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Anderson Acceleration of Gradient Methods with Energy for Optimization Problems

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Communications on Applied Mathematics and Computation 2024年第2期6卷 1299-1318页

作者： Hailiang Liu jia-hao He Xuping Tian Department of Mathematics Iowa State UniversityAmesIAUSA Department of Agricultural and Biosystems Engineering Iowa State UniversityAmesIAUSA

Anderson acceleration(AA)is an extrapolation technique designed to speed up fixed-point *** optimization problems,we propose a novel algorithm by combining the AA with the energy adaptive gradient method(AEGD)[arXiv:2010.05109].The feasibility of our algorithm is ensured in light of the convergence theory for AEGD,though it is not a fixed-point *** provide rigorous convergence rates of AA for gradient descent(GD)by an acceleration factor of the gain at each implementation of *** experimental results show that the proposed AA-AEGD algorithm requires little tuning of hyperparameters and exhibits superior fast convergence.

关键词： Anderson acceleration(AA) Gradient descent(GD) Energy stability

Lead-free perovskites-based photonic synaptic devices with zero electric energy consumption

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Science China(Information Sciences) 2024年第6期67卷 433-441页

作者： Dandan hao Di YANG Haixia LIANG jia HUANG Fukai SHAN College of Electronics and Information Qingdao University Key Laboratory of Biofuels Qingdao Institute of Bioenergy and Bioprocess TechnologyChinese Academy of Sciences School of Materials Science and Engineering Tongji University National Key Laboratory of Autonomous Intelligent Unmanned Systems Tongji University

The von Neumann bottleneck is a critical limitation in synaptic devices. Therefore, artificial synaptic devices resembling biological neuromorphic synapses have been developed to overcome the von Neumann bottleneck. However, synaptic devices require voltages, which results in considerable energy consumption. Here, photonic synaptic devices with the vertical structure of indium tin oxide（ITO）/SnO2/Al2O3/CsBi3I10/Au are fabricated, which can work in the self-powered mode owing to the photovoltaic effect endowed by a vertical multilayer structure. Several fundamental synaptic functions, such as excitatory postsynaptic current, paired-pulse facilitation, short-term plasticity（STP）, long-term plasticity（LTP）, pulse-frequency-dependent plasticity, transition of STP to LTP, and the learning experience are emulated. Moreover, Morse-coded external light information is decoded by self-powered photonic synaptic devices. The results indicate that self-powered photonic synaptic devices based on lead-free perovskites exhibit great potential for efficient neuromorphic computing and optical wireless communication.

关键词： photonic synaptic devices lead-free perovskites zero energy consumption synaptic plasticity Morse code

Recent advances of high-entropy electrocatalysts for water electrolysis by electrodeposition technology:a short review

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Rare Metals 2024年第6期43卷 2371-2390页

作者： Han-Ming Zhang Shao-Fei Zhang Li-hao Zuo jia-Kang Li Jun-Xia Guo peng Wang Jin-Feng Sun Lei Dai Hebei Key Laboratory of Flexible Functional Materials School of Materials Science and EngineeringHebei University of Science and TechnologyShijiazhuang 050018China Department of Chemistry National University of SingaporeSingapore117543Singapore

Hydrogen is considered as the promising energy carrier to substitute traditional fossil fuel,due to its cleanliness,renewability and high energy *** electrolysis is a simple and eonvenient technology for hydrogen *** efficiency of water electrolysis for hydrogen production is limited by the electrocatalytic performances on hydrogen evolution reaction(HER)and oxygen evolution reaction(OER).The exorbitant Pt-and Ir-/Ru-based electrocatalysts as optimal HER and OER electrocatalysts,respectively,restrict water electrolysis ***,non-precious metal-based high-entropy electrocatalysts have exhibited excellent electrocatalytic activities and long-term stabilities for water electrolysis,as promising precious cataly st ***,the construction of the high-entropy electroc atalysts is vital to water electrolysis *** technology is an efficient method for the preparation of high-entropy electrocatalysts due to its simple,fast,energy-saving and environmental-friendly ***-component co-precipitation facilely occurs during the electroredox in electrodeposition ***-entropy alloys,oxides,(oxy)hydroxides,phosphides and phosphorus sulfide oxides have been successfully prepared by galvanostatic,potentiostatic electrodeposition,cyclic voltammetry,pulse,nanodroplet-mediated and cathodic plasma electrodeposition ***,introduction of the development of high-entropy electrocatalysts synthesized by electrodeposition technology is significant to researchers and *** and outlooks are also concluded to boost the industrial application of electrodeposition in water electrolysis and other energy conversion areas.

