Design and development of learning model for compression and processing of deoxyribonucleic acid genome sequence

Owing to the substantial volume of human genome sequence data files (from 30-200 GB exposed) Genomic data compression has received considerable traction and storage costs are one of the major problems faced by genomics laboratories. This involves a modern technology of data compression that reduces not only the storage but also the reliability of the operation. There were few attempts to solve this problem independently of both hardware and software. A systematic analysis of associations between genes provides techniques for the recognition of operative connections among genes and their respective yields, as well as understandings into essential biological events that are most important for knowing health and disease phenotypes. This research proposes a reliable and efficient deep learning system for learning embedded projections to combine gene interactions and gene expression in prediction comparison of deep embeddings to strong baselines. In this paper we preform data processing operations and predict gene function, along with gene ontology reconstruction and predict the gene interaction. The three major steps of genomic data compression are extraction of data, storage of data, and retrieval of the data. Hence, we propose a deep learning based on computational optimization techniques which will be efficient in all the three stages of data compression.

Efficiency and Effectiveness of Web Application Vulnerability Detection Approaches: A Review

Most existing surveys and reviews on web application vulnerability detection (WAVD) approaches focus on comparing and summarizing the approaches’ technical details. Although some studies have analyzed the efficiency and effectiveness of specific methods, there is a lack of a comprehensive and systematic analysis of the efficiency and effectiveness of various WAVD approaches. We conducted a systematic literature review (SLR) of WAVD approaches and analyzed their efficiency and effectiveness. We identified 105 primary studies out of 775 WAVD articles published between January 2008 and June 2019. Our study identified 10 categories of artifacts analyzed by the WAVD approaches and 8 categories of WAVD meta-approaches for analyzing the artifacts. Our study’s results also summarized and compared the effectiveness and efficiency of different WAVD approaches on detecting specific categories of web application vulnerabilities and which web applications and test suites are used to evaluate the WAVD approaches. To our knowledge, this is the first SLR that focuses on summarizing the effectiveness and efficiencies of WAVD approaches. Our study results can help security engineers choose and compare WAVD tools and help researchers identify research gaps.

When Less Is More: Systematic Analysis of Cascade-Based Community Detection

Information diffusion, spreading of infectious diseases, and spreading of rumors are fundamental processes occurring in real-life networks. In many practical cases, one can observe when nodes become infected, but the underlying network, over which a contagion or information propagates, is hidden. Inferring properties of the underlying network is important since these properties can be used for constraining infections, forecasting, viral marketing, and so on. Moreover, for many applications, it is sufficient to recover only coarse high-level properties of this network rather than all its edges. This article conducts a systematic and extensive analysis of the following problem: Given only the infection times, find communities of highly interconnected nodes. This task significantly differs from the well-studied community detection problem since we do not observe a graph to be clustered. We carry out a thorough comparison between existing and new approaches on several large datasets and cover methodological challenges specific to this problem. One of the main conclusions is that the most stable performance and the most significant improvement on the current state-of-the-art are achieved by our proposed simple heuristic approaches agnostic to a particular graph structure and epidemic model. We also show that some well-known community detection algorithms can be enhanced by including edge weights based on the cascade data.

Identity Politics Past and Present

This new book in Critical Discourse Studies uses detailed and systematic analysis of the discursive construction of Austrian identities across a period of 20 years – from 1995 to 2015 – to trace the re-emergence of nationalism in the media, popular culture and politics, and the normalization of far-right nativist ideologies and attitudes. Contradictory and intertwined tendencies towards re-nationalization and trans-nationalization have always framed debates about European identities, but during the so-called ‘refugee crisis’ of 2015, the debates became polarized. During the COVID-19 pandemic, nation states first reacted by closing borders, while symbols of banal nationalism proliferated. The data, drawn from a variety of empirical studies, suggests changes in memory politics – the way past events are remembered – are due to a range of factors, including the growth of migrant societies; the influence of financial and climate crises; changing gender politics; and a new transnational European politics of the past. The authors assess the challenges to liberal democracies and fundamental human and constitutional rights, and analyze how the pandemic contributes to a new re-nationalization across Europe and beyond.

