907 resultados para MOdular Quantitative Analysis (MOQA)
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Mammalian promoters can be separated into two classes, conserved TATA box-enriched promoters, which initiate at a welldefined site, and more plastic, broad and evolvable CpG-rich promoters. We have sequenced tags corresponding to several hundred thousand transcription start sites (TSSs) in the mouse and human genomes, allowing precise analysis of the sequence architecture and evolution of distinct promoter classes. Different tissues and families of genes differentially use distinct types of promoters. Our tagging methods allow quantitative analysis of promoter usage in different tissues and show that differentially regulated alternative TSSs are a common feature in protein-coding genes and commonly generate alternative N termini. Among the TSSs, we identified new start sites associated with the majority of exons and with 3' UTRs. These data permit genome-scale identification of tissue-specific promoters and analysis of the cis-acting elements associated with them.
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The conformational characteristics of poly(dimethylsilmethylene), poly(dimethylsilethene), poly(dimethylsilethane) and a related material, poly(2,2,5,5-tetramethyl-1-oxa-2,5-disilapentane), have been investigated using the method of molecular mechanics. In this method, a quantitative analysis of the factors affecting the nature and magnitude of the bond rotation potentials governing their conformational behaviour has been undertaken. Along with their structural data, the results obtained were employed to calculate a variety of conformationally-dependent properties for these polymers, including the characteristic ratio, the dipole moment ratio and the mean-square radius of gyration. In addition, the dielectric relaxation behaviour of two samples of poly(2,2,5,5-tetramethyl-1-oxa-2,5-disilapentane) with molar masses Mw = 28000 and Mw = 46000 respectively, have been studied as a function of temperature (179K-205K) and frequency (100-105Hz). Activation energies for the α-relaxation process and Davidson-Cole empirical distribution factors have been calculated.
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This work concerns the developnent of a proton irduced X-ray emission (PIXE) analysis system and a multi-sample scattering chamber facility. The characteristics of the beam pulsing system and its counting rate capabilities were evaluated by observing the ion-induced X-ray emission from pure thick copper targets, with and without beam pulsing operation. The characteristic X-rays were detected with a high resolution Si(Li) detector coupled to a rrulti-channel analyser. The removal of the pile-up continuum by the use of the on-demand beam pulsing is clearly demonstrated in this work. This new on-demand pu1sirg system with its counting rate capability of 25, 18 and 10 kPPS corresponding to 2, 4 am 8 usec main amplifier time constant respectively enables thick targets to be analysed more readily. Reproducibility tests of the on-demard beam pulsing system operation were checked by repeated measurements of the system throughput curves, with and without beam pulsing. The reproducibility of the analysis performed using this system was also checked by repeated measurements of the intensity ratios from a number of standard binary alloys during the experimental work. A computer programme has been developed to evaluate the calculations of the X-ray yields from thick targets bornbarded by protons, taking into account the secondary X-ray yield production due to characteristic X-ray fluorescence from an element energetically higher than the absorption edge energy of the other element present in the target. This effect was studied on metallic binary alloys such as Fe/Ni and Cr/Fe. The quantitative analysis of Fe/Ni and Cr/Fe alloy samples to determine their elemental composition taking into account the enhancement has been demonstrated in this work. Furthermore, the usefulness of the Rutherford backscattering (R.B.S.) technique to obtain the depth profiles of the elements in the upper micron of the sample is discussed.
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We present an imaging system based on light emitting diode (LED) illumination that produces multispectral optical images of the human ocular fundus. It uses a conventional fundus camera equipped with a high power LED light source and a highly sensitive electron-multiplying charge coupled device camera. It is able to take pictures at a series of wavelengths in rapid succession at short exposure times, thereby eliminating the image shift introduced by natural eye movements (saccades). In contrast with snapshot systems the images retain full spatial resolution. The system is not suitable for applications where the full spectral resolution is required as it uses discrete wavebands for illumination. This is not a problem in retinal imaging where the use of selected wavelengths is common. The modular nature of the light source allows new wavelengths to be introduced easily and at low cost. The use of wavelength-specific LEDs as a source is preferable to white light illumination and subsequent filtering of the remitted light as it minimizes the total light exposure of the subject. The system is controlled via a graphical user interface that enables flexible control of intensity, duration, and sequencing of sources in synchrony with the camera. Our initial experiments indicate that the system can acquire multispectral image sequences of the human retina at exposure times of 0.05 s in the range of 500-620 nm with mean signal to noise ratio of 17 dB (min 11, std 4.5), making it suitable for quantitative analysis with application to the diagnosis and screening of eye diseases such as diabetic retinopathy and age-related macular degeneration.
