Search Results (14,516)

Obesity hypoventilation syndrome (OHS) is a severe and underrecognized respiratory disorder characterized by the coexistence of obesity, daytime hypercapnia, and sleep-disordered breathing. Although well described in adults, pediatric OHS remains poorly defined despite the rising prevalence of childhood obesity. Its pathophysiology is multifactorial, involving obesity-related mechanical constraints, impaired ventilatory control, altered chemosensitivity, and frequent overlap with obstructive sleep apnea. Clinical manifestations in children are often subtle and nonspecific, including snoring, sleep fragmentation, daytime sleepiness, and neurocognitive impairment, frequently leading to delayed diagnosis and, in some cases, acute cardiopulmonary decompensation. Management of pediatric OHS is challenging and largely extrapolated from adult data. Positive airway pressure therapy remains the cornerstone of treatment, while weight reduction is essential but difficult to achieve in pediatric populations. Pharmacological approaches such as medroxyprogesterone or acetazolamide remain experimental, with limited pediatric evidence. This review synthesizes current knowledge on pediatric OHS, focusing on epidemiology, pathophysiology, clinical presentation, diagnostic challenges, and therapeutic strategies. Increased awareness and earlier recognition are essential to prevent progression to chronic respiratory failure and long-term cardiovascular complications. Full article

The microstructure and wear behaviors of Mg₂Si/Al composites with 0 wt.%, 5 wt.%, and 10 wt.% SiC particles were studied using XRD, OM observation, SEM observation, EDS analysis, an extraction experiment, a hardness test, and the dry sliding wear test. It is shown by the results that after the addition of 10 wt.% SiC particles, the population of primary Mg₂Si particles increased, while the mean size of these particles reduced from 40 ± 10 μm (in the SiC-free composite) to 25 ± 8 μm. Both the matrix and the eutectic structure were refined. The tetrakaidecahedral morphologies of Mg₂Si crystals were confirmed by the results of extraction tests. The wear test results with GCr15 steel as the friction pair show that the Mg₂Si/Al composite with 10 wt.% SiC particles displayed more favorable wear resistance than the specimens with 0 wt.% and 5 wt.% SiC particle additions under both constant load and constant sliding velocity conditions. Under applied loads of 10 N, 20 N, and 30 N at a fixed sliding speed of 300 r/min, the wear rate of the Mg₂Si-Al composites reinforced with 10 wt.% SiC particles was 36.01%, 48.29%, and 23.32% lower than that of the SiC-free composites, respectively. When the sliding speed was set to 300 r/min, 550 r/min, 750 r/min, and 1000 r/min under a constant applied load of 20 N, the wear rate of the 10 wt.% SiC-reinforced Mg₂Si-Al composites was reduced by 40.37%, 40.87%, 26.20%, and 25.78%, respectively, compared with the SiC-free counterparts. The wear failure mechanisms of (Mg₂Si + SiC_P)/Al composites were mainly adhesive wear and abrasive wear, but the proportion of oxidation wear increased after the addition of the SiC particles. Full article

Accurately assessing collapse risks of high-elevation, concealed rock mass blocks within the steep cliffs of Bijiashan, Three Gorges Reservoir Area, is challenging. This study employed a multidimensional approach—integrating airborne Light Detection and Ranging (LiDAR), the transient electromagnetic method (TEM), close-range photogrammetry, horizontal drilling, and borehole optical imaging—to characterize the rock mass structure of the WD1 cliff belt and delineate 52 individual blocks. Stability analysis incorporated stereographic projection for macro-scale assessment and employed mechanical models specific to three primary failure modes (toppling, sliding, falling). Finite element strength reduction quantified the stress–strain response of a representative block under natural and rainstorm conditions. Particle Flow Code (PFC) simulated dynamic instability of the exceptionally large block W1-37. Results indicate the WD1 rock mass is highly fractured, with base sections prone to weakness. Toppling failure dominates (90.4%). Under rainstorm conditions, the average Factor of Safety (FOS) decreased by 14.7%, and 73.1% of the blocks that were stable under natural conditions were destabilized—specifically transitioning to marginally stable or substable states—often triggering chain-reaction instability characterized by “crack propagation—base buckling”. W1-37 exhibited staged failure under rainstorm: “strain localization at fissure tips—penetration of basal cracks—overturning of the upper rock mass”. Its frontal rock reached a peak sliding velocity of 15.17 m/s, indicative of base-breaking toppling. The integrated “multi-technology survey—multi-method evaluation—multi-scale simulation” framework provides a quantitative basis for risk assessment of rock mass disasters in the Three Gorges Reservoir Area and offers a technical paradigm for similar high-steep canyon regions. Full article

