Neuromorphic photonic computing has emerged as a competitive computing paradigm to overcome the bottlenecks of the von-Neumann architecture.Linear weighting and nonlinear spike activation are two fundamental functions...Neuromorphic photonic computing has emerged as a competitive computing paradigm to overcome the bottlenecks of the von-Neumann architecture.Linear weighting and nonlinear spike activation are two fundamental functions of a photonic spiking neural network(PSNN).However,they are separately implemented with different photonic materials and devices,hindering the large-scale integration of PSNN.Here,we propose,fabricate and experimentally demonstrate a photonic neuro-synaptic chip enabling the simultaneous implementation of linear weighting and nonlinear spike activation based on a distributed feedback(DFB)laser with a saturable absorber(DFB-SA).A prototypical system is experimentally constructed to demonstrate the parallel weighted function and nonlinear spike activation.Furthermore,a fourchannel DFB-SA laser array is fabricated for realizing matrix convolution of a spiking convolutional neural network,achieving a recognition accuracy of 87%for the MNIST dataset.The fabricated neuro-synaptic chip offers a fundamental building block to construct the large-scale integrated PSNN chip.展开更多
Liquid silicone injection for cosmetic purposes has a long and notorious history.However,reports of delayed and extensive lesions are rare.Here,we report a case of long-term complications after the use of liquid silic...Liquid silicone injection for cosmetic purposes has a long and notorious history.However,reports of delayed and extensive lesions are rare.Here,we report a case of long-term complications after the use of liquid silicone materials for the correction of facial deformities.In this case,the complications of foreign body granulomas and unique silicone nodules lasting for more than 10 years were reported.Liquid silicone injection can induce delayed adverse reactions,which are difficult to treat.This case presents the successful surgical treatment of a mass injection of liquid silicone.The focus of treatment should be to remove the injected material and degenerated tissue as much as possible while protecting normal tissue and its function.Through open reconstructive surgery with an appropriate incision,postoperative scars can be hidden.Consequently,both functional and aesthetic outcomes can be achieved.展开更多
The pathogenesis of striae distensae(SD) is complicated and has not yet been fully elucidated. Hormonal changes,overstretched skin, and structural and functional changes in the skin may be crucial factors in the devel...The pathogenesis of striae distensae(SD) is complicated and has not yet been fully elucidated. Hormonal changes,overstretched skin, and structural and functional changes in the skin may be crucial factors in the development of SD. Therapy aims to stimulate dermal collagen synthesis and improve skin texture. Mainstream treatments include topical medications, chemical peeling, laser and radiofrequency therapy, microdermabrasion, microneedle therapy, and filler injection therapy. In the present review, we summarize current perspectives on the pathogenesis and clinical therapy of SD.展开更多
Background Nasal alarplasty is an important component of esthetic rhinoplasty in Asians.The two main surgical techniques that correct alar hypertrophy by reducing the height or length often leave external scars and ar...Background Nasal alarplasty is an important component of esthetic rhinoplasty in Asians.The two main surgical techniques that correct alar hypertrophy by reducing the height or length often leave external scars and are associated with a high relapse rate.Methods We developed a new technique,called three-dimensional(3D)M-shaped resection,which corrects both the nasal alar height and length and simultaneously minimizes external scarring.We performed this procedure from January 2013 to September 2016 in 49 consecutive female patients diagnosed with saddle nose and nasal alar hypertrophy.Their mean age was 28.6(range,18–40)years.All patients had previously undergone simple rhinoplasty.Nasal alar length and height,nostril length and width,and maximal nose width were analyzed preoperatively and postoperatively from photographs.Results After a mean of 9(range,3–24)months of follow-up,surgery was considered successful in 46 women(94%)with good cosmetic effects.In three patients,nasal alar hypertrophy recurred(6 months postoperatively).There were no early complications such as hematomas,infections,skin or mucosal necrosis,or wound dehiscence.The mean reductions postoperatively were 1.7 mm and 0.9 mm for nasal alar length and height,respectively,1.6 mm for both nostril length and width,and 3.5 mm for nose width.Conclusion The 3D M-shaped resection for nasal alar hypertrophy effectively reduced hypertrophy in 94%of patients for up to 24 months,producing minimal external scars and good cosmetic effects.It is a simple and convenient technique that is an effective and safe option for nasal alarplasty.展开更多
