71 resultados para quantitative


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There is a substantial literature which suggests that appraisals are smoothed and lag the true level of prices. This study combines a qualitative interview survey of the leading fund manager/owners in the UK and their appraisers with a empirical study of the number of appraisals which change each month within the IPD Monthly Index. The paper concentrates on how the appraisal process operates for commercial property performance measurement purposes. The survey interviews suggest that periodic appraisal services are consolidating in fewer firms and, within these major firms, appraisers adopt different approaches to changing appraisals on a period by period basis, with some wanting hard transaction evidence while others act on "softer' signals. The survey also indicates a seasonal effect with greater effort and information being applied to annual and quarterly appraisals than monthly. The analysis of the appraisals within the Investment Property Databank Monthly Index confirms this effect with around 5% more appraisals being moved at each quarter day than the other months. January and August have significantly less appraisal changes than other months.

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Information on the genetic variation of plant response to elevated CO2 (e[CO2]) is needed to understand plant adaptation and to pinpoint likely evolutionary response to future high atmospheric CO2 concentrations.• Here, quantitative trait loci (QTL) for above- and below-ground tree growth were determined in a pedigree – an F2 hybrid of poplar (Populus trichocarpa and Populus deltoides), following season-long exposure to either current day ambient CO2 (a[CO2]) or e[CO2] at 600 µl l−1, and genotype by environment interactions investigated.• In the F2 generation, both above- and below-ground growth showed a significant increase in e[CO2]. Three areas of the genome on linkage groups I, IX and XII were identified as important in determining above-ground growth response to e[CO2], while an additional three areas of the genome on linkage groups IV, XVI and XIX appeared important in determining root growth response to e[CO2].• These results quantify and identify genetic variation in response to e[CO2] and provide an insight into genomic response to the changing environment

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Quantitation is an inherent requirement in comparative proteomics and there is no exception to this for plant proteomics. Quantitative proteomics has high demands on the experimental workflow, requiring a thorough design and often a complex multi-step structure. It has to include sufficient numbers of biological and technical replicates and methods that are able to facilitate a quantitative signal read-out. Quantitative plant proteomics in particular poses many additional challenges but because of the nature of plants it also offers some potential advantages. In general, analysis of plants has been less prominent in proteomics. Low protein concentration, difficulties in protein extraction, genome multiploidy, high Rubisco abundance in green tissue, and an absence of well-annotated and completed genome sequences are some of the main challenges in plant proteomics. However, the latter is now changing with several genomes emerging for model plants and crops such as potato, tomato, soybean, rice, maize and barley. This review discusses the current status in quantitative plant proteomics (MS-based and non-MS-based) and its challenges and potentials. Both relative and absolute quantitation methods in plant proteomics from DIGE to MS-based analysis after isotope labeling and label-free quantitation are described and illustrated by published studies. In particular, we describe plant-specific quantitative methods such as metabolic labeling methods that can take full advantage of plant metabolism and culture practices, and discuss other potential advantages and challenges that may arise from the unique properties of plants.

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There is a substantial literature which suggests that appraisals are smoothed and lag the true level of prices. This study combines a qualitative interview survey of the leading fund manager/owners in the UK and their appraisers with a empirical study of the number of appraisals which change each month within the IPD Monthly Index. The paper concentrates on how the appraisal process operates for commercial real estate performance measurement purposes. The survey interviews suggest that periodic appraisal services are consolidating in fewer firms and, within these major firms, appraisers adopt different approaches to changing appraisals on a period by period basis, with some wanting hard transaction evidence while others act on ‘softer’ signals. The survey also indicates a seasonal effect with greater effort and information being applied to annual and quarterly appraisals than monthly. The analysis of the appraisals within the IPD Monthly Index confirms this effect with around 5% more appraisals being moved at each quarter day than the other months. More November appraisals change than expected and this suggests that the increased information flows for the December end year appraisals are flowing through into earlier appraisals, especially as client/appraiser draft appraisal meetings for the December appraisals, a regular occurrence in the UK, can occur in November. January illustrates significantly less activity than other months, a seasonal effect after the exertions of the December appraisals.

