Homeostatic plasticity is important in neurobiology for stabilising neuronal networks in the face of Hebbian forms of synaptic plasticity that are thought to mediate memory storage. Impairment of homeostatic plasticity has also been implicated in neurological diseases such as Rett syndrome and fragile X syndrome. Homeostatic plasticity can be achieved through scaling of the strength of synaptic connections between neurones or by changes in intrinsic excitability. While homeostatic plasticity has been studied mainly using in vitro preparations, it is for the most part not known whether changes of neural activity in vivo induce homeostatic changes. The molecular pathway responsible for homeostatic plasticity still remains unclear. In this thesis, I have used stereotaxic surgery to over express Kir2.1, an inwardly rectifying potassium channel, in vivo in the brains of adult mice. I show that the expression of Kir2.1 through adeno-associated virus (AAV) does not cause any adverse effects in the dentate gyrus nor the CA1 of the mouse hippocampus. I go on to use slice patch clamp methods to measure the change in electrical properties of granule cells in the dentate gyrus and pyramidal cells in CA1 caused by expression of Kir2.1. I show that the excitability of neurones expressing Kir2.1 was reduced compared to control neurones. By 2 weeks after virus injection the neurones showed homeostatic plasticity in response to Kir2.1 over expression. Interestingly, the mechanism of adaptation was different in different types of cells; dentate gyrus granule cells adapted through change in their intrinsic excitability, whereas CA1 pyramidal cells adapted by modifying the strength of their synaptic inputs. To establish whether induction of homeostatic plasticity is associated with changes in gene expression I used fluorescent activated cell sorting (FACs) to isolate pure population of neurones infected with viruses. I then sequenced RNA extracted from neurones expressing Kir2.1 and control neurones. Analysis of the RNAseq data revealed molecular candidates involved in homeostatic plasticity. In summary, I show that Kir2.1 over expression causes change in excitability and subsequent homeostatic plasticity in vivo. The mechanism of adaptation differs between cell types. RNAseq results identify novel candidates for future investigation.

The function of a Content-Addressable Memory (CAM) is to efficiently search the information stored in the memory, by using hardware rather than software with a corresponding improvement in searching speed. This hardware allows a parallel search by matching the data stored in memory to a search key rather than sequentially searching address by address as is done in a Random Access Memory. Although existing CAMs are more efficient in finding relevant information than RAM, there are additional improvements that can be made to further improve its efficiency. For example, previous CAMs use a word parallel searching scheme that can only identify exact matches. To find the best (closest) match, previous CAMs had to use bit serial approaches. Although still more efficient than RAM searching, these CAMs were limited by the word size (bit width) of the memory. Responding to this inefficiency, the CAM described in this thesis improves best-fit searching by using analog design in combination with digital design. This design retains a mismatch line to collect the result of the comparison of each bit of a word which is decoded by a simple flash A/D. This means that after a single operation the best-fit plus all words with zero to three bits of mismatch, are determined. This word/bit parallel searching makes this CAM more efficient than existing CAMs. The best-fit function of this CAM is good for database retrieval, communications and error correction circuitry. By using the high speed searching and the inexact match feature, this CAM also provides efficient sorting and set operations. The accumulated searching time is shortened when compared to regular CAM and RAM. The inexact CAM in this thesis is designed using mixed analog/digital design in a 2~ CMOS technology.

Doctor of Philosophy / This thesis reports two tests of information-based theories of the returns to education, in the labour market for young Australians. The first is a test of whether these returns increase discontinuously with credentials such as high school graduation and university degrees. The second is a test of employer learning based upon how the returns to education, and to measures of ability not initially observed by employers, evolve with experience. These tests are conducted using a new data source which tracks individuals during the years in which they are entering and establishing themselves in the labour market, the period during which such credential and learning effects are most likely to be important. It is found that there are large and highly significant credential returns to completion of bachelor’s degrees, of 14% for males and 10% for females. For males, around 39% of the returns to 15 years of education (relative to 9 or fewer years) are attributable to credential effects, while the corresponding figure for females is 36%. These effects are stronger among workers who were recruited through hiring channels that convey less initial information to employers. There is also evidence that post-secondary admission or attendance without completion of a credential may itself have a sorting effect in the labour market. In the employer learning estimates, when parental education is used as a measure of ability observed by the researcher but not initially by employers, it is found to become increasingly correlated with wages as experience accumulates. However, no such result is found when a standardised test score is used as the ability variable – apparently because the information captured by this score is already observed by employers at the time of labour market entry. When the model is estimated separately by occupational class, the finding of employer learning holds only among white-collar workers. This may be due to the types of attributes that are reflected in parental education as a measure of initially unobserved ability.