The burgeoning volume of parameters in artificial neural network models has posed substantial challenges to conventional tensor computing hardware.Benefiting from the available optical multidimensional information ent...The burgeoning volume of parameters in artificial neural network models has posed substantial challenges to conventional tensor computing hardware.Benefiting from the available optical multidimensional information entropy,optical intelligent computing is used as an alternative solution to address the emerging challenges of electrical computing.These limitations,in terms of device size and photonic integration scale,have hindered the performance of optical chips.Herein,an ultrahigh computing density optical tensor processing unit(OTPU),which is grounded in an individual microring resonator(MRR),is introduced to respond to these challenges.Through the independent tuning of multiwavelength lasers,the operational capabilities of an MRR are orchestrated,culminating in the formation of an optical tensor core.This design facilitates the execution of tensor convolution operations via the lightwave and microwave multidomain hybrid multiplexing in terms of the time,wavelength,and frequency of microwaves.The experimental results for the MRR-based OTPU show an extraordinary computing density of 34.04 TOPS/mm2.Additionally,the achieved accuracy rate in recognizing MNIST handwritten digits was 96.41%.These outcomes signify a significant advancement toward the realization of high-performance optical tensor processing chips.展开更多
Matrix computation,as a fundamental building block of information processing in science and technology,contributes most of the computational overheads in modern signal processing and artificial intelligence algorithms...Matrix computation,as a fundamental building block of information processing in science and technology,contributes most of the computational overheads in modern signal processing and artificial intelligence algorithms.Photonic accelerators are designed to accelerate specific categories of computing in the optical domain,especially matrix multiplication,to address the growing demand for computing resources and capacity.Photonic matrix multiplication has much potential to expand the domain of telecommunication,and artificial intelligence benefiting from its superior performance.Recent research in photonic matrix multiplication has flourished and may provide opportunities to develop applications that are unachievable at present by conventional electronic processors.In this review,we first introduce the methods of photonic matrix multiplication,mainly including the plane light conversion method,Mach–Zehnder interferometer method and wavelength division multiplexing method.We also summarize the developmental milestones of photonic matrix multiplication and the related applications.Then,we review their detailed advances in applications to optical signal processing and artificial neural networks in recent years.Finally,we comment on the challenges and perspectives of photonic matrix multiplication and photonic acceleration.展开更多
Artificial neural networks have dramatically improved the performance of many machine-learning applications such as image recognition and natural language processing. However, the electronic hardware implementations o...Artificial neural networks have dramatically improved the performance of many machine-learning applications such as image recognition and natural language processing. However, the electronic hardware implementations of the above-mentioned tasks are facing performance ceiling because Moore’s Law is slowing down. In this article, we propose an optical neural network architecture based on optical scattering units to implement deep learning tasks with fast speed, low power consumption and small footprint.The optical scattering units allow light to scatter back and forward within a small region and can be optimized through an inverse design method. The optical scattering units can implement high-precision stochastic matrix multiplication with mean squared error < 10-4 and a mere 4*4 um2 footprint.Furthermore, an optical neural network framework based on optical scattering units is constructed by introducing "Kernel Matrix", which can achieve 97.1% accuracy on the classic image classification dataset MNIST.展开更多
