Extending the roughness of the data via transitive closures of similarity indexes

One main assumption in the theory of rough sets applied to information tables is that the elements that exhibit the same information are indiscernible (similar) and form blocks that can be understood as elementary granules of knowledge about the universe. We propose a variant of this concept defining a measure of similarity between the elements of the universe in order to consider that two objects can be indiscernible even though they do not share all the attribute values because the knowledge is partial or uncertain. The set of similarities define a matrix of a fuzzy relation satisfying reflexivity and symmetry but transitivity thus a partition of the universe is not attained. This problem can be solved calculating its transitive closure what ensure a partition for each level belonging to the unit interval [0,1]. This procedure allows generalizing the theory of rough sets depending on the minimum level of similarity accepted. This new point of view increases the rough character of the data because increases the set of indiscernible objects. Finally, we apply our results to a not real application to be capable to remark the differences and the improvements between this methodology and the classical one

Combining genetic and demographic data for the conservation of a Mediterranean habitat-forming species

The integration of ecological and evolutionary data is highly valuable for conservation planning. However, it has been rarely used in the marine realm, where the adequate design of marine protected areas (MPAs) is urgently needed. Here, we examined the interacting processes underlying the patterns of genetic structure and demographic strucuture of a highly vulnerable Mediterranean habitat-forming species (i.e. Paramuricea clavata (Risso, 1826)), with particular emphasis on the processes of contemporary dispersal, genetic drift, and colonization of a new population. Isolation by distance and genetic discontinuities were found, and three genetic clusters were detected; each submitted to variations in the relative impact of drift and gene flow. No founder effect was found in the new population. The interplay of ecology and evolution revealed that drift is strongly impacting the smallest, most isolated populations, where partial mortality of individuals was highest. Moreover, the eco-evolutionary analyses entailed important conservation implications for P. clavata. Our study supports the inclusion of habitat-forming organisms in the design of MPAs and highlights the need to account for genetic drift in the development of MPAs. Moreover, it reinforces the importance of integrating genetic and demographic data in marine conservation.

Advanced chemometric methods: Applicability on industrial data

Recent years have produced great advances in the instrumentation technology. The amount of available data has been increasing due to the simplicity, speed and accuracy of current spectroscopic instruments. Most of these data are, however, meaningless without a proper analysis. This has been one of the reasons for the overgrowing success of multivariate handling of such data. Industrial data is commonly not designed data; in other words, there is no exact experimental design, but rather the data have been collected as a routine procedure during an industrial process. This makes certain demands on the multivariate modeling, as the selection of samples and variables can have an enormous effect. Common approaches in the modeling of industrial data are PCA (principal component analysis) and PLS (projection to latent structures or partial least squares) but there are also other methods that should be considered. The more advanced methods include multi block modeling and nonlinear modeling. In this thesis it is shown that the results of data analysis vary according to the modeling approach used, thus making the selection of the modeling approach dependent on the purpose of the model. If the model is intended to provide accurate predictions, the approach should be different than in the case where the purpose of modeling is mostly to obtain information about the variables and the process. For industrial applicability it is essential that the methods are robust and sufficiently simple to apply. In this way the methods and the results can be compared and an approach selected that is suitable for the intended purpose. Differences in data analysis methods are compared with data from different fields of industry in this thesis. In the first two papers, the multi block method is considered for data originating from the oil and fertilizer industries. The results are compared to those from PLS and priority PLS. The third paper considers applicability of multivariate models to process control for a reactive crystallization process. In the fourth paper, nonlinear modeling is examined with a data set from the oil industry. The response has a nonlinear relation to the descriptor matrix, and the results are compared between linear modeling, polynomial PLS and nonlinear modeling using nonlinear score vectors.

