Search Results (5,733)

In order to achieve 0.1 m resolution and fully polarimetric observation capabilities for airborne SAR systems, the adoption of stepped-frequency modulation waveform combined with the polarization time-division transmit/receive (T/R) technique proves to be an effective technical approach. Considering the issue of range resolution degradation and paired echoes caused by multichannel amplitude–phase mismatch in fully polarimetric airborne SAR with 0.1 m resolution, an amplitude–phase error estimation algorithm based on echo data is proposed in this paper. Firstly, the subband amplitude spectrum correction curve is obtained by the statistical average of the subband amplitude spectrum. Secondly, the paired-echo broadening function is obtained by selecting high-quality sample points after single-band imaging and the nonlinear phase error within the subbands is estimated via Sinusoidal Frequency Modulation Fourier Transform (SMFT). Thirdly, based on the minimum entropy criterion of the synthesized compressed pulse image, residual linear phase errors between subbands are quickly acquired. Finally, two-dimensional cross-correlation of the image slice is utilized to estimate the positional deviation between polarization channels. This method only requires high-quality data samples from the echo data, then rapidly estimates both intra-band and inter-band amplitude/phase errors by using SMFT and the minimum entropy criterion, respectively, with the characteristics of low computational complexity and fast convergence speed. The effectiveness of this method is verified by the imaging results of the experimental data. Full article

Contactless vital sign monitoring has emerged as a transformative healthcare technology, enabling the assessment of vital signs without physical contact with the human body. This review comprehensively reviews the rapidly evolving landscape of this field, with particular emphasis on multi-modal sensing approaches and multi-task learning paradigms. We systematically categorize and analyze existing technologies based on sensing modalities (vision-based, radar-based, thermal imaging, and ambient sensing), integration strategies, and application domains. The paper examines how artificial intelligence has revolutionized this domain, transitioning from early single-modality, single-parameter approaches to sophisticated systems that combine complementary sensing technologies and simultaneously extract multiple vital sign parameters. We discuss the theoretical foundations and practical implementations of multi-modal fusion, analyzing signal-level, feature-level, decision-level, and deep learning approaches to sensor integration. Similarly, we explore multi-task learning frameworks that leverage the inherent relationships between vital sign parameters to enhance measurement accuracy and efficiency. The review also critically addresses persisting technical challenges, clinical limitations, and ethical considerations, including environmental robustness, cross-subject variability, sensor fusion complexities, and privacy concerns. Finally, we outline promising future directions, from emerging sensing technologies and advanced fusion architectures to novel application domains and privacy-preserving methodologies. This review provides a holistic perspective on contactless vital sign monitoring, serving as a reference for researchers and practitioners in this rapidly advancing field. Full article

CT scanners are essential tools in modern medical imaging. Sudden failures of their X-ray tubes can lead to equipment downtime, affecting healthcare services and patient diagnosis. However, existing prediction methods based on a single model struggle to adapt to the multi-stage variation characteristics of tube lifespan and have limited modeling capabilities for temporal features. To address these issues, this paper proposes an intelligent prediction architecture for CT tubes’ remaining useful life based on a dual-branch neural network. This architecture consists of two specialized branches: a residual self-attention BiLSTM (RSA-BiLSTM) and a multi-layer dilation temporal convolutional network (D-TCN). The RSA-BiLSTM branch extracts multi-scale features and also enhances the long-term dependency modeling capability for temporal data. The D-TCN branch captures multi-scale temporal features through multi-layer dilated convolutions, effectively handling non-linear changes in the degradation phase. Furthermore, a dynamic phase detector is applied to integrate the prediction results from both branches. In terms of optimization strategy, a dynamically weighted triplet mixed loss function is designed to adjust the weight ratios of different prediction tasks, effectively solving the problems of sample imbalance and uneven prediction accuracy. Experimental results using leave-one-out cross-validation (LOOCV) on six different CT tube datasets show that the proposed method achieved significant advantages over five comparison models, with an average MSE of 2.92, MAE of 0.46, and R² of 0.77. The LOOCV strategy ensures robust evaluation by testing each tube dataset independently while training on the remaining five, providing reliable generalization assessment across different CT equipment. Ablation experiments further confirmed that the collaborative design of multiple components is significant for improving the accuracy of X-ray tubes remaining life prediction. Full article

