Search Results (590)

Background: Vascular calcification has been highlighted as a prognostic factor for perioperative thrombosis but a protective factor for late restenosis in lower limb peripheral artery disease (LLPAD). The aim of this study was to investigate the association between calcification and twelve-month primary patency in patients with stenting of the common femoral artery (CFA) and its bifurcation for atheromatous stenosis. Materials/Methods: This single-center retrospective study analyzed consecutive limbs (n = 90) that underwent CFA stenting for symptomatic lesions between January 2018 and January 2023. Calcification was assessed using dedicated computed tomography angiography analysis software (EndoSize; Therenva), with blinded evaluation of volume (mm³) and density (Hounsfield Units) across three anatomically distinct zones: proximal CFA (Zone 1); distal CFA (Zone 2); and bifurcation segments (Zone 3). The primary endpoint was twelve-month primary patency, defined as a peak systolic velocity ratio (PSVR) < 2.4 on duplex ultrasound without target lesion revascularization. Secondary endpoints included predictors of restenosis using multivariable logistic regression. Results: Ninety cases of CFA stenting for LLPAD (lower limb peripheral artery disease) were analyzed. A total of 78.9% of CFA lesions were treated for claudication and 21.1% for critical limb-threatening ischemia (CLTI). Lesions were distributed as Azema types I (1%), II (43%), and III (56%). At twelve-month follow-up, primary patency (PSVR < 2.4) was achieved in 77.4% of limbs. Patent CFA stenting demonstrated significantly higher median calcification density in Zone 2 compared to those with restenosis (1122 [IQR: 903–1248] vs. 858 [788–987] HU; p = 0.006; q = 0.021 after false discovery rate correction). ROC curve analysis identified a density threshold of 800 HU with a 76% reduction in restenosis risk (OR 0.24; 95% CI: 0.08–0.72; p = 0.011). Bootstrap validation (1000 replications) confirmed threshold stability at 821 HU (95% CI: 656–990 HU). Conclusions: In this exploratory study, dense calcification (≥800 HU) in the distal CFA appears to be protective against twelve-month restenosis following stenting. These findings suggest that calcification density may serve as a valuable predictor for patient selection and procedural planning in CFA interventions. Full article

Background: Rowing is a highly demanding endurance sport, requiring simultaneous work of approximately 70% of the body’s muscle mass and the combined contribution of aerobic and anaerobic energy systems. Objective: This study aimed to analyze the cardiorespiratory responses and performance characteristics of elite junior male and female rowers during maximal effort over 2000 m on a rowing ergometer. Methods: Fifteen junior rowers (six males aged 15–17 and nine females aged 15–18) participated in the study. Anthropometric data (body height, weight, and body surface area) were recorded. All participants performed a maximal 2000 m test on a Concept2 D-model ergometer. Throughout the test, oxygen uptake (VO₂), carbon dioxide production (VCO₂), heart rate, and ventilation parameters were continuously measured. Performance and physiological data were analyzed in three intensity zones, defined by ventilatory thresholds (VT1–VT3), as well as at peak exercise. Results: Significant anthropometric differences were observed between genders. In terms of performance, males completed the 2000 m test significantly faster than females (208.83 ± 87.66 s vs. 333.78 ± 97.51 s, p = 0.0253). Relative VO₂ at peak exercise was higher in males (58.73 ± 5.25 mL·kg⁻¹·min⁻¹) than females (48.32 ± 6.09 mL·kg⁻¹·min⁻¹, p = 0.0046). In most cardiorespiratory parameters, males outperformed females significantly, except for heart rate and ventilatory equivalents. Ranking analysis revealed that higher VO₂max values were generally associated with a better placement in both genders, though this relationship was not perfectly linear. Performance time was negatively correlated with VO₂Peak (r = −0.8286; p < 0.001), rVO₂Peak (r = −0.6781; p < 0.01), and O₂P_Peak (r = −0.7729; p < 0.01). Conclusions: The findings confirm significant gender differences in anthropometric and cardiorespiratory characteristics of elite junior rowers and reinforce VO₂max as a key determinant of performance. Yet, deviations from a direct VO₂max–rank correlation highlight the influence of tactical, psychological, and biomechanical factors. Future research should provide practical recommendations for monitoring performance and tailoring training to optimize adaptation and long-term athlete development. Full article

