Preparation and Photocatalytic Activity of Fe3+ - doped TiO2 Modified

Photocatalytic materials of TiO2 / coarse silica gel microspheres were prepared by sol-gel impregnation method and doped with transition metal ions Fe3+ to form Fe3+ modified TiO2 / coarse silica gel microspheres. The surface of the Fe modified photocatalytic materials were analyzed by XRD and surface scanning. Degradation of reactive dyes using X-3B dye wastewater water samples for validation tests. The results show that the photocatalytic activity of the photocatalytic material reaches the best when the Fe doping amount is 0.5%, and the most photocatalyst amount is 10g / L. The degradation rate of COD under this dosage was 72.32%. At the same time, according to the characterization analysis, it was found that Fe did not react with the photocatalytic material of TiO2 / coarse silica microspheres in the reaction, Fe increased the defect structure of TiO2 surface and promoted the formation of anatase, A red shift occurred and the corresponding range of the spectrum expanded toward the visible region. The results show that the doping of Fe affects the formation of TiO2 crystals, but increases the photocatalytic efficiency of TiO2

Mechanical Behavior and Application of a Novel Supporting and Retaining Structure for Slope

This paper proposed a novel supporting and retaining structure used to high-steep building slope reinforcement. It combined with an anti-sliding pile and an inclined supporting column, which is used as a fulcrum on the upper part of pile. The mechanical characteristics of the novel supporting and retaining structure are studied firstly by two mechanical methods and two numerical methods, respectively. Result shows that the axial force will be evenly distributed along the column body and it provide a quite resistant force, meanwhile. There are two shear force concentrated areas of the anti-sliding pile, one is from the top of the embedded area of the pile body to the potential slip plane, the other is at the joint. Subsequently, the results of these methods are compared synthetically and the differences between the results are also discussed. It shows that a large shear force and moment will be caused at the restrained end of the pile body by the force method and 2D numerical model 1. And in Wenkler model and the 2D numerical model 2, the rock is considered non-rigid, the anti-sliding pile will produce a certain amount of deflection under the sliding thrust, which reduces the shear force and moment at the top of the embedded area of the pile body. Finally, the novel supporting and retaining structure is applied to the site, and the monitoring data shows that the novel supporting and retaining structure is economic and effective for the reinforcement of the high-steep building slope

TripleRE: Knowledge Graph Embeddings via Tripled Relation Vectors

Translation-based knowledge graph embedding has been one of the most important branches for knowledge representation learning since TransE came out. Although many translation-based approaches have achieved some progress in recent years, the performance was still unsatisfactory. This paper proposes a novel knowledge graph embedding method named TripleRE with two versions. The first version of TripleRE creatively divide the relationship vector into three parts. The second version takes advantage of the concept of residual and achieves better performance. In addition, attempts on using NodePiece to encode entities achieved promising results in reducing the parametric size, and solved the problems of scalability. Experiments show that our approach achieved state-of-the-art performance on the large-scale knowledge graph dataset, and competitive performance on other datasets

Evaluation of Urban Infrastructure Investment Efficiency: Empirical Evidence from Heilongjiang Province, China

The rapid growth of urban infrastructure investment in China has brought with it some serious problems that cannot be ignored, such as low investment efficiency and faulty investment decision-making. Therefore, based on the latest research findings related to infrastructure efficiency evaluation theory and evaluation methods, this paper uses empirical evidence from Heilongjiang province to analyze urban infrastructure investment efficiency. To analyze investment efficiency in the province, a new infrastructure investment efficiency evaluation model is developed known as the SDEA-Malmquist model. The model reveals that urban infrastructure investment projects in Heilongjiang province are relatively effective and stable but that the efficiency of such investments varies according to the city in which they are made. Overall efficiency is consistent with the TFC (total final consumption) index, but the index fluctuates within a narrow range between cities due to technological differences

Temporal and Quantitative Analysis of Atherosclerotic Lesions in Diet-Induced Hypercholesterolemic Rabbits

