Pressure dependence of spin fluctuations in metallic glasses Zrâ â Niâ â ,Zrâ â (Nix/Feâ â â -x)â â and /Zrx/feâ â â -x

The superconducting transition temperature Tc of metallic glasses ZrxFelOO-x (x=80, 75), Zr75(NixFelOO-x)25 (x=75, 50, 25), and CU2SZr75 were measured under quasi-hydrostatic pressure up to 8 OPa (80kbar). The volume (pressure) dependence of the electron-phonon coupling parameters Aep for CU25Zr75 was calculated using the McMillan equatio11. Using this volume dependence of Aep and the modified McMillan equation which incorporates spin-fluctuations, the volume dependence of the spin fluctuation parameter, Asf, was determined in Zr75Ni25, ZrxFelOO-x , a11d Zr75(NixFelOO-x)25. It was found that with increasing pressure, spinfluctuations are suppressed at a faster rate in ZrxFe lOO-x and Zr75(NixFelOO-x)25, as Fe concentration is increased. The rate of suppression of spin-fluctuations with pressure was also found to be higher in Fe-Zr glasses than in Ni-Zr glasses of similar composition.

The diffusion of Co⠶溩 Zrâ â Tiâ â alloy /|nS. Kumar. -- 260 St Catharines [Ont.] : Dept. of Physics, Brock University,

The diffusion of Co60 in the body centered cubic beta phase of a ZrSOTi SO alloy has been studied at 900°, 1200°, and 1440°C. The results confirm earlier unpublished data obtained by Kidson17 • The temperature dependence of the diffusion coefficient is unusual and suggests that at least two and possibly three mechanisms may be operative Annealing of the specimen in the high B.C.C. region prior to the deposition of the tracer results in a large reduction in the diffusion coefficient. The possible significance of this effect is discussed in terms of rapid transport along dislocation network.

Pressure dependence of superconducting properties of MgB2 /

We prepared samples of MgB2 and ran sets of experiments aimed for investigation of superconducting properties under pressure. We found the value of pressure derivative of the transition temperature -1.2 ± 0.05 K/GPa. Then, using McMillan formula, we found that the main contribution to the change of the transition temperature under the pressure is due to the change in phonon frequencies. Griineisen parameter was calculated to be 7g = 2.4. Our results suggest that MgB2 is a conventional superconductor.

Pressure dependence of superconductivity in amorphous Ni x Zr 100-x alloys

Pressure variations of the superconducting transition temperature Ic of a series of amorphous NixZr 1 OO-x alloys have been studied under quasmydrostatic pressures upto 8 G Pa. For amorphous samples having Ni-concentration less than 40%, i)Tc/dP is positive in sign and it decreases non linearly with increase in I. whereasdTcldP is negative in sign for Ni concentration of 45%. Comparison with the Hall coefficient (I) and the thermoelectric power (2) results for the same amorphous alloys leads to the conclusion that s-d hybridization nature of the d-band (Nil plays a central role in the sign reversal behaviour. Application of pressures greater than 2 G Pa to Ni20ZrgO led to the formation of a new phase, w-Zr. which retains its form after the pressure is released.

Evolutionary synthesis of stochastic gene network models using feature-based search spaces

A feature-based fitness function is applied in a genetic programming system to synthesize stochastic gene regulatory network models whose behaviour is defined by a time course of protein expression levels. Typically, when targeting time series data, the fitness function is based on a sum-of-errors involving the values of the fluctuating signal. While this approach is successful in many instances, its performance can deteriorate in the presence of noise. This thesis explores a fitness measure determined from a set of statistical features characterizing the time series' sequence of values, rather than the actual values themselves. Through a series of experiments involving symbolic regression with added noise and gene regulatory network models based on the stochastic 'if-calculus, it is shown to successfully target oscillating and non-oscillating signals. This practical and versatile fitness function offers an alternate approach, worthy of consideration for use in algorithms that evaluate noisy or stochastic behaviour.

