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Optimization of the methane production in batch anaerobic digestion of maize straw by adjustment of total solid and substrate-to-inoculum ratio based on kinetics

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International Journal of Agricultural and Biological Engineering 2024年第1期17卷 225-231页

作者： Feng Zhen Tao Xing lianhua li Yongming Sun Hongqiong Zhang Guangzhou Institute of Energy Conversion Chinese Academy of SciencesGuangzhou 510640China Guangdong Provincial Key Laboratory of New and Renewable Energy Research and Development Guangzhou 510640China College of Engineering Northeast Agricultural UniversityHarbin 150030China

Anaerobic digestion(AD)operating under conditions of organic overload stress typically exacerbates the potential for process instability,thereby resulting in significant economic and ecological *** this investigation,an augmented substrate-to-inoculum ratio(S/I)along with varying total solid content(TS)levels was employed to replicate diverse organic loadings,utilizing maize straw and cattle *** findings reveal that a moderate augmentation in S/I and TS proves advantageous in augmenting methane yield,while an excessive substrate loading diminishes methane yield,hampers the kinetics of methane production,and even induces severe process *** study also displayed the variation of the model parameters for the first-order model,the modified Gompertze model,and the transfer function *** the modified Gompertze model and transfer function model exhibited the same environmental stress ***,both the increase in particulate content and the increase in S/I had a substantial effect on the substrate conversion rate to *** analysis demonstrates the dominant influence of Firmicutes and Methanosarcina under different organic loading *** both a kinetic and a microbiological point of view,this work provides novel insights into the fundamental processes that regulate anaerobic digestion(AD)under varying loading ***,it has significant implications for improving the operating efficiency of AD,which is a significant benefit.

关键词： maize straw dry anaerobic digestion methane production microbial characteristics kinetic model

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A prognosis model for predicting immunotherapy response of esophageal cancer based on oxidative stress-related signatures

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Oncology Research 2024年第1期32卷 199-212页

作者： JING GUO CHANGYONG TONG JIANGUANG SHI XINJIAN li XUEQIN CHEN Department of Thoracic Surgery The First Affiliated Hospital of Ningbo UniversityNingboChina Department of Chinese Traditional Medicine The First Affiliated Hospital of Ningbo UniversityNingboChina

Oxidative stress(OS)is intimately associated with tumorigenesis and has been considered a potential therapeutic ***,the OS-associated therapeutic target for esophageal squamous cell carcinoma(ESCC)remains *** our study,gene expression data of ESCC and clinical information from public databases were *** LASSO-Cox regression analysis,a risk score(RS)signature map of prognosis was constructed and performed external verification with the GSE53625 *** ESTIMATE,xCell,CIBERSORT,TIMER,and ImmuCellAI algorithms were employed to analyze infiltrating immune cells and generate an immune microenvironment(IM).Afterward,functional enrichment analysis clarified the underlying mechanism of the *** was utilized for forecasting the survival rate of individual ESCC *** a result,we successfully constructed an OS-related genes(OSRGs)model and found that the survival rate of high-risk groups was lower than that of low-risk *** AUC of the ROC verified the strong prediction performance of the signal in these two cohorts *** to independent prognostic analysis,the RS was identified as an independent risk factor for *** nomogram and follow-up data revealed that the RS possesses favorable predictive value for the prognosis of ESCC ***-PCR detection demonstrated increased expression of MPC1,COX6C,CYB5R3,CASP7,and CYCS in esophageal cancer *** conclusion,we have constructed an OSRGs model for ESCC to predict patients’prognosis,offering a novel insight into the potential application of the OSRGs model in ESCC.

