Multi-Omics Analysis Provides Insight into the Possible Molecular Mechanism of Hay Fever Based on Gut MicrobiotaOA

Due to the worldwide epidemic of allergic disease and a cure nowhere in sight, there is a crucial need to explore its pathophysiological mechanisms. As allergic disease has been associated with gut dysbiosis, we searched for a possible mechanism from the perspective of the molecular interface between host and microbiota with concurrent metabolomics and microbiome composition analysis. Sprague-Dawley rats were injected with Artemisia pollen extract to stimulate a hyper reaction to pollen. This hy...     

Research on a Vibrating Mill Control System Based on a Fuzzy Neural Network

Vibrating mills play an important role in the field of preparation of ultrafine powder.The purpose of a vibrating mill load control system is to increase productivity and ensure the mill runs smoothly.In this paper,we first summarized prior knowledge of control rules on the basis of analysis after repeated experiments,and realized fuzzy automation taking advantage of fuzzy theory.Since fuzzy control systems not only over rely on experience but also lack a self-learning function,we design a fuzzy neural netw...     

Approximation and universality of fuzzy Turing machines

Fuzzy Turing machines are the formal models of fuzzy algorithms or fuzzy computations. In this paper we give several different formulations of fuzzy Turing machine, which correspond to nondeterministic fuzzy Turing machine using max-＊ composition for some t-norm＊ （or NFTM＊, for short）, nondeterministic fuzzy Turing machine （or NFTM）, deterministic fuzzy Turing machine （or DFTM）, and multi-tape versions of fuzzy Turing machines. Some distinct results compared to those of ordinary Turing machines are obtained. First, it is shown that NFTM＊, NFTM, and DFTM are not necessarily equivalent in the power of recognizing fuzzy languages if the t-norm＊ does not satisfy finite generated condition, but are equivalent in the approximation sense. That is to say, we can approximate an NFTM＊ by some NFTM with any given accuracy; the related constructions are also presented. The level characterization of fuzzy recursively enumerable languages and fuzzy recursive languages are exploited by ordinary r.e. languages and recursive languages. Second, we show that universal fuzzy Turing machine exists in the approximated sense. There is a universal fuzzy Turing machine that can simulate any NFTM＊ on it with a given accuracy.     

An Efficient WRF Framework for Discovering Risk Genes and Abnormal Brain Regions in Parkinson’s Disease Based on Imaging Genetics Data

As an emerging research field of brain science,multimodal data fusion analysis has attracted broader attention in the study of complex brain diseases such as Parkinson's disease (PD).However,current studies primarily lie with detecting the association among different modal data and reducing data attributes.The data mining method after fusion and the overall analysis framework are neglected.In this study,we propose a weighted random forest (WRF) model as the feature screening classifier.The interactions between genes and brain regions are detected as input multimodal fusion features by the correlation analysis method.We implement sample classification and optimal feature selection based on WRF,and construct a multimodal analysis framework for exploring the pathogenic factors of PD.The experimental results in Parkinson's Progression Markers Initiative (PPMI) database show that WRF performs better compared with some advanced methods,and the brain regions and genes related to PD are detected.The fusion of multi-modal data can improve the classification of PD patients and detect the pathogenic factors more comprehensively,which provides a novel perspective for the diagnosis and research of PD.We also show the great potential of WRF to perform the multimodal data fusion analysis of other brain diseases.     

Extended hopanes and 8,14-secohopanes up to C40in unbiodegraded marine oils from the Tarim Basin,NW China

Extended 17α(H),21β(H)-hopanes and three series of 8,14-secohopanes up to C₄₀,including 8α(H),14α(H),17α(H),21β(H)-,8α(H),14α(H),17β(H),21α(H)-and 8α(H),14β(H),17 β(H),21α(H)-,were detected by GC-MS-MS method in the branched/cyclic hydrocarbon fractions of some unbiodegraded marine oils from the Tazhong uplift in the Tarim Basin,NW China.The coexistence of extended hopanes and 8,14-secohopanes up to C₄₀ in unbiodegraded oils suggests that they are primary and independent on...     

