Search Results (2,796)

Objective: Osteosynthesis in the case of a sternal wound infection is challenging. It requires osteosynthesis systems that go beyond the usual wire techniques. In principle, there are three different systems, namely plates with locking screws, clips, and distance systems, which are the original methods used in chest wall reconstruction. The aim of this study is to assign these systems to the corresponding sternal pathologies. Patients and methods: This is a retrospective single-center analysis. Bone pathology is divided into three grades: grade I (good substance/no fractures), grade II (good substance/few transverse fractures), grade III (poor substance/substance defects/multiple transverse fractures). The individual osteosynthesis systems are assigned to the different grades accordingly. The suitability of the individual systems is analyzed in the short term and long term. Results: A total of 130 patients were included. Stable osteosynthesis was achieved in all patients. For grade I defects, 75 plates and 24 clips were used. For grade II defects, mainly plates (255) but also clips (16) were used. A distance system was used 24 times for grade III defects. One plate fractured. No other implant-related complications occurred. Discussion: If the different osteosynthesis systems are used according to the bone pathology, a stable chest wall can be restored in all patients. The individual systems have their own specific characteristics, which must be taken into account with regard to the suitability and invasiveness of the procedure. No single system is suitable for treating all sternal pathologies. Full article

Background/Objectives: Short-term functional outcomes after outpatient pulmonary rehabilitation are heterogeneous. We examined whether a study-derived cardio-nutrition-inflammation-oxygen (CNIO) index integrating echocardiographic filling pressure, nutritional status, inflammation, and oxygen requirement was associated with 3-month functional outcomes in chronic respiratory disease. Methods: This single-center retrospective cohort study included 60 adults with chronic obstructive pulmonary disease, interstitial lung disease, or bronchiectasis who completed outpatient pulmonary rehabilitation and had baseline and 3-month functional assessments. The CNIO index was calculated as standardized E/e′ plus standardized ln(neutrophil-to-lymphocyte ratio) plus standardized resting oxygen flow rate minus standardized Geriatric Nutritional Risk Index, and the summed score was then standardized to mean 0 and SD 1. The primary outcome was 3-month 6 min walk test (6MWT) distance, and the exploratory secondary outcome was 3-month Short Physical Performance Battery (SPPB) score. The primary 6MWT analysis used multivariable analysis of covariance adjusted for baseline 6MWT, age, sex, body mass index, and diagnosis, whereas the exploratory SPPB analysis used ordinal logistic regression adjusted for baseline SPPB and the same covariates. Results: Mean 6MWT increased from 340.3 ± 61.0 m to 368.0 ± 102.0 m, corresponding to a mean change of 27.7 ± 90.3 m. Each 1-SD increase in CNIO was associated with a lower 3-month 6MWT distance (β = −43.42 m; 95% confidence interval [CI], −77.55 to −9.30; p = 0.014). In the exploratory ordinal logistic regression model for SPPB, each 1-SD increase in CNIO was associated with lower odds of being in a higher 3-month SPPB category, although the estimate was fragile and the confidence interval was close to the null (odds ratio = 0.39; 95% CI, 0.15 to 0.99; p = 0.048). Bootstrap internal stability analysis for the primary 6MWT model showed a wide percentile bootstrap 95% CI of −76.05 to −13.97 m per 1-SD increase in CNIO, supporting the need for cautious interpretation. Conclusions: In this hypothesis-generating derivation study, a higher standardized CNIO index was associated with lower 3-month 6MWT distance among adults with chronic respiratory disease who completed outpatient pulmonary rehabilitation. The association with SPPB was weaker and should be interpreted cautiously. These findings are not generalizable to patients who discontinue rehabilitation or are hospitalized for exacerbation during follow-up, and prospective external validation in larger, diagnostically stratified cohorts is required before CNIO can be considered for clinical risk stratification or rehabilitation planning. Full article

