An on-line library of design patterns

This project is to develop an on-line library to help software engineers who utilize design patterns for developing e-commerce applications it translates generic design patterns to concrete design patterns. The graphical user interface was developed to allow the user to develop their own design patterns by modifying or changing stored design patterns

Design of a multi-layer interior ferrite permanent magnet synchronous machine for traction applications

A novel design of interior ferrite permanent magnet synchronous machine with multi-layer configuration is proposed for traction applications. Although the ferrite magnet can be disadvantaged by its low residual flux density and energy product, it is proposed that flux-focusing and multi-layer configurations can be utilized to harness both permanent magnet (PM) torque and reluctance torque to recoup the loss of the PM torque due to its intrinsic property. The machines with up to three-layer magnets are presented and evaluated comprehensively. The results suggest that the two-layer machine provides the best performance among the three configurations. Furthermore, compared against a commercial rare-earth equivalent, the proposed ferrite machine is shown to have nearly the same torque with 32% less electromagnetic losses. The findings underpin interior ferrite permanent magnet synchronous machine as an attractive alternative for traction application

Alternative Splicing Regulated by Butyrate in Bovine Epithelial Cells

As a signaling molecule and an inhibitor of histone deacetylases (HDACs), butyrate exerts its impact on a broad range of biological processes, such as apoptosis and cell proliferation, in addition to its critical role in energy metabolism in ruminants. This study examined the effect of butyrate on alternative splicing in bovine epithelial cells using RNA-seq technology. Junction reads account for 11.28 and 12.32% of total mapped reads between the butyrate-treated (BT) and control (CT) groups. 201,326 potential splicing junctions detected were supported by ≥3 junction reads. Approximately 94% of these junctions conformed to the consensus sequence (GT/AG) while ∼3% were GC/AG junctions. No AT/AC junctions were observed. A total of 2,834 exon skipping events, supported by a minimum of 3 junction reads, were detected. At least 7 genes, their mRNA expression significantly affected by butyrate, also had exon skipping events differentially regulated by butyrate. Furthermore, COL5A3, which was induced 310-fold by butyrate (FDR <0.001) at the gene level, had a significantly higher number of junction reads mapped to Exon#8 (Donor) and Exon#11 (Acceptor) in BT. This event had the potential to result in the formation of a COL5A3 mRNA isoform with 2 of the 69 exons missing. In addition, 216 differentially expressed transcript isoforms regulated by butyrate were detected. For example, Isoform 1 of ORC1 was strongly repressed by butyrate while Isoform 2 remained unchanged. Butyrate physically binds to and inhibits all zinc-dependent HDACs except HDAC6 and HDAC10. Our results provided evidence that butyrate also regulated deacetylase activities of classical HDACs via its transcriptional control. Moreover, thirteen gene fusion events differentially affected by butyrate were identified. Our results provided a snapshot into complex transcriptome dynamics regulated by butyrate, which will facilitate our understanding of the biological effects of butyrate and other HDAC inhibitors

Obfuscation-resilient Android Malware Analysis Based on Contrastive Learning

Due to its open-source nature, Android operating system has been the main target of attackers to exploit. Malware creators always perform different code obfuscations on their apps to hide malicious activities. Features extracted from these obfuscated samples through program analysis contain many useless and disguised features, which leads to many false negatives. To address the issue, in this paper, we demonstrate that obfuscation-resilient malware analysis can be achieved through contrastive learning. We take the Android malware classification as an example to demonstrate our analysis. The key insight behind our analysis is that contrastive learning can be used to reduce the difference introduced by obfuscation while amplifying the difference between malware and benign apps (or other types of malware). Based on the proposed analysis, we design a system that can achieve robust and interpretable classification of Android malware. To achieve robust classification, we perform contrastive learning on malware samples to learn an encoder that can automatically extract robust features from malware samples. To achieve interpretable classification, we transform the function call graph of a sample into an image by centrality analysis. Then the corresponding heatmaps are obtained by visualization techniques. These heatmaps can help users understand why the malware is classified as this family. We implement IFDroid and perform extensive evaluations on two widely used datasets. Experimental results show that IFDroid is superior to state-of-the-art Android malware familial classification systems. Moreover, IFDroid is capable of maintaining 98.2% true positive rate on classifying 8,112 obfuscated malware samples

