Search Results (5,383)

Background: Accurate assessment of volume status remains a central challenge in hemodialysis (HD). Although bioimpedance spectroscopy (BIS) can quantify fluid compartments, it is time-consuming and requires a lot of personnel. Modern HD machines provide continuous relative blood volume (RBV) monitoring. We examined whether intradialytic RBV dynamics reflect pre-dialysis extracellular fluid (ECW) status to inform personalized fluid management. Methods: In an ancillary, monocentric, prospective study of the SkInDialysis trial (DRKS00036332), 11 maintenance-HD patients underwent three standardized dialysis sessions with simultaneous measurement of RBV and BIS. BIS was performed at five time points per session (pre-HD; 20, 80, and 160 min after the start of HD; and post-HD). Ultrafiltration (UF), RBV, total body water (TBW), ECW, and intracellular water (ICW) were recorded. Results: Mean total UF was 2809 ± 894 mL/session. RBV declined to 94.7 ± 3.1% at 20 min and to 87.6 ± 5.5% by the end of the session. TBW decreased by 2.9 ± 2.7%, driven by ECW reduction (−3.15 ± 2.9%) over ICW (−1.1 ± 1.65%). Cumulative UF correlated with declines in TBW (R² = 0.18; p = 0.02) and ECW (R² = 0.23; p = 0.01) and more modestly with ICW (R² = 0.16; p = 0.04). In contrast, ΔRBV (pre- vs. post-HD) did not correlate with UF, weight loss, or compartmental water changes. Early steady-state RBV at 80 min correlated with pre-HD ECW (R² = 0.19; p = 0.02) and more strongly with the pre-HD ECW/ICW ratio (R² = 0.34; p = 0.001). Conclusions: In this small, repeated-measures cohort, absolute early steady state RBV levels were associated with pre-dialysis ECW and the ECW/ICW ratio, whereas RBV change (ΔRBV) did not track absolute fluid removal. Our data support a time-anchored RBV level as a pragmatic, device-embedded indicator of the pre-dialysis extracellular reservoir. Full article

This study examines the design and implementation of a sensor developed to measure total pressure in supersonic flow conditions using nitrogen as the working fluid. Using a combination of absolute and differential pressure sensors, the total pressure distribution downstream of a nozzle—where normal shock waves are generated—was characterized across a range of low-pressure regimes. The experimental results were employed to validate and calibrate computational fluid dynamics (CFD) models, particularly within pressure ranges approaching the limits of continuum mechanics. The validated analyses enabled a more detailed examination of shock-wave behavior under near-continuum conditions, with direct relevance to the operational environment of differentially pumped chambers in Environmental Scanning Electron Microscopy (ESEM). Furthermore, an entropy increase across the normal shock wave at low pressures was quantified, attributed to the extended molecular mean free path and local deviations from thermodynamic equilibrium. Full article

Knee osteoarthritis (OA) is a prevalent condition in older adults that often results in impaired gait and balance, increased risk of falls, and reduced quality of life. Conventional clinical assessments may not adequately capture these deficiencies. This study investigated the gait and balance of elderly individuals with knee OA using wearable inertial measurement units (IMUs). Forty-four participants with Kellgren–Lawrence grade 2–3 knee OA (71.23 ± 5.75 years) and forty-five age-matched controls (70.87 ± 4.30 years) completed dynamic balance (balance board), static balance (single-leg stance), ‘timed up and go’ (TUG), and normal walking tasks. Between 2 and 8 IMUs, depending on the task, were placed on the head, chest, waist, knees, ankles, soles, and balance board to record kinematic data. Balance was quantified using absolute angular velocity and linear acceleration, with group differences analyzed by MANOVA and Bonferroni-adjusted univariate tests. The participants with knee OA exhibited greater gait asymmetry, although the difference was not significant. However, they consistently demonstrated higher absolute angular velocities than controls across most body segments during static and dynamic tasks, indicating reduced postural stability. No group differences were observed in TUG performance. These findings suggest that IMU-based measures, particularly angular velocity, are sensitive to balance impairment detection in knee OA. Incorporating IMU technology into clinical assessments may facilitate early identification of instability and guide targeted interventions to reduce fall risk. Full article