Comparison of classification ability of hyperball algorithms to neural network and k-nearest neighbour algorithms

The main focus of this thesis is to evaluate and compare Hyperbalilearning algorithm (HBL) to other learning algorithms. In this work HBL is compared to feed forward artificial neural networks using back propagation learning, K-nearest neighbor and 103 algorithms. In order to evaluate the similarity of these algorithms, we carried out three experiments using nine benchmark data sets from UCI machine learning repository. The first experiment compares HBL to other algorithms when sample size of dataset is changing. The second experiment compares HBL to other algorithms when dimensionality of data changes. The last experiment compares HBL to other algorithms according to the level of agreement to data target values. Our observations in general showed, considering classification accuracy as a measure, HBL is performing as good as most ANn variants. Additionally, we also deduced that HBL.:s classification accuracy outperforms 103's and K-nearest neighbour's for the selected data sets.

Riffing on a Theme: Faculty Experiences With Service-Learning in a Food Security Research Network in Ontario

While service-learning is often said to be beneficial for all those involved—students, community members, higher education institutions, and faculty members—there are relatively few studies of the attraction to, and effect of, service-learning on faculty members. Existing studies have tended to use a survey design, and to be based in the United States. There is a lack of information on faculty experiences with service-learning in Ontario or Canada. This qualitative case study of faculty experiences with service-learning was framed through an Appreciative Inquiry social constructionist approach. The data were drawn from interviews with 18 faculty members who belong to a Food Security Research Network (FSRN) at a university in northern Ontario, reports submitted by the network, and personal observation of a selection of network-related events. This dissertation study revealed how involvement with service-learning created opportunities for faculty learning and growth. The focus on food security and a commitment to the sustainability of local food production was found to be an ongoing attraction to service-learning and a means to engage in and integrate research and teaching on matters of personal and professional importance to these faculty members. The dissertation concludes with a discussion of the FSRN’s model and the perceived value of a themed, transdisciplinary approach to service-learning. This study highlights promising practices for involving faculty in service-learning and, in keeping with an Appreciative Inquiry approach, depicts a view of faculty work at its best.

Using Network Analysis to Understand and Advance Falls Prevention Services and Programs

The purpose of this study was to understand referral linkages that exist among falls prevention agencies in a southern Ontario region using network analysis theory. This was a single case study which included fifteen individual interviews. The data was analyzed through the constant comparative approach. Ten themes emerged and are classified into internal and external factors. Themes associated with internal factors are: 1) health professionals initiating services; 2) communication strategies; 3) formal partnerships; 4) trust; 5) program awareness; and 6) referral policies. Themes associated with external factors are: 1) client characteristics; 2) primary and community care collaboration; 3) networking; and 4) funding. Recommendations to improve the referral pathway are: 1) electronic database; 2) electronic referral forms; 3) educating office staff; and 4) education days. This study outlined the benefit of using network analysis to understand referral pathways and the importance of implementing strategies that will improve falls prevention referral pathways.

A game-theoretic network formation model

We study the dynamics of a game-theoretic network formation model that yields large-scale small-world networks. So far, mostly stochastic frameworks have been utilized to explain the emergence of these networks. On the other hand, it is natural to seek for game-theoretic network formation models in which links are formed due to strategic behaviors of individuals, rather than based on probabilities. Inspired by Even-Dar and Kearns (2007), we consider a more realistic model in which the cost of establishing each link is dynamically determined during the course of the game. Moreover, players are allowed to put transfer payments on the formation of links. Also, they must pay a maintenance cost to sustain their direct links during the game. We show that there is a small diameter of at most 4 in the general set of equilibrium networks in our model. Unlike earlier model, not only the existence of equilibrium networks is guaranteed in our model, but also these networks coincide with the outcomes of pairwise Nash equilibrium in network formation. Furthermore, we provide a network formation simulation that generates small-world networks. We also analyze the impact of locating players in a hierarchical structure by constructing a strategic model, where a complete b-ary tree is the seed network.

