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Uncertainty analysis in the simulation of hydrological processes in Euphrates River Basin with contrasting climates
Task-oriented visual SLAM: a comprehensive map classification framework for dynamic indoor robot manipulation
A multicenter study on occult lymph node metastases in sinonasal malignancies
Abstract Surgical interventions for head and neck carcinoma patients with clinically node-negative neck encompass either elective neck dissection (ND) during primary tumor excision or a wait-and-scan approach. For the rare entity of sinonasal malignancies, no standard guideline exists. This study aims to assess the prevalence of occult lymph node metastasis and evaluate the impact of elective ND on recurrence and survival. This retrospective multicenter study included patients with histologically confirmed sinonasal malignancy between 2012 and 2022. Patient-, disease-, and therapy-specific factors were systematically collected and analyzed. The therapeutic approach was based on recommendations from an interdisciplinary head and neck tumor board. A total of 438 patients with a mean age of 62 years was included. Occult metastases were observed in 8.0% of all cN0 patients assessed by objective imaging. Elective ND was performed in 25% of patients. Histologic subtype of squamous cell carcinoma (SCC) was the only pretherapeutic risk factor identified (OR 6.10; p = 0.019). Five-year disease-free survival (DFS) was significantly reduced in patients with occult lymph node metastasis ( p < 0.001). This multicenter study demonstrates a comparatively low risk of occult lymph node metastases in sinonasal malignancies, but significantly reduced DFS. The low rate of occult metastases questions the necessity of systematic elective ND. The indication for elective ND should be critically assessed depending on histology.
A flow field reconstruction based on cylindrical wake flow data using the PSO-CNN-LSTM algorithm
Assessment of nausea across pregnancy and its association with maternal psychological status and perinatal outcomes: a prospective observational study in pregnant women
Abstract Nausea during pregnancy is common, but previous studies have reported inconsistent findings regarding its associations with maternal mental health and perinatal complications. We assessed nausea across pregnancy using both subjective and quantitative measures and examined its associations with maternal mental health and perinatal outcomes. This prospective observational study included 424 pregnant women who received antenatal care and delivery management at our hospital between March 2024 and October 2025. Nausea was assessed at three gestational stages (early, mid, and late pregnancy) using (1) a three-level subjective assessment and (2) the Emesis Index (EI). We examined the associations of (i) nausea severity in early pregnancy, (ii) the presence of nausea at each gestational stage, and (iii) a nausea duration score (0–3) with maternal characteristics, mental health, and perinatal outcomes. Maternal mental health was evaluated using the State–Trait Anxiety Inventory (STAI) and the Patient Health Questionnaire-9 (PHQ-9). Group comparisons were performed using the Mann–Whitney U test, Kruskal–Wallis test, chi-square test, or Fisher’s exact test, as appropriate. In addition, multivariable linear regression analyses were performed to examine the associations between nausea and maternal psychological status after adjustment for maternal age, BMI, nulliparity, and history of psychiatric disorders. In both subjective and EI-based assessments, greater nausea severity in early pregnancy was associated with higher STAI-State and PHQ-9 scores. At each gestational stage, participants with nausea had significantly higher STAI-State and PHQ-9 scores than those without nausea. Higher nausea duration scores were also associated with a greater prevalence of psychiatric history and with higher STAI and PHQ-9 scores across pregnancy. In contrast, nausea showed little consistent association with most perinatal outcomes. The presence, greater severity, and persistence of nausea during pregnancy were associated with increased maternal anxiety and depressive symptoms. These findings suggest that persistent nausea may serve as a clinical indicator of increased psychological burden during pregnancy and support the need for greater attention to maternal mental health in women with ongoing symptoms.
Comparison of three contrast agents in the diagnosis of cracked teeth using Cone Beam Computed Tomography (CBCT)
Abstract Cracked teeth are difficult to detect on conventional cone beam computed tomography (CBCT). Contrast agents may improve visualization of fine and superficial cracks. This study compared three contrast agents for their diagnostic performance. Thirty-nine extracted premolars with induced micro-cracks were examined using three contrast agents: ioversol, barium sulfate, and meglumine ioxitalamate. Each tooth underwent CBCT before and after contrast application, followed by micro-computed tomography (micro-CT) as the reference standard. Two blinded observers recorded the number of cracks detected on CBCT and confirmed by micro-CT. Statistical analysis was performed using ANOVA with LSD post hoc comparisons. Micro-CT detected an average of 19.9 ± 9.3 cracks per tooth. On CBCT, ioversol and barium sulfate performed similarly (5.6 ± 2.3 and 5.8 ± 2.1 cracks, respectively), whereas meglumine ioxitalamate detected fewer (3.4 ± 1.7, p = 0.001). When matched against micro-CT, ioversol and barium sulfate detected ~ 4 cracks, while meglumine ioxitalamate detected fewer than 3. Barium sulfate detected the largest proportion of deep cracks (20.7%). Contrast-enhanced CBCT improves detection of fine cracks compared with unenhanced scans. Ioversol and barium sulfate demonstrated superior diagnostic value, while meglumine ioxitalamate offered limited benefit.
