A study of neolignan compounds with biological activity against Paracoccidioides brasiliensis by using quantum chemical and chemometric methods

Métodos quimiométricos (estatísticos) são empregados para classificar um conjunto de compostos derivados de neolignanas com atividade biológica contra a Paracoccidioides brasiliensis. O método AM1 (Austin Model 1) foi utilizado para calcular um conjunto de descritores moleculares (propriedades) para os compostos em estudo. A seguir, os descritores foram analisados utilizando os seguintes métodos de reconhecimento de padrões: Análise de Componentes Principais (PCA), Análise Hierárquica de Agrupamentos (HCA) e o método de K-vizinhos mais próximos (KNN). Os métodos PCA e HCA mostraram-se bastante eficientes para classificação dos compostos estudados em dois grupos (ativos e inativos). Três descritores moleculares foram responsáveis pela separação entre os compostos ativos e inativos: energia do orbital molecular mais alto ocupado (EHOMO), ordem de ligação entre os átomos C1'-R7 (L14) e ordem de ligação entre os átomos C5'-R6 (L22). Como as variáveis responsáveis pela separação entre compostos ativos e inativos são descritores eletrônicos, conclui-se que efeitos eletrônicos podem desempenhar um importante papel na interação entre receptor biológico e compostos derivados de neolignanas com atividade contra a Paracoccidioides brasiliensis.

Pattern recognition issues on anisotropic smoothed particle hydrodynamics

This is a preliminary theoretical discussion on the computational requirements of the state of the art smoothed particle hydrodynamics (SPH) from the optics of pattern recognition and artificial intelligence. It is pointed out in the present paper that, when including anisotropy detection to improve resolution on shock layer, SPH is a very peculiar case of unsupervised machine learning. On the other hand, the free particle nature of SPH opens an opportunity for artificial intelligence to study particles as agents acting in a collaborative framework in which the timed outcomes of a fluid simulation forms a large knowledge base, which might be very attractive in computational astrophysics phenomenological problems like self-propagating star formation.

MATHEMATICAL ANALYSIS OF MAXIMUM POWER GENERATED BY PHOTOVOLTAIC SYSTEMS AND FITTING CURVES FOR STANDARD TEST CONDITIONS

The rural electrification is characterized by geographical dispersion of the population, low consumption, high investment by consumers and high cost. Moreover, solar radiation constitutes an inexhaustible source of energy and in its conversion into electricity photovoltaic panels are used. In this study, equations were adjusted to field conditions presented by the manufacturer for current and power of small photovoltaic systems. The mathematical analysis was performed on the photovoltaic rural system I- 100 from ISOFOTON, with power 300 Wp, located at the Experimental Farm Lageado of FCA/UNESP. For the development of such equations, the circuitry of photovoltaic cells has been studied to apply iterative numerical methods for the determination of electrical parameters and possible errors in the appropriate equations in the literature to reality. Therefore, a simulation of a photovoltaic panel was proposed through mathematical equations that were adjusted according to the data of local radiation. The results have presented equations that provide real answers to the user and may assist in the design of these systems, once calculated that the maximum power limit ensures a supply of energy generated. This real sizing helps establishing the possible applications of solar energy to the rural producer and informing the real possibilities of generating electricity from the sun.

Respiratory inductive plethysmography: a comparative study between isovolume maneuver calibration and qualitative diagnostic calibration in healthy volunteers assessed in different positions

Objective: To compare two methods of respiratory inductive plethysmography (RIP) calibration in three different positions. Methods: We evaluated 28 healthy subjects (18 women and 10 men), with a mean age of 25.4 +/- 3.9 years. For all of the subjects, isovolume maneuver calibration (ISOCAL) and qualitative diagnostic calibration (QDC) were used in the orthostatic, sitting, and supine positions. In order to evaluate the concordance between the two calibration methods, we used ANOVA and Bland-Altman plots. Results: The values of the constant of proportionality (X) were significantly different between ISOCAL and QDC in the three positions evaluated: 1.6 +/- 0.5 vs. 2.0 +/- 1.2, in the supine position, 2.5 +/- 0.8 vs. 0.6 +/- 0.3 in the sitting position, and 2.0 +/- 0.8 vs. 0.6 +/- 0.3 in the orthostatic position (p < 0.05 for all). Conclusions: Our results suggest that QDC is an inaccurate method for the calibration of RIP. The K values obtained with ISOCAL reveal that RIP should be calibrated for each position evaluated.

