An artificial neural network model for prediction of quality characteristics of apples during convective dehydration

In this study, the effects of hot-air drying conditions on color, water holding capacity, and total phenolic content of dried apple were investigated using artificial neural network as an intelligent modeling system. After that, a genetic algorithm was used to optimize the drying conditions. Apples were dried at different temperatures (40, 60, and 80 °C) and at three air flow-rates (0.5, 1, and 1.5 m/s). Applying the leave-one-out cross validation methodology, simulated and experimental data were in good agreement presenting an error < 2.4 %. Quality index optimal values were found at 62.9 °C and 1.0 m/s using genetic algorithm.

Artificial neural networks (ANN): prediction of sensory measurements from instrumental data

The objective of this study was to predict by means of Artificial Neural Network (ANN), multilayer perceptrons, the texture attributes of light cheesecurds perceived by trained judges based on instrumental texture measurements. Inputs to the network were the instrumental texture measurements of light cheesecurd (imitative and fundamental parameters). Output variables were the sensory attributes consistency and spreadability. Nine light cheesecurd formulations composed of different combinations of fat and water were evaluated. The measurements obtained by the instrumental and sensory analyses of these formulations constituted the data set used for training and validation of the network. Network training was performed using a back-propagation algorithm. The network architecture selected was composed of 8-3-9-2 neurons in its layers, which quickly and accurately predicted the sensory texture attributes studied, showing a high correlation between the predicted and experimental values for the validation data set and excellent generalization ability, with a validation RMSE of 0.0506.

Analysis of Phase Separator Design Criteria Using Computational Fluid Dynamics

Gravitational phase separation is a common unit operation found in most large-scale chemical processes. The need for phase separation can arise e.g. from product purification or protection of downstream equipment. In gravitational phase separation, the phases separate without the application of an external force. This is achieved in vessels where the flow velocity is lowered substantially compared to pipe flow. If the velocity is low enough, the denser phase settles towards the bottom of the vessel while the lighter phase rises. To find optimal configurations for gravitational phase separator vessels, several different geometrical and internal design features were evaluated based on simulations using OpenFOAM computational fluid dynamics (CFD) software. The studied features included inlet distributors, vessel dimensions, demister configurations and gas phase outlet configurations. Simulations were conducted as single phase steady state calculations. For comparison, additional simulations were performed as dynamic single and two-phase calculations. The steady state single phase calculations provided indications on preferred configurations for most above mentioned features. The results of the dynamic simulations supported the utilization of the computationally faster steady state model as a practical engineering tool. However, the two-phase model provides more truthful results especially with flows where a single phase does not determine the flow characteristics.

Computational models for and from biology : simple gene assembly and reaction systems

The advancement of science and technology makes it clear that no single perspective is any longer sufficient to describe the true nature of any phenomenon. That is why the interdisciplinary research is gaining more attention overtime. An excellent example of this type of research is natural computing which stands on the borderline between biology and computer science. The contribution of research done in natural computing is twofold: on one hand, it sheds light into how nature works and how it processes information and, on the other hand, it provides some guidelines on how to design bio-inspired technologies. The first direction in this thesis focuses on a nature-inspired process called gene assembly in ciliates. The second one studies reaction systems, as a modeling framework with its rationale built upon the biochemical interactions happening within a cell. The process of gene assembly in ciliates has attracted a lot of attention as a research topic in the past 15 years. Two main modelling frameworks have been initially proposed in the end of 1990s to capture ciliates’ gene assembly process, namely the intermolecular model and the intramolecular model. They were followed by other model proposals such as templatebased assembly and DNA rearrangement pathways recombination models. In this thesis we are interested in a variation of the intramolecular model called simple gene assembly model, which focuses on the simplest possible folds in the assembly process. We propose a new framework called directed overlap-inclusion (DOI) graphs to overcome the limitations that previously introduced models faced in capturing all the combinatorial details of the simple gene assembly process. We investigate a number of combinatorial properties of these graphs, including a necessary property in terms of forbidden induced subgraphs. We also introduce DOI graph-based rewriting rules that capture all the operations of the simple gene assembly model and prove that they are equivalent to the string-based formalization of the model. Reaction systems (RS) is another nature-inspired modeling framework that is studied in this thesis. Reaction systems’ rationale is based upon two main regulation mechanisms, facilitation and inhibition, which control the interactions between biochemical reactions. Reaction systems is a complementary modeling framework to traditional quantitative frameworks, focusing on explicit cause-effect relationships between reactions. The explicit formulation of facilitation and inhibition mechanisms behind reactions, as well as the focus on interactions between reactions (rather than dynamics of concentrations) makes their applicability potentially wide and useful beyond biological case studies. In this thesis, we construct a reaction system model corresponding to the heat shock response mechanism based on a novel concept of dominance graph that captures the competition on resources in the ODE model. We also introduce for RS various concepts inspired by biology, e.g., mass conservation, steady state, periodicity, etc., to do model checking of the reaction systems based models. We prove that the complexity of the decision problems related to these properties varies from P to NP- and coNP-complete to PSPACE-complete. We further focus on the mass conservation relation in an RS and introduce the conservation dependency graph to capture the relation between the species and also propose an algorithm to list the conserved sets of a given reaction system.

