STATISTICAL ANALYSYS OF THE SCFE OF A BRAZILAN MINERAL COAL

The influence of some process variables on the productivity of the fractions (liquid yield times fraction percent) obtained from SCFE of a Brazilian mineral coal using isopropanol and ethanol as primary solvents is analyzed using statistical techniques. A full factorial 23 experimental design was adopted to investigate the effects of process variables (temperature, pressure and cosolvent concentration) on the extraction products. The extracts were analyzed by the Preparative Liquid Chromatography-8 fractions method (PLC-8), a reliable, non destructive solvent fractionation method, especially developed for coal-derived liquids. Empirical statistical modeling was carried out in order to reproduce the experimental data. Correlations obtained were always greater than 0.98. Four specific process criteria were used to allow process optimization. Results obtained show that it is not possible to maximize both extract productivity and purity (through the minimization of heavy fraction content) simultaneously by manipulating the mentioned process variables.

A statistical approach to define some tofu processing conditions

The aim of this work was to make tofu from soybean cultivar BRS 267 under different processing conditions in order to evaluate the influence of each treatment on the product quality. A fractional factorial 2(5-1) design was used, in which independent variables (thermal treatment, coagulant concentration, coagulation time, curd cutting, and draining time) were tested at two different levels. The response variables studied were hardness, yield, total solids, and protein content of tofu. Polynomial models were generated for each response. To obtain tofu with desirable characteristics (hardness ~4 N, yield 306 g tofu.100 g-1 soybeans, 12 g proteins.100 g-1 tofu and 22 g solids.100 g-1 tofu), the following processing conditions were selected: heating until boiling plus 10 minutes in water bath, 2% dihydrated CaSO4 w/w, 10 minutes coagulation, curd cutting, and 30 minutes draining time.

Correlation, by multivariate statistical analysis, between the scavenging capacity against reactive oxygen species and the bioactive compounds from frozen fruit pulps

The contents of total phenolic compounds (TPC), total flavonoids (TF), and ascorbic acid (AA) of 18 frozen fruit pulps and their scavenging capacities against peroxyl radical (ROO•), hydrogen peroxide (H2O2), and hydroxyl radical (•OH) were determined. Principal Component Analysis (PCA) showed that TPC (total phenolic compounds) and AA (ascorbic acid) presented positive correlation with the scavenging capacity against ROO•, and TF (total flavonoids) showed positive correlation with the scavenging capacity against •OH and ROO• However, the scavenging capacity against H2O2 presented low correlation with TF (total flavonoids), TPC (total phenolic compounds), and AA (ascorbic acid). The Hierarchical Cluster Analysis (HCA) allowed the classification of the fruit pulps into three groups: one group was formed by the açai pulp with high TF, total flavonoids, content (134.02 mg CE/100 g pulp) and the highest scavenging capacity against ROO•, •OH and H2O2; the second group was formed by the acerola pulp with high TPC, total phenolic compounds, (658.40 mg GAE/100 g pulp) and AA , ascorbic acid, (506.27 mg/100 g pulp) contents; and the third group was formed by pineapple, cacao, caja, cashew-apple, coconut, cupuaçu, guava, orange, lemon, mango, passion fruit, watermelon, pitanga, tamarind, tangerine, and umbu pulps, which could not be separated considering only the contents of bioactive compounds and the scavenging properties.

