Search Results (788)

Continuous blood pressure (BP) monitoring provides valuable insight into the body’s dynamic cardiovascular regulation across various physiological states such as physical activity, emotional stress, postural changes, and sleep. Continuous BP monitoring captures different variations in systolic and diastolic pressures, reflecting autonomic nervous system activity, vascular compliance, and circadian rhythms. This enables early identification of abnormal BP trends and allows for timely diagnosis and interventions to reduce the risk of cardiovascular diseases (CVDs) such as hypertension, stroke, heart failure, and chronic kidney disease as well as chronic stress or anxiety disorders. To facilitate continuous BP monitoring, we propose an AI-powered estimation framework. The proposed framework first uses an expert-driven feature engineering approach that systematically extracts physiological features from photoplethysmogram (PPG)-based arterial pulse waveforms (APWs). Extracted features include pulse rate, ascending/descending times, pulse width, slopes, intensity variations, and waveform areas. These features are fused with demographic data (age, gender, height, weight, BMI) to enhance model robustness and accuracy across diverse populations. The framework utilizes a Tab-Transformer to learn rich feature embeddings, which are then processed through an ensemble machine learning framework consisting of CatBoost, XGBoost, and LightGBM. Evaluated on a dataset of 1000 subjects, the model achieves Mean Absolute Errors (MAE) of 3.87 mmHg (SBP) and 2.50 mmHg (DBP), meeting British Hypertension Society (BHS) Grade A and Association for the Advancement of Medical Instrumentation (AAMI) standards. The proposed architecture advances non-invasive, AI-driven solutions for dynamic cardiovascular health monitoring. Full article

A novel unified progressive hybrid censoring is introduced to combine both progressive and hybrid censoring plans to allow flexible test termination either after a prespecified number of failures or at a fixed time. This work develops both frequentist and Bayesian inferential procedures for estimating the parameters, reliability, and hazard rates of the inverted Nadarajah–Haghighi lifespan model when a sample is produced from such a censoring plan. Maximum likelihood estimators are obtained through the Newton–Raphson iterative technique. The delta method, based on the Fisher information matrix, is utilized to build the asymptotic confidence intervals for each unknown quantity. In the Bayesian methodology, Markov chain Monte Carlo techniques with independent gamma priors are implemented to generate posterior summaries and credible intervals, addressing computational intractability through the Metropolis–-Hastings algorithm. Extensive Monte Carlo simulations compare the efficiency and utility of frequentist and Bayesian estimates across multiple censoring designs, highlighting the superiority of Bayesian inference using informative prior information. Two real-world applications utilizing rare minerals from gold and diamond durability studies are examined to demonstrate the adaptability of the proposed estimators to the analysis of rare events in precious materials science. By applying four different optimality criteria to multiple competing plans, an analysis of various progressive censoring strategies that yield the best performance is conducted. The proposed censoring framework is effectively applied to real-world datasets involving diamonds and gold, demonstrating its practical utility in modeling the reliability and failure behavior of rare and high-value minerals. Full article

Background: In advanced heart failure patients implanted with a fully magnetically levitated HeartMate 3 (HM3) Abbott left ventricular assist device (LVAD), it is unknown how the role of the LVAD outpatient clinic may affect the long-term survival after hospital discharge. Our objective is to share our standardized protocol for outpatient care, to describe the role of the LVAD outpatient clinic in postoperative long-term care after LVAD implantation, and to report survival. Methods: We retrospectively reviewed all patients implanted with HM3 LVAD in our institute between September 2015 and January 2025. Patients who received HeartWare Ventricular Assist Device (HVAD) and HeartMate 2 LVAD devices were excluded from our study, to ensure a homogenous cohort focusing on the latest and the only currently used LVAD device generation. We included a total of 48 patients. After LVAD patients are discharged from our center, they are followed in our outpatient clinic in 3-month intervals. During visits, bloodwork, EKG, wound inspection, and echocardiography are performed in addition to LVAD analysis. The role of the outpatient clinic is to detect early signs of deterioration or problems and act accordingly to prevent serious complications. Results: Thirty-three patients (68.7%) are still alive in 2025; two patients (4.2%) had a successful heart transplantation; and thirty-one patients (64.5%) are still on LVAD support. There were 210 total patient years of support. The mean time on device is 4.4 years. During the follow-up period we noticed 15 deaths (31.3%). Notably, there was no technical device-related death. Kaplan–Meier analysis estimated an overall survival rate of 97.9%, 92.8%, 83.7%, and 51.1% at 1, 2, 4, and 8 years, respectively. Conclusion: Strict control of patients after discharge in an outpatient clinic is essential for the long-term survival of these patients. A well-structured outpatient program is of utter importance to avoid LVAD-related complications and should be a cornerstone for the treatment, especially in non-transplant centers. Full article

