Search Results (301)

High-Voltage Fragmentation is a novel comminution technology that utilizes shock waves generated in water by nanosecond pulsed voltages with fast rise times (<500 ns) to fracture materials, offering significant advantages in energy efficiency and environmental friendliness. This study established an underwater pulsed discharge experimental platform to meet the fast-rise-time pulse parameter requirements. It analyzed the influence patterns of the needle-mesh electrode gap distance, the needle electrode tip radius of curvature, and water conductivity on shock wave pressure intensity and time-domain characteristics. The research found that the energy conversion efficiency of underwater pulsed discharge is significantly affected by the pre-breakdown process. The peak pressure, impulse, velocity, and rise slope of the shock wave exhibit a trend of initially increasing and then decreasing with increasing needle-mesh electrode gap distance and needle electrode tip radius of curvature. The maximum pressure intensity, maximum equivalent wave velocity, maximum rise slope, and shortest wavefront time occurred at a 20 mm gap distance and a needle electrode tip curvature radius of 0.45 mm. Both pressure intensity and propagation velocity initially increased and then decreased with increasing water conductivity, reaching their maxima at a water conductivity of 340 μS/cm. Water conductivity showed no significant effect on rise slope and wavefront time. Full article

Background/Objectives: Infection prevention and control (IPC) programs combine pathogen-targeted measures (e.g., admission screening) with hospital-wide standard precautions (e.g., hand hygiene, HH). We assessed temporal associations between screening, HH, antimicrobial stewardship (AMS), and hospital-level outcomes in a tertiary paediatric hospital. Methods: This study was a retrospective hospital-wide ecological time-series at the Children’s Memorial Health Institute. Annual aggregate data: 2011–2024 for screening, colonisation, and healthcare-associated infections (HAIs) with alert pathogens; 2016–2024 for antibiotic consumption (ATC J01, systemic antibacterials). Process indicators: number of screening tests and alcohol-based hand rub (ABHR) consumption per 1000 patient-days (PD). Outcomes: colonisations/HAIs per 1000 PD and defined daily doses (DDD) per 1000 PD overall and by class. Trends used linear regression and Spearman’s rank correlation. Results: Screening intensity increased from 39 to 150/1000 PD (slope +8.3/year; R² = 0.90; p < 0.001). Detected colonisation rose (2.5 → peak 8.05/1000 PD in 2023; slope +0.39; R² = 0.81; p < 0.001), while multidrug-resistant-organism (MDRO)-attributable HAIs remained low/stable (0.27–0.62/1000 PD; slope −0.014; p = 0.023). ABHR consumption increased from 26.1 to 78.0 L/1000 PD in 2020 (p < 0.001) and partially normalised to 60.0 in 2024 (>2 × baseline). Overall ATC J01 showed no long-term linear trend (~278–356 DDD/1000 PD; +2.57/year; p = 0.46), but class mix shifted: carbapenems, fluoroquinolones, and amoxicillin–clavulanate decreased; third/fourth-generation cephalosporins, piperacillin/tazobactam, and glycopeptides increased. Conclusions: In this tertiary paediatric setting, expansion of risk-based admission screening and sustained implementation of horizontal IPC measures were accompanied by increased detection of colonisation with alert pathogens, while MDRO-attributable HAIs remained low and stable at the hospital level. Over the same period, AMS activity coincided with a redistribution in antibiotic class use without a clear long-term reduction in total antibiotic consumption. These hospital-level findings are descriptive and hypothesis-generating; causal inference is limited by the ecological study design, and the heterogeneous, multispecialty structure of a tertiary paediatric centre. Full article

This study systematically verified the applicability and accuracy of the Probability Density Evolution Method (PDEM) in the probabilistic modeling of the dynamic response of anchored rock slopes under random seismic action through large-scale shaking table model tests. Across 144 sets of non-stationary random ground motions and 7 sets of white noise excitations, key response data such as acceleration, displacement, and changes in anchor axial force were collected. The PDEM was used to model the instantaneous probability density function (PDF) and cumulative distribution function (CDF), which were then compared with the results of normal distribution, Gumbel distribution, and direct sample statistics from multiple dimensions. The results show that the PDEM does not require a preset distribution form and can accurately reproduce the non-Gaussian, multi-modal, and time evolution characteristics of the response; in the reliability assessment of peak responses, its prediction deviation is much smaller than that of traditional parametric models; the three-dimensional probability density evolution cloud map further reveals the law governing the entire process of the response PDF from “narrow and high” in the early stage of the earthquake, “wide and flat” in the main shock stage, to “re-convergence” after the earthquake. The study confirms that the PDEM has significant advantages and engineering application value in the analysis of random seismic responses and the dynamic reliability assessment of anchored slopes. Full article

