A METHOD AND SYSTEM TO IMPLEMENT ADAPTIVE TRAINING ALGORITHM: ADAM Q

The present disclosure relates to providing a method and system for training neural networks. It discloses an adaptive training algorithm Adam Q to overcome the challenges associated with its predecessors. It proposes a look-up table to be fused with the existing Adam algorithm such that Adam Q may not need to run all the computational operations while determining the updated weights and instead may directly see the results from the fused look-up table. It further goes on to propose a quantization technique where the received inputs from the previous iterations are first quantized and then taken as an input for the provided look-up table to make the proposed algorithm more efficient. Thus, by subjecting the inputs to quantization and fusing the look-up table, Adam Q aims to provide a more computationally efficient and financially sustainable way while ensuring data privacy

Large-angle Polarization of the Cosmic Microwave Background Radiation and Reionization

We discuss the effect of matter reionization on the large-angular-scale anisotropy and polarization of the cosmic microwave background radiation (CMBR) in the standard CDM model. We separate three cases in which the anisotropy is induced by pure scalar, pure tensor, and mixed metric perturbations respectively. It is found that, if reionization occurs early enough, the polarization can reach a detectable level of sequentially $6\%$, $9\%$, and $6.5\%$ of the anisotropy. In general, a higher degree of polarization implies a dominant contribution from the tensor mode or reionization at high redshift. Since early reionization will suppress small-scale CMBR anisotropies and polarizations significantly, measuring the polarization on few degree scales can be a direct probe of the reionization history of the early universe.Comment: Changes in the revised version: 1. Below Eq. (2), we demonstrate the method of our numerical work, by adding the evolution equations for the Legendre coefficents for both the scalar and tensor mode pertubations. 2. Below Eq. (9), we added a paragraph on discussing the basis we employed in computing the polarization correlation function. 3. In Sec. 4, we have rewritten the first and second paragraphs, where we illustrate how to the explain the discrepancies with the previous wor

論牟宗三對康德的《純粹理性批判》之詮釋

牟宗三在其《智的直覺與中國哲學》中對康德的《純粹理性批判》進行了詳 細的評論與詮釋，有關評論與詮釋乃其後來《現象與物自身》之準備工作。 在《智的直覺與中國哲學》中，牟宗三對康德的「超越的對象=X」、「智的 直覺」、「物自身」等關鍵概念進行了特殊的詮釋，甚至可說是帶有東方色彩 的詮釋；與此同時，由於他的詮釋亦與西方學者的詮釋存在著一定的差異， 遂產生出這樣的問題：牟宗三的康德詮釋（尤其是有關「智的直覺」以及「物 自身」概念之詮釋）之意義，究竟是在於「表示康德最終所應表示者以及促 成東西哲學之應有對話」，抑或僅僅是在於「借用康德之哲學語言來詮釋中 國哲學」？筆者在本文中，將嘗試討論有關問題。在處理牟宗三之康德詮釋 的合法性問題後，我們亦進一步討論牟宗三如何融攝康德哲學而建立其有關 「現象與物自身」之理論，並將此理論應用於儒家哲學的天道思想

ncRNAppi – A tool for identifying disease-related miRNA and siRNA targeting pathways

[[abstract]]Summary: Currently, there are a number of databases which store microRNA (miRNA) information, and tools available which provide miRNA target prediction. In this paper we describe a novel web-based tool that integrate the miRNA-targeted mRNA data, protein-protein interactions (PPI) records, tissues, biochemical pathways, human disease and gene function information to establish a disease-related miRNA target pathway database. This database is unique in the sense that it links miRNA target genes with their PPI partners ac-cording to being tissue-specific, diseases-specific or both. The same approach is also applied to siRNA data. This database provides two types of searches; (i) tissue-specific, and (ii) disease-specific miRNA (or siRNA) targeting pathways. The search allows one to identify tissue-specific or disease-specific miRNA (or siRNA) target gene's PPI partners two levels beyond