Metagenome Plasticity of the Bovine Abomasal Microbiota in Immune Animals in Response to Ostertagia Ostertagi Infection

Infections in cattle by the abomasal nematode Ostertagia ostertagi result in impaired gastrointestinal function. Six partially immune animals were developed using multiple drug-attenuated infections, and these animals displayed reduced worm burdens and a slightly elevated abomasal pH upon reinfection. In this study, we characterized the abomasal microbiota in response to reinfection using metagenomic tools. Compared to uninfected controls, infection did not induce a significant change in the microbial community composition in immune animals. 16S rRNA gene-based phylogenetic analysis identified 15 phyla in the bovine abomasal microbiota with Bacteroidetes (60.5%), Firmicutes (27.1%), Proteobacteria (7.2%), Spirochates (2.9%), and Fibrobacteres (1.5%) being the most predominant. The number of prokaryotic genera and operational taxonomic units (OTU) identified in the abomasal microbial community was 70.8±19.8 (mean ± SD) and 90.3±2.9, respectively. However, the core microbiome comprised of 32 genera and 72 OTU. Infection seemingly had a minimal impact on the abomasal microbial diversity at a genus level in immune animals. Proteins predicted from whole genome shotgun (WGS) DNA sequences were assigned to 5,408 Pfam and 3,381 COG families, demonstrating dazzling arrays of functional diversity in bovine abomasal microbial communities. However, none of COG functional classes were significantly impacted by infection. Our results demonstrate that immune animals may develop abilities to maintain proper stability of their abomasal microbial ecosystem. A minimal disruption in the bovine abomasal microbiota by reinfection may contribute equally to the restoration of gastric function in immune animals

RISK PRIORITY EVALUATION OF POWER TRANSFORMER PARTS BASED ON HYBRID FMEA FRAMEWORK UNDER HESITANT FUZZY ENVIRONMENT

The power transformer is one of the most critical facilities in the power system, and its running status directly impacts the power system's security. It is essential to research the risk priority evaluation of the power transformer parts. Failure mode and effects analysis (FMEA) is a methodology for analyzing the potential failure modes (FMs) within a system in various industrial devices. This study puts forward a hybrid FMEA framework integrating novel hesitant fuzzy aggregation tools and CRITIC (Criteria Importance Through Inter-criteria Correlation) method. In this framework, the hesitant fuzzy sets (HFSs) are used to depict the uncertainty in risk evaluation. Then, an improved HFWA (hesitant fuzzy weighted averaging) operator is adopted to fuse risk evaluation for FMEA experts. This aggregation manner can consider different lengths of HFSs and the support degrees among the FMEA experts. Next, the novel HFWGA (hesitant fuzzy weighted geometric averaging) operator with CRITIC weights is developed to determine the risk priority of each FM. This method can satisfy the multiplicative characteristic of the RPN (risk priority number) method of the conventional FMEA model and reflect the correlations between risk indicators. Finally, a real example of the risk priority evaluation of power transformer parts is given to show the applicability and feasibility of the proposed hybrid FMEA framework. Comparison and sensitivity studies are also offered to verify the effectiveness of the improved risk assessment approach

Perturbation Dynamics of the Rumen Microbiota in Response to Exogenous Butyrate

The capacity of the rumen microbiota to produce volatile fatty acids (VFAs) has important implications in animal well-being and production. We investigated temporal changes of the rumen microbiota in response to butyrate infusion using pyrosequencing of the 16S rRNA gene. Twenty one phyla were identified in the rumen microbiota of dairy cows. The rumen microbiota harbored 54.5±6.1 genera (mean ± SD) and 127.3±4.4 operational taxonomic units (OTUs), respectively. However, the core microbiome comprised of 26 genera and 82 OTUs. Butyrate infusion altered molar percentages of 3 major VFAs. Butyrate perturbation had a profound impact on the rumen microbial composition. A 72 h-infusion led to a significant change in the numbers of sequence reads derived from 4 phyla, including 2 most abundant phyla, Bacteroidetes and Firmicutes. As many as 19 genera and 43 OTUs were significantly impacted by butyrate infusion. Elevated butyrate levels in the rumen seemingly had a stimulating effect on butyrate-producing bacteria populations. The resilience of the rumen microbial ecosystem was evident as the abundance of the microorganisms returned to their pre-disturbed status after infusion withdrawal. Our findings provide insight into perturbation dynamics of the rumen microbial ecosystem and should guide efforts in formulating optimal uses of probiotic bacteria treating human diseases

