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Grid-Connected/Islanded Switching Control Strategy for Photovoltaic Storage Hybrid Inverters Based on Modified Chimpanzee Optimization Algorithm

第11届全国脂质与脂蛋白学术会议

作者： Chang Xie zhang-sen zhou Bo-Liang Li Bao-Liang Song The State Key Laboratory of Molecular Biology Institute of Biochemistry and Cell BiologyShanghai Institutes for Biological SciencesChinese Academy of Sciences

The multiple transmembrane protein Niemann-Pick C1 like1(NPC1L1) is essential for intestinal cholesterol *** binds to NPC1L1 and is a clinically used cholesterol absorption *** studies in cultured cells have shown that NPC1L1 mediates cholesterol uptake through vesicular endocytosis that can be blocked by ezctimibe. However,how NPC1L1 and ezetimibe work in small intestine is *** this study,we

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Energy Engineering 2025年第1期122卷 265-284页

作者： Chao zhou NarisuWang Fuyin Ni Wenchao zhang School of Electrical and Information Engineering Jiangsu University of TechnologyChangzhou213001China Jiangsu Key Laboratory of Power Transmission&Distribution Equipment Technology Jiangsu University of TechnologyChangzhou213001China

Uneven power distribution,transient voltage,and frequency deviations are observed in the photovoltaic storage hybrid inverter during the switching between grid-connected and island *** response to these issues,this paper proposes a grid-connected/island switching control strategy for photovoltaic storage hybrid inverters based on the modified chimpanzee optimization *** proposed strategy incorporates coupling compensation and power differentiation elements based on the traditional droop ***,it combines the angular frequency and voltage amplitude adjustments provided by the phase-locked loop-free pre-synchronization control *** pre-synchronization is achieved by regulating the virtual current to zero and aligning the photovoltaic storage hybrid inverter with the grid ***,two novel operators,learning and emotional behaviors are introduced to enhance the optimization precision of the chimpanzee *** operators ensure high-precision and high-reliability optimization of the droop control parameters for photovoltaic storage hybrid inverters.A Simulink model was constructed for simulation analysis,which validated the optimized control strategy’s ability to evenly distribute power under load *** strategy effectively mitigated transient voltage and current surges during mode ***,seamless and efficient switching between gridconnected and island modes was achieved for the photovoltaic storage hybrid *** enhanced energy utilization efficiency,in turn,offers robust technical support for grid stability.

关键词： Photovoltaic storage hybrid inverters modified chimpanzee optimization algorithm droop control seamless switching

A Generative Model-Based Network Framework for Ecological Data Reconstruction

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Computers, Materials & Continua 2025年第1期82卷 929-948页

作者： Shuqiao Liu Zhao zhang Hongyan zhou Xuebo Chen School of Electronic and Information Engineering University of Science and Technology LiaoningAnshan114051China School of Computer Science and Software Engineering University of Science and Technology LiaoningAnshan114051China

This study examines the effectiveness of artificial intelligence techniques in generating high-quality environmental data for species introductory site selection *** Strengths,Weaknesses,Opportunities,Threats(SWOT)analysis data with Variation Autoencoder(VAE)and Generative AdversarialNetwork(GAN)the network framework model(SAE-GAN),is proposed for environmental data *** model combines two popular generative models,GAN and VAE,to generate features conditional on categorical data embedding after SWOT *** model is capable of generating features that resemble real feature distributions and adding sample factors to more accurately track individual sample *** data is used to retain more semantic information to generate *** model was applied to species in Southern California,USA,citing SWOT analysis data to train the *** show that the model is capable of integrating data from more comprehensive analyses than traditional methods and generating high-quality reconstructed data from them,effectively solving the problem of insufficient data collection in development *** model is further validated by the Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS)classification assessment commonly used in the environmental data *** study provides a reliable and rich source of training data for species introduction site selection systems and makes a significant contribution to ecological and sustainable development.

