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Energy & Environmental Materials 2024年第2期7卷 200-208页

作者： Jiale ke xing zhao Jie Yang Kai ke Yu Wang Mingbo Yang Wei Yang College of Polymer Science and Engineering Sichuan UniversityState Key Laboratory of Polymer Materials EngineeringChengdu 610065China

Thermoelectric(TE)generators capable of converting thermal energy into applicable electricity have gained great popularity among emerging energy conversion ***-based ionic thermoelectric(i-TE)materials are promising candidates for energy conversion systems because of their wide sources,innocuity,and low manufacturing ***,common physically crosslinked biopolymer gels induced by single hydrogen bonding or hydrophobic interaction suffer from low differential thermal voltage and poor thermodynamic ***,we develop a novel i-TE gel with supramolecular structures through multiple noncovalent interactions between ionic liquids(ILs)and gelatin molecular *** thermopower and thermoelectric power factor of the ionic gels are as high as 2.83 mV K-1 and 18.33μW m^(-1)K^(-2),*** quasi-solid-state gelatin-[EMIM]DCA i-TE cells achieve ultrahigh 2 h output energy density(E_(2h)=9.9 mJ m^(-2))under an optimal temperature ***,the remarkable stability of the supramolecular structure provides the i-TE hydrogels with a thermal stability of up to 80℃.It breaks the limitation that biopolymer-based i-TE gels can only be applied in the low temperature range and enables biopolymer-based i-TE materials to pursue better performance in a higher temperature range.

关键词： biopolymer gel ionic liquid multiple noncovalent interactions supramolecular structure thermoelectric conversion

Intracellular RNA Labeling Technologies for the Analysis of RNA Biology

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Chinese Journal of Chemistry 2024年第7期42卷 790-801页

作者： Ruiqi zhao xin Fang Xiaocheng Weng Department of Clinical Laboratory Center for Gene DiagnosisDepartment of NeurosurgeryZhongnan Hospital of Wuhan UniversityWuhanHubei 430071China College of Chemistryand Molecular Sciences Key Laboratory of Biomedical Polymers-Ministry of EducationWuhan UniversityWuhan Hubei 430072China

As a cornerstone of the central dogma of molecular biology,RNA plays vital roles in living *** the past few decades,many RNA labeling technologies have been developed to elucidate the biological function of *** technologies have signifi-cantly advanced our understanding of RNA secondary structure,localization,and ***,taking advantage of these innovative RNA labeling approaches,plenty of tool kits have been devised for the regulation of RNA-related biological process,such as gene expression and gene *** this review,we primarily focus on an array of intracellular RNA labeling methods,encom-passing chemical probes-based labeling,metabolic labeling,and proximity-dependent *** also provide a brief overview of their applications in the research of RNA ***,the perspectives of RNA labeling are also discussed.

关键词： RNA Chemical probes Metabolic labeling Proximity-dependent labeling RNA structures Gene sequencing RNA recognition

Probabilistic seismic inversion based on physics-guided deep mixture density network

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Petroleum Science 2024年第3期21卷 1611-1631页

作者： Qian-Hao Sun zhao-Yun Zong xin Li National key Laboratory of Deep Oil and Gas China University of Petroleum(East China)Qingdao266580ShandongChina Laoshan Laboratory Qingdao266580ShandongChina CNOOC Research Institute Ltd. Beijing100028China

Deterministic inversion based on deep learning has been widely utilized in model parameters *** by logging data,seismic data,wavelet and modeling operator,deterministic inversion based on deep learning can establish nonlinear relationships between seismic data and model ***,seismic data lacks low-frequency and contains noise,which increases the non-uniqueness of the *** conventional inversion method based on deep learning can only establish the deterministic relationship between seismic data and parameters,and cannot quantify the uncertainty of *** order to quickly quantify the uncertainty,a physics-guided deep mixture density network(PG-DMDN)is established by combining the mixture density network(MDN)with the deep neural network(DNN).Compared with Bayesian neural network(BNN)and network dropout,PG-DMDN has lower computing cost and shorter training time.A low-frequency model is introduced in the training process of the network to help the network learn the nonlinear relationship between narrowband seismic data and low-frequency *** addition,the block constraints are added to the PG-DMDN framework to improve the horizontal continuity of the inversion *** illustrate the benefits of proposed method,the PG-DMDN is compared with existing semi-supervised inversion *** synthetic data examples of Marmousi II model are utilized to quantify the influence of forward modeling part,low-frequency model,noise and the pseudo-wells number on inversion results,and prove the feasibility and stability of the proposed *** addition,the robustness and generality of the proposed method are verified by the field seismic data.

