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CFD simulation of pumping ventilation in a three-story isolated building with internal partitioning:Effects of partition widths,heights and locations

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Building Simulation 2024年第2期17卷 267-284页

作者： Huai-Yu Zhong Jie Sun Chao Lin Song-Heng Wu Jin Shang Hideki Kikumoto fu-Ping Qian Carlos Jimenez-Bescos fu-yun zhao School of Energy and Environment Anhui University of TechnologyMa-An-ShanAnhui Province243002China State Key Laboratory of Green Building in Western China Xi’an University of Architecture&TechnologyXi’anShaanxi ProvinceChina School of Power and Mechanical Engineering Wuhan UniversityWuhanHubei Province430072China Institute of Industrial Science The University of Tokyo4-6-1 KomabaMeguro-kuTokyo153-8505Japan School of Built and Natural Environment University of DerbyDerbyUK

Pumping ventilation(PV),a special single-sided ventilation(SSV),has been certified as an effective strategy to improve the air exchange rate of ***,most studies targeted on the single space,and few studies have been focused on the effect of internal partitioning on *** paper aims to evaluate the ventilation performance of PV influenced by different configurations of internal *** fluid dynamics(CFD)simulation was used to predict the flow fields and ventilation *** width(w/H),height(h/H)and location(d/H)are the three main internal partition parameters considered in this *** simulation results showed that the total,mean and fluctuating ventilation rates all decrease with wider internal *** normalized total ventilation rate decreases by 7.6%when w/H is increased from 50%to 75%.However,the reduction rate is only 0.23%between w/H=0 and 25%,and only 0.61%between w/H=25%and 50%.The ventilation rate is hardly reduced by increasing the partition width when w/H50%.Increasing the partition height will reduce the mean ventilation rate but promote the fluctuating and total ventilation rate in some *** increase of total ventilation rate by 1.4%is observed from h/H=50%to 75%.The ventilation rate is larger when the internal partition is attached to the leeward or windward *** total,mean and fluctuating ventilation rates for d/H=50%are relatively higher than d/H=0 by 1.5%,3.1%and 0.8%,*** the internal partition should be mounted attached to the windward wall so as to obtain the greatest pumping ventilation *** periodicity of pumping flow oscillation and pumping frequency are independent of the partition *** peak power of pumping flow is the lowest for the widest internal partition and is negatively affected by the partition height,but it generally has a positive correlation with the distance between the partition and leeward wa

关键词： pumping ventilation single-sided ventilation internal partitioning periodic oscillation ventilation rate

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Development of SV2A Ligands for Epilepsy Treatment:A Review of Levetiracetam,Brivaracetam,and Padsevonil

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Neuroscience Bulletin 2024年第5期40卷 594-608页

作者： Peng-Peng Wu Bi-Rong Cao fu-yun Tian zhao-Bing Gao Center for Neurological and Psychiatric Research and Drug Discovery Shanghai Institute of Materia MedicaChinese Academy of SciencesShanghai201203China University of Chinese Academy of Sciences Beijing100049China Zhongshan Institute for Drug Discovery Shanghai Institute of Materia MedicaChinese Academy of SciencesZhongshan528400China

Epilepsy is a common neurological disorder that is primarily treated with antiseizure medications(ASMs).Although dozens of ASMs are available in the clinic,approximately 30%of epileptic patients have medically refractory seizures;other limitations in most traditional ASMs include poor tolerability and drug-drug ***,there is an urgent need to develop alternative ***(LEV)is a first-line ASM that is well tolerated,has promising efficacy,and has little drug-drug *** it is widely accepted that LEV acts through a unique therapeutic target synaptic vesicle protein(SV)2A,the molecular basis of its action remains *** so,the next-generation SV2A ligands against epilepsy based on the structure of LEV have achieved clinical *** review highlights the research and development(R&D)process of LEV and its analogs,brivaracetam and padsevonil,to provide ideas and experience for the R&D of novel ASMs.

