Graph Convolutional Neural Networks(GCNs)have been widely used in various fields due to their powerful capabilities in processing graph-structured data.However,GCNs encounter significant challenges when applied to sca...Graph Convolutional Neural Networks(GCNs)have been widely used in various fields due to their powerful capabilities in processing graph-structured data.However,GCNs encounter significant challenges when applied to scale-free graphs with power-law distributions,resulting in substantial distortions.Moreover,most of the existing GCN models are shallow structures,which restricts their ability to capture dependencies among distant nodes and more refined high-order node features in scale-free graphs with hierarchical structures.To more broadly and precisely apply GCNs to real-world graphs exhibiting scale-free or hierarchical structures and utilize multi-level aggregation of GCNs for capturing high-level information in local representations,we propose the Hyperbolic Deep Graph Convolutional Neural Network(HDGCNN),an end-to-end deep graph representation learning framework that can map scale-free graphs from Euclidean space to hyperbolic space.In HDGCNN,we define the fundamental operations of deep graph convolutional neural networks in hyperbolic space.Additionally,we introduce a hyperbolic feature transformation method based on identity mapping and a dense connection scheme based on a novel non-local message passing framework.In addition,we present a neighborhood aggregation method that combines initial structural featureswith hyperbolic attention coefficients.Through the above methods,HDGCNN effectively leverages both the structural features and node features of graph data,enabling enhanced exploration of non-local structural features and more refined node features in scale-free or hierarchical graphs.Experimental results demonstrate that HDGCNN achieves remarkable performance improvements over state-ofthe-art GCNs in node classification and link prediction tasks,even when utilizing low-dimensional embedding representations.Furthermore,when compared to shallow hyperbolic graph convolutional neural network models,HDGCNN exhibits notable advantages and performance enhancements.展开更多
Voice portrait technology has explored and established the relationship between speakers’ voices and their facialfeatures, aiming to generate corresponding facial characteristics by providing the voice of an unknown ...Voice portrait technology has explored and established the relationship between speakers’ voices and their facialfeatures, aiming to generate corresponding facial characteristics by providing the voice of an unknown speaker.Due to its powerful advantages in image generation, Generative Adversarial Networks (GANs) have now beenwidely applied across various fields. The existing Voice2Face methods for voice portraits are primarily based onGANs trained on voice-face paired datasets. However, voice portrait models solely constructed on GANs facelimitations in image generation quality and struggle to maintain facial similarity. Additionally, the training processis relatively unstable, thereby affecting the overall generative performance of the model. To overcome the abovechallenges,wepropose a novel deepGenerativeAdversarialNetworkmodel for audio-visual synthesis, namedAVPGAN(Attention-enhanced Voice Portrait Model using Generative Adversarial Network). This model is based ona convolutional attention mechanism and is capable of generating corresponding facial images from the voice ofan unknown speaker. Firstly, to address the issue of training instability, we integrate convolutional neural networkswith deep GANs. In the network architecture, we apply spectral normalization to constrain the variation of thediscriminator, preventing issues such as mode collapse. Secondly, to enhance the model’s ability to extract relevantfeatures between the two modalities, we propose a voice portrait model based on convolutional attention. Thismodel learns the mapping relationship between voice and facial features in a common space from both channeland spatial dimensions independently. Thirdly, to enhance the quality of generated faces, we have incorporated adegradation removal module and utilized pretrained facial GANs as facial priors to repair and enhance the clarityof the generated facial images. Experimental results demonstrate that our AVP-GAN achieved a cosine similarity of0.511, outperforming the performance of our comparison model, and effectively achieved the generation of highqualityfacial images corresponding to a speaker’s voice.展开更多