In late July 2018, a compound drought and heat event(CDHE) occurred in the middle of the Yangtze River basin(MYRB) and caused great damage to the national economy. The CDHE over the MYRB has been documented to be link...In late July 2018, a compound drought and heat event(CDHE) occurred in the middle of the Yangtze River basin(MYRB) and caused great damage to the national economy. The CDHE over the MYRB has been documented to be linked with intraseasonal oscillations(ISOs) from different regions. However, specific roles of different ISOs on the development of the CDHE cannot be separated in the observational analysis. By using partial lateral forcing experiments driven by ISO in the Weather Research and Forecasting(WRF) model, we found that the midlatitude ISO generated by a westerly wave train in the upper troposphere played an important role in this heatwave and drought event in the northern MYRB, causing a regional average temperature rise of 1.65°C and intensification of drought over23.49% of the MYRB area. On the other hand, the ISO associated with the Pacific-Japan(PJ)-like teleconnection wave train in the lower troposphere induced a more pronounced impact on the event, causing an average temperature rise of 2.44°C, intensifying drought over 29.62% of the MYRB area. The MYRB was mainly affected by northward warm advection driven by the westward extension of the western North Pacific subtropical high in the early period of the CDHE development. In the late period, because of the establishment of a deep positive geopotential height field through the troposphere leading to intensive local subsidence, there was a remarkable temperature rise and moisture decrease in the MYRB. The results will facilitate a better understanding of the occurrence of CDHE and provide empirical precursory signals for subseasonal forecast of CDHE.展开更多
The rapid development of artificial general intelligence(AGI)introduces significant performance challenges for next-generation computing.Electronic devices such as graphics processing units(GPUs)are constrained by com...The rapid development of artificial general intelligence(AGI)introduces significant performance challenges for next-generation computing.Electronic devices such as graphics processing units(GPUs)are constrained by computational and energy efficiency limitations,hindering the advancement of modern AGI models.展开更多
Information and communication technologies enable the transformation of traditional energy systems into cyber-physical energy systems(CPESs),but such systems have also become popular targets of cyberattacks.Currently,...Information and communication technologies enable the transformation of traditional energy systems into cyber-physical energy systems(CPESs),but such systems have also become popular targets of cyberattacks.Currently,available methods for evaluating the impacts of cyberattacks suffer from limited resilience,efficacy,and practical value.To mitigate their potentially disastrous consequences,this study suggests a two-stage,discrepancy-based optimization approach that considers both preparatory actions and response measures,integrating concepts from social computing.The proposed Kullback-Leibler divergence-based,distributionally robust optimization(KDR)method has a hierarchical,two-stage objective function that incorporates the operating costs of both system infrastructures(e.g.,energy resources,reserve capacity)and real-time response measures(e.g.,load shedding,demand-side management,electric vehicle charging station management).By incorporating social computing principles,the optimization framework can also capture the social behavior and interactions of energy consumers in response to cyberattacks.The preparatory stage entails day-ahead operational decisions,leveraging insights from social computing to model and predict the behaviors of individuals and communities affected by potential cyberattacks.The mitigation stage generates responses designed to contain the consequences of the attack by directing and optimizing energy use from the demand side,taking into account the social context and preferences of energy consumers,to ensure resilient,economically efficient CPES operations.Our method can determine optimal schemes in both stages,accounting for the social dimensions of the problem.An original disaster mitigation model uses an abstract formulation to develop a risk-neutral model that characterizes cyberattacks through KDR,incorporating social computing techniques to enhance the understanding and response to cyber threats.This approach can mitigate the impacts more effectively than several existing methods,even with limited data availability.To extend this risk-neutral model,we incorporate conditional value at risk as an essential risk measure,capturing the uncertainty and diverse impact scenarios arising from social computing factors.The empirical results affirm that the KDR method,which is enriched with social computing considerations,produces resilient,economically efficient solutions for managing the impacts of cyberattacks on a CPES.By integrating social computing principles into the optimization framework,it becomes possible to better anticipate and address the social and behavioral aspects associated with cyberattacks on CPESs,ultimately improving the overall resilience and effectiveness of the system’s response measures.展开更多
基金financial supports from National Key Research and Development Program of China (2021YFB2801900,2021YFB2801901,2021YFB2801902,2021YFB2801904)National Natural Science Foundation of China (No.61974177)+1 种基金National Outstanding Youth Science Fund Project of National Natural Science Foundation of China (62022062)The Fundamental Research Funds for the Central Universities (QTZX23041).
