Development of a digital model of ground-water flow in deeply weathered crystalline rock, Chester County, Pennsylvania /

"August 1980."

Examining the Differential Effects of a Universal SEL Curriculum on Student Functioning on a Dual Continua Model of Mental Health

Thesis (Ph.D.)--University of Washington, 2016-06

A conceptual model of personalized virtual learning environments

The Virtual Learning Environment (VLE) is one of the fastest growing areas in educational technology research and development. In order to achieve learning effectiveness, ideal VLEs should be able to identify learning needs and customize solutions, with or without an instructor to supplement instruction. They are called Personalized VLEs (PVLEs). In order to achieve PVLEs success, comprehensive conceptual models corresponding to PVLEs are essential. Such conceptual modeling development is important because it facilitates early detection and correction of system development errors. Therefore, in order to capture the PVLEs knowledge explicitly, this paper focuses on the development of conceptual models for PVLEs, including models of knowledge primitives in terms of learner, curriculum, and situational models, models of VLEs in general pedagogical bases, and particularly, the definition of the ontology of PVLEs on the constructivist pedagogical principle. Based on those comprehensive conceptual models, a prototyped multiagent-based PVLE has been implemented. A field experiment was conducted to investigate the learning achievements by comparing personalized and non-personalized systems. The result indicates that the PVLE we developed under our comprehensive ontology successfully provides significant learning achievements. These comprehensive models also provide a solid knowledge representation framework for PVLEs development practice, guiding the analysis, design, and development of PVLEs. (c) 2005 Elsevier Ltd. All rights reserved.

A simulation model of cereal-legume intercropping systems for semi-arid regions I. Model development

Cereal-legume intercropping plays an important role in subsistence food production in developing countries, especially in situations of limited water resources. Crop simulation can be used to assess risk for intercrop productivity over time and space. In this study, a simple model for intercropping was developed for cereal and legume growth and yield, under semi-arid conditions. The model is based on radiation interception and use, and incorporates a water stress factor. Total dry matter and yield are functions of photosynthetically active radiation (PAR), the fraction of radiation intercepted and radiation use efficiency (RUE). One of two PAR sub-models was used to estimate PAR from solar radiation; either PAR is 50% of solar radiation or the ratio of PAR to solar radiation (PAR/SR) is a function of the clearness index (K-T). The fraction of radiation intercepted was calculated either based on Beer's Law with crop extinction coefficients (K) from field experiments or from previous reports. RUE was calculated as a function of available soil water to a depth of 900 mm (ASW). Either the soil water balance method or the decay curve approach was used to determine ASW. Thus, two alternatives for each of three factors, i.e., PAR/SR, K and ASW, were considered, giving eight possible models (2 methods x 3 factors). The model calibration and validation were carried out with maize-bean intercropping systems using data collected in a semi-arid region (Bloemfontein, Free State, South Africa) during seven growing seasons (1996/1997-2002/2003). The combination of PAR estimated from the clearness index, a crop extinction coefficient from the field experiment and the decay curve model gave the most reasonable and acceptable result. The intercrop model developed in this study is simple, so this modelling approach can be employed to develop other cereal-legume intercrop models for semi-arid regions. (c) 2004 Elsevier B.V. All rights reserved.

The in vivo expression of actin/salt-resistant hyperactive DNase I inhibits the development of anti-ssDNA and anti-histone autoantibodies in a murine model of systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is characterised by the production of autoantibodies against ubiquitous antigens, especially nuclear components. Evidence makes it clear that the development of these autoantibodies is an antigen-driven process and that immune complexes involving DNA-containing antigens play a key role in the disease process. In rodents, DNase I is the major endonuclease present in saliva, urine and plasma, where it catalyses the hydrolysis of DNA, and impaired DNase function has been implicated in the pathogenesis of SLE. In this study we have evaluated the effects of transgenic overexpression of murine DNase I endonucleases in vivo in a mouse model of lupus. We generated transgenic mice having T-cells that express either wild-type DNase I (wt. DNase I) or a mutant DNase I ( ash. DNase I), engineered for three new properties - resistance to inhibition by G-actin, resistance to inhibition by physiological saline and hyperactivity compared to wild type. By crossing these transgenic mice with a murine strain that develops SLE we found that, compared to control nontransgenic littermates or wt. DNase I transgenic mice, the ash. DNase I mutant provided significant protection from the development of anti-single-stranded DNA and anti-histone antibodies, but not of renal disease. In summary, this is the first study in vivo to directly test the effects of long-term increased expression of DNase I on the development of SLE. Our results are in line with previous reports on the possible clinical benefits of recombinant DNase I treatment in SLE, and extend them further to the use of engineered DNase I variants with increased activity and resistance to physiological inhibitors.

