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Enhancement of pacemaker induced stochastic resonance by an autapse in a scale-free neuronal network

Science China(Technological Sciences) 2016年第3期59卷 364-370页

作者： YILMAZ Ergin BAYSAL Veli PERC Matjaz OZER Mahmut epartment of Biomedical engineering Engineering Faculty bülent Ecevit University Zonguldak 67100 Turkey Department of Physics Faculty of Sciences King Abdulaziz University Jeddah 21431 Saudi Arabia faculty of Natural Sciences and Mathematics University of Maribor Korogka cesta 160 Maribor SI-2000 Slovenia Department of Electrical and Electronics engineering Engineering Faculty bülent Ecevit University Zonguldak 67100 Tarkey

An autapse is an unusual synapse that occurs between the axon and the soma of the same neuron. Mathematically, it can be described as a self-delayed feedback loop that is defined by a specific time-delay and the so-called autaptic coupling strength. Recently, the role and function of autapses within the nervous system has been studied extensively. Here, we extend the scope of theoretical research by investigating the effects of an autapse on the transmission of a weak localized pacemaker activity in a scale-free neuronal network. Our results reveal that by mediating the spiking activity of the pacemaker neuron, an autapse increases the propagation of its rhythm across the whole network, if only the autaptic time delay and the autaptic coupling strength are properly adjusted. We show that the autapse-induced enhancement of the transmission of pacemaker activity occurs only when the autaptic time delay is close to an integer multiple of the intrinsic oscillation time of the neurons that form the network. In particular, we demonstrate the emergence of multiple resonances involving the weak signal, the intrinsic oscillations, and the time scale that is dictated by the autapse. Interestingly, we also show that the enhancement of the pacemaker rhythm across the network is the strongest if the degree of the pacemaker neuron is lowest. This is because the dissipation of the localized rhythm is contained to the few directly linked neurons, and only afterwards, through the secondary neurons, it propagates further. If the pacemaker neuron has a high degree, then its rhythm is simply too weak to excite all the neighboring neurons, and propagation therefore fails.

关键词：心脏起搏器无标度网络神经元随机共振突触诱导网络传播耦合强度

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Microstructure to thermomagnetic and mechanical properties relationship in Gd75Ge15Si5Pr5 alloy

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Journal of Rare Earths 2019年第11期37卷 1213-1217页

作者： M.Hasiak A.Laszcz faculty of Mechanical engineering Department of Mechanics and Materials Science EngineeringWroclaw University of Science and Technology

The relationship between topography,thermo magnetic and mechanical properties in the as-cast Gd75Ge15Si5Pr5 alloy was *** force microscopy investigations accompanied by micrograph analysis confirm dual phase nature(observed as dark and bright phase)of the investigated *** mechanical properties studies performed with respect to the Oliver-Pharr procedure show that the average instrumental hardness,Young’s modulus and elastic deformation energy to total energy ratio equal 905 HV and 596 HV,131 and 91 GPa,40%and 45%for the dark and bright phase,*** Curie point defined as inflection point on the magnetization versus temperature curve M(T)recorded in zero-field cooled mode equals 283 *** the law of approach to magnetic saturation the temperature dependence of effective anisotropy constant Keff was calculated in ferromagnetic *** is also stated that the minimum observed on thermomagnetic M(T)characteristic at 100 K is associated with Keff(T)dependence.

关键词： Thermomagnetic properties Nanomechanical properties Magnetocrystalline anisotropy GdGeSi alloys Curie point Rare earths

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Microstructures,Thermal and Mechanical Properties of Pure Tungsten—A Comparison Between Selective Laser Melting and Hot Rolling

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Chinese Journal of Mechanical engineering 2022年第3期35卷 219-226页

作者： Chong Wang Daobing Chen Yan Zhou Zhuoming Xie Qianfeng Fang Shifeng Wen Chunze Yan State Key Laboratory of Material Processing and Die&Mold Technology School of Materials Science and EngineeringHuazhong University of Science and TechnologyWuhan 430074China faculty of engineering China University of GeosciencesWuhan 430074China Key Laboratory of Materials Physics Institute of Solid State PhysicsChinese Academy of SciencesHefei 230031China

A comparative study on the influence of different manufacturing methods(selective laser melting and hot rolling)on the microstructure,mechanical and thermal behaviours of tungsten(W)was presented for the first *** results indicated that the selective laser melting(SLM)W exhibited a finer grain sizes,a lower strength ductility,hardness and thermal conductivity compared to hot-rolled *** main reason for this result was that the laser underwent rapid heating and cooling when it was used to melt W powder with high energy density,resulting in large internal stress in the sample after ***,the internal stress was released,leading to the generation of microcracks at the grain boundaries,thereby affecting the performance of SLM W *** addition,the higher fraction of high-angle grain boundaries(HAGBs)of SLM W was found to be the key factor for intrinsic *** the HAGBs are the preferred crack paths,which could promote crack propagation and decrease fracture energy.

