E7766, a Macrocycle-Bridged Stimulator of Interferon Genes (STING) Agonist with Potent Pan-Genotypic Activity

A strategy for creating potent and pan-genotypic stimulator of interferon genes (STING) agonists is described. Locking a bioactive U-shaped conformation of cyclic dinucleotides by introducing a transannular macrocyclic bridge between the nucleic acid bases leads to a topologically novel macrocycle-bridged STING agonist (MBSA). In addition to substantially enhanced potency, the newly designed MBSAs, exemplified by clinical candidate E7766 , exhibit broad pan-genotypic activity in all major human STING variants. E7766 is shown to have potent antitumor activity with long lasting immune memory response in a mouse liver metastatic tumor model. Two complementary stereoselective synthetic routes to E7766 are also described.     

Phase composition,microstructure and thermophysical properties of the Srx(Zr0.9Y0.05Yb0.05)O1.95+x ceramics

Sr_x(Zr_0.9Y_0.05Yb_0.05)O_1.95+x (x=1.0, 0.9, 0.8, 0.7) ceramics were prepared by solid state reaction sintering. The sintered Sr_1.0(Zr_0.9Y_0.05Yb_0.05)O_2.95 is a single-phase solid solution while the sintered Sr_x(Zr_0.9Y_0.05Yb_0.05)O_1.95+x (x=0.9?0.7) are composites, and a significant grain growth inhibition is observed in the sintered Sr_x(Zr_0.9Y_0.05Yb_0.05)O_1.95+x (x=1.0, 0.9). Rare-earth elements distribution in the bulk materials indicates that Yb and Y preferentially substitute Zr-sites in SrZrO₃, and the highest solubility of RE₂O₃ in pure SrZrO₃ is ～0.8 mol%. The sintered Sr_x(Zr_0.9Y_0.05Yb_0.05)O_1.95+x have high thermal expansion coefficients up to ～11.0×10^?6 K^-1 (1200°C). Sr_0.8(Zr_0.9Y_0.05Yb_0.05)O_2.75 has the lowest thermal conductivity of 1.38 W·m^-1·K^-1 at 800°C. Sr_x(Zr_0.9Y_0.05Yb_0.05)O_1.95+x (x=1.0, 0.9, 0.8) show no phase transition from 600 to 1400°C, whereas Sr_x(Zr_0.9Y_0.05Yb_0.05)O_1.95+x (x=0.9, 0.8) have excellent high-temperature phase stability over the whole investigated temperature range. Therefore, Sr_x(Zr_0.9Y_0.05Yb_0.05)O_1.95+x (x=1.0, 0.9, 0.8) are considered as promising TBCs materials that might be operated at higher temperatures compared to YSZ.     

Reconstructed Water Oxidation Electrocatalysts: The Impact of Surface Dynamics on Intrinsic Activities

Electroreduction of small molecules such as H₂O, CO₂, and N₂ for producing clean fuels or valuable chemicals provides a sustainable approach to meet the increasing global energy demands and to alleviate the concern on climate change resulting from fossil fuel consumption. On the path to implement this purpose, however, several scientific hurdles remain, one of which is the low energy efficiency due to the sluggish kinetics of the paired oxygen evolution reaction (OER). In response, it is highly desirable to synthesize high-performance and cost-effective OER electrocatalysts. Recent advances have witnessed surface reconstruction engineering as a salient tool to significantly improve the catalytic performance of OER electrocatalysts. In this review, recent progress on the reconstructed OER electrocatalysts and future opportunities are discussed. A brief introduction of the fundamentals of OER and the experimental approaches for generating and characterizing the reconstructed active sites in OER nanocatalysts are given first, followed by an expanded discussion of recent advances on the reconstructed OER electrocatalysts with improved activities, with a particular emphasis on understanding the correlation between surface dynamics and activities. Finally, a prospect for clean future energy communities harnessing surface reconstruction-promoted electrochemical water oxidation will be provided.     

