981 resultados para Micro-Raman mapping


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This paper attempts to estimate the impact of population ageing on house prices. There is considerable debate about whether population ageing puts downwards or upwards pressure on house prices. The empirical approach differs from earlier studies of this relationship, which are mainly regression analyses of macro time-series data. A micro-simulation methodology is adopted that combines a macro-level house price model with a micro-level household formation model. The case study is Scotland, a country that is expected to age rapidly in the future. The parameters of the household formation model are estimated with panel data from the British Household Panel Survey covering the period 1999-2008. The estimates are then used to carry out a set of simulations. The simulations are based on a set of population projections that represent a considerable range in the rate of population ageing. The main finding from the simulations is that population ageing—or more generally changes in age structure—is not likely a main determinant of house prices, at least in Scotland.

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This study presents a first attempt to extend the “Multi-scale integrated analysis of societal and ecosystem metabolism (MuSIASEM)” approach to a spatial dimension using GIS techniques in the Metropolitan area of Barcelona. We use a combination of census and commercial databases along with a detailed land cover map to create a layer of Common Geographic Units that we populate with the local values of human time spent in different activities according to MuSIASEM hierarchical typology. In this way, we mapped the hours of available human time, in regards to the working hours spent in different locations, putting in evidence the gradients in spatial density between the residential location of workers (generating the work supply) and the places where the working hours are actually taking place. We found a strong three-modal pattern of clumps of areas with different combinations of values of time spent on household activities and on paid work. We also measured and mapped spatial segregation between these two activities and put forward the conjecture that this segregation increases with higher energy throughput, as the size of the functional units must be able to cope with the flow of exosomatic energy. Finally, we discuss the effectiveness of the approach by comparing our geographic representation of exosomatic throughput to the one issued from conventional methods.

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The molecular karyotypes for 20 reference strais of species complexes of Leishmania were determined by contour-clamped homogeneous eletric field (CHEF) electrosphoresis. Determination of number/position of chromosome-sized bands and chromosomal DNA locations of house-keeping genes were the two criteria used for differentiating and classifying the Leishmania species. We have established two gel running conditions of optimal separation of chromosomes, wich resolved DNA molecules as large as 2,500 kilobase pairs (kb). Chromosomes were polymorphic in number (22-30) and size (200-2,500 kb) of bands among members of five complexes of Leishmania. Although each stock had a distinct karyotype, in general the differences found between strains and/or species within each complex were not clear enough for parasite identification. However, each group showed a specific number of size-concordant DNA molecules, wich allowed distinction among the Leishmania complex parasites. Clear differences between the Old and New world groups of parasites or among some New World Leishmania species were also apparent in relation to the chromosome locations of beta-tubulin genes. Based on these results as well as data from other published studies the potencial of using DNA karyotype for identifying and classifying leishmanial field isolates is discussed.

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The aim of this work is to evaluate the capabilities and limitations of chemometric methods and other mathematical treatments applied on spectroscopic data and more specifically on paint samples. The uniqueness of the spectroscopic data comes from the fact that they are multivariate - a few thousands variables - and highly correlated. Statistical methods are used to study and discriminate samples. A collection of 34 red paint samples was measured by Infrared and Raman spectroscopy. Data pretreatment and variable selection demonstrated that the use of Standard Normal Variate (SNV), together with removal of the noisy variables by a selection of the wavelengths from 650 to 1830 cm−1 and 2730-3600 cm−1, provided the optimal results for infrared analysis. Principal component analysis (PCA) and hierarchical clusters analysis (HCA) were then used as exploratory techniques to provide evidence of structure in the data, cluster, or detect outliers. With the FTIR spectra, the Principal Components (PCs) correspond to binder types and the presence/absence of calcium carbonate. 83% of the total variance is explained by the four first PCs. As for the Raman spectra, we observe six different clusters corresponding to the different pigment compositions when plotting the first two PCs, which account for 37% and 20% respectively of the total variance. In conclusion, the use of chemometrics for the forensic analysis of paints provides a valuable tool for objective decision-making, a reduction of the possible classification errors, and a better efficiency, having robust results with time saving data treatments.

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Debris flow susceptibility mapping at a regional scale has been the subject of various studies. The complexity of the phenomenon and the variability of local controlling factors limit the use of process-based models for a first assessment. GISbased approaches associating an automatic detection of the source areas and a simple assessment of the debris flow spreading may provide a substantial basis for a preliminary susceptibility assessment at the regional scale. The use of a digital elevation model, with a 10 m resolution, for the Canton de Vaud territory (Switzerland), a lithological map and a land use map, has allowed automatic identification of the potential source areas. The spreading estimates are based on basic probabilistic and energy calculations that allow to define the maximal runout distance of a debris flow.

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The aim of this study is to perform a thorough comparison of quantitative susceptibility mapping (QSM) techniques and their dependence on the assumptions made. The compared methodologies were: two iterative single orientation methodologies minimizing the l2, l1TV norm of the prior knowledge of the edges of the object, one over-determined multiple orientation method (COSMOS) and anewly proposed modulated closed-form solution (MCF). The performance of these methods was compared using a numerical phantom and in-vivo high resolution (0.65mm isotropic) brain data acquired at 7T using a new coil combination method. For all QSM methods, the relevant regularization and prior-knowledge parameters were systematically changed in order to evaluate the optimal reconstruction in the presence and absence of a ground truth. Additionally, the QSM contrast was compared to conventional gradient recalled echo (GRE) magnitude and R2* maps obtained from the same dataset. The QSM reconstruction results of the single orientation methods show comparable performance. The MCF method has the highest correlation (corrMCF=0.95, r(2)MCF =0.97) with the state of the art method (COSMOS) with additional advantage of extreme fast computation time. The l-curve method gave the visually most satisfactory balance between reduction of streaking artifacts and over-regularization with the latter being overemphasized when the using the COSMOS susceptibility maps as ground-truth. R2* and susceptibility maps, when calculated from the same datasets, although based on distinct features of the data, have a comparable ability to distinguish deep gray matter structures.