The development of an in vivo model of drug-induced terminal differentiation of Leukaemic cells

The technique of growing human leukaemic cells in diffusion chambers was developed to enable chemicals to be assessed for their ability to induce terminal differentiation. HL-60 promyelocytic leukaemia cell growth, in a lucite chamber with a Millipore filter, was optimised by use of a lateral incision site. Chambers were constructed using 0.45um filters and contained 150ul of serum-free HL-60 cells at a density of 1x106 cells/ml. The chambers were implanted into CBA/Ca mice and spontaneous terminal differentiation of the cells to granulocytes was prevented by the use of serum-free medium. Under these conditions there was an initial growth lag of 72 hours and a logarithmic phase of growth for 96 hours; the cell number reached a plateau after 168 hours of culture in vivo. The amount of drug in the plasma of the animal and in chambers that had been implanted for 5 days, was determined after a single ip injection of equitoxic doses of N-methylformamide, N-ethylformamide, tetramethylurea, N-dibutylformamide, N-tetramethylbutylformamide and hexamethylenebisacetamide. Concentrations of both TMU and HMBA were obtained in the plasma and in the chamber which were pharmacologically effective for the induction of differentiation of HL-60 cells in vitro, that is 12mM TMU and 5mM HMBA. A 4 day regime of treatment of animals implanted with chambers demonstrated that TMU and HMBA induced terminal differentiation of 50% and 35%, respectively, of the implanted HL-60 cells to granulocyte-like cells, assessed by measurement of functional and biochemical markers of maturity. None of the other agents attained concentrations in the plasma that were pharmacologically effective for the induction of differentiation of the cells in vitro and were unable to induce the terminal differentiation of the cells in vivo.

Development of a conceptual model of the soil-moisture-plant sub-system of the hydrological cycle

The soil-plant-moisture subsystem is an important component of the hydrological cycle. Over the last 20 or so years a number of computer models of varying complexity have represented this subsystem with differing degrees of success. The aim of this present work has been to improve and extend an existing model. The new model is less site specific thus allowing for the simulation of a wide range of soil types and profiles. Several processes, not included in the original model, are simulated by the inclusion of new algorithms, including: macropore flow; hysteresis and plant growth. Changes have also been made to the infiltration, water uptake and water flow algorithms. Using field data from various sources, regression equations have been derived which relate parameters in the suction-conductivity-moisture content relationships to easily measured soil properties such as particle-size distribution data. Independent tests have been performed on laboratory data produced by Hedges (1989). The parameters found by regression for the suction relationships were then used in equations describing the infiltration and macropore processes. An extensive literature review produced a new model for calculating plant growth from actual transpiration, which was itself partly determined by the root densities and leaf area indices derived by the plant growth model. The new infiltration model uses intensity/duration curves to disaggregate daily rainfall inputs into hourly amounts. The final model has been calibrated and tested against field data, and its performance compared to that of the original model. Simulations have also been carried out to investigate the effects of various parameters on infiltration, macropore flow, actual transpiration and plant growth. Qualitatively comparisons have been made between these results and data given in the literature.

Development of a multicellular co-culture model of normal and cystic fibrosis human airways in vitro

Cystic fibrosis (CF) is the most common lethal inherited disease among Caucasians and arises due to mutations in a chloride channel, called cystic fibrosis transmembrane conductance regulator. A hallmark of this disease is the chronic bacterial infection of the airways, which is usually, associated with pathogens such as Pseudomonas aeruginosa, S. aureus and recently becoming more prominent, B. cepacia. The excessive inflammatory response, which leads to irreversible lung damage, will in the long term lead to mortality of the patient at around the age of 40 years. Understanding the pathogenesis of CF currently relies on animal models, such as those employing genetically-modified mice, and on single cell culture models, which are grown either as polarised or non-polarised epithelium in vitro. Whilst these approaches partially enable the study of disease progression in CF, both types of models have inherent limitations. The overall aim of this thesis was to establish a multicellular co-culture model of normal and CF human airways in vitro, which helps to partially overcome these limitations and permits analysis of cell-to-cell communication in the airways. These models could then be used to examine the co-ordinated response of the airways to infection with relevant pathogens in order to validate this approach over animals/single cell models. Therefore epithelial cell lines of non-CF and CF background were employed in a co-culture model together with human pulmonary fibroblasts. Co-cultures were grown on collagen-coated permeable supports at air-liquid interface to promote epithelial cell differentiation. The models were characterised and essential features for investigating CF infections and inflammatory responses were investigated and analysed. A pseudostratified like epithelial cell layer was established at air liquid interface (ALI) of mono-and co-cultures and cell layer integrity was verified by tight junction (TJ) staining and transepithelial resistance measurements (TER). Mono- and co-cultures were also found to secrete the airway mucin MUC5AC. Influence of bacterial infections was found to be most challenging when intact S. aureus, B. cepacia and P. aeruginosa were used. CF mono- and co-cultures were found to mimic the hyperinflammatory state found in CF, which was confirmed by analysing IL-8 secretions of these models. These co-culture models will help to elucidate the role fibroblasts play in the inflammatory response to bacteria and will provide a useful testing platform to further investigate the dysregulated airway responses seen in CF.