Genetics of inherited small vessel diseases – in search of a novel small vessel disease and modifiers of the clinical course of CADASIL

The genetic and environmental risk factors of vascular cognitive impairment are still largely unknown. This thesis aimed to assess the genetic background of two clinically similar familial small vessel diseases (SVD), CADASIL (Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy) and Swedish hMID (hereditary multi-infarct dementia of Swedish type). In the first study, selected genetic modifiers of CADASIL were studied in a homogenous Finnish CADASIL population of 134 patients, all carrying the p.Arg133Cys mutation in NOTCH3. Apolipoprotein E (APOE) genotypes, angiotensinogen (AGT) p.Met268Thr polymorphism and eight NOTCH3 polymorphisms were studied, but no associations between any particular genetic variant and first-ever stroke or migraine were seen. In the second study, smoking, statin medication and physical activity were suggested to be the most profound environmental differences among the monozygotic twins with CADASIL. Swedish hMID was for long misdiagnosed as CADASIL. In the third study, the CADASIL diagnosis in the Swedish hMID family was ruled out on the basis of genetic, radiological and pathological findings, and Swedish hMID was suggested to represent a novel SVD. In the fourth study, the gene defect of Swedish hMID was then sought using whole exome sequencing paired with a linkage analysis. The strongest candidate for the pathogenic mutation was a 3’UTR variant in the COL4A1 gene, but further studies are needed to confirm its functionality. This study provided new information about the genetic background of two inherited SVDs. Profound knowledge about the pathogenic mutations causing familial SVD is also important for correct diagnosis and treatment options.

Utilization of Statistical Methods for Management in the Forest Industry

The strongest wish of the customer concerning chemical pulp features is consistent, uniform quality. Variation may be controlled and reduced by using statistical methods. However, studies addressing the application and benefits of statistical methods in forest product sector are scarce. Thus, the customer wish is the root cause of the motivation behind this dissertation. The research problem addressed by this dissertation is that companies in the chemical forest product sector require new knowledge for improving their utilization of statistical methods. To gain this new knowledge, the research problem is studied from five complementary viewpoints – challenges and success factors, organizational learning, problem solving, economic benefit, and statistical methods as management tools. The five research questions generated on the basis of these viewpoints are answered in four research papers, which are case studies based on empirical data collection. This research as a whole complements the literature dealing with the use of statistical methods in the forest products industry. Practical examples of the application of statistical process control, case-based reasoning, the cross-industry standard process for data mining, and performance measurement methods in the context of chemical forest products manufacturing are brought to the public knowledge of the scientific community. The benefit of the application of these methods is estimated or demonstrated. The purpose of this dissertation is to find pragmatic ideas for companies in the chemical forest product sector in order for them to improve their utilization of statistical methods. The main practical implications of this doctoral dissertation can be summarized in four points: 1. It is beneficial to reduce variation in chemical forest product manufacturing processes 2. Statistical tools can be used to reduce this variation 3. Problem-solving in chemical forest product manufacturing processes can be intensified through the use of statistical methods 4. There are certain success factors and challenges that need to be addressed when implementing statistical methods

The genetics of glucosamine resistance in yeast /

Thesis (M. Sc.) - Brock University, 1975.

Modified statistical methods to calculate rare gas interaction potentials

New density functionals representing the exchange and correlation energies (per electron) are employed, based on the electron gas model, to calculate interaction potentials of noble gas systems X2 and XY, where X (and Y) are He,Ne,Ar and Kr, and of hydrogen atomrare gas systems H-X. The exchange energy density functional is that recommended by Handler and the correlation energy density functional is a rational function involving two parameters which were optimized to reproduce the correlation energy of He atom. Application of the two parameter function to other rare gas atoms shows that it is "universal"; i. e. ,accurate for the systems considered. The potentials obtained in this work compare well with recent experimental results and are a significant improvement over those from competing statistical modelS.

On the path integral formulation and the evaluation of quantum statistical averages

