Design and Material Selection of High-Speed Rotating Electrical Machines

The increasing emphasis on energy efficiency is starting to yield results in the reduction in greenhouse gas emissions; however, the effort is still far from sufficient. Therefore, new technical solutions that will enhance the efficiency of power generation systems are required to maintain the sustainable growth rate, without spoiling the environment. A reduction in greenhouse gas emissions is only possible with new low-carbon technologies, which enable high efficiencies. The role of the rotating electrical machine development is significant in the reduction of global emissions. A high proportion of the produced and consumed electrical energy is related to electrical machines. One of the technical solutions that enables high system efficiency on both the energy production and consumption sides is high-speed electrical machines. This type of electrical machines has a high system overall efficiency, a small footprint, and a high power density compared with conventional machines. Therefore, high-speed electrical machines are favoured by the manufacturers producing, for example, microturbines, compressors, gas compression applications, and air blowers. High-speed machine technology is challenging from the design point of view, and a lot of research is in progress both in academia and industry regarding the solution development. The solid technical basis is of importance in order to make an impact in the industry considering the climate change. This work describes the multidisciplinary design principles and material development in high-speed electrical machines. First, high-speed permanent magnet synchronous machines with six slots, two poles, and tooth-coil windings are discussed in this doctoral dissertation. These machines have unique features, which help in solving rotordynamic problems and reducing the manufacturing costs. Second, the materials for the high-speed machines are discussed in this work. The materials are among the key limiting factors in electrical machines, and to overcome this limit, an in-depth analysis of the material properties and behavior is required. Moreover, high-speed machines are sometimes operating in a harsh environment because they need to be as close as possible to the rotating tool and fully exploit their advantages. This sets extra requirements for the materials applied.

Habitat selection of three rodents in a frequently burned boreal environment : productivity and habitat diversity

How does fire affect the plant and animal community of the boreal forest? This study attempted to examine the changes in plant composition and productivity, and small mammal demography brought about by fire in the northern boreal environment at Chick Lake, N.W.T. (65053fN, 128°14,W). Two 5*6 ha plots measuring 375m x 150m were selected for study during the summers of 1973 and 197^. One had been unburned for 120 years, the other was part of a fire which burned in the spring of 1969. Grids of 15m x 15m were established in each plot and meter square quadrats taken at each of the 250 grid intersections in order to determine plant composition and density. Aerial primary production was assessed by clipping and drying 80 samples of terminal new production for each species under investigation. Small mammal populations were sampled by placing a Sherman live trap at each grid intersection for ten days in every month. The two plots were similar in plant species composition which suggested that most regrowth in the burned area was from rootstocks which survived the fire. The plant data were submitted to a cluster analysis that revealed nine separate species associations, six of which occured in the burned area and eight of which occured in the control. These were subsequently treated as habitats for purposes of comparison with small mammal distributions. The burned area showed a greater productivity in flowers and fruits although total productivity in the control area was higher due to a large contribution from the non-vascular component. Maximum aerial productivity as dry wieght was measured at 157.1 g/m and 207.8 g/m for the burn and control respectively. Microtus pennsylvanicus and Clethrionomys rutilus were the two most common small mammals encountered; Microtus xanthognathus, Synaptomys borealis, and Phenacomys intermedius also occured in the area. Populations of M. pennsylvanicus and C. rutilus were high during the summer of 1973; however, M. pennsylvanicus was rare on the control but abundant on the burn, while C. rutilus was rare on the burn but abundant in the control. During the summer of 197^ populations declined, with the result that few voles of any species were caught in the burn while equal numbers of the two species were caught in the control. During the summer of 1973 M. pennsylvanicus showed a positive association to the most productive habitat type in the burn which was avoided by C. rutilus. In the control £• rutilus showed a similar positive association to the most productive habitat type which was avoided by M. pennsylvanicus. In all cases for the high population year of 1973# the two species never overlapped in habitat preference. When populations declined in 197^f "both species showed a strong association for the most productive habitat in the control. This would suggest that during a high population year, an abundant species can exclude competitors from a chosen habitat, but that this dominance decreases as population levels decrease. It is possible that M. pennsylvanicus is a more efficient competitor in a recently burned environment, while C. rutilus assumes this role once non-vascular regrowth becomes extensive.

