Los biocombustibles se utilizan principalmente en forma de blends, mezclados con combustibles fósiles, derivados del petróleo. Los blends de nafta + bioetanol juegan un rol muy importante en países tales como Brasil y EEUU. Existen otras alternativas, tales como etanol + diesel y diesel + biodiesel. Cada combinación contempla un rango de composiciones de mezcla. Si sumamos a esto el hecho de que nuevos avances en el procesamiento de la biomasa pueden hacer aparecer nuevos biocombustibles, resulta clara la utilidad de disponer de un modelo termodinámico de soporte que permita predecir propiedades de interés de las mezclas combustibles. Esto permitiría, entre otras cosas, ahorrar tiempo y dinero en experiencias de laboratorio, en la búsqueda de mezclas con buen potencial, descartando aquellas que no satisfagan los criterios fijados. En la presente tesis se estudian en particular los blends naftas + bioalcoholes. La nafta es una mezcla multicomponente constituida principalmente por cuatro familias de hidrocarburos: alcanos normales, ramificados y cíclicos e hidrocarburos aromáticos. La presencia de compuestos oxigenados tiene un fuerte impacto sobre la volatilidad y el comportamiento de fases los combustibles, debido a la no-idealidad típica de mezclas de compuestos polares y no-polares. Por otra parte, las mezclas están formadas por un gran número de compuestos de una misma familia, por lo que los modelos a contribución grupal constituyen la mejor opción para calcular sus propiedades. Comparados con los modelos moleculares, los modelos a contribución grupal requieren un menor número de parámetros para caracterizar las interacciones entre los componentes de una mezcla y ofrecen una mayor capacidad predictiva. En esta tesis se utiliza la ecuación de estado a contribución grupal con asociación GCA-EoS. En el Capítulo I se introduce el tema de tesis y se plantean sus objetivos. En el Capítulo II se describen las características del modelo GCA-EoS y se explican en detalle cada uno de sus términos. Los Capítulos III al VII describen el proceso de parametrización llevado a cabo sobre mezclas de agentes oxigenados (alcoholes y éteres) y agua, con cada tipo de hidrocarburo (alcano normal, ramificado y cíclico e hidrocarburo aromático) presente en las naftas. En el Capítulo VIII se analizan detalladamente las propiedades de volatilidad y tolerancia al agua de las naftas, y el impacto que produce sobre las mismas, el agregado de un compuesto oxigenado como aditivo. El Capítulo IX muestra la simulación del proceso de extracción/deshidratación de etanol mediante un fluido supercrítico (propano), utilizando como soporte termodinámico la ecuación GCA-EoS con los parámetros determinados en esta Tesis. Finalmente, en el Capítulo X se discuten las conclusiones generales de este trabajo de tesis, y se propone trabajo a futuro que permita ampliar las capacidades en el modelado de mezclas de biocombustibles y combustibles fósiles. / Biofuels are mainly used as blends, mixed with fossil fuels derived from crude oil. Bioethanol + gasoline blends play a major role in countries like Brazil and USA. There are other alternative blends, such as ethanol + diesel and biodiesel + diesel. Every combination covers a range of compositions. If we also take into account that new developments in biomass processing can make new biofuels available, it becomes clear the advantage of having a suitable thermodynamic model to predict the properties of the fuel blends. This would allow, among other things, to save time and money in laboratory experiments, in the search of mixtures with good potential as transport fuels, disregarding those that do not meet standard properties. In particular, bioalcohol + gasoline blends are studied in the present thesis. Gasoline is a multicomponent mixture of hydrocarbons, belonging mainly to four families: normal-, branched- and cyclic-alkanes and aromatic hydrocarbons. The presence of oxygenated compounds has a strong impact on the volatility and phase behavior of fuels, due to the typical non-ideality of mixtures having polar and non-polar compounds. On the other hand, a great number of different compounds in these mixtures belong to the same chemical species. For this reason group-contribution models are the best option to calculate their properties. Compared against molecular models, group-contribution models require a lower number of parameters to represent interactions among mixture components and offer a more ample predictive capacity. In this Thesis, the group-contribution with association equation of state GCA-EoS is used. In Chapter I, the research subject and objectives of the Thesis are presented. Chapter II describes the characteristics of the GCA-EoS model and explains in detail each term of the equation. Chapters III to VII explain the parameterization process carried out on mixtures containing oxygenated additives (alcohols and ethers), water and each family of the typical gasoline hydrocarbons (normal-, branched- and cyclic-alkanes and aromatic hydrocarbons). Chapter VIII contains a detailed analysis of the volatility properties and water tolerance of gasoline, and discusses the impact produced on these properties by the addition of oxygenated additives to the fuel. Chapter IX shows the results of the simulation of a supercritical process for the extraction and dehydration of bioethanol from a fermentation broth. The GCA-EoS equation, with the parameters obtained in this thesis, was used to model the phase equilibrium conditions in each of the process units. Finally, Chapter X discusses the general results of the thesis and proposes future work to increase modeling capacity in the area of biofuel-fossil fuel blends.

