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| 1 | Deep-learning-powered photonic analogto-digital conversion显示文摘Analog-to-digital converters(ADCs)must be high speed,broadband,and accurate for the development of modern information systems,such as radar,imaging,and communications systems;photonic technologies are regarded as promising technologies for realizing these advanced requirements.Here,we present a deep-learning-powered photonic ADC architecture that simultaneously exploits the advantages of electronics and photonics and overcomes the bottlenecks of the two technologies,thereby overcoming the ADC tradeoff among speed,bandwidth,and accuracy.Via supervised training,the adopted deep neural networks learn the patterns of photonic system defects and recover the distorted data,thereby maintaining the high quality of the electronic quantized data succinctly and adaptively.The numerical and experimental results demonstrate that the proposed architecture outperforms state-ofthe-art ADCs with developable high throughput;hence,deep learning performs well in photonic ADC systems.We anticipate that the proposed architecture will inspire future high-performance photonic ADC design and provide opportunities for substantial performance enhancement for the next-generation information systems. | Shaofu Xu Xiuting Zou Bowen Ma Jianping Chen Lei Yu Weiwen Zou | 2019 | Light(Science & Applications)2019，8，1： | 8 |
| 2 | A review:Photonics devices,architectures,and algorithms for optical neural computing显示文摘The explosive growth of data and information has motivated various emerging non-von Neumann computational approaches in the More-than-Moore era.Photonics neuromorphic computing has attracted lots of attention due to the fascinating advantages such as high speed,wide bandwidth,and massive parallelism.Here,we offer a review on the optical neural computing in our research groups at the device and system levels.The photonics neuron and photonics synapse plasticity are presented.In addition,we introduce several optical neural computing architectures and algorithms including photonic spiking neural network,photonic convolutional neural network,photonic matrix computation,photonic reservoir computing,and photonic reinforcement learning.Finally,we summarize the major challenges faced by photonic neuromorphic computing,and propose promising solutions and perspectives. | Shuiying Xiang Yanan Han Ziwei Song Xingxing Guo Yahui Zhang Zhenxing Ren Suhong Wang Yuanting Ma Weiwen Zou Bowen Ma Shaofu Xu Jianji Dong Hailong Zhou Quansheng Ren Tao Deng Yan Liu Genquan Han Yue Hao | 2021 | Journal of Semiconductors2021，42，2： | 7 |
| 3 | New approach to determine common weights in DEA efficiency evaluation model显示文摘Data envelopment analysis(DEA) is a mathematical programming approach to appraise the relative efficiencies of peer decision-making unit(DMU),which is widely used in ranking DMUs.However,almost all DEA-related ranking approaches are based on the self-evaluation efficiencies.In other words,each DMU chooses the weights it prefers to most,so the resulted efficiencies are not suitable to be used as ranking criteria.Therefore this paper proposes a new approach to determine a bundle of common weights in DEA efficiency evaluation model by introducing a multi-objective integer programming.The paper also gives the solving process of this multi-objective integer programming,and the solution is proven a Pareto efficient solution.The solving process ensures that the obtained common weight bundle is acceptable by a great number of DMUs.Finally a numeral example is given to demonstrate the approach. | Feng Yang Chenchen Yang Liang Liangc Shaofu Du | 2010 | Journal of Systems Engineering and Electronics2010，21，4： | 7 |
