The advent of multi-photon microscopes and highly sensitive protein sensors enables the recording of astrocyte activities on a large population of cells over a long-time period in vivo. Existing tools cannot fully characterize these activities, both within single cells and at the population-level, because of the insufficiency of current region-of-interest-based approaches to describe the activity that is often spatially unfixed, size-varying, and propagative. Here, we present Astrocyte Quantitative Analysis (AQuA), an analytical framework that releases astrocyte biologists from the ROI-based paradigm. The framework takes an event-based perspective to model and accurately quantify the complex activity in astrocyte imaging datasets, with an event defined jointly by its spatial occupancy and temporal dynamics. To model the signal propagation in astrocyte, we developed graphical time warping (GTW) to align curves with graph-structured constraints and integrated it into AQuA. To make AQuA easy to use, we designed a comprehensive software package. The software implements the detection pipeline in an intuitive step by step GUI with visual feedback. The software also supports proof-reading and the incorporation of morphology information. With synthetic data, we showed AQuA performed much better in accuracy compared with existing methods developed for astrocytic data and neuronal data. We applied AQuA to a range of ex vivo and in vivo imaging datasets. Since AQuA is data-driven and based on machine learning principles, it can be applied across model organisms, fluorescent indicators, experimental modes, and imaging resolutions and speeds, enabling researchers to elucidate fundamental astrocyte physiology. / Doctor of Philosophy / Astrocyte is an important type of glial cell in the brain. Unlike neurons, astrocyte cannot be electrically excited. However, the concentrations of many different molecules inside and near astrocytes change over space and time and show complex patterns. Recording, analyzing, and deciphering these activity patterns enables the understanding of various roles astrocyte may play in the nervous system. Many of these important roles, such as sensory-motor integration and brain state modulation, were traditionally considered the territory of neurons, but recently found to be related to astrocytes. These activities can be monitored in the intracellular and extracellular spaces in either brain slices and living animals, thanks to the advancement of microscopes and genetically encoded fluorescent sensors. However, sophisticated analytical tools lag far behind the impressive capability of generating the data. The major reason is that existing tools are all based on the region-of-interest-based (ROI) approach. This approach assumes the field of view can be segmented to many regions, and all pixels in the region should be active together. In neuronal activity analysis, all pixels in an ROI (region of interest) correspond to a neuron and are assumed to share a common activity pattern (curve). This is not true for astrocyte activity data because astrocyte activities are spatially unfixed, size-varying, and propagative. In this dissertation, we developed a framework called AQuA to detect the activities directly. We designed an accurate and flexible detection pipeline that works with different types of astrocyte activity data sets. We designed a machine learning model to characterize the signal propagation for the pipeline. We also implemented a compressive and user-friendly software package. The advantage of AQuA is confirmed in both simulation studies and three different types of real data sets.

Circadian rhythms are periodic physiological cycles that recur about every 24 hours, by means of which organisms integrate their physiology and behavior to the daily cycle of light and temperature imposed by the rotation of the earth. Circadian derives from the Latin word circa "about" and dies "day". Circadian rhythms have three noteworthy properties. They are endogenous, that is, they persist in the absence of external cues (in an environment of constant light intensity, temperature, etc.). Secondly, they are temperature compensated, that is, the nearly 24 hour period of the endogenous oscillator is remarkably independent of ambient temperature. Finally, they are phase shifted by light. The circadian rhythm can be either advanced or delayed by applying a pulse of light in constant darkness. Consequently, the circadian rhythm will synchronize to a periodic light-dark cycle, provided the period of the driving stimulus is not too far from the period of the endogenous rhythm. A window on the molecular mechanism of 24-hour rhythms was opened by the identification of circadian rhythm mutants and their cognate genes in Drosophila, Neurospora, and now in other organisms. Since Konopka and Benzer first discovered the period mutant in Drosophila in 1971 (Konopka and Benzer, 1971), there have been remarkable developments. Currently, the consensus opinion of molecular geneticists is that the 24-hour period arises from a negative feedback loop controlling the transcription of clock genes. However, a better understanding of this mechanism requires an approach that integrates both mathematical and molecular biology. From the recent discoveries in molecular biology and through a mathematical approach, we propose that the mechanism of circadian rhythm is based upon the combination of both negative and positive feedback. / Master of Science