关键词： Levetiracetam Epilepsy Antiseizure medications Synaptic vesicle protein 2A Brivaracetam Padsevonil

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A stochastic gradient-based two-step sparse identification algorithm for multivariate ARX systems

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Control Theory and Technology 2024年第2期22卷 213-221页

作者： Yanxin fu Wenxiao zhao Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing100049China

We consider the sparse identification of multivariate ARX systems, i.e., to recover the zero elements of the unknown parameter matrix. We propose a two-step algorithm, where in the first step the stochastic gradient (SG) algorithm is applied to obtain initial estimates of the unknown parameter matrix and in the second step an optimization criterion is introduced for the sparse identification of multivariate ARX systems. Under mild conditions, we prove that by minimizing the criterion function, the zero elements of the unknown parameter matrix can be recovered with a finite number of observations. The performance of the algorithm is testified through a simulation example.

关键词： ARX system Stochastic gradient algorithm Sparse identification Support recovery Parameter estimation Strong consistency

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Call for knowledge systematization:An example from lithium ion batteries recycling

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Journal of Energy Chemistry 2024年第7期94卷 169-170页

作者： yun zhao Baohua Li Institute of Materials Research Tsinghua Shenzhen International Graduate SchoolTsinghua UniversityShenzhen 518055GuangdongChina

Scientific research is one of the primary ways to drive human civilization *** research institutions and researchers worldwide are dedicated to exploring the unknown,resulting in a flood of research findings[1].For instance,Web of Science alone collects over 10,000 academic papers on a daily *** each research field typically has around 10%of review articles,these mainly focus on a limited portion of the subject,failing to provide a comprehensive and real-time updated *** a result,researchers or students in a particular field may spend several months,or even longer,comprehending the state of research that has developed over just a few *** lack of systematic background often leads to redundant or similar studies,which is highly detrimental to the progress of science and technology.

关键词： lithium typically spend

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Biomarkers in aortic dissection:Diagnostic and prognostic value from clinical research

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Chinese Medical Journal 2024年第3期137卷 257-269页

作者： Yufei zhao Weiguo fu Lixin Wang Department of Vascular Surgery Zhongshan HospitalFudan UniversityShanghai 200032China Vascular Surgery Institute Zhongshan HospitalFudan UniversityShanghai 200032China National Clinical Research Center for Interventional Medicine Zhongshan HospitalFudan UniversityShanghai 200032China Department of Vascular Surgery Xiamen BranchZhongshan HospitalFudan UniversityXiamenFujian 361015China

Aortic dissection is a life-threatening condition for which diagnosis mainly relies on imaging examinations,while reliable biomarkers to detect or monitor are still under *** advances in technologies provide an unprecedented opportunity to yield the identification of clinically valuable biomarkers,including proteins,ribonucleic acids(RNAs),and deoxyribonucleic acids(DNAs),for early detection of pathological changes in susceptible patients,rapid diagnosis at the bedside after onset,and a superior therapeutic regimen primarily within the concept of personalized and tailored endovascular therapy for aortic dissection.

关键词： Aortic dissection Biomarker Protein Cell-free DNA miRNA Inflammation Lipid-metabolism

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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) Laoshan Laboratory CNOOC Research Institute Ltd.

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 solutions. 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 inversion. In 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 impedance. In addition, the block constraints are added to the PG-DMDN framework to improve the horizontal continuity of the inversion results. To illustrate the benefits of proposed method, the PG-DMDN is compared with existing semi-supervised inversion method. Four 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 method. In 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

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Mangrove wetlands distribution status identification, changing trend analyzation and carbon storage assessment of China

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China Geology 2024年第1期7卷 1-11页

作者： Chang Li fu Wang Peng Yang Fei-cui Wang yun-zhuang Hu Yan-lin zhao Li-zhu Tian Rui-bin zhao Tianjin Center(North China Center of Geoscience Innovation) China Geological Survey(CGS)Tianjin 300170China Tangshan Hydrological Survey and Research Center of Heibei Province Tangshan063000China Key Laboratory of Coast Geo-Environment China Geological SurveyCGSTianjin 300170China Tianjin Key Laboratory of Coast Geological Processes and Environmental Safety Tianjin 300170China

This research investigates the ecological importance,changes,and status of mangrove wetlands along China’s *** interpretation,geological surveys,and ISO clustering unsupervised classification methods are employed to interpret mangrove distribution from remote sensing images from 2021,utilizing ArcGIS software ***,the carbon storage capacity of mangrove wetlands is quantified using the carbon storage module of InVEST *** show that the mangrove wetlands in China covered an area of 278.85 km2 in 2021,predominantly distributed in Hainan,Guangxi,Guangdong,fujian,Zhejiang,Taiwan,Hong Kong,and *** total carbon storage is assessed at 2.11×10^(6) t,with specific regional data *** since the 1950s reveal periods of increase,decrease,sharp decrease,and slight-steady increases in mangrove areas in *** important finding is the predominant replacement of natural coastlines adjacent to mangrove wetlands by artificial ones,highlighting the need for creating suitable spaces for mangrove *** study is poised to guide future mangroverelated investigations and conservation strategies.