This study examined the effect of east–west orientation of willow tree (Salix alba L.) rows on soil biological activity and weed dynamics in a temperate maize (Zea mays L.) intercropped agroforestry (AF) system in Eastern Hungary. The experiment evaluated how the year (2022, 2023), location (distance from the rows), and irrigation (IR) influenced spatial patterns of earthworm (EW) parameters and weed cover. The study aimed to assess how willow-based AF systems influence soil biological and weed community dynamics under varying IR and row spacing, in comparison with monoculture cropland (MC) systems, and to evaluate their potential role in climate change adaptation in arable farming. Both soil sampling for the EW survey and vegetation studies were conducted along perpendicular transects extending from the tree rows to measure EW abundance and biomass, as well as total weed cover. Experimental results revealed clear spatial gradients in EW distribution and weed abundance near the tree rows, driven by litter input, shading, moisture, and reduced disturbance. These effects were intensified under IR at narrower row spacings. No significant differences were observed between AF-South (shaded), AF-Center, and MC plots; however, significantly higher EW abundance and biomass were found on the AF-North (sunny) side. As for the location, significantly greater total EW abundance was found at AF-North (105.0 individual m⁻²) compared with the MC plots. AF systems enhance soil biological activity and shape weed dynamics through spatial ecological gradients influenced by tree row spacing and irrigation, supporting their role as sustainable land-use systems while emphasizing the need for site-specific management and further long-term optimization. Full article

During the start stage of ship welding, obtaining the three-dimensional coordinates of welding target points is affected by confined installation space, surface reflection, and deployment constraints. This paper proposes a low-complexity point-wise three-dimensional localization method based on two-dimensional visual planar guidance and one-dimensional point-laser distance constraints. A direct computation model of the laser incident point in the robot base coordinate system is established from the tool center point pose, the extrinsic parameters of the point-laser module, and real-time ranging data, enabling target-point coordinate estimation without dense three-dimensional reconstruction. A dual-stage stabilization strategy is introduced by combining ranging-level filtering, spatial coordinate smoothing, and outlier suppression. Image error-based visual closed-loop alignment is further used as a pre-measurement step to ensure that the point laser acts on the target region. Experimental results show that, after workplane-level extrinsic correction, independent validation points achieve a mean three-dimensional Euclidean error of 1.54 mm with a standard deviation of 0.28 mm. The average planar error in closed-loop alignment experiments is 1.124 mm. Passive binocular depth measurement on the current platform still yields an RMSE of 6.16 mm after linear correction. A simulated fillet-weld task verifies the feasibility of the complete perception-to-execution workflow. The proposed method provides a low-complexity coordinate acquisition route for discrete welding target points before arc ignition. Full article

Background: Health accessibility is a key determinant of equitable cancer care. In many countries, specialized oncology services are concentrated in urban and socioeconomically advantaged regions, forcing many patients to travel long distances for treatment. Consequently, geographic and social characteristics may be impactful in determining cancer healthcare outcomes. Objective: The aim of this study was to evaluate the association between the municipal-level Social Progress Index (SPI) and geographic travel burden, stage at diagnosis, treatment, and survival in patients with pancreatic cancer in São Paulo state, Brazil. Methods: We conducted a population-based study using data from “Fundação Oncocentro” on adults with pancreatic adenocarcinoma (2005–2025). The SPI (0–100 scale), a composite measure of municipal social and environmental development, was the primary exposure. It is structured into 3 dimensions and 12 components: Basic Human Needs (nutrition, medical care, water and sanitation, housing, safety); Foundations of Well-being (education, information access, health, environmental quality); and Opportunity (rights, freedom of choice, social inclusion, higher education). Municipal residence and cancer center locations were geocoded, and travel distance (km) was estimated. Multivariable Cox, logistic, and linear regression models assessed associations between SPI and overall survival, stage IV at diagnosis, surgery, and travel distance. Results: A total of 13,478 patients were included (mean follow-up 15.1 ± 27.2 months; mean age 62.3 years; 50.4% male). Stage IV disease was frequent (46.3%), and surgery was performed in 33% of cases. Over half of patients (53.2%) traveled more than 10 km for treatment. Increasing SPI was strongly associated with shorter travel distance (β −62.6 km per SPI unit; p < 0.001) and higher odds of surgery (OR 1.04; p < 0.001) and remained independently associated with a higher likelihood of undergoing surgical treatment (adjusted OR 1.04; p < 0.001). The proportion of stage IV disease did not decrease with increasing SPI and was slightly higher in the highest quartile (49.3%). In survival analysis, SPI demonstrated a protective effect in univariate modeling (HR 0.987; p < 0.001), but lost significance in multivariable analysis (p = 0.125). Travel burden was not retained as an independent predictor of survival after adjustment. Conclusions: Municipal-level SPI was a strong determinant of healthcare access and the likelihood of receiving surgical treatment for pancreatic cancer. Social and geographic vulnerability directly influence care pathways, revealing structural inequities in access to treatment. SPI-based stratification may serve as a practical tool to identify priority regions for transport support and equitable allocation of oncology services. Full article

