Identificación y evaluación de la creación de valor mediante la implantación y desarrollo de políticas de responsabilidad social corporativa estratégica

La Responsabilidad Social Corporativa (RSC) sigue constituyendo en la actualidad un área de estudio de elevado interés tanto para la comunidad académica como para los negocios en general. A pesar del gran número de investigaciones realizadas en las pasadas décadas sobre los distintos aspectos que la caracterizan, y la definición generalizada de políticas relacionadas en las compañías más importantes, existen todavía algunos asuntos clave sobre los que se plantean interrogantes fundamentales. La complejidad asociada al constructo RSC y su carácter intrínsecamente dinámico explican en parte esta afirmación. En su aplicación práctica, las dudas sobre la RSC se enfocan hoy en día hacia su implantación con carácter permanente en el día a día de las organizaciones, la relevancia estratégica de las principales iniciativas, o la posibilidad de obtención de beneficios a medio y largo plazo. Se observa de esta forma la traslación de los debates principales hacia las consecuencias más estratégicas de dichas políticas, influenciados por prestigiosos estudios académicos en los que se caracteriza la denominada RSC Estratégica (RSCE), y por las principales organizaciones de certificación de memorias anuales de RSC y sostenibilidad. En este contexto se sitúa el objeto principal de esta investigación, consistente en el diseño de un modelo de implantación de RSCE que permita no sólo identificar los factores más importantes a tener en consideración para su éxito, sino para caracterizar las potenciales formas de creación de valor que pueden surgir de la aplicación del mismo. Se argumenta la elección del tema por considerarse que los asuntos asociados a la RSC no están lo suficientemente explorados desde la visión estratégica más actual, y por constituir la creación de valor el objetivo más crítico dentro de los procesos directivos de planificación estratégica. De esta forma, se utilizan dos metodologías para destacar qué factores son esenciales en la implantación de la RSCE, con qué fines las compañías aplican esas políticas, y qué resultados obtienen como consecuencia: análisis comparativo de casos de estudio y análisis estadístico cuantitativo. Los casos de estudio analizan en profundidad políticas globales de RSCE bajo diferentes puntos de vista, para derivar conclusiones sobre los factores que facilitan u obstaculizan su implantación permanente en las organizaciones. Su desarrollo se estructura en torno a un marco conceptual de referencia obtenido a través de la revisión bibliográfica específica, y se complementa con la información primaria y secundaria de investigación. Por su parte, el análisis cuantitativo se desarrolla mediante tres técnicas exploratorias: estadística descriptiva, regresión múltiple y análisis de componentes principales. Su aplicación combinada va a posibilitar el contraste de aspectos destacados en los análisis de casos, así como la configuración final del modelo de implantación, y la expresión numérica de la creación de valor a través de la RSCE en función de las dimensiones estratégicas consideradas. En consecuencia, los resultados de la tesis se estructuran alrededor de tres preguntas de investigación: ¿cómo se están produciendo y qué caracterización presentan los beneficios que resultan como consecuencia de la implantación de la RSCE en los procesos de planificación estratégica de las compañías?, ¿qué factores esenciales y característicos de la RSCE pueden resultar críticos en los procesos de implantación y futuro desarrollo?, y ¿qué importancia puede tener en el medio y largo plazo el poder de decisión de compra de los consumidores y usuarios finales en la implantación y desarrollo de políticas de RSCE? ABSTRACT Corporate Social Responsibility (CSR) remains a study area of high interest today to both the academic community and businesses in general. Despite the large number of investigations of various aspects of CSR in past decades, and its generalized consideration by the world’s most important companies, there are still some key issues and fundamental questions to resolve. The complexity associated with the CSR construct and its inherently dynamic character, partly explains this statement. In its practical application, doubts about CSR arise today about its permanent implementation in normal business activities, the strategic relevance of related policies, and the possibility of making profits in the medium and long term. It is observed in this way the translation of the main debates towards the more strategic consequences of these policies, influenced by prestigious academic studies that characterize the so-called Strategic CSR (SCSR), and by leading certification agencies of CSR and sustainability reports. In this context, the main purpose of this investigation is to design a model of SCSR for implementation that allows one to not only identify the most important factors to consider for SCSR success, but also to characterize potential forms of value creation that can arise from its application. The selection of this research approach is justified because it is believed that important issues that are associated with CSR have not been sufficiently explored from the aspect of the strategic vision in the current context, and because value creation constitutes the most critical objective within the strategic planning steering processes. Thus, two methods are used to highlight which factors are essential in SCSR implementation processes, the end to which companies apply these policies, and the kind of results that they expect. These methods are: comparative analysis of case studies and quantitative statistical analysis. The case studies discuss in depth SCSR global policies under different perspectives to draw conclusions about the factors that facilitate or hinder permanent implantation in organizations. Their development is structured around a conceptual framework that is obtained by review of specific literature, and is complemented by primary and secondary research information. On the other hand, quantitative analysis is developed by means of three exploratory techniques: descriptive statistics, multiple regression and principal component analysis. Their combined application facilitates a contrast of highlighted aspects in analyzing cases, the final configuration of the implementation model, and the numerical expression of value creation by SCSR as a consequence of the strategic dimensions considered by companies. Finally, the results of the thesis are structured around three research questions: what are the benefits that result from the implementation of SCSR policies in companies’ strategic planning processes?, which essential SCSR factors are potentially critical in the implementation and future development of companies’ processes?, and how decisive in the medium and long term will be the purchase decision power of consumers to the success of SCSR policies?