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In the year 2007 a General Observation Period (GOP) has been performed within the German Priority Program on Quantitative Precipitation Forecasting (PQP). By optimizing the use of existing instrumentation a large data set of in-situ and remote sensing instruments with special focus on water cycle variables was gathered over the full year cycle. The area of interest covered central Europe with increasing focus towards the Black Forest where the Convective and Orographically-induced Precipitation Study (COPS) took place from June to August 2007. Thus the GOP includes a variety of precipitation systems in order to relate the COPS results to a larger spatial scale. For a timely use of the data, forecasts of the numerical weather prediction models COSMO-EU and COSMO-DE of the German Meteorological Service were tailored to match the observations and perform model evaluation in a near real-time environment. The ultimate goal is to identify and distinguish between different kinds of model deficits and to improve process understanding.

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Developed in response to the new challenges of the social Web, this study investigates how involvement with brand-related user-generated content (UGC) affects consumers’ perceptions of brands. The authors develop a model that provides new insights into the links between drivers of UGC creation, involvement, and consumer-based brand equity. Expert opinions were sought on a hypothesized model, which further was tested through data from an online survey of 202 consumers. The results provide guidance for managerial initiatives involving UGC campaigns for brand building. The findings indicate that consumer perceptions of co-creation, community, and self-concept have a positive impact on UGC involvement that, in turn, positively affects consumer based brand equity. These empirical results have significant implications for avoiding problems and building deeper relationships between consumers and brands in the age of social media.

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The organization of non-crystalline polymeric materials at a local level, namely on a spatial scale between a few and 100 a, is still unclear in many respects. The determination of the local structure in terms of the configuration and conformation of the polymer chain and of the packing characteristics of the chain in the bulk material represents a challenging problem. Data from wide-angle diffraction experiments are very difficult to interpret due to the very large amount of information that they carry, that is the large number of correlations present in the diffraction patterns.We describe new approaches that permit a detailed analysis of the complex neutron diffraction patterns characterizing polymer melts and glasses. The coupling of different computer modelling strategies with neutron scattering data over a wide Q range allows the extraction of detailed quantitative information on the structural arrangements of the materials of interest. Proceeding from modelling routes as diverse as force field calculations, single-chain modelling and reverse Monte Carlo, we show the successes and pitfalls of each approach in describing model systems, which illustrate the need to attack the data analysis problem simultaneously from several fronts.

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Mannitol is a polymorphic excipient which is usually used in pharmaceutical products as the beta form, although other polymorphs (alpha and delta) are common contaminants. Binary mixtures containing beta and delta mannitol were prepared to quantify the concentration of the beta form using FT-Raman spectroscopy. Spectral regions characteristic of each form were selected and peak intensity ratios of beta peaks to delta peaks were calculated. Using these ratios, a correlation curve was established which was then validated by analysing further samples of known composition. The results indicate that levels down to 2% beta could be quantified using this novel, non-destructive approach. Potential errors associated with quantitative studies using FT-Raman spectroscopy were also researched. The principal source of variability arose from inhomogeneities on mixing of the samples; a significant reduction of these errors was observed by reducing and controlling the particle size range. The results show that FT-Raman spectroscopy can be used to rapidly and accurately quantitate polymorphic mixtures.

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Mannitol is a polymorphic pharmaceutical excipient, which commonly exists in three forms: alpha, beta and delta. Each polymorph has a needle-like morphology, which can give preferred orientation effects when analysed by X-ray powder diffractometry (XRPD) thus providing difficulties for quantitative XRPD assessments. The occurrence of preferred orientation may be demonstrated by sample rotation and the consequent effects on X-ray data can be minimised by reducing the particle size. Using two particle size ranges (less than 125 and 125–500�microns), binary mixtures of beta and delta mannitol were prepared and the delta component was quantified. Samples were assayed in either a static or rotating sampling accessory. Rotation and reducing the particle size range to less than�125 microns halved the limits of detection and quantitation to 1 and 3.6%, respectively. Numerous potential sources of assay errors were investigated; sample packing and mixing errors contributed the greatest source of variation. However, the rotation of samples for both particle size ranges reduced the majority of assay errors examined. This study shows that coupling sample rotation with a particle size reduction minimises preferred orientation effects on assay accuracy, allowing discrimination of two very similar polymorphs at around the 1% level

