Density functional theory BLYP (Becke's exchange and Lee-Yang-Parr's correlation functionals), ab initio Hartree-Fock (HF) and hybrid DFT/HF B3LYP calculations were carried out to study the structure and vibrational spectra of quadricyclane. The BLYP/6-31G* and scaled HF/6-31G* frequencies correspond well with each other and with available experimental assignment of the fundamental vibrational modes. Based on conformity between the calculated and experimental results, a plausible assignment of two remaining a1 modes and all non-CH stretching a2, b1, and b2 modes is proposed.

Thesis (Ed.D.)--Boston University / This quasi-experimental study was undertaken to determine the effect of context on learning a functional living skill for individuals with cognitive deficits associated with the negative symptoms of schizophrenia. Forty-six people (ages 27-62) with non-paranoid schizophrenia or schizoaffective disorder were matched on cognitive level (Allen Cognitive Level Screen- 90, Allen, Kerberg, & Bums, 1992), cooking experience, and living situation (group home or apartment). They were then randomly assigned to one of two treatment conditions, clinic or home. All participants were evaluated and taught basic cooking skills in either the clinic or their homes. Finally, all participants were evaluated in their homes. Both groups scored significantly higher after cooking lessons (t=5.57, df = 21, p<.0001 for those in the clinic; t = 7.81. df = 21, p<.0002 for those learning at home); there was no significant difference between the two groups in where the learning took place (B = -1.8, df = 42, p<0.23). Those who learned in the clinic scored lower than the home group when tested at home (t = -2.07, df = 42, p<.0489) although this result must be accepted with caution because of a significant difference between the two groups on the first assessment of cooking skill. Additional questions yielded the following: there was a positive correlation between cognitive level and cooking skill (df = 44, r =.55, p <.001); there was a positive correlation between cognitive level and transfer of learning (df = 21, F = 52.49, p < .0000); no significant correlation was found between amount of practice and increase in cooking skill ( df = 27, r = .256, r2 = .066). People with cognitive deficits associated with schizophrenia can learn a specific functional living skill in different contexts. Qualitative aspects of those contexts are discussed. Further research is recommended to describe/understand transfer of learning from one context to another. Cognitive level is highly correlated with both ability to learn and ability to transfer learning. Additional research is recommended to adequately describe the effect of practice on learning a functional living skill. Implications for treatment and suggestions for clinical research are presented.

No description available.

The synthesis of novel polyurethanes for use in blood contacting applications was investigated. A series of polyurethanes containing biologically active groups in the hard segment was synthesized. Sulphonate-containing polyurethanes were produced using a sulphonated chain extender (biphenyl diamino disulphonic acid) and these polymers were subsequently reacted to incorporate arginine methyl ester groups via sulphonamide bonds. The novel polyurethanes were initially evaluated using elemental sulphur analysis and nitrogen analysis, gel permeation chromatography and Fourier transform infrared spectroscopy to verify reaction of the sulphonated chain extender and addition of arginine methyl ester. Three sulphonated polyurethanes covering a range of sulphonate content were produced by varying the prepolymer and hard segment lengths. These three polymers and the three corresponding arginine methyl ester containing polymers were characterized to relate both bulk and surface structure to physical and biological properties. Elemental analysis, gel permeation chromatography and Fourier transform infrared spectroscopy were used to characterize the molecular structure. These techniques provided results consistent with the expected reaction mechanisms. Electron spectroscopy for chemical analysis and contact angle measurements were used to analyse the surface structure. Preliminary contact angle data indicate that the sulphonated polyurethane surfaces are hydrophilic, but further investigation is required before a firm conclusion can be reached. ESCA results indicate that while soft segment surface enrichment is taking place there are significant numbers of sulphonate groups present at the polyurethane surface. Mechanically these polymers have similar ultimate tensile strength but lower elongation than polyurethanes produced using aliphatic diamines, like ethylene diamine. This is probably due to increased microphase segregation arising partly from incompatibility of the aromatic chain extender with the aliphatic soft segment and possibly partly to ion cluster formation. The incorporation of arginine methyl ester groups increases both the elongation and the tensile strength, probably due to reduced phase segregation. Fibrinogen adsorption experiments in plasma were conducted to evaluate the blood response of these polymers. The plasma adsorption "isotherms" for the novel polyurethanes do not show transient fibrinogen adsorption (Vroman effect) which has been observed on a number of other surfaces including a wide range of polyurethanes. Instead, the initially adsorbed fibrinogen remains adsorbed. Also the levels of fibrinogen adsorption from plasma are three to four times greater than observed on previously studied surfaces. Conversion of some of the sulphonate groups to sulphonamide-bonded arginine methyl ester restores the Vroman effect and results in lower levels of retained fibrinogen. These data suggest the possibility of a specific interaction between sulphonate groups and fibrinogen. / Thesis / Master of Engineering (ME)