Study of PM10 and PM2.5 levels in three European cities: Analysis of intra and inter urban variations

In the present paper, 1-year PM10 and PM 2.5 data from roadside and urban background monitoring stations in Athens (Greece), Madrid (Spain) and London (UK) are analysed in relation to other air pollutants (NO,NO2,NOx,CO,O3 and SO2)and several meteorological parameters (wind velocity, temperature, relative humidity, precipitation, solar radiation and atmospheric pressure), in order to investigate the sources and factors affecting particulate pollution in large European cities. Principal component and regression analyses are therefore used to quantify the contribution of both combustion and non-combustion sources to the PM10 and PM 2.5 levels observed. The analysis reveals that the EU legislated PM 10 and PM2.5 limit values are frequently breached, forming a potential public health hazard in the areas studied. The seasonal variability patterns of particulates varies among cities and sites, with Athens and Madrid presenting higher PM10 concentrations during the warm period and suggesting the larger relative contribution of secondary and natural particles during hot and dry days. It is estimated that the contribution of non-combustion sources varies substantially among cities, sites and seasons and ranges between 38-67% and 40-62% in London, 26-50% and 20-62% in Athens, and 31-58% and 33-68% in Madrid, for both PM10 and PM 2.5. Higher contributions from non-combustion sources are found at urban background sites in all three cities, whereas in the traffic sites the seasonal differences are smaller. In addition, the non-combustion fraction of both particle metrics is higher during the warm season at all sites. On the whole, the analysis provides evidence of the substantial impact of non-combustion sources on local air quality in all three cities. While vehicular exhaust emissions carry a large part of the risk posed on human health by particle exposure, it is most likely that mitigation measures designed for their reduction will have a major effect only at traffic sites and additional measures will be necessary for the control of background levels. However, efforts in mitigation strategies should always focus on optimal health effects.

