123 research outputs found

    Accelerating In-Browser Deep Learning Inference on Diverse Edge Clients through Just-in-Time Kernel Optimizations

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    Web applications are increasingly becoming the primary platform for AI service delivery, making in-browser deep learning (DL) inference more prominent. However, current in-browser inference systems fail to effectively utilize advanced web programming techniques and customize kernels for various client devices, leading to suboptimal performance. To address the issues, this paper presents the first in-browser inference system, nn-JIT.web, which enables just-in-time (JIT) auto-generation of optimized kernels for both CPUs and GPUs during inference. The system achieves this by using two novel web programming techniques that can significantly reduce kernel generation time, compared to other tensor compilers such as TVM, while maintaining or even improving performance. The first technique, Tensor-Web Compiling Co-Design, lowers compiling costs by unifying tensor and web compiling and eliminating redundant and ineffective compiling passes. The second technique, Web-Specific Lite Kernel Optimization Space Design, reduces kernel tuning costs by focusing on web programming requirements and efficient hardware resource utilization, limiting the optimization space to only dozens. nn-JIT.web is evaluated for modern transformer models on a range of client devices, including the mainstream CPUs and GPUs from ARM, Intel, AMD and Nvidia. Results show that nn-JIT.web can achieve up to 8.2x faster within 30 seconds compared to the baselines across various models

    Effects of Behavioral Interventions for Salt Reduction on Blood Pressure and Urinary Sodium Excretion: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

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    Hypertension is a prevalent cardiovascular condition, with excessive sodium intake being a significant risk factor. Various studies have investigated measures to reduce salt intake, including integrated lifestyle interventions and health education. However, the effectiveness of behavioral interventions focused solely on salt reduction remains unclear. This systematic review and meta-analysis aimed to investigate the effects of a behavioral intervention based on salt reduction on blood pressure and urinary sodium excretion. A comprehensive search of the Cochrane Central Register of Controlled Trials, EMBASE, PubMed, and Web of Science was conducted to identify relevant literature. Study and intervention characteristics were extracted for descriptive synthesis, and the quality of the included studies was assessed. A total of 10 studies, comprising 4,667 participants (3,796 adults and 871 children), were included. The interventions involved the provision of salt-restriction spoons or devices, salt-reduction education, self-monitoring devices for urinary sodium, and salt-reduction cooking classes. Meta-analysis results showed that behavioral interventions focused on salt reduction significantly reduced systolic blood pressure (SBP) (–1.17 mmHg; 95% CI, –1.86 to –0.49), diastolic blood pressure (DBP) (–0.58 mmHg; 95% CI, –1.07 to –0.08) and urinary sodium excretion (–21.88 mmol/24 hours; 95% CI, –32.12 to –11.64). These findings suggest that behavioral change interventions centered on salt reduction can effectively lower salt intake levels and decrease blood pressure levels. However, to enhance effectiveness, behavioral interventions for salt reduction should be combined with other salt-reduction strategies

    Ketogenic Diet as a Treatment for Super-Refractory Status Epilepticus in Febrile Infection-Related Epilepsy Syndrome

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    Background: Febrile infection-related epilepsy syndrome (FIRES) is a fatal epileptic encephalopathy associated with super-refractory status epilepticus (SRSE). Several treatment strategies have been proposed for this condition although the clinical outcomes are poor. Huge efforts from neurointensivists have been focused on identifying the characteristics of FIRES and treatment to reduce the mortality associated with this condition. However, the role of ketogenic diet (KD) in FIRES is not fully understood.Methods: We performed a retrospective review of patients who met the diagnostic criteria of FIRES, SRSE, and were treated with KD between 2015 and 2018 at the Department of Pediatrics, Xiangya Hospital of Central South University. The following data were recorded: demographic features, clinical presentation, anticonvulsant treatment, timing and duration of KD and follow-up information. Electroencephalography recordings were reviewed and analyzed.Results: Seven patients with FIRES were put on KD (5 via enteral route, and 2 via intravenous line) for SRSE in the PICU. The median age was 8. Four patients were male and 3 were female. Although patients underwent treatment with a median of 4 antiepileptic drugs and 2 anesthetic agents, the status epilepticus (SE) persisted for 7–31 days before KD initiation. After KD initiation, all patients achieved ketosis and SE disappeared within an average of 5 days (IQR 3.5), although there were minor side effects. In 6 patients, a unique pattern was identified in the EEG recording at the peak period. After initiation of KD, the number of seizures reduced, the duration of seizure shortened, the background recovered and sleep architecture normalized in the EEG recordings. The early initiation of KD (at the onset of SE) in the acute phase of patients decreased the mRS score in the subsequent period (p = 0.012, r = 0.866).Conclusions: The characteristic EEG pattern in the acute phase promoted timely diagnosis of FIRES. Our data suggest that KD may be a safe and promising therapy for FIRES with SRSE, and that early initiation of KD produces a favorable prognosis. Therefore, KD should be applied earlier in the course of FIRES. Intravenous KD can be an effective alternative route of administration for patients who may not take KD enterally

    End-of-treatment anti-HBs levels and HBeAg status identify durability of HBsAg loss after PEG-IFN discontinuation

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    BackgroundHepatitis B surface antigen (HBsAg) loss, namely, the functional cure, can be achieved through the pegylated interferon (PEG-IFN)-based therapy. However, it is an unignorable fact that a small proportion of patients who achieved functional cure develop HBsAg reversion (HRV) and the related factors are not well described.MethodsA total of 112 patients who achieved PEG-IFN-induced HBsAg loss were recruited. HBV biomarkers and biochemical parameters were examined dynamically. HBV RNA levels were assessed in the cross-sectional analysis. The primary endpoint was HRV, defined as the reappearance of HBsAg after PEG-IFN discontinuation.ResultsHRV occurred in 17 patients during the follow-up period. Univariable analysis indicated that hepatitis B e antigen (HBeAg) status, different levels of hepatitis B surface antibody (anti-HBs), and hepatitis B core antibody (anti-HBc) at the end of PEG-IFN treatment (EOT) were significantly associated with the incidence of HRV through using the log-rank test. Additionally, time-dependent receiver operating characteristic (ROC) analysis showed that the anti-HBs was superior to anti-HBc in predictive power for the incidence of HRV during the follow-up period. Multivariable Cox proportional hazard analysis found that anti-HBs ≥1.3 log10IU/L (hazard ratio (HR), 0.148; 95% confidence interval (CI), 0.044-0.502) and HBeAg negativity (HR, 0.183; 95% CI, 0.052-0.639) at EOT were independently associated with lower incidence of HRV. Cross-sectional analysis indicated that the HBV RNA levels were significantly correlated with the HBsAg levels in patients with HRV (r=0.86, p=0.003).ConclusionsEOT HBeAg negativity and anti-HBs ≥1.3 log10IU/L identify the low risk of HRV after PEG-IFN discontinuation

    Potential of Core-Collapse Supernova Neutrino Detection at JUNO

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    JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

    Detection of the Diffuse Supernova Neutrino Background with JUNO

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    As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

    Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

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    Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30M⊙M_{\odot} for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure
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