The role of learning and growth hormone-releasing factor in the control of protein intake in rats /

Both learning and basic biological mechanisms have been shown to play a role in the control of protein int^e. It has previously been shown that rats can adapt their dietary selection patterns successfully in the face of changing macronutrient requirements and availability. In particular, it has been demonstrated that when access to dietary protein is restricted for a period of time, rats selectively increase their consumption of a proteincontaining diet when it becomes available. Furthermore, it has been shown that animals are able to associate various orosensory cues with a food's nutrient content. In addition to the role that learning plays in food intake, there are also various biological mechanisms that have been shown to be involved in the control of feeding behaviour. Numerous studies have documented that various hormones and neurotransmitter substances mediate food intake. One such hormone is growth hormone-releasing factor (GRF), a peptide that induces the release of growth hormone (GH) from the anterior pituitary gland. Recent research by Vaccarino and Dickson ( 1 994) suggests that GRF may stimulate food intake by acting as a neurotransmitter in the suprachiasmatic nucleus (SCN) and the adjacent medial preoptic area (MPOA). In particular, when GRF is injected directly into the SCN/MPOA, it has been shown to selectively enhance the intake of protein in both fooddeprived and sated rats. Thus, GRF may play a role in activating protein consumption generally, and when animals have a need for protein, GRF may serve to trigger proteinseeking behaviour. Although researchers have separately examined the role of learning and the central mechanisms involved in the control of protein selection, no one has yet attempted to bring together these two lines of study. Thus, the purpose of this study is to join these two parallel lines of research in order to further our understanding of mechanisms controlling protein selection. In order to ascertain the combined effects that GRF and learning have on protein intake several hypothesis were examined. One major hypothesis was that rats would successfully alter their dietary selection patterns in response to protein restriction. It was speculated that rats kept on a nutritionally complete maintenance diet (NCMD) would consume equal amount of the intermittently presented high protein conditioning diet (HPCD) and protein-free conditioning diet (PFCD). However, it was hypothesized that rats kept on a protein-free maintenance diet (PFMD) would selectively increase their intake of the HPCD. Another hypothesis was that rats would learn to associate a distinct marker flavour with the nutritional content of the diets. If an animal is able to make the association between a marker flavour and the nutrient content of the food, then it is hypothesized that they will consume more of a mixed diet (equal portion HPCD and PFCD) with the marker flavour that was previously paired with the HPCD (Mixednp-f) when kept on the PFMD. In addition, it was hypothesized that intracranial injection of GRF into the SCN/MPOA would result in a selective increase in HPCD as well as Mixednp-t consumption. Results demonstrated that rats did in fact selectively increase their consumption of the flavoured HPCD and Mixednp-f when kept on the NCMD. These findings indicate that the rats successfully learned about the nutrient content of the conditioning diets and were able to associate a distinct marker flavour with the nutrient content of the diets. However, the results failed to support previous findings that GRF increases protein intake. In contrast, the administration of GRF significantly reduced consumption of HPCD during the first hour of testing as compared to the no injection condition. In addition, no differences in the intake of the HPCD were found between the GRF and vehicle condition. Because GRF did not selectively increase HPCD consumption, it was not surprising that GRF also did not increase MixedHP-rintake. What was interesting was that administration of GRF and vehicle did not reduc^Mixednp-f consumption as it had decreased HPCD consumption.

Frequency-dependent selection at the amylase locus in Drosophila melanogaster

A. strain of Drosophila melanog-aster deficient in null amylase activity (Amylase ) was isolated from a wild null population of flies. The survivorship of Amylase homozygous flies is very low when the principal dietary carbohydrate source is starch. However, the survivorship of the null Amylase genotype is comparable to the wild type when the dietary starch is replaced by glucose. In addition, the null viability of the amylase-producing and Amylase strains is comparable v and very lm<] f on a medium with no carbohydrates . Furthermore, amylase-producing genotypes were shovm to excrete enzymatically active amylase protein into the food medium. The excreted amylase causes the external breakdown of dietary starch to sugar. These results led to the following null prediction: the viability of the A.mvlase genotype (fed on a starch rich diet) might increase in the presence of individuals which were amylase-producing. It was shown experimentally that such an increase in viability did in fact occur and that this increase v\Tas proportional to the number of mnylase..::producing fli.es present. These results provide a unique example of a non-"competi ti ve inter-genotype interaction, and one where the underlying physio~ logical and biochemical mechanism has been fully understood.

