Estabilidade relativa de alcenos: análise dos critérios encontrados nos livros textos de graduação e uma proposta de explicação operacional para alcenos dissubstituídos

Despite of being used as thermodynamic criterion to rank alkene stability in a number of undergraduate textbooks, the heat of hydrogenation does not describe adequately the relative stability of disubstituted alkenes. In this work, both the heat of formation and the heat of combustion were used as thermodynamic criteria to rank correctly the stability of alkenes according to the degree of alkyl substitution and also in the disubstituted series (geminal > trans > cis). An operational model based on molecular orbital and valence bond representations of hyperconjugation is proposed to show how this effect can explain the order of stability of this class of compounds.

Niche Differentiation and Fine-Scale Projections for Argentine Ants Based on Remotely Sensed Data

Modeling ecological niches of species is a promising approach for predicting the geographic potential of invasive species in new environments. Argentine ants (Linepithema humile) rank among the most successful invasive species: native to South America, they have invaded broad areas worldwide. Despite their widespread success, little is known about what makes an area susceptible - or not - to invasion. Here, we use a genetic algorithm approach to ecological niche modeling based on high-resolution remote-sensing data to examine the roles of niche similarity and difference in predicting invasions by this species. Our comparisons support a picture of general conservatism of the species' ecological characteristics, in spite of distinct geographic and community contexts

Regression analysis of compositional data when both the dependent variable and independent variable are components

It is well known that regression analyses involving compositional data need special attention because the data are not of full rank. For a regression analysis where both the dependent and independent variable are components we propose a transformation of the components emphasizing their role as dependent and independent variables. A simple linear regression can be performed on the transformed components. The regression line can be depicted in a ternary diagram facilitating the interpretation of the analysis in terms of components. An exemple with time-budgets illustrates the method and the graphical features

Self-assessment of individual differences in language switching

Language switching is omnipresent in bilingual individuals. In fact, the ability to switch languages (code switching) is a very fast, efficient, and flexible process that seems to be a fundamental aspect of bilingual language processing. In this study, we aimed to characterize psychometrically self-perceived individual differences in language switching and to create a reliable measure of this behavioral pattern by introducing a bilingual switching questionnaire. As a working hypothesis based on the previous literature about code switching, we decomposed language switching into four constructs: (i) L1 switching tendencies (the tendency to switch to L1; L1-switch); (ii) L2 switching tendencies (L2-switch); (iii) contextual switch, which indexes the frequency of switches usually triggered by a particular situation, topic, or environment; and (iv) unintended switch, which measures the lack of intention and awareness of the language switches. A total of 582 SpanishCatalan bilingual university students were studied. Twelve items were selected (three for each construct). The correlation matrix was factor-analyzed using minimum rank factor analysis followed by oblique direct oblimin rotation. The overall proportion of common variance explained by the four extracted factors was 0.86. Finally, to assess the external validity of the individual differences scored with the new questionnaire, we evaluated the correlations between these measures and several psychometric (language proficiency) and behavioral measures related to cognitive and attentional control. The present study highlights the importance of evaluating individual differences in language switching using self-assessment instruments when studying the interface between cognitive control and bilingualism.

The trouble with resonance energies: a Hückel theory topic

Resonance energies are shown to be quasithermodynamic in character. Hence, they are generally unsuitable as bases for anticipating kinetic stabilities. Examples are provided, leading to the conclusion that those who intend the word 'aromatic' to mean chemically unreactive, need to carry out full Hückel calculations in order to rank hydrocarbons using the frontier orbital energies.

Role of human hydroxysteroid (17beta) dehydrogenase type 1 (HSD17B1) in steroid-dependent diseases in females –novel indications for HSD17B1 inhibitors. Phenotypic analysis of transgenic mice overexpressing human HSD17B1.