To address low training efficiency and poor reconstruction in traditional K Singular Value Decomposition (KSVD) for compressive sensing of shock wave signals, this study proposes an improved algorithm, DH-KSVD, integrating dynamic pruning and hybrid coding. The dynamic pruning mechanism eliminates redundant atoms according to their contributions and adaptive thresholds, while incorporating residual features to enhance dictionary compactness and training efficiency. The hybrid sparse constraint integrates the sparsity of ${\ell }_0$-Orthogonal Matching Pursuit (OMP) with the noise robustness of ${\ell }_1$-Least Absolute Shrinkage and Selection Operator (LASSO), dynamically adjusting their relative weights to enhance both coding quality and reconstruction stability. Experiments on typical shock wave datasets show that, compared with Discrete Cosine Transform (DCT), KSVD, and feature-based segmented dictionary methods (termed CC-KSVD), DH-KSVD reduces average training time by 46.4%, 31%, and 13.7%, respectively. At a Compression Ratio (CR) of 0.7, the Root Mean Square Error (RMSE) decreases by 67.1%, 65.7%, and 36.2%, while the Peak Signal-to-Noise Ratio (PSNR) increases by 35.5%, 39.8%, and 11.8%, respectively. The proposed algorithm markedly improves training efficiency and achieves lower RMSE and higher PSNR under high compression ratios, providing an effective solution for compressing long-duration, transient shock wave signals. Full article

Accurate quantification of minor mineral phases is important in Powder X-Ray Diffraction (PXRD) and Rietveld phase quantification. The precise limit of quantification for the various phases is rarely considered but rather approximated to 0.2–2 wt% by applying a global minimum weight percentage threshold. This approximation often leads to false positive or false negative phase quantity, jeopardizing the trustworthiness of the analytic method in general. In this work (1) we propose a dynamic and adaptable false positive filtering method for Rietveld Quantitative X-ray diffraction (QXRD) based on a phase-specific signal-to-noise ratio referred to as “Phase-SNR”; (2) we introduce the method baptized “Phase Guard” which is implemented in the software HighScore Plus. Phase Guard is based on peaks counting statistics and it automatically adapts to different mineral scattering powers, different mineral crystallinity, instrumental configuration and measurement time. Its applicability and benefits are demonstrated with several examples in cement and mining applications. The adoption of Phase Guard is especially beneficial for industrial black-box solutions, where all “probable” phases are included in the model, even when they are absent from the sample. Phase Guard eliminates false positives, it reduces the likelihood of false negatives, and it is an essential tool to answer the question “what is the limit of quantification for Rietveld analysis?” Full article

Background: Chimeric antigen receptor (CAR) T-cell therapy has revolutionized treatment of relapsed/refractory large B-cell lymphoma (LBCL), but its administration is often complicated by cytokine release syndrome (CRS). Interleukin-6 (IL-6) is widely used to monitor CRS, though its clinical value diminishes after tocilizumab administration. We aimed to evaluate serum amyloid A (SAA), a dynamic acute-phase reactant, as a treatment-independent biomarker of inflammation and toxicity in CAR-T recipients. Methods: This retrospective study included 43 adults with LBCL treated with axicabtagene ciloleucel. SAA and other inflammatory markers were assessed from lymphodepletion through day +11 post-infusion. CRS and ICANS were graded per ASTCT criteria. Statistical analyses included Mann–Whitney U tests, Spearman’s correlation, and ROC curve analysis to evaluate predictive performance. Results: SAA levels peaked at day +4 and normalized by day +11, displaying wave-like kinetics. Levels were significantly higher in patients with any-grade CRS at early timepoints but showed no association with ICANS. SAA correlated strongly with CRP, suPAR, sST2, fibrinogen, ferritin, procalcitonin, and IL-6. Compared to IL-6, SAA was more predictive of CRS at day +2 and +4, and unaffected by tocilizumab. Baseline SAA also correlated with the mEASIX score, suggesting linkage to endothelial stress. Non-responders at 3-month PET had higher baseline SAA than responders (196.0 vs. 17.7 mg/L, p = 0.036), with ROC analysis yielding an AUC of 0.74 and an optimal threshold of 79.8 mg/L. Conclusions: SAA is a robust and dynamic marker of systemic inflammation, with potential utility in both toxicity monitoring and response prediction in the CAR-T setting. Its independence from IL-6 modulation positions it as a promising biomarker for future integration into clinical algorithms. Full article

