Physico-chemical, spectroscopical and thermal characterization of biodiesel obtained by enzymatic route as a tool to select the most efficient immobilized lipase

Two microbial lipases from Burkholderia cepacia and Pseudomonas fluorescens were evaluated as catalysts for the enzymatic transesterification of beef tallow with ethanol and the most efficient lipase source was selected by taking into account the properties of the product to be used as fuel. Both lipases were immobilized on an epoxy silica-polyvinyl alcohol composite by covalent immobilization and used to perform the reactions under the following operational conditions: beef tallow-to-ethanol molar ratio of 1:9, 45ºC and 400 units of enzymatic activity per gram of fat. Products, characterized using Fourier Transform Infrared spectroscopy (FTIR), viscosimetry, thermogravimetry and ¹H NMR spectroscopy, suggested that the biodiesel sample obtained in the reaction catalyzed by Burkholderia cepacia lipase has the best set of properties for fuel usage.

A contribution for developing more efficient dynamic modelling algorithms of parallel robots

Parallel kinematic structures are considered very adequate architectures for positioning and orienti ng the tools of robotic mechanisms. However, developing dynamic models for this kind of systems is sometimes a difficult task. In fact, the direct application of traditional methods of robotics, for modelling and analysing such systems, usually does not lead to efficient and systematic algorithms. This work addre sses this issue: to present a modular approach to generate the dynamic model and through some convenient modifications, how we can make these methods more applicable to parallel structures as well. Kane’s formulati on to obtain the dynamic equations is shown to be one of the easiest ways to deal with redundant coordinates and kinematic constraints, so that a suitable c hoice of a set of coordinates allows the remaining of the modelling procedure to be computer aided. The advantages of this approach are discussed in the modelling of a 3-dof parallel asymmetric mechanisms.

Applying many-body expansion aiming to make ab in initio molecular dynamics more efficient

In this present work we present a methodology that aims to apply the many-body expansion to decrease the computational cost of ab initio molecular dynamics, keeping acceptable accuracy on the results. We implemented this methodology in a program which we called ManBo. In the many-body expansion approach, we partitioned the total energy E of the system in contributions of one body, two bodies, three bodies, etc., until the contribution of the Nth body [1-3]: E = E1 + E2 + E3 + …EN. The E1 term is the sum of the internal energy of the molecules; the term E2 is the energy due to interaction between all pairs of molecules; E3 is the energy due to interaction between all trios of molecules; and so on. In Manbo we chose to truncate the expansion in the contribution of two or three bodies, both for the calculation of the energy and for the calculation of the atomic forces. In order to partially include the many-body interactions neglected when we truncate the expansion, we can include an electrostatic embedding in the electronic structure calculations, instead of considering the monomers, pairs and trios as isolated molecules in space. In simulations we made we chose to simulate water molecules, and use the Gaussian 09 as external program to calculate the atomic forces and energy of the system, as well as reference program for analyzing the accuracy of the results obtained with the ManBo. The results show that the use of the many-body expansion seems to be an interesting approach for reducing the still prohibitive computational cost of ab initio molecular dynamics. The errors introduced on atomic forces in applying such methodology are very small. The inclusion of an embedding electrostatic seems to be a good solution for improving the results with only a small increase in simulation time. As we increase the level of calculation, the simulation time of ManBo tends to largely decrease in relation to a conventional BOMD simulation of Gaussian, due to better scalability of the methodology presented. References [1] E. E. Dahlke and D. G. Truhlar; J. Chem. Theory Comput., 3, 46 (2007). [2] E. E. Dahlke and D. G. Truhlar; J. Chem. Theory Comput., 4, 1 (2008). [3] R. Rivelino, P. Chaudhuri and S. Canuto; J. Chem. Phys., 118, 10593 (2003).

CID: an efficient complexity-invariant distance for time series

The ubiquity of time series data across almost all human endeavors has produced a great interest in time series data mining in the last decade. While dozens of classification algorithms have been applied to time series, recent empirical evidence strongly suggests that simple nearest neighbor classification is exceptionally difficult to beat. The choice of distance measure used by the nearest neighbor algorithm is important, and depends on the invariances required by the domain. For example, motion capture data typically requires invariance to warping, and cardiology data requires invariance to the baseline (the mean value). Similarly, recent work suggests that for time series clustering, the choice of clustering algorithm is much less important than the choice of distance measure used.In this work we make a somewhat surprising claim. There is an invariance that the community seems to have missed, complexity invariance. Intuitively, the problem is that in many domains the different classes may have different complexities, and pairs of complex objects, even those which subjectively may seem very similar to the human eye, tend to be further apart under current distance measures than pairs of simple objects. This fact introduces errors in nearest neighbor classification, where some complex objects may be incorrectly assigned to a simpler class. Similarly, for clustering this effect can introduce errors by “suggesting” to the clustering algorithm that subjectively similar, but complex objects belong in a sparser and larger diameter cluster than is truly warranted.We introduce the first complexity-invariant distance measure for time series, and show that it generally produces significant improvements in classification and clustering accuracy. We further show that this improvement does not compromise efficiency, since we can lower bound the measure and use a modification of triangular inequality, thus making use of most existing indexing and data mining algorithms. We evaluate our ideas with the largest and most comprehensive set of time series mining experiments ever attempted in a single work, and show that complexity-invariant distance measures can produce improvements in classification and clustering in the vast majority of cases.

Constraints on the origin of cosmics rays above '10 POT. 18' eV from large-scale anisotropy searches in data of the Pierre Auger observatory

A thorough search for large-scale anisotropies in the distribution of arrival directions of cosmic rays detected above '10 POT. 18' eV at the Pierre Auger Observatory is reported. For the first time, these large-scale anisotropy searches are performed as a function of both the right ascension and the declination and expressed in terms of dipole and quadrupole moments.Within the systematic uncertainties, no significant deviation from isotropy is revealed. Upper limits on dipole and quadrupole amplitudes are derived under the hypothesis that any cosmic ray anisotropy is dominated by such moments in this energy range. These upper limits provide constraints on the production of cosmic rays above '10 POT. 18' eV, since they allow us to challenge an origin from stationary galactic sources densely distributed in the galactic disk and emitting predominantly light particles in all directions.

Efficient 1535 nm light emission from an all-Si-based optical micro-cavity containing Er3+ and Yb3+ ions

This work reports on the construction and spectroscopic analyses of optical micro-cavities (OMCs) that efficiently emit at ~1535 nm. The emission wavelength matches the third transmission window of commercial optical fibers and the OMCs were entirely based on silicon. The sputtering deposition method was adopted in the preparation of the OMCs, which comprised two Bragg reflectors and one spacer layer made of either Er- or ErYb-doped amorphous silicon nitride. The luminescence signal extracted from the OMCs originated from the 4I13/2→4I15/2 transition (due to Er3+ ions) and its intensity showed to be highly dependent on the presence of Yb3+ ions.According to the results, the Er3+-related light emission was improved by a factor of 48 when combined with Yb3+ ions and inserted in the spacer layer of the OMC. The results also showed the effectiveness of the present experimental approach in producing Si-based light-emitting structures in which the main characteristics are: (a) compatibility with the actual microelectronics industry, (b) the deposition of optical quality layers with accurate composition control, and (c) no need of uncommon elements-compounds nor extensive thermal treatments. Along with the fundamental characteristics of the OMCs, this work also discusses the impact of the Er3+-Yb3+ ion interaction on the emission intensity as well as the potential of the present findings.