Hormone-dependent diseases, e.g. cancers, rank high in mortality in the modern world, and thus, there is an urgent need for new drugs to treat these diseases. Although the diseases are clearly hormone-dependent, changes in circulating hormone concentrations do not explain all the pathological processes observed in the diseased tissues. A more inclusive explanation is provided by intracrinology – a regulation of hormone concentrations at the target tissue level. This is mediated by the expression of a pattern of steroid-activating and -inactivating enzymes in steroid target tissues, thus enabling a concentration gradient between the blood circulation and the tissue. Hydroxysteroid (17beta) dehydrogenases (HSD17Bs) form a family of enzymes that catalyze the conversion between low active 17-ketosteroids and highly active 17beta-hydroxysteroids. HSD17B1 converts low active estrogen (E1) to highly active estradiol (E2) with high catalytic efficiency, and altered HSD17B1 expression has been associated with several hormone-dependent diseases, including breast cancer, endometriosis, endometrial hyperplasia and cancer, and ovarian epithelial cancer. Because of its putative role in E2 biosynthesis in ovaries and peripheral target tissues, HSD17B1 is considered to be a promising drug target for estrogen-dependent diseases. A few studies have indicated that the enzyme also has androgenic activity, but they have been ignored. In the present study, transgenic mice overexpressing human HSD17B1 (HSD17B1TG mice) were used to study the effects of the enzyme in vivo. Firstly, the substrate specificity of human HSD17B1 was determined in vivo. The results indicated that human HSD17B1 has significant androgenic activity in female mice in vivo, which resulted in increased fetal testosterone concentration and female disorder of sexual development appearing as masculinized phenotype (increased anogenital distance, lack of nipples, lack of vaginal opening, combination of vagina with urethra, enlarged Wolffian duct remnants in the mesovarium and enlarged female prostate). Fetal androgen exposure has been linked to polycystic ovary syndrome (PCOS) and metabolic syndrome during adulthood in experimental animals and humans, but the genes involved in PCOS are largely unknown. A putative mechanism to accumulate androgens during fetal life by HSD17B1 overexpression was shown in the present study. Furthermore, as a result of prenatal androgen exposure locally in the ovaries, HSD17B1TG females developed ovarian benign serous cystadenomas in adulthood. These benign lesions are precursors of low-grade ovarian serous tumors. Ovarian cancer ranks fifth in mortality of all female cancers in Finland, and most of the ovarian cancers arise from the surface epithelium. The formation of the lesions was prevented by prenatal antiandrogen treatment and by transplanting wild type (WT) ovaries prepubertally into HSD17B1TG females. The results obtained in our non-clinical TG mouse model, together with a literature analysis, suggest that HSD17B1 has a role in ovarian epithelial carcinogenesis, and especially in the development of serous tumors. The role of androgens in ovarian carcinogenesis is considered controversial, but the present study provides further evidence for the androgen hypothesis. Moreover, it directly links HSD17B1-induced prenatal androgen exposure to ovarian epithelial carcinogenesis in mice. As expected, significant estrogenic activity was also detected for human HSD17B1. HSD17B1TG mice had enhanced peripheral conversion of E1 to E2 in a variety of target tissues, including the uterus. Furthermore, this activity was significantly decreased by treatments with specific HSD17B1 inhibitors. As a result, several estrogen-dependent disorders were found in HSD17B1TG females. Here we report that HSD17B1TG mice invariably developed endometrial hyperplasia and failed to ovulate in adulthood. As in humans, endometrial hyperplasia in HSD17B1TG females was reversible upon ovulation induction, triggering a rise in circulating progesterone levels, and in response to exogenous progestins. Remarkably, treatment with a HSD17B1 inhibitor failed to restore ovulation, yet completely reversed the hyperplastic morphology of epithelial cells in the glandular compartment. We also demonstrate that HSD17B1 is expressed in normal human endometrium, hyperplasia, and cancer. Collectively, our non-clinical data and literature analysis suggest that HSD17B1 inhibition could be one of several possible approaches to decrease endometrial estrogen production in endometrial hyperplasia and cancer. HSD17B1 expression has been found in bones of humans and rats. The non-clinical data in the present study suggest that human HSD17B1 is likely to have an important role in the regulation of bone formation, strength and length during reproductive years in female mice. Bone density in HSD17B1TG females was highly increased in femurs, but in lesser amounts also in tibias. Especially the tibia growth plate, but not other regions of bone, was susceptible to respond to HSD17B1 inhibition by increasing bone length, whereas the inhibitors did not affect bone density. Therefore, HSD17B1 inhibitors could be safer than aromatase inhibitors in regard to bone in the treatment of breast cancer and endometriosis. Furthermore, diseases related to improper growth, are a promising new indication for HSD17B1 inhibitors.