Educational admission systems, particularly in developing countries, often suffer from opaque decision processes, unstructured data, and limited analytic insight. This study proposes a novel methodology that integrates structural causal models (SCMs), ontological modeling, and machine learning to uncover and apply interpretable knowledge from an admission database. Using a dataset of 12,043 records from Benue State Polytechnic, Nigeria, we demonstrate this approach as a proof of concept by constructing a domain-specific SCM ontology, validate it using conditional independence testing (CIT), and extract features for predictive modeling. Five classifiers, Logistic Regression, Decision Tree, Random Forest, K-Nearest Neighbors (KNN), and Support Vector Machine (SVM) were evaluated using stratified 10-fold cross-validation. SVM and KNN achieved the highest classification accuracy (92%), with precision and recall scores exceeding 95% and 100%, respectively. Feature importance analysis revealed ‘mode of entry’ and ‘current qualification’ as key causal factors influencing admission decisions. This framework provides a reproducible pipeline that combines semantic representation and empirical validation, offering actionable insights for institutional decision-makers. Comparative benchmarking, ethical considerations, and model calibration are integrated to enhance methodological transparency. Limitations, including reliance on single-institution data, are acknowledged, and directions for generalizability and explainable AI are proposed. Full article

This paper presents field investigations of a corrugated steel soil–steel arch structure with a span of 25.7 m and a rise of 9.0 m—currently the largest single-span structure of its kind in Europe. The structure, serving as a wildlife crossing along the DK16 expressway in northeastern Poland, was constructed using deep corrugated steel plates (500 mm× 237 mm) made from S315MC steel, without additional reinforcements such as stiffening ribs or geosynthetics. The study focused on monitoring the structural behavior during the critical backfilling phase. Displacements and strains were recorded using 34 electro-resistant strain gauges and a geodetic laser system at successive backfill levels, with particular attention to the loading stage at the crown. The measured results were compared with predictions based on the Swedish Design Method (SDM). The SDM equations did not accurately predict internal forces during backfilling. At the crown level, bending moments and axial forces were overestimated by approximately 69% and 152%, respectively. At the final backfill level, the SDM underestimated bending moments by 55% and overestimated axial forces by 90%. These findings highlight limitations of current design standards and emphasize the need for revised analytical models and long-term monitoring of large-span soil–steel structures. Full article

Objectives: This study investigated levels of work engagement and the occurrence of compassion fatigue among nursing professionals during the COVID-19 pandemic. Methods: A cross-sectional, descriptive, and correlational study was conducted at a Brazilian university hospital between February and April 2022. The Brazilian versions of the Utrecht Work Engagement Scale (UWES-9) and the Professional Quality of Life Scale (ProQOL-BR) were administered. Results: High levels of compassion satisfaction (44.9 points), low levels of burnout (21.0 points), and low levels of secondary traumatic stress (22.8 points) were observed. No professional demonstrated a profile consistent with compassion fatigue. Engagement levels were high for dedication (5.3) and moderate for vigor (4.9), absorption (4.5), and overall engagement (4.9). Burnout showed moderate negative correlations with vigor (r = −0.611, p = 0.005) and dedication (r = −0.599, p = 0.019). Compassion satisfaction showed moderate positive correlations with vigor (r = 0.522, p < 0.001) and dedication (r = 0.572, p < 0.001). The overall engagement score was moderately and positively correlated with compassion satisfaction (r = 0.532, p < 0.001). Conclusions: This study identified high levels of work engagement, especially regarding dedication, and low levels of compassion fatigue among nursing professionals. The data suggest that even amid the emotional and physical demands imposed by the pandemic, participants preserved their emotional well-being and maintained a positive relationship with their work. Full article