To mitigate the drawbacks of joint crossover (IoU) in complex detection scenarios, this paper proposes a normalized IoU strategy. This strategy enhances the matching robustness in multi-scale object detection by introducing target scale parameters. The proposed method shows comparable or superior average precision (mAP) performance to traditional methods on public datasets. In addition, we have designed a dual-center distance penalty mechanism that implicitly enforces symmetric constraints between bounding boxes, increasing the number of positive samples detected. Our method has been evaluated on mainstream public datasets and unmanned aerial vehicle (UAV) water level gauge datasets, as well as evaluated using the You Only Look Once (YOLO) framework. Our method increased the average number of positive samples by 2.28% compared to CIoU. It also surpasses the most advanced technology. The dual-center constraint enhances the spatial alignment between bounding boxes. This results in notable performance gains in challenging scenarios. These scenarios involve blurred and heavily occluded objects. After parameter optimization, the proposed method achieves significant accuracy improvements. These improvements are seen in detecting small-scale and occluded characters. Full article

Background/Objectives: To evaluate early postoperative changes in scleral and iris thicknesses together with corneal layer thicknesses and tomographic parameters following corneal collagen cross-linking (CXL) in eyes with progressive keratoconus. Methods: This retrospective study included 94 eyes of 94 patients with progressive keratoconus who underwent standard epithelium-off CXL using the Dresden protocol. Corneal tomography (Pentacam) and anterior segment optical coherence tomography (AS-OCT) measurements were obtained preoperatively and at the early postoperative follow-up (3 months ± 2 weeks). Thickness measurements of the tear film, corneal epithelium, Bowman layer, stroma, Descemet–endothelium complex, sclera (1–3 mm from the limbus), and iris (1–2 mm from the pupillary margin) were analyzed. Pre- and post-CXL values were compared using paired statistical tests, and effect sizes were calculated. Results: In the early postoperative period, scleral thickness showed a significant increase at all measured distances from the limbus, with medium effect sizes, while iris thickness demonstrated a significant decrease at all measurement points with large effect sizes (p < 0.001). Tear film, epithelial, and stromal thicknesses decreased significantly after CXL, whereas Bowman layer and Descemet–endothelium complex thicknesses remained unchanged. Pachymetric measurements revealed significant thinning at the pupil center, corneal apex, and thinnest point. No significant changes were observed in Kmax or anterior chamber depth, indicating stabilization rather than progression in the early postoperative period. Conclusions: Corneal collagen cross-linking was associated with measurable early structural changes in corneal layers and extra-corneal anterior segment tissues during the postoperative period. The observed increase in scleral thickness and decrease in iris thickness suggest that structural alterations may occur in extra-corneal anterior segment tissues following CXL. These findings support the concept that CXL influences anterior segment biomechanics in a tissue-specific manner and that extra-corneal parameters may serve as complementary markers for early postoperative assessment. Full article

