Social Radars: Finding Targets in Cyberspace for Cybersecurity

INSPIRED by the insight from American political scientist Lasswell, who summarized the environmental role in societal surveillance [1], Schramm coined the term “social radar” [2] as it resembles the activities of radar in collecting and processing information, playing a crucial role in helping humans perceive changes in the internal and external environment and promptly adjusting adaptive behaviors.

EDSUCh:A robust ensemble data summarization method for effective medical diagnosis

Identifying rare patterns for medical diagnosis is a challenging task due to heterogeneity and the volume of data.Data summarization can create a concise version of the original data that can be used for effective diagnosis.In this paper,we propose an ensemble summarization method that combines clustering and sampling to create a summary of the original data to ensure the inclusion of rare patterns.To the best of our knowledge,there has been no such technique available to augment the performance of anomaly detection techniques and simultaneously increase the efficiency of medical diagnosis.The performance of popular anomaly detection algorithms increases significantly in terms of accuracy and computational complexity when the summaries are used.Therefore,the medical diagnosis becomes more effective,and our experimental results reflect that the combination of the proposed summarization scheme and all underlying algorithms used in this paper outperforms the most popular anomaly detection techniques.

Video Summarization Approach Based on Binary Robust Invariant Scalable Keypoints and Bisecting K-Means

Due to the exponential growth of video data,aided by rapid advancements in multimedia technologies.It became difficult for the user to obtain information from a large video series.The process of providing an abstract of the entire video that includes the most representative frames is known as static video summarization.This method resulted in rapid exploration,indexing,and retrieval of massive video libraries.We propose a framework for static video summary based on a Binary Robust Invariant Scalable Keypoint(BRISK)and bisecting K-means clustering algorithm.The current method effectively recognizes relevant frames using BRISK by extracting keypoints and the descriptors from video sequences.The video frames’BRISK features are clustered using a bisecting K-means,and the keyframe is determined by selecting the frame that is most near the cluster center.Without applying any clustering parameters,the appropriate clusters number is determined using the silhouette coefficient.Experiments were carried out on a publicly available open video project(OVP)dataset that contained videos of different genres.The proposed method’s effectiveness is compared to existing methods using a variety of evaluation metrics,and the proposed method achieves a trade-off between computational cost and quality.

Adaptive Graph Convolutional Adjacency Matrix Network for Video Summarization

Video summarization aims to select key frames or key shots to create summaries for fast retrieval,compression,and efficient browsing of videos.Graph neural networks efficiently capture information about graph nodes and their neighbors,but ignore the dynamic dependencies between nodes.To address this challenge,we propose an innovative Adaptive Graph Convolutional Adjacency Matrix Network(TAMGCN),leveraging the attention mechanism to dynamically adjust dependencies between graph nodes.Specifically,we first segment shots and extract features of each frame,then compute the representative features of each shot.Subsequently,we utilize the attention mechanism to dynamically adjust the adjacency matrix of the graph convolutional network to better capture the dynamic dependencies between graph nodes.Finally,we fuse temporal features extracted by Bi-directional Long Short-Term Memory network with structural features extracted by the graph convolutional network to generate high-quality summaries.Extensive experiments are conducted on two benchmark datasets,TVSum and SumMe,yielding F1-scores of 60.8%and 53.2%,respectively.Experimental results demonstrate that our method outperforms most state-of-the-art video summarization techniques.

Enhanced Topic-Aware Summarization Using Statistical Graph Neural Networks

The rapid expansion of online content and big data has precipitated an urgent need for efficient summarization techniques to swiftly comprehend vast textual documents without compromising their original integrity.Current approaches in Extractive Text Summarization(ETS)leverage the modeling of inter-sentence relationships,a task of paramount importance in producing coherent summaries.This study introduces an innovative model that integrates Graph Attention Networks(GATs)with Transformer-based Bidirectional Encoder Representa-tions from Transformers(BERT)and Latent Dirichlet Allocation(LDA),further enhanced by Term Frequency-Inverse Document Frequency(TF-IDF)values,to improve sentence selection by capturing comprehensive topical information.Our approach constructs a graph with nodes representing sentences,words,and topics,thereby elevating the interconnectivity and enabling a more refined understanding of text structures.This model is stretched to Multi-Document Summarization(MDS)from Single-Document Summarization,offering significant improvements over existing models such as THGS-GMM and Topic-GraphSum,as demonstrated by empirical evaluations on benchmark news datasets like Cable News Network(CNN)/Daily Mail(DM)and Multi-News.The results consistently demonstrate superior performance,showcasing the model’s robustness in handling complex summarization tasks across single and multi-document contexts.This research not only advances the integration of BERT and LDA within a GATs but also emphasizes our model’s capacity to effectively manage global information and adapt to diverse summarization challenges.

