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Genomic insights into adaptation to bipedal saltation and desert-like habitats of jerboas

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Science China(Life Sciences) 2024年第9期67卷 2003-2015页

作者： Simin Chai Yujie Chong Daiqing yin Qiang Qiu Shixia Xu Guang yang Southern Marine Science and Engineering Guangdong Laboratory(Guangzhou) Guangzhou 511458China Jiangsu Key Laboratory for Biodiversity and Biotechnology School of Life SciencesNanjing Normal UniversityNanjing 210023China School of Ecology and Environment Northwestern Polytechnical UniversityXi’an 710072China

Jerboas is a lineage of small rodents displaying atypical mouse-like morphology with elongated strong hindlimbs and short *** have evolved obligate bipedal saltation and acute senses,and been well-adapted to vast desert-like *** a newly sequenced chromosome-scale genome of the Mongolian five-toed jerboa(Orientallactaga sibirica),our comparative genomic analyses and in vitro functional assays showed that the genetic innovations in both protein-coding and non-coding regions played an important role in jerboa morphological and physiological ***-specific amino acid substitutions,and segment insertions/deletions(indels)in conserved non-coding elements(CNEs)were found in components of proteoglycan biosynthesis pathway(XYLT1 and CHSY1),which plays an important role in limb ***,we found specific evolutionary changes functionally associated with energy or water metabolism(e.g.,specific amino acid substitutions in ND5 and indels in CNEs physically near ROR2)and senses(e.g.,expansion of vomeronasal receptors and the FAM136A gene family)in *** dual-luciferase reporter assay verified that some of the CNEs with jerboa-specific segment indels exerted a significantly different influence on luciferase activity,suggesting changes in their regulatory function in *** results revealed the potential molecular mechanisms underlying jerboa adaptation since the divergence from the Eocene-Oligocene transition,and provided more resources and new insights to enhance our understanding of the molecular basis underlying the phenotypic diversity and the environmental adaptation of mammals.

关键词： jerboa adaptive evolution comparative genomics conserved non-coding elements bipedal saltation

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Modelling and validation of flash flood inundation in drylands

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Journal of Geographical Sciences 2024年第1期34卷 185-200页

作者： GAO Dan yin Jie WANG Dandan yang Yuhan LU Yi CHEN Ruishan School of Geographic Sciences East China Normal UniversityShanghai 200241China Key Laboratory of Geographic Information Science of Ministry of Education East China Normal UniversityShanghai 200241China National Disaster Reduction Center of China Ministry of Emergency Management of People's Republic of ChinaBeijing 100124China School of Design Shanghai Jiao Tong UniversityShanghai 200240China

In the context of climate change and human activities,flood disasters in arid mountainous areas have become increasingly frequent,and seriously threatened the safety of people's lives and *** and accurate flash flood inundation modelling is an essential foundational research area,which can aid in the reduction of casualties and the minimization of disaster losses;however,this modelling is also very difficult,and models need to be urgently developed to address flash flood forecasting and *** objective of this study is to construct a numerical modelling method for flash floods in *** on a 2D high-resolution flood numerical model(Flood Map-Hydro Inundation2D),we hindcasted the dynamic process of flash flooding and show the spatio-temporal characteristics of flash flood inundation for the“8·18”flash flood disaster that occurred in Datong county,Qinghai *** results showed that the model output effectively agreed with the observed inundation after the event in terms of both spatial extent and temporal *** flooding mainly occurred between 00:00 and 01:00 on August 18,***,Hejiazhuang and Longwo villages were affected most *** further conducted model sensitivity analysis and found that the model was highly sensitive to both roughness and hydraulic conductivity in drylands,and the effect of hydraulic conductivity was more *** study confirmed the good performance of our model for the simulation of flash flooding in arid areas and provides a potential method for flash flood assessment and management in arid areas.

