The biomechanics and muscle activity of forward and backward slope walking was investigated in humans to gain additional insight into neural control strategies. An adjustable instrumented ramped walkway was constructed and validated. Kinematic, ground reaction force, and muscle activity data were collected from nine subjects walking at three grades (0%, 15%, and 39%) for each of four conditions (forward upslope and downslope and backward upslope and downslope). The changes observed in the data were generally progressive from 0% to 15% to 39% grade. During forward downslope walking the joint moment pattern at the knee changed significantly, power absorption increased, and changes in the muscle activity patterns corresponded directly to changes in joint mechanics. During forward upslope walking, the hip joint moment pattern changed significantly, power generation increased, and changes in the muscle activity pattern were not directly related to changes in the joint moments at all joints. The muscle activity pattern data suggest that modifications to the level walking control strategies were necessary during slope walking. Backward slope walking was used to further explore these findings. Backward upslope and forward downslope kinematics and kinetics were similar, as were those from backward downslope and forward upslope walking. However, power generation increased during upslope walking tasks and power absorption increased during downslope walking tasks, and the changes in muscle firing patterns were more similar for these tasks than for those with similar kinetics. Increased power generation required compensatory muscle activity at adjacent joints that was not directly related to the moments at those joints; increased power absorption did not require such compensatory activity, and muscle activity was directly related to the joint moments. Overall, these data suggest that changes in the control strategy and/or modifications of the level walking control strategy are strongly influenced by the power demands of a task. The characterization of forward and backward slope walking presented here is novel and has important implications for many patient populations; knowledge of the task mechanics may be used to develop or improve physical therapy and rehabilitation exercise programs as well as the design of replacement and/or assistive devices.

Unconventional reservoir systems can best be described as petroleum (oil and/or gas) accumulations which are difficult to be characterized and produced by conventional technologies. In this work we present the development of a systematic procedure to evaluate well performance in unconventional (i.e., low to ultra-low permeability) reservoir systems. The specific tasks achieved in this work include the following: ● Integrated Diagnostics and Analysis of Production Data in Unconventional Reservoirs: We identify the challenges and common pitfalls of production analysis and provide guidelines for the analysis of production data. We provide a comprehensive workflow which consists of model-based production analysis (i.e., rate-transient or model matching approaches) complemented by traditional decline curve analysis to estimate reserves in unconventional reservoirs. In particular, we use analytical solutions (e.g., elliptical flow, horizontal well with multiple fractures solution, etc.) which are applicable to wells produced in unconventional reservoirs. ● Deconvolution: We propose to use deconvolution to identify the correlation between pressure and rate data. For our purposes we modify the B-spline deconvolution algorithm to obtain the constantpressure rate solution using cumulative production and bottomhole pressure data in real time domain. It is shown that constant-pressure rate and constant-rate pressure solutions obtained by deconvolution could identify the correlation between measured rate and pressure data when used in conjunction. ● Series of Rate-Time Relations: We develop three new main rate-time relations and five supplementary rate-time relations which utilize power-law, hyperbolic, stretched exponential, and exponential components to properly model the behavior of a given set of rate-time data. These relations are well-suited for the estimation of ultimate recovery as well as for extrapolating production into the future. While our proposed models can be used for any system, we provide application almost exclusively for wells completed in unconventional reservoirs as a means of providing estimates of time-dependent reserves. We attempt to correlate the rate-time relation model parameters versus model-based production analysis results. As example applications, we present a variety of field examples using production data acquired from tight gas, shale gas reservoir systems.