This article is an attempt to empirically establish a new category of social beliefs defined as postmodern beliefs. They are cognitive categorizations of social and media messages regarding ways of understanding the world which are based on the basic assumptions of postmodernism, quite widely recognised as fundamental. The theoretical model adopted in the article assumes the existence of three beliefs: antifundamentalism, absolutization of freedom and relativization of truth. The hypothesised concept was operationalized as Postmodern Beliefs Questionnaire (PMBQ). Verification studies were carried out on three groups of over 600 people. The verification of the tool was carried out by using exploratory factor analysis (EFA) to select the appropriate pool of statements, then data in two subsequent datasets was analysed using Confirmatory Factor Analysis (CFA) to empirically verify the selected set of statements and estimate relevant parameters. The tool constructed allows for investigating the distinguished beliefs at a satisfactory level of reliability and validity. It can be used to measure the extent to which the representations that make up the popular understanding of postmodernism have been recognised and built into the overall belief system about the world of the respondents. The distinguished postmodern beliefs differ in terms of relations with other social beliefs of the respondents, such as anthropocentrism, traditionalism, faith in a just world, as well as the attitude of individuals to material values or their individualistic orientation. Full article

Background: The Healthy Japan 21-Phase III dietary recommendations comprise a staple food, main dish, and side dish to maintain nutritional balance and support healthy child growth. The relationship between the frequency of such balanced meals and early adiposity rebound (AR), a predictor of obesity, remains unclear. Objective: This study aimed to examine the association between the frequency of balanced meals (staple food, main dish, and side dish) and early AR in preschool children. Methods: In this cross-sectional secondary analysis of nationwide online survey data of 688 mothers of children aged 3–6 years, dietary habits were assessed using a validated NutriSTEP-based 22-item Japanese Nutrition Screening Questionnaire. AR constituted a body mass index (BMI) increase from the 18- to 36-month health checkups recorded in the Maternal and Child Health Handbook. Risk scores reflecting lower frequency of balanced meals were calculated for staple foods, main dishes, and side dishes. Logistic regression evaluated associations between dietary risk scores and AR, adjusting for the child’s sex, age, gestational age, birth weight, daycare attendance, and parental obesity. Results: Among 688 children, 193 (28.1%) exhibited early AR and had significantly higher BMI at age 3 and the most recent measurement (both p < 0.01). A higher total dietary risk score was independently associated with AR (adjusted odds ratio; 2.58 [95% CI: 1.08–6.16]). In addition, the absolute risk difference between high- and low-risk groups was 8.5% (95% CI: 1.7–15.2%). Conclusions: A lower frequency of balanced meals is associated with early AR. These findings suggest that a simple, meal-balance screening tool could potentially aid in the early identification of the risk of later obesity and timely nutritional guidance. Full article

We previously developed machine learning (ML) models for predicting cycloplegic spherical equivalent refraction (SER) and myopia using non-cycloplegic data and following a standardized protocol (cycloplegia with 0.5% tropicamide and biometry using NIDEK A-scan), but the models’ performance may not be generalizable to other settings. This study evaluated the performance of ML models in an independent cohort using a different cycloplegic agent and biometer. Chinese students (N = 614) aged 8–13 years underwent autorefraction before and after cycloplegia with 0.5% tropicamide (n = 505) or 1% cyclopentolate (n = 109). Biometric measures were obtained using an IOLMaster 700 (n = 207) or Optical Biometer SW-9000 (n = 407). ML models were evaluated using R², mean absolute error (MAE), sensitivity, specificity, and area under the ROC curve (AUC). The XGBoost model predicted cycloplegic SER very well (R² = 0.95, MAE (SD) = 0.32 (0.30) D). Both ML models predicted myopia well (random forest: AUC 0.99, sensitivity 93.7%, specificity 96.4%; XGBoost: sensitivity 90.1%, specificity 96.8%) and accurately predicted the myopia rate (observed 62.9%; random forest: 60.6%; XGBoost: 58.8%) despite heterogeneous cycloplegia and biometry factors. In this independent cohort of students, XGBoost and random forest performed very well for predicting cycloplegic SER and myopia status using non-cycloplegic data. This external validation study demonstrated that ML may provide a useful tool for estimating cycloplegic SER and myopia prevalence with heterogeneous clinical parameters, and study in additional populations is warranted. Full article