Endocrine disruptors are natural or manmade substances which affect hormonal systems of organisms. Biologically relevant concentrations are commonly being detected in the environment. The effluents of wastewater treatment plant present their significant secondary source. Due to their occurence and quantity the interest in mixtures increases. Ecotoxicological assays with genetically modified Saccharomyces cerevisiae were aplied to verify reliability of predictive mathematical models for mixtures of standards (estrone, 17β-estradiol, 17α-ethinylestradiol, estriol, bisphenol A, irgasan, 4-nonylphenol). Chromatographic analysis along with yeast assays were used for the evaluation of real samples of wastewater treatment plant effluents and sediments. Schindler's predictive model and Full logistic model (FLM) were more reliable for predicting the whole dose-response curve compared to Generalized concentration addition (GCA). Predicted values of a parameter EC50 from all three models were comparable to empirical measurements. Three out of four samples exhibited estrogenic activity 0.65 - 1.70 ng/L 17β-estradiol ekvivalent (EEQ) above the limit of detection 0.13 - 0.33 ng/L EEQ. Antiestrogenic activity was detected in one of the samples. Prediction could be carried out only in the case of the sediments...

En la presente tesis se plantea el modelado del equilibrio entre fases de mezclas de importancia en biorrefinerías, y el desarrollo de módulos de simulación de procesos y productos. El modelo termodinámico empleado es la Ecuación de Estado a Contribución Grupal con Asociación (gca-eos) que ha sido desarrollada y exitosamente aplicada al procesamiento de mezclas derivadas de sustratos vegetales y de sistemas a alta presión por el grupo de Termodinámica de Procesos de plapiqui. La gca-eos es robusta para la representación, tanto a baja como alta presión, de sistemas altamente no ideales que presenten asimetría en tamaño y energética y con presencia de interacciones de tipo puente hidrógeno, generalmente presentes en mezclas procedentes del procesamiento de productos naturales. Su carácter a contribución grupal facilita la predicción de compuestos complejos y mezclas a los que se les desconoce sus propiedades, como también frecuentemente ocurre con los de origen natural. Dadas las características favorables de este modelo se propone su extensión para cubrir un número mayor de grupos funcionales típicos del procesamiento en biorrefinerías y una mejor descripción de las interacciones asociativas que pueden presentar el agua, alcoholes, compuestos nitrogenados y aromáticos. Teniendo en cuenta esta premisa se implementaron algoritmos de cálculo termodinámico que fueron incorporados a simuladores de procesos, con énfasis en equipos involucrados en la purificación de biocombustibles, como por ejemplo equipos de destilación flash, columnas de destilación y extractores líquido-líquido. La presente tesis se desarrolla en 8 capítulos. Luego de un apartado introductorio, el capítulo 2 describe el modelo termodinámico gca-eos, destacando leyes físicas que lo sustentan ya que resultan una herramienta sólida para generar las estrategias de parametrización desarrolladas en esta tesis. Los siguientes capítulos, muestran la extensión del modelo a las distintas familias de compuestos orgánicos estudiados. Específicamente, el capítulo 3 trata la extensión la gca-eos, a hidrocarburos aromáticos en sistemas que involucren alcoholes alifáticos y agua. El capítulo 4 por su parte, discute una nueva definición de los grupos fenólicos en sistemas con hidro - carburos aromáticos, alifáticos y agua. Los capítulos 5 y 6 