Investigating the characteristics and influencing mechanisms of urban vitality in mountainous cities can contribute to enhanced urban resilience, optimised resource allocation, and sustainable development. However, most existing studies have focused on static analyses at single spatial scales, making it difficult to fully reveal the evolutionary trends of urban vitality under complex topographic constraints or the spatiotemporal heterogeneity of its influencing factors. This study examines Guiyang, one of China’s fastest-growing cities, focusing on both its economic development and population growth. Based on social media data and geospatial big data from 2019 to 2024, the spatiotemporal permutation scan statistics (STPSS) model was employed to identify spatiotemporal areas of interest (ST-AOIs) and to analyse the spatial distribution and day-night dynamics of urban vitality across different phases. Furthermore, by incorporating transportation and topographic factors characteristic of mountainous cities, the multiscale geographically and temporally weighted regression (MGTWR) model was applied to reveal the driving mechanisms of urban vitality. The main findings are as follows: (1) Urban vitality exhibits a multi-center, clustered structure, gradually expanding from gentle to steeper slopes over time, with activity patterns shifting from an afternoon peak to an all-day distribution. (2) Significant differences in regional vitality resilience were observed: the core vitality areas exhibited stable ST-AOI spatial patterns, flexible temporal rhythms, and strong adaptability; the emerging vitality areas recovered quickly with low losses, while low-vitality areas showed slow recovery and insufficient resilience. (3) The density of commercial service facilities and the level of housing prices were continuously enhancing factors for vitality improvement, whereas the density of subway stations and the degree of functional mix played key roles in supporting resilience during the COVID-19 pandemic. (4) The synergistic effect between transportation systems and commercial facilities is crucial for forming high-vitality zones in mountainous cities. In contrast, reliance on a single factor tends to lead to vitality spillover. This study provides a crucial foundation for promoting sustainable urban development in Guiyang and other mountainous regions. Full article

Background/Objectives: Preoperative differentiation between oral squamous cell carcinoma (SCC) and minor salivary gland carcinoma (SGC) remains clinically challenging due to overlapping imaging characteristics. This study aimed to develop a diagnostic model based on quantitative dynamic contrast-enhanced MRI (qDCE-MRI) parameters to distinguish SCC from SGC prior to surgery. Methods: Patients with histopathologic confirmed SCC or minor SGC who underwent preoperative 3.0T qDCE-MRI were recruited. Clinical characteristics and pharmacokinetic parameters, including volume transfer constant (K^trans), reverse reflux rate constant (K_ep), volume fraction of extravascular extracellular space (V_e), plasma volume fraction (V_p), time to peak (TTP), maximum concentration (MAXConc), maximal slope (MAXSlope), and area under the concentration-time curve (AUCt), along with the apparent diffusion coefficient (ADC), were extracted. Univariate and multivariable logistic regression analyses were performed to identify independent discriminators. Diagnostic performance was assessed using receiver operating characteristic analysis, and model comparisons were conducted with the DeLong test. Interobserver agreement was evaluated using intraclass correlation coefficients (ICC). Results: All qDCE-MRI parameters demonstrated excellent interobserver agreement (ICC range, 0.82–0.94). Multivariable analysis identified K_ep (OR = 2620.172, p = 0.001), maximal slope (OR = 1.715, p = 0.024), and tumor location (OR = 5.561, p = 0.027) as independent predictors. The qDCE-MRI model achieved superior diagnostic performance compared with the clinical model (AUC: 0.945 vs. 0.747; p = 0.012). Conclusions: A qDCE-MRI–based model incorporating K_ep and MAXSlope was shown to provide excellent accuracy for preoperative differentiation between oral SCC and minor SGC. 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

