Genetic Variation among Major Human Geographic Groups Supports a Peculiar Evolutionary Trend in PAX9

A total of 172 persons from nine South Amerindian, three African and one Eskimo populations were studied in relation to the Paired box gene 9 (PAX9) exon 3 (138 base pairs) as well as its 5' and 3' flanking intronic segments (232 bp and 220 bp, respectively) and integrated with the information available for the same genetic region from individuals of different geographical origins. Nine mutations were scored in exon 3 and six in its flanking regions; four of them are new South American tribe-specific singletons. Exon3 nucleotide diversity is several orders of magnitude higher than its intronic regions. Additionally, a set of variants in the PAX9 and 101 other genes related with dentition can define at least some dental morphological differences between Sub-Saharan Africans and non-Africans, probably associated with adaptations after the modern human exodus from Africa. Exon 3 of PAX9 could be a good molecular example of how evolvability works.

Kernel machines for epilepsy diagnosis via EEG signal classification: A comparative study

Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.

Support vector machines for detecting age-related changes in running kinematics

Age-related changes in running kinematics have been reported in the literature using classical inferential statistics. However, this approach has been hampered by the increased number of biomechanical gait variables reported and subsequently the lack of differences presented in these studies. Data mining techniques have been applied in recent biomedical studies to solve this problem using a more general approach. In the present work, we re-analyzed lower extremity running kinematic data of 17 young and 17 elderly male runners using the Support Vector Machine (SVM) classification approach. In total, 31 kinematic variables were extracted to train the classification algorithm and test the generalized performance. The results revealed different accuracy rates across three different kernel methods adopted in the classifier, with the linear kernel performing the best. A subsequent forward feature selection algorithm demonstrated that with only six features, the linear kernel SVM achieved 100% classification performance rate, showing that these features provided powerful combined information to distinguish age groups. The results of the present work demonstrate potential in applying this approach to improve knowledge about the age-related differences in running gait biomechanics and encourages the use of the SVM in other clinical contexts. (C) 2010 Elsevier Ltd. All rights reserved.

Normal Versus Pathological Voice Signals Using Wavelet Analysis and Least Squares Support-Vector Machines

State of Sao Paulo Research Foundation (FAPESP)

Remote control of CNC machines using the CyberOPC communication system over public networks

During the last few years, the evolution of fieldbus and computers networks allowed the integration of different communication systems involving both production single cells and production cells, as well as other systems for business intelligence, supervision and control. Several well-adopted communication technologies exist today for public and non-public networks. Since most of the industrial applications are time-critical, the requirements of communication systems for remote control differ from common applications for computer networks accessing the Internet, such as Web, e-mail and file transfer. The solution proposed and outlined in this work is called CyberOPC. It includes the study and the implementation of a new open communication system for remote control of industrial CNC machines, making the transmission delay for time-critical control data shorter than other OPC-based solutions, and fulfilling cyber security requirements.

Comparison Between Voltage Control Structures of Synchronous Machines

This paper compares the behaviour of two different control structures of automatic voltage regulators of synchronous machines equipped with static excitation systems. These systems have a fully controlled thyristor bridge that supplies DC current to the rotor winding. The rectifier bridge is fed by the stator terminals through a step-down transformer. The first control structure, named ""Direct Control"", has a single proportional-integral (PI) regulator that compares stator voltage setpoint with measured voltage and acts directly on the thyristor bridge`s firing angle. This control structure is usually employed in commercial excitation systems for hydrogenerators. The second structure, named ""Cascade Control"", was inspired on control loops of commercial DC motor drives. Such drives employ two PIs in a cascade arrangement, the external PI deals with the motor speed while the internal one regulates the armature current. In the adaptation proposed, the external PI compares setpoint with the actual stator voltage and produces the setpoint to the internal PI-loop which controls the field current.

Stabilization of an amylase from Neurospora crassa by immobilization on highly activated supports

The amylase from Neurospora crassa is an interesting enzyme, having higher stability than amylase from Aspergillus oryzea under a broad range of pH values. Moreover, the N. crassa enzyme may be immobilized on different supports with good retention of enzyme activity. The best stabilizations were achieved using Eupergit C 250 L or glyoxyl agarose, with which the enzyme remained fully active at 60C for 24 h while the soluble enzyme remained about 17%. The glyoxyl agarose immobilized enzyme had high thermostability, high optimal temperature (65C) and broad pH/activity profile, suggesting that this enzyme has potential for food and industrial applications for starch modification.

