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Construction of 2D/2D Ti_(3)C_(2)T_(x)MXene/Cds heterojunction with photothermal effect for efficient photocatalytic hydrogen production

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Journal of MaterialS.Science & Technology 2024年第4期171卷 1-9页

作者： T.Y.Huang Z.Yang s.Y.Yang Z.H.Dai Y.J.Liu J.H.Liao G.Y.Zhong Z.J.Xie Y.P.Fang S.S.Zhang Key Laboratory for Biobased Materials and Energy of Ministry of Education Guangdong Laboratory for Lingnan Modern AgricultureCollege of Materials and EnergySouth China Agricultural UniversityGuangzhou 510643China school of Physics and Optoelectronics South China University of TechnologyGuangzhou 510640China school of Chemical Engineering and Energy Technology Guangdong Provincial Key Laboratory of Distributed Energy SystemsDongguan University of TechnologyDongguan 523808China

The insensitivity of semiconductors to visible and infrared light is a key constraint on the utilization of light energy in photocatalytic reactions.Constructing photocatalyS.S with full-spectrum absorption through surface engineering is an effective approach to fully harnessing light energy in semiconductor materials.Herein,a novel stable Ti_(3)C_(2)T_(x)MXene/Cds heterojunction catalyst is obtained by in-situ epitaxial growth of two-dimensional(2D)Cds nanosheets on 2D MXene interface via a solvothermal method.The exceptional light absorption properties of MXene confer outstanding full-spectrum driven photocat-alytic hydrogen evolution capability upon the heterogeneous catalyst.The unique 2D/2D structure effectively mitigated the recombination of photogenerated carriers,enhancing the photocatalytic performance of the catalyst.Moreover,the composite catalyst exhibits a significantly higher surface temperature of 80.4℃under visible light irradiation at an intensity of 0.1 W/cm^(2),which is 1.84 times higher than that of Cds.Under irradiation of visible and near infrared light,the composite catalyst with photothermal ef-fect demonstrates a remarkable hydrogen evolution rate of 65.4 mmol g^(-1)h^(-1),which is 7.2 times higher than that of Cds catalyst.ThiS.Study introduces a novel approach for constructing full-spectrum absorption catalyS.S and expands the application of the photothermal effect in photocatalytic hydrogen evolution research.

关键词： Two-dimensional structure Heterostructure Photothermal effect Photocatalyst Hydrogen evolution

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Exploring van der Waals materials with high anisotropy:geometrical and optical approaches

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Light(science & Applications) 2024年第4期13卷 645-653页

作者： Aleksandr S.Slavich Georgy A.Ermolaev Mikhail K.Tatmyshevskiy Adilet N.Toksumakov Olga G.Matveeva Dmitriy V.Grudinin Kirill V.Voronin Arslan Mazitov Konstantin V.Kravtsov Alexander V.syuy Dmitry M.Tsymbarenko Mikhail s.Mironov sergey M.Novikov Ivan Kruglov Davit A.Ghazaryan Andrey A.Vyshnevyy Aleksey V.Arsenin Valentyn s.Volkov Kostya s.Novoselov Moscow Center for Advanced studies Kulakova str.20Moscow 123592Russia. Emerging Technologies Research Center XPANCEOInternet CityEmmay TowerDubaiUnited Arab Emirates. Donostia International Physics Center(DIPC) Donostia/San-Sebastián 20018Spain. Institute of Materials Ecole Polytechnique Federale de Lausanne1015 LausanneSwitzerland. Department of Chemistry Lomonosov Moscow State UniversityMoscow 119991Russia. Laboratory of Advanced Functional Materials Yerevan State UniversityYerevan 0025Armenia. National Graphene Institute(NGI) University of ManchesterManchester M139PLUK. Department of MaterialS.Science and Engineering National University of SingaporeSingapore 03-09 EASingapore. Institute for Functional Intelligent Materials National University of Singapore117544 SingaporeSingapore

