Structural Entropy of the Stochastic Block Models

With the rapid expansion of graphs and networks and the growing magnitude of data from all areas of science, effective treatment and compression schemes of context-dependent data is extremely desirable. A particularly interesting direction is to compress the data while keeping the “structural information” only and ignoring the concrete labelings. Under this direction, Choi and Szpankowski introduced the structures (unlabeled graphs) which allowed them to compute the structural entropy of the Erdős–Rényi random graph model. Moreover, they also provided an asymptotically optimal compression algorithm that (asymptotically) achieves this entropy limit and runs in expectation in linear time. In this paper, we consider the stochastic block models with an arbitrary number of parts. Indeed, we define a partitioned structural entropy for stochastic block models, which generalizes the structural entropy for unlabeled graphs and encodes the partition information as well. We then compute the partitioned structural entropy of the stochastic block models, and provide a compression scheme that asymptotically achieves this entropy limit.     

A New Strategy in Boosting Information Spread

Finding a seed set to propagate more information within a specific budget is defined as the influence maximization (IM) problem. The traditional IM model contains two cardinal aspects: (i) the influence propagation model and (ii) effective/efficient seed-seeking algorithms. However, most of models only consider one kind of node (i.e., influential nodes), ignoring the role of other nodes (e.g., boosting nodes) in the spreading process, which are irrational. Specifically, in the real-world propagation scenario, the boosting nodes always improve the spread of influence from the initial activated seeds, which is an efficient and cost-economic measure. In this paper, we consider the realistic budgeted influence maximization (RBIM) problem, which contains two kind of nodes to improve the diffusion of influence. Facing the newly modified objective function, we propose a novel B-degree discount algorithm to solve it. The novel B-degree discount algorithm which adopts the cost-economic boosting nodes to retweet the influence from the predecessor nodes can greatly reduce the cost, and performs better than other state-of-the-art algorithms in both effect and efficiency on RBIM problem solving.     

Production of 2,3- butanediol from pretreated corn cob byKlebsiella oxytoca in the presence of fungal cellulase

A simple and effective method of treatment of lignocellulosic material was used for the preparation of corn cob for the production of 2,3-butanediol byKlebsiella oxytoca ATCC 8724 in a simultaneous saccharification and fermentation process. During the treatment, lignin, and alkaline extractives were solubilized and separated from cellulose and hemicellulose fractions by dilute ammonia (10%) steeping. Hemicellulose was then hydrolyzed by dilute hydrochloric acid (1%, wJv) hydrolysis at 100°C at atmospheric pressure and separated from cellulose fraction. The remaining solid, with 90% of cellulose, was then used as the substrate. A butanediol concentration of 25 g/L and an ethanol concentration of 7 g/L were produced byK. oxytoca from 80 g/L of corn cob cellulose with a cellulase dosage of 8.5 IFPU/g corn cob cellulose after 72 h of SSF. With only dilute acid hydrolysis, a butanediol production rate of 0.21 g/L/h was obtained that is much lower than the case in which corn cob was treated with ammonia steeping prior to acid hydrolysis. The butanediol production rate for the latter was 0.36 g/L/h.     

Rh/Al2O3上CO和NO的吸附性能及相互作用

利用ＴＰ－ＩＲ动态方法研究了ＣＯ和ＮＯ在Ｒｈ／Ａｌ２Ｏ３上吸附性能和相互作用的动态行为，结果表明，Ｒｈ／Ａｌ２Ｏ３的孪生中心对ＣＯ的吸附强于对ＮＯ的吸会，线式和桥式中心则对ＮＯ的吸附强于对ＣＯ的吸附，ＣＯ和ＮＯ共吸附－ＴＰ（ＣＯ和ＮＯ中）－ＩＲ动态过程结果揭示出２２２４ｃｍ＾－１谱带的出现和强度的增加与孪生ＣＯ谱带以及吸附的ＮＯ谱带的强度减弱同时发生，表明是由吸附的ＮＯ和孪生ＣＯ形成Ｒｈ－ＮＣＯ。     

以萘酰亚胺衍生物基荧光高分子为载体和指示剂的 相分离免疫分析方法

以4-甲氧基-N-(2-N’,N’-二甲基氨基乙基-N’-烯丙基)萘二甲酰亚胺氯化铵(DMNAA)为荧光单体, 合成了一种pH敏感荧光高分子聚N-异丙基丙烯酰胺-4-甲氧基-N-(2-N’,N’-二甲基氨基乙基-N’-烯丙基)萘二甲酰亚胺氯化铵-N,N-二甲基氨丙基甲基丙烯酰胺[P(NIP-DMAPM-DMNAA)]. 采用共聚法将日本血吸虫抗原(SjAg)固定在P(NIP-DMAPM-DMNAA)上, 制备P(NIP-DMAPM-DMNAA)-SjAg连接物, 与日本血吸虫抗体(待测, SjAb)发生免疫反应后, 调节pH值, 使荧光高分子相变分离高分子-免疫组分连接物, 最后, 利用蛋白A对抗体的亲和性捕获P(NIP-DMAPM-DMNAA)-SjAg-SjAb, 通过测定高分子自身的荧光信号来定量 SjAb. 该新型高分子具有良好的荧光特性, 对pH响应快速, 37 ℃下相转变pH值为7.2, 分离免疫复合物时造成的损害低. 与传统相分离免疫分析比较, 新方法通过高分子相变分离和蛋白A捕获双重分离作用, 消除了非特异性组分和未反应的特异性免疫成分等的干扰; 利用高分子自身的荧光信号检测, 无须另外的标记物, 大大提高了免疫分析的简便性. 以日本血吸虫抗体为分析对象, 测得线性范围为1～1500 ng/mL, 抗体检出限为1.3 ng/mL, 相对标准偏差为3.6% (n＝10), 结果令人满意.     

常用玻璃量器检定注意事项

总结了常用玻璃量器检定过程中的注意事项,讨论了外观检查、清洁度、涂抹油脂、温度控制、液面观察方法对常用玻璃量器检定结果的影响,其中定容时是否使用黑色遮光带造成的影响最大。     

加速溶剂萃取–液相色谱法测定五灵脂药材中原儿茶酸的含量

建立了五灵脂中原儿茶酸含量的测定方法。利用加速溶剂萃取仪(ASE),以75%乙醇水溶液提取样品中的待测物,用Diamosil C18(4.6 mm×250 mm,5.0μm)色谱柱在梯度洗脱条件下分离待测物,外标法定量。原儿茶酸的线性范围为0.1~10.0 mg/L,相关系数r=0.9998。方法的回收率为83%~107%,测定结果的相对标准偏差为4.6%~10.5%,方法的定量限为1.0 mg/kg。该方法操作简便、快速,提取效率高,适用于检测和分析五灵脂中原儿茶酸的含量。     

水泥聚苯模壳格构式混凝土墙体的抗侧性能试验及分析

论文介绍6片不同高宽比的水泥聚苯模壳格构式混凝土墙体在轴压力和水平往复侧推力作用下的试验,分析这种墙体的抗侧强度、刚度和延性等力学性能.试验表明,高宽比大于1的墙体破坏时表现为墙体跟部的单一水平裂缝,其他部位完好;高宽比3∶4的墙体破坏时存在多条通过格构梁柱的斜向裂缝,墙体裂缝分布密集,变形能力好.     

复合二项风险模型的破产概率

本文讨论了一般情形的复合二项风险模型,得出了初始资本为０时的破产概率以及初始资本为ｕ≥０的情况下的破产概率的一般公式．