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In this paper we present the design and analysis of an intonation model for text-to-speech (TTS) synthesis applications using a combination of Relational Tree (RT) and Fuzzy Logic (FL) technologies. The model is demonstrated using the Standard Yorùbá (SY) language. In the proposed intonation model, phonological information extracted from text is converted into an RT. RT is a sophisticated data structure that represents the peaks and valleys as well as the spatial structure of a waveform symbolically in the form of trees. An initial approximation to the RT, called Skeletal Tree (ST), is first generated algorithmically. The exact numerical values of the peaks and valleys on the ST is then computed using FL. Quantitative analysis of the result gives RMSE of 0.56 and 0.71 for peak and valley respectively. Mean Opinion Scores (MOS) of 9.5 and 6.8, on a scale of 1 - -10, was obtained for intelligibility and naturalness respectively.
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Human mesenchymal stem cell (hMSC) therapies have the potential to revolutionise the healthcare industry and replicate the success of the therapeutic protein industry; however, for this to be achieved there is a need to apply key bioprocessing engineering principles and adopt a quantitative approach for large-scale reproducible hMSC bioprocess development. Here we provide a quantitative analysis of the changes in concentration of glucose, lactate and ammonium with time during hMSC monolayer culture over 4 passages, under 100% and 20% dissolved oxgen (dO2), where either a 100%, 50% or 0% growth medium exchange was performed after 72h in culture. Yield coefficients, specific growth rates (h-1) and doubling times (h) were calculated for all cases. The 100% dO2 flasks outperformed the 20% dO2 flasks with respect to cumulative cell number, with the latter consuming more glucose and producing more lactate and ammonium. Furthermore, the 100% and 50% medium exchange conditions resulted in similar cumulative cell numbers, whilst the 0% conditions were significantly lower. Cell immunophenotype and multipotency were not affected by the experimental culture conditions. This study demonstrates the importance of determining optimal culture conditions for hMSC expansion and highlights a potential cost savings from only making a 50% medium exchange, which may prove significant for large-scale bioprocessing. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Since the 1990s, scholars have paid special attention to public management’s role in theory and research under the assumption that effective management is one of the primary means for achieving superior performance. To some extent, this was influenced by popular business writings of the 1980s as well as the reinventing literature of the 1990s. A number of case studies but limited quantitative research papers have been published showing that management matters in the performance of public organizations. ^ My study examined whether or not management capacity increased organizational performance using quantitative techniques. The specific research problem analyzed was whether significant differences existed between high and average performing public housing agencies on select criteria identified in the Government Performance Project (GPP) management capacity model, and whether this model could predict outcome performance measures in a statistically significant manner, while controlling for exogenous influences. My model included two of four GPP management subsystems (human resources and information technology), integration and alignment of subsystems, and an overall managing for results framework. It also included environmental and client control variables that were hypothesized to affect performance independent of management action. ^ Descriptive results of survey responses showed high performing agencies with better scores on most high performance dimensions of individual criteria, suggesting support for the model; however, quantitative analysis found limited statistically significant differences between high and average performers and limited predictive power of the model. My analysis led to the following major conclusions: past performance was the strongest predictor of present performance; high unionization hurt performance; and budget related criterion mattered more for high performance than other model factors. As to the specific research question, management capacity may be necessary but it is not sufficient to increase performance. ^ The research suggested managers may benefit by implementing best practices identified through the GPP model. The usefulness of the model could be improved by adding direct service delivery to the model, which may also improve its predictive power. Finally, there are abundant tested concepts and tools designed to improve system performance that are available for practitioners designed to improve management subsystem support of direct service delivery.^