This study proposes a coupled constitutive model that captures the anisotropic failure characteristics and damage evolution of nickel-based single-crystal (SX) superalloys under various temperature conditions. The model accounts for both creep rate and material damage evolution, enabling accurate prediction of the typical three-stage creep curves, macroscopic fracture morphologies, and microstructural features under uniaxial tensile creep for specimens with different crystallographic orientations. Creep behavior of SX superalloys was simulated under multiple orientations and various temperature-stress conditions using the proposed model. The resulting creep curves aligned well with experimental observations, thereby validating the model’s feasibility and accuracy. Furthermore, a finite element model of cylindrical specimens was established, and simulations of the macroscopic fracture morphology were performed using a user-defined material subroutine. By integrating the rafting theory governed by interfacial energy density, the model successfully predicts the rafting morphology of the microstructure at the fracture surface for different crystallographic orientations. The proposed model maintains low programming complexity and computational cost while effectively predicting the creep life and deformation behavior of anisotropic materials. The model accurately captures the three-stage creep deformation behavior of SX specimens and provides reliable predictions of stress fields and microstructural changes at critical cross-sections. The model demonstrates high accuracy in life prediction, with all predicted results falling within a ±1.5× error band and an average error of 14.6%. Full article

Objective: To determine reference values of liver stiffness during the first week of extrauterine life in healthy newborns, according to gestational age, sex, and birth weight, using three elastography techniques: point shear wave elastography (pSWE) and two-dimensional shear wave elastography (2D-SWE) with convex and linear probes. Materials and Methods: This was a cross-sectional observational study conducted at a single center on a hospital-based cohort of 287 newborns between 24 and 42 weeks of gestation, admitted between January 2023 and May 2024. Cases with liver disease, significant neonatal morbidity, or technically invalid studies were excluded. Hepatic elastography was performed during the first week of life using pSWE and 2D-SWE with both convex and linear probes. Clinical and technical neonatal variables were recorded. Liver stiffness values were analyzed in relation to gestational age, birth weight, and sex. Linear regression models were applied to assess associations, considering p-values < 0.05 as statistically significant. Results: After applying exclusion criteria, valid liver stiffness measurements were obtained in 208 cases with pSWE, 224 with 2D-SWE (convex probe), and 222 with 2D-SWE (linear probe). A statistically significant inverse association between liver stiffness and gestational age (p < 0.03) was observed across all techniques except for 2D-SWE with the linear probe. Only 2D-SWE with the convex probe showed a significant association with birth weight. No significant differences were observed based on neonatal sex. The 2D-SWE technique with the convex probe demonstrated significantly shorter examination times compared to pSWE (p < 0.001). Conclusions: Neonatal liver stiffness measured by pSWE and 2D-SWE with a convex probe shows an inverse correlation with gestational age, potentially reflecting the structural and functional maturation of the liver. These techniques are safe, reliable, and provide useful information for distinguishing normal findings in preterm neonates from early hepatic pathology. The values obtained represent a valuable reference for clinical hepatic assessment in the neonatal period. Full article

