Orientadores: Antonio José de Almeida Meirelles, Ronei Jesus Poppi / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia de Alimentos / Made available in DSpace on 2018-08-11T20:39:27Z (GMT). No. of bitstreams: 1 Lanza_Marcelo_D.pdf: 1103711 bytes, checksum: 19a1312d5296b09ceef2d0797ede9f97 (MD5) Previous issue date: 2008 / Resumo: O objetivo do presente trabalho foi determinar dados de equilíbrio líquido-líquido de sistemas reacionais de interesse na produção de biodiesel via rota etílica e a correlação destes dados empregando o modelo NRTL. A técnica instrumental de espectroscopia no infravermelho próximo aliada a métodos quimiométricos (neste trabalho, esta união foi chamada de ¿método NIR¿) foram utilizados para quantificação das composições das fases em equilíbrio. Inicialmente, com a proposta de validar o método NIR, dados de equilíbrio para o sistema óleo de algodão neutro + ácido linoléico comercial + etanol anidro foram determinados a 25 °C pelo método convencional, baseado na titulação ácido-base e evaporação do solvente, e pelo método NIR. O erro relativo entre as composições determinadas por ambos os métodos analíticos foi de 2,07 %. Posteriormente, diagramas de equilíbrio foram determinados para sistemas contendo óleo vegetal + etanol anidro + hexano a 25 °C, sendo os seguintes óleos vegetais investigados: óleo de algodão neutro, óleo de soja refinado, óleo de soja degomado, óleo de canola refinado e óleo de milho refinado. Ademais, foram determinados sistemas contendo óleo de soja refinado + etanol anidro + hexano a (40 e 55) °C, óleo de canola refinado + etanol anidro + hexano a (40 e 55) °C e óleo de palma refinado + etanol anidro + hexano a (45 e 55) °C. Os seguintes sistemas foram também determinados: óleo de soja refinado + etanol anidro + biodiesel etílico a (25 e 40) °C e biodiesel etílico + glicerol + etanol anidro a (25 e 40) °C. Todos os sistemas apresentaram desvios no balanço de massa global menores que 0,5 % e desvios na correlação empregando o modelo NRTL menores que 1,5 % os quais indicaram a boa qualidade dos dados experimentais e o bom desempenho do método NIR / Abstract: The objective of this work was to determine liquid-liquid equilibrium data for systems of interest in biodiesel production via ethylic route and their correlation using the NRTL model. The instrumental technique of near infrared spectroscopy allied to chemometric methods (in this work, this union was called of ¿NIR method¿) were used for quantification of the phase compositions in equilibrium. Initially, with the purpose of validating the NIR method, equilibrium data for the system pretreated cottonseed oil + commercial linoleic acid + anhydrous ethanol were determined at 25 °C by conventional method, based on acid-base titration and solvent evaporation, and by NIR method. The relative error between the phase compositions determined by both analytical methods was 2.07 %. Subsequently, equilibrium diagrams were determined for systems containing vegetable oil + anhydrous ethanol + hexane at 25 °C, being the following vegetables oils investigated: pretreated cottonseed oil, refined soybean oil, degummed soybean oil, refined canola oil, and refined corn oil. Furthermore, were determined systems containing refined soybean oil + anhydrous ethanol + hexane at (40 and 55) °C, refined canola oil + anhydrous ethanol + hexane at (40 and 55) °C, and refined palm oil + anhydrous ethanol + hexane at (45 and 55) °C. The following systems also were determined: refined soybean oil + anhydrous ethanol + ethylic biodiesel at (25 and 40) °C, and ethylic biodiesel + glycerol + anhydrous ethanol at (25 and 40) °C. All systems presented overall mass balance deviations lower than 0.5 % and deviations in correlation using the NRTL model lower than 1.5 %, which indicated the good quality of the experimental data and the good performance of the NIR method / Doutorado / Doutor em Engenharia de Alimentos