The emergence of van der Waals(vdW)materials resulted in the discovery of their high optical,mechanical,and electronic anisotropic properties,immediately enabling countless novel phenomena and applicationS.Such success inspired an intensive search for the highest possible anisotropic properties among vdW materials.Furthermore,the identification of the most promising among the huge family of vdW materials is a challenging quest requiring innovative approaches.Here,we suggest an easy-to-use method for such a survey based on the crystallographic geometrical perspective of vdW materials followed by their optical characterization.Using our approach,we found AS.S3 as a highly anisotropic vdW material.It demonstrates high in-plane optical anisotropy that is~20%larger than for rutile and over two times as large as calcite,high refractive index,and transparency in the visible range,overcoming the century-long record set by rutile.Given these benefits,AS.S3 opens a pathway towards nextgeneration nanophotonics as demonstrated by an ultrathin true zero-order quarter-wave plate that combines classical and the Fabry–Pérot optical phase accumulations.Hence,our approach provides an effective and easy-to-use method to find vdW materials with the utmost anisotropic properties.

关键词： anisotropy anisotropic high

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An Efficient Modelling of Oversampling with Optimal Deep Learning Enabled Anomaly Detection in streaming Data

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China Communications 2024年第5期21卷 249-260页

作者： R.Rajakumar S.Sathiya Devi srinivasa Ramanujan Centre SASTRA Deemed UniversityKumbakonamTamil Nadu 612001India University College of Engineering BIT CampusAnna UniversityTiruchirappalli 620024India

Recently,anomaly detection(AD)in streaming data gained significant attention among research communities due to its applicability in finance,business,healthcare,education,etc.The recent developments of deep learning(DL)models find helpful in the detection and classification of anomalies.This article designs an oversampling with an optimal deep learning-based streaming data classification(Os-ODLsDC)model.The aim of the OsODLsDC model is to recognize and classify the presence of anomalies in the streaming data.The proposed Os-ODLsDC model initially undergoes preprocessing step.since streaming data is unbalanced,support vector machine(sVM)-synthetic Minority Over-sampling Technique(sVM-sMOTE)is applied for oversampling process.Besides,the Os-ODLsDC model employs bidirectional long short-term memory(Bi LsTM)for AD and classification.Finally,the root meanS.Square propagation(RMsProp)optimizer is applied for optimal hyperparameter tuning of the Bi LsTM model.For ensuring the promising performance of the Os-ODLsDC model,a wide-ranging experimental analyS.S is performed using three benchmark datasetS.Such as CICIDs 2018,KDD-Cup 1999,and NsL-KDD datasets.

关键词： anomaly detection deep learning hyperparameter optimization oversampling sMOTE streaming data

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Enhancing Renewable Energy Integration:A Gaussian-Bare-Bones Levy Cheetah Optimization Approach to Optimal Power Flow in Electrical Networks

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Computer Modeling in Engineering & sciences 2024年第8期140卷 1339-1370页

作者： Ali s.Alghamdi Mohamed A.Zohdy saad Aldoihi Department of Electrical Engineering College of EngineeringMajmaah UniversityAl-Majmaah11952Saudi Arabia Electrical and Computer Engineering Department Oakland UniversityRochesterMI48309USA Institute of Earth and space science King Abdulaziz City for Science and Technology(KACST)Riyadh11442Saudi Arabia Computer science and S.Stems Engineering Institute Polytechnique de ParisPalaiseau CedexFrance