关键词： High-entropy electrocatalysts Electrodeposition technology Water electrolysis Multi-component co-precipitation Excellent electrocatalytic performances

Deep Learning and Tensor-Based Multiple Clustering Approaches for Cyber-Physical-Social Applications

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Computers, Materials & Continua 2024年第3期78卷 4109-4128页

作者： Hongjun Zhang hao Zhang Yu Lei hao Ye peng Li Desheng Shi School of Computer Science Nanjing University of Posts and TelecommunicationsNanjing210023China China Communications Services Co. Ltd.Beijing100071China China Communications Services Hexin Science&Technology Co. Ltd.Hefei230031China

The study delves into the expanding role of network platforms in our daily lives, encompassing various mediums like blogs, forums, online chats, and prominent social media platforms such as Facebook, Twitter, and Instagram. While these platforms offer avenues for self-expression and community support, they concurrently harbor negative impacts, fostering antisocial behaviors like phishing, impersonation, hate speech, cyberbullying, cyberstalking, cyberterrorism, fake news propagation, spamming, and fraud. Notably, individuals also leverage these platforms to connect with authorities and seek aid during disasters. The overarching objective of this research is to address the dual nature of network platforms by proposing innovative methodologies aimed at enhancing their positive aspects and mitigating their negative repercussions. To achieve this, the study introduces a weight learning method grounded in multi-linear attribute ranking. This approach serves to evaluate the significance of attribute combinations across all feature spaces. Additionally, a novel clustering method based on tensors is proposed to elevate the quality of clustering while effectively distinguishing selected features. The methodology incorporates a weighted average similarity matrix and optionally integrates weighted Euclidean distance, contributing to a more nuanced understanding of attribute importance. The analysis of the proposed methods yields significant findings. The weight learning method proves instrumental in discerning the importance of attribute combinations, shedding light on key aspects within feature spaces. Simultaneously, the clustering method based on tensors exhibits improved efficacy in enhancing clustering quality and feature distinction. This not only advances our understanding of attribute importance but also paves the way for more nuanced data analysis methodologies. In conclusion, this research underscores the pivotal role of network platforms in contemporary society, emp

关键词： Network platform tensor-based clustering weight learning multi-linear euclidean

A hybrid machine learning optimization algorithm for multivariable pore pressure prediction

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Petroleum Science 2024年第1期21卷 535-550页

作者： Song Deng hao-Yu Pan Hai-Ge Wang Shou-Kun Xu Xiao-peng Yan Chao-Wei Li Ming-Guo peng hao-Ping peng Lin Shi Meng Cui Fei Zhao School of Petroleum and Natural Gas Engineering Changzhou UniversityChangzhou213164JiangsuChina Tubular Goods Research Institute of CNPC Beijing102249China CNPC Engineering Technology R&D Company Limited Beijing102206China

Pore pressure is essential data in drilling design,and its accurate prediction is necessary to ensure drilling safety and improve drilling *** methods for predicting pore pressure are limited when forming particular structures and *** this paper,a machine learning algorithm and effective stress theorem are used to establish the transformation model between rock physical parameters and pore *** study collects data from three *** 1 had 881 data sets for model training,and Wells 2 and 3 had 538 and 464 data sets for model *** this paper,support vector machine(SVM),random forest(RF),extreme gradient boosting(XGB),and multilayer perceptron(MLP)are selected as the machine learning algorithms for pore pressure *** addition,this paper uses the grey wolf optimization(GWO)algorithm,particle swarm optimization(PSO)algorithm,sparrow search algorithm(SSA),and bat algorithm(BA)to establish a hybrid machine learning optimization algorithm,and proposes an improved grey wolf optimization(IGWO)*** IGWO-MLP model obtained the minimum root mean square error(RMSE)by using the 5-fold cross-validation method for the training *** the pore pressure data in Well 2 and Well 3,the coefficients of determination(R^(2))of SVM,RF,XGB,and MLP are 0.9930 and 0.9446,0.9943 and 0.9472,0.9945 and 0.9488,0.9949 and *** achieves optimal performance on both training and test data,and the MLP model shows a high degree of *** indicates that the IGWO-MLP is an excellent predictor of pore pressure and can be used to predict pore pressure.