Astaxanthin Exerts Anabolic Effects via Pleiotropic Modulation of the Excitable Tissue

Astaxanthin is a lipid-soluble carotenoid influencing lipid metabolism, body weight, and insulin sensitivity. We provide a systematic analysis of acute and chronic effects of astaxanthin on different organs. Changes by chronic astaxanthin feeding were analyzed on general metabolism, expression of regulatory proteins in the skeletal muscle, as well as changes of excitation and synaptic activity in the hypothalamic arcuate nucleus of mice. Acute responses were also tested on canine cardiac muscle and different neuronal populations of the hypothalamic arcuate nucleus in mice. Dietary astaxanthin significantly increased food intake. It also increased protein levels affecting glucose metabolism and fatty acid biosynthesis in skeletal muscle. Inhibitory inputs innervating neurons of the arcuate nucleus regulating metabolism and food intake were strengthened by both acute and chronic astaxanthin treatment. Astaxanthin moderately shortened cardiac action potentials, depressed their plateau potential, and reduced the maximal rate of depolarization. Based on its complex actions on metabolism and food intake, our data support the previous findings that astaxanthin is suitable for supplementing the diet of patients with disturbances in energy homeostasis.

Screening and Comprehensive Analysis of Cancer-Associated tRNA-Derived Fragments

tRNA-derived fragments (tRFs) constitute a novel class of small non-coding RNA cleaved from tRNAs. In recent years, researches have shown the regulatory roles of a few tRFs in cancers, illuminating a new direction for tRF-centric cancer researches. Nonetheless, more specific screening of tRFs related to oncogenesis pathways, cancer progression stages and cancer prognosis is continuously demanded to reveal the landscape of the cancer-associated tRFs. In this work, by combining the clinical information recorded in The Cancer Genome Atlas (TCGA) and the tRF expression profiles curated by MINTbase v2.0, we systematically screened 1,516 cancer-associated tRFs (ca-tRFs) across seven cancer types. The ca-tRF set collectively combined the differentially expressed tRFs between cancer samples and control samples, the tRFs significantly correlated with tumor stage and the tRFs significantly correlated with patient survival. By incorporating our previous tRF-target dataset, we found the ca-tRFs tend to target cancer-associated genes and onco-pathways like ATF6-mediated unfolded protein response, angiogenesis, cell cycle process regulation, focal adhesion, PI3K-Akt signaling pathway, cellular senescence and FoxO signaling pathway across multiple cancer types. And cell composition analysis implies that the expressions of ca-tRFs are more likely to be correlated with T-cell infiltration. We also found the ca-tRF expression pattern is informative to prognosis, suggesting plausible tRF-based cancer subtypes. Together, our systematic analysis demonstrates the potentially extensive involvements of tRFs in cancers, and provides a reasonable list of cancer-associated tRFs for further investigations.

Divergence and dispersion of global eddy propagation from satellite altimetry

It is well understood that isolated eddies are presumed to propagate westward intrinsically at the speed of the annual baroclinic Rossby wave. This classic description, however, is known to be frequently violated in both propagation speed and its direction in the real ocean. Here, we present a systematic analysis on the divergence of eddy propagation direction (i.e., global pattern of departure from due west) and dispersion of eddy propagation speed (i.e., zonal pattern of departure from Rossby wave phase speed). Our main findings include the following: 1) A global climatological phase map (the first of its kind to our knowledge) indicating localized direction of most likely eddy propagation has been derived from twenty-eight years (1993-2020) of satellite altimetry, leading to a leaf-like full-angle pattern in its overall divergence. 2) A meridional deflection map of eddy motion is created with prominent equatorward/poleward deflecting zones identified, revealing that it is more geographically correlated rather than polarity determined as previously thought (i.e., poleward for cyclonic eddies and equatorward for anticyclonic ones). 3) The eddy-Rossby wave relationship has a duality nature (waves riding by eddies) in five subtropical bands centered around 27°N and 26°S in the two hemispheres, outside which their relationship has a dispersive nature with dominant waves (eddies) propagating faster in the tropical (extratropical) oceans. Current, wind and topographic effects are major external forcings responsible for the observed divergence and dispersion of eddy propagations. These results are expected to make a significant contribution to eddy trajectory prediction using physically based and/or data-driven models.