In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(REss).Efficient integration of stochastic REss and optimal power flow(OPF)management are critical for network optimization.ThiS.Study introduces an innovative solution,the Gaussian Bare-Bones Levy Cheetah Optimizer(GBBLCO),addressing OPF challenges in power generation S.Stems with stochastic REss.The primary objective is to minimize the total operating coS.S of REss,considering four functions:overall operating coS.S,voltage deviation management,emissions reduction,voltage stability index(VsI)and power loss mitigation.Additionally,a carbon tax is included in the objective function to reduce carbon emissions.Thorough scrutiny,using modified IEEE 30-bus and IEEE 118-buS.Systems,validates GBBLCO’S.Superior performance in achieving optimal solutionS.Simulation results demonstrate GBBLCO’s efficacy in six optimization scenarios:total cost with valve point effects,total cost with emission and carbon tax,total cost with prohibited operating zones,active power loss optimization,voltage deviation optimization and enhancing voltage stability index(VsI).GBBLCO outperforms conventional techniques in each scenario,showcasing rapid convergence and superior solution quality.Notably,GBBLCO navigates complexities introduced by valve point effects,adapts to environmental constraints,optimizes coS.S while considering prohibited operating zones,minimizes active power losS.S,and optimizes voltage deviation by enhancing the voltage stability index(VsI)effectively.This research significantly contributes to advancing OPF,emphasizing GBBLCO’s improved global search capabilities and ability to address challenges related to local minima.GBBLCO emerges as a versatile and robust optimization tool for diverse challenges in power S.Stems,offering a promising solution for the evolving needs of renewable energy-integrated power grids.

关键词： Renewable energy integration optimal power flow stochastic renewable energy sources gaussian-bare-bones levy cheetah optimizer electrical network optimization carbon tax optimization

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Generalized polynomial chaos expansion by reanalyS.S using static condensation based on substructuring

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Applied Mathematics and Mechanics(English Edition) 2024年第5期45卷 819-836页

作者： D.LEE s.CHANG J.LEE Department of Automotive Engineering Hanyang UniversitySeoul 04763Republic of Korea school of Mechanical Engineering Chungnam National UniversityDaejeon 34134Republic of Korea Department of Mechanical Robotics and Energy EngineeringDongguk UniversitySeoul 04620Republic of Korea

This paper presents a new computational method for forward uncertainty quantification(UQ)analyS.S on large-scale structural S.Stems in the presence of arbitrary and dependent random inputs.The method conS.Sts of a generalized polynomial chaos expansion(GPCE)for statistical moment and reliability analyS.S associated with the stochastic output and a static reanalyS.S method to generate the input-output data set.In the reanalyS.S,we employ substructuring for a structure to isolate its local regions that vary due to random inputs.This allows for avoiding repeated computations of invariant substructures while generating the input-output data set.Combining substructuring with static condensation further improves the computational efficiency of the reanalyS.S without losing accuracy.Consequently,the GPCE with the static reanalyS.S method can achieve significant computational saving,thus mitigating the curse of dimensionality to some degree for UQ under high-dimensional inputs.The numerical results obtained from a simple structure indicate that the proposed method for UQ produces accurate solutions more efficiently than the GPCE using full finite element analyS.S(FEAs).We also demonstrate the efficiency and scalability of the proposed method by executing UQ for a large-scale wing-box structure under ten-dimensional(all-dependent)random inputs.

关键词： forward uncertainty quantification(UQ) generalized polynomial chaos expansion(GPCE) static reanalyS.S method static condensation substructuring

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Accuracy comparison and improvement for state of health estimation of lithium-ion battery based on random partial recharges and feature engineering

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Journal of Energy Chemistry 2024年第5期92卷 591-604页

作者： Xingjun Li Dan Yu søren Byg Vilsen Daniel Ioan stroe Department of Energy Aalborg UniversityAalborg 9220Denmark Department of Mathematical sciences Aalborg UniversityAalborg 9220Denmark Walker Department of Mechanical Engineering The University of Texas at AustinAustinTX 78712USA

state of health(sOH)estimation of e-mobilities operated in real and dynamic conditions is essential and challenging.Most of existing estimations are based on a fixed constant current charging and discharging aging profiles,which overlooked the fact that the charging and discharging profiles are random and not complete in real application.This work investigates the influence of feature engineering on the accuracy of different machine learning(ML)-based sOH estimations acting on different recharging sub-profiles where a realistic battery mission profile is considered.Fifteen features were extracted from the battery partial recharging profiles,considering different factorS.Such aS.Starting voltage values,charge amount,and charging sliding windows.Then,features were selected based on a feature selection pipeline conS.Sting of filtering and supervised ML-based subset selection.Multiple linear regression(MLR),Gaussian process regression(GPR),and support vector regression(sVR)were applied to estimate sOH,and root mean square error(RMsE)was used to evaluate and compare the estimation performance.The resultS.Showed that the feature selection pipeline can improve sOH estimation accuracy by 55.05%,2.57%,and 2.82%for MLR,GPR and sVR respectively.It was demonstrated that the estimation based on partial charging profiles with lower starting voltage,large charge,and large sliding window size is more likely to achieve higher accuracy.This work hopes to give some insights into the supervised ML-based feature engineering acting on random partial recharges on sOH estimation performance and tries to fill the gap of effective sOH estimation between theoretical study and real dynamic application.