As shale gas development extends into deeper formations, the unclear brittle-ductile transition (BDT) mechanism and low fracturing efficiency have emerged as critical bottlenecks, posing challenges to the sustainable and economical utilization of this clean energy resource. This study, focusing on the Liangshang Formation shale of Sichuan Basin’s Pingye-1 Well, pioneers a paradigm shift by identifying Poisson’s ratio ($\mathsf{\nu }$) as the master variable governing this transition. Triaxial tests reveal that $\mathsf{\nu }$ systematically increases with depth, directly regulating the failure mode shift from brittle fracture to ductile flow. Building on this, we innovatively propose the Poisson’s Ratio-regulated Energy-based Brittleness Index (PNE-BI) model. This model achieves a decoupled diagnosis of BDT by quantifying how ν intrinsically orchestrates the energy redistribution between elastic storage and plastic dissipation, utilizing ν as the sole governing variable to regulate energy weighting for rapid and accurate distinction between brittle, transitional, and ductile states. Experiments confirm the $\mathsf{\nu }$-dominated energy evolution: Low $\mathsf{\nu }$ rocks favor elastic energy accumulation, while high $\mathsf{\nu }$ rocks (>0.22) exhibit a dramatic 1520% surge in plastic dissipation, dominating energy consumption (35.9%) and confirming that $\mathsf{\nu }$ enhances ductility by reducing intergranular sliding barriers. Compared to traditional multi-variable models, the PNE-BI model utilizes $\mathsf{\nu }$ values readily obtained from conventional well logs, providing a transformative field-ready tool that significantly reduces the experimental footprint and promotes resource efficiency. It guides toughened fracturing fluid design in ductile zones to suppress premature closure and optimizes injection rates in brittle zones to prevent fracture runaway, thereby enhancing operational longevity and minimizing environmental impact. This work offers a groundbreaking and sustainable solution for boosting the efficiency of mid-deep shale gas development, contributing directly to more responsible and cleaner energy extraction. Full article

Ischemic heart disease (IHD) remains a leading cause of global morbidity and mortality despite advances in prevention, diagnosis, and therapy. Traditional clinical risk scores and biomarkers often fail to fully capture the complex molecular processes underlying atherosclerosis, myocardial infarction, and ischemic cardiomyopathy, leaving substantial residual risk. MicroRNAs have emerged as promising regulators and biomarkers of cardiovascular disease, among which microRNA-21 (miR-21) has attracted particular attention. MiR-21 is deeply involved in key pathophysiological mechanisms of IHD, including endothelial dysfunction, vascular inflammation, vascular smooth muscle cell proliferation, plaque development and vulnerability, cardiomyocyte survival, and myocardial fibrosis. Accumulating clinical evidence suggests that circulating miR-21 holds diagnostic value across the ischemic continuum, from stable coronary artery disease to acute coronary syndromes, myocardial infarction, and ischemic heart failure. Moreover, miR-21 demonstrates prognostic relevance, correlating with plaque instability, adverse remodeling, heart failure progression, and long-term cardiovascular outcomes. Preclinical studies further indicate that miR-21 represents a double-edged therapeutic target, offering cardio protection in acute ischemic injury while contributing to fibrosis and maladaptive remodeling if dysregulated. This narrative review summarizes current evidence on the diagnostic, prognostic, and therapeutic utility of miR-21 in IHD, highlighting its clinical promise as well as key limitations and future translational challenges. Full article

Fatigue crack propagation is a critical failure mechanism in engineering structures, requiring meticulous monitoring for timely maintenance. This research introduces a deep learning framework for estimating fatigue fracture length in metallic plates through acoustic emission (AE) signals. AE waveforms recorded during crack growth are transformed into time-frequency images using the Choi–Williams distribution. First, a clustering system is developed to analyze the distribution of the AE image-based dataset. This system employs a CNN-based model to extract features from the input images. The AE dataset is then divided into three categories according to fatigue lengths using the K-means algorithm. Principal Component Analysis (PCA) is used to reduce the feature vectors to two dimensions for display. The results show how close together the data points are in the clusters. Second, convolutional neural network (CNN) models are trained using the AE dataset to categorize fracture lengths into three separate ranges. Using the pre-trained models ResNet50V2 and VGG16, we compare the performance of a bespoke CNN using transfer learning. It is clear from the data that transfer learning models outperform the custom CNN by a wide margin, with an accuracy of approximately 99% compared to 93%. This research confirms that convolutional neural networks (CNNs), particularly when trained with transfer learning, are highly successful at understanding AE data for data-driven structural health monitoring. Full article