Background: Failure to rescue (FTR), defined as death after major postoperative complications, is a critical quality indicator in pancreatic cancer surgery. Despite advances in surgical techniques and perioperative care, FTR rates remain high and vary across institutions. Methods: This systematic review uses a narrative synthesis followed by PRISMA 2020. A PubMed search (1992–2025) identified 83 studies; after screening, 52 studies (2010–2025) were included. Eligible designs were registry-based, multicenter, single-center, or prospective audits. Given substantial heterogeneity in study designs, FTR definitions, and outcome measures, a narrative synthesis was performed; no formal risk-of-bias assessment or meta-analysis was conducted. Results: Definitions of FTR varied (in-hospital, 30-day, 90-day, severity-based, and complication-specific cases). Reported rates differed by definition: average reported rates were 13.2% for 90-day CD ≥ III (G1); 10.3% for in-hospital/30-day CD ≥ III (G3); and 7.4% for 30-day “serious/major” morbidity (G8). Absolute differences were +3.0 and +2.9 percentage points (exploratory, descriptive comparisons). Five domains were consistently associated with lower FTR: (i) centralization to high-volume centers; (ii) safe adoption/refinement of surgical techniques; (iii) optimized perioperative management including early imaging and structured escalation pathways; (iv) patient-level risk stratification and prehabilitation; and (v) non-technical skills (NTSs) such as decision-making, situational awareness, communication, teamwork, and leadership. Among NTS domains, stress and fatigue management were not addressed in any included study. Limitations: Evidence is predominantly observational with substantial heterogeneity in study designs and FTR definitions; the search was limited to PubMed; and no formal risk-of-bias, publication-bias assessment, or meta-analysis was performed. Consequently, estimates and associations are descriptive/associative with limited certainty and generalizability. Conclusions: NTSs were rarely used or measured across the included studies, with validated instruments; quantitative assessment was uncommon, and no study evaluated stress or fatigue management. Reducing the FTR after pancreatic surgery will require standardized, pancreas-specific definitions of FTR, process-level rescue metrics, and deliberate strengthening of NTS. We recommend a pancreas-specific operational definition with an explicit numerator/denominator: numerator = all-cause mortality within 90 days of surgery; denominator = patients who experience major complications (Clavien–Dindo grade III–V, often labeled “CD ≥ 3”). Addressing the gaps in stress and fatigue management and embedding behavioral metrics into quality improvement programs are critical next steps to reduce preventable mortality after complex pancreatic cancer procedures. Full article

To address the challenge that MOSFET temperature in motor controllers is influenced by multiple factors, exhibits strong temporal dependence, and involves complex feature interactions, this study proposes a temperature prediction model that integrates Temporal Convolutional Networks (TCNs) and the Informer architecture in parallel, enhanced with a cross-attention mechanism. The model leverages TCNs to capture local temporal patterns, while the Informer extracts long-range dependencies, and cross-attention strengthens feature interactions across channels to improve predictive accuracy. A dataset was constructed based on measured MOSFET temperatures under various operating conditions, with input features including voltage, load current, switching frequency, and multiple ambient temperatures. Experimental evaluation shows that the proposed method achieves a mean absolute error of 0.2521 °C, a root mean square error of 0.3641 °C, and an R² of 0.9638 on the test set, outperforming benchmark models such as Times-Net, Informer, and LSTM. These results demonstrate the effectiveness of the proposed approach in reducing prediction errors and enhancing generalization, providing a reliable tool for real-time thermal monitoring of motor controllers. Full article

