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| 1 | Overview of SARS-CoV-2 genome-encoded proteins显示文摘Severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)has spread rapidly throughout the world.SARS-CoV-2 is an enveloped,plus-stranded RNA virus with a single-stranded RNA genome of approximately 30,000 nucleotides.The SARS-CoV-2 genome encodes 29 proteins,including 16 nonstructural,4 structural and 9 accessory proteins.To date,over 1,228 experimental structures of SARS-CoV-2 proteins have been deposited in the Protein Data Bank(PDB),including 16 protein structures,two functional domain structures of nucleocapsid(N)protein,and scores of complexes.Overall,they exhibit high similarity to SARS-CoV proteins.Here,we summarize the progress of structural and functional research on SARS-CoV-2 proteins.These studies provide structural and functional insights into proteins of SARS-CoV-2,and further elucidate the daedal relationship between different components at the atomic level in the viral life cycle,including attachment to the host cell,viral genome replication and transcription,genome packaging and assembly,and virus release.It is important to understand the structural and functional properties of SARS-CoV-2 proteins as it will facilitate the development of anti-CoV drugs and vaccines to prevent and control the current SARS-CoV-2 pandemic. | Chongzhi Bai Qiming Zhong George Fu Gao | 2022 | Science China(Life Sciences)2022，65，2： | 5 |
| 2 | Ductile and ultrahigh-strength eutectic high-entropy alloys by large-volume 3D printing显示文摘1.Introduction Additive manufacturing or 3D printing outweighs conventional casting methods in the aspect of complex parts fabrication,which can realize one-step formation without the need of complicated cast dies.3D printing significantly promotes industrial production for making near-net shaped components.However,this promising technique is not always ideally applicable for metals and alloys.For example,titanium alloys prepared by 3D printing often suf-fer from poor plasticity,and usually require further complex heat treatment or hot isostatic pressing treatment,in order to remove internal stress and regulate plasticity and strength[1,2],which de-feats the original intention of employing additive manufacturing.One of the fundamental causes for such issues is the low fluidity of the alloys upon melting,leading to great chemical heterogeneity,high porosity content and residual stresses.This limitation hinders further design and fabrication of high-performance printable alloys from large scale production and application. | Yiping Lu Xiaoxiang Wu Zhenghong Fu Qiankun Yang Yong Zhang Qiming Liu Tianxin Li Yanzhong Tian Hua Tan Zhiming Li Tongmin Wang Tingju Li | 2022 | Journal of Materials Science & Technology2022，，31： | 4 |
| 3 | Multi-label Image Classification via Coarse-to-Fine Attention显示文摘Great efforts have been made by using deep neural networks to recognize multi-label images.Since multi-label image classification is very complicated,many studies seek to use the attention mechanism as a kind of guidance.Conventional attention-based methods always analyzed images directly and aggressively,which is difficult to well understand complicated scenes.We propose a global/local attention method that can recognize a multi-label image from coarse to fine by mimicking how human-beings observe images.Our global/local attention method first concentrates on the whole image,and then focuses on its local specific objects.We also propose a joint max-margin objective function,which enforces that the minimum score of positive labels should be larger than the maximum score of negative labels horizontally and vertically.This function further improve our multi-label image classification method.We evaluate the effectiveness of our method on two popular multi-label image datasets(i.e.,Pascal VOC and MS-COCO).Our experimental results show that our method outperforms state-of-the-art methods. | LYU Fan LI Linyan Victor S.Sheng FU Qiming HU Fuyuan | 2019 | Chinese Journal of Electronics2019，28，6： | 3 |
| 4 | Efficient reinforcement learning in continuous state and action spaces with Dyna and policy approximation显示文摘Dyna is an effective reinforcement learning (RL) approach that combines value function evaluation with model learning.However,existing works on Dyna mostly discuss only its efficiency in RL problems with discrete action spaces.This paper proposes a novel Dyna variant,called Dyna-LSTD-PA,aiming to handle problems with continuous action spaces.Dyna-LSTD-PA stands for Dyna based on least-squares temporal difference (LSTD)and policy approximation.Dyna-LSTD-PA consists of two simultaneous,interacting processes.The learning process determines the probability distribution over action spaces using the Gaussian distribution;estimates the underlying value function,policy,and model by linear representation;and updates their parameter vectors online by LSTD(,t).The planning process updates the parameter vector of the value function again by using ofttine LSTD(2).Dyna-LSTD-PA also uses the Sherman-Morrison formula to improve the efficiency of LSTD(,t),and weights the parameter vector of the value function to bring the two processes together.Theoretically,the global error bound is derived by considering approximation,estimation,and model errors.Experimentally,Dyna-LSTD-PA outperforms two representative methods in terms of convergence rate,success rate,and stability performance on four benchmark RL problems. | Shan ZHONG Quan LIU Zongzhang ZHANG Qiming FU | 2019 | Frontiers of Computer Science2019，13，1： | 3 |