Mountain treelines are among the most climate-sensitive ecosystems on Earth, yet their fine-scale structural and species level dynamics remain poorly resolved in the Himalayas. In particular, the absence of three-dimensional, crown level measurements have hindered the detection of structural thresholds and species turnover that often precede treeline shifts. To bridge this gap, we introduce UAV LiDAR—applied for the first time in the Hindu Kush Himalayas—to quantify canopy structure and tree species distributions across a steep treeline ecotone in the Manang Valley of central Nepal. High-density UAV-LiDAR data acquired over elevations of 3504–4119 m was used to quantify elevation-dependent changes in canopy stature and cover from a canopy height model derived from the 3D point cloud, while individual tree segmentation and species classification were performed directly on the 3D, height-normalized point cloud at the crown level. Individual trees were delineated using a watershed-based segmentation algorithm while tree species were classified using a random forest model trained on LiDAR-derived structural and intensity metrics, supported by field-validated reference data. Results reveal a sharply defined treeline characterized by an abrupt collapse in canopy height and cover within a narrow ~60–80 m vertical interval. Treeline “threshold” was quantified as a breakpoint elevation from a piecewise model of tree cover versus elevation, and the elevation span over which modeled cover and height distributions rapidly declined from forest values to near-zero. Segmented regression identified a distinct structural breakpoint near 3995 m elevation. Crown-level species predictions aggregated by elevation quantified an ordered turnover in dominance, with Pinus wallichiana most frequent at lower elevations, Abies spectabilis peaking mid-slope, and Betula utilis concentrated near the upper treeline. Species classification achieved high overall accuracy (>85%), although performance varied among taxa, with broadleaf Betula more difficult to discriminate than conifers. These findings underscore UAV LiDAR’s value for resolving sharp ecological thresholds, identifying elevation-driven simplification in forest structure, and bridging observation gaps in remote, rugged mountain ecosystems. Full article

Progressive rock slope destabilization poses significant geohazard risks, necessitating advanced monitoring frameworks to detect precursory failure signals. This study presents a comprehensive time-dependent evaluation of the displacement probability (CTEDP) model, which integrates GNSS-derived spatiotemporal data with multi-parameter reliability indices to enhance landslide risk assessment. Five monitoring points on a destabilizing rock slope were analyzed from mid-November 2024 to early January 2025 using kinematic metrics (velocity, acceleration, and jerk), statistical measures (e.g., moving averages), and reliability indices (RI₀, RI₁, RI₂, and RI_combined). Point 1 exhibited the most critical behavior, with a cumulative displacement of ~60 mm, peak velocities of 34.5 mm/day, and accelerations up to 1.15 mm/day². The CTEDP for active points converged to 0.56–0.61, indicating sustained high risk. The 90th percentile displacement threshold was 58.48 mm for Point 1. Sensitivity analysis demonstrated that the GNSS-derived reliability indices dominated the RI_combined variance (r = 0.999, explaining 99.8% of variance). The first- and second-order reliability indices (RI₁, RI₂) at Point 1 exceeded the 60-index threshold, indicating a transition to Class B (“Low Risk—Trend Surveillance Required”) status, while other points showed coherent deformation of 37–45 mm. Results underscore the framework’s ability to integrate spatiotemporal displacement, kinematic precursors, and statistical variability for early-warning systems. This approach bridges gaps in landslide prediction by accounting for spatial heterogeneity and nonlinear geomechanical responses. Full article

The absence of a recognizable P wave in an electrocardiogram (ECG) is a critical indicator for the diagnosis of atrial fibrillation (AF). An algorithm capable of distinguishing between physiological and pathological states in a short period of time could serve as a valuable tool for timely and effective diagnosis, even in a home setting. To achieve this goal, a deterministic algorithm is proposed. The Fantasia Database and the AF Termination Challenge Database were used for training the model. Subsequently, for the test session, a one-minute recording was extracted from the Autonomic Aging Dataset and the Long-Term AF Database. After band-pass filtering, characteristic points such as R-peaks and P waves were extracted. The R-peak detection algorithm was compared with the gold standard Pan-Tompkins, obtaining a p-value > 0.05 on the Fantasia Database, which means that there is no statistical difference between them. Subsequently derived features such as duration, amplitude, subtended area, and P wave slope have been used to discriminate healthy subjects from AF patients. The P-wave slope emerged as the most effective feature, achieving a classification accuracy of 100% and 96% for the training and test sets, respectively. This algorithm thus represents a significant advancement as it achieves a performance comparable to other deterministic methods based on P wave analysis using only one-minute recordings, thereby enabling accurate diagnosis in a shorter time frame. Full article