关键词： Tungsten(W) Selective laser melting(SLM) Hot rolling Microstructure Thermal conductivity Mechanical property

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Simultaneously enhancing mechanical and tribological properties of carbon fiber composites by grafting SiC hexagonal nanopyramids for brake disk application

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Journal of Materials Science & Technology 2022年第26期121卷 1-8页

作者： Yao Guo Leilei Zhang Qiang Song Ruonan Zhang Fei Zhao Wei Li Hongchao Sheng Xianghui Hou Hejun Li State Key Laboratory of Solidification Processing Shaanxi Key Laboratory of Fiber Reinforced Light Composite MaterialsNorthwestern Polytechnical UniversityXi’an 710072China Department of Materials Science and engineering Jiangsu University of Science and TechnologyZhenjiang 212003China faculty of engineering The University of NottinghamUniversity ParkNottingham NG72RDUnited Kingdom

Extensive attention has been drawn to the development of carbon fiber composites for their application in brake disks due to the increasing demand for brake disks with high mechanical strength and better tribological ***,we design SiC hexagonal nanopyramids modified carbon/carbon(SiCNPsC/C)composites,in which SiCNPs are radially grafted on the carbon fibers by the combined sol-gel and carbothermal reduction method,and pyrolytic carbon(Py C)matrix is deposited on nucleation sites including carbon fibers and SiCNPs by isothermal chemical vapor infiltration(ICVI).Benefiting from the special structure,SiCNPs-C/C composites exhibit superior mechanical and frictional *** with C/C composites,SiCNPs-C/C composites have 147%,90.3%,70.6%,and 117.9%improvement in the hardness,interlaminar shear strength,and out-of-plane and in-plane compressive strength,respectively,which is attributed to the optimized fiber/matrix(F/M)interfaces bonding and the enhanced cohesion strength of Py C *** addition,the friction coefficient of SiCNPs-C/C composites increases by 25.5%,and the wear rate decreases by 38.0%.This work provides an optional design thought for the nanomaterials and enlightens the mechanical and frictional modification of composites in the field of the brakes.

关键词： SiC hexagonal nanopyramids Carbon/carbon composites Microstructure Mechanical properties Tribological properties

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Mechanically flexible V_(3)S_(4)@carbon composite fiber as a high-capacity and fast-charging anode for sodium-ion capacitors

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稀有金属:英文版 2023年第8期42卷 2633-2642页

作者： Zhi-Fei Mao Xiao-Jun Shi Tao-Qiu Zhang Peng-Ju Liang Rui Wang Jun Jin Bei-Bei He Yan-Sheng Gong Qiang Wang Xi-Li Tong Huan-Wen Wang faculty of Material Science and Chemistry China University of GeosciencesWuhan 430074China engineering Laboratory of Chemical Resources Utilization in South Xinjiang of XPCC Department of Chemistry and Chemical EngineeringCollege of LifeTarim UniversityAlar 843300China State Key Laboratory of Coal Conversion Institute of Coal ChemistryChinese Academy of SciencesTaiyuan 030001China

Hybrid Na-ion capacitors(NICs)have received considerable interests owing to their low-cost,high-safety,and rapidly charging energy-storage *** NICs are composed of a capacitor-type cathode and a battery-type *** major challenge for NICs is to search for suitable electrode materials to overcome the sluggish diffusion of Na^(+)in the ***,ultrafine vanadium sulfide is encapsulated in carbon fiber(V_(3)S_(4)@CNF)as a self-supported electrode by electrospinning and in situ *** carbon cladding and one-dimensional(ID)nanofiber network-like structure could alleviate the volume expansion of V_(3)S_(4)during Na^(+)de-/intercalation ***,the V_(3)S_(4)@CNF anode exhibited a pseudocapacitive sodium storage in terms of large Na^(+)-storage capacity(476 mAh·g^(-1)at 0.1A·g^(-1)),high-rate capability(290 mAh·g^(-1)at 20.0 A·g^(-1))and excellent cycling stability(95%capacity retention for1500 cycles at 2.0 A·g^(-1))in Na *** employing V_(3)S_(4)@CNF as the anode and the activated carbon(AC)cathode,the as-assembled NICs could deliver a high energy density of 110 Wh·kg^(-1)at a power density of200 W·kg^(-1).Even at a high power of 10,000 W·kg^(-1),the specific energy is still up to 42 Wh·kg^(-1).

