896 resultados para senior housing, relocation, later life, decision to move, push and pull factors


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The oxidative behaviour of fluoxetine was studied at a glassy carbon electrode in various buffer systems and at different pH using cyclic, differential pulse and square wave voltammetry. A new square wave voltammetric method suitable for the quality control of fluoxetine in commercial formulations has been developed using a borate pH 9 buffer solution as supporting electrolyte. Under optimized conditions, a linear response was obtained in the range 10 to 16 μM with a detection limit of 1.0 μM. Validation parameters such as sensitivity, precision and accuracy were evaluated. The proposed method was successfully applied to the determination of fluoxetine in pharmaceutical formulations. The results were statistically compared with those obtained by the reference high-performance liquid chromatographic method. No significant differences were found between the methods.

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MSC Dissertation in Computer Engineering

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No literature data above atmospheric pressure could be found for the viscosity of TOTIVI. As a consequence, the present viscosity results could only be compared upon extrapolation of the vibrating wire data to 0.1 MPa. Independent viscosity measurements were performed, at atmospheric pressure, using an Ubbelohde capillary in order to compare with the vibrating wire results, extrapolated by means of the above mentioned correlation. The two data sets agree within +/- 1%, which is commensurate with the mutual uncertainty of the experimental methods. Comparisons of the literature data obtained at atmospheric pressure with the present extrapolated vibrating-wire viscosity measurements have shown an agreement within +/- 2% for temperatures up to 339 K and within +/- 3.3% for temperatures up to 368 K. (C) 2014 Elsevier B.V. All rights reserved.

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In Part I of the present work we describe the viscosity measurements performed on tris(2-ethylhexyl) trimellitate or 1,2,4-benzenetricarboxylic acid, tris(2-ethylhexyl) ester (TOTM) up to 65 MPa and at six temperatures from (303 to 373)K, using a new vibrating-wire instrument. The main aim is to contribute to the proposal of that liquid as a potential reference fluid for high viscosity, high pressure and high temperature. The present Part II is dedicated to report the density measurements of TOTM necessary, not only to compute the viscosity data presented in Part I, but also as complementary data for the mentioned proposal. The present density measurements were obtained using a vibrating U-tube densimeter, model DMA HP, using model DMA5000 as a reading unit, both instruments from Anton Paar GmbH. The measurements were performed along five isotherms from (293 to 373)K and at eleven different pressures up to 68 MPa. As far as the authors are aware, the viscosity and density results are the first, above atmospheric pressure, to be published for TOTM. Due to TOTM's high viscosity, its density data were corrected for the viscosity effect on the U-tube density measurements. This effect was estimated using two Newtonian viscosity standard liquids, 20 AW and 200 GW. The density data were correlated with temperature and pressure using a modified Tait equation. The expanded uncertainty of the present density results is estimated as +/- 0.2% at a 95% confidence level. Those results were correlated with temperature and pressure by a modified Tait equation, with deviations within +/- 0.25%. Furthermore, the isothermal compressibility, K-T, and the isobaric thermal expansivity, alpha(p), were obtained by derivation of the modified Tait equation used for correlating the density data. The corresponding uncertainties, at a 95% confidence level, are estimated to be less than +/- 1.5% and +/- 1.2%, respectively. No isobaric thermal expansivity and isothermal compressibility for TOTM were found in the literature. (C) 2014 Elsevier B.V. All rights reserved.

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Many learning problems require handling high dimensional datasets with a relatively small number of instances. Learning algorithms are thus confronted with the curse of dimensionality, and need to address it in order to be effective. Examples of these types of data include the bag-of-words representation in text classification problems and gene expression data for tumor detection/classification. Usually, among the high number of features characterizing the instances, many may be irrelevant (or even detrimental) for the learning tasks. It is thus clear that there is a need for adequate techniques for feature representation, reduction, and selection, to improve both the classification accuracy and the memory requirements. In this paper, we propose combined unsupervised feature discretization and feature selection techniques, suitable for medium and high-dimensional datasets. The experimental results on several standard datasets, with both sparse and dense features, show the efficiency of the proposed techniques as well as improvements over previous related techniques.

