Analysis of spring break-up and its effects on a biomass feedstock supply chain in northern Michigan

Demand for bio-fuels is expected to increase, due to rising prices of fossil fuels and concerns over greenhouse gas emissions and energy security. The overall cost of biomass energy generation is primarily related to biomass harvesting activity, transportation, and storage. With a commercial-scale cellulosic ethanol processing facility in Kinross Township of Chippewa County, Michigan about to be built, models including a simulation model and an optimization model have been developed to provide decision support for the facility. Both models track cost, emissions and energy consumption. While the optimization model provides guidance for a long-term strategic plan, the simulation model aims to present detailed output for specified operational scenarios over an annual period. Most importantly, the simulation model considers the uncertainty of spring break-up timing, i.e., seasonal road restrictions. Spring break-up timing is important because it will impact the feasibility of harvesting activity and the time duration of transportation restrictions, which significantly changes the availability of feedstock for the processing facility. This thesis focuses on the statistical model of spring break-up used in the simulation model. Spring break-up timing depends on various factors, including temperature, road conditions and soil type, as well as individual decision making processes at the county level. The spring break-up model, based on the historical spring break-up data from 27 counties over the period of 2002-2010, starts by specifying the probability distribution of a particular county’s spring break-up start day and end day, and then relates the spring break-up timing of the other counties in the harvesting zone to the first county. In order to estimate the dependence relationship between counties, regression analyses, including standard linear regression and reduced major axis regression, are conducted. Using realizations (scenarios) of spring break-up generated by the statistical spring breakup model, the simulation model is able to probabilistically evaluate different harvesting and transportation plans to help the bio-fuel facility select the most effective strategy. For early spring break-up, which usually indicates a longer than average break-up period, more log storage is required, total cost increases, and the probability of plant closure increases. The risk of plant closure may be partially offset through increased use of rail transportation, which is not subject to spring break-up restrictions. However, rail availability and rail yard storage may then become limiting factors in the supply chain. Rail use will impact total cost, energy consumption, system-wide CO2 emissions, and the reliability of providing feedstock to the bio-fuel processing facility.

Molecular analysis of the human $\gamma$-chain T cell receptor genes

In our studies we have focused on the issue of variability and diversity of the $\gamma$ (or $\delta)$ chain T cell receptor (TCR) genes by studying cDNA transcripts in peripheral blood mononuclear cells or $\gamma\delta$ TCR+ T cell clones. The significance of these studies lies in the better understanding of the molecular biology of the $\gamma\delta$ T cell receptor as well as in answering the question whether certain molecular forms predominate in $\gamma\delta$ T cells exhibiting specific immunologic functions. We establish that certain $\gamma$-chain TCR genes exhibit particular patterns of rearrangements in cDNA transcripts in normal individuals. V$\gamma$I subgroup were shown to preferentially rearrange to J$\gamma$2C$\gamma$2 gene segments. These preferential VJC rearrangements, may have implications regarding the potential for diversity and polymorphism of the $\gamma$-chain TCR gene. In addition, the preferential association of V$\gamma$I genes with J$\gamma$2C$\gamma$2, which encode a non-disulfide-linked $\gamma\delta$ TCR, suggests that $\gamma$ chains utilizing V$\gamma$I are predominantly expressed as non-disulfide-linked $\gamma\delta$ TCR heterodimers. The implications of this type of expression remain to be determined. We identified two alternative splicing events of the $\gamma$-chain TCR genes occurring in high frequency in all the normal individuals examined. These events may suggest additional mechanisms of regulation and control as well as diversification of $\gamma\delta$ TCR gene expression. The question whether particular forms of $\gamma$ or $\delta$-chain TCR genes are involved in HLA Class I recognition by specific $\gamma\delta$ cytotoxic T cell clones was addressed. Our results indicated that the T cell clones expressed identical $\gamma$ but distinct $\delta$-chains suggesting that the specificity for recognition of HLA-A2 or HLA-A3 may be conferred by the $\delta$-chain TCR. The issue of the degree of diversity and polymorphism of the $\delta$-chain TCR genes in a patient with a primary immunodeficiency (Omenn's syndrome) was addressed. A limited pattern of rearrangements in peripheral blood transcripts was found, suggesting that a limited $\gamma\delta$ TCR repertoire may be expressed in this particular primary immunodeficiency syndrome. Overall, our findings suggest that $\delta$-chain TCR genes exhibit the potential for significant diversity and that there are certain preferential patterns of expression that may be associated with particular immunologic functions. ^

New methods for quantification and analysis of quantitative real-time polymerase chain reaction data

Quantitative real-time polymerase chain reaction (qPCR) is a sensitive gene quantitation method that has been widely used in the biological and biomedical fields. The currently used methods for PCR data analysis, including the threshold cycle (CT) method, linear and non-linear model fitting methods, all require subtracting background fluorescence. However, the removal of background fluorescence is usually inaccurate, and therefore can distort results. Here, we propose a new method, the taking-difference linear regression method, to overcome this limitation. Briefly, for each two consecutive PCR cycles, we subtracted the fluorescence in the former cycle from that in the later cycle, transforming the n cycle raw data into n-1 cycle data. Then linear regression was applied to the natural logarithm of the transformed data. Finally, amplification efficiencies and the initial DNA molecular numbers were calculated for each PCR run. To evaluate this new method, we compared it in terms of accuracy and precision with the original linear regression method with three background corrections, being the mean of cycles 1-3, the mean of cycles 3-7, and the minimum. Three criteria, including threshold identification, max R2, and max slope, were employed to search for target data points. Considering that PCR data are time series data, we also applied linear mixed models. Collectively, when the threshold identification criterion was applied and when the linear mixed model was adopted, the taking-difference linear regression method was superior as it gave an accurate estimation of initial DNA amount and a reasonable estimation of PCR amplification efficiencies. When the criteria of max R2 and max slope were used, the original linear regression method gave an accurate estimation of initial DNA amount. Overall, the taking-difference linear regression method avoids the error in subtracting an unknown background and thus it is theoretically more accurate and reliable. This method is easy to perform and the taking-difference strategy can be extended to all current methods for qPCR data analysis.^