No description available.

Trait-based approaches are useful in ecological research because of their potential ability to predict species responses from patterns present in the community and to infer mechanisms driving community assembly. Current approaches for fishes are lacking traits across all five fundamental niche dimensions (i.e. habitat, life history, trophic, metabolic and defense). This study quantified a broad range of fish functional traits across all five niche dimensions (commonly used traits and novel traits), quantified intra- and interspecific variation for each trait, tested for relationships among traits within and among niche dimensions, tested for phylogenetic conservatism of traits and assessed trait-environment relationships for a subset of these traits under two different contexts. Approximately one third of the quantified traits exhibited greater intraspecific variation than interspecific variation and were not included in subsequent analyses. There were similarities between phylogeny and trait dendrograms for all traits, and habitat, metabolic and defense traits. The traits identified in chapter 2 were able to explain species responses during different flow periods in two intermittent streams as well as species-specific differences in host microbiome at the onset of drought in one intermittent stream. The novel traits identified in chapter 2 did contribute to our understanding of the community assembly dynamics in chapter 3.

Doctor of Philosophy / Department of Statistics / Suzanne Dubnicka / Christopher Vahl / Photoplethysmograph sensors use a light-based technology to sense the rate of blood flow as controlled by the heart’s pumping action. This allows for a graphical display of a patient’s pulse wave form and the description of its key features. A person’s pulse wave has been proposed as a tool in a wide variety of applications. For example, it could be used to diagnose the cause of coldness felt in the extremities or to measure stress levels while performing certain tasks. It could also be applied to quantify the risk of heart disease in the general population. In the present work, we explore its use for identity authentication. First, we visualize the pulse waves from individual patients using functional boxplots which assess the overall behavior and identify unusual observations. Functional boxplots are also shown to be helpful in preprocessing the data by shifting individual pulse waves to a proper starting point. We then employ functional analysis of variance (FANOVA) and permutation tests to demonstrate that the identities of a group of subjects could be differentiated and compared by their pulse wave forms. One of the primary tasks of the project is to confirm the identity of a person, i.e., we must decide if a given person is whom they claim to be. We used an equivalence test to determine whether the pulse wave of the person under verification and the actual person were close enough to be considered equivalent. A nonparametric bootstrap functional equivalence test was applied to evaluate equivalence by constructing point-wise confidence intervals for the metric of identity assurance. We also proposed new testing procedures, including the way of building the equivalence hypothesis and test statistics, determination of evaluation range and equivalence bands, to authenticate the identity.

