Effect of neutralization and cross-linking on the thermal degradation of chitosan electrospun membranes

Thermal degradation of as electrospun chitosan membranes and samples subsequently treated with ethanol and cross-linked with glutaraldehyde (GA) have been studied by thermogravimetry (TG) coupled with an infrared spectrometer (FTIR). The influence of the electrospinning process and cross-linking in the electrospun chitosan thermal stability was evaluated. Up to three degradation steps were observed in the TG data, corresponding to water dehydration reaction at temperatures below 100 ºC, loss of side groups formed between the amine groups of chitosan and trifluoroacetic acid between 150 – 270 ºC and chitosan thermal degradation that starts around 250 ºC and goes up to 400 ºC. The Kissinger model was employed to evaluate the activation energies of the electrospun membranes during isothermal experiments and revealed that thermal degradation activation energy increases for the samples processed by electrospinning and subsequent neutralization and cross-linking treatments with respect to the neat chitosan powder.

Historical Heritage: A Study to Conservation

Considering ancient monuments and historical buildings, it seems that these mortars have proved to be durable and reliable materials. The restoration and maintenance of old renders is one of the key aspects of correct rehabilitation practice. The ideal course of action is to replace the damaged material by a material with compatible characteristics.The study in development presents the chemical, physical and morphologic analysis performed for ancient air lime mortars belonging to historical monuments: Santa Marta Fortress in the coast line Lisbon-Cascais dated from XVII century and Defense Wall of Lisbon dated from XI century, which layout could be associated to roman period. It is important to underline that the studied samples of ancient portuguese air lime mortars, have been submitted during centuries to very severe maritime environment that includes daily cycles of wet/dry, wind, friction and the constant presence of salts, generally aggressive. However, they show very good performance and conservation state, unlike most of the new air lime mortars, which are generally considered weak, not very durable, materials. This work is included in a study intending to determine key factors to the durability of these ancient materials in presence of water. Visible reaction rims around some aggregates suggests the occurrence of pozzolanic reactions between aggregates and the lime binder that creates neoformation products, such as calcium-silico-aluminates, which seems be, besides the pores filling, the responsible for the resistance and cohesion of these ancient mortars submitted to aggressive humid environments.

Autoxidação de ácidos gordos na presença de antioxidantes naturais e sintéticos

Nas últimas décadas, devido ao desenvolvimento económico, e a uma necessidade constante de gerir os recursos energéticos, existe uma necessidade de procurar novas fontes de energia, em particular fontes de energia renováveis. O biodiesel surge assim como uma energia alternativa ao combustível fóssil. Este biocombustível tem ganho uma importância significativa na sociedade moderna. Quimicamente o biodiesel é constituído por ésteres metílicos de ácidos gordos de cadeia longa, derivados de óleos vegetais ou gorduras animais. O principal problema que este enfrenta é a sua susceptibilidade à oxidação, devido ao seu conteúdo de ácidos gordos insaturados, logo existe uma procura constante de soluções que possam solucionar este problema. É necessária a identificação de técnicas e métodos para retardar a seu envelhecimento ao longo do tempo. O objectivo deste trabalho consiste no estudo da estabilidade do biodiesel ao longo do tempo, quando armazenado a diferentes condições de temperatura, superiores às normalmente suportadas pelo biodiesel durante o armazenamento, de modo a acelerar o processo de degradação. As amostras de biodiesel foram sujeitas a duas temperaturas. Uma amostra de biodiesel não estabilizado foi colocada a uma temperatura entre 40 e 50ºC ao longo de 203 dias, e uma outra amostra foi colocada a uma temperatura entre 95º e 105ºC ao longo de 146 dias. Realizaram-se ensaios semanais de modo registar a evolução do envelhecimento do biodiesel. As análises foram efectuadas por espectrofotometria de ultravioleta e visível (UV-VIS) e por espectroscopia de absorção na região do infravermelho (FTIR). No UV-VIS foi possível observar que o aumento de temperatura foi responsável pela aceleração da oxidação do biodiesel que resulta num aumento generalizado da absorvância do biodiesel. Através das análises efectuadas no FTIR verificou-se a formação e aumento da banda dos hidroperóxidos (grupo ROOH) localizada entre 3000 e 3600 cm-1 nos espectros, e igualmente um alargamento na banda dos carbonilos (grupo C=O) entre 1500 e 1900 cm-1. Numa fase posterior testaram-se antioxidantes para retardar o envelhecimento do biodiesel. Os ensaios foram efectuados a uma temperatura entre 95º e 105ºC. Os antioxidantes utilizados foram o galhato de propilo (PG), o galhato de etilo (EG) e o ácido gálhico (AG). Recorreu-se a técnicas como o UV-VIS e o FTIR para o registo dos espectros do biodiesel ao longo do tempo. Através destas técnicas foi possível verificar a influência de antioxidantes na estabilidade oxidativa do biodiesel. O PG foi o antioxidante que melhor desempenho mostrou no retardamento da oxidação do biodiesel e a técnica que melhor permitiu analisar a acção dos antioxidantes foi o UVVIS. Os resultados obtidos por FTIR não se mostraram tão conclusivos. Para caracterizar o envelhecimento do biodiesel não estabilizado e estabilizado utilizou-se também a cromatografia gasosa (CG) para quantificar a percentagem de ésteres metílicos presentes nas diferentes amostras no inicio e no fim do processo de oxidação. O biodiesel envelheceu mais rapidamente para temperaturas mais elevadas e comprovou-se que o antioxidante que melhor estabiliza o biodiesel é o PG.

