A Point-Wise Model of Adhesion Suitable for Real-Time Applications of Bio-Inspired Climbing Robots

Bio-inspired climbing robots relying on adhesion systems are believed to become essential tools for several industrial applications in the near future. In recent years, research has mainly focused on modeling micro-scale adhesion phenomena; a macro-scale adhesion model has however to be developed for the design of macro-scale systems. In this paper a macro-model of adhesion suitable for real-time applications is presented; it relies on a continuous representation of adhesion. An extension of the von Mises criterion is proposed as failure adhesion criterion in order to estimate the occurrence of detachment at any point of the contacting surface. An experimental set up has been designed in order to define the parameters of the model. A semi-automatic process has been developed to ensure repeatability and accuracy of the results. Polydimethylsiloxane (PDMS), which has revealed promising adhesive features for robotic use, has been used during the experimental phase. The macro-model of adhesion has been implemented in a multi-body dynamics environment based on Open Dynamics Engine (ODE) to simulate a spider-inspired robot. Simulations based on this model are suitable to represent the behaviour of climbing robots and also to optimize their design.     

Na‐Ion Batteries for Large Scale Applications: A Review on Anode Materials and Solid Electrolyte Interphase Formation

The urgent need for optimizing the available energy through smart grids and efficient large‐scale energy storage systems is pushing the construction and deployment of Li‐ion batteries in the MW range which, in the long term, are expected to hit the GW dimension while demanding over 1000 ton of positive active material per system. This amount of Li‐based material is equivalent to almost 1% of current Li consumption and can strongly influence the evolution of the lithium supply and cost. Given this uncertainty, it becomes mandatory to develop an energy storage technology that depends on almost infinite and widespread resources: Na‐ion batteries are the best technology for large‐scale applications. With small working cells in the market that cannot compete in cost ($/W h) with commercial Li‐ion batteries, the consolidation of Na‐ion batteries mainly depends on increasing their energy density and stability, the negative electrodes being at the heart of these two requirements. Promising Na‐based negative electrodes for large‐scale battery applications are reviewed, along with the study of the solid electrolyte interphase formed in the anode surface, which is at the origin of most of the stability problems.     

A Strategy for Sensitive,Large Scale Quantitative Metabolomics

Metabolite profiling has been a valuable asset in the study of metabolism in health and disease. However, current platforms have different limiting factors, such as labor intensive sample preparations, low detection limits, slow scan speeds, intensive method optimization for each metabolite, and the inability to measure both positively and negatively charged ions in single experiments. Therefore, a novel metabolomics protocol could advance metabolomics studies. Amide-based hydrophilic chromatography enables polar metabolite analysis without any chemical derivatization. High resolution MS using the Q-Exactive (QE-MS) has improved ion optics, increased scan speeds (256 msec at resolution 70,000), and has the capability of carrying out positive/negative switching. Using a cold methanol extraction strategy, and coupling an amide column with QE-MS enables robust detection of 168 targeted polar metabolites and thousands of additional features simultaneously.  Data processing is carried out with commercially available software in a highly efficient way, and unknown features extracted from the mass spectra can be queried in databases.     

杂交瘤细胞的大量培养

杂交瘤细胞的大量培养是一项迅速发展的技术。本文评述了杂交瘤细胞培养条件和代谢调控方面的研究进展,包括反应器培养中的过程参数优化、细胞损伤和保护、营养物质利用和有害副产物的形成、细胞生长和单抗分泌的动力学以及长期培养的稳定性等问题。同时,本文也讨论了在生物反应器中培养杂交瘤细胞的操作模式和控制策略的研究工作,特别是近年来备受重视的灌注培养和补料培养。     

Optimal Transmission Radius for Flooding in Large Scale Sensor Networks

One of the principal characteristics of large scale wireless sensor networks is their distributed, multi-hop nature. Due to this characteristic, applications such as query propagation rely regularly on network-wide flooding for information dissemination. If the transmission radius is not set optimally, the flooded packet may be holding the transmission medium for longer periods than are necessary, reducing overall network throughput. We analyze the impact of the transmission radius on the average settling time—the time at which all nodes in the network finish transmitting the flooded packet. Our analytical model takes into account the behavior of the underlying contention-based MAC protocol, as well as edge effects and the size of the network. We show that for large wireless networks there exists an intermediate transmission radius which minimizes the settling time, corresponding to an optimal tradeoff between reception and contention times. We also explain how physical propagation models affect small wireless networks and why there is no intermediate optimal transmission radius observed in these cases. The mathematical analysis is supported and validated through extensive simulations.Marco Zuniga is currently a PhD student in the Department of Electrical Engineering at the University of Southern California. He received his Bachelors degree in Electrical Engineering from the Pontificia Universidad Catolica del Peru in 1998, and his Masters degree in Electrical Engineering from the University of Southern California in 2002. His interests are in the area of Wireless Sensor Networks in general, and more specifically in studying the interaction amongst different layers to improve the performance of these networks. He is a member of IEEE and the Phi Kappa Phi Honor society.Bhaskar Krishnamachari is an Assistant Professor in the Department of Electrical Engineering at the University of Southern California (USC), where he also holds a joint appointment in the Department of Computer Science. He received his Bachelors degree in Electrical Engineering with a four-year full-tuition scholarship from The Cooper Union for the Advancement of Science and Art in 1998. He received his Masters degree and his Ph.D. in Electrical Engineering from Cornell University in 1999 and 2002, under a four-year university graduate fellowship. Dr. Krishnamacharis previous research has included work on critical density thresholds in wireless networks, data centric routing in sensor networks, mobility management in cellular telephone systems, multicast flow control, heuristic global optimization, and constraint satisfaction. His current research is focused on the discovery of fundamental principles and the analysis and design of protocols for next generation wireless sensor networks. He is a member of IEEE, ACM and the Tau Beta Pi and Eta Kappa Nu Engineering Honor Societies     

