Search Results (4,457)

Background/Objectives: Heart rate variability (HRV) is a reliable, non-invasive marker of autonomic nervous system function and is often impaired in individuals with metabolic syndrome (MetS). Physical exercise has emerged as an effective strategy to improve autonomic modulation; however, the comparative effects of different training modalities on HRV in individuals with MetS remain unclear. This systematic review and meta-analysis aimed to evaluate the impact of various exercise interventions on HRV and to identify which training types yield the most significant improvements. Methods: A systematic search was conducted in PubMed and Scopus up to April 2025. Eligible studies (n = 16) included adults with obesity and MetS (n = 752) who underwent structured exercise interventions with HRV assessments pre- and post-intervention. Standardized mean differences were calculated using random effects models. Subgroup analyses were performed based on training modality (endurance training [ET], resistance training [RT], high-intensity interval training [HIIT], and concurrent training [CT]). Results: Sixteen studies of moderate to high quality were included, with eleven studies eligible for meta-analysis. ET and HIIT significantly improved time-domain indices (Root mean square of differences of successive R-R intervals —rMSSD—, Standard deviation of the R-R interval series —SDNN—) and frequency-domain parameters (high-frequency —HF—), suggesting enhanced parasympathetic activity. RT showed inconsistent effects, while CT improved long-term HF and total power (TP). Non-linear indices were the least reported due to insufficient data. Conclusions: Physical exercise—particularly ET and HIIT—appears to enhance cardiac autonomic modulation in individuals with obesity and MetS. These findings support incorporating targeted training strategies into clinical practice to optimize cardiovascular health in these populations. Full article

This in vivo animal study aimed to evaluate the effects of two different implant placement micromotor systems on implant stability and removal torque. In a within-animal crossover design, twenty titanium implants (AnyOne fixture; internal type; diameter, 3.5 mm; length, 7.0 mm; Megagen, Daegu, Republic of Korea) were placed in the tibiae of five rabbits using a conventional micromotor system (NSK group: SurgicPro+; NSK, Kanuma, Japan) and a diode laser-integrated micromotor system (SAESHIN group: BLP 10; Saeshin, Daegu, Republic of Korea). Resonance frequency analysis provided the implant stability quotient (ISQ) immediately after placement and at four weeks. Micro-computed tomography quantified the bone–implant interface gap (BIG). Removal torque was measured at sacrifice. Linear mixed-effects models with a random intercept for rabbit generated adjusted means with 95% confidence intervals (CIs) (α = 0.05). Equivalence for the four-week ISQ used two one-sided tests with a margin of ±5 ISQ. The SAESHIN group achieved a higher immediate ISQ than the NSK group (difference =+6.9 ISQ; 95% CI +1.3–+12.5; p = 0.018). At four weeks, the ISQ did not differ (difference = −1.2 ISQ; 95% CI −4.3–+1.9; p = 0.42), and equivalence was supported (TOST p_lower = 0.024; p_upper = 0.019). Removal torque was comparable (difference = +4.3 N·cm; 95% CI −5.2–+13.8; p = 0.36). BIG metrics showed no between-system differences across regions. ICC indicated clustering for ISQ and torque (0.36 and 0.31). The diode laser-integrated micromotor system yielded a higher immediate ISQ under a standardized 35 N·cm seating torque, whereas the ISQ, removal torque, and BIG at four weeks were comparable to those of the conventional system. The immediate ISQ should be interpreted as stiffness under fixed torque rather than superior device-dependent interlocking. These findings support the clinical interchangeability of the two systems for early osseointegration endpoints in preclinical settings. Full article

Determining the Jensen–Mercer inequality for interval-valued coordinated convex functions has been a challenging task for researchers in the fields of inequalities and interval analysis. We use ${\ominus }_g$ to establish the Jensen–Mercer inequality for interval-valued coordinated convex functions. In this paper, we make significant strides in establishing new results by introducing a novel approach. We present a Hermite–Hadamard (H.H.) Mercer-type inequality for interval-valued coordinated convex functions and show how it generalizes the traditional H.H. inequality. Specifically, the H.H. inequality for interval-valued coordinated convex functions can be derived as a special case by considering the endpoints of the H.H. Mercer-type inequality. Furthermore, we provide computational results that verify the accuracy of recent findings in the literature. Our results indicate that the proposed new results impose highly effective constraints on integrals of the specified functions and are valid for a broader class of functions. These new findings have significant implications for applications in fields such as economics, engineering, and physics, where they can improve the precision of system modeling and optimization. Full article