Relação espacial dos óbitos e internações por tuberculose com indicadores sociais em Ribeirão Preto (SP)

Objetivo: Propôs-se analisar a relação espacial dos óbitos e internações evitáveis por TB com indicadores sociais em Ribeirão Preto/SP. Métodos: Trata-se de um estudo ecológico em que foram considerados os casos de óbitos e internações, tendo como causa básica do óbito e motivo principal da internação, a tuberculose (CID A15.0 a A19.9), ocorridos na zona urbana de Ribeirão Preto e registrados respectivamente no Sistema de Informação sobre Mortalidade e no Sistema de Internação Hospitalar do Sistema Único de Saúde no período de 2006 a 2012. Foi realizada a análise univariada das variáveis sociodemográficas e operacionais dos casos investigados. Para construção dos indicadores sociais utilizou-se a análise de componentes principais, sendo selecionados dados das áreas de abrangência do município, considerando os dados do Censo Demográfico de 2010. A geocodificação dos casos foi processada no TerraView versão 4.2.2. Recorreu-se à regressão linear múltipla, pelo método dos mínimos quadrados e à regressão espacial para análise da relação de dependência espacial entre os indicadores sociais e as taxas de mortalidade e de internações por TB. A autocorrelação nos resíduos da regressão linear múltipla foi testada por meio do Teste Global de Moran, as análises foram realizadas considerando os softwares Arcgis-versão 10.1, Statistica versão 12.0, OpenGeoDa versão 1.0 e R versão 3.2.3. Para o diagnóstico do melhor modelo de regressão espacial, utilizou-se o teste Multiplicador de Lagrange. Em todos os testes, foi fixado o nivel de significancia de alfa em 5% (p< 0,05). Resultados: Foram registrados 50 casos de óbitos e 196 casos de internações por TB. A maioria dos casos registrados em ambos os sistemas se deu em pessoas do sexo masculino (n=41; 82%/n=146; 74,5%) e com a forma clínica pulmonar (n=44; 80,0%/n=138; 67,9%). Na construção dos indicadores sociais, três novas variáveis surgiram, apresentando respectivamente variância total de 46,2%, 18,7% e 14,6% sendo denominadas como indicadores de renda, desigualdade social e equidade social. Na modelagem para verificar relação espacial entre os óbitos e os indicadores sociais observou-se que a equidade social foi indicador estatisticamente significativo (p=0,0013) com relação negativa a mortalidade, sendo o Modelo da Defasagem Espacial o melhor método para testar a dependência espacial, com valor de ? (rho) estimado em 0,53 e altamente significativo (p=0,0014). Já na modelagem da relação espacial entre as internações por tuberculose e os indicadores sociais, o indicador de renda apresentou-se estatisticamente significativo (p=0,015) com relação negativa a internação e o melhor método para testar a dependência espacial também foi o Modelo da Defasagem Espacial com valor de ? (rho) estimado em 0,80 e altamente significativo (p<0,0001). Conclusão: O estudo contribuiu no avanço do conhecimento de que a mortalidade e as internações por tuberculose são eventos socialmente determinados, o que sugere investimento por parte da gestão

Stable isotope record of foraminifera from South Atlantic sediments with reconstruction of paleotemperatures and paleosalinities

