Proteome analysis of tissues by mass spectrometry

Tissues and biofluids are important sources of information used for the detection of diseases and decisions on patient therapies. There are several accepted methods for preservation of tissues, among which the most popular are fresh‐frozen and formalin‐fixed paraffin embedded methods. Depending on the preservation method and the amount of sample available, various specific protocols are available for tissue processing for subsequent proteomic analysis. Protocols are tailored to answer various biological questions, and as such vary in lysis and digestion conditions, as well as duration. The existence of diverse tissue‐sample protocols has led to confusion in how to choose the best protocol for a given tissue and made it difficult to compare results across sample types. Here, we summarize procedures used for tissue processing for subsequent bottom‐up proteomic analysis. Furthermore, we compare protocols for their variations in the composition of lysis buffers, digestion procedures, and purification steps. For example, reports have shown that lysis buffer composition plays an important role in the profile of extracted proteins: the most common are tris(hydroxymethyl)aminomethane, radioimmunoprecipitation assay, and ammonium bicarbonate buffers. Although, trypsin is the most commonly used enzyme for proteolysis, in some protocols it is supplemented with Lys‐C and/or chymotrypsin, which will often lead to an increase in proteome coverage. Data show that the selection of the lysis procedure might need to be tissue‐specific to produce distinct protocols for individual tissue types. Finally, selection of the procedures is also influenced by the amount of sample available, which range from biopsies or the size of a few dozen of mm² obtained with laser capture microdissection to much larger amounts that weight several milligrams.     

Maximizing Convergence Speed for Second Order Consensus in Leaderless Multi-Agent Systems

The paper deals with the consensus problem in a leaderless network of agents that have to reach a common velocity while forming a uniformly spaced string. Moreover, the final common velocity (reference velocity) is determined by the agents in a distributed and leaderless way. Then, the consensus protocol parameters are optimized for networks characterized by a communication topology described by a class of directed graphs having a directed spanning tree, in order to maximize the convergence rate and avoid oscillations. The advantages of the optimized consensus protocol are enlightened by some simulation results and comparison with a protocol proposed in the related literature. The presented protocol can be applied to coordinate agents such as mobile robots, automated guided vehicles (AGVs) and autonomous vehicles that have to move with the same velocity and a common inter-space gap.      

The 9‐point hedonic scale and hedonic ranking in food science: some reappraisals and alternatives

The 9‐point hedonic scale has been used routinely in food science, the same way for 60 years. Now, with advances in technology, data from the scale are being used for more and more complex programs for statistical analysis and modeling. Accordingly, it is worth reconsidering the presentation protocols and the analyses associated with the scale, as well as some alternatives. How the brain generates numbers and the types of numbers it generates has relevance for the choice of measurement protocols. There are alternatives to the generally used serial monadic protocol, which can be more suitable. Traditionally, the ‘words’ on the 9‐point hedonic scale are reassigned as ‘numbers’, while other ‘9‐point hedonic scales’ are purely numerical; the two are not interchangeable. Parametric statistical analysis of scaling data is examined critically and alternatives discussed. The potential of a promising alternative to scaling itself, simple ranking with a hedonic R‐Index signal detection analysis, is explored in comparison with the 9‐point hedonic scale. © 2014 Society of Chemical Industry     

机载网络MAC协议研究综述

随着航空通信应用的不断深化、无线自组织网络研究的迅猛发展,机载网络介质访问控制（MAC）协议的研究已成为新的研究热点。首先总结和分析了机载网络MAC协议设计的应用需求,进而重点从信道接入方式角度综述了机载网络的基于竞争类MAC协议、基于调度类MAC协议、混合类MAC协议和跨层协议设计等四类MAC协议的研究进展,最后对比分析了各类典型协议的特点、性能和适用范围,并给出了需要进一步重点研究的问题,以期为从事该方面研究的人员提供参考。     

卫星通信组呼业务MAC层研究

组呼通信在指挥调度中有着重要作用,而在一些地面没有基站的地方,就无法正常使用。卫星通信具有无视地形,通信范围广,不易受陆地灾害影响,易于建设等优点。把卫星通信和组呼通信结合在一起的卫星组呼通信技术兼顾两者的优点,能更好的发挥指挥调度这一作用。当前卫星组呼通信采用固定频率方式,组呼成员在一个频率下进行通信,这种方式实用性不好。本文研究的是移动卫星组呼,在GMR-1系统的基础上研究了卫星组呼通信中MAC层的功能,提出了MAC-Ready-Gcc、MAC-Dedicated-Gcc这两个为了支持组呼的状态,并针对在MAC层发生的PTT竞争提出了一种回退策略。     

IEEE 802.11b DCF三维Markov非饱和链路模型

为了准确评估实际网络中IEEE 802.11b分布式协调功能(Distributed Coordination Function,DCF)的系统性能,提出了一种三维Markov链路模型,该模型综合考虑了DCF协议退避计数器冻结状态和有限重传次数,并结合M/M/1/K排队模型给出了在负载有限的情况下DCF系统性能的理论模型。仿真结果表明,该模型能准确地预测IEEE 802.11b DCF协议的系统性能。     

一种基于Ad Hoc网络的协作MAC方案

在 IEEE 802.11b MAC层协议的研究基础上,提出了一种基于无线Ad Hoc网络的最佳中继选择策略,该策略综合考虑瞬时信道信息和节点剩余能量,能够有效防止信道条件好的节点的过度使用,并能保证系统高吞吐量。文中以饱和吞吐量和网络生存时间为性能指标,对新算法和以往协作MAC算法进行仿真和比较,结果表明新算法在网络吞吐量下降不明显的情况下,能大大增加网络生存时间。     

华为OLT下“流氓ONU”的故障处理

众所周知,EPON系统光传输机制是:下行广播方式,上行TDMA方式。所谓TDMA方式就是将上行总带宽分成若干个时隙,各个ONU通过占用不同的时隙来传送业务。上行时隙的分配由OLT来完成,并由OLT通知各个ONU,各ONU只能在分配的时隙内发光。若某个ONU持续长时间发光,它就会占用OLT分配给其他ONU的发光时间,从而与其它ONU的发光信号发生冲突,造成了其它ONU的离线。这种不按照分配的时间戳向上发送光信号的ONU,即是我们通常说的"流氓ONU"。     

可充电无线传感器网络动态拓扑问题研究

在可充电无线传感器网络中的能量补给设备兼任数据采集设备的情况下,提出了可充电无线传感器网络时变动态拓扑模型,并在此基础上根据最大化能量补给设备驻站时间比为目标提出了最优化问题。通过分析不同时刻不同传感器节点和无线能量补给/数据采集设备的工作情况及需要遵循的约束条件,得到与原问题具有等优性的多状态线性规划问题。求解该优化问题,获得可充电无线传感器网络动态拓扑下的周期动态路由和无线能量补给/数据采集设备的工作策略。与之前的研究成果相比,优化目标值均有20%以上的提升。