Study of some volatile compounds evolved from the thermal decomposition of atenolol

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Thermal study in solid state of Zn(II)-diclofenac complex: Behavior kinetic of dehydration, transition phase and thermal decomposition

The dehydration, thermal decomposition and transition phase stage of Zn(II)-diclofenac compoundwere studied by simultaneous TG-DTA and DSC techniques. The TG and DSC curves of this compoundwere obtained with the mass of sample of 2 and 5 mg. Additionally, DSC curves were carried out inopened and closed a-alumina pans under static and nitrogen atmosphere. The DTA and DSC curves showthat this compound possesses exothermic transition phase between 170-180 ºC, which it is irreversible(monotropic reaction). The kinetics study of this transition phase stage was evaluated by DSC undernon-isothermal conditions. The obtained data were evaluated with the isoconversional method, where thevalues of activation energy (Ea/kJmol-1) was plotted in function of the conversion degree (a). The resultsshow that due to mass sample, different activation energies were obtained. From these curves a tendencycan be seen where the plots maintain the same profile for closed lids and almost run parallel to each other.

Thermal stability and thermal decomposition of the antihypertensive drug amlodipine besylate

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Organic material decomposition and nutrient dynamics in a mulch system enriched with leguminous trees in the Amazon

As novas técnicas propostas para a agricultura na Amazônia incluem sistema de rotação de capoeira enriquecido com árvores leguminosas e transformando a queima da biomassa em cobertura morta sobre o solo. A decomposição e a liberação de nutrientes da cobertura morta foram estudadas usando sacos de liteira com malha fina que continham cinco tratamentos com diferentes espécies de leguminosas em comparação a um tratamento-controle com vegetação natural. As amostras para cada tratamento foram analisadas para conteúdos de C total, N, P, K, Ca, Mg, lignina, celulose e polifenóis solúveis em diferentes tempos de amostragem durante um ano. A razão constante de decomposição variou com a espécie e com o tempo. A perda de massa nos sacos de decomposição foi de 30,1 % para Acacia angustissima, de 32,7 % para Sclerolobium paniculatum, de 33,9 % para Inga edulis e para a vegetação secundária, de 45,2 % para Acacia mangium e de 63,6 % para Clitoria racemosa. Foi observada imobilização de N e P em todos os tratamentos, sendo a mineralização do N negativamente correlacionada com o fenol, razão C/N, razão (lignina + fenol)/N, razão fenol/P e o conteúdo de N nos sacos de liteira. Depois de 362 dias de incubação no campo, 3,3 % de K, 32,2 % de Ca e 22,4 % de Mg permaneceram no material em decomposição. Os resultados evidenciaram que a baixa qualidade mineral e a alta quantidade de carbono orgânico e aplicado como cobertura morta podem limitar a quantidade de energia disponível para os microrganismos resultando em uma competição por nutrientes com as plantas agrícolas.

Decomposition and reformulation of integer linear programming problems

This thesis deals with an investigation of Decomposition and Reformulation to solve Integer Linear Programming Problems. This method is often a very successful approach computationally, producing high-quality solutions for well-structured combinatorial optimization problems like vehicle routing, cutting stock, p-median and generalized assignment . However, until now the method has always been tailored to the specific problem under investigation. The principal innovation of this thesis is to develop a new framework able to apply this concept to a generic MIP problem. The new approach is thus capable of auto-decomposition and autoreformulation of the input problem applicable as a resolving black box algorithm and works as a complement and alternative to the normal resolving techniques. The idea of Decomposing and Reformulating (usually called in literature Dantzig and Wolfe Decomposition DWD) is, given a MIP, to convexify one (or more) subset(s) of constraints (slaves) and working on the partially convexified polyhedron(s) obtained. For a given MIP several decompositions can be defined depending from what sets of constraints we want to convexify. In this thesis we mainly reformulate MIPs using two sets of variables: the original variables and the extended variables (representing the exponential extreme points). The master constraints consist of the original constraints not included in any slaves plus the convexity constraint(s) and the linking constraints(ensuring that each original variable can be viewed as linear combination of extreme points of the slaves). The solution procedure consists of iteratively solving the reformulated MIP (master) and checking (pricing) if a variable of reduced costs exists, and in which case adding it to the master and solving it again (columns generation), or otherwise stopping the procedure. The advantage of using DWD is that the reformulated relaxation gives bounds stronger than the original LP relaxation, in addition it can be incorporated in a Branch and bound scheme (Branch and Price) in order to solve the problem to optimality. If the computational time for the pricing problem is reasonable this leads in practice to a stronger speed up in the solution time, specially when the convex hull of the slaves is easy to compute, usually because of its special structure.

