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comparisons of oxbow lake fish assemblages in relation to bigheaded carp establishment in the lower White River, Arkansas

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Ecological Processes 2024年第1期13卷 188-205页

作者： michael A.Eggleton cody J.Salzmann Joseph E.Kaiser Shannon c.F.smith Department of Aquaculture and Fisheries University of Arkansas at Pine Bluff Arkansas Game and Fish commission Virginia Institute of marine Science

Background Since the late 1990s, bigheaded carps(largely silver carp [Hypophthalmichthys molitrix] but also bighead carp [H. nobilis]) have established throughout the lower mississippi River basin. Using previously studied oxbow lakes in the lower White River basin, Arkansas, we compared current(2017, “post-carp” establishment) fish assemblages to historical(2002, “pre-carp” establishment) fish assemblages. Fish assemblages were comprehensively assessed using multiple gears, including boat electrofishing, mini-fyke nets, and experimental small-mesh gill *** T-tests suggested that fish assemblage indices of richness, diversity, evenness, and dominance were often greater(P carp period as reflected by boat electrofishing and experimental gill nets. However, all indices were generally similar(P > 0.05) between the pre-carp and post-carp period with fish assemblages depicted using mini-fyke nets. Nonmetric multidimensional scaling analyses indicated that fish assemblages differed structurally between pre-carp and post-carp periods. Assemblage differences were linked to both small and large abundance changes for more than 20 species. Abundances of gizzard shad(Dorosoma cepedianum), emerald shiner(Notropis atherinoides), pugnose minnow(Opsopoeodus emiliae), crappies(Pomoxis spp.), bluegill(Lepomis macrochirus), orangespotted sunfish(L. humilis), and yellow bass(morone mississippiensis) declined between the pre-carp and postcarp periods. conversely, abundances of weed shiner(N. texanus), pallid shiner(Hybopsis amnis), longear sunfish(L. megalotis), buffalofishes(Ictiobus spp.), and gars(Lepisosteus spp.) generally increased during the same *** Although not possible to conclude assemblage shifts were entirely related to bigheaded carps due to the absence of an appropriate reference system where carps did not establish, the wide establishment of these carps is one of the most pervasive changes to have occurred in the lower White

关键词： Bigheaded carp Silver carp Aquatic nuisance species Fish assemblage Oxbow lake Large river

Thermodynamic analysis of metal segregation in dual phase high entropy ceramics

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Journal of materiomics 2024年第4期10卷 889-895页

作者： Steven m.smith II William G.Fahrenholtz Gregory E.Hilmas Stefano curtarolo missouri University of Science and Technology Materials Science and Engineering DepartmentRollaMO65409USA Duke University Department of Mechanical Engineering and Materials ScienceDurhamNC27708USA Duke University Center of Autonomous Materials DesignDurhamNC27708USA

Equilibrium Gibbs'free energy calculations were used to determine metal segregation trends between boride and carbide solid solutions containing two metals that are relevant to dual phase high entropy *** model predicted that Ti had the strongest tendency to segregate to the boride phase followed by Zr,Nb,mo,V,Hf,and Ta,which matches experimental results of measured *** ratio of a metal in the carbide phase to the content of the same metal in the corresponding metal boride had a linear trend with the change in standard Gibbs'free energy of reaction for a metal carbide reacting with B_(4)c to produce its corresponding metal boride and *** proposed model was used to predict the changes in standard Gibbs'free energy for crc→crB_(2) to be−260 kJ and Wc→WB_(2) to be 148 kJ,which indicates that cr has the strongest segregation to the boride and W has the strongest segregation to the *** proposed model can be used to estimate the segregation of metals in dual phase high entropy boride-carbide ceramics of any boride/carbide ratio or metal content.