Background: Muscle strength asymmetries between limbs are common in physically active populations and may influence performance and injury risk. This study aimed to: (i) analyze the reliability of the seated unilateral cable row exercise using a functional electromechanical dynamometer (FEMD) and to examine differences in reliability between sides and contraction types; (ii) investigate the relationship between the dominant and non-dominant sides, as well as between the dynamic and static force production of the back muscles; and (iii) quantify force output and assess interlimb asymmetries. Methods: Twenty-nine young physically active athletes completed two sets of four repetitions of a seated unilateral cable row at 0.30 m·s⁻¹ using the FEMD, followed by a 6-s isometric contraction. Two testing sessions were conducted seven days apart. Reliability was assessed using paired t-tests, the effect size, the coefficient of variation (CV), the standard error of measurement, and the intraclass correlation coefficient (ICC), with 95% confidence intervals. Results: Peak and average force values showed very high to extremely high relative reliability (ICC = 0.86–0.96) and acceptable absolute reliability (CV ≈ 10%). Differences between dominant and non-dominant sides varied depending on contraction type. While group-level asymmetries did not exceed 10%, individual analysis revealed that 14%, 32%, and 7% of participants had asymmetries greater than 15% in isometric, concentric, and eccentric force, respectively. Conclusions: This test demonstrates strong reliability and provides a practical method for assessing upper limb asymmetries in physically active individuals, with potential applications in performance monitoring and injury prevention. Full article

Background/Objectives: The glymphatic system is a recently characterized glial-dependent waste clearance pathway in the brain, which makes use of perivascular spaces for cerebrospinal fluid exchange. Diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) offers a non-invasive method for estimating perivascular flow, but its biological specificity and susceptibility to methodological variation, particularly head position during MRI acquisition, remain as threats to the validity of this technique. This study aimed to assess the prevalence of current DTI-ALPS practices, evaluate the impact of head orientation on ALPS index calculation, and propose a novel computational approach to improve measurement validity. Methods: We briefly reviewed DTI-ALPS literature to determine the use of head-orientation correction strategies. We then analyzed diffusion MRI data from 172 participants in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) to quantify the influence of head orientation on ALPS indices computed using the conventional Unrotated-ALPS, a vecrec-corrected ALPS, and the new LD-ALPS method proposed within. Results: A majority of studies employed Unrotated-ALPS, which does not correct for head orientation. In our sample, Unrotated-ALPS values were significantly associated with absolute head pitch (r₁₆₉ = −0.513, p < 0.001), indicating systematic bias. This relationship was eliminated using either vecreg or LD-ALPS. Additionally, LD-ALPS showed more sensitivity to cognitive status as measured by Mini-Mental State Examination scores. Conclusions: Correcting for head orientation is essential in DTI-ALPS studies. The LD-ALPS method, while computationally more demanding, improves the reliability and sensitivity of perivascular fluid estimates, supporting its use in future research on aging and neurodegeneration. Full article

Background: Repeat induced abortion (defined as ≥two lifetime procedures) is becoming more common worldwide, yet its independent influence on women’s psychological health remains contested, particularly in settings where access to modern contraception is restricted. Objectives: This review sought to quantify the burden of depression, anxiety, stress, and generic quality of life (QoL) among women with repeat abortions and to determine how barriers to contraceptive access alter those outcomes. Methods: Following the preregistered PRISMA-2020 protocol, PubMed, Embase and Scopus were searched from inception to 31 June 2025. Results: Eight eligible studies comprising approximately 262,000 participants (individual sample sizes up to 79,609) revealed wide variation in psychological morbidity. Prevalence of clinically significant symptoms ranged from 5.5% to 24.8% for depression, 8.3% to 31.2% for anxiety, and 18.8% to 27% for perceived stress; frequent mental distress affected 12.3% of women in neutral policy environments but rose to 21.9% under highly restrictive abortion legislation. Having three or more abortions, compared with none or one, increased the odds of depressive symptoms by roughly one-third (pooled OR ≈ 1.37, 95% CI 1.13–1.67). Contextual factors exerted comparable or stronger effects: abortions sought for socioeconomic reasons elevated depression odds by 34%, unwanted disclosure of the abortion episode increased depressive scores by 0.62 standard deviations, and low partner support raised them by 0.67 SD. At the structural level, every standard deviation improvement in a state’s reproductive rights index reduced frequent mental distress odds by 5%, whereas enactment of a near-total legal ban produced an absolute increase of 6.8 percentage points. QoL outcomes were less frequently reported; where measured, denied or heavily delayed abortions were associated with a 0.41-unit decrement on a seven-point life satisfaction scale. Conclusions: Psychological morbidity after abortion clusters where legal hostility, financial hardship, or interpersonal coercion constrain contraceptive autonomy while, in comparison, the mere number of procedures is a weaker predictor. Interventions that integrate stigma-free mental health support with confidential, affordable, and rights-based contraception are essential to protect well-being in women who experience repeat abortions. Full article