Orientador: Celio Pasquini / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Química / Made available in DSpace on 2018-08-25T08:12:03Z (GMT). No. of bitstreams: 1 Silva_CarlosJulianoda_M.pdf: 4366426 bytes, checksum: f7c8d6474698d79b5e218e2896eec667 (MD5) Previous issue date: 2014 / Resumo: No presente trabalho foi feita uma comparação entre as técnicas de reflectância difusa convencional e imagem hiperespectral na região do infravermelho próximo para determinação de viscosidade Mooney (VM), plasticidade inicial (Po), plasticidade após envelhecimento acelerado (P30) e Índice de Retenção de Plasticidade (PRI) em amostras de borracha natural pré-vulcanizadas. Os espectros foram adquiridos utilizando dois espectrofotômetros com transformada de Fourier e uma câmera hiperespectral e os valores de referência determinados de acordo com suas respectivas normas ASTM. Foram construídos modelos de regressão PLS e os seus respectivos valores de erro médio quadrático da previsão (RMSEP) avaliados. Como resultados, foi possível observar um ganho na capacidade preditiva dos modelos PLS com o aumento da área medida de cada amostra. Os modelos obtidos por ambos os pré-processamentos (MSC e derivada de segunda ordem) não apresentaram diferenças significativas quanto às suas capacidades preditivas, ao passo que a seleção de variáveis usando o método Jack-Knife possibilitou a obtenção de modelos com menor número de fatores. Os valores de RMSEP dos modelos otimizados foram de 4,6; 2,9; 3,0 e 5,3 para a determinação da VM, Po, P30 e PRI. Embora os resultados para os três instrumentos possam ser considerados equivalentes, o uso da câmera hiperespectral apresenta algumas vantagens, tais como: tempo de aquisição espectral aproximadamente seis vezes menor quando comparada aos equipamentos convencionais e maior robustez para determinação da viscosidade e plasticidade na presença de contaminantes / Abstract: In this work a comparison between conventional diffuse reflectance (FT-NIR) and hyperspectral image (HI-NIR) in the Near-Infrared region for determination of Mooney viscosity (VM), initial Plasticity (Po), plasticity after accelerated aging and plasticity retention index (PRI) in pre-vulcanized rubber samples was made. The spectra were acquired by using two Conventional Fourier Transform Spectrometer and one hyperspectral camera. The reference values of the rheological parameters were determined according to their respective ASTM standards. Partial least squares (PLS) regression models were constructed and their respective root mean square error of prediction (RMSEP) were evaluated. As results, it was possible to observe a gain in the prediction ability of the PLS models with increasing probed area. The models obtained for both pretreatments (MSC and second derivative) showed no significant differences. However, the variables selection using the Jack-Knife method allowed to obtain models with a low number of factors. The RMSEP values of the optimized models were 4.6, 2.9, 3.0 and 5.3 for determination of MV, Po, P30 and PRI, respectively. Though the results for the three instruments can be considered equivalent, the hyperspectral image instrument presents some relevant advantages, being about six times faster than most of conventional bulk spectrometers, and producing robust spectral data by ensuring sample representativeness, and minimizing the degrading effect of the presence of contaminants / Mestrado / Quimica Analitica / Mestre em Química

Orientador: Márcia Miguel Castro Ferreira / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Química / Made available in DSpace on 2018-08-24T05:57:14Z (GMT). No. of bitstreams: 1 Rambo_MagaleKarineDiel_D.pdf: 17781681 bytes, checksum: b58e114895e86072193e680baa88746e (MD5) Previous issue date: 2013 / Resumo: A geração de materiais residuais e o seu descarte no ambiente têm sido motivo de grande preocupação, tanto ambiental quanto econômica. O aproveitamento dessas matérias-primas residuais renováveis, não apenas para a produção de energia e calor, mas também para a geração de produtos tecnológicos, tornou-se uma prioridade. Neste trabalho, utilizaram-se caracterizações físico-químicas para o aproveitamento de resíduos agroindustriais e agroflorestais como caroço de açaí; serragem de eucalipto; cascas de arroz, café e soja; capim elefante; bambu; resíduos de banana e coco. Tais biomassas foram submetidas à caracterizações físico-químicas a fim de avaliá-las como potenciais matérias-primas no conceito de biorrefinarias. Essas foram caracterizadas e analisadas por meio de técnicas de difração de raios-X (XRD), espectrometria no infravermelho próximo (NIR), extração acelerada por solvente (ASE), cromatografia de troca iônica (HPAEC), análise térmica (TGA), poder calorífico, análise no ultravioletavisível (UV-Vis), análise elementar e análise imediata. Com base nesses resultados, os resíduos de banana, café e coco foram selecionados como biomassas promissoras no contexto de biorrefinarias. Vários estágios de processamento dessas amostras, úmidas - não