检索结果-南通市图书馆

Impact of sourdough fermentation on nutrient transformations in cereal-based foods:Mechanisms,practical applications,and health implications

在线全文

学校读者我要写书评

暂无评论

Grain & Oil Science and Technology 2024年第2期7卷 124-132页

作者： zhen wang Luyang wang State Key Laboratory of Crop Stress Adaptation and Improvement College of AgricultureHenan UniversityKaifeng 475004China

Sourdough is often considered a healthy choice and quality improver for use in cereal production due to its unique microbial composition and fermentation *** sourdough fermentation of cereals,biotransformation of nutrients occurs,resulting in notable changes to proteins,carbohydrates,fats,vitamins,and *** nutrient undergoes specific transformations,providing various advantages for human *** undergo hydrolysis to produce small molecular weight peptides and amino acids that are more easily digested and absorbed by the human *** break down to improve the digestibility and absorption of cereals and lower the glycemic *** acids experience oxidation to produce new substances with health ***,the application of sourdough fermentation can enhance the texture,flavor,and nutritional value of cereal foods while also extending their shelf life and improving food *** conclusion,sourdough fermentation has a broad range of applications in cereal food *** research is encouraged to investigate the mechanisms and processes of sourdough fermentation to develop even more nutritious,healthy,and flavorful cereal-based foods.

关键词： Sourdough fermentation Lactic acid bacteria Proteolysis Starch hydrolysis Low-GI Nutrients

Polymer-to-Monomers Chemically Recyclable Poly(imide-imine)Plastics with Extreme-Condition Resistance and Flame Retardancy

在线全文

学校读者我要写书评

暂无评论

Chinese Journal of Polymer Science 2024年第10期42卷 1525-1535,I0012页

作者： zhen-Yu wang Xiao-Kong Liu State Key Laboratory of Supramolecular Structure and Materials College of ChemistryJilin UniversityChangchun130012China

Polyimides are a family of high-tech plastics that have irreplaceable applications in the fields of aerospace,defense,and opto-electronics,but polyimides are difficult to be reprocessed and recycled at the end of their service life,resulting in a significant waste of ***,it is of great significance to develop recyclable polyimides with comparable properties to the commercial ***,we report a novel polymer-to-monomers chemically recyclable poly(imide-imine)(PtM-CR-PII)plastic,synthesized by cross-linking the amine-terminated aromatic bisimide monomer and the hexa-vanillin terminated cyclophosphazene monomer via dynamic imine *** PtM-CR-PII plastic exhibits comparable mechanical and thermal properties as well as chemical stability to the commercial *** PtM-CR-PII plastic possesses a high Young’s modulus of≈3.2 GPa and a tensile strength as high as≈108 MPa,which also exhibits high thermal stability with a glass transition temperature of≈220℃.Moreover,the PtM-CR-PII plastic exhibits outstanding waterproofness,acid/alkali-resistance,and solvent-resistance,its appearance and mechanical properties can be well maintained after long-term soaking in water,highly concentrated acid and base,and various organic ***,the cyclophosphazene moieties endow the PtM-CR-PII plastic with excellent flame *** PtM-CR-PII plastic exhibits the highest UL-94 flame-retarding rating of V-0 and a limiting oxygen index(LOI)value of 45.5%.Importantly,the PtM-CR-PII plastic can be depolymerized in an organic solvents-acid mixture medium at room temperature,allowing easy separation and recovery of both monomers in high *** recovered pure monomers can be used to regenerate new PtM-CR-PII plastics,enabling sustainable polymer-monomers-polymer circulation.