关键词： Dual phase High entropy ceramic Boride carbide Thermodynamics

consumer transparency in the production chain for plant varieties produced using new genomic techniques

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aBIOTEcH 2024年第2期5卷 239-246页

作者： J.m.Lukasiewicz c.c.m.van de Wiel L.A.P.Lotz m.J.m.Smulders Wageningen University&Research P.O.Box 386NL-6700 AJ WageningenThe Netherlands

Plants edited with new genomic techniques(NGTs)currently fall under the Genetically modified Organisms Directive(2001/18/Ec)in the European *** the proposal of the European commission,NGT plants are partially exempted from the regulations of this *** proposal makes a distinction between two categories of NGT plants:NGT-1 and ***-1 category plants are considered equal to plants obtained through conventional breeding *** plants will not be labelled for the consumer,although they will be labelled as ***-2 category plants may be labelled with additional information as a positive *** of seeds of varieties made with gene editing,but not the products,would mean that most steps in the production chain are transparent,but not the last step towards ***“right to know”and increasing knowledge of gene-edited food is a common theme in food labelling towards ***,we describe current labelling regimes and registers and how these may be applied to provide transparency on gene-edited products to ***,we also look into consumer studies,which indicate a greater acceptance of gene-edited food among consumers,especially when additional benefits such as sustainability are mentioned.

关键词： Labelling New genomic techniques consumer transparency Plant products

multiple sclerosis is at a checkpoint: advancing the program

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Neural Regeneration Research 2025年第3期20卷 811-812页

作者： Brandon c.smith Jessica L.Williams Department of Neurosciences Lerner Research InstituteCleveland ClinicClevelandOHUSA Department of Biological Geologicaland Environmental SciencesCleveland State UniversityClevelandOHUSA

multiple sclerosis(mS) is a chronic inflammatory and demyelinating disease of the central nervous system(cNS). Patients with mS experience sensory and motor function loss due to myelin and/or axon damage perpetuated b... 详细信息

关键词： Hauser sclerosis damage

cOVID-19 vaccination produces exercise-responsive SARS-coV-2 specific T-cells regardless of infection history

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Journal of Sport and Health Science 2024年第1期13卷 99-107页

作者： Kyle A.smith Tiffany m.Zúñiga Forrest L.Baker Helena Batatinha charles R.Pedlar Shane c.Burgess michael P.Gustafson Emmanuel Katsanis Richard J.Simpson School of Nutritional Sciences and Wellness The University of ArizonaTucsonAZ 85721USA Department of Pediatrics The University of ArizonaTucsonAZ 85724USA Faculty of Sport Allied Health and Performance ScienceSt.Mary's UniversityTwickenham TW14SXUK Institute of Sport Exercise and Health University College LondonLondon WC1E 7HUUK Department of Animal and comparative Biomedical Sciences The University of ArizonaTucsonAZ 85721USA The University of Arizona cancer center The University of ArizonaTucsonAZ 85719USA Laboratory medicine and Pathology Mayo Clinic ArizonaPhoenixAZ 85054USA Department of Immunobiology The University of ArizonaTucsonAZ 85724USA Department of medicine The University of ArizonaTucsonAZ 85724USA Department of Pathology The University of ArizonaTucsonAZ 85724USA

Background:The mobilization and redistribution of severe acute respiratory syndrome coronavirus 2(SARS-coV-2)specific T-cells and neutralizing antibodies(nAbs)during exercise is purported to increase immune surveillance and protect against severe coronavirus disease 2019(cOVID-19).We sought to determine if cOVID-19 vaccination would elicit exercise-responsive SARS-coV-2 T-cells and transiently alter nAb ***:Eighteen healthy participants completed a 20-min bout of graded cycling exercise before and/or after receiving a cOVID-19 *** major leukocyte subtypes were enumerated before,during,and after exercise by flow cytometry,and immune responses to SARS-coV-2 were determined using whole blood peptide stimulation assays,T-cell receptor(TcR)-βsequencing,and SARS-coV-2 nAb ***:cOVID-19 vaccination had no effect on the mobilization or egress of major leukocyte subsets in response to intensity-controlled graded ***,non-infected participants had a significantly reduced mobilization of cD4+and cD8+naive T-cells,as well as cD4+central memory T-cells,after vaccination(synthetic immunity group);this was not seen after vaccination in those with prior SARS-coV-2 infection(hybrid immunity group).Acute exercise after vaccination robustly mobilized SARS-coV-2 specific T-cells to blood in an intensity-dependent *** groups mobilized T-cells that reacted to spike protein;however,only the hybrid immunity group mobilized T-cells that reacted to membrane and nucleocapsid *** increased significantly during exercise only in the hybrid immunity ***:These data indicate that acute exercise mobilizes SARS-coV-2 specific T-cells that recognize spike protein and increases the redistribution of nAbs in individuals with hybrid immunity.