Aim: This study analyzed the concurrent validity of the Optojump infrared photocell system for estimating lower limb peak power by comparing it with the 15 s Wingate anaerobic test (WAnT) and examining relationships with sprint performance indicators. Methods: Twelve physically active university students (ten males, two females; age: 23.39 ± 1.47 years; body mass: 73.08 ± 9.19 kg; height: 173.67 ± 6.97 cm; BMI: 24.17 ± 1.48 kg·m⁻²) completed a cross-sectional validation protocol. Participants performed WAnT on a calibrated Monark ergometer (7.5% body weight for males, 5.5% for females), 30 s continuous jump tests using the Optojump system (Microgate, Italy), and 30 m sprint assessments with 10 m and 20 m split times. Peak power was expressed in absolute (W), relative (W·kg⁻¹), and allometric (W·kg^−0.67) terms. Results: Thirty-second continuous jump testing produced systematically higher peak power values across all metrics (p < 0.001). Mean differences indicated large effect sizes: relative power (Cohen’s d = 0.99; 18.263 ± 4.243 vs. 10.99 ± 1.58 W·kg⁻¹), absolute power (d = 0.86; 1381.71 ± 393.44 vs. 807.28 ± 175.45 W), and allometric power (d = 0.79). Strong correlations emerged between protocols, with absolute power showing the strongest association (r = 0.842, p < 0.001). Linear regression analysis revealed that 30 s continuous jump-derived measurements explained 71% of the variance in Wingate outcomes (R² = 0.710, p < 0.001). Sprint performance showed equivalent predictive capacity for both tests (Wingate: R² = 0.66; 30 s continuous jump: R² = 0.67). Conclusions: The Optojump infrared photocell system provides a valid and practical alternative to laboratory-based ergometry for assessing lower limb anaerobic power. While it systematically overestimates absolute values compared with the Wingate anaerobic test, its strong concurrent validity (r > 0.80), large effect sizes, and equivalent predictive ability for sprint performance (R² = 0.66–0.71) confirm its reliability as a field-based assessment tool. These findings underscore the importance of sport-specific, weight-bearing assessment technologies in modern sports biomechanics, providing coaches, practitioners, and clinicians with a feasible method for monitoring performance, talent identification, and training optimization. The results further suggest that Optojump-based protocols can bridge the gap between laboratory precision and ecological validity, supporting both athletic performance enhancement and injury prevention strategies. Full article