Network Similarity Measures and Automatic Construction of Graph Models using Genetic Programming

A complex network is an abstract representation of an intricate system of interrelated elements where the patterns of connection hold significant meaning. One particular complex network is a social network whereby the vertices represent people and edges denote their daily interactions. Understanding social network dynamics can be vital to the mitigation of disease spread as these networks model the interactions, and thus avenues of spread, between individuals. To better understand complex networks, algorithms which generate graphs exhibiting observed properties of real-world networks, known as graph models, are often constructed. While various efforts to aid with the construction of graph models have been proposed using statistical and probabilistic methods, genetic programming (GP) has only recently been considered. However, determining that a graph model of a complex network accurately describes the target network(s) is not a trivial task as the graph models are often stochastic in nature and the notion of similarity is dependent upon the expected behavior of the network. This thesis examines a number of well-known network properties to determine which measures best allowed networks generated by different graph models, and thus the models themselves, to be distinguished. A proposed meta-analysis procedure was used to demonstrate how these network measures interact when used together as classifiers to determine network, and thus model, (dis)similarity. The analytical results form the basis of the fitness evaluation for a GP system used to automatically construct graph models for complex networks. The GP-based automatic inference system was used to reproduce existing, well-known graph models as well as a real-world network. Results indicated that the automatically inferred models exemplified functional similarity when compared to their respective target networks. This approach also showed promise when used to infer a model for a mammalian brain network.

Untangling the Organizational Ambiguities in Supply Chain Risk Recognition, Assessment, and Response: The Role of Network Embeddedness

In this thesis, I focus on supply chain risk related ambiguity, which represents the ambiguities firms exhibit in recognizing, assessing, and responding to supply chain disruptions. I, primarily, argue that ambiguities associated with recognizing and responding to supply chain risk are information gathering and processing problems. Guided by the theoretical perspective of bounded rationality, I propose a typology of supply chain risk related ambiguity with four distinct dimensions. I, also, argue that the major contributor to risk related ambiguity is often the environment, specifically the web of suppliers. Hence, I focus on the characteristics of these supplier networks to examine the sources of ambiguity. I define three distinct elements of network embeddedness – relational, structural, and positional embeddedness – and argue that the ambiguity faced by a firm in appropriately identifying the nature or impacts of major disruptions is a function of these network properties. Based on a survey of large North American manufacturing firms, I found that the extent of the relational ties a firm has and its position in the network are significantly related to supply chain risk related ambiguity. However, this study did not provide any significant support for the hypothesized relationship between structural embeddedness and ambiguity. My research contributes towards the study of supply chain disruptions by using the idea of bounded rationality to understand supply chain risk related ambiguity and by providing evidence that the structure of supply chain networks influences the organizational understanding of and responses to supply chain disruptions.

Understanding Network Governance: A Case Study Exploration of Active Canada 20/20

Consistent with the governance shift towards network forms of governance, a number of new social movements have formed in response to the declining levels of physical activity in the Western world. One such movement is Active Canada 20/20: A Physical Activity Strategy and Change Agenda for Canada. Network governance is employed as the theoretical framework for this case study exploration of Active Canada 20/20 and the political landscape surrounding its development and implementation. Semi-structured interviews were conducted in addition to document/policy analysis and direct observations. Analysis of the data resulted in three overarching themes – the defining characteristics of network governance, the political landscape, and intersectoral linkages – that interconnect multifariously based the nature of the Canadian federal government and its relationship with the voluntary sector for physical activity. Despite progress in driving Active Canada 20/20 forward, entrenched dynamics of power need to be navigated within the political landscape surrounding network governance.

Minimal Contact Intervention for Tobacco Dependence

This study was conducted to measure the degree of adherence by public health care providers to a policy that requires them to implement minimal contact intervention for tobacco cessation with their clients. This study also described what components of the intervention may have contributed to the adherence of the policy and how health care providers felt about adhering to the policy. The intervention consisted of a policy for implementation of minimal contact intervention, changes to documentation, a health care provider mentor trained, a training session for health care providers, and ongoing paper and people supports for implementation. Data for this study were collected through a health care provider questionnaire, focus group interviews, and a compliance protocol including a chart audit. The findings of this study showed a high degree of adherence to the policy, that health care providers thought minimal contact intervention was important to conduct with their clients, and that health care providers felt supported to implement the intervention. No statistically significant difference was found between new and experienced health care providers on 17 of the 18 questions on the health care provider questionnaire. However there was a statistically significant difference between new and experienced health care providers with respect to their perception that “clients often feel like they have to accept tobacco cessation information from me.” Changes could be made to the minimal contact intervention and to documentation of the intervention. Implications for future research include implementation within other programs within Hamilton Public Health Services and implementation of this model within other public health units and other types of health care providers within Ontario.