Computational Market Dynamics of Virtual Economies

The last two decades have provided a vast opportunity to live and explore the compulsive imaginary world or virtual world through massively multiplayer online role-playing games (MMORPGs). MMORPG gives a wide range of opportunities to its users to participate with multi-players on the same platform, to communicate and to do real time actions. There is a virtual economy in these games which is largely player-driven. In-game currency provides its users to build up their Avatars, to buy or sell the necessary goods to play, survive in the games and so on. As a part of virtual economies generated through EVE Online, this thesis mainly focuses on how the prices of the minerals in EVE Online behave by applying the Jabłonska- Capasso-Morale (JCM) mathematical simulation model. It is to verify up to what degree the model can reproduce the virtual economy behavior. The model is applied to buy and sell prices of two minerals namely, isogen and morphite. The simulation results demonstrate that JCM model ts reasonably well to the mineral prices, which lets us conclude that virtual economies behave similarly to the real ones.

Prediction of neurodevelopment and neuromotor trajectories in very preterm born children up to 11 years of age: PIPARI Study

Very preterm birth is a risk for brain injury and abnormal neurodevelopment. While the incidence of cerebral palsy has decreased due to advances in perinatal and neonatal care, the rate of less severe neuromotor problems continues to be high in very prematurely born children. Neonatal brain imaging can aid in identifying children for closer follow-up and in providing parents information on developmental risks. This thesis aimed to study the predictive value of structural brain magnetic resonance imaging (MRI) at term age, serial neonatal cranial ultrasound (cUS), and structured neurological examinations during the longitudinal follow-up for the neurodevelopment of very preterm born children up to 11 years of age as a part of the PIPARI Study (The Development and Functioning of Very Low Birth Weight Infants from Infancy to School Age). A further aim was to describe the associations between regional brain volumes and long-term neuromotor profile. The prospective follow-up comprised of the assessment of neurosensory development at 2 years of corrected age, cognitive development at 5 years of chronological age, and neuromotor development at 11 years of age. Neonatal brain imaging and structured neurological examinations predicted neurodevelopment at all age-points. The combination of neurological examination and brain MRI or cUS improved the predictive value of neonatal brain imaging alone. Decreased brain volumes associated with neuromotor performance. At the age of 11 years, the majority of the very preterm born children had age-appropriate neuromotor development and after-school sporting activities. Long-term clinical follow-up is recommended at least for all very preterm infants with major brain pathologies.

Exploring the use of prediction and summarization to increase students' listening and reading comprehension /

