An End-To-End Hyperbolic Deep Graph Convolutional Neural Network Framework

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.

Attention-Enhanced Voice Portrait Model Using Generative Adversarial Network

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.

Surgical treatment of pulsatile tinnitus related to the sigmoid sinus

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.

Resource Trading and Miner Competition in Wireless Blockchain Networks with Edge Computing

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.

ICMPTend: Internet Control Message Protocol Covert Tunnel Attack Intent Detector

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.

中国特色社会主义监狱理论体系研究

中国特色社会主义监狱理论制度是中国特色社会主义监狱制度的重要组成部分,深入研究中国特色社会主义监狱理论制度体系在当前尤为重要和必要。当前,应从加强和增进中国特色社会主义监狱理论制度的深度和厚度,进一步凸显中国特色社会主义监狱理论制度的文化元素和文化传承,整合和构建中国特色社会主义监狱理论制度的学术理论体系、人才培养体系、专业教材体系,全面拓展和创新中国特色社会主义监狱理论制度等四个方面加以完善和提高。

论文化改造

将文化改造明确列入"五大改造"新格局中,是新时代监狱工作改造手段的新表述、新概括、新发展。然而,如何对文化改造进行科学诠释,其本质内涵又该如何揭示,怎样发挥文化改造的价值和功能无疑是当前首先必须回答的现实问题。而要落实文化改造,需要从文化改造的含义、文化改造的意义、文化改造的内容和文化改造的实现四个方面进行全面阐述,以服务于当前我国监狱的文化改造工作和罪犯改造事业。

An adaptive sequential experiment design method for model validation

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.

Hybrid 1D/2D heterostructure with electronic structure engineering toward high-sensitivity and polarization-dependent photodetector

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.

Development levels of pediatric palliative care teams and the extent of palliative care understanding and implementation among pediatric oncologists in China

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.

社区矫正公益活动的发展进路、时代价值及主要功能

社区矫正公益活动经历了公益劳动、社区服务、公益活动的发展进程。目前社区矫正公益活动具有以下时代价值:适应了建设社会主义法治国家的根本目标;顺应了推进国家治理体系和治理能力现代化的根本要求;是中国特色社区矫正制度的具体体现;是中国非监禁刑罚执行制度的发展方向和重要的执法载体。社区矫正公益活动的主要功能有:思想转化功能;灵魂净化功能;关系修复功能;特长发挥功能;恶习矫正功能;心理调适功能。