Quantification of Transcriptome Responses of the Rumen Epithelium to Butyrate Infusion using RNA-seq Technology

Short-chain fatty acids (SCFAs), such as butyrate, produced by gut microorganisms, play a critical role in energy metabolism and physiology of ruminants as well as in human health. In this study, the temporal effect of elevated butyrate concentrations on the transcriptome of the rumen epithelium was quantified via serial biopsy sampling using RNA-seq technology. The mean number of genes transcribed in the rumen epithelial transcriptome was 17,323.63 ± 277.20 (±SD; N = 24) while the core transcriptome consisted of 15,025 genes. Collectively, 80 genes were identified as being significantly impacted by butyrate infusion across all time points sampled. Maximal transcriptional effect of butyrate on the rumen epithelium was observed at the 72-h infusion when the abundance of 58 genes was altered. The initial reaction of the rumen epithelium to elevated exogenous butyrate may represent a stress response as Gene Ontology (GO) terms identified were predominantly related to responses to bacteria and biotic stimuli. An algorithm for the reconstruction of accurate cellular networks (ARACNE) inferred regulatory gene networks with 113,738 direct interactions in the butyrate-epithelium interactome using a combined cutoff of an error tolerance (ɛ = 0.10) and a stringent P-value threshold of mutual information (5.0 × 10−11). Several regulatory networks were controlled by transcription factors, such as CREBBP and TTF2, which were regulated by butyrate. Our findings provide insight into the regulation of butyrate transport and metabolism in the rumen epithelium, which will guide our future efforts in exploiting potential beneficial effect of butyrate in animal well-being and human health

Recovery of oil with unsaturated fatty acids and polyphenols from chaenomelessinensis (Thouin) Koehne: Process optimization of pilot-scale subcritical fluid assisted extraction

The potential effects of three modern extraction technologies (cold-pressing, microwaves and subcritical fluids) on the recovery of oil from Chaenomelessinensis (Thouin) Koehne seeds have been evaluated and compared to those of conventional chemical extraction methods (Soxhlet extraction). This oil contains unsaturated fatty acids and polyphenols. Subcritical fluid extraction (SbFE) provided the highest yield—25.79 g oil/100 g dry seeds—of the three methods. Moreover, the fatty acid composition in the oil samples was analysed using gas chromatography–mass spectrometry. This analysis showed that the percentages of monounsaturated (46.61%), and polyunsaturated fatty acids (42.14%), after applying SbFE were higher than those obtained by Soxhlet, cold-pressing or microwave-assisted extraction. In addition, the oil obtained under optimized SbFE conditions (35 min extraction at 35 °C with four extraction cycles), showed significant polyphenol (527.36 mg GAE/kg oil), and flavonoid (15.32 mg RE/kg oil), content, had a good appearance and was of high quality

Computational Analysis of Drought Stress-Associated miRNAs and miRNA Co-Regulation Network in Physcomitrella patens.

miRNAs are non-coding small RNAs that involve diverse biological processes. Until now, little is known about their roles in plant drought resistance. Physcomitrella patens is highly tolerant to drought; however, it is not clear about the basic biology of the traits that contribute P. patens this important character. In this work, we discovered 16 drought stress-associated miRNA (DsAmR) families in P. patens through computational analysis. Due to the possible discrepancy of expression periods and tissue distributions between potential DsAmRs and their targeting genes, and the existence of false positive results in computational identification, the prediction results should be examined with further experimental validation. We also constructed an miRNA co-regulation network, and identified two network hubs, miR902a-5p and miR414, which may play important roles in regulating drought-resistance traits. We distributed our results through an online database named ppt-miRBase, which can be accessed at http://bioinfor.cnu.edu.cn/ppt_miRBase/index.php. Our methods in finding DsAmR and miRNA co-regulation network showed a new direction for identifying miRNA functions