关键词： Deep learning Probabilistic inversion Physics-guided Deep mixture density network

Polyp-Canal Reconstruction Reveals Evolution Toward Complexity in Corals

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Research 2024年第1期2023卷 417-428页

作者： Yixin Li xin Liao xin Wang Yuanchao Li Hongwei zhao Yunpeng zhao Junyuan Chen Chunpeng He Zuhong Lu State key Laboratory of Bioelectronics School of Biological Science and Medical EngineeringSoutheast UniversityNanjing 210096China State key Laboratory of Coastal and Offshore Engineering Dalian University of TechnologyDalian 116024China Guangxi key Lab of Mangrove Conservation and Utilization Guangxi Mangrove Research CenterGuangxi Academy of SciencesBeihai 536000China Hainan Academy of Ocean and Fishery Sciences Haikou 571126China State key Laboratory of Marine Resources Utilization in South China Sea Hainan UniversityHaikou 570228China Nanjing Institute of Geology and Palaeontology Chinese Academy of Sciences39 East Beijing RoadNanjing 210008China

Modern scleractinian corals are classified into robust,complex,and basal clades through comparative molecular ***,only few morphological or biological criteria can systematically determine the evolutionary trajectories of these major scleractinian coral ***,we obtained the structural information of 21 scleractinian coral species representing robust and complex clades:High-resolution micro-computed tomography was used to reconstruct the polyp-canal systems in their colonies and to visualize the dynamic polyp growth *** found that the emergence of mesh-like canals may distinguish representatives of complex and robust *** differences in polyp-canal connections suggest distinct evolutionary trajectories among coral species:The formation of the canal network promoted the development of more complex coral structures,and coral polyps within this network formed calices of very similar volume,following precise axial growth *** influence of individual polyps on the coral colony becomes less significant as coral structures become more complex,and coral species with more complicated polyp-canal systems occupied niches more *** work supplements current evolutionary studies on reef-building corals,providing insight for further studies on coral growth patterns.

关键词： Coral representing directions

Adaptive 5G-and-beyond network-enabled interpretable federated learning enhanced by neuroevolution

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Science China(Information Sciences) 2024年第7期67卷 107-132页

作者： Bin CAO Jianwei zhao xin LIU Yun LI State key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology School of Artificial Intelligence Hebei University of Technology School of Economics and Management Hebei University of Technology Industrial Artificial Intelligence Centre Shenzhen Institute for Advanced StudyUniversity of Electronic Science and Technology of China

Mobile telemedicine systems based on the next-generation communication will significantly enhance deep fusion of network automation and federated learning(FL), but data privacy is a paramount issue in sectors like healthcare. This work hence considers FL augments 5G-and-beyond networks by training deep learning(DL) models without the need to exchange raw data. The substantial communication loads imposed on by extensive parameters involved in DL models are managed through adaptive scheduling mechanisms effectively. To address the opaque nature of DL models and to improve the interpretability of FL models, we introduce a convolutional fuzzy rough neural network specifically designed for medical image processing. We also develop a multiobjective memetic evolutionary algorithm to streamline and optimize the neural network architectures. Our comprehensive FL framework integrates smart scheduling, interpretable fuzzy rough logic,and neuroevolution. This framework is shown to improve communication efficiency, increase interpretability of diagnosis with protected privacy, and generate low-complexity neural architectures.