Reliable long-range onboard perception is a prerequisite for future railway safety systems, where potential obstacles must be recognized under long braking distances, sparse far-field returns, and strongly constrained rail-corridor geometry. This paper presents Rail-BEV as an initial reproducible baseline study for LiDAR-centric, sensor-aware bird’s-eye-view (BEV) railway obstacle perception. LiDAR is used as the primary geometric sensing modality, while a front-center RGB camera provides lightweight auxiliary visual evidence through calibrated LiDAR-to-image projection. The aligned geometric and visual cues are organized within a unified railway-oriented BEV backend that integrates geometry-aware fusion, rail-geometry prediction, and lightweight inference-time structural refinement. Evaluation was conducted on a scene-isolated railway benchmark with range-stratified center-distance matching, and all model variants were assessed on independent test sequences rather than on validation-selected checkpoints. Compared with CenterPoint and BEVFusion baselines evaluated under the same settings, Rail-BEV achieved the highest overall mAP of 0.6669, with particularly improved long-range pedestrian perception. The controlled ablation further shows that front-view RGB evidence improves the LiDAR-only baseline from 0.5612 to 0.5750 mAP, while ROI-based rail-corridor refinement further increases mAP to 0.5916 and Rail-BEV mIoU to 0.1193. These results indicate that LiDAR-centered sensing, lightweight visual assistance, and coarse rail-aware structural reasoning can be jointly organized to support reproducible long-range railway obstacle perception. This study also clarifies the remaining limitations in rail-geometry quality, calibration robustness, sensor degradation, and strict railway-oriented localization. Full article

A 660 MW coal-fired unit was investigated to clarify the combustion behavior over a wide load range and the effects of static mixers on selective catalytic reduction (SCR) performance. A full-process CFD model covering the furnace, rear pass duct, and SCR system was established, and the combustion characteristics, NO_x formation, and SCR performance were analyzed over a boiler load range of 25–100%. The results showed that, as the boiler load decreased, the furnace heat release weakened, the high-temperature zone contracted, and the flame center shifted downward, with more pronounced flame maldistribution at 25% load. The average NO_x concentration at the SCR inlet first decreased and then increased with decreasing boiler load, reaching a minimum at 75% load. Without a static mixer, the NO_x concentration at the SCR inlet increased from 238 mg/Nm³ at 100% load to 312 mg/Nm³ at 25% load. After a static mixer was installed, the distance required for NH₃ homogenization downstream of the ammonia injection grid was markedly shortened, and the uniformity of the velocity, NH₃ concentration, and temperature fields at the SCR catalyst inlet was improved. In particular, the coefficient of variation in NH₃ concentration decreased from about 4–5% to about 2–3%, while the denitrification efficiency increased by about 1–5 percentage points compared with the case without a static mixer. The variation in denitrification efficiency among different boiler loads was also significantly reduced, indicating improved adaptability of the SCR system to wide-load operation. Among the tested configurations, the static mixer with small blades and a larger blade angle relative to the vertical plane showed the best overall performance. These results provide useful guidance for SCR system improvement in coal-fired units operating over a wide load range. Full article

To address the lack of long-term, wide-area surface deformation observations along the geologically complex Dangxiong–Yangbajing section of the G6 Expressway in the frozen-ground region of the Qinghai–Tibet Plateau, where conventional monitoring is insufficient, we applied Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) to retrieve surface deformation within a 2.0 km corridor on both sides of the highway from 24 November 2021 to 26 December 2024, and to characterize the spatiotemporal evolution of deformation. We then integrated eight explanatory factors (slope, surface roughness, distance to rivers, distance to faults, surface soil moisture, precipitation, land surface temperature (LST), and fractional vegetation cover (FVC)). Geodetector was used to quantify their explanatory power and spatial heterogeneity with respect to deformation. The results show pronounced spatially uneven settlement along this highway segment, with maximum annual settlement rates exceeding −45 mm/a. Five settlement centers were identified, including two major pavement subsidence zones. Distance to faults and soil moisture showed higher single-factor explanatory power, whereas FVC, precipitation, and LST also contributed to deformation heterogeneity. Interaction detection further indicated that the interactions between fault-related conditions with vegetation, soil moisture, precipitation, and LST substantially enhanced the explanatory power, suggesting that the deformation pattern was associated with multi-factor coupling rather than a single dominant environmental factor. These findings demonstrate the utility of integrating SBAS-InSAR with Geodetector analysis for corridor-scale highway deformation assessment and provide a remote sensing basis for targeted hazard assessment and risk mitigation for highways in frozen-ground environments. Full article