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Thiosalt species are unstable, partially oxidized sulfur oxyanions formed in sulfur-rich environments but also during the flotation and milling of sulfidic minerals especially those containing pyrite (FeS₂) and pyrrhotite (Fe₍₁₋ₓ₎S, x = 0 to 0.2). Detecting and quantifying the major thiosalt species such as sulfate (SO₄²⁻), thiosulfate (S₂O₃²⁻), trithionate (S₃O₆²⁻), tetrathionate (S₄O₆²⁻) and higher polythionates (SₓO₆²⁻, where 3 ≤ x ≤ 10) in the milling process and in the treated tailings is important to understand how thiosalts are generated and provides insight into potential treatment. As these species are unstable, a fast and reliable analytical technique is required for their analysis. Three capillary zone electrophoresis (CZE) methods using indirect UV-vis detection were developed for the simultaneous separation and determination of five thiosalt anions: SO₄²⁻, S₂O₃²⁻, S₃O₆²⁻, S₄O₆²⁻ and S₅O₆²⁻. Both univariate and multivariate experimental design approaches were used to optimize the most critical factors (background electrolyte (BGE) and instrumental conditions) to achieve fast separation and quantitative analysis of the thiosalt species. The mathematically predicted responses for the multivariate experiments were in good agreement with the experimental results. Limits of detection (LODs) (S/N = 3) for the methods were between 0.09 and 0.34 μg/mL without a sample stacking technique and nearly four-fold increase in LODs with the application of field-amplified sample stacking. As direct analysis of thiosalts by mass spectrometry (MS) is limited by their low m/z values and detection in negative mode electrospray ionization (ESI), which is typically less sensitive than positive ESI, imidazolium-based (IP-L-Imid and IP-T-Imid) and phosphonium-based (IP-T-Phos) tricationic ion-pairing reagents were used to form stable high mass ions non-covalent +1 ion-pairs with these species for ESI-MS analysis and the association constants (Kassoc) determined for these ion-pairs. Kassoc values were between 6.85 × 10² M⁻¹ and 3.56 × 10⁵ M⁻¹ with the linear IP-L-Imid; 1.89 ×10³ M⁻¹ and 1.05 × 10⁵ M⁻¹ with the trigonal IP-T-Imid ion-pairs; and 7.51×10² M⁻¹ and 4.91× 10⁴ M⁻¹ with the trigonal IP-T-Phos ion-pairs. The highest formation constants were obtained for S₃O₆²⁻ and the imidazolium-based linear ion-pairing reagent (IP-L-Imid), whereas the lowest were for IP-L-Imid: SO₄²⁻ ion-pair.
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This dissertation goes into the new field from applied linguistics called forensic linguistics, which studies the language as an evidence for criminal cases. There are many subfields within forensic linguistics, however, this study belongs to authorship attribution analysis, where the authorship of a text is attributed to an author through an exhaustive linguistic analysis. Within this field, this study analyzes the morphosyntactic and discursive-pragmatic variables that remain constant in the intra-variation or personal style of a speaker in the oral and written discourse, and at the same time have a high difference rate in the interspeaker variation, or from one speaker to another. The theoretical base of this study is the term used by professor Maria Teresa Turell called “idiolectal style”. This term establishes that the idiosyncratic choices that the speaker makes from the language build a style for each speaker that is constant in the intravariation of the speaker’s discourse. This study comes as a consequence of the problem appeared in authorship attribution analysis, where the absence of some known texts impedes the analysis for the attribution of the authorship of an uknown text. Thus, through a methodology based on qualitative analysis, where the variables are studied exhaustively, and on quantitative analysis, where the findings from qualitative analysis are statistically studied, some conclusions on the evidence of such variables in both oral and written discourses will be drawn. The results of this analysis will lead to further implications on deeper analyses where larger amount of data can be used.