moídas (WU), secas ¿ não moídas (DU) e secas moídas (DS) foram analisadas. Usando a espectroscopia NIR e análise multivariada foi possível construir modelos de regressão para predizer os teores de lignina Klason, lignina ácida solúvel, resíduo ácido insolúvel, lignina total, extrativos, umidade, cinzas, glicose, xilose, manose, arabinose, ramnose, galactose, bem como o teor de açúcares totais de 104 amostras de resíduos de banana, 102 resíduos de café e 30 resíduos de coco oriundos de diferentes regiões do Brasil. Modelos utilizando o método de regressão por quadrados mínimos parciais (PLS) foram construídos para amostras de banana, café, coco e amostras combinadas de (Banana + Café) e de (Banana + Café + Coco). Os coeficientes de regressão multivariados de cada modelo foram interpretados a fim de garantir a obtenção de modelos confiáveis e não obtidos ao acaso. A precisão da metodologia NIR foi melhor (p < 0,05) que o método de referência para quase todos os parâmetros, sendo pior apenas para a umidade. Com exceção do teor de cinzas, lignina ácida solúvel, e açúcares (principalmente os minoritários) que foram preditos pobremente (Rval < 0,80) em alguns modelos de diferentes frações, os modelos para os demais analitos exibiram Rval > 0,80. Normalmente as frações DU e WU forneceram modelos um pouco inferiores, necessitando um maior número de variáveis latentes, provavelmente devido à heterogeneidade dessas amostras. Os erros relativos variaram de 2 a 25%, e os desvios padrões entre os valores de referência e os previstos foram todos menores que 10%. Os modelos foram validados utilizando figuras de mérito de calibração multivariada. Com base nos resultados da validação externa e figuras de mérito, a espectroscopia NIR mostrou-se útil para a predição química dos resíduos de banana, coco e café, podendo ser usada como uma alternativa rápida, econômica e com menor produção de resíduos químicos frente às metodologias padrões. / Abstract: The generation of waste disposed in the environment has been of great concern, both environmentally and economically. The use of the wastes from renewable feedstocks, not only for the production of power and heat, but also for the generation of technology products, has become a priority. In this work, we investigated the physicochemical characteristics for the utilization of agro-industrial and agroforestry residues such as acai seed; eucalyptus sadwust; rice husks, coffee husks, soypeel, elephant grass; bamboo; banana and coconut wastes. These biomasses were subjected to physicochemical characterizations in order to evaluate their as potential as raw materials in the biorefinery concept. They were characterized and analyzed using techniques of X-ray diffraction (XRD), Near-infrared spectroscopy (NIR), Accelerated Solvent Extraction (ASE), Anion-Exchange chromatography (HPAEC-PAD), Thermogravimetric analysis (TGA), Heating Value, ultraviolet-visible spectroscopy analysis (UV-Vis), proximate and elemental analysis. Based on the results, banana, coffee and coconut residues were selected for biorefineries opportunities. Several stages of processing of the samples, wet and unground (WU), dried and unground (DU), dried and sieving (DS) were analyzed. Using NIR spectroscopy, coupled with chemometric tools was possible to build regression models to predict the Klason lignin (KL), acid soluble lignin (ASL), acid insoluble residue (AIR), total lignin (TL), extractives, moisture, ash, glucose, xylose, manose, arabinose, rhamnose, glactose and the total sugar content, of 104 samples of banana residues, 102 samples of coffee residues and 30 samples of coconut residues, all from different regions of Brazil. Models using the Partial least squares regression (PLS) method were built for Banana, Coffee and Coconut samples and for pooled samples (Banana + Coffee) and (Banana + Coffee + Coconut). Regression Coefficients Interpretation of the model was made to help in the identification of spectral signals characteristics to the analyte and also to detect potential spurious correlations. The precision of the NIR methodology was better (p < 0.05) than the reference method for almost all the parameters, being worse for moisture. With the exception of ash, acid soluble lignin and sugars (especially the minority) content, which was predicted poorly (Rval < 0.80) in some biomass models from different fractions, the models for all the analytes exhibited Rval > 0.80. Normally WU and DU fractions provided somewhat worse models, requiring a greater number of latent variables (LV), probably due to the heterogeneity of the samples. The relative errors varied from 2.00 to 25.00%, and the standard deviations between the reference and predicted values were less than 10.00%. The quality of the models were evaluated by the determination of the multivariate figures of merit. Based on the results of external validation and figures of merit, NIR spectroscopy proved to be useful for chemical prediction of banana, coconut and coffee residues and can be used as a faster and more economical alternative to the standard methodologies. / Doutorado / Quimica Analitica / Doutora em Ciências