Prestationsångest är ett vanligt ämne inom idrott. Syftet med studien var att undersöka hur unga kvinnor inom lagidrott upplever prestationsångest. Semistrukturerade intervjuer genomfördes med 10 unga kvinnor mellan 18–25 år som spelade i samma handbollslag. Intervjuerna transkriberades och tematiserades där 6 teman identifierades: individernas upplevelse av prestationsångest, lagom prestationsångest ger bra prestation, lagkamraterna minskar prestationsångest, tränarna ökar prestationsångesten, prestationsångest ökar vid match, hög prestationsångest ger sämre spel. Studiens resultat visade att prestationsångest hos spelarna upplevdes på olika sätt både psykiskt och fysiskt, där mängden prestationsångest påverkade. Prestationsångesten påverkades olika av lagkamraterna och tränarna vilket främst upplevdes vid match. Utifrån tidigare forskning diskuterades hur mängden prestationsångest bidrog till idrottarens prestation där den omvända U-kurvan beskriver förhållandet mellan anspänning och prestation. Hur spelarna uppfattade lagkamraterna som minskande faktor till prestationsångest är något som diskuteras. Studien kan ge mer kunskap och en djupare förståelse för hur unga kvinnor upplever prestationsångest inom lagidrott.

Microfluidics are devices with channels or reservoirs that have dimensions in the range of micrometers. They have an increasing role in biological analysis processes due to their ability to use very small sample volumes. Many microfluidic processes rely heavily on precise temperature measurement and control. Advances in 3D printing have led to high resolution digital light processing stereolithography (DLP-SLA) printers capable of using bio-compatible materials, available at BYU. This custom 3D printer has a resolution of 7.6 µm in the XY plane and 10 µm in the Z axis. Combined with a custom-made resin, we can produce microfluidic features as small as 18 µm x 20 µm. These advances allow for more complex internal geometries with multiple overlapping channels. As the internal geometry becomes more complex, traditional microfluidic temperature measurement tools are limited in their application. This dissertation considers the use of temperature sensitive quantum dots (QDs), nano-scale semiconductor crystals that fluoresce, as an internal temperature measurement tool. This work presents two types of QDs, CdTe and CdSe/ZnS, and their performance as a temperature sensor by relating either photoluminescence peak intensity to temperature or a feed-forward neural network combining multiple features of the fluorescent spectra to temperature. Additionally, 3D printing's ability to create arbitrary 3D structures with an arbitrary 3D orientation, as opposed to traditional microfluidic fabrication methods, enables new three-dimensional heater geometries to be created that provide better internal heat distributions. We present new heater geometries only feasible through 3D printing that can isothermally heat a precisely defined volume. One such design is for a device that can control the temperature of a 5 µL internal chamber to within 0.2°C. This last design is aimed at a new microfluidic device for high resolution DNA melt curve analysis for the detection of single nucleotide polymorphisms. This set of tools we developed will enable the expansion of 3D printed microfluidics beyond the current planar limitations and fluid flow processes into temperature sensitive analyses.

Yes / The misery index (the unweighted sum of unemployment and inflation rates) was probably the first attempt to develop a single statistic to measure the level of a population’s economic malaise. In this letter, we develop a dynamic approach to decompose the misery index using two basic relations of modern macroeconomics: the expectations-augmented Phillips curve and Okun’s law. Our reformulation of the misery index is closer in spirit to Okun’s idea. However, we are able to offer an improved version of the index, mainly based on output and unemployment. Specifically, this new Okun’s index measures the level of economic discomfort as a function of three key factors: (1) the misery index in the previous period; (2) the output gap in growth rate terms; and (3) cyclical unemployment. This dynamic approach differs substantially from the standard one utilised to develop the misery index, and allow us to obtain an index with five main interesting features: (1) it focuses on output, unemployment and inflation; (2) it considers only objective variables; (3) it allows a distinction between short-run and long-run phenomena; (4) it places more importance on output and unemployment rather than inflation; and (5) it weights recessions more than expansions.