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Single-particle mixing state information can be a powerful tool for assessing the relative impact of local and regional sources of ambient particulate matter in urban environments. However, quantitative mixing state data are challenging to obtain using single-particle mass spectrometers. In this study, the quantitative chemical composition of carbonaceous single particles has been determined using an aerosol time-of-flight mass spectrometer (ATOFMS) as part of the MEGAPOLI 2010 winter campaign in Paris, France. Relative peak areas of marker ions for elemental carbon (EC), organic aerosol (OA), ammonium, nitrate, sulfate and potassium were compared with concurrent measurements from an Aerodyne high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS), a thermal-optical OCEC analyser and a particle into liquid sampler coupled with ion chromatography (PILS-IC). ATOFMS-derived estimated mass concentrations reproduced the variability of these species well (R-2 = 0.67-0.78), and 10 discrete mixing states for carbonaceous particles were identified and quantified. The chemical mixing state of HR-ToF-AMS organic aerosol factors, resolved using positive matrix factorisation, was also investigated through comparison with the ATOFMS dataset. The results indicate that hydrocarbon-like OA (HOA) detected in Paris is associated with two EC-rich mixing states which differ in their relative sulfate content, while fresh biomass burning OA (BBOA) is associated with two mixing states which differ significantly in their OA/EC ratios. Aged biomass burning OA (OOA(2)-BBOA) was found to be significantly internally mixed with nitrate, while secondary, oxidised OA (OOA) was associated with five particle mixing states, each exhibiting different relative secondary inorganic ion content. Externally mixed secondary organic aerosol was not observed. These findings demonstrate the range of primary and secondary organic aerosol mixing states in Paris. Examination of the temporal behaviour and chemical composition of the ATOFMS classes also enabled estimation of the relative contribution of transported emissions of each chemical species and total particle mass in the size range investigated. Only 22% of the total ATOFMS-derived particle mass was apportioned to fresh, local emissions, with 78% apportioned to regional/continental-scale emissions. Single-particle mixing state information can be a powerful tool for assessing the relative impact of local and regional sources of ambient particulate matter in urban environments. However, quantitative mixing state data are challenging to obtain using single-particle mass spectrometers. In this study, the quantitative chemical composition of carbonaceous single particles has been determined using an aerosol time-of-flight mass spectrometer (ATOFMS) as part of the MEGAPOLI 2010 winter campaign in Paris, France. Relative peak areas of marker ions for elemental carbon (EC), organic aerosol (OA), ammonium, nitrate, sulfate and potassium were compared with concurrent measurements from an Aerodyne high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS), a thermal-optical OCEC analyser and a particle into liquid sampler coupled with ion chromatography (PILS-IC). ATOFMS-derived estimated mass concentrations reproduced the variability of these species well (R-2 = 0.67-0.78), and 10 discrete mixing states for carbonaceous particles were identified and quantified. The chemical mixing state of HR-ToF-AMS organic aerosol factors, resolved using positive matrix factorisation, was also investigated through comparison with the ATOFMS dataset. The results indicate that hydrocarbon-like OA (HOA) detected in Paris is associated with two EC-rich mixing states which differ in their relative sulfate content, while fresh biomass burning OA (BBOA) is associated with two mixing states which differ significantly in their OA/EC ratios. Aged biomass burning OA (OOA(2)-BBOA) was found to be significantly internally mixed with nitrate, while secondary, oxidised OA (OOA) was associated with five particle mixing states, each exhibiting different relative secondary inorganic ion content. Externally mixed secondary organic aerosol was not observed. These findings demonstrate the range of primary and secondary organic aerosol mixing states in Paris. Examination of the temporal behaviour and chemical composition of the ATOFMS classes also enabled estimation of the relative contribution of transported emissions of each chemical species and total particle mass in the size range investigated. Only 22% of the total ATOFMS-derived particle mass was apportioned to fresh, local emissions, with 78% apportioned to regional/continental-scale emissions.
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The Olivia framework is a set of concepts and measures that, when mature, will allow users to describe, in a consistent and integrated manner, everything about individuals and institutions that is of potential interest to social policy. The present paper summarizes the current stage of development in achieving this highly ambitious goal. The current version of the framework supports analysis of social trends and policy responses from many perspectives: • The point-in-time, resource-flow perspectives that underlie most traditional, economics-based policy analysis. • Life-course perspectives, including both transitions/trajectories analysis and asset-based analysis. • Spatial perspectives that anchor people in space and history and that provide a link to macro-analysis. • The perspective of the purposes/goals of individuals and institutions, including the objectives of different types of government programming. The concepts of the framework, which are all potentially measurable, provide a language that can support integrated analysis in all these areas at a much finer level of description than is customary. It provides a language that is especially well suited for analysis of the incremental policy changes that are typical of a mature welfare state. It supports both qualitative and quantitative analysis, enabling some integration between the two. It supports citizen-centric as well as a government-centric view of social policy. In its current version, the concepts are most highly developed as they related to social policies as they related to labour markets, equality and social integration, care-giving, immigration, income security, sustainability, and social and economic well-being more generally. However the paper points to likely extensions in the areas of health, justice and safety.