Interfacial adhesion between selective laser-melted (SLM) AlSi10Mg and polyimide (PI) insulating coatings is often limited by mismatched physicochemical properties. To improve adhesion, Al-rich and Si-rich microstructured surfaces were fabricated on the XY plane (perpendicular to the build direction) and the Z plane (parallel to the build direction) by acidic and alkaline etching, exploiting the characteristic microstructure of SLM AlSi10Mg. Surface topography, chemical composition, and wettability were characterized, and interfacial mechanical performance was evaluated by shear and pull-off tests. The microstructures increased surface roughness and improved wettability. The shear strength rose from 2.6 ± 1.5 MPa for the polished surface to 43.2 ± 8.6 MPa. The polished surface showed a pull-off strength of 2.2 ± 0.25 MPa. In pull-off tests, failure mainly occurred within the dolly/adhesive/PI system, indicating that the interfacial tensile strength exceeded the strength of the adhesive system; the maximum measured pull-off strength was 29.0 ± 1.3 MPa. Fractography predominantly showed cohesive failure in PI on Al-rich microstructures. Si-rich microstructures exhibited mixed failure, including fracture of the Si skeleton and tearing of PI, together with interfacial microcracks. Full article

Freeze–thaw cycles (FTCs) are a prevalent weathering process that threatens the stability of canal slopes in seasonally frozen regions. This study combines direct shear tests under multiple F-T cycles with coupled thermo-hydro-mechanical numerical modeling to investigate the failure mechanisms of slopes with different moisture contents (18%, 22%, 26%). The test results quantify a marked strength degradation, where the cohesion decreases to approximately 50% of its initial value and the internal friction angle is weakened by about 10% after 10 freeze–thaw cycles. The simulation reveals that temperature gradient-driven moisture migration is the core process, leading to a dynamic stress–strain concentration zone that propagates from the upper slope to the toe. The safety factors of the three soil specimens with different moisture contents fell below the critical threshold of 1.3. They registered values of 1.02, 0.99, and 0.78 within 44, 44, and 46 days, which subsequently induced shallow failure. The failure mechanism elucidated in this study enhances the understanding of freeze–thaw-induced slope instability in seasonally frozen regions. Full article

Roadways driven along the floor of thick coal seams, while retaining the top coal, form “thick coal seam floor roadways.” These large-section roadways feature a composite coal-rock roof and weak coal ribs, leading to low overall strength and poor stability of the surrounding rock. Significant deformation and “necking” often occur, accompanied by roof falls and rib spalling, which are exacerbated under high stress or adverse geology, threatening mine safety and production. In this study, the 2201 haulage gateway in Yingpanhao Coal Mine is investigated to address surrounding rock control in such deep roadways. Using field investigation, theoretical analysis, numerical simulation, and similar simulation tests, the failure mechanisms of ribs and roofs are analyzed. Rib failure is characterized by tensile fracture in the shallow zone, splitting failure in the medium-depth zone, and incomplete conjugate shear in the deep zone. Corresponding mechanical models are established, and a method for calculating total rib failure depth—combining tensile/splitting and shear failure depths—is proposed, along with a bolt length design formula. Based on this, a synergistic roof-and-rib support technology is developed. The failure mechanism and optimal support scheme are validated through simulation tests and successfully applied in the field, demonstrating satisfactory performance. The findings provide a valuable reference for support design in similar mining roadways. Full article