Changes in surface water hydrography in the Southern Ocean (eastern Atlantic sector) could be reconstructed on the basis of isotope-geochemical and micropaleontological studies. A total of 75 high quality multicorer sediment surface samples from the southern South Atlantic Ocean and three Quaternary sediment cores, taken on a meridional transect across the Antarctic Circumpolar Current, have been investigated. The results of examining stable oxygen isotope compositions of 24 foraminiferal species and morphotypes were compared to the near-surface hydrography. The different foraminifera have been divided into four groups living at different depths in the upper water column. The 8180 differences between shallow-living (e.g. G. bulloides, N. pachyderma) and deeper-dwelling (e. g. G. inflata) species reflect the measured temperature gradient of the upper 250 m in the water column. Thus, the 6180 difference between shallow-living and deeper-living foraminifera can be used as an indicator for the vertical temperature gradient in the surface water of the Antarctic Circumpolar Current, which is independent of ice volume. All planktonic foraminifera in the surface sediment samples have been counted. 27 species and morphotypes have been selected, to form a reference data Set for statistical purposes. By using R- and Q-mode principal component analysis these planktonic foraminifera have been divided into four and five assemblages, respectively. The geographic distribution of these assemblages is mainly linked to the temperature of sea-surface waters. The five assemblages (factors) of the Q-mode principal component analysis account for 97.l % of the variance of original data. Following the transferfunction- technique a multiple regression between the Q-mode factors and the actual mean sea-surface environmental parameters resulted in a set of equations. The new transfer function can be used to estimate past sea-surface seasonal temperatures for paleoassemblages of planktonic foraminifera with a precision of approximately ±1.2°C. This transfer function F75-27-5 encompasses in particular the environmental conditions in the Atlantic sector of the Antarctic Circumpolar Current. During the last 140,000 years reconstructed sea-surface temperatures fluctuated in the present northern Subantarctic Zone (PS2076-1/3) at an amplitude of up to 7.5°C in summer and of up to 8.5°C in winter. In the present Polarfrontal Zone (PS1754-1) these fluctuations between glacials and interglacials show lower temperatures from 2.5 to 8.5°C in summer and from 1.0 to 5.0°C in winter, respectively. Compared to today, calculated oxygen isotope temperature gradients in the present Subantarctic Zone were lower during the last 140,000 years. This is an indicator for a good mixing of the upper water column. In the Polarfrontal Zone also lower oxygen isotope temperature gradients were found for the glacials 6, 4 and 2. But almost similar temperature gradients as today were found during the interglacial stages 5, 3 and the Holocene, which implicates a mixing of the upper water column compared to present. Paleosalinities were reconstructed by combining d18O-data and the evaluated transfer function paleotemperatures. Especially in the present Polarfrontal Zone (PS1754-1) and in the Antarctic Zone (PS1768-8), a short-term reduction of salinity up to 4 %o, could be detected. This significant reduction in sea-surface water salinity indicates the increased influx of melt-water at the beginning of deglaciation in the southern hemisphere at the end of the last glacial, approximately 16,500-13,000 years ago. The reconstruction of environmental Parameters indicates only small changes in the position of the frontal Systems in the eastern sector of the Antarctic Circumpolar Current during the last 140,000 years. The average position of the Subtropical Front and Subantarctic Front shifted approximately three latitudes between interglacials and glacials. The Antarctic Polar Front shifted approximately four latitudes. But substantial modifications of this scenario have been interpreted for the reconstruction of cold sea-surface temperatures at 41Â S during the oxygen isotope stages 16 and 14 to 12. During these times the Subtropical Front was probably shified up to seven latitudes northwards.

Non-linear principal components analysis: an alternative method for finding patterns in environmental data

The main purpose of this article is to gain an insight into the relationships between variables describing the environmental conditions of the Far Northern section of the Great Barrier Reef, Australia, Several of the variables describing these conditions had different measurement levels and often they had non-linear relationships. Using non-linear principal component analysis, it was possible to acquire an insight into these relationships. Furthermore. three geographical areas with unique environmental characteristics could be identified. Copyright (c) 2005 John Wiley & Sons, Ltd.

DVMS 1.5: A user manual (the data visualization and modeling system)

The data available during the drug discovery process is vast in amount and diverse in nature. To gain useful information from such data, an effective visualisation tool is required. To provide better visualisation facilities to the domain experts (screening scientist, biologist, chemist, etc.),we developed a software which is based on recently developed principled visualisation algorithms such as Generative Topographic Mapping (GTM) and Hierarchical Generative Topographic Mapping (HGTM). The software also supports conventional visualisation techniques such as Principal Component Analysis, NeuroScale, PhiVis, and Locally Linear Embedding (LLE). The software also provides global and local regression facilities . It supports regression algorithms such as Multilayer Perceptron (MLP), Radial Basis Functions network (RBF), Generalised Linear Models (GLM), Mixture of Experts (MoE), and newly developed Guided Mixture of Experts (GME). This user manual gives an overview of the purpose of the software tool, highlights some of the issues to be taken care while creating a new model, and provides information about how to install & use the tool. The user manual does not require the readers to have familiarity with the algorithms it implements. Basic computing skills are enough to operate the software.

