General control of atoms and molecules has long been a goal for atomic physicists and physical chemists. Techniques such as laser cooling have been a huge breakthrough in studying ultra cold atoms and BECs. Although laser cooling has been a remarkable tool, it is limited to small group of atoms on the periodic table. A general technique to control and manipulate the entire periodic table has been out of reach until now. In this thesis I describe two methods of general control of atoms in the contexts of stopping supersonic beams and of isotope separation. Both these methods take advantage of high flux supersonic beams and the fact that every atom has a magnetic moment in the ground state or a long-lived excited state which can be manipulated using magnetic field gradients. The first method uses a series of pulsed electomagnetic coils to slow and stop a supersonic beam of paramagnetic atoms and molecules. We have demonstrated the slowing of metastable neon and molecular oxygen using 64 coils from 446.5 m/s to 55.8 m/s for metastable neon, and from 389 m/s to 83 m/s for molecular oxygen respectively. The second method is a novel and efficient approach to isotope separation which utilizes the concept of Maxwell's Demon. We call this technique Single-Photon Atomic Sorting as it is closely related to Single-Photon Cooling, a cooling technique developed in our laboratory. Our method uses a laser beam to change the magnetic moment to mass ratio in such a way that the desired isotopes are guided through a multi-pole magnetic field and collected. We show simulation results for various test cases which highlight the general applicability of this method. / text

In order to optimize limited infrastructure, many power systems are frequently operated close to critical, or bifurcation, points. While operating close to such critical points can be economically advantageous, doing so increases the probability of a blackout. With the continued deployment of Phasor Measurement Units (PMUs), high sample rate data are dramatically increasing the real time observability of the power grids. Prior research has shown that the statistics of these data can provide useful information regarding network stability and associated bifurcation proximity. Currently, it is not common practice for transmission and distribution control centers to leverage the higher order statistical properties of PMU data. If grid operators have the tools to determine when these statistics warrant control action, though, then the otherwise unused statistical data present in PMU streams can be transformed into actionable information. In order to address this problem, we present two methods that aim to gauge and improve system stability using the statistics of PMU data. The first method shows how sensitivity factors associated with the spectral analysis of the reduced power flow Jacobian can be used to weight and filter incoming PMU data. We do so by demonstrating how the derived participation factors directly predict the relative strength of bus voltage variances throughout a system. The second method leverages an analytical solver to determine a range of "critical" bus voltage variances. The monitoring and testing of raw statistical data in a highly observable load pocket of a large system are then used to reveal when control actions are needed to mitigate the risk of voltage collapse. A simple reactive power controller is then implemented that pushes the stability of the system back to a stable operating paradigm. Full order dynamic time domain simulations are used in order to test this method on both the IEEE 39 bus system and the 2383 bus Polish system. We also compare this method to two other, more conventional, controllers. The first relies on voltage magnitude signals, and the second depends only on local control of a reactive power resource. This comparison illustrates how the use of statistical information from PMU measurements can substantially improve the performance of voltage collapse mitigation methods.

A l'origine de notre travail se trouve le constat selon lequel, lorsqu'on s'intéresse au vieillissement, les recherches sont partitionnées en une multitude de domaines, de paradigmes expérimentaux et de théories résultant en un large puzzle de connaissance. Pourtant, au niveau comportemental, malgré les apparentes différences entre tous les champs d'étude, il existe des résultats empiriques montrant des évolutions communes dans les comportements des différents systèmes fonctionnels au cours de l'âge. C'est le cas notamment pour les tâches cognitives et sensorimotrices. Par exemple, pour les tâches où la rapidité est le critère de performance, les personnes âgées sont plus lentes que les jeunes ; elles sont aussi plus variables et moins adaptables face à l'augmentation de la difficulté. On observe cela à la fois au niveau cognitif et au niveau sensori-moteur. Plus généralement, avec l'âge les corrélations entre les performances de différents domaines fonctionnels augmentent, notamment entre la cognition et la sensori-motricité (Schäfer et al., 2006 ; Lindenberger & Ghisletta, 2009). Nous avons donc voulu comprendre comment et pourquoi des phénomènes comportementaux communs étaient observés aussi bien dans la cognition que la sensori-motricité. Une hypothèse envisagée est qu'ils seraient dus à des modifications structurelles et fonctionnelles du système nerveux central qui deviendrait de moins en moins différencié au fur et à mesure de l'avancement dans la vie (Reuter-Lorenz & Park, 2010 ; Heuninckx et al., 2005). C'est cette hypothèse que nous avons voulu explorer. / The starting point of this work was to realize that, when looking at aging research, studies are split in a multitude of domains, paradigms and theories resulting in a vast puzzle of knowledge. However, at the behavioral level, despite obvious differences between field of studies, there are empirical results showing common evolution between functional systems during the aging process. It is notably the case for cognitive and sensorimotor tasks. For example, when speed is the performance criterion, elderly are slower than their younger counterparts; there are also more variable and less adaptable as difficulty increases. These phenomenons can be observed in both cognitive and sensorimotor domain. More generally, correlation between performance in different functional domain increases through aging, and most notably between the cognitive and sensorimotor domain (Schäfer et al., 2006 ; Lindenberger & Ghisletta, 2009). We thus wanted to understand how and why those common behavioral phenomenon were observed. A considered hypothesis is that there would come from structural and functional modifications of the central nervous system which would become less and less differentiated through the course of aging (Reuter-Lorenz & Park, 2010 ; Heuninckx et al., 2005). We wanted to explore this hypothesis. At the start of our work, to our knowledge there was no theoretical framework explaining the compression of the cognitive and sensorimotor system in one less differentiated.

