measurement approach. High-quality, standardised RCTs targeting specific functional domains are needed to strengthen the evidence base and inform clinical decision making. However, substantial variability in intervention effects across studies suggests that treatment effectiveness may vary with population characteristics, intervention approaches, and outcome measurement methods. Full article

Machine learning (ML)-assisted design of epsilon-negative polymer nanocomposites requires a clear connection between experimentally controllable synthesis parameters, core–shell nanoparticle geometry, and the resulting effective optical response. The targeted optical response is unusual because the polymer film is predicted to exhibit near-zero or negative real effective permittivity in selected visible spectrum regions, arising from Ag core plasmonic polarizability, SiO₂-mediated dielectric spacing, nanoparticle filling factor, and effective medium coupling rather than from the intrinsic polymer matrix. In this study, a two-stage ML-assisted synthesis-to-optics framework is developed for Ag@SiO₂ core–shell nanoparticle/polymer composite films intended for visible spectrum effective permittivity screening. In the first stage, Stöber synthesis parameters, including water volume, ethanol volume, TEOS content, catalyst volume, reaction time, Ag nanoparticle size, and Ag nanoparticle concentration, were used to predict SiO₂ shell thickness. In the second stage, Ag core size, SiO₂ shell thickness, wavelength, and nanoparticle filling factor were used to screen the real effective permittivity of Ag@SiO₂/polymer nanocomposites within an effective medium design space. Using a duplicate-aware validation workflow, Gradient Boosting provided the strongest held-out test performance for shell thickness prediction, with a test R² of 0.8997, MAE of 7.1822 nm, RMSE of 8.8344 nm, and cross-validation R² of 0.5371 ± 0.4648. The relatively large cross-validation variability indicates that the model is useful for interpolation-based synthesis screening but should not be interpreted as fully robust across heterogeneous literature-derived data. For the optical response task, the highest held-out test performance was obtained by a Decision Tree model (test R² = 0.7586), but cross-validation results were unstable, indicating that the epsilon model should be interpreted as a design space screening tool rather than a generalizable predictor. Design window analysis identified candidate negative effective permittivity regions primarily at 400 nm and high nanoparticle filling factor, with predicted $\mathrm{R}\mathrm{e}\left({\epsilon }_{\mathrm{e}\mathrm{f}\mathrm{f}}\right)$ values ranging from −5.4229 to −0.2086 across selected windows. The main contribution of this work is the treatment of SiO₂ shell thickness as a bridge variable between Stöber-derived synthesis control and effective permittivity screening. Experimental validation remains necessary to confirm the predicted design windows, particularly because shell uniformity, Ag core polydispersity, nanoparticle aggregation, polymer dispersion, high-filling-factor feasibility, and effective medium validity can strongly influence the measured optical response. Full article

Accurate forest height reference points are essential for large-scale forest canopy mapping and carbon stock estimation. Currently, spaceborne Light Detection and Ranging (LiDAR) systems, primarily GEDI and ICESat-2, serve as the main data sources for acquiring global forest height reference points. To ensure data quality, conventional processing often relies on strict physical parameter filtering, such as retaining only nighttime and strong (full power) beam observations, which considerably reduces the available data density. Moreover, gross errors caused by signal attenuation or solar background noise often remain, limiting the accuracy of subsequent spatial modeling. To address the trade-off between measurement accuracy and data density, this study proposes a physically constrained outlier filtering strategy for spaceborne LiDAR retrievals, assisted by a priori continuous canopy height model (CHM) products. Aiming to maximize data retention, this method introduces a morphologically consistent global continuous CHM (such as the 10 m Pauls CHM) as a prior spatial envelope. By calculating the local height difference distribution and applying a 1$\sigma$ adaptive truncation, outliers are effectively removed. Comparative validations in the Genhe (coniferous forest, China) and HARV (mixed broadleaf forest, USA) study areas indicate that: (1) traditional filtering results in a data loss of over 80% while yielding limited accuracy; (2) after relaxing the initial filtering conditions, the proposed strategy reduces the overall root mean square error (RMSE) of GEDI and ICESat-2 retrievals by 12.6% to 36.0%; (3) owing to the effective removal of gross errors, the conventionally discarded daytime and weak (or coverage) beam data achieve substantially reduced error levels, sometimes even lower than those of traditional nighttime strong beam observations. Consequently, the spatial density of high-quality reference points is increased by 1.5 to 4.4 times. This study demonstrates the application value of low signal-to-noise ratio (SNR) spaceborne observations and provides a practical approach for obtaining high-quality, high-density control points for large-scale forest structure mapping. Full article