BFAST: An Alignment Tool for Large Scale Genome Resequencing

Background

The new generation of massively parallel DNA sequencers, combined with the challenge of whole human genome resequencing, result in the need for rapid and accurate alignment of billions of short DNA sequence reads to a large reference genome. Speed is obviously of great importance, but equally important is maintaining alignment accuracy of short reads, in the 25–100 base range, in the presence of errors and true biological variation.

Methodology

We introduce a new algorithm specifically optimized for this task, as well as a freely available implementation, BFAST, which can align data produced by any of current sequencing platforms, allows for user-customizable levels of speed and accuracy, supports paired end data, and provides for efficient parallel and multi-threaded computation on a computer cluster. The new method is based on creating flexible, efficient whole genome indexes to rapidly map reads to candidate alignment locations, with arbitrary multiple independent indexes allowed to achieve robustness against read errors and sequence variants. The final local alignment uses a Smith-Waterman method, with gaps to support the detection of small indels.

Conclusions

We compare BFAST to a selection of large-scale alignment tools - BLAT, MAQ, SHRiMP, and SOAP - in terms of both speed and accuracy, using simulated and real-world datasets. We show BFAST can achieve substantially greater sensitivity of alignment in the context of errors and true variants, especially insertions and deletions, and minimize false mappings, while maintaining adequate speed compared to other current methods. We show BFAST can align the amount of data needed to fully resequence a human genome, one billion reads, with high sensitivity and accuracy, on a modest computer cluster in less than 24 hours. BFAST is available at http://bfast.sourceforge.net.     

A Large Scale Procedure for Purification of Desmosine and Isodesmosine

A rapid large scale procedure was devised for the purification of desmosine and isodesmosine from ligamentum nuchae elastin. The method makes use of the hydrophilic nature of the desmosines which preferentially absorbs to cellulose fibers in mixtures of organic solvents. Resolution of the isomers was achieved on a polystyrene resin column.     

利用RNAi技术大规模分析基因功能的研究

将双链RNA导入细胞内会干扰与之同源的基因的表达 ,使生物体产生相应的功能缺陷表型 ,这种作用称为RNAi(RNAinterference)。针对人类、植物、微生物等大规模基因组测序后所面临的功能鉴定难题 ,着重探讨了RNAi的机制及其研究进展。复合物RISC和酶Dicer的发现揭示了RNAi导致同源基因沉默的作用机理。通过使用RNAi这种反向遗传学工具可使生物体产生相应的功能缺陷表型 ,从而确定未知基因的功能。因此RNAi对大规模分析动、植物基因功能的研究具有重要的作用。     

利用RNAi技术大规模分析基因功能的研究

将双链RNA导入细胞内会干扰与之同源的基因的表达,使生物体产生相应的功能缺陷表型,这种作用称为RNAi（RNA interference）。针对人类、植物、微生物等大规模基因组测序后所面临的功能鉴定难题,着重探讨了RNAi的机制及其研究进展。复合物RISC和酶Dicer的发现揭示了RNAi导致同源基因沉默的作用机理。通过使用RNAi这种反向遗传学工具可使生物体产生相应的功能缺陷表型,从而确定未知基因的功能。因此RNAi对大规模分析动、植物基因功能的研究具有重要的作用。     

Large Scale Preparation of Wheat Germ Agglutinin

A highly active form of wheat germ agglutinin (WGA) was isolated by affinity chromatography on a partially acid hydrolyzed chitin column after extraction of the wheat germ with 0.5 M formic acid and removal of the denatured or water insoluble WGA by dialyzing against distilled water before and after affinity chromatography. The purified preparation was found to be homogeneous by gel filtration, disc electrophoresis, and chemical analysis. It reacted readily with WGA receptors in human serum and urine, giving well-defined bands on agar gel double diffusion and electrophoresis. When chemically coupled to Sepharose the WGA was very reactive with red blood cells, WGA receptors in serum, urine and other biological fluids. The Sepharose-WGA has proven to be stable over a long period of time.     