| 5 | High performance liquid chromatographic separation of eight drugs collected in Chinese Pharmacopoeia 2010 on amylose ramification chiral stationary phase显示文摘The enantiomers separation of ei ght pharmaceutical racemates collected in Chinese Pharmacopoeia 2010(Ch.P2010),including nitrendipine,felodipine,omeprazole,praziquantel,sulpiride,clenbuterol hydrochloride,verapamil hydrochloride and chlorphenamine maleate,was performed on chiral stationary phase of amylose ramification by high performance liquid chromatography(HPLC)on Chiralpak AD-H column and Chiralpak AS-H column with the mobile phase consisted of isopropanol and n-hexane.The detection wavelength and the flow rate were set at 254 nm and 0.7 mL/min,respectively.The effects of proportion of organic additives,alcohol displacer and temperature on the separation were investigated.The results indicated that eight chiral drugs were separated on chiral stationary phase of amylase ramification in normal phase chroma tographic system.The chromatographic retention and resolution of enantiomers were adjusted by factors,including the changes of the concentration of alcohol displacer in mobile phase,organic alkaline modifier and column temperature.It was shown that the resolution was improved with reducing concentration of alcohol displacer.When the concentration of organic alkaline modifier was 0.2%,the resolution and the peak shape were fairly good.Most racemates mentioned above had the best resolution at column temperature of 25℃.The best temperature should be kept unchanged in the process of separation so as to obtain stable separation results. | Yan Wang Ying Zhou Chao Ma Beibei Yang Ru Feng Yiying Zhang Jie Fu Wenjing Chen Yupeng Sun Jingyi Ma Qiming Zhang Yulin Deng Yukui Zhang Wenyi He | 2012 | Acta Pharmaceutica Sinica B2012，2，5： | 3 |
| 6 | A new method for evaluating the oil mobility based on the relationship between pore structure and state of oil显示文摘An accurate evaluation of the shale oil mobility is crucial to its cost-effective exploitation.This study presents a method to assess shale oil mobility by integrating the pore structure and oil states distributions.First,a set of three discrete organic extracts(EOM-A,B and C)were obtained by sequential extraction.The relationships among the EOMs and the oil states were inferred from the group compositions and fluorescence properties of the produced shale oil(free state).The results showed that EOMs A and B represent free oil in the open and closed pores,respectively,while the EOM-C represents adsorbed oil.Then,NMR T_(1)-T_(2)map is used to determine the T_(2-cutoff)values that indicate the pore size ranges of different oil states.Free oil resides mainly in larger pore space(T_(2)>0.5 ms),while the adsorbed oil in smaller pore space(0.2 ms0.5 and T_(2-cutoff)>1.0 ms suggest that the free oil in connected pores has the highest mobility.This work can provide a reference for evaluating the shale oil potential and prospectivity in other regions. | Longhui Bai Bo Liu Xiaofei Fu Qinhong Hu Qiuli Huo Liu Wang Qiming Wang Li FuMehdi Ostadhassan | 2023 | Geoscience Frontiers2023，14，6： | 2 |
| 7 | Reasoning and predicting POMDP planning complexity via covering numbers显示文摘 | Zongzhang ZHANG Qiming FU Xiaofang ZHANG Quan LIU | 2016 | Frontiers of Computer Science2016，10，4： | 1 |
| 8 | Experience Replay for Least-Squares Policy Iteration显示文摘Policy iteration,which evaluates and improves the control policy iteratively,is a reinforcement learning method.Policy evaluation with the least-squares method can draw more useful information from the empirical data and therefore improve the data validity.However,most existing online least-squares policy iteration methods only use each sample just once,resulting in the low utilization rate.With the goal of improving the utilization efficiency,we propose an experience replay for least-squares policy iteration(ERLSPI)and prove its convergence.ERLSPI method combines online least-squares policy iteration method with experience replay,stores the samples which are generated online,and reuses these samples with least-squares method to update the control policy.We apply the ERLSPI method for the inverted pendulum system,a typical benchmark testing.The experimental results show that the method can effectively take advantage of the previous experience and knowledge,improve the empirical utilization efficiency,and accelerate the convergence speed. | Quan Liu Xin Zhou Fei Zhu Qiming Fu Yuchen Fu | 2014 | IEEE/CAA Journal of Automatica Sinica2014，1，3： | 1 |