Context: The study of expertise in medical education has tended to follow the traditions of describing either the analytic processes or the non-analytic resources that experts acquire with experience. We argue that a critical function of expertise is the ability to transition from the automatic mode to the more effortful mode when required – a transition referred to as ‘slowing down when you should’. Objectives: To explore the phenomenon of ‘slowing down when you should’ in operative surgical practice and its role in intra-operative surgical judgment, and to develop conceptual models of the factors involved in the display of this transition in surgical operative practice. Design: In Phase 1A, 28 surgeons were interviewed about their views of surgical judgment in general and their perceptions of the role of this phenomenon in operative judgment. In Phase 1B, a subset of surgeons from Phase 1A was re-interviewed to explore their perceptions of automaticity in operative practice. In Phase 2, observational sessions (and brief interviews) were conducted of surgeons in the operating room to explore the nature of this phenomenon in its natural environment. Results: The surgeons in this study recognized the phenomenon of ‘slowing down’ in their operative practice and acknowledged its link to surgical judgment. Two main initiators were described and observed: proactively planned ‘slowing down’ moments occurring intra-operatively initiated by critical events anticipated pre-operatively and situationally responsive ‘slowing down’ moments initiated by emergent cues intra-operatively. Numerous influences of this transition were uncovered. A control dynamic emerged as surgeon’s negotiated ‘slowing down’ moments through trainees in their supervisory academic practice. Numerous manifestations of this phenomenon were observed in the operating room and considered using a cognitive psychology attention capacity model. Conclusions: This study offers a conceptual framework for understanding the role of ‘slowing down when you should’ in operative surgical practice, providing a vocabulary that will allow more explicit consideration of what contributes to surgical expertise. Consideration of this framework with its consequent ability to make surgical practices more explicit has implications for self-regulation in practice, surgical error, and surgical training.

Context: The study of expertise in medical education has tended to follow the traditions of describing either the analytic processes or the non-analytic resources that experts acquire with experience. We argue that a critical function of expertise is the ability to transition from the automatic mode to the more effortful mode when required – a transition referred to as ‘slowing down when you should’. Objectives: To explore the phenomenon of ‘slowing down when you should’ in operative surgical practice and its role in intra-operative surgical judgment, and to develop conceptual models of the factors involved in the display of this transition in surgical operative practice. Design: In Phase 1A, 28 surgeons were interviewed about their views of surgical judgment in general and their perceptions of the role of this phenomenon in operative judgment. In Phase 1B, a subset of surgeons from Phase 1A was re-interviewed to explore their perceptions of automaticity in operative practice. In Phase 2, observational sessions (and brief interviews) were conducted of surgeons in the operating room to explore the nature of this phenomenon in its natural environment. Results: The surgeons in this study recognized the phenomenon of ‘slowing down’ in their operative practice and acknowledged its link to surgical judgment. Two main initiators were described and observed: proactively planned ‘slowing down’ moments occurring intra-operatively initiated by critical events anticipated pre-operatively and situationally responsive ‘slowing down’ moments initiated by emergent cues intra-operatively. Numerous influences of this transition were uncovered. A control dynamic emerged as surgeon’s negotiated ‘slowing down’ moments through trainees in their supervisory academic practice. Numerous manifestations of this phenomenon were observed in the operating room and considered using a cognitive psychology attention capacity model. Conclusions: This study offers a conceptual framework for understanding the role of ‘slowing down when you should’ in operative surgical practice, providing a vocabulary that will allow more explicit consideration of what contributes to surgical expertise. Consideration of this framework with its consequent ability to make surgical practices more explicit has implications for self-regulation in practice, surgical error, and surgical training.

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The motivation for this research is to leverage the increasing deployment of the phasor measurement unit (PMU) technology by electric utilities in order to improve situational awareness in power systems. PMUs provide unprecedentedly fast and synchronized voltage and current measurements across the system. Analyzing the big data provided by PMUs may prove helpful in reducing the risk of blackouts, such as the Northeast blackout in August 2003, which have resulted in huge costs in past decades. In order to provide deeper insight into early warning signs (EWS) of catastrophic events in power systems, this dissertation studies changes in statistical properties of high-resolution measurements as a power system approaches a critical transition. The EWS under study are increases in variance and autocorrelation of state variables, which are generic signs of a phenomenon known as critical slowing down (CSD). Critical slowing down is the result of slower recovery of a dynamical system from perturbations when the system approaches a critical transition. CSD has been observed in many stochastic nonlinear dynamical systems such as ecosystem, human body and power system. Although CSD signs can be useful as indicators of proximity to critical transitions, their characteristics vary for different systems and different variables within a system. The dissertation provides evidence for the occurrence of CSD in power systems using a comprehensive analytical and numerical study of this phenomenon in several power system test cases. Together, the results show that it is possible extract information regarding not only the proximity of a power system to critical transitions but also the location of the stress in the system from autocorrelation and variance of measurements. Also, a semi-analytical method for fast computation of expected variance and autocorrelation of state variables in large power systems is presented, which allows one to quickly identify locations and variables that are reliable indicators of proximity to instability.

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