Automatic evaluation and data generation for analytical chemistry instrumental analysis exercises

In general, laboratory activities are costly in terms of time, space, and money. As such, the ability to provide realistically simulated laboratory data that enables students to practice data analysis techniques as a complementary activity would be expected to reduce these costs while opening up very interesting possibilities. In the present work, a novel methodology is presented for design of analytical chemistry instrumental analysis exercises that can be automatically personalized for each student and the results evaluated immediately. The proposed system provides each student with a different set of experimental data generated randomly while satisfying a set of constraints, rather than using data obtained from actual laboratory work. This allows the instructor to provide students with a set of practical problems to complement their regular laboratory work along with the corresponding feedback provided by the system's automatic evaluation process. To this end, the Goodle Grading Management System (GMS), an innovative web-based educational tool for automating the collection and assessment of practical exercises for engineering and scientific courses, was developed. The proposed methodology takes full advantage of the Goodle GMS fusion code architecture. The design of a particular exercise is provided ad hoc by the instructor and requires basic Matlab knowledge. The system has been employed with satisfactory results in several university courses. To demonstrate the automatic evaluation process, three exercises are presented in detail. The first exercise involves a linear regression analysis of data and the calculation of the quality parameters of an instrumental analysis method. The second and third exercises address two different comparison tests, a comparison test of the mean and a t-paired test.

Intensity-duration-frequency ratios obtained from annual records and partial duration records in the locality of Pelotas - RS, Brazil

The intensity-duration-frequency occurrence ratio (IDF) is a tool commonly used for precipitation-runoff data transformation, which is established from observations of intense precipitations over a period sufficiently long as to allow the occurrence of extremes at the observation site. This study focused on verifying the existence or absence of new data, in terms of IDF ratio, by using partial duration records produced from data on maximum daily disaggregated rainfall for pre determined durations. The partial duration records considered a base value of 55 mm, totaling 279 values. After the rainfall series were established, their independence and seasonality were assessed. Using the Student's t-test statistics, it was established that no new data, as IDF ratio, emerged from the analysis of the partial duration series with the recommended base value of precipitation, as compared to the historical records.

Novel Regression Methods For Spectral Data

Singular Value Decomposition (SVD), Principal Component Analysis (PCA) and Multiple Linear Regression (MLR) are some of the mathematical pre- liminaries that are discussed prior to explaining PLS and PCR models. Both PLS and PCR are applied to real spectral data and their di erences and similarities are discussed in this thesis. The challenge lies in establishing the optimum number of components to be included in either of the models but this has been overcome by using various diagnostic tools suggested in this thesis. Correspondence analysis (CA) and PLS were applied to ecological data. The idea of CA was to correlate the macrophytes species and lakes. The di erences between PLS model for ecological data and PLS for spectral data are noted and explained in this thesis. i

Partial recovery of erythrocyte glycogen in diabetic rats treated with phenobarbital

Erythrocytes may play a role in glucose homeostasis during the postprandial period. Erythrocytes from diabetic patients are defective in glucose transport and metabolism, functions that may affect glycogen storage. Phenobarbital, a hepatic enzyme inducer, has been used in the treatment of patients with non-insulin-dependent diabetes mellitus (NIDDM), increasing the insulin-mediated glucose disposal. We studied the effects of phenobarbital treatment in vivo on glycemia and erythrocyte glycogen content in control and alloxan-diabetic rats during the postprandial period. In control rats (blood glucose, 73 to 111 mg/dl in femoral and suprahepatic veins) the erythrocyte glycogen content was 45.4 ± 1.1 and 39.1 ± 0.8 µg/g Hb (mean ± SEM, N = 4-6) in the femoral artery and vein, respectively, and 37.9 ± 1.1 in the portal vein and 47.5 ± 0.9 in the suprahepatic vein. Diabetic rats (blood glucose, 300-350 mg/dl) presented low (P<0.05) erythrocyte glycogen content, i.e., 9.6 ± 0.1 and 7.1 ± 0.7 µg/g Hb in the femoral artery and vein, respectively, and 10.0 ± 0.7 and 10.7 ± 0.5 in the portal and suprahepatic veins, respectively. After 10 days of treatment, phenobarbital (0.5 mg/ml in the drinking water) did not change blood glucose or erythrocyte glycogen content in control rats. In diabetic rats, however, it lowered (P<0.05) blood glucose in the femoral artery (from 305 ± 18 to 204 ± 45 mg/dl) and femoral vein (from 300 ± 11 to 174 ± 48 mg/dl) and suprahepatic vein (from 350 ± 10 to 174 ± 42 mg/dl), but the reduction was not sufficient for complete recovery. Phenobarbital also stimulated the glycogen synthesis, leading to a partial recovery of glycogen stores in erythrocytes. In treated rats, erythrocyte glycogen content increased to 20.7 ± 3.8 µg/g Hb in the femoral artery and 30.9 ± 0.9 µg/g Hb in the suprahepatic vein (P<0.05). These data indicate that phenobarbital activated some of the insulin-stimulated glucose metabolism steps which were depressed in diabetic erythrocytes, supporting the view that erythrocytes participate in glucose homeostasis