关键词： Esophageal carcinoma OS Prognosis Risk markers Immune cell infiltration

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Terrorism Attack Classification Using Machine Learning: The Effectiveness of Using Textual Features Extracted from GTD Dataset

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Computer Modeling in Engineering & Sciences 2024年第2期138卷 1427-1467页

作者： Mohammed Abdalsalam Chunlin li Abdelghani Dahou Natalia Kryvinska School of Computer Science and Technology Wuhan University of TechnologyWuhan430070China LDDI Laboratory Faculty of Science and TechnologyUniversity of Ahmed DRAIAAdrar01000Algeria Information Systems Department Faculty of ManagementComenius UniversityBratislava82005Slovakia

One of the biggest dangers to society today is terrorism, where attacks have become one of the most significantrisks to international peace and national security. Big data, information analysis, and artificial intelligence (AI) havebecome the basis for making strategic decisions in many sensitive areas, such as fraud detection, risk management,medical diagnosis, and counter-terrorism. However, there is still a need to assess how terrorist attacks are related,initiated, and detected. For this purpose, we propose a novel framework for classifying and predicting terroristattacks. The proposed framework posits that neglected text attributes included in the Global Terrorism Database(GTD) can influence the accuracy of the model’s classification of terrorist attacks, where each part of the datacan provide vital information to enrich the ability of classifier learning. Each data point in a multiclass taxonomyhas one or more tags attached to it, referred as “related tags.” We applied machine learning classifiers to classifyterrorist attack incidents obtained from the GTD. A transformer-based technique called DistilBERT extracts andlearns contextual features from text attributes to acquiremore information from text data. The extracted contextualfeatures are combined with the “key features” of the dataset and used to perform the final classification. Thestudy explored different experimental setups with various classifiers to evaluate the model’s performance. Theexperimental results show that the proposed framework outperforms the latest techniques for classifying terroristattacks with an accuracy of 98.7% using a combined feature set and extreme gradient boosting classifier.

关键词： Artificial intelligence machine learning natural language processing data analytic DistilBERT feature extraction terrorism classification GTD dataset

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On group structures of strategic-form games

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Fundamental Research 2024年第3期4卷 540-549页

作者： Zhigang Cao Guopeng li Zhibin Tan Xiaoguang Yang School of Economics and Management Beijing Jiaotong UniversityBeijing 100044China School of Economics Huazhong University of Science and TechnologyWuhan 430074China University of Chinese Academy of Sciences Beijing 100049China MADIS Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100049China

There are two recognized classes of strategic-form symmetric games,both of which can be conveniently defined through the corresponding player symmetry *** investigate the basic properties of these groups and several related *** generalize the notion of coveringness and adapt their results to characterize these player symmetry *** study the relationships between the coveringnesses of various symmetry *** results demonstrate that these symmetry groups have rich mathematical structures that are of game theoretical and economic interests.

关键词： Noncooperativegames Strategic-form games Symmetricgames Symmetry groups Covering groups

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Beta-alanine promotes angiogenesis in laser-induced choroidal neovascularization mice models

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International Journal of Ophthalmology(English edition) 2024年第9期17卷 1592-1598页

作者： Jia-li Wu Min Zhang Xiao-Dong Sun Department of Ophthalmology Shanghai General Hospital(Shanghai First People’s Hospital)Shanghai Jiao Tong UniversitySchool of MedicineShanghai 200080China National Clinical Research Center for Ophthalmic Diseases Shanghai 200080China National Clinical Research Center for Eye Diseases Shanghai 200080China Shanghai Key Laboratory of Fundus Diseases Shanghai 200080China Shanghai Engineering Center for Visual Science and Photomedicine Shanghai 200080China

AIM:To investigate the effect ofβ-alanine(BA)on laserinduced choroidal neovascularization(CNV)mice ***:Laser-induced CNV mice models were established,and BA was administrated for one week and two weeks in advance,***,retinal pigment epithelium(RPE)-choroid flat mounts were separated,and immunohistochemical staining was *** laser-induced CNV lesion areas were measured and *** addition,liver and kidney morphologies were observed to identify potential hepatorenal ***:Enlarged CNV lesion areas were observed in the BA treated *** significant differences were observed in the liver and kidney sections between ***:BA treatment increase CNV lesion areas,suggesting the detrimental effects of BA as a nutritional supplement in age-related macular degeneration(AMD)population.