The principles of least effort and the illusion of control may influence the decision-making process. It is challenging for a decision-maker to maintain complete independence when assessing the membership and non-membership degrees of indicators. However, existing neutrosophic sets and q-rung orthopair fuzzy sets assume full independence of such information. In view of this, this paper proposes a new neutrosophic set, namely the q-type semi-dependent neutrosophic set (QTSDNS), based on the classical neutrosophic set, whose membership and non-membership degrees are interrelated. QTSDNS is a generalized form of classical semi-dependent fuzzy sets, such as the intuitionistic neutrosophic set. It contains a regulatory parameter, which allows for decision-makers to flexibly adjust the model. Furthermore, a multi-attribute group decision-making (MAGDM) algorithm is proposed by integrating QTSDNS with evidence theory to solve the supplier selection problem. The algorithm first utilizes QTSDNS to represent the preference information of experts, then employs the q-TSDNWAA (or q-TSDNWGA) operator to aggregate the evaluation information of individual experts. Following the analysis of the mathematical relationship between QTSDNS and evidence theory, evidence theory is used to aggregate the evidence from each expert to obtain the group trust interval. Then, the best supplier is determined using interval number ranking methods. Finally, a numerical example is provided to demonstrate the feasibility of the proposed method. Full article

Background and objectives: Knee osteoarthritis (KOA) is a degenerative joint disorder often associated with altered gait mechanics. This systematic review aims to evaluate the effect of rehabilitation treatment on walking, with a focus on gait speed. Material and methods: A systematic search was conducted in PubMed, Scopus, Web of Science, Cochrane, and PEDro databases, following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology. Randomised controlled trials published in English between 2015 and 2025, involving patients with KOA undergoing rehabilitation and using computerised gait measurements, including 3D motion capture, force plates, and instrumented treadmills, were included. A meta-analysis was conducted on the selected studies assessing gait speed, with the risk of bias being evaluated using the Cochrane Risk of Bias 2 tool for RCTs. Results: Out of 2143 articles, 7 studies met the inclusion criteria. These studies showed increased gait speed in patients with KOA following exercise therapy, various walking training programmes, massage, or dietary interventions. The meta-analysis revealed a standardised mean difference (SMD) of 1.807, with a 95% confidence interval (CI) of [1.637, 1.977] (p < 0.001). The interventions were associated with improvements in walking parameters and quality of life, as well as reductions in pain and fall risk. Substantial heterogeneity was noted, likely due to variations in intervention types and study populations. Conclusions: The results suggest an overall improvement in gait speed in the intervention groups compared to the control groups. However, only a limited number of studies have investigated the effects of physiotherapy, bath therapy, or mud therapy on gait mechanics in patients with KOA. Full article

This paper presents an integrated workflow for smart manufacturing, combining CAD modeling, Digital Twin synchronization, and automated visual inspection to detect defective fuses in industrial electrical panels. The proposed system connects Onshape CAD models with a collaborative robot via the ThingWorx IoT platform and leverages computer vision with HSV color segmentation for real-time fuse validation. A custom ROI-based calibration method is implemented to address visual variation across fuse types, and a 5-s time-window validation improves detection robustness under fluctuating conditions. The system achieves a 95% accuracy rate across two fuse box types, with confidence intervals reported for statistical significance. Experimental findings indicate an approximate 85% decrease in manual intervention duration. Because of its adaptability and extensibility, the design can be implemented in a variety of assembly processes and provides a foundation for smart factory systems that are more scalable and independent. Full article

Background: Excessive parental control has been found to be associated with an increasing risk of emotional eating in children, yet the potential moderating role of emotion regulation abilities remains unclear. This study investigated the relationships between different types of parental control and emotional eating, as well as the mediating effects of specific emotion regulation strategies and negative emotions. Methods: A cross-sectional online survey was conducted with 1167 Chinese college students (62.5% females, age: 20.23 ± 1.50 years) recruited via social media. Participants completed the Parental Control Scale, Emotion Regulation Questionnaire, Depression Anxiety Stress Scales, and Dutch Eating Behavior Questionnaire. Data were analyzed using SPSS and PROCESS (Model 81), with BMI, age, and gender controlled as a covariate. Mediation effects were tested using the 95% bias-corrected bootstrap confidence intervals (based on 5000 samples). Results: The results indicate that (1) both parental behavioral control and psychological control were significantly positively correlated with emotional eating, with effect sizes ranging from small to moderate; (2) anxiety and stress in negative emotions partially mediate the relationship between the two dimensions of parental control and emotional eating, while depression did not serve as a mediator in this relationship; (3) expression suppression and stress chain-mediated between the two dimensions of parental control and emotional eating; expression suppression and anxiety chain-mediated between parental psychological control and emotional eating. Conclusions: Higher parental control is associated with increased emotional eating behaviors in children. Anxiety, stressful emotions, and expressive suppression play significant roles. These findings suggest new interventions to reduce emotional eating and associated overweight risks in college students. Full article

