Search Results (5,832)

Background: The benefits of metabolic bariatric surgery (MBS) in people with a body mass index (BMI) ≥ 50 kg/m² are not well-established, with concerns of increased risk and poorer weight loss. The optimal surgical type (gastric bypass [GB] versus sleeve gastrectomy [SG]) is unclear, with studies comparing complication rates, weight loss, and glycaemic outcomes reporting mixed results. Methods: Participants with a BMI ≥ 50 kg/m² undergoing MBS (SG or GB) from 2008 to 2022 were recruited. Demographics, anthropometrics, biochemistry, and diabetes status were analysed at baseline, 12 months, and 24 months post-operatively. Surgical outcomes and complications were analysed. Results: The study included n = 184, with BMI ≥ 50 kg/m² (57.6% female, age 38.6 ± 10.5 years, and BMI 55.3 ± 6.0 kg/m²). Pre-operatively, 21.1% had pre-diabetes, and 33.2% had diabetes (mean HbA1c 8.0 ± 1.7%). Most subjects (89.1%) underwent SG. The overall 30-day adverse event rate was 4.9%, with a higher, but not statistically significant, rate in the GB group (15.0% vs 3.7%, p = 0.061). The GB group had a longer length of stay (GB =4.5 ± 0.6 days, SG = 3.1 ± 0.2, and p = 0.023). The rate of revisional surgery was 2.7%, with no significant difference between groups. The follow-up rate was 67.9% at 12 months and 51.1% at 24 months. The average %total weight loss (%TWL) at 12 months (27.4 ± 9.0%, SG = 27.6 ± 9.0%, GB = 26.0 ± 9.4%, and p = 0.481) and 24 months (27.1 ± 10.9%, SG = 27.4 ± 11.1%, GB = 24.9 ± 8.9%, and p = 0.495) were similar between groups. The GB group had a larger HbA1c reduction (3.2 ± 1.1%) than SG (1.9 ±1.3%, p = 0.030) but no difference in diabetes remission rates (69.2% at 12 months, 76.7% at 24 months). Conclusions: MBS is safe and effective for individuals with a BMI ≥ 50 kg/m², with low complication rates and good weight loss and glycaemic outcomes at 2 years. No statistically significant differences in %TWL, diabetes remission, or complication rates were noted between SG and GB groups, though results are limited by the small number of participants who underwent GB. Full article

Thermal hazards in industrial environments often remain undetected until critical failure or injury occurs. Conventional handheld infrared cameras require manual operation and limit continuous situational awareness. This study presents the design and field validation of a wearable helmet-mounted real-time thermal system based on the MLX90640 infrared array sensor and a Raspberry Pi 5 edge computing platform. Experimental validation was performed across multiple scenarios of 400 measurements based on industrial distances of 100 cm and 150 cm. The performance of the system was tested against a pre-calibrated hotspot infrared thermometer using linear regression analysis and standard error metrics to determine proportional agreement. The results indicate a strong proportional relationship between the two systems at both industrial distances, with R² values ranging from 0.9885 to 0.9973 at 100 cm and from 0.9586 to 0.9867 at 150 cm. A moderate increase in mean absolute error (MAE) was observed as the measurement distance increased. Statistically significant increases in error were identified in mechanically dynamic scenarios where statistically significant increases in measurement error were observed (p-value < 0.05), indicating distance-dependent sensitivity under moving mechanical conditions. The higher absolute errors at longer distances mainly result from field-of-view expansion, reduced target occupancy, and mixed-pixel hotspot effects rather than weakened proportional trend stability. An industrial distance-aware linear regression model was developed to describe behavior and support calibrations under different deployment conditions. Despite minor absolute deviations during dynamic operations, the system maintained strong trend-tracking performance, suggesting suitability for daily preliminary hazard monitoring in industrial safety maintenance. Full article