Development of a co-culture model of the human lungs for toxicity testing and identification of biomarkers of inhalation toxicity

The airway epithelium is the first point of contact in the lung for inhaled material, including infectious pathogens and particulate matter, and protects against toxicity from these substances by trapping and clearance via the mucociliary escalator, presence of a protective barrier with tight junctions and initiation of a local inflammatory response. The inflammatory response involves recruitment of phagocytic cells to neutralise and remove and invading materials and is oftern modelled using rodents. However, development of valid in vitro airway epithelial models is of great importance due to the restrictions on animal studies for cosmetic compound testing implicit in the 7th amendment to the European Union Cosmetics Directive. Further, rodent innate immune responses have fundamental differences to human. Pulmonary endothelial cells and leukocytes are also involved in the innate response initiated during pulmonary inflammation. Co-culture models of the airways, in particular where epithelial cells are cultured at air liquid interface with the presence of tight junctions and differentiated mucociliary cells, offer a solution to this problem. Ideally validated models will allow for detection of early biomarkers of response to exposure and investigation into inflammatory response during exposure. This thesis describes the approaches taken towards developing an in vitro epithelial/endothelial cell model of the human airways and identification biomarkers of response to exposure to xenobiotics. The model comprised normal human primary microvascular endothelial cells and the bronchial epithelial cell line BEAS-2B or normal human bronchial epithelial cells. BEAS-2B were chosen as their characterisation at air liquid interface is limited but they are robust in culture, thereby predicted to provide a more reliable test system. Proteomics analysis was undertaken on challenged cells to investigate biomarkers of exposure. BEAS-2B morphology was characterised at air liquid interface compared with normal human bronchial epithelial cells. The results indicate that BEAS-2B cells at an air liquid interface form tight junctions as shown by expression of the tight junction protein zonula occludens-1. To this author’s knowledge this is the first time this result has been reported. The inflammatory response of BEAS-2B (measured as secretion of the inflammatory mediators interleukin-8 and -6) air liquid interface mono-cultures to Escherichia coli lipopolysaccharide or particulate matter (fine and ultrafine titanium dioxide) was comparable to published data for epithelial cells. Cells were also exposed to polymers of “commercial interest” which were in the nanoparticle range (and referred to particles hereafter). BEAS-2B mono-cultures showed an increased secretion of inflammatory mediators after challenge. Inclusion of microvascular endothelial cells resulted in protection against LPS- and particle- induced epithelial toxicity, measured as cell viability and inflammatory response, indicating the importance of co-cultures for investigations into toxicity. Two-dimensional proteomic analysis of lysates from particle-challenged cells failed to identify biomarkers of toxicity due to assay interference and experimental variability. Separately, decreased plasma concentrations of serine protease inhibitors, and the negative acute phase proteins transthyretin, histidine-rich glycoprotein and alpha2-HS glycoprotein were identified as potential biomarkers of methyl methacrylate/ethyl methacrylate/butylacrylate treatment in rats.

Development of a probabilistic graphical structure from a model of mental health clinical expertise

This thesis explores the process of developing a principled approach for translating a model of mental-health risk expertise into a probabilistic graphical structure. Probabilistic graphical structures can be a combination of graph and probability theory that provide numerous advantages when it comes to the representation of domains involving uncertainty, domains such as the mental health domain. In this thesis the advantages that probabilistic graphical structures offer in representing such domains is built on. The Galatean Risk Screening Tool (GRiST) is a psychological model for mental health risk assessment based on fuzzy sets. In this thesis the knowledge encapsulated in the psychological model was used to develop the structure of the probability graph by exploiting the semantics of the clinical expertise. This thesis describes how a chain graph can be developed from the psychological model to provide a probabilistic evaluation of risk that complements the one generated by GRiST’s clinical expertise by the decomposing of the GRiST knowledge structure in component parts, which were in turned mapped into equivalent probabilistic graphical structures such as Bayesian Belief Nets and Markov Random Fields to produce a composite chain graph that provides a probabilistic classification of risk expertise to complement the expert clinical judgements

The development of a computer simulation model of the interaction between the supply and usage of major components in car assembly you use in stock control

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Development of a physiologically-based pharmacokinetic model of the rat central nervous system

Central nervous system (CNS) drug disposition is dictated by a drug’s physicochemical properties and its ability to permeate physiological barriers. The blood–brain barrier (BBB), blood-cerebrospinal fluid barrier and centrally located drug transporter proteins influence drug disposition within the central nervous system. Attainment of adequate brain-to-plasma and cerebrospinal fluid-to-plasma partitioning is important in determining the efficacy of centrally acting therapeutics. We have developed a physiologically-based pharmacokinetic model of the rat CNS which incorporates brain interstitial fluid (ISF), choroidal epithelial and total cerebrospinal fluid (CSF) compartments and accurately predicts CNS pharmacokinetics. The model yielded reasonable predictions of unbound brain-to-plasma partition ratio (Kpuu,brain) and CSF:plasma ratio (CSF:Plasmau) using a series of in vitro permeability and unbound fraction parameters. When using in vitro permeability data obtained from L-mdr1a cells to estimate rat in vivo permeability, the model successfully predicted, to within 4-fold, Kpuu,brain and CSF:Plasmau for 81.5% of compounds simulated. The model presented allows for simultaneous simulation and analysis of both brain biophase and CSF to accurately predict CNS pharmacokinetics from preclinical drug parameters routinely available during discovery and development pathways.