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With the development of information technology, the theory and methodology of complex network has been introduced to the language research, which transforms the system of language in a complex networks composed of nodes and edges for the quantitative analysis about the language structure. The development of dependency grammar provides theoretical support for the construction of a treebank corpus, making possible a statistic analysis of complex networks. This paper introduces the theory and methodology of the complex network and builds dependency syntactic networks based on the treebank of speeches from the EEE-4 oral test. According to the analysis of the overall characteristics of the networks, including the number of edges, the number of the nodes, the average degree, the average path length, the network centrality and the degree distribution, it aims to find in the networks potential difference and similarity between various grades of speaking performance. Through clustering analysis, this research intends to prove the network parameters’ discriminating feature and provide potential reference for scoring speaking performance.
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This thesis presents quantitative studies of T cell and dendritic cell (DC) behaviour in mouse lymph nodes (LNs) in the naive state and following immunisation. These processes are of importance and interest in basic immunology, and better understanding could improve both diagnostic capacity and therapeutic manipulations, potentially helping in producing more effective vaccines or developing treatments for autoimmune diseases. The problem is also interesting conceptually as it is relevant to other fields where 3D movement of objects is tracked with a discrete scanning interval. A general immunology introduction is presented in chapter 1. In chapter 2, I apply quantitative methods to multi-photon imaging data to measure how T cells and DCs are spatially arranged in LNs. This has been previously studied to describe differences between the naive and immunised state and as an indicator of the magnitude of the immune response in LNs, but previous analyses have been generally descriptive. The quantitative analysis shows that some of the previous conclusions may have been premature. In chapter 3, I use Bayesian state-space models to test some hypotheses about the mode of T cell search for DCs. A two-state mode of movement where T cells can be classified as either interacting to a DC or freely migrating is supported over a model where T cells would home in on DCs at distance through for example the action of chemokines. In chapter 4, I study whether T cell migration is linked to the geometric structure of the fibroblast reticular network (FRC). I find support for the hypothesis that the movement is constrained to the fibroblast reticular cell (FRC) network over an alternative 'random walk with persistence time' model where cells would move randomly, with a short-term persistence driven by a hypothetical T cell intrinsic 'clock'. I also present unexpected results on the FRC network geometry. Finally, a quantitative method is presented for addressing some measurement biases inherent to multi-photon imaging. In all three chapters, novel findings are made, and the methods developed have the potential for further use to address important problems in the field. In chapter 5, I present a summary and synthesis of results from chapters 3-4 and a more speculative discussion of these results and potential future directions.
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International audience
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Even though today’s corporations recognize that they need to understand modern project management techniques (Schwalbe, 2002, p2), many researchers continue to provide evidence of poor IT project success. With Kotnour, (2000) finding that project performance is positively associated with project knowledge, a better understanding of how to effectively manage knowledge in IT projects should have considerable practical significance for increasing the chances of project success. Using a combined qualitative/quantitative method of data collection in multiple case studies spanning four continents, and comprising a variety of organizational types, the focus of this current research centered on the question of why individuals working within IT project teams might be motivated towards, or inhibited from, sharing their knowledge and experience in their activities, procedures, and processes. The research concluded with the development of a new theoretical model of knowledge sharing behavior, ‘The Alignment Model of Motivational Focus’. This model suggests that an individual’s propensity to share knowledge and experience is a function of perceived personal benefits and costs associated with the activity, balanced against the individual’s alignment to a group of ‘institutional’ factors. These factors are identified as alignments to the project team, to the organization, and dependent on the circumstances, to either the professional discipline or community of practice, to which the individual belongs.