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P-functionalized carbon nanotubes promote highly stable electrocatalysts based on Fe-phthalocyanines for oxygen reduction: Experimental and computational studies

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Journal of Energy Chemistry 2022年第9期31卷 276-290,I0008页

作者： Beatriz martinez-Sanchez diego Cazorla-Amors Emilia Morallon Departamento de Quimica Fisica and Instituto Universitario de Materiales de Alicante(IUMA)University of Alicante Ap.99.03080 AlicanteSpain Departamento de Quimica Inorganica and Instituto Universitario de Materiales de Alicante(IUMA) University of AlicanteAp.9903080 AlicanteSpain

Iron(Ⅱ) phthalocyanines(FePc) supported on functionalized nanostructured carbon materials have been studied as electrocatalysts for the oxygen reduction reaction(ORR) in an alkaline medium. Herein, two types of carbon nanotubes(CnTs) have been explored as support, Single-Walled Carbon nanotubes and Herringbone Carbon nanotubes(SWCnTs and h CnTs, respectively), both electrochemically modified with ortho-aminophenylphosphonic acid(2APPA), which provides phosphate axial coordinating ligands for the immobilization of FePc molecules. All the catalysts were prepared via a facile incipient wetness impregnation method. Comprehensive experimental analysis together with density functional theory(DFT) calculations has demonstrated both the importance of the five-coordinated Fe macrocycles that favor the interaction between the FePc and the carbon support, as well as the effect of the CnT structure in the ORR. FePc axial coordination provides a better dispersion, leading to higher stability and a favorable electron redistribution that also tunes the ORR performance by lowering the stability of the reaction intermediates. Interestingly, such improvement occurs with a very low content of metal(~1 wt% Fe),which is especially remarkable when h CnT support is employed. This work provides a novel strategy for the development of Fe-containing complexes as precious metal-free catalysts towards the ORR.

关键词： Carbon nanotubes Iron phthalocyanine Oxygen reduction Electrocatalysis Axial ligand

Glutamine synthetase activity and glutamate uptake in hippocampus and frontal cortex in portal hypertensive rats

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World Journal of Gastroenterology 2009年第23期15卷 2893-2899页

作者： Gabriela Beatriz Acosta María Alejandra Fernández diego martín Roselló María Luján Tomaro Karina Balestrasse Abraham Lemberg Institute of Pharmacological Research (InInFA) National Research Council of Argentina (CONICET) and University of Buenos Aires Junín 956. 5th floor C1113AAD Buenos Aires Argentina Laboratory of Portal Hypertension School of Pharmacy and Biochemistry University of Buenos Aires Junín 956. 5th floor C1113AAD Buenos Aires Argentina Department of Biological Chemistry School of Pharmacy and Biochemistry University of Buenos Aires Junín 596. 5th floor C1113AAD Buenos Aires Argentina

AIM: To study glutamine synthetase (GS) activity and glutamate uptake in the hippocampus and frontal cortex (FC) from rats with prehepatic portal vein hypertension. METHODS: Male Wistar rats were divided into shamoperated group and a portal hypertension (PH) group with a regulated stricture of the portal vein. Animals were sacrificed by decapitation 14 d after portal vein stricture. GS activity was determined in the hippocampus and FC. Specific uptake of radiolabeled L-glutamate was studied using synaptosome-enriched fractions that were freshly prepared from both brain areas. RESULTS: We observed that the activity of GS increased in the hippocampus of PH rats, as compared to control animals, and decreased in the FC. A significant decrease in glutamate uptake was found in both brain areas, and was more marked in the hippocampus. The decrease in glutamate uptake might have been caused by a deficient transport function, signif icantly and persistent increase in this excitatory neurotransmitter activity. COnCLUSIOn: The presence of moderate ammonia blood levels may add to the toxicity of excitotoxic glutamate in the brain, which causes alterations in brain function. Portal vein stricture that causes portal hypertension modif ies the normal function in some brain regions.

