Federal University of São Carlos

About: Federal University of São Carlos is a education organization based out in São Carlos, Brazil. It is known for research contribution in the topics: Population & Microstructure. The organization has 16471 authors who have published 34057 publications receiving 456654 citations. The organization is also known as: UFSCar & Federal University of São Carlos.

Structural transformation in densified silica glass: A molecular-dynamics study

Abstract: Pressure-induced structural transformation and the concomitant loss of intermediate-range order (IRO) in high-density ${\mathrm{SiO}}_{2}$ glass are investigated with the molecular-dynamics (MD) approach. The MD simulations cover a wide range of mass densities---from normal density (2.20 g/${\mathrm{cm}}^{3}$) to the density corresponding to stishovite (4.28 g/${\mathrm{cm}}^{3}$). This twofold increase in the density produces significant changes in the short-range order and intermediate-range order. As the density increases from 2.20 to 4.28 g/${\mathrm{cm}}^{3}$, the Si-O bond length increases from 1.61 to 1.67 \AA{}, the Si-O and O-O coordinations change from 4 to 5.8 and from 6 to 12, respectively, and the O-Si-O bond angle changes from 109\ifmmode^\circ\else\textdegree\fi{} to 90\ifmmode^\circ\else\textdegree\fi{}. These results provide firm evidence of structural transition from a corner-sharing Si(${\mathrm{O}}_{1/2}$${)}_{4}$ tetrahedral network to a network of Si(${\mathrm{O}}_{1/3}$${)}_{6}$ octahedra jointed at corners and edges. At normal density, the first sharp diffraction peak (FSDP) in the static structure factor S(q) is at 1.6 A${\mathrm{\r{}}}^{\mathrm{\ensuremath{-}}1}$ whereas under pressure the height of the FSDP is considerably diminished and its position shifts to larger q values. At a density of 2.64 g/${\mathrm{cm}}^{3}$, a peak in S(q) appears at 2.85 A${\mathrm{\r{}}}^{\mathrm{\ensuremath{-}}1}$. The height of this peak grows as the density increases. All of these results are in agreement with the recent high-pressure x-ray measurements on ${\mathrm{SiO}}_{2}$ glass.

Enhanced Beetle Luciferase for High-Resolution Bioluminescence Imaging

Abstract: We developed an enhanced green-emitting luciferase (ELuc) to be used as a bioluminescence imaging (BLI) probe. ELuc exhibits a light signal in mammalian cells that is over 10-fold stronger than that of the firefly luciferase (FLuc), which is the most widely used luciferase reporter gene. We showed that ELuc produces a strong light signal in primary cells and tissues and that it enables the visualization of gene expression with high temporal resolution at the single-cell level. Moreover, we successfully imaged the nucleocytoplasmic shuttling of importin α by fusing ELuc at the intracellular level. These results demonstrate that the use of ELuc allows a BLI spatiotemporal resolution far greater than that provided by FLuc.

Effect of Cu content on the surface and catalytic properties of Cu/ZrO2 catalyst for ethanol dehydrogenation

Abstract: ZrO2-supported Cu catalysts with different Cu content (5–30 wt%) were prepared by impregnation method The effect of Cu content on the structure, surface and catalytic properties of Cu/ZrO2 catalysts in the reaction of ethanol conversion was studied The physicochemical characterization of the calcined and reduced samples was carried out by: N2 adsorption–desorption isotherms, N2O titration, XRD, XPS, TPR and DRFTS of CO adsorption It was observed that the increase of Cu content leads to decrease of the apparent copper metal dispersion caused by the strong agglomeration of the metal particles The selectivity to different reaction products was connected with the electronic properties of the catalysts defined by the copper particle size and the interface at metal-oxide support The highest selectivity to ethyl acetate over samples with Cu content ≥10 wt% was assigned to the high density of basic sites of O2− ions and more heterogeneous distribution of copper species (Cu0/Cu+) defined by DRIFTS of CO adsorption and XPS

Improving the ranking quality of medical image retrieval using a genetic feature selection method

Abstract: In this paper, we take advantage of single-valued functions that evaluate rankings to develop a family of feature selection methods based on the genetic algorithm approach, tailored to improve the accuracy of content-based image retrieval systems. Experiments on three image datasets, comprising images of breast and lung nodules, showed that developing functions to evaluate the ranking quality allows improving retrieval performance. This approach produces significantly better results than those of other fitness function approaches, such as the traditional wrapper and than filter feature selection algorithms.