We study the half-hourly electricity generation by coal and by gas in the UK over a period of three years from 2012 to 2014. As a highly frequent time series, daily cycles along with seasonality and trend across days can be seen in the data for each fuel. Taylor (2003), Taylor et al. (2006), and Taylor (2008) studied time series of the similar features by introducing double seasonality into the methods for a single univariate time series. As we are interested in the continuous variation in the generation within a day, the half-hourly observations within a day are considered as a continuous function. In this way, a time series of half-hourly discrete observations is transformed into a time series of daily functions. The idea of a time series of functions can also seen in Shang (2013), Shang and Hyndman (2011) and Hyndman and Ullah (2007). We improve their methods in a few ways. Firstly, we identify the systematic effect due to the factors that take effect in a long term, such as weather and prices of fuels, and the intrinsic differences between the days of the week. The systematic effect is modeled and removed before we study the day-by-day random variation in the functions. Secondly, we extend functional principal component analysis (PCA), which was applied on one group of functions in Shang (2013), Shang and Hyndman (2011) and Hyndman and Ullah (2007), into partial common PCA, in order to consider the covariance structures of two groups of functions and their similarities. A test on the goodness of the approximation to the functions given by the common eigenfunctions is also proposed. The idea of bootstrapping residuals from the approximation seen in Shang (2014) is employed but is improved with non-overlapping blocks and moving blocks of residuals. Thirdly, we use a vector autoregressive (VAR) model, which is a multivariate approach, to model the scores on common eigenfunctions of a group such that the cross-correlation between the scores can be considered. We include Lasso penalties in the VAR model to select the significant covariates and refit the selection with ordinary least squares to reduce the bias. Our method is compared with the stepwise procedure by Pfaff (2007), and is proved to be less variable and more accurate on estimation and prediction. Finally, we propose the method to give the point forecasts of the daily functions. It is more complicated than the methods of Shang (2013), Shang and Hyndman (2011) and Hyndman and Ullah (2007) as the systematic effect needs to be included. An adjustment interval is also given along with a point forecast, which represents the range within which the true function might vary. Our methods to give the point forecast and the adjustment interval include the information updating after the training period, which is not considered in the classical predicting equations of VAR and GARCH seen in Tsay (2013) and Engle and Bollerslev (1986).

The non-interacting, nonuniform electron gas exhibits simplifications in two dimensions, that are of particular interest in the application of density functional theory. The results of linear response theory for an attractive impurity in a two-dimensional gas have been shown to be surprisingly accurate even though there are bound states, and were shown to be exact in the high density limit (Zaremba et al. Phys. Rev. B, 71:125323, 2005 and Zaremba et al. Phys. Rev. Lett., 90(4):046801, 2003). The density resulting from linear response theory and the Thomas-Fermi approximation coincide in the high density limit. As an alternative to linear response theory, the Kirzhnits gradient expansion gives corrections to Thomas-Fermi in gradients of the potential. In two dimensions, all of the gradient corrections vanish at zero temperature, which is a new result presented in this work. We have performed numerical calculations which show that while Thomas-Fermi appears to be a surprisingly accurate approximation in two dimensions, it is not exact. The differences between two and three dimensions that lead to the vanishing of the gradient corrections, however, are of great interest since these may lead to better understanding and simplifications of the corresponding three-dimensional problem. / Thesis (Master, Physics, Engineering Physics and Astronomy) -- Queen's University, 2007-11-07 09:47:00.316

The thesis consists of two coherent projects. The first project presents the results of evaluating salinity tolerance in barley using growth curve analysis where different growth trajectories are observed within barley families. The study of salinity tolerance in plants is crucial to understanding plant growth and productivity. Because fully-automated smarthouses with conveyor systems allow non-destructive and high-throughput phenotyping of large number of plants, it is now possible to apply advanced statistical tools to analyze daily measurements and to study salinity tolerance. To compare different growth patterns of barley variates, we use functional data analysis techniques to analyze the daily projected shoot areas. In particular, we apply the curve registration method to align all the curves from the same barley family in order to summarize the family-wise features. We also illustrate how to use statistical modeling to account for spatial variation in microclimate in smarthouses and for temporal variation across runs, which is crucial for identifying traits of the barley variates. In our analysis, we show that the concentrations of sodium and potassium in leaves are negatively correlated, and their interactions are associated with the degree of salinity tolerance. The second project studies change-points detection methods in extremes when multiple time series data are available. Motived by the scientific question of whether the chances to experience extreme weather are different in different seasons of a year, we develop a change-points detection model to study changes in extremes or in the tail of a distribution. Most of existing models identify seasons from multiple yearly time series assuming a season or a change-point location remains exactly the same across years. In this work, we propose a random effect model that allows the change-point to vary from year to year, following a given distribution. Both parametric and nonparametric methods are developed for detecting single and multiple change-points, and their performance is compared by simulation studies. The proposed method is illustrated using sea surface temperature data and the tail distributions before and after the change-point from two models, with and without random effects are compared.