The nesting biology of Ceratina (Hymenoptera: Apidae) in the Niagara Region : new species, nest site selection and parasitism

One of the most common bee genera in the Niagara Region, the genus Ceratina (Hymenoptera: Apidae) is composed of four species, C. dupla, C. calcarata, the very rare C. strenua, and a previously unknown species provisionally named C. near dupla. The primary goal of this thesis was to investigate how these closely related species coexist with one another in the Niagara ~ee community. The first necessary step was to describe and compare the nesting biologies and life histories of the three most common species, C. dupla, C. calcarata and the new C. near dupla, which was conducted in 2008 via nest collections and pan trapping. Ceratina dupla and C. calcarata were common, each comprising 49% of the population, while C. near dupla was rare, comprising only 2% of the population. Ceratina dupla and C. near dupla both nested more commonly in teasel (Dipsacus sp.) in the sun, occasionally in raspberry (Rubus sp.) in the shade, and never in shady sumac (Rhus sp.), while C. calcarata nested most commonly in raspberry and sumac (shaded) and occasionally in teasel (sunny). Ceratina near dupla differed from both C. dupla and C. calcarata in that it appeared to be partially bivoltine, with some females founding nests very early and then again very late in the season. To examine the interactions and possible competition for nests that may be taking place between C. dupla and C. calcarata, a nest choice experiment was conducted in 2009. This experiment allowed both species to choose among twigs from all three substrates in the sun and in the shade. I then compared the results from 2008 (where bees chose from what was available), to where they nested when given all options (2009 experiment). Both C. dupla and C. calcarata had the same preferences for microhabitat and nest substrate in 2009, that being raspberry and sumac twigs in the sun. As that microhabitat and nest substrate combination is extremely rare in nature, both species must make a choice. In nature Ceratina dupla nests more often in the preferred microhabitat (sun), while C. calcarata nests in the preferred substrate (raspberry). Nesting in the shade also leads to smaller clutch sizes, higher parasitism and lower numbers of live brood in C. calcarata, suggesting that C. dupla may be outcompeting C. calcarata for the sunny nesting sites. The development and host preferences of Ceratina parasitoids were also examined. Ceratina species in Niagara were parasitized by no less than eight species of arthropod. Six of these were wasps from the superfamily Chalcidoidea (Hymenoptera), one was a wasp from the family Ichneumonidae (Hymenoptera) and one was a physogastric mite from the family Pyemotidae (Acari). Parasites shared a wide range of developmental strategies, from ichneumonid larvae that needed to consume multiple Ceratina immatures to complete development, to the species from the Eulophidae (Baryscapus) and Encyrtidae (Coelopencyrtus), in which multiple individuals completed development inside a single Ceratina host. Biological data on parasitoids is scarce in the scientific literature, and this Chapter documents these interactions for future research.

Improving Short DNA Sequence Alignment with Parallel Computing

Variations in different types of genomes have been found to be responsible for a large degree of physical diversity such as appearance and susceptibility to disease. Identification of genomic variations is difficult and can be facilitated through computational analysis of DNA sequences. Newly available technologies are able to sequence billions of DNA base pairs relatively quickly. These sequences can be used to identify variations within their specific genome but must be mapped to a reference sequence first. In order to align these sequences to a reference sequence, we require mapping algorithms that make use of approximate string matching and string indexing methods. To date, few mapping algorithms have been tailored to handle the massive amounts of output generated by newly available sequencing technologies. In otrder to handle this large amount of data, we modified the popular mapping software BWA to run in parallel using OpenMPI. Parallel BWA matches the efficiency of multithreaded BWA functions while providing efficient parallelism for BWA functions that do not currently support multithreading. Parallel BWA shows significant wall time speedup in comparison to multithreaded BWA on high-performance computing clusters, and will thus facilitate the analysis of genome sequencing data.

The Order of Canada Investiture Ceremony Program (Selection of Pages)

A selection of pages from the program for the Order of Canada Investiture Ceremony in 2003 when Dorothy Wetherald Rungeling was a recipient.

Feature Selection and Classification Using Age Layered Population Structure Genetic Programming

The curse of dimensionality is a major problem in the fields of machine learning, data mining and knowledge discovery. Exhaustive search for the most optimal subset of relevant features from a high dimensional dataset is NP hard. Sub–optimal population based stochastic algorithms such as GP and GA are good choices for searching through large search spaces, and are usually more feasible than exhaustive and deterministic search algorithms. On the other hand, population based stochastic algorithms often suffer from premature convergence on mediocre sub–optimal solutions. The Age Layered Population Structure (ALPS) is a novel metaheuristic for overcoming the problem of premature convergence in evolutionary algorithms, and for improving search in the fitness landscape. The ALPS paradigm uses an age–measure to control breeding and competition between individuals in the population. This thesis uses a modification of the ALPS GP strategy called Feature Selection ALPS (FSALPS) for feature subset selection and classification of varied supervised learning tasks. FSALPS uses a novel frequency count system to rank features in the GP population based on evolved feature frequencies. The ranked features are translated into probabilities, which are used to control evolutionary processes such as terminal–symbol selection for the construction of GP trees/sub-trees. The FSALPS metaheuristic continuously refines the feature subset selection process whiles simultaneously evolving efficient classifiers through a non–converging evolutionary process that favors selection of features with high discrimination of class labels. We investigated and compared the performance of canonical GP, ALPS and FSALPS on high–dimensional benchmark classification datasets, including a hyperspectral image. Using Tukey’s HSD ANOVA test at a 95% confidence interval, ALPS and FSALPS dominated canonical GP in evolving smaller but efficient trees with less bloat expressions. FSALPS significantly outperformed canonical GP and ALPS and some reported feature selection strategies in related literature on dimensionality reduction.