A avaliação do risco a contaminação e a escolha de técnicas de remediação de poluentes em aquíferos fraturados depende da quantificação dos fenômenos envolvidos no transporte de solutos. A geometria da fratura, usualmente caracterizada pela abertura, é o principal parâmetro que indiretamente controla o transporte nos aquíferos fraturados. A simplificação mais comum desse problema é assumir que as fraturas são um par de placas planas e paralelas, isto é, com uma abertura constante. No entanto, por causa do limitado número de trabalhos experimentais, não está esclarecida a adequabilidade do uso de uma abertura constante para simular o transporte conservativo em fraturas do Aquífero Serra Geral (ASG), Brasil. O objetivo deste trabalho é avaliar a influência da abertura de uma fratura natural do Aquífero Serra Geral sob o transporte conservativo de solutos. Uma amostra natural de basalto fraturado foi usada em um experimento hidráulico e de transporte de um traçador conservativo (escala de laboratório). O campo de abertura foi medido usando a técnica avançada, de alta resolução e tridimensional, chamada microtomografia computadorizada de raios-X. A concentração de traçador medida foi utilizada para validar uma solução analítica unidimensional da Equação de Advecção-dispersão (ADE). O desemprenho do ajuste da ADE às curvas de passagem experimentais foi avaliado para quatro diferentes tipos de aberturas constantes. Os resultados mostraram que o escoamento de água e o transporte de contaminantes pode ocorrer através de fraturas micrométricas, ocasionando, eventualmente, a contaminação do ASG. A abertura de balanço de massa é a única que pode ser chamada propriamente de \"abertura equivalente\". O uso de aberturas constantes na ADE não permitiu representar completamente o formato das curvas de passagem porque o campo de velocidade não é uniforme e intrinsicamente bidimensional. Portanto, na simulação do transporte deve-se incorporar a heterogeneidade da abertura da fratura. / The contamination risk assessment and the choice of suitable cleanup techniques for pollutants in fractured rock depends on the quantification of the transport phenomena. Fracture geometry often described by the apertures is the major parameter that controls indirectly solute transport in fractured rock. The simplest approach is describing fractures as a pair of smooth parallel plates with constant aperture. However, there is a lack of information about the suitability for using a constant aperture for the conservative solute transport prediction in a single fracture of Serra Geral Aquifer (SGA), Brazil. The aim of this work is to evaluate the effect of aperture variability in a natural single rough-walled fracture of Serra Geral Aquifer on conservative solute transport. A natural core of fractured basalt was used for a hydraulic and tracer tests (laboratory scale). The aperture field was measured using the advanced, high-resolution and tridimensional technique X-ray computed tomography. The measured tracer concentration was validated by means of an analytical solution of the Advection-dispersion Equation (ADE). The ADE fit performance was measured against experimental breakthrough curves for four distinct kind of constant apertures. It was found that water flow and solute transport can take place through micrometric fractures, eventually leading the SGA contamination. Results show that the mass balance aperture is the only appropriate \"equivalent aperture\" for describing solute transport in a single rough-walled fracture. The results showed that ADE is not appropriate for modeling the complete behavior of experimental breakthrough curves because of the dimensional non-uniform velocity field. Therefore, the aperture heterogeneity must be considered in solute transport simulation.