关键词： Chemical recyclability Polyimides Polyimines Dynamic imine bonds Mechanical properties Chemical stability

Novel intelligent reasoning system for tool wear prediction and parameter optimization in intelligent milling

在线全文

学校读者我要写书评

暂无评论

Advances in Manufacturing 2024年第1期12卷 76-93页

作者： Long-Hua Xu Chuan-zhen Huang zhen wang Han-Lian Liu Shui-Quan Huang Jun wang School of Mechanical Engineering Yanshan UniversityQinhuangdao066004HebeiPeople’s Republic of China Center for Advanced Jet Engineering Technologies(CaJET) Key Laboratory of High-efficiency and Clean Mechanical Manufacture(Ministry of Education)National Experimental Teaching Demonstration Center for Mechanical Engineering(Shandong University)School of Mechanical EngineeringShandong UniversityJinan250061People’s Republic of China Institute of Manufacturing Technology Guangdong University of TechnologyGuangzhou510006People’s Republic of China

Accurate intelligent reasoning systems are vital for intelligent *** this study,a new intelligent reasoning system was developed for milling processes to accurately predict tool wear and dynamically optimize machining *** developed system consists of a self-learning algorithm with an improved particle swarm optimization(IPSO)learning algorithm,prediction model determined by an improved case-based reasoning(ICBR)method,and optimization model containing an improved adaptive neural fuzzy inference system(IANFIS)and *** results showed that the IPSO algorithm exhibited the best global convergence *** ICBR method was observed to have a better performance in predicting tool wear than standard CBR *** IANFIS model,in combination with IPSO,enabled the optimization of multiple objectives,thus generating optimal milling *** paper offers a practical approach to developing accurate intelligent reasoning systems for sustainable and intelligent manufacturing.

关键词： Improved particle swarm optimization(IPSO)algorithm Improved case-based reasoning(ICBR)method Adaptive neural fuzzy inference system(ANFIS)model Tool wear prediction Intelligent manufacturing

Decentralized Primary Frequency Regulation for Hybrid Multi-terminal Direct Current Power Systems Considering Multi-source Enhancement

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 958-970页

作者： Jialiang Wu zhen wang Ruixu Liu Yu Shan Chenxuan wang the College of Electrical Engineering Zhejiang UniversityHangzhou 310027China the Economic Research Institute of State Grid Zhejiang Electric Power Co. Ltd.Hangzhou 310016China

Hybrid multi-terminal direct current(MTDC)transmission technology has been a research focus,and primary frequency regulation(FR)improvement in the receiving-end system is one of the problems to be *** paper presents a decentralized primary FR scheme for hybrid MTDC power systems considering multi-source enhancement to help suppress frequency disturbance in the receiving-end *** the converters only need local frequency or DC voltage signal input to respond to system disturbance without communication or a control center,i.e.,a decentralized control *** proposed scheme can activate appropriate power sources to assist in FR in various system disturbance severities with fine-designed thresholds,ensuring sufficient utilization of each power *** better balance FR performance and FR resource participation,an evaluation index is proposed and the parameter optimization problem is further ***,the validity of the proposed scheme is verified by simulations in MATLAB/Simulink.

关键词： Decentralized control scheme primary frequency regulation(FR) rate of change of frequency(ROCOF) system frequency disturbance

Partition-based Network Equivalent Method for Power System Subsynchronous Oscillation Analysis

在线全文

学校读者我要写书评

暂无评论

Journal of Modern Power Systems and Clean Energy 2024年第1期12卷 313-320页

作者： Chenxuan wang Weimin zheng zhen wang Yangqing Dan Ping Ju the Department of Electrical Engineering Zhejiang UniversityHangzhou 310027China the Economic Research Institute of State Grid Zhejiang Electric Power Co. Ltd.Hangzhou 310016China the College of Energy and Electrical Engineering Hohai UniverstiyNanjing 211100China

Given large-scale modern power systems with pow er electronic converters,the numerical simulation with subsyn chronous oscillation(SSO)faces great challenges in engineering practice due to sharply enlarged modeling scale and high com putational *** reduce the modeling scale,network parti tion and equivalent becomes a vital technique in numerical sim *** several methods have been developed for net work equivalent,a generally accepted rule for network parti tion is still *** paper proposes that the system can be partitioned into three parts,i.e.,the internal,the middle,and the external subsystems,in which the internal subsystem consists of all power electronic components,the middle subsys tem includes those selected AC dynamic components with de tailed models,and the remaining components and buses consti tute the external *** external subsystem is further represented by an equivalent RLC network determined by the frequency dependent network equivalent(FDNE)*** the proposed method,the observability index and the electrical distance index are used to identify the interface between the middle and the external *** studies based on a modified Hydro-Quebec system are used to verify the effective ness of the proposed method.

