Detection of antigens in the embryo by labelled antisera

Résumé Des anticorps contre le cristallin et contre le muscle cardiaque de la souris ont été marqués par le radio-iode, puis employés pour la localisation histochimique et pour une analyse quantitative de ces antigènes au cours du développement.     

Stabilization of the disk around beta Pictoris by extremely carbon-rich gas

The edge-on disk surrounding the nearby young star beta Pictoris is the archetype of 'debris disks', which are composed of dust and gas produced by collisions between--and evaporation of--planetesimals, analogues of Solar System comets and asteroids. These disks may provide insight into the formation and early evolution of terrestrial planets. Previous work on beta Pic concluded that the disk gas has roughly solar abundances of elements, but this poses a problem because such gas should rapidly be blown away from the star, contrary to observations showing a stable gas disk in keplerian rotation. Here we report the detection of singly and doubly ionized carbon (C II, C III) and neutral atomic oxygen (O I) gas in the beta Pic disk. Carbon is extremely overabundant relative to every other measured element. This appears to solve the problem of the stable gas disk, because the carbon overabundance should keep the gas disk in keplerian rotation. The overabundance may indicate that the gas is produced from material more carbon-rich than expected of Solar System analogues.     

Caveman网络及其在复杂网络熵分析中的应用

熵可以有效反映复杂系统内网络结构的异质性.针对熵指标在刻画网络全局异构上是否适用这一问题,目前仍缺少用以评测的基准网络.对此,在已有结构熵研究的基础上,提出一种Caveman网络构造及其演化规则,为网络复杂性的度量提供新的思路。通过数理分析和仿真实验验证该Caveman网络可以有效评测各类结构熵指标对其演化过程的敏感性,反映熵指标对网络复杂特征识别能力的差异。同时由于Caveman网络可以更好地探索信息空间和抵御攻击,将有助于设计鲁棒、高效的系统结构。     

浅谈高校图书馆服务模式创新和形象塑造

网络化、信息化、数字化时代的到来改变了图书馆的运行环境,使高校图书馆的信息服务出现了危机,因此需要创新服务模式,优化服务流程,即开展个性化服务,设立学科信息服务中心,开展层次化信息服务。     

基于节点属性的社群结构探测算法改进

对Vincent D. Blondel等提出的B算法的特点及机理进行了分析, 讨论了节点属性对社群结构探测的可能影响. 进而通过重构初始化网络, 控制节点(社群)合并过程两个方面, 对B算法进行了改进, 获得更优的模块性指标及对应的社群划分. 经计算机模拟网络与实际网络的社群结构探测, 结果表明所提改进算法有效可用, 能在获得较大模块性指标的同时, 获得较好的社群划分结果, 且拥有更低的运算时间.