Four problems of physical interest have been solved in this thesis using the path integral formalism. Using the trigonometric expansion method of Burton and de Borde (1955), we found the kernel for two interacting one dimensional oscillators• The result is the same as one would obtain using a normal coordinate transformation, We next introduced the method of Papadopolous (1969), which is a systematic perturbation type method specifically geared to finding the partition function Z, or equivalently, the Helmholtz free energy F, of a system of interacting oscillators. We applied this method to the next three problems considered• First, by summing the perturbation expansion, we found F for a system of N interacting Einstein oscillators^ The result obtained is the same as the usual result obtained by Shukla and Muller (1972) • Next, we found F to 0(Xi)f where A is the usual Tan Hove ordering parameter* The results obtained are the same as those of Shukla and Oowley (1971), who have used a diagrammatic procedure, and did the necessary sums in Fourier space* We performed the work in temperature space• Finally, slightly modifying the method of Papadopolous, we found the finite temperature expressions for the Debyecaller factor in Bravais lattices, to 0(AZ) and u(/K/ j,where K is the scattering vector* The high temperature limit of the expressions obtained here, are in complete agreement with the classical results of Maradudin and Flinn (1963) .

The genetics of glucosamine in yeast : cytoplasmic determinants conferring resistance

Two cytoplasmic, glucosamine resistant mutants of Saccharomyces cerevisiae, GR6 and GR10, were examined to determine whether or not the lesions involved were located on mitochondrial DNA. Detailed investigation of crosses of GR6 and GR10 or their derivatives to strains bearing known mitochondrial markers demonstrated that: 1. the frequency of glucos~~ine resistance in diploids was independent of factors influencing mitochondrial marker output. 2. upon tetrad analysis a variety of tetrad ratios was observed for glucosamine resistance whereas mitochondrial markers segregated 4:0 or 0:4 (resistant:sensitive). 3. glucosamine resistance and mitochondrial markers segregated differentially with time. 4. glucosamine resistance persisted following treatment of a GRIO derivative with ethidium bromide at concentrations high enough to eliminate all mitochondrial DNA. 5. haploid spore clones displayed two degrees of glucosamine resistance, weak and strong, while growth due to mitochondrial mutations was generally thick and confluent. 6. a number of glucosamine resistant diploids and haploids, which also possessed a mithchondrial resistance mutation, were unable to grow on medium containing both glucosamine and the particular drug involved. 3 These observations 1~ 6 provided strong evidence that the cytoplasmic glucosamine resistant mutations present in GR6 and GRiO were not situated on mitochondrial DNA. Comparison of the glucosamine resistance mutations to some other known cytoplasmic determinants revealed that: 7. glucosamine resistance and the expression of the killer phenotype were separate phenomena. 8. unlike yeast carrying resistance conferring episomes GR6 and GR10 were not resistant to venturicidin or oligomycin and the GR factor exhibited genetic behaviour different from that of the episomal determinants. These results 7--+8 suggested that glucosamine resistance was not associated with the killer determinant nor with alleged yeast episomes. It is therefore proposed that a yeast plasmid(s), previously undescribed, is responsible for glucosamine resistance. The evidence to date is compatible with the hypothesis that GR6 and GR10 carry allelic mutations of the same plasmid which is tentatively designated (GGM).

Life Insurance and Genetics: A Comparative International Overview

La possibilité d'utiliser l'information génétique dans le domaine de l'assurance vie a soulevé des discussions autour des politiques et des législations, et ce, au niveau international, régional et national. Dans certains pays offrant des services de santé universels, le débat sur la génétique et l'assurance vie a envisagé de possibles restrictions quant à l'utilisation de l’information génétique en matière d’assurance.

Physicians, genetics and life insurance

Par contraste avec de nombreux pays européens qui ont clarifié leur position vis-à-vis la génétique et l’assurance vie, le Canada en est encore à établir la sienne. Toute initiative en ce domaine doit être basée sur une compréhension des mécanismes de l’assurance vie, de la nature de l’information génétique, de l’historique du débat au sujet de la génétique et de l’assurance vie au Canada et, finalement, des raisons pour lesquelles un groupe de travail canadien a décidé de relever le défi.