Forest canopy water storage capacity is a critical component of ecohydrological research. However, because most current studies focus on the plot or stand scale, upscaling these fine-scale measurements to regional spatial scales remains a major challenge. Taking the forest in southern Jiangxi province as a case study, we integrated water immersion experiments, Handheld Laser Scanning (HLS), Unmanned Aerial Vehicle LiDAR (UAV-LiDAR), and optical remote sensing data to construct a spatial upscaling model. This model aims to quantify regional canopy water storage capacity and delineate its spatial patterns. The results indicate that: (1) the water storage capacity of branches and leaves per unit surface area of coniferous trees was significantly higher than that of broad-leaved trees, and the water storage capacity of branches was 6.0–10.7 times that of leaves. The mean canopy water storage capacities of coniferous forests, mixed coniferous and broad-leaved forests, and broad-leaved forests were 1.41 ± 0.27 mm, 1.30 ± 0.45 mm, and 1.26 ± 0.36 mm, respectively. (2) The canopy water storage capacity was significantly positively correlated with canopy volume ($V_C$) and average canopy area ($A_C$) extracted from UAV-LiDAR data, and vegetation structure factors such as normalized difference vegetation index (NDVI) and vegetation cover (FVC) extracted from optical remote sensing, and significantly negatively correlated with altitude and slope. Among them, canopy closure (C), average canopy area ($A_C$), and altitude were key factors affecting canopy water storage capacity. (3) The upscaling prediction models based on UAV-LiDAR data and optical remote sensing factors, respectively, show reliable prediction performance, with R² values of 0.884 and 0.815, RMSE of 0.951 and 0.116 mm, respectively. (4) The canopy water storage in the study area ranged from 0 to 1.76 mm, with a prediction uncertainty ranging from 0.12 to 0.49 mm. Canopy water storage is higher in the continuous middle and low mountain and hill areas within the region, while it is relatively lower in the high elevation ridge areas along the western, eastern, and southern margins. The results provide baseline structural information for understanding the spatial patterns of regional forest canopy interception potential. Full article

The heritagisation of cultural landscapes is often understood as a state-led administrative process. At the same time, the discursive origins and adaptive mechanisms that precede formal designation remain underexplored, especially in relation to cultural sustainability. This study examines the pre-heritagisation of Suzhou’s classical gardens during China’s modern transformation by analysing periodical discourse published between 1870 and 1948. Using a mixed-methods approach that combines quantitative content analysis and Critical Discourse Analysis (CDA), it investigates 699 historical texts from the Index to Chinese Newspapers & Periodicals database. The findings reveal a dual discursive process. On the one hand, reports portrayed the gardens as accessible, multifunctional civic spaces through narratives of public use. On the other hand, literati discourse reinforced their classical value through historical memory and aesthetic preservation. Together, these tendencies show how the gardens were materially refunctioned and symbolically re-anchored under modern conditions. Rather than directly producing later heritage designation, this process helped create the socio-cultural conditions through which the gardens acquired broader public intelligibility, cultural legitimacy, and heritage-like meanings before formal institutional recognition. Full article