In order to improve the reliability evaluation accuracy of a new generation of substation relay protection equipment under small-sample failure rate data, a Generative Adversarial Network (GAN) model based on the Adaptive Spiral Flying Sparrow Search Algorithm (ASFSSA) to optimize the Long Short-Term Memory (LSTM) network is proposed. Because of the adaptability of LSTM for processing time series, LSTM is embedded into the GAN, and the LSTM optimized by ASFSSA is used as the generator of GAN. The trained model is used to expand the original data samples, and the least squares method is used to estimate the distribution model parameters, to obtain the reliability function of the relay protection equipment, and to predict the operating life of the equipment. The results show that compared with other methods, the correlation coefficient of the expanded data samples is closer to the original data, and the life estimation of the equipment is more accurate. The model can be used as a reference for reliability assessment and acceptance testing of the new generation of substation relay protection equipment. Full article

Background/Objectives: We aimed to identify the factors associated with clinically important changes in quality of life (QoL) of real-world heart failure (HF) patients. Methods: This is a single-centre, prospective cohort study including 419 patients at an HF clinic between January 2013 and February 2020. QoL was assessed regularly using Minnesota Living with Heart Failure Questionnaire (MLHFQ). We used five nested linear mixed-effects models to account for QoL measurements between patients and within-patient. Models were adjusted for time, sociodemographic factors, comorbidities, self-care adherence, and HF severity factors. Results: Median age was 78 years, 54.4% of patients were female, and 49.6% had left ventricle ejection fraction ≥ 50%. At baseline, 62.5% of patients were New York Heart Association (NYHA) class II. Median N-terminal-pro-B type natriuretic peptide level was 1454 pg/mL. Mean MLHFQ total score at baseline was 25 points (95%CI: 22.97–27.60). Having an implanted cardiac resynchronization therapy-pacemaker (CRT-P) was associated with moderate to large improvement in QoL (−13.55 points, 95%CI: −22.45–−4.65). NYHA class II and estimated glomerular filtration rate < 30 mL/min/1.73 m² were associated with small to moderate QoL deterioration (9.74 points, 95%CI: 6.74–12.75 and 5.82 points, 95%CI: 1.17–10.47, respectively). NYHA classes III or IV and a recent HF hospitalization were associated with large to very large QoL deterioration (28.39 points, 95%CI: 23.82–32.96; 60.59 points, 95%CI: 34.46–86.72; and 26.91 points, 95%CI: 21.80–32.03, respectively). Conclusions: CRT-P implantation, NYHA class and HF hospitalization are associated with the most clinically important QoL changes. Full article

To address traditional methods’ limitations in neglecting the interaction between random shock loads and progressive degradation, as well as failure correlations, this study proposes a dynamic reliability framework integrating Gamma processes, homogeneous Poisson processes (HPP), and mixed Copula functions. The framework develops a wind turbine gearbox reliability model under shock–degradation coupling while quantifying failure correlations. Gamma processes characterize continuous degradation, with parameters estimated from P-S-N curves. Based on stress–strength interference theory, random shocks within damage thresholds are integrated to form a coupled reliability model. A Gumbel–Clayton–Frank mixed Copula with a multi-layer nested algorithm quantifies failure correlations, with correlation parameters estimated via the RSS principle and genetic algorithms. Validation using a 2 MW gearbox’s planetary gear-stage system covers four scenarios: natural degradation, shock–degradation coupling, and both scenarios with failure correlations. The results show that compared to independent assumptions, the model accelerates reliability decline, increasing failure rates by >37%. Relative to natural degradation-only models, failure rates rise by >60%, validating the model’s effectiveness and alignment with real-world operational conditions. Full article