Intuitive Human-Robot-Environment Interaction With EMG Signals:A Review

A long history has passed since electromyography(EMG)signals have been explored in human-centered robots for intuitive interaction.However,it still has a gap between scientific research and real-life applications.Previous studies mainly focused on EMG decoding algorithms,leaving a dynamic relationship between the human,robot,and uncertain environment in real-life scenarios seldomly concerned.To fill this gap,this paper presents a comprehensive review of EMG-based techniques in human-robot-environment interaction(HREI)systems.The general processing framework is summarized,and three interaction paradigms,including direct control,sensory feedback,and partial autonomous control,are introduced.EMG-based intention decoding is treated as a module of the proposed paradigms.Five key issues involving precision,stability,user attention,compliance,and environmental awareness in this field are discussed.Several important directions,including EMG decomposition,robust algorithms,HREI dataset,proprioception feedback,reinforcement learning,and embodied intelligence,are proposed to pave the way for future research.To the best of what we know,this is the first time that a review of EMG-based methods in the HREI system is summarized.It provides a novel and broader perspective to improve the practicability of current myoelectric interaction systems,in which factors in human-robot interaction,robot-environment interaction,and state perception by human sensations are considered,which has never been done by previous studies.

SHEL:a semantically enhanced hardware-friendly entity linking method

With the help of pre-trained language models,the accuracy of the entity linking task has made great strides in recent years.However,most models with excellent performance require fine-tuning on a large amount of training data using large pre-trained language models,which is a hardware threshold to accomplish this task.Some researchers have achieved competitive results with less training data through ingenious methods,such as utilizing information provided by the named entity recognition model.This paper presents a novel semantic-enhancement-based entity linking approach,named semantically enhanced hardware-friendly entity linking(SHEL),which is designed to be hardware friendly and efficient while maintaining good performance.Specifically,SHEL's semantic enhancement approach consists of three aspects:(1)semantic compression of entity descriptions using a text summarization model;(2)maximizing the capture of mention contexts using asymmetric heuristics;(3)calculating a fixed size mention representation through pooling operations.These series of semantic enhancement methods effectively improve the model's ability to capture semantic information while taking into account the hardware constraints,and significantly improve the model's convergence speed by more than 50%compared with the strong baseline model proposed in this paper.In terms of performance,SHEL is comparable to the previous method,with superior performance on six well-established datasets,even though SHEL is trained using a smaller pre-trained language model as the encoder.

Preliminary Reflections on the Establishment of a New Energy System for the Achievement of Dual Carbon Goals

China has pledged to the world to achieve carbon peak in 10 years and carbon neutrality in 30 years.This is an extremely arduous task,as it faces numerous challenges,including high energy consumption,heavy reliance on coal within its energy mix,and a large base of carbon emissions that must be controlled.To this end,it is necessary to advance the new energy security strategy of“Four Revolutions,One Cooperation”to a deeper level.According to interpretations from various parties,the new energy system is preliminarily summarized to have six features:new energy structure,new system form,new industrial system,new governance system,new system and mechanism,and new regulatory method.Considering building a new energy system comprehensively,“Ten Commitments”have been proposed to help achieve the dual-carbon goals.The specific measures include:ensuring the security and stability of energy supply,accelerating the transformation to green and low-carbon energy,giving priority to energy conservation and efficiency improvement,promoting multi-energy complementation and synergistic and integrated development,enhancing the digital intelligence level in the energy industry,developing centralized and distributed energy,advancing the rural energy revolution,developing critical and core technological equipment and the comprehensive energy service industry,and promoting high-quality development of the Belt and Road Initiative.

