Abstract In 2007, an adaptive grazing management process began on the Santa Rita Experimental Range (SRER) in southern Arizona with a primary management objective to reduce repeated defoliation of perennial bunchgrass plants during the summer growing season. In order to follow defoliation events, 1400 individual plants were identified in 6 pastures scheduled for summer grazing from June 15 to October 2, 2013. Plant height and diameter categories were measured before cattle entered each pasture and were re-measured daily or alternate days throughout the grazing period. The differences between heights and diameters were used to calculate any regrowth that occurred. Of the 1400 plants marked, 738 (52.7%) were not defoliated, 453 (32.3%) plants were defoliated once, 199 (14.2%) plants were defoliated twice, and 10 (0.7%) plants were defoliated three-times for a total of 881 defoliation events recorded. The majority of first defoliation events and first incidences of second defoliation occurred on day 3. Cattle began switching their grazing strategy from undefoliated plants to new growth of previously defoliated plants by day 9 with 48 of a total 161 previously defoliated plants being defoliated. The highest number of second defoliations were measured on day 11 when 115 plants were observed as having been defoliated for a second time and 5 plants were defoliated for a third time. Arizona cottontop (Digitaria californica) had a higher percentage of both single and multiple defoliation events when compared to the other perennial grass species. Distance from a permanent water source was not found to have a significant impact on the number of defoliations that an individual plant received. Plants defoliated the first time were taller and had a larger circumference (21.0±5.6 cm and 40.8±9.0 cm) than plants that were re-defoliated (15.5±5.6 cm and 31.4±9.0 cm). This study found that the planned 10 day SRER grazing rotation, when followed, would minimize multiple defoliations by cattle on perennial bunchgrasses.

Spike-timing dependent plasticity is a learning mechanism used extensively within neural modelling. The learning rule has been shown to allow a neuron to find the onset of a spatio-temporal pattern repeated among its afferents. In this thesis, the first question addressed is ‘what does this neuron learn?’ With a spiking neuron model and linear prediction, evidence is adduced that the neuron learns two components: (1) the level of average background activity and (2) specific spike times of a pattern. Taking advantage of these findings, a network is developed that can train recognisers for longer spatio-temporal input signals using spike-timing dependent plasticity. Using a number of neurons that are mutually connected by plastic synapses and subject to a global winner-takes-all mechanism, chains of neurons can form where each neuron is selective to a different segment of a repeating input pattern, and the neurons are feedforwardly connected in such a way that both the correct stimulus and the firing of the previous neurons are required in order to activate the next neuron in the chain. This is akin to a simple class of finite state automata. Following this, a novel resource-based STDP learning rule is introduced. The learning rule has several advantages over typical implementations of STDP and results in synaptic statistics which match favourably with those observed experimentally. For example, synaptic weight distributions and the presence of silent synapses match experimental data.

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal.

Midlife women are vulnerable to developing obesity. Both sleep timing and negative emotion are risk factors, yet limited research has explored their role on weight outcomes in this population. The current investigation explored the association of sleep timing (i.e., mean sleep time, sleep time variability) and obesity (i.e., BMI, waist circumference) in midlife women, considering emotional pathways (i.e., depressive symptoms, anger) that might mediate this association. PROCESS parallel mediation models assessed direct and indirect pathways. In follow-up analyses, sleep duration was explored as an indirect pathway linking sleep timing to obesity. Results demonstrated that sleep timing does not directly predict obesity. Emotion was also not a significant indirect pathway. Conversely, sleep duration emerged as an indirect link in the sleep timing and obesity association. Future work is needed to further disentangle the impact of sleep on weight in midlife women using prospective, well-controlled studies, implementing daily assessments of sleep behavior.