关键词： Mangrove Wetland Carbon storage Ecological conservation ArcGIS software platform Restoration InVEST model Quantitative analysis Coastal zone of China

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Echo State Network Based on Improved Knowledge Distillation for Edge Intelligence

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Chinese Journal of Electronics 2024年第1期33卷 101-111页

作者： Jian ZHOU Yuwen JIANG Lijie XU Lu zhao fu XIAO College of Computer Nanjing University of Posts and Telecommunications Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks

Echo state network(ESN) as a novel artificial neural network has drawn much attention from time series prediction in edge intelligence. ESN is slightly insufficient in long-term memory, thereby impacting the prediction performance. It suffers from a higher computational overhead when deploying on edge devices. We firstly introduce the knowledge distillation into the reservoir structure optimization, and then propose the echo state network based on improved knowledge distillation(ESN-IKD) for edge intelligence to improve the prediction performance and reduce the computational overhead. The model of ESN-IKD is constructed with the classic ESN as a student network, the long and short-term memory network as a teacher network, and the ESN with double loop reservoir structure as an assistant network. The student network learns the long-term memory capability of the teacher network with the help of the assistant network. The training algorithm of ESN-IKD is proposed to correct the learning direction through the assistant network and eliminate the redundant knowledge through the iterative pruning. It can solve the problems of error learning and redundant learning in the traditional knowledge distillation process. Extensive experimental simulation shows that ESN-IKD has a good time series prediction performance in both long-term and short-term memory, and achieves a lower computational overhead.

关键词： Knowledge engineering Training Performance evaluation Computational modeling Time series analysis Artificial neural networks Reservoirs

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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

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Co_(3)O_(4)as an efficient passive NO_(x) adsorber for emission control during cold-start of diesel engines

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Chinese Journal of Chemical Engineering 2024年第2期66卷 1-7页

作者： Jinhuang Cai Shijie Hao yun Zhang Xiaomin Wu Zhenguo Li Huawang zhao Department of Environmental Science&Engineering College of Chemical EngineeringHuaqiao UniversityXiamen 361021China Wuxi Weifu Environmental Catalysts Co. LtdWuxi 214000China National Engineering Laboratory for Mobile Source Emission Control Technology China Automotive Technology&Research Center Co.Ltd.Tianjin 300300China

The Co_(3)O_(4)nanoparticles,dominated by a catalytically active(110)lattice plane,were synthesized as a low-temperature NO_(x) adsorbent to control the cold start emissions from *** nanoparticles boast a substantial quantity of active chemisorbed oxygen and lattice oxygen,which exhibited a NO_(x) uptake capacity commensurate with Pd/SSZ-13 at 100℃.The primary NO_(x) release temperature falls within a temperature range of 200-350℃,making it perfectly suitable for diesel *** characterization results demonstrate that chemisorbed oxygen facilitate nitro/nitrites intermediates formation,contributing to the NO_(x) storage at 100℃,while the nitrites begin to decompose within the 150-200℃***,lattice oxygen likely becomes involved in the activation of nitrites into more stable nitrate within this particular temperature *** concurrent processes of nitrites decomposition and its conversion to nitrates results in a minimal NO_(x) release between the temperatures of 150-200℃.The nitrate formed via lattice oxygen mainly induces the NO_(x) to be released as NO_(2) within a temperature range of 200-350℃,which is advantageous in enhancing the NO_(x) activity of downstream NH_(3)-SCR catalysts,by boosting the fast SCR reaction *** to its low cost,considerable NO_(x) absorption capacity,and optimal release temperature,Co_(3)O_(4)demonstrates potential as an effective material for passive NO_(x) adsorber applications.

关键词： Emission control Cold-start Low-temperature adsorption Co_(3)O_(4) Nitrate formation

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