| 9 | AN APPLIED RESEARCH ON APPROACH OF DYADIC WAVELET TRANSFORM FOR REMOTE SENSING IMAGE EDGE DETECTION显示文摘In the edge detection of Remote Sensing (RS) image, the useful detail losing and the spurious edge often appear. To solve the problem, the authors uses the dyadic wavelet to detect the edge of surface features by combining the edge detecting with the multi-resolution analyzing of the wavelet transform. Via the dyadic wavelet decomposing, the RS image of a certain appropriate scale is obtained, and the edge data of the plane and the upright directions are respectively figured out, then the gradient vector module of the surface features is worked out. By tracing them, the authors get the edge data of the object, therefore build the RS image which obtains the checked edge. This method can depress the effect of noise and examine exactly the edge data of the object by rule and line. With an experiment of an RS image which obtains an airport, the authors certificate the feasibility of the application of dyadic wavelet in the object edge detection. | Fu Wei Xing Guangzhong Hou Lantian Qin Qiming Wang Wenjun | 2006 | Journal of Electronics(China)2006，23，4： | 1 |
| 10 | MAML^(2):meta reinforcement learning via meta-learning for task categories显示文摘Meta-learning has been widely applied to solving few-shot reinforcement learning problems,where we hope to obtain an agent that can learn quickly in a new task.However,these algorithms often ignore some isolated tasks in pursuit of the average performance,which may result in negative adaptation in these isolated tasks,and they usually need sufficient learning in a stationary task distribution.In this paper,our algorithm presents a hierarchical framework of double meta-learning,and the whole framework includes classification,meta-learning,and re-adaptation.Firstly,in the classification process,we classify tasks into several task subsets,considered as some categories of tasks,by learned parameters of each task,which can separate out some isolated tasks thereafter.Secondly,in the meta-learning process,we learn category parameters in all subsets via meta-learning.Simultaneously,based on the gradient of each category parameter in each subset,we use meta-learning again to learn a new metaparameter related to the whole task set,which can be used as an initial parameter for the new task.Finally,in the re-adaption process,we adapt the parameter of the new task with two steps,by the meta-parameter and the appropriate category parameter successively.Experimentally,we demonstrate our algorithm prevents the agent from negative adaptation without losing the average performance for the whole task set.Additionally,our algorithm presents a more rapid adaptation process within readaptation.Moreover,we show the good performance of our algorithm with fewer samples as the agent is exposed to an online meta-learning setting. | Qiming FU Zhechao WANG Nengwei FANG Bin XING Xiao ZHANG Jianping CHEN | 2023 | Frontiers of Computer Science2023，17，4： | 0 |
| 11 | HVAC Optimal Control Based on the Sensitivity Analysis:An Improved SA Combination Method Based on a Neural Network显示文摘Aiming at optimizing the energy consumption of HVAC,an energy conservation optimization method was proposed for HVAC systems based on the sensitivity analysis(SA),named the sensitivity analysis combination method(SAC).Based on the SA,neural network and the related settings about energy conservation of HVAC systems,such as cooling water temperature,chilled water temperature and supply air temperature,were optimized.Moreover,based on the data of the existing HVAC system,various optimal control methods ofHVAC systems were tested and evaluated by a simulated HVAC system in TRNSYS.The results show that the proposed SA combination method can reduce significant computational load while maintaining an equivalent energy performance compared with traditional optimal control methods. | Lifan Zhao Zetian Huang Qiming Fu Nengwei Fang Bin Xing Jianping Chen | 2023 | Computer Modeling in Engineering & Sciences2023，，9： | 0 |
