<p>  The adiabatic hyperspherical representation has been applied to study few-body systems in both ultracold atomic physics and low energy nuclear physics, as it is a powerful tool that can be used to solve a variety of few-body Hamiltonian's across a wide range of disciplines in physics. In conjunction with the adiabatic hyperspherical representation, we utilized an explicitly correlated Gaussian basis expansion, different from the traditional hyperspherical harmonic expansion typically used with this method. In atomic physics, we applied this method to study the four-body (e^-e^-e⁺e⁺) coulombic system to study positronium-positronium collisions and to get a theoretical value of the 1<em>s</em>-2<em>s</em> scattering length. This work is published in [Phys. Rev. A 100, 012711 (2019)]. We also looked at few-body physics near the unitary limit, particularly near the <em>s</em>- and <em>p</em>-wave unitary limits where the dominant length scale is the scattering length and scattering volume. On this front, we studied universal physics in this regime for the equal-mass system. This work is published in [Phys. Rev. A 106, 023304 (2022)]. This method was further applied to few-body nuclear physics.</p> <p><br></p> <p>  We treat the three and four neutron scattering problems in the <em>N</em>-body continuum to understand and gain insight into possible few-neutron resonances, most notably whether a four-neutron resonance exists. There have been many conflicting theoretical results on whether a four-neutron resonance exists that stemmed from a recent experiment by Kisimori et al. in 2016 [Phys. Rev. Lett. 116, 052501 (2016)]. To provide further theoretical insight on this problem, we use the adiabatic hyperspherical toolkit to probe the scattering continuum and from the 4<em>n</em> density of states, conclude that there is no 4<em>n</em> resonance state. Our work on this is published in [Phys. Rev. Lett. 125, 052501 (2020)] and [Phys. Rev. C 103, 024004 (2021)]. There are other few-body systems in nuclear physics that are explored in the adiabatic hyperspherical representation, including systems like the triton, helium-3, and helium-4 nuclei to visualize and characterize the different reaction pathways the <em>N</em>-body system can fragment into at a given collision energy.</p>

This thesis aims at evaluating a proposed interferometry Angle of Arrival method for Bluetooth Low Energy and investigating the feasibility of using it together with current technology in a keyless entry access control solution. The current technology is an evaluation kit from Texas Instrument that is used together with various types of antennae arranged in arrays. An in-depth look at it revealed that it does not implement the proposed Angle of Arrival method for Bluetooth Low Energy but the deviations are minor. Results obtained from tests with delay lines show enough accuracy for a keyless entry access control solution. However, none of the tested antenna types do. The work concludes that current technology cannot be used as a keyless entry access control solution due to strong antenna dependencies. Future work is thus proposed to be done on antenna development. / Detta arbete syftar till att utvärdera en förslagen interferometri Angle of Arrival-metod för Bluetooth Low Energy samt undersöka möjligheten att använda den tillsammans med nuvarande tekniken i nyckellös åtkomstkontroll. Den nuvarande tekniken är ett utvärderingspaket från Texas Instrument som används tillsammans med olika typer av antenner. En utförlig undersökning av tekniken avslöjade att den inte implementerar den föreslagna Angle of Arrival-metod för Bluetooth Low Energy men avvikelserna är minimala. Resultat som erhållits från tester med fördröjningslinjer visar tillräckligt noggrannhet för nyckellös åtkomstkontroll. Men ingen av de testade antenntyperna gör det. Arbetet drar slutsatsen att den nuvarande tekniken inte kan användas som nyckellös åtkomstkontroll på grund av starka antennberoende. Framtida arbete föreslås således att fokusera på antennutveckling.

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Low energy electron (LEE) driven chemistry underpins a wide range of interdisciplinary fields, including radiation biology, redox chemistry, astrochemistry and biomaterial design. A growing interest in the chemistry of LEEs concerns the radiative damage to DNA. Studies have found that LEEs can induce single and double-strand breaks in DNA by forming a negative ion resonance (NIR). These processes are remarkably site-specific and have been utilized to synthesize radiosensitizers, which aid in identifying target cells in hypoxic tumors in radiation therapy. Despite the prevalence of LEE-induced reactions, computational studies of such processes are limited compared to thermal and photochemical reactions. The relative scarcity in computational studies of LEE-induced reactions stems from the difficulties in the theoretical treatment of NIRs. In our work, we report new developments on the application of quantum chemical methods to NIRs. We demonstrate that the combination of approaches developed for resonances with multi reference electronic structure methods enables the computation of various types of NIRs in a single calculation. Additionally, we show that multi-reference methods can also quantify the mixing between NIRs. It is observed that the mixing between resonances can have significant consequences on their lifetimes. We also report the development of a new technique, the continuum remover Feshbach projection operator approach, which uses the conventional methods developed for bound states to characterize resonances. We show that this new approach is straightforward to implement with standard electronic structure packages, it is efficient, and provides promising results. / Chemistry

<p> The interaction mechanisms of an ion beam with a solid target are identified. Basic parameters associated with ion scattering, charge neutralization, inelastic energy losses and secondary ion production are described. Low energy (1-20 kev) experimental studies on these topics are reviewed. A low energy ion mass spectrometer is described. The ion beam is generated by an existing kev ion accelerator and is directed to a newly constructed UHV target chamer. The energy and angular distributions of the backscattered particles are measured with a hemispherical electrostatic analyser and a channeltron detector. A high precision goniometer allows target rotation about two perpendicular axes by angles of 180° and 90° with an accuracy and repeatability of 0.1°. The interaction chamber is bakeable to 250°c and was designed for an ultimate pressure of 10^-11 torr. The data acquisition system chamber scans the energy spectrum automatically so that the radiation dosage at the target is equalized for all channels. </p> / Thesis / Master of Engineering (MEngr)