Pattern recognition analysis on heavy ion reaction data

One of the problems in the analysis of nucleus-nucleus collisions is to get information on the value of the impact parameter b. This work consists in the application of pattern recognition techniques aimed at associating values of b to groups of events. To this end, a support vec- tor machine (SVM) classifier is adopted to analyze multifragmentation reactions. This method allows to backtracing the values of b through a particular multidimensional analysis. The SVM classification con- sists of two main phase. In the first one, known as training phase, the classifier learns to discriminate the events that are generated by two different model:Classical Molecular Dynamics (CMD) and Heavy- Ion Phase-Space Exploration (HIPSE) for the reaction: 58Ni +48 Ca at 25 AMeV. To check the classification of events in the second one, known as test phase, what has been learned is tested on new events generated by the same models. These new results have been com- pared to the ones obtained through others techniques of backtracing the impact parameter. Our tests show that, following this approach, the central collisions and peripheral collisions, for the CMD events, are always better classified with respect to the classification by the others techniques of backtracing. We have finally performed the SVM classification on the experimental data measured by NUCL-EX col- laboration with CHIMERA apparatus for the previous reaction.

Fingerprint Recognition: Enhancement, Feature Extraction and Automatic Evaluation of Algorithms

The identification of people by measuring some traits of individual anatomy or physiology has led to a specific research area called biometric recognition. This thesis is focused on improving fingerprint recognition systems considering three important problems: fingerprint enhancement, fingerprint orientation extraction and automatic evaluation of fingerprint algorithms. An effective extraction of salient fingerprint features depends on the quality of the input fingerprint. If the fingerprint is very noisy, we are not able to detect a reliable set of features. A new fingerprint enhancement method, which is both iterative and contextual, is proposed. This approach detects high-quality regions in fingerprints, selectively applies contextual filtering and iteratively expands like wildfire toward low-quality ones. A precise estimation of the orientation field would greatly simplify the estimation of other fingerprint features (singular points, minutiae) and improve the performance of a fingerprint recognition system. The fingerprint orientation extraction is improved following two directions. First, after the introduction of a new taxonomy of fingerprint orientation extraction methods, several variants of baseline methods are implemented and, pointing out the role of pre- and post- processing, we show how to improve the extraction. Second, the introduction of a new hybrid orientation extraction method, which follows an adaptive scheme, allows to improve significantly the orientation extraction in noisy fingerprints. Scientific papers typically propose recognition systems that integrate many modules and therefore an automatic evaluation of fingerprint algorithms is needed to isolate the contributions that determine an actual progress in the state-of-the-art. The lack of a publicly available framework to compare fingerprint orientation extraction algorithms, motivates the introduction of a new benchmark area called FOE (including fingerprints and manually-marked orientation ground-truth) along with fingerprint matching benchmarks in the FVC-onGoing framework. The success of such framework is discussed by providing relevant statistics: more than 1450 algorithms submitted and two international competitions.

The therapeutic potential of the humoral pattern recognition molecule PTX3 in chronic lung infection caused by Pseudomonas aeruginosa

Chronic lung infections by Pseudomonas aeruginosa strains are a major cause of morbidity and mortality in cystic fibrosis (CF) patients. Although there is no clear evidence for a primary defect in the immune system of CF patients, the host is generally unable to clear P. aeruginosa from the airways. PTX3 is a soluble pattern recognition receptor that plays nonredundant roles in the innate immune response to fungi, bacteria, and viruses. In particular, PTX3 deficiency is associated with increased susceptibility to P. aeruginosa lung infection. To address the potential therapeutic effect of PTX3 in P. aeruginosa lung infection, we established persistent and progressive infections in mice with the RP73 clinical strain RP73 isolated from a CF patient and treated them with recombinant human PTX3. The results indicated that PTX3 has a potential therapeutic effect in P. aeruginosa chronic lung infection by reducing lung colonization, proinflammatory cytokine levels (CXCL1, CXCL2, CCL2, and IL-1β), and leukocyte recruitment in the airways. In models of acute infections and in in vitro assays, the prophagocytic effect of PTX3 was maintained in C1q-deficient mice and was lost in C3- and Fc common γ-chain-deficient mice, suggesting that facilitated recognition and phagocytosis of pathogens through the interplay between complement and FcγRs are involved in the therapeutic effect mediated by PTX3. These data suggested that PTX3 is a potential therapeutic tool in chronic P. aeruginosa lung infections, such as those seen in CF patients.