Estudo da influência das condições de armazenamento nas propriedades e composição do biodiesel

O objectivo deste trabalho era a determinação da influência das condições de armazenamento do biodiesel nas suas propriedades e composição. Para isso foi produzido biodiesel a partir de óleo alimentar usado e armazenado em diferentes condições. O biodiesel foi colocado em frascos de vidro e dividido em três grupos diferentes de temperatura. O primeiro foi colocado a uma temperatura de 6ºC (frigorifico) com frascos fechados e expostos ao ar e água. O segundo grupo foi colocado a uma temperatura de 40ºC (banho termostático) com frascos fechados, abertos ao ar e abertos ao ar e água. O terceiro e ultimo grupo foi colocado à temperatura ambiente (18,6constantes ao longo do tempo. O índice de iodo não permitiu concluir claramente que houve uma diminuição nas ligações duplas como seria espectável. Ao analisar os cromatogramas obtidos na determinação dos ésteres das amostras armazenadas em contacto com ar e água, a 40ºC verifica-se a formação de ácidos gordos a partir dos 81 dias de armazenamento. Com os resultados obtidos verificou-se que para as amostras colocadas a 40ºC e em contacto com ar e água a taxa de oxidação é mais acelerada, fazendo com que o biodiesel perca as características e propriedades iniciais, já no caso das amostras armazenadas a 6ºC e em frascos fechados verifica-se que os parâmetros estudados praticamente não sofrem alterações, mantendo quase inalteradas as propriedades e composição do biodiesel ao fim das 16 semanas de estudo. Assim é possível concluir que para se conseguir manter as características e propriedades do biodiesel durante um armazenamento prolongado é necessário garantir um ambiente fresco de preferência inerte e depósitos completamentos secos, de forma a evitar as condições que provocam oxidação.

Transferência de calor em fluidos Não-Newtonianos

Foi realizado um estudo sobre o efeito do tipo de fluidos na transferência de calor. Pretende-se determinar a influência da concentração da solução de Goma de Xantano, do número de Reynolds, do número de Weissenberg, da temperatura e do tempo de escoamento no coeficiente de transferência de calor, jH. O estudo da transferência de calor foi feito num permutador de tubos duplos concêntricos. Já o estudo da reologia foi realizado num reómetro. Na caracterização reológica das soluções de XG, a viscosidade aumenta com a concentração das soluções, diminui para taxas de deformação crescentes e com o aumento da temperatura para ambas as soluções. Os dados mostram um aumento da intensidade da pseudoplasticidade com a concentração do polímero, sendo os valores representados pelo modelo de Sisco. A degradação da solução de 0,20% de goma de xantano a 25 ºC, com o escoamento, é muito acelerada. Os resultados dos ensaios apresentam uma diminuição da viscosidade de 9,4% a 22,9%, para tempos de escoamento de 12 a 47 horas, respectivamente. Num escoamento turbulento em conduta de secção circular constante os resultados mostram uma redução de arrasto total de 18 para 33%. Para a solução de 0,10 % de XG, verifica-se um aumento do calor transferido de 115% e de 130%, quando a temperatura aumenta de 25 ºC para 36 ºC, respectivamente. A água apresenta valores de calor transferido superiores, cerca de 170%, aos da solução de 0,1 %XG. O factor de correlação empírico de Colbourn (jH), utilizado neste trabalho apresenta valores de acordo com a relação de Cho and Hartnett (1985): jH<2/f. Quando o caudal do fluido quente aumenta verifica-se uma diminuição do factor jH. Em relação ao tempo de escoamento verifica-se uma diminuição de cerca de 70% do coeficiente de transferência de calor ao fim de 47 horas. Finalmente verificamos uma diminuição do factor de transferência de calor com o aumento da temperatura do fluido quente, para ambas as concentrações de goma de xantano. Para as soluções de 0,10 e 0,20% de XG essa diminuição variou entre 38 e 15% e entre 34 e 3%, respectivamente.