关键词： Convolutional Neural Network(CNN) VAE GAN TOPSIS data reconstruction

Viscosity and structure relationship with equimolar substitution of CaO with MgO in the CaO–MgO–Al_(2)O_(3)–SiO_(2)slag melts

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International Journal of Minerals,Metallurgy and Materials 2025年第1期32卷 70-79页

作者： Yong Hou Shuo zhang Jie Dang Jia Guo Hanghang zhou Xuewei Lü College of Materials Science and Engineering Chongqing UniversityChongqing 400044China Chongqing Key Laboratory of Vanadium-Titanium Metallurgy and New Materials Chongqing UniversityChongqing 400044China

Currently,the Al_(2)O_(3)content in the high-alumina slag systems within blast furnaces is generally limited to 16wt%–18.5wt%,making it challenging to overcome this *** most studies that concentrated on managing the MgO/Al_(2)O_(3)ratio or basicity,this paper explored the effect of equimolar substitution of MgO for CaO on the viscosity and structure of a high-alumina CaO-MgO-Al_(2)O_(3)-SiO_(2)slag system,providing theoretical guidance and data to facilitate the application of high-alumina *** results revealed that the viscosity first decreased and then increased with higher MgO substitution,reaching a minimum at 15mol%MgO *** transform infrared spectroscopy(FTIR)results found that the depths of the troughs representing[SiO_(4)]tetrahedra,[AlO_(4)]tetrahedra,and Si-O-Al bending became progressively deeper with increased MgO *** of the Raman spectra showed that the average number of bridging oxygens per Si atom and the X_(Q^(3))/X_(Q^(2))(X_(Q^(i))is the molar fraction of Q^(i) unit,and i is the number of bridging oxygens in a[SiO_(4)]tetrahedral unit)ratio increased from 2.30 and 1.02 to 2.52 and 2.14,respectively,indicating a progressive polymerization of the silicate structure.X-ray photoelectron spectroscopy(XPS)results highlighted that non-bridging oxygen content decreased from 77.97mol% to 63.41mol% with increasing MgO concentration,whereas bridging oxygen and free oxygen contents *** analysis demonstrated a gradual increase in the polymerization degree of the tetrahedral structure with the increase in MgO ***,bond strength is another important factor affecting the slag *** occurrence of a viscosity minimum can be attributed to the complex evolution of bond strengths of non-bridging oxygens generated during depolymerization of the[SiO_(4)]and[AlO_(4)]tetrahedral structures by CaO and MgO.

关键词： aluminosilicate viscosity structure spectroscopy

Text-Image Feature Fine-Grained Learning for Joint Multimodal Aspect-Based sentiment Analysis

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Computers, Materials & Continua 2025年第1期82卷 279-305页

作者： Tianzhi zhang Gang zhou Shuang zhang Shunhang Li Yepeng Sun Qiankun Pi Shuo Liu School of Data and Target Engineering Information Engineering UniversityZhengzhou450001China Information Engineering Department Liaoning Provincial College of CommunicationsShenyang110122China School of Computer and Artificial Intelligence Zhengzhou UniversityZhengzhou450000China

Joint Multimodal Aspect-based sentiment Analysis(JMASA)is a significant task in the research of multimodal fine-grained sentiment analysis,which combines two subtasks:Multimodal Aspect Term Extraction(MATE)and Multimodal Aspect-oriented sentiment Classification(MASC).Currently,most existing models for JMASA only perform text and image feature encoding from a basic level,but often neglect the in-depth analysis of unimodal intrinsic features,which may lead to the low accuracy of aspect term extraction and the poor ability of sentiment prediction due to the insufficient learning of intra-modal *** this problem,we propose a Text-Image Feature Fine-grained Learning(TIFFL)model for ***,we construct an enhanced adjacency matrix of word dependencies and adopt graph convolutional network to learn the syntactic structure features for text,which addresses the context interference problem of identifying different aspect ***,the adjective-noun pairs extracted from image are introduced to enable the semantic representation of visual features more intuitive,which addresses the ambiguous semantic extraction problem during image feature ***,the model performance of aspect term extraction and sentiment polarity prediction can be further optimized and *** on two Twitter benchmark datasets demonstrate that TIFFL achieves competitive results for JMASA,MATE and MASC,thus validating the effectiveness of our proposed methods.

