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Nanosecond-level time-domain coding metasurface for radar signal generation
Youth with high support needs, families and social services: a relation of resources and gaps
Correction: The influencing factors of health status among low-income individuals living alone in Wuxi, China
Global warming amplifies wildfire health burden and reshapes inequality
Convergent flow-mediated mesenchymal force drives embryonic foregut constriction and splitting
Crustal velocity structure for Northern Egypt using ambient noise tomography
Cause-specific mortality following sustained virologic response in hepatitis C patients treated with direct-acting antivirals: a standardized mortality ratio analysis
Abstract Direct-acting antivirals (DAAs) achieve high sustained virologic response (SVR) rates in patients with hepatitis C virus (HCV) infection. However, the long-term prognosis and cause-specific mortality post-SVR remain unclear. This study analyzed 1753 HCV-infected patients without a history of hepatocellular carcinoma treatment who achieved SVR with DAAs and did not develop cancer. Liver disease-related (LDR) and non-LDR mortalities were assessed using age- and sex-adjusted standardized mortality ratios (SMRs) compared with the general population. During a mean follow-up of 59.2 months, 122 patients died. The SMR for all-cause mortality was 1.050 ( p = 0.588). The SMRs for LDR and non-LDR mortalities were 7.819 ( p < 0.001) and 0.566 ( p < 0.001), respectively. The SMR for extrahepatic malignancy-related mortality was significantly lower at 0.593 ( p = 0.013), whereas cardiovascular disease (CVD)-related mortality did not differ significantly at 0.884 ( p = 0.554). These findings were consistent regardless of age, sex, liver cirrhosis presence, diabetes, or chronic kidney disease. Overall mortality after SVR in patients with HCV was comparable with that of the general population. Nevertheless, LDR mortality remained significantly elevated, whereas non-LDR and extrahepatic malignancy-related mortalities were significantly reduced. These results underscore the importance of continued liver disease surveillance post-SVR, while CVD management should parallel that of the general population.
Chiral valley edge states based on Dirac mass engineering
Seamless integration for enhanced seizure prediction using HybridConvMobileNet on Typhoon HIL
Abstract Real-time seizure prediction is essential for enabling timely interventions that significantly improve patient outcomes. Therefore, in this present work, we have introduced HybridConvMobileNet , a novel hybrid model that integrates 1D convolutional neural networks (CNN) with the MobileNet model to achieve efficient and accurate seizure prediction. The proposed model uses 1D Short-Time Fourier Transform (STFT) coefficients from pre-processed EEG data as input features. In the proposed algorithm, the developed 1D CNN framework captures the critical spatial features from frequency-domain EEG data, while MobileNet network enhances computational efficiency and speed, making the model highly appropriate for real-time applications. The efficacy of the developed model is corroborated on the Children’s Hospital Boston-Massachusetts Institute of Technology (CHB-MIT) and Siena benchmark datasets. On the CHB-MIT dataset, the model reached 99.70% accuracy, 99.31% sensitivity, and a 99.43% F1-score, while on the Siena dataset, it reached 99.67% accuracy, 99.08% sensitivity, and a 99.57% F1-score, outperforming eight existing methods across both datasets. Furthermore, real-time implementation on the Typhoon HIL emulator with embedded C2000 microcontrollers demonstrated a low mean detection latency of 0.1 to 1 second, underscoring its potential for clinical applications in seizure monitoring and control.