文摘Neuromorphic photonic computing has emerged as a competitive computing paradigm to overcome the bottlenecks of the von-Neumann architecture.Linear weighting and nonlinear spike activation are two fundamental functions of a photonic spiking neural network(PSNN).However,they are separately implemented with different photonic materials and devices,hindering the large-scale integration of PSNN.Here,we propose,fabricate and experimentally demonstrate a photonic neuro-synaptic chip enabling the simultaneous implementation of linear weighting and nonlinear spike activation based on a distributed feedback(DFB)laser with a saturable absorber(DFB-SA).A prototypical system is experimentally constructed to demonstrate the parallel weighted function and nonlinear spike activation.Furthermore,a fourchannel DFB-SA laser array is fabricated for realizing matrix convolution of a spiking convolutional neural network,achieving a recognition accuracy of 87%for the MNIST dataset.The fabricated neuro-synaptic chip offers a fundamental building block to construct the large-scale integrated PSNN chip.
文摘Liquid silicone injection for cosmetic purposes has a long and notorious history.However,reports of delayed and extensive lesions are rare.Here,we report a case of long-term complications after the use of liquid silicone materials for the correction of facial deformities.In this case,the complications of foreign body granulomas and unique silicone nodules lasting for more than 10 years were reported.Liquid silicone injection can induce delayed adverse reactions,which are difficult to treat.This case presents the successful surgical treatment of a mass injection of liquid silicone.The focus of treatment should be to remove the injected material and degenerated tissue as much as possible while protecting normal tissue and its function.Through open reconstructive surgery with an appropriate incision,postoperative scars can be hidden.Consequently,both functional and aesthetic outcomes can be achieved.
基金supported by the National Natural Science Foundation of China(grant no.81873937)。
文摘The pathogenesis of striae distensae(SD) is complicated and has not yet been fully elucidated. Hormonal changes,overstretched skin, and structural and functional changes in the skin may be crucial factors in the development of SD. Therapy aims to stimulate dermal collagen synthesis and improve skin texture. Mainstream treatments include topical medications, chemical peeling, laser and radiofrequency therapy, microdermabrasion, microneedle therapy, and filler injection therapy. In the present review, we summarize current perspectives on the pathogenesis and clinical therapy of SD.
文摘Background Nasal alarplasty is an important component of esthetic rhinoplasty in Asians.The two main surgical techniques that correct alar hypertrophy by reducing the height or length often leave external scars and are associated with a high relapse rate.Methods We developed a new technique,called three-dimensional(3D)M-shaped resection,which corrects both the nasal alar height and length and simultaneously minimizes external scarring.We performed this procedure from January 2013 to September 2016 in 49 consecutive female patients diagnosed with saddle nose and nasal alar hypertrophy.Their mean age was 28.6(range,18–40)years.All patients had previously undergone simple rhinoplasty.Nasal alar length and height,nostril length and width,and maximal nose width were analyzed preoperatively and postoperatively from photographs.Results After a mean of 9(range,3–24)months of follow-up,surgery was considered successful in 46 women(94%)with good cosmetic effects.In three patients,nasal alar hypertrophy recurred(6 months postoperatively).There were no early complications such as hematomas,infections,skin or mucosal necrosis,or wound dehiscence.The mean reductions postoperatively were 1.7 mm and 0.9 mm for nasal alar length and height,respectively,1.6 mm for both nostril length and width,and 3.5 mm for nose width.Conclusion The 3D M-shaped resection for nasal alar hypertrophy effectively reduced hypertrophy in 94%of patients for up to 24 months,producing minimal external scars and good cosmetic effects.It is a simple and convenient technique that is an effective and safe option for nasal alarplasty.