关键词： Multimodal sentiment analysis aspect-based sentiment analysis feature fine-grained learning graph convolutional network adjective-noun pairs

Defects‑Rich Heterostructures Trigger Strong Polarization Coupling in Sulfides/Carbon Composites with Robust Electromagnetic Wave Absorption

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Nano-Micro Letters 2025年第1期17卷 528-547页

作者： Jiaolong Liu Siyu zhang Dan Qu Xuejiao zhou Moxuan Yin Chenxuan Wang Xuelin zhang Sichen Li Peijun zhang Yuqi zhou Kai Tao Mengyang Li Bing Wei Hongjing Wu Mengyang Li Bing Wei Hongjing Wu School of Physics Xidian UniversityXi’an 710071People’s Republic of China School of Advanced Materials and Nanotechnology State Key Discipline Laboratory of Wide Band Gap Semiconductor TechnologyXidian UniversityXi’an 710071People’s Republic of China School of Microelectronics Xidian UniversityXi’an 710071People’s Republic of China School of Telecommunication Engineering Xidian UniversityXi’an 710071People’s Republic of China MOE Key Laboratory of Material Physics and Chemistry Under Extraordinary School of Physical Science and TechnologyNorthwestern Polytechnical UniversityXi’an 710072People’s Republic of China The Ministry of Education Key Laboratory of Micro and Nano Systems forAerospace School of Mechanical EngineeringNorthwestern PolytechnicalUniversityXi’an 710072People’s Republic of China

Defects-rich heterointerfaces integrated with adjustable crystalline phases and atom vacancies,as well as veiled dielectric-responsive character,are instrumental in electromagnetic *** methods,however,constrain their delicate ***,an innovative alternative is proposed:carrageenan-assistant cations-regulated(CACR)strategy,which induces a series of sulfides nanoparticles rooted in situ on the surface of carbon *** unique configuration originates from strategic vacancy formation energy of sulfides and strong sulfides-carbon support interaction,benefiting the delicate construction of defects-rich heterostructures in M_(x)S_(y)/carbon composites(M-CAs).Impressively,these generated sulfur vacancies are firstly found to strengthen electron accumulation/consumption ability at heterointerfaces and,simultaneously,induct local asymmetry of electronic structure to evoke large dipole moment,ultimately leading to polarization coupling,i.e.,defect-type interfacial ***“Janus effect”(Janus effect means versatility,as in the Greek two-headed Janus)of interfacial sulfur vacancies is intuitively confirmed by both theoretical and experimental investigations for the first ***,the sulfur vacancies-rich heterostructured Co/Ni-CAs displays broad absorption bandwidth of 6.76 GHz at only 1.8 mm,compared to sulfur vacancies-free CAs without any dielectric *** defects-rich heterostructures,this one-pot CACR strategy may steer the design and development of advanced nanomaterials,boosting functionality across diverse application domains beyond electromagnetic response.

关键词： Defects-rich heterointerfaces Sulfides Polarization coupling Electromagnetic wave absorption

Integration of Electrical Properties and Polarization Loss Modulation on Atomic Fe–N‑RGO for Boosting Electromagnetic Wave Absorption

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Nano-Micro Letters 2025年第2期17卷 517-532页

作者： Kaili zhang Yuefeng Yan Zhen Wang Guansheng Ma Dechang Jia Xiaoxiao Huang Yu zhou State Key Laboratory of Precision Welding&Joining of Materials and Structures Harbin Institute of TechnologyHarbin 150001People’s Republic of China School of Materials Science and Engineering Harbin Institute of TechnologyHarbin 150001People’s Republic of China MIIT Key Laboratory of Advanced Structural‑Functional Integration Materials&Green Manufacturing Technology Harbin Institute of TechnologyHarbin 150001People’s Republic of China

Developing effective strategies to regulate graphene’s conduction loss and polarization has become a key to expanding its application in the electromagnetic wave absorption(EMWA)*** on the unique energy band structure of graphene,regulating its bandgap and electrical properties by introducing heteroatoms is considered a feasible ***,metal-nitrogen doping reduced graphene oxide(M–N-RGO)was prepared by embedding a series of single metal atoms M–N_(4) sites(M=Mn,Fe,Co,Ni,Cu,Zn,Nb,Cd,and Sn)in RGO using an N-coordination atom-assisted *** composites had adjustable conductivity and polarization to optimize dielectric loss and impedance matching for efficient EMWA *** results showed that the minimum reflection loss(RL_(min))of Fe–N-RGO reaches−74.05 dB(2.0 mm)and the maximum effective absorption bandwidth(EAB_(max))is 7.05 GHz(1.89 mm)even with a low filler loading of only 1 wt%.Combined with X-ray absorption spectra(XAFS),atomic force microscopy,and density functional theory calculation analysis,the Fe–N_(4) can be used as the polarization center to increase dipole polarization,interface polarization and defect-induced polarization due to d-p orbital hybridization and structural ***,electron migration within the Fe further leads to conduction loss,thereby synergistically promoting energy *** study demonstrates the effectiveness of metal-nitrogen doping in regulating the graphene′s dielectric properties,which provides an important basis for further investigation of the loss mechanism.