卫拉特方言语法研究综述

Oirat dialect is a unique Mongolian dialect,having its own writing system.This paper analyzed the grammatical research of the Oirat dialect,and summarized the achievements and existing problems of previous studies,and provided suggestions about strengthening comprehensive in-depth study of morphology,syntax and word formation in this Mongolian dialect.

Current Research Status of Traditional Chinese Medicine External Treatment for Diarrhea Type Irritable Bowel Syndrome

Irritable bowel syndrome(IBS-D)with diarrhea is a common gastrointestinal functional disease in clinical practice,which seriously affects the quality of life of patients.Cur‐rently,Western medicine has poor therapeutic effects,while traditional Chinese medi‐cine has unique advantages in relieving IBS-D symptoms and preventing recurrence.In recent years,especially with external treatment of traditional Chinese medicine,it has become a new treatment direction in clinical practice and has achieved good therapeutic effects.This article will provide a review of recent research on the treatment of IBS-D using traditional Chinese medicine external treatment methods.

CRETACEOUS-TERTIARY DESERTS IN SOUTHWESTERN CHINA AND DESERT SEDIMENTOLOGY

The special issue deals with the Cretaceous-Tertiary deserts in southwestern China and relevant sedimentological problems about deserts. The study area is located between 101°10＇- 107°00＇E and 28°00＇-30°40′ N. The ancient desert study is so little in China that there has not been a systematic report about it up to now. Based on the study in many ways on Cretaceous-Tertiary deserts in southwestern China, plentiful data have been obtained. Though it is still a bit rough, the study is a good beginning of the ancient desert study in China. The main ideas and conclusions are summarized as follows.

Opportunities and Challenges for Chinese Enterprises ──Viewpoints from Foreign Counterparts at Chinese Enterprises' Summit Meeting 2000

This paper is summarized from the speeches given by foreign entrepreneurs at Chinese Enterprises’ Summit Meeting 2000. In the paper, the entrepreneurs set forth the opportunities for Chinese enterprises and the existing problems from several aspects as globalization of China, influence of WTO, as well as financial reform and capital market opening, etc.

PROGRESS OF LIMNOLOGY IN CHINA

The following six aspects in the utilization of lake resources and progress of limnological research in China are described : 1 . Expeditions for comprehensive investigation of lakes ; 2 . Physical limnology; 3 . Lacustrine sedimentology and paleolimnology ; 4 . Hydrobiology and ecology ; 5 . Hydrochemistry and environmental protection; 6 . Development and utilization of lake resources.

Advances in regenerative medicine applications of tetrahedral framework nucleic acid-based nanomaterials: an expert consensus recommendation

With the emergence of DNA nanotechnology in the 1980s, self-assembled DNA nanostructures have attracted considerable attention worldwide due to their inherent biocompatibility, unsurpassed programmability, and versatile functions. Especially promising nanostructures are tetrahedral framework nucleic acids(t FNAs), first proposed by Turberfield with the use of a one-step annealing approach. Benefiting from their various merits, such as simple synthesis, high reproducibility, structural stability, cellular internalization, tissue permeability, and editable functionality, t FNAs have been widely applied in the biomedical field as threedimensional DNA nanomaterials. Surprisingly, t FNAs exhibit positive effects on cellular biological behaviors and tissue regeneration,which may be used to treat inflammatory and degenerative diseases. According to their intended application and carrying capacity,t FNAs could carry functional nucleic acids or therapeutic molecules through extended sequences, sticky-end hybridization,intercalation, and encapsulation based on the Watson and Crick principle. Additionally, dynamic t FNAs also have potential applications in controlled and targeted therapies. This review summarized the latest progress in pure/modified/dynamic t FNAs and demonstrated their regenerative medicine applications. These applications include promoting the regeneration of the bone,cartilage, nerve, skin, vasculature, or muscle and treating diseases such as bone defects, neurological disorders, joint-related inflammatory diseases, periodontitis, and immune diseases.

