Dislipidemias in Patients with Cardiopathy Isquemica

The dislipidemias are a risk factor well recognized of the cardiovascular diseases and constitute a problem of public health. A descriptive study in 150 patient elders of 30 years with diagnosis of Izquemic Cardiopathyes accomplished itself for the sake of identifying dislipidemias in patients of high cardiovascular risk that they helped the high-technology General Medical Center state James Mariño Aragua, at the Republic Bolivariana of Venezuela, that you constituted the sign of study from October 2011 to October 2012. They used quantitative and qualitative variables like weight, age, sex, pathological personal background, risk factors cardiovascular associates, seric levels of total cholesterol, triglycerides, HDL cholesterol, LDL cholesterol VLDL cholesterol. 63 percent of patients with dislipidemias were detected, being hypercholesterolemia the more alteration frequently found. The ages understood between 41 and 60 years evidenced the bigger frequency

Effect of band-filling and structural distortions on the Curie temperature of Fe-Mo double perovkites

By means of high resolution neutron powder diffraction at low temperature we have characterized the structural details of $\rm La_{x}Sr_{2-x}FeMoO_6$ ($0\leq {\rm x}\leq 0.5$) and $\rm Ca_{x}Sr_{2-x}FeMoO_6$ ($0\leq {\rm x}\leq 0.6$) series of compounds. This study reveals a similar variation of the mean bond-angle \FeOMo in both series. In contrast, the mean bond-distance \FeMoO\ increases with La but not with Ca substitution. Both series also present a different evolution of the Curie temperature ($T_C$), which raises in the La series and slightly decreases in the Ca one. We thus conclude that the enhancement of $T_C$ in the La series is due to the electron filling of the conduction band and a concomitant rising of the density of states at the Fermi level.Comment: Revtex, 4 Journal pages, 2 figures, 1 tabl

Amphiphilic Elastin-Like Block Co-Recombinamers Containing 2 Leucine Zippers: Cooperative Interplay between Both Domains 3 Results in Injectable and Stable Hydrogels

Many biological processes are regulated by reversible binding events, with these interactions between macromolecules representing the core of dynamic chemistry. As such, any attempt to gain a better understanding of such interactions, which would pave the way to the extrapolation of natural designs to create new advanced systems, is clearly of interest. This work focuses on the development of a leucine zipper-elastin-like recombinamer (ZELR) in order to elucidate the behavior of such domains when coexisting along the same molecule and to engineer reversible, injectable and stable hydrogels. The unique propensity of the Z-moiety selected to dimerize, together with the thermosensitive behavior of the ELR, which has been constructed as a thermosensitive amphiphilic tetrablock, has been engineered into a single recombinant molecule. In this molecular design, the Z-moieties are unable to form a network, while the ELR is below its Tt, thus, guaranteeing the liquid-like state of the system. However, this situation changes rapidly as the temperature increases above Tt, where a stable hydrogel is formed, as demostrated by rheological tests. The inability of the ELR molecule (without Z-domains) to form such a stable hydrogel above Tt clearly points to a positive cooperative effect between these two domains (Z and EL), and no conformational changes in the former are involved, as demonstrated by circular dichroism analysis. AFM shows that Z-motifs seem to induce the aggregation of micelles, which supports the enhanced stability displayed by ZELRs when compared to ELR at the macroscale level. To the best of our knowledge, this is the first time that such an interplay between these two domains has been reported. Furthermore, the cytocompatibility of the resulting hydrogels opens the door to their use in biomedical applications.Este trabajo forma parte de Proyectos de Investigación financiados por la Comisión Europea a través del Fondo Social Europeo (FSE) y el Fondo Europeo de Desarrollo Regional (ERDF), por el del MINECO (MAT2013-41723R, MAT2013-42473-R, MAT2012-38043 y PRI-PIBAR-2011-1403), la Junta de Castilla y León (VA049A11, VA152A12 y VA155A12) y el Instituto de Salud Carlos III bajo el Centro en Red de Medicina Regenerativa y Terapia Celular de Castilla y León

A wavelet-based approach for describing the mechanical behaviour of cellular beams

This paper describes how a wavelet model comprised of a linear combination of sine terms is capable of representing the cross-section inertia variation along the length of cellular beams. This allows the efficient computation of deflections of cellular beams when these are deployed as a part of steel-concrete composite flooring systems. This method does not involve purely statistical approaches or piece-wise integration of moment-curvature relationships that lead to cumbersome matrix approaches and complicate the assessment of deflections. Despite its simplicity, the proposed approach is found to be reliable as it successfully predicts displacements obtained through finite element model representations of more than 260 cases with errors smaller than ±5 %. Furthermore, the proposed analytical description of cross-section inertia along the beam length is defined by only three parameters that can be inferred through linear expressions considering the geometrical characteristics of a perforated beam, namely, the ratio of flange to web thickness, the second moment of inertia of the steel beam and the ratio between beam length and depth, making it easy for widespread application by practitioners

Low precision matrix multiplication for efficient deep learning in NVIDIA Carmel processors

[EN] We introduce a high performance, multi-threaded realization of the gemm kernel for the ARMv8.2 architecture that operates with 16-bit (half precision)/queryKindly check and confirm whether the corresponding author is correctly identified. floating point operands. Our code is especially designed for efficient machine learning inference (and to a certain extent, also training) with deep neural networks. The results on the NVIDIA Carmel multicore processor, which implements the ARMv8.2 architecture, show considerable performance gains for the gemm kernel, close to the theoretical peak acceleration that could be expected when moving from 32-bit arithmetic/data to 16-bit. Combined with the type of convolution operator arising in convolutional neural networks, the speed-ups are more modest though still relevant.This work was supported by projects TIN2017-82972-R and RTI2018-093684-B-I00 from the Ministerio de Ciencia, Innovacion y Universidades, project S2018/TCS-4423 of the Comunidad de Madrid, project PR65/19-22445 of the UCM, and project Prometeo/2019/109 of the Generalitat Valenciana.San Juan-Sebastian, P.; Rodríguez-Sánchez, R.; Igual, FD.; Alonso-Jordá, P.; Quintana-Ortí, ES. (2021). Low precision matrix multiplication for efficient deep learning in NVIDIA Carmel processors. The Journal of Supercomputing. 77(10):11257-11269. https://doi.org/10.1007/s11227-021-03636-41125711269771