关键词： age-related macular degeneration choroidal neovascularization β-alanine angiogenesis

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Artificial selection shapes the lower genomic diversity and higher selective pressures on the sex chromosomes of domestic animals

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Science China(life Sciences) 2024年第5期67卷 1072-1075页

作者： Meiming Wu Dongfeng Wang Meng-Hua li Fenghua Lv College of Animal Science and Technology China Agricultural UniversityBeijing 100193China CAS Key Laboratory of Animal Ecology and Conservation Biology Institute of ZoologyChinese Academy of Science(CAS)Beijing 100101China College of life Sciences University of Chinese Academy of SciencesBeijing 100049China Sanya Institute of China Agricultural University Sanya 572024China

Dear Editor,Sheep and goats were among the earliest domestic animals(Zeder,2008).During the transition from being hunted to being herded,excess males not involved in propagation were slaughtered at young ages under th... 详细信息

关键词： earliest harvest young

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DGConv: A Novel Convolutional Neural Network Approach for Weld Seam Depth Image Detection

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Computers, Materials & Continua 2024年第2期78卷 1755-1771页

作者： Pengchao li Fang Xu Jintao Wang Haibing Guo Mingmin liu Zhenjun Du State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang110169China University of Chinese Academy of Sciences Beijing100049China Shenyang SIASUN Robot&Automation Co. Ltd.Shenyang110168China

We propose a novel image segmentation algorithm to tackle the challenge of limited recognition and segmentation performance in identifying welding seam images during robotic intelligent ***,to enhance the capability of deep neural networks in extracting geometric attributes from depth images,we developed a novel deep geometric convolution operator(DGConv).DGConv is utilized to construct a deep local geometric feature extraction module,facilitating a more comprehensive exploration of the intrinsic geometric information within depth ***,we integrate the newly proposed deep geometric feature module with the Fully Convolutional Network(FCN8)to establish a high-performance deep neural network algorithm tailored for depth image ***,we enhance the FCN8 detection head by separating the segmentation and classification *** enhancement significantly boosts the network’s overall detection ***,for a comprehensive assessment of our proposed algorithm and its applicability in real-world industrial settings,we curated a line-scan image dataset featuring weld *** dataset,named the Standardized linear Depth Profile(SLDP)dataset,was collected from actual industrial sites where autonomous robots are in ***,we conducted experiments utilizing the SLDP dataset,achieving an average accuracy of 92.7%.Our proposed approach exhibited a remarkable performance improvement over the prior method on the identical ***,we have successfully deployed the proposed algorithm in genuine industrial environments,fulfilling the prerequisites of unmanned robot operations.

关键词： Weld image detection deep learning semantic segmentation depth map geometric feature extraction

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Evolutionary Neural Architecture Search and Its Applications in Healthcare

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 143-185页

作者： Xin liu Jie li Jianwei Zhao Bin Cao Rongge Yan Zhihan Lyu School of Economics and Management Hebei University of TechnologyTianjin300401China School of Artificial Intelligence Hebei University of TechnologyTianjin300401China School of Electrical Engineering Hebei University of TechnologyTianjin300401China Department of Game Design Uppsala UniversityUppsalaS-75105Sweden

Most of the neural network architectures are based on human experience,which requires a long and tedious trial-and-error *** architecture search(NAS)attempts to detect effective architectures without human *** algorithms(EAs)for NAS can find better solutions than human-designed architectures by exploring a large search space for possible *** multiobjective EAs for NAS,optimal neural architectures that meet various performance criteria can be explored and discovered ***,hardware-accelerated NAS methods can improve the efficiency of the *** existing reviews have mainly focused on different strategies to complete NAS,a few studies have explored the use of EAs for *** this paper,we summarize and explore the use of EAs for NAS,as well as large-scale multiobjective optimization strategies and hardware-accelerated NAS *** performs well in healthcare applications,such as medical image analysis,classification of disease diagnosis,and health *** for NAS can automate the search process and optimize multiple objectives simultaneously in a given healthcare *** neural network has been successfully used in healthcare,but it lacks *** data is highly sensitive,and privacy leaks are frequently reported in the healthcare *** solve these problems,in healthcare,we propose an interpretable neuroevolution framework based on federated learning to address search efficiency and privacy ***,we also point out future research directions for evolutionary ***,for researchers who want to use EAs to optimize NNs in healthcare,we analyze the advantages and disadvantages of doing so to provide detailed guidance,and propose an interpretable privacy-preserving framework for healthcare applications.