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Animal Cognition, V.6, pp. 259–267

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Paracoccidioidomycosis (South American blastomycosis) is a systemic disease, strikingly more frequent in males, caused by the dimorphic fungus Paracoccidioides brasiliensis. A radiometric assay system has been applied to study the metabolic activity and the effect of drugs on this fungus "in vitro". The Y form of the yeast, grown in liquid Sabouraud medium was inoculated into sterile reaction vials containing the 6B aerobic medium along with 2.0 μCi of 14C-substrates. Control vials, prepared in the same way, contained autoclaved fungi. To study the effects of amphotericin B (AB) (0.1 and 10 μg/ml) and diethylstilbestrol (DSB) (1.0, 5.0 and 10 μg/ml) extra controls with live fungi and no drug were used. All vials were incubated at 35°C and metabolism measured daily with a Bactec instrument. 14CO2 production by P. brasiliensis was slow and could be followed for as long as 50 days. AB at 10mg/ml and DSB at 5 μg/ml inhibited the metabolism and had a cidal effect on this fungus. The results with DSB might explain the low incidence of the disease in females. This technique shows promise for studying metabolic pathways, investi gating more convenient 14C-substrates to expedite radiometric detection and for monitoring the effects of other drugs and factors on the metabolism of P. brasiliensis "in vitro".

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Paper presented at the 9th European Conference on Knowledge Management, Southampton Solent University, Southampton, UK, 4-5 Sep. 2008. URL: http://academic-conferences.org/eckm/eckm2008/eckm08-home.htm

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In search of an efficient but simple, low cost procedure for the serodiagnosis of Toxoplasmosis, especially suited for routine laboratories facing technical and budget limitations as in less developed countries, the diagnostic capability of Hematoxo® , an hemagglutination test for toxoplasmosis, was evaluated in relation to a battery of tests including IgG- and IgM-immunofluorescence tests, hemagglutination and an IgM-capture enzymatic assay. Detecting a little as 5 I.U. of IgG antitoxoplasma antibodies, Hematoxo® showed a straight agreement as to reactivity and non-reactivity for the 443 non-reactive and the 387 reactive serum samples, included in this study. In 23 cases presenting a serological pattern of acute toxoplasmosis and showing IgM antibodies, Hematoxo® could detect IgM antibodies in 18, indicated by negativation or a significant decrease in titers as a result of treating samples with 2-mercapto-ethanol. However, a neat increase in sensitivity for IgM specific antibodies could be achieved by previously removing IgG from the sample, as demonstrated in a series of acute toxoplasmosis sera. A simple procedure was developed for this purpose, by reconstituting a lyophilized suspension of Protein A - rich Staphylococcus with the lowest serum dilution to be tested. Of low cost and easy to perform, Hematoxo® affords not only a practical qualitative procedure for screening reactors and non-reactors, as in prenatal services, but also quantitative assays that permit to titrate antibodies as well as to identify IgM antibodies.

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The prediction of the time and the efficiency of the remediation of contaminated soils using soil vapor extraction remain a difficult challenge to the scientific community and consultants. This work reports the development of multiple linear regression and artificial neural network models to predict the remediation time and efficiency of soil vapor extractions performed in soils contaminated separately with benzene, toluene, ethylbenzene, xylene, trichloroethylene, and perchloroethylene. The results demonstrated that the artificial neural network approach presents better performances when compared with multiple linear regression models. The artificial neural network model allowed an accurate prediction of remediation time and efficiency based on only soil and pollutants characteristics, and consequently allowing a simple and quick previous evaluation of the process viability.

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Coal contains trace elements and naturally occurring radionuclides such as 40K, 232Th, 238U. When coal is burned, minerals, including most of the radionuclides, do not burn and concentrate in the ash several times in comparison with their content in coal. Usually, a small fraction of the fly ash produced (2-5%) is released into the atmosphere. The activities released depend on many factors (concentration in coal, ash content and inorganic matter of the coal, combustion temperature, ratio between bottom and fly ash, filtering system). Therefore, marked differences should be expected between the by-products produced and the amount of activity discharged (per unit of energy produced) from different coal-fired power plants. In fact, the effects of these releases on the environment due to ground deposition have been received some attention but the results from these studies are not unanimous and cannot be understood as a generic conclusion for all coal-fired power plants. In this study, the dispersion modelling of natural radionuclides was carried out to assess the impact of continuous atmospheric releases from a selected coal plant. The natural radioactivity of the coal and the fly ash were measured and the dispersion was modelled by a Gaussian plume estimating the activity concentration at different heights up to a distance of 20 km in several wind directions. External and internal doses (inhalation and ingestion) and the resulting risk were calculated for the population living within 20 km from the coal plant. In average, the effective dose is lower than the ICRP’s limit and the risk is lower than the U.S. EPA’s limit. Therefore, in this situation, the considered exposure does not pose any risk. However, when considering the dispersion in the prevailing wind direction, these values are significant due to an increase of 232Th and 226Ra concentrations in 75% and 44%, respectively.