An fMRI Normative Database for Connectivity Networks Using One-Class Support Vector Machines

The application of functional magnetic resonance imaging (fMRI) in neuroscience studies has increased enormously in the last decade. Although primarily used to map brain regions activated by specific stimuli, many studies have shown that fMRI can also be useful in identifying interactions between brain regions (functional and effective connectivity). Despite the widespread use of fMRI as a research tool, clinical applications of brain connectivity as studied by fMRI are not well established. One possible explanation is the lack of normal pattern, and intersubject variability-two variables that are still largely uncharacterized in most patient populations of interest. In the current study, we combine the identification of functional connectivity networks extracted by using Spearman partial correlation with the use of a one-class support vector machine in order construct a normative database. An application of this approach is illustrated using an fMRI dataset of 43 healthy Subjects performing a visual working memory task. In addition, the relationships between the results obtained and behavioral data are explored. Hum Brain Mapp 30:1068-1076, 2009. (C) 2008 Wiley-Liss. Inc.

The impact of functional connectivity changes on support vector machines mapping of fMRI data

Functional magnetic resonance imaging (fMRI) is currently one of the most widely used methods for studying human brain function in vivo. Although many different approaches to fMRI analysis are available, the most widely used methods employ so called ""mass-univariate"" modeling of responses in a voxel-by-voxel fashion to construct activation maps. However, it is well known that many brain processes involve networks of interacting regions and for this reason multivariate analyses might seem to be attractive alternatives to univariate approaches. The current paper focuses on one multivariate application of statistical learning theory: the statistical discrimination maps (SDM) based on support vector machine, and seeks to establish some possible interpretations when the results differ from univariate `approaches. In fact, when there are changes not only on the activation level of two conditions but also on functional connectivity, SDM seems more informative. We addressed this question using both simulations and applications to real data. We have shown that the combined use of univariate approaches and SDM yields significant new insights into brain activations not available using univariate methods alone. In the application to a visual working memory fMRI data, we demonstrated that the interaction among brain regions play a role in SDM`s power to detect discriminative voxels. (C) 2008 Elsevier B.V. All rights reserved.

Lectins and/or xyloglucans/alginate layers as supports for immobilization of dengue virus particles

Formation of stable thin films of mixed xyloglucan (XG) and alginate (ALG) onto Si/SiO2 wafers was achieved under pH 11.6, 50 mM CaCl2, and at 70 degrees C. XG-ALG films presented mean thickness of (16 +/- 2) nun and globules rich surface, as evidenced by means of ellipsometry and atomic force microscopy (AFM), respectively. The adsorption of two glucose/mannose-binding seed (Canavalia ensiformis and Dioclea altissima) lectins, coded here as ConA and DAlt, onto XG-ALG surfaces took place under pH 5. Under this condition both lectins present positive net charge. ConA and DAIt adsorbed irreversibly onto XG-ALG forming homogenous monolayers similar to(4 +/- 1)nm thick. Lectins adsorption was mainly driven by electrostatic interaction between lectins positively charged residues and carboxylated (negatively charged) ALG groups. Adhesion of four serotypes of dengue virus, DENV (1-4), particles to XG-ALG surfaces were observed by ellipsometry and AFM. The attachment of dengue particles onto XG-ALG films might be mediated by (i) H bonding between E protein (located at virus particle surface) polar residues and hydroxyl groups present on XG-ALG surfaces and (ii) electrostatic interaction between E protein positively charged residues and ALG carboxylic groups. DENV-4 serotype presented the weakest adsorption onto XG-ALG surfaces, indicating that E protein on DENV-4 surface presents net charge (amino acid sequence) different from E proteins of other serotypes. All four DENV particles serotypes adsorbed similarly onto lectin films adsorbed. Nevertheless, the addition of 0.005 mol/L of mannose prevented dengue particles from adsorbing onto lectin films. XG-ALG and lectin layers serve as potential materials for the development of diagnostic methods for dengue. (c) 2008 Elsevier B.V. All rights reserved.

Mitochondrial population genomics supports a single pre-Clovis origin with a coastal route for the peopling of the Americas

It is well accepted that the Americas were the last continents reached by modern humans, most likely through Beringia. However, the precise time and mode of the colonization of the New World remain hotly disputed issues. Native American populations exhibit almost exclusively five mitochondrial DNA (mtDNA) haplogroups (A-D and X). Haplogroups A-D are also frequent in Asia, suggesting a northeastern Asian origin of these lineages. However, the differential pattern of distribution and frequency of haplogroup X led some to suggest that it may represent an independent migration to the Americas. Here we show, by using 86 complete mitochondrial genomes, that all Native American haplogroups, including haplogroup X, were part of a single founding population, thereby refuting multiple-migration models. A detailed demographic history of the mtDNA sequences estimated with a Bayesian coalescent method indicates a complex model for the peopling of the Americas, in which the initial differentiation from Asian populations ended with a moderate bottleneck in Beringia during the last glacial maximum (LGM), around similar to 23,000 to similar to 19,000 years ago. Toward the end of the LGM, a strong population expansion started similar to 18,000 and finished similar to 15,000 years ago. These results support a pre-Clovis occupation of the New World, suggesting a rapid settlement of the continent along a Pacific coastal route.