A avaliação do risco a contaminação e a escolha de técnicas de remediação de poluentes em aquíferos fraturados depende da quantificação dos fenômenos envolvidos no transporte de solutos. A geometria da fratura, usualmente caracterizada pela abertura, é o principal parâmetro que indiretamente controla o transporte nos aquíferos fraturados. A simplificação mais comum desse problema é assumir que as fraturas são um par de placas planas e paralelas, isto é, com uma abertura constante. No entanto, por causa do limitado número de trabalhos experimentais, não está esclarecida a adequabilidade do uso de uma abertura constante para simular o transporte conservativo em fraturas do Aquífero Serra Geral (ASG), Brasil. O objetivo deste trabalho é avaliar a influência da abertura de uma fratura natural do Aquífero Serra Geral sob o transporte conservativo de solutos. Uma amostra natural de basalto fraturado foi usada em um experimento hidráulico e de transporte de um traçador conservativo (escala de laboratório). O campo de abertura foi medido usando a técnica avançada, de alta resolução e tridimensional, chamada microtomografia computadorizada de raios-X. A concentração de traçador medida foi utilizada para validar uma solução analítica unidimensional da Equação de Advecção-dispersão (ADE). O desemprenho do ajuste da ADE às curvas de passagem experimentais foi avaliado para quatro diferentes tipos de aberturas constantes. Os resultados mostraram que o escoamento de água e o transporte de contaminantes pode ocorrer através de fraturas micrométricas, ocasionando, eventualmente, a contaminação do ASG. A abertura de balanço de massa é a única que pode ser chamada propriamente de \"abertura equivalente\". O uso de aberturas constantes na ADE não permitiu representar completamente o formato das curvas de passagem porque o campo de velocidade não é uniforme e intrinsicamente bidimensional. Portanto, na simulação do transporte deve-se incorporar a heterogeneidade da abertura da fratura. / The contamination risk assessment and the choice of suitable cleanup techniques for pollutants in fractured rock depends on the quantification of the transport phenomena. Fracture geometry often described by the apertures is the major parameter that controls indirectly solute transport in fractured rock. The simplest approach is describing fractures as a pair of smooth parallel plates with constant aperture. However, there is a lack of information about the suitability for using a constant aperture for the conservative solute transport prediction in a single fracture of Serra Geral Aquifer (SGA), Brazil. The aim of this work is to evaluate the effect of aperture variability in a natural single rough-walled fracture of Serra Geral Aquifer on conservative solute transport. A natural core of fractured basalt was used for a hydraulic and tracer tests (laboratory scale). The aperture field was measured using the advanced, high-resolution and tridimensional technique X-ray computed tomography. The measured tracer concentration was validated by means of an analytical solution of the Advection-dispersion Equation (ADE). The ADE fit performance was measured against experimental breakthrough curves for four distinct kind of constant apertures. It was found that water flow and solute transport can take place through micrometric fractures, eventually leading the SGA contamination. Results show that the mass balance aperture is the only appropriate \"equivalent aperture\" for describing solute transport in a single rough-walled fracture. The results showed that ADE is not appropriate for modeling the complete behavior of experimental breakthrough curves because of the dimensional non-uniform velocity field. Therefore, the aperture heterogeneity must be considered in solute transport simulation.

A determinação das principais propriedades magnéticas de um ímã permanente geralmente requer sistemas de medição sofisticados e custosos. Este trabalho analisa e propõe um sistema de caracterização de ímãs permanentes de Terras Raras à temperatura ambiente de baixo custo e de implementação mais simples e rápida. Ele consiste de um circuito magnético formado pelo ímã permanente sob caracterização, uma culatra de aço, um entreferro variável e uma sonda de efeito Hall com seu respectivo gaussímetro para a medição da intensidade do campo magnético no entreferro. Como introdução se apresenta o estado da arte da caracterização dos ímãs permanentes, conceitos básicos de magnetismo e em relação aos ímãs permanentes, sua história, os principais tipos, sua importância e suas aplicações principais. Os resultados teóricos e experimentais são comparados a resultados certificados, validando o método como proposto. / Determining the main magnetic properties of a permanent magnet usually requires sophisticated and expensive measurement setups. This work analyses and proposes a low-cost system to characterize Rare Earth permanent magnets at ambient temperature with easy and fast implementation. It consists of a magnetic circuit with the permanent magnet under test, appropriate pole pieces, a variable air gap and a Hall Effect probe with its respective Gaussmeter. As an introduction, it is presented the state of the art of permanent magnets characterization, basic concepts of magnetism and its history, the main types of permanent magnets, their importance and applications. The theoretical and experimental results are compared to certified ones, validating so the method as proposed.

