7,187 research outputs found

    Graduate Catalog of Studies, 2023-2024

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    An investigation into mild traumatic brain injury identification, management, and mitigation

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    Concussion is classified as a mild traumatic brain injury which can be induced by biomechanical forces such as a physical impact to the head or body, which results in a transient neurological disturbance without obvious structural brain damage. Immediate access to tools that can identify, diagnosis and manage concussion are wide ranging and can lack consistency in application. It is well documented that there are frequent incidences of concussion across amateur and professional sport such as popular contact sports like rugby union. A primary aim of this thesis was to establish the current modalities of ‘pitch side’ concussion management, identification, and diagnosis across amateur and professional sporting populations. Furthermore, the research sought to understand existing concussion management and concussion experiences by means of recording the player’s experiences and perceptions (retired professional rugby union players). These qualitative studies sought to gain insights into concussion experiences, the language used to discuss concussion and the duty of care which medical staff, coaching personnel, and club owners have towards professional rugby players in their employment. In addition, possible interventions to reduce the incidence of concussion in amateur and professional sports were investigated. These included a ‘proof of concept’ using inertial measurement units and a smartphone application, a tackle technique coaching app for amateur sports. Other research data investigating the use of neurological function data and neuromuscular fatigue in current professional rugby players as a novel means of monitoring injury risk were included in this research theme. The findings of these studies suggest that there is an established head injury assessment process for professional sports. However, in amateur sport settings, this is not the existing practice and may expose amateur players to an increased risk of post-concussion syndrome or early retirement. Many past professional rugby union players stated that they did not know the effects of cumulative repetitive head impacts. They discussed how they minimised and ignored repeated concussions due to peer pressure or pressure from coaches or their own internal pressures of maintaining a livelihood. These data suggest that players believed that strong willed medical staff, immutable to pressures from coaching staff or even athletes themselves, were essential for player welfare and that club owners have a long-term duty of care to retired professional rugby union players. However, there are anecdotal methods suggested to reduce concussion incidence. For example, neck strengthening techniques to mitigate against collision impacts. There is, no longitudinal evidence to suggest that neck strength can reduce the impacts of concussion in adult populations . Additionally, other factors such as lowering the tackle height in the professional and amateur game is currently being investigated as a mitigating factor to reduce head injury risk. The final theme of the thesis investigated possible methods to reduce injury incidence in amateur and professional athletes. The novel tackle technique platform could assist inexperienced amateur coaches on how to coach effective tackle technique to youth players. The findings from the neurological function data suggests that this may be an alternative way for coaches to assess and gather fatigue data on professional rugby union players alongside additional subjective measures and neuromuscular function data. Recently, the awareness of concussion as an injury and the recognition of concussion in many sports settings has improved. These incremental improvements have led to increased discussion regarding possible measures to mitigate the effects of concussion. There are many additional procedures to be implemented before a comprehensive concussion management is universally available, particularly in amateur and community sports. These necessary processes could be technological advances (e.g., using smart phone technology) for parents and amateur coaches to assist in the early identification of concussion or evidence-based concussion reduction strategies

    Contributions to improve the technologies supporting unmanned aircraft operations

