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Systemic analysis of metabolome reconfiguration in Arabidopsis after abiotic stressors uncovers metabolites that modulate defense against pathogens

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Plant communications 2024年第1期5卷 55-68页

作者： Antoni Garcia-molina Victoria pastor centre for Research in Agricultural Genomics(cRAG)cSIc-IRTA-UAB-UB C/Vall MorontaEdifici CRAG08193 Bellaterra(Cerdanyola del Valles)BarcelonaSpain Department of Biology Biochemistryand Natural SciencesSchool of Technology and Experimental SciencesUniversitat Jaume I12006 Castellode la PlanaSpain

Understanding plant immune responses is complex because of the high interdependence among biological processes in homeostatic ***,the integration of environmental cues causes network rewiring that interferes with defense ***,plants retain molecular signatures configured under abiotic stress periods to rapidly respond to recurrent stress,and these can alter *** changes imposed by abiotic stressors are persistent,although their impact on defense remains to be *** this study,we profiled metabolomes of Arabidopsis plants under several abiotic stress treatments applied individually or simultaneously to capture temporal trajectories in metabolite composition during adverse conditions and *** systemic analysis was performed to address the relevance of me-tabolome changes and extract central features to be tested in *** results demonstrate irreversibility in major fractions of metabolome changes as a general pattern in response to abiotic stress ***-tionalanalysisofmetabolomesandco-abundancenetworkspoints toconvergence inthereconfigurationof organic acid and secondary metabolite *** mutant lines for components related to these metabolic pathways showed altered defense capacities against different ***,our data suggest that sustained metabolome changes configured in adverse environments can act as mod-ulators of immune responses and provide evidence for a new layer of regulation in plant defense.

关键词： abiotic stress Arabidopsis biotic stress combinatorial stress metabolomics systems biology

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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

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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

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Stay in touch with the endoplasmic reticulum

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Science china(Life Sciences) 2024年第2期67卷 230-257页

作者： Sha Sun Gan Zhao mingkang Jia Qing Jiang Shulin Li Haibin Wang Wenjing Li Yunyun Wang Xin Bian Yan G.Zhao Xun Huang Ge Yang Huaqing cai Jose c.pastor-Pareja Liang Ge chuanmao Zhang Junjie Hu National Laboratory of Biomacromolecules Institute of BiophysicsUniversity of Chinese Academy of SciencesChinese Academy of SciencesBeijing 100101China The ministry of Education Key Laboratory of cell Proliferation and Differentiation College of Life SciencesPeking UniversityBeijing 100871China State Key Laboratory of membrane Biology Tsinghua-Peking Center for Life SciencesSchool of Life SciencesTsinghua UniversityBeijing 100084China Laboratory of computational Biology&machine Intelligence School of Artificial IntelligenceUniversity of Chinese Academy of SciencesBeijing 100049China State Key Laboratory of medicinal chemical Biology College of Life SciencesNankai UniversityTianjin 300071China Brain Research center Department of BiologySchool of Life SciencesSouthern University of Science and TechnologyShenzhen 518055China State Key Laboratory of molecular Developmental Biology Institute of Genetics and Developmental BiologyInnovation Academy for Seed DesignChinese Academy of SciencesBeijing 100101China Institute of Neurosciences Consejo Superior de Investigaciones Científicas-Universidad Miguel HernándezSan Juan de Alicante 03550Spain

The endoplasmic reticulum(ER),which is composed of a continuous network of tubules and sheets,forms the most widely distributed membrane system in eukaryotic *** a result,it engages a variety of organelles by establishing membrane contact sites(mcSs).These contacts regulate organelle positioning and remodeling,including fusion and fission,facilitate precise lipid exchange,and couple vital signaling ***,we systematically review recent advances and converging themes on ER-involved organellar *** molecular basis,cellular influence,and potential physiological functions for ER/nuclear envelope contacts with mitochondria,Golgi,endosomes,lysosomes,lipid droplets,autophagosomes,and plasma membrane are summarized.

关键词： endoplasmic reticulum nuclear envelope mitochondria Golgi apparatus endosome lysosome lipid droplets autophagosome plasma membrane membrane contact site

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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

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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

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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

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cO oxidation under lean and stoichiometric conditions over ceriazirconia with very low metal contents(cu,co,Ag and Pt)

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Journal of Rare Earths 2024年第9期42卷 1669-1681,I0002页

作者： J.c.martínez-munuera m.P.Yeste A.García-García mcmA Group Department of Inorganic Chemistry and Institute of MaterialsUniversity of AlicanteCarretera de San Vicente del Raspeig s/n03690San Vicente del RaspeigAlicanteSpain Solid chemistry and catalysis Group Department of Materials ScienceMetallurgic Engineering and Inorganic ChemistryInstitute of Electronic Microscopy and Materials ResearchUniversity of CádizAp.40E-11510Puerto RealCádizSpain