关键词： Electromagnetic wave absorption Fe-N-RGO Dipole polarization Conduction loss Impedance matching

The emerging role of nitric oxide in the synaptic dysfunction of vascular dementia

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Neural Regeneration Research 2025年第2期20卷 402-415页

作者： Xiaorong zhang Zhiying Chen Yinyi Xiong Qin zhou Ling-Qiang Zhu Dan Liu Department of Pathology Affiliated Hospital of Jiujiang UniversityJiujiangJiangxi ProvinceChina Jiujiang Clinical Precision Medicine Research Center JiujiangJiangxi ProvinceChina Center for Cognitive Science and Transdisciplinary Studies Jiujiang UniversityJiangxi ProvinceChina Department of Neurology Affiliated Hospital of Jiujiang UniversityJiujiangJiangxi ProvinceChina Department of Rehabilitation Affiliated Hospital of Jiujiang UniversityJiujiangJiangxi ProvinceChina Department of Pathophysiology School of Basic MedicineTongji Medical CollegeHuazhong University of Science and TechnologyWuhanHubei ProvinceChina

With an increase in global aging,the number of people affected by cerebrovascular diseases is also increasing,and the incidence of vascular dementia-closely related to cerebrovascular risk-is increasing at an epidemic ***,few therapeutic options exist that can markedly improve the cognitive impairment and prognosis of vascular dementia *** in Alzheimer’s disease and other neurological disorders,synaptic dysfunction is recognized as the main reason for cognitive *** oxide is one of the ubiquitous gaseous cellular messengers involved in multiple physiological and pathological processes of the central nervous ***,nitric oxide has been implicated in regulating synaptic plasticity and plays an important role in the pathogenesis of vascular *** review introduces in detail the emerging role of nitric oxide in physiological and pathological states of vascular dementia and summarizes the diverse effects of nitric oxide on different aspects of synaptic dysfunction,neuroinflammation,oxidative stress,and blood-brain barrier dysfunction that underlie the progress of vascular ***,we propose that targeting the nitric oxide-sGC-cGMP pathway using certain specific approaches may provide a novel therapeutic strategy for vascular dementia.

关键词： endoplasmic reticulum stress endothelial nitric oxide synthase gene therapy nitric oxide NO-sGC-cGMP pathway synaptic dysfunction vascular dementia

Ketogenic diet and cancer:multidimensional exploration and research

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Science China Life Sciences 2025年

作者： Shiyun Wan Xiaoxue zhou Feng Xie Fangfang zhou Long zhang The First Affiliated Hospital the Institutes of Biology and Medical Sciences Suzhou Medical College Soochow University School of Medicine Hangzhou City University Life Sciences Institute and State Key Laboratory of Transvascular Implantation Devices of the Second Affiliated Hospital of Zhejiang University School of Medicine Zhejiang University The MOE Basic Research and Innovation Center for the Targeted Therapeutics of Solid Tumors The First Affiliated Hospital Jiangxi Medical College Nanchang University Cancer Center Zhejiang University

The ketogenic diet(KD) has attracted attention in recent years for its potential anticancer effects. KD is a dietary structure of high fat,moderate protein, and extremely low carbohydrate content. Originally introduced as a treatment for epilepsy, KD has been widely applied in weight loss programs and the management of metabolic diseases. Previous studies have shown that KD can potentially inhibit the growth and spread of cancer by limiting energy supply to tumor cells, thereby inhibiting tumor angiogenesis, reducing oxidative stress in normal cells, and affecting cancer cell signaling and other processes. Moreover, KD has been shown to influence T-cell-mediated immune responses and inflammation by modulating the gut microbiota, enhance the efficacy of standard cancer treatments, and mitigate the complications of chemotherapy. However, controversies and uncertainties remain regarding the specific mechanisms and clinical effects of KD as an adjunctive therapy for cancer. Therefore, this review summarizes the existing research and explores the intricate relationships between KD and cancer treatment.

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