大型综合医院科研绩效评价指标体系的构建研究

目的 为大型综合医院构建较为科学合理的科研绩效评价指标体系。方法 采用德尔菲法获得大型综合医院科研绩效评价的指标体系,运用层次分析法对各级指标进行权重的确定。结果 建立了大型综合医院科研绩效评价指标体系,其中一级指标2个,二级指标12个,三级指标40个。结论 构建的医院科研评价指标体系具有科学性、可操作性,可以作为评估医院科研绩效的工具。     

大量分离叶绿素a和b的方法

在原有分离叶绿素a和b的DEAE SepharoseCL 6B和SepharoseCL 6B柱层析法的基础上 ,用较大的层析柱 ,在保持分离效果的前提下 ,提高流速 ,并对层析柱进行原位再生处理 ,实现循环分离 ,可节省装柱和平衡时间 ,快速大量分离纯化叶绿素并可循环再生。 10 0 g菠菜叶可分离得到叶绿素a约 5 0mg ,叶绿素b约 15mg。     

Bio-Inspired Binary Bees Algorithm for a Two-Level Distribution Optimisation Problem

<正> Two uncoupleable distributions, assigning missions to robots and allocating robots to home stations, accompany the use ofmobile service robots in hospitals.In the given problem, two workload-related objectives and five groups of constraints areproposed.A bio-mimicked Binary Bees Algorithm (BBA) is introduced to solve this multiobjective multiconstraint combinatorialoptimisation problem, in which constraint handling technique (Multiobjective Transformation, MOT), multiobjectiveevaluation method (nondominance selection), global search strategy (stochastic search in the variable space), local searchstrategy (Hamming neighbourhood exploitation), and post-processing means (feasibility selection) are the main issues.TheBBA is then demonstrated with a case study, presenting the execution process of the algorithm, and also explaining the change ofelite number in evolutionary process.Its optimisation result provides a group of feasible nondominated two-level distributionschemes.     

A Bio-Inspired Approach for the Reduction of Left Ventricular Workload

Previous studies have demonstrated the existence of optimization criteria in the design and development of mammalians cardiovascular systems. Similarities in mammalian arterial wave reflection suggest there are certain design criteria for the optimization of arterial wave dynamics. Inspired by these natural optimization criteria, we investigated the feasibility of optimizing the aortic waves by modifying wave reflection sites. A hydraulic model that has physical and dynamical properties similar to a human aorta and left ventricle was used for a series of in-vitro experiments. The results indicate that placing an artificial reflection site (a ring) at a specific location along the aorta may create a constructive wave dynamic that could reduce LV pulsatile workload. This simple bio-inspired approach may have important implications for the future of treatment strategies for diseased aorta.     

Large Scale Isolation of Pig Muscle Phosphoglucose Isomerase

large-scale purification procedure for phosphoglucose isomerase from pig skeletal muscle is described. It consists of two fractionations by selective precipitation and two ion exchange chromatography steps yielding an end product of approximately 900 units (micromoles of sub-strate converted to product per rain per mg of protein, at 30°) specific activity. The method separates three isoenzymic forms with an overall recovery of about 30% of the original total enzyme activity in the form of Isoenzyme III, the latter being the predominant enzyme species.     

Multistability in Large Scale Models of Brain Activity

Noise driven exploration of a brain network’s dynamic repertoire has been hypothesized to be causally involved in cognitive function, aging and neurodegeneration. The dynamic repertoire crucially depends on the network’s capacity to store patterns, as well as their stability. Here we systematically explore the capacity of networks derived from human connectomes to store attractor states, as well as various network mechanisms to control the brain’s dynamic repertoire. Using a deterministic graded response Hopfield model with connectome-based interactions, we reconstruct the system’s attractor space through a uniform sampling of the initial conditions. Large fixed-point attractor sets are obtained in the low temperature condition, with a bigger number of attractors than ever reported so far. Different variants of the initial model, including (i) a uniform activation threshold or (ii) a global negative feedback, produce a similarly robust multistability in a limited parameter range. A numerical analysis of the distribution of the attractors identifies spatially-segregated components, with a centro-medial core and several well-delineated regional patches. Those different modes share similarity with the fMRI independent components observed in the “resting state” condition. We demonstrate non-stationary behavior in noise-driven generalizations of the models, with different meta-stable attractors visited along the same time course. Only the model with a global dynamic density control is found to display robust and long-lasting non-stationarity with no tendency toward either overactivity or extinction. The best fit with empirical signals is observed at the edge of multistability, a parameter region that also corresponds to the highest entropy of the attractors.