This study examined the effect of expHcitly instructing students to use a repertoire of reading comprehension strategies. Specifically, this study examined whether providing students with a "predictive story-frame" which combined the use of prediction and summarization strategies improved their reading comprehension relative to providing students with generic instruction on prediction and summarization. Results were examined in terms of instructional condition and reading ability. Students from 2 grade 4 classes participated in this study. The reading component of the Canadian Achievement Tests, Second Edition (CAT/2) was used to identify students as either "average or above average" or "below average" readers. Students received either strategic predication and summarization instruction (story-frame) or generic prediction and summarization instruction (notepad). Students were provided with new but comparable stories for each session. For both groups, the researcher modelled the strategic tools and provided guided practice, independent practice, and independent reading sessions. Comprehension was measured with an immediate and 1-week delayed comprehension test for each of the 4 stories, hi addition, students participated in a 1- week delayed interview, where they were asked to retell the story and to answer questions about the central elements (character, setting, problem, solution, beginning, middle, and ending events) of each story. There were significant differences, with medium to large effect sizes, in comprehension and recall scores as a fimction of both instructional condition and reading ability. Students in the story-frame condition outperformed students in the notepad condition, and average to above average readers performed better than below average readers. Students in the story-frame condition outperformed students in the notepad condition on the comprehension tests and on the oral retellings when teacher modelling and guidance were present. In the cued recall sessions, students in the story-frame instructional condition recalled more correct information and generated fewer errors than students in the notepad condition. Average to above average readers performed better than below average readers across comprehension and retelling measures. The majority of students in both instructional conditions reported that they would use their strategic tool again.

Personality traits and personal values : an investigation into the importance of each in the prediction of behaviour /

Personality traits and personal values are two important domains of individual differences. Traits are enduring and distinguishable patterns of behaviour whereas values are societally taught, stable, individual preferences that guide behaviour in order to reach a specific end state. The purpose of the present study was to investigate the relations between self and peer report within the domains of personality traits and values, to examine the correlations between values and traits, and to explore the amount of incremental validity of traits and values in predicting behaviour. Two hundred and fiftytwo men and women from a university setting completed self and peer reports on three questionnaires. In order to assess personality traits, the HEXACO-PI (Lee & Ashton, 2004) was used to identify levels of 6 major dimensions of personality in participants. To assess values, the Schwartz Value Survey (Schwartz, 1992) was used to identify the importance each participant placed on each of Schwartz's 10 value types. To measure behaviour, a Behavior Scale, created by Bardi and Schwartz (2003), consisting of items designed to measure the frequency of value-expressive behaviour was used. As expected, correlations between self and peer reports for the personality scales were high indicating that personality traits are easily observable to other people. Correlations between self and peer reports for the values and behaviour scales were only moderate, suggesting that some goals, and behaviours expressive of those goals, may not always be observable to others. Consistent with previous research, there were many strong correlations between traits and values. In addition to the similarities with past research, the present study found that the personality factor Honesty-Humility was correlated strongly with values scales (with five correlations exceeding .25). In the prediction of behaviour, it was found that both personahty and values were able to account for significant and similar amounts of variance. Personality outpredicted values for some behaviours, but the opposite was true of other behaviours. Each domain provided incremental validity beyond the other domain. The impUcations for these findings, along with limitations, and possibilities for future research are also discussed.

Autonomic prediction of error-related ERP components in perceptual and conceptual tasks in older and younger adults

In studies of cognitive processing, the allocation of attention has been consistently linked to subtle, phasic adjustments in autonomic control. Both autonomic control of heart rate and control of the allocation of attention are known to decline with age. It is not known, however, whether characteristic individual differences in autonomic control and the ability to control attention are closely linked. To test this, a measure of parasympathetic function, vagal tone (VT) was computed from cardiac recordings from older and younger adults taken before and during performance of two attentiondemanding tasks - the Eriksen visual flanker task and the source memory task. Both tasks elicited event-related potentials (ERPs) that accompany errors, i.e., error-related negativities (ERNs) and error positivities (Pe's). The ERN is a negative deflection in the ERP signal, time-locked to responses made on incorrect trials, likely generated in the anterior cingulate. It is followed immediately by the Pe, a broad, positive deflection which may reflect conscious awareness of having committed an error. Age-attenuation ofERN amplitude has previously been found in paradigms with simple stimulus-response mappings, such as the flanker task, but has rarely been examined in more complex, conceptual tasks. Until now, there have been no reports of its being investigated in a source monitoring task. Age-attenuation of the ERN component was observed in both tasks. Results also indicated that the ERNs generated in these two tasks were generally comparable for young adults. For older adults, however, the ERN from the source monitoring task was not only shallower, but incorporated more frontal processing, apparently reflecting task demands. The error positivities elicited by 3 the two tasks were not comparable, however, and age-attenuation of the Pe was seen only in the more perceptual flanker task. For younger adults, it was Pe scalp topography that seemed to reflect task demands, being maximal over central parietal areas in the flanker task, but over very frontal areas in the source monitoring task. With respect to vagal tone, in the flanker task, neither the number of errors nor ERP amplitudes were predicted by baseline or on-task vagal tone measures. However, in the more difficult source memory task, lower VT was marginally associated with greater numbers of source memory errors in the older group. Thus, for older adults, relatively low levels of parasympathetic control over cardiac response coincided with poorer source memory discrimination. In both groups, lower levels of baseline VT were associated with larger amplitude ERNs, and smaller amplitude Pe's. Thus, low VT was associated in a conceptual task with a greater "emergency response" to errors, and at the same time, reduced awareness of having made them. The efficiency of an individual's complex cognitive processing was therefore associated with the flexibility of parasympathetic control of heart rate, in response to a cognitively challenging task.