Radiatively induced Lorentz and CPT violation in Schwinger constant field approximation

The Schwinger proper-time method is an effective calculation method, explicitly gauge-invariant and nonperturbative. We make use of this method to investigate the radiatively induced Lorentz- and CPT-violating effects in quantum electrodynamics when an axial-vector interaction term is introduced in the fermionic sector. The induced Lorentz- and CPT-violating Chern-Simons term coincides with the one obtained using a covariant derivative expansion but differs from the result usually obtained in other regularization schemes. A possible ambiguity in the approach is also discussed. (C) 2001 Published by Elsevier Science B.V.

Estratégias de implementação de plataformas de e-maintenance na indústria: desenvolvimento de uma aplicação para um sistema logístico de viaturas

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

Influence of mixtures of acenaphthylene and benzo[a] anthracene on their degradation by Pleurotus ostreatus in sandy soil

Purpose Polycyclic aromatic hydrocarbons (PAHs) are a class of organic compounds commonly found as soil contaminants. Fungal degradation is considered as an environmentally friendly and cost-effective approach to remove PAHs from soil. Acenaphthylene (Ace) and Benzo[a]anthracene (BaA) are two PAHs that can coexist in soils; however, the influence of the presence of each other on their biodegradation has not been studied. The biodegradation of Ace and BaA, alone and in mixtures, by the white rot fungus Pleurotus ostreatus was studied in a sandy soil. Materials and methods Experimental microcosms containing soil spiked with different concentrations of Ace and BaAwere inoculated with P. ostreatus. Initial (t 0) and final (after 15 days of incubation) soil concentrations of Ace and BaA were determined after extraction of the PAHs. Results and discussion P. ostreatus was able to degrade 57.7% of the Ace in soil spiked at 30 mg kg−1 dry soil and 65.8% of Ace in soil spiked at 60 mg kg−1 dry soil. The degradation efficiency of BaA by P. ostreatus was 86.7 and 77.4% in soil spiked with Ace at 30 and 60 mg kg−1 dry soil, respectively. After 15 days of incubation, there were no significant differences in Ace concentration between soil spiked with Ace and soil spiked with Ace + BaA, irrespective of the initial soil concentration of both PAHs. There were also no differences in BaA concentration between soil spiked with BaA and soil spiked with BaA + Ace. Conclusions The results indicate that the fungal degradation of Ace and BaA was not influenced by the presence of each other’s PAH in sandy soil. Bioremediation of soils contaminated with Ace and BaA using P. ostreatus is a promising approach to eliminate these PAHs from the environment.

Determination of methiocarb and Its degradation products, methiocarb sulfoxide and methiocarb sulfone, in bananas using QuEChERS extraction

The present work describes the development of an analytical method for the determination of methiocarb and its degradation products (methiocarb sulfoxide and methiocarb sulfone) in banana samples, using the QuEChERS (quick, easy, cheap, effective, rugged, and safe) procedure followed by liquid chromatography coupled to photodiode array detector (LCPAD). Calibration curves were linear in the range of 0.5−10 mg L−1 for all compounds studied. The average recoveries, measured at 0.1 mg kg−1 wet weight, were 92.0 (RSD = 1.8%, n = 3), 84.0 (RSD = 3.9%, n = 3), and 95.2% (RSD = 1.9%, n = 3) for methiocarb sulfoxide, methiocarb sulfone, and methiocarb, respectively. Banana samples treated with methiocarb were collected from an experimental field. The developed method was applied to the analysis of 24 samples (peel and pulp) and to 5 banana pulp samples. Generally, the highest levels were found for methiocarb sulfoxide and methiocarb. Methiocarb sulfone levels were below the limit of quantification, except in one sample (not detected).