Watermelons account for 7% of the world’s fruit vegetable production. In the European market, Spain contributes around 35% of total watermelon supply, with the majority grown in greenhouses in Almería, Southern Spain. This study presents experimental results from the first agrivoltaic watermelon trial conducted in a raspa-y-amagado greenhouse during the 2024 growing season in Almería, Spain. Watermelons were cultivated under two shading treatments with 30% and 50% of the roof area covered with PV modules and compared against an unshaded control group. Throughout the experiment, temperature values in the 30% and 50% zones were 2.2 °C and 4.3 °C lower than in the control zone, respectively. The unshaded control zone and the 30% shading treatment maintained DLI conditions within the optimal range between 21 mol m⁻² d⁻¹ and 32 mol m⁻² d⁻¹ for most of the crop cycle, while the 50% shading zone remained largely above the minimum threshold of 15 mol m⁻² d⁻¹ required for adequate crop growth. No statistically significant differences were observed in fruit weight, rind width, fruit firmness, or soluble solids content at harvest. In addition, the experimentally measured irradiance data from this study were compared with simulations from a previously established irradiance model. The model was applied to the raspa-y-amagado greenhouse, and the experimental data were used to perform a long-term comparison between simulated and measured irradiance for 265 days of data. The irradiance model accurately reproduced shading effects from both the PV modules and greenhouse structure, achieving nRMSE values of 0.09, 0.18, and 0.27 for the control, 30% shading, and 50% shading zones, respectively. Full article

In the northern Sichuan Basin, distant from the main body of the Emeishan Large Igneous Province (ELIP), marine deposits of the Wujiaping Formation from the Permian period contain widely distributed tuffs of varying thicknesses. To clarify the genesis of these tuffs and their relationship with the ELIP, this study conducted field measurements and sample collection at the Daliang Section, Wangcang County, and the Qiaoting Section, Nanjiang County, of the northern Sichuan Basin and compared them with basalts and tuffs from Well DY1 in a minor basaltic eruption zone in the northern Sichuan Basin. The results indicate that tuffs from the Daliang and Qiaoting Sections of the northern Sichuan Basin exhibit high Al₂O₃/TiO₂ ratios (23.65–39.55) and significant depletion of Eu, Ba, and Sr elements. These characteristics suggest that their origin is linked to multiphase felsic volcanic activity within the ELIP and formation in an intraplate extensional setting. The basalts and tuffs developed at Well DY1 share the same low Al₂O₃/TiO₂ ratios (4.02–4.97), similar to the Emeishan basalts. In the Zr-Ti, Zr/Sc-Th/Sc, Nb/Y-Zr/TiO₂, and Zr/TiO₂-SiO₂ diagram plots, they fall within the basalt range, indicating that the tuffs at Well DY1 originated from the mid-ELIP eruption of basic basalt. In contrast to the felsic nature of the tuffs at Well DY1, the northern Sichuan Basin lacks records of such basic–alkaline igneous eruptions, suggesting that the influence of basalt eruptions in the northeastern Sichuan Basin is limited and does not affect the Wujiaping Formation in the northern Sichuan Basin. There is a positive correlation between volcanic activity and the total organic carbon (TOC) content of black siliceous rocks and siliceous shales in the Wujiaping Formation of northern Sichuan. The acid volcanic eruptions from Emeishan likely also played a key role in the formation of high-quality hydrocarbon source rocks in the deep-water continental shelf areas of the Wujiaping Formation in the northern Sichuan Basin. Full article