discuten la parametrización de sistemas nitrogenados: el primero define los nuevos grupos amino, y si interacción con hi - drocarburos y alcoholes, mientras que en el segundo se incluye mezclas acuosas de estos compuestos y se prueba la capacidad predictiva de la gca-eos en soluciones acuosas de alcanolaminas. Siendo estas últimas un reconocido solvente para la remoción de gases ácidos también presentes en el procesamiento, tanto bio- como termo-químico, de biomasa. Por último, el capítulo 7 trata el desarrollo de un módulo de simulación de columnas trifásicas. Se desarrollan las ecuaciones básicas que permiten adaptar un algoritmo tradicional de destilación líquido-vapor para considerar la posible existencia de dos fases líquidas. Como caso de estudio, se analiza una columna de remoción de metanol en el contexto del proceso supercrítico de producción de biodiesel. / Phase equilibrium modeling of mixtures of importance in biorefineries, and the development of process simulation modules and products are presented in this thesis. The thermodynamic model chosen is the Group Contribution with Association Equation of State (gca-eos). This model has been developed by the group of Process Thermodynamics in plapiqui and successfully applied to model processes of mixtures of vegetable substrates and high-pressure systems. The gca-eos is capable to model systems of highly non-ideal mixtures, at low or high pressures, which exhibit important energetic and size asymmetry. Also the model is able to handle molecules that present h-bond interactions, characteristic of natural products mixtures. Moreover, its group contribution formulation allows the predictions of unknown properties of complex compounds and mixtures, as in the case of natural compounds. These characteristics encourage an extension of its parameter table to cover a greater number of functional groups that are common in biorefineries processes. Another goal of this thesis was to obtain a better description of associative interactions present in mixtures of water, alcohols, with aromatic and nitrogen compounds. With this premise, thermodynamic calculation algorithms were incorporated into process simulators, with emphasis on equipment involved in the purification of biofuels, such as flash distillation equipment, distillation columns and liquid–liquid extractors. This thesis is presented in eight chapters. After an introductory section, Chapter 2 describes the mathematical formulation of the gca-eos, with emphasis on underlying physical laws which generate robust parameterization strategies developed in this dissertation. The following chapters show the extension of this model to different families of organic compounds studied in this work. Chapter 3 addresses the extension of the model to aromatic hydrocarbons in systems with water and aliphatic alcohols. Chapter 4 discuss a new definition of the phenolic group present in systems with aromatic and aliphatic hydrocarbons and water. Chapters 5 and 6 discuss the parameterization of amine groups: the first one defines new amine groups and its interaction with aliphatic hydrocarbons and alcohols, while the second one includes aqueous amine mixtures, and the predictive capability of the gca-eos is tested with aqueous alkanolamine solutions. Finally, Chapter 7 shows the development of a simulation module of a three phase distillation column. Basic equations that enable a typical vapor–liquid distillation algorithm to represent the existence of two liquid phases are presented. Furthermore, a methanol stripping column in the context of supercritical biodiesel production is analyzed as a case of study.