Objective: Tinnitus-a common clinical symptom-can be categorized into pulsatile tinnitus(PT) and non-PT. Among these, PT is usually associated with sigmoid sinus symptoms, such as sigmoid sinus wall defect or divertic...Objective: Tinnitus-a common clinical symptom-can be categorized into pulsatile tinnitus(PT) and non-PT. Among these, PT is usually associated with sigmoid sinus symptoms, such as sigmoid sinus wall defect or diverticulum, for which various surgical treatments are available. We have discussed the clinical efficacy of surgery for sigmoid sinus-associated PT via the transmastoid approach in this study.Methods: We conducted a retrospective review of 4 patients who underwent surgery for sigmoid sinusassociated PT via the transmastoid approach at Nanjing Drum Tower Hospital from January to December2020. Of these, 2 patients had sigmoid sinus wall defect and 2 had sigmoid sinus diverticulum. Postoperative tinnitus grading and surgical efficacy were determined.Results: After surgery, PT dissolved in 3 patients, while tinnitus significantly decreased in 1 patient.During the follow-up period of 12-18 months, none of the 4 patients showed complications related to increased intracranial pressure or venous sinus thrombosis, and tinnitus symptoms disappeared in 3patients without recurrence, although 1 patient occasionally developed tinnitus. Postoperative thin-slice CTA of the temporal bone indicated that the sigmoid sinus bone wall defect or diverticulum was completely repaired with a thick soft tissue coverage.Conclusion: Surgical repair of sigmoid sinus-associated PT via the transmastoid approach deserves clinical promotion as it exhibited better efficiency while being relatively less invasive.展开更多
To promote the application of edge com-puting in wireless blockchain networks,this paper presents a business ecosystem,where edge comput-ing is introduced to assist blockchain users in imple-menting the mining process...To promote the application of edge com-puting in wireless blockchain networks,this paper presents a business ecosystem,where edge comput-ing is introduced to assist blockchain users in imple-menting the mining process.This paper exploits re-source trading and miner competition to enable se-cure and efficient transactions in the presented busi-ness ecosystem.The resource trading problem is for-mulated as a Stackelberg game between miner candi-dates and edge computing servers,where computing,caching,and communication resources are jointly op-timized to maximize the potential profit.Partial of-floading is introduced to further enhance the system performance when compared with the existing work.We analyze the existence and uniqueness of the Nash equilibrium and Stackelberg equilibrium.Based on the optimization result,winners are selected from the set of miner candidates by bidding and constitute the mining network.Simulation results demonstrate that the proposal is able to improve the social welfare of blockchain miners,thus stimulating more blockchain users to join the mining network.展开更多
The Internet Control Message Protocol(ICMP)covert tunnel refers to a network attack that encapsulates malicious data in the data part of the ICMP protocol for transmission.Its concealment is stronger and it is not eas...The Internet Control Message Protocol(ICMP)covert tunnel refers to a network attack that encapsulates malicious data in the data part of the ICMP protocol for transmission.Its concealment is stronger and it is not easy to be discovered.Most detection methods are detecting the existence of channels instead of clarifying specific attack intentions.In this paper,we propose an ICMP covert tunnel attack intent detection framework ICMPTend,which includes five steps:data collection,feature dictionary construction,data preprocessing,model construction,and attack intent prediction.ICMPTend can detect a variety of attack intentions,such as shell attacks,sensitive directory access,communication protocol traffic theft,filling tunnel reserved words,and other common network attacks.We extract features from five types of attack intent found in ICMP channels.We build a multi-dimensional dictionary of malicious features,including shell attacks,sensitive directory access,communication protocol traffic theft,filling tunnel reserved words,and other common network attack keywords.For the high-dimensional and independent characteristics of ICMP traffic,we use a support vector machine(SVM)as a multi-class classifier.The experimental results show that the average accuracy of ICMPTend is 92%,training ICMPTend only takes 55 s,and the prediction time is only 2 s,which can effectively identify the attack intention of ICMP.展开更多
The recovery and reconstruction of central nervous system function after spinal cord injury(SCI)is a worldwide problem.The difficulty lies in the feasibility issue of new axons passing through the injured area and the...The recovery and reconstruction of central nervous system function after spinal cord injury(SCI)is a worldwide problem.The difficulty lies in the feasibility issue of new axons passing through the injured area and the negative effect of scarring after injury.As a biological material,the human amniotic membrane(HAM)has the advantages of protecting nerve growth,inhibiting scar formation,and promoting neovascularization,but its weak physical properties are difficult to apply in treating SCI.In this study,HAMs were first decellularized and then chemically grafted with methacrylic anhydride.Next,the composite was photocrosslinked with gelatin methacrylate to prepare a cross-network biological complex.The final complexes prepared by appeal were used for in vitro and in vivo studies of SCI in rats,separately.In the in vitro experiment,the composite scaffold inherited abundant biological factors from the amniotic membrane and had the physical properties of a hydrogel,thus providing a favorable environment for the growth and development of neurons and blood vessels.In the in vivo experiment,the composite reduced scarring and promoted the growth of new nerves.Overall,the composite scaffolds can stably simulate the extracellular microenvironment in SCI defects,regulate pathological changes,and promote the generation of new neurons.Therefore,decellularized HAM hydrogels are promising biocomposite materials for central nerve repair after SCI.展开更多