The purpose of this study is to analyze how estimates of an important geomorphic parameter, effective discharge, are impacted by the choice of bed material load equations and flow duration curves (FDCs). The Yang (1979), Brownlie (1981), and Pagosa equations developed by Rosgen (2006) were compared for predicting bed material load. To calculate the bed material load using the Pagosa equations, the bedload and suspended load are calculated separately and the results are added together. To compare the effectiveness of the equations, measured bed material load data from the USGS Open-File Report 89-67 were used. Following the calculations, the equation results were compared to the measured data. It was determined that the Pagosa equations performed the best overall, followed by Brownlie and then Yang. The superior performance of the Pagosa equations is likely due to the equations being calibrated. USGS regression equations for FDCs were compared to a method developed by Dr. David Rosgen in which a dimensionless FDC (DFDC) is developed. Weminuche Creek in southwestern Colorado was used as the study site. Rosgen's DFDC method requires the selection of a streamgage for a stream that exhibits the same hydro-physiographic characteristics as the site of interest. An FDC is developed for the gaged site and made dimensionless by dividing the discharges by the bankfull discharge of the gaged site. The DFDC is then made dimensional by multiplying by the bankfull discharge of the site of interest and the resulting dimensional FDC is taken as the FDC of the ungaged site. The USGS regression equations underpredicted the discharges while Rosgen's DFDC method overpredicted them. Rosgen's DFDC method produced more accurate results than the USGS regression equations for Weminuche Creek. To calculate the effective discharge, the FDC was used to develop a flow frequency curve which was then multiplied by the sediment rating curve. Effective discharge calculations were performed for Weminuche Creek using several combinations of bed material load prediction equations and FDCs. The USGS regression equations, Rosgen's DFDC method, and streamgage data were all used in conjunction with the Yang and Pagosa equations. The Brownlie equation predicted zero bed material load for Weminuche Creek, and was thus not used to calculate the effective discharge. When the USGS regression equations were used with the Yang and Pagosa equations, the calculated effective discharge was approximately 4.5 cms for both bed material load prediction equations. When Rosgen's DFDC method and streamgage data were used with the Yang and Pagosa equations, the effective discharge was approximately 13.5 cms. From these results, it was determined that the bed material load prediction equations had little impact on the effective discharge for Weminuche Creek while the FDCs did influence the results.

One trend in the ‘omics’ sciences is the generation of increasing amounts of data, describing complex biological samples. To cope with this and facilitate progress towards reliable diagnostic tools, it is crucial to develop methods for extracting representative and predictive information. In global metabolite analysis (metabolomics and metabonomics) NMR, GC/MS and LC/MS are the main platforms for data generation. Multivariate projection methods (e.g. PCA, PLS and O-PLS) have been recognized as efficient tools for data analysis within subjects such as biology and chemistry due to their ability to provide interpretable models based on many, correlated variables. In global metabolite analysis, these methods have been successfully applied in areas such as toxicology, disease diagnosis and plant functional genomics. This thesis describes the development of processing methods for the unbiased extraction of representative and predictive information from metabolic GC/MS and LC/MS data characterizing biofluids, e.g. plant extracts, urine and blood plasma. In order to allow the multivariate projections to detect and highlight differences between samples, one requirement of the processing methods is that they must extract a common set of descriptors from all samples and still retain the metabolically relevant information in the data. In Papers I and II this was done by applying a hierarchical multivariate compression approach to both GC/MS and LC/MS data. In the study described in Paper III a hierarchical multivariate curve resolution strategy (H-MCR) was developed for simultaneously resolving multiple GC/MS samples into pure profiles. In Paper IV the H-MCR method was applied to a drug toxicity study in rats, where the method’s potential for biomarker detection and identification was exemplified. Finally, the H-MCR method was extended, as described in Paper V, allowing independent samples to be processed and predicted using a model based on an existing set of representative samples. The fact that these processing methods proved to be valid for predicting the properties of new independent samples indicates that it is now possible for global metabolite analysis to be extended beyond isolated studies. In addition, the results facilitate high through-put analysis, because predicting the nature of samples is rapid compared to the actual processing. In summary this research highlights the possibilities for using global metabolite analysis in diagnosis.