Evaluation of the inclusion of a mixture of organic acids or lactulose into the feed of pigs experimentally challenged with Salmonella Typhimurium

A mixture of organic acids and lactulose for preventing or reducing colonization of the gut by Salmonella Typhimurium was evaluated in pigs. A total of 63 4-week-old commercial piglets were randomly distributed into three different experimental dietary groups: a plain diet without additives (PD) and the same diet supplemented with either 0.4% (w/v) formic acid and 0.4% lactic acid (w/v) (AC) or 1% (w/v) lactulose (LC). After 7 days of adaptation, two-thirds of the pigs (14 from each diet) were challenged with a 2-mL oral dose of 10(8) CFU/mL of Salmonella Typhimurium, leaving the remaining animals unchallenged (UC). After 4 and 10 days post-challenge, pigs were euthanized and the ileum and caecum content were aseptically sampled to (a) quantify lactic, formic, and short-chain fatty acids (SCFA), (b) quantify bacterial populations and Salmonella by fluorescence in situ hybridization and (c) qualitatively analyse bacterial populations through denaturing gradient gel electrophoresis (DGGE). Modification of fermentation products and counts of some of the bacterial groups analysed in the challenged pigs receiving the treatments AC and LC were minimal. Treatments only influenced the bacterial diversity after 10 days post-challenge, with AC generating a lower number of DGGE bands than UC(P < 0.05). Neither the inclusion of a mixture of 0.4% (w/v) formic and 0.4% (w/v) lactic acids nor of 1% (w/v) lactulose in the feed influenced numbers of Salmonella in the ileum and caecum of experimentally challenged pigs. (C) 2009 Elsevier B.V. All rights reserved.

Investigation into the performance of an algorithm for deriving concise descriptions of optic flow fields for real-time control

This paper describes a region-based algorithm for deriving a concise description of a first order optical flow field. The algorithm described achieves performance improvements over existing algorithms without compromising the accuracy of the flow field values calculated. These improvements are brought about by not computing the entire flow field between two consecutive images, but by considering only the flow vectors of a selected subset of the images. The algorithm is presented in the context of a project to balance a bipedal robot using visual information.

A cluster-based implementation of a fault-tolerant parallel reduction algorithm using swarm-array computing

Recent research in multi-agent systems incorporate fault tolerance concepts. However, the research does not explore the extension and implementation of such ideas for large scale parallel computing systems. The work reported in this paper investigates a swarm array computing approach, namely ‘Intelligent Agents’. In the approach considered a task to be executed on a parallel computing system is decomposed to sub-tasks and mapped onto agents that traverse an abstracted hardware layer. The agents intercommunicate across processors to share information during the event of a predicted core/processor failure and for successfully completing the task. The agents hence contribute towards fault tolerance and towards building reliable systems. The feasibility of the approach is validated by simulations on an FPGA using a multi-agent simulator and implementation of a parallel reduction algorithm on a computer cluster using the Message Passing Interface.

Variable selection algorithm for the construction of MIMO operating point dependent neurofuzzy networks

An input variable selection procedure is introduced for the identification and construction of multi-input multi-output (MIMO) neurofuzzy operating point dependent models. The algorithm is an extension of a forward modified Gram-Schmidt orthogonal least squares procedure for a linear model structure which is modified to accommodate nonlinear system modeling by incorporating piecewise locally linear model fitting. The proposed input nodes selection procedure effectively tackles the problem of the curse of dimensionality associated with lattice-based modeling algorithms such as radial basis function neurofuzzy networks, enabling the resulting neurofuzzy operating point dependent model to be widely applied in control and estimation. Some numerical examples are given to demonstrate the effectiveness of the proposed construction algorithm.

Simulated annealing technique for fast learning of SOM networks

The Self-Organizing Map (SOM) is a popular unsupervised neural network able to provide effective clustering and data visualization for multidimensional input datasets. In this paper, we present an application of the simulated annealing procedure to the SOM learning algorithm with the aim to obtain a fast learning and better performances in terms of quantization error. The proposed learning algorithm is called Fast Learning Self-Organized Map, and it does not affect the easiness of the basic learning algorithm of the standard SOM. The proposed learning algorithm also improves the quality of resulting maps by providing better clustering quality and topology preservation of input multi-dimensional data. Several experiments are used to compare the proposed approach with the original algorithm and some of its modification and speed-up techniques.

