Improved filtered mesoscale interphase heat transfer model

Mesoscale structures that form in gas-solid flows considerably affect interphase heat transfer.A filtered interphase heat transfer model accounts for the effect...     

Rapid Identification for the Pterocarpus Bracelet by Three-Step Infrared Spectrum Method

In order to explore a rapid identification method for the anti-counterfeit of commercial high value collections, a three-step infrared spectrum method was used for the pterocarpus collection identification to confirm whether a commercial pterocarpus bracelet (PB) was made from the precious species of Pterocarpus santalinus (P. santalinus). In the first step, undertaken by Fourier transform infrared spectroscopy (FTIR) spectrum, the absorption peaks intensity of PB was slightly higher than that of P. santalinus only at 1594 cm⁻¹, 1205 cm⁻¹, 1155 cm⁻¹ and 836 cm⁻¹. In the next step of second derivative IR spectra (SDIR), the FTIR features of the tested samples were further amplified, and the peaks at 1600 cm⁻¹, 1171 cm⁻¹ and 1152 cm⁻¹ become clearly defined in PB. Finally, by means of two-dimensional correlation infrared (2DIR) spectrum, it revealed that the response of holocellulose to thermal perturbation was stronger in P. santalinus than that in PB mainly at 977 cm⁻¹, 1008 cm⁻¹, 1100 cm⁻¹, 1057 cm⁻¹, 1190 cm⁻¹ and 1214 cm⁻¹, while the aromatic functional groups of PB were much more sensitive to the thermal perturbation than those of P. santalinus mainly at 1456 cm⁻¹, 1467 cm⁻¹, 1518 cm⁻¹, 1558 cm⁻¹, 1576 cm⁻¹ and 1605 cm⁻¹. In addition, fluorescence microscopy was used to verify the effectiveness of the above method for wood identification and the results showed good consistency. This study demonstrated that the three-step IR method could provide a rapid and effective way for the anti-counterfeit of pterocarpus collections.     

EGFAFS: A Novel Feature Selection Algorithm Based on Explosion Gravitation Field Algorithm

Feature selection (FS) is a vital step in data mining and machine learning, especially for analyzing the data in high-dimensional feature space. Gene expression data usually consist of a few samples characterized by high-dimensional feature space. As a result, they are not suitable to be processed by simple methods, such as the filter-based method. In this study, we propose a novel feature selection algorithm based on the Explosion Gravitation Field Algorithm, called EGFAFS. To reduce the dimensions of the feature space to acceptable dimensions, we constructed a recommended feature pool by a series of Random Forests based on the Gini index. Furthermore, by paying more attention to the features in the recommended feature pool, we can find the best subset more efficiently. To verify the performance of EGFAFS for FS, we tested EGFAFS on eight gene expression datasets compared with four heuristic-based FS methods (GA, PSO, SA, and DE) and four other FS methods (Boruta, HSICLasso, DNN-FS, and EGSG). The results show that EGFAFS has better performance for FS on gene expression data in terms of evaluation metrics, having more than the other eight FS algorithms. The genes selected by EGFAGS play an essential role in the differential co-expression network and some biological functions further demonstrate the success of EGFAFS for solving FS problems on gene expression data.     

Deep Multilabel Multilingual Document Learning for Cross-Lingual Document Retrieval

Cross-lingual document retrieval, which aims to take a query in one language to retrieve relevant documents in another, has attracted strong research interest in the last decades. Most studies on this task start with cross-lingual comparisons at the word level and then represent documents via word embeddings, which leads to insufficient structure information. In this work, the cross-lingual comparison at the document level is achieved through the cross-lingual semantic space. Our method, MDL (deep multilabel multilingual document learning), leverages a six-layer fully connected network to project cross-lingual documents into a shared semantic space. The semantic distances can be calculated when the cross-lingual documents are transformed into embeddings in semantic space. The supervision signals are automatically extracted from the data and then used to construct the semantic space via a linear classifier. The ambiguity of manual labels could be avoided and the multilabel supervision signals can be acquired instead of a single label. The representation of the semantic space is enriched by multilabel supervision signals, which improves the discriminative ability of the embeddings. The MDL is easy to extend to other fields since it does not depend on specific data. Furthermore, MDL is more efficient than the models training all languages jointly, since each language is trained individually. Experiments on Wikipedia data showed that the proposed method outperforms the state-of-the-art cross-lingual document retrieval methods.     

Facile Fabrication of 1-Methylimidazole/Cu Nanozyme with Enhanced Laccase Activity for Fast Degradation and Sensitive Detection of Phenol Compounds

Facile construction of functional nanomaterials with laccase-like activity is important in sustainable chemistry since laccase is featured as an efficient and promising catalyst especially for phenolic degradation but still has the challenges of high cost, low activity, poor stability and unsatisfied recyclability. In this paper, we report a simple method to synthesize nanozymes with enhanced laccase-like activity by the self-assembly of copper ions with various imidazole derivatives. In the case of 1-methylimidazole as the ligand, the as-synthesized nanozyme (denoted as Cu-MIM) has the highest yield and best activity among the nanozymes prepared. Compared to laccase, the K_m of Cu-MIM nanozyme to phenol is much lower, and the v_max is 6.8 times higher. In addition, Cu-MIM maintains excellent stability in a variety of harsh environments, such as high pH, high temperature, high salt concentration, organic solvents and long-term storage. Based on the Cu-MIM nanozyme, we established a method for quantitatively detecting phenol concentration through a smartphone, which is believed to have important applications in environmental protection, pollutant detection and other fields.     