关键词： Pore pressure Grey wolf optimization Multilayer perceptron Effective stress Machine learning

Strategies for constructing seven-membered rings:Applications in natural product synthesis

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Chinese Chemical Letters 2024年第6期35卷 53-70页

作者： peng Chen Lijuan Liang Yufei Zhu Zhimin Xing Zhenhua jia Teck-peng Loh College of Advanced Interdisciplinary Science and Technology Henan University of TechnologyZhengzhou 450001China Division of Chemistry and Biological Chemistry School of Chemistry Chemical Engineeringand BiotechnologyNanyang Technological UniversitySingapore 637371Singapore Institute of Advanced Synthesis School of Chemistry and Molecular Engineering Nanjing Tech UniversityNanjing 211816China State Key Laboratory of Applied Organic Chemistry Department of ChemistryLanzhou UniversityLanzhou 730000China

The seven-membered ring motifs are found in bioactive pharmaceuticals and a wide range of natural products,including alkaloids and terpenoids,which hold significant importance in synthetic chemistry and has garnered considerable attention from both academia and *** the challenges faced in the past decade,the total synthesis of natural products incorporating the non-aromatic cycloheptane skeletons remains a compelling ***,numerous elegant strategies for constructing the sevenmembered ring system have been successfully *** review focuses on the recent advancements in this field from 2017 to April 2023,highlighting key transformations utilized to construct the non-aromatic cycloheptane core structures and serves as a valuable guide for synthetic chemists engaged in the total synthesis of natural products containing seven-membered ring motifs.

关键词： Seven-membered rings Total synthesis Natural products Synthetic strategy Cycloheptane

Recent applications of macrocycles in supramolecular catalysis

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Chinese Chemical Letters 2024年第4期35卷 132-141页

作者： Conghui Wang Lei Xu Zhenhua jia Teck-peng Loh College of Advanced Interdisciplinary Science and Technology Henan University of TechnologyZhengzhou 450001China Division of Chemistry and Biological Chemistry School of Chemistry Chemical Engineeringand BiotechnologyNanyang Technological UniversitySingapore 637371Singapore Institute of Advanced Synthesis School of Chemistry and Molecular Engineering Nanjing Tech UniversityNanjing 211816China

Numerous supramolecular macrocycles have been utilized for developing catalysts by exploiting their specific molecular recognition and ability to form inclusion complexes through noncovalent interactions. The cyclic structure and modified functional groups of these macrocycles can influence substrate and transition state stability, as well as reaction selectivity. The inner cavities of these macrocycles are particularly beneficial, as they enable substrates to adopt preorganized arrangements and serve as versatile platforms for highly efficient supramolecular catalytic systems. This minireview provides an overview of recent advancements in supramolecular catalysis using various macrocycles, such as crown ethers, cyclodextrins,calixarenes, pillararenes, cucurbiturils, and other novel macrocycles.

关键词： Supramolecular catalysis Macrocycle Host-guest interactions Confinement Selectivity

Development and validation of a machine learning-based early prediction model for massive intraoperative bleeding in patients with primary hepatic malignancies

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World Journal of Gastrointestinal Oncology 2024年第1期16卷 90-101页

作者： Jin Li Yu-Ming jia Zhi-Lei Zhang Cheng-Yu Liu Zhan-Wu jiang Zhi-Wei hao Li peng Department of Hepatological Surgery The Fourth Hospital of Hebei Medical UniversityShijiazhuang 050011Hebei ProvinceChina Department of General Surgery II Baoding First Central HospitalBaoding 071000Hebei ProvinceChina