基金supported by the Youth Innovation Promotion Association of Chinese Academy of Sciences under grant no.2022111(N.S.)the International Partnership Program of Chinese Academy of Sciences under grant no.100GJHZ2022028GC(M.L.)+1 种基金the Beijing Municipal Natural Science Foundation under grant no.Z210005(M.L.)the National Natural Science Foundation of China under grant nos.61925505(M.L.),62235011(N.S.)and 62075212(N.S.).
文摘The burgeoning volume of parameters in artificial neural network models has posed substantial challenges to conventional tensor computing hardware.Benefiting from the available optical multidimensional information entropy,optical intelligent computing is used as an alternative solution to address the emerging challenges of electrical computing.These limitations,in terms of device size and photonic integration scale,have hindered the performance of optical chips.Herein,an ultrahigh computing density optical tensor processing unit(OTPU),which is grounded in an individual microring resonator(MRR),is introduced to respond to these challenges.Through the independent tuning of multiwavelength lasers,the operational capabilities of an MRR are orchestrated,culminating in the formation of an optical tensor core.This design facilitates the execution of tensor convolution operations via the lightwave and microwave multidomain hybrid multiplexing in terms of the time,wavelength,and frequency of microwaves.The experimental results for the MRR-based OTPU show an extraordinary computing density of 34.04 TOPS/mm2.Additionally,the achieved accuracy rate in recognizing MNIST handwritten digits was 96.41%.These outcomes signify a significant advancement toward the realization of high-performance optical tensor processing chips.
基金Chaoran Huang would like to thank Alexander Tait,Bhavin Shastri and Paul Prucnal for the fruitful discussions.J.J.D.acknowledges the support of the National Key Research and Development Project of China(2018YFB2201901)the National Natural Science Foundation of China(61805090,62075075).
文摘Matrix computation,as a fundamental building block of information processing in science and technology,contributes most of the computational overheads in modern signal processing and artificial intelligence algorithms.Photonic accelerators are designed to accelerate specific categories of computing in the optical domain,especially matrix multiplication,to address the growing demand for computing resources and capacity.Photonic matrix multiplication has much potential to expand the domain of telecommunication,and artificial intelligence benefiting from its superior performance.Recent research in photonic matrix multiplication has flourished and may provide opportunities to develop applications that are unachievable at present by conventional electronic processors.In this review,we first introduce the methods of photonic matrix multiplication,mainly including the plane light conversion method,Mach–Zehnder interferometer method and wavelength division multiplexing method.We also summarize the developmental milestones of photonic matrix multiplication and the related applications.Then,we review their detailed advances in applications to optical signal processing and artificial neural networks in recent years.Finally,we comment on the challenges and perspectives of photonic matrix multiplication and photonic acceleration.
基金This work was supported by the National Key Research and Development Program of China(2017YFA0205700)the National Natural Science Foundation of China(61927820)Yurui Qu was supported by Zhejiang Lab’s International Talent Fund for Young Professionals.
文摘Artificial neural networks have dramatically improved the performance of many machine-learning applications such as image recognition and natural language processing. However, the electronic hardware implementations of the above-mentioned tasks are facing performance ceiling because Moore’s Law is slowing down. In this article, we propose an optical neural network architecture based on optical scattering units to implement deep learning tasks with fast speed, low power consumption and small footprint.The optical scattering units allow light to scatter back and forward within a small region and can be optimized through an inverse design method. The optical scattering units can implement high-precision stochastic matrix multiplication with mean squared error < 10-4 and a mere 4*4 um2 footprint.Furthermore, an optical neural network framework based on optical scattering units is constructed by introducing "Kernel Matrix", which can achieve 97.1% accuracy on the classic image classification dataset MNIST.
基金Supported by the National Natural Science Foundation of China(41875111 and 41975073)Special Program for Innovation and Development of China Meteorological Administration(CXFZ2022J031).