Purpose: While peak oxygen uptake ($\stackrel{.}{\mathrm{V}}$O_2peak) is the gold standard method for assessing exercise tolerance, there is a tendency for underestimation. Several other cardiopulmonary exercise testing (CPET) variables may provide additive prognostic value beyond $\stackrel{.}{\mathrm{V}}$O_2peak alone. The aim of this study was to examine if alternative CPET indices of exercise tolerance are (a) impaired in people with T2D and (b) independently associated with measures of cardiovascular structure and function measured via echocardiography and cardiac MRI. Methods: Participants with type 2 diabetes (T2D) and healthy controls underwent cardiac magnetic resonance imaging, transthoracic echocardiography, and a CPET. Multiple linear regression was used to determine the relationship between indices of exercise tolerance and markers of cardiovascular structure and function. Results: A total of 84 people with T2D and 36 healthy volunteers were included in the analysis. All CPET outcomes were worse in those with T2D vs. the controls. Three CPET outcomes were associated with markers of cardiovascular structure and function: $\stackrel{.}{\mathrm{V}}$O₂ recovery with mean aortic distensibility (β = 0.218, p = 0.049); heart rate recovery with early filling velocity on transmitral Doppler/early relaxation velocity (β = −0.270, p = 0.024), left ventricular mass/volume ratio (β = −0.248, p = 0.030) and mean aortic distensibility (β = 0.222, p = 0.029); and $\stackrel{.}{\mathrm{V}}$O₂ at the ventilatory threshold with myocardial perfusion reserve (β = 0.273, p = 0.018). Perspective: These lesser-used CPET indices could be used to identify which people with T2D are at elevated risk of progression to symptomatic heart failure. However, larger longitudinal studies are required to confirm these findings and their potential clinical application. Full article

This paper introduces a new class of probability distributions, termed the generated log exponentiated polynomial (GLEP) family, designed to enhance flexibility in modeling complex real financial data. The proposed family is constructed through a novel cumulative distribution function that combines logarithmic and exponentiated polynomial structures, allowing for rich distributional shapes and tail behaviors. We present comprehensive mathematical properties, including useful series expansions for the density, cumulative, and quantile functions, which facilitate the derivation of moments, generating functions, and order statistics. Characterization results based on the reverse hazard function and conditional expectations are established. The model parameters are estimated using various frequentist methods, including Maximum Likelihood Estimation (MLE), Cramer–von Mises (CVM), Anderson–Darling (ADE), Right Tail Anderson–Darling (RTADE), and Left Tail Anderson–Darling (LEADE), with a comparative simulation study assessing their performance. Risk analysis is conducted using actuarial key risk indicators (KRIs) such as Value-at-Risk (VaR), Tail Value-at-Risk (TVaR), Tail Variance (TV), Tail Mean Variance (TMV), and excess function (EL), demonstrating the model’s applicability in financial and insurance contexts. The practical utility of the GLEP family is illustrated through applications to real and simulated datasets, including house price dynamics and insurance claim sizes. Peaks Over Random Threshold Value-at-Risk (PORT-VaR) analysis is applied to U.K. motor insurance claims and U.S. house prices datasets. Some recommendations are provided. Finally, a comparative study is presented to prove the superiority of the new family. Full article

Xinjiang is a critical wind energy region in China. This study characterizes extreme wind speed (EWS) events in Xinjiang by using ERA5 reanalysis (1979–2023) and station observations (2022–2023). Through k-means clustering and wind power density classification, four distinct regions and representative nodes were identified, aligned with the “Three Mountains and Two Basins” topography: Region #1 (eastern wind-rich corridor), Region #2 (Tarim Basin, west–east increasing wind power density), Region #3 (northern valleys), and Region #4 (mountainous areas with weakest wind power density). Peaks-over-threshold analysis revealed 10~30-year return levels varying regionally, with 10-year return level for Node #1 reaching Beaufort Scale 11 but only Scale 6 for Node #4. Since 2001, EWS occurrences increased, with Nodes #2–4 showing doubled 10-year event occurrences in 2012–2023. Events exhibit consistent afternoon peaks and spring dominance (except Node #2 with summer maxima). Such long-term trends and diurnal and seasonal preferences of EWS could be partly explained by diverging synoptic drivers: orographic effects and enhanced pressure gradients (Node #1 and #3) associated with Ural blocking and polar vortex shifts, both showing intensification trends; thermal lows in the Tarim Basin (Node #2) accounting for their summer prevalence; boundary-layer instability that leads to localized wind intensification (Node #4). The results suggest the necessity of region-specific forecasting strategies for wind energy resilience. Full article

