Universidad de Carabobo, UC

Valencia, Estado Carabobo, Venezuela

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Department of Physics (FACYT)
9
Total Impact Points
20
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  • [Show abstract] [Hide abstract]
    ABSTRACT: Abstract Levothyroxine (T4) has a well-known effect on the central nervous system (CNS). This effect requires hours of latency by genetic pathway. We tested for short latency nongenomic effects of T4 superfusion on the spinal dorsal horn (DH) evaluating lumbar somatosensory evoked potentials in rats. T4 increased N and P wave amplitudes and N wave area under the curve, but reduced P wave duration and N-P interval, suggesting that T4 exerts both excitatory and synchronizing effects on DH interneurons in less than 300 s, thus, providing evidence of nongenomic effects of T4 on DH.
    Somatosensory & Motor Research 08/2013;
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    ABSTRACT: Obesity leads to a deterioration of glucose tolerance and the action of insulin. The purpose of this study was to determine insulin resistance (IR) by indirect methods, and its correlation with clinical, anthropometric and biochemical variables in obese normoglycemic school children. This was a descriptive-correlational study of 72 school prepubescent children, who attended the ambulatory "El Concejo" of the University of Carabobo (UC) and at the Gastroenterology and Pediatric Nutrition service of the city hospital "Enrique Tejera" (CHET), in Valencia, Venezuela, between January-April 2011. Inclusion criteria: exogenous obesity. We assessed personal and family history, presence of Acanthosis Nigricans and nutritional and biochemical status. We found a higher percentage of IR, through the use of the QUICKI method (66.7%), followed by the HOMA (55.6%) and basal insulin (45.9%). The mean (chi) indexes of body mass and waist circumference were significantly greater (p < 0.05) in patients with IR, by HOMA and QUICKI techniques. The QUICKI method detected significant differences (p < 0.05) in the values of glycemia, basal insulin and postprandial insulin, among patients with diminished and normal insulin sensitivities. While HOMA, detected these differences (p < 0.05) in the values of glycemia and basal insulin. A statistically significant relationship was observed (p < 0.05), between the presence of Acanthosis Nigricans and IR, by the HOMA, QUICKI and basal insulin methods. In conclusion, the evaluated techniques, QUICKI, HOMA and basal insulin indexes, were most effective for detecting the IR.
    Investigación clínica 06/2013; 54(2):149-60.
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    ABSTRACT: Frequently, the computational core in general engineering simulation software is the linear system solver. This solver may be dense or sparse depending on the numerical discretization. If the system matrix related to the linear system is sparse, it is desirable to use a sparse structure. The direct sparse linear solvers such as Cholesky, LDLT, or LU are perfect black boxes, i.e., they only need the matrix (A) and the right hand side vector (b) of the linear system Ax=b as inputs. Nevertheless, their main disadvantage is that the memory they require usually increases rapidly with problem size. In this work, we propose an out-of-core implementation for the Cholesky solver in order to overcome the memory problem. The out-of-core layer is based on a specialized cache memory development that stores only a part of the problem matrix A and the factor L whose complete data are stored in temporary disk files. The factor L is computed in a two step process, specifically: The first step is symbolical and the second numerical. The first step computes position of the non-zero element of each row/col and the second computes the numerical value for each position using the Multifrontal Method. We have obtained significant saving of memory with our proposal. The proposed implementation overlaps computation with I/O to speed up the different phases of the solver overcoming disk latencies. The improvements on cache structure, together with the implementation of prefetch techniques show very good results for multi-core processors.
    Mathematical and Computer Modelling 05/2013;

Information

  • Address
    Barbula, Valencia, Estado Carabobo, Venezuela
  • Website
    www.uc.edu.ve
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