Viral membrane fusion: is glycoprotein G of rhabdoviruses a representative of a new class of viral fusion proteins?

Enveloped viruses always gain entry into the cytoplasm by fusion of their lipid envelope with a cell membrane. Some enveloped viruses fuse directly with the host cell plasma membrane after virus binding to the cell receptor. Other enveloped viruses enter the cells by the endocytic pathway, and fusion depends on the acidification of the endosomal compartment. In both cases, virus-induced membrane fusion is triggered by conformational changes in viral envelope glycoproteins. Two different classes of viral fusion proteins have been described on the basis of their molecular architecture. Several structural data permitted the elucidation of the mechanisms of membrane fusion mediated by class I and class II fusion proteins. In this article, we review a number of results obtained by our laboratory and by others that suggest that the mechanisms involved in rhabdovirus fusion are different from those used by the two well-studied classes of viral glycoproteins. We focus our discussion on the electrostatic nature of virus binding and interaction with membranes, especially through phosphatidylserine, and on the reversibility of the conformational changes of the rhabdovirus glycoprotein involved in fusion. Taken together, these data suggest the existence of a third class of fusion proteins and support the idea that new insights should emerge from studies of membrane fusion mediated by the G protein of rhabdoviruses. In particular, the elucidation of the three-dimensional structure of the G protein or even of the fusion peptide at different pH's might provide valuable information for understanding the fusion mechanism of this new class of fusion proteins.

Selection of patients for myocardial perfusion scintigraphy based on fuzzy sets theory applied to clinical-epidemiological data and treadmill test results

Coronary artery disease (CAD) is a worldwide leading cause of death. The standard method for evaluating critical partial occlusions is coronary arteriography, a catheterization technique which is invasive, time consuming, and costly. There are noninvasive approaches for the early detection of CAD. The basis for the noninvasive diagnosis of CAD has been laid in a sequential analysis of the risk factors, and the results of the treadmill test and myocardial perfusion scintigraphy (MPS). Many investigators have demonstrated that the diagnostic applications of MPS are appropriate for patients who have an intermediate likelihood of disease. Although this information is useful, it is only partially utilized in clinical practice due to the difficulty to properly classify the patients. Since the seminal work of Lotfi Zadeh, fuzzy logic has been applied in numerous areas. In the present study, we proposed and tested a model to select patients for MPS based on fuzzy sets theory. A group of 1053 patients was used to develop the model and another group of 1045 patients was used to test it. Receiver operating characteristic curves were used to compare the performance of the fuzzy model against expert physician opinions, and showed that the performance of the fuzzy model was equal or superior to that of the physicians. Therefore, we conclude that the fuzzy model could be a useful tool to assist the general practitioner in the selection of patients for MPS.