关键词： 5G-and-beyond network interpretable federated learning mobile telemedicine system fuzzy rough set theory neuroevolution

Smart Contract Vulnerability Detection Method Based on Feature Graph and Multiple Attention Mechanisms

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Computers, Materials & Continua 2024年第5期79卷 3023-3045页

作者： Zhenxiang He Zhenyu zhao ke Chen Yanlin Liu School of Cyber Security Gansu University of Political Science and LawLanzhou730070China

The fast-paced development of blockchain technology is ***,the security concerns of smart contracts represent a significant challenge to the stability and dependability of the entire blockchain *** smart contract vulnerability detection primarily relies on static analysis tools,which are less efficient and *** deep learning methods have improved detection efficiency,they are unable to fully utilize the static relationships within ***,we have adopted the advantages of the above two methods,combining feature extraction mode of tools with deep learning ***,we have constructed corresponding feature extraction mode for different vulnerabilities,which are used to extract feature graphs from the source code of smart ***,the node features in feature graphs are fed into a graph convolutional neural network for training,and the edge features are processed using a method that combines attentionmechanismwith gated ***,the revised node features and edge features are concatenated through amulti-head *** result of the splicing is a global representation of the entire feature *** method was tested on three types of data:Timestamp vulnerabilities,reentrancy vulnerabilities,and access control vulnerabilities,where the F1 score of our method reaches 84.63%,92.55%,and 61.36%.The results indicate that our method surpasses most others in detecting smart contract vulnerabilities.

关键词： Blockchain smart contracts deep learning graph neural networks

Adaptable "bubble particles" prepared by green aqueous phase reshaping for completely removing odor

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Nano Research 2024年第3期17卷 2172-2180页

作者： Jiajia Ma Yichang Xia Tienan zhao Wenfeng Hu Weifeng Zhang Qinfei ke Yi zhao Shanghai Frontiers Science Center of Advanced Textiles Donghua UniversityShanghai 201620China Engineering Research Center of Technical Textiles Ministry of EducationDonghua UniversityShanghai 201620China School of Fashion Engineering Central Laboratory Shanghai University of Engineering ScienceShanghai 201620China Department of Materials Science and Engineering National University of SingaporeSingapore 117575Singapore School of Perfume and Aroma Technology Shanghai Institute of TechnologyShanghai 201418China

Facile and ecofriendly loading of micro/nano function-specific substances to create functional materials is a trend being pursued by ***,current micro/nano particles loading approaches are often hindered by issues such as uneven distribution,unsatisfactory stability and complicate *** this work,we present an aqueous phase reshaping method that only utilizes the moisture to fabricate the"bubble particles",which could perfectly cater to the topography of the *** green preparation of bubble particles adopts an absolutely zero-pollution method,realizing the firm loading of particles on the *** the preparation and loading of particles overcomes the traditional complicate process,while the aqueous phase reshaping ensures uniform and firm loading of the"bubble particles"onto the *** mechanism demonstrates a significant enhancement in the interface relation after aqueous phase reshaping,with a 121-fold increase in contact surface area achieved by reducing the height by 1μ***,we explore for the first time the influence of the nature of the receiving substrate on the interface morphology of particles during electrostatic spraying,which has important guiding significance for the interface relationship of electrostatic spraying and even electrostatic spinning *** also screen out the natural antibacterial essential oil linalool as the effective specialized antibacterial agent,which can specifically inhibit the odor-producing Proteus in urine,with an antibacterial rate of up to 100%.Taken together,this simple,ecofriendly method for fabricating functional materials with optimal interface stability appears highly promising for use in various products formed by electrostatic spraying/spinning.