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Wireless technology is used daily across the globe. A very common wireless technology is Bluetooth. The Bluetooth technology exists everywhere, from cars to mobile phones and even kitchen appliances. Recently, Bluetooth Low Energy has added support for another physical layer, LE 2M PHY. This physical layer is supposed to be faster and more energy efficient than its predecessor, LE 1M PHY, with a decrease in range. Because of this new physical layer, Bluetooth Low Energy can now compete with Bluetooth Classic during data transmission, in both speed and energy efficiency. This thesis aims to find the breaking point where Bluetooth Low Energy becomes less energy efficient than Bluetooth Classic, in relation to bit rate speed and total amount of bytes sent. Before experiments were conducted, multiple iterations of an artifact had to be done to end up with an artifact that provides valid and reliable data. The experiments were then conducted by changing the bit rate speed and sending different amounts of bytes. The results from the experiments show that Bluetooth Classic is practically both faster and more energy efficient with its fastest modulation than Bluetooth Low Energy is with LE 2M PHY enabled, even though this should not be the case theoretically. Bluetooth Classic is overall more energy efficient than Bluetooth Low Energy and thus the conclusion of this study is that no breaking points between the two technologies exist.

Ballet dancers are a unique population of athletes in that, unlike other sports, their success strictly depends on both physical capabilities and aesthetic factors. While the physical demands of the performing sport are strenuous, ballet dancers are often required to exhibit a thin physique, frequently resulting in weights 10-12% below the ideal. These low weights are commonly achieved by low energy intakes which increase dancers' susceptibility to the development of various health conditions. Research investigating the health of dancers, however, is limited and hampered by methodological limitations. To address these issues, we tested the hypothesis that dancers would report a low habitual energy intake and, therefore, be subject to conditions comprising the Female Athlete Triad, including low energy availability, suboptimal bone density and menstrual irregularities. In addition, we hypothesized that elite female dancers would have lower than expected resting metabolic rate (RMR) based upon their fat-free mass, and thus greater energetic efficiency as a result of chronic energy deficiency. As hypothesized, dancers reported a significantly lower energy intake and exhibited a lower RMR as compared to lean, pair-matched controls. Because treatment of these metabolic abnormalities is challenging, prevention of adverse health outcomes among adolescent pre-professional dancers is key in promoting overall health and optimal performance. Through our subsequent 'formative work', we determined that the current availability of nutrition education offered to both professional and pre-professional dancers is minimal and of questionable quality. Thus, we developed, implemented, and evaluated a DVD-based educational program, entitled "Nutrition for Optimal Performance", aimed at improving health knowledge and behaviors of pre-professional adolescent ballet dancers. Our findings indicate that participants increased their knowledge of basic nutrition principles and self-efficacy for adopting healthier dietary habits, as compared to pre-program and control group scores, and that knowledge gains were sustained at a six-week follow-up assessment. Collectively, these studies provide the field of dance medicine with novel findings related to the characteristics and health conditions of professional ballet dancers, and the effectiveness of a low-resource, disseminable nutrition education program which promotes the health and optimal performance of pre-professional adolescent ballet dancers. / Ph. D.

A wireless sensor node (WSN) system, capable of sensing animal motion and transmitting motion data wirelessly, is an effective and efficient way to monitor pigs' activity. However, the raw sensor data sampling and transmission consumes lots of power such that WSNs' battery have to be frequently charged or replaced. The proposed work solves this issue through WSN edge computing solution, in which a Random Forest Classifier (RFC) is trained and implemented into WSNs. The implementation of RFC on WSNs does not save power, but the RFC predicts animal behavior such that WSNs can adaptively adjust the data sampling frequency to reduce power consumption. In addition, WSNs can transmit less data by sending RFC predictions instead of raw sensor data to save power. The proposed RFC classifies common animal activities: eating, drinking, laying, standing, and walking with a F-1 score of 93%. The WSN power consumption is reduced by 25% with edge computing intelligence, compare to WSN power that samples and transmits raw sensor data periodically at 10 Hz. / Master of Science / A wireless sensor node (WSN) system that detects animal movement and wirelessly transmits this data is a valuable tool for monitoring pigs' activity. However, the process of sampling and transmitting raw sensor data consumes a significant amount of power, leading to frequent recharging or replacement of WSN batteries. To address this issue, our proposed solution integrates edge computing into WSNs, utilizing a Random Forest Classifier (RFC). The RFC is trained and deployed within the WSNs to predict animal behavior, allowing for adaptive adjustment of data sampling frequency to reduce power consumption. Additionally, by transmitting RFC predictions instead of raw sensor data, WSNs can conserve power by transmitting less data. Our RFC can accurately classify common animal activities, such as eating, drinking, laying, standing, and walking, achieving an F-1 score of 93%. With the integration of edge computing intelligence, WSN power consumption is reduced by 25% compared to traditional WSNs that periodically sample and transmit raw sensor data at 10 Hz.