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L'exposition aux microorganismes en environnement intérieur a été associée à la survenue de troubles respiratoires et symptômes allergiques chez les personnes exposées (1). Investiguer la relation dose-réponse entre exposition et effets sur la santé est essentiel dans la prévention de l'apparition de ces symptômes. Cependant, la mesure de l'exposition par prélèvement actif des bioaérosols est coûteuse et contraignante à mettre en place sur un grand nombre de sites en parallèle. C'est pourquoi les méthodes de prélèvement passif de la poussière sédimentée sont de plus en plus souvent envisagées pour répondre à cette problématique. Pour valider l'efficacité d'évaluation de l'exposition par ces dernières méthodes, il est nécessaire de montrer que la poussière sédimentée est bien représentative de la poussière inhalable. Le premier article cité dans cette note se propose de répondre à ce point. De plus, il faut identifier les facteurs qui peuvent influencer les concentrations en micro-organismes dans ces poussières sédimentées. Le deuxième article choisi dans cette note répond à ce dernier aspect.

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A slide micro-immunoenzymatic assay (micro-SIA) to detectantibodies to non-particulate Toxoplasma gondii antigens is described. This assay allows the diagnosis of toxoplasmosis infection in about 1 hr. Twenty-four determinations can be performed per slide. Five hundred ng of antigen and 5 or 10 µl drop of each reactive are necessary per well. The clear contrast of colours obtained for negative and positive sera after the test is finished, allows direct discrimination of the results. However, it is possible to quantify the results of the reaction using a minireader. Sera dilution cutoff value, determined as themost frequent titre for the general population, is 1:100. The toxoplasma micro-SIA correlates well with indirect immunofluorescence (IIF), its sensitivity is atleast three times as much as IIF. The test has an intra and inter assay variation coefficient of 5.46 per cent and of 6.24 per cent respectively. Sera obtained at random from argentinian people were analyzed and a 56 per cent of infection was found. The main features of the Toxoplasma micro-SIA are its simplicity, sensitivity, reproducibility, and the virtual absence of background making it very suitable for screening tests.

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This book combines geostatistics and global mapping systems to present an up-to-the-minute study of environmental data. Featuring numerous case studies, the reference covers model dependent (geostatistics) and data driven (machine learning algorithms) analysis techniques such as risk mapping, conditional stochastic simulations, descriptions of spatial uncertainty and variability, artificial neural networks (ANN) for spatial data, Bayesian maximum entropy (BME), and more.

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Functional imaging with intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) is demonstrated. Images were acquired at 3 Tesla using a standard Stejskal-Tanner diffusion-weighted echo-planar imaging sequence with multiple b-values. Cerebro-spinal fluid signal, which is highly incoherent, was suppressed with an inversion recovery preparation pulse. IVIM microvascular perfusion parameters were calculated according to a two-compartment (vascular and non-vascular) diffusion model. The results obtained in 8 healthy human volunteers during visual stimulation are presented. The IVIM blood flow related parameter fD* increased 170% during stimulation in the visual cortex, and 70% in the underlying white matter.

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L’èxit del Projecte Genoma Humà (PGH) l’any 2000 va fer de la “medicina personalitzada” una realitat més propera. Els descobriments del PGH han simplificat les tècniques de seqüenciació de tal manera que actualment qualsevol persona pot aconseguir la seva seqüència d’ADN complerta. La tecnologia de Read Mapping destaca en aquest tipus de tècniques i es caracteritza per manegar una gran quantitat de dades. Hadoop, el framework d’Apache per aplicacions intensives de dades sota el paradigma Map Reduce, resulta un aliat perfecte per aquest tipus de tecnologia i ha sigut l’opció escollida per a realitzar aquest projecte. Durant tot el treball es realitza l’estudi, l’anàlisi i les experimentacions necessàries per aconseguir un Algorisme Genètic innovador que utilitzi tot el potencial de Hadoop.

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The aim of this study was to develop a polymerase chain reaction (PCR) for the detection of respiratory syncytial virus (RSV) genomes. The primers were designed from published sequences and selected from conserved regions of the genome encoding for the N protein of subgroups A and B of RSV. PCR was applied to 20 specimens from children admitted to the respiratory ward of "William Soler" Pediatric Hospital in Havana City with a clinical diagnosis of bronchiolitis. The PCR was compared with viral isolation and with an indirect immunofluorescence technique that employs monoclonal antibodies of subgroups A and B. Of 20 nasopharyngeal exudates, 10 were found positive by the three assayed methods. In only two cases, samples that yielded positive RNA-PCR were found negative by indirect immunofluorescence and cell culture. Considering viral isolation as the "gold standard" technique, RNA-PCR had 100% sensitivity and 80% specificity. RNA-PCR is a specific and sensitive technique for the detection of the RSV genome. Technical advantages are discussed