Design, Calibration, and Evaluation of Depth-of-Interaction-Capable PET Detector Modules

High-resolution, small-bore PET systems suffer from a tradeoff between system sensitivity, and image quality degradation. In these systems long crystals allow mispositioning of the line of response due to parallax error and this mispositioning causes resolution blurring, but long crystals are necessary for high system sensitivity. One means to allow long crystals without introducing parallax errors is to determine the depth of interaction (DOI) of the gamma ray interaction within the detector module. While DOI has been investigated previously, newly available solid state photomultipliers (SSPMs) well-suited to PET applications and allow new modules for investigation. Depth of interaction in full modules is a relatively new field, and so even if high performance DOI capable modules were available, the appropriate means to characterize and calibrate the modules are not. This work presents an investigation of DOI capable arrays and techniques for characterizing and calibrating those modules. The methods introduced here accurately and reliably characterize and calibrate energy, timing, and event interaction positioning. Additionally presented is a characterization of the spatial resolution of DOI capable modules and a measurement of DOI effects for different angles between detector modules. These arrays have been built into a prototype PET system that delivers better than 2.0 mm resolution with a single-sided-stopping-power in excess of 95% for 511 keV g's. The noise properties of SSPMs scale with the active area of the detector face, and so the best signal-to-noise ratio is possible with parallel readout of each SSPM photodetector pixel rather than multiplexing signals together. This work additionally investigates several algorithms for improving timing performance using timing information from multiple SSPM pixels when light is distributed among several photodetectors.

Analysis of pattern recognition techniques for in-air signature biometrics

As a result of advances in mobile technology, new services which benefit from the ubiquity of these devices are appearing. Some of these services require the identification of the subject since they may access private user information. In this paper, we propose to identify each user by drawing his/her handwritten signature in the air (in-airsignature). In order to assess the feasibility of an in-airsignature as a biometric feature, we have analysed the performance of several well-known patternrecognitiontechniques—Hidden Markov Models, Bayes classifiers and dynamic time warping—to cope with this problem. Each technique has been tested in the identification of the signatures of 96 individuals. Furthermore, the robustness of each method against spoofing attacks has also been analysed using six impostors who attempted to emulate every signature. The best results in both experiments have been reached by using a technique based on dynamic time warping which carries out the recognition by calculating distances to an average template extracted from several training instances. Finally, a permanence analysis has been carried out in order to assess the stability of in-airsignature over time.

On the suitability of Prototype Selection methods for kNN classification with distributed data

In the current Information Age, data production and processing demands are ever increasing. This has motivated the appearance of large-scale distributed information. This phenomenon also applies to Pattern Recognition so that classic and common algorithms, such as the k-Nearest Neighbour, are unable to be used. To improve the efficiency of this classifier, Prototype Selection (PS) strategies can be used. Nevertheless, current PS algorithms were not designed to deal with distributed data, and their performance is therefore unknown under these conditions. This work is devoted to carrying out an experimental study on a simulated framework in which PS strategies can be compared under classical conditions as well as those expected in distributed scenarios. Our results report a general behaviour that is degraded as conditions approach to more realistic scenarios. However, our experiments also show that some methods are able to achieve a fairly similar performance to that of the non-distributed scenario. Thus, although there is a clear need for developing specific PS methodologies and algorithms for tackling these situations, those that reported a higher robustness against such conditions may be good candidates from which to start.

Electrogram analysis and pacing are complimentary for recognition of abnormal conduction and far-field potentials during substrate mapping of infarct-related ventricular tachycardia.

BACKGROUND Mapping to identify scar-related ventricular tachycardia re-entry circuits during sinus rhythm focuses on sites with abnormal electrograms or pace-mapping findings of QRS morphology and long stimulus to QRS intervals. We hypothesized that (1) these methods do not necessarily identify the same sites and (2) some electrograms are far-field potentials that can be recognized by pacing. METHODS AND RESULTS From 12 patients with coronary disease and recurrent ventricular tachycardia undergoing catheter ablation, we retrospectively analyzed electrograms and pacing at 546 separate low bipolar voltage (<1.5 mV) sites. Electrograms were characterized as showing evidence of slow conduction if late potentials (56%) or fractionated potentials (76%) were present. Neither was present at (13%) sites. Pacing from the ablation catheter captured 70% of all electrograms. Higher bipolar voltage and fractionation were independent predictors for pace capture. There was a linear correlation between the stimulus to QRS duration during pacing and the lateness of a capturing electrogram (P<0.001), but electrogram and pacing markers of slow conduction were discordant at 40% of sites. Sites with far-field potentials, defined as those that remained visible and not captured by pacing stimuli, were identified at 48% of all pacing sites, especially in areas of low bipolar voltage and late potentials. Initial radiofrequency energy application rendered 74% of targeted sites electrically unexcitable. CONCLUSIONS Far-field potentials are common in scar areas. Combining analysis of electrogram characteristics and assessment of pace capture may refine identification of substrate targets for radiofrequency ablation.

Instrumentation for measuring pavement-vehicle interaction. Volume I: system description, operation, calibration and maintenance manual. Final report.

Federal Highway Administration, Structures and Applied Mechanics Division, Washington, D.C.

The Illinois pattern recognition computer (Illiac III) /

"Presented at the 18th Annual ACM National Conference, Denver, Colorado August 27, 1963"

Pattern recognition as knowledge-guided computer induction /

Bibliography: p. 39-41.