Search Results (6,743)

Water-lubricated bearings (WLBs) may exhibit marked friction-induced vibration during low-speed and heavy-load operation as hydrodynamic lubrication becomes insufficient. However, the load dependence of the low-speed operating limit and associated vibration characteristics remains insufficiently understood. In this study, a WLB was tested under specific pressures of 0.28, 0.42, 0.56, and 0.84 MPa during stepwise deceleration from 20 to 6 r/min. A joint three-standard-deviation criterion based on root mean square and peak-to-peak acceleration was used to identify the first measured speed point with marked vibration amplification. The coefficient of friction, time-domain features, spectral energy distribution, envelope characteristics, and FSI-based limiting hydrodynamic capacity were analyzed. The first vibration amplification points occurred at 6, 8, 10, and 10 r/min, respectively, accompanied by audible abnormal sound used only as qualitative corroboration. The onset responses varied from isolated or repeated bursts to pronounced medium-high-frequency impulsive excitation and quasi-periodic low-frequency amplitude modulation. The limiting hydrodynamic capacity calculated at a prescribed eccentricity ratio decreased with increasing load and was lower at the onset condition than at the adjacent pre-onset condition. This vibration-based framework provides an operational method for identifying low-speed operating boundaries related to loads and may support operating-condition selection and early warning of abnormal vibration in WLB systems. Full article

Background and Objectives: SPES was a 2016–2017 regional biomonitoring program. We conducted a secondary cross-sectional analysis of associations between current serum trace-element distributions and heterogeneous, self-reported physician-diagnosed tumor history, rather than registry-confirmed or incident cancer. Materials and Methods: Among 4137 questionnaire responders, 86 reported a tumor history. Mixed-effects logistic models for 20 channels were adjusted for age, sex, smoking, and geographic cluster and pooled across 30 completed datasets. Benjamini–Hochberg FDR control was applied across 20 primary comparisons. Results: Higher Cr-52 was associated with lower prevalence odds of reported history (odds ratio per one-standard-deviation increase in log concentration, 0.751; 95% confidence interval, 0.601–0.937; p = 0.011; q = 0.226), but no channel met q < 0.05. Cr-52 was below the limit of quantification in 45/86 (52.3%) participants with reported history and 1646/4048 (40.7%) without. The inverse direction persisted in non-independent complementary analyses; none met the applicable FDR threshold. Conclusions: No channel met the FDR criterion. The Cr-52 pattern was nominal and exploratory. These prevalence associations with a heterogeneous, unvalidated self-reported outcome do not establish temporality, causality, chromium speciation, or a protective effect. Full article

In this paper, we propose a receiver deployment optimization method that ensures robust localization performance under Direction of Arrival (DoA) estimation errors arising in practical environments. The proposed method accounts for DoA estimation errors and optimizes receiver deployments by incorporating Position Dilution of Precision (PDoP) to mitigate their amplification into localization errors. To accurately characterize DoA estimation errors under realistic propagation and installation constraints, a ray-tracing-based Wireless InSite simulator is employed to model environments including actual terrain and buildings. Based on this model, a cost function incorporating both the DoA estimation errors at each receiver and the PDoP is defined, and a Genetic Algorithm (GA) is applied to minimize this cost function and determine the optimal receiver deployment. The optimal deployment achieves low localization RMSE and maintains high robustness against environmental and system uncertainties, particularly when the standard deviation of the DoA estimation error exceeds approximately 8°. These results demonstrate that the proposed deployment method provides reliable localization performance in realistic propagation environments and remains robust against increasing DoA estimation errors. Full article

Smart factories need transparent methods that distinguish high energy demand caused by production from poor energy performance. This study presents an interpretable decision-support framework based on daily total energy consumption and product-referenced specific energy consumption (SEC) for three distinct anonymized products. The analysis used 436 daily records collected between 2019 and 2026 from a single manufacturing plant. After the data-quality audit, 401 valid energy records were retained. Normality was rejected in seven of the eight annual datasets. Chronological Q90 and Q95 thresholds were therefore used as the main approach and compared with limits based on the mean and standard deviation and on the median and MAD. A complete rule matrix assigned four recommendation levels, while a separate robust score identified unusual operating days. Across 907 evaluations, activation rates ranged from 16.96% to 26.95%, Level 3 recommendations from 1.77% to 2.60%, and anomaly rates from 6.65% to 8.48%. Confidence intervals and sensitivity analyses showed that the main conclusions remained stable across the analytical choices. The framework supports monitoring, inspection, scheduling, and prioritized operator review. Full article