The Western Qinling Orogenic Belt, China’s second-largest Au-metallogenic province, hosts numerous polymetallic deposits, with gold resources particularly concentrated in the northwestern Xiahe–Hezuo area. The Changshitougounao gold deposit, located south of the Xiahe Fault, comprises disseminated ores controlled by near E–W-trending faults and is primarily hosted in quartz diorite and the Lower Triassic Longwuhe Formation. Zircon LA–ICP–MS U–Pb dating of fresh quartz diorite yields an age of 241.8 ± 2.6 Ma. Two generations of monazite were identified: type I magmatic monazite and type II hydrothermal monazite. Type I monazite is intergrown with feldspar, quartz, and biotite, and in situ LA–ICP–MS U–Pb analysis gives an age of 239.2 ± 2.2 Ma. Type II monazite occurs as irregular granular aggregates associated with Au-bearing sulfides and hydrothermal sericite, with an in situ U–Pb age of 230 ± 3.5 Ma. Apatite, also coeval with Au-bearing sulfides and type II monazite, yields an LA–ICP–MS U–Pb age of 230.9 ± 2.5 Ma and 230.7 ± 3.0 Ma. Zircon and type I monazite thus constrain the emplacement of the ore-bearing quartz diorite to ca. 240 Ma, whereas hydrothermal type II monazite and apatite constrain the timing of mineralization to ca. 230 Ma. The ~10 Ma interval between magmatism and mineralization indicates that goldmineralization in the Changshitougounao deposit is decoupled from Early Triassic magmatic activity. Integrating previous studies of the West Qinling geodynamic evolution, we infer that the Changshitougounao deposit formed during collisional orogenesis, in response to the closure of the Paleo-Tethys Ocean. Consequently, the Changshitougounao gold deposit is best classified as an orogenic gold system. Pyrite–arsenopyrite and sericite alteration serve as effective exploration vectors, and the contact zone between quartz diorite veins and slate represents a favorable structural setting for ore prospecting. Full article

Background: One’s dietary pattern throughout life is established during the perinatal period, especially in the intrauterine environment. This study aims to analyze whether maternal and birth characteristics are associated with food consumption in young adults using baseline data from the Nutritionists’ Health Study (NutriHS). Methods: We employed cross-sectional analysis of data from 386 undergraduate nutrition students and nutritionists. Current food consumption was evaluated as per the NOVA classification. The maternal and birth factors included maternal age, parity, type of childbirth, health problems during pregnancy, prematurity, and birth weight, and multiple correspondence analysis of these variables was performed to identify patterns in them. Results: The energy contribution of ultra-processed foods was positively associated with the pattern characterized by participants whose mothers were 19 years of age or younger, primiparous, and had a vaginal delivery (β = 0.48; 95% confidence interval = 0.02, 1.66). Conclusions: We concluded that maternal age at birth was associated with the dietary patterns of adult children. Participants whose mothers were 19 or younger at birth had significantly higher consumption of ultra-processed foods in adulthood compared to those whose mothers were older. Full article

Diabetic cardiomyopathy (DCM) is a serious complication of type 2 diabetes mellitus (T2DM), characterized by cardiac dysfunction, inflammation, and fibrosis. In this study, a T2DM mouse model was established by administering a high-fat diet (60% fat) in combination with streptozotocin injection in male C57BL/6J mice. The mice subsequently underwent an eight-week exercise intervention consisting of swimming training, resistance training, or high-intensity interval training (HIIT). The results showed that all three forms of exercise improved cardiac function and attenuated myocardial hypertrophy in DCM mice. Exercise training further downregulated the expression of pro-inflammatory cytokines, including interleukin-6, tumor necrosis factor-α, nuclear factor κB, and monocyte chemoattractant protein-1, and mitigated myocardial fibrosis by suppressing fibronectin, α-SMA, collagen type I alpha 1 chain, collagen type III alpha 1 chain, and the TGF-β1/Smad signaling pathway. Moreover, exercise inhibited the expression of PANoptosis-related genes and proteins in cardiomyocytes of DCM mice. Notably, HIIT produced the most pronounced improvements across these pathological markers. In addition, all three exercise modalities effectively suppressed the aberrant activation of the cGAS–STING signaling pathway in the myocardium. In conclusion, exercise training exerts beneficial effects against DCM by improving cardiac function and reducing inflammation, PANoptosis, and fibrosis, and HIIT emerged as the most effective strategy. Full article