Background and Objectives: Acute respiratory failure (ARF) has a heterogeneous course in the emergency department (ED), and early prediction of noninvasive mechanical ventilation (NIMV) failure is difficult. The PaCO₂–ETCO₂ gap reflects ventilation–perfusion mismatch and increased physiologic dead space; however, the prognostic value of its short-term change during NIMV is unclear. This study evaluated baseline, post-treatment, and delta (post–pre) PaCO₂–ETCO₂ gap values for predicting intubation, intensive care unit (ICU) admission, and mortality in ED patients with ARF receiving NIMV. Materials and Methods: This prospective observational study enrolled adults (≥18 years) treated with NIMV in a tertiary ED. Exclusion criteria included GCS < 15, intoxication, pneumothorax, trauma, pregnancy, gastrointestinal bleeding, need for immediate intubation/CPR, or incomplete data. ETCO₂ was recorded within the first 3 min of NIMV and at 30 min; concurrent arterial blood gases provided PaCO₂. The PaCO₂–ETCO₂ gap was calculated at both time points and as delta. Outcomes were intubation, ICU admission, and mortality. ROC analyses determined discriminatory performance and cutoffs using the Youden index. Results: Thirty-four patients were included (50% female; mean age 73.26 ± 10.07 years). Intubation occurred in 9 (26.5%), ICU admission in 20 (58.8%), and mortality in 10 (29.4%). The post-treatment gap and delta gap were significantly higher in intubated patients (p = 0.007 and p = 0.001). For predicting intubation, post-treatment gap > 10.90 mmHg yielded AUC 0.807 (p = 0.007; sensitivity 77.8%, specificity 76.0), while delta gap > 2.90 mmHg yielded AUC 0.982 (p = 0.001; sensitivity 88.9%, specificity 92.0). Delta gap also predicted ICU admission (cutoff > 0.65 mmHg; AUC 0.746, p = 0.016) and mortality (cutoff > 2.90 mmHg; AUC 0.865, p = 0.001). Conclusions: In ED ARF patients receiving NIMV, an increasing PaCO₂–ETCO₂ gap—especially the delta gap—was associated with higher risks of intubation, ICU admission, and mortality, supporting serial CO₂ gap monitoring as a practical early warning marker of deterioration. Full article

Rainfall-induced failures in red clay slopes are common, yet the coupled influence of soil structure degradation and rainfall temporal patterns on slope hydromechanical behavior remains poorly understood. This study advances the understanding by investigating a cut slope failure in Yunnan through integrated field monitoring, laboratory testing, and numerical modeling. Key advancements include: (1) elucidating the coupled effect of structure degradation on both shear strength reduction and hydraulic conductivity alteration; (2) systematically quantifying the impact of rainfall temporal patterns beyond total rainfall; and (3) providing a mechanistic explanation for the critical role of early-peak rainfall. Mechanical and hydrological parameters were obtained from intact and remolded samples, with soil-water retention estimated via pedotransfer functions. A hydro-mechanical finite element model of the slope was constructed and calibrated using recorded rainfall, displacement data and failure surface. Six simulation scenarios were designed by combining three strength conditions (intact at natural water content, intact at saturation, remolded at natural water content) with two hydraulic conductivity values (intact vs. remolded). Additionally, four synthetic rainfall patterns, including uniform, peak-increasing, peak-decaying and bell-shaped rainfall, were simulated to evaluate their influence on pore water pressure development and slope stability. Results show remolding reduced hydraulic conductivity 4.7-fold, slowing wetting front advance and increasing shallow pore water pressure. Intact soil facilitated deeper drainage, elevating pressure near the soil-rock interface. Strength reduction induced by structure degradation (water saturating and remolding) enlarged the slope deformation zone by 1.5 times under same hydraulic conductivity. Simulations using saturated intact strength best matched field observations. The results from this specific slope indicate that strength parameters primarily control stability, while permeability affects deformation depth. Simulations considering different rainfall patterns indicate that slope stability depends more critically on the temporal distribution of rainfall intensity than on the total amount. Overall, peak-decaying rainfall led to the most rapid rise in pore water pressure, earliest instability and lowest failure rainfall threshold, whereas peak-increasing rainfall showed the opposite trends. Our findings outline a practical framework for assessing red clay slope stability during rainfall. This framework recommends using saturated intact strength parameters in stability analysis. It highlights the important influence of rainfall temporal patterns, especially those with an early peak, on failure timing and rainfall threshold. Full article

This study investigates a hybrid processing route that integrates localized fusion-based additive manufacturing and hot forging for the production of complex-shaped components, with emphasis on metallurgical integrity and mechanical performance. The DIN 8555 E6-UM-60 alloy, traditionally classified as martensitic and applied under severe wear conditions, exhibited atypical metallurgical behavior during hybrid processing, notably the consistent formation of chromium carbides under specific thermomechanical conditions. Metallographic analyses, microhardness measurements, thermographic monitoring, hot tensile tests, and room-temperature tensile tests were performed to establish correlations between microstructure, thermal history, and mechanical response. Specimens produced by additive manufacturing and subsequently hot forged showed a significant reduction in porosity, improved microstructural homogeneity, and partial retention of hardening phases, enabling discussion of recrystallization mechanisms, phase stabilization, and precipitation phenomena in martensitic alloys processed by additive manufacturing. Hot tensile tests revealed limited hot workability of the alloy, while room-temperature tensile tests led to premature fracture, with failure consistently initiating at pre-existing microcracks formed during the forging stage. Although detrimental, these microcracks provide valuable insight into critical processing conditions and ductility limits of the material. Overall, the hybrid route demonstrates strong potential for industrial applications, highlighting the importance of precise thermomechanical cycle control to mitigate defects and enhance structural reliability. Full article