Orientador: Ronei Jesus Poppi / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Química / Made available in DSpace on 2018-08-24T05:27:34Z (GMT). No. of bitstreams: 1 Breitkreitz_MarciaCristina_D.pdf: 4580305 bytes, checksum: 77a15e51b9d1be694cc7c5db18fa63bb (MD5) Previous issue date: 2013 / Resumo: Este trabalho teve como objetivo demonstrar como a espectroscopia NIR e Raman de imagem, juntamente com diversos métodos quimiométricos podem auxiliar a tomada de decisões durante o desenvolvimento farmacêutico de formulações de fármacos pouco solúveis em água, tendo como modelo a atorvastatina cálcica. Foram avaliados dois excipientes inovadores, o Gelucire® 44/14 e o Soluplus® que serviram de base para o desenvolvimento das formulações. O Gelucire® 44/14 foi utilizado para o preparo de dispersões sólidas pelos métodos da fusão e da evaporação do solvente e formulações do tipo SEDDS (Self-Emulsifying drug Delivery Sytems), enquanto o Soluplus® foi utilizado para o preparo de dispersões sólidas pelo método da evaporação do solvente. Nas dispersões preparadas pelo método da fusão foram observados aglomerados do fármaco, enquanto o método de evaporação do solvente apresentou melhor homogeneidade na distribuição dos componentes, porém a amostra se apresentou enrijecida após a secagem. Com as formulacoes SEDDS foi possível contornar estes problemas. Foram obtidas dispersões sólidas homogêneas de atorvastatina em Soluplus® utilizando etanol como solvente e lactose como diluente. As imagens foram geradas por calibração univariada, análise de componentes principais (PCA), regressão em mínimos quadrados clássicos (CLS) e regressão em mínimos quadrados parciais (PLS) e os resultados foram comparados. O método CLS foi estudado com mais detalhes devido às suas vantagens para utilização na pesquisa farmacêutica. Os principais fatores que levaram à problemas de exatidão com este método foram identificados e procedimentos para contorná-los foram apresentados e discutidos. / Abstract: The aim of this work was to demonstrate how NIR and Raman image spectroscopy associated with different chemometric methods can support decision making during pharmaceutical development of formulations of low water soluble drugs, using atorvastatin calcium as a model drug. Two innovative excipientes were used, Gelucire® 44/14 and Soluplus®. The former was used to prepare solid dispersions by both hot melt and solvent evaporation methods and to formulate Self Emulsifying Drug Delivery Systems (SEDDS). The latter was used to prepare solid dispersions by the solvent evaporation method. In solid dispersions prepared by the hot melt method it was observed lumps of the drug, whereas the solvent evaporation method presented more homogeneous distribution of the components, even though the sample became stiffened after drying. By preparing SEDDS formulations, it was possible to overcome these problems. A homogeneous solid dispersion of atorvastatin in Soluplus® was achieved by using ethanol as solvent and lactose as diluent. Chemical images were generated by univariate calibration, principal component analysis (PCA), classical least squares (CLS) and partial least squares (PLS). The capability of these methods to generate chemical images were compared. CLS method was studied more carefully due to its advantages for pharmaceutical research use. The main features that lead to accuracy issues were identified both in Raman and in NIR spectroscopy and procedures to overcome them were presented and discussed. / Doutorado / Quimica Analitica / Doutora em Ciências

