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目的 探讨磷脂酰肌醇3激酶/蛋白激酶B（phosphatidylinositol-3-kinase/protein kinase B，PI3K/PKB）信号通路介导脂联素对脑缺血再灌注大鼠的保护作用。 方法 随机将SD大鼠分为假手术组、模型组、脂联素治疗组和PI3K/PKB抑制剂LY294002组（抑制剂组），每组15只。通过线栓法构建大脑中动脉缺血模型，缺血1.5 h后再灌注。脂联素治疗组在再灌注2 h后，给予大鼠尾静脉注射脂联素（180 μg/100 g）；抑制剂组在再灌注2 h后给予大鼠尾静脉注射脂联素（180 μg/100 g）+LY294004（0.03 mg/100 g）；假手术组和模型组尾静脉注射相应体积的0.9%生理盐水（0.09 mL/100 g）。各组缺血再灌注24 h后，检测各组大鼠脑梗死面积和脑含水量；采用Longa 5分法进行神经功能缺损评分；蛋白质印迹法（Western blotting）检测大鼠脑组织PI3K、PKB、磷酸化的蛋白激酶B（phosphorylated PKB，p-PKB）和脂联素蛋白表达水平；酶联免疫吸附（enzyme linked immunosorbent assay，ELISA）法检测大鼠血清丙二醛（malondialdehyde，MDA）和超氧化物歧化酶（superoxide dismutase，SOD）水平。 结果 与假手术组相比，模型组大鼠的脑梗死面积、脑含水量、神经功能缺损评分和MDA水平均升高（均P

同轴晶体管外形（TO）封装的半导体探测器年出货量高达千万只,其质量控制与检测是非常重要的。传统的人工借助显微镜的目视检验因受主观判断和视觉疲劳影响,误检率和漏检率较高。为了解决此问题,文章提出了一种适用于同轴型半导体探测器封前外观自动光学检验（AOI）的方案,运用视觉检测将合格品和不合格品自动识别并分拣,引入景深合成技术实现线弧的高度检测。样机测试结果表明,所提方案具备良好的检测适应性和较低的误检率,适合生产线批量检测任务,可以取代人工目视检验。

针对柔性直流输电系统直流侧故障快速清除的难题，结合南澳多端柔性直流输电工程的实际生产应用需求，提出了一种新型机械式高压直流断路器拓扑方案，研制出了160 kV超快速机械式高压直流断路器产品，提出了一种采用发电机源提供电流来模拟直流故障的开断试验方法，并完成了双向大电流开断试验，开断电流大于9 kA、开断时间小于5 ms。研究并提出了160 kV机械式高压直流断路器工程应用技术方案，并完成南澳加装高压直流断路器示范工程的现场系统调试，试验结果表明其圆满地解决了南澳多端柔性直流系统第三站在线投切和直流线路故障隔离清除的难题，有效地提高了南澳多端柔性直流输电系统的灵活性和可靠性。

基于密集波分复用（DWDM）的光传送网构成了整个通信网络的基础物理层。为了满足DWDM技术的应用和升级,能够进行在线监测的光通道性能模块成为当前很多光器件公司研究和开发的热点。一个典型的在线光性能监测（OPM）模块能够在线监测通道光功率、中心波长及光信噪比（OSNR）等指标。文章系统地阐述了OPM的应用背景、技术特点、性能指标以及发展前景,并对各厂家生产的OPM模块进行了比较分析。

Copyright of Journal of Shaanxi University of Science & Technology is the property of Journal of Shaanxi University of Science & Technology Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To predict the load-displacement hysteresis curves of four-limb concrete-filled steel tubular(CFST)lattice columns under low-cycle reciprocating loading tests, the research employs the sparrow search optimization algorithm(SSA)to optimize the Elman neural network model(SSA-Elman). The performance of SSA is compared with particle swarm optimization(PSO)and firefly algorithm(FA)using five standard test functions. Low-cycle reciprocating loading tests were conducted on four-limb CFST lattice columns to determine their damage patterns and load-displacement hysteresis curves. The obtained test results are utilized for training, prediction, and error analysis of each model. Damage values are calculated and compared between the predicted results of the SSA-Elman model and the test data based on traditional energy damage models and Park's model. The results indicate that the load-displacement hysteresis curves of specimens SCC1 and SCC2 are arched, while specimen SCC3 exhibits an anti-S-shaped curve, and specimen SCC4 shows a shuttle-shaped curve. Comparisons among the five standard test functions reveal that the SSA algorithm outperforms PSO and FA algorithms in terms of search performance, optimization accuracy, convergence speed, and global search ability. The SSA-Elman model demonstrates lower mean absolute percentage error(MAPE)when predicting the seismic performance of the four specimens compared with Elman, PSO-SVR, and FA-BP. The SSA technique effectively optimizes the weights and thresholds of the Elman model. Moreover, the damage values predicted by the SSA-Elman model are consistent with those obtained from the traditional model, suggesting that the SSA-Elman model is suitable for predicting the load-displacement hysteresis curve of four-limb CFST lattice columns under low-cycle reciprocating loading tests. [ABSTRACT FROM AUTHOR]

