On the manifold structure of the set of unparameterized embeddings with low regularity

Given manifolds M and N, with M compact, we study the geometrical structure of the space of embeddings of M into N, having less regularity than C(infinity) quotiented by the group of diffeomorphisms of M.

Dynamic Changes in the Mental Rotation Network Revealed by Pattern Recognition Analysis of fMRI Data

We investigated the temporal dynamics and changes in connectivity in the mental rotation network through the application of spatio-temporal support vector machines (SVMs). The spatio-temporal SVM [Mourao-Miranda, J., Friston, K. J., et al. (2007). Dynamic discrimination analysis: A spatial-temporal SVM. Neuroimage, 36, 88-99] is a pattern recognition approach that is suitable for investigating dynamic changes in the brain network during a complex mental task. It does not require a model describing each component of the task and the precise shape of the BOLD impulse response. By defining a time window including a cognitive event, one can use spatio-temporal fMRI observations from two cognitive states to train the SVM. During the training, the SVM finds the discriminating pattern between the two states and produces a discriminating weight vector encompassing both voxels and time (i.e., spatio-temporal maps). We showed that by applying spatio-temporal SVM to an event-related mental rotation experiment, it is possible to discriminate between different degrees of angular disparity (0 degrees vs. 20 degrees, 0 degrees vs. 60 degrees, and 0 degrees vs. 100 degrees), and the discrimination accuracy is correlated with the difference in angular disparity between the conditions. For the comparison with highest accuracy (08 vs. 1008), we evaluated how the most discriminating areas (visual regions, parietal regions, supplementary, and premotor areas) change their behavior over time. The frontal premotor regions became highly discriminating earlier than the superior parietal cortex. There seems to be a parcellation of the parietal regions with an earlier discrimination of the inferior parietal lobe in the mental rotation in relation to the superior parietal. The SVM also identified a network of regions that had a decrease in BOLD responses during the 100 degrees condition in relation to the 0 degrees condition (posterior cingulate, frontal, and superior temporal gyrus). This network was also highly discriminating between the two conditions. In addition, we investigated changes in functional connectivity between the most discriminating areas identified by the spatio-temporal SVM. We observed an increase in functional connectivity between almost all areas activated during the 100 degrees condition (bilateral inferior and superior parietal lobe, bilateral premotor area, and SMA) but not between the areas that showed a decrease in BOLD response during the 100 degrees condition.

A quantum chemical study on a set of non-imidazole H(3) antihistamine molecules

Molecular orbital calculations were carried out on a set of 28 non-imidazole H(3) antihistamine compounds using the Hartree-Fock method in order to investigate the possible relationships between electronic structural properties and binding affinity for H3 receptors (pK(i)). It was observed that the frontier effective-for-reaction molecular orbital (FERMO) energies were better correlated with pK(i) values than highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energy values. Exploratory data analysis through hierarchical cluster (HCA) and principal component analysis (PCA) showed a separation of the compounds in two sets, one grouping the molecules with high pK(i) values, the other gathering low pK(i) value compounds. This separation was obtained with the use of the following descriptors: FERMO energies (epsilon(FERMO)), charges derived from the electrostatic potential on the nitrogen atom (N(1)), electronic density indexes for FERMO on the N(1) atom (Sigma((FERMO))c(i)(2)). and electrophilicity (omega`). These electronic descriptors were used to construct a quantitative structure-activity relationship (QSAR) model through the partial least-squares (PLS) method with three principal components. This model generated Q(2) = 0.88 and R(2) = 0.927 values obtained from a training set and external validation of 23 and 5 molecules, respectively. After the analysis of the PLS regression equation and the values for the selected electronic descriptors, it is suggested that high values of FERMO energies and of Sigma((FERMO))c(i)(2), together with low values of electrophilicity and pronounced negative charges on N(1) appear as desirable properties for the conception of new molecules which might have high binding affinity. 2010 Elsevier Inc. All rights reserved.

Classification of Parkinson’s Disease using MultiPass Lvq,Logistic Model Tree,K-Star for Audio Data set : Classification of Parkinson Disease using Audio Dataset

Parkinson's disease (PD) is a degenerative illness whose cardinal symptoms include rigidity, tremor, and slowness of movement. In addition to its widely recognized effects PD can have a profound effect on speech and voice.The speech symptoms most commonly demonstrated by patients with PD are reduced vocal loudness, monopitch, disruptions of voice quality, and abnormally fast rate of speech. This cluster of speech symptoms is often termed Hypokinetic Dysarthria.The disease can be difficult to diagnose accurately, especially in its early stages, due to this reason, automatic techniques based on Artificial Intelligence should increase the diagnosing accuracy and to help the doctors make better decisions. The aim of the thesis work is to predict the PD based on the audio files collected from various patients.Audio files are preprocessed in order to attain the features.The preprocessed data contains 23 attributes and 195 instances. On an average there are six voice recordings per person, By using data compression technique such as Discrete Cosine Transform (DCT) number of instances can be minimized, after data compression, attribute selection is done using several WEKA build in methods such as ChiSquared, GainRatio, Infogain after identifying the important attributes, we evaluate attributes one by one by using stepwise regression.Based on the selected attributes we process in WEKA by using cost sensitive classifier with various algorithms like MultiPass LVQ, Logistic Model Tree(LMT), K-Star.The classified results shows on an average 80%.By using this features 95% approximate classification of PD is acheived.This shows that using the audio dataset, PD could be predicted with a higher level of accuracy.