Listeria monocytogenes is a Gram-positive bacterial species that causes listeriosis, a major foodborne disease worldwide. The virulence factor inlA facilitates the invasion of L. monocytogenes into intestinal epithelial cells expressing E-cadherin receptors. Naturally occurring premature stop codon (PMSC) mutations in inlA have been shown to result in the production of truncated proteins associated with attenuated virulence. Moreover, different L. monocytogenes strains contain distinct inlA variants. In this study, we first characterized inlA in 546 L. monocytogenes strains isolated from various foods in Shanghai. The results showed that 36.1% (95% Confidence Interval: 32.0~40.2%) of the food isolates harbored inlA with PMSC, which was found to be associated with clonal complex (CC) types, with the highest proportions observed in CC9 and CC121. To investigate the function of inlA, we first used the dominant CC87 isolated from patients as the test strain and constructed an inlA-deleted strain via homologous recombination. Resistance tests and virulence tests showed that while inlA did not affect the resistance of L. monocytogenes, it significantly influenced cell adhesion and invasiveness. To further explore the function of inlA, we performed virulence tests on five CC-type strains carrying inlA with PMSC and their corresponding strains with intact inlA. We found that the virulence of L. monocytogenes strains carrying inlA or inlA with PMSC was associated with their CC type. Our preliminary results showed that premature termination of inlA did not significantly affect the adhesion and invasion abilities of low-virulence CC-type L. monocytogenes strains in Caco-2 cells, but substantially promoted those of high-virulence strains such as CC8 and CC7. In summary, this study preliminarily evaluated the effects of inlA integrity and PMSC mutation variation on the virulence of L. monocytogenes, providing a foundation for further research on inlA-related pathogenic mechanisms. Full article

Background: The association between dietary vitamin A intake and cancer risk remains unclear. There may be under-researched links between dietary vitamin A and cancer. This study aimed to clarify this relationship and a possible reference vitamin A intake. Methods: We conducted a hospital-based case–control study. Exposure data was determined from participants, including 3758 incident cancer cases (esophagus, stomach, colon, rectum, lung, breast, and other cancers) and 2995 hospital controls before the day of surgery treatment at the same hospitals. Dietary vitamin A intake was assessed using a validated semi-quantitative food frequency questionnaire. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to evaluate the association between vitamin A intake and cancer risk. Restricted cubic splines suggest a safe range of vitamin A intake of 85.3–104.0 µg/day, which is a reference quantile. Results: We found a U-shaped association between vitamin A intake and cancer incidence compared to the reference. Both the lowest and highest intakes were associated with an increased cancer risk, with OR (95% CI) values 1.98 (1.57, 2.49) and 2.06 (1.66, 2.56), respectively. This U-shaped pattern was consistent across subgroups defined by sex, body mass index, smoking status, alcohol consumption, blood type A, and cancers of the esophagus, stomach, breast, and rectum, but not lung and colon cancer. The U-shaped relationship remained after adjusting for dietary vitamin A intake per kg of body weight and vitamin A–energy residual estimation adjustment. Confidence intervals were wider at the highest exposure levels. Conclusions: We observed a U-shaped relationship between vitamin A intake and the risk of cancer incidence, with a reference dietary vitamin A intake of 85.3–104.0 µg/day. These findings warrant further investigation to understand the mechanisms of this U-shaped association. Full article

Floods are among the most devastating natural disasters; predicting their depth and extent remains a global challenge. Machine Learning (ML) models have demonstrated improved accuracy over traditional probabilistic flood mapping approaches. While previous studies have developed ML-based models for specific local regions, this study aims to establish a methodology for estimating flood depth on a global scale using ML algorithms and freely available datasets—a challenging yet critical task. To support model generalization, 45 catchments from diverse geographic regions were selected based on elevation, land use, land cover, and soil type variations. The datasets were meticulously preprocessed, ensuring normality, eliminating outliers, and scaling. These preprocessed data were then split into subgroups: 75% for training and 25% for testing, with six additional unseen catchments from the USA reserved for validation. A sensitivity analysis was performed across several ML models (ANN, CNN, RNN, LSTM, Random Forest, XGBoost), leading to the selection of the Random Forest (RF) algorithm for both flood inundation classification and flood depth regression models. Three regression models were assessed for flood depth prediction. The pixel-based regression model achieved an R² of 91% for training and 69% for testing. Introducing a pixel clustering regression model improved the testing R² to 75%, with an overall validation (for unseen catchments) R² of 64%. The catchment-based clustering regression model yielded the most robust performance, with an R² of 83% for testing and 82% for validation. The developed ML model demonstrates breakthrough computational efficiency, generating complete flood depth predictions in just 6 min—a 225× speed improvement (90–95% time reduction) over conventional HEC-RAS 6.3 simulations. This rapid processing enables the practical implementation of flood early warning systems. Despite the dramatic speed gains, the solution maintains high predictive accuracy, evidenced by statistically robust 95% confidence intervals and strong spatial agreement with HEC-RAS benchmark maps. These findings highlight the critical role of the spatial variability of dependencies in enhancing model accuracy, representing a meaningful approach forward in scalable modeling frameworks with potential for global generalization of flood depth. Full article