Produção científica da área da Química no desenvolvimento da oceanografia no Brasil

This paper analyses the scientific contribution of chemists and of the Brazilian Chemical Society (SBQ) and its publications to the development of Oceanography in Brazil, as well as major drivers of this participation. A total of 528 articles were analyzed. Most articles (72%) originated in research groups not associated with graduate programs in oceanography. Nearly 50% dealt with the contamination of the marine environment, followed by chemical process studies (32%) and analytical methods development (15%). SBQ journals contributed with 78 articles (14.7% of the total), and rank 1st (QN) and 2nd (JBCS) among scientific journals publishing the analyzed articles.

Aumento del contenido de ácidos húmicos en un carbón de bajo rango a través de la oxidación con aire y con peróxido de hidrogeno o ácido nítrico

Low-rank coals are an important source of humic acids, which are important in retention processes of water and nutrients in plants. In this study coal samples of Montelibano, Colombia, were oxidized with air at different temperatures and subsequently with H2O2 and HNO3. The materials were characterized by FTIR, proximate and elemental analysis, and quantification of humic acids. The oxidation process led to an increased content of oxygenated groups and humic acids in the carbonaceous structure. The solid oxidized with air at 200 ºC for 12 h and re-oxidized with HNO3 for 12 h showed the highest percentage of humic acids (85.3%).

MCR-ALS APLICADO NO MONITORAMENTO QUANTITATIVO DO PROCESSO DE ELETRODEGRADAÇÃO DA ATRAZINA USANDO ESPECTROS UV: RESULTADOS COMPARATIVOS COM HPLC-DAD COMO UM MÉTODO DE REFERÊNCIA

Electrodegradation of atrazine in water was performed using homemade (PA and PB) and purchased (PC) boron-doped diamond anodes. The degradation was monitored off-line by analyzing total organic carbon and high performance liquid chromatography with diode array detector (HPLC-DAD) and at-line by UV spectroscopy. The spectra were recorded every 2 min. The rank deficiency problem was resolved by assembling an augmented column-wise matrix. HPLC was employed to separate the original and byproducts degradation components. Aiming the same goal, multivariate curve resolution - alternating least squares (MCR-ALS) was applied to resolve the UV spectroscopic data. Comparison between HPLC and MCR-ALS separations is presented. By using MCR-ALS the spectra of atrazine and two byproducts were successfully resolved and the resulted concentration profiles properly represented the system studied. The ALS explained variance (R2) for PA, PB and PC was equal to 99.99% for all of them and the lack of fit for PA, PB and PC were 0.39, 0.34 and 0.54 respectively. The correlation (R) between the recovered and pure spectra were calculate for each electrodegradation, validating the MCR-ALS results. The average R was equal to 0.997. The spectral and concentration profiles described with this new approach are in agreement with HPLC-DAD results. The proposed method is an alternative to classical analyses for monitoring of the degradation process, mainly due to the simplicity, fast results and economy.

Síntese e caracterização de compostos diorganoestânicos com ácido dl-mandélico

Por reação de quantidades eqüimoleculares de R2SnO ou R2SnCl2 (R = -CH3; -C4H9) com ácido dl-mandélico, C6H5CH(OH)COOH, em meio de etanol, foram obtidos novos compostos formulados como [(LR2Sn)2O] [L= C6H5CH(OH)COO-], nos quais o átomo de estanho é pentacoordenado, com o ligante L estabelecendo uma ligação bidentada através dos átomos de oxigênio dos grupos ácido e hidroxila alcoólica. Nas mesmas condições, nenhum produto obtido a partir da reação de (C6H5)2SnO ou (C6H5)2SnCl2 pode ser identificado. No entanto, quando da reação de (C6H5)2SnCl2 com ácido dl-mandélico, em meio de acetonitrila, foi preparado um composto dimérico hexacoordenado formulado como [L(C6H5)2SnCl]2. Este composto não pode ser isolado de forma pura e está misturado com 7% de impurezas não identificadas, cujos parâmetros de interação hiperfina sugerem tratar de estanho tetravalente octaedricamente coordenado por oxigênio. Os compostos obtidos foram caracterizados por determinação de ponto de fusão, microanálise e espectroscopias i.v. e Mössbauer.