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    Mención Internacional en el título de doctorUnmanned Aerial Vehicles (UAVs), in their smaller versions known as drones, are becoming increasingly important in today's societies. The systems that make them up present a multitude of challenges, of which error can be considered the common denominator. The perception of the environment is measured by sensors that have errors, the models that interpret the information and/or define behaviors are approximations of the world and therefore also have errors. Explaining error allows extending the limits of deterministic models to address real-world problems. The performance of the technologies embedded in drones depends on our ability to understand, model, and control the error of the systems that integrate them, as well as new technologies that may emerge. Flight controllers integrate various subsystems that are generally dependent on other systems. One example is the guidance systems. These systems provide the engine's propulsion controller with the necessary information to accomplish a desired mission. For this purpose, the flight controller is made up of a control law for the guidance system that reacts to the information perceived by the perception and navigation systems. The error of any of the subsystems propagates through the ecosystem of the controller, so the study of each of them is essential. On the other hand, among the strategies for error control are state-space estimators, where the Kalman filter has been a great ally of engineers since its appearance in the 1960s. Kalman filters are at the heart of information fusion systems, minimizing the error covariance of the system and allowing the measured states to be filtered and estimated in the absence of observations. State Space Models (SSM) are developed based on a set of hypotheses for modeling the world. Among the assumptions are that the models of the world must be linear, Markovian, and that the error of their models must be Gaussian. In general, systems are not linear, so linearization are performed on models that are already approximations of the world. In other cases, the noise to be controlled is not Gaussian, but it is approximated to that distribution in order to be able to deal with it. On the other hand, many systems are not Markovian, i.e., their states do not depend only on the previous state, but there are other dependencies that state space models cannot handle. This thesis deals a collection of studies in which error is formulated and reduced. First, the error in a computer vision-based precision landing system is studied, then estimation and filtering problems from the deep learning approach are addressed. Finally, classification concepts with deep learning over trajectories are studied. The first case of the collection xviiistudies the consequences of error propagation in a machine vision-based precision landing system. This paper proposes a set of strategies to reduce the impact on the guidance system, and ultimately reduce the error. The next two studies approach the estimation and filtering problem from the deep learning approach, where error is a function to be minimized by learning. The last case of the collection deals with a trajectory classification problem with real data. This work completes the two main fields in deep learning, regression and classification, where the error is considered as a probability function of class membership.Los vehículos aéreos no tripulados (UAV) en sus versiones de pequeño tamaño conocidos como drones, van tomando protagonismo en las sociedades actuales. Los sistemas que los componen presentan multitud de retos entre los cuales el error se puede considerar como el denominador común. La percepción del entorno se mide mediante sensores que tienen error, los modelos que interpretan la información y/o definen comportamientos son aproximaciones del mundo y por consiguiente también presentan error. Explicar el error permite extender los límites de los modelos deterministas para abordar problemas del mundo real. El rendimiento de las tecnologías embarcadas en los drones, dependen de nuestra capacidad de comprender, modelar y controlar el error de los sistemas que los integran, así como de las nuevas tecnologías que puedan surgir. Los controladores de vuelo integran diferentes subsistemas los cuales generalmente son dependientes de otros sistemas. Un caso de esta situación son los sistemas de guiado. Estos sistemas son los encargados de proporcionar al controlador de los motores información necesaria para cumplir con una misión deseada. Para ello se componen de una ley de control de guiado que reacciona a la información percibida por los sistemas de percepción y navegación. El error de cualquiera de estos sistemas se propaga por el ecosistema del controlador siendo vital su estudio. Por otro lado, entre las estrategias para abordar el control del error se encuentran los estimadores en espacios de estados, donde el filtro de Kalman desde su aparición en los años 60, ha sido y continúa siendo un gran aliado para los ingenieros. Los filtros de Kalman son el corazón de los sistemas de fusión de información, los cuales minimizan la covarianza del error del sistema, permitiendo filtrar los estados medidos y estimarlos cuando no se tienen observaciones. Los modelos de espacios de estados se desarrollan en base a un conjunto de hipótesis para modelar el mundo. Entre las hipótesis se encuentra que los modelos del mundo han de ser lineales, markovianos y que el error de sus modelos ha de ser gaussiano. Generalmente los sistemas no son lineales por lo que se realizan linealizaciones sobre modelos que a su vez ya son aproximaciones del mundo. En otros casos el ruido que se desea controlar no es gaussiano, pero se aproxima a esta distribución para poder abordarlo. Por otro lado, multitud de sistemas no son markovianos, es decir, sus estados no solo dependen del estado anterior, sino que existen otras dependencias que los modelos de espacio de estados no son capaces de abordar. Esta tesis aborda un compendio de estudios sobre los que se formula y reduce el error. En primer lugar, se estudia el error en un sistema de aterrizaje de precisión basado en visión por computador. Después se plantean problemas de estimación y filtrado desde la aproximación del aprendizaje profundo. Por último, se estudian los conceptos de clasificación con aprendizaje profundo sobre trayectorias. El primer caso del compendio estudia las consecuencias de la propagación del error de un sistema de aterrizaje de precisión basado en visión artificial. En este trabajo se propone un conjunto de estrategias para reducir el impacto sobre el sistema de guiado, y en última instancia reducir el error. Los siguientes dos estudios abordan el problema de estimación y filtrado desde la perspectiva del aprendizaje profundo, donde el error es una función que minimizar mediante aprendizaje. El último caso del compendio aborda un problema de clasificación de trayectorias con datos reales. Con este trabajo se completan los dos campos principales en aprendizaje profundo, regresión y clasificación, donde se plantea el error como una función de probabilidad de pertenencia a una clase.I would like to thank the Ministry of Science and Innovation for granting me the funding with reference PRE2018-086793, associated to the project TEC2017-88048-C2-2-R, which provide me the opportunity to carry out all my PhD. activities, including completing an international research internship.Programa de Doctorado en Ciencia y Tecnología Informática por la Universidad Carlos III de MadridPresidente: Antonio Berlanga de Jesús.- Secretario: Daniel Arias Medina.- Vocal: Alejandro Martínez Cav