Background: Day-to-day movement behavior may influence short-term glycemic variability in adults with type 2 diabetes, but free-living evidence integrating accelerometry with continuous glucose monitoring (CGM) remains limited. Objectives: This study examined whether daily moderate-to-vigorous physical activity (MVPA) and accelerometer-defined sedentary time were associated with 24-h within-day glycemic variability. Methods: In this longitudinal repeated-measures study, 140 adults with type 2 diabetes underwent 14 days of concurrent hip-worn ActiGraph GT3X+ accelerometry and FreeStyle Libre 2 CGM under free-living conditions in Lima, Peru. The primary outcome was a daily CGM-derived coefficient of variation (CV). Linear mixed-effects models separated within-person and between-person components, with Holm adjustment for the two primary within-person associations. Results: The fully adjusted primary analysis included 132 participants and 1728 participant-days. Higher within-person MVPA was associated with a lower daily CV (β = −0.27 percentage points per 10 min/day, 95% CI −0.45 to −0.09; Holm-adjusted p = 0.006), whereas greater accelerometer-defined sedentary time was associated with a higher CV (β = 0.05, 95% CI 0.01 to 0.09; Holm-adjusted p = 0.014). Secondary concurrent analyses showed favorable MVPA and opposite sedentary time associations for time in range, time above range, mean glucose, and glucose standard deviation (all false discovery rate q ≤ 0.018), with no statistically detectable association with time below range. Lagged associations were directionally consistent, but none remained statistically significant after multiplicity correction. Conclusions: Daily MVPA and accelerometer-defined sedentary times were associated with modest differences in within-day glycemic variability and concurrent CGM profiles. These observational findings do not establish causality or a specific exercise dose. Full article

Background: Food noise describes persistent, intrusive thoughts about food, eating, and cravings that occur in the absence of physiological hunger. Its occurrence among healthcare students and professionals in Saudi Arabia is unknown. This study measured food noise in this group in Al-Ahsa, described the proportion meeting study-defined severity thresholds, and identified its main correlates. Methods: In this cross-sectional study, healthcare students and professionals in Al-Ahsa completed a bilingual (Arabic–English) electronic questionnaire capturing demographic and lifestyle characteristics, a 14-item food noise scale adapted from the Food Thought Suppression Inventory (each item rated 1–5; total range 14–70), the SCOFF eating disorder screen, and the four-item Perceived Stress Scale. The factor structure of the food noise scale was examined by exploratory factor analysis with parallel analysis and random split-half replication. Severity was graded from the mean item score as low, moderate, or high using exploratory thresholds, and associations were tested using t-tests, one-way analysis of variance, the Pearson correlation, and complete-case multivariable linear regression with robust standard errors and six sensitivity analyses. Results: Among 593 participants (mean age 25.7 years; 67.5% women; 60.0% students), the food noise scale was unidimensional (Kaiser–Meyer–Olkin 0.95; one eigenvalue above both unity and the parallel analysis threshold; 41.8% of variance explained; loadings 0.50 to 0.74) and internally consistent (Cronbach alpha 0.91). The mean total score was 41.9 (standard deviation 12.7). At least moderate food noise was present in 75.9% of participants (95% CI 72.3 to 79.2) and high food noise in 29.0% (95% CI 25.5 to 32.8). A positive SCOFF screen was recorded in 70.2% (95% CI 66.3 to 73.7), and the mean perceived stress score was 8.1 (standard deviation 2.8). In the adjusted model (n = 573; unadjusted R-squared 0.279, adjusted R-squared 0.266), food noise was independently associated with the SCOFF score (B 3.85 per point) and perceived stress (B 0.69 per point), both of which held across every sensitivity analysis, although both relationships proved concave rather than linear. Weaker associations with age (B 0.19 per year) and any night shift work (B 2.45) did not survive alternative model specifications, and crude differences by sex, role, weekly hours, and fasting did not persist after adjustment. Conclusions: Food noise was common in this sample and tracked eating disorder risk and perceived stress more closely than demographic or occupational characteristics. Because recruitment was by convenience and the severity thresholds are exploratory rather than validated, the proportions reported here describe this sample and should not be read as population prevalence. The findings provide a first benchmark for the construct in this population and support attention to the cognitive dimension of eating within health professions settings. Full article

