A scalable constraint-based Q-hash indexing for moving objects

In this paper, we develop a Q-hash index structure to efficiently store the position of moving objects. An environment of moving objects contains continuously changing locations which are hard to index using traditional index structures such as R-trees, QuadTrees and their variants. In order to answer the queries accurately, one of the problems faced in storing these positions is the number of updates that have to be made to the database whenever locations change. The high maintenance overhead on updates leads to performance degradation of these index structures; additionally, it makes the database very bulky which results in very poor performance in terms of query execution time. One of the main objectives of the structure we propose is to minimize the number of updates to the database to an optimal number so that the accuracy and response time of the query result are not compromised and at the same time the number of wireless communications can be reduced. The indexing is done using a hashing technique where the hashing function makes use of a region based QuadTree structure. To improve the efficiency of the query processing our index structure helps us define constraints over speed, direction and location of the moving object at the device level which controls the number of updates. In addition, in order to answer different query types efficiently at all levels we propose a three-tier (moving object, regional server, central repository) architecture. Our extensive performance evaluation and comparison of the proposed technique concludes that our scheme outperforms existing Q + R-tree and QuadTree in terms of range query execution time by a high order of magnitude.     

Multi-rate model predictive control of particle size distribution in a semibatch emulsion copolymerization reactor

A multi-rate model predictive controller algorithm is presented for the in-batch closed-loop control of the full particle size distribution (PSD) in a semibatch emulsion copolymerization system. The lack of frequent measurements of the PSD and the measurement delay of these measurements are addressed through the use of frequent density measurements from which the current conditions of the system are estimated. The high dimensionality of the discretized full PSD is reduced by the use of model order reduction based on principal component analysis. This method effectively reduces the size of the problem while preserving the main characteristics of the population balance system. Disturbances that perturb the surfactant and monomer amounts inside the semibatch vinyl acetate–butyl acrylate reactor are considered to demonstrate the performance of the proposed control algorithm.     

Parallel evolution using multi-chromosome cartesian genetic programming

Parallel and distributed methods for evolutionary algorithms have concentrated on maintaining multiple populations of genotypes, where each genotype in a population encodes a potential solution to the problem. In this paper, we investigate the parallelisation of the genotype itself into a collection of independent chromosomes which can be evaluated in parallel. We call this multi-chromosomal evolution (MCE). We test this approach using Cartesian Genetic Programming and apply MCE to a series of digital circuit design problems to compare the efficacy of MCE with a conventional single chromosome approach (SCE). MCE can be readily used for many digital circuits because they have multiple outputs. In MCE, an independent chromosome is assigned to each output. When we compare MCE with SCE we find that MCE allows us to evolve solutions much faster. In addition, in some cases we were able to evolve solutions with MCE that we unable to with SCE. In a case-study, we investigate how MCE can be applied to to a single objective problem in the domain of image classification, namely, the classification of breast X-rays for cancer. To apply MCE to this problem, we identify regions of interest (RoI) from the mammograms, divide the RoI into a collection of sub-images and use a chromosome to classify each sub-image. This problem allows us to evaluate various evolutionary mutation operators which can pairwise swap chromosomes either randomly or topographically or reuse chromosomes in place of other chromosomes.     

Disruption of epithelial cell-matrix interactions induces apoptosis

Cell-matrix interactions have major effects upon phenotypic features such as gene regulation, cytoskeletal structure, differentiation, and aspects of cell growth control. Programmed cell death (apoptosis) is crucial for maintaining appropriate cell number and tissue organization. It was therefore of interest to determine whether cell-matrix interactions affect apoptosis. The present report demonstrates that apoptosis was induced by disruption of the interactions between normal epithelial cells and extracellular matrix. We have termed this phenomenon "anoikis." Overexpression of bcl-2 protected cells against anoikis. Cellular sensitivity to anoikis was apparently regulated: (a) anoikis did not occur in normal fibroblasts; (b) it was abrogated in epithelial cells by transformation with v-Ha-ras, v-src, or treatment with phorbol ester; (c) sensitivity to anoikis was conferred upon HT1080 cells or v-Ha-ras-transformed MDCK cells by reverse-transformation with adenovirus E1a; (d) anoikis in MDCK cells was alleviated by the motility factor, scatter factor. The results suggest that the circumvention of anoikis accompanies the acquisition of anchorage independence or cell motility.     

Model-based 3-D segmentation of multiple sclerosis lesions in magnetic resonance brain images

Human investigators instinctively segment medical images into their anatomical components, drawing upon prior knowledge of anatomy to overcome image artifacts, noise, and lack of tissue contrast. The authors describe: 1) the development and use of a brain tissue probability model for the segmentation of multiple sclerosis (MS) lesions in magnetic resonance (MR) brain images, and 2) an empirical comparison of the performance of statistical and decision tree classifiers, applied to MS lesion segmentation. Based on MR image data obtained from healthy volunteers, the model provides prior probabilities of brain tissue distribution per unit voxel in a standardized 3-D "brain space". In comparison to purely data-driven segmentation, the use of the model to guide the segmentation of MS lesions reduced the volume of false positive lesions by 50-80%     

用于烯烃复分解反应的钌茚基催化剂的合成研究进展

基于钌金属的烯烃复分解反应现今已成为一种至关重要且快速有效的催化反应类型,在聚合领域以及现代有机合成的应用方面起着改革性的推进作用。作为烯烃复分解反应催化剂的一种,钌茚基催化剂在该领域得到成功应用。结合近年来钌茚基催化剂在烯烃复分解反应中的合成研究进展,简述了其发展过程,介绍了该领域创新性的研究成果,重点论述了一些新型钌茚基催化剂的合成方法,并且探讨了辅助配体的结构对催化剂稳定性和活性的影响,最后对其发展方向以及应用前景进行了展望。     

Erratum to: Charge transfer in graphene/polymer interfaces for CO2 detection

Nano Research - The order of the authors in the original version of this article was unfortunately incorrect on the first page and the first page of the ESM. Instead of Myungwoo Son1, Yusin Pak1,...     

Periodic orbits: a new language for neuronal dynamics

A new nonlinear dynamical analysis is applied to complex behavior from neuronal systems. The conceptual foundation of this analysis is the abstraction of observed neuronal activities into a dynamical landscape characterized by a hierarchy of "unstable periodic orbits" (UPOs). UPOs are rigorously identified in data sets representative of three different levels of organization in mammalian brain. An analysis based on UPOs affords a novel alternative method of decoding, predicting, and controlling these neuronal systems.     

Modelling co-operation in the design of knowledge production systems: The Made In'Coop method

This paper presents the latest developments of the MadeIn 'Coop method for modelling the human-machine and human-human co-operation process, and an application of this method for the design of a more co-operative version of the C³I System CHEOPS. We first consider that the design of software systems for organizations is tied more and more to the perspective of compound Knowledge Production Systems that link humans and machines engaged in a co-operative problem solving process. After exposing the four principles upon which MadeIn 'Coop rests for modelling co-operation, we present an artificial problem solving dialogue between CHEOPS and its users. Consistent with the Group Cognitive Processes Theory framework, we propose a dialogue analysis according to two complimentary points of view: the Collective Problem Solving model, and the Coordination model. This analysis should help system designers to identify new system functionalities to assist problem solving.(C³I) Command Control Communication Intelligence Systems