Bayesian estimation of the double hurdle model in the presence of fixed costs

We present a model of market participation in which the presence of non-negligible fixed costs leads to random censoring of the traditional double-hurdle model. Fixed costs arise when household resources must be devoted a priori to the decision to participate in the market. These costs, usually of time, are manifested in non-negligible minimum-efficient supplies and supply correspondence that requires modification of the traditional Tobit regression. The costs also complicate econometric estimation of household behavior. These complications are overcome by application of the Gibbs sampler. The algorithm thus derived provides robust estimates of the fixed-costs, double-hurdle model. The model and procedures are demonstrated in an application to milk market participation in the Ethiopian highlands.

Gaze stabilization testing: The efficiency and test-retest reliability of user operated control versus the parameter estimation (PEST) algorithm

The primary objective of this research study is to determine which form of testing, the PEST algorithm or an operator-controlled condition is most accurate and time efficient for administration of the gaze stabilization test

Ac and dc magnetotransport properties of the phase-separated La(0.6)Y(0.1)Ca(0.3)MnO(3) manganite

The physical properties of the La(0.6)Y(0.1)Ca(0.3)MnO(3) compound have been investigated, focusing on the magnetoresistance phenomenon studied by both dc and ac electrical transport measurements. X-ray diffraction and scanning electron microscopy analysis of ceramic samples prepared by the sol-gel method revealed that specimens are single phase and have average grain size of similar to 0.5 mu m. Magnetization and 4-probe dc electrical resistivity rho(T,H) experiments showed that a ferromagnetic transition at T(C) similar to 170 K is closely related to a metal-insulator (MI) transition occurring at essentially the same temperature T(MI). The magnetoresistance effect was found to be more pronounced at low applied fields (H <= 2.5 T) and temperatures close to the MI transition. The ac electrical transport was investigated by impedance spectroscopy Z(f,T,H) under applied magnetic field H up to 1 T. The Z(f,T,H) data exhibited two well-defined relaxation processes that exhibit different behaviors depending on the temperature and applied magnetic field. Pronounced effects were observed close to T (C) and were associated with the coexistence of clusters with different electronic and magnetic properties. In addition, the appreciable decrease of the electrical permittivity epsilon`(T,H) is consistent with changes in the concentration of e(g) mobile holes, a feature much more pronounced close to T (C).

An algorithm for automatic checking of exercises in a dynamic geometry system: iGeom

One of the key issues in e-learning environments is the possibility of creating and evaluating exercises. However, the lack of tools supporting the authoring and automatic checking of exercises for specifics topics (e.g., geometry) drastically reduces advantages in the use of e-learning environments on a larger scale, as usually happens in Brazil. This paper describes an algorithm, and a tool based on it, designed for the authoring and automatic checking of geometry exercises. The algorithm dynamically compares the distances between the geometric objects of the student`s solution and the template`s solution, provided by the author of the exercise. Each solution is a geometric construction which is considered a function receiving geometric objects (input) and returning other geometric objects (output). Thus, for a given problem, if we know one function (construction) that solves the problem, we can compare it to any other function to check whether they are equivalent or not. Two functions are equivalent if, and only if, they have the same output when the same input is applied. If the student`s solution is equivalent to the template`s solution, then we consider the student`s solution as a correct solution. Our software utility provides both authoring and checking tools to work directly on the Internet, together with learning management systems. These tools are implemented using the dynamic geometry software, iGeom, which has been used in a geometry course since 2004 and has a successful track record in the classroom. Empowered with these new features, iGeom simplifies teachers` tasks, solves non-trivial problems in student solutions and helps to increase student motivation by providing feedback in real time. (c) 2008 Elsevier Ltd. All rights reserved.

Study of Water-Gas-Shift Reaction over La((1-y))Sr(y)Ni(x)Co((1-x))O(3) Perovskite as Precursors

The performance of La((1-y))Sr(y)Ni(x)Co((1-x))O(3) perovskites for the water gas shift reaction (WGSR) was investigated. The samples were prepared by the co- precipitation method and were performed by the BET method, XRD, TPR, and XPS. The catalytic tests were performed at 300 and 400 A degrees C and H(2)O(v)/CO = 2.3/1 (molar ratio). The sample with the highest surface area is La(0.70)Sr(0.30)NiO(3). The XRD results showed the formation of perovskite structure for all samples, and the La(0.70)Sr(0.30)NiO(3) sample also presented peaks corresponding to La(2)NiO(4) and NiO, indicating that the solubility limit of Sr in the perovskite lattice was surpassed. The replacement of Co by Ni favored the reduction of the species at lower temperatures, and the sample containing Sr presented the highest amount of reducible species, as identified by TPR results. All samples were active, the Sr containing perovskite appearing the most active due to the highest surface area, presence of the La(2)NiO(4) phase, and higher content of Cu in the surface, as detected by XPS. Among the samples containing Co, the most active one was that with x = 0.70 (60% of CO conversion).