Background: Quality of life (QoL) after transradial access in diagnostic cerebral angiography may be shaped by procedural demands as well as by the ambulatory setting itself. This study, for the first time, prospectively explored this dimension through follow-up assessments of QoL after the procedure. Methods: In this prospective study, QoL was assessed using the 36-Item Short Form Survey (SF-36), including the Physical and Mental Component Summary (PCS and MCS) as well as eight domain-specific subscales. After right transradial cerebral angiography, the SF-36 questionnaire was administered at baseline (pre-procedure), as well as at 1-month and 3-month follow-up visits. Mean PCS and MCS values were analyzed over time using linear mixed-effects regression models. In post hoc analyses, univariate and multivariable models were used to assess the influence of potential confounders. For subgroup analysis, patients were classified as transient deteriorators if PCS and/or MCS worsened by more than 0.5 SD at 1 month compared with baseline but not at 3 months. Permanent deteriorators were defined as worsening by more than 0.5 SD at both 1 month and 3 months compared with baseline. Results: A total of 35 patients (62.9% female) were recruited over the 12-month study period, with a mean age of 59.1 ± 10.1 years. No significant overall time effect was observed for mean PCS and MCS (p = 0.970 and p = 0.076). MCS showed a significant increase at 1 month compared with baseline (p = 0.046), with a trend toward significance at 3 months (p = 0.053). In post hoc analyses, sex, neurosurgical status, and dose area product were associated with MCS in univariate analyses (p < 0.05), but these associations did not persist after multivariable adjustment. For PCS, only age showed a significant association in univariate analysis (p < 0.05). In subgroup analyses, transient deterioration was more frequent in PCS than in MCS (11.4% [95% CI 3.2–26.7%] vs. 5.7% [95% CI 0.7–19.2%]), and permanent deterioration was also more common in PCS at 1- and 3-month follow-up (14.3% [95% CI 4.8–30.3%] vs. 8.6% [95% CI 1.8–23.1%]). Impairment predominantly involved the bodily pain subscale (88.9% [95% CI 51.8–99.7%]) within PCS and the vitality (80.0% [95% CI 28.4–99.5%]) and mental health sub-scales (80.0% [95% CI 28.4–99.5%]) within MCS. Conclusions: This short-term follow-up assessment demonstrated preserved QoL following transradial diagnostic cerebral angiography. Transient or permanent deterioration occurred in no more than five patients per subgroup (14%). These findings support the notion that a radial-first approach can be safely considered for diagnostic cerebral angiography without compromising patient-reported outcomes. Full article

To address the issues of high energy consumption and unstable construction quality caused by high-temperature heating during the preparation of traditional hot-mixed/grouted semi-flexible pavement (SFP) mixtures, a cold-mixed integrated (CMI) process was proposed. In addition, the material composition of the mixtures was optimized. The effects of the preparation process and binder type on the high- and low-temperature performance, water stability, and fatigue performance were then analyzed. Furthermore, the microstructural characteristics of the semi-flexible mixture were also investigated. The results indicated that the CMI process facilitated the formation and uniform distribution of calcium silicate hydrate (C-S-H), enhanced the binder’s ability to encapsulate aggregates and fill skeletal voids, significantly reduced the mixture’s void ratio, and improved its pavement performance. The proposed procedure was a means of enhancing high-temperature stability and fatigue life (an increase of 80% and 200 times compared to the hot-mixed/grouted (HMG) process, and 5 times and 300 times compared to AC-13, respectively). Compared with the HMG process, the CMI process offered greater advantages in enhancing the high-temperature stability and fatigue resistance of the mixture, particularly when using SBS-modified asphalt, where fatigue performance exhibited an order-of-magnitude improvement. Furthermore, while SBS modification could improve the road performance of SFP materials, mixtures prepared with SBS-modified emulsified asphalt demonstrated more significant enhancements in high-temperature stability and fatigue resistance, approximately 2 times and 10 times higher than SBS-modified mixtures, respectively. The addition of styrene–acrylic emulsion (SAE) could further enhance the low-temperature crack resistance by approximately 7%. The research results can provide a reference for the development and application of preparation processes for semi-flexible mixtures. Full article

The production of fiber-reinforced polymer composites using 3D printing technology offers significant potential and opportunities for industrial applications. However, current dimensional limitations in 3D printing necessitate the use of joining techniques to obtain larger components. Recently, innovative strategies such as friction stir spot welding (FSSW) have attracted considerable attention for joining polymer composites due to their ability to produce strong joints with relatively low heat input (solid-state welding). Nevertheless, it is important to understand how the fibers present in fiber-reinforced polymer composites influence material flow and welding performance during the FSSW process. In this study, glass fiber-reinforced polylactic acid (PLA-GF) composite samples produced using a 3D printer were joined by means of FSSW. Five different tool rotational speeds (900, 1200, 1500, 1800, and 2100 rpm) and three different plunge rates (10, 20, and 30 mm/min) were employed during the welding process. Mechanical tests were performed on the welded joints to investigate the relationship between the welding parameters and the resulting mechanical properties. In addition, microstructural analyses were conducted to examine the formation of welding defects. The results revealed that three distinct zones were formed in the material after the FSSW process: the stir zone, mixed zone, and shoulder zone. Defects were observed in the mixed zone of the samples exhibiting relatively lower mechanical properties. The highest tensile force was achieved at a plunge rate of 20 mm/min and a rotational speed of 900 rpm. The highest bending force, on the other hand, was obtained at a plunge rate of 30 mm/min and a tool rotational speed of 2100 rpm. Full article

