1,253 research outputs found
Oxidative stress responses and cellular energy allocation changes in microalgae following exposure to widely used human antibiotics
The individual effect of four human antibiotics on the microalgae Raphidocelis subcapitata was investigated following a 120-h exposure. The effects were assessed by analyzing growth, and biochemical parameters related with: 1) antioxidant capacity and oxidative damage by measuring superoxide dismutase (SOD) activity and lipid peroxidation (LPO) levels; and 2) cellular energy allocation (CEA) by quantifying the content in energy reserves, which represents the energy available (Ea), and the electron transport system activity that represents a measure of oxygen and cellular energy consumption (Ec). Growth yield inhibitory concentrations of sulfamethoxazole (18-30%), clarithromycin (28.7%), ciprofloxacin (28%) and erythromycin (17-39%) were found to elicit a considerable increase in Ec, thereby causing a significant decrease in the CEA. The elevated Ec can be a result of the need to respond to oxidative stress occurring under those conditions given the significant increase in SOD activity at these levels. For sulfamethoxazole, erythromycin and ciprofloxacin, the antioxidant responses do not seem to be enough to cope with the reactive oxygen species and prevent oxidative damage, given the elevated LPO levels observed. A stimulatory effect on growth yield was observed (up to 16%) at ciprofloxacin lowest concentration, which highly correlated with the increase in CEA. Based on the no observed effect concentration (NOECs) and/or effective concentration (EC10) results, Ec, SOD and CEA were more sensitive than the classical endpoint of growth rate for all the tested antibiotics. By revealing the antibiotic stress effects in R. subcapitata at the cellular level, this study suggests CEA as a more reliable indicator of the organisms' physiological status.info:eu-repo/semantics/publishedVersio
Comparison of low and high pressure infiltration regimes on the density and highly porous microstructure of ceria ecoceramics made from sustainable cork templates
Cork templates were used to produce lightweight bulk biomimetic ecoceramic (environmentally conscious ceramic) monoliths. Bulk/monolithic ceramics are vital for many applications, i.e. energy materials and fuel cells. Using simple and flexible, aqueous green-chemistry procedures, for the first time the influence of infiltration regime, number of infiltration cycles and sintering temperature on ecoceramic density and microstructure was studied. This lightweight three-dimensionally ordered macroporous (3DOM) CeO2 preserved the hexagonal cellular structure of cork, but unlike the wood, the rear cell walls were open, greatly increasing open porosity. Higher sintering temperatures (1600 instead of 1000 °C) were required to produce cm size monolithic ecoceramics mechanically strong enough to be handled. The infiltration regime and number of infiltration cycles affected density and porosity. Lower infiltration pressure led to higher porosity ecoceramics (3.3–5.7%), which may favour catalytic performance, showing the possibility of tailoring porosity and specific surface area by modifying the number of infiltration cycles
Natural variability of lotic Mediterranean ecosystems or wildfire perturbations: who will win?