As mudanças na organização da produção na indústria gáfica do Grande ABC: um estudo sobre o segmento off set

O presente trabalho tem por objetivo caracterizar a indústria gráfica do ponto de vista da gestão, tecnologia, inovação e competição. A economia ao longo de sua história foi marcante por alguma situação peculiar que a caracterizasse. Em particular a partir da década de 1960 acompanhamos o crescimento em larga escala na região do Grande ABC onde, a indústria automobilística e seus fornecedores necessitaram de maior estrutura e apoio para as suas operações, provocando alterações nos modos de atuação das empresas industriais no país. Nessa mesma direção pelas necessidades criadas à época, a indústria gráfica na região do ABC também teve seu crescimento para atender a demanda e, criando o caráter da regionalidade e se fortalecendo economicamente. Entretanto a partir da década de 1980 com as crises econômicas e a abertura de mercado, houve uma redução nos postos de trabalho, mas as empresas também alteraram as formas de produzir. O trabalho de campo foi apoiado num referencial teórico baseado na revisão bibliográfica e um roteiro de entrevistas que orientou a coleta de dados. Na presente pesquisa foram realizadas entrevistas com os sujeitos relacionados e verificação de documentos. A análise realizada buscou confrontar os dados coletados e sistematizados com o quadro conceitual utilizado para a elaboração da pesquisa, possibilitando apurar as principais transformações verificadas no segmento estudado, bem como oferecendo embasamento para a tomada de decisão dos atores econômicos envolvidos com o desenvolvimento da indústria gráfica no Grande ABC.

Graphical models and point set matching

Point pattern matching in Euclidean Spaces is one of the fundamental problems in Pattern Recognition, having applications ranging from Computer Vision to Computational Chemistry. Whenever two complex patterns are encoded by two sets of points identifying their key features, their comparison can be seen as a point pattern matching problem. This work proposes a single approach to both exact and inexact point set matching in Euclidean Spaces of arbitrary dimension. In the case of exact matching, it is assured to find an optimal solution. For inexact matching (when noise is involved), experimental results confirm the validity of the approach. We start by regarding point pattern matching as a weighted graph matching problem. We then formulate the weighted graph matching problem as one of Bayesian inference in a probabilistic graphical model. By exploiting the existence of fundamental constraints in patterns embedded in Euclidean Spaces, we prove that for exact point set matching a simple graphical model is equivalent to the full model. It is possible to show that exact probabilistic inference in this simple model has polynomial time complexity with respect to the number of elements in the patterns to be matched. This gives rise to a technique that for exact matching provably finds a global optimum in polynomial time for any dimensionality of the underlying Euclidean Space. Computational experiments comparing this technique with well-known probabilistic relaxation labeling show significant performance improvement for inexact matching. The proposed approach is significantly more robust under augmentation of the sizes of the involved patterns. In the absence of noise, the results are always perfect.

The set of equilibria of first-price auctions

In this note I specify the class of functions that are equilibria of symmetric first-price auctions.

A linguagem de Oscar Niemeyer

Este trabalho tem como objetivo a descrição dos elementos que caracterizam a singularidade da linguagem arquitetônica de Oscar Niemeyer. Argumenta que a identificação de tais elementos passa pelo escrutínio de aspectos não visíveis da obra do arquiteto. A identificação foi possível a partir da análise de edifícios caracterizados pelo perfil curvilíneo e da construção de um modelo que associa os elementos compositivos utilizados por Niemeyer a uma Gramática de Formas. A utilização do modelo possibilitou revelar os princípios generativos - conjunto de regras, vocabulário e relações geométricas – que caracterizam o estilo – ou linguagem arquitetônica de Niemeyer. Ajudou ainda a demonstrar como a linguagem de Niemeyer associa de forma original, operações de transformação como rotação, reflexão, e translação a um vocabulário de curvas. A associação é parametrizada segundo um traçado regulador baseado na seção áurea. Em suas conclusões o trabalho sugere possibilidades de desenvolvimento desta gramática para todas as figuras utilizadas por Niemeyer e a aplicação de princípios generativos no ensino de arquitetura.

Produção e qualidade fisiológica de sementes de soja avaliadas na semeadura de inverno

O cultivo da soja fora da época convencional pode ser uma alternativa de rotação de cultura além de proporcionar sementes de melhor qualidade fisiológica, que podem ser utilizadas na semeadura da próxima safra diminuindo o período de armazenamento. O trabalho de pesquisa teve por objetivo avaliar o comportamento de sete cultivares de soja, em três densidades populacionais, quanto ao porte e altura de inserção da primeira vagem, assim como quanto à produção e qualidade fisiológica das sementes, semeadas no período de inverno, na região de Selvíria-MS. O delineamento experimental foi em blocos casualizados, com quatro repetições, dispostos em esquema fatorial 7 ×3. Os tratamentos constaram de sete cultivares (IAC-16, IAC-Foscarin 31, FT-2, IAC-17, IAC-8, Doko e FT-Cristalina) e três densidades de plantas (300, 400 e 500 mil plantas ha-1). O ciclo da soja foi reduzido no cultivo de inverno, principalmente nos cultivares considerados tardios. O fotoperíodo no cultivo de inverno reduziu o período entre o florescimento e a maturação. O cultivar IAC-8 foi o menos sensível ao fotoperíodo, possuindo maturação em época semelhante aos cultivares tardios, e apresentou as melhores características agronômicas para o cultivo no período de inverno. É aconselhável o aumento de densidade de semeadura quando do uso de cultivares precoces em cultivos de inverno. Não é aconselhável armazenar sementes em condições ambientes, principalmente com valores de germinação próximo ao limite inferior desejável (80%).