    Nanomaterial fate and bioavailability in freshwater environments

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    Given the widespread use of silver nanomaterials (AgNM), their accidental or intentional release into the environment is inevitable. AgNM release into riverine systems is a daily occurrence, and following their release, they will undoubtedly interact with naturally occurring organic and inorganic particulates and sediment interfaces. At this point, AgNM's long-term threat to freshwater ecosystems is unclear. We must develop our understanding of AgNM fate, toxicity, and bioavailability using testing approaches that systematically investigate AgNM environmental interaction within single-factor and multifactor systems. This body of research aimed to comprehensively examine selected AgNM particles that were tracked within parallel fate scenarios and toxicity and bioavailability studies. Results showed contrasting behavior between the two tested AgNM. Findings also demonstrated that low shear flow is a significant factor influencing the flocculation and settling rates of AgNM, which differentially regulated the persistence and residence time of aqueous phase AgNM within simulated riverine systems. Experiments with low shear flow showed a significant increase in AgNM water column removal and modulated the physicochemistry differentially compared to quiescent systems. The findings on the influence of bed sediment interactions with waterborne AgNM demonstrated that they are a vital process that increases the transfer and exchange of AgNM from the water column to the bed. Toxicity studies showed how abiotic factors could modulate toxicity differentially between aquatic species and how inorganic and organic matter can increase and decrease AgNM toxicity. Exposure studies contrasting singular and multifactor exposures with and without low shear flow demonstrated that they modulate the exposure of AgNM significantly differently. In conclusion, the proof-of-concept flume designs for testing the environmental fate and exposure of AgNM showed promise and that, with further refinement, could be further incorporated into the life-cycle testing framework of ENMs, to produce accurate semi-empirical coefficients for environmental models for the assessment of hazard

    Communication, Localization and Synchronization of Spacecraft for Swarm Missions

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    Swarm missions are based on the use of several spacecraft working together to pursue a specific task for a specific mission. To allow these elements to work together, it is necessary for them to be able to communicate with each other and to synchronize themselves within the swarm. Moreover, the mission may likely require knowing the relative or absolute positions of the spacecraft in the swarm. In order to collect simultaneous measurements allowing computing localization and synchronization in the swarm, a full duplex CDMA communication method is studied by CNES. An Inter Satellite Link (ISL) transmitter prototype is currently under development and first performance evaluation is conducted. CNES is also working on measurement signal processing. Based on signal exchange between satellites, one can estimate jointly the distance and clock offset between a pair of satellites. In parallel, CNES is developing a swarm simulator implying both dynamics and functional behavior of each spacecraft in the swarm. First, this simulator will be software only but its architecture will allow integration of hardware equipment in a future version. This simulator will be used for the validation of the services provided by the link at a system level

    Is there a Moore's law for quantum computing?

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    There is a common wisdom according to which many technologies can progress according to some exponential law like the empirical Moore's law that was validated for over half a century with the growth of transistors number in chipsets. As a still in the making technology with a lot of potential promises, quantum computing is supposed to follow the pack and grow inexorably to maturity. The Holy Grail in that domain is a large quantum computer with thousands of errors corrected logical qubits made themselves of thousands, if not more, of physical qubits. These would enable molecular simulations as well as factoring 2048 RSA bit keys among other use cases taken from the intractable classical computing problems book. How far are we from this? Less than 15 years according to many predictions. We will see in this paper that Moore's empirical law cannot easily be translated to an equivalent in quantum computing. Qubits have various figures of merit that won't progress magically thanks to some new manufacturing technique capacity. However, some equivalents of Moore's law may be at play inside and outside the quantum realm like with quantum computers enabling technologies, cryogeny and control electronics. Algorithms, software tools and engineering also play a key role as enablers of quantum computing progress. While much of quantum computing future outcomes depends on qubit fidelities, it is progressing rather slowly, particularly at scale. We will finally see that other figures of merit will come into play and potentially change the landscape like the quality of computed results and the energetics of quantum computing. Although scientific and technological in nature, this inventory has broad business implications, on investment, education and cybersecurity related decision-making processes.Comment: 32 pages, 24 figure

