The duration of capture and restraint during anesthesia and euthanasia influences glucocorticoid levels in male golden hamsters

Deep litter has been shown to decrease stereotypic wire-gnawing in male golden hamsters, suggesting that increased litter depth may be associated with decreased chronic stress levels. To determine the relationship between litter depth and stress levels in hamsters, the authors measured serum levels of corticosterone, cortisol, and ACTH in male golden hamsters kept in cages with three different depths of litter. The duration of handling the hamsters significantly increased the concentrations of corticosterone, cortisol, and the ratio of cortisol/corticosterone. It took longer to catch hamsters housed in cages with deep litter and the ACTH levels were higher in these hamsters. The positive effect of the enrichment (deep litter) was diminished by methodological problems during handling/anesthesia.

Approach to carbon dioxide capture and storage at ambient conditions

Carbon dioxide (CO2) capture and storage experiments were conducted at ambient conditions in varying weight % sodium carbonate (Na2CO3) solutions. Experiments were conducted to determine the optimal amount of Na2CO3 in solution for CO2 absorption. It was concluded that a 2% Na2CO3 solution, by weight, was the most efficient solution. The 2% Na2CO3 solution is able to absorb 0.5 g CO2/g Na2CO3. These results led to studies to determine how the gas bubble size affected carbon dioxide absorption in the solution. Studies were conducted using ASTM porosity gas diffusers to vary the bubble size. Gas diffusers with porosities of fine, medium, and extra coarse were used. Results found that the medium porosity gas diffuser was the most efficient at absorbing CO2 at 50%. Variation in the bubble size concluded that absorption of carbon dioxide into the sodium carbonate solution does depend on the bubble size, thus is mass transfer limited. Once the capture stage was optimized (amount of Na2CO3 in solution and bubble size), the next step was to determine if carbon dioxide could be stored as a calcium carbonate mineral using calcium rich industrial waste and if the sodium carbonate solution could be simultaneously regenerated. Studies of CO2 sequestration at ambient conditions have shown that it is possible to permanently sequester CO2 in the form of calcium carbonate using a calcium rich industrial waste. Studies have also shown that it is possible to regenerate a fraction of the sodium carbonate solution.

A Novel Approach to Carbon Dioxide Capture and Storage

The novel approach to carbon capture and storage (CCS) described in this dissertation is a significant departure from the conventional approach to CCS. The novel approach uses a sodium carbonate solution to first capture CO2 from post combustion flue gas streams. The captured CO2 is then reacted with an alkaline industrial waste material, at ambient conditions, to regenerate the carbonate solution and permanently store the CO2 in the form of an added value carbonate mineral. Conventional CCS makes use of a hazardous amine solution for CO2 capture, a costly thermal regeneration stage, and the underground storage of supercritical CO2. The objective of the present dissertation was to examine each individual stage (capture and storage) of the proposed approach to CCS. Study of the capture stage found that a 2% w/w sodium carbonate solution was optimal for CO2 absorption in the present system. The 2% solution yielded the best tradeoff between the CO2 absorption rate and the CO2 absorption capacity of the solutions tested. Examination of CO2 absorption in the presence of flue gas impurities (NOx and SOx) found that carbonate solutions possess a significant advantage over amine solutions, that they could be used for multi-pollutant capture. All the NOx and SOx fed to the carbonate solution was able to be captured. Optimization studies found that it was possible to increase the absorption rate of CO2 into the carbonate solution by adding a surfactant to the solution to chemically alter the gas bubble size. The absorption rate of CO2 was increased by as much as 14%. Three coal combustion fly ash materials were chosen as the alkaline industrial waste materials to study the storage CO2 and regeneration the absorbent. X-ray diffraction analysis on reacted fly ash samples confirmed that the captured CO2 reacts with the fly ash materials to form a carbonate mineral, specifically calcite. Studies found that after a five day reaction time, 75% utilization of the waste material for CO2 storage could be achieved, while regenerating the absorbent. The regenerated absorbent exhibited a nearly identical CO2 absorption capacity and CO2 absorption rate as a fresh Na2CO3 solution.

Evaluation of a Bayesian MCMC Random Effects Inference Methodology for Capture-Mark-Recapture Data

Monte Carlo simulation was used to evaluate properties of a simple Bayesian MCMC analysis of the random effects model for single group Cormack-Jolly-Seber capture-recapture data. The MCMC method is applied to the model via a logit link, so parameters p, S are on a logit scale, where logit(S) is assumed to have, and is generated from, a normal distribution with mean μ and variance σ2 . Marginal prior distributions on logit(p) and μ were independent normal with mean zero and standard deviation 1.75 for logit(p) and 100 for μ ; hence minimally informative. Marginal prior distribution on σ2 was placed on τ2=1/σ2 as a gamma distribution with α=β=0.001 . The study design has 432 points spread over 5 factors: occasions (t) , new releases per occasion (u), p, μ , and σ . At each design point 100 independent trials were completed (hence 43,200 trials in total), each with sample size n=10,000 from the parameter posterior distribution. At 128 of these design points comparisons are made to previously reported results from a method of moments procedure. We looked at properties of point and interval inference on μ , and σ based on the posterior mean, median, and mode and equal-tailed 95% credibility interval. Bayesian inference did very well for the parameter μ , but under the conditions used here, MCMC inference performance for σ was mixed: poor for sparse data (i.e., only 7 occasions) or σ=0 , but good when there were sufficient data and not small σ .