Title: Effects of PNF to change the motoric stereotype of the abduction in the shoulder joint Objectives: The aim of this thesis, which is conceived as a pilot experimental study is to verify the changes in the timing of selected muscles during stereotype abduction of the shoulder after performing repetitive cyclic motion by therapeutic method PNF if a specific number of repetitions of the movement is performed. Methods: This is a pilot experimental study, which was done on seven probands, 4 men and 3 women with an average age of 26.6 years. The surface EMG muscle activity was scanned on selected muscles during the motoric testing of stereotype of the abduction of the shoulder joint before and after the PNF techniques. The EMG signal was then analyzed and we evaluated the timing of muscles before and after the PNF techniques. The results were then compared in terms of both intra-individually and inter-individually comparison. Results: Results provided contradictory answers to the fundamental questions relating to changes in the timing of selected muscles after PNF techniques. In terms of the change in intra-individually timing after PNF hypothesis was proved. But from the perspective of inter-individually comparison the hypothesis was not proved. Keywords: PNF, surface electromyography, motion...

Title: Assessment of the timing of tennis strokes using kinematic analysis and surface electromyography Aims: Assess the timing of tennis forhand, service and appropriate training exercises using kinematic analysis. Describe the activation of muscles in time for the chosen execution of the strokes by recording surface electromyography (SEMG). Compare the results of various executions and describe the differences between using the racquets with different parameters and between executions of various training exercises. Method: Case study using kinematic analysis and surface electromyography was made. Results: We have found out that the execution of the strokes using the players own racquet was the most stable. We have found the differences in timing while using various racquets. The heavier the equipment we are using in training exercise is the more different is the timing of this movement. We concluded that the chosen training exercises are inappropriate as the special exercises to improve coordination. Key words: tennis, timing, service, forhand, electromyographic analysis, kinematic analysis

In the thesis, we investigate whether hedge fund managers have liquidity timing skills in the fixed income market, foreign exchange market and commodity market, respectively. Managers with the liquidity timing skills can strategically adjust hedge funds exposure to the target financial market based on their forecasts about the future changes in market liquidity. We find empirical evidence that hedge funds in certain categories have the skills to time the liquidity levels in the fixed income market, foreign exchange market and commodity market. We conduct a range of robustness tests, which show that hedge funds still exhibit liquidity timing skills after controlling for the factors that may affect timing ability. In particular, our findings are robust to the usage of leverage, funding constraints, investor redemption restrictions, hedge funds trades on market liquidity, financial crisis, hedge fund data biases, market return and volatility timing, liquidity risk factor, systematic stale pricing and option factors. We also conduct bootstrap analysis to ensure the results are not dependent on the normality assumption. Our investigation is helpful to understand the importance of market liquidity to hedge funds professional portfolio management.

Doctor of Philosophy / Department of Agronomy / P. V. Vara Prasad / Sweet sorghum (Sorghum bicolor L. Moench) is an important bioenergy crop. There is a wide array of genetic diversity in sweet sorghum germplasm collections. However, information on traits associated with sugar yield, optimum harvesting time for maximum sugar yield, effects of abiotic stresses on sugar yield is scarce. The objectives of the present study were: to identify traits that are associated with sugar yield, to determine the optimum harvesting time for maximum sugar yield and to understand the physiological responses of different sweet sorghum genotypes to drought and high temperature. In order to meet these objectives, five independent field and greenhouse studies were conducted. Field experiments were conducted using 280 sweet sorghum germplasm and were evaluated for 2 years. From this study, 30 genotypes representing high and low sugar yielders were selected for the subsequent experiment. We observed a significant variation in physiological, morphological and sugar yield traits associated with biofuel production. In the selection experiment, investigations on the morphological, physiological attributes helped to identify those characters which influence or limit sugar yield in the sweet sorghum. Another field study was conducted to optimize the harvesting time for obtaining highest sugar and juice yields in sweet sorghum. Sweet sorghum variety M81E was harvested at ten growth stages. Our results suggest that the optimum time for harvesting of sweet sorghum cultivar M81E is between milk and hard dough stages when highest sugar yield was observed. Studies on different levels of water stress were studied under greenhouse conditions. Four sweet sorghum genotypes (Awanlek, Smith, Tracy and Wray) were subjected to three water stress treatments (100% pot capacity (PC); 70% PC and 30% PC) for 20 days at early seed filling (Milk) stage. The results showed that genotypes differed significantly for all growth and yield, biochemical and physiological traits. Severe water stress significantly decreased juice and sugar yields by decreasing net photosynthetic rate, transpiration rate, stomatal conductance and sucrose content in the stem juice. Genotypes Tracy and Wray produced significantly highest brix, stem fresh weight, juice and sugar yield under both irrigated and water stress conditions. In another greenhouse study, we quantified the effects of drought, high temperature, and their combinations on growth, physiology and yield of sweet sorghum genotypes. The same four genotypes above were subjected to four treatments, T1 - control, T2 - drought stress, T3 - high temperature stress and T4 - combination of drought and high temperature for 16 days after anthesis. The result showed that significant difference was observed for growth and yield traits, physiological traits and non-reducing and total sugar content in juice for genotypes and treatments. Among the genotypes Tracy recorded higher juice and sugar yield. Among the various treatments, combination of drought and high temperature was found to be more deleterious in reducing most of the biofuel traits followed by drought and high temperature stress. The above studies gave significant findings with regards to the identification of superior sweet sorghum germplasm, their tolerance capacity to different abiotic stresses, which allows better selection for the use of bioenergy production.