Efficient experiment design is of great significance for the validation of simulation model with high nonlinearity and large input space.Excessive validation experiment raises the cost while insufficient test increase...Efficient experiment design is of great significance for the validation of simulation model with high nonlinearity and large input space.Excessive validation experiment raises the cost while insufficient test increases the risks of accepting an invalid model.In this paper,an adaptive sequential experiment design method combining global exploration criterion and local exploitation criterion is proposed.The exploration criterion utilizes discrepancy metric to improve the space-filling property of the design points while the exploitation criterion employs the leave one out error to discover informative points.To avoid the clustering of samples in the local region,an adaptive weight updating approach is provided to maintain the balance between exploration and exploitation.Besides,the credibility distribution function characterizing the relationship between the input and result credibility is introduced to support the model validation experiment design.Finally,six benchmark problems and an engineering case are applied to examine the performance of the proposed method.The experiments indicate that the proposed method achieves satisfactory performance for function approximation in accuracy and convergence.展开更多
Importance:Pediatric palliative care(PPC)is an interdisciplinary collaboration that focuses on the prevention and relief of patient suffering.PPC has emerged as a critical field of medical expertise and practice.Howev...Importance:Pediatric palliative care(PPC)is an interdisciplinary collaboration that focuses on the prevention and relief of patient suffering.PPC has emerged as a critical field of medical expertise and practice.However,no information is available regarding the progress of PPC in the Chinese mainland.Objective:This study investigated the geographic distribution,team structure,and services of PPC teams in the Chinese mainland.It also investigated the level of understanding and implementation among pediatric oncologists regarding PPC.Methods:The PPC subspecialty group of the Pediatrics Society of the Chinese Medical Association included 45 PPC teams.The team structure and services were investigated using questionnaires mailed to the team leader of each PPC team.In addition,we sent questionnaires regarding the level of PPC understanding and implementation of PPC practices to 170 pediatric oncologists in 11 hospitals.Results:The geographical distribution of PPC teams is uneven in China.Most PPC teams are concentrated in the eastern provincial capital of China.Most PPC teams had limited staff and services.The level of PPC understanding was considerably limited across all demographics;most pediatric oncologists reported“some understanding”(n=71,41.8%)or“poor understanding”(n=50,29.4%).Only 62.9%of pediatric oncologists had experience providing advice to family members regarding PPC matters.Interpretation:China is currently experiencing a critical shortage of PPC resources.Most pediatric oncologists had a limited understanding of PPC and reported limited practical implementation of PPC,which leads to underutilization of PPC resources.展开更多
The widespread application of photodetectors has triggered an urgent need for high-sensitivity and polarization-dependent photodetection.In this field,the two-dimensional(2D)tungsten disulfide(WS_(2))exhibits intrigui...The widespread application of photodetectors has triggered an urgent need for high-sensitivity and polarization-dependent photodetection.In this field,the two-dimensional(2D)tungsten disulfide(WS_(2))exhibits intriguing optical and electronic properties,making it an attractive photosensitive material for optoelectronic applications.However,the lack of an effective built-in electric field and photoconductive gain mechanism in 2D WS_(2)impedes its application in high-performance photodetectors.Herein,we propose a hybrid heterostructure photodetector that contains 1D Te and 2D WS_(2).In this device,1D Te induces in-plane strain in 2D WS_(2),which regulates the electronic structures of local WS_(2)and gives rise to type-Ⅱ band alignment in the horizontal direction.Moreover,the vertical heterojunction built of 2D WS_(2)and 1D Te introduces a high photoconductive gain.Benefiting from these two effects,the transfer of photogenerated carriers is optimized,and the proposed photodetector exhibits high sensitivity(photoresponsivity of ~27.7 A W^(-1),detectivity of 9.5×10^(12)Jones,and short rise/decay time of 19.3/17.6 ms).In addition,anisotropic photodetection characteristics with a dichroic ratio up to 2.1 are achieved.This hybrid 1D/2D heterostructure overcomes the inherent limitations of each material and realizes novel properties,opening up a new avenue towards constructing multifunctional optoelectronic devices.展开更多
基金supported by the National Natural Science Foundation of China-China State Railway Group Co.,Ltd.Railway Basic Research Joint Fund (Grant No.U2268217)the Scientific Funding for China Academy of Railway Sciences Corporation Limited (No.2021YJ183).