Diagnosis and Fault detection in Electrical Machines and Drives based on Advanced Signal Processing Techniques

In the present thesis, a new methodology of diagnosis based on advanced use of time-frequency technique analysis is presented. More precisely, a new fault index that allows tracking individual fault components in a single frequency band is defined. More in detail, a frequency sliding is applied to the signals being analyzed (currents, voltages, vibration signals), so that each single fault frequency component is shifted into a prefixed single frequency band. Then, the discrete Wavelet Transform is applied to the resulting signal to extract the fault signature in the frequency band that has been chosen. Once the state of the machine has been qualitatively diagnosed, a quantitative evaluation of the fault degree is necessary. For this purpose, a fault index based on the energy calculation of approximation and/or detail signals resulting from wavelet decomposition has been introduced to quantify the fault extend. The main advantages of the developed new method over existing Diagnosis techniques are the following: - Capability of monitoring the fault evolution continuously over time under any transient operating condition; - Speed/slip measurement or estimation is not required; - Higher accuracy in filtering frequency components around the fundamental in case of rotor faults; - Reduction in the likelihood of false indications by avoiding confusion with other fault harmonics (the contribution of the most relevant fault frequency components under speed-varying conditions are clamped in a single frequency band); - Low memory requirement due to low sampling frequency; - Reduction in the latency of time processing (no requirement of repeated sampling operation).

Techniques and Methods for a multi-scale analysis of neuromuscular fatigue

This thesis proposes an integrated holistic approach to the study of neuromuscular fatigue in order to encompass all the causes and all the consequences underlying the phenomenon. Starting from the metabolic processes occurring at the cellular level, the reader is guided toward the physiological changes at the motorneuron and motor unit level and from this to the more general biomechanical alterations. In Chapter 1 a list of the various definitions for fatigue spanning several contexts has been reported. In Chapter 2, the electrophysiological changes in terms of motor unit behavior and descending neural drive to the muscle have been studied extensively as well as the biomechanical adaptations induced. In Chapter 3 a study based on the observation of temporal features extracted from sEMG signals has been reported leading to the need of a more robust and reliable indicator during fatiguing tasks. Therefore, in Chapter 4, a novel bi-dimensional parameter is proposed. The study on sEMG-based indicators opened a scenario also on neurophysiological mechanisms underlying fatigue. For this purpose, in Chapter 5, a protocol designed for the analysis of motor unit-related parameters during prolonged fatiguing contractions is presented. In particular, two methodologies have been applied to multichannel sEMG recordings of isometric contractions of the Tibialis Anterior muscle: the state-of-the-art technique for sEMG decomposition and a coherence analysis on MU spike trains. The importance of a multi-scale approach has been finally highlighted in the context of the evaluation of cycling performance, where fatigue is one of the limiting factors. In particular, the last chapter of this thesis can be considered as a paradigm: physiological, metabolic, environmental, psychological and biomechanical factors influence the performance of a cyclist and only when all of these are kept together in a novel integrative way it is possible to derive a clear model and make correct assessments.

Topographic time-frequency decomposition of the EEG

Frequency-transformed EEG resting data has been widely used to describe normal and abnormal brain functional states as function of the spectral power in different frequency bands. This has yielded a series of clinically relevant findings. However, by transforming the EEG into the frequency domain, the initially excellent time resolution of time-domain EEG is lost. The topographic time-frequency decomposition is a novel computerized EEG analysis method that combines previously available techniques from time-domain spatial EEG analysis and time-frequency decomposition of single-channel time series. It yields a new, physiologically and statistically plausible topographic time-frequency representation of human multichannel EEG. The original EEG is accounted by the coefficients of a large set of user defined EEG like time-series, which are optimized for maximal spatial smoothness and minimal norm. These coefficients are then reduced to a small number of model scalp field configurations, which vary in intensity as a function of time and frequency. The result is thus a small number of EEG field configurations, each with a corresponding time-frequency (Wigner) plot. The method has several advantages: It does not assume that the data is composed of orthogonal elements, it does not assume stationarity, it produces topographical maps and it allows to include user-defined, specific EEG elements, such as spike and wave patterns. After a formal introduction of the method, several examples are given, which include artificial data and multichannel EEG during different physiological and pathological conditions.