Implication of RNA-Binding Protein La in Proliferation, Migration and Invasion of Lymph Node-Metastasized Hypopharyngeal SCC Cells

The 5-year survival rate for oral cavity cancer is poorer than for breast, colon or prostate cancer, and has improved only slightly in the last three decades. Hence, new therapeutic strategies are urgently needed. Here we demonstrate by tissue micro array analysis for the first time that RNA-binding protein La is significantly overexpressed in oral squamous cell carcinoma (SCC). Within this study we therefore addressed the question whether siRNA-mediated depletion of the La protein may interfere with known tumor-promoting characteristics of head and neck SCC cells. Our studies demonstrate that the La protein promotes cell proliferation, migration and invasion of lymph node-metastasized hypopharyngeal SCC cells. We also reveal that La is required for the expression of beta-catenin as well as matrix metalloproteinase type 2 (MMP-2) within these cells. Taken together these data suggest a so far unknown function of the RNA-binding protein La in promoting tumor progression of head and neck SCC.

Improvement of fatigue resistance on La modified BiFeO(3) thin films

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Mutational analyses of human eIF5A-1-identification of amino acid residues critical for eIF5A activity and hypusine modification

The eukaryotic translation initiation factor 5A (eIF5A) is the only protein that contains hypusine [N-epsilon-(4-amino-2-hydroxybutyl)lysine], which is required for its activity. Hypusine is formed by post-translational modification of one specific lysine (Lys50 for human eIF5A) by deoxyhypusine synthase and deoxyhypusine hydroxylase. To investigate the features of eIF5A required for its activity, we generated 49 mutations in human eIF5A-1, with a single amino acid substitution at the highly conserved residues or with N-terminal or C-terminal truncations, and tested mutant proteins in complementing the growth of a Saccharomyces cerevisiae eIF5A null strain. Growth-supporting activity was abolished in only a few mutant eIF5As (K47D, G49A, K50A, K50D, K50I, K50R, G52A and K55A), with substitutions at or near the hypusine modification site or with truncation of 21 amino acids from either the N-terminus or C-terminus. The inactivity of the Lys50 substitution proteins is obviously due to lack of deoxyhypusine modification. In contrast, K47D and G49A were effective substrates for deoxyhypusine synthase, yet failed to support growth, suggesting critical roles of Lys47 and Gly49 in eIF5A activity, possibly in its interaction with effector(s). By use of a UBHY-R strain harboring genetically engineered unstable eIF5A, we present evidence for the primary function of eIF5A in protein synthesis. When selected eIF5A mutant proteins were tested for their activity in protein synthesis, a close correlation was observed between their ability to enhance protein synthesis and growth, lending further support for a central role of eIF5A in translation.

Microstructure of doped barium titanate prepared from polymeric precursors

Barium titanate is used extensively as a dielectric in ceramic capacitors, particularly due to its high dielectric constant and low dielectric loss characteristics. It can be made semiconducting by addition of certain dopants and by proper modification of grains and grain boundary properties obtaining very interesting characteristics for various applications. The synthesis method and sintering regime have a strong influence on properties of obtained barium titanate ceramics. Doped barium titanate was prepared with Nb+5 and Y+3 ions as donor dopants, and with Mn+2 ions as acceptor dopant by polymeric precursors method. By this procedure nanosized powders were obtained after calcination. Sintering was performed in the temperature range of 1290°C to 1380°C The microstructure of doped BaTiO3 was performed using scanning electron microscopy. The influence of dopants and sintering temperature on grain size was analysed.

Distribution system restoration in a DG environment using a heuristic constructive multi-start algorithm

This paper proposes a heuristic constructive multi-start algorithm (HCMA) to distribution system restoration in real time considering distributed generators installed in the system. The problem is modeled as nonlinear mixed integer and considers the two main goals of the restoration of distribution networks: minimizing the number of consumers without power and the number of switching. The proposed algorithm is implemented in C++ programming language and tested using a large real-life distribution system. The results show that the proposed algorithm is able to provide a set of feasible and good quality solutions in a suitable time for the problem. © 2011 IEEE.