Exploring the interplay between systemic immune–inflammatory response, nutritional patterns, and metabolic health in MAFLD
Systemic lipid abnormalities and choriocapillaris flow deficits in patients with hard drusen
Determinants of pesticide use and food safety awareness in a dryland vegetable system in Burao Somaliland using an exploratory value chain approach
NMR-based metabolomics analysis in breast cancer patients from Saudi Arabia: a pilot study
Machine learning-based prediction of 3-month mortality in elderly patients with non-small cell lung cancer and bone metastases
Robust and intelligent control strategies for a 3-DOF robotic arm: a comparative study
Abstract This paper presents a comparative study of PID, Fuzzy Logic Control (FLC), and Sliding Mode Control (SMC) strategies for trajectory tracking of a nonlinear 3-DOF robotic manipulator. A complete dynamic model is derived using the Euler–Lagrange formulation, incorporating inertia coupling, Coriolis and centrifugal effects, gravitational forces, and joint friction. The developed model is validated against published results, demonstrating close agreement in amplitude and phase characteristics under sinusoidal joint trajectories. The three controllers are implemented under identical conditions and evaluated in both joint space and Cartesian space using step inputs, infinity trajectories, and circular paths. Performance is quantitatively assessed using RMSE, ITAE, and IAE metrics. The results indicate that SMC achieves the highest tracking accuracy, reducing average RMSE by approximately 80% compared to PID, while FLC achieves nearly 50% improvement. In Cartesian tracking, SMC maintains peak position errors below 0.005 m, significantly outperforming PID, which exhibits deviations up to 0.11 m under dynamic motion. Statistical analysis further confirms improved robustness under the considered simulation scenarios and the consistency of SMC across all joints. The findings demonstrate that robust nonlinear control significantly enhances convergence speed, tracking precision, and disturbance rejection capability in planar 3-DOF manipulators. The validated modeling framework and systematic benchmarking provide practical guidance for selecting appropriate control strategies in industrial robotic applications.
Evaluating community pharmacists’ knowledge, attitudes, and practices toward nutritional counselling and healthy lifestyles: evidence from a lower-middle-income country
Improved Pied Kingfisher Optimization Algorithm for optimal scheduling of microgrids with hybrid energy storage
A federated blockchain framework for secure and intelligent smart farming in sustainable industrial agriculture
Seroincidence of Brucella spp. infection among humans and livestock in Northern Kenya
Explainable machine learning identifies features and thresholds predictive of immunotherapy response
From sleep staging to spindle detection: a case study on end-to-end automated sleep analysis
Abstract Automation of sleep analysis, including both macrostructural (sleep stages) and microstructural (e.g., sleep spindles) elements, promises to enable large-scale sleep studies and to reduce variance due to inter-rater incongruencies. While individual steps, such as sleep staging and spindle detection, have been studied separately, the feasibility of automating multi-step sleep analysis remains unclear. In this case study, we evaluate whether a fully automated analysis using validated machine learning models for sleep staging (RobustSleepNet) and subsequent spindle detection (SUMOv2) can replicate findings from an expert-based study of bipolar disorder. The automated analysis qualitatively reproduced key findings from the expert-based study, including significant differences in fast spindle densities between bipolar patients and healthy controls, accomplishing in minutes what previously took months to complete manually. While the results of the automated analysis differed quantitatively from the expert-based study, possibly due to biases between expert raters or between raters and the models, the models individually performed at or above inter-rater agreement for both sleep staging and spindle detection. Our results demonstrate that fully automated approaches have the potential to facilitate large-scale sleep research. We are providing public access to the tools used in our automated analysis by sharing our code and introducing SomnoBot, a privacy-preserving sleep analysis platform.
The association between nationality, gender, age and running performance in endurance runners: an empirical analysis of worldwide multi-distance race data from 1999 to 2024
Abstract In recent years, the increasing popularity of half-marathon and marathon events has promoted the significant growth of global endurance running participants. In endurance running, the gender, age and nationality of athletes are closely related to their running performance. To this end, this study, based on the official data from World Athletics (formerly IAAF) and the Association of Road Racing Statisticians (ARRS), selects three demographic variables: nationality, gender, and age, aiming to explore the performance characteristics and their correlations of global runners in four different distance endurance running events: 5 km, 10 km, half marathon, and marathon from 1999 to 2024. The study included a total of 152,943 runners from 203 countries and regions (covering 180 countries, 21 regions and 2 special representative teams) (Male: n = 91,182; Female: n = 61,761). In terms of data analysis, this study used a mixed-effects model to analyze the trend of running performance and age over years, and used a three-way analysis of variance (nationality × gender × year) to test the interaction between variables. In addition, 8 multiple linear regression models were determined through the Akaike Information Criterion (AIC), and independent samples t-tests and Pearson correlation coefficients were used to analyze gender differences and the association between various demographic variables and performance. This study draws the following four main conclusions: (1) In all four different distance endurance running events, there were more male runners than females; (2)In the 5km, most runners were from the United States and Japan, while in the 10km, half marathon and marathon events, runners from Japan and Kenya accounted for the main share; (3) In all endurance running events except the 5km event, females were significantly older than males; (4) Males were faster than females in all distance endurance running events.