关键词： Portal hypertension Glutamine synthetase Glutamate uptake Frontal cerebral cortex Hippocampus Rat

Improved IChOA-Based Reinforcement Learning for Secrecy Rate Optimization in Smart Grid Communications

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Computers, Materials & Continua 2024年第11期81卷 2819-2843页

作者： Mehrdad Shoeibi Mohammad Mehdi Sharifi nevisi Sarvenaz Sadat Khatami diego martín Sepehr Soltani Sina Aghakhani The WPI Business School Worcester Polytechnic InstituteWorcesterMA 01609-2280USA Department of Computer Science Escuela de Ingeniería Informática de SegoviaUniversidad de ValladolidSegovia40005Spain Department of Data Science Engineering University of HoustonHoustonTX 77204USA Department of Industrial Engineering College of EngineeringUniversity of HoustonHoustonTX 77204USA Department of Industrial and Manufacturing Systems Engineering Iowa State UniversityAmesIA 50011USA

In the evolving landscape of the smart grid(SG),the integration of non-organic multiple access(nOMA)technology has emerged as a pivotal strategy for enhancing spectral efficiency and energy ***,the open nature of wireless channels in SG raises significant concerns regarding the confidentiality of critical control messages,especially when broadcasted from a neighborhood gateway(nG)to smart meters(SMs).This paper introduces a novel approach based on reinforcement learning(RL)to fortify the performance of *** by the need for efficient and effective training of the fully connected layers in the RL network,we employ an improved chimp optimization algorithm(IChOA)to update the parameters of the *** integrating the IChOA into the training process,the RL agent is expected to learn more robust policies faster and with better convergence properties compared to standard optimization *** can lead to improved performance in complex SG environments,where the agent must make decisions that enhance the security and efficiency of the *** compared the performance of our proposed method(IChOA-RL)with several state-of-the-art machine learning(ML)algorithms,including recurrent neural network(Rnn),long short-term memory(LSTM),K-nearest neighbors(Knn),support vector machine(SVM),improved crow search algorithm(I-CSA),and grey wolf optimizer(GWO).Extensive simulations demonstrate the efficacy of our approach compared to the related works,showcasing significant improvements in secrecy capacity rates under various network *** proposed IChOA-RL exhibits superior performance compared to other algorithms in various aspects,including the scalability of the nOMA communication system,accuracy,coefficient of determination(R2),root mean square error(RMSE),and convergence *** our dataset,the IChOA-RL architecture achieved coefficient of determination of 95.77%and accuracy of 97.41%in validation *** was accompanied by the lowes

关键词： Smart grid communication secrecy rate optimization reinforcement learning improved chimp optimization algorithm

A novel Attack on Complex APUFs Using the Evolutionary Deep Convolutional neural network

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Intelligent Automation & Soft Computing 2023年第9期37卷 3059-3081页

作者： Ali Ahmadi Shahrakht Parisa Hajirahimi Omid Rostami diego martín Department of Industrial Engineering Sharif University of TechnologyTehran14588-89694Iran Department of Business Administration Boston UniversityBostonMA02215USA Department of Industrial Engineering University of HoustonHoustonTX77204USA ETSI de Telecomunicación Universidad Politécnica de MadridMadrid28040Spain

As the internet of things(IoT)continues to expand rapidly,the significance of its security concerns has grown in recent *** address these concerns,physical unclonable functions(PUFs)have emerged as valuable tools for enhancing IoT *** leverage the inherent randomness found in the embedded hardware of IoT ***,it has been shown that some PUFs can be modeled by attackers using machine-learning-based *** this paper,a new deep learning(DL)-based modeling attack is introduced to break the resistance of complex *** training DL models is a problem that falls under the category of nP-hard problems,there has been a significant increase in the use of meta-heuristics(MH)to optimize DL ***,it is widely recognized that finding the right balance between exploration and exploitation when dealing with complex problems can pose a significant *** address these chal-lenges,a novel migration-based multi-parent genetic algorithm(MBMPGA)is developed to train the deep convolutional neural network(DCnn)in order to achieve a higher rate of accuracy and convergence speed while decreas-ing the run-time of the *** the proposed MBMPGA,a non-linear migration model of the biogeography-based optimization(BBO)is utilized to enhance the exploitation ability of GA.A new multi-parent crossover is then introduced to enhance the exploration ability of *** behavior of the proposed MBMPGA is examined on two real-world optimization *** benchmark problems,MBMPGA outperforms other MH algorithms in convergence *** proposed model are also compared with previous attacking models on several simulated challenge-response pairs(CRPs).The simulation results on the XAPUF datasets show that the introduced attack in this paper obtains more than 99%modeling accuracy even on *** addition,the proposed MBMPGA-DCnn outperforms the state-of-the-art modeling attacks in a reduced timeframe and with a smaller number of requi