关键词： Neural architecture search evolutionary computation large-scale multiobjective optimization distributed parallelism healthcare

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Experimental and Numerical Evaluation of the Cavitation Performances of Self-Excited Oscillating Jets

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Fluid Dynamics & Materials Processing 2024年第8期20卷 1883-1901页

作者： Yuanyuan Zhao Fujian Zhao Guohui li Wei Xu Xiuli Wang School of the Environment and Safety Engineering Jiangsu UniversityZhenjiang212013China Research Center of Fluid Machinery Engineering and Technology Jiangsu UniversityZhenjiang212013China GongQing Institute of Science and Technology Jiujiang332020China School of Energy and Power Engineering Jiangsu UniversityZhenjiang212013China

Self-excited oscillating jets(SOJ)are used in several practical *** performances are significantly affected by structural parameters and the target *** this study,a geometric model of the SOJ nozzle accounting for multiple structural parameters is introduced,then the related cavitation performances and the optimal target distance are investigated using a Large-Eddy Simulation(LES)*** are also provided about an experiment,which was conducted to validate the simulation *** analyzing the evolution of the vapor volume fraction at the nozzle outlet,a discussion is presented about the effect of the aforementioned structural parameters on the cavitation performances and the target *** is shown that the distribution of cavitation clouds at the outlet of the SOJ nozzle displays a non-monotonic trend(first increasing,then decreasing).Under working conditions with an inlet pressure of 4 MPa,a SOJ nozzle outlet/inlet diameter ratio(D_(1)/D_(2))of 1.2,and a chamber diameter ratio(D/L)close to 1.8,the nozzle outlet cavitation performance attains a *** optimal structural parameters correspond to the optimal target distance,which is near 50 *** experiments have revealed that the SOJ nozzle with the above parameters displays a good cavitation erosion effect at the target distance of 50 mm,in satisfactory agreement with the numerical simulation results.

关键词： Self-excited oscillating nozzle cavitating jet target distant LES cavitation

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A chromosome-level genome assembly of the miiuy croaker(Miichthys miiuy)using nanopore sequencing and Hi-C

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Aquaculture and Fisheries 2024年第2期9卷 218-225页

作者： Tianjun Xu Ye li Weiwei Zheng Yuena Sun Laboratory of Fish Molecular Immunology College of Fisheries and Life ScienceShanghai Ocean UniversityShanghai201306China Laboratory of Marine Biology and Biotechnology Qingdao National Laboratory for Marine Science and TechnologyQingdao266200China Key Laboratory of Exploration and Utilization of Aquatic Genetic Resources(Shanghai Ocean University) Ministry of EducationShanghai201306China National Pathogen Collection Center for Aquatic Animals Shanghai Ocean UniversityShanghai201306China

Miiuy croaker,Miichthys miiuy is an ecologically important teleost species which is widely distributed in southeast coast of *** this study,we present a chromosomal-scale genome assembly of the miiuy croaker which is an important Sciaenidae fish and economical *** adopted Oxford Nanopore and Hi-C sequencing techniques to achieve an assembly with high accuracy and *** investigation of genome characteristic and functional features may provide insights into the study of phylogenetic diversity of miiuy *** study can also be beneficial to improve molecular assisted breeding ***,it can be a great resource to better conduct further study of other sciaenids.

关键词： Miiuy croaker Chromosomal assembly Genome annotation Genome evolution Phylogenetic

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