Background/Objectives: Impaired quality of life (QoL) represents one of the most important clinical determinants in heart failure with preserved ejection fraction (HFpEF). This study aimed to evaluate the incremental explanatory value of functional performance and inflammatory biomarkers for QoL in a clinically stable HFpEF cohort. Methods: A single-center observational study enrolled 110 consecutive patients with stable HFpEF. Functional capacity was assessed using the six-minute walk test (6MWT), expressed mainly as percentage of predicted distance. Health-related QoL was measured using the EQ-5D-5L utility index (primary outcome). Circulating IL-6, CRP, and NT-proBNP were obtained from peripheral blood. Hierarchical multivariable linear regression was applied to quantify the incremental contribution of clinical variables, functional capacity, and biomarkers. Results: The median age was 72 years, and 52.7% of the participants were women. The median 6MWT distance was 340 m (75.9% of predicted), and the median EQ-5D index was 0.76. The baseline clinical regression model (age, sex, atrial fibrillation, and glomerular filtration rate) explained 23.5% of EQ-5D variance. The addition of functional capacity increased explained variance to 45.2% (ΔR² = +0.217). The inclusion of IL-6 and NT-proBNP provided a modest additional increase (R² = 0.468; ΔR² = +0.042 in addition to Model 2). In the fully adjusted model, functional capacity (β = 0.376, p < 0.001) and IL-6 (β = −0.185, p < 0.05) remained independent predictors, whereas NT-proBNP lost significance. Conclusions: In stable HFpEF, objective functional capacity represents the dominant determinant of QoL, while inflammatory activation provides an independent but smaller contribution. Functional assessment may therefore be central to patient-centered phenotyping and therapeutic targeting. Full article

Apple (Malus domestica Borkh.) rootstocks play a key role in modern intensive orchard systems, where their accurate identification is essential for breeding, nursery production, and certification of planting material. This is particularly important in Kazakhstan, a recognized center of origin of cultivated apple, where local germplasm remains insufficiently characterized at the molecular level. In this study, we integrated simple sequence repeat (SSR) genotyping and morphological trait analysis to develop a reliable approach for the identification of clonal apple rootstocks cultivated in Kazakhstan. Five widely used rootstocks (Zhetysu 5, ARM-18, B-7-35, M9, and B9) were analyzed using 17 polymorphic SSR markers and 30 vegetative traits. SSR analysis revealed moderate genetic polymorphism (PIC = 0.28–0.54; He = 0.35–0.58) and enabled clear discrimination among all studied genotypes. Cluster analysis based on genetic distances grouped rootstocks according to their genetic similarity, reflecting their origin and differentiation. Morphological evaluation demonstrated significant phenotypic variability and identified correlations among key vegetative traits related to plant vigor and leaf development. The integration of molecular and morphological data allowed the development of comprehensive genotype profiles (“molecular–morphological passports”) for each rootstock, ensuring their reliable identification. The proposed approach provides a practical framework for the certification of planting material and the management of apple genetic resources in Kazakhstan. It can be applied to improve nursery systems, support breeding programs, and ensure the production of true-to-type planting material in modern horticulture. Full article