Background and Objectives: Although survival after congenital cardiac malformations (CCM) has improved, little is known about Romanian children’s own perceptions of health-related quality of life (HRQoL) or their emotional burden. We compared HRQoL, depressive symptoms, and anxiety across lesion severity strata and explored clinical predictors of impaired HRQoL. Methods: In this cross-sectional study (1 May 2023–30 April 2025), 72 children (mean age 7.9 ± 3.0 years, 52.8% male) attending a tertiary cardiology clinic completed the Romanian-validated Pediatric Quality of Life Inventory (PedsQL), Children’s Depression Inventory (CDI) and the Screen for Child Anxiety-Related Emotional Disorders questionnaire (SCARED-C, child version). Lesions were classified as mild (n = 22), moderate (n = 34), or severe (n = 16). Left-ventricular ejection fraction (LVEF) and unplanned cardiac hospitalisations over the preceding 12 months were extracted from electronic records. Results: Mean PedsQL total scores declined stepwise by severity (mild 80.9 ± 7.3; moderate 71.2 ± 8.4; severe 63.1 ± 5.4; p < 0.001). CDI and SCARED-C scores rose correspondingly (CDI: 9.5 ± 3.0, 13.6 ± 4.0, 18.0 ± 2.7; anxiety: 15.2 ± 3.3, 17.2 ± 3.8, 24.0 ± 3.4; both p < 0.001). PedsQL correlated positively with LVEF (r = 0.51, p < 0.001) and negatively with hospitalisations (r = −0.39, p = 0.001), depression (r = −0.44, p < 0.001), and anxiety (r = −0.47, p < 0.001). In multivariable analysis, anatomical severity remained the sole independent predictor of lower HRQoL (β = −8.4 points per severity tier, p < 0.001; model R² = 0.45). Children with ≥ 1 hospitalisation (n = 42) reported poorer HRQoL (69.6 ± 8.0 vs. 76.1 ± 11.1; p = 0.005) and higher depressive scores (p < 0.001). Conclusions: HRQoL and internalising symptoms in Romanian children with CCM worsen with increasing anatomical complexity and recent hospital utilisation. The severity tier outweighed functional markers as the main determinant of HRQoL, suggesting that psychosocial screening and support should be scaled to lesion complexity. Integrating the routine use of the Romanian-validated PedsQL, CDI, and SCARED-C questionnaire into cardiology follow-up may help identify vulnerable patients early and guide targeted interventions. Full article

Background/Objectives: Neck pain caused by myofascial pain syndrome (MPS) is a highly prevalent musculoskeletal condition. Repetitive peripheral magnetic stimulation (rPMS) is a promising treatment option; however, its therapeutic effect and optimal treatment frequency remain unclear. This study aimed to investigate the therapeutic effect and duration of effect of rPMS in patients with MPS of the neck. Methods: In this randomized, sham-controlled, crossover trial, 27 patients with neck MPS and baseline visual analog scale (VAS) scores ≥ 40 were enrolled. The mean age was 43.8 ± 9.1 years, and 63% were female. Participants were randomly assigned to receive either an initial rPMS treatment (a 10 min session delivering 3900 pulses at 5–10 Hz) or sham stimulation. After 7 days, groups crossed over. Pain intensity (VAS), disability (Neck Disability Index; NDI), and analgesic use were recorded daily for seven consecutive days. A linear mixed-effects model was used for analysis. Results: At baseline, the VAS and NDI scores were 61.8 ± 10.5 and 26.0 ± 6.3, respectively. rPMS produced a significantly greater reduction in both VAS and NDI scores, with the greatest differences observed on Day 4: the differences were −24.1 points in VAS and −8.5 points in NDI compared to the sham group. There was no significant difference in analgesic use between the two groups. Conclusions: A single rPMS session provides short-term improvement in pain and disability in neck MPS. Based on the observed therapeutic window, more frequent sessions (e.g., twice weekly) may provide sustained benefit and should be explored in future studies. Full article