关键词： IoT security PUFs modeling attacks evolutionary deep learning migration-based multi-parent genetic algorithm

5-Bromo-2'-deoxyuridine labeling:historical perspectives,factors infiuencing the detection,toxicity,and its implications in the neurogenesis

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neural Regeneration Research 2024年第2期19卷 302-308页

作者： Joaquín martí-Clúa Unidad de Citología e Histología.Departament de Biologia Cel·lular de Fisiologia i d’Immunologia.Facultad de Biociencias.Institut de Neurociències.Universidad Autónoma de Barcelona08193 BellaterraBarcelonaSpain

The halopyrimidine 5-bromo-2′-deoxyuridine(BrdU)is an exogenous marker of DnA *** the introduction of monoclonal antibodies against BrdU,an increasing number of methodologies have been used for the immunodetection of this synthesized bromine-tagged base analogue into replicating *** labeling is widely used for identifying neuron precursors and following their fate during the embryonic,perinatal,and adult neurogenesis in a variety of vertebrate species including birds,reptiles,and *** to BrdU toxicity,its incorporation into replicating DnA presents adverse consequences on the generation,survival,and settled patterns of *** may lead to false results and misinterpretation in the identification of proliferative *** this review,I will indicate the detrimental effects of this nucleoside during the development of the central nervous system,as well as the reliability of BrdU labeling to detect proliferating ***,it will show factors influencing BrdU immunodetection and the contribution of this nucleoside to the study of prenatal,perinatal,and adult *** adult neurogenesis will also be *** is my hope that this review serves as a reference for those researchers who focused on detecting cells that are in the synthetic phase of the cell cycle.

关键词： 5-bromo-2′-deoxyuridine adult neurogenesis human adult neurogenesis labeling pitfalls prenatal neurogenesis proliferation S-phase suturing S-phase toxicity

A Deep Reinforcement Learning-Based Technique for Optimal Power Allocation in Multiple Access Communications

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Intelligent Automation & Soft Computing 2024年第1期39卷 93-108页

作者： Sepehr Soltani Ehsan Ghafourian Reza Salehi diego martín Milad Vahidi Department of Industrial Engineering College of EngineeringUniversity of HoustonHoustonTX77204USA Department of Computer Science Iowa State UniversityAmesIowaUSA ETSI de Telecomunicación Universidad Politécnica de MadridMadridSpain Faculty of School of Plant and Environmental Sciences Virginia Polytechnic Institute and StateUniversityBlacksburgVirginia24060USA

Formany years,researchers have explored power allocation(PA)algorithms driven bymodels in wireless networks where multiple-user communications with interference are ***,data-driven machine learning methods have become quite popular in analyzing wireless communication systems,which among them deep reinforcement learning(DRL)has a significant role in solving optimization issues under certain *** this purpose,in this paper,we investigate the PA problem in a k-user multiple access channels(MAC),where k transmitters(e.g.,mobile users)aim to send an independent message to a common receiver(e.g.,base station)through wireless *** this end,we first train the deep Q network(DQn)with a deep Q learning(DQL)algorithm over the simulation environment,utilizing offline ***,the DQn will be used with the real data in the online training method for the PA issue by maximizing the sumrate subjected to the source ***,the simulation results indicate that our proposedDQnmethod provides better performance in terms of the sumrate compared with the available DQL training approaches such as fractional programming(FP)and weighted minimum mean squared error(WMMSE).Additionally,by considering different user densities,we show that our proposed DQn outperforms benchmark algorithms,thereby,a good generalization ability is verified over wireless multi-user communication systems.