Underground infrastructure inspection requires sensing methods capable of characterizing both ferromagnetic and non-ferromagnetic subsurface features. This study evaluated a portable nitrogen-vacancy (NV) quantum diamond magnetometer (QDM) together with multi-frequency ground-penetrating radar (GPR; 250, 500, and 800 MHz) at a 90 m full-scale pavement test site containing documented subsurface targets. Repeated stationary QDM measurements were first conducted to characterize temporal variability and establish site-specific magnetic baselines, followed by a 1 m interval spatial survey and corresponding GPR measurements. The QDM showed reproducible spatial magnetic patterns despite substantial variability in reinforcement-dense sections, and all 10 cross-session measurements remained within ±1.5 standard deviations of their repeated-measurement baselines. Ferromagnetic targets produced localized magnetic responses, whereas post hoc classification using disturbance-normalized magnetic anomalies showed limited target-level discrimination (AUC = 0.495). GPR likewise showed limited post hoc target classification (500 MHz AUC = 0.472), but section-level radar responses differed significantly across pavement environments. The two modalities exhibited contrasting section-level responses while showing weak and inconsistent point-level correspondence. These results indicate that NV-diamond magnetometry and GPR provide complementary physical information, while repeated magnetic measurements are important for interpreting QDM observations under heterogeneous field conditions. Full article

Background: Optical neuropathy is a severe complication in patients with type 2 diabetes mellitus (T2DM) undergoing vitreoretinal surgeries. Early diagnostic indicators are critical to preventing irreversible vision loss. This study aimed to evaluate the alterations in blood serum amino acid profiles, with a specific focus on serine levels, and their potential clinical association with the severity of neuroretinal impairment. Methods: The clinical cohort included 28 patients aged 32 to 77 years with T2DM following vitreoretinal interventions. Visual field functional status was assessed using Humphrey automated perimetry, with mean deviation (MD), pattern standard deviation (PSD), and visual field index (VFI). Structural changes were quantified using optical coherence tomography (OCT) to measure peripapillary retinal nerve fiber layer (RNFL) thickness. Serum amino acid profiles were determined using an ion-exchange chromatography amino acid analyzer, alongside a reference group (n = 12). Results: All patients presented with moderate-to-severe visual field impairment. A profound decline in serum serine levels was observed in diabetic patients compared to the reference group (p < 0.001). The reduction in serine content closely mirrored both the degree of retinal sensitivity loss (MD and PSD values) and the number of thinned peripapillary RNFL sectors. Notably, the compensatory synthesis of serine via glycine cleavage appeared insufficient, as evidenced by a concomitant statistical decrease in glycine content (p < 0.05). No significant differences in serine levels were found between the subgroups when stratified strictly by age or isolated severity stages. Conclusions: It was demonstrated that the decline in serum serine levels in patients with T2DM following vitreoretinal interventions is significantly associated with the severity of optic neuropathy as assessed by optical coherence tomography (OCT). Consequently, serum serine may serve as a valuable dual biomarker, acting as a prognostic indicator for retinopathy progression and a predictive marker for early-stage neuropathy development. Full article