Sorting is one of the more computationally intensive tasks a computer performs. One of the most effective ways to speed up the task of sorting is by using parallel algorithms. When implementing a parallel algorithm, the designer has to make several decisions. Among the decisions are the algorithm and the physical implementation of the algorithm. A dedicated hardware solution is often physically quicker than a software solution. In this thesis, we will investigate the optimization of a hardware implementation of max-min sort. I propose an optimization to the data structures used in the algorithm. The new data structure allows quicker sorting by changing the basic workings of the max-min sort. The results are presented by comparing the new data structure with the original data structure. The thesis also discusses the design and performance issues related to implementing the algorithm in hardware. / Graduation date: 1998

We consider the often-studied problem of sorting, for a parallel computer. Given an input array distributed evenly over p processors, the task is to compute the sorted output array, also distributed over the p processors. Many existing algorithms take the approach of approximately load-balancing the output, leaving each processor with Θ(n/p) elements. However, in many cases, approximate load-balancing leads to inefficiencies in both the sorting itself and in further uses of the data after sorting. We provide a deterministic parallel sorting algorithm that uses parallel selection to produce any output distribution exactly, particularly one that is perfectly load-balanced. Furthermore, when using a comparison sort, this algorithm is 1-optimal in both computation and communication. We provide an empirical study that illustrates the efficiency of exact data splitting, and shows an improvement over two sample sort algorithms. / Singapore-MIT Alliance (SMA)

Thesis (M.S.)--Brigham Young University. School of Technology, 2006. / Includes bibliographical references (p. 119-121).

Notre thèse est consacrée à l’étude des méthodes de rangements multicritères dans le cadre de la problématique de tri. Dans un problème de tri une personne, appelée décideur, désire assigner un objet, appelé action, à des catégories prédéfinies. Des problèmes de tri surgissent régulièrement dans la vie de tous les jours. Par exemple, un médecin ausculte son patient et sur base des symptômes observés, il assigne son patient à une catégorie de pathologies. Ainsi, le médecin peut prescrire un traitement approprié. Par ailleurs, on catégorise les cyclones tropicaux en fonction de leur vitesse, pression superficielle et de la hauteur de marée. En fonction de la catégorie du cyclone, des dégâts éventuels peuvent être prédits et des mesures de protection adéquates devront être prises. Dans un problème de tri, un décideur regroupe ainsi les actions qu’il considère similaires, à des fins descriptives, organisationnelles ou préventives. Nous supposerons en outre que le décideur exprime une relation de préférence entre les classes préalablement définies. D’autre part, les méthodes de rangement permettent de ranger les actions de la meilleure à la moins bonne. Nul étudiant ne peut nier l’existence des " rankings " d’universités. Une société ordonne les candidats à l’issue d’un entretien d’embauche. Une société désire par ailleurs établir des partenariats avec les fournisseurs les plus performants. Nous sommes tous confrontés à cette tâche délicate de ranger les actions de la meilleure à la moins bonne. Les méthodes d’aide à la décision proposent des techniques permettant à un décideur d’obtenir un rangement d’actions. L’objectif de cette thèse est d’étudier la possibilité de résoudre des problèmes de tri à l’aide de méthodes de rangement. L’approche adoptée est de ranger une action particulière par rapport à des normes ou profils définissant les catégories. L’assignation de l’action sera dès lors basée sur sa position dans ce rangement particulier. Quelles sont les hypothèses nécessaires pour un tel modèle ? Ces méthodes présentent-elles un biais ou ont-elles d’autres avantages par rapport aux méthodes de tri existantes? Est-il préférable de modéliser les catégories à l’aide de critères même si celles-ci ne présentent pas de relation de préférence ? Dans cette thèse nous donnerons des premiers éléments de réponse en développant de nouvelles méthodes de tri basées sur des méthodes de rangement existantes.

The intracellular space of eukaryotic cells is subdivided into functionally distinct membrane-enclosed organelles. Regulation of these intracellular membranes requires an intricate network of specialized lipids and proteins that maintain organellar integrity and mediate transport between organelles. Proteins of the sorting nexin (SNX) family are membrane-binding regulators of transport events within the endomembrane system. The endomembrane system includes organelles associated with endocytic, secretory and degradative processes in the cell. The aims of this thesis were to functionally characterize SNX18 and SNX33, members of the SNX9-subfamily of sorting nexins, and to elucidate the role of SNX18 in autophagy. We demonstrated that all three proteins in the SNX9-family are capable of both membrane binding and remodeling, and interact with the membrane scission enzyme dynamin. We found that SNX18 localizes to endosomal structures in the endomembrane system, together with several identified factors previously described as regulators of endosomal transport. These results indicate that SNX18 mediates budding of membrane carriers in endosomal trafficking. In addition to this, knockdown of SNX18 in cultured cells was found to inhibit autophagy. Autophagy is a catabolic process by which cells degrade and recycle cellular components. It is a cellular response to various stress conditions such as oxidative stress, nutrient deprivation and infections. The components destined for degradation by autophagy are sequestered into a double-membrane structure called the autophagosome in which they are delivered to the lysosome. SNX18 interacts directly with proteins connected to autophagosome formation. Moreover, we demonstrated that the membrane-remodeling capability of SNX18 is a prerequisite for autophagosome formation. Taken together, our results lead to the conclusions that SNX18 remodels cellular membranes during formation of carriers for endosomal transport and that it is a positive regulator of autophagy and autophagosome formation.