Soluble solids content (SSC) is one of the most important indicators of sweetness, ripeness, and market quality in sweet cherries. However, conventional SSC determination is destructive, labor-intensive, and unsuitable for rapid or large-scale quality assessment. Therefore, there is a need for fast, non-destructive, and data-driven sensing approaches that can estimate internal fruit quality without damaging the sample. This study aimed to develop a non-destructive approach for SSC prediction in sweet cherries by combining open-ended coaxial probe dielectric spectroscopy with deep learning models. An open-ended coaxial probe measurement system was designed and developed to determine the dielectric properties of sweet cherries and was coupled with an Agilent E4991A impedance analyzer operating over a frequency range of 5–3005 MHz. A total of 10,080 dielectric measurements and 2100 reference SSC measurements were collected over 26 experimental days. The dielectric constant (ε′), loss factor (ε″), and loss tangent (tan δ) were extracted and used to construct separate ε′, ε″, tan δ, and integrated combined datasets. Six deep learning architectures, namely convolutional neural network (CNN), long short-term memory (LSTM), bidirectional long short-term memory (BiLSTM), gated recurrent unit (GRU), CNN-LSTM, and convolutional long short-term memory (ConvLSTM), were trained and optimized using Bayesian optimization and early stopping. CNN achieved the best performance on the tan δ dataset (test R² = 0.9099, RMSE = 0.8354 °Brix, MAE = 0.6599 °Brix), whereas GRU yielded the highest accuracy on the integrated combined dataset (test R² = 0.8622, RMSE = 1.0331 °Brix, MAE = 0.7958 °Brix). ConvLSTM provided the most consistent performance across all four datasets (test R² = 0.8081–0.8651), demonstrating strong predictive capability and practical computational efficiency. These findings confirm the potential of reduced-range dielectric spectroscopy combined with deep learning for rapid, non-destructive SSC assessment in sweet cherries. Full article

This study presents the results from a comparison of measurement quantification methods of methane emissions from two onshore liquefied natural gas (LNG) export terminals, comparing site-level measurements, made using an in situ airborne technique, and estimates based on emission factors (EFs) derived from measurements using a remote sensing, ground-based, differential absorption LIDAR (DIAL) technique. The methane emissions from each site were quantified at an approximately one-year interval for each of the two techniques. DIAL was used to measure emissions at the sub-site, functional element (FE) level and calculate EFs for each FE using the specific FE activity data (AD). The total site methane emissions during the airborne measurements were estimated for each site using these EFs and the AD at the time. The results show the estimated methane emissions and the airborne measurements are close to agreement when considering the average of all the flight curtains (down to a 7% difference between uncertainty limits), whilst individual curtains were potentially significantly different. These results highlight the importance of fully characterising the methodology and uncertainty of both approaches. Using up-to-date, site-specific EFs or comparing over a statistically large sample size should improve agreement by reducing unknown emission uncertainties associated with site changes affecting the emission profile. Understanding each FE emission profile across a range of AD is critical to address potential differences due to non-linearity. It is important that accurate, specific and up-to-date AD is obtained to give a reliable estimate of emissions. The potential of the concept to estimate methane emissions from the FE EFs is demonstrated. Full article

Multiple three-phase machine drives are inherently fault-tolerant due to their multiphase structure; however, they remain susceptible to inverter-related faults. A common fault is the loss of gate signals in one inverter leg, resulting in an open-phase condition. Under such conditions, a reverse conduction path is established through the freewheeling diodes of the faulted leg, leading to uncontrolled freewheeling diode current generation. The resulting freewheeling diode current becomes particularly critical in the field-weakening region, when the back-EMF may exceed the DC-link voltage and a large reverse current can occur. This paper derives an analytical expression for real-time prediction of the freewheeling diode current in a triple three-phase surface-mounted permanent magnet synchronous machine drive. The method is applicable in both the constant-torque and field-weakening regions. The analytical prediction is validated through comparison with both experimentally measured and numerically simulated freewheeling diode current waveforms over a wide range of operating points, including no-load and loaded conditions. The results show that the proposed model accurately reproduces the envelope and conduction boundaries, while maintaining good agreement with simulations and measurements. The predicted current can be utilized in post-fault control, fault detection, and sensorless position estimation. Full article