关键词： Deep reinforcement learning deep Q learning multiple access channel power allocation

Rheological and tribological approaches as a tool for the development of sustainable lubricating greases based on nano-montmorillonite and castor oil

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Friction 2021年第2期9卷 415-428页

作者： Jose Enrique martÍn-ALFOnSO María Jose martÍn-ALFOnSO Concepción VALEnCIA María Teresa CUBERES Department of Chemical Engineering and Materials Science Campus de“El Carmen”University of HuelvaChemical Product and Process Technology Research Center(Pro2TecS)Huelva 21071Spain Department of Applied Mechanics and Project Engineering University of Castilla-La ManchaAlmadén 13400Spain

This study investigates the development of novel montmorillonite/castor oil blends to formulate sustainable lubricating greases to promote the replacement of petrochemicals industry-derived materials by substances obtained from renewable ***,the effect of the thickener concentration on the rheological,chemical,thermal,tribological properties,and atomic force microscopy(AFM)microstructure of these systems were *** results showed that the C20A nanoclay content could be used to modulate the viscosity values,the linear viscoelastic functions,and tribological properties of these montmorillonite *** general,these gel-like dispersions exhibited remarkable lubricant properties;the samples showed values of the friction coefficient and wear scars similar or lower than those obtained with model bentonite grease.

关键词： lubricating greases nanoclay vegetable oil rheology tribology

THE BAnACH-LIE GROUP OF LIE TRIPLE AUTOMORPHISMS OF An H^＊-ALGEBRA^＊

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Acta Mathematica Scientia 2010年第4期30卷 1219-1226页

作者： A.J.Calderón martín C.martín González Departamento de Matemáticas Universidad de Cádiz Departamento de Algebra Geometría y Topología Universidad de Málaga

We study the Banach-Lie group Ltaut（A） of Lie triple automorphisms of a complex associative H^＊-algebra A. Some consequences about its Lie algebra, the algebra of Lie triple derivations of A, Ltder（A）, are obtained. For a topologically simple A, in the infinite-dimensional case we have Ltaut（A）0 = Aut（A） implying Ltder（A） = Der（A）. In the finite-dimensional case Ltaut（A）0 is a direct product of Aut（A） and a certain subgroup of Lie derivations δ from A to its center, annihilating commutators.

关键词： Banach-Lie group Lie triple automorphism Lie triple derivation

Large-Scale Group Decision Making:A Systematic Review and a Critical Analysis

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IEEE/CAA Journal of Automatica Sinica 2022年第6期9卷 949-966页

作者： diego García-Zamora Alvaro Labella Weiping Ding Rosa M.Rodríguez Luis martínez Department of Computer Science University of JaénJaén 23071Spain IEEE School of Information Science and Technology Nantong UniversityNantong 226019China

The society in the digital transformation era demands new decision schemes such as e-democracy or based on social *** novel decision schemes require the participation of many experts/decision makers/stakeholders in the decision *** a result,large-scale group decision making(LSGDM)has attracted the attention of many researchers in the last decade and many studies have been conducted in order to face the challenges associated with the ***,this paper aims at reviewing the most relevant studies about LSGDM,identifying the most profitable research trends and analyzing them from a critical point of *** do so,the Web of Science database has been consulted by using different *** these results a total of 241 contributions were found and a selection process regarding language,type of contribution and actual relation with the studied topic was then carried *** 87 contributions finally selected for this review have been analyzed from four points of view that have been highly remarked in the topic,such as the preference structure in which decision-makers’opinions are modeled,the group decision rules used to define the decision making process,the techniques applied to verify the quality of these models and their applications to real world problems ***,a critical analysis of the main limitations of the existing proposals is ***,taking into account these limitations,new research lines for LSGDM are proposed and the main challenges are stressed out.

关键词： Challenges large-scale consensus models large-scale group decision making(LSGDM) systematic review