The role of jumps in the agricultural futures market on forecasting stock market volatility: New evidence

In this study, we explore the effect of cojumps within the agricultural futures market, and cojumps between the agricultural futures market and the stock market, on stock volatility forecasting. Also, we take into account large and small components of cojumps. We have several noteworthy findings. First, large jumps may lead to more substantial fluctuations and are more powerful than small jumps. The effect of cojumps and their decompositions on future volatility are mixed. Second, a model including large and small cojumps between the agricultural futures market and the stock market can achieve a higher forecasting accuracy, implying that large and small cojumps contain more useful predictive information than cojumps themselves. Third, our conclusions are robust based on various robustness tests such as the realized kernel, expanding forecasts, different forecasting windows, different jump tests, and different threshold values.     

融合视惯传感数据的非接触式物体尺寸获取方法

从视觉数据和惯性测量单元(Inertial Measurement Unit, IMU)数据各自的特点出发,利用计算机视觉三维重建技术从视觉数据中恢复视觉传感器的六维位姿信息,分析计算惯性测量数据和视觉位姿数据的时空关系,实现融合视惯传感数据的场景重建及尺度估计,进而获取待测对象的绝对物理尺寸数据。上述方法在实验数据上取得了相对误差约为3%的非接触式物体尺寸估计结果,由于该方法无需在待测场景中嵌入额外标定物或辅助定位装置,具有较好的灵活性和适用范围。     

Resource Allocation in Public Healthcare: A Team-DEA Model

This paper combines the theory of teams and data envelopment analysis (DEA) to design a mechanism to optimally allocate resources in public healthcare. A statutory authority and the public hospitals under its governance are interpreted as a team, the members of which seek to operate efficiently under the shared institutional constraint that public healthcare is a public good. The individual public hospital exploits DEA to maximize own-payoff, subject to the team-condition that the payoff of each other public hospital does not fall and thereby subtract from the external effects created by the public supply of healthcare. The resulting team-DEA solution, which is shown to be both an individually-efficient and team-satisficing equilibrium and to be computable in terms of a convergent algorithm, can then be applied by the authority to determine the optimal allocation of resources in public healthcare. A case based on Chinese data is presented to illustrate the team-DEA model’s ready operationalization and computation.     

淬火分配处理对高碳钢组织、力学性能和磨损性能的影响

The present work employed the X-ray diffraction, scanning electron microscopy, electron backscattered diffraction, and electron probe microanalysis techniques to identify the microstructural evolution and mechanical and abrasive behavior of high carbon steel during quenching-partitioning treatment with an aim to enhance the toughness and wear resistance of high carbon steel. Results showed that, with the increase in partitioning temperature from 250 to 400°C, the amount of retained austenite (RA) decreased resulting from the carbide precipitation effect after longer partitioning times. Moreover, the stability of RA generally increased because of the enhanced degree of carbon enrichment in RA. Given the factors affecting the toughness of high carbon steel, the stability of RA associated with size, carbon content, and morphology plays a significant role in determining the toughness of high carbon steel. The analysis of the wear resistance of samples with different mechanical properties shows that hardness is the primary factor affecting the wear resistance of high carbon steel, and the toughness is the secondary one.     

鄂尔多斯盆地白于山井网加密区延长组长4+5特低渗储层沉积特征和储层物性分析

以岩芯、薄片资料为基础, 结合常规测井和成像测井等资料, 综合分析鄂尔多斯盆地白于山井网加密区上三叠统延长组长4+5特低渗储层的沉积特征和储层特征, 进而解剖储层砂体在纵向及平面的展布特征。结果表明, 长4+5储层主要为一套中?细粒长石砂岩, 发育平行层理和交错层理; 储集空间以中小孔径的粒间孔为主, 发育少量裂缝, 储层物性较差。储层砂体在平面上呈较均匀的条带状展布, 厚度在2~5 m之间; 沉积亚相以三角洲前缘为主, 发育水下分流主河道、水下分流浅河道、水下分流浅滩和水下分流间湾4种沉积微相。在纵向上, 水下分流主河道及浅河道交替变化, 在各小层有规律的展布。研究结果对进一步寻找白于山地区的油气富集区有一定的指示意义。     

基于脑电的多媒体情绪诱发对智力发挥影响研究

多媒体能够对情绪产生影响,而情绪与智力发挥息息相关.通过多媒体诱发情绪来探究情绪对智力发挥的影响,对移动传媒、教育教学等领域具有十分重要的意义.本文基于脑电信号探究多媒体诱发情绪对智力发挥的影响.为此,本文构建了新的情绪诱发视频数据集,设计了基于情绪视频的情绪与智力发挥脑电实验,并创新性地提出机器学习情绪识别方法对智力发挥阶段的真实情绪进行识别,从而探究情绪对智力发挥的影响.结果 表明,积极情绪相对于中性情绪在被试的数学计算正确率上有积极影响,但在答题反应时上存在抑制作用,而消极情绪则相反.不同难度的数学计算中,积极情绪在解决中高等难度问题时表现更佳,而消极情绪在解决高难度问题时更有利于智力发挥.结果 暗示,积极情绪和消极情绪在解决问题时,可能会针对不同的问题调用不同的影响策略,从而导致在不同难度问题上,情绪对智力发挥的影响也不同.     

S-激发剂对高钙粉煤灰潜在水硬性的激发

本文采用测定水化过程结合水量、XRD和 SEM等技术研究了纯高钙粉煤灰的水化及S—激发剂对高钙粉煤灰的激发作用。结果表明 ,高钙粉煤灰由于含有较多的 f Ca O,水化时产生较大的膨胀而使试样粉化、无一点强度 ,掺入 S—激发剂可较好地激发高钙粉煤灰的潜在水硬性 ,增加水化过程结合水量 ,从而使掺有 S—激发剂的高钙粉煤灰试样水化不同龄期后均有一定的强度