Decomposition studies of group 6 hexacarbonyl complexes. Part 1: Production and decomposition of Mo(CO)6 and W(CO)6

Chemical studies of superheavy elements require fast and efficient techniques, due to short half-lives and low production rates of the investigated nuclides. Here, we advocate for using a tubular flow reactor for assessing the thermal stability of the Sg carbonyl complex – Sg(CO)6. The experimental setup was tested with Mo and W carbonyl complexes, as their properties are established and supported by theoretical predictions. The suggested approach proved to be effective in discriminating between the thermal stabilities of Mo(CO)6 and W(CO)6. Therefore, an experimental verification of the predicted Sg–CO bond dissociation energy seems to be feasible by applying this technique. By investigating the effect of 104,105Mo beta-decay on the formation of 104,105Tc carbonyl complex, we estimated the lower reaction time limit for the metal carbonyl synthesis in the gas phase to be more than 100 ms. We examined further the influence of the wall material of the recoil chamber, the carrier gas composition, the gas flow rate, and the pressure on the production yield of 104Mo(CO)6, so that the future stability tests with Sg(CO)6 can be optimized accordingly.

Factor decomposition of income inequality change : Japan's regional income disparity from 1955 to 1998

We propose a method for the decomposition of inequality changes based on panel data regression. The method is an efficient way to quantify the contributions of variables to changes of the Theil T index while satisfying the property of uniform addition. We illustrate the method using prefectural data from Japan for the period 1955 to 1998. Japan experienced a diminishing of regional income disparity during the years of high economic growth from 1955 to 1973. After estimating production functions using panel data for prefectures in Japan, we apply the new decomposition approach to identify each production factor’s contributions to the changes of per capita income inequality among prefectures. The decomposition results show that total factor productivity (residual) growth, population change (migration), and public capital stock growth contributed to the diminishing of per capita income disparity.