| 4 | Preparation of nano-sized tungsten carbide via fluidized bed显示文摘Ultrafine or nano-sized of tungsten carbide(WC)is the key material to prepare ultrafine grained cemented carbides.In this paper,nano-sized WC powders were directly prepared by using industrial nano-needle violet tungsten oxide(WO2.72)as the raw material,a fluidized bed as the reactor,and CO as the carbonization gas.The relationship between particle sizes and reaction temperatures,residence times,atmospheres has been investigated systematically.In addition,the physical–chemical indexes(such as residual oxygen,total carbon and free carbon)of the products were measured.The results indicated that the particle size of WC increased with the increase of temperature from 800 to 950°C.As the residence time increased,the particle size decreased gradually,and then increased due to slight sintering.The introduction of hydrogen reduced the carbonization rate,and is not beneficial to obtaining nano-sized WC.Products that satisfy the standard were obtained when WO2.72 reacted with CO at 850°C,900°C and 950°C for 3.0 h,2.5 h and 2.0 h,respectively.The particle sizes of the three samples calculated from the specific surface area were 46.4 nm,53.2 nm and 52.1 nm,respectively. | Feng Pan Zhan Du Shaofu Li Jun Li Meiju Zhang Maoqiao Xiang Qingshan Zhu | 2020 | Chinese Journal of Chemical Engineering2020，28，3： | 4 |
| 5 | Cloned goats (Gapra hircus) from foetal fibroblast cell lines显示文摘Mammalian cloning has been one of the most active research topics in the world. Cioning with in vitro culured foetal fibroblast cells, in comparison with embryonic cells, can be used not only to theoretically study the embryonic or cellular development and differentiation in mammals, but also to utilize the unlimited fibroblast cells to produce large numbers of clonings. The preliminary results are as follows: (i) The division and development of the cloned embryos with embryonic donor cells and goat foetal fibroblast donor cells were 55%, 77% and 35%, 31%, respectively. There is no significant statistical difference between them. (? These studies result in the birth of two cloned goats derived from two 30-day foetal fibroblast celi lines, which are the first cloned mammals from somatic cells in China. This project has established a technological data base for the furture research on adult mammalian somatic cloning and nucleocytoplasmic interactions in animal development, and a novel technique for the | WANG Yuge ZOU Xiangang LIU Jie ZHANG Jingpu ZHANG Xuechen LAO Weide DU Miao CHENG Guoxing CHENG Yong CHEN Jianquan ZHANG Suolin XU Shaofu | 2000 | Chinese Science Bulletin2000，45，1： | 4 |
| 6 | Towards an intelligent photonic system显示文摘The emerging intelligence technologies represented by deep learning have broadened their applications to various fields.Beyond the conventional electronics-based processing systems,the convergence of photonics and artificial intelligence(AI)technology enhances the performance and learning ability of AI.In this review,we propose the concept of an intelligent photonic system(IPS),illustrating it as a developing architecture with three different versions.For each version of IPS,we review several representative studies.Moreover we discuss the challenges towards an IPS and provide some prospects for the future development. | Weiwen ZOU Bowen MA Shaofu XU Xiuting ZOU Xingjun WANG | 2020 | Science China(Information Sciences)2020，63，6： | 3 |
| 7 | Global Synchronization of Stochastically Disturbed Memristive Neurodynamics via Discontinuous Control Laws显示文摘This paper presents the theoretical results on the master-slave(or driving-response) synchronization of two memristive neural networks in the presence of additive noise. First,a control law with a linear time-delay feedback term and a discontinuous feedback term is introduced. By utilizing the stability theory of stochastic differential equations, sufficient conditions are derived for ascertaining global synchronization in mean square using this control law. Second, an adaptive control law consisting of a linear feedback term and a discontinuous feedback term is designed to achieve global synchronization in mean square, and it does not need prior information of network parameters or random disturbances. Finally, simulation results are presented to substantiate the theoretical results. | Zhenyuan Guo Shaofu Yang Jun Wang | 2016 | IEEE/CAA Journal of Automatica Sinica2016，3，2： | 2 |