BACKGROUND Surgical resection remains the primary treatment for hepatic malignancies,and intraoperative bleeding is associated with a significantly increased risk of ***,accurate prediction of intraoperative bleeding risk in patients with hepatic malignancies is essential to preventing bleeding in advance and providing safer and more effective *** To develop a predictive model for intraoperative bleeding in primary hepatic malignancy patients for improving surgical planning and *** The retrospective analysis enrolled patients diagnosed with primary hepatic malignancies who underwent surgery at the Hepatobiliary Surgery Department of the Fourth Hospital of Hebei Medical University between 2010 and *** regression analysis was performed to identify potential risk factors for intraoperative bleeding.A prediction model was developed using Python programming language,and its accuracy was evaluated using receiver operating characteristic(ROC)curve *** Among 406 primary liver cancer patients,16.0%(65/406)suffered massive intraoperative *** regression analysis identified four variables as associated with intraoperative bleeding in these patients:ascites[odds ratio(OR):22.839;P<0.05],history of alcohol consumption(OR:2.950;P<0.015),TNM staging(OR:2.441;P<0.001),and albumin-bilirubin score(OR:2.361;P<0.001).These variables were used to construct the prediction *** 406 patients were randomly assigned to a training set(70%)and a prediction set(30%).The area under the ROC curve values for the model’s ability to predict intraoperative bleeding were 0.844 in the training set and 0.80 in the prediction *** The developed and validated model predicts significant intraoperative blood loss in primary hepatic malignancies using four preoperative clinical factors by considering four preoperative clinical factors:ascites,history of alcohol consumption,TNM staging,and albumin-bilirubin ***

关键词： Primary liver cancer Intraoperative bleeding Machine learning Model

A core scientific problem in the treatment of central nervous system diseases:newborn neurons

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Neural Regeneration Research 2024年第12期19卷 2588-2601页

作者： peng hao Zhaoyang Yang Kwok-Fai So Xiaoguang Li Department of Neurobiology School of Basic Medical SciencesCapital Medical UniversityBeijingChina Guangdong-HongKong-Macao Institute of CNS Regeneration Ministry of Education CNS Regeneration Collaborative Joint LaboratoryJinan UniversityGuangzhouGuangdong ProvinceChina Bioland Laboratory(Guangzhou Regenerative Medicine and Health Guangdong Laboratory) GuangzhouGuangdong ProvinceChina Department of Ophthalmology and State Key Laboratory of Brain and Cognitive Sciences The University of Hong KongHong Kong Special Administration RegionChina Center for Brain Science and Brain-Inspired Intelligence Guangdong-Hong Kong-Macao Greater Bay AreaGuangzhouGuangdong ProvinceChina Co-innovation Center of Neuroregeneration Nantong UniversityNantongJiangsu ProvinceChina Department of Biomedical Engineering School of Biological Science and Medical EngineeringBeihang UniversityBeijingChina

It has long been asserted that failure to recover from central nervous system diseases is due to the system's intricate structure and the regenerative incapacity of adult *** over recent decades,numerous studies have established that endogenous neurogenesis occurs in the adult central nervous system,including humans'.This has challenged the long-held scientific consensus that the number of adult neurons remains constant,and that new central nervous system neurons cannot be created or ***,we present a comprehensive overview of the alterations and regulatory mechanisms of endogenous neurogenesis following central nervous system injury,and describe novel treatment strategies that to rget endogenous neurogenesis and newborn neurons in the treatment of central nervous system *** nervous system injury frequently results in alterations of endogenous neurogenesis,encompassing the activation,proliferation,ectopic migration,diffe rentiation,and functional integration of endogenous neural stem *** of the unfavorable local microenvironment,most activated neural stem cells diffe rentiate into glial cells rather than ***,the injury-induced endogenous neurogenesis response is inadequate for repairing impaired neural *** have attempted to enhance endogenous neurogenesis using various strategies,including using neurotrophic factors,bioactive materials,and cell reprogramming *** alone or in combination,these therapeutic strategies can promote targeted migration of neural stem cells to an injured area,ensure their survival and diffe rentiation into mature functional neurons,and facilitate their integration into the neural *** can integration re plenish lost neurons after central nervous system injury,by improving the local *** regulating each phase of endogenous neurogenesis,endogenous neural stem cells can be harnessed to promote effective regeneration of newborn ***

关键词： bioactive materials brain trauma endogenous neurogenesis hippocampal dentate gyrus neural stem cells neurotrophic factors newborn neurons spinal cord injury stroke subventricular zone