Mining and Predicting Smart Device User Behavior

Three types of user behavior are mined in this paper: application usage, smart device usage and periodicity of user behavior. When mining application usage, the application installation, most frequently used applications and application correlation are analyzed. The application usage is long-tailed. When mining the device usage, the mean, variance and autocorrelation are calculated both for duration and interval. Both the duration and interval are long-tailed but only duration satisfies power-law distribution. Meanwhile, the autocorrelation of both duration and interval is weak, which makes predicting user behavior based on adjacent behavior not so reasonable in related works. Then DFT (Discrete Fourier Transform) is utilized to analyze the periodicity of user behavior and results show that the most obvious periodicity is 24 hours, which is in agreement with related works. Based on the results above, an improved user behavior predicting model is proposed based on Chebyshev inequality. Experiment results show that the performance is good in accurate rate and recall rate

Rice black-streaked dwarf virus P6 self-interacts to form punctate, viroplasm-like structures in the cytoplasm and recruits viroplasm-associated protein P9-1

<p>Abstract</p> <p>Background</p> <p><it>Rice black-streaked dwarf virus </it>(RBSDV), a member of the genus <it>Fijivirus </it>within the family <it>Reoviridae</it>, can infect several graminaceous plant species including rice, maize and wheat, and is transmitted by planthoppers. Although several RBSDV proteins have been studied in detail, functions of the nonstructural protein P6 are still largely unknown.</p> <p>Results</p> <p>In the current study, we employed yeast two-hybrid assays, bimolecular fluorescence complementation and subcellular localization experiments to show that P6 can self-interact to form punctate, cytoplasmic viroplasm-like structures (VLS) when expressed alone in plant cells. The region from residues 395 to 659 is necessary for P6 self-interaction, whereas two polypeptides (residues 580-620 and 615-655) are involved in the subcellular localization of P6. Furthermore, P6 strongly interacts with the viroplasm-associated protein P9-1 and recruits P9-1 to localize in VLS. The P6 395-659 region is also important for the P6-P9-1 interaction, and deleting any region of P9-1 abolishes this heterologous interaction.</p> <p>Conclusions</p> <p>RBSDV P6 protein has an intrinsic ability to self-interact and forms VLS without other RBSDV proteins or RNAs. P6 recruits P9-1 to VLS by direct protein-protein interaction. This is the first report on the functionality of RBSDV P6 protein. P6 may be involved in the process of viroplasm nucleation and virus morphogenesis.</p

Graph-Driven Generative Models for Heterogeneous Multi-Task Learning

We propose a novel graph-driven generative model, that unifies multiple heterogeneous learning tasks into the same framework. The proposed model is based on the fact that heterogeneous learning tasks, which correspond to different generative processes, often rely on data with a shared graph structure. Accordingly, our model combines a graph convolutional network (GCN) with multiple variational autoencoders, thus embedding the nodes of the graph i.e., samples for the tasks) in a uniform manner while specializing their organization and usage to different tasks. With a focus on healthcare applications (tasks), including clinical topic modeling, procedure recommendation and admission-type prediction, we demonstrate that our method successfully leverages information across different tasks, boosting performance in all tasks and outperforming existing state-of-the-art approaches.Comment: Accepted by AAAI-202

Both low and high levels of low-density lipoprotein cholesterol are risk factors for diabetes diagnosis in Chinese adults

Aims: This study aimed to investigate whether both high and low levels of low-density lipoprotein cholesterol (LDL-C), i.e., hypercholesterolemia and hypocholesterolemia, were associated with diabetes in Chinese adults. Methods: This cross-sectional study included 22,557 Chinese adults. The LDL-C reference interval was determined from a healthy sub-cohort. Associations between hypocholesterolemia or hypercholesterolemia with diabetes were analyzed using binary logistic regression. Results: The LDL-C reference interval was 1.48–3.77 mmol/L (57.23–145.78 mg/dL). Therefore, hypocholesterolemia, normocholesterolemia, and hypercholesterolemia were defined as an LDL-C concentration of 3.77 mmol/L, respectively. Prevalence of diabetes was higher in people with hypocholesterolemia or hypercholesterolemia than that in people with normocholesterolemia. Hypocholesterolemia was associated with an increased multivariable-adjusted risk for diabetes diagnosis (odds ratio, 1.57; 95% confidence interval, 1.18–2.08), and so was hypercholesterolemia (odds ratio, 1.29; 95% confidence interval, 1.10–1.51). The results remained significant after exclusion of those who took lipid-lowering drugs from the analysis. Conclusions: This study demonstrated that both low and high levels of LDL-C were associated with a higher risk of diabetes diagnosis. Patients with either high or low LDL-C may need to be closely monitored for the risk of diabetes

Orthogonal printing of uniform nanocomposite monolayer and oriented organic semiconductor crystals for high-performance nano-crystal floating gate memory

Inkjet printing is of great interest in the preparation of optoelectronic and microelectronic devices due to its low cost, low process temperature, versatile material compatibility, and ability to precisely manufacture multi-layer devices on demand. However, interlayer solvent erosion is a typical problem that limits the printing of organic semiconductor devices with multi-layer structures. In this study, we proposed a solution to address this erosion problem by designing polystyrene-block-poly(4-vinyl pyridine)-grafted Au nanoparticles (Au@PS-b-P4VP NPs). With a colloidal ink containing the Au@PS-b-P4VP NPs, we obtained a uniform monolayer of Au nano-crystal floating gates (NCFGs) embedded in the PS-b-P4VP tunneling dielectric (TD) layer using direct-ink-writing (DIW). Significantly, PS-b-P4VP has high erosion resistance against the semiconductor ink solvent, which enables multi-layer printing. An active layer of semiconductor crystals with high crystallinity and well-orientation was obtained by DIW. Moreover, we developed a strategy to improve the quality of the TD/semiconductor interface by introducing a polystyrene intermediate layer. We show that the NCFG memory devices exhibit a low threshold voltage (100 cycles), and long-term retention (>10 years). This study provides universal guidance for printing functional coatings and multi-layer devices

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

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

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