3D Wavelet-based Fusion Techniques for Biomedical Imaging

Hoy en día las técnicas de adquisición de imágenes tridimensionales son comunes en diversas áreas, pero cabe destacar la relevancia que han adquirido en el ámbito de la imagen biomédica, dentro del cual encontramos una amplia gama de técnicas como la microscopía confocal, microscopía de dos fotones, microscopía de fluorescencia mediante lámina de luz, resonancia magnética nuclear, tomografía por emisión de positrones, tomografía de coherencia óptica, ecografía 3D y un largo etcétera. Un denominador común de todas esas aplicaciones es la constante necesidad por aumentar la resolución y la calidad de las imágenes adquiridas. En algunas de dichas técnicas de imagen tridimensional se da una interesante situación: aunque que cada volumen adquirido no contiene información suficiente para representar el objeto bajo estudio dentro de los parámetros de calidad requeridos por algunas aplicaciones finales, el esquema de adquisición permite la obtención de varios volúmenes que representan diferentes vistas de dicho objeto, de tal forma que cada una de las vistas proporciona información complementaria acerca del mismo. En este tipo de situación es posible, mediante la combinación de varias de esas vistas, obtener una mejor comprensión del objeto que a partir de cada una de ellas por separado. En el contexto de esta Tesis Doctoral se ha propuesto, desarrollado y validado una nueva metodología de proceso de imágenes basada en la transformada wavelet disc¬reta para la combinación, o fusión, de varias vistas con información complementaria de un mismo objeto. El método de fusión propuesto aprovecha la capacidad de descom¬posición en escalas y orientaciones de la transformada wavelet discreta para integrar en un solo volumen toda la información distribuida entre el conjunto de vistas adquiridas. El trabajo se centra en dos modalidades diferentes de imagen biomédica que per¬miten obtener tales adquisiciones multi-vista. La primera es una variante de la micro¬scopía de fluorescencia, la microscopía de fluorescencia mediante lámina de luz, que se utiliza para el estudio del desarrollo temprano de embriones vivos en diferentes modelos animales, como el pez cebra o el erizo de mar. La segunda modalidad es la resonancia magnética nuclear con realce tardío, que constituye una valiosa herramienta para evaluar la viabilidad del tejido miocárdico en pacientes con diversas miocardiopatías. Como parte de este trabajo, el método propuesto ha sido aplicado y validado en am¬bas modalidades de imagen. En el caso de la aplicación a microscopía de fluorescencia, los resultados de la fusión muestran un mejor contraste y nivel de detalle en comparación con cualquiera de las vistas individuales y el método no requiere de conocimiento previo acerca la función de dispersión puntual del sistema de imagen. Además, los resultados se han comparado con otros métodos existentes. Con respecto a la aplicación a imagen de resonancia magnética con realce tardío, los volúmenes fusionados resultantes pre-sentan una mejora cuantitativa en la nitidez de las estructuras relevantes y permiten una interpretación más sencilla y completa de la compleja estructura tridimensional del tejido miocárdico en pacientes con cardiopatía isquémica. Para ambas aplicaciones los resultados de esta tesis se encuentran actualmente en uso en los centros clínicos y de investigación con los que el autor ha colaborado durante este trabajo. Además se ha puesto a libre disposición de la comunidad científica la implementación del método de fusión propuesto. Por último, se ha tramitado también una solicitud de patente internacional que cubre el método de visualización desarrollado para la aplicación de Resonancia Magnética Nuclear. Abstract Nowadays three dimensional imaging techniques are common in several fields, but es-pecially in biomedical imaging, where we can find a wide range of techniques including: Laser Scanning Confocal Microscopy, Laser Scanning Two Photon Microscopy, Light Sheet Fluorescence Microscopy, Magnetic Resonance Imaging, Positron Emission To-mography, Optical Coherence Tomography, 3D Ultrasound Imaging, etc. A common denominator of all those applications being the constant need for further increasing resolution and quality of the acquired images. Interestingly, in some of the mentioned three-dimensional imaging techniques a remarkable situation arises: while a single volume does not contain enough information to represent the object being imaged within the quality parameters required by the final application, the acquisition scheme allows recording several volumes which represent different views of a given object, with each of the views providing complementary information. In this kind of situation one can get a better understanding of the object by combining several views instead of looking at each of them separately. Within such context, in this PhD Thesis we propose, develop and test new image processing methodologies based on the discrete wavelet transform for the combination, or fusion, of several views containing complementary information of a given object. The proposed fusion method exploits the scale and orientation decomposition capabil¬ities of the discrete wavelet transform to integrate in a single volume all the available information distributed among the set of acquired views. The work focuses in two different biomedical imaging modalities which provide such multi-view datasets. The first one is a particular fluorescence microscopy technique, Light-Sheet Fluorescence Microscopy, used for imaging and gaining understanding of the early development of live embryos from different animal models (like zebrafish or sea urchin). The second is Delayed Enhancement Magnetic Resonance Imaging, which is a valuable tool for assessing the viability of myocardial tissue on patients suffering from different cardiomyopathies. As part of this work, the proposed method was implemented and then validated on both imaging modalities. For the fluorescence microscopy application, the fusion results show improved contrast and detail discrimination when compared to any of the individual views and the method does not rely on prior knowledge of the system’s point spread function (PSF). Moreover, the results have shown improved performance with respect to previous PSF independent methods. With respect to its application to Delayed Enhancement Magnetic Resonance Imaging, the resulting fused volumes show a quantitative sharpness improvement and enable an easier and more complete interpretation of complex three-dimensional scar and heterogeneous tissue information in ischemic cardiomyopathy patients. In both applications, the results of this thesis are currently in use in the clinical and research centers with which the author collaborated during his work. An imple¬mentation of the fusion method has also been made freely available to the scientific community. Finally, an international patent application has been filed covering the visualization method developed for the Magnetic Resonance Imaging application.

Bacterial community structure associated with white band disease in the elkhorn coral Acropora palmata determined using culture-independent 16S rRNA techniques

Culture-independent molecular (16S ribosomal RNA) techniques showed distinct differences in bacterial communities associated with white band disease (WBD) Type I and healthy elkhorn coral Acropora palmata. Differences were apparent at all levels, with a greater diversity present in tissues of diseased colonies. The bacterial community associated with remote, non-diseased coral was distinct from the apparently healthy tissues of infected corals several cm from the disease lesion. This demonstrates a whole-organism effect from what appears to be a localised disease lesion, an effect that has also been recently demonstrated in white plague-like disease in star coral Montastraea annularis. The pattern of bacterial community structure changes was similar to that recently demonstrated for white plague-like disease and black band disease. Some of the changes are likely to be explained by the colonisation of dead and degrading tissues by a micro-heterotroph community adapted to the decomposition of coral tissues. However, specific ribosomal types that are absent from healthy tissues appear consistently in all samples of each of the diseases. These ribotypes are closely related members of a group of alpha-proteobacteria that cause disease, notably juvenile oyster disease, in other marine organisms. It is clearly important that members of this group are isolated for challenge experiments to determine their role in the diseases.