High-entropy alloys (HEAs) are typically produced using high-temperature metallurgical routes; however, alternative synthesis approaches based on wet-chemical processing remain relatively unexplored. In this study, a compositionally complex two-phase AgCuCoNiFe high-entropy alloy was synthesized using a precipitation–reduction strategy involving co-precipitation of mixed metal carbonates followed by thermal reduction in a reducing atmosphere. The objective of the work was to evaluate the feasibility of this hydrometallurgical route for preparing compositionally complex alloys and to investigate the structural evolution of the material as a function of reduction time. Quantitative MP-AES analysis confirmed efficient co-precipitation of all five elements, enabling the preparation of a precursor with near-equimolar metal composition. Structural characterization using SEM, EDS, and XRD revealed the presence of surface compositional heterogeneity in the as-reduced state, characterized by Ag-enriched domains. After controlled surface abrasion, the internal material exhibited significantly more uniform elemental distribution, although the obtained composition was not equimolar. X-ray diffraction patterns showed a transition from multiple sharp reflections at the surface to broadened peaks in the bulk, consistent with enhanced alloying within the bulk compared to the surface, while still revealing a two-phase character. Microhardness measurements indicated moderate hardness with mean values in the range of 187–221 HV with no significant dependence on reduction time, while wettability analysis revealed moderately hydrophilic behavior with contact angles in the range of approximately 75–83°. The results suggest that precipitation–reduction can be a viable alternative route for the synthesis of multicomponent HEAs, enabling the formation of chemically mixed alloy structures without the use of conventional melting-based processing. However, the obtained alloy exhibits incomplete chemical homogeneity, indicating that further optimization of the synthesis conditions is required to achieve a fully uniform composition. Full article

Background: Multi-center resting-state functional magnetic resonance imaging (rs-fMRI) is important for neurodevelopmental disorder diagnosis, but cross-site differences in repetition time (TR) can cause temporal feature misalignment. In addition, blood-oxygen-level-dependent (BOLD) signals are non-stationary, so disease-related information may be distributed across multiple time scales. Existing methods usually do not explicitly model physical sampling intervals or coordinate temporal and spectral information across scales, which may limit cross-site generalization in heterogeneous multi-center settings. Methods: We propose Spec-RWKV, a spectrum-guided linear recurrent framework for multi-site rs-fMRI diagnosis. It includes three components: PrismTimeMix, which models temporal dynamics using decay rates derived from physical half-lives and converts them adaptively across TRs; a TR-adaptive continuous wavelet transform, which aligns spectral representations across sites by adjusting frequency coverage; and spectrum-guided adaptive temporal aggregation, which uses spectral context to weight temporal features. Results: On ABIDE-I and ADHD-200, Spec-RWKV achieved AUCs of 75.86% and 76.31%, respectively. Under leave-one-site-out validation, it achieved the best mean AUC on ABIDE-I and the best mean accuracy and AUC on ADHD-200. Conclusions: Spec-RWKV explicitly models sampling-rate differences and multi-scale spectral structure, with results supporting strong cross-site generalizability. Full article

Sea surface cooling (SSC) induced by typhoons has a significant impact on typhoon intensity and regional air–sea interaction. This study develops a machine learning model based on a multilayer perceptron (MLP) to predict SSC during typhoon passage over the western North Pacific. The model uses pre-typhoon ocean background conditions and ocean states at the typhoon peak moment as inputs, including wind field, sea level anomaly (SLA), mixed layer depth (MLD), and 100 m water temperature. Trained on historical typhoon data and multi-source ocean observations from 2002 to 2018, the model directly predicts SSC during typhoon events from 2019 to 2020. Results show that the model achieves a mean absolute error (MAE) of 0.379 °C, a root mean square error (RMSE) of 0.488 °C, and a bias of 0.087 °C. The model reproduces the typical rightward bias in SSC spatial distribution. Under normal ocean conditions, such as open deep-water areas with moderate stratification and no strong eddy interference, the model performs well, with errors below 0.1 °C at some points. Although some biases exist under complex ocean environments and abrupt changes in typhoon dynamics, the model still captures the overall cooling trend. This study demonstrates the feasibility of machine learning for typhoon–ocean interaction forecasting. The proposed framework can provide technical support for typhoon intensity forecasting, marine disaster warning, and aquaculture risk prevention. Full article