关键词： Electrospinning Na-ion capacitor(NIC) Nanofibers Vanadium sulfide Fast-charging

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Covid-19 CT Lung Image Segmentation Using Adaptive Donkey and Smuggler Optimization Algorithm

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Computers, Materials & Continua 2022年第4期71卷 1133-1152页

作者： P.Prabu K.Venkatachalam Ala Saleh Alluhaidan Radwa Marzouk Myriam Hadjouni Sahar A.El_Rahman Department of Computer Science CHRIST(Deemed to be University)BengaluruIndia Department of Computer Science and engineering CHRIST(Deemed to be University)BengaluruIndia Information Systems Department College of Computer and Information SciencePrincess Nourah Bint Abdulrahman UniversityRiyadhKSA 84428Saudi Arabia Department of Mathematics Faculty of ScienceCairo UniversityGiza12613Egypt Computer Sciences Department College of Computer and Information SciencePrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia Department of Electrical engineering Faculty of Engineering-ShoubraBenha UniversityCairoEgypt

COVID’19 has caused the entire universe to be in existential healthcrisis by spreading globally in the year 2020. The lungs infection is detected inComputed Tomography (CT) images which provide the best way to increasethe existing healthcare schemes in preventing the deadly virus. Nevertheless,separating the infected areas in CT images faces various issues such as lowintensity difference among normal and infectious tissue and high changes inthe characteristics of the infection. To resolve these issues, a new inf-Net (LungInfection Segmentation Deep Network) is designed for detecting the affectedareas from the CT images automatically. For the worst segmentation results,the Edge-Attention Representation (EAR) is optimized using AdaptiveDonkey and Smuggler Optimization (ADSO). The edges which are identifiedby the ADSO approach is utilized for calculating dissimilarities. An IFCM(Intuitionistic Fuzzy C-Means) clustering approach is applied for computingthe similarity of the EA component among the generated edge maps andGround-Truth (GT) edge maps. Also, a Semi-Supervised Segmentation(SSS) structure is designed using the Randomly Selected Propagation (RP)technique and Inf-Net, which needs only less number of images and unlabelleddata. Semi-Supervised Multi-Class Segmentation (SSMCS) is designed usinga Bi-LSTM (Bi-Directional Long-Short-Term-memory), acquires all theadvantages of the disease segmentation done using Semi Inf-Net and enhancesthe execution of multi-class disease labelling. The newly designed SSMCSapproach is compared with existing U-Net++, MCS, and *** such as MAE (Mean Absolute Error), Structure measure, Specificity(Spec), Dice Similarity coefficient, Sensitivity (Sen), and Enhance-AlignmentMeasure are considered for evaluation purpose.

关键词： Adaptive donkey and snuggler optimization.bi-directional long short term memory coronavirus disease 2019 randomly selected propagation semi-supervised learning

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Optimal Load Forecasting Model for Peer-to-Peer Energy Trading in Smart Grids

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Computers, Materials & Continua 2022年第1期70卷 1053-1067页

作者： Lijo Jacob Varghese K.Dhayalini Suma Sira Jacob Ihsan Ali Abdelzahir Abdelmaboud Taiseer Abdalla Elfadil Eisa Department of Electrical and Electronics engineering Christian College of Engineering and TechnologyOddanchatram624619India Department of Electrical and Electronics engineering K.Ramakrishnan College of EngineeringTiruchirappalli621112India Department of Computer Science and engineering Christian College of Engineering and TechnologyOddanchatram624619India Department of Computer System and Technology Faculty of Computer Science and Information TechnologyUniversity of Malaya50603Kuala LumpurMalaysia Department of Information Systems King Khalid UniversityMuhayel Aseer62529Saudi Arabia Department of Information Systems-Girls Section King Khalid UniversityMahayil62529Saudi Arabia

Peer-to-Peer(P2P)electricity trading is a significant research area that offers maximum fulfilment for both prosumer and *** also decreases the quantity of line loss incurred in Smart Grid(SG).But,uncertainities in demand and supply of the electricity might lead to instability in P2P market for both prosumer and *** recent times,numerous Machine Learning(ML)-enabled load predictive techniques have been developed,while most of the existing studies did not consider its implicit features,optimal parameter selection,and prediction *** order to overcome fulfill this research gap,the current research paper presents a new Multi-Objective Grasshopper Optimisation Algorithm(MOGOA)with Deep Extreme Learning Machine(DELM)-based short-term load predictive technique i.e.,MOGOA-DELM model for P2P Energy Trading(ET)in *** proposed MOGOA-DELM model involves four distinct stages of operations namely,data cleaning,Feature Selection(FS),prediction,and parameter *** addition,MOGOA-based FS technique is utilized in the selection of optimum subset of ***,DELM-based predictive model is also applied in forecasting the load *** proposed MOGOA model is also applied in FS and the selection of optimalDELM parameters to improve the predictive *** inspect the effectual outcome of the proposed MOGOA-DELM model,a series of simulations was performed using UK Smart Meter *** the experimentation procedure,the proposed model achieved the highest accuracy of 85.80%and the results established the superiority of the proposed model in predicting the testing data.

