苯乙炔与二苯丁二炔的共聚及共聚物的表征

本文以(Ph_3P)_2PdCl_2作催化剂,合成出聚二苯丁二炔和二苯丁二炔与苯乙炔共聚物。均聚物及共聚物产率都在90%以上,均聚物分子量为900,二苯丁二炔与苯乙炔最佳摩尔比为1/2(数均分子量为1205)。结构分析表明,均聚物及共聚物均具有反—反式结构。     

一种完全分布式的空间服务及组合模型

针对服务组合中控制流和数据流的不同协调机制,可将组合模型分为4种类型,分别是控制流集中式且数据流集中式、控制流集中式且数据流分布式、控制流分布式且数据流集中式、控制流分布式且数据流分布式.空间服务组合流程需处理较大规模的数据流,采用控制流分布式和数据流分布式的协调机制能有效降低组合过程中系统整体通信规模并减少空间服务组合响应时间.通过对各种不同组合类型建模的定量分析对上述观点进行了正确性论证.模拟实验证明,定量分析结果可信.     

A model of supply-chain decisions for resource sharing with an application to ventilator allocation to combat COVID-19

We present a stochastic optimization model for allocating and sharing a critical resource in the case of a pandemic. The demand for different entities peaks at different times, and an initial inventory for a central agency are to be allocated. The entities (states) may share the critical resource with a different state under a risk-averse condition. The model is applied to study the allocation of ventilator inventory in the COVID-19 pandemic by FEMA to different U.S. states. Findings suggest that if less than 60% of the ventilator inventory is available for non-COVID-19 patients, FEMA's stockpile of 20 000 ventilators (as of March 23, 2020) would be nearly adequate to meet the projected needs in slightly above average demand scenarios. However, when more than 75% of the available ventilator inventory must be reserved for non-COVID-19 patients, various degrees of shortfall are expected. In a severe case, where the demand is concentrated in the top-most quartile of the forecast confidence interval and states are not willing to share their stockpile of ventilators, the total shortfall over the planning horizon (until May 31, 2020) is about 232 000 ventilator days, with a peak shortfall of 17 200 ventilators on April 19, 2020. Results are also reported for a worst-case where the demand is at the upper limit of the 95% confidence interval. An important finding of this study is that a central agency (FEMA) can act as a coordinator for sharing critical resources that are in short supply over time to add efficiency in the system. Moreover, through properly managing risk-aversion of different entities (states) additional efficiency can be gained. An additional implication is that ramping up production early in the planning cycle allows to reduce shortfall significantly. An optimal timing of this production ramp-up consideration can be based on a cost-benefit analysis.     

努力争当知识型开拓型有为型自律型领导型干部

在新的历史起点上,我们的干部要努力争当学习力强、知识面广、业务上精的知识型干部;争当视野开阔、勇于创新、充满激情的开拓型干部;争当心无旁骛想干事、素质过硬能干事、不辱使命干成事的有为型干部;争当善于律心、心理不失衡,长于律言、言语不失规,严于律行、行为不失范的自律型干部;争当能说会道、让人信服,公道正派、让人诚服,硕果...     

Multi-scale traffic vehicle detection based on faster R-CNN with NAS optimization and feature enrichment

It well known that vehicle detection is an important component of the field of object detection. However, the environment of vehicle detection is particularly sophisticated in practical processes. It is compara-tively difficult to detect vehicles of various scales in traffic scene images, because the vehicles partially obscured by green belts, roadblocks or other vehicles, as well as influence of some low illumination weather. In this paper, we present a model based on Faster R-CNN with NAS optimization and feature enrichment to realize the effective detection of multi-scale vehicle targets in traffic scenes. First, we proposed a Retinex-based image adaptive correction algorithm (RIAC) to enhance the traffic images in the dataset to reduce the influence of shadow and illumination, and improve the image quality. Second, in order to improve the feature expression of the backbone network, we conducted Neural Architecture Search (NAS) on the backbone network used for feature extraction of Faster R-CNN to generate the optimal cross-layer connection to extract multi-layer features more effectively. Third, we used the object Feature Enrichment that combines the multi-layer feature information and the context information of the last layer after cross-layer connection to enrich the information of vehicle targets, and improve the robustness of the model for challenging targets such as small scale and severe occlusion. In the imple-mentation of the model, K-means clustering algorithm was used to select the suitable anchor size for our dataset to improve the convergence speed of the model. Our model has been trained and tested on the UN-DETRAC dataset, and the obtained results indicate that our method has art-of-state detection performance.     

战争观念的语源原型

本文从汉字语源出发,根据荣格心理学的原型观念,通过汉字“战”的语源分析,探寻蕴含在汉字深处(因而也是汉文化底层)的战争观念。文字学认为,“战”()字中单为声符,戈为形符,而作为声符的单系“战”字的隐义,亦即“战”的战争原型。古文字研究表明“单”为鳄类爬行动物,象征着人性中凶猛残暴的兽性;而脑科学研究表明,大脑深处的主管攻击、暴力的部分正是原始脑的“爬虫复合体”(鳄类)。这些研究成果与无意识心理学中的阴影原型(人性中的兽性)不谋而合。因此通过文字学与心理学我们找到了战争冲动的原始意象,也从中发现了相应的化解方法。     

降低执政成本提高执政成效

降低执政成本,提高执政成效,是执政党追求的永恒目标,也是执政过程中始终面临的重大课题。从政治意义上看,执政成效关系到党的兴衰成败、生死存亡;从经济意义上看,执政成效是执政党保持执政合法性的重要条件。降低执政成本、提高执政成效是一个系统工程,要提高执政的成本效益意识;建立一支高素质的领导干部队伍;精兵简政,降低政府行政成本;加强制度建设。     

不断增强旅团党委依法从严治军的本领

从严治军是军队建设的铁律。旅团党委是部队建设的“一线指挥部”,应当树立依法指导和开展工作的法制观念,严格职责管理权限,突出作风纪律建设这个重点,把提高部队战斗力作为根本标准,不断增强依法从严治军、加强部队正规化建设的本领。     

栅格数据处理中邻域型算法的并行优化方法

随着并行计算的成熟,众多数据密集型的栅格处理算法亟需利用并行计算来缩减执行时间.针对其中一类邻域型算法,构建了用于估计是时间代价的串行/并行时域模型,分析了各个组成的代价影响因素,提出了降低数据I/O代价的并行I/O方法和降低数据通信代价的光圈预测方法.实验证明,所提的两个优化方法可以使邻域型栅格处理算法的并行程序更加充分地利用并行计算资源,进而在一般并行化的基础上进一步提升其并行性能.     

一种计算涡轮增压柴油机高原性能的方法

提出了一种计算涡轮增压柴油机高原性能的方法.这种方法不涉及复杂的数值模拟计算,可以在较宽广的环境压力和环境温度范围预测涡轮增压柴油机的性能,具有较高的计算精度.对两台车用涡轮增压柴油机进行了实例计算,并与试验结果进行了对比.分析了海拔高度变化和温度变化引起的涡轮增压器和发动机性能的变化趋势.