Evaluating service quality and customer satisfaction evaluation in an emerging markets

Developing economies offer tremendous potential for future growth and organizations appreciating these consumers’ requirements stand to reap considerable returns. However, compared with more developed economies published consumer studies are few. In particular, there is a dearth of service quality research and hardly any from Africa. Furthermore, the little available research tends to apply Western methodologies, which may not be entirely appropriate. This research investigates East African consumer perceptions of retail banking using an approach that takes account of the research context. Qualitative research was undertaken to define the relevant service attributes. Performance along these was then investigated through a survey with over 2000 respondents. Principal component analysis identifies 13 core service dimensions and multinomial logistic regression reveals which are the key drivers of customer satisfaction. Comparison of the results with studies from other regions confirms that established standardized research instruments are likely to miss or under-represent service attributes important in developing countries.

Chemometric modelling to relate antioxidants, neutral lipid fatty acids and flavour components in chicken breast

Relationships among quality factors in retailed free-range, corn-fed, organic, and conventional chicken breasts (9) were modeled using chemometric approaches. Use of principal component analysis (PCA) to neutral lipid composition data explained the majority (93%) of variability (variance) in fatty acid contents in 2 significant multivariate factors. PCA explained 88 and 75% variance in 3 factors for, respectively, flame ionization detection (FID) and nitrogen phosphorus (NPD) components in chromatographic flavor data from cooked chicken after simultaneous distillation extraction. Relationships to tissue antioxidant contents were modeled. Partial least square regression (PLS2), interrelating total data matrices, provided no useful models. By using single antioxidants as Y variables in PLS (1), good models (r2 values > 0.9) were obtained for alpha-tocopherol, glutathione, catalase, glutathione peroxidase, and reductase and FID flavor components and among the variables total mono and polyunsaturated fatty acids and subsets of FID, and saturated fatty acid and NPD components. Alpha-tocopherol had a modest (r2 = 0.63) relationship with neutral lipid n-3 fatty acid content. Such factors thus relate to flavor development and quality in chicken breast meat.

Development and validation of an instrument to predict online student success using faculty perceptions

Distance learning is growing and transforming educational institutions. The increasing use of distance learning by higher education institutions and particularly community colleges coupled with the higher level of student attrition in online courses than in traditional classrooms suggests that increased attention should be paid to factors that affect online student course completion. The purpose of the study was to develop and validate an instrument to predict community college online student course completion based on faculty perceptions, yielding a prediction model of online course completion rates. Social Presence and Media Richness theories were used to develop a theoretically-driven measure of online course completion. This research study involved surveying 311 community college faculty who taught at least one online course in the past 2 years. Email addresses of participating faculty were provided by two south Florida community colleges. Each participant was contacted through email, and a link to an Internet survey was given. The survey response rate was 63% (192 out of 303 available questionnaires). Data were analyzed through factor analysis, alpha reliability, and multiple regression. The exploratory factor analysis using principal component analysis with varimax rotation yielded a four-factor solution that accounted for 48.8% of the variance. Consistent with Social Presence theory, the factors with their percent of variance in parentheses were: immediacy (21.2%), technological immediacy (11.0%), online communication and interactivity (10.3%), and intimacy (6.3%). Internal consistency of the four factors was calculated using Cronbach's alpha (1951) with reliability coefficients ranging between .680 and .828. Multiple regression analysis yielded a model that significantly predicted 11% of the variance of the dependent variable, the percentage of student who completed the online course. As indicated in the literature (Johnson & Keil, 2002; Newberry, 2002), Media Richness theory appears to be closely related to Social Presence theory. However, elements from this theory did not emerge in the factor analysis.