The diet-induced atherosclerotic rabbit is an ideal model for atherosclerosis study, but temporal changes in atherosclerotic development in hypercholesterolemic rabbits are poorly understood. Japanese white rabbits were fed a high-cholesterol diet to induce sustained hypercholesterolemia, and each group of 10–12 animals was then sacrificed at 6, 12, 16, or 28 weeks. The rabbit aortas were harvested, and the sizes of the gross and intima atherosclerotic lesions were quantified. The cellular component of macrophages (Mφs) and smooth muscle cells (SMCs) in aortic intimal lesions was also quantified by immunohistochemical staining, and the correlation between plasma cholesterol levels and the progress of atherosclerotic lesions was studied. The ultrastructure of the atherosclerotic lesions was observed by transmission electron microscopy (TEM). Widely variable atherosclerotic plaques were found from 6 weeks to 28 weeks, and the lesional progress was closely correlated with cholesterol exposure. Interestingly, a relatively reduced accumulation of Mφ, an increased numbers of SMCs, and a damaged endothelial layer were presented in advanced lesions. Moreover, SMCs were closely correlated with cholesterol exposure and lesional progress for the whole period. Cholesterol exposure directly determines atherosclerotic progress in a rabbit model, and the changes in the cellular component of advanced lesions may affect plaque stability in an atherosclerotic rabbit model

A novel machine learning-derived four-gene signature predicts STEMI and post-STEMI heart failure

High mortality and morbidity rates associated with ST-elevation myocardial infarction (STEMI) and post-STEMI heart failure (HF) necessitate proper risk stratification for coronary artery disease (CAD). A prediction model that combines specificity and convenience is highly required. This study aimed to design a monocyte-based gene assay for predicting STEMI and post-STEMI HF. A total of 1,956 monocyte expression profiles and corresponding clinical data were integrated from multiple sources. Meta-results were obtained through the weighted gene co-expression network analysis (WGCNA) and differential analysis to identify characteristic genes for STEMI. Machine learning models based on the decision tree (DT), support vector machine (SVM), and random forest (RF) algorithms were trained and validated. Five genes overlapped and were subjected to the model proposal. The discriminative performance of the DT model outperformed the other two methods. The established four-gene panel (HLA-J, CFP, STX11, and NFYC) could discriminate STEMI and HF with an area under the curve (AUC) of 0.86 or above. In the gene set enrichment analysis (GSEA), several cardiac pathogenesis pathways and cardiovascular disorder signatures showed statistically significant, concordant differences between subjects with high and low expression levels of the four-gene panel, affirming the validity of the established model. In conclusion, we have developed and validated a model that offers the hope for accurately predicting the risk of STEMI and HF, leading to optimal risk stratification and personalized management of CAD, thereby improving individual outcomes

SilkDB: a knowledgebase for silkworm biology and genomics

The Silkworm Knowledgebase (SilkDB) is a web-based repository for the curation, integration and study of silkworm genetic and genomic data. With the recent accomplishment of a ∼6X draft genome sequence of the domestic silkworm (Bombyx mori), SilkDB provides an integrated representation of the large-scale, genome-wide sequence assembly, cDNAs, clusters of expressed sequence tags (ESTs), transposable elements (TEs), mutants, single nucleotide polymorphisms (SNPs) and functional annotations of genes with assignments to InterPro domains and Gene Ontology (GO) terms. SilkDB also hosts a set of ESTs from Bombyx mandarina, a wild progenitor of B.mori, and a collection of genes from other Lepidoptera. Comparative analysis results between the domestic and wild silkworm, between B.mori and other Lepidoptera, and between B.mori and the two sequenced insects, fruitfly and mosquito, are displayed by using B.mori genome sequence as a reference framework. Designed as a basic platform, SilkDB strives to provide a comprehensive knowledgebase about the silkworm and present the silkworm genome and related information in systematic and graphical ways for the convenience of in-depth comparative studies. SilkDB is publicly accessible at http://silkworm.genomics.org.cn

ChickVD: a sequence variation database for the chicken genome

Working in parallel with the efforts to sequence the chicken (Gallus gallus) genome, the Beijing Genomics Institute led an international team of scientists from China, USA, UK, Sweden, The Netherlands and Germany to map extensive DNA sequence variation throughout the chicken genome by sampling DNA from domestic breeds. Using the Red Jungle Fowl genome sequence as a reference, we identified 3.1 million non-redundant DNA sequence variants. To facilitate the application of our data to avian genetics and to provide a foundation for functional and evolutionary studies, we created the ‘Chicken Variation Database’ (ChickVD). A graphical MapView shows variants mapped onto the chicken genome in the context of gene annotations and other features, including genetic markers, trait loci, cDNAs, chicken orthologs of human disease genes and raw sequence traces. ChickVD also stores information on quantitative trait loci using data from collaborating institutions and public resources. Our data can be queried by search engine and homology-based BLAST searches. ChickVD is publicly accessible at http://chicken.genomics.org.cn