Systematic variation in gene expression patterns in human cancer cell lines

We used cDNA microarrays to explore the variation in expression of approximately 8,000 unique genes among the 60 cell lines used in the National Cancer Institute's screen for anti-cancer drugs. Classification of the cell lines based solely on the observed patterns of gene expression revealed a correspondence to the ostensible origins of the tumours from which the cell lines were derived. The consistent relationship between the gene expression patterns and the tissue of origin allowed us to recognize outliers whose previous classification appeared incorrect. Specific features of the gene expression patterns appeared to be related to physiological properties of the cell lines, such as their doubling time in culture, drug metabolism or the interferon response. Comparison of gene expression patterns in the cell lines to those observed in normal breast tissue or in breast tumour specimens revealed features of the expression patterns in the tumours that had recognizable counterparts in specific cell lines, reflecting the tumour, stromal and inflammatory components of the tumour tissue. These results provided a novel molecular characterization of this important group of human cell lines and their relationships to tumours in vivo.     

A homochiral metal-organic porous material for enantioselective separation and catalysis

Inorganic zeolites are used for many practical applications that exploit the microporosity intrinsic to their crystal structures. Organic analogues, which are assembled from modular organic building blocks linked through non-covalent interactions, are of interest for similar applications. These range from catalysis, separation and sensor technology to optoelectronics, with enantioselective separation and catalysis being especially important for the chemical and pharmaceutical industries. The modular construction of these analogues allows flexible and rational design, as both the architecture and chemical functionality of the micropores can, in principle, be precisely controlled. Porous organic solids with large voids and high framework stability have been produced, and investigations into the range of accessible pore functionalities have been initiated. For example, catalytically active organic zeolite analogues are known, as are chiral metal-organic open-framework materials. However, the latter are only available as racemic mixtures, or lack the degree of framework stability or void space that is required for practical applications. Here we report the synthesis of a homochiral metal-organic porous material that allows the enantioselective inclusion of metal complexes in its pores and catalyses a transesterification reaction in an enantioselective manner. Our synthesis strategy, which uses enantiopure metal-organic clusters as secondary building blocks, should be readily applicable to chemically modified cluster components and thus provide access to a wide range of porous organic materials suitable for enantioselective separation and catalysis.     

Services oriented architecture of foundation data platform of digital city

Digital city, a large complex system, is comprised many subsystem of different fields. It involves common field data, flexible field processes, seamless intra-organization and inter-organization collaborations, and increasing connectivity and interoperability between distributed or decentralized systems. All above these are involved Foundation Data of Digital city. To promote the sustainable development of Digital City, this paper investigates to the construction of Foundation Data Platform (FDP) from the view of the architecture. The paper introduces the conceptions, characteristics and underlying problems of the FDP, and discusses the key issues of the architecture paradigms what FDP might adopted via comparing Object-Oriented Architecture (OOA), Component-Based Architecture (CBA), and Service-based Architecture (SBA). The Process Embedded Service-Oriented Architecture (SOA), one of the recent SOA Application Architecture is introduced. The results indicate that the Process Embedded SOA could promote the sustainable development of Digital City and accommodate the dynamic development environments of different fields which constantly changes requirements.     

Design of a 3-tier smart middleware system for ubiquitous sensor networks

As ubiquitous sensor networks (USN) technologies and its middleware are still at its early stages, the system of the USN relies on the middleware and applications. The past sensor networks are assumed to be designed for specific applications, having data communication protocols tightly coupled to applications. To avoid these problems, several kinds of USN middleware have been researched and developed. However, most middleware of USN are still restricted by its own infrastructure so far. This paper proposes appropriate 3 tier Smart Middleware System (3SMS) for USN.     

Improved D-IDS using the federated peer-to-peer architecture

A number of IDSs have been proposed for a networked or distributed environment. A modified D-IDS using federated peer-to-peer architecture, MCR (Multicast Reflector) and modified shaker protocol were proposed. The suggested scheme can be implemented easily and performs the information sharing between low-level IDS agents. As all users within a group monitor each other's, the common control server can perform detect intrusions with less cost and support the detection of the inside intruders.     

On-line Cutting Quality Recognition in Milling Using a Radical Basis Function Neural Network

Tool wear, chatter vibration, chip breaking and built-up edge are main phenomena to be monitored in modern manufacturing processes, which are considered as important factors to the quality of products.They are closely related to the cutting parameters, which are to be selected in manufacturing process.However, it is very difficult to measure directly the cutting quality based on on-line monitoring.In this study, the relationship between the cutting parameters and cutting quality is analyzed.A Radical Basis Function (RBF) neural network based on-line quality recognition scheme is also presented, which monitors the level of surface roughness.The experimental results reveal that the RBF neural network has a high prediction success rate.     

A renormalization group approach to crowd psychology and inter-group coupling in social many-body systems

By adopting majority rule within a renormalization group approach, we can show that the strength of inter-group interaction in a social system either grows or shrinks monotonically with increasing group size, depending on the initial coupling strength of individuals in the group. This contrasts with the findings of previous studies in which the strength of the interaction grows with group size regardless of the initial strength. Our approach clearly demonstrates that the phenomena of crowd psychology, such as an extreme anti-reaction between different ethnic or ideological groups, could be a consequence of the many-particle nature of social systems when the initial strength of the interaction is larger than a critical value. The effect of neutral opinion holders is critically examined using the spin-one Ising model. The critical size of the population of neutral opinion holders, that can prevent crowd polarization, depends on the block spin rule.     

Default Priors for Neural Network Classification

Feedforward neural networks are a popular tool for classification, offering a method for fully flexible modeling. This paper looks at the underlying probability model, so as to understand statistically what is going on in order to facilitate an intelligent choice of prior for a fully Bayesian analysis. The parameters turn out to be difficult or impossible to interpret, and yet a coherent prior requires a quantification of this inherent uncertainty. Several approaches are discussed, including flat priors, Jeffreys priors and reference priors.