Assessing the effects of professionals' career decision -making on their participation reasons in continuing education in Taiwan

The purpose of this study was to assess the relationship between working professionals' Career Decision-Making Self-Efficacy beliefs (CDMSE beliefs) and their reasons for participating in in-service master's level programs in Taiwan. ^ The data collection instruments used were Grotelueschen's (1985) Participation Reasons Scale (PRS), and Betz, Klein, and Taylor's (1996) Career Decision-Making Self-Efficacy-Short Form (CDMSE-SF), and a Demographic Data Form (DDF) developed specifically for this study. ^ Surveys were administered to 800 working professionals who participated in inservice master's level programs at 22 Taiwanese universities. The survey was conducted in May 2004. Data were analyzed by simple descriptive statistics, principal component factor analysis, and multiple regression. Four factors of participation reasons were found and five components of CDMSE beliefs were scored. ^ Five components of CDMSE beliefs are structured into the CDMSE-SF instrument: Self-Appraisal, Occupational Information, Goal-Selection, Planning, and Problem Solving. The reasons for participation found in this study were: Professional Improvement and Development, Professional Service, Personal Benefit and Job Security, and Professional Competence and Collegial Interaction. Pearson-product moment correlations revealed significant positive correlations between the five CDMSE subscales and the four factors of participation reasons. Multiple regression analysis revealed that participants' beliefs in their abilities to obtain information about occupations accounted for the preponderance of variance of scores on the Participation Reasons Scale (PRS). ^ This study concluded that professionals who believed that they were efficacious in obtaining information about occupations or professions tended to believe that the four reasons for participation represented by the factors of the PRS were important to them in making the decision to participate in continuing education. Additionally, it was noted that the reasons for participations for professionals who did not feel confident in their abilities to find such information could not be determined. ^ Recommendations are offered to assist those individuals responsible for developing recruiting programs in continuing education for professionals in Taiwan. These recommendations focus only on strategies intended to attract this target population of professionals who believe that they are efficacious in obtaining information about occupations. ^

Benthic foraminifera in surface sediments, South Atlantic

Sixty surface sediment samples from the eastern South Atlantic Ocean including the Walvis Ridge, the Angola and Cape basins, and the Southwest African continental margin were analysed for their benthic foraminiferal content to unravel faunal distribution patterns and ecological preferences. Live (stained with Rose Bengal) and dead faunas were counted separately and then each grouped by Q-mode principal component analysis into seven principal faunal end-members. Then, multiple regression technique was used to correlate Recent assemblages with available environmental variables and to finally differentiate between four principal groups of environmental agents acting upon the generation of benthic foraminiferal assemblages: (1) seasonality of food supply and organic carbon flux rates, together with oxygen content in the pore and bottom waters; (2) lateral advection of deep-water masses; (3) bottom water carbonate corrosiveness; and (4) energetic state at the benthic boundary layer and grain size composition of the substrate. Food supply and corresponding dissolved oxygen contents in the pore and bottom waters turned out to be the most important factors which control the distribution pattern of the Recent benthic foraminifera. At the continental margin, in the zone of coastal upwelling and its mixing area, benthic foraminiferal assemblages are dominated by stenobathic high-productivity faunas, characterized by elevated standing stocks, low diversities and a large number of endobenthic living species. At the continental shelf and upper continental slope the live assemblages are characterized by Rectuvigerina cylindrica, Uvigerina peregrina s.1., Uvigerina auberiana and Rhizammina spp. while the dead assemblages are characterized by Cassidulina laevigata, Bolivina dilatata, Bulimina costata and B. mexicana. At the lower continental slope strong influence of high organic matter fluxes on the species composition is restricted to the area off the Cunene river mouth, where the live assemblage is dominated by Uvigerina peregrina s.1., the corresponding dead assemblage by Melonis barleeanum and M. zaandamae. In the adjacent areas of the lower continental slope the biocoenosis is characterized by Reophax bilocularis, and Epistominella exigua which becomes dominant in the corresponding dead assemblage. At the Walvis Ridge and in the abyssal Angola and Cape basins, where organic matter fluxes are low and highly seasonal, benthic foraminiferal assemblages reflect both the oligotrophic situation and the deep and bottom water mass configuration. The top and flanks of the Walvis Ridge are inhabited by the Rhizammina, Psammosphaera and R. bilocularis live assemblages, the corresponding dead assemblages are dominated by G. subglobosa on the ridge top and E. exigua on the flanks. Within the highly diverse E. exigua dead assemblage several associated epibenthic species coincide with the core of NADW between about 1600 and 3700 m water depth. These species include Osangularia culter, Cibicidoides kullenbergi, Melonis pompilioides, Bolivinita pseudothalmanni and Bulimina alazanensis. The assemblages of the abyssal Cape and Angola basins are characterized by Nuttallides umbonifer and a high proportion of agglutinated species. These species are adapted to very low organic matter fluxes and a carbonate corrosive environment.