新能源实时错误数据辨识与修正深度学习模型

针对新能源电站实时采集数据错误的问题，利用新能源电站历史数据，采用基于数据间模型的方法辨识和修正错误数据，进而利用辨识和修正的结果数据，建立基于决策树分类模型的新能源实时错数辨识模型，以及基于深度神经网路的新能源实时错数修正模型，从而在实时运行过程中，可利用得到的模型对新能源错数进行实时快速辨识和修正，可显著提高错数辨识和修正效率，支撑新能源电站的实时分析应用，保障新能源电站的实时安全稳定运行。通过某典型风电场和光伏电站真实历史数据的算例分析，验证了所提方法的有效性。     

基于数值微分核脉冲信号数字处理方法

核反应堆核测量系统测量探测器输出的核脉冲信号，该信号后沿拖尾很长，在计数率较高时容易产生信号堆积和基线漂移等问题，导致源区计数率测量上限仅能达到105 Hz左右。文中基于数值微分方法，采用数字处理技术，在时域上分析了核脉冲信号经过前置放大、信号成形、低通滤波和脉冲甄别后的输出，并利用探测器实测信号进行了仿真。仿真结果表明，基于数值微分的数字处理方法可以实现相邻0.4 μs脉冲信号的识别和测量，将源区测量计数率上限提升到2×106 Hz以上。      

电力系统自动化发展方向分析

计算机技术、控制技术及信息技术的发展,电力系统自动化面临着空前的变革,多媒体技术、智能控制技术将迅速进入电力系统自动化领域。     

结合深度学习与支持向量机的金属零件识别

目的 在视觉引导的工业机器人自动拾取研究中，关键技术难点之一是机器人抓取目标区域的识别问题。特别是金属零件，其表面的反光、随意摆放时相互遮挡等非结构化因素都给抓取区域的识别带来巨大的挑战。因此，本文提出一种结合深度学习和支持向量机的抓取区域识别方法。方法 分别提取抓取区域的方向梯度直方图（HOG）和局部二进制模式（LBP）特征，利用主成分分析法（PCA）对融合后的特征进行降维，以此来训练支持向量机（SVM）分类器。通过训练Mask R-CNN（regions with convolutional neural network）神经网络完成抓取区域的初步分割。然后利用SVM对Mask R-CNN识别的抓取区域进行二次分类，完成对干扰区域的剔除。最后计算掩码完成实例分割，以此达到对抓取区域的精确识别。结果 对于随机摆放的铜质金属零件，本文算法与单一的Mask R-CNN及多特征融合的SVM算法就识别准确率、错检率、漏检率3个指标进行了比较，结果表明本文算法在识别准确率上较Mask R-CNN和SVM算法分别提高了7%和25%，同时有效降低了错检率与漏检率。结论 本文算法结合了Mask R-CNN与SVM两种方法，对于反光和遮挡情况具有一定的鲁棒性，同时有效地提升了目标识别的准确率。     

Field‐based robotic phenotyping of sorghum plant architecture using stereo vision

Sorghum (Sorghum bicolor) is known as a major feedstock for biofuel production. To improve its biomass yield through genetic research, manually measuring yield component traits (e.g. plant height, stem diameter, leaf angle, leaf area, leaf number, and panicle size) in the field is the current best practice. However, such laborious and time‐consuming tasks have become a bottleneck limiting experiment scale and data acquisition frequency. This paper presents a high‐throughput field‐based robotic phenotyping system which performed side‐view stereo imaging for dense sorghum plants with a wide range of plant heights throughout the growing season. Our study demonstrated the suitability of stereo vision for field‐based three‐dimensional plant phenotyping when recent advances in stereo matching algorithms were incorporated. A robust data processing pipeline was developed to quantify the variations or morphological traits in plant architecture, which included plot‐based plant height, plot‐based plant width, convex hull volume, plant surface area, and stem diameter (semiautomated). These image‐derived measurements were highly repeatable and showed high correlations with the in‐field manual measurements. Meanwhile, manually collecting the same traits required a large amount of manpower and time compared to the robotic system. The results demonstrated that the proposed system could be a promising tool for large‐scale field‐based high‐throughput plant phenotyping of bioenergy crops.     

基于自然伽马测井曲线的旋回识别及古气候判断

尼玛盆地地处青藏高原腹地,由于环境恶劣交通不便等问题,导致尼玛盆地沉积旋回和层序地层研究程度极低.收集盆地内第1口探井(尼1井)的地球物理数据,利用自然伽马测井曲线对尼1井牛堡组一段进行频谱分析,共识别出405 kyr周期旋回37个、100 kyr周期旋回148个、54 kyr周期旋回274个、41 kyr周期旋回362个和23 kyr周期旋回646个,各周期对应旋回沉积厚度分别为17.7305、4.4623、2.3680、1.7873、1.0886 m,平均沉积速率44.03 m/Ma,沉积时限14.8 Ma.在此基础上,结合带通滤波变化趋势分析,认为该地区的气候反常现象由印度板块与亚欧板块的碰撞隆升引起,风化作用与焚风作用共同控制了高原内部的气候变化.