Investigação por espectroscopia Mössbauer de compostos de ferro(0) contendo dissulfeto de carbono

Neste trabalho são apresentados resultados proveniente da aplicação da Espectroscopia Mössbauer na investigação de compostos carbonilferro contendo o ligante CS2, [Fe(CO)2(h²-CS2 )(PPh3)2] e [Fe(CO)2(h²-CS2) {P(OPh)3}2]. Nas sínteses dessas espécies, a utilização de TMNO (trimetilaminóxido) como agente descarbonilante mostrou-se bastante eficiente, superando aquelas descritas na literatura que requerem inclusive preparação de compostos precursores. Os resultados de espectroscopia Mössbauer, juntamente com dados no IV e de RMN de 31P, foram conclusivos na proposição da geometria octaédrica distorcida ao redor do átomo de ferro para ambos os compostos investigados.

Reatividade do [Fe(CO)2(eta2-CS2)(PPh 3)2] frente a compostos de Cu(I): síntese de espécies binucleares heterometálicas contendo CS2 em ponte entre Fe(0) e Cu(I)

Este trabalho contempla a síntese e caracterização espectroscópica de dois compostos carbonílicos heterometálicos do tipo [Fe(CO)3(m-CS2)(PPh3 )(CuX)], X = Cl, ClO4. Os dados provenientes da espectroscopia no infravermelho e de RMN de 31P{¹H} foram conclusivos quanto à proposição da geometria octaédrica distorcida ao redor do átomo de ferro (0), como também sobre a natureza bimetálica de ambos compostos. Estes dados esclareceram o modo de coordenação dos grupos carbonilos, da trifenilfosfina (PPh3), bem como a disposição do ligante dissulfeto de carbono em ponte entre os átomos de Fe (0) e Cu (I).

Choosing the optimal energy system for buildings and districts

The purpose of this master’s thesis was to develop a method to be used in the selection of an optimal energy system for buildings and districts. The term optimal energy system was defined as the energy system which best fulfils the requirements of the stakeholder on whose preferences the energy systems are evaluated. The most influential stakeholder in the process of selecting an energy system was considered to be the district developer. The selection method consisted of several steps: Definition of the district, calculating the energy consumption of the district and buildings within the district, defining suitable energy system alternatives for the district, definition of the comparing criteria, calculating the parameters of the comparing criteria for each energy system alternative and finally using a multi-criteria decision method to rank the alternatives. For the purposes of the selection method, the factors affecting the energy consumption of buildings and districts and technologies enabling the use of renewable energy were reviewed. The key element of the selection method was a multi-criteria decision making method, PROMETHEE II. In order to compare the energy system alternatives with the developed method, the comparing criteria were defined in the study. The criteria included costs, environmental impacts and technological and technical characteristics of the energy systems. Each criterion was given an importance, based on a questionnaire which was sent for the steering groups of two district development projects. The selection method was applied in two case study analyses. The results indicate that the selection method provides a viable and easy way to provide the decision makers alternatives and recommendations regarding the selection of an energy system. Since the comparison is carried out by changing the alternatives into numeric form, the presented selection method was found to exclude any unjustified preferences over certain energy systems alternatives which would affect the selection.