Multivariate Techniques in Biomechanical Analysis

This work outlines the theoretical advantages of multivariate methods in biomechanical data, validates the proposed methods and outlines new clinical findings relating to knee osteoarthritis that were made possible by this approach. New techniques were based on existing multivariate approaches, Partial Least Squares (PLS) and Non-negative Matrix Factorization (NMF) and validated using existing data sets. The new techniques developed, PCA-PLS-LDA (Principal Component Analysis – Partial Least Squares – Linear Discriminant Analysis), PCA-PLS-MLR (Principal Component Analysis – Partial Least Squares –Multiple Linear Regression) and Waveform Similarity (based on NMF) were developed to address the challenging characteristics of biomechanical data, variability and correlation. As a result, these new structure-seeking technique revealed new clinical findings. The first new clinical finding relates to the relationship between pain, radiographic severity and mechanics. Simultaneous analysis of pain and radiographic severity outcomes, a first in biomechanics, revealed that the knee adduction moment’s relationship to radiographic features is mediated by pain in subjects with moderate osteoarthritis. The second clinical finding was quantifying the importance of neuromuscular patterns in brace effectiveness for patients with knee osteoarthritis. I found that brace effectiveness was more related to the patient’s unbraced neuromuscular patterns than it was to mechanics, and that these neuromuscular patterns were more complicated than simply increased overall muscle activity, as previously thought.

Effect of Wealth on Health Care Seeking Behavior And Out of Pocket Health Expenditure in Malawi

Thesis (Master's)--University of Washington, 2016-06

Desenvolvimento e aplicação de modelo de calibração multivariada para determinação de açúcares e ácidos orgânicos em bebidas comerciais utilizando espectroscopia no infravermelho

The routine analysis for quantization of organic acids and sugars are generally slow methods that involve the use and preparation of several reagents, require trained professional, the availability of special equipment and is expensive. In this context, it has been increasing investment in research whose purpose is the development of substitutive methods to reference, which are faster, cheap and simple, and infrared spectroscopy have been highlighted in this regard. The present study developed multivariate calibration models for the simultaneous and quantitative determination of ascorbic acid, citric, malic and tartaric and sugars sucrose, glucose and fructose, and soluble solids in juices and fruit nectars and classification models for ACP. We used methods of spectroscopy in the near infrared (Near Infrared, NIR) in association with the method regression of partial least squares (PLS). Were used 42 samples between juices and fruit nectars commercially available in local shops. For the construction of the models were performed with reference analysis using high-performance liquid chromatography (HPLC) and refractometry for the analysis of soluble solids. Subsequently, the acquisition of the spectra was done in triplicate, in the spectral range 12500 to 4000 cm-1. The best models were applied to the quantification of analytes in study on natural juices and juice samples produced in the Paraná Southwest Region. The juices used in the application of the models also underwent physical and chemical analysis. Validation of chromatographic methodology has shown satisfactory results, since the external calibration curve obtained R-square value (R2) above 0.98 and coefficient of variation (%CV) for intermediate precision and repeatability below 8.83%. Through the Principal Component Analysis (PCA) was possible to separate samples of juices into two major groups, grape and apple and tangerine and orange, while for nectars groups separated guava and grape, and pineapple and apple. Different validation methods, and pre-processes that were used separately and in combination, were obtained with multivariate calibration models with average forecast square error (RMSEP) and cross validation (RMSECV) errors below 1.33 and 1.53 g.100 mL-1, respectively and R2 above 0.771, except for malic acid. The physicochemical analysis enabled the characterization of drinks, including the pH working range (variation of 2.83 to 5.79) and acidity within the parameters Regulation for each flavor. Regression models have demonstrated the possibility of determining both ascorbic acids, citric, malic and tartaric with successfully, besides sucrose, glucose and fructose by means of only a spectrum, suggesting that the models are economically viable for quality control and product standardization in the fruit juice and nectars processing industry.