    Environmental responses of carbon dioxide and methane fluxes of subarctic ecosystems in Northern Finland

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    The subarctic landscape consists of diverse ecosystems, each having a multitude of biological processes controlling the carbon (C) cycle. Thus, the ecosystem-atmosphere exchange of carbon dioxide (CO2) and methane (CH4) can display substantial temporal and spatial variation. In this thesis, the objective was to study the C flux responses to changing environmental conditions on the plant community, ecosystem and landscape level. The study sites included fen, upland pine forest, pine bog and lake ecosystems and a mountain birch foresttundra ecotone. The CO2 and CH4 fluxes were measured with the eddy covariance and flux chamber methods during two meteorologically contrasting years. The fen acted as a small annual CO2 sink and an effective CH4 source to the atmosphere, while the pine forest was an effective CO2 sink. The emissions of CO2 and CH4 were sevenfold from the organic compared to the mineral sediment lake. The annual pine bog CO2 sink was estimated to be between the fen and forest sinks. The C fluxes of the four main plant community types (PCTs) of the flark-string microtopography continuum at the fen were controlled by vegetation composition, water table and meteorology. The driest PCTs had larger ecosystem respiration and gross photosynthesis than the wet ones. The three wettest PCTs contributed roughly equally to the total CH4 emissions of the fen, while the emissions from the driest PCT were minor. The fen C fluxes differed between the measurement years during two distinct periods: the warmer-than-average spring in 2018 and a heatwave and drought event in July 2018. The warm spring increased CO2 uptake, while the drought decreased both CO2 uptake and CH4 emissions. The drought also decreased the CO2 uptake of the other terrestrial ecosystems including the birch ecotone. The pine forest CO2 fluxes were affected by the rainy summer in 2017 by increasing the respiration, and a cold spell in autumn 2018, which decreased respiration. Since the post-glacial peatland initiation, peatland expansion and vegetation shifts have altered the CO2 and CH4 fluxes within the current fen area, and it was estimated that the net C exchange during this period has varied between a close-to-neutral balance and an effective sink.Subarktinen luonto koostuu useista monimuotoisista ekosysteemeistä, joissa hiilenkiertoa säätelevät lukuisat biologiset prosessit. Tämä ekosysteemien monimuotoisuus johtaa siihen, että ekosysteemien ja ilmakehän väliset hiilidioksidin (CO2) ja metaanin (CH4) vuot voivat vaihdella merkittävästi sekä paikallisesti että ajallisesti. Tässä väitöskirjassa tavoitteena oli tutkia hiilivoiden käyttäytymistä muuttuvissa ympäristöolosuhteissa kahden vuoden ajan kasviyhteisö-, ekosysteemi- ja maisematasolla. Tutkimusekosysteemeinä olivat Kaamasessa aapasuo, mäntyinen kangasmetsä, mäntyräme ja järvet sekä Kevolla tunturikoivikko. Vuomittauksiin käytettiin pyörrekovarianssi- ja kammiomenetelmiä. Molempina vuosina suo oli pieni CO2-nielu, selvä CH4-lähde ja kokonaisuudessaan pieni hiilinielu. Mäntymetsä oli huomattava CO2-nielu molempina vuosina, kun taas järvet vapauttivat sekä CO2:a että CH4:a ilmakehään. Turvepohjainen järvi suon alajuoksulla vapautti seitsemänkertaisen määrän hiiltä ilmakehään harjujen reunustamaan hiekkapohjaiseen järveen verrattuna. Mallinnettujen mäntyrämeiden CO2-taseet sijoittuivat suon ja mäntymetsän CO2-nielujen välimaastoon. Suon märissä rimmissä ja kuivilla jänteillä kasvavien neljän pääkasviyhteisötyypin hiilivuot riippuivat pohjaveden korkeudesta, kasvilajistosta ja meteorologiasta. Kasvi- ja maahengitys sekä yhteyttäminen olivat suurempia jänteillä kuin rimmissä. Lähes kaikki suosta vapautunut CH4 vapautui kolmesta kosteimmasta kasviyhteisötyypistä. Tutkimusvuosien välillä suon hiilivoihin vaikuttivat keskivertoa lämpimämpi kevät vuonna 2018 ja sitä seurannut helle ja kuivuusjakso heinäkuussa. Lämmin kevät tehosti suoekosysteemin CO2-nielua edellisvuoden viileään kevätkauteen verrattuna. Kuivuusjakso puolestaan heikensi suon CO2-nielua muuttaen suon hetkellisesti jopa CO2-lähteeksi samalla kun suon CH4-päästöt pienenivät. Samainen kuivuus heikensi myös muiden Kaamasen maaekosysteemien ja Kevon tunturikoivikon CO2-nieluja. Mäntymetsän CO2-voissa havaittiin lisäksi vuonna 2017 sateisen kesän aikana kohonnutta maahengitystä sekä seuraavana vuonna kylmän syksyn aiheuttamaa madaltunutta ekosysteemihengitystä. Jääkauden jälkeinen suon muodostuminen, laajeneminen ja lajimuutokset kasviyhteisöissä ovat johtaneet vaihteleviin CO2 ja CH4 voihin suon laajenemisen aikana. Arvioimme suon hiilitaseen vaihdelleen alkuaikojen lähes neutraalista taseesta pari tuhatta vuotta sitten olleeseen huomattavaan kokonaishiilinieluun