Orientadores: Juliana Azevedo Lima Pallone, Ronei Jesus Poppi / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia de Alimentos / Made available in DSpace on 2018-08-22T02:38:43Z (GMT). No. of bitstreams: 1 Ferreira_DanielaSouza_D.pdf: 2148960 bytes, checksum: 45b2c46dd9d82dfd00f454c5a430d494 (MD5) Previous issue date: 2013 / Resumo: A avaliação da qualidade nutricional de alimentos é realizada principalmente por meio da determinação dos componentes majoritários, conhecida como composição centesimal (umidade, proteína, cinza, lipídio, carboidrato e fibra). No entanto, os métodos tradicionais de análise são demorados e utilizam materiais, equipamentos e diversos reagentes químicos, que além de oferecerem risco ao analista, geram resíduos tóxicos. Diante disto, uma alternativa para a análise química de grãos, rápida, de baixo custo e sem uso de reagentes químicos é a espectroscopia na região do infravermelho. Visando atender a demanda do Brasil por pesquisas empregando espectroscopia no infravermelho para análise de alimentos, o objetivo desse trabalho foi avaliar a possibilidade de utilização das técnicas espectroscopia no infravermelho próximo (NIR), principalmente, e médio MIR, associadas à quimiometria, para previsão de parâmetros de qualidade da soja brasileira e quinoa da América do Sul. Para comparar a aplicação de NIR e MIR, amostras de soja provenientes do Paraná foram analisadas pelas duas técnicas para previsão da composição centesimal. Os erros relativos (E%) entre os valores de referência e os valores previstos pelos modelos de calibração PLS, foram pequenos tanto para o NIR como para o MIR, no entanto, os resultados sugerem o uso de NIR para previsão de lipídios (0,2 a 9,2%) e o uso de MIR para proteínas (0,2 a 5,6%), cinzas (0 a 5,0%) e umidade (0,1 a 2,0%). Posteriormente, foram construídos modelos de calibração PLS com NIR para previsão dos parâmetros de qualidade em soja moída e para a quinoa, grão inteiro e moído. Os melhores modelos de calibração para soja encontrados neste estudo foram para o conteúdo de proteína e umidade, com melhores coeficientes de determinação e raiz quadrada do erro médio quadrático de calibração (R2= 0,81, RMSEC = 0,58% e R2 = 0,80, RMSEC = 0,28%, respectivamente), contudo, a técnica mostrou capacidade adequada de predição para todos os parâmetros, incluindo lipídios, cinzas, carboidratos e fibras. Para amostras de quinoa, os espectros NIR foram inicialmente submetidos a uma análise de componentes principais (PCA) para tentar separá-las em grupos, de acordo com a origem geográfica destes grãos, os quais eram provenientes do Brasil, Bolívia e Peru. Duas componentes principais explicaram 98,2% do total da variância e três grupos foram observados na separação por PCA de acordo com o país de origem. A técnica de calibração por PLS produziu modelos adequados, que permitiu a quantificação da composição majoritária tanto para o grão inteiro como farinha de quinoa, mostrando boa correlação entre o valor previsto e o valor real, com R2 > 0,65 e RMSEC< 1,70%. Portanto, este estudo demonstra que a técnica de NIR é potencialmente útil como um método analítico não destrutivo para determinações rápidas e simples de constituintes alimentares, além de não necessitar nenhum tipo de preparo de amostra, já que os espectros dos grãos inteiros de quinoa forneceram bons resultados para previsão dos parâmetros estudados / Abstract: Evaluation of nutritional quality of food has been mainly performed by determination of major compounds, which is known as centesimal composition (moisture, protein, ash, lipid, carbohydrate and fiber). However, the traditional methods of analysis are time-consuming, use many materials and equipment, and also toxic reagents, that generate waste and are a risk for the analyst. Thus, infrared spectroscopy is an alternative to chemical analysis of grains, as it is a rapid, low cost technique and it does not use toxic reagents. In coming years, Brazilian researches using infrared for food analysis should increase, thus the objective of this work was to evaluate the possibility of application mainly of near-infrared (NIR) and mid-infrared (MIR) spectroscopy techniques coupled with chemometrics to predict quality parameters in Brazilian soybean and South America quinoa. In order to compare NIR and MIR techniques, the soybean group from Paraná (Brazil) was analyzed using both techniques to predict centesimal composition. The related errors (E%) between reference values and predicted values by partial least square (PLS) were low for both the NIR and the MIR. However, the results propose the use of NIR to predict lipid (E% of 0.2 to 9.2) content and the use of MIR to predict protein (E% of 0.2 to 5.6), ash (E% of 0 to 5.0), and moisture (E% of 0.1 to 