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An iterative evaluation method for testability of avionics electronic system in field is proposed to improve the accuracy of testability evaluation and solve the problems of few testability evaluation samples and low evaluation accuracy of avionics electronic system after aircraft service. Firstly, the idea of field testability evaluation based on Bayesian framework is expounded. Secondly, according to the prior information, the maximum entropy method, combined with PSO algorithm, is used to find hyper-parameters in the prior distribution of fault detection rate, and hyper-parameters consistency check is carried out. Then, the posterior distribution is obtained by Bayes formula, and the iterative estimation results of fault detection rate are obtained. Combined with the example, the comparison and analyses between this method and existing method further proved the correctness and advantages of the proposed method.

Introduction: Sepsis-associated acute kidney injury (SA-AKI) is strongly associated with poor prognosis. We aimed to build a machine learning (ML)-based clinical model to predict 1-year mortality in patients with SA-AKI. Methods: Six ML algorithms were included to perform model fitting. Feature selection was based on the feature importance evaluated by the SHapley Additive exPlanations (SHAP) values. Area under the receiver operating characteristic curve (AUROC) was used to evaluate the discriminatory ability of the prediction model. Calibration curve and Brier score were employed to assess the calibrated ability. Our ML-based prediction models were validated both internally and externally. Results: A total of 12,750 patients with SA-AKI and 55 features were included to build the prediction models. We identified the top 10 predictors including age, ICU stay and GCS score based on the feature importance. Among the six ML algorithms, the CatBoost showed the best prediction performance with an AUROC of 0.813 and Brier score of 0.119. In the external validation set, the predictive value remained favorable (AUROC = 0.784). Conclusion: In this study, we developed and validated a ML-based prediction model based on 10 commonly used clinical features which could accurately and early identify the individuals at high-risk of long-term mortality in patients with SA-AKI. [ABSTRACT FROM AUTHOR]

Background: Substantial focus has been placed on atrial fibrillation (AF) treatment and associated stroke prevention rather than preventing AF itself. We employed Mendelian randomization (MR) approach to examine the causal relationships between 50 modifiable risk factors (RFs) and AF. Methods: Instrumental variables for genetically predicted exposures were derived from corresponding genome‐wide association studies (GWASs). Summary‐level statistical data for AF were obtained from a GWAS meta‐analysis (discovery dataset, N = 1,030,836) and FinnGen (validation dataset, N = 208,594). Univariable and multivariable MR analyses were performed, primarily using inverse variance weighted method with a series of robust sensitivity analyses. Results: Genetic predisposition to insomnia, daytime naps, apnea, smoking initiation, moderate to vigorous physical activity and obesity traits, including body mass index, waist–hip ratio, central and peripheral fat/fat‐free mass, exhibited significant associations with an increased risk of AF. Coffee consumption and ApoB had suggestive increased risks. Hypertension (odds ratio (OR) 95% confidence interval (CI): 5.26 (4.42, 6.24)), heart failure (HF) (OR 95% CI, 4.77 (2.43, 9.37)) and coronary artery disease (CAD) (OR 95% CI: 1.20 (1.16, 1.24)) were strongly associated with AF, while college degree, higher education attachment and HDL levels were associated with a decreased AF risk. Reverse MR found a bidirectional relationship between genetically predicted AF and CAD, HF and ischemic stroke. Multivariable analysis further indicated that obesity‐related traits, systolic blood pressure and lower HDL levels independently contributed to the development of AF. Conclusions: This study identified several lifestyles and cardiometabolic factors that might be causally related to AF, underscoring the importance of a holistic approach to AF management and prevention. [ABSTRACT FROM AUTHOR]

Aims The aim of this study was to investigate the outcomes of catheter ablation (CA) in preventing arrhythmic events among patients with symptomatic Brugada syndrome (BrS) who declined implantable cardioverter defibrillator (ICD) implantation. Methods and results A total of 40 patients with symptomatic BrS were included in the study, of which 18 refused ICD implantation and underwent CA, while 22 patients received ICD implantation. The study employed substrate modification (including endocardial and epicardial approaches) and ventricular fibrillation (VF)-triggering pre-mature ventricular contraction (PVC) ablation strategies. The primary outcomes were a composite endpoint consisting of episodes of VF and sudden cardiac death during the follow-up period. The study population had a mean age of 43.8 ± 9.6 years, with 36 (90.0%) of them being male. All patients exhibited the typical Type 1 BrS electrocardiogram pattern, and 16 (40.0%) were carriers of an SCN5A mutation. The Shanghai risk scores were comparable between the CA and the ICD groups (7.05 ± 0.80 vs. 6.71 ± 0.86, P = 0.351). Ventricular fibrillation–triggering PVCs were ablated in 3 patients (16.7%), while VF substrates were ablated in 15 patients (83.3%). Epicardial ablation was performed in 12 patients (66.7%). During a median follow-up of 46.2 (17.5–73.7) months, the primary outcomes occurred more frequently in the ICD group than in the CA group (5.6 vs. 54.5%, Log-rank P = 0.012). Conclusion Catheter ablation is an effective alternative therapy for improving arrhythmic outcomes in patients with symptomatic BrS who decline ICD implantation. Our findings support the consideration of CA as an alternative treatment option in this population. [ABSTRACT FROM AUTHOR]

Passivation is commonly used to suppress current collapse in AlGaN/GaN HEMTs. However, the conventional PECV-fabricated SiNx passivation layer is incompatible with the latest process, like the "passivation-prior-to-ohmic" method. Research attention has therefore turned to high-temperature passivation schemes. In this paper, we systematically investigated the differences between the SiNx/GaN interface of two high-temperature passivation schemes, MOCVD-SiNx and LPCVD-SiNx, and investigated their effects on the ohmic contact mechanism. By characterizing the device interface using TEM, we reveal that during the process of MOCVD-SiNx, etching damage and Si diffuses into the semiconductor to form a leakage path and reduce the breakdown voltage of the AlGaN/GaN HEMTs. Moreover, N enrichment at the edge of the ohmic region of the LPCVD-SiNx device indicates that the device is more favorable for TiN formation, thus reducing the ohmic contact resistance, which is beneficial to improving the PAE of the device. Through the CW load-pull test with drain voltage VDS = 20V, LPCVD-SiNx devices obtain a high PAE of 66.35%, which is about 6% higher than MOCVD-SiNx devices. This excellent result indicates that the prospect of LPCVD-SiNx passivation devices used in 5G small terminals will be attractive. [ABSTRACT FROM AUTHOR]