Weaning diet induces sustained metabolic phenotype shift in the pig and influences host response to Bifidobacterium lactis NCC2818

Background The process of weaning causes a major shift in intestinal microbiota and is a critical period for developing appropriate immune responses in young mammals.Objective To use a new systems approach to provide an overview of host metabolism and the developing immune system in response to nutritional intervention around the weaning period.Design Piglets (n=14) were weaned onto either an egg-based or soya-based diet at 3 weeks until 7 weeks, when all piglets were switched onto a fish-based diet. Half the animals on each weaning diet received Bifidobacterium lactis NCC2818 supplementation from weaning onwards. Immunoglobulin production from immunologically relevant intestinal sites was quantified and the urinary (1)H NMR metabolic profile was obtained from each animal at post mortem (11 weeks).Results Different weaning diets induced divergent and sustained shifts in the metabolic phenotype, which resulted in the alteration of urinary gut microbial co-metabolites, even after 4 weeks of dietary standardisation. B lactis NCC2818 supplementation affected the systemic metabolism of the different weaning diet groups over and above the effects of diet. Additionally, production of gut mucosa-associated IgA and IgM was found to depend upon the weaning diet and on B lactis NCC2818 supplementation.ConclusionThe correlation of urinary (1)H NMR metabolic profile with mucosal immunoglobulin production was demonstrated, thus confirming the value of this multi-platform approach in uncovering non-invasive biomarkers of immunity. This has clear potential for translation into human healthcare with the development of urine testing as a means of assessing mucosal immune status. This might lead to early diagnosis of intestinal dysbiosis and with subsequent intervention, arrest disease development. This system enhances our overall understanding of pathologies under supra-organismal control.

Distributed hoeffding trees for pocket data mining

Collaborative mining of distributed data streams in a mobile computing environment is referred to as Pocket Data Mining PDM. Hoeffding trees techniques have been experimentally and analytically validated for data stream classification. In this paper, we have proposed, developed and evaluated the adoption of distributed Hoeffding trees for classifying streaming data in PDM applications. We have identified a realistic scenario in which different users equipped with smart mobile devices run a local Hoeffding tree classifier on a subset of the attributes. Thus, we have investigated the mining of vertically partitioned datasets with possible overlap of attributes, which is the more likely case. Our experimental results have validated the efficiency of our proposed model achieving promising accuracy for real deployment.

Distributed classification for pocket data mining

Distributed and collaborative data stream mining in a mobile computing environment is referred to as Pocket Data Mining PDM. Large amounts of available data streams to which smart phones can subscribe to or sense, coupled with the increasing computational power of handheld devices motivates the development of PDM as a decision making system. This emerging area of study has shown to be feasible in an earlier study using technological enablers of mobile software agents and stream mining techniques [1]. A typical PDM process would start by having mobile agents roam the network to discover relevant data streams and resources. Then other (mobile) agents encapsulating stream mining techniques visit the relevant nodes in the network in order to build evolving data mining models. Finally, a third type of mobile agents roam the network consulting the mining agents for a final collaborative decision, when required by one or more users. In this paper, we propose the use of distributed Hoeffding trees and Naive Bayes classifers in the PDM framework over vertically partitioned data streams. Mobile policing, health monitoring and stock market analysis are among the possible applications of PDM. An extensive experimental study is reported showing the effectiveness of the collaborative data mining with the two classifers.

Cross-layer design for MIMO systems over spatially correlated and keyhole Nakagami-m fading channels

Cross-layer design is a generic designation for a set of efficient adaptive transmission schemes, across multiple layers of the protocol stack, that are aimed at enhancing the spectral efficiency and increasing the transmission reliability of wireless communication systems. In this paper, one such cross-layer design scheme that combines physical layer adaptive modulation and coding (AMC) with link layer truncated automatic repeat request (T-ARQ) is proposed for multiple-input multiple-output (MIMO) systems employing orthogonal space--time block coding (OSTBC). The performance of the proposed cross-layer design is evaluated in terms of achievable average spectral efficiency (ASE), average packet loss rate (PLR) and outage probability, for which analytical expressions are derived, considering transmission over two types of MIMO fading channels, namely, spatially correlated Nakagami-m fading channels and keyhole Nakagami-m fading channels. Furthermore, the effects of the maximum number of ARQ retransmissions, numbers of transmit and receive antennas, Nakagami fading parameter and spatial correlation parameters, are studied and discussed based on numerical results and comparisons. Copyright © 2009 John Wiley & Sons, Ltd.

Compensation for HPA nonlinearity and I/Q imbalance in MIMO beamforming systems

In this paper, we investigate the effects of high-power amplifier (HPA) nonlinearity and in-phase and quadrature-phase (I/Q) imbalance on the performance of multiple-input multiple-output (MIMO) transmit beamforming (TB) systems. Specifically, we propose a compensation method for HPA nonlinearity and I/Q imbalance together in MIMO TB systems. The performance of the MIMO TB system under study is evaluated in terms of the average symbol error probability (SEP) and system capacity, considering transmission over uncorrelated frequency-flat Rayleigh fading channels. Numerical results are provided and show the effects of several system parameters, such as the HPA parameters, image-leakage ratio, numbers of transmit and receive antennas, length of pilot symbols, and modulation order of phase-shift keying (PSK), on performance.