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Phonological development was assessed in six alphabetic orthographies (English, French, Greek, Icelandic, Portuguese and Spanish) at the beginning and end of the first year of reading instruction. The aim was to explore contrasting theoretical views regarding: the question of the availability of phonology at the outset of learning to read (Study 1); the influence of orthographic depth on the pace of phonological development during the transition to literacy (Study 2); and the impact of literacy instruction (Study 3). Results from 242 children did not reveal a consistent sequence of development as performance varied according to task demands and language. Phonics instruction appeared more influential than orthographic depth in the emergence of an early meta-phonological capacity to manipulate phonemes, and preliminary indications were that cross-linguistic variation was associated with speech rhythm more than factors such as syllable complexity. The implications of the outcome for current models of phonological development are discussed.

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Isoniazid (INH) is still one of the two most effective antitubercular drugs and is included in all recommended multitherapeutic regimens. Because of the increasing resistance of Mycobacterium tuberculosis to INH, mainly associated with mutations in the katG gene, new INH-based compounds have been proposed to circumvent this problem. In this work, we present a detailed comparative study of the molecular determinants of the interactions between wt KatG or its S315T mutant form and either INH or INH-C10, a new acylated INH derivative. MD simulations were used to explore the conformational space of both proteins, and results indicate that the S315T mutation did not have a significant impact on the average size of the access tunnel in the vicinity of these residues. Our simulations also indicate that the steric hindrance role assigned to Asp137 is transient and that electrostatic changes can be important in understanding the enzyme activity data of mutations in KatG. Additionally, molecular docking studies were used to determine the preferred modes of binding of the two substrates. Upon mutation, the apparently less favored docking solution for reaction became the most abundant, suggesting that S315T mutation favors less optimal binding modes. Moreover, the aliphatic tail in INH-C10 seems to bring the hydrazine group closer to the heme, thus favoring the apparent most reactive binding mode, regardless of the enzyme form. The ITC data is in agreement with our interpretation of the C10 alkyl chain role and helped to rationalize the significantly lower experimental MIC value observed for INH-C10. This compound seems to be able to counterbalance most of the conformational restrictions introduced by the mutation, which are thought to be responsible for the decrease in INH activity in the mutated strain. Therefore, INH-C10 appears to be a very promising lead compound for drug development.

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Recent data suggest that the clinical course of reactional states in leprosy is closely related to the cytokine profile released locally or systemically by the patients. In the present study, patients with erythema nodosum leprosum (ENL) were grouped according to the intensity of their clinical symptoms. Clinical and immunological aspects of ENL and the impact of these parameters on bacterial load were assessed in conjunction with patients' in vitro immune response to mycobacterial antigens. In 10 out of the 17 patients tested, BI (bacterial index) was reduced by at least 1 log from leprosy diagnosis to the onset of their first reactional episode (ENL), as compared to an expected 0.3 log reduction in the unreactional group for the same MDT (multidrug therapy) period. However, no difference in the rate of BI reduction was noted at the end of MDT among ENL and unreactional lepromatous patients. Accordingly, although TNF-alpha (tumor necrosis factor) levels were enhanced in the sera of 70.6% of the ENL patients tested, no relationship was noted between circulating TNF-alpha levels and the decrease in BI detected at the onset of the reactional episode. Evaluation of bacterial viability of M. leprae isolated from the reactional lesions showed no growth in the mouse footpads. Only 20% of the patients demonstrated specific immune response to M. leprae during ENL. Moreover, high levels of soluble IL-2R (interleukin-2 receptor) were present in 78% of the patients. Circulating anti-neural (anti-ceramide and anti-galactocerebroside antibodies) and anti-mycobacterial antibodies were detected in ENL patients' sera as well, which were not related to the clinical course of disease. Our data suggest that bacterial killing is enhanced during reactions. Emergence of specific immune response to M. leprae and the effective role of TNF-alpha in mediating fragmentation of bacteria still need to be clarified.

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The smart grid concept is a key issue in the future power systems, namely at the distribution level, with deep concerns in the operation and planning of these systems. Several advantages and benefits for both technical and economic operation of the power system and of the electricity markets are recognized. The increasing integration of demand response and distributed generation resources, all of them mostly with small scale distributed characteristics, leads to the need of aggregating entities such as Virtual Power Players. The operation business models become more complex in the context of smart grid operation. Computational intelligence methods can be used to give a suitable solution for the resources scheduling problem considering the time constraints. This paper proposes a methodology for a joint dispatch of demand response and distributed generation to provide energy and reserve by a virtual power player that operates a distribution network. The optimal schedule minimizes the operation costs and it is obtained using a particle swarm optimization approach, which is compared with a deterministic approach used as reference methodology. The proposed method is applied to a 33-bus distribution network with 32 medium voltage consumers and 66 distributed generation units.