The two-parameter Birnbaum–Saunders (B-S) distribution is widely applied across various fields due to its favorable statistical properties. This study aims to enhance the efficiency of modified moment estimators for the B-S distribution by systematically incorporating auxiliary non-sample information. To this end, we developed and analyzed a suite of estimation strategies, including restricted estimators, preliminary test estimators, and Stein-type shrinkage estimators. A pretest procedure was formulated to guide the decision on whether to integrate the non-sample information. The relative performance of these estimators was rigorously evaluated through an asymptotic distributional analysis, comparing their asymptotic distributional bias and risk under a sequence of local alternatives. The finite-sample properties were assessed via Monte Carlo simulation studies. The practical utility of the proposed methods is demonstrated through applications to two real-world datasets: failure times for mechanical valves and bone mineral density measurements. Both numerical results and theoretical analysis confirm that the proposed shrinkage-based techniques deliver substantial efficiency gains over conventional estimators. Full article

Forming tools adjustable by tensile elastic deformations offer opportunities for improved process control and reduced wear in high-volume metal forming processes such as ironing. However, the lack of tensile and fatigue data for hardened cold-work tool steels limits their broader adoption. This study investigates the mechanical performance of three tool steels—Vanadis^®4 Extra SuperClean, Vancron^® SuperClean, and Caldie^®—through uniaxial tensile and fatigue testing, supplemented by destructive static and fatigue/wear tests on specimens representative of an adjustable ironing punch. Non-coated specimens exhibited ultimate tensile strengths above 2700 MPa with approximately 2% plastic strain, while coated specimens fractured in a brittle manner between 1600–1900 MPa. Fatigue life at stress ranges between 1450–1750 MPa varied from several thousand to over four million cycles, with crack initiation linked to non-metallic inclusions and precipitates 10–30 $\mathsf{\mu }$m in size. Finite element simulations accurately linked failure observed in uniaxial tests to the component-level tests, confirming that first principal stress is a reliable predictor for punch failure. All punch specimens withstood ${10}^6$ cycles at diameter changes up to 140 $\mathsf{\mu }$m (4‰), with coated punches exhibiting minimal wear and non-coated ones showing localized surface damage. The findings support material and coating selection for adjustable forming tools and highlight opportunities for further optimization. Full article

With the explosive growth in the quantity of electrical equipment in distribution networks, traditional manual inspection struggles to achieve comprehensive coverage due to limited manpower and low efficiency. This has led to frequent equipment failures including partial discharge, insulation aging, and poor contact. These issues seriously compromise the safe and stable operation of distribution networks. Real-time monitoring and defect identification of their operation status are critical to ensuring the safety and stability of power systems. Currently, commonly used methods for defect identification in distribution network electrical equipment mainly rely on single-image or voiceprint data features. These methods lack consideration of the complementarity and interleaved nature between image and voiceprint features, resulting in reduced identification accuracy and reliability. To address the limitations of existing methods, this paper proposes distribution network electrical equipment defect identification based on multi-modal image voiceprint data fusion and channel interleaving. First, image and voiceprint feature models are constructed using two-dimensional principal component analysis (2DPCA) and the Mel scale, respectively. Multi-modal feature fusion is achieved using an improved transformer model that integrates intra-domain self-attention units and an inter-domain cross-attention mechanism. Second, an image and voiceprint multi-channel interleaving model is applied. It combines channel adaptability and confidence to dynamically adjust weights and generates defect identification results using a weighting approach based on output probability information content. Finally, simulation results show that, under the dataset size of 3300 samples, the proposed algorithm achieves a 8.96–33.27% improvement in defect recognition accuracy compared with baseline algorithms, and maintains an accuracy of over 86.5% even under 20% random noise interference by using improved transformer and multi-channel interleaving mechanism, verifying its advantages in accuracy and noise robustness. Full article