Tumor budding is increasingly recognized as a histopathologic feature associated with invasive behavior in gastrointestinal malignancies. While its prognostic value is well established in colorectal carcinoma, its significance in gastric adenocarcinoma remains less clearly defined because of marked morphologic heterogeneity, variable growth patterns, and the absence of gastric-specific assessment criteria. Multiple studies have associated high budding density with adverse clinicopathologic features, including lymph node metastasis, lymphovascular invasion, advanced tumor stage, and poorer survival, particularly in intestinal-type tumors. However, these associations are more difficult to interpret in diffuse-type and mixed carcinomas, where intrinsic discohesion and architectural variability complicate the distinction between true budding and baseline growth patterns. Beyond prognostic assessment, tumor budding has been linked to localized alterations in cell adhesion, cytoskeletal organization, tumor–stroma interaction, and partial epithelial–mesenchymal transition. Emerging evidence also suggests that its biological significance may differ across molecular subtypes of gastric cancer. This review examines the current evidence on the definition, morphologic spectrum, methodological limitations, and biologic context of tumor budding in gastric adenocarcinoma. We propose that, in gastric cancer, tumor budding is best interpreted not as a uniformly applicable scoring parameter, but as a context-dependent morphologic indicator of invasive tumor remodeling whose meaning varies according to tumor architecture, stromal interface, and molecular subtype. Full article

Postpartum depression (PPD) affects a substantial proportion of women globally and is often underdiagnosed due to barriers in screening, stigma, and limited access to care. This study presents the design and pilot evaluation of an mHealth application (“HeartHabit”) intended to support user awareness, self-monitoring, and potential identification of symptoms of PPD among Greek-speaking mothers. An alpha version of the application was evaluated through an online survey with 30 women within the first postpartum year, using a walkthrough video. The evaluation focused on perceived usability and acceptability rather than clinical outcomes or real-world use. Usability and app quality were assessed via the System Usability Scale (SUS) and a qualitative version of the user Mobile Application Rating Scale (uMARS), respectively, adopting a mixed-methods approach. Demographics, and mood and stress screening data were also captured. Quantitative data were analysed via descriptive statistics and qualitative responses via Framework Analysis. The results indicated high perceived usability (mean SUS = 83.7/100). Qualitative findings highlighted the importance of practical usability, self-regulation tools, personalisation, and connectivity with healthcare professionals. Privacy, data transparency, and user control over personal data were perceived as critical for trust. The application was perceived as a potentially useful adjunct to formal care or as at-home support when access to services is limited. Larger, controlled trials, clinical implementation protocols and clinician training are needed to promote the app’s safe integration into formal care. This mixed-methods evaluation, incorporating usability assessment and patient involvement, may offer a useful paradigm for early-stage digital mental health intervention development. Full article