文摘Graph Convolutional Neural Networks(GCNs)have been widely used in various fields due to their powerful capabilities in processing graph-structured data.However,GCNs encounter significant challenges when applied to scale-free graphs with power-law distributions,resulting in substantial distortions.Moreover,most of the existing GCN models are shallow structures,which restricts their ability to capture dependencies among distant nodes and more refined high-order node features in scale-free graphs with hierarchical structures.To more broadly and precisely apply GCNs to real-world graphs exhibiting scale-free or hierarchical structures and utilize multi-level aggregation of GCNs for capturing high-level information in local representations,we propose the Hyperbolic Deep Graph Convolutional Neural Network(HDGCNN),an end-to-end deep graph representation learning framework that can map scale-free graphs from Euclidean space to hyperbolic space.In HDGCNN,we define the fundamental operations of deep graph convolutional neural networks in hyperbolic space.Additionally,we introduce a hyperbolic feature transformation method based on identity mapping and a dense connection scheme based on a novel non-local message passing framework.In addition,we present a neighborhood aggregation method that combines initial structural featureswith hyperbolic attention coefficients.Through the above methods,HDGCNN effectively leverages both the structural features and node features of graph data,enabling enhanced exploration of non-local structural features and more refined node features in scale-free or hierarchical graphs.Experimental results demonstrate that HDGCNN achieves remarkable performance improvements over state-ofthe-art GCNs in node classification and link prediction tasks,even when utilizing low-dimensional embedding representations.Furthermore,when compared to shallow hyperbolic graph convolutional neural network models,HDGCNN exhibits notable advantages and performance enhancements.
基金the Double First-Class Innovation Research Projectfor People’s Public Security University of China (No. 2023SYL08).
文摘Voice portrait technology has explored and established the relationship between speakers’ voices and their facialfeatures, aiming to generate corresponding facial characteristics by providing the voice of an unknown speaker.Due to its powerful advantages in image generation, Generative Adversarial Networks (GANs) have now beenwidely applied across various fields. The existing Voice2Face methods for voice portraits are primarily based onGANs trained on voice-face paired datasets. However, voice portrait models solely constructed on GANs facelimitations in image generation quality and struggle to maintain facial similarity. Additionally, the training processis relatively unstable, thereby affecting the overall generative performance of the model. To overcome the abovechallenges,wepropose a novel deepGenerativeAdversarialNetworkmodel for audio-visual synthesis, namedAVPGAN(Attention-enhanced Voice Portrait Model using Generative Adversarial Network). This model is based ona convolutional attention mechanism and is capable of generating corresponding facial images from the voice ofan unknown speaker. Firstly, to address the issue of training instability, we integrate convolutional neural networkswith deep GANs. In the network architecture, we apply spectral normalization to constrain the variation of thediscriminator, preventing issues such as mode collapse. Secondly, to enhance the model’s ability to extract relevantfeatures between the two modalities, we propose a voice portrait model based on convolutional attention. Thismodel learns the mapping relationship between voice and facial features in a common space from both channeland spatial dimensions independently. Thirdly, to enhance the quality of generated faces, we have incorporated adegradation removal module and utilized pretrained facial GANs as facial priors to repair and enhance the clarityof the generated facial images. Experimental results demonstrate that our AVP-GAN achieved a cosine similarity of0.511, outperforming the performance of our comparison model, and effectively achieved the generation of highqualityfacial images corresponding to a speaker’s voice.
基金This study was supported by the National Natural Science Foundation of China(Nos.81870721)the Major Program of National Natural Science Foundation of China(Nos.82192862).
