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The migration of contaminants from the subsurface into the indoor air environment, in a process described as soil vapor intrusion, is gaining attention as a potential pathway for exposure to contaminated soil and water. Indoor, outdoor and soil air samples were collected from forty homes in North Texas to investigate the attenuation of trichloroethylene (TCE) from contaminated groundwater into residential buildings. The mean and standard deviation of the soil and indoor air attenuation factors (ratio of indoor air concentration to soil vapor concentration) were 0.14 and 0.17, respectively. Five of the 40 values were greater than 0.1 which is the suggested upper-bound by the U.S. EPA (2002). Statistical tools were used to draw correlative relationships between contaminant groundwater, soil air and indoor air concentrations. The VolaSoil model described by Waitz et al. (1996), was modified for use as a screening tool for future investigations of indoor TCE concentration. Using measured soil vapor data, the model under predicted indoor air TCE concentrations likely due to heterogeneities in the unsaturated subsurface. Inputting groundwater TCE concentrations, the model was able to capture the contaminant migration processes and produce results consistent with measured indoor TCE concentrations. Therefore, the model described in this paper maybe appropriate to be use as a screening tool in future investigations in the contamination area. / text

Abstract¡G With the rapid development of electronic marketplace, buyers and sellers can trade more easily without the limitations of time and distance. Internet trading is benefited to both sides in many ways. However, the matching mechanism between buyers and sellers in the electronic marketplace is not explored deeply. Consequently, the purpose of this research is to study the screening and negotiation in the process of matching. In this research, four screening models and related flow charts have been proposed. A negotiation model is also proposed to deal with the bargaining process. Finally, a prototype based on development method is built to demonstrate how the screening models and negotiation models work.

Citizens in the United States are fortunate to have an excellent system of roadways and the affluence with which to afford automobiles. The flexibility of travel on demand for most allows for a variety of lifestyles, assists with conducting business, and contributes to the feeling of freedom that most citizens enjoy. The current vehicle fleet, which is primarily powered by internal combustion engines burning fossil fuels, does however contribute to the deterioration of air quality. This effect is particularly significant in metropolitan areas. Motor vehicle exhausts contain several combustion bi-products that pose harmful effects to the environment and human health, in particular. The United States Environmental Protection Agency (EPA) and the Federal Highway Administration (FHWA) have selected carbon monoxide (CO) as the air pollutant on which it has based its guidelines for assessing potential air quality impacts from roadway construction (EPA 1992). The design of roadway networks must consider traffic flows, Level of Service (LOS), cost, and National Ambient Air Quality Standards (NAAQS) requirements. In light of the environmental standards it is necessary to model to estimate potential future near-road concentrations of CO. This modeling has two aspects, first determining the rate of pollutant emissions, and second determining how those pollutants disperse near the road. Obtaining a precise, realistic estimate of the near-road CO concentrations under a wide variety of weather and traffic patterns is a potentially huge undertaking. With budgetary constraints in mind, the development of a screening model is appropriate. CO Florida 2012 (COFL2012) is such a model that uses conservative assumptions to predict worst-case, near-road CO concentration. Projects that pass a COFL2012 model run do not require additional air quality modeling. Projects that fail a COFL2012 model run, however, may still be viable, but will require additional, detailed modeling and possibly project modifications. COFL2012 uses tables of emission factors (EFs) that were derived from numerous runs of the EPA's MOtor Vehicle Emission Simulator (MOVES2010a), which is indicated as the preferred model for near-road modeling of CO.(EPA 2009) COFL2012 then inputs the EFs, along with assumed link configurations, geographical assumptions, and user-inputted traffic information into input files that are run through CAL3QHC Version 2.0 (CAL3QHC2), the EPA's approved near-road dispersion model (EPA 1995). COFL2012 is a brand new Florida CO screening model, written from scratch. This author has written the computer code for COFL2012 in Visual Basic, using Microsoft Visual Studios 2010. Visual Studios utilizes the .net Framework 4. COFL2012 is easy to learn, quick to operate, and has been written to allow for future updates simply and easily, whenever the EPA releases updates to the databases that feed MOVES2010a.