Background/Objectives: The clinical meaning of a given C-reactive protein (CRP) threshold may differ by age and sex; however, a comprehensive framework to elucidate demographic differences is lacking. We examined age- and sex-related differences in the central tendency and upper tail of the CRP distribution and their implications for fixed-threshold interpretation. Methods: We retrospectively analyzed 1,845,151 serum CRP results from 336,360 individuals at a single tertiary-care hospital. Quantile regression estimated the median (q = 0.50) and 95th percentile (q = 0.95), and logistic regression assessed frequencies and odds ratios (ORs) for CRP thresholds ≥1, ≥3, and ≥10 mg/dL. Patient-year-first sensitivity and generalized estimating equation (GEE) analyses were performed. Results: CRP showed marked right-skewness, with a progressively heavier upper tail with age. The median increased from 0.19/0.26 mg/dL in females/males aged < 1 year to 2.55/3.44 mg/dL in those aged ≥ 85 years. The 95th percentile increased from 3.28/4.31 to 17.50/18.80 mg/dL. Among records aged ≥ 85 years, CRPs ≥ 1, ≥3, and ≥10 mg/dL occurred in 67.6%/72.3%, 46.6%/53.4%, and 15.3%/19.1% of females/males, respectively. For CRP ≥ 10 mg/dL, ORs increased stepwise to 12.7, 15.4, and 18.1 in those aged 65–74, 75–84, and ≥85 years, respectively. These patterns were preserved in sensitivity and GEE analyses. Conclusions: CRP distributions differed substantially by age and sex, indicating that a single threshold may not have uniform interpretive meaning across demographic groups. These findings support more context-aware interpretation of CRP thresholds in hospital-based practice, while suggesting that observed differences reflect not only demographic variation but also differences in underlying case-mix and clinical complexity. Full article

γ-Aminobutyric acid (GABA), a major inhibitory neurotransmitter, is known for its physiological functions in alleviating anxiety and improving sleep. Currently, high-yielding GABA food products are mainly obtained through screening wild-type high-producing strains (e.g., Saccharomyces cerevisiae isolated from Sichuan pickles yielding 0.67 g/L) or employing co-culture systems (e.g., Enterococcus faecium and Lactiplantibacillus plantarum reaching 6.35 g/L). While effective, these methods often rely on natural screening strains or multi-microbial interactions. This study employed CRISPR-Cas9 technology to knockout the UGA1 gene in Saccharomyces cerevisiae, a key gene responsible for GABA degradation. Starting from the low higher alcohol Saccharomyces cerevisiae SY-LH, we successfully constructed the recombinant strain SY-LHU. Remarkably, this study discovered a significant upregulation of GAD1 gene expression following UGA1 knockout, which further enhanced GABA synthesis capacity. Under optimal fermentation conditions (inoculum size 4 × 10⁷ cells/mL, wort concentration 10 °P, sugar addition 60 g/L, 30 °C for 10 days, and mixing the malt broth every 48 h), the validation fermentation was performed and the GABA content in the wort beverage reached 280.36 mg/L, representing a 385.4% increase compared to the pre-optimization level. Furthermore, sensory evaluation by a trained panel yielded a mean score of 88, with no significant off-flavors detected, demonstrating the product’s high consumer acceptance. This pioneering work provides a novel and feasible technical pathway for developing functional alcoholic beverages with sleep-aiding properties. Full article

Background/Objectives: Perceptual–cognitive abilities such as visual discrimination, reaction time, and attentional control are important for performance in dynamic sports. However, evidence remains limited regarding how simplified visual tasks capture performance variability and dynamics under repeated exposure. This study examined session-to-session performance changes and individual trajectories in a programmable visual discrimination task of increasing complexity in elite futsal players. Methods: An exploratory repeated-measures study was conducted with ten first-league futsal players. Participants completed between six and ten sessions of a color-cue visual discrimination task (“Follow the Color”) under one- and two-stimulus conditions. Outcomes included correct responses, errors, and reaction time per session. A total of 465 observations were analyzed using linear mixed-effects models to assess changes across sessions and the influence of task complexity. Individual analyses were also performed to explore player-specific trajectories. Results: Mean session accuracy was 63.8 ± 9.8 correct responses, with a mean error rate of 3.6 ± 6.1 and a mean reaction time of 0.63 ± 0.15 s. Error rates declined significantly across sessions (β = −0.008, p < 0.001), while reaction time improved modestly (β = −0.00011, p = 0.025). Correct responses showed a small negative trend over time. Increased task complexity was associated with fewer correct responses, higher error rates, and slower reaction times (all p < 0.001). Conclusions: This programmable visual discrimination task captured variability in visuomotor responses under controlled conditions and may support monitoring of performance dynamics in sports vision research. Full article