This study evaluates the impacts of wildfires in lotic Mediterranean ecosystems. It was carried out at Monchique ridge after big wildfires occurred during 2002 and 2003. Deferential impacts were evaluated comparing historical results obtained before the wildfires (1999 and 2001), with the post fire ones (2006 and 2007). Physical and chemical parameters of the water, habitat morphology, diatoms, macrophytes, macroinvertebrates and fishes were evaluated at 10 collecting places, before and after wildfires. High recovering rates were observed to the vegetation, but it is still possible to found fire impacts over macrophytes and river morphology. Wildfires, contributed to canopy decrease and, consequently to the growth of plants that usually are controlled by shadow. As a result, vegetation biodiversity tend to increase. River banks tend also to be invaded by terrestrial plants. Higher post fires recover rates were observed to the more aquatic communities (diatoms, macroinvertebrates and fishes). For those communities, comparing spring situations before and after the fires no substantial differences were observed. Sometimes differences between consecutive years are even higher. So it can be concluded that magnitude of wildfire impacts is less than the natural inter-annual variability of Mediterranean rivers. Long-term effects of forest fires, resulting from large woody debries, were also detected by morphological alterations, like debries dams. Habitat diversity increase and impacts on aquatic communities are expected
Reduction of crosstalk in blended-shot migration
CNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOCAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIORWhen migrating more than one shot at the same time, the nonlinearity of the imaging condition causes the final image to contain so-called crosstalk, i.e., the results of the interference of wavefields associated with different sources. We studied various ideas of using weights in the imaging condition, called encoding, for the reduction of crosstalk. We combined the ideas of random phase and/or amplitude encoding and random alteration of the sign with additional multiplication with powers of the imaginary unit. This procedure moved part of the crosstalk to the imaginary part of the resulting image, leaving the desired crosscorrelation in the real part. In this way, the final image is less impaired. Our results indicated that with a combination of these weights, the crosstalk can be reduced by a factor of four as compared with unencoded shot blending. Moreover, we evaluated the selection procedure of sources contributing to each group of shots. We compared random choice with a deterministic procedure, in which the random numbers were exchanged for numbers similar to those of a Costas array. These numbers preserve certain properties of a random choice, but avoid the occurrence of patterns in the distribution. Our objective was to avoid nearby source being added to the same group of shots, which cannot be guaranteed with a random choice. Finally, we determined that the crosstalk noise can be reduced after migration by image processing.When migrating more than one shot at the same time, the nonlinearity of the imaging condition causes the final image to contain so-called crosstalk, i.e., the results of the interference of wavefields associated with different sources. We studied various ideas of using weights in the imaging condition, called encoding, for the reduction of crosstalk. We combined the ideas of random phase and/or amplitude encoding and random alteration of the sign with additional multiplication with powers of the imaginary unit. This procedure moved part of the crosstalk to the imaginary part of the resulting image, leaving the desired crosscorrelation in the real part. In this way, the final image is less impaired. Our results indicated that with a combination of these weights, the crosstalk can be reduced by a factor of four as compared with unencoded shot blending. Moreover, we evaluated the selection procedure of sources contributing to each group of shots. We compared random choice with a deterministic procedure, in which the random numbers were exchanged for numbers similar to those of a Costas array. These numbers preserve certain properties of a random choice, but avoid the occurrence of patterns in the distribution. Our objective was to avoid nearby source being added to the same group of shots, which cannot be guaranteed with a random choice. Finally, we determined that the crosstalk noise can be reduced after migration by image processing.801S31S41CNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOCAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIORCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOCAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIORsem informaçãosem informaçã
Easy resolution of severe obstructive kidney injury
Chronic constipation is a common diagnosis with a high prevalence in the elderly. Constipation affects the quality of life of sick individuals, bringing several clinical complications.info:eu-repo/semantics/publishedVersio
Dispersion of carbon nanotubes in poly(lactic acid)
Carbon nanotubes (CNT) present excellent mechanical, electrical and thermal properties, and are expected to impart these properties into their composites. However, the CNT are grown as entangled bundles that are difficult to disperse in polymer matrices, or even in solvents. Several approaches have been tried for the efficient dispersion of CNT in polymer matrices, ranging from the CNT chemical modification to the use of different mixing methods. Previous studies have shown that the resulting filler dispersion is strongly dependent on the characteristics of the melt mixing equipment [1]. It is also known that the dispersion level of nanofillers strongly affects the final nanocomposite properties [2].