Pocket data mining - big data on small devices

Owing to continuous advances in the computational power of handheld devices like smartphones and tablet computers, it has become possible to perform Big Data operations including modern data mining processes onboard these small devices. A decade of research has proved the feasibility of what has been termed as Mobile Data Mining, with a focus on one mobile device running data mining processes. However, it is not before 2010 until the authors of this book initiated the Pocket Data Mining (PDM) project exploiting the seamless communication among handheld devices performing data analysis tasks that were infeasible until recently. PDM is the process of collaboratively extracting knowledge from distributed data streams in a mobile computing environment. This book provides the reader with an in-depth treatment on this emerging area of research. Details of techniques used and thorough experimental studies are given. More importantly and exclusive to this book, the authors provide detailed practical guide on the deployment of PDM in the mobile environment. An important extension to the basic implementation of PDM dealing with concept drift is also reported. In the era of Big Data, potential applications of paramount importance offered by PDM in a variety of domains including security, business and telemedicine are discussed.

Urban integrated meteorological observations: practice and experience in Shanghai, China

Observations of atmospheric conditions and processes in citiesare fundamental to understanding the interactions between the urban surface and weather/climate, improving the performance of urban weather, air quality and climate models, and providing key information for city end-users (e.g. decision-makers, stakeholders, public). In this paper, Shanghai's urban integrated meteorological observation network (SUIMON) and some examples of intended applications are introduced. Its characteristics include being: multi- purpose (e.g. forecast, research, service), multi-function (high impact weather, city climate, special end-users), multi-scale (e.g. macro/meso-, urban-, neighborhood, street canyon), multi-variable (e.g. thermal, dynamic, chemical, bio-meteorological, ecological), and multi- platform (e.g. radar, wind profiler, ground-based, satellite based, in-situ observation/ sampling). Underlying SUIMON is a data management system to facilitate exchange of data and information. The overall aim of the network is to improve coordination strategies and instruments; to identify data gaps based on science and user driven requirements; and to intelligently combine observations from a variety of platforms by using a data assimilation system that is tuned to produce the best estimate of the current state of the urban atmosphere.

Building an Interactive, Three-dimensional Virtual World

The movement of graphics and audio programming towards three dimensions is to better simulate the way we experience our world. In this project I looked to use methods for coming closer to such simulation via realistic graphics and sound combined with a natural interface. I did most of my work on a Dell OptiPlex with an 800 MHz Pentium III processor and an NVIDlA GeForce 256 AGP Plus graphics accelerator -high end products in the consumer market as of April 2000. For graphics, I used OpenGL [1], an open·source, multi-platform set of graphics libraries that is relatively easy to use, coded in C . The basic engine I first put together was a system to place objects in a scene and to navigate around the scene in real time. Once I accomplished this, I was able to investigate specific techniques for making parts of a scene more appealing.

Arquitetura para um ambiente de grade computacional direcionado às aplicações distribuídas, móveis e conscientes do contexto da computação pervasiva

Neste início de década, observa-se a transformação das áreas de Computação em Grade (Grid Computing) e Computação Móvel (Mobile Computing) de uma conotação de interesse emergente para outra caracterizada por uma demanda real e qualificada de produtos, serviços e pesquisas. Esta tese tem como pressuposto a identificação de que os problemas hoje abordados isoladamente nas pesquisas relativas às computações em grade, consciente do contexto e móvel, estão presentes quando da disponibilização de uma infra-estrutura de software para o cenário da Computação Pervasiva. Neste sentido, como aspecto central da sua contribuição, propõe uma solução integrada para suporte à Computação Pervasiva, implementada na forma de um middleware que visa criar e gerenciar um ambiente pervasivo, bem como promover a execução, sob este ambiente, das aplicações que expressam a semântica siga-me. Estas aplicações são, por natureza, distribuídas, móveis e adaptativas ao contexto em que seu processamento ocorre, estando disponíveis a partir de qualquer lugar, todo o tempo. O middleware proposto, denominado EXEHDA (Execution Environment for Highly Distributed Applications), é adaptativo ao contexto e baseado em serviços, sendo chamado de ISAMpe o ambiente por este disponibilizado. O EXEHDA faz parte dos esforços de pesquisa do Projeto ISAM (Infra-Estrutura de Suporte às Aplicações Móveis Distribuídas), em andamento na UFRGS. Para atender a elevada flutuação na disponibilidade dos recursos, inerente à Computação Pervasiva, o EXEHDA é estruturado em um núcleo mínimo e em serviços carregados sob demanda. Os principais serviços fornecidos estão organizados em subsistemas que gerenciam: (a) a execução distribuída; (b) a comunicação; (c) o reconhecimento do contexto; (d) a adaptação; (e) o acesso pervasivo aos recursos e serviços; (f) a descoberta e (g) o gerenciamento de recursos No EXEHDA, as condições de contexto são pró-ativamente monitoradas e o suporte à execução deve permitir que tanto a aplicação como ele próprio utilizem essas informações na gerência da adaptação de seus aspectos funcionais e não-funcionais. O mecanismo de adaptação proposto para o EXEHDA emprega uma estratégia colaborativa entre aplicação e ambiente de execução, através da qual é facultado ao programador individualizar políticas de adaptação para reger o comportamento de cada um dos componentes que constituem o software da aplicação. Aplicações tanto do domínio da Computação em Grade, quanto da Computação Pervasiva podem ser programadas e executadas sob gerenciamento do middleware proposto.