Feature Selection and Classification Using Age Layered Population Structure Genetic Programming

The curse of dimensionality is a major problem in the fields of machine learning, data mining and knowledge discovery. Exhaustive search for the most optimal subset of relevant features from a high dimensional dataset is NP hard. Sub–optimal population based stochastic algorithms such as GP and GA are good choices for searching through large search spaces, and are usually more feasible than exhaustive and determinis- tic search algorithms. On the other hand, population based stochastic algorithms often suffer from premature convergence on mediocre sub–optimal solutions. The Age Layered Population Structure (ALPS) is a novel meta–heuristic for overcoming the problem of premature convergence in evolutionary algorithms, and for improving search in the fitness landscape. The ALPS paradigm uses an age–measure to control breeding and competition between individuals in the population. This thesis uses a modification of the ALPS GP strategy called Feature Selection ALPS (FSALPS) for feature subset selection and classification of varied supervised learning tasks. FSALPS uses a novel frequency count system to rank features in the GP population based on evolved feature frequencies. The ranked features are translated into probabilities, which are used to control evolutionary processes such as terminal–symbol selection for the construction of GP trees/sub-trees. The FSALPS meta–heuristic continuously refines the feature subset selection process whiles simultaneously evolving efficient classifiers through a non–converging evolutionary process that favors selection of features with high discrimination of class labels. We investigated and compared the performance of canonical GP, ALPS and FSALPS on high–dimensional benchmark classification datasets, including a hyperspectral image. Using Tukey’s HSD ANOVA test at a 95% confidence interval, ALPS and FSALPS dominated canonical GP in evolving smaller but efficient trees with less bloat expressions. FSALPS significantly outperformed canonical GP and ALPS and some reported feature selection strategies in related literature on dimensionality reduction.

Dealing with Moral Hazard and Adverse Selection Simultaneously

Although Insurers Face Adverse Selection and Moral Hazard When They Set Insurance Contracts, These Two Types of Asymmetrical Information Have Been Given Separate Treatments Sofar in the Economic Literature. This Paper Is a First Attempt to Integrate Both Problems Into a Single Model. We Show How It Is Possible to Use Time in Order to Achieve a First-Best Allocation of Risks When Both Problems Are Present Simultaneously.

Finite-Sample Simulation-Based Inference in VAR Models with Applications to Order Selection and Causality Testing

Statistical tests in vector autoregressive (VAR) models are typically based on large-sample approximations, involving the use of asymptotic distributions or bootstrap techniques. After documenting that such methods can be very misleading even with fairly large samples, especially when the number of lags or the number of equations is not small, we propose a general simulation-based technique that allows one to control completely the level of tests in parametric VAR models. In particular, we show that maximized Monte Carlo tests [Dufour (2002)] can provide provably exact tests for such models, whether they are stationary or integrated. Applications to order selection and causality testing are considered as special cases. The technique developed is applied to quarterly and monthly VAR models of the U.S. economy, comprising income, money, interest rates and prices, over the period 1965-1996.

Bundling under the Threat of Parallel Trade

This paper examines the use of bundling by a firm that sells in two national markets and faces entry by parallel traders. The firm can bundle its main product, - a tradable good- with a non-traded service. It chooses between the strategies of pure bundling, mixed bundling and no bundling. The paper shows that in the low-price country the threat of grey trade elicits a move from mixed bundling, or no bundling, towards pure bundling. It encourages a move from pure bundling towards mixes bundling or no bundling in the high-price country. The set of parameter values for which the profit maximizing strategy is not to supply the low price country is smaller than in the absence of bundling. The welfare effects of deterrence of grey trade are not those found in conventional models of price arbitrage. Some consumers in the low-price country may gain from the threat of entry by parallel traders although they pay a higher price. This is due to the fact that the firm responds to the threat of arbitrageurs by increasing the amount of services it puts in the bundle targeted at consumers in that country. Similarly, the threat of parallel trade may affect some consumers in the hight-price country adversely.

SCaFoS: a tool for Selection, Concatenation and Fusion of Sequences for phylogenomics

Affiliation: Département de Biochimie, Université de Montréal