Precise electro-reduction of alkyl halides for radical defluorinative alkylation

Reported here is a precise electro-reduction strategy for radical defluorinative alkylation towards the synthesis of gem-difluoroalkenes from α-trifluoromethylstyrenes. According to the redox-potential difference of the radical precursors, direct or indirect electrolysis is respectively adopted to realize the precise reduction. An easy-to-handle, catalyst-and metal-free condition is developed for the reduction of alkyl radical precursors that are generally easier to be reduced than α-trifluorome...     

金红石TiO_2中本征缺陷扩散性质的第一性原理计算

基于密度泛函理论的爬坡弹性带方法,对金红石相二氧化钛晶体中钛间隙、钛空位、氧间隙、氧空位4种本征缺陷的扩散特征进行了研究.对比4种本征缺陷在晶格内部沿不同扩散路径的过渡态势垒后发现,缺陷扩散过程呈现出明显的各向异性.其中,钛间隙和氧间隙沿[001]方向具有最小的扩散势垒路径,激活能分别为0.505 eV和0.859 eV;氧空位和钛空位的势垒最小的扩散路径分别沿[110]方向和[111]方向,激活能分别为0.735 eV和2.375 eV.     

在任意温度的热库中量子位的消相干

本文在Markov 近似下推导了在任意温度的热库中,一个量子位(qubit)的主方程,并由此讨论了由于振幅阻尼而引起的量子位消相干(decoherence). 结论表明量子位的跃迁频率与热库的特征频率及截止频率的关系对消相干有明显的影响。     

Pogostone Enhances the Antibacterial Activity of Colistin against MCR-1-Positive Bacteria by Inhibiting the Biological Function of MCR-1

The emergence of the plasmid-mediated colistin resistance gene mcr-1 has resulted in the loss of available treatments for certain severe infections. Here we identified a potential inhibitor of MCR-1 for the treatment of infections caused by MCR-1-positive drug-resistant bacteria, especially MCR-1-positive carbapenem-resistant Enterobacteriaceae (CRE). A checkerboard minimum inhibitory concentration (MIC) test, a killing curve test, a growth curve test, bacterial live/dead assays, scanning electron microscope (SEM) analysis, cytotoxicity tests, molecular dynamics simulation analysis, and animal studies were used to confirm the in vivo/in vitro synergistic effects of pogostone and colistin. The results showed that pogostone could restore the bactericidal activity of colistin against all tested MCR-1-positive bacterial strains or MCR-1 mutant–positive bacterial strains (FIC < 0.5). Pogostone does not inhibit the expression of MCR-1. Rather, it inhibits the binding of MCR-1 to substrates by binding to amino acids in the active region of MCR-1, thus inhibiting the biological activity of MCR-1 and its mutants (such as MCR-3). An in vivo mouse systemic infection model, pogostone in combination with colistin resulted in 80.0% (the survival rates after monotherapy with colistin or pogostone alone were 33.3% and 40.0%) survival at 72 h after infection of MCR-1-positve Escherichia coli (E. coli) ZJ487 (blaNDM-1-carrying), and pogostone in combination with colistin led to one or more order of magnitude decreases in the bacterial burdens in the liver, spleen and kidney compared with pogostone or colistin alone. Our results confirm that pogostone is a potential inhibitor of MCR-1 for use in combination with polymyxin for the treatment of severe infections caused by MCR-1-positive Enterobacteriaceae.     

Discriminant Analysis of the Nutritional Components between Organic Eggs and Conventional Eggs: A 1H NMR-Based Metabolomics Study

The difference of nutrient composition between organic eggs and conventional eggs has always been a concern of people. In this study, ¹H nuclear magnetic resonance (NMR) technique combined with multivariate statistical analyses was conducted to identify the metabolite different in egg yolk and egg white in order to reveal the nutritional components information between organic and conventional eggs. The results showed that the nutrient content and composition characteristics were different between organic and conventional eggs, among which the content of glucose, putrescine, amino acids and their derivatives were found higher in the organic eggs yolk, while phospholipids were demonstrated higher in conventional eggs yolk. Organic acid, alcohol, amine, choline and amino acids were higher in conventional eggs white, but glucose and lactate in organic egg were higher. Our study demonstrated that there are more nutritive components and higher nutritional value in organic eggs than conventional eggs, especially for the growth and development of infants and young children, and conventional eggs have more advantages in promoting lipid metabolism, preventing fatty liver, and reducing serum cholesterol. Eggs have important nutritional value to human body, and these two kinds of eggs can be selected according to the actual nutrient needs.