Worldwide, unconventional resources are important sources of oil and gas when most conventional resources are declining and demand for hydrocarbons is growing. The Masters? (1979) concept of the energy resource triangle suggest that the exploitation of unconventional reservoirs is particularly sensitive to both technology and commodity price parameters. In the United States, production from unconventional reservoirs has been stimulated by a combination of Federal tax credits, technical development programs -supported by government agencies and private organizations- and high commodity prices. In this work, the effect of technology and different economic events for selected unconventional oil and gas plays in the United States was evaluated according to the concept of the Resource Triangle Theory (RTT). Studies conducted in the Austin Chalk -our textbook case- and other seven unconventional plays in the United States have supported the RTT concept that high prices and better technologies do result in more drilling activity and more oil and gas production from unconventional reservoirs. For instance, two approaches were employed to support RTT concept: Correlation study and Forecasting graphs. On the first one, correlations of commodity prices and technology with drilling activity demonstrated that periods of high commodity prices coincide with increase in unconventional producing wells approximately 75% from selected plays in this study. The second one shows that high prices and technological advances also translate into additional oil and gas production and reserves. This behavior was observed through the analysis of a series of decline production curves using a VBA program in Excel that compute oil and gas production volumes and their corresponding economic values under specific conditions. The results indicated that maximum value of approximately $50 billion oil plus gas would have been possible using conventional hydraulic fracturing technology only. Moreover, subsequent episodes of high commodity allow the introduction of new technologies that have boosted even more oil and gas production from the plays. Great examples are the use of horizontal and multilateral wells which has opened up additional areas for development, such as the Barnett Shale and the Bakken Shale. Using horizontal wells has also revived older plays, such as the Austin Chalk. The combination of horizontal well technology and water fracturing technology has led to a dramatic increase in the development of both oil and gas from shale reservoirs. Current production schemes suggest that the plays could produce an additional of $320 billion when producing at rates higher than 5 BOE/day. Our results confirm the concept of the resource triangle that natural gas and oil resources can be produced from low quality resources when either product prices increase or when better technology is available. The seven oil and gas plays studied in this research are demonstrative examples.

The recent success in economical production of US shales and other low permeability reservoirs is primarily due to advances in hydraulic fracturing. In this well stimulation technique, a fracturing fluid is injected into the reservoir at pressures high enough to break down the reservoir rock and form fractures. The fractures drain the hydrocarbons in the rock matrix and provide connected pathways for the transport of hydrocarbons to the wellbore. Given the low permeability of the matrix, recent studies of shale gas production suggest that nearly all of the production has to come from a ramified, well-connected network of fractures. A recent study has shown, however, that for reasons yet unknown, the production history of more than 8000 wells in the Barnett Shale can be fit with reasonable accuracy with a linear flow model based on parallel planar hydraulic fractures perpendicular to the wellbore and spaced 1-2 meters apart. The current study is carried out to provide insights into the formation and production properties of complex hydraulic fracture networks. The end goal here is optimization of hydraulic fracture treatments: creating better-connected, more productive fracture networks that can drain the reservoir more quickly. The study provides a mechanistic model of how complexity can emerge in the pattern of hydraulic fracture networks, and describes production from such networks. Invasion percolation has been used in this study to model how the pattern of hydraulic fracture networks develop. The algorithm was chosen because it allows quick testing of different “what if” scenarios while avoiding the high computation cost associated with numerical methods such as the finite element method. The rules that govern the invasion are based on a proposed geo-mechanical model of hydraulic fracture-natural fracture interactions. In the geo-mechanical model, development of fracture networks is modeled as a sequence of basic geo-mechanical events that take place as hydraulic fractures grow and interact with natural fractures. Analytical estimates are provided to predict the occurrence of each event. A complex network of connected fractures is the output of the invasion percolation algorithm and the geo-mechanical model. To predict gas production from the network, this study uses a random walk algorithm. The random walk algorithm was chosen over other numerical methods because of its advantage in handling the complex boundary conditions present in the problem, simplicity, accuracy and speed. / text

Current models used to forecast production in unconventional oil and gas formations are often not producing valid results. When traditional decline curve analysis models are used in shale formations, Arps b-values greater than 1 are commonly obtained, and these values yield infinite cumulative production, which is non-physical.. Additional methods have been developed to prevent the unrealistic values produced, like truncating hyperbolic declines with exponential declines when a minimum production rate is reached. Truncating a hyperbolic decline with an exponential decline solves some of the problems associated with decline curve analysis, but it is not an ideal solution. The exponential decline rate used is arbitrary, and the value picked greatly effects the results of the forecast. A new empirical model has been developed and used as an alternative to traditional decline curve analysis with the Arps equation. The new model is based on the concept of logistic growth models. Logistic growth models were originally developed in the 1830s by Belgian mathematician, Pierre Verhulst, to model population growth. The new logistic model for production forecasting in ultra-tight reservoirs uses the concept of a carrying capacity. The carrying capacity provides the maximum recoverable oil or gas from a single well, and it causes all forecasts produced with this model to be within a reasonable range of known volumetrically available oil. Additionally the carrying capacity causes the production rate forecast to eventually terminate as the cumulative production approaches the carrying capacity. The new model provides a more realistic method for forecasting reserves in unconventional formations than the traditional Arps model. The typical problems encountered when using conventional decline curve analysis are not present when using the logistic model. Predictions of the future are always difficult and often subject to factors such as operating conditions, which can never be predicted. The logistic growth model is well established, robust, and flexible. It provides a method to forecast reserves, which has been shown to accurately trend to existing production data and provide a realistic forecast based on known hydrocarbon volumes. / text