文摘In late July 2018, a compound drought and heat event(CDHE) occurred in the middle of the Yangtze River basin(MYRB) and caused great damage to the national economy. The CDHE over the MYRB has been documented to be linked with intraseasonal oscillations(ISOs) from different regions. However, specific roles of different ISOs on the development of the CDHE cannot be separated in the observational analysis. By using partial lateral forcing experiments driven by ISO in the Weather Research and Forecasting(WRF) model, we found that the midlatitude ISO generated by a westerly wave train in the upper troposphere played an important role in this heatwave and drought event in the northern MYRB, causing a regional average temperature rise of 1.65°C and intensification of drought over23.49% of the MYRB area. On the other hand, the ISO associated with the Pacific-Japan(PJ)-like teleconnection wave train in the lower troposphere induced a more pronounced impact on the event, causing an average temperature rise of 2.44°C, intensifying drought over 29.62% of the MYRB area. The MYRB was mainly affected by northward warm advection driven by the westward extension of the western North Pacific subtropical high in the early period of the CDHE development. In the late period, because of the establishment of a deep positive geopotential height field through the troposphere leading to intensive local subsidence, there was a remarkable temperature rise and moisture decrease in the MYRB. The results will facilitate a better understanding of the occurrence of CDHE and provide empirical precursory signals for subseasonal forecast of CDHE.
文摘The rapid development of artificial general intelligence(AGI)introduces significant performance challenges for next-generation computing.Electronic devices such as graphics processing units(GPUs)are constrained by computational and energy efficiency limitations,hindering the advancement of modern AGI models.
基金supported in part by the New Generation Artificial Intelligence Development Plan of China(2015–2030)(Grants No.2021ZD0111205)the National Natural Science Foundation of China(Grants No.72025404,No.71621002,No.71974187)+1 种基金Beijing Natural Science Foundation(L192012)Beijing Nova Program(Z201100006820085).
文摘Information and communication technologies enable the transformation of traditional energy systems into cyber-physical energy systems(CPESs),but such systems have also become popular targets of cyberattacks.Currently,available methods for evaluating the impacts of cyberattacks suffer from limited resilience,efficacy,and practical value.To mitigate their potentially disastrous consequences,this study suggests a two-stage,discrepancy-based optimization approach that considers both preparatory actions and response measures,integrating concepts from social computing.The proposed Kullback-Leibler divergence-based,distributionally robust optimization(KDR)method has a hierarchical,two-stage objective function that incorporates the operating costs of both system infrastructures(e.g.,energy resources,reserve capacity)and real-time response measures(e.g.,load shedding,demand-side management,electric vehicle charging station management).By incorporating social computing principles,the optimization framework can also capture the social behavior and interactions of energy consumers in response to cyberattacks.The preparatory stage entails day-ahead operational decisions,leveraging insights from social computing to model and predict the behaviors of individuals and communities affected by potential cyberattacks.The mitigation stage generates responses designed to contain the consequences of the attack by directing and optimizing energy use from the demand side,taking into account the social context and preferences of energy consumers,to ensure resilient,economically efficient CPES operations.Our method can determine optimal schemes in both stages,accounting for the social dimensions of the problem.An original disaster mitigation model uses an abstract formulation to develop a risk-neutral model that characterizes cyberattacks through KDR,incorporating social computing techniques to enhance the understanding and response to cyber threats.This approach can mitigate the impacts more effectively than several existing methods,even with limited data availability.To extend this risk-neutral model,we incorporate conditional value at risk as an essential risk measure,capturing the uncertainty and diverse impact scenarios arising from social computing factors.The empirical results affirm that the KDR method,which is enriched with social computing considerations,produces resilient,economically efficient solutions for managing the impacts of cyberattacks on a CPES.By integrating social computing principles into the optimization framework,it becomes possible to better anticipate and address the social and behavioral aspects associated with cyberattacks on CPESs,ultimately improving the overall resilience and effectiveness of the system’s response measures.