In spinal cord injury the amount of total surviving white matter is known to be strongly related to post injury neurological functions (1). Accurate segmentation of these regions is shown to be critical in terms of developing effective treatment (1). Diffusion Tensor Imaging (DTI) has been shown to be effective in obtaining spinal cord images (2). However challenges still exist in clear separation of gray/white/cerebrospinal fluid (CSF) structures within the cord using DTI. The purpose of this study is to (1) test a semi-automatic tissue segmentation algorithm based on grow cut algorithm (GCA), to classify CSF, gray and white matter in conventional T2 weighted MRI and Diffusion Tensor Imaging (DTI) images in pediatric spinal cord injury (SCI) subjects, and (2) to compare the results of semi-automatic GCA segmentation with manually segmented spinal cord data performed on various DTI images by a board certified pediatric neuroradiologist. Results show that semi-automatic segmentation of the spinal cord using GCA was successfully implemented. Qualitatively, good separation of cord/CSF was seen in B0, CFA and FA maps (of a representative patient with SCI and a control using this GCA method. They demonstrate more homogeneous signal within the cervical spinal cord as well as greater conspicuity of the cord and surrounding CSF interface. Quantitative analysis of images segmented using GCA and manual segmentation between and within the groups showed no significant differences in CFA (p=0.1347) and FA (p=0.1442) images but B0 (p=0.0001) images showed statistically significant differences. Overall, in both the controls and subjects with SCI, quantitative and qualitative analysis showed a superior semi-automated segmentation on CFA and FA images over a B0 image the using modified GCA. Key words: Grow Cut Algorithm (GCA), Magnetic Resonance Imaging (MRI), segmentation, Diffusion Tensor Imaging (DTI), cervical spinal cord, cerebral-spinal fluid (CSF). / Bioengineering

<p>Najznačajniji ograničavajući činilac proizvodnje svih biljnih vrsta je nedostatak dovoljnih količina vode. Dobijanje novih genotipova sa povećanom tolerantno&scaron;ću prema nedostatku vode bi doveo do stabilnijih prinosa i u nepovoljnim uslovima, ali oplemenjivanje prema ovom abiotičkom faktoru je jo&scaron; uvek dugotrajno i iziskuje značajna finansijska sredstva. Do sada je bilo veoma malo istraživanja o uticaju nedostatka vode na &scaron;ećernu repi koristeći morfolo&scaron;ke i fiziolo&scaron;ke pokazatelje i kod roditeljskih linija i njihovih hibridnih kombinacija. Zbog toga, potraga za jednostavnim i brzim metodama za opis oplemenjivačkog materijala u odnosu na nedostatak vode igra važnu ulogu u programima oplemenjivanja.<br />Cilj istraživanja je bio da se u uslovima vodnog deficita ispitaju: razlike između roditeljskih linija i njihovih hibrida za 10 odabranih svojstava (masa svežeg korena, masa suvog korena, broj listova, masa liske po biljci, masa lisne dr&scaron;ke po biljci, gustina stoma, difuzni otpor stoma, sadržaj prolina, relativni sadržaj vode u listovima i specifična masa lista), kombinacione sposobnosti linija, međusobna povezanost između svojstava, kao i koja od ispitivanih svojstava bi se mogla koristiti kao pouzdan pokazatelj prema nedostatku vode.<br />Za materijal su odabrane: 4 jednoklične fertilne inbred linije &scaron;ećerne repe različite tolerantnosti prema venjenju u poljskim uslovima (linije 3, 4, 5 i 6), 2 monogermna citoplazmatski mu&scaron;ko sterilna testera ( linija 1 i 2 ) i njihovih 8 hibrida (3x1, 3x2, 4x1, 4x2, 5x1, 5x2, 6x1 i 6x2). Biljke su gajene u stakleniku, a primenjena su tri tretmana zalivanja i to: 30% od izmerene dnevne potro&scaron;nje vode (DPV), 60% od DPV i kontrola (100% od DPV).<br />Najmanja masa svežeg korena (jedna godina istraživanja) je zabeležena kod linija 3 i 4 (u polju ocenjene kao osetljive na nedostatak vode). Masa korena linija i hibrida kao jedno od najvažnijih svojstava u oplemenjivanju je bila u pozitivnoj korelaciji sa masom liske i masom lisne dr&scaron;ke u kontroli kao i u tretmanima. Masa liske osetljivih linija 3 i 4 je u jednoj godini bila najmanja u kontroli (100% DPV) i 60% DPV, a u uslovima najvećeg nedostatka vode skoro da nije bilo razlika između linija, kao ni&nbsp;između hibrida. Veći sadržaj prolina i veća specifična lisna masa se ne mogu koristiti kao pogodna svojstva za veću tolerantnost &scaron;ećerne repe prema nedostatku vode. Primenom PCA analize jasno su se izdvojile linije 3 i 4, koje su u poljskim uslovima ocenjene da su osetljive na nedostatak vode. Prema klaster analizi može se reći da su sa svojstvima korena najvi&scaron;e povezana: masa liske, masa lisne dr&scaron;ke, broj listova i RWC. Tako da su ova svojstva od većeg značaja za oplemenjivanje &scaron;ećerne repe u uslovima dobro obezbeđenih vodom kao i u uslovima sa smanjenim količinama vode. Svojstva koja su bila u najslabijoj vezi sa korenom &scaron;ećerne repe su: gustina stoma, difuzni otpor stoma, specifična masa listova i sadržaj prolina.