Objectives: We investigated the relationship between bone metabolic markers or bone mineral density (BMD) and sarcopenia in patients with type 2 diabetes mellitus (T2DM). Methods: In this cross-sectional study involving 119 subjects (76 women and 43 men), bone metabolic markers were evaluated by bone alkaline phosphatase and bone tartrate-resistant acid phosphatase (TRACP-5b). BMD was measured using the dual-energy X-ray absorptiometry method, and sarcopenia was diagnosed using skeletal muscle mass index (SMI), evaluated by body composition measurement and handgrip strength. Results: Significant correlation was observed between handgrip strength or SMI and TRACP-5b in both sexes (correlation coefficients were −0.50 in handgrip strength and −0.41 in SMI in men; −0.25 in handgrip strength and −0.21 in SMI in women). Furthermore, significant correlation was observed between handgrip strength or SMI and BMD of the femoral neck in both sexes (correlation coefficients were 0.33 in handgrip strength and 0.44 in SMI in men; 0.34 in handgrip strength and 0.47 in SMI in women). The concentrations of TRACP-5b with sarcopenia were significantly higher than those without (643.8 ± 261.9 vs. 455.7 ± 165.6 mU/dL), and BMD of femoral neck with sarcopenia was significantly lower than those without (0.54 ± 0.12 vs. 0.66 ± 0.16 g/cm²). TRACP-5b (odds ratio 1.05, 95% confidence interval 1.01–1.10) and femoral neck BMD (odds ratio 0.30, 95% confidence interval 0.14–0.68) were associated with the presence of sarcopenia after adjustment for confounders. Conclusions: TRACP-5b and BMD of the femoral neck were associated with sarcopenia in patients with T2DM. Full article

Turbidite lobe reservoirs represent critical deep-sea hydrocarbon targets, yet preferred seepage channels within them remain poorly characterized. This paper establishes a method for identifying internal preferred seepage channels in turbidite lobe reservoirs using data including seismic, core, thin section, logging, and production performance, combined with neural network technology. A neural network model for predicting reservoir productivity types can be obtained by taking the average logging data of reservoir intervals as input and the reservoir productivity types categorized by meter oil production index calculated by actual production data as the target. By applying the trained neural network model and inputting actual logging attribute model, the reservoir productivity types of single wells are obtained. Using the attribute model of natural gamma ray, acoustic, neutron, density, deep lateral, and shallow lateral logs, which are built by using the actual logging data and Sequential Gaussian Simulation, and supervising with the single well reservoir productivity type, the reservoir productivity type at any position in the reservoir can be predicted. It predicts their spatial distribution characteristics, reveals the genetic mechanism of preferred seepage channels, and discusses the significance of identifying preferred seepage channels for oilfield development. The results show that the reservoir productivity types in the study area can be divided into five categories with progressive improvement in productivity (A, B, C, D, and E) according to the increase in oil production index per meter, among which Type E reservoirs represent typical preferred seepage channels. The attribute model of reservoir productivity types indicates that, horizontally, types E and B are locally developed in the study area, while types D, C, and A are widely distributed. The preferred seepage channels can be divided into two types according to the shape: zonal (length to width > 2:1) and sheet-like (length to width ≤ 2:1). Vertically, types C, D, and E are relatively well-developed in layers III and IV, whereas types A and B are more common in layers I and II. The vertical combination patterns of preferred seepage channels reveal four types, including homogeneous, bottom-dominated, top-dominated, and interbedded patterns. The formation of preferred seepage channels is influenced by both sedimentary and diagenetic processes, and sedimentary is the most important controlling factors. The identification of preferred seepage channels in turbidite lobe reservoirs is of great significance for formulating development policies and tapping remaining oil. Full article