COVID-19 portal: Profiling researchers, bio-entities, and institutions

The outbreak of COVID-19 has a severe impact on our families, communities, and businesses. White House released the COVID19 literature dataset (called CORD-19 dataset) which has grown exponentially into a gigantic collection of over 500,000 articles. Researchers, practitioners, and administrators need a tool to help them digest this enormous amount of knowledge to address various scientific questions related to COVID-19. This paper showcases the COVID-19 portal to portray the research profiles of scientists, bio entities (e.g., gene, drug, disease), and institutions based on the integration of CORD-19 research literature, COVID-19 related clinical trials, PubMed knowledge graph, and the drug discovery knowledge graph. This portal provides the following profiles related to COVID-19: 1) the profile of a research scientist with his/her COVID-19 related publications and clinical trials which can be ranked by year or by the number of tweets; 2) the profile of a bio entity which could be a gene, a drug, or a disease with articles and clinical trials mentioned this bio entity; and 3) the profile of an institution with papers authored by researchers from this institution

Variational capacitance modeling using orthogonal polynomial method

ABSTRACT In this paper, we propose a novel statistical capacitance extraction method for interconnects considering process variations. The new method, called statCap, is based on the spectral stochastic method where orthogonal polynomials are used to represent the statistical processes in a deterministic way. We first show how the variational potential coefficient matrix is represented in a first-order form using Taylor expansion and orthogonal decomposition. Then an augmented potential coefficient matrix, which consists of the coefficients of the polynomials, is derived. After that, corresponding augmented system is solved to obtain the variational capacitance values in the orthogonal polynomial form. Experimental results show that our method is two orders of magnitude faster than the recently proposed statistical capacitance extraction method based on the spectral stochastic collocation approac

Fault Monitoring Based on the VLSW-MADF Test and DLPPCA for Multimodal Processes

Actual industrial processes often exhibit multimodal characteristics, and their data exhibit complex features, such as being dynamic, nonlinear, multimodal, and strongly coupled. Although many modeling approaches for process fault monitoring have been proposed in academia, due to the complexity of industrial data, challenges remain. Based on the concept of multimodal modeling, this paper proposes a multimodal process monitoring method based on the variable-length sliding window-mean augmented Dickey–Fuller (VLSW-MADF) test and dynamic locality-preserving principal component analysis (DLPPCA). In the offline stage, considering the fluctuation characteristics of data, the trend variables of data are extracted and input into VLSW-MADF for modal identification, and different modalities are modeled separately using DLPPCA. In the online monitoring phase, the previous moment’s historical modal information is fully utilized, and modal identification is performed only when necessary to reduce computational cost. Finally, the proposed method is validated to be accurate and effective for modal identification, modeling, and online monitoring of multimodal processes in TE simulation and actual plant data. The proposed method improves the fault detection rate of multimodal process fault monitoring by about 14% compared to the classical DPCA method

A novel memristor-based rSRAM structure for multiple-bit upsets immunity

A radiation hardened resistive SRAM structure (rSRAM) is proposed for the SRAM-based FPGAs in this paper. The rSRAM extends the conventional 6T SRAM structure by connecting memristors between the information nodes and drains of the transistors which compose cross-coupled invertors. With memristors connected to drains of OFF transistors configured to high resistance state while others configured to low resistance state forming stable voltage dividing path, the rSRAM structure is immune to both multiple-node upsets and multiple-bit upsets (MBUs). The simulation result demonstrates that rSRAM cell can tolerate simultaneous disruptions affecting all sensitive nodes with an LET (Liner Energy Transfer) of 100Mev-cm2/mg.Published Versio

Techniques for dual forms of Reed-Muller expansion conversion.

Dual forms of Reed-Muller (DFRM) are implemented in OR/XNOR forms, which are based on the features of coincidence operation. Map folding and transformation techniques are proposed for the conversion between Boolean and DFRM expansions. However, map techniques can only be used for uo to 6 variables. To overcome the limitation, serial tabular technique (STT) and parallel tabular technique (PTT) are proposed. STT deals with one variable at a time while PTT generates terms in parallel. Both tabular techniques outperform published work significantly in terms of conversion time. Methods based on on-set canonical sum-of-products minterms and canonical product-of-sums maxterms are also investigated

Exact minimization of large fixed polarity dual form of reed-muller functions

Dual form of Reed-Muller (DFRM) expansions are implemented in OX/XNOR logic, which are based on the features of coincidence operation and are known as fixed polarity Canonical OR-Coincidence (COC) expansions. An efficient minimization method is proposed to find the best polarity COC expansion for large functions. The method derives one expansion from another adjacent polarity expansion using gray code, resulting in small space complexity O(M) and time complexity O(2nthMlogM), where n and M are the number of input variables and the number of on-set COC maxterms. Hence, it makes minimization for large functions practical

Heat shock factor 2 levels are associated with the severity of ulcerative colitis.

BACKGROUND AND AIMS: The morbidity of ulcerative colitis (UC) is increasing in China every year. In addition, there is a lack of accurate diagnostic indices with which to evaluate the activity of the disease. The aim of this study was to identify UC-associated proteins as biomarkers for the diagnosis, and objective assessment of disease activity. METHODS: Differential expression of serum proteins from UC patients compared to normal controls was analyzed by two-dimensional electrophoresis (2-DE) and matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF-MS). The expression of heat shock factor 2(HSF2)in colonic mucosa in Crohn's disease, Behcet's disease, ulcerative colitis, intestinal tuberculosis, infective enteritis, intestinal lymphoma, and normal controls was investigated by immunohistochemistry (IHC). The expression of the HSF2 in colonic mucosa of UC subjects with varying severity of disease was measured by real time-PCR and Western Blots. The expression of HSF2 was inhibited by HSF2 small interfering RNA (siRNA) transfection in Caco-2 cells. The concentrations of HSF2, IL-1β, and TNF-α in serum and IL-1β, and TNF-α in the supernatants of transfected Caco-2 cells were determined by ELISA. RESULTS: HSF2 was differentially expressed in UC patients compared to normal controls. HSF2 expression was significantly higher in the intestinal mucosa of UC patients compared to other six groups. The results of immunohistochemistry, real time-PCR, Western Blots, and ELISA showed that the expression of HSF2 increased in parallel with the severity of UC. The serum concentration of HSF2 also positively correlated with levels of IL-1β and TNF-α. After down-regulation expression of HSF2 in Caco-2 cells by RNA interference, the productions of IL-1β and TNF-α stimulated by lipopolysaccharide (LPS) increased dramatically. CONCLUSIONS: HSF2 appears to be a potential novel molecular marker for UC activity, and may provide a basis for studies on the pathogenesis and novel therapeutic targets for UC