关键词： bubble particle electrostatic spraying aqueous phase reshaping interface bonding remove odor nano spraying

Threshold Selection and Resource Allocation for Quantized Identification

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Journal of Systems Science & Complexity 2024年第1期37卷 204-229页

作者： WANG Ying LI xin zhao Yanlong ZHANG Ji-Feng key Laboratory of Systems and Control Institute of Systems ScienceAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049China

This paper is concerned with the optimal threshold selection and resource allocation problems of quantized identification, whose aims are improving identification efficiency under limited resources. Firstly, the first-order asymptotically optimal quantized identification theory is extended to the weak persistent excitation condition. Secondly, the characteristics of time and space complexities are established based on the Cramér-Rao lower bound of quantized systems. On these basis, the optimal selection methods of fixed thresholds and adaptive thresholds are established under aperiodic signals, which answer how to achieve the best efficiency of quantized identification under the same time and space complexity. In addition, based on the principle of maximizing the identification efficiency under a given resource, the optimal resource allocation methods of quantized identification are given for the cases of fixed thresholds and adaptive thresholds, respectively, which show how to balance time and space complexity to realize the best identification efficiency of quantized identification.

关键词： Quantized output resource allocation system identification threshold selection.

Biochar with self-doped N to activate peroxymonosulfate for bisphenol-A degradation via electron transfer mechanism:The active edge graphitic N site

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Chinese Chemical Letters 2024年第9期35卷 351-355页

作者： Yun-xin Huang Lin-Qian Yu ke-Yu Chen Hao Wang Shou-Yan zhao Bao-Cheng Huang Ren-Cun Jin School of Engineering Hangzhou Normal UniversityHangzhou 311121China Zhejiang Provincial key Laboratory of Urban Wetlands and Regional Change Hangzhou 311121China

Environmental endocrine disruptors,represented by bisphenol A(BPA),have been widely detected in the environment,bringing potential health risks to human ***-containing biocarbon catalyst can activate peroxymonosulfate(PMS)to degrade BPA in water,but its active sites remain ***,in this work,nitrogen-containing biochar,i.e.,C–Nedge,enriched with graphitic-N defects at the edges was prepared by one-pot co-pyrolysis of chitosan and potassium *** results showed that the C–Nedge/PMS system can effectively degrade 98%of BPA(50 mg/L).The electron transfer based non-radical oxidation mechanism was responsible for BPA *** graphitic-N doping endows biochar with strong electron transfer *** catalyst had good recovery and reuse *** catalytic oxidation was also feasible for other refractory pollutants removal and worked well for treating practical *** work may provide valuable information in unraveling the N doping configurationactivity relationship during activating PMS by biochar.

关键词： Peroxymonosulfate Carbon-based catalysts Edge graphitic-N Non-radicals Bisphenol A

Health diagnosis of ultrahigh arch dam performance using heterogeneous spatial panel vector model

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Water Science and Engineering 2024年第2期17卷 177-186页

作者： Er-feng zhao xin Li Chong-shi Gu The National key Laboratory of Water Disaster Prevention Hohai UniversityNanjing 210098China NationalEngineering Research Centerof Water Resources Eficient Utilization and Engineering Safety Hohai UniversityNanjing 20098China

Currently,more than ten ultrahigh arch dams have been constructed or are being constructed in *** control is essential to long-term operation of these *** study employed the flexibility coefficient and plastic complementary energy norm to assess the structural safety of arch dams.A comprehensive analysis was conducted,focusing on differences among conventional methods in characterizing the structural behavior of the Xiaowan arch dam in ***,the spatiotemporal characteristics of the measured performance of the Xiaowan dam were explored,including periodicity,convergence,and time-effect *** findings revealed the governing mechanism of main ***,a heterogeneous spatial panel vector model was developed,considering both common factors and specific factors affecting the safety and performance of arch *** model aims to comprehensively illustrate spatial heterogeneity between the entire structure and local regions,introducing a specific effect quantity to characterize local deformation ***,the proposed model was applied to the Xiaowan arch dam,accurately quantifying the spatiotemporal heterogeneity of dam ***,the spatiotemporal distri-bution characteristics of environmental load effects on different parts of the dam were reasonably *** of the model prediction enhances its credibility,leading to the formulation of health diagnosis criteria for future long-term operation of the Xiaowan *** findings not only enhance the predictive ability and timely control of ultrahigh arch dams'performance but also provide a crucial basis for assessing the effectiveness of engineering treatment measures.

关键词： Ultrahigh arch dam Structural performance Deformation behavior Diagnosis criterion Panel data model