Database Translation Mechanism: Generating Data Dictionary for Relational Database

In order to optimize workflow and improve efficiency, modern enterprises usually entrust software providers to build the Enterprise Information System (EIS). However, the software providers generally do not provide the data dictionary for the EIS relational database, which brings great difficulties for enterprises to use the data stored in the EIS database. This paper proposes a method named database translation mechanism for generating the data dictionary of the EIS relational database which only utilizes the data collected from the interfaces of EIS. Inspired by the great success that Graph Neural Networks (GNNs) have achieved, the study builds a graph structure for the EIS relational database by mining the relationships between columns and then train a GNN-based classifier to predict to which column the value belongs. In addition, a table-based sampling method is designed to construct graph datasets for mini-batch training on the large-scale graph structure. Furthermore, a uniform encoding method and a hybrid aggregator function are proposed to improve the performance of the GNN-based classifier. The trained GNN-based classifier can be used to predict the matching relationships between the columns of the EIS database and the tables extracted from the EIS interfaces given the fact that the data in the database is entered at the interfaces. In this way, the detailed information at the interface to translate the database can be used. Experimental results on a real-world ERP relational database demonstrate the superior performance of the proposed method, which efficiently exploits and utilizes the graph structure information in the relational database.     

卡塞格伦镜头的猫眼效应激光反射特性

卡塞格伦(Cassegrain)及类卡塞格伦式光学镜头在光电装备中应用广泛.为了研究具备卡塞格伦式光学镜头的光电装备所特有的猫眼效应特性,采用ZEMAX光学设计分析软件建立了卡塞格伦镜头反射模型,利用物理光学传输方法仿真分析了其猫眼效应反射特性,并得出了猫眼效应可探测入射角范围.对一特定卡塞格伦镜头进行了激光辐照实验,得到了猫眼效应反射光斑图像,测试了猫眼效应绝对反射率以及反射光发散角.结果表明,当发射系统位于该卡塞格伦镜头的视场内时,可以探测到猫眼效应反射光,中心遮挡造成原路返回处光强分布中心能量降低,猫眼效应绝对反射率为11.48%,反射光发散角为3.3 mrad,按照假设条件可以满足30 km内激光主动探测的需要.     

Research on Laser Direct Deposition Process of Ti-6Al-4V Alloy

Laser direct deposition （LDD） of metallic components is an advanced technology of combining CAD/CAM （computer aided design/computer aided manufacturing）, high power laser, and rapid prototyping. This technology uses laser beam to melt the powders fed coaxiaUy into the molten pool by the laser beam to fabricate fuUy dense metallic components. The present article mainly studies the LDD of Ti-6Al-4V alloy, which can be used to fabricate aircraft components. The mechanical properties of the Ti-6Al-4V alloy, fabricated by LDD, are obtained using the tension test, and the oxygen content of used powders and deposited specimens are measured. In the present article, it can be seen that the mechanical properties obtained using this method are higher than the ones obtained by casting, and equal to those got by wrought anneal. One aircraft part has been made using the LDD process. Because of this aircraft part, with sophisticated shape, the effect of the laser scanning track on the internal soundness of the deposited part was discussed.     

Orientation Field Code Hashing: A Novel Method for Fast Palmprint Identification

For a large-scale palmprint identification system,it is necessary to speed up the identification process to reduce the response time and also to have a high rate of identification accuracy.In this paper,we propose a novel hashing-based technique called orientation field code hashing for fast palmprint identification.By investigating hashing-based algorithms,we first propose a double-orientation encoding method to eliminate the instability of orientation codes and make the orientation codes more reasonable.Secondly,we propose a window-based feature measurement for rapid searching of the target.We explore the influence of parameters related to hashing-based palmprint identification.We have carried out a number of experiments on the Hong Kong Poly U large-scale database and the CASIA palmprint database plus a synthetic database.The results show that on the Hong Kong Poly U large-scale database,the proposed method is about 1.5 times faster than the state-of-the-art ones,while achieves the comparable identification accuracy.On the CASIA database plus the synthetic database,the proposed method also achieves a better performance on identification speed.     

NUMERICAL SIMULATION OF TURBULENT JETS WITH LATERAL INJECTION INTO A CROSSFLOW

1. INTRODUCTION The interaction of jets with crossflow generates complex flow fields which exist in a variety of industrial applications, e.g. internal film cooling of turbine blades, dilution air jets in combustion chambers, jet from V/STOL aircraft in transition flight. Systematic experimental, theoretical and numerical investigations of the flow fields began several decades ago, where the parameters studied include the jet injection angel, the jet-to-crossflow velocity ratio, the jet …