2.0) contents. Subsequently, PLS regression models were constructed using NIR to predict quality parameters in ground soybean and quinoa, grain and ground. The best calibration models to soybean found in this study were the ones used to determine protein and moisture content (R2 = 0.81, RMSEP = 1.61% and R2 = 0.80, RMSEC = 1.55%, respectively). However, the technique shows high predictability for all parameters, including lipids, ash, carbohydrates and fibers, RMSECV of 0.40 to 2.30% and RMSEP 0.38 to 3.71%. For quinoa samples NIR spectra were obtained and principal component analysis (PCA) was applied to try to identify the geographic origin of quinoa samples, from Brazil, Peru and Bolivia. Two principal components explained 98.3% of the total variance and three groups were observed using PCA. The PLS models developed for the chemical composition showed that the proposed methodology produced adequate results, as whole grain as ground quinoa, with the graph of the real and predicted concentration having a coefficient of determination (R2) > 0.65 and RMSEC < 1.70%. The viability of the NIR technique with no waste generation, low cost, reduced time and no kind of sample preparation for replacing laborious methods of analysis was demonstrated because the results for grains were satisfactory / Doutorado / Ciência de Alimentos / Doutora em Ciência de Alimentos

Mosquitoes spread diseases that shorten and worsen the lives of many people, chiefly children in poor countries, around the world. Since Ronald Ross' discovery at the end of the nineteenth century that mosquitoes transmit malaria, field entomologists have collected a great deal of information about mosquito ecology. Despite this tremendous effort, there still remain significant gaps in our knowledge of mosquito ecology, in part, reflecting the significant variation in mosquito ecology across species and geographies. The main aim of this thesis is an attempt to synthesise the substantial information that field entomologists have collected on mosquito lifespan. In Chapters 2 and 3, I conduct meta-analyses of the two predominant approaches used to estimate mosquito lifespan: mark-release-recapture experiments and female mosquito dissection-based studies, respectively. These analyses produce estimates of mosquito lifespan by species and genus, and more broadly, allow for an appraisal of these two experimental approaches. In Chapter 4, I describe a recently developed approach, known as near-infrared spectroscopy, which enables estimation of the age of individual mosquitoes, and then perform an in silico analysis to explore the use of this technology for estimating the average lifespan of wild populations of mosquitoes. The emergence of mosquito resistance to the main insecticides used in vector control, along with the concerning recent discovery that the malaria parasites in Asia are becoming resistant to arteminisin - an important drug used to treat malaria - highlight the need for novel approaches to control disease transmission. Some recently-proposed approaches involve genetic modification of the mosquito vectors, for example, to render them incapable of acting as hosts for disease or to reduce their fecundity. In Chapter 5, I model the impact of a release of mosquitoes carrying a genetic construct known as a homing endonuclease, which has been constructed to bias the sex of mosquito offspring towards males, in computational environments that capture some facets of the real life landscapes where mosquito borne disease is rife. About a century ago, the famous Italian Malariologist Giovanni Grassi declared that malaria was a "giant with clay feet"; reflecting the optimism, in some academic circles at the time, that eradication of this terrible disease would soon occur. Unfortunately, a century of often unsuccessful attempts to control and eradicate malaria, and other mosquito borne diseases, would follow Grassi's statement, meaning that this fight is likely to continue throughout the twenty-first century. We now know much more about mosquitoes and mosquito borne disease than we did a generation ago, but there is still crucial information that we do not. In this thesis, I argue that in order to make significant inroads to disease eradication, further research on mosquito ecology is crucial. Only when we better understand our unwitting mosquito foe, can we design and implement effective disease control measures that are so desperately needed in those most desperate parts of the world.