In response to the inability to quickly assess wind noise performance during the early stages of automotive styling design, this paper proposes a method for predicting interior wind noise by integrating automotive point cloud models with the Gray Wolf Optimization Residual Network model (GWO-ResNet). Based on wind tunnel test data under typical operating conditions, the point cloud model of the test vehicle is compressed using an auto-encoder and used as input features to construct a nonlinear mapping model between the whole vehicle point cloud and the wind noise level at the driver’s left ear. Through adaptive optimization of key hyperparameters of the ResNet model using the gray wolf optimization algorithm, the accuracy and generalization of the prediction model are improved. The prediction results on the test set indicate that the proposed GWO-ResNet model achieves prediction results that are consistent with the actual measured values for the test samples, thereby validating the effectiveness of the proposed method. A comparative analysis with traditional ResNet models, GWO-LSTM models, and LSTM models revealed that the GWO-ResNet model achieved Mean Absolute Percentage Error (MAPE) and mean squared error (MSE) of 9.72% and 20.96, and 9.88% and 19.69, respectively, on the sedan and SUV test sets, significantly outperforming the other comparison models. The prediction results on the independent validation set also demonstrate good generalization ability and stability (MAPE of 10.14% and 10.15%, MSE of 23.97 and 29.15), further proving the reliability of this model in practical applications. The research results provide an efficient and feasible technical approach for the rapid evaluation of wind noise performance in vehicles and provide a reference for wind noise control in the early design stage of vehicles. At the same time, due to the limitations of the current test data, it is impossible to predict the wind noise during the actual driving of the vehicle. Subsequently, the wind noise during actual driving can be predicted by the test data of multiple working conditions. Full article

Photogrammetry offers a non-contact and efficient alternative for monitoring structural deformation and is particularly suited to large or complex surfaces such as masonry walls. This study proposes a spatio-temporal photogrammetric refinement framework that enhances the accuracy of three-dimensional (3D) deformation and strain analysis by integrating advanced filtering techniques into markerless image-based measurement workflows. A hybrid methodology was developed using natural image features extracted using the Speeded-Up Robust Features algorithm and refined through a three-stage filtering process: median absolute deviation filtering, Gaussian smoothing, and representative point selection. These techniques significantly mitigated the influence of noise and outliers on deformation and strain analysis. Comparative experiments using both manually placed targets and automatically extracted feature points on a full-scale masonry wall under destructive loading demonstrated that the proposed spatio-temporal filtering effectively improves the consistency of displacement and strain fields, achieving results comparable to traditional marker-based methods. Validation against laser rangefinder measurements confirmed sub-millimeter accuracy in displacement estimates. Additionally, strain analysis based on filtered data captured crack evolution patterns and spatial deformation behavior. Therefore, integrating photogrammetric 3D point tracking with spatio-temporal refinement provides a practical, accurate, and scalable approach to monitor structural deformation in civil engineering applications. Full article

Background: Immunization coverage has increased substantially in the Western Pacific Region, saving millions of lives and supporting disease elimination efforts. However, gaps in coverage and inequitable vaccine access persist, leaving millions unvaccinated. Wealth-based inequalities remain a critical barrier to achieving equitable immunization coverage and maximizing the health benefits of vaccination programs. Methods: We analyzed full immunization coverage among 1-year-olds in 10 middle-income countries of the Western Pacific Region using data from the WHO Health Inequalities Data Repository. National and wealth quintile-specific coverage rates and within-country inequalities were assessed using absolute and relative measures (difference, ratio, slope index of inequality, and relative index of inequality). Trends over time were examined in countries with longitudinal data (n = 5), identifying pro-rich or pro-poor changes based on shifts in quintile-specific coverage. We also calculated the population attributable risk (PAR) and fraction (PAF) to estimate the potential increase in national coverage if wealth-based inequalities were eliminated. Findings: Substantial gaps in immunization coverage persist across all countries studied (n = 10), but with substantial between- and within-country disparities. Coverage was higher among the richest quintiles in half of the countries, with the rest showing no significant disparities. Trends in inequalities were mixed: Cambodia, Mongolia, and Viet Nam experienced pro-poor improvements over time; the Philippines saw widening pro-rich inequalities; and Lao PDR showed little change. Population attributable risks (PAR) showed that eliminating wealth-based inequalities could increase national coverage significantly in five countries (Fiji, Lao PDR, Papua New Guinea, Samoa, and Tonga), with relative gains that could increase national coverage by up to 50% while achieving equity gains. Conclusions: Addressing wealth-based inequalities in immunization could drive substantial gains in national coverage across the Western Pacific Region. Sustained, equity-oriented approaches are essential to achieving universal vaccine access and ensuring no population is left behind. Inequality patterns can guide equity-focused policies to reach underserved and disadvantaged populations. Full article