Master of Science / Department of Biology / Brett K. Sandercock / The migratory period is a critical time for birds. Population declines in long-distance migratory birds have been associated with trophic mismatches among climate change, timing of food availability, and timing of migratory movements. Studies on migratory songbirds have been limited to eastern North America and Europe, and migration strategies of birds may differ along the Pacific flyway. We evaluated the stopover ecology of five species of migratory songbirds at a coastal site in northern California. We found variation in changes in timing of spring migration, but consistent changes in timing of autumn migration over a 22-year period. Timing of spring migration advanced for Swainson’s Thrushes (Catharus ustulatus) and Yellow Warblers (Setophaga petechia), was compressed for Pacific-slope Flycatchers (Empidonax difficilis) and Wilson’s Warblers (Cardellina pusilla), but was protracted for Orange-crowned Warblers (Oreothlypis celata). In contrast, timing of autumn migration was delayed for Pacific-slope Flycatchers, Orange-crowned Warblers, and Yellow Warblers, but was protracted for Wilson’s Warblers. Warm, wet conditions were associated with advanced spring migration, and warm, dry conditions were associated with delayed autumn migration. Changes in timing of migration related to climate conditions were strongest for Pacific-slope Flycatchers and Orange-crowned Warblers. Stopover duration of our five study species was longer than songbirds in eastern flyways, and on average, was longer in spring than autumn. Pacific-slope Flycatchers and Yellow Warblers had longer stopovers in spring, whereas Swainson’s Thrushes and Wilson’s Warblers stopped had longer stopovers in autumn. Birds captured at low body mass had longer stopovers in spring and autumn. Migratory birds in western North America may have different migration strategies because of differences in climate and geography, but more study is needed to discover migratory routes and compare our results to other stopover sites along the Pacific flyway. Understanding differences in migration strategies of different populations of the same species are important in directing conservation efforts, especially in light of ongoing climate change.

With advances in technology, modern integrated circuits have higher complexities and reduced transistor sizing. In deep sub-micron, the parameter variation-control is difficult and component delays vary from one manufactured chip to another. Therefore, the delays are not discrete values but are a statistical quantity, and statistical evaluation methods have gained traction. Furthermore, fault injection based gate-level fault coverage is non-scalable and statistical estimation methods are preferred. This dissertation focuses on scalable statistical methods to select critical paths in the presence of process variations, and to improve the defect coverage for complex integrated circuits. In particular, we investigate the sensitization probability of a path by a test pattern under statistical delays. Next, we investigate test pattern generation for improving the sensitization probability of a path, selecting critical paths that yield high defect coverage, and scalable method to estimate fault coverage of complex designs using machine learning techniques.