| 12 | MAQMC:Multi-Agent Deep Q-Network for Multi-Zone Residential HVAC Control显示文摘The optimization of multi-zone residential heating,ventilation,and air conditioning(HVAC)control is not an easy task due to its complex dynamic thermal model and the uncertainty of occupant-driven cooling loads.Deep reinforcement learning(DRL)methods have recently been proposed to address the HVAC control problem.However,the application of single-agent DRL formulti-zone residential HVAC controlmay lead to non-convergence or slow convergence.In this paper,we propose MAQMC(Multi-Agent deep Q-network for multi-zone residential HVAC Control)to address this challenge with the goal of minimizing energy consumption while maintaining occupants’thermal comfort.MAQMC is divided into MAQMC2(MAQMC with two agents:one agent controls the temperature of each zone,and the other agent controls the humidity of each zone)and MAQMC3(MAQMC with three agents:three agents control the temperature and humidity of three zones,respectively).The experimental results showthatMAQMC3 can reduce energy consumption by 6.27%andMAQMC2 by 3.73%compared with the fixed point;compared with the rule-based,MAQMC3 andMAQMC2 respectively can reduce 61.89%and 59.07%comfort violation.In addition,experiments with different regional weather data demonstrate that the well-trained MAQMC RL agents have the robustness and adaptability to unknown environments. | Zhengkai Ding Qiming Fu Jianping Chen You Lu Hongjie Wu Nengwei Fang Bin Xing | 2023 | Computer Modeling in Engineering & Sciences2023，，9： | 0 |
| 13 | Improved comprehensive performance of CsPbI_(2) Br perovskite solar cells by modifying the photoactive layers with carbon nanodots显示文摘Introducing additives into perovskite layers is an effective method to enhance the power conversion efficiency(PCE)and operation stability of perovskite solar cells(PSCs).Herein,we reported an addition of carbon nanodots(CNDs)into the CsPbI_(2) Br photoactive layer to boost performance of the related PSCs.It is found that the trap density can be notably suppressed,and the crystallinity can be enhanced after introducing CNDs with an optimal quantity.The PSC with 1.0 wt%addition of CNDs delivers a notable improved average PCE of 13.77%(the highest PCE:14.69%)from that of 12.14%for the control device without CND addition.Moreover,the CND-added CsPbI 2 Br PSCs exhibit superior stability,i.e.,~86% retention of the initial PCE after 160 h aging in air with the humidity of 20%-30%,to the control device. | Yanzhou Wang Caidong Xie Xincheng Yao Qiulu Chen Weining Liu Yujun Fu Qiming Liu Junshuai Li Yali Li Deyan He | 2022 | Journal of Materiomics2022，8，2： | 0 |
| 14 | Enhancement of photoelectric performance for CsPbI2Br solar cells by the synergistic effect of binary additives显示文摘CsPbI_(2)Br-based perovskite solar cells(PSCs)have attracted much attention because of their excellent phase stability and appropriate bandgap.However,numerous defects of undercoordinated ions or mobile species are the sites of carrier nonradiative recombination,causing a low power conversion efficiency(PCE).In this work,NaCl and nitrogen-doped graphene quantum dots(N-GQDs)as binary additives are introduced into perovskite precursor to obtain high-quality photoactive films.Chloride ion(Cl^(-))is incorporated into perovskite due to the same physical and chemical properties as bromine(Br^(-)),that align the energy level of CsPbI_(2)Br,decrease the energy barrier between perovskite and P3HT to promote carrier transport and extraction,hence result in the reduced energy loss.Meanwhile,because of its good conductivity,N-GQDs at grain boundaries can rapidly conduct photogenerated electrons to SnO_(2),suppressing carrier recombination at grain boundaries.Furthermore,the trap state density of the CsPbI_(2)Br film with binary additives is reduced,which could prolong the carrier lifetime,and improve surface morphology.As a result,a PCE of 15.37%for CsPbI_(2)Br PSCs with binary additives is obtained,which shows~22.76%relative increment compare with the pristine PSCs.Therefore,a simple and convenient optimization strategy of binary additives for PSCs is proposed in this work. | Qiulu Chen Like Lin Yanzhou Wang Zhe Gao Yujun Fu Qiming Liu Junshuai Li Deyan He | 2023 | Journal of Materiomics2023，9，1： | 0 |
| 15 | Multi-aperture optical imaging systems and their mathematical light field acquisition models显示文摘Inspired by the compound eyes of insects,many multi-aperture optical imaging systems have been proposed to improve the imaging quality,e.g.,to yield a high-resolution image or an image with a large field-ofview.Previous research has reviewed existing multi-aperture optical imaging systems,but few papers emphasize the light field acquisition model which is essential to bridge the gap between configuration design and application.In this paper,we review typical multi-aperture optical imaging systems(i.e.,artificial compound eye,light field camera,and camera array),and then summarize general mathematical light field acquisition models for different configurations.These mathematical models provide methods for calculating the key indexes of a specific multiaperture optical imaging system,such as the field-of-view and sub-image overlap ratio.The mathematical tools simplify the quantitative design and evaluation of imaging systems for researchers. | Qiming QI Ruigang FU Zhengzheng SHAO Ping WANG Hongqi FAN | 2022 | Frontiers of Information Technology & Electronic Engineering2022，23，6： | 0 |
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