关键词： flash flood numerical modelling arid areas Datong county Flood Map-Hydro Inundation2D

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DeepOCL:A deep neural network for Object Constraint Language generation from unrestricted nature language

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CAAI Transactions on Intelligence Technology 2024年第1期9卷 250-263页

作者： Yilong yang Yibo Liu Tianshu Bao Weiru Wang Nan Niu Yongfeng yin School of Software Beihang UniversityBeijingChina College of Computer Science and Technology Guizhou UniversityGuiyangGuizhouChina Faculty of Information Technology Beijing University of TechnologyBeijingChina Department of Electrical Engineering and Computer Sciences University of CincinnatiCincinnatiOhioUSA

Object Constraint Language(OCL)is one kind of lightweight formal specification,which is widely used for software verification and validation in NASA and Object Management Group *** OCL provides a simple expressive syntax,it is hard for the developers to write correctly due to lacking knowledge of the mathematical foundations of the first-order logic,which is approximately half accurate at the first stage of devel-opment.A deep neural network named DeepOCL is proposed,which takes the unre-stricted natural language as inputs and automatically outputs the best-scored OCL candidates without requiring a domain conceptual model that is compulsively required in existing rule-based generation *** demonstrate the validity of our proposed approach,ablation experiments were conducted on a new sentence-aligned dataset named *** experiments show that the proposed DeepOCL can achieve state of the art for OCL statement generation,scored 74.30 on BLEU,and greatly outperformed experienced developers by 35.19%.The proposed approach is the first deep learning approach to generate the OCL expression from the natural *** can be further developed as a CASE tool for the software industry.

关键词： deep learning OCL software engineering

Remote copper-catalyzed enantioselective substitution of yne-thiophene carbonates

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Science China Chemistry 2024年第4期67卷 1175-1180页

作者： Hao-Dong Qian Xiang Li Tingrui yin Wei-Feng Qian Chunhui zhao Cuiju Zhu Hao Xu CCNU-uOttawa Joint Research Centre Key Laboratory of Pesticides&Chemical Biology of Ministry of EducationInternational Joint Research Center for Intelligent Biosensing Technology and HealthCollege of ChemistryCentral China Normal UniversityWuhan 430079China

Here,we describe a strategy for the copper-catalyzed asymmetric heteroarylation of yne-thiophene carbonates with indoles via remote *** key to the success of this strategy lies in the design of the alkynyl group at the ortho-position of the heterocycle thiophene,enabling the formation of a triarylmethane moiety via very remote ***,the concept of remote copper-catalyzed asymmetric transformation extends not only to yne-allylic esters but also to yne-aryl *** reaction readily provides a diverse array of chiral triarylmethanes with high efficiency,enantioselectivity,and excellent functional group ***,facile follow-up transformations underscore their potential utility in the synthesis of various enantioenriched building *** mechanistic studies support the plausibility of the remote substitution pathway.

关键词： remote substitution copper catalyst asymmetric catalysis triaryl methanes

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Generative adversarial networks based motion learning towards robotic calligraphy synthesis

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CAAI Transactions on Intelligence Technology 2024年第2期9卷 452-466页

作者： Xiaoming Wang Yilong yang Weiru Wang Yuanhua Zhou Yongfeng yin Zhiguo Gong Department of Computer and Information Science University of MacaoMacaoChina School of Software Beihang UniversityBeijingChina Department of Computer Science and Technology Faculty of Information TechnologyBeijing University of TechnologyBeijingChina School of Foreign Languages Guangzhou Huashang CollegeGuangzhouChina

Robot calligraphy visually reflects the motion capability of robotic *** traditional researches mainly focus on image generation and the writing of simple calligraphic strokes or characters,this article presents a generative adversarial network(GAN)-based motion learning method for robotic calligraphy synthesis(Gan2CS)that can enhance the efficiency in writing complex calligraphy words and reproducing classic calligraphy *** key technologies in the proposed approach include:(1)adopting the GAN to learn the motion parameters from the robot writing operation;(2)converting the learnt motion data into the style font and realising the transition from static calligraphy images to dynamic writing demonstration;(3)reproducing high-precision calligraphy works by synthesising the writing motion data *** this study,the motion trajectories of sample calligraphy images are firstly extracted and converted into the robot *** robot performs the writing with motion planning,and the writing motion parameters of calligraphy strokes are learnt with *** the motion data of basic strokes is synthesised based on the hierarchical process of‘stroke-radicalpart-character’.And the robot re-writes the synthesised characters whose similarity with the original calligraphy characters is *** calligraphy characters have been tested in the experiments for method validation and the results validated that the robot can actualise the robotic calligraphy synthesis of writing motion data with GAN.