As economically important sympatric species in the Northwest Pacific, the Japanese sardine (Sardinops melanostictus) and Chub mackerel (Scomber japonicus) exhibit significant biological interactions. Understanding the impact of interspecies competition on their habitat dynamics can provide crucial insights for the sustainable development and management of these interconnected species resources. This study utilizes fisheries data of S. melanostictus and S. japonicus from the Northwest Pacific, collected from June to November between 2017 and 2020. We integrated various environmental parameters, including temperature at different depths (0, 50, 100, 150, and 200 m), eddy kinetic energy (EKE), sea surface height (SSH), chlorophyll-a concentration (Chl-a), and the oceanic Niño index (ONI), to construct interspecific competition species distribution model (icSDM) for both species. We validated these models by overlaying the predicted habitats with fisheries data from 2021 and performing cross-validation to assess the models’ reliability. Furthermore, we conducted correlation analyses of the habitats of these two species to evaluate the impact of interspecies relationships on their habitat dynamics. The results indicate that, compared to single-species habitat models, the interspecific competition species distribution model (icSDM) for these two species exhibit a significantly higher explanatory power, with R² values increasing by up to 0.29; interspecific competition significantly influences the habitat dynamics of S. melanostictus and S. japonicus, strengthening the correlation between their habitat changes. This relationship exhibits a positive correlation at specific stages, with the highest correlations observed in June, July, and October, at 0.81, 0.80, and 0.88, respectively; interspecific competition also demonstrates stage-specific differences in its impact on the habitat dynamics of S. melanostictus and S. japonicus, with the most pronounced differences occurring in August and November. Compared to S. melanostictus, interspecific competition is more beneficial for the expansion of the optimal habitat (HIS ≥ 0.6) for S. japonicus and, to some extent, inhibits the habitat expansion of S. melanostictus. The variation in migratory routes and predatory interactions (with larger individuals of S. japonicus preying on smaller individuals of S. melanostictus) likely constitutes the primary factors contributing to these observed differences. Full article

Hepatocellular carcinoma (HCC) is the most prevalent subtype of liver cancer with an increasing incidence worldwide. Single nucleotide polymorphisms (SNPs) may influence disease risk and serve as predictive markers. This study aimed to evaluate the association of PNPLA3 (rs738409 and rs2294918), GCKR (rs780094), MBOAT7 (rs641738), NCAN (rs2228603), and TM6SF2 (rs58542926) SNPs with the risk of developing HCC in a Mexican population. A case-control study was conducted in unrelated Mexican individuals. Cases were 173 adults with biopsy-confirmed HCC and 346 were healthy controls. Genotyping was performed using TaqMan allelic discrimination assay. Logistic regression was applied to evaluate associations under codominant, dominant, and recessive inheritance models. p-values were corrected using the Bonferroni test (pC). Haplotype and gene–gene interaction were also analyzed. The GG homozygous of rs738409 and rs2294918 of PNPLA3, TT, and TC genotypes of GCKR, as well as the TT genotype of MBOAT7, were associated with a significant increased risk to HCC under different inheritance models (~Two folds in all cases). The genotypes of NCAN and TM6SF2 did not show differences. The haplotype G-G of rs738409 and rs2294918 of PNPLA3 was associated with an increased risk of HCC [OR (95% CI) = 2.2 (1.7–2.9)]. There was a significant gene–gene interaction between PNPLA3 (rs738409), GCKR (rs780094), and MBOAT7 (rs641738) (Cross-validation consistency (CVC): 10/10; Testing accuracy = 0.6084). This study demonstrates for the first time that PNPLA3 (rs738409 and rs2294918), GCKR (rs780094), and MBOAT7 (rs641738) are associated with an increased risk of developing HCC from multiple etiologies in Mexican patients. Full article