关键词： Electrical distance network equivalent subsyn chronous oscillation observability index

Ensemble successor representations for task generalization in offline-to-online reinforcement learning

在线全文

学校读者我要写书评

暂无评论

Science China(Information Sciences) 2024年第7期67卷 240-255页

作者： Changhong wang Xudong YU Chenjia BAI Qiaosheng ZHANG zhen wang Space Control and Inertial Technology Research Center Harbin Institute of Technology Shanghai Artificial Intelligence Laboratory Shenzhen Research Institute of Northwestern Polytechnical University School of Cybersecurity Northwestern Polytechnical University

In reinforcement learning(RL), training a policy from scratch with online experiences can be inefficient because of the difficulties in exploration. Recently, offline RL provides a promising solution by giving an initialized offline policy, which can be refined through online interactions. However, existing approaches primarily perform offline and online learning in the same task, without considering the task generalization problem in offline-to-online adaptation. In real-world applications, it is common that we only have an offline dataset from a specific task while aiming for fast online-adaptation for several tasks. To address this problem, our work builds upon the investigation of successor representations for task generalization in online RL and extends the framework to incorporate offline-to-online learning. We demonstrate that the conventional paradigm using successor features cannot effectively utilize offline data and improve the performance for the new task by online fine-tuning. To mitigate this, we introduce a novel methodology that leverages offline data to acquire an ensemble of successor representations and subsequently constructs ensemble Q functions. This approach enables robust representation learning from datasets with different coverage and facilitates fast adaption of Q functions towards new tasks during the online fine-tuning *** empirical evaluations provide compelling evidence showcasing the superior performance of our method in generalizing to diverse or even unseen tasks.

关键词： offline reinforcement learning online fine-tuning task generalization successor representations ensembles

A New Industrial Intrusion Detection Method Based on CNN-BiLSTM

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第6期79卷 4297-4318页

作者： Jun wang Changfu Si zhen wang Qiang Fu College of Computer Science and Technology Shenyang University of Chemical TechnologyShenyang110142China

Nowadays,with the rapid development of industrial Internet technology,on the one hand,advanced industrial control systems(ICS)have improved industrial production ***,there are more and more cyber-attacks targeting industrial control *** ensure the security of industrial networks,intrusion detection systems have been widely used in industrial control systems,and deep neural networks have always been an effective method for identifying cyber *** intrusion detection methods still suffer from low accuracy and a high false alarm ***,it is important to build a more efficient intrusion detection *** paper proposes a hybrid deep learning intrusion detection method based on convolutional neural networks and bidirectional long short-term memory neural networks(CNN-BiLSTM).To address the issue of imbalanced data within the dataset and improve the model’s detection capabilities,the Synthetic Minority Over-sampling Technique-Edited Nearest Neighbors(SMOTE-ENN)algorithm is applied in the preprocessing *** algorithm is employed to generate synthetic instances for the minority class,simultaneously mitigating the impact of noise in the majority *** approach aims to create a more equitable distribution of classes,thereby enhancing the model’s ability to effectively identify patterns in both minority and majority *** the experimental phase,the detection performance of the method is verified using two data *** results show that the accuracy rate on the CICIDS-2017 data set reaches 97.7%.On the natural gas pipeline dataset collected by Lan Turnipseed from Mississippi State University in the United States,the accuracy rate also reaches 85.5%.