关键词： Feature engineering Dynamic forklift aging profile state of health comparison Machine learning Lithium-ion batteries

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sexual dimorphism of G protein-coupled receptor signaling in the brain

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Neural Regeneration Research 2024年第8期19卷 1635-1636页

作者： sara Aljoudi Hamdan Hamdan Khaled s.Abd-Elrahman Department of Physiology and Immunology College of Medicine and Health SciencesKhalifa UniversityAbu DhabiUnited Arab Emirates Healthcare Engineering Innovation Center(HEIC) Khalifa UniversityAbu DhabiUnited Arab Emirates Department of Anesthesiology Pharmacology and Therapeuticsand Djavad Mowafaghian Center for Brain HealthUniversity of British ColumbiaVancouverBCCanada Department of Pharmacology and Therapeutics College of Medicine and Health ScienceKhalifa UniversityAbu DhabiUnited Arab Emirates Department of Pharmacology and Toxicology Faculty of PharmacyAlexandria UniversityAlexandriaEgypt

G protein-coupled receptors(GPCRs)represent the most substantial family of membrane receptors that are targeted by U.s.Food and Drug Administration-approved drugs.Much of the preclinical research to understand the pharmacology of many membrane receptors including GPCRs is derived from studies in male animal models(Karp and Reavey,2019).

关键词： drugs clinical targeted

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study of hybrid nanofluid flow in a stationary cone-disk S.Stem with temperature-dependent fluid properties

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Applied Mathematics and Mechanics(English Edition) 2024年第4期45卷 677-694页

作者： A.s.JOHN B.MAHANTHEsH G.LORENZINI Center for Mathematical Needs Department of MathematicsCHRIST(Deemed to be University)Karnataka 560029India school of Mathematical and statistical sciences The University of Texas Rio Grande ValleyTexas 78539U.S.A. Department of Engineering and Architecture University of ParmaParma 43124Italy

Cone-disk S.Stems find frequent use such as conical diffusers,medical devices,various rheometric,and viscosimetry applications.In thiS.Study,we investigate the three-dimensional flow of a water-based Ag-Mg O hybrid nanofluid in a static cone-disk S.Stem while considering temperature-dependent fluid properties.How the variable fluid properties affect the dynamics and heat transfer features iS.Studied by ReynoldS.S linearized model for variable viscosity and Chiam's model for variable thermal conductivity.The single-phase nanofluid model is utilized to describe convective heat transfer in hybrid nanofluids,incorporating the experimental data.This model is developed as a coupled S.Stem of convective-diffusion equations,encompassing the conservation of momentum and the conservation of thermal energy,in conjunction with an incompressibility condition.A self-similar model is developed by the Lie-group scaling transformations,and the subsequent self-similar equations are then solved numerically.The influence of variable fluid parameters on both swirling and non-swirling flow caS.S is analyzed.Additionally,the Nusselt number for the disk surface is calculated.It is found that an increase in the temperature-dependent viscosity parameter enhances heat transfer characteristics in the static cone-disk S.Stem,while the thermal conductivity parameter has the opposite effect.