</p> / <p>The most limiting factor for production of all plant species is the lack of appropriate amount of water. Breeding of new genotypes with increased tolerance to the water stress would lead to more stable yields under dry conditions. Breeding for this abiotic factor is time-consuming and requires significant financial resources. There have been very few researches of the impact of water stress in the sugar beet using morphological and physiological parameters in the parent lines and their hybrid combinations. Therefore, the search for simple and rapid methods for the description of breeding materials in relation to water stress, play an important role in breeding programs.<br />The aim of this research was to examine the differences between parental lines and their hybrids under water deficit for 10 selected traits: (fresh root weight, dry rootweight, number of leaves, lamina weight per plant, petiole weight per plant, stomatal density, stomatal diffusive resistance, proline content, relative water content in leaves and specific leaf weight). The aim of this research was also to test combining ability of lines, correlation between the traits and which trait could be used as a reliable parameter in water stress conditions.<br />As plant material were used: 4 monogerm fertile sugar beet inbred lines with different tolerance to leaf wilting in field conditions (lines 3, 4, 5 and 6), 2 monogerm cytoplasmic male sterile testers (lines 1 and 2) and their hybrids 8 (3x1, 3x2 , 4x1, 4x2, 5x1, 5x2, 6x1 and 6x2). Plants were grown in a greenhouse, and there were applied two treatments of irrigations: 30% of the daily water need (DWN), 60% of the DWN and control (100% of DWN).<br />Line 3 and 4 (in the field marked as sensitive to water stress) had a lowest fresh root weight. Root weight as one of the most important trait in breeding was positively correlated with the lamina weight and petiole weigh in the control and in the treatments. Lines 3 and 4 had lowest lamina weight in the control (100% DWN) and 60% of DWN. The higher content of proline and higher specific leaf weight cannot be&nbsp;used as a suitable trait for higher tolerance to water stress. Lines 3 and 4 were separeted by PCA analysis from other genotypes. These lines were marked as sensitive to water stress in field conditions. According to cluster analysis, the root traits were the most correlated with lamina weight, petiole weight, number of leaves and RWC. These traits are significant for sugar beet breeding in well water and dry water conditions. Stomatal density, stomatal diffusive resistance, specific leaf weight and proline content were in the lowest correlation with root traits.</p>

The physic nut (Jatropha curcas L.) is oilseed species belonging to Euphorbiaceae family with a widespread distribution in tropical regions. The quality and high oil content in seeds, perenicity and rusticity makes this species a potential feedstock for biodiesel production. However, the success of this insertion involves research ranging from the exploration of divergent genetic materials to selection and acquisition of productive cultivars. In this context, this study aimed to assess the combining ability of jatropha access for agronomic traits of interest, as well as information about genetic parameters associated with morphological and agronomic characters, and investigate their correlations. The study was carried out in the Experimental Farm of the UFS during the year 2012 in hybrids of jatropha evaluated up to 24 months. The experimental design was in randomized blocks with three replications and plots with six plants. There were evaluated seed yield (PR), plant height (PH), number of secondary branches (NRS), the number of female flowers (NFF), stem diameter (DC), 100-seed weight (P100 ), branching height (AR) and crown diameter (DCO). The general combining ability (GCA) was significant for the variables PR, DC, NRS and AR (Group 1) and P100 and NRS (Group 2), whereas specific combining ability (SCA) was significant for variables NFF and NRS. The sum of squares due to GCA was higher than the sum of squares due to SCA for the majority of traits, indicating that the additive effects of loci are more important than the dominance effect loci. The genitors JCUFS-04 and JCUFS-05 highlight from the others for concentration of favorable alleles. The consistent estimation of the coefficient of genetic variation allows us to infer the existence of significant genetic variability among hybrids. The characters which more contributed to genetic diversity were NFF (20.99%), DC (16.83%), PR (15.06%), and NRS (14.06). High, significance and positive