关键词： Anti-viral cOVID-19 Exercise immunology SARS-coV-2 T-cells Vaccine

Performance of evolutionary optimized machine learning for modeling total organic carbon in core samples of shale gas fields

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Petroleum 2024年第1期10卷 150-164页

作者： Leonardo Goliatt c.m.Saporetti L.c.Oliveira E.Pereira Department of computational and Applied mechanics Federal University of Juiz de ForaJuiz de ForaBrazil Department of computational modeling Polytechnic InstituteRio de Janeiro State UniversityNova FriburgoBrazil Petrobras Rio de JaneiroBrazil Department of Stratigraphy and Paleontology Rio de Janeiro State UniversityRio de JaneiroBrazil

Rock samples'TOc content is the best indicator of the organic matter in source *** origin rock samples’analysis is used to calculate it manually by *** method requires time and resources because it relies on samples from many well intervals in source ***,research has been done to aid this *** learning algorithms can estimate total organic carbon instead of well logs and stratigraphic *** light of these efforts,the current work present a study on automating the total organic carbon estimation using machine learning approaches improved by an evolutionary methodology to give the model flexibility and *** algorithms,differential evolution,particle swarm optimization,grey wolf optimization,artificial bee colony,and evolution strategies were used to improve machine learning models to predict *** six metaheuristics were integrated into four machine learning methods:extreme learning machine,elastic net linear model,linear support vector regression,and multivariate adaptive regression *** samples from the YuDong-Nan shale gas field,located in the Sichuan basin,were used to evaluate the hybrid *** findings show that combining machine learning models with an evolutionary algorithms in a hybrid fashion produce flexible models that accurately predict *** results show that,independent of the metaheuristic used to guide the model selection,optimized extreme learning machines attained the best performance scores according to six *** hybrid models can be used in exploratory geological research,particularly for unconventional oil and gas resources.

关键词： Total organic carbon Hybrid models Automated machine learning Evolutionary algorithms Geology

An improved pulse coupled neural networks model for semantic IoT

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Digital communications and Networks 2024年第3期10卷 557-567页

作者： Rong ma Zhen Zhang Yide ma Xiping Hu Edith c.H.Ngai Victor c.m.Leung School of Information Science and Engineering Lanzhou UniversityLanzhou 730000China School of medical Technology Beijing Institute of TechnologyBeijing100081China Department of Electrical and Electronic Engineer The University of Hong KongHong Kong 999077China college of computer Science and Software Engineering Shenzhen UniversityShenzhen 518060China Department of Electrical and computer Engineering the University of British ColumbiaVancouverBC V6T 1Z4Canada

In recent years,the Internet of Things(IoT)has gradually developed applications such as collecting sensory data and building intelligent services,which has led to an explosion in mobile data ***,with the rapid development of artificial intelligence,semantic communication has attracted great attention as a new communication ***,for IoT devices,however,processing image information efficiently in real time is an essential task for the rapid transmission of semantic *** the increase of model parameters in deep learning methods,the model inference time in sensor devices continues to *** contrast,the Pulse coupled Neural Network(PcNN)has fewer parameters,making it more suitable for processing real-time scene tasks such as image segmentation,which lays the foundation for real-time,effective,and accurate image ***,the parameters of PcNN are determined by trial and error,which limits its *** overcome this limitation,an Improved Pulse coupled Neural Networks(IPcNN)model is proposed in this *** IPcNN constructs the connection between the static properties of the input image and the dynamic properties of the neurons,and all its parameters are set adaptively,which avoids the inconvenience of manual setting in traditional methods and improves the adaptability of parameters to different types of *** segmentation results demonstrate the validity and efficiency of the proposed self-adaptive parameter setting method of IPcNN on the gray images and natural images from the matlab and Berkeley Segmentation *** IPcNN method achieves a better segmentation result without training,providing a new solution for the real-time transmission of image semantic information.