关键词： hybrid nanofluid cone-disk S.Stem laminar flow variable fluid property Nusselt number

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Limited impacts of occasional tillage on dry aggregate size distribution and soil carbon and nitrogen fractions in semi-arid drylands

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International soil and Water Conservation Research 2024年第1期12卷 96-106页

作者： Wooiklee s.Paye Vesh R.Thapa Rajan Ghimire New Mexico state University Agricultural Science CenterClovisNM88101USA New Mexico state University Department of Plant and Environmental SciencesLas CrucesNM88003USA

Tillage management that minimizes the frequency and intensity of soil disturbance can increase soil carbon(C)and nitrogen(N)sequestration and improve the resilience of dryland cropping S.Stems,yet the impact of occasional disturbance on soil aggregate formation and the soil organic carbon(sOC)storage within aggregates has not been studied well.We evaluated the effect of four tillage management practices on soil dry aggregate size distribution,aggregate-protected C and N,mineral-associated organic matter carbon(MAOM-C),particulate organic matter carbon(POM-C),and corn(Zea mays L.)and sorghum(sorghum bicolor(L.)Moench)yields in a semi-arid dryland cropping S.Stem.Treatments included conventional tillage(CT),strip-tillage(sT),no-tillage(NT),and occasional tillage(OT)management in a corn-sorghum rotation.soil macro-aggregates were 51-54%greater under sT,NT,and OT,while small and micro-aggregates were greater in CT.Conventional tillage reduced soil aggregate-associated C by 28-31%in macro-aggregates and 47-53%in small aggregates at 26 months(M)sampling compared to sT,NT,and OT.In clay+silt fraction,CT had 14-16%,21-26%,and 36-43%lesS.SOC at 7,14,and 26M samplings,respectively,than sT,NT,and OT.Aggregate associated N was generally similar under sT,NT,and OT,which was greater on average than CT.soil MOAM-C and POM-C under sT,NT,and OT were generally greater than respective sOC fractions under CT at 19 and 26 M after OT implementation.Corn and sorghum yields were similar among tillage S.Stems in 2020,but greater under sT,NT,and OT than CT in 2021.Our resultS.Suggest that while frequent intensive tillage can lower sOC and N storage,a single stubble mulch occasional tillage after several years of NT does not lead to soil C and N losS.S and soil structural instability in semi-arid drylands.

关键词： Conventional tillage Occasional tillage Aggregate associated carbon Mineral associated organic matter carbon(MAOM-C) Particulate organic matter carbon(POM-C)

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The autophagy protein Atg9 functions in glia and contributes to parkinsonian symptoms in a Drosophila model of Parkinson’s disease

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Neural Regeneration Research 2024年第5期19卷 1150-1155页

作者： shuanglong Yi Linfang Wang Margaret s.Ho shiping Zhang school of Life science and Technology ShanghaiTech UniversityShanghaiChina College of Life sciences University of Chinese Academy of SciencesBeijingChina

Parkinson’s disease is a progressive neurodegenerative disease characterized by motor deficits,dopaminergic neuron loss,and brain accumulation ofα-synuclein aggregates called Lewy bodies.Dysfunction in protein degradation pathwayS.Such as autophagy,has been demonstrated in neurons as a critical mechanism for eliminating protein aggregates in Parkinson’s disease.However,it is less well understood how protein aggregates are eliminated in glia,the other cell type in the brain.In the present study,we show that autophagy-related gene 9(Atg9),the only transmembrane protein in the autophagy machinery,is highly expressed in Drosophila glia from adult brain.Results from immunostaining and live cell imaging analyS.S reveal that a portion of Atg9 localizes to the trans-Golgi network,autophagosomes,and lyS.Somes in glia.Atg9 is perS.Stently in contact with these organelles.Lacking glial atg9 reduces the number of omegasomes and autophagosomes,and impairs autophagic substrate degradation.ThiS.SuggeS.S that glial Atg9 participates in the early steps of autophagy,and hence the control of autophagic degradation.Importantly,loss of glial atg9 induces parkinsonian symptoms in Drosophila including progressive loss of dopaminergic neurons,locomotion deficits,and glial activation.Our findings identify a functional role of Atg9 in glial autophagy and establish a potential link between glial autophagy and Parkinson’s disease.These results may provide new insights on the underlying mechanism of Parkinson’s disease.

关键词： Atg9 autophagy glia Parkinson’s disease

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