Genetics and Life Insurance in Canada: Points to Consider

Par contraste avec de nombreux pays européens qui ont clarifié leur position vis-à-vis la génétique et l’assurance vie, le Canada en est encore à établir la sienne. Toute initiative en ce domaine doit être basée sur une compréhension des mécanismes de l’assurance vie, de la nature de l’information génétique, de l’historique du débat au sujet de la génétique et de l’assurance vie au Canada et, finalement, des raisons pour lesquelles un groupe de travail canadien a décidé de relever le défi.

Statistical Inference for Computable General Equilibrium Models with Application to a Model of the Moroccan Economy

We study the problem of measuring the uncertainty of CGE (or RBC)-type model simulations associated with parameter uncertainty. We describe two approaches for building confidence sets on model endogenous variables. The first one uses a standard Wald-type statistic. The second approach assumes that a confidence set (sampling or Bayesian) is available for the free parameters, from which confidence sets are derived by a projection technique. The latter has two advantages: first, confidence set validity is not affected by model nonlinearities; second, we can easily build simultaneous confidence intervals for an unlimited number of variables. We study conditions under which these confidence sets take the form of intervals and show they can be implemented using standard methods for solving CGE models. We present an application to a CGE model of the Moroccan economy to study the effects of policy-induced increases of transfers from Moroccan expatriates.

Projection-Based Statistical Inference in Linear Structural Models with Possibly Weak Instruments

It is well known that standard asymptotic theory is not valid or is extremely unreliable in models with identification problems or weak instruments [Dufour (1997, Econometrica), Staiger and Stock (1997, Econometrica), Wang and Zivot (1998, Econometrica), Stock and Wright (2000, Econometrica), Dufour and Jasiak (2001, International Economic Review)]. One possible way out consists here in using a variant of the Anderson-Rubin (1949, Ann. Math. Stat.) procedure. The latter, however, allows one to build exact tests and confidence sets only for the full vector of the coefficients of the endogenous explanatory variables in a structural equation, which in general does not allow for individual coefficients. This problem may in principle be overcome by using projection techniques [Dufour (1997, Econometrica), Dufour and Jasiak (2001, International Economic Review)]. AR-types are emphasized because they are robust to both weak instruments and instrument exclusion. However, these techniques can be implemented only by using costly numerical techniques. In this paper, we provide a complete analytic solution to the problem of building projection-based confidence sets from Anderson-Rubin-type confidence sets. The latter involves the geometric properties of “quadrics” and can be viewed as an extension of usual confidence intervals and ellipsoids. Only least squares techniques are required for building the confidence intervals. We also study by simulation how “conservative” projection-based confidence sets are. Finally, we illustrate the methods proposed by applying them to three different examples: the relationship between trade and growth in a cross-section of countries, returns to education, and a study of production functions in the U.S. economy.

Identification, Weak Instruments and Statistical Inference in Econometrics

We discuss statistical inference problems associated with identification and testability in econometrics, and we emphasize the common nature of the two issues. After reviewing the relevant statistical notions, we consider in turn inference in nonparametric models and recent developments on weakly identified models (or weak instruments). We point out that many hypotheses, for which test procedures are commonly proposed, are not testable at all, while some frequently used econometric methods are fundamentally inappropriate for the models considered. Such situations lead to ill-defined statistical problems and are often associated with a misguided use of asymptotic distributional results. Concerning nonparametric hypotheses, we discuss three basic problems for which such difficulties occur: (1) testing a mean (or a moment) under (too) weak distributional assumptions; (2) inference under heteroskedasticity of unknown form; (3) inference in dynamic models with an unlimited number of parameters. Concerning weakly identified models, we stress that valid inference should be based on proper pivotal functions —a condition not satisfied by standard Wald-type methods based on standard errors — and we discuss recent developments in this field, mainly from the viewpoint of building valid tests and confidence sets. The techniques discussed include alternative proposed statistics, bounds, projection, split-sampling, conditioning, Monte Carlo tests. The possibility of deriving a finite-sample distributional theory, robustness to the presence of weak instruments, and robustness to the specification of a model for endogenous explanatory variables are stressed as important criteria assessing alternative procedures.