Modeling of the lung impedance using a fractional order ladder network with constant phase elements

The self similar branching arrangement of the airways makes the respiratory system an ideal candidate for the application of fractional calculus theory. The fractal geometry is typically characterized by a recurrent structure. This study investigates the identification of a model for the respiratory tree by means of its electrical equivalent based on intrinsic morphology. Measurements were obtained from seven volunteers, in terms of their respiratory impedance by means of its complex representation for frequencies below 5 Hz. A parametric modeling is then applied to the complex valued data points. Since at low-frequency range the inertance is negligible, each airway branch is modeled by using gamma cell resistance and capacitance, the latter having a fractional-order constant phase element (CPE), which is identified from measurements. In addition, the complex impedance is also approximated by means of a model consisting of a lumped series resistance and a lumped fractional-order capacitance. The results reveal that both models characterize the data well, whereas the averaged CPE values are supraunitary and subunitary for the ladder network and the lumped model, respectively.

Two distinct arabinofuranosidases contribute to arabino-oligosaccharide degradation in Bacillus subtilis.

Microbiology 154 (2008) 2719-2729

Characterization of the abn2(yxiA) encoding a Bacillus subtilis GH43 arabinanase, Abn2, and its role in arabino-polysaccharides degradation.

Journal of Bacteriology (Junho 2008) 4272-4280

trans-Acting factors and cis elements involved in glucose repression of arabinan degradation in Bacillus subtilis.

Journal of Bacteriology (Nov 2007) 8371-8376

Processos de avaliação dos pavimentos rodoviários: Caso de estudo: reforço do pavimento em dois trechos do sublanço Enxara/Torres Vedras Sul

Relatório de Estágio Curricular para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Vias de Comunicação e Transportes