The effect of performing corrections on reported uterine cancer mortality data in the city of São Paulo

Reports of uterine cancer deaths that do not specify the subsite of the tumor threaten the quality of the epidemiologic appraisal of corpus and cervix uteri cancer mortality. The present study assessed the impact of correcting the estimated corpus and cervix uteri cancer mortality in the city of São Paulo, Brazil. The epidemiologic assessment of death rates comprised the estimation of magnitudes, trends (1980-2003), and area-level distribution based on three strategies: i) using uncorrected death certificate information; ii) correcting estimates of corpus and cervix uteri mortality by fully reallocating unspecified deaths to either one of these categories, and iii) partially correcting specified estimates by maintaining as unspecified a fraction of deaths certified as due to cancer of "uterus not otherwise specified". The proportion of uterine cancer deaths without subsite specification decreased from 42.9% in 1984 to 20.8% in 2003. Partial and full corrections resulted in considerable increases of cervix (31.3 and 48.8%, respectively) and corpus uteri (34.4 and 55.2%) cancer mortality. Partial correction did not change trends for subsite-specific uterine cancer mortality, whereas full correction did, thus representing an early indication of decrease for cervical neoplasms and stability for tumors of the corpus uteri in this population. Ecologic correlations between mortality and socioeconomic indices were unchanged for both strategies of correcting estimates. Reallocating unspecified uterine cancer mortality in contexts with a high proportion of these deaths has a considerable impact on the epidemiologic profile of mortality and provides more reliable estimates of cervix and corpus uteri cancer death rates and trends.

Partial purification of tightly bound mitochondrial hexokinase from maize (Zea mays L.) root membranes

In mammals, hexokinase (HK) is strategically located at the outer membrane of mitochondria bound to the porin protein. The mitochondrial HK is a crucial modulator of apoptosis and reactive oxygen species generation. In plants, these properties related to HK are unknown. In order to better understand the physiological role of non-cytosolic hexokinase (NC-HK) in plants, we developed a purification strategy here described. Crude extract of 400 g of maize roots (230 mg protein) contained a specific activity of 0.042 µmol G6P min-1 mg PTN-1. After solubilization with detergent two fractions were obtained by DEAE column chromatography, NC-HK 1 (specific activity = 3.6 µmol G6P min-1 mg PTN-1 and protein recovered = 0.7 mg) and NC-HK 2. A major purification (yield = 500-fold) was obtained after passage of NC-HK 1 through the hydrophobic phenyl-Sepharose column. The total amount of protein and activity recovered were 0.04 and 18%, respectively. The NC-HK 1 binds to the hydrophobic phenyl-Sepharose matrix, as observed for rat brain HK. Mild chymotrypsin digestion did not affect adsorption of NC-HK 1 to the hydrophobic column as it does for rat HK I. In contrast to mammal mitochondrial HK, glucose-6-phosphate, clotrimazole or thiopental did not dissociate NC-HK from maize (Zea mays) or rice (Oryza sativa) mitochondrial membranes. These data show that the interaction between maize or rice NC-HK to mitochondria differs from that reported in mammals, where the mitochondrial enzyme can be displaced by modulators or pharmacological agents known to interfere with the enzyme binding properties with the mitochondrial porin protein.

Organization of the marketing communication activities after fusion - the integration and the decision making processes

This master’s thesis was made in order to gain answers to the question of how the integration of the marketing communications and the decision making related to it in a geographically dispersed service organization could be improved in a situation where an organization has gone through a merger. The effects of the organizational design dimensions towards the integration of the marketing communications and the decision making related to it was the main focus. A case study as a research strategy offered a perfect frames for an exploratory study and the data collection was conducted by semi-structured interviews and observing. The main finding proved that from the chosen design dimensions, decentralization, coordination and power, could be found specific factors that in a geographically dispersed organization are affecting the integration of the marketing communications negatively. The effects can be seen mostly in the decision making processes, roles and in the division of responsibility, which are affecting the other dimensions and by this, the integration. In a post-merger situation, the coordination dimension and especially the information asymmetry and the information flow seem to have a largest affect towards the integration of the marketing communications. An asymmetric information distribution with the lack of business and marketing education resulted in low self-assurance and at the end in fragmented management and to the inability to set targets and make independent decisions. As conclusions it can be stated, that with the organizational design dimensions can the effects of a merger towards the integration process of the marketing communications to be evaluated.