Multiple criteria decision analysis (MCDA) techniques are developed to address challenging classification problems arising in engineering management and elsewhere. MCDA consists of a set of principles and tools to assist a decision maker (DM) to solve a decision problem with a finite set of alternatives compared according to two or more criteria, which are usually conflicting. The three types of classification problems to which original research contributions are made are <ol> <li>Screening: Reduce a large set of alternatives to a smaller set that most likely contains the best choice. </li> <li>Sorting: Arrange the alternatives into a few groups in preference order, so that the DM can manage them more effectively. </li> <li>Nominal classification: Assign alternatives to nominal groups structured by the DM, so that the number of groups, and the characteristics of each group, seem appropriate to the DM. </ol> Research on screening is divided into two parts: the design of a sequential screening procedure that is then applied to water resource planning in the Region of Waterloo, Ontario, Canada; and the development of a case-based distance method for screening that is then demonstrated using a numerical example. <br /><br /> Sorting problems are studied extensively under three headings. Case-based distance sorting is carried out with Model I, which is optimized for use with cardinal criteria only, and Model II, which is designed for both cardinal and ordinal criteria; both sorting approaches are applied to a case study in Canadian municipal water usage analysis. Sorting in inventory management is studied using a case-based distance method designed for multiple criteria ABC analysis, and then applied to a case study involving hospital inventory management. Finally sorting is applied to bilateral negotiation using a case-based distance model to assist negotiators that is then demonstrated on a negotiation regarding the supply of bicycle components. <br /><br /> A new kind of decision analysis problem, called multiple criteria nominal classification (MCNC), is addressed. Traditional classification methods in MCDA focus on sorting alternatives into groups ordered by preference. MCNC is the classification of alternatives into nominal groups, structured by the DM, who specifies multiple characteristics for each group. The features, definitions and structures of MCNC are presented, emphasizing criterion and alternative flexibility. An analysis procedure is proposed to solve MCNC problems systematically and applied to a water resources planning problem.

Multiple criteria decision analysis (MCDA) techniques are developed to address challenging classification problems arising in engineering management and elsewhere. MCDA consists of a set of principles and tools to assist a decision maker (DM) to solve a decision problem with a finite set of alternatives compared according to two or more criteria, which are usually conflicting. The three types of classification problems to which original research contributions are made are <ol> <li>Screening: Reduce a large set of alternatives to a smaller set that most likely contains the best choice. </li> <li>Sorting: Arrange the alternatives into a few groups in preference order, so that the DM can manage them more effectively. </li> <li>Nominal classification: Assign alternatives to nominal groups structured by the DM, so that the number of groups, and the characteristics of each group, seem appropriate to the DM. </ol> Research on screening is divided into two parts: the design of a sequential screening procedure that is then applied to water resource planning in the Region of Waterloo, Ontario, Canada; and the development of a case-based distance method for screening that is then demonstrated using a numerical example. <br /><br /> Sorting problems are studied extensively under three headings. Case-based distance sorting is carried out with Model I, which is optimized for use with cardinal criteria only, and Model II, which is designed for both cardinal and ordinal criteria; both sorting approaches are applied to a case study in Canadian municipal water usage analysis. Sorting in inventory management is studied using a case-based distance method designed for multiple criteria ABC analysis, and then applied to a case study involving hospital inventory management. Finally sorting is applied to bilateral negotiation using a case-based distance model to assist negotiators that is then demonstrated on a negotiation regarding the supply of bicycle components. <br /><br /> A new kind of decision analysis problem, called multiple criteria nominal classification (MCNC), is addressed. Traditional classification methods in MCDA focus on sorting alternatives into groups ordered by preference. MCNC is the classification of alternatives into nominal groups, structured by the DM, who specifies multiple characteristics for each group. The features, definitions and structures of MCNC are presented, emphasizing criterion and alternative flexibility. An analysis procedure is proposed to solve MCNC problems systematically and applied to a water resources planning problem.