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Measuring the retention, or residence time, of dosage forms to biological tissue is commonly a qualitative measurement, where no real values to describe the retention can be recorded. The result of this is an assessment that is dependent upon a user's interpretation of visual observation. This research paper outlines the development of a methodology to quantitatively measure, both by image analysis and by spectrophotometric techniques, the retention of material to biological tissues, using the retention of polymer solutions to ocular tissue as an example. Both methods have been shown to be repeatable, with the spectrophotometric measurement generating data reliably and quickly for further analysis.

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We have developed a new Bayesian approach to retrieve oceanic rain rate from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), with an emphasis on typhoon cases in the West Pacific. Retrieved rain rates are validated with measurements of rain gauges located on Japanese islands. To demonstrate improvement, retrievals are also compared with those from the TRMM/Precipitation Radar (PR), the Goddard Profiling Algorithm (GPROF), and a multi-channel linear regression statistical method (MLRS). We have found that qualitatively, all methods retrieved similar horizontal distributions in terms of locations of eyes and rain bands of typhoons. Quantitatively, our new Bayesian retrievals have the best linearity and the smallest root mean square (RMS) error against rain gauge data for 16 typhoon overpasses in 2004. The correlation coefficient and RMS of our retrievals are 0.95 and ~2 mm hr-1, respectively. In particular, at heavy rain rates, our Bayesian retrievals outperform those retrieved from GPROF and MLRS. Overall, the new Bayesian approach accurately retrieves surface rain rate for typhoon cases. Accurate rain rate estimates from this method can be assimilated in models to improve forecast and prevent potential damages in Taiwan during typhoon seasons.

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Many studies warn that climate change may undermine global food security. Much work on this topic focuses on modelling crop-weather interactions but these models do not generally account for the ways in which socio-economic factors influence how harvests are affected by weather. To address this gap, this paper uses a quantitative harvest vulnerability index based on annual soil moisture and grain production data as the dependent variables in a Linear Mixed Effects model with national scale socio-economic data as independent variables for the period 1990-2005. Results show that rice, wheat and maize production in middle income countries were especially vulnerable to droughts. By contrast, harvests in countries with higher investments in agriculture (e.g higher amounts of fertilizer use) were less vulnerable to drought. In terms of differences between the world's major grain crops, factors that made rice and wheat crops vulnerable to drought were quite consistent, whilst those of maize crops varied considerably depending on the type of region. This is likely due to the fact that maize is produced under very different conditions worldwide. One recommendation for reducing drought vulnerability risks is coordinated development and adaptation policies, including institutional support that enables farmers to take proactive action.

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Specific traditional plate count method and real-time PCR systems based on SYBR Green I and TaqMan technologies using a specific primer pair and probe for amplification of iap-gene were used for quantitative assay of Listeria monocytogenes in seven decimal serial dilution series of nutrient broth and milk samples containing 1.58 to 1.58×107 cfu /ml and the real-time PCR methods were compared with the plate count method with respect to accuracy and sensitivity. In this study, the plate count method was performed using surface-plating of 0.1 ml of each sample on Palcam Agar. The lowest detectable level for this method was 1.58×10 cfu/ml for both nutrient broth and milk samples. Using purified DNA as a template for generation of standard curves, as few as four copies of the iap-gene could be detected per reaction with both real-time PCR assays, indicating that they were highly sensitive. When these real-time PCR assays were applied to quantification of L. monocytogenes in decimal serial dilution series of nutrient broth and milk samples, 3.16×10 to 3.16×105 copies per reaction (equals to 1.58×103 to 1.58×107 cfu/ml L. monocytogenes) were detectable. As logarithmic cycles, for Plate Count and both molecular assays, the quantitative results of the detectable steps were similar to the inoculation levels.