In this work,several ceria-zirconia based catalysts with very lo w(and equimolar) metal contents were prepared,characterised and tested for the cO oxidatio n reaction(under lean and stoichiometric conditions),trying to emulate those conditions found in a diesel oxidation catalyst(DOc) system from a diesel engine and those encountered under gasoline exhaust(λ=1).The metals chosen are cu,co,Ag and Pt(as a reliable benchmark).The results reveal enormous differences among reducibility and catalytic activity despite quite similar structural and textural properties of the catalysts,showing differences among dispersion(Ag-catalyst seems to present a low level of dispersion).This catalyst seems to be characterised,as well,by a strong electronic interaction between ce and Ag centres which is suggested to yield an improved reducibility under H_(2)-TPR ***,the order in catalytic activity(cu>Ag>co≈Pt>>support) seems not to follow the order found in reducibility and the cu-catalyst seems to be the most active independently on the reaction conditions,yielding nearly overlapped cO oxidation catalytic *** restingly,a stro ng correlation between the catalytic activity under the two conditions tested and the OSc values of the ce_(0.8)Zr_(0.2)O_(2)-supported metal catalysts is ***,OSc parameter measured at 150℃ can be used as a relevant descriptor to evaluate the cO oxidation activity at low and medium conversions for the investigated catalysts,much better than the H_(2)-TPR measurements.

关键词： cO oxidation Low metal content ceria-zirconia copper species OSc parameter Rare earths

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Effect of radiative loss mechanisms on FIR thermometric parameters of Nd^(3+)-doped lithium tellurite glasses

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Journal of Rare Earths 2024年第7期42卷 1250-1257,I0002页

作者： c.Y.morassuti A.P.L Silva L.A.O.Nunes S.m.Lima L.H.c.Andrade Optical and Photothermal Spectroscopy Group(GEOF) Center for Studies in Natural Resources(CERNA)State University of Mato Grosso do Sul(UEMS)C.P.351DouradosMSBrazil Renato Archer Information Technology center Dom Pedro I Highway(SP-65)Km 1436-Chácaras Campos dos AmaraisCampinasSPBrazil Institute of Physics of São carlos University of São PauloSão CarlosSPBrazil

Nd^(3+)-doped tellurite glasses are promising materials for thermometers based on the fluorescence intensity ratio(FIR)***,at high Nd^(3+)concentrations,energy transfer(ET)processes such as optical reabsorption and cross-relaxation can affect the Nd^(3+)emission,which has been little explored in the ***,the present work investigated the use of Nd^(3+)-doped tellurite glass(samples doped with Nd^(3+)at 0.2 mol%,0.5 mol%,2.0 mol%,and 4.0 mol%)in fluorescence thermometers,in the temperature range from 299 to 371 *** results indicate a strong dependence of the FIR parameters on the Nd^(3+)concentration,due to changes in the emission band profiles caused by optical reabsorption of the Nd^(3+)emissions and cross-relaxation processes.A decrease of the relative sensitivity of the ratio^(4)F_(5/2)→^(4)I_(9/2)/^(4)F_(3/2)→^(4)I_(9/2)is observed for samples doped with higher amounts of Nd^(3+).The maximum relative sensitivity at 299 K is 3.00%/K,which is the highest value among the reported Nd^(3+)ions.

关键词： Nd^(3+)-doped tellurite glass Fluorescence intensity ratio Optical thermometry Judd-Ofelt Rare earths

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Radiative decays D*(s)→ D(s)γ in covariant confined quark model

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chinese Physics c 2024年第2期48卷 45-56页

作者： c.T.Tran m.A.Ivanov P.Santorelli Q.c.Vo Department of Physics HCMC University of Technology and EducationVo Van Ngan 1700000 Ho Chi Minh CityVietnam Bogoliubov Laboratory of Theoretical Physics Joint Institute for Nuclear Research141980 DubnaRussia Dipartimento di Fisica"E.Pancini" Universitàdi Napoli Federico ⅡComplesso Universitario di Monte S.AngeloVia CintiaEdificio 680126 NapoliItaly Istituto Nazionale di Fisica Nucleare Sezione di Napoli80126 NapoliItaly University of Science 700000 Ho Chi Minh CityVietnam

Radiative decays D((s))*→D((s))γare revisited in light of new experimental data from the BaBar and BESⅢ*** radiative couplings gD*Dγencoding nonperturbative QcD effects are calculated in the framework of the covariant confined quark model developed by *** compare our results with other theoretical studies and experimental *** couplings(in GeV-1)|g(D*+D+γ)|=0.45(9)and|g(D*0D0γ)|=1.72(34)calculated in our model agree with the corresponding experimental data|g(D*+D+γ)|=0.47(7)and|g(D*0D0γ)|=1.77(16).The most interesting case is the decay Ds*→Dsγ,for which a recent prediction based on light-cone sum rules at next-to-leading order|gDs*Dsγ|=0.60(19)deviates from the first(and only to date)lattice QcD result|gDs*Dsγ|=0.11(2)at nearly3σ.Our calculation yields|gDs*Dsγ|=0.29(6),which falls somehow between the two mentioned results,although it is larger than those predicted in other studies using quark models or QcD sum rules.

关键词： covariant quark model radiative decay charmed meson

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