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        Research on Model of Micro-grid Green Power Transaction Based on Blockchain Technology and Double Auction Mechanism

        Zhao Wenhui,Zhang Shaochong,Xue Lei,Chang Tao,Wang Liao 대한전기학회 2024 Journal of Electrical Engineering & Technology Vol.19 No.1

        The confict between climate change and energy scarcity has recently gained widespread attention. The development and promotion of green power and renewable energy is an efcient strategy to address this issue. The widespread use of distributed renewable energy in microgrids results in decentralized power supply. The features of distributed power trading, such as low single transaction volume and frequent transaction intervals, present both possibilities and problems to the green electricity market. The usual centralized control and selling of power are no longer appropriate in this circumstance. This study proposes a decentralized energy transaction system architecture in the microgrid and connects the double auction mechanism to achieve the interests of each participant based on blockchain technology and the status quo green power trade in China. Finally, using the trading strategy and model, this study constructs a real and operational energy trading platform, and simulated experiments demonstrate the dependability and efcacy of the proposed trading mechanism.

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        Deep Learning-Enhanced Hand Grip and Release Test for Degenerative Cervical Myelopathy: Shortening Assessment Duration to 6 Seconds

        Yongyu Ye,Yunbing Chang,Weihao Wu,Tianying Liao,Tao Yu,Chong Chen,Zhengran Yu,Junying Chen,Guoyan Liang 대한척추신경외과학회 2024 Neurospine Vol.21 No.1

        Objective: Hand clumsiness and reduced hand dexterity can signal early signs of degenerative cervical myelopathy (DCM). While the 10-second grip and release (10-s G&R) test is a common clinical tool for evaluating hand function, a more accessible method is warranted. This study explores the use of deep learning-enhanced hand grip and release test (DL-HGRT) for predicting DCM and evaluates its capability to reduce the duration of the 10-s G&R test. Methods: The retrospective study included 508 DCM patients and 1,194 control subjects. Propensity score matching (PSM) was utilized to minimize the confounding effects related to age and sex. Videos of the 10-s G&R test were captured using a smartphone application. The 3D-MobileNetV2 was utilized for analysis, generating a series of parameters. Additionally, receiver operating characteristic curves were employed to assess the performance of the 10-s G&R test in predicting DCM and to evaluate the effectiveness of a shortened testing duration. Results: Patients with DCM exhibited impairments in most 10-s G&R test parameters. Before PSM, the number of cycles achieved the best diagnostic performance (area under the curve [AUC], 0.85; sensitivity, 80.12%; specificity, 74.29% at 20 cycles), followed by average grip time. Following PSM for age and gender, the AUC remained above 0.80. The average grip time achieved the highest AUC of 0.83 after 6 seconds, plateauing with no significant improvement in extending the duration to 10 seconds, indicating that 6 seconds is an adequate timeframe to efficiently evaluate hand motor dysfunction in DCM based on DLHGRT. Conclusion: DL-HGRT demonstrates potential as a promising supplementary tool for predicting DCM. Notably, a testing duration of 6 seconds appears to be sufficient for accurate assessment, enhancing the test more feasible and practical without compromising diagnostic performance.

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        Isolation and phylogenetic analysis of hemagglutinin gene of H9N2 influenza viruses from chickens in South China from 2012 to 2013

        Han-Qin Shen,Zhuan-Qiang Yan,Fan-Gui Zeng,Chang-Tao Liao,Qing-Feng Zhou,Jian-Ping Qin,Qingmei Xie,Yingzuo Bi,Feng Chen 대한수의학회 2015 Journal of Veterinary Science Vol.16 No.3

        As part of our ongoing influenza surveillance program in South China, 19 field strains of H9N2 subtype avian influenza viruses (AIVs) wereisolated from dead or diseased chicken flocks in Guangdong province, South China, between 2012 and 2013. Hemagglutinin (HA) genes ofthese strains were sequenced and analyzed and phylogenic analysis showed that 12 of the 19 isolates belonged to the lineage h9.4.2.5, whilethe other seven belonged to h9.4.2.6. Specifically, we found that all of the viruses isolated in 2013 belonged to lineage h9.4.2.5. The lineageh9.4.2.5 viruses contained a PSRSSR↓GLF motif at HA cleavage site, while the lineage h9.4.2.6 viruses contained a PARSSR↓GLF at thesame position. Most of the isolates in lineage h9.4.2.5 lost one potential glycosylation site at residues 200–202, and had an additional oneat residues 295–297 in HA1. Notably, 19 isolates had an amino acid exchange (Q226L) in the receptor binding site, which indicated that theviruses had potential affinity of binding to human like receptor. The present study shows the importance of continuing surveillance of newH9N2 strains to better prepare for the next epidemic or pandemic outbreak of H9N2 AIV infections in chicken flocks.

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