关键词： Internet of things(IoT) Semantic information Real-time application Improved pulse coupled neural network Image segmentation

Semi-analytical investigation of heat transfer in a porous convective radiative moving longitudinal fin exposed to magnetic field in the presence of a shape-dependent trihybrid nanofluid

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Applied mathematics and mechanics(English Edition) 2024年第1期45卷 197-216页

作者： c.G.PAVITHRA B.J.GIREESHA m.L.KEERTHI Department of PG Studies and Research in mathematics Kuvempu UniversityShankaraghatta 577451India Department of mathematics and Statistics M.S.Ramaiah University of Applied SciencesBengaluru 560058India

The thermal examination of a non-integer-ordered mobile fin with a magnetism in the presence of a trihybrid nanofluid(Fe_3O_4-Au-Zn-blood) is carried out. Three types of nanoparticles, each having a different shape, are considered. These shapes include spherical(Fe_3O_4), cylindrical(Au), and platelet(Zn) configurations. The combination approach is utilized to evaluate the physical and thermal characteristics of the trihybrid and hybrid nanofluids, excluding the thermal conductivity and dynamic viscosity. These two properties are inferred by means of the interpolation method based on the volume fraction of nanoparticles. The governing equation is transformed into a dimensionless form, and the Adomian decomposition Sumudu transform method(ADSTm) is adopted to solve the conundrum of a moving fin immersed in a trihybrid nanofluid. The obtained results agree well with those numerical simulation results, indicating that this research is reliable. The influence of diverse factors on the thermal overview for varying noninteger values of γ is analyzed and presented in graphical representations. Furthermore, the fluctuations in the heat transfer concerning the pertinent parameters are studied. The results show that the heat flux in the presence of the combination of spherical, cylindrical, and platelet nanoparticles is higher than that in the presence of the combination of only spherical and cylindrical nanoparticles. The temperature at the fin tip increases by 0.705 759% when the value of the Peclet number increases by 400%, while decreases by 11.825 13% when the value of the Hartman number increases by 400%.

关键词： convection radiation moving longitudinal fin Adomian decomposition Sumudu transform method(ADSTm) trihybrid nanofluid magnetic field

Optimization of a photovoltaic-battery system using deep reinforcement learning and load forecasting

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Energy and AI 2024年第2期16卷 168-183页

作者： António corte Real G.Pontes Luz J.m.c.Sousa m.c.Brito S.m.Vieira IDmEc Instituto Superior TécnicoUniversidade de LisboaLisboa1049-001Portugal Instituto Dom Luiz Faculdade de CiênciasUniversidade de LisboaCampo Grande1749-016LisboaPortugal

Home Energy management Systems(HEmS)are increasingly relevant for demand-side management at the residential level by collecting data(energy,weather,electricity prices)and controlling home appliances or storage *** control can be performed with classical models that find optimal solutions,with high real-time computational cost,or data-driven approaches,like Reinforcement Learning,that find good and flexible solutions,but depend on the availability of load and generation data and demand high computational resources for *** this work,a novel HEmS is proposed for the optimization of an electric battery operation in a real,online and data-driven environment that integrates state-of-the-art load forecasting combining cNN and LSTm neural networks to increase the robustness of *** Reinforcement Learning agents are trained with different algorithms(Double DQN,Dueling DQN,Rainbow and Proximal Policy Optimization)in order to minimize the cost of electricity purchase and to maximize photovoltaic self-consumption for a PV-Battery residential *** show that the best Reinforcement Learning agent achieves a 35%reduction in total cost when compared with an optimization-based agent.

关键词： Energy management system Deep reinforcement learning Demand-side management Load forecasting Deep learning Energy storage systems