Optimizing the allocation of hydropower resources is essential for aligning high-quality economic growth with China’s carbon neutrality goals. Due to constraints such as market segmentation and government regulation, the resource allocation function of the Chinese market has not been effectively utilized, which leads to hydropower resources being allocated inefficiently. In the digital age, it is valuable to investigate whether digital economic development can rectify the misallocation of hydropower resources and whether the corrective effects exhibit temporal dynamics and spatial heterogeneity. Accordingly, this study employs panel data collected from 30 provincial-level administrative regions in China from 2000 to 2023, employing the production function method combined with a counterfactual analysis framework for quantifying the degree of hydropower resource mismatch. Additionally, panel vector autoregression models and panel threshold regression utilized for discussing spatio-temporal effects of digital economic development on hydropower resource mismatch. Empirical results demonstrate that digital economic development significantly curbs hydropower resource misallocation, albeit with a discernible time lag. When the digital economy experiences a positive impulse shock, its impact on the hydropower resources mismatch emerges in the first lag period, peaks in the second lag period, and then stabilizes. Secondly, the corrective impact of digital economic development on hydropower resources mismatch is contingent upon the level of regional industrialization, which is more pronounced in regions with higher levels of industrialization. In conclusion, this paper offers evidence-based policy recommendations to facilitate the localized implementation of digital economy policies and enhance the efficiency of hydropower resources allocation. Full article

Motion perception is a fundamental function of the tactile system, essential for object exploration and manipulation. While human studies have largely focused on discrete or pulsed stimuli with staggered onsets, many natural tactile signals are continuous and rhythmically patterned. Here, we investigate whether phase differences between “simultaneously” presented, “continuous” amplitude-modulated vibrations can induce the perception of motion across fingertips. Participants reliably perceived motion direction at modulation frequencies up to 1 Hz, with discrimination performance systematically dependent on the phase lag between vibrations. Critically, trial-level confidence reports revealed the lowest certainty for anti-phase (180°) conditions, consistent with stimulus ambiguity as predicted by the mathematical framework. I propose two candidate computational mechanisms for tactile motion processing. The first is a conventional cross-correlation computation over the envelopes; the second is a probabilistic model based on the uncertain detection of temporal reference points (e.g., envelope peaks) within threshold-defined windows. This model, despite having only a single parameter (uncertainty width determined by an amplitude discrimination threshold), accounts for both the non-linear shape and asymmetries of observed psychometric functions. These results demonstrate that the human tactile system can extract directional information from distributed phase-coded signals in the absence of spatial displacement, revealing a motion perception mechanism that parallels arthropod systems but potentially arises from distinct perceptual constraints. The findings underscore the feasibility of sparse, phase-coded stimulation as a lightweight and reproducible method for conveying motion cues in wearable, motion-capable haptic devices. Full article

To address the issues of image quality degradation and file size expansion encountered during reversible data hiding (RDH) of JPEG images, a JPEG reversible data hiding algorithm based on block smoothness estimation and optimal zero coefficient selection is proposed. Firstly, a block smoothness estimation strategy is designed based on the number of zero coefficients and non-zero quantisation table values within DCT blocks, prioritising DCT blocks with higher smoothness for information embedding. Subsequently, under a given embedding payload, an optimal zero coefficient selection strategy is introduced. Blocks are partitioned into embedding regions and non-embedding regions based on a preset position threshold T. Within embedding regions, the frequency of zero coefficients at different positions across all blocks is statistically analysed, with embedding prioritised at positions exhibiting the highest zero coefficient frequency to enhance embedding efficiency. Concurrently, by setting positive and negative displacement gaps to constrain the modification range of non-zero coefficients, invalid shifts are minimised. This further enhances visual quality while controlling file expansion. Experimental results demonstrate that, compared to existing algorithms, the proposed method achieves a peak signal-to-noise ratio improvement of 0.75 to 3.62 dB under fixed embedding capacity. File expansion is reduced by 1038 to 2243 bits, whilst enabling fully reversible image restoration. Full article

Background/Objectives: Knee osteoarthritis (OA) is a major cause of pain and functional disability worldwide, leading to a growing interest in more durable and less invasive therapies. Micro-fragmented adipose tissue (MFAT) injections have emerged as a promising frontier in regenerative therapies using mesenchymal stem cells (MSCs). This study assessed the safety and effectiveness of MFAT injections for symptomatic knee OA while investigating the duration of treatment effects. Methods: This longitudinal study screened patients with symptomatic Kellgren-Lawrence (KL) grade II-IV knee OA who received single-dose MFAT injections. Outcomes were assessed using the Knee injury and Osteoarthritis Outcome Score (KOOS) subscales at baseline, 3, 6, and 12 months. A linear mixed effects model was performed to explore how age, BMI, sex, and OA severity influence outcomes. Results: Among 39 evaluable patients, mean baseline KOOS was 46.5 (SD 18.1). KOOS scores improved significantly across all subscales, peaking at six months and remaining higher than baseline at 12 months. Improvements exceeded clinically meaningful thresholds, including KL grades IV. Female patients reported significantly worse overall outcomes than male patients (p < 0.05). Minor self-limiting synovitis was reported in 18% of cases, and no severe adverse events were observed. Conclusions: MFAT infiltration may represent a safe, minimally invasive option to improve symptoms and delay surgery in patients with knee OA, including those with advanced disease. These findings highlight the potential role of MFAT as part of the treatment algorithm for knee OA, although strategies to sustain long-term benefits and confirmatory trials are needed. Full article