关键词： Peer to Peer energy trade smart grid load forecasting machine learning feature selection

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Predictive Control Based on Ranking Multi-objective Optimization Approaches for a quasi-Z Source Inverter

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CSEE Journal of Power and Energy Systems 2021年第6期7卷 1152-1160页

作者： Abualkasim Bakeer Gaber Magdy Andrii Chub Dmitri Vinnikov the Department of Electrical engineering Faculty of EngineeringAswan University81542 AswanEgypt the Power Electronics Group Department of Electrical Power Engineering and MechatronicsTallinn University of TechnologyTallinn 19086Estonia the Department of Electrical engineering Faculty of Energy EngineeringAswan University81542 AswanEgypt

In power converter control,predictive control has several merits,such as simple concept and fast ***,the necessity to use the weighting factor inside the cost function makes the control design complex in the case of regulating multivariables where the value of the weighting factor is obtained by a nontrivial ***,it primarily depends on the system parameters and operating points of the control *** paper aims to enhance the model predictive algorithm of the singlestage topology of a quasi-Z Source Inverter(qZSI).The concept of a multi-objective optimization approach is used in addition to the sub-cost function definition to remove the weighting *** using the sub-cost function definition,the inductor current is pushed away from the main loop of the predictive ***,no weighting factor is needed to manage the priority of the inductor *** other two control targets,which are the capacitor voltage and load currents,will be controlled by the multi-objective optimization approach without using any weighting factors.A detailed theoretical analysis of the proposed technique will be given and validated based on simulation results.

关键词： Cost function definition model predictive control optimization methods quasi-Z Source Inverter(qZSI) weighting factors

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Batch-to-batch Optimization of Batch Crystallization Processes

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Chinese Journal of Chemical engineering 2008年第1期16卷 26-29页

作者： Woranee Paengjuntuek Paisan Kittisupakorn Amornchal Arpornwlchanop Control and Systems engineering Research Center Department of Chemical Engineering Faculty of Engineering Chulalongkorn University Bangkok 10330 Thailand

几个过程参数未知或不明确，这是事实。因此，最佳的控制侧面关于这与发达进程模型一起推测当实现了到真实进程时，进程参数不能给最佳的表演。这研究在硫酸钾生产的一个批结晶化过程为不明确的运动参数的评价建议 batch-to-batch 优化... 详细信息

几个过程参数未知或不明确，这是事实。因此，最佳的控制侧面关于这与发达进程模型一起推测当实现了到真实进程时，进程参数不能给最佳的表演。这研究在硫酸钾生产的一个批结晶化过程为不明确的运动参数的评价建议 batch-to-batch 优化策略。在批操作的结束的产品的晶体大小分布的知识在建议方法论被使用。更新的运动参数被申请为下一个成批处理决定一条最佳的操作温度政策。

关键词：间歇结晶实验研究结晶过程分批优化

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Development of calibration models for rapid determination of moisture content in rubber sheets using portable near-infrared spectrometers

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Journal of Innovative Optical Health Sciences 2020年第2期13卷 81-92页

作者： Amorndej Puttipipatkajorn Amornrit Puttipipatkajorn Department of Food engineering faculty of engineering at Kamphaeng Saen Kasetsart University Nakorn Pathom 73140Thailand Department of Computer engineering faculty of engineering at Kamphaeng Saen Kasetsart University Nakorn Pathom 73140Thailand

Rubber sheets are one of the primary products of natural rubber and are the main raw material in various rubber *** quality of a rubber sheet can be visually examined by holding it against clear light to inspect for any specks and impurities inside,but its moisture content is difficult to evaluate based on a visual inspection and this might lead to unfair ***,we developed a rapid,robust and nondestructive near-infrared spectroscopy(NIRS)-based method for moisture content determination in rubber sheets.A set of 300 rubber sheets were divided into a calibration(200 samples)and prediction groups(100 samples).The calibration set was used to develop NIRS calibration equation using different calibration models,Partial Least Square Regression(PLSR),Least Square Support Vector Machine(LS-SVM)and Articial Neural Network(ANN).Among the models investigated,the ANN model with therst derivative of spectral preprocessing presented the best prediction with a coe±cient of determination(R^(2)_(P))of 0.993,root mean square error of calibration(RMSEC)of 0.126%and root mean square error of prediction(RMSEP)of 0.179%.The results indicated that the proposed NIRS-ANN model will be able to reduce human error and provide a highly accurate estimate of the moisture content in a rubber sheet compared to traditional wet chemistry estimation methods according to AOAC standards.

关键词： NIR spectroscopy rubber sheet moisture content partial least squares regression arti¯cial neural network least squares support vector machine

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