Background/Objectives: This pilot study aimed to develop and compare advanced machine learning models, specifically a Bayesian-regularized artificial neural network (ANN) and a transformer-enhanced physics-informed neural network (PINN), by integrating periodontal health indices and hematological inflammatory markers for the prediction of GDM. Methods: Utilizing a prospective case–control study design, a clinical dataset comprising 80 pregnant women (40 with GDM and 40 healthy controls) was evaluated to develop and compare advanced machine learning models. Clinical, periodontal, and complete blood count-derived inflammatory parameters were integrated into two predictive models: a Bayesian regularization-based artificial neural network (ANN) and a transformer-enhanced physics-informed neural network (PINN). Model performance was evaluated using the coefficient of determination (R²), mean squared error (MSE), root mean squared error (RMSE), mean absolute error (MAE), and residual error analyses. Results: The ANN demonstrated superior predictive performance, achieving an R² of 0.9872 and an MSE of 3.38 × 10⁻³, compared with an R² of 0.9833 for the PINN model. Residual analysis showed that the ANN provided greater prediction stability, with a mean deviation of 0.5691 and a standard deviation of 3.6400. The findings demonstrate that the integrated analysis of periodontal and hematological markers through advanced neural architectures, particularly the Bayesian-regularized ANN, provides a high-fidelity diagnostic signal for GDM prediction. This integrated feature set, when processed by the proposed machine learning framework, enables the identification of complex biological patterns with remarkable precision. Conclusions: The proposed machine learning framework provides an accurate, non-invasive, and clinically applicable approach for predicting GDM. Integrating routinely available periodontal and hematological data may improve early risk stratification and support personalized prenatal care. Further validation in larger and more diverse populations is warranted before clinical implementation. Full article

Background/Objectives: The triglyceride–glucose (TyG) index, a surrogate marker associated with insulin resistance, has been linked to both blood pressure elevation and circadian blood pressure dysregulation; however, its relationship with ambulatory blood pressure (BP) phenotypes across the full spectrum of contemporary ambulatory BP categories remains incompletely characterised. This study investigated the association of the TyG index with ambulatory BP categories and circadian BP phenotypes in untreated adults undergoing ambulatory blood pressure monitoring (ABPM). Methods: This retrospective cross-sectional study included 723 consecutive adults with no current or previous exposure to antihypertensive medication (treatment-naïve status refers exclusively to antihypertensive pharmacotherapy) who underwent 24 h ABPM and same-day laboratory assessment at a tertiary referral centre. Participants were classified according to the 2024 European Society of Cardiology ambulatory BP thresholds into non-elevated BP (n = 199), elevated BP (n = 243), or hypertension (n = 281) groups. Circadian BP phenotypes were categorised as extreme-dippers, dippers, non-dippers, and reverse-dippers. Associations between the TyG index and ambulatory BP categories were evaluated using multivariable proportional-odds ordinal logistic regression. The joint effect of BP category and circadian phenotype was examined by adding a TyG index × circadian phenotype interaction term to the ordinal model, and circadian phenotypes were characterised using multinomial logistic regression. Results: The TyG index increased progressively across ambulatory BP categories (8.8 ± 0.5, 9.1 ± 0.5, and 9.2 ± 0.6; p-trend < 0.001). After adjustment for age, sex, HbA1c, estimated glomerular filtration rate, and body mass index, each one-standard-deviation increase in the TyG index was associated with higher ambulatory BP category (OR 1.57, 95% CI 1.34–1.83; p < 0.001). The Brant test provided no evidence against the proportional-odds assumption (p = 0.379). In an exploratory analysis, the TyG–BP category association differed across circadian phenotypes (TyG × phenotype interaction, likelihood-ratio χ² = 8.26, df = 3, p = 0.041). In multinomial analysis, a higher TyG index was associated with the reverse-dipper (OR 2.90 per SD, 95% CI 2.06–4.08) and extreme-dipper (OR 2.77, 95% CI 1.87–4.10) phenotypes relative to the results for the dippers (both p < 0.001), but not with non-dipping (OR 1.02, 95% CI 0.84–1.24; p = 0.86) after multivariable adjustment. Conclusions: Among untreated adults undergoing ABPM, higher TyG index values were associated with progressively higher ambulatory BP categories and with reverse- or extreme-dipper circadian BP phenotypes after multivariable adjustment. Because insulin resistance was not measured directly, these results describe an association between the TyG index, a surrogate marker, and ambulatory BP phenotypes; they should be interpreted as hypothesis-generating because of the retrospective cross-sectional design. Prospective studies are warranted to determine their temporal and clinical significance. Full article