The purpose of this study was to describe the relationships among common signs/symptoms (depression, fatigue, declines in cognitive function) in women with multiple sclerosis (MS) using a modified version of Braden's Self Help Theoretical Model and evaluate whether depression, fatigue, declines in cognitive function and uncertainty, enabling skills (self-control in this study) and self-management (coping in this study) influence quality of life outcomes in women with MS. MS is one of the most common causes of disability among young adults and is the most prevalent neurological disease among young and middle-aged adults in certain parts of the world. Although research had previously been undertaken with regards to the common symptoms of MS, uncertainty, enabling skills, self-management and quality of life, there had been no studies undertaken that involved all of them. This descriptive study was the first to explore relationships among common symptoms of MS, uncertainty, enabling skills, self-management and quality of life in an MS population using Braden's Learned Response Chronic Illness Self Help Model. A cross-sectional descriptive study was conducted with 106 participants. Measurement tools utilized in the study included: 1) Demographic and Illness Characteristics, 2) The Modified Fatigue Impact Scale, 3) Perceived Deficits Questionnaire, 4) Patient Health Questionnaire-9, 5) Mishel's Uncertainty in Illness Scale- Adult, 6) Rosenbaum's Self-Control Scale- Modified, 7) COPE Inventory-Brief, and 8) SF-36 Health Status Questionnaire. Data analysis involved descriptive statistics, correlations and linear regression to answer the specific aims. The study findings indicate that relationships exist among depression, fatigue, declines in cognitive function, uncertainty, enabling skills and self-management in women with MS. The study findings also indicate that depression, fatigue, declines in cognitive function, uncertainty, enabling skills and self-management influence quality of life outcomes in women with MS. Finally, while only a first study, the research findings indicate using a modified version of Braden's Learned Response Chronic Illness Self Help Model (LRCISHM) is appropriate in a population of women with MS. Future research involving women with MS who meet the inclusion criteria across the contiguous United States as well as male military veterans with MS is recommended. Research involving this modified version of Braden's LRCISHM as well as research incorporating disability levels is recommended. Research to develop interventions to improve quality of life outcomes and minimize distress is also recommended.

The effect of fruit removal from cantaloupe was studied under field conditions in a soil naturally infested with Monosporascus cannonballus. Fruit removal resulted in greater sugar accumulation in the cantaloupe roots compared to the roots from plants on which the fruits were allowed to develop normally. Individual, total, and combined root carbohydrate levels were greater in plants without fruit than in plants with fruit. Five major sugars (stachyose, raffinose, sucrose, glucose, and fructose) were found in the cantaloupe roots. Stachyose concentrations were higher than all the other sugars in the cantaloupe roots. Disease severity on the cantaloupe roots with fruit removed was less severe than on roots of plants with fruit, and dry weights were higher in the fruit removal treatment than those of the fruit non-removal treatment. Fruit removal results in increased root growth and carbohydrate accumulation in the cantaloupe roots. Root sugar concentrations affected infection efficiency and disease progress of Monosporascus root rot and vine decline. Therefore, the retarded development of Monosporascus root rot and vine decline is associated with a greater carbohydrate accumulation in the cantaloupe root.

At the present time, wireless sensor networks are becoming more and more  common and energy consumption is a key factor in the deployment and  maintenance of these networks. This thesis compares non-SFN multi-hop and  a single frequency network (SFN) or cooperative diversity algorithms with  respect to the energy consumed by the nodes. Since the nodes have limited  power capacity it is extremely important to have an efficient algorithm. In  addition, the behaviour of the network when SFN is employed must be  studied and advice offered with regards to improvements in order to achieve  preferential results. The effect on the network regarding macro diversity is  positive but, the battery energy consumption is still higher and has a drainage  effect on the network for simple multi-hop. The report will include  background information regarding mobile ad-hoc networks and the  relationship with cooperative diversity. It will also deal with how different  algorithms affect the energy consumption in multi-hop networks. Simulations  will also be presented in Matlab plots for two single frequency network  scenarios against a simple multi-hop regarding node energy during the  network discovery and decline. Results will include comparative figures which  are followed by a discussion concerning the simulation results and its effects.  The applications for wireless sensor networks include area monitoring,  environmental monitoring, data logging, industrial monitoring, agriculture  and the idea can additionally be used for wireless radio and TV distribution.  The simulations have been conducted for cooperative diversity algorithms  (SFN-A and SFN-D) against an algorithm which does not use cooperative  diversity in Matlab. The node energy consumption is compared for both  scenarios with regards to both  network reachability and decline. The node  power is analysed during the reachability of the network from the start to  attaining 100% of the discovered network. During network decline, the  behaviour of the node energy is studied for algorithms with SFN-A, SFN-D  and non SFN.  Also, the number of times node transmission occurs with  regards to  node discovery is also analysed.