Quantificação de açúcares com uma língua eletrónica: calibração multivariada com seleção de sensores

Este trabalho incide na análise dos açúcares majoritários nos alimentos (glucose, frutose e sacarose) com uma língua eletrónica potenciométrica através de calibração multivariada com seleção de sensores. A análise destes compostos permite contribuir para a avaliação do impacto dos açúcares na saúde e seu efeito fisiológico, além de permitir relacionar atributos sensoriais e atuar no controlo de qualidade e autenticidade dos alimentos. Embora existam diversas metodologias analíticas usadas rotineiramente na identificação e quantificação dos açúcares nos alimentos, em geral, estes métodos apresentam diversas desvantagens, tais como lentidão das análises, consumo elevado de reagentes químicos e necessidade de pré-tratamentos destrutivos das amostras. Por isso se decidiu aplicar uma língua eletrónica potenciométrica, construída com sensores poliméricos selecionados considerando as sensibilidades aos açucares obtidas em trabalhos anteriores, na análise dos açúcares nos alimentos, visando estabelecer uma metodologia analítica e procedimentos matemáticos para quantificação destes compostos. Para este propósito foram realizadas análises em soluções padrão de misturas ternárias dos açúcares em diferentes níveis de concentração e em soluções de dissoluções de amostras de mel, que foram previamente analisadas em HPLC para se determinar as concentrações de referência dos açúcares. Foi então feita uma análise exploratória dos dados visando-se remover sensores ou observações discordantes através da realização de uma análise de componentes principais. Em seguida, foram construídos modelos de regressão linear múltipla com seleção de variáveis usando o algoritmo stepwise e foi verificado que embora fosse possível estabelecer uma boa relação entre as respostas dos sensores e as concentrações dos açúcares, os modelos não apresentavam desempenho de previsão satisfatório em dados de grupo de teste. Dessa forma, visando contornar este problema, novas abordagens foram testadas através da construção e otimização dos parâmetros de um algoritmo genético para seleção de variáveis que pudesse ser aplicado às diversas ferramentas de regressão, entre elas a regressão pelo método dos mínimos quadrados parciais. Foram obtidos bons resultados de previsão para os modelos obtidos com o método dos mínimos quadrados parciais aliado ao algoritmo genético, tanto para as soluções padrão quanto para as soluções de mel, com R²ajustado acima de 0,99 e RMSE inferior a 0,5 obtidos da relação linear entre os valores previstos e experimentais usando dados dos grupos de teste. O sistema de multi-sensores construído se mostrou uma ferramenta adequada para a análise dos iii açúcares, quando presentes em concentrações maioritárias, e alternativa a métodos instrumentais de referência, como o HPLC, por reduzir o tempo da análise e o valor monetário da análise, bem como, ter um preparo mínimo das amostras e eliminar produtos finais poluentes.