Real-time BDS-3 PPP-B2b satellite clock products exhibit satellite-dependent clock product deviations (CPDs) relative to post-processed precise clocks, an important error source for real-time precise positioning and timing. Previous studies largely treat CPDs as static statistics or estimable parameters, leaving their nonstationary periodic structure and prediction potential unexplored. A hierarchical analytical framework based on the normalized time–frequency transform (NTFT) is therefore established, whose dynamic ridge model tracks the joint time-varying trajectories of amplitude, frequency, and phase without period priors. The modeling residual standard deviation is reduced from 5.273 ns to 0.429 ns, and three cross-satellite common components are identified. Building on this structure, a unified ridge envelope extrapolation (uREE) method converts the envelope trend and phase evolution into short-term forecasts through three satellite adaptive modes. On an independent single-day test, uREE reduces the overall RMS from 3.649 ns to 1.665 ns, corresponding to a 54.4% improvement, and outperforms all four benchmark models. Bias–dispersion decomposition reveals that this gain stems from the mitigation of systematic bias (whose contribution falls from above 83% to 18.5%) rather than from random noise suppression. These results shift CPD research from static bias estimation to physically interpretable time-varying modeling and forecasting. Full article

Background and Objectives: Ankle instructions during the active straight leg raise (ASLR) are not consistently standardized and may alter lumbopelvic measurements. This study tested whether a relaxed ankle, maximal active dorsiflexion (DF), and maximal active plantarflexion (PF) changed lateral abdominal muscle thickness and pressure biofeedback unit (PBU) responses during a standardized supine ASLR performed at 30° of hip flexion. Methods: Thirty-three healthy adults completed three trials per condition according to a pre-generated schedule containing all six possible condition orders. B-mode rehabilitative ultrasound imaging (RUSI) measured transversus abdominis (TrA), internal oblique (IO), and external oblique (EO) thickness at rest and during ASLR. Three end-expiratory images were acquired for each participant, condition, and state; each image was measured three times, and the three image means were averaged. Rest-to-ASLR changes yielded 99 participant-condition values. Pressure biofeedback unit (PBU) pressure was recorded at four prespecified events and analyzed at the trial level. Results: Across participant-condition means, TrA thickness was 2.44 ± 0.59 mm at rest and 2.66 ± 0.70 mm during ASLR; the largest observed mean was 4.46 mm under the study task, not a physiological maximum. DF increased the change in transversus abdominis thickness (ΔTrA) versus the relaxed ankle by 0.172 mm (95% CI, 0.077–0.267; p < 0.001) and total lateral abdominal wall change by 0.672 mm (95% CI, 0.413–0.931; p < 0.001). PF increased signed image-moment pressure deviation by 1.505 mmHg (95% CI, 0.985–2.025; p < 0.001). Conclusions: Ankle-position instructions changed ultrasound and PBU outcomes during ASLR. Standardizing ankle positioning instructions and image aggregation may improve measurement reproducibility. Full article

Background: Mitoxyperilysis is a recently described form of regulated cell death, but its clinical and immunological relevance in hepatocellular carcinoma (HCC) remains unclear. This study investigated the prognostic significance of mitoxyperilysis-related transcriptional activity and its role in remodeling the tumor immune microenvironment. Methods: A Mitoxyperilysis Score was generated by single-sample gene set enrichment analysis. Prognostic associations were evaluated using Kaplan–Meier analysis, multivariable Cox regression, independent cohort validation, and random-effects meta-analysis. Immune infiltration and cell–cell communication were examined using bulk transcriptomic and single-cell RNA-sequencing data. The functional role of ANXA1 was assessed by ELISA, Western blotting, macrophage co-culture, immunofluorescence, flow cytometry, ANXA1 knockdown, and subcutaneous tumor models. Results: High Mitoxyperilysis Scores were associated with shorter overall survival in TCGA-LIHC (log-rank p = 0.032), although the association was attenuated after adjustment for age, sex, stage, grade, and vascular invasion. The adverse survival association was independently reproduced in the Gao2019 CHCC-HBV cohort (log-rank p = 0.00383). Across TCGA-LIHC, GSE14520, and Gao2019 CHCC-HBV, a random-effects analysis showed an overall hazard ratio of 1.42 per 1-standard-deviation increase in score (95% CI, 1.08–1.86; p = 0.011), with substantial between-cohort heterogeneity (I² = 77.5%). High-score tumors displayed increased immune and stromal infiltration, immune-checkpoint expression, and M2-like macrophage enrichment. ANXA1 expression correlated positively with the Mitoxyperilysis Score in independent cohorts. Mitoxyperilysis induction increased both intracellular and extracellular ANXA1, while ANXA1 overexpression promoted CD163⁺CD206⁺ macrophage polarization. ANXA1 knockdown attenuated this response, reduced subcutaneous tumor burden, and decreased intratumoral CD163 staining. Conclusions: Mitoxyperilysis-related transcriptional activity is associated with adverse survival and an M2-enriched immunosuppressive microenvironment in HCC. ANXA1 is an important, although probably not exclusive, mediator of this process and may represent a potential therapeutic target. Full article