Bio-inspired optimization & sampling technique for side-chain packing in MCCE

The prediction of proteins' conformation helps to understand their exhibited functions, allows for modeling and allows for the possible synthesis of the studied protein. Our research is focused on a sub-problem of protein folding known as side-chain packing. Its computational complexity has been proven to be NP-Hard. The motivation behind our study is to offer the scientific community a means to obtain faster conformation approximations for small to large proteins over currently available methods. As the size of proteins increases, current techniques become unusable due to the exponential nature of the problem. We investigated the capabilities of a hybrid genetic algorithm / simulated annealing technique to predict the low-energy conformational states of various sized proteins and to generate statistical distributions of the studied proteins' molecular ensemble for pKa predictions. Our algorithm produced errors to experimental results within .acceptable margins and offered considerable speed up depending on the protein and on the rotameric states' resolution used.

Flow regime prediction via froude number calculation in a rock-bedded stream

Mathematical predictions of flow conditions along a steep gradient rock bedded stream are examined. Stream gage discharge data and Manning's Equation are used to calculate alternative velocities, and subsequently Froude Numbers, assuming varying values of velocity coefficient, full depth or depth adjusted for vertical flow separation. Comparison of the results with photos show that Froude Numbers calculated from velocities derived from Manning's Equation, assuming a velocity coefficient of 1.30 and full depth, most accurately predict flow conditions, when supercritical flow is defined as Froude Number values above 0.84. Calculated Froude Number values between 0.8 and 1.1 correlate well with observed transitional flow, defined as the first appearance of small diagonal waves. Transitions from subcritical through transitional to clearly supercritical flow are predictable. Froude Number contour maps reveal a sinuous rise and fall of values reminiscent of pool riffle energy distribution.

THE PREVALENCE AND PREDICTION OF PULMONARY FIBROSIS IN AN

This thesis describes an ancillary project to the Early Diagnosis of Mesothelioma and Lung Cancer in Prior Asbestos Workers study and was conducted to determine the effects of asbestos exposure, pulmonary function and cigarette smoking in the prediction of pulmonary fibrosis. 613 workers who were occupationally exposed to asbestos for an average of 25.9 (SD=14.69) years were sampled from Sarnia, Ontario. A structured questionnaire was administered during a face-to-face interview along with a low-dose computed tomography (LDCT) of the thorax. Of them, 65 workers (10.7%, 95%CI 8.12—12.24) had LDCT-detected pulmonary fibrosis. The model predicting fibrosis included the variables age, smoking (dichotomized), post FVC % splines and post- FEV1% splines. This model had a receiver operator characteristic area under the curve of 0.738. The calibration of the model was evaluated with R statistical program and the bootstrap optimism-corrected calibration slope was 0.692. Thus, our model demonstrated moderate predictive performance.