Longitudinal categorical data analysis: A continuous -time Markov chain approach

In this dissertation, we propose a continuous-time Markov chain model to examine the longitudinal data that have three categories in the outcome variable. The advantage of this model is that it permits a different number of measurements for each subject and the duration between two consecutive time points of measurements can be irregular. Using the maximum likelihood principle, we can estimate the transition probability between two time points. By using the information provided by the independent variables, this model can also estimate the transition probability for each subject. The Monte Carlo simulation method will be used to investigate the goodness of model fitting compared with that obtained from other models. A public health example will be used to demonstrate the application of this method. ^

Shadow Analysis of Soil Surface Roughness Compared to the Chain Set Method and Direct Measurement of Micro-relief.

Erosion potential and the effects of tillage can be evaluated from quantitative descriptions of soil surface roughness. The present study therefore aimed to fill the need for a reliable, low-cost and convenient method to measure that parameter. Based on the interpretation of micro-topographic shadows, this new procedure is primarily designed for use in the field after tillage. The principle underlying shadow analysis is the direct relationship between soil surface roughness and the shadows cast by soil structures under fixed sunlight conditions. The results obtained with this method were compared to the statistical indexes used to interpret field readings recorded by a pin meter. The tests were conducted on 4-m2 sandy loam and sandy clay loam plots divided into 1-m2 subplots tilled with three different tools: chisel, tiller and roller. The highly significant correlation between the statistical indexes and shadow analysis results obtained in the laboratory as well as in the field for all the soil?tool combinations proved that both variability (CV) and dispersion (SD) are accommodated by the new method. This procedure simplifies the interpretation of soil surface roughness and shortens the time involved in field operations by a factor ranging from 12 to 20.

Analysis of Respiratory Chain Regulation in Roots of Soybean Seedlings1

Changes in the respiratory rate and the contribution of the cytochrome (Cyt) c oxidase and alternative oxidase (COX and AOX, respectively) were investigated in soybean (Glycine max L. cv Stevens) root seedlings using the 18O-discrimination method. In 4-d-old roots respiration proceeded almost entirely via COX, but by d 17 more than 50% of the flux occurred via AOX. During this period the capacity of COX, the theoretical yield of ATP synthesis, and the root relative growth rate all decreased substantially. In extracts from whole roots of different ages, the ubiquinone pool was maintained at 50% to 60% reduction, whereas pyruvate content fluctuated without a consistent trend. In whole-root immunoblots, AOX protein was largely in the reduced, active form at 7 and 17 d but was partially oxidized at 4 d. In isolated mitochondria, Cyt pathway and succinate dehydrogenase capacities and COX I protein abundance decreased with root age, whereas both AOX capacity and protein abundance remained unchanged. The amount of mitochondrial protein on a dry-mass basis did not vary significantly with root age. It is concluded that decreases in whole-root respiration during growth of soybean seedlings can be largely explained by decreases in maximal rates of electron transport via COX. Flux via AOX is increased so that the ubiquinone pool is maintained in a moderately reduced state.

Cloning and comparative analysis of the human pre-T-cell receptor alpha-chain gene.

In immature T cells the T-cell receptor (TCR) beta-chain gene is rearranged and expressed before the TCR alpha-chain gene. At this stage TCR beta chain can form disulfide-linked heterodimers with the pre-T-cell receptor alpha chain (pTalpha). Using the recently isolated murine pTalpha cDNA as a probe, we have isolated the human pTalpha cDNA. The complete nucleotide sequence predicts a mature protein of 282 aa consisting of an extracellular immunoglobulin-like domain, a connecting peptide, a transmembrane region, and a long cytoplasmic tail. Amino acid sequence comparison of human pTalpha with the mouse pTalpha molecule reveals high sequence homology in the extracellular as well as the transmembrane region. In contrast, the cytoplasmic region differs in amino acid composition and in length from the murine homologue. The human pTalpha gene is expressed in immature but not mature T cells and is located at the p21.2-p12 region of the short arm of chromosome 6.

Causal Maps and Indirect Influences Analysis in the Diagnosis of Second-Home Tourism Impacts

This paper proposes a method for diagnosing the impacts of second-home tourism and illustrates it for a Mediterranean Spanish destination. This method proposes the application of network analysis software to the analysis of causal maps in order to create a causal network model based on stakeholder-identified impacts. The main innovation is the analysis of indirect relations in causal maps for the identification of the most influential nodes in the model. The results show that the most influential nodes are of a political nature, which contradicts previous diagnoses identifying technical planning as the ultimate cause of problems.

Young men and drugs in Manhattan : a causal analysis /

Mode of access: Internet.

Sequences of immunoglobulin chains : tabulation and analysis of amino acid sequences of precursors, V-regions, C-regions, J-chain and -microglobulins /

1976 ed. issued under title: Variable regions of immunoglobulin chains.