Mechanism Analysis and Dynamics Simulation of Assist Manipulator

In order to reduce labour intensity and improve working efficiency, a kind of assist manipulator was designed which is an auxiliary tool used for the assembly line of the marine diesel engine that can conveniently realize the delivery of parts and field assembly. Motion and force analysis of the mechanism of assist manipulator was examined with the help of MATLAB software on the base of d\u27Alembert principle, the disciplinary of displacement, velocity, acceleration, and force rules in the process of mechanism movement was obtained by mechanical analysis. Based on the kinematical analysis, the parameters of mechanism size were optimized to improve the loading state. The Creo software, ANSYS software, and RecurDyn software were used to model and analyse the rigid-flexible coupling dynamics of the manipulator, and the motion law and stress distribution of the key components was obtained

Two New Species of Dryinidae (Hymenoptera: Chrysidoidea) from China

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A new species of the genus Cryptoxilos Viereck (Hymenoptera: Braconidae: Euphorinae) from China

A new species of the genus Cryptoxilos Viereck, 1911 is described from China. This is the first record of the genus from the East Palaearctic region. The new species is included in a key to the described species of the genus. The subgeneric name Cryptoxiloides Capek & Capecki, 1979 is used to accommodate the Palaearctic species in the genus Cryptoxilos Viereck

Extremal permutations in routing cycles

Let G be a graph whose vertices are labeled 1, ... , n, and pi be a permutation on [n] := {1, 2, ... , n}. A pebble p(i) that is initially placed at the vertex i has destination pi(i) for each i is an element of [n]. At each step, we choose a matching and swap the two pebbles on each of the edges. Let rt(G, pi), the routing number for pi, be the minimum number of steps necessary for the pebbles to reach their destinations. Li, Lu and Yang proved that rt(C-n, pi) = 5, if rt(C-n, pi) = n-1, then pi = 23 ... n1 or its inverse. By a computer search, they showed that the conjecture holds for n \u3c 8. We prove in this paper that the conjecture holds for all even n \u3e= 6

NCAGC: A Neighborhood Contrast Framework for Attributed Graph Clustering

Attributed graph clustering is one of the most fundamental tasks among graph learning field, the goal of which is to group nodes with similar representations into the same cluster without human annotations. Recent studies based on graph contrastive learning method have achieved remarkable results when exploit graph-structured data. However, most existing methods 1) do not directly address the clustering task, since the representation learning and clustering process are separated; 2) depend too much on data augmentation, which greatly limits the capability of contrastive learning; 3) ignore the contrastive message for clustering tasks, which adversely degenerate the clustering results. In this paper, we propose a Neighborhood Contrast Framework for Attributed Graph Clustering, namely NCAGC, seeking for conquering the aforementioned limitations. Specifically, by leveraging the Neighborhood Contrast Module, the representation of neighbor nodes will be 'push closer' and become clustering-oriented with the neighborhood contrast loss. Moreover, a Contrastive Self-Expression Module is built by minimizing the node representation before and after the self-expression layer to constraint the learning of self-expression matrix. All the modules of NCAGC are optimized in a unified framework, so the learned node representation contains clustering-oriented messages. Extensive experimental results on four attributed graph datasets demonstrate the promising performance of NCAGC compared with 16 state-of-the-art clustering methods. The code is available at https://github.com/wangtong627/NCAGC

Discovery of Xestophanopsis gen. n. from China and taxonomic revision of two species misplaced in Ceroptres Hartig, 1840 (Hymenoptera, Cynipoidea: Cynipidae)

In the present paper, we describe Xestophanopsis Pujade-Villar &Wang gen. n. to the tribe Diastrophini based on Ceroptres distinctusWang, Liu & Chen, 2012 and transfer Ceroptres distinctusWang, Liu&Chen, 2012 to Periclistus Foerster, 1869 as Periclistus setosus (Wang, Liu & Chen, 2012) comb. n. In addition, we report the first record of Periclistus capillatus Kovalev, 1968 from China, along with the first report and description of themale. Finally, we provide a taxonomic key to all Eastern Palaearctic species of the genus Periclistus

Inversion of Different Cultivated Soil Types’ Salinity Using Hyperspectral Data and Machine Learning

Soil salinization is one of the main causes of global desertification and soil degradation. Although previous studies have investigated the hyperspectral inversion of soil salinity using machine learning, only a few have been based on soil types. Moreover, agricultural fields can be improved based on the accurate estimation of the soil salinity, according to the soil type. We collected field data relating to six salinized soils, Haplic Solonchaks (HSK), Stagnic Solonchaks (SSK), Calcic Sonlonchaks (CSK), Fluvic Solonchaks (FSK), Haplic Sonlontzs (HSN), and Takyr Solonetzs (TSN), in the Hetao Plain of the upper reaches of the Yellow River, and measured the in situ hyperspectral, pH, and electrical conductivity (EC) values of a total of 231 soil samples. The two-dimensional spectral index, topographic factors, climate factors, and soil texture were considered. Several models were used for the inversion of the saline soil types: partial least squares regression (PLSR), random forest (RF), extremely randomized trees (ERT), and ridge regression (RR). The spectral curves of the six salinized soil types were similar, but their reflectance sizes were different. The degree of salinization did not change according to the spectral reflectance of the soil types, and the related properties were inconsistent. The Pearson’s correlation coefficient (PCC) between the two-dimensional spectral index and the EC was much greater than that between the reflectance and EC in the original band. In the two-dimensional index, the PCC of the HSK-NDI was the largest (0.97), whereas in the original band, the PCC of the SSK400 nm was the largest (0.70). The two-dimensional spectral index (NDI, RI, and DI) and the characteristic bands were the most selected variables in the six salinized soil types, based on the variable projection importance analysis (VIP). The best inversion model for the HSK and FSK was the RF, whereas the best inversion model for the CSK, SSK, HSN, and TSN was the ERT, and the CSK-ERT had the best performance (R2 = 0.99, RMSE = 0.18, and RPIQ = 6.38). This study provides a reference for distinguishing various salinization types using hyperspectral reflectance and provides a foundation for the accurate monitoring of salinized soil via multispectral remote sensing

Characterization of RNA editome in primary and metastatic lung adenocarcinomas

RNA editing results in post-transcriptional modification and could potentially contribute to carcinogenesis. However, RNA editing in advanced lung adenocarcinomas has not yet been studied. Based on whole genome and transcriptome sequencing data, we identified 1,071,296 RNA editing events from matched normal, primary and metastatic samples contributed by 24 lung adenocarcinoma patients, with 91.3% A-to-G editing on average, and found significantly more RNA editing sites in tumors than in normal samples. To investigate cancer relevant editing events, we detected 67,851 hyper-editing sites in primary and 50,480 hyper-editing sites in metastatic samples. 46 genes with hyper-editing in coding regions were found to result in amino acid alterations, while hundreds of hyper-editing events in non-coding regions could modulate splicing or gene expression, including genes related to tumor stage or clinic prognosis. Comparing RNA editome of primary and metastatic samples, we also discovered hyper-edited genes that may promote metastasis development. These findings showed a landscape of RNA editing in matched normal, primary and metastatic tissues of lung adenocarcinomas for the first time and provided new insights to understand the molecular characterization of this disease