| 8 | Progress in Light-weight High Entropy Alloys显示文摘High entropy alloys(HEAs)possess good mechanical properties and a wide range of industrial applications.In this paper,phase formation prediction theory,microstructure,properties and preparation methods of light-weight HEAs(LWHEAs)were reviewed.The problems and challenges faced by LWHEAs development were analyzed.The results showed that many aspects are still weak and require investigation for future advanced alloys,such as clarification of the role of entropy in phase formation and properties of HEAs,improved definition and different generations division of HEAs,close-packed hexagonal(HCP)phase structure prediction and corresponding alloy design and fabrication.Finally,some suggestions were presented in this paper including in-depth research on formation mechanism of multi-component alloy phase and strengthening of large-scale HEA preparation methods via technology compounding and 3D printing technology.Also,there is a need for more research on the in-situ preparation of HEA coatings and films,as well as developing LWHEAs with superior strength and elevated temperature resistance or ultra-low temperature resistance to meet the requirements of future engineering applications. | 蔡志海 GUO Yu 柳建 LIU Jun GUO Jie DU Xian HUANG Shaofu | 2021 | Journal of Wuhan University of Technology(Materials Science)2021，36，5： | 2 |
| 9 | Emission-dependent supply chain and environment-policy-making in the ‘cap-and-trade’ system显示文摘 | Shaofu Du Lili Zhu Liang Liang Fang Ma | 2012 | Energy Policy2012，，： | 2 |
| 10 | High-efficient crystal particle manufacture by microscale process intensification technology显示文摘High-end crystal manufacture has drawn a permanent concern on the high-efficient manufacture of crystal particles,especially in fine chemical,pharmaceutical,electronics,biological and relative engineering fields.In recent years,a series of microscale process intensification(MPI)technologies have been widely used in crystal particles preparation via addressing the control of nucleation and growth process.Herein,we review the research progresses of microscale process intensification technology from three aspects,microfluidics devices,microscale force field technology and membrane-based microchannels and interface transfer process.Firstly,the principle of microfluidic and relative microscale device on improving micro-mixing and mass transfer are briefly described.The advantage of microfluidic in continuous nano particle preparation is outlined.Microscale external force field(ultrasonic,high-gravity,electric and magnetic fields)is then introduced as another novel approach for ultrafine nanoparticles and continuous drug crystallization process.Further,in view of the micro-scale intensified mass transfer and microscale interfacial force field established on membrane technology,the basic mechanism of membrane crystallization(microscale 2D supersaturation degree control,auto seed detachment,microporous membrane dispersion,etc.)is reviewed.The process coupling and design strategy aiming for enhancing the manufacture capacity is also illustrated.Finally,the developing tendency and key challenges of high-efficient crystal particle preparation technology via microscale processes are overviewed. | Yuchao Niu Shaofu Du Lei Sheng Wu Xiao Xiaobin Jiang Gaohong He | 2021 | Green Chemical Engineering2021，2，1： | 2 |
| 11 | Optical coherent dot-product chip for sophisticated deep learning regression显示文摘Optical implementations of neural networks(ONNs)herald the next-generation high-speed and energy-efficient deep learning computing by harnessing the technical advantages of large bandwidth and high parallelism of optics.However,due to the problems of the incomplete numerical domain,limited hardware scale,or inadequate numerical accuracy,the majority of existing ONNs were studied for basic classification tasks.Given that regression is a fundamental form of deep learning and accounts for a large part of current artificial intelligence applications,it is necessary to master deep learning regression for further development and deployment of ONNs.Here,we demonstrate a silicon-based optical coherent dot-product chip(OCDC)capable of completing deep learning regression tasks.The OCDC adopts optical fields to carry out operations in the complete real-value domain instead of in only the positive domain.Via reusing,a single chip conducts matrix multiplications and convolutions in neural networks of any complexity.Also,hardware deviations are compensated via in-situ backpropagation control provided the simplicity of chip architecture.Therefore,the OCDC meets the requirements for sophisticated regression tasks and we successfully demonstrate a representative neural network,the AUTOMAP(a cutting-edge neural network model for image reconstruction).The quality of reconstructed images by the OCDC and a 32-bit digital computer is comparable.To the best of our knowledge,there is no precedent of performing such state-of-the-art regression tasks on ONN chips.It is anticipated that the OCDC can promote the novel accomplishment of ONNs in modern AI applications including autonomous driving,natural language processing,and scientific study. | Shaofu Xu Jing Wang Haowen Shu Zhike Zhang Sicheng Yi Bowen Bai Xingjun Wang Jianguo Liu Weiwen Zou | 2021 | Light(Science & Applications)2021，10，12： | 2 |