Adenovirus is an important respiratory virus that causes severe diseases in immunocompromised patients. Data on its impact in immunocompetent patients are relatively limited. We conducted a territory-wide retrospective study on adult patients hospitalized for respiratory tract infections caused by adenovirus or influenza viruses in Hong Kong between 1 January 2016 and 30 June 2023. Inpatient mortality, severe respiratory failure (SRF), secondary bacterial pneumonia and acute kidney injury (AKI) were compared. The risk factors for these outcomes in patients hospitalized for adenovirus respiratory tract infections were assessed. Overall, 41,206 and 528 patients were hospitalized for influenza and adenovirus respiratory tract infections, respectively. Patients with respiratory tract infections due to adenoviruses showed significantly higher risk of inpatient mortality, SRF, secondary bacterial pneumonia and AKI compared to seasonal influenza. Medical comorbidities including cardio-pulmonary diseases, end-stage kidney disease requiring dialysis, and a lower estimated glomerular filtration rate were robust independent risk factors for inpatient mortality and serious respiratory outcomes in adenovirus respiratory tract infections. Adults hospitalized for adenoviruses respiratory tract infections had a significantly higher risk of inpatient mortality and adverse outcomes than adults infected with seasonal influenza. Medical comorbidities are important risk factors for severe adenovirus infections in adult patients. Full article

This paper introduces a novel and flexible class of continuous probability distributions, termed the Alpha Power Survival Ratio-X (APSR-X) family. Unlike many existing transformation-based families, the APSR-X class integrates an alpha power transformation with a survival ratio structure, offering a new mechanism for enhancing shape flexibility while maintaining mathematical tractability. This construction enables fine control over both the tail behavior and the symmetry properties, distinguishing it from traditional alpha power or survival-based extensions. We focus on a key member of this family, the two-parameter Alpha Power Survival Ratio Exponential (APSR-Exp) distribution, deriving essential mathematical properties including moments, quantile functions and hazard rate structures. We estimate the model parameters using eight frequentist methods: the maximum likelihood (MLE), maximum product of spacings (MPSE), least squares (LSE), weighted least squares (WLSE), Anderson–Darling (ADE), right-tailed Anderson–Darling (RADE), Cramér–von Mises (CVME) and percentile (PCE) estimation. Through comprehensive Monte Carlo simulations, we evaluate the estimator performance using bias, mean squared error and mean relative error metrics. The proposed APSR-X framework uniquely enables preservation or controlled modification of the symmetry in probability density and hazard rate functions via its shape parameter. This capability is particularly valuable in reliability and survival analyses, where symmetric patterns represent balanced risk profiles while asymmetric shapes capture skewed failure behaviors. We demonstrate the practical utility of the APSR-Exp model through three real-world applications: economic (tax revenue durations), engineering (mechanical repair times) and medical (infection durations) datasets. In all cases, the proposed model achieves a superior fit over that of the conventional alternatives, supported by goodness-of-fit statistics and visual diagnostics. These findings establish the APSR-X family as a unique, symmetry-aware modeling framework for complex lifetime data. Full article

Background/Objectives: Impaired kidney function significantly increases mortality in recipients of implantable cardioverter defibrillators (ICDs). However, in the landmark studies evaluating ICDs and cardiac resynchronization therapy with a defibrillator (CRT-D) for the treatment of heart failure (HF) with a reduced ejection fraction (HFrEF), patients with Chagas cardiomyopathy (CC) have been underrepresented. This study aimed to determine whether kidney dysfunction has the same negative impacts on patients with ICDs or CRT-Ds and CC. Methods: We prospectively followed patients with CC and left ventricular ejection fractions (LVEFs) of ≤40% who underwent ICD or CRT-D implantation and had at least one prior creatinine measurement. The primary outcome was the survival rate during follow-up. Variables with a p of <0.10 from the univariate analysis were selected for inclusion in the Cox regression model. Results: A total of 343 patients were enrolled, with a median follow-up duration of 777 days. The mean age was 60.2 (±11.2) years. Fifty percent of patients were observed to have a New York Heart Association (NYHA) functional class of III, and the median left ventricular ejection fraction (LVEF) was 27% (22–32). Overall mortality events occurred in 113 (32.9%) participants during follow-up. Although the estimated glomerular filtration rate (eGFR) was significantly associated with survival in the univariate analysis [HR 0.98 (CI 95% 0.98–0.99), p = 0.007], it did not retain significance in the multivariate model [HR 0.99 (0.98–1.00), p = 0.138], which was adjusted for age, gender, atrial fibrillation (AF), body mass index (BMI), and the use of digoxin, furosemide, anticoagulants, and LVEF. Conclusions: Unlike other cardiomyopathies, impaired eGFR was not an independent predictor of mortality in this cohort of CC patients undergoing ICD or CRT-D implantation, possibly due to the distinctive pathophysiological mechanisms of the disease. These findings suggest that clinicians should not be discouraged from recommending CIEDs in patients with CC and moderately impaired kidney function, although further studies are warranted to assess outcomes in those with advanced CKD. Full article