文摘Objective: Tinnitus-a common clinical symptom-can be categorized into pulsatile tinnitus(PT) and non-PT. Among these, PT is usually associated with sigmoid sinus symptoms, such as sigmoid sinus wall defect or diverticulum, for which various surgical treatments are available. We have discussed the clinical efficacy of surgery for sigmoid sinus-associated PT via the transmastoid approach in this study.Methods: We conducted a retrospective review of 4 patients who underwent surgery for sigmoid sinusassociated PT via the transmastoid approach at Nanjing Drum Tower Hospital from January to December2020. Of these, 2 patients had sigmoid sinus wall defect and 2 had sigmoid sinus diverticulum. Postoperative tinnitus grading and surgical efficacy were determined.Results: After surgery, PT dissolved in 3 patients, while tinnitus significantly decreased in 1 patient.During the follow-up period of 12-18 months, none of the 4 patients showed complications related to increased intracranial pressure or venous sinus thrombosis, and tinnitus symptoms disappeared in 3patients without recurrence, although 1 patient occasionally developed tinnitus. Postoperative thin-slice CTA of the temporal bone indicated that the sigmoid sinus bone wall defect or diverticulum was completely repaired with a thick soft tissue coverage.Conclusion: Surgical repair of sigmoid sinus-associated PT via the transmastoid approach deserves clinical promotion as it exhibited better efficiency while being relatively less invasive.
基金This work was supported by National Natural Science Foundation of China(No.62271368,No.62201421)National Natural Science Foundation of Shaanxi Province(No.2021JQ-206)+1 种基金Guangdong Basic and Applied Basic Research Foundation(No.2020A1515110084)China Postdoctoral Science Foundation(No.2018M640960,No.2019T120879).
文摘To promote the application of edge com-puting in wireless blockchain networks,this paper presents a business ecosystem,where edge comput-ing is introduced to assist blockchain users in imple-menting the mining process.This paper exploits re-source trading and miner competition to enable se-cure and efficient transactions in the presented busi-ness ecosystem.The resource trading problem is for-mulated as a Stackelberg game between miner candi-dates and edge computing servers,where computing,caching,and communication resources are jointly op-timized to maximize the potential profit.Partial of-floading is introduced to further enhance the system performance when compared with the existing work.We analyze the existence and uniqueness of the Nash equilibrium and Stackelberg equilibrium.Based on the optimization result,winners are selected from the set of miner candidates by bidding and constitute the mining network.Simulation results demonstrate that the proposal is able to improve the social welfare of blockchain miners,thus stimulating more blockchain users to join the mining network.
基金This research was supported by National Natural Science Foundation of China(Grant Nos.61972048,62072051).
文摘The Internet Control Message Protocol(ICMP)covert tunnel refers to a network attack that encapsulates malicious data in the data part of the ICMP protocol for transmission.Its concealment is stronger and it is not easy to be discovered.Most detection methods are detecting the existence of channels instead of clarifying specific attack intentions.In this paper,we propose an ICMP covert tunnel attack intent detection framework ICMPTend,which includes five steps:data collection,feature dictionary construction,data preprocessing,model construction,and attack intent prediction.ICMPTend can detect a variety of attack intentions,such as shell attacks,sensitive directory access,communication protocol traffic theft,filling tunnel reserved words,and other common network attacks.We extract features from five types of attack intent found in ICMP channels.We build a multi-dimensional dictionary of malicious features,including shell attacks,sensitive directory access,communication protocol traffic theft,filling tunnel reserved words,and other common network attack keywords.For the high-dimensional and independent characteristics of ICMP traffic,we use a support vector machine(SVM)as a multi-class classifier.The experimental results show that the average accuracy of ICMPTend is 92%,training ICMPTend only takes 55 s,and the prediction time is only 2 s,which can effectively identify the attack intention of ICMP.
基金supported by the National Natural Science Foundation of China(No.82371383)。
文摘The recovery and reconstruction of central nervous system function after spinal cord injury(SCI)is a worldwide problem.The difficulty lies in the feasibility issue of new axons passing through the injured area and the negative effect of scarring after injury.As a biological material,the human amniotic membrane(HAM)has the advantages of protecting nerve growth,inhibiting scar formation,and promoting neovascularization,but its weak physical properties are difficult to apply in treating SCI.In this study,HAMs were first decellularized and then chemically grafted with methacrylic anhydride.Next,the composite was photocrosslinked with gelatin methacrylate to prepare a cross-network biological complex.The final complexes prepared by appeal were used for in vitro and in vivo studies of SCI in rats,separately.In the in vitro experiment,the composite scaffold inherited abundant biological factors from the amniotic membrane and had the physical properties of a hydrogel,thus providing a favorable environment for the growth and development of neurons and blood vessels.In the in vivo experiment,the composite reduced scarring and promoted the growth of new nerves.Overall,the composite scaffolds can stably simulate the extracellular microenvironment in SCI defects,regulate pathological changes,and promote the generation of new neurons.Therefore,decellularized HAM hydrogels are promising biocomposite materials for central nerve repair after SCI.