| 12 | Timing Crisis Information Release via Television显示文摘 | Jiuchang Wei Dingtao Zhao Feng Yang Shaofu Du Dora Ma rinova | 2010 | Disasters(The Journal of Disaster Studies Policy and Manage ment)2010，34，4： | 1 |
| 13 | Multi - product newsboy problem with lim- ited capacity and outsourcing 显示文摘 | Bin Zhang Shaofu Dub | 2010 | European Journal of Operational Research2010，202，1： | 1 |
| 14 | Integrating dual-role variables in data envelopment analysis显示文摘Traditional data envelopment analysis(DEA) theory assumes that decision variables are regarded as inputs or outputs,and no variable can play the roles of both an input and an output at the same time.In fact,there exist some variables that work as inputs and outputs simultaneously and are called dual-role variables.Traditional DEA models cannot be used to appraise the performance of decision making units containing dual-role variables.The paper analyzes the structure and properties of the production systems comprising dual-role variables,and proposes a DEA model integrating dual-role variables.Finally the proposed model is illustrated to evaluate the efficiency of university departments. | Feng Yang Liang Liang Zhaoqiong Li Shaofu Du | 2010 | Journal of Systems Engineering and Electronics2010，21，5： | 1 |
| 15 | Emission-de- pendent supply chain and environment-policy-making in the 'cap-and-trade' system显示文摘 | Du Shaofu Zhu Lili Liang Liang | 2013 | Energy Policy2013，57，： | 1 |
| 16 | Highly ductile hypereutectic Al-Si alloys fabricated by selective laser melting显示文摘In the endeavor to maximize the refinement effect of primary Si and alleviate the inherent brittleness of hypereutectic Al-Si alloy,the approach of coating P as a modifier on powder was adopted.The ultimate aim was to create more heterogeneous fine Al P nucleus and enhance the nucleation efficiency of primary Si on Al P to refine the coarse primary Si to nano-scale during 3D printing.In the combination of large undercooling and high density of nucleation sites,the size of primary Si was successfully refined to 200–300 nm and the divorced eutectic was also induced to modify the microstructure of matrix.In the presence of nano-scale primary Si,the melting pool boundary(MPB)feature disappeared and the fracture mechanism also changed from load transfer to interfacial fracture.Compared with the pristine alloy,the ductility was increased four times without significantly changing the ultimate tensile strength(UTS)and wear resistance.The improvement of ductility is attributed to the refinement of primary Si,the disappearance of MPB features and the formation of divorced eutectic.The optimal tensile properties were:UTS-482 MPa,yield strength-320 MPa and ductility of 8.1%at 0.05 wt.%P.These are comparable to those for high-strength Al alloys. | Yafeng Yang Kang Geng Shaofu Li Michael Bermingham R.D.K.Misra | 2022 | Journal of Materials Science & Technology2022，，15： | 1 |
| 17 | Finite element analysis and tests on bolted end-plate connections in steel portal frames显示文摘 | Gang Shi Yongjiu Shi Yuanqing Wang Shaofu Li Hong Chen | 2004 | Advances in Structural Engineering2004，7，3： | 1 |
| 18 | Diversity of Pathogens Responsible for Acute Diarrheal Disease in China显示文摘 | Rongzhang Hao Peng Li Shaofu Qiu | 2013 | Clinical Infectious Diseases2013，57，12： | 1 |
| 19 | Quinolone-Resistant Escherichia coli O127a:K63 Serotype with an Extended-Spectrum-Beta-Lactamase Phenotype from a Food Poisoning Outbreak in China显示文摘 | Rongzhang Hao Shaofu Qiu Yong Wang Guang Yang Wenli Su Lixue Song Jia Zhang Jiaxu Chen Leili Jia Ligui Wang Hongbin Song | 2012 | Journal of Clinical Microbiology2012，，7： | 1 |
| 20 | Emissiondependent supply chain and environment-policy-making in the‘cap-and-trade’system显示文摘 | SHAOFU DU LILI ZHU LIANG LIANG | 2013 | Energy Policy2013，57，： | 1 |
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