Characterization of spliced leader genes of Trypanosoma (Megatrypanum) theileri: phylogeographical analysis of Brazilian isolates from cattle supports spatial clustering of genotypes and parity with ribosomal markers

Trypanosoma (Megatrypanum) theileri from cattle and trypanosomes of other artiodactyls form a clade of closely related species in analyses using ribosomal sequences. Analysis of polymorphic sequences of a larger number of trypanosomes from broader geographical origins is required to evaluate the Clustering of isolates as suggested by previous studies. Here, we determined the sequences of the spliced leader (SL) genes of 21 isolates from cattle and 2 from water buffalo from distant regions of Brazil. Analysis of SL gene repeats revealed that the 5S rRNA gene is inserted within the intergenic region. Phylogeographical patterns inferred using SL sequences showed at least 5 major genotypes of T. theileri distributed in 2 strongly divergent lineages. Lineage TthI comprises genotypes IA and IB from buffalo and cattle, respectively, from the Southeast and Central regions, whereas genotype IC is restricted to cattle from the Southern region. Lineage Tth II includes cattle genotypes IIA, which is restricted to the North and Northeast, and IIB, found in the Centre, West, North and Northeast. PCR-RFLP of SL genes revealed valuable markers for genotyping T. theileri. The results of this study emphasize the genetic complexity and corroborate the geographical structuring of T. theileri genotypes found in cattle.

Phylogenetic analysis of Trypanosoma vivax supports the separation of South American/West African from East African isolates and a new T-vivax-like genotype infecting a nyala antelope from Mozambique

In this study, we addressed the phylogenetic and taxonomic relationships of Trypanosoma vivax and related trypanosomes nested in the subgenus Duttonella through combined morphological and phylogeographical analyses. We previously demonstrated that the clade T. vivax harbours a homogeneous clade comprising West African/South American isolates and the heterogeneous East African isolates. Herein we characterized a trypanosome isolated from a nyala antelope (Tragelaphus angasi) wild-caught in Mozambique (East Africa) and diagnosed as T. vivax-like based on biological, morphological and molecular data. Phylogenetic relationships, phylogeographical patterns and estimates of genetic divergence were based on SSU and ITS rDNA sequences of T. vivax from Brazil and Venezuela (South America), Nigeria (West Africa), and from T. vivax-like trypanosomes from Mozambique, Kenya and Tanzania (East Africa). Despite being well-supported within the T. vivax clade, the nyala trypanosome was highly divergent from all other T. vivax and T. vivax-like trypanosomes, even those from East Africa. Considering its host origin, morphological features, behaviour in experimentally infected goats, phylogenetic placement, and genetic divergence this isolate represents a new genotype of trypanosome closely phylogenetically related to T. vivax. This study corroborated the high complexity and the existence of distinct genotypes yet undescribed within the subgenus Duttonella.

Checking Completeness of Tests for Finite State Machines

In testing from a Finite State Machine (FSM), the generation of test suites which guarantee full fault detection, known as complete test suites, has been a long-standing research topic. In this paper, we present conditions that are sufficient for a test suite to be complete. We demonstrate that the existing conditions are special cases of the proposed ones. An algorithm that checks whether a given test suite is complete is given. The experimental results show that the algorithm can be used for relatively large FSMs and test suites.

On the Stabilization of Gold Nanoparticles over Silica-Based Magnetic Supports Modified with Organosilanes

The immobilization of gold nanoparticles (Au NPs) on silica is made possible by the functionalization of the silica surfaces with organosilanes. Au NPs could only be stabilized and firmly attached to silica-support surfaces that were previously modified with amino groups. Au NPs could not be stabilized on bare silica surfaces and most of the NPs were then found in the solution. The metal-support interactions before and after the Au NP formation, observed by X-ray absorption fine structure spectroscopy (XAFS), indicate a stronger interaction of gold-(III) ions with amino-modified silica surfaces than with the silanol groups in bare silica. An amino-modified, silica-based, magnetic support was used to prepare an active Au NP catalyst for the chemoselective oxidation of alcohols, a reaction of great interest for the fine chemical industry.