Much attention is paid to the increasing number of people living in cities while a relatively understudied but related phenomenon is silently gaining strength: that of “shrinking cities.” In the context of massive economic restructuring and increasing globalization, a growing number of cities in industrialized countries such as the United States and Canada are experiencing a population decline. The usual approach of planners in shrinking cities is either to do nothing or to focus on “growing” their cities to previous population levels. To date, both approaches have been largely unsuccessful. This leads to the question I ask in this thesis: What are other possible approaches to planning besides a population and economic growth orientation that might be successfully implemented in shrinking cities? A small but growing number of shrinking cities researchers are encouraging planners in shrinking cities neither to focus on growth nor to ignore decline but to focus on planning to meet the needs of the remaining population. While improving the quality of life of existing residents should be the goal of planners in all cities – growing or declining – what is different about this approach in the context of shrinkage is the belief that shrinking cities can offer a high quality of life. In this thesis, I use four general principles of “good planning” in shrinking cities, collected from the literature, as a point of departure for comparing the recent planning exercises in two shrinking cities: Youngstown, Ohio (which has begun to tackle the issues of population decline in a way that is ostensibly resembles the principles of good planning) and Sudbury, Ontario (which has opted for the traditional “growth is the only option” approach). Based on a mix of quantitative and qualitative data, I find that the principles of “good planning” for shrinking cities are in practice difficult to achieve. Whether or not planners in shrinking cities will decide to adopt these principles is influenced by a number of factors, including the presence or absence of young, innovative leadership, levels of devolution and autonomy, current fiscal structures, local economic structure, and political dynamics.

Freshwater ecological issues are increasingly being recognized within the context of multiple stressors, even though relatively little is known about the limnological and biological consequences of the interactions between various environmental impacts. Moreover, long-term monitoring data are often lacking. To help address these issues, the overall goal of this thesis was to use paleolimnological approaches to document how multiple environmental stressors have altered limnological communities in south-central Ontario lakes. During the last two centuries, Ontario lakes have been subjected to varying intensities of different environmental impacts, including increases in shoreline residential development, forest clearance and regrowth, the deposition of strong acids via the atmosphere, invasion by non-indigenous species, and climate change. I used multiple paleolimnological approaches to: 1) demonstrate how multiple natural and anthropogenic stressors have affected biological assemblages across lakes in the Muskoka-Haliburton region of south-central Ontario, and 2) reconstruct the limnological histories of four lakes from Algonquin Park that have recorded the near complete extirpation of native crayfish species. In the Muskoka-Haliburton lakes, I assessed the extent of limnological changes that have occurred during the past ~15 years by resampling lakes from an earlier survey, using identical paleolimnological methods. Limnological monitoring data document that, since 1992, the lakes have experienced declines in lakewater calcium and SO4 concentrations, while pH declined marginally; in contrast dissolved organic carbon, silica and Total Kjeldahl Nitrogen increased. Marked regional increases in planktonic diatom taxa, including Cyclotella stelligera, Asterionella formosa and Fragilaria crotonensis, occurred in many lake systems, while colonial scaled chrysophyte algae have undergone a widespread decline in favour of unicellular forms (i.e., Mallomonas spp.), driven by interactions between resource limitation and climate change. In the Algonquin Park study lakes, crustacean zooplankton remains revealed a marked decline in daphniid species with high Ca requirements, in favour of smaller Bosmina spp., while diatom and chrysophyte analysis suggest varying degrees of industrial acidification in the four study lakes. The paleolimnological data suggest that the crayfish decline may have began prior to the long-term monitoring record, likely as a result of declines in pH and lakewater Ca related to atmospheric acid deposition. / Thesis (Ph.D, Biology) -- Queen's University, 2012-09-27 12:53:20.518