不同钙质原料对干式振动料性能的影响

采用新型环保复合结合剂和引入无水化钙质材料(石灰石、白云石、消石灰等)作为CaO源原料,研究开发环保型抗水化镁钙质干式料.结果表明, 钙质原料的种类、粒度和数量对干式料性能影响很大.加入部分石灰石颗粒,采用环保型结合剂可制得具有较好物理性能的干式料,其中粒度为3～1mm和1～0mm的石灰石加入量分别为5%和30%时,试样获得了较好的综合性能,是一种理想的CaO源材料.     

An Efficient Multidimensional Fusion Algorithm for IoT Data Based on Partitioning

The Internet of Things (IoT) implies a worldwide network of interconnected objects uniquely addressable, via standard communication protocols. The prevalence of IoT is bound to generate large amounts of multisource, heterogeneous, dynamic, and sparse data. However, IoT offers inconsequential practical benefits without the ability to integrate, fuse, and glean useful information from such massive amounts of data. Accordingly, preparing us for the imminent invasion of things, a tool called data fusion can be used to manipulate and manage such data in order to improve process efficiency and provide advanced intelligence. In order to determine an acceptable quality of intelligence, diverse and voluminous data have to be combined and fused. Therefore, it is imperative to improve the computational efficiency for fusing and mining multidimensional data. In this paper, we propose an efficient multidimensional fusion algorithm for IoT data based on partitioning. The basic concept involves the partitioning of dimensions (attributes), i.e., a big data set with higher dimensions can be transformed into certain number of relatively smaller data subsets that can be easily processed. Then, based on the partitioning of dimensions, the discernible matrixes of all data subsets in rough set theory are computed to obtain their core attribute sets. Furthermore, a global core attribute set can be determined. Finally, the attribute reduction and rule extraction methods are used to obtain the fusion results. By means of proving a few theorems and simulation, the correctness and effectiveness of this algorithm is illustrated.     

浅述外围护结构的建筑节能技术

外围护结构在建筑节能中起着重要作用,对外围护结构进行合理的设计选择,能极大地降低建筑能耗.文章针对外围护结构,从墙体、屋面、门窗3方面提出了一些提高外围护结构热保温性能的措施,从而改善建筑节能,以供借鉴.     

基于神经网络技术自动筛选Monastrol抑制剂的算法研究

带自动荧光显微镜的HCS（high content screening）系统是一种新兴的显微摄影、筛选和处理系统.HCS系统在摄影过程中会产生大量数据,人工筛选和识别费时费力.本文为了进行Monastrol抑制剂的筛选,基于前馈式神经网络技术研究了一种对HCS系统摄影的大量细胞同时进行特征提取和细胞显型识别的自动算法.在得到各个通道分离的图像后,对不同通道图像进行并行预处理,并采用神经网络和逻辑运算相结合的算法进行处理.我们将该方法运用于Monastrol抑制剂的筛选中,并将结果与人工识别结果进行分析比较.相比较前人提出的multi-phenotypic mitotic analysis（MMA）算法自动识别的正确率得以提高,可更好评估抗癌药剂效用.     

大学生耐力性素质练习的价值及对策研究

文章针对当前学生耐力素质的现状,运用文献资料调研法,旨在阐明耐力素质的重要性,并就如何科学合理地运用方法手段,提高学生的耐力素质,以促进学生身体素质的全面发展.     

Simultaneous mineralization of CO2 and recovery of soluble potassium using earth-abundant potassium feldspar

CO2 capture and storage(CCS) is an important strategy in combatting anthropogenic climate change.However,commercial application of the CCS technique is currently hampered by its high energy expenditure and costs.To overcome this issue,CO2 capture and utilization(CCU) is a promising CO2 disposal method.We,for the first time,developed a promising method to mineralize CO2 using earth-abundant potassium feldspar in order to effectively reduce CO2 emissions.Our experiments demonstrate that,after adding calcium chloride hexahydrate as an additive,the K-feldspar can be transformed to Ca-silicates at 800 C,which can easily mineralize CO2 to form stable calcium carbonate and recover soluble potassium.The conversion of this process reached 84.7%.With further study,the pretreatment temperature can be reduced to 250 C using hydrothermal method by adding the solution of triethanolamine(TEA).The highest conversion can be reached 40.1%.The process of simultaneous mineralization of CO2 and recovery of soluble potassium can be easily implemented in practice and may provide an economically feasible way to tackle global anthropogenic climate change.     

提高大学生上课出勤率的工作方案探索

高校的学风建设对教育质量的提高有着重要作用,而大学生上课出勤率问题也越来越受到高校的关注.目前,大学生缺勤现象十分普遍,这一问题不仅影响了高校教学工作的正常开展与大学生专业知识水平的提高,而且对高校的声誉也造成不好的影响.因此,大学生的上课出勤率问题已成为高校教学与管理不能忽视的重要问题,对这一问题的研究越来越具有实际的意义.     

PLC在电力系统自动化技术中的应用现状与发展趋势

PLC系统技术成熟、性价比高,在电力系统自动化领域有着广泛的应用。本文介绍了PLC的定义、使用特点和应用领域,为进一步应用PLC提供了一定的理论参考。     

内燃机配气机构传动链脱节概率

以某型发动机配气机构传动链为研究对象,应用随机摄动和概率可靠性等分析方法,建立了配气机构脱节概率可靠性数学模型.当配气机构基本随机变量为正态分布时,提出了传动链脱节的可靠性分析方法.通过算例分析获得了凸轮在不同运动阶段的传动链脱节概率,以及在不同转速下的脱节失效概率,并且随着转速升高传动链发生脱节的概率也会升高,与实际情况相符合,进一步表明了所提方法的正确性.此外,通过分析脱节的原因,提出了为降低脱节概率而应采取的方法,为今后内燃机配气机构传动链的可靠性设计提供了理论依据.     

Uncertainty in crossing time of 2 °C warming threshold over China

The 2 °C warming target has been used widely in global and regional climate change research. Previous studies have shown large uncertainties in the time when surface air temperature (SAT) change over China will reach 2 °C relative to the pre-industrial era. To understand the uncertainties, we analyzed the projected SAT in the twenty-first century using 40 state-of-the-art climate models under two Representative Concentration Pathways (RCP4.5 and RCP8.5) from the Coupled Model Intercomparison Project Phase 5. The 2 °C threshold-crossing time (TCT) of SAT averaged across China was around 2033 and 2029 for RCP4.5 and RCP8.5, respectively. Considering a ±1σ range of intermodel SAT change, the upper and lower bounds of the 2 °C TCT could differ by about 25 years or even more. Uncertainty in the projected SAT and the warming rate around the TCT are the two main factors responsible for the TCT uncertainty. The former is determined by the climate sensitivity represented by the global mean surface temperature response. About 45 % of the intermodel variance of the projected 2 °C TCT for averaged SAT over China can be explained by climate sensitivity across the models, which is contributed mainly by central and southern China. In a climate more sensitive to CO₂ forcing, stronger greenhouse effect, less stratus cloud over the East Asian monsoon region, and less snow cover on the Tibetan Plateau result in increased downward longwave radiation, increased shortwave radiation, and decreased shortwave radiation reflected by the surface, respectively, all of which may advance the TCT.