Background/Objectives: Motion artifacts significantly distort fluorescence measurements during surgical perfusion assessment, potentially leading to incorrect clinical decisions. This study evaluates the efficacy of automated motion compensation (MC) in quantitative indocyanine green (q-ICG) imaging to improve the accuracy of perfusion assessment. Methods: Frames from ICG perfusion assessment during 17 pancreaticoduodenectomies were analyzed. Regions of interest (ROIs) were systematically placed on each frame series, and automated MC was applied to track tissue movement. Performance was evaluated by comparing MC with surgeon-adjusted placement using multiple image quality metrics and analyzing perfusion metrics on time–intensity curves. Principal Component Analysis (PCA) was applied to explore whether image patterns could distinguish between successful and unsuccessful motion compensation. Results: Automated motion compensation successfully corrected motion artifacts in 67.5% of frame sequences, achieving comparable performance to surgeon-guided adjustments. PCA demonstrated clear separation between sufficient and insufficient corrections (AUC = 0.80). At the population level, MC did not significantly change perfusion slope (t(59) = 1.60, p = 0.11) or time-to-peak (Tmax; t(58) = 0.81, p = 0.42). Bland–Altman analysis showed a mean bias of −0.54 (SD = 3.32) for slope and 24.95 (SD = 238.40) for Tmax. At the individual level, 86.7% of slope and 79.7% of Tmax values differed by ≥10% after MC, with mean absolute percentage changes of 108.5% (median 37.8%) and 431.5% (median 65.9%), respectively. Conclusions: MC effectively reduces motion artifacts in fluorescence-guided perfusion assessment. By improving the precision of ICG-derived parameters, this technology enhances measurement reliability and represents an enabler for accurate intraoperative perfusion quantification. Full article

Background: Amateur runners may benefit from combining respiratory muscle training (RMT) with resistance or aerobic modalities, but direct comparisons are scarce. This study compared different RMT-based combinations on pulmonary function, respiratory muscle strength, and whole-body exercise capacity. Methods: In this randomized four-arm trial, 48 amateur runners were allocated equally to stand-alone RMT, RMT plus upper-limb resistance (RMT + ULRT), RMT plus lower-limb resistance (RMT + LLRT), or RMT plus aerobic exercise (RMT + AET). All groups completed supervised sessions three times per week for six weeks. Pulmonary function (forced vital capacity [FVC], forced expiratory volume in one second [FEV₁], FEV₁/FVC), respiratory muscle strength (maximal inspiratory and expiratory pressures, MIP and MEP), and cardiopulmonary exercise test indices (peak oxygen uptake [VO₂peak], VE/VCO₂ slope) were assessed before and after training using standardized spirometry, mouth-pressure measurements, and treadmill cardiopulmonary exercise testing (CPET). Pre–post changes within groups and the overall between-group differences were evaluated using standard parametric methods. Results: All four interventions were associated with improvements in at least one respiratory or cardiopulmonary domain. FVC and FEV₁ tended to improve more in the resistance-combination groups, whereas the FEV₁/FVC ratio increased with RMT alone and when combined with resistance. MIP increased in the RMT, RMT + ULRT, and RMT + LLRT groups, and MEP increased across all groups. VO₂peak rose in every group, while the VE/VCO₂ slope improved only when RMT was combined with upper- or lower-limb resistance or aerobic exercise. Between-group differences in change scores were not statistically significant and did not clearly favor any single regimen. Conclusions: In amateur runners, six weeks of RMT-based programs are feasible and associated with domain-specific improvements in lung function, respiratory muscle strength, and exercise capacity. Because between-group differences in change scores were not statistically significant and the sample size was modest, these findings should be considered exploratory and may inform hypothesis generation regarding the use of different RMT combinations in future, larger trials. Full article

MCSGP (Multicolumn Countercurrent Solvent Gradient Purification) with AutoPeak control is increasingly used for production of synthetic peptides and oligonucleotides at scale, requiring guidance on how to perform regulatory-compliant Process Validation. This work, for the first time, presents a Process Characterization and Process Performance Qualification approach to support regulatory filings of therapeutics produced using MCSGP, based on the relevant Process Validation guidelines. The approach was demonstrated for the purification of synthetic Bivalirudin. During Process Characterization, MCSGP process parameter criticality was investigated, and the gradient slope was classified as a critical process parameter to be controlled within tighter limits. As a further outcome of Process Characterization, a supervision strategy was developed and verified in four Process Performance Qualification MCSGP runs. The strategy was backed by AutoPeak, a UV-based Process Analytical Technology. The Process Validation/Process Performance Qualification (PPQ) runs not only confirmed the selected control and supervision strategy but also the advantages of MCSGP/AutoPeak as a continuous manufacturing technology, including the fully automatic operation and the reduction in in-process control sampling and Process Mass Intensity (PMI). In the presented case, the PMI was reduced from around 5200 to 1400 kg/kg, the number of in-process controls (IPCs) was reduced from 81 IPCs (60 cm i.D. column batch) per kg to 3.2 IPCs per kg (2 × 30 cm i.D. column MCSGP), while yield (gross-to-gross) increased from 57% to 62%, comparing MCSGP/AutoPeak to a process with extensive side-cut recycling. Full article