genotypic correlations were recorded among (NRS), (DC), (DCO) and grain yield (PR). / O pinhão-manso (Jatropha curcas L.) é uma espécie oleaginosa da família Euphorbiaceae com ampla distribuição em regiões tropicais. A qualidade de óleo e alto teor nas sementes, perenicidade e rusticidade fazem desta espécie uma matéria-prima potencial para produção de biodiesel. Todavia, o sucesso desta inserção passa por pesquisas que vão desde a prospecção de materiais genéticos divergentes, até a seleção e obtenção de cultivares produtivos. Nesse contexto, esse trabalho teve por objetivo avaliar a capacidade combinatória de acessos de pinhão-manso, para caracteres de interesse agronômico, bem como, obter informações acerca de parâmetros genéticos associados a caracteres morfo-agronômicos, e investigar a correlação entre estes. O trabalho foi realizado na Fazenda experimental da UFS durante o ano de 2012 em híbridos de pinhão-manso avaliados até os 24 meses de idade. O delineamento experimental empregado foi em blocos casualizados com três repetições e parcelas compostas por seis plantas. Os caracteres avaliados foram rendimento de sementes (PR), altura de planta (AP), número de ramos secundários (NRS), número de flores femininas do racemo floral (NFF), diâmetro de caule (DC), massa de 100 sementes (P100), altura de ramificação (AR) e diâmetro de copa (DCO). A capacidade geral de combinação (CGC) foi significativa para as variáveis PR, DC, NRS e AR (Grupo 1) e para P100 e NRS (Grupo 2), enquanto a capacidade específica de combinação (CEC) foi significativa para as variáveis NFF e NRS. A soma de quadrados devido à CGC foi maior que a soma de quadrados devido à CEC para a maioria dos caracteres, indicando que os locos de efeito aditivo têm maior importância que os locos de efeito dominante. Os genitores JCUFS-04 e JCUFS-05 se destacaram dos demais quanto à concentração de alelos favoráveis. As estimativas consistentes dos coeficientes de variação genética permitem inferir sobre a existência de variabilidade genética significativa entre os híbridos obtidos. Os caracteres que mais contribuíram para a diversidade genética encontrada entre a populações foram, NFF (20,99%), DC (16,83%), PR (15,06%) e NRS (14,06). Altas e significativas correlações genotípicas positivas foram registradas entre (NRS), (DC), (DCO) e o rendimento de grãos (PR).

With the deregulation of power industry and the market competition, stable and reliable power supply is a major concern of the independent system operator (ISO). Power-quality (PQ) study has become a more and more important subject lately. Harmonics, voltage swell, voltage sag, and power interruption could downgrade the service quality. In recent years, high speed railway (HSR) and massive rapid transit (MRT) system have been rapidly developed, with the applications of widespread semiconductor technologies in the auto-traction system. The harmonic distortion level worsens due to these increased uses of electronic equipment and non-linear loads. To ensure the PQ, power-quality disturbances (PQD) detection becomes important. A detection method with classification capability will be helpful for detecting disturbance locations and types. Electric machinery fault diagnosis is another issue of considerable attentions from utilities and customers. ISO need to provide a high quality service to retain their customers. Fault diagnosis of turbine-generator has a great effect on the benefit of power plants. The generator fault not only damages the generator itself, but also causes outages and loss of profits. With high-temperature, high-pressure and factors such as thermal fatigues, many components may go wrong, which will not only lead to great economic loss, but sometimes a threat to social security. Therefore, it is necessary to detect generator faults and take immediate actions to cut the loss. Besides, induction motor plays a major role in a power system. For saving cost, it is important to run periodical inspections to detect incipient faults inside the motor. Preventive techniques for early detection can find out the incipient faults and avoid outages. This dissertation developed various soft computing (SC) algorithms for detection including power-quality disturbances (PQD), turbine-generator fault diagnosis, and induction motor fault diagnosis. The proposed SC algorithms included support vector machine (SVM), grey clustering analysis (GCA), and probabilistic neural network (PNN). Integrating the proposed diagnostic procedure and existing monitoring instruments, a well-monitored power system will be constructed without extra devices. Finally, all the methods in the dissertation give reasonable and practical estimation method. Compared with conventional method, the test results showed a high accuracy, good robustness, and a faster processing performance.