    IMPACTS OF WASTEWATER EFFLUENTS AND SEASONAL TRENDS ON LEVELS OF EMERGING CONTAMINANTS IN TWO COLD-REGION RIVERS

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    Emerging contaminants such as pharmaceutical drugs have been detected in waters across the globe and are of concern for human and aquatic ecosystems health. Most pharmaceuticals are found at trace concentrations, but the continuous use and potential accumulation of some of these compounds can potentially lead to effects in aquatic organisms. The principal aim of this research was to enhance our understanding of the environmental risks associated with pharmaceuticals as one group of emerging contaminants. Many pharmaceuticals are ionizable organic chemicals (IOCs), which makes their environmental and toxicological behavior particularly challenging to predict due to their partitioning mechanism which is useful to estimate the distribution of the chemical. Therefore, the objective of this thesis was to evaluate the hypothesis that uptake and effects of IOCs in aquatic organisms are influenced by the interaction between environmental, physicochemical, and biological factors. To this end, first, field studies were conducted during spring, summer, and fall of 2021 on water (diffusive gradient in thin film and conventional grab) and sediments at four locations including upstream and downstream of the wastewater treatment plants (WWTPs) of the cities of Saskatoon and Regina in the South Saskatchewan River and Wascana Creek, Saskatchewan, Canada, respectively. Second, seven representative antipsychotic pharmaceuticals were measured in water, sediment, and fish samples up- and downstream of the City of Regina WWTP. Data collected from this research effort indicate contamination with antipsychotic pharmaceuticals, with the potential to adversely impact exposed organisms. Third, non-target chemical analysis was conducted in water, sediments, and fish samples, at the two locations in Wascana Creek and throughout the three seasons. Data collected from non-target analysis indicated that pharmaceuticals, rubber components and personal care products were the priority pollutants in all the matrices and their transcriptomics changes were also supported by the qPCR analysis. Finally, transcripts of several genes of interest were determined in brain and liver samples from in fathead minnow (Pimephales promelas) exposed to the wastewater effluents in Wascana Creek during summer and fall in 2021, using a qPCR gene expression array (the EcoToxChips). The integrative approach used in this study, strongly supports the need to combine chemical analysis with transcriptomics-based approaches as useful tools for assessing of complex mixtures of contaminants in wastewater discharges and their effects in aquatic organisms. This research provides a better understanding of the risks that pharmaceuticals may pose to aquatic organisms under varying environmental conditions and thereby aid in better protecting aquatic ecosystems in the future

    2023-2024 Boise State University Undergraduate Catalog

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    This catalog is primarily for and directed at students. However, it serves many audiences, such as high school counselors, academic advisors, and the public. In this catalog you will find an overview of Boise State University and information on admission, registration, grades, tuition and fees, financial aid, housing, student services, and other important policies and procedures. However, most of this catalog is devoted to describing the various programs and courses offered at Boise State
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