Unmixing hyperspectral data: independent and dependent component analysis

The development of high spatial resolution airborne and spaceborne sensors has improved the capability of ground-based data collection in the fields of agriculture, geography, geology, mineral identification, detection [2, 3], and classification [4–8]. The signal read by the sensor from a given spatial element of resolution and at a given spectral band is a mixing of components originated by the constituent substances, termed endmembers, located at that element of resolution. This chapter addresses hyperspectral unmixing, which is the decomposition of the pixel spectra into a collection of constituent spectra, or spectral signatures, and their corresponding fractional abundances indicating the proportion of each endmember present in the pixel [9, 10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. The linear mixing model holds when the mixing scale is macroscopic [13]. The nonlinear model holds when the mixing scale is microscopic (i.e., intimate mixtures) [14, 15]. The linear model assumes negligible interaction among distinct endmembers [16, 17]. The nonlinear model assumes that incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [18]. Under the linear mixing model and assuming that the number of endmembers and their spectral signatures are known, hyperspectral unmixing is a linear problem, which can be addressed, for example, under the maximum likelihood setup [19], the constrained least-squares approach [20], the spectral signature matching [21], the spectral angle mapper [22], and the subspace projection methods [20, 23, 24]. Orthogonal subspace projection [23] reduces the data dimensionality, suppresses undesired spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel onto a subspace that is orthogonal to the undesired signatures. As shown in Settle [19], the orthogonal subspace projection technique is equivalent to the maximum likelihood estimator. This projection technique was extended by three unconstrained least-squares approaches [24] (signature space orthogonal projection, oblique subspace projection, target signature space orthogonal projection). Other works using maximum a posteriori probability (MAP) framework [25] and projection pursuit [26, 27] have also been applied to hyperspectral data. In most cases the number of endmembers and their signatures are not known. Independent component analysis (ICA) is an unsupervised source separation process that has been applied with success to blind source separation, to feature extraction, and to unsupervised recognition [28, 29]. ICA consists in finding a linear decomposition of observed data yielding statistically independent components. Given that hyperspectral data are, in given circumstances, linear mixtures, ICA comes to mind as a possible tool to unmix this class of data. In fact, the application of ICA to hyperspectral data has been proposed in reference 30, where endmember signatures are treated as sources and the mixing matrix is composed by the abundance fractions, and in references 9, 25, and 31–38, where sources are the abundance fractions of each endmember. In the first approach, we face two problems: (1) The number of samples are limited to the number of channels and (2) the process of pixel selection, playing the role of mixed sources, is not straightforward. In the second approach, ICA is based on the assumption of mutually independent sources, which is not the case of hyperspectral data, since the sum of the abundance fractions is constant, implying dependence among abundances. This dependence compromises ICA applicability to hyperspectral images. In addition, hyperspectral data are immersed in noise, which degrades the ICA performance. IFA [39] was introduced as a method for recovering independent hidden sources from their observed noisy mixtures. IFA implements two steps. First, source densities and noise covariance are estimated from the observed data by maximum likelihood. Second, sources are reconstructed by an optimal nonlinear estimator. Although IFA is a well-suited technique to unmix independent sources under noisy observations, the dependence among abundance fractions in hyperspectral imagery compromises, as in the ICA case, the IFA performance. Considering the linear mixing model, hyperspectral observations are in a simplex whose vertices correspond to the endmembers. Several approaches [40–43] have exploited this geometric feature of hyperspectral mixtures [42]. Minimum volume transform (MVT) algorithm [43] determines the simplex of minimum volume containing the data. The MVT-type approaches are complex from the computational point of view. Usually, these algorithms first find the convex hull defined by the observed data and then fit a minimum volume simplex to it. Aiming at a lower computational complexity, some algorithms such as the vertex component analysis (VCA) [44], the pixel purity index (PPI) [42], and the N-FINDR [45] still find the minimum volume simplex containing the data cloud, but they assume the presence in the data of at least one pure pixel of each endmember. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. Hyperspectral sensors collects spatial images over many narrow contiguous bands, yielding large amounts of data. For this reason, very often, the processing of hyperspectral data, included unmixing, is preceded by a dimensionality reduction step to reduce computational complexity and to improve the signal-to-noise ratio (SNR). Principal component analysis (PCA) [46], maximum noise fraction (MNF) [47], and singular value decomposition (SVD) [48] are three well-known projection techniques widely used in remote sensing in general and in unmixing in particular. The newly introduced method [49] exploits the structure of hyperspectral mixtures, namely the fact that spectral vectors are nonnegative. The computational complexity associated with these techniques is an obstacle to real-time implementations. To overcome this problem, band selection [50] and non-statistical [51] algorithms have been introduced. This chapter addresses hyperspectral data source dependence and its impact on ICA and IFA performances. The study consider simulated and real data and is based on mutual information minimization. Hyperspectral observations are described by a generative model. This model takes into account the degradation mechanisms normally found in hyperspectral applications—namely, signature variability [52–54], abundance constraints, topography modulation, and system noise. The computation of mutual information is based on fitting mixtures of Gaussians (MOG) to data. The MOG parameters (number of components, means, covariances, and weights) are inferred using the minimum description length (MDL) based algorithm [55]. We study the behavior of the mutual information as a function of the unmixing matrix. The conclusion is that the unmixing matrix minimizing the mutual information might be very far from the true one. Nevertheless, some abundance fractions might be well separated, mainly in the presence of strong signature variability, a large number of endmembers, and high SNR. We end this chapter by sketching a new methodology to blindly unmix hyperspectral data, where abundance fractions are modeled as a mixture of Dirichlet sources. This model enforces positivity and constant sum sources (full additivity) constraints. The mixing matrix is inferred by an expectation-maximization (EM)-type algorithm. This approach is in the vein of references 39 and 56, replacing independent sources represented by MOG with mixture of Dirichlet sources. Compared with the geometric-based approaches, the advantage of this model is that there is no need to have pure pixels in the observations. The chapter is organized as follows. Section 6.2 presents a spectral radiance model and formulates the spectral unmixing as a linear problem accounting for abundance constraints, signature variability, topography modulation, and system noise. Section 6.3 presents a brief resume of ICA and IFA algorithms. Section 6.4 illustrates the performance of IFA and of some well-known ICA algorithms with experimental data. Section 6.5 studies the ICA and IFA limitations in unmixing hyperspectral data. Section 6.6 presents results of ICA based on real data. Section 6.7 describes the new blind unmixing scheme and some illustrative examples. Section 6.8 concludes with some remarks.