This thesis presents temporal perspectives of lake acidification in Sweden. Sediment records have been used to study timing, trends and causes of acidification, and two different techniques for assessing past lake-water acidity are presented. A new technique for pH prediction, based on near-infrared (NIR) spectroscopy of surface sediments, is developed. This study shows that there is a pH related fraction of lake sediments that can be recorded by NIR analysis. Relationships between NIR spectra of surface sediment samples and measured lake-water pH values, and between NIR spectra of sediment cores and historical pH values inferred by diatom analysis, are modelled by partial least squares regression. The prediction errors of the models are comparable to those obtained by modelling of diatom and lake-water pH data. By further development NIR spectroscopy can become useful for inferring past pH, as well as several other lake-water parameters, from sediment cores. Diatom-based predictive models, using multivariate calibration methods, are developed for inferences of lake-water pH, alkalinity and colour. These models are used to provide a regional assessment of recent lake acidification in the provinces of Västerbotten and Norrbotten, northern Sweden. The study shows that a pH decline has occurred in some southeastern lakes, but that most of the lakes have not faced significant changes in lake-water pH, alkalinity and colour. The inferred water chemistiy changes are discussed in relation to atmospheric deposition and land-use. In a study of eight acid-sensitive Swedish boreal-forest lakes a past-analogue approach is used to test whether contemporary expansion of conifers could cause lake acidification. Water chemistry changes associated with the natural pre-historic colonization and expansion of spruce in Sweden (≈3000 years B.P.), at times of background atmospheric acidity, are inferred to evaluate the acidification ability of spruce per se on surface waters. This study shows that under natural, unpolluted conditions spruce colonization and expansion did not cause lake acidification. In a synthesis of palaeolimnological acidification research in Sweden a general model for pH- development for acid clear-water lakes in southern Sweden is presented. The pH-development from the last deglaciation to present time can be divided into four different periods; (i) a natural long-term acidification period (12000 B.P. - 2300 B.P., or later), with a gradual decrease in pH resulting from declining fluxes of base cations from catchment soils; (ii) a human induced alkalization period (2300 B.P. - 1900 A.D.), with a pH increase due to human activities in the catchments; (iii) the recent acidification period (about 1900 A.D. - present), when pH decreased towards 4.5 due to acid deposition and possibly ceased land-use; and (iv) the liming period (1970s - present), when pH often increases to values above 7 following lime treatment to counteract acidification. The implications of these past pH changes for the concept of contemporary lake acidification and for liming policy are outlined. / digitalisering@umu

Frequency Domain Diffuse Optical Spectroscopy (FD-DOS) is an emerging optical technique that uses near infrared light to probe the hemodynamics of biological tissue. Compared to more common Continuous Wave (CW) methods, FD-DOS uses light that is temporally modulated on the order of MHz to quantify the absorption and scattering of tissue. FD-DOS can also be used to obtain absolute concentration of tissue chromophores such as oxy- and deoxy-hemoglobin, which allow for quantitative measurements of tissue hemodynamics. This dissertation focuses on the evolution of our lab’s custom digital FD-DOS as a platform for taking optical measurement of biological tissue for respiratory and cardiovascular applications. Several important instrumentation improvements will be reviewed that have enhanced the performance of the system while making it more portable and clinic ready. Two translational applications will be described in detail: 1) the use of high-speed FD-DOS for the non-invasive extraction of venous oxygen saturation (SvO2) and 2) the use of FD-DOS to monitor the hemodynamics of the sternocleidomastoid (SCM) muscle towards the non-invasive monitoring of patients on mechanical ventilation. The custom FD-DOS system parameters were adjusted for each application, with a focus on high speed to extract the cardiac signal for the SvO2 project, and a focus on high SNR to measure the highly absorbing SCM. Measurements on healthy volunteers and rabbits were used to assess the feasibility of using FD-DOS for these applications. Finally, preliminary work was conducted to characterize a miniature FD-DOS source and detector with the goal of moving towards a wearable version of FD-DOS. / 2022-05-15T00:00:00Z

Title: Physiological responses on standardized climbing task in sport climbers Purpose: To determine the effect of height, wall angle, climbing speed and climbing ability on physiological responses in sport climbers. Methods: The study was divided into three parts. 75 sport climbers (36 female and 39 male) completed differing tests on climbing wall and motorized climbing ergometer. Perceived exertion was assessed on a scale suggested by Borg. Indirect calorimetry, venous blood samples and near-infrared spectroscopy were used to assess physiological response, hormonal response and muscle oxygen saturation, respectively. Results: Perceived exertions were higher when climbing to height as opposes to climbing low to the ground on the treadwall (+5,3%; P = 0,013; ηp 2 = 0,149) (Study 1A). The physiological response was higher on the climbing wall as opposed to the treadwall: V̇ O2 (+6%; P = 0,03; ηp 2 = 0,22), SF (+4%; P = 0,04; ηp 2 = 0,20), V̇ E (+9%; P = 0,01; ηp 2 = 0,30) a EC (+16%; P < 0,001; ηp 2 = 0,48). There was an interaction for climbing ability and post- climbing catecholamine concentration (P < 0,01, ηp 2 = 0,28) (Study 1B). With increasing climbing speed greater differences were found for V̇ O2 (P < 0,001, ηp 2 = 0,923) than for StO2 (P < 0,001, ηp 2 = 0,448). Between-subject effect...

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