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<p>The influence of particle shape of coating pigments on theirpacking ability and on the flow properties of coating colourshas been investigated. The particle shapes considered werespherical, flaky and acicular (needle-shaped). In the case ofsuspensions containing monodisperse spherical polystyreneparticles, a concentration gradient appeared in the filter cakeforming during filtration under static conditions. Such agradient, monitoredby non-destructive magnetic resonanceimaging (MRI), is not accounted for in the traditionalfiltration theory used in coating technology. Good agreementwas found between a literature model describing filtrationthrough a compressible filter cake and the concentrationgradients measured by MRI. According to this model, the scaledconcentration gradient was the same at all times.</p><p>For flaky (mainly kaolin) and acicular (aragonite)particles, a rapid method was evaluated to estimate a shapefactor of the pigment particle. Generalised mathematical modelsof oblate and prolate spheroids were applied to reduce thethree geometrical dimensions of the particle to two, the majoraxis and the minor axis. The shape factor, which is mass-based,was derived from a comparison between the results obtained bytwo different size-assessment instruments, viz. the Sedigraphand an instrument using light scattering. This yields a shapefactor distribution as a function of equivalent sphericalparticle size, but the results are uncertain for small particlediameters, below 0.2 µm. Good agreement was obtainedbetween the shape factor and a mass-based aspect ratio obtainedby image analysis, but the rapid method is generally moreaccurate for flaky than for acicular particles.</p><p>Results obtained by capillary viscometry showed that therewas a relationship between the viscosity at high shear rates(>10⁵s^-1) and the shape factor, but that it was notsufficient to use the median value of the shape factor toachieve proper information. A more complete evaluation requiresknowledge of the shape factor distribution, which is also givenin part by the method mentioned above. However, a large medianshape factor was related to a high high-shear viscosity.Non-Newtonian entrance pressure losses were sometimessignificant in capillary viscometry, indicating that it wasinappropriate to measure the shear viscosity with only onecapillary. Such effects were however relatively much morepronounced in slit die viscometry, especially in the case ofacicular particles, where the aspect ratio was a crucialparameter. The influence of the shape factor of kaolinparticles on the non-Newtonian entrance pressure losses over aslit die was surprisingly small. The high-shear viscosity ofcoating suspensions based on different pigments correlated withthe median pore size of the corresponding coating layer ratherthan with the porosity.</p><p><b>Keywords</b>: Aspect ratio, capillary viscometry, coatingcolour, filtration, particle packing, pigment, pore structure,rheology, shape factor, slit die viscometry, spheroid.</p>

Thesis (Ph. D.)--University of Missouri-Columbia, 2001. / Typescript. Vita. Includes bibliographical references (leaves 70-71). Also available on the Internet.

Thesis (Ph. D.)--University of Missouri-Columbia, 2001. / Typescript. Vita. Includes bibliographical references (leaves 70-71). Also available on the Internet.

Computerized classification tests (CCT) have been used in high-stakes assessment settings where the express purpose of the testing is to assign a classification decision (e.g. pass/fail). One key feature of sequential probability ratio test-type procedures is that items are selected to maximize information around the cutscore region of the examinee ability distribution as opposed to common features of CATs where items are selected to maximize information at examinees' interim estimates. Previous research has examined the effectiveness of computerized adaptive tests (CAT) utilizing classification testing procedures a single cutscore as well as multiple cutscores (e.g. below basic/proficient/advanced). Several variations of the SPRT procedure have been advanced recently including a generalized likelihood ratio (GLR). While the GLR procedure has shown evidences of improved average test length while reasonably maintaining classification accuracy, it also introduces unnecessary error. The purpose of this dissertation was to propose and investigate the functionality of a modified GLR procedure which does not incorporate the unnecessary error inherent in the GLR procedure. Additionally this dissertation explored the use of the multiple cutscores and the use of ability-based item selection. This dissertation investigated the performance of three classification procedures (SPRT, GLR, and modified GLR), multiple cutscores, and two test lengths. An additional set of conditions were developed in which an ability-based item selection method was used with the modified GLR. A simulation study was performed to gather evidences of the effectiveness and efficiency of a modified GLR procedure by comparing it to the SPRT and GLR procedures. The study found that the GLR and mGLR procedures were able to yield shorter test lengths as anticipated. Additionally, the mGLR procedure using ability-based item selection produced even shorter test lengths than the cutscore-based mGLR method. Overall, the classification accuracy of the procedures were reasonably close. Examination of conditional classification accuracy in the multiple-cutscore conditions showed unexpectedly low values for each of the procedures. Implications and future research are discussed herein. / text