Partial characterization and inactivation of peroxidases and polyphenol-oxidases of umbu-cajá (Spondias spp.)

A crude extract of Spondias spp. was evaluated for the influence of pH and temperature on the activity and stability of its peroxidases and polyphenol-oxidases. In order to evaluate the conditions for the inactivation of the enzymes by heat treatment and by addition of a reducing agent, a factorial experimental design (n = 3) was employed using the Statistica (6.0) software package for data analysis. The optimal conditions found for peroxidases were: pH = 5.0 and temperature = 40 ºC, and for polyphenol-oxidases they were pH = 7.0 and temperature = 40 ºC. The peroxidases and polyphenol-oxidases were stable at all pH values tested (3.0 - 10.0) and maintained more than 60% of their activity at temperatures above 30 and 40 ºC, respectively. To achieve the total inactivation of these enzymes, two alternatives can be suggested: incubation at 92 ºC for 3.15 minutes with 200 mg.L-1 of ascorbic acid or incubation at 96 ºC for 2.80 minutes with 100 mg.L-1 of ascorbic acid.

Partial purification and characterization of a bacteriocin produced by Enterococcus faecium 130 isolated from mozzarella cheese

Lactic acid bacteria are important in foods as potential probiotics and also due to the ability to produce antimicrobial compounds that can contribute for biopreservation. In this work, the bacteriocin produced by the food isolate Enterococcus faecium 130 was partially purified and characterized. The compound was active against Gram-positive bacteria, including Listeria monocytogenes. It was produced after 4 days of storage at a broad temperature range (4 to 37 °C); it was stable at pH ranging from 2 to 10 with no loss of activity after heating at 100 °C for 15 minutes. Bacteriocin was partially purified by the adsorption-desorption technique, and the analysis by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) showed a molecular mass of 3.5 to 6.5 kDa. These data encourage studies on application of this bacteriocin in food systems as an additional hurdle to microbial growth.

Urban Detection From Hyperspectral Images Using Dimension-Reduction Model and Fusion of Multiple Segmentations Based on Stuctural and Textural Features

Ce mémoire de maîtrise présente une nouvelle approche non supervisée pour détecter et segmenter les régions urbaines dans les images hyperspectrales. La méthode proposée n ́ecessite trois étapes. Tout d’abord, afin de réduire le coût calculatoire de notre algorithme, une image couleur du contenu spectral est estimée. A cette fin, une étape de réduction de dimensionalité non-linéaire, basée sur deux critères complémentaires mais contradictoires de bonne visualisation; à savoir la précision et le contraste, est réalisée pour l’affichage couleur de chaque image hyperspectrale. Ensuite, pour discriminer les régions urbaines des régions non urbaines, la seconde étape consiste à extraire quelques caractéristiques discriminantes (et complémentaires) sur cette image hyperspectrale couleur. A cette fin, nous avons extrait une série de paramètres discriminants pour décrire les caractéristiques d’une zone urbaine, principalement composée d’objets manufacturés de formes simples g ́eométriques et régulières. Nous avons utilisé des caractéristiques texturales basées sur les niveaux de gris, la magnitude du gradient ou des paramètres issus de la matrice de co-occurrence combinés avec des caractéristiques structurelles basées sur l’orientation locale du gradient de l’image et la détection locale de segments de droites. Afin de réduire encore la complexité de calcul de notre approche et éviter le problème de la ”malédiction de la dimensionnalité” quand on décide de regrouper des données de dimensions élevées, nous avons décidé de classifier individuellement, dans la dernière étape, chaque caractéristique texturale ou structurelle avec une simple procédure de K-moyennes et ensuite de combiner ces segmentations grossières, obtenues à faible coût, avec un modèle efficace de fusion de cartes de segmentations. Les expérimentations données dans ce rapport montrent que cette stratégie est efficace visuellement et se compare favorablement aux autres méthodes de détection et segmentation de zones urbaines à partir d’images hyperspectrales.