Higher education institutions face the persistent challenge of student attrition, a critical risk node within the educational supply chain (ESC). This study adopts a supply chain management (SCM) perspective to apply artificial intelligence (AI) for sustainable transformation of the ESC and evaluates an early warning system (EWS) for student performance prediction on a single programming course at Tamkang University. Learning trajectory data from 188 students across four semesters (90 for training, 98 for temporal validation; 30 fail cases in total) were collected from the iClass learning management system. To match the operational goal of the EWS—maximizing detection of at-risk students—the minority Failclass was treated as the positive class, so that recall directly measures sensitivity to at-risk cases. Three models were compared under a 5-seed protocol with time-masking to prevent future-week leakage: Random Forest (RF) with SMOTE, GRU, and LSTM. Averaged across weeks 6–16 and both validation semesters, RF achieved an accuracy 85.59%, a Fail-recall 91.19%, a precision 58.89%, and an F1 70.36%, already providing reliable warning at Week 6 (Fail-recall 87.86%). Under the same protocol LSTM and GRU collapsed to the majority class during weeks 6–10 (Fail-recall 0–42%), yielding higher headline accuracy but substantially lower sensitivity; they became usable only from Week 14 onwards (LSTM Fail-recall 80.00% at Week 14, 82.86% at Week 16). A Wilcoxon test on Cohen’s d over 90 (week×feature) pairs showed that cumulative features exhibit larger, not smaller, between-class separation than original features ($\left|d\right|$ 0.717 vs. 0.192; $p<0.001$), indicating that the original-vs-cumulative trade-off is one of sensitivity versus precision rather than information dilution. As design-level companions to these empirical results, the study also proposes a three-tier institutionalization framework and a four-dimensional impact assessment framework; these are offered as implementation blueprints rather than empirically validated outcomes. The contributions of this paper are operational rather than methodologically novel: (i) a reproducible EWS benchmark on a small, imbalanced ESC dataset, including a diagnosis of LSTM/GRU’s early-week majority-class collapse under naive augmentation, and (ii) design-level institutionalisation and impact-assessment scaffolding offered as a template for subsequent institutional pilots, not as empirically validated outcomes of the present study. Full article

Background and Objectives: Although the anterior mandible is generally considered a safe region for implant placement, injury to the medial lingual foramen (MLF) may result in significant vascular complications. Accurate identification of this structure is challenging due to its small size, low volumetric representation, and anatomical variability. This study aimed to evaluate the anatomical characteristics of the MLF using cone-beam computed tomography (CBCT) and to develop and validate a deep learning-based approach for its automated detection and segmentation. Materials and Methods: A total of 106 CBCT scans were retrospectively analyzed to assess the morphology and position of the MLF. Manual pixel-wise annotations of the complete canal trajectory were performed on sagittal slices and used to train convolutional neural network models based on a U-Net-derived framework. Multiple configurations, including multi-class, binary, two-dimensional, and three-dimensional approaches, were evaluated. Given the extremely limited volumetric representation of the MLF, severe class imbalance represented a major challenge during model training and evaluation. Model performance was assessed using the Dice similarity coefficient, precision, recall, and Hausdorff distance. External validation was performed on an independent dataset of 10 CBCT scans. Results: The MLF was identified in all patients, with a single canal observed in 63% of cases. The sagittal-plane binary segmentation model achieved the best performance, with a test Dice score of 0.79, precision of 0.88, and recall of 0.73. External validation demonstrated a Dice score of 0.81, precision of 0.89, and recall of 0.71. The 95th percentile Hausdorff distance was 2.6 mm, and the mean center-point localization error was 1.2 mm. The model correctly detected the MLF in 90% of external cases. Conclusions: Deep learning-based segmentation of the MLF is feasible and may support automated localization assistance during preoperative CBCT assessment. Performance was influenced by the alignment between the annotation strategy and model input, highlighting an important consideration for small-structure segmentation. Further validation on larger multicenter datasets is required before clinical implementation can be considered. Full article

A method for analyzing and calculating the offset between the elastic center and the center of mass, based on inertial sensor output signals, is proposed to address the problem of vibration-induced coupled angular motion in inertial measurement units. First, the spatial six-degree-of-freedom vibration differential equations of the inertial system are derived, and an approximate decomposition approach for analyzing the six-degree-of-freedom model is introduced. Subsequently, based on practical engineering considerations, the rationality of the proposed decomposition method is verified using numerical simulation and finite element analysis software, and the relationship between the offset distance and the coupled angular velocity is further investigated. Full article