One of the most challenging issues in reservoir modeling is to integrate information coming from different sources at disparate scales and precision. The primary data are borehole measurements, but in most cases, these are too sparse to construct accurate reservoir models. Therefore, in most cases, the information from borehole measurements has to be supplemented with other secondary data. The secondary data for reservoir modeling could be static data such as seismic data or dynamic data such as production history, well test data or time-lapse seismic data. Several algorithms for integrating different types of data have been developed. A novel method for data integration based on the permanence of ratio hypothesis was proposed by Journel in 2002. The premise of the permanence of ratio hypothesis is to assess the information from each data source separately and then merge the information accounting for the redundancy between the information sources. The redundancy between the information from different sources is accounted for using parameters (tau or nu parameters, Krishnan, 2004). The primary goal of this thesis is to derive a practical expression for the tau parameters and demonstrate the procedure for calibrating these parameters using the available data. This thesis presents two new algorithms for data integration in reservoir modeling. The algorithms proposed in this thesis overcome some of the limitations of the current methods for data integration. We present an extension to the direct sampling based multiple-point statistics method. We present a methodology for integrating secondary soft data in that framwork. The algorithm is based on direct pattern search through an ensemble of realizations. We show that the proposed methodology is sutiable for modeling complex channelized reservoirs and reduces the uncertainty associated with production performance due to integration of secondary data. We subsequently present the permanence of ratio hypothesis for data integration in great detail. We present analytical equations for calculating the redundancy factor for discrete or continuous variable modeling. Then, we show how this factor can be infered using available data for different scenarios. We implement the method to model a carbonate reservoir in the Gulf of Mexico. We show that the method has a better performance than when primary hard and secondary soft data are used within the traditional geostatistical framework. / text

The focus of this study was the development of an improved correlation that more accurately quantifies the relationships between optimum salinity, optimum solubilization ratios, chemical formulation variables such as surfactant and co-solvent structures, and the EACN. Entrained in this study are improved correlations for co-solvent partition coefficients and correlations for the optimum salinity and solubilization ratio with EACN. Several trends in the oil-water partition coefficient were observed with the alcohol type (IBA and phenol), the number of ethylene oxide groups in the co-solvent, the EACN of the oil, temperature, and salinity. New EACN measurements were made using optimized formulations containing various combinations of primary surfactants, co-surfactants, co-solvents and alkali. The new EACN measurements ranged from 11.3 to 21.1. These new data significantly expand the total number of reliable EACN values available to understand and correlate chemical EOR formulation results. An improved correlation that more accurately quantifies the relationship between surfactant structure, co-solvents, oil, temperature, and optimum salinity was developed using a new and much larger high quality formulation dataset now available from studies done in recent years in the Center for Petroleum and Geosystems Engineering at the University of Texas at Austin. The correlation is useful for understanding the now very large number of microemulsion phase behavior experiments as well as the uncertainties associated with these data, and for suggesting new chemical structures to develop and test. / text

Many human traits and diseases have a polygenic architecture, where phenotype is partially determined by variation in many genes. These complex traits or diseases can be highly heritable and genome-wide association studies (GWAS) have been relatively successful in the identification of associated variants. However, these variants typically do not account for most of the heritability and thus, the genetic architecture remains uncertain.

Bakgrund: Under flera årtionden har handeln med aktier och värdepapper moderniserats och utvecklats. En investerare kan idag placera en order för att köpa en aktie över hela världen. Investerare letar alltid efter nya aktier att investera för att maximera sin avkastning dock medför detta en risk. Att analysera en investering kan göras på flera olika sätt där Sharpekvoten är en av flera sätt att analysera på. Tidigare har Sharpekvoten oftast använts vid analys av fonder och inte aktier och i tidigare forskning används Sharpkvoten flitigt men flera olika parametrar används då. Syfte: Studiens syfte är att undersöka skillnaderna i portföljer med aktier med låg risk kontra portföljer med aktier med hög risk och se vilken av dessa typer av portföljer som gett bäst avkastning, i förhållande till den risk som tagits. Sharpekvoten kommer att användas som ett nyckeltal för att svara på syftet. Metod: Studien har behandlat aktier på den Svenska, Amerikanska och Japanska marknaden och på dess Large- och Small cap marknader. Utifrån den data som har samlats in har en kvantitativ studie utförts för att sedan analyserats i förhållande med de teorier och studier som har berörts. Studien har även kompletterats med intervjuer för att bredda analysen och tänkanden kring hur investerare agerar vid hög risk aktier. Resultat: Sharpekvoten är högre på den svenska och japanska marknaden på respektive lands large cap samt 1st section. Intervjuerna som gjordes gav svaret att den bästa strategin är att differentiera sin aktieportfölj och att högrisk aktier endast bör utgöra en liten del av portföljen. I analysen framkommer det att sharpekvoten inte kan ge ett entydigt svar på förhållandet avkastning och risk, då det är vår uppfattning att avkastningen påverkas av en mängd andra faktorer.

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