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Copyright of Chinese Journal of Tissue Engineering Research / Zhongguo Zuzhi Gongcheng Yanjiu is the property of Chinese Journal of Tissue Engineering Research and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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Objective：To analyze the expression of malic enzyme 3 (ME3) in hepatocellular carcinoma (HCC) tissues and celllines, and explore the effects of ME3 on the proliferation, migration, and invasion of HCC cells, as well as its underlying mechanism. Methods：The Cancer Genome Atlas (TCGA) database was used to study the expression of ME3 in HCC tissues. RT - qPCR and Western blot were performed to detect the mRNA and protein expression levels of ME3 in HCC cells. After knocking down or over expressing ME3 in HCC cell lines, the effects of ME3 on the proliferation, migration and invasion of HCC cells were detected by CCK-8 assay, colony formation assay, transwell assay, and invasion assay. Western blot was used to detect the expression of proteins related to the PI3K/AKT signaling pathway. Results：Compared with adjacent normal tissues and normal liver celline, ME3 was significantly up-regulated in HCC tissues and cell lines. Knockdown of ME3 markedly inhibited the ability of proliferation, migration and invasion of HCC cells, while overexpression of ME3 resulted in the opposite effects. Furthermore, we found that the activity of PI3K/AKT signaling pathway was significantly activated by ME3. Conclusion：ME3 is highly expressed in HCC tissues, promoting the proliferation, migration and invasion of HCC cells, and may function as an oncogene in HCC by activating the PI3K/AKT signaling pathway． [ABSTRACT FROM AUTHOR]

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Copyright of Journal of New Medicine is the property of Sun Yat Sen University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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Sparse matrix vector multiplication (SpMV) is of great significance in the solution of linear systems, and is one of the core problems in scientific computing and engineering practice. Its performance highly depends on the non-zero distribution of sparse matrices. Sparse diagonal matrices are a special type of sparse matrices, whose non-zero elements are densely arranged in the form of diagonals. For sparse diagonal matrices, scholars have proposed various storage formats on the GPU platform, which have improved SpMV performance, but still suffer from zero padding and load imbalance issues. To address these issues, a DRM (Divide-Rearrange & Merge) storage format is proposed. This format uses matrix partitioning strategies based on fixed threshold values and matrix reconstruction strategies based on iterative merging to achieve sparse zero padding and load balancing between blocks. Experimental results show that on the NVIDIA􀆿 Tesla􀆿 V100 platform, compared to DIA, HDC, HDIA, and DIA-Adaptive formats, the time performance is accelerated by 20.76, 1.94, 1.13, and 2.26 times, respectively, and the floating point performance is improved by 1.54, 5.28, 1.13, and 1.94 times, respectively. [ABSTRACT FROM AUTHOR]

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Artificial intelligence-driven dialogue is a current research hotspot with a wide range of promising applications. However, such dialogue systems currently generally lack emotional interaction capabilities, limiting their application in psychological care, depression and other mental disorders. How to make dialogue systems fully understand users’ emotions and generate responses with empathy is one of the main challenges facing dialogue systems today. This paper first introduces two major challenges in empathic dialogue research: emotion perception and empathic dialogue generation, and summarises the relevant research methods in separate studies. Emotion perception tasks can be broadly classified into rule-based, machine-learning and deep-learning approaches, while empathic dialogue generation can be broadly classified into retrieval-based and dynamic generation-based approaches. The latest developments in empathic dialogue are then introduced, and the features and links of empathic dialogue datasets, generic dialogue datasets and multimodal datasets are summarised, and different evaluation methods in current empathic dialogue research are summarised to facilitate subsequent research. Finally, a summary and outlook of the research work on empathic dialogue is presented. [ABSTRACT FROM AUTHOR]

Copyright of Acta Scientiarum Naturalium Universitatis Sunyatseni / Zhongshan Daxue Xuebao is the property of Sun-Yat-Sen University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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Copyright of Journal of Capital Institute of Physical Education is the property of Shoudu Tiyu Xueyuan and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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An OpenFOAM-based solver for spray combustion simulation with the large eddy simulation (LES) and the flamelet generated manifold (FGM) method, was developed. A simple reduction of the temperature was employed to account for the evaporative heat loss. The solver was firstly validated against the Sydney piloted ethanol spray flame benchmark EtF7. The predicted mean gas temperature and droplet statistics correspond well with the experimental data and have similar accuracy to the spray flamelet model. The turbulence-chemistry interaction modeling may have a larger influence on the simulation accuracy. Then a realistic gas turbine slinger combustor was simulated with 2 sets of operating conditions. The simulation results reveal different flame characteristics of the 2 working conditions. The predicted total pressure losses are close to the measured values. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Zhejiang University (Science Edition) is the property of Journal of Zhejiang University (Science Edition) Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)