基金supported by the National Natural Science Foundation of China(No.61627810)。
文摘Efficient experiment design is of great significance for the validation of simulation model with high nonlinearity and large input space.Excessive validation experiment raises the cost while insufficient test increases the risks of accepting an invalid model.In this paper,an adaptive sequential experiment design method combining global exploration criterion and local exploitation criterion is proposed.The exploration criterion utilizes discrepancy metric to improve the space-filling property of the design points while the exploitation criterion employs the leave one out error to discover informative points.To avoid the clustering of samples in the local region,an adaptive weight updating approach is provided to maintain the balance between exploration and exploitation.Besides,the credibility distribution function characterizing the relationship between the input and result credibility is introduced to support the model validation experiment design.Finally,six benchmark problems and an engineering case are applied to examine the performance of the proposed method.The experiments indicate that the proposed method achieves satisfactory performance for function approximation in accuracy and convergence.
基金The Special Fund of the Pediatric Medical Coordinated Development Center of Beijing Municipal Administration of Hospitals(No.XTCX201812)Management Research Project of Beijing Children’s Hospital,Capital Medical University(No.YGLQ202001)。
文摘Importance:Pediatric palliative care(PPC)is an interdisciplinary collaboration that focuses on the prevention and relief of patient suffering.PPC has emerged as a critical field of medical expertise and practice.However,no information is available regarding the progress of PPC in the Chinese mainland.Objective:This study investigated the geographic distribution,team structure,and services of PPC teams in the Chinese mainland.It also investigated the level of understanding and implementation among pediatric oncologists regarding PPC.Methods:The PPC subspecialty group of the Pediatrics Society of the Chinese Medical Association included 45 PPC teams.The team structure and services were investigated using questionnaires mailed to the team leader of each PPC team.In addition,we sent questionnaires regarding the level of PPC understanding and implementation of PPC practices to 170 pediatric oncologists in 11 hospitals.Results:The geographical distribution of PPC teams is uneven in China.Most PPC teams are concentrated in the eastern provincial capital of China.Most PPC teams had limited staff and services.The level of PPC understanding was considerably limited across all demographics;most pediatric oncologists reported“some understanding”(n=71,41.8%)or“poor understanding”(n=50,29.4%).Only 62.9%of pediatric oncologists had experience providing advice to family members regarding PPC matters.Interpretation:China is currently experiencing a critical shortage of PPC resources.Most pediatric oncologists had a limited understanding of PPC and reported limited practical implementation of PPC,which leads to underutilization of PPC resources.
基金supported by the National Natural Science Foundation of China(61805044,62004071 and 11674310)the Key Platforms and Research Projects of Department of Education of Guangdong Province(2018KTSCX050)+1 种基金Guangdong Provincial Key Laboratory of Information Photonics Technology(2020B121201011)"The Pearl River Talent Recruitment Program"(2019ZT08X639)。
文摘The widespread application of photodetectors has triggered an urgent need for high-sensitivity and polarization-dependent photodetection.In this field,the two-dimensional(2D)tungsten disulfide(WS_(2))exhibits intriguing optical and electronic properties,making it an attractive photosensitive material for optoelectronic applications.However,the lack of an effective built-in electric field and photoconductive gain mechanism in 2D WS_(2)impedes its application in high-performance photodetectors.Herein,we propose a hybrid heterostructure photodetector that contains 1D Te and 2D WS_(2).In this device,1D Te induces in-plane strain in 2D WS_(2),which regulates the electronic structures of local WS_(2)and gives rise to type-Ⅱ band alignment in the horizontal direction.Moreover,the vertical heterojunction built of 2D WS_(2)and 1D Te introduces a high photoconductive gain.Benefiting from these two effects,the transfer of photogenerated carriers is optimized,and the proposed photodetector exhibits high sensitivity(photoresponsivity of ~27.7 A W^(-1),detectivity of 9.5×10^(12)Jones,and short rise/decay time of 19.3/17.6 ms).In addition,anisotropic photodetection characteristics with a dichroic ratio up to 2.1 are achieved.This hybrid 1D/2D heterostructure overcomes the inherent limitations of each material and realizes novel properties,opening up a new avenue towards constructing multifunctional optoelectronic devices.