关键词： calligraphy synthesis generative adversarial networks Motion learning robot writing

Joint UAV trajectory and communication design with heterogeneous multi-agent reinforcement learning

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Science China(Information Sciences) 2024年第3期67卷 225-245页

作者： Xuanhan ZHOU Jun XIONG Haitao zhao Xiaoran LIU Baoquan REN Xiaochen ZHANG Jibo WEI Hao yin College of Electronic Science and Technology National University of Defense Technology Systems Engineering Institute Academy of Military Sciences PLA

Unmanned aerial vehicles(UAVs) are recognized as effective means for delivering emergency communication services when terrestrial infrastructures are unavailable. This paper investigates a multiUAV-assisted communication system, where we jointly optimize UAVs’ trajectories, user association, and ground users(GUs)’ transmit power to maximize a defined fairness-weighted throughput metric. Owing to the dynamic nature of UAVs, this problem has to be solved in real time. However, the problem’s non-convex and combinatorial attributes pose challenges for conventional optimization-based algorithms, particularly in scenarios without central controllers. To address this issue, we propose a multi-agent deep reinforcement learning(MADRL) approach to provide distributed and online solutions. In contrast to previous MADRLbased methods considering only UAV agents, we model UAVs and GUs as heterogeneous agents sharing a common objective. Specifically, UAVs are tasked with optimizing their trajectories, while GUs are responsible for selecting a UAV for association and determining a transmit power level. To learn policies for these heterogeneous agents, we design a heterogeneous coordinated QMIX(HC-QMIX) algorithm to train local Q-networks in a centralized manner. With these well-trained local Q-networks, UAVs and GUs can make individual decisions based on their local observations. Extensive simulation results demonstrate that the proposed algorithm outperforms state-of-the-art benchmarks in terms of total throughput and system fairness.

关键词： unmanned aerial vehicle (UAV) trajectory design resource allocation multi-agent deep reinforcement learning (MADRL) heterogeneous agents

Review on analytical technologies and applications in metabolomics

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BIOCELL 2024年第1期48卷 65-78页

作者： XIN MENG YAN LIU SHUJUN XU LIANRONG yang RUI yin School of Pharmacy Heilongjiang University of Chinese MedicineHarbinChina

Over the past decade,the swift advancement of metabolomics can be credited to significant progress in technologies such as mass spectrometry,nuclear magnetic resonance,and multivariate ***,metabolomics garners widespread application across diverse fields including drug research and development,early disease detection,toxicology,food and nutrition science,biology,prescription,and chinmedomics,among *** serves as an effective characterization technique,offering insights into physiological process alterations in *** changes may result from various exogenous factors like environmental conditions,stress,medications,as well as endogenous elements including genetic and protein-based *** potential scientific outcomes gleaned from these insights have catalyzed the formulation of innovative methods,poised to further broaden the scope of this ***,metabolomics has evolved into a valuable and widely accepted instrument in the life ***,comprehensive reviews focusing on the sample preparation and analytical methodologies employed in metabolomics within the life sciences are surprisingly *** review aims to fill that gap,providing an overview of current trends and recent advancements in *** emphasis is placed on sample preparation,sophisticated analytical techniques,and their applications in life science research.