Machine Learning-based Techniques to Address Spectral Distortions in Photon Counting X-ray Computed Tomography

Spectral CT using a photon counting x-ray detector (PCXD) shows great potential for measuring material composition based on energy dependent x-ray attenuation. Spectral CT is especially suited for imaging with K-edge contrast agents to address the otherwise limited contrast in soft tissues. We have developed a micro-CT system based on a PCXD. This system enables full spectrum CT in which the energy thresholds of the PCXD are swept to sample the full energy spectrum for each detector element and projection angle. Measurements provided by the PCXD, however, are distorted due to undesirable physical eects in the detector and are very noisy due to photon starvation. In this work, we proposed two methods based on machine learning to address the spectral distortion issue and to improve the material decomposition. This rst approach is to model distortions using an articial neural network (ANN) and compensate for the distortion in a statistical reconstruction. The second approach is to directly correct for the distortion in the projections. Both technique can be done as a calibration process where the neural network can be trained using 3D printed phantoms data to learn the distortion model or the correction model of the spectral distortion. This replaces the need for synchrotron measurements required in conventional technique to derive the distortion model parametrically which could be costly and time consuming. The results demonstrate experimental feasibility and potential advantages of ANN-based distortion modeling and correction for more accurate K-edge imaging with a PCXD. Given the computational eciency with which the ANN can be applied to projection data, the proposed scheme can be readily integrated into existing CT reconstruction pipelines.

Study of Co-based hydrotalcite-derived mixed metal oxides partially modified with silver as potential catalysts for N2O decomposition

Co-Al-Ox mixed metal oxides partially modified with Cu or Mg, as well as Ag were successfully prepared, characterized and evaluated as potential catalysts for the N2O decomposition. The materials were characterized by the following techniques: X-Ray Diffraction, Thermogravimetric Analysis (TGA), N2 Physisorption, Hydrogen Temperature-Programmed Reduction (H2-TPR), and X-ray photoelectron spectroscopy (XPS). Ag-modified HT-derived mixed oxides showed enhanced activity compared to the undoped materials, the optimum composition was found for (1 wt.% Ag)CHT-Co3Al. The catalyst characterization studies suggested that the improved catalytic activity of Ag-promoted catalysts were mainly because of the altered redox properties of the materials.

Low cost 3D global instability analysis and flow sensitivity based on dynamic mode decomposition and high-order numerical tools

We explore the recently developed snapshot-based dynamic mode decomposition (DMD) technique, a matrix-free Arnoldi type method, to predict 3D linear global flow instabilities. We apply the DMD technique to flows confined in an L-shaped cavity and compare the resulting modes to their counterparts issued from classic, matrix forming, linear instability analysis (i.e. BiGlobal approach) and direct numerical simulations. Results show that the DMD technique, which uses snapshots generated by a 3D non-linear incompressible discontinuous Galerkin Navier?Stokes solver, provides very similar results to classical linear instability analysis techniques. In addition, we compare DMD results issued from non-linear and linearised Navier?Stokes solvers, showing that linearisation is not necessary (i.e. base flow not required) to obtain linear modes, as long as the analysis is restricted to the exponential growth regime, that is, flow regime governed by the linearised Navier?Stokes equations, and showing the potential of this type of analysis based on snapshots to general purpose CFD codes, without need of modifications. Finally, this work shows that the DMD technique can provide three-dimensional direct and adjoint modes through snapshots provided by the linearised and adjoint linearised Navier?Stokes equations advanced in time. Subsequently, these modes are used to provide structural sensitivity maps and sensitivity to base flow modification information for 3D flows and complex geometries, at an affordable computational cost. The information provided by the sensitivity study is used to modify the L-shaped geometry and control the most unstable 3D mode.