The present work reports the optimization of the CNT dispersion in poly (lactic acid) (PLA) using a small-scale twin-screw extruder. The CNT were chemically modified for improved interaction with PLA. The effect of varying the mixing parameters on the dispersion level of the CNT and functionalized CNT was evaluated using optical and electron microscopy. The electrical resistivity and mechanical properties of the composites were measured. It was observed that the incorporation of 1% (weight) of CNT reduced the electrical resistivity of the composite to 400 Ohm.m, and that 3% CNT rendered the composite conductive, with an electrical resistivity of 0.6 Ohm.m.Fundação para a Ciência e a Tecnologia (FCT) - POCI/QUI/59835/2004, bolsa de doutoramento SFRH/BD/32189/2006
Hydrogen PEMFC stack performance analysis : a data-driven approach
For low power fuel cells, it is paramount that management of reactants, water and heat, be realized in a passive fashion in order to minimize parasitic losses. Effective fuel, oxygen supply and water management for reliable performance are also greatly affected by cell geometry and materials. Fuel cells are complex systems to optimize on a mere experimental basis. As an aid to this goal, data-driven analysis techniques, requiring no mathematical model to be fixed a priori, are gaining a reputation in other fields of work, where a phenomenological modeling approach might be intractable. This work presents a characterization study of a 12W PEMFC series stack by means of a new data-driven technique, M-NMF. The stack was developed for low temperature operation, uses own designed flow field plates, integrated in a series configuration, and is operated for 12 combinations of hydrogen/air flowrate ratios, generating as many polarization curves. M-NMF is applied, in combination with an alternating least squares algorithm, to the analysis of the overvoltage data matrix derived from the original experimental polarization data. From this analysis, it is possible to group and differentiate data according to similar overvoltage patterns and gain insight into their relative contribution to fuel cell performance immunization
A comparative study of the dispersion of carbon nanofibres in polymer melts
The dispersion of carbon nanofibres (CNF) in a polymer matrix using two melt mixing methods is studied. Distributive and dispersive mixing were evaluated by optical and electron microscopy. The CNF were chemically modified to improve the interface with the matrix. The results showed that the two methods produced good distribution of the filler, but extensional stresses induced higher dispersion. The latter correlated well with a decrease in electrical resistivity. Also, the chemical modification largely improved the CNF/polymer interfaceFundação para a Ciência e a Tecnologia (FCT
Novel data-driven methodologies for parameter estimation and interpretation of fuel cells performance
Fuel cell based power generation systems are expected to become more widespread in the near future. Stationary fuel cells may be used as an uninterruptible or back-up power supply, or to supply micro-grids. In particular, proton exchange membrane fuel cells (PEMFC) are an attractive technology due to its high energy density, rigid and simple structure, low operating temperature and fast start-up characteristics. The power quality assessment of fuel cells as a viable power sources requires a good understanding of the fuel cell performance characteristics. This paper presents two novel data-driven methodologies for the identification of the main steady state (polarization curve) and the dynamic (impedance response) characteristics for fuel-cells allowing the development of rapid, accurate and empirical models based on the experimental data. M-NMF is a modified non-negative matrix factorization technique developed for the analysis of polarization curve data that allows to identify the three main contributions for the fuel-cell power degradation, while for impedance spectroscopy data, this paper proposes the use of fractional order transfer functions (FC-FOTC) to describe the main dynamic modes present in the fuel-cell. A brief description of these two approaches is presented, together with the analysis of a real experimental dataset obtained from a 12W open cathode PEMFC stack to illustrate their potential and scope. While the former is instrumental for the deconvolution of the fuel cell polarization curves into its major components, the latter enables the estimation of the parameters related to the inherent transport and kinetic phenomena, thus opening the way, in both cases, for the interpretation of the effect of the operating conditions on the relative dominance and magnitude of these components and phenomena
Electrochemical impedance spectroscopy modeling using the dis-tribution of relaxation times and error analysis for fuel cells
This paper proposes a new approach to determine the distribution of relaxation times (DRT) directly from the electro-chemical impedance spectroscopy (EIS) data, i.e. without the use of an equivalent electrical circuit model. The method uses a generalized fractional-order Laguerre basis to represent EIS where both the parameters of the basis and their co-efficients are estimated by solving a nonconvex minimization problem. Furthermore, the DRT confidence region is de-termined to assess the accuracy and precision of the DRT estimate. The approach is applied to analyze the dominant dynamic properties of an open-cathode hydrogen fuel-cell under different current and air-flow conditions. Results showed that the estimated DRT closely reconstructs EIS data even when there is a higher variance at smaller relaxation times
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