关键词： Metabolomics Sample preparation Analytical methods Application of metabolomics

Natural rubber latex as a potential additive for water-based drilling fluids

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Petroleum Science 2024年第4期21卷 2677-2687页

作者： Jun yang Guan-Cheng Jiang Jing-Tian Yi yin-Bo He Li-Li yang Teng-Fei Dong Guo-Shuai Wang College of Petroleum Engineering China University of Petroleum (Beijing) National Engineering Research Center of Oil & Gas Drilling and Completion Technology Changqing Drilling General Company CNPC Chuanqing Drilling Engineering Company Limited

The environmental hazards and "carbon footprint" of oil and gas drilling can be significantly reduced by replacing traditional petroleum-based chemical additives with natural materials derived from plants and animals. This paper explored for the first time the interaction mechanism between natural rubber latex(NRL) and bentonite suspensions(BTs) through a series of characterization experiments, as well as the potential applications in water-based drilling fluids(WBDF). The gel viscoelasticity experiments showed that NRL could decrease the consistency coefficient(k) and flow index(n) of BTs, and enhance the shear thinning performance of BTs as pseudo-plastic fluids. In addition, 0.5 w/v% NRL not only increased the critical yield stress and strengthened the structural strength between the bentonite particles, but also facilitated the compatibility of pressure loss and flow efficiency. The evaluation of colloidal stability and WBDF performance indicated that NRL particles could promote the hydration and charge stability on the surface of BTs particles, and optimize the particle size distribution and flow resistance of WBDF under the "intercalation-exfoliation-encapsulation" synergistic interaction. Moreover, NRL can improve the rheological properties of WBDF at high temperatures(<150.C), and form a dense blocking layer by bridging and sealing the pores and cracks of the filter cake, which ultimately reduces the permeability of the cake and the filtration loss of WBDF.

关键词： Natural materials Water-based drilling fluids Natural rubber latex Bentonite suspensions Filtration loss

Convolution-Transformer for Image Feature Extraction

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Computer Modeling in Engineering & Sciences 2024年第10期141卷 87-106页

作者： Lirong yin Lei Wang Siyu Lu Ruiyang Wang Youshuai yang Bo yang Shan Liu Ahmed AlSanad Salman A.AlQahtani Zhengtong yin Xiaolu Li Xiaobing Chen Wenfeng Zheng Department of Geography and Anthropology Louisiana State UniversityBaton RougeLA70803USA School of Automation University of Electronic Science and Technology of ChinaChengdu610054China College of Computer and Information Sciences King Saud UniversityRiyadh11574Saudi Arabia College of Resources and Environmental Engineering Key Laboratory of Karst Georesources and Environment(Guizhou University)Ministry of EducationGuiyang550025China School of Geographical Sciences Southwest UniversityChongqing400715China School of Electrical and Computer Engineering Louisiana State UniversityBaton RougeLA70803USA

This study addresses the limitations of Transformer models in image feature extraction,particularly their lack of inductive bias for visual *** to Convolutional Neural Networks(CNNs),the Transformers are more sensitive to different hyperparameters of optimizers,which leads to a lack of stability and slow *** tackle these challenges,we propose the Convolution-based Efficient Transformer Image Feature Extraction Network(CEFormer)as an enhancement of the Transformer *** model incorporates E-Attention,depthwise separable convolution,and dilated convolution to introduce crucial inductive biases,such as translation invariance,locality,and scale invariance,into the Transformer ***,we implement a lightweight convolution module to process the input images,resulting in faster convergence and improved *** results in an efficient convolution combined Transformer image feature extraction *** results on the ImageNet1k Top-1 dataset demonstrate that the proposed network achieves better accuracy while maintaining high computational *** achieves up to 85.0%accuracy across various model sizes on image classification,outperforming various baseline *** integrated into the Mask Region-ConvolutionalNeuralNetwork(R-CNN)framework as a backbone network,CEFormer outperforms other models and achieves the highest mean Average Precision(mAP)*** research presents a significant advancement in Transformer-based image feature extraction,balancing performance and computational efficiency.

关键词： Transformer E-Attention depth convolution dilated convolution CEFormer