Using a Bayesian model for bankruptcy prediction : a comparative approach

The purpose of this study is to examine the impact of the choice of cut-off points, sampling procedures, and the business cycle on the accuracy of bankruptcy prediction models. Misclassification can result in erroneous predictions leading to prohibitive costs to firms, investors and the economy. To test the impact of the choice of cut-off points and sampling procedures, three bankruptcy prediction models are assessed- Bayesian, Hazard and Mixed Logit. A salient feature of the study is that the analysis includes both parametric and nonparametric bankruptcy prediction models. A sample of firms from Lynn M. LoPucki Bankruptcy Research Database in the U. S. was used to evaluate the relative performance of the three models. The choice of a cut-off point and sampling procedures were found to affect the rankings of the various models. In general, the results indicate that the empirical cut-off point estimated from the training sample resulted in the lowest misclassification costs for all three models. Although the Hazard and Mixed Logit models resulted in lower costs of misclassification in the randomly selected samples, the Mixed Logit model did not perform as well across varying business-cycles. In general, the Hazard model has the highest predictive power. However, the higher predictive power of the Bayesian model, when the ratio of the cost of Type I errors to the cost of Type II errors is high, is relatively consistent across all sampling methods. Such an advantage of the Bayesian model may make it more attractive in the current economic environment. This study extends recent research comparing the performance of bankruptcy prediction models by identifying under what conditions a model performs better. It also allays a range of user groups, including auditors, shareholders, employees, suppliers, rating agencies, and creditors' concerns with respect to assessing failure risk.

Experimental and Computational Studies on Copper and Hydrobenzoin Derivatives in Catalytic Asymmetric Reactions

The use of theory to understand and facilitate catalytic enantioselective organic transformations involving copper and hydrobenzoin derivatives is reported. Section A details the use of theory to predict, facilitate, and understand a copper promoted amino oxygenation reaction reported by Chemler et al. Using Density Functional Theory (DFT), employing the hybrid B3LYP functional and a LanL2DZ/6-31G(d) basis set, the mechanistic details were studied on a N-tosyl-o-allylaniline and a [alpha]-methyl-[gamma]-alkenyl sulfonamide substrate. The results suggest the N-C bond formation proceeds via a cisaminocupration, and not through a radical-type mechanism. Additionally, the origin of diastereoselection observed with [alpha]-methyl-[gamma]-alkenyl sulfonamide arises from avoidance of unfavourable steric interactions between the methyl substituent and the N -protecting group. Section B details the computationally guided, experimental investigation of two hydrobenzoin derivatives as ligands/ catalysts, as well as the attempted synthesis of a third hydrobenzoin derivative. The bis-boronic acid derived from hydrobenzoin was successful as a Lewis acid catalyst in the Bignielli reaction and the Conia ene reaction, but provided only racemic products. The chiral diol derived from hydrobenzoin successfully increased the rate of the addition of diethyl zinc to benzaldehyde in the presence of titanium tetraisopropoxide, however poor enantioinduction was obseverved. Notably, the observed reactivity was successfully predicted by theoretical calculations.

Human Endogenous Retrovirus (HERV) Insertional Polymorphisms

Human endogenous retroviruses (HERVs) are the result of ancient germ cell infections of human germ cells by exogenous retroviruses. HERVs belong to the long terminal repeat (LTR) group of retrotransposons that comprise ~8% of the human genome. The majority of the HERVs documented have been truncated and/or incurred lethal mutations and no longer encode functional genes; however a very small number of HERVs seem to maintain functional in making new copies by retrotranspositon as suggested by the identification of a handful of polymorphic HERV insertions in human populations. The objectives of this study were to identify novel insertion of HERVs via analysis of personal genomic data and survey the polymorphism levels of new and known HERV insertions in the human genome. Specifically, this study involves the experimental validation of polymorphic HERV insertion candidates predicted by personal genome-based computation prediction and survey the polymorphism level within the human population based on a set of 30 diverse human DNA samples. Based on computational analysis of a limited number of personal genome sequences, PCR genotyping aided in the identification of 15 dimorphic, 2 trimorphic and 5 fixed full-length HERV-K insertions not previously investigated. These results suggest that the proliferation rate of HERVKs, perhaps also other ERVs, in the human genome may be much higher than we previously appreciated and the recently inserted HERVs exhibit a high level of instability. Throughout this study we have observed the frequent presence of additional forms of genotypes for these HERV insertions, and we propose for the first time the establishment of new genotype reporting nomenclature to reflect all possible combinations of the pre-integration site, solo-LTR and full-length HERV alleles.