The article presents a new AM (Additive Manufacturing) process development, necessary to repair parts made from Aluminum 6061 material, with T6 treatment. The laser Directed Energy Deposition (DED) and Extreme High-Speed Directed Energy Deposition (EHLA) capabilities are evaluated for repairing Al large components. To optimize the process parameters, single-track depositions were analyzed for both laser-powder DED (feed rate of 2 m/min) and EHLA (feed rate 20 m/min) for AlSi10Mg and Al6061 powders. The cross-sections of single tracks revealed the bonding characteristics and provided laser-powder DED, a suitable parameter selection for the repair. Three damage types were identified on the Al component to define the specification of the repair process and to highlight the capabilities of laser-powder DED and EHLA in repairing intricate surface scratches and dents. Our research is based on variation of the powder mass flow and beam power, studying the influence of these parameters on the weld bead geometry and bonding quality. The evaluation criteria include bonding defects, crack formation, porosity, and dilution zone depth. The bidirectional path planning strategy was applied with a fly-in and fly-out path for the hatching adjustment and acceleration distance. Samples were etched for a qualitative microstructure analysis, and the HV hardness was tested. The novelty of the paper is the new process parameters for laser-powder DED and EHLA deposition strategies to repair large Al components (6061 T6), using AlSi10Mg and Al6061 powder. Our experimental research tested the defect-free deposition and the compatibility of AlSi10Mg on the Al6061 substrate. The readers could replicate the method presented in this article to repair by laser-powder DED/EHLA large Al parts and avoid the replacement of Al components with new ones. Full article

Surface electromyographic (sEMG) signal-driven joint-angle estimation plays a critical role in intelligent rehabilitation systems, as its accuracy directly affects both control performance and rehabilitation efficacy. This study proposes a continuous elbow joint angle estimation method based on time–frequency domain analysis. Raw sEMG signals were processed using the Short-Time Fourier Transform (STFT) to extract time–frequency features. A Scale Temporal–Channel Cross-Encoder (STCCE) network was developed, integrating temporal and channel attention mechanisms to enhance feature representation and establish the mapping from sEMG signals to elbow joint angles. The model was trained and evaluated on a dataset comprising approximately 103,000 samples collected from seven subjects. In the single-subject test set, the proposed STCCE model achieved an average Mean Absolute Error (MAE) of $2.96\pm {0.24}^{\circ }$, Root Mean Square Error (RMSE) of $4.41\pm {0.45}^{\circ }$, Coefficient of Determination ($R^2$) of $0.9924\pm 0.0020$, and Correlation Coefficient (CC) of $0.9963\pm 0.0010$. It achieved a MAE of ${3.30}^{\circ }$, RMSE of ${4.75}^{\circ }$, $R^2$ of 0.9915, and CC of 0.9962 on the multi-subject test set, and an average MAE of $15.53\pm {1.80}^{\circ }$, RMSE of $21.72\pm {2.85}^{\circ }$, $R^2$ of $0.8141\pm 0.0540$, and CC of $0.9100\pm 0.0306$ on the inter-subject test set. These results demonstrated that the STCCE model enabled accurate joint-angle estimation in the time–frequency domain, contributing to a better motion intent perception for upper-limb rehabilitation. Full article

Early detection of clinical deterioration in emergency department (ED) patients is critical for timely interventions. This study evaluated the predictive performance of the National Early Warning Score (NEWS) parameters using machine learning. We conducted a single-center retrospective observational study including 27,238 adult ED patients admitted to Merano Hospital (Italy) between June 2022 and June 2023. NEWS vital signs were collected at triage, and mortality at 48 h, 7 days, and 30 days was obtained from ED database. Decision tree analysis (CHAID algorithm) was used to identify predictors of mortality; 10-fold cross-validation was applied to avoid overfitting. Mortality was 0.4% at 48 h, 1% at 7 days, and 2.45% at 30 days. For 48-h mortality, oxygen supplementation (FiO₂ >21%) and AVPU = “U” were the strongest predictors, with a maximum risk of 31.6%. For 7-day mortality, SpO₂ was the key predictor, with mortality up to 48.1%. At 30 days, patients with AVPU ≠ A, FiO₂ > 21%, and SpO₂ ≤ 94% had a mortality risk of 66.7%. Decision trees revealed different cut-offs compared to the standard NEWS. This study demonstrated that for ED patients, the NEWS may require some adjustments in both the cut-offs for vital parameters and the methods of collecting these parameters. Full article