Alzheimer’s disease (AD) and Parkinson’s disease (PD) are defined by neurodegeneration and accumulations of misfolded proteins that spread through the brain in a well characterized manner. In AD these accumulations consist mainly of β-amyloid (Aβ) and tau, while in PD, α-synuclein (α-syn) make up the characteristic lewy pathology.     The general aim of this thesis was to investigate mechanisms associated with neurotoxic peptide activity by Aβ, tau and α-syn in relation to cellular degradation and transfer with a cell-to-cell transfer model system.    We found that intercellular transfer of oligomeric Aβ occurs independently of isoform. However, the amount of transfer correlates with each isoforms ability to resist degradation or cellular clearance. The Aβ1-42 isoform showed particular resistance to clearance, which resulted in higher levels of cell-to-cell transfer of the isoform and lysosomal stress caused by accumulation.    As Aβ accumulations can inhibit the proteasomal degradation we investigated how reduced proteasomal degradation affected neuron-like cells. We found increased levels of phosphorylated tau protein, disturbed microtubule stability and impaired neuritic transport after reduced proteasomal activity. These changes was partly linked to c-Jun and ERK 1/2 kinase activity.    We could also show that α-syn transferred from cell-to-cell in our model system, with a higher degree of transfer for the larger oligomer and fibrillar species. Similar to Aβ, α-syn mainly colocalized with lysosomes, before and after transfer.     Lastly, we have developed our cell-to-cell transfer system into a model suitable for high throughput screening (HTS). The type of cells have been upgraded from SH-SY5Y cells to induced pluripotent stem cells (iPSCs), with a differentiation profile more similar to mature neurons. The next step will be screening a small molecular library for substances with inhibitory effect on cell-to-cell transfer of Aβ peptides.     The importance of the degradative systems in maintaining protein homeostasis and prevent toxic accumulations in general is well known. Our findings shows the importance of these systems for neurodegenerative diseases and also highlight the link between degradation and cell-to-cell transfer. To restore or enhance the degradative systems would be an interesting avenue to treat neurodegenerative diseases. Another way would be to inhibit the transfer of misfolded protein aggregates. By using the HTS model we developed, a candidate substance with good inhibitory effect on transfer can hopefully be found.

This study of 509 (340 female) undergraduate university students in southern Appalachia who completed the Adult Temperament Questionnaire (ATQ) and the State-Trait Anxiety Inventory (STAI), is the first phase in the development of a model to predict risk for stress-related health problems. Results indicate that high negative affect strongly predicted individuals with above average anxiety (OR = 3.7, 95% CI 2.43, 5.64), while high positive affect, effortful control, and sociability predicted that individuals would be low in reported anxiety (OR = .33 [95% CI .25, .44], .29 [95% CI .19, .45], and .69 [95% CI .56, .86], respectively).

Screening models are tools for predicting which stock are the most likely to perform well on a stock market. They do so by examining the financial ratios of the companies behind the stock. The ratios examined by the model are chosen according to the personal preferences of the particular investor. Furthermore, an investor can apply different weights to the different parameters they choose to consider, according to the importance they apply to each included parameter. In this thesis, it is investigated whether a screening model can beat the market average in the long term. It is also explored whether parameter-weight-optimization in the context of equity trading can be used to improve an already existing screening model. More specifically, a starting point is set in a screening model currently in use at a successful asset management firm, through data analysis and an optimization algorithm, it is then examined whether a programmatic approach can identify ways to improve the original screening model by adjusting the parameters it looks at as well as the weights assigned to each parameter. The data set used in the model contains daily price data and annual data on financial ratios for all stocks on the Stockholm Stock Exchange as well as the NASDAQ-100 over the time period 2004-2018. The results indicate that it is possible to beat the market average in the long term. Results further show that a programmatic approach is suitable for optimizing screening models.

<p>  </p> <p>Thrombosis is the pathological formation of a blood clot in the body that blocks blood circulation, leading to high morbidity and mortality rates. Thrombolytic drugs that offer rapid clot dissolution are promising treatments yet current drugs are often associated with limited efficacy and high bleeding risks. While numerous animal thrombosis models have been developed for drug screening, the translation of therapeutic agents into and through clinical trials remains limited. This is largely due to animal models’ poor reproducibility and distinctive physiology to that of humans. <em>In-vitro</em> flow models that utilize both human blood components and physiologically relevant flow conditions can provide for a more representative testing environment to screen thrombolytic drugs. Developing better <em>in-vitro</em> models may not eliminate the need for preclinical animal testing but can help exclude inefficient agents earlier in the drug development pipeline to expedite the drug evaluation process. Existing <em>in-vitro</em> thrombolysis flow models are not ideal as they either adopt over-simplified clot substrates or utilize small-length-scale geometries that insufficiently mimic native hemodynamics. Thus, we propose to first develop a static fluorescently labeled clot lysis assay for an initial high throughput screening of thrombolytic drugs, and ultimately engineer a highly reproducible, physiological scale, flowing clot lysis model for more human relevant drug efficacy evaluation. Developing the static clot lysis assay not only helps to understand the mechanism of how diversified clotting conditions affect clot properties but also offer a chance to well-characterize fluorescence conjugations to fibrins. The ultimate flow model combines an <em>in-vivo</em>-like fluorescence incorporated synthetic clot (FISC) and a human-relevant flow system. Guided by results from static clotting experiments diversified FISCs are fluorescently optimized and fabricated dynamically using a Chandler loop setup at various conditions. The flow system is a tubing-based structure that comprises of a peristaltic pump, and a well-controlled flow chamber to provide for physiological shear and pulsatile levels. Therefore, the proposed synthetic clot model is a versatile platform that can mimic a variety of thrombosis conditions and offer representative drug testing and dosing results across numerous thrombolytic agents.</p>