Application of differential scanning calorimetry in hair samples as a possible tool in Forensic Science

A calorimetria Exploratória Diferencial (DSC) foi utilizada para estudar o comportamento térmico de amostras de cabelo e verificar a possibilidade de identificar um indivíduo com base nas curvas DSC de um banco de dados. Amostras de cabelo de estudantes e funcionários do Instituto de Química de Araraquara UNESP, foram obtidas para construir um banco de dados. Procurou-se assim identificar de um indivíduo sob incógnita, utilizando-se a curva DSC deste banco de dados.

Sintering of tin oxide and its applications in electronics and processing of high purity optical glasses

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Multi-wavelength holography in Bi12TiO20 crystals: Applications in refractometry

We present a recent development in holography with multimode, large free-spectral range (FSR) diode lasers in photorefractive sillenite crystals. A novel refractometry method based on this type of holographic recording in Bi12TiO20 (BTO) crystals is proposed. The holographic image of a prism-shaped transparent sample appears covered of interference fringes, and as the sample is properly translated, the fringes run along the holographic image. An expression providing the refractive index of the medium as a function of the sample displacement and the correspondent number of running fringes was derived. The refractive indexes of optical (BK7) glass, ethanol, hexan, cumene and aqueous solution of NaCl with different concentrations were measured in order to test the method. The obtained results are in good agreement with the ones reported in literature or measured by us using a commercial Abbe refractometre. (c) 2006 Elsevier B.V. All rights reserved.

Difference variance dispersion graphs for comparing response surface designs with applications in food technology

Variance dispersion graphs have become a popular tool in aiding the choice of a response surface design. Often differences in response from some particular point, such as the expected position of the optimum or standard operating conditions, are more important than the response itself. We describe two examples from food technology. In the first, an experiment was conducted to find the levels of three factors which optimized the yield of valuable products enzymatically synthesized from sugars and to discover how the yield changed as the levels of the factors were changed from the optimum. In the second example, an experiment was conducted on a mixing process for pastry dough to discover how three factors affected a number of properties of the pastry, with a view to using these factors to control the process. We introduce the difference variance dispersion graph (DVDG) to help in the choice of a design in these circumstances. The DVDG for blocked designs is developed and the examples are used to show how the DVDG can be used in practice. In both examples a design was chosen by using the DVDG, as well as other properties, and the experiments were conducted and produced results that were useful to the experimenters. In both cases the conclusions were drawn partly by comparing responses at different points on the response surface.

Porous polyethylene for tissue engineering applications in diabetic rats treated with calcitonin: Histomorphometric analysis

Purpose: The purpose of this work was to study the bone tissue reaction after porous polyethylene (Polipore) implantation into surgical defects in the parietal bones of rats with streptozotocin-induced diabetes, treated with salmon calcitonin. Materials and Methods: Porous polyethylene implants were placed in bone defects created in 36 adult female rats. The rats were divided into 3 equal groups: diabetic treated with calcitonin (DCa), diabetic (D), and control (C). The animals of the DCa group received applications of salmon calcitonin on alternating days immediately after the surgery until sacrifice. The rats were sacrificed after 15, 30, 60, and 90 days, and the defects were examined histologically and statistically through histomorphometric analysis. Results: Histomorphometric analysis showed that there was no statistically significant difference in the mean quantity of inflammatory cells among all study groups after 15 and 90 days. At 30 days, a statistically significant difference was observed between the D and C groups and the D and DCa groups. At 60 days, there was no statistically significant difference between the D and DCa groups. Discussion: Porous polyethylene can be considered an option for implant material when there are investigations that prove its biocompatibility and stability in the host tissues. Salmon calcitonin positively aided the bone repair and attenuated the inflammatory response until 30 days after the surgery. Conclusion: Porous polyethylene was tolerated by the host tissues in all groups, and moderate chronic inflammatory reaction was observed up to the 90-day period. Salmon calcitonin attenuated the inflammatory response up until 30 days.

ARISupport - Interaction support for augmented reality systems

The communication between user and software is a basic stage in any Interaction System project. In interactive systems, this communication is established by the means of a graphical interface, whose objective is to supply a visual representation of the main entities and functions present in the Virtual Environment. New ways of interacting in computational systems have been minimizing the gap in the relationship between man and computer, and therefore enhancing its usability. The objective of this paper, therefore, is to present a proposal for a non-conventional user interface library called ARISupport, which supplies ARToolKit applications developers with an opportunity to create simple GUI interfaces, and provides some of the functionality used in Augmented Reality systems. © Springer-Verlag Berlin Heidelberg 2005.

Implementation of filters for image pre-processing for leaf analyses in plantations

In this work an image pre-processing module has been developed to extract quantitative information from plantation images with various degrees of infestation. Four filters comprise this module: the first one acts on smoothness of the image, the second one removes image background enhancing plants leaves, the third filter removes isolated dots not removed by the previous filter, and the fourth one is used to highlight leaves' edges. At first the filters were tested with MATLAB, for a quick visual feedback of the filters' behavior. Then the filters were implemented in the C programming language. At last, the module as been coded in VHDL for the implementation on a Stratix II family FPGA. Tests were run and the results are shown in this paper. © 2008 Springer-Verlag Berlin Heidelberg.

