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| 1 | Impulsivity-related right superior frontal gyrus as a biomarker of internet gaming disorder显示文摘Background Internet gaming disorder(IGD)is a mental health issue that affects individuals worldwide.However,the lack of knowledge about the biomarkers associated with the development of IGD has restricted the diagnosis and treatment of this disorder.Aims We aimed to reveal the biomarkers associated with the development of IGD through resting-state brain network analysis and provide clues for the diagnosis and treatment of IGD.Methods Twenty-six patients with IGD,23 excessive internet game users(EIUs)who recurrently played internet games but were not diagnosed with IGD and 29 healthy controls(HCs)performed delay discounting task(DDT)and Iowa gambling task(IGT).Resting-state functional magnetic resonance imaging(fMRI)data were also collected.Results Patients with IGD exhibited significantly lower hubness in the right medial orbital part of the superior frontal gyrus(ORBsupmed)than both the EIU and the HC groups.Additionally,the hubness of the right ORBsupmed was found to be positively correlated with the highest excessive internet gaming degree during the past year in the EIU group but not the IGD group;this might be the protective mechanism that prevents EIUs from becoming addicted to internet games.Moreover,the hubness of the right ORBsupmed was found to be related to the treatment outcome of patients with IGD,with higher hubness of this region indicating better recovery when undergoing forced abstinence.Further modelling analysis of the DDT and IGT showed that patients with IGD displayed higher impulsivity during the decision-making process,and impulsivity-related parameters were negatively correlated with the hubness of right ORBsupmed.Conclusions Our findings revealed that the impulsivity-related right ORBsupmed hubness could serve as a potential biomarker of IGD and provide clues for the diagnosis and treatment of IGD. | Pengyu Zhang Yu Pan Rujing Zha Hongwen Song Cunfeng Yuan Qian Zhao Yi Piao Jiecheng Ren Yijun Chen Peipeng Liang Ran Tao Zhengde Wei Xiaochu Zhang | 2023 | General Psychiatry2023，36，4： | 1 |
| 2 | Research on Real-Time High Reliable Network File Distribution Technology显示文摘The rapid development of Internet of Things(IoT)technology has made previously unavailable data available,and applications can take advantage of device data for people to visualize,explore,and build complex analyses.As the size of the network and the number of network users continue to increase,network requests tend to aggregate on a small number of network resources,which results in uneven load on network requests.Real-time,highly reliable network file distribution technology is of great importance in the Internet of Things.This paper studies real-time and highly reliable file distribution technology for large-scale networks.In response to this topic,this paper studies the current file distribution technology,proposes a file distribution model,and proposes a corresponding load balancing method based on the file distribution model.Experiments show that the system has achieved real-time and high reliability of network transmission. | Chenglong Li Peipeng Liu Hewei Yu Mengmeng Ge Xiangzhan Yu Yi Xin Yuhang Wang Dongyu Zhang | 2020 | Computers, Materials & Continua2020，，11： | 0 |
| 3 | An Application Review of Artificial Intelligence in Prevention and Cure of COVID-19 Pandemic显示文摘Coronaviruses are a well-known family of viruses that can infect humans or animals.Recently,the new coronavirus(COVID-19)has spread worldwide.All countries in the world are working hard to control the coronavirus disease.However,many countries are faced with a lack of medical equipment and an insufficient number of medical personnel because of the limitations of the medical system,which leads to the mass spread of diseases.As a powerful tool,artificial intelligence(AI)has been successfully applied to solve various complex problems ranging from big data analysis to computer vision.In the process of epidemic control,many algorithms are proposed to solve problems in various fields of medical treatment,which is able to reduce the workload of the medical system.Due to excellent learning ability,AI has played an important role in drug development,epidemic forecast,and clinical diagnosis.This research provides a comprehensive overview of relevant research on AI during the outbreak and helps to develop new and more powerful methods to deal with the current pandemic. | Peipeng Yu Zhihua Xia Jianwei Fei Sunil Kumar Jha | 2020 | Computers, Materials & Continua2020，，10： | 0 |
| 4 | QDCT Encoding-Based Retrieval for Encrypted JPEG Images显示文摘A privacy-preserving search model for JPEG images is proposed in paper,which uses the bag-of-encrypted-words based on QDCT(Quaternion Discrete Cosine Transform)encoding.The JPEG image is obtained by a series of steps such as DCT(Discrete Cosine Transform)transformation,quantization,entropy coding,etc.In this paper,we firstly transform the images from spatial domain into quaternion domain.By analyzing the algebraic relationship between QDCT and DCT,a QDCT quantization table and QDTC coding for color images are proposed.Then the compressed image data is encrypted after the steps of block permutation,intra-block permutation,single table substitution and stream cipher.At last,the similarity between original image and query image can be measured by the Manhattan distance,which is calculated by two feature vectors with the model of bag-of-words on the cloud server side.The outcome shows good performance in security attack and retrieval accuracy. | Qiuju Ji Peipeng Yu Zhihua Xia | 2020 | Journal on Big Data2020，2，1： | 0 |
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