AUTOMATIC TEXT SUMMARIZATION BASED ON TEXTUAL COHESION

This paper presents two different algorithms that derive the cohesion structure in the form of lexical chains from two kinds of language resources HowNet and TongYiCiCiLin. The re-search that connects the cohesion structure of a text to the derivation of its summary is displayed. A novel model of automatic text summarization is devised,based on the data provided by lexical chains from original texts. Moreover,the construction rules of lexical chains are modified accord-ing to characteristics of the knowledge database in order to be more suitable for Chinese summa-rization. Evaluation results show that high quality indicative summaries are produced from Chi-nese texts.

Cancer vaccines: prospects and problems

Cytokines provided locally at tbe tumor site mayinitiate an effective anti-tumor immune responsewhich leads to rejection of a tumor which otherwisegrows progressively. Experimentillly, this can betested by gene transfer into cultured tumor cellsfollowed by the analysis of the tumorigenicity of suchgenetically engincered cells. This approach allows

Mechanisms and regulation of organic acid accumulation in plant vacuoles

In fleshy fruits,organic acids are the main source of fruit acidity and play an important role in regulating osmotic pressure,pH homeostasis,stress resistance,and fruit quality.The transport of organic acids from the cytosol to the vacuole and their storage are complex processes.A large number of transporters carry organic acids from the cytosol to the vacuole with the assistance of various proton pumps and enzymes.However,much remains to be explored regarding the vacuolar transport mechanism of organic acids as well as the substances involved and their association.In this review,recent advances in the vacuolar transport mechanism of organic acids in plants are summarized from the perspectives of transporters,channels,proton pumps,and upstream regulators to better understand the complex regulatory networks involved in fruit acid formation.

Immunomodulatory effects and mechanisms of distraction osteogenesis

Distraction osteogenesis(DO) is widely used for bone tissue engineering technology. Immune regulations play important roles in the process of DO like other bone regeneration mechanisms. Compared with others, the immune regulation processes of DO have their distinct features. In this review, we summarized the immune-related events including changes in and effects of immune cells, immune-related cytokines, and signaling pathways at different periods in the process of DO. We aim to elucidated our understanding and unknowns about the immunomodulatory role of DO. The goal of this is to use the known knowledge to further modify existing methods of DO, and to develop novel DO strategies in our unknown areas through more detailed studies of the work we have done.

Thermal Stability of High Power 26650-Type Cylindrical Na-Ion Batteries

As a new electrochemical power system,safety(especially thermal safety)of Na-ion batteries(NIBs)is the key towards large-scale industrialization and market application.Thus,research on the thermal stability of NIBs is helpful to evaluate the safety properties and to provide effective strategies to prevent the occurrence of battery safety failure.Thermal stability of the high-power 26650 cylindrical NIBs using Cu-based layered oxide cathode and hard carbon anode is studied.The high power NIBs can achieve fast charge and discharge at 5–10 C rate and maintain 80%capacity after 4729 cycles at 2 C/2 C rate,where the unit C denotes a measure of the rate at which a battery is charge-discharged relative to its maximum capacity.The results of accelerating rate calorimeter and differential scanning calorimetry(ARC-DSC)test results show that NIBs have a higher initial decomposition temperature(≥110℃)and a lower maximum thermal runaway temperature(≤350℃)than those of Li-ion batteries(LIBs),exhibiting a favorable thermal stability.It should be noted that the heat generation of cathode accounts for a large proportion of the total heat generation while the thermal stability of the anode determines the initial thermal runaway temperature,which is similar to LIBs.Finally,the whole temperature characteristics of the NIBs in the range of−60℃–1000℃are summarized,which provide guidance for the safety design and applications of NIBs.

Using LSA and text segmentation to improve automatic Chinese dialogue text summarization

Automatic Chinese text summarization for dialogue style is a relatively new research area. In this paper, Latent Semantic Analysis （LSA） is first used to extract semantic knowledge from a given document, all question paragraphs are identified, an automatic text segmentation approach analogous to Text＇filing is exploited to improve the precision of correlating question paragraphs and answer paragraphs, and finally some ＂important＂ sentences are extracted from the generic content and the question-answer pairs to generate a complete summary. Experimental results showed that our approach is highly efficient and improves significantly the coherence of the summary while not compromising informativeness.