The subtropical transitional zone of China exhibits highly complex climatic conditions and diverse forest ecosystems, making it a critical region for understanding vegetation–water interactions. This study employed the Thermal Dissipation Probe (TDP) method to monitor sap flow in three typical forest types—evergreen broad-leaved forest, bamboo forest (Dendrocalamus latiflorus), and Chinese fir (Cunninghamia lanceolata)—in a subtropical transitional watershed in southern China. The aims were to quantify seasonal and annual variations in sap flow, to examine the effects of environmental drivers, and to analyze the hysteretic responses between sap flow and the drivers. The main findings were as follows: (1) bamboo forests exhibited significantly higher sap flow density than evergreen broad-leaved and fir forests at both annual and seasonal scales, though the overall transpiration of bamboo forests was lower than the others due to its limited sapwood area; (2) sap flow was positively correlated with potential evapotranspiration, solar radiation (Ra), vapor pressure deficit (VPD), air temperature, and soil temperature, while it was negatively correlated with relative humidity, atmospheric pressure, soil moisture, and precipitation; (3) Ra and VPD were identified as the dominant drivers of sap flow variations, with nonlinear increases that leveled off once thresholds were reached; (4) clear hysteresis patterns were observed, with sap flow peaks consistently lagging behind Ra but occurring earlier than VPD. These results advance our understanding of forest water-use strategies in the subtropical transitional zone and provide a scientific basis for improving water resource management and ecosystem sustainability in this region. Full article

Highway congestion is a persistent issue, and dynamically activating emergency lanes offers a promising mitigation strategy. However, traditional fixed-time or single-threshold methods often fail to balance traffic efficiency and safety. This paper introduces a dynamic optimization framework that integrates a Kriging surrogate model with the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to identify optimal activation strategies. By simultaneously minimizing total travel time (efficiency) and the duration vehicles spend in unsafe proximity (safety), our method generates a set of Pareto-optimal solutions. We calibrated and validated the model using real-world highway data. The results are compelling: the optimized compromise strategy reduced total travel time by 20.5% compared to having no activation, while keeping safety risks within an acceptable range. The use of a Kriging surrogate model sped up the optimization process by approximately 20 times compared to direct simulation, achieving a prediction accuracy of 97.8%. The optimal strategies characteristically involve opening the emergency lane at the downstream bottleneck during peak congestion and closing it promptly as traffic eases. This research provides a robust, efficient, and practical decision-support tool for intelligent traffic management, offering a clear pathway to safer and less congested highways. Full article

This paper aims to unveil the symmetry–asymmetry transition mechanisms in transient fault waveforms of offshore wind power AC/DC transmission systems, addressing the critical limitation of traditional simulation methods of the fact that they cannot characterize the dynamic evolution of system symmetry, such as static impedance adjustment failing to capture transient asymmetry caused by parameter imbalance or converter control. It proposes a fault waveform simulation approach integrating mechanism analysis, scenario extraction, and model optimization. Key contributions include clarifying the quantitative links between key system parameters like submarine cable capacitance and inductance and symmetry–asymmetry characteristics, defining the transient decay rate oscillation frequency and voltage peak as core indicators to quantify symmetry breaking intensity; classifying typical fault scenarios into a symmetry-breaking type with synchronous three-phase imbalance and a persistent asymmetry type with zero-sequence and negative-sequence distortion based on symmetry evolution dynamics and revising grid-connection test indices such as lowering the low-voltage ride-through threshold and specifying the voltage type for different test objectives; and constructing a simplified embedded RLC second-order model with symmetry–asymmetry constraints to reproduce the whole process of symmetric steady state–fault symmetry breaking–recovery symmetry reconstruction. Simulation results verify the method’s effectiveness, with symmetry indicator reproduction errors ≤ 5% and asymmetric feature fitting goodness R² ≥ 0.92, which confirms that the method can effectively reveal the symmetry–asymmetry mechanisms of offshore wind power fault transients and provides reliable technical support for improving offshore wind power fault simulation accuracy and grid-connection test reliability, laying a theoretical basis for the grid-connection testing of offshore wind turbines and promoting the stable operation of offshore wind power systems. Full article