关键词： Intrusion detection convolutional neural network bidirectional long short-term memory neural network multi-head self-attention mechanism

Track-Pattern-Based Characteristics of Extratropical Transitioning Tropical Cyclones in the Western North Pacific

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Advances in Atmospheric Sciences 2024年第6期41卷 1251-1263页

作者： Hong HUANG Dan WU Yuan wang zhen wang Yu LIU College of Meteorology and Oceanography National University of Defense TechnologyChangsha 410000China No.31631 Army of PLA Huizhou 516000China School of Atmospheric Sciences and Key Laboratory of Mesoscale Severe Weather/Ministry of Education Nanjing 210023China No.93721 Army of PLA Shuozhou 038300China

Based on the Regional Specialized Meteorological Center(RSMC)Tokyo-Typhoon Center best-track data and the NCEP-NCAR reanalysis dataset,extratropical transitioning(ET)tropical cyclones(ETCs)over the western North Pacific(WNP)during 1951–2021 are classified into six clusters using the fuzzy c-means clustering method(FCM)according to their track *** characteristics of the six hard-clustered ETCs with the highest membership coefficient are *** tropical cyclones(TCs)that were assigned to clusters C2,C5,and C6 made landfall over eastern Asian countries,which severely threatened these *** landfalling TCs,93.2%completed their ET after landfall,whereas 39.8%of ETCs completed their transition within one *** frequency of ETCs over the WNP has decreased in the past four decades,wherein cluster C5 demonstrated a significant decrease on both interannual and interdecadal timescales with the expansion and intensification of the western Pacific subtropical high(WPSH).This large-scale circulation pattern is favorable for C2 and causes it to become the dominant track pattern,owning to it containing the largest number of intensifying ETCs among the six clusters,a number that has increased insignificantly over the past four *** surface roughness variation and three-dimensional background circulation led to C5 containing the maximum number of landfalling TCs and a minimum number of intensifying *** results will facilitate a better understanding of the spatiotemporal distributions of ET events and associated environment background fields,which will benefit the effective monitoring of these events over the WNP.

关键词： Western North Pacific tropical cyclone extratropical transition fuzzy c-means clustering method

Reliable calculations of nuclear binding energies by the Gaussian process of machine learning

在线全文

学校读者我要写书评

暂无评论

Nuclear Science and Techniques 2024年第6期35卷 130-144页

作者： Zi-Yi Yuan Dong Bai zhen wang Zhong-Zhou Ren School of Physics Science and Engineering Tongji UniversityShanghai 200092China College of Science Hohai UniversityNanjing 211100China Key Laboratory of Advanced Micro-Structure Materials Ministry of EducationShanghai 200092China

Reliable calculations of nuclear binding energies are crucial for advancing the research of nuclear physics. Machine learning provides an innovative approach to exploring complex physical problems. In this study, the nuclear binding energies are modeled directly using a machine-learning method called the Gaussian process. First, the binding energies for 2238 nuclei with Z > 20 and N > 20 are calculated using the Gaussian process in a physically motivated feature space, yielding an average deviation of 0.046 MeV and a standard deviation of 0.066 MeV. The results show the good learning ability of the Gaussian process in the studies of binding energies. Then, the predictive power of the Gaussian process is studied by calculating the binding energies for 108 nuclei newly included in AME2020. The theoretical results are in good agreement with the experimental data, reflecting the good predictive power of the Gaussian process. Moreover, the α-decay energies for 1169 nuclei with 50 ≤ Z ≤ 110 are derived from the theoretical binding energies calculated using the Gaussian process. The average deviation and the standard deviation are, respectively, 0.047 MeV and 0.070 MeV. Noticeably, the calculated α-decay energies for the two new isotopes ^ (204 )Ac(Huang et al. Phys Lett B 834, 137484(2022)) and ^ (207) Th(Yang et al. Phys Rev C 105, L051302(2022)) agree well with the latest experimental data. These results demonstrate that the Gaussian process is reliable for the calculations of nuclear binding energies. Finally, the α-decay properties of some unknown actinide nuclei are predicted using the Gaussian process. The predicted results can be useful guides for future research on binding energies and α-decay properties.

关键词： Nuclear binding energies decay Machine learning Gaussian process