A framework for learning in humanoid simulated robots

One of the most important characteristics of intelligent activity is the ability to change behaviour according to many forms of feedback. Through learning an agent can interact with its environment to improve its performance over time. However, most of the techniques known that involves learning are time expensive, i.e., once the agent is supposed to learn over time by experimentation, the task has to be executed many times. Hence, high fidelity simulators can save a lot of time. In this context, this paper describes the framework designed to allow a team of real RoboNova-I humanoids robots to be simulated under USARSim environment. Details about the complete process of modeling and programming the robot are given, as well as the learning methodology proposed to improve robot's performance. Due to the use of a high fidelity model, the learning algorithms can be widely explored in simulation before adapted to real robots. © 2008 Springer-Verlag Berlin Heidelberg.

Automatic classification of enzyme family in protein annotation

Most of the tasks in genome annotation can be at least partially automated. Since this annotation is time-consuming, facilitating some parts of the process - thus freeing the specialist to carry out more valuable tasks - has been the motivation of many tools and annotation environments. In particular, annotation of protein function can benefit from knowledge about enzymatic processes. The use of sequence homology alone is not a good approach to derive this knowledge when there are only a few homologues of the sequence to be annotated. The alternative is to use motifs. This paper uses a symbolic machine learning approach to derive rules for the classification of enzymes according to the Enzyme Commission (EC). Our results show that, for the top class, the average global classification error is 3.13%. Our technique also produces a set of rules relating structural to functional information, which is important to understand the protein tridimensional structure and determine its biological function. © 2009 Springer Berlin Heidelberg.

Towards a java bytecodes compiler for nios II soft-core processor

Reconfigurable computing is one of the most recent research topics in computer science. The Altera - Nios II soft-core processor can be included in a large set of reconfigurable architectures, especially because it is designed in software, allowing it to be configured according to the application. The recent growth in applications that demand reconfigurable computing made necessary the building of compilers that translate high level languages source codes into reconfigurable devices instruction sets. In this paper we present a compiler that takes as input the bytecodes generated by a Java front-end compiler and generates a set of instructions that attends to the Nios II processor instruction set rules. Our work shows how we process Java bytecodes to the intermediate code, in the Nios II instructions format, and build the control flow and the control dependence graphs. © 2009 IEEE.

JSEG-based image segmentation in computer vision for agricultural mobile robot navigation

This project aims to apply image processing techniques in computer vision featuring an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of patterns in which reasonably accurate results were obtained.

ENCORE: Enhanced code Galileo receiver for land management applications in Brazil

Taking benefit of the new Galileo ranging signals, the ENCORE (Enhanced Code Galileo Receiver) project aims to develop a low-cost Land Management Application to cover needs of the Brazilian market in terms of geo-referencing and rural/urban cadastre, using a low-cost Enhanced Galileo Code Receiver as baseline. Land management applications require precision and accuracy levels from a few to several decimetres that are under-met with current pseudorange-based receiver and over-met with phase observations. This situation leads either to a waste of resources, or to lack of accuracy. In this project, it is proposed to fill this gap using the new possibilities of the Galileo ranging signals, in particular E5 AltBOC and E1 CBOC. This approach reduces the cost of the end-user solution, helping the rapid penetration of Galileo technology outside Europe. ©2010 IEEE.

Improving accuracy and speed of optimum-path forest classifier using combination of disjoint training subsets

The Optimum-Path Forest (OPF) classifier is a recent and promising method for pattern recognition, with a fast training algorithm and good accuracy results. Therefore, the investigation of a combining method for this kind of classifier can be important for many applications. In this paper we report a fast method to combine OPF-based classifiers trained with disjoint training subsets. Given a fixed number of subsets, the algorithm chooses random samples, without replacement, from the original training set. Each subset accuracy is improved by a learning procedure. The final decision is given by majority vote. Experiments with simulated and real data sets showed that the proposed combining method is more efficient and effective than naive approach provided some conditions. It was also showed that OPF training step runs faster for a series of small subsets than for the whole training set. The combining scheme was also designed to support parallel or distributed processing, speeding up the procedure even more. © 2011 Springer-Verlag.

LUTS: A lightweight user-level transaction scheduler

Software Transactional Memory (STM) systems have poor performance under high contention scenarios. Since many transactions compete for the same data, most of them are aborted, wasting processor runtime. Contention management policies are typically used to avoid that, but they are passive approaches as they wait for an abort to happen so they can take action. More proactive approaches have emerged, trying to predict when a transaction is likely to abort so its execution can be delayed. Such techniques are limited, as they do not replace the doomed transaction by another or, when they do, they rely on the operating system for that, having little or no control on which transaction should run. In this paper we propose LUTS, a Lightweight User-Level Transaction Scheduler, which is based on an execution context record mechanism. Unlike other techniques, LUTS provides the means for selecting another transaction to run in parallel, thus improving system throughput. Moreover, it avoids most of the issues caused by pseudo parallelism, as it only launches as many system-level threads as the number of available processor cores. We discuss LUTS design and present three conflict-avoidance heuristics built around LUTS scheduling capabilities. Experimental results, conducted with STMBench7 and STAMP benchmark suites, show LUTS efficiency when running high contention applications and how conflict-avoidance heuristics can improve STM performance even more. In fact, our transaction scheduling techniques are capable of improving program performance even in overloaded scenarios. © 2011 Springer-Verlag.

How bioinformatics enables livestock applied sciences in the genomic era

This review paper presents the three main approaches currently used in livestock genomic sciences where the bioinfomatics plays a critical role. They are named as Genomic Selection (GS), Genome Wide Association Study (GWAS) and Signatures of Selection (SS). The subsides for the construction of this article were generated in a current project (started in 2011), so called Zebu Genome Consortium (ZGC), which joins researchers from different institutions and countries, aiming to scientifically explore genomic information of Bos taurus indicus cattle breeds and deliver useful information to breeders and academic community, specially from the tropical regions of the world. © 2012 Springer-Verlag.