Applications of domain-domain interactions in pathway study

[[abstract]]The domain combination pair approach is employed to derive putative protein domain-domain interactions (DDI) from the protein-protein interactions (PPI) database DIP. The results of putative DDI are computed for seven species. To determine the prediction performance, putative DDI results are compared with that of the database InterDom, where an average matching ratio of about 76% can be achieved. Several real PPI pathways are reconstructed based on the predicted DDI results. It is found that the pathways could be reconstructed with reasonable accuracy. Furthermore, a novel quantity, so called AP-order index, is introduced to predict the regulatory order for six PPI pathways. It is found that the AP-order index is a very reliable parameter to determine the regulatory order of PPI

ncRNAppi-a tool for identifying disease-related miRNA and siRNA targeting pathways

[[abstract]]Currently, there are a number of databases which store microRNA ( miRNA) information, and tools available which provide miRNA target prediction. In this article, we describe a novel web-based tool that integrate the miRNA-targeted mRNA data, protein-protein interactions ( PPI) records, tissues, biochemical pathways, human disease and gene function information to establish a disease-related miRNA target pathway database. This database is unique in the sense that it links miRNA target genes with their PPI partners according to being tissue- and diseases-speci. c or both. The same approach is also applied to siRNA data. This database provides two types of searches: ( i) tissue- and ( ii) disease-specific miRNA ( or siRNA) targeting pathways. The search allows one to identify tissue- or disease-specific miRNA ( or siRNA) target gene's PPI partners two levels beyond

Reliability Through Life of Internal Protection Devices in Small-Cell ABSL Batteries

This viewgraph presentation reviews a reliability analysis of small cell protection batteries. The contents include: 1) The s-p Topology; 2) Cell Level Protection Devices; 3) Battery Level Fault Protection; 4) Large Cell Comparison; and 5) Battery Level Testing and Results

How competitive, cooperative, and collaborative gamification impacts student learning and engagement

Gamification is an increasingly popular approach to engage learners in educational contexts. Although many studies have examined the effects of gamification in comparison to a non-gamification approach, less attention has been paid to the impact of different ways of implementing gamification on students’ learning and engagement. In this study, we performed a quasi-experiment on the competitive, cooperative, and collaborative types of gamification among secondary school students who learn English as a foreign language. The quantitative results indicate students in the competitive condition significantly outperformed their peers in the cooperative condition on a reading-related skill (morphological awareness), word reading, and reading comprehension. They also had higher gains in morphological awareness than students in the collaborative condition, although these two groups showed similar improvement in far-transfer measures (i.e., word reading and reading comprehension). Concerning engagement, qualitative data collected from interviews suggested gamification contributed to students’ behavioural, emotional, and cognitive engagement. The qualitative data also reflected the possible reasons for the quantitative results. We conclude that cooperative and collaborative gamification should be designed carefully and take various factors into account (e.g., establishing shared goals and rewards, emphasising individual and collective contributions, and collaboration training) to ensure that the gamification approach does not hinder student learning

Dissecting molecular network structures using a network subgraph approach

Biological processes are based on molecular networks, which exhibit biological functions through interactions of genetic elements or proteins. This study presents a graph-based method to characterize molecular networks by decomposing the networks into directed multigraphs: network subgraphs. Spectral graph theory, reciprocity and complexity measures were used to quantify the network subgraphs. Graph energy, reciprocity and cyclomatic complexity can optimally specify network subgraphs with some degree of degeneracy. Seventy-one molecular networks were analyzed from three network types: cancer networks, signal transduction networks, and cellular processes. Molecular networks are built from a finite number of subgraph patterns and subgraphs with large graph energies are not present, which implies a graph energy cutoff. In addition, certain subgraph patterns are absent from the three network types. Thus, the Shannon entropy of the subgraph frequency distribution is not maximal. Furthermore, frequently-observed subgraphs are irreducible graphs. These novel findings warrant further investigation and may lead to important applications. Finally, we observed that cancer-related cellular processes are enriched with subgraph-associated driver genes. Our study provides a systematic approach for dissecting biological networks and supports the conclusion that there are organizational principles underlying molecular networks