Partial discharge (PD) in insulators will not only lead to the gradual degradation of insulation performance but even cause power system failure in serious cases. Because there is strong noise interference in the field, it is difficult to accurately locate the position of the PD source. Therefore, this paper proposes a three-dimensional spatial localization method of the PD source with a four-element ultra-high-frequency (UHF) array based on improved wavelet packet dynamic threshold denoising and the $G_{xx}-\beta$ generalized cross-correlation algorithm. Firstly, considering the field noise interference, the PD signal is decomposed into sub-signals with different frequency bands by the wavelet packet, and the corresponding wavelet packet coefficients are extracted. By using the improved threshold function to process the wavelet packet coefficients, the PD signal with low distortion rate and high signal-to-noise ratio (SNR) is reconstructed. Secondly, in order to solve the problem that the amplitude of the first wave of the PD signal is small and the SNR is low, an improved weighting function, $G_{xx}-\beta$, is proposed, which is based on the self-power spectral density of the signal and is adjusted by introducing an exponential factor to improve the accuracy of the first wave arrival time and time difference calculation. Finally, the influence of different sensor array shapes and PD source positions on the localization results is analyzed, and a reasonable arrangement scheme is found. In order to verify the performance of the proposed method, simulation and experimental analysis are carried out. The results show that the improved wavelet packet denoising algorithm can effectively realize the separation of PD signal and noise and improve the SNR of the localization signal with low distortion rate. The improved $G_{xx}-\beta$ weighting function significantly improves the estimation accuracy of the time difference between UHF sensors. With the sensor array designed in this paper, the relative localization error is 3.46%, and the absolute error is within 6 cm, which meets the requirements of engineering applications. Full article

Visual tracking from the unmanned aerial vehicle (UAV) perspective has been at the core of many low-altitude remote sensing applications. Most of the aerial trackers follow “tracking-by-detection” paradigms or their temporal-context-embedded variants, where the only visual appearance cue is encompassed for representation learning and estimating the spatial likelihood of the target. However, the variation of the target appearance among consecutive frames is inherently unpredictable, which degrades the robustness of the temporal context-aware representation. To address this concern, we advocate extra visual motion exhibiting predictable temporal continuity for complete temporal context-aware representation and introduce a dual-stream tracker involving explicit heterogeneous visual tracking experts. Our technical contributions involve three-folds: (1) high-order temporal context-aware representation integrates motion and appearance cues over a temporal context queue, (2) bidirectional cross-domain refinement enhances feature representation through cross-attention based mutual guidance, and (3) consistent decision-making allows for anti-drifting localization via dynamic gating and failure-aware recovery. Extensive experiments on four UAV benchmarks (UAV123, UAV123@10fps, UAV20L, and DTB70) illustrate that our method outperforms existing aerial trackers in terms of success rate and precision, particularly in occlusion and fast motion scenarios. Such superior tracking stability highlights its potential for real-world UAV applications. Full article

Background/Objectives: Antibiotic management of hospitalized penicillin-allergic patients (PAPs) is associated with prolonged hospital stays, adverse reactions and treatment failure, resulting in increased healthcare costs. This study aimed to estimate the cost-effectiveness of beta-lactam desensitization (DES) in the management of PAPs. Methods: A cost-effectiveness analysis was performed using a probabilistic model with 1000 s-order Monte Carlo simulations. Hospital costs (in 2025 Euros) and effectiveness outcomes (cure and survival rates) were derived from a Spanish retrospective case–control study conducted between 2015 and 2022, which included 56 PAPs (14 in the desensitization group [DES] and 42 in the control group without DES [NDES]; ratio 1:3), and collected healthcare costs per patient. Results: The incremental cost of the DES group was EUR 37,805 (95% CI: EUR 2023–EUR 126,785), with a 100% probability of incurring additional costs compared to the NDES group. The cure rate was 16.5% higher in the DES group (95% CI: 13.3–20.0%), and the estimated gain in life-years per patient (LYG) was 1.42 (95% CI: 1.15–1.73) versus NDES. The cost per life-year gained (LYG) with DES versus NDES was EUR 24,618 ± EUR 19,535 (95% CI: EUR 1755–EUR 73,488). The probability that DES would be cost-effective (cost per LYG < EUR 25,000 and <EUR 30,000) was 61.1% and 100%, respectively. Conclusions: According to this analysis, DES appears to be a cost-effective option for managing PAPs. These findings should be confirmed in clinical studies with larger sample sizes. Full article