In the context of the global implementation of the United Nations 2030 Sustainable Development Goals (SDGs), urban green development serves as a core practical pathway to advance SDG8 (Decent Work and Economic Growth), SDG11 (Sustainable Cities and Communities), and SDG15 (Life on Land). This study constructed a three-dimensional evaluation framework encompassing the green economy, green ecology, and green society, and utilized panel data from 282 Chinese prefecture-level cities from 2009 to 2021. By integrating the CRITIC weighting method, spatial autocorrelation, the Standard Deviational Ellipse (SDE) approach, and the Dagum Gini decomposition, we systematically quantified multi-scale spatiotemporal evolution and disparity patterns at the national scale, as well as across four major economic zones and five core urban agglomerations. Nationwide, the composite green development index rose from 0.422 to 0.522 (+23.70%), while the overall Dagum Gini coefficient declined from 0.072 to 0.053 (−26.39%), with the spatial center of gravity gradually shifting toward the southwest. Eastern China persistently maintained the highest development level; Western China achieved the fastest cumulative growth (26.43%), and Northeastern China lagged behind with the lowest growth rate (20.10%). Among five major urban agglomerations, the Yangtze River Delta (YRD) and Pearl River Delta (PRD) shared an identical average score of 0.582, whereas the Chengdu–Chongqing (CC) agglomeration recorded the highest growth of 33.07%. This research contributes multi-scale empirical evidence for localized SDG implementation in China and provides differentiated policy insights for cross-regional green transition governance. Full article

Organophosphate esters (OPEs) are commonly used flame retardants and plasticizers, which can easily be released into the soil environment and have potential hazards such as neurotoxicity and developmental toxicity. Establishing an efficient and sensitive detection method plays a crucial role in soil pollution assessment. Currently, there have been numerous studies on the detection of OPEs in soil using ultrasonic extraction and solid-phase extraction, while relatively few studies have focused on the analysis of multiple OPEs in soil by accelerated solvent extraction combined with d-SPE clean-up and ultra-high performance liquid chromatography–tandem mass spectrometry. The d-SPE purification method eliminates the need for column passage, shortens sample preparation time, and avoids the risk of background contamination from OPEs that may be introduced by SPE. This study developed a liquid chromatography–tandem quadrupole mass spectrometry (LC-MS/MS) method for the determination of 25 OPEs in soil, and systematically optimized the pretreatment and instrumental analysis conditions. Accelerated solvent extraction was used for pretreatment, and dichloromethane–methanol (1:1, V/V) was determined as the optimal extraction solvent. A mixed adsorbent of N-propyl ethylenediamine (PSA) and C18 was selected for dispersive purification, effectively removing matrix interference and improving recovery rates. The mass spectrometry parameters such as collision energy and declustering voltage were optimized, significantly enhancing ion response intensity and detection sensitivity. The method showed good linearity within the concentration range of 1–100 ng/mL, with correlation coefficients all greater than 0.994. The spiked recovery rates ranged from 70.6% to 111% with a relative standard deviation (RSD) of 1.2–11.8%. The precision and accuracy met the requirements for environmental sample analysis. The method was applied to the detection of actual soil samples, and the results were stable and reliable. This method is simple to operate, highly sensitive, and widely applicable, providing reliable technical support for the pollution monitoring, source tracing, and ecological risk assessment of OPEs in soil. Full article