Vaccination Competence - The Concept and Evaluation

The purpose of this two-phase study was to define the concept of vaccination competence and assess the vaccination competence of graduating public health nurse students (PHN students) and public health nurses (PHNs) in Finland, with the goal of promoting and maintaining vaccination competence and developing vaccination education. The first phase of the study included semi-structured interviews with vaccination professionals, graduating PHN students and clients (a total of n=40), asking them to describe vaccination competence as well as the factors strengthening and weakening it. The data were analyzed through content analysis. In the second phase of the study, structured instruments were developed, and vaccination competence of PHN students (n=129) in Finland and PHNs (n=405) was assessed using a self-assessment scale (VAS) and taking a knowledge test. PHNs were used as a reference group, enabling us to determine whether a satisfactory level of vaccination competence was achieved by the end of studies, or whether it was gained through work experience vaccinating clients. The data were collected from five polytechnic institutions and seven health centers located in various parts of the country. The data were collected using instruments developed for this study, and were analyzed statistically. In the first phase, based on the results of the interviews, vaccination competence was defined as a large multi-faceted entity, including the concepts of competent vaccinator, competent implementation of the vaccination, and the outcome of the implementation. Semi-structured interviews revealed that factors strengthening and weakening vaccination competence were connected to the vaccinator, the client being vaccinated, the vaccination environment and vaccinator education. On the whole, factors strengthening and weakening vaccination were the opposite of each other. In the second phase, on the self-assessment of vaccination competence, students rated themselves as significantly lower than working professionals. On the knowledge test, the percentage of correct answers was lower for students than PHNs. When all background variables were taken into account in multivariate analysis, there was no longer a significant difference between the students and PHNs on the self-assessment. However, in multivariate analysis, the PHNs still performed better than students on the knowledge test. For this study, a satisfactory level of vaccination competence was defined as a mean of 8.0 on the self-assessment and 80% correct answers on the knowledge test. Based on these criteria, students almost reached the level of satisfactory in their overall self-assessment, and PHNs did. Both groups, however, did rank themselves as satisfactory in some sum variables. On the knowledge test the students did not achieve a level of satisfactory (80%) in their total score, though PHNs did. As before, both groups did achieve a level of satisfactory in several sum variables. Further research and development should focus on vaccination education, the testing of vaccination competence and vaccination practices in clinical practice, as well as on developing the measurement tools.

Kernel-Based Ranking. Methods for Learning and Performance Estimation

Machine learning provides tools for automated construction of predictive models in data intensive areas of engineering and science. The family of regularized kernel methods have in the recent years become one of the mainstream approaches to machine learning, due to a number of advantages the methods share. The approach provides theoretically well-founded solutions to the problems of under- and overfitting, allows learning from structured data, and has been empirically demonstrated to yield high predictive performance on a wide range of application domains. Historically, the problems of classification and regression have gained the majority of attention in the field. In this thesis we focus on another type of learning problem, that of learning to rank. In learning to rank, the aim is from a set of past observations to learn a ranking function that can order new objects according to how well they match some underlying criterion of goodness. As an important special case of the setting, we can recover the bipartite ranking problem, corresponding to maximizing the area under the ROC curve (AUC) in binary classification. Ranking applications appear in a large variety of settings, examples encountered in this thesis include document retrieval in web search, recommender systems, information extraction and automated parsing of natural language. We consider the pairwise approach to learning to rank, where ranking models are learned by minimizing the expected probability of ranking any two randomly drawn test examples incorrectly. The development of computationally efficient kernel methods, based on this approach, has in the past proven to be challenging. Moreover, it is not clear what techniques for estimating the predictive performance of learned models are the most reliable in the ranking setting, and how the techniques can be implemented efficiently. The contributions of this thesis are as follows. First, we develop RankRLS, a computationally efficient kernel method for learning to rank, that is based on minimizing a regularized pairwise least-squares loss. In addition to training methods, we introduce a variety of algorithms for tasks such as model selection, multi-output learning, and cross-validation, based on computational shortcuts from matrix algebra. Second, we improve the fastest known training method for the linear version of the RankSVM algorithm, which is one of the most well established methods for learning to rank. Third, we study the combination of the empirical kernel map and reduced set approximation, which allows the large-scale training of kernel machines using linear solvers, and propose computationally efficient solutions to cross-validation when using the approach. Next, we explore the problem of reliable cross-validation when using AUC as a performance criterion, through an extensive simulation study. We demonstrate that the proposed leave-pair-out cross-validation approach leads to more reliable performance estimation than commonly used alternative approaches. Finally, we present a case study on applying machine learning to information extraction from biomedical literature, which combines several of the approaches considered in the thesis. The thesis is divided into two parts. Part I provides the background for the research work and summarizes the most central results, Part II consists of the five original research articles that are the main contribution of this thesis.