As the population of adults with congenital heart disease (ACHD) continues to grow, a significant and often underrecognized complication is the development of cardiorenal syndrome (CRS)—a complex, bidirectional interaction between cardiac and renal dysfunction. While CRS has been extensively studied in acquired heart failure, its manifestations and implications in ACHD remain insufficiently understood. Emerging data suggest that renal dysfunction is highly prevalent in ACHD, with significant associations to adverse outcomes regardless of cardiac lesion type or functional status. This review explores CRS within three key physiologic categories in ACHD: patients with a systemic right ventricle, those with a subpulmonary right ventricle, and those with Fontan circulation. Each subgroup presents unique hemodynamic challenges that affect renal perfusion, filtration pressure, and systemic congestion, contributing to both acute and chronic renal impairment. The utility of renal biomarkers such as albuminuria, cystatin C, and estimated glomerular filtration rate (eGFR) is emphasized, alongside the importance of early detection and multidisciplinary management. Heart failure therapy tailored to congenital anatomy, neurohormonal modulation, and careful volume control remain the cornerstones of treatment, while transplantation strategies must consider the potential for irreversible end-organ damage. Given the profound implications of CRS on quality of life and survival, a comprehensive understanding of its pathophysiology and management in ACHD is critical to optimizing long-term outcomes in this increasingly complex patient population. Full article

In lifetime testing, the failure times of highly reliable products under normal usage conditions are often impractically long, making direct reliability assessment impractical. To overcome this, step-stress partially accelerated life testing is employed to reduce testing time while preserving data quality. This paper develops a Bayesian model based on Type II censored data, assuming that item lifetimes follow the Topp–Leone inverted Kumaraswamy distribution, a flexible alternative to classical lifetime models due to its ability to capture various hazard rate shapes and to model bounded and skewed lifetime data more effectively than traditional models observed in real-world reliability data. Bayes estimators of the model parameters and acceleration factor are derived under both symmetric (balanced squared error) and asymmetric (balanced linear exponential) loss functions using informative priors. The novelty of this work lies in the integration of the Topp–Leone inverted Kumaraswamy distribution within the Bayesian step-stress partially accelerated life testing framework, which has not been explored previously, offering improved modeling capability for complex lifetime data. The proposed method is validated through comprehensive simulation studies under various censoring schemes, demonstrating robustness and superior estimation performance compared to traditional models. A real-data application involving COVID-19 mortality data further illustrates the practical relevance and improved fit of the model. Overall, the results highlight the flexibility, efficiency, and applicability of the proposed Bayesian approach in reliability analysis. Full article

Background: GLP-1 receptor agonists (GLP-1 RAs) lower glucose and reduce cardiovascular events in type 2 diabetes, with noted renal benefits. Few studies directly compare GLP-1 RAs. This study aims to compare the effects of semaglutide and dulaglutide on renal function decline and proteinuria reduction in diabetic patients. Methods: The present study was conducted at Wanfang Hospital, Taipei Medical University. Diabetic patients using either semaglutide or dulaglutide for more than 1 year in the outpatient department from 1 January 2022 to 30 September 2024 were enrolled retrospectively. The outcome events in the present study included a decline in the estimated glomerular filtration rate (eGFR), an increase in the urine albumin–creatinine ratio (UACR), and patient death. Results: A total of 268 patients on dulaglutide and 747 on semaglutide were included. Baseline eGFR levels were similar in both groups. After 12 months, eGFR levels did not significantly decline in both groups. However, the dulaglutide group showed significantly higher UACR increases than the semaglutide group (p < 0.01). More death events also occurred in the dulaglutide group (p < 0.01). Multivariate logistic regression revealed a higher risk of UACR increase with dulaglutide (p < 0.01). Subgroup analysis found dulaglutide associated with higher UACR in patients younger than 60, males, those with hypertension, without heart failure, those using angiotensin receptor blockers, biguanides, and statins, and those not using sodium-glucose cotransporter-2 inhibitors. Conclusions: Dulaglutide and semaglutide had comparable effects on slowing eGFR decline. However, dulaglutide was less effective in reducing UACR, particularly in the subgroups mentioned above. Full article