The correct assessment of slope stability under seismic loading requires not only the magnitude of ground acceleration to be considered but also its frequency content. In this study, a hybrid finite element/limit equilibrium (FEM–LEM) approach is used to quantify how the dominant frequency of harmonic ground motion affects the dynamic factor of safety, FSdyn, of a large homogeneous slope. Dynamic stresses are computed in QUAKE/W and transferred to SLOPE/W, where a FS calculation is performed at each time step to obtain FS_dyn(t). A design-of-experiment framework is applied to explore combinations of peak ground acceleration and dominant frequency. The results show that FS_dyn is much more sensitive to dominant frequency than to acceleration amplitude within the analyzed ranges, with the strongest reduction in stability occurring with the low input frequencies. Comparison with conventional pseudo-static analysis demonstrates that pseudo-static factors of safety can significantly overestimate stability at low dominant frequencies, and frequency thresholds are identified above which pseudo-static results become closer to the hybrid solution for the studied configuration. Although the model is intentionally simplified (homogeneous, drained conditions and single-frequency excitation), the findings highlight that dominant frequency is a decisive control parameter and should not be neglected in the seismic assessment of large earth structures. Full article

Asphalt binders that perform exceptionally well in resisting both rutting and cracking are highly desirable for withstanding the combined effects of extreme low temperatures and heavy vehicle loads. This work highlights the benefits of softening oils on the cracking performance of styrene–butadiene–styrene-modified asphalt (SBSMA). Additionally, the inherent correlations between cracking-performance parameters of binders and mixtures were thoroughly analyzed. A bio-based oil (bio-oil) and a petroleum-based oil (re-refined engine oil bottom, REOB) were selected as the softening oils. The benefit provided by softening oils was evaluated using various rheological indices, while the adverse effects of oxidative aging on cracking resistance were also considered. The cracking properties at intermediate temperatures were characterized by the modified Glover–Rowe (M G–R) parameter, δ_{8967 kPa}, and fatigue life (N_f). The low-temperature cracking properties of binders were evaluated by stiffness and m-value. The indirect tensile asphalt cracking (IDEAL-CT) test was conducted utilizing the CT-index and post-peak slope to estimate the fracture properties of the mixtures. The oxidative aging of binder and mixture samples was simulated and carried out based on lab aging methods; meanwhile, the carbonyl index obtained from the Fourier transform infrared (FTIR) scanning was used to track and evaluate the aging level of binders. The results show that the cracking performance could be greatly improved by the application of softening oils. Meanwhile, the bio-oils were found to operate with much higher efficiency than REOB, since the oil modification index (OMI) result showed that bio-oils exhibited four to six times the efficiency of REOB, in terms of improving the stress relaxation property. The correlations proved that the cracking-related parameters shared an inherent relationship with R² above 0.85, while these parameters consistently declined as the binder aged. The cracking performance of the mixtures at intermediate temperatures was mainly governed by the fatigue life of the binder, whereas thermal cracking performance was highly associated with the binder’s relaxation property. Full article

Our study introduces a surface electromyography (sEMG)-based Cheonjiin speller system developed to assist individuals with restricted hand mobility. The interface incorporates a directional control framework—comprising up, down, left, right, and select commands—integrated with a Korean keyboard layout to enable efficient and accessible text input. Two-channel surface EMG signals were recorded from the rectus femoris and gastrocnemius muscles at a sampling rate of 200 Hz using an EMG acquisition module. The signals were processed in real time using notch and bandpass filtering, followed by full-wave rectification. To decode user intent, three physiologically interpretable time-domain features—root mean square (RMS), slope sign change (SSC), and peak amplitude—were extracted and subsequently used for classification. The Cheonjiin speller was implemented in Python 3.10.8 and operated through directional cursor navigation. System performance was quantitatively evaluated in two experiments: in Experiment 1, recognition accuracy for five discrete commands reached an average of 90.0%, while Experiment 2, involving continuous Korean word and sentence input, achieved an average accuracy of 88.65%. Across both experimental conditions, the system attained an average information transfer rate (ITR) of 96.19 bits/min, confirming efficient real-time communication capability. The results demonstrate that high recognition performance can be achieved using simple, low-computation features without deep learning models, confirming the feasibility of real-time implementation in resource-limited environments. Overall, the proposed speller system exhibits high operability, accessibility, and practical usability in constrained conditions and holds potential for integration into augmentative and alternative communication (AAC) systems for users with motor impairments. Moreover, its lightweight architecture, minimal computational load, and flexible directional control structure make it adaptable to a wide range of assistive and wearable technology applications. Full article