<p> A common method to identify or model the dominant directional reflective properties of a surface is the bidirectional reflectance distribution function (BRDF). BRDF describes the angular behavior by which light interacts with surfaces. Remote sensing technology has advanced to the stage where hyperspectral sensors, with hundreds of separate wavelength bands, are fairly common. This necessitates examining BRDF in the hyperspectral regime, which implies examining the directional reflective properties of hundreds of narrowly spaced wavelength bands. </p><p> In this dissertation I hypothesize that beach sand BRDF is wavelength dependent. Principal component analysis (PCA) and correlation matrix analysis of in situ measurements were used to test whether the spectral variability in the visible, near-infrared and shortwave directional reflectance factor of beach sands with and without freshwater surface films are wavelength dependent. The hyperspectral BRDF of beach sands exhibit weak spectral variability, the majority of which can be described with three to four broad spectral bands. These occur in the absence of a water layer on top of the sand in three wavelength ranges of 350-450 nm, 700-1350 nm, and 1450-2400 nm. When observing sheet flow on sand, a thin layer of water enhances reflectance in the specular direction at all wavelengths, and that spectral variability may be described using four spectral band regions of 350-450 nm, 500-950 nm, 950-1350 nm, and 1450-2400 nm. Spectral variations are more evident in sand surfaces of greater visual roughness than in smooth surfaces, regardless of sheetflow.</p>

The differential Optical Transfer Function (dOTF) is a focal plane wavefront sensing method that uses a diversity in the pupil plane to generate two different focal plane images. The difference of their Fourier transforms recovers the complex amplitude of the pupil down to the spatial scale of the diversity. We produce two simultaneous PSF images with diversity using a polarizing filter at the edge of the telescope pupil, and a polarization camera to simultaneously record the two images. Here we present the first on-sky demonstration of polarization dOTF at the 1.0m South African Astronomical Observatory telescope in Sutherland, and our attempt to validate it with simultaneous Shack-Hartmann wavefront sensor images.

<p> This dissertation presents new studies of waves and turbulence in the Arctic middle atmosphere. The study has a primary focus on wintertime conditions when the large-scale circulation of the middle atmosphere is disrupted by the breaking of planetary waves associated with sudden stratospheric warming (SSW) events. We used ongoing Rayleigh lidar measurements of density and temperature to conduct a multi-year study of gravity waves in the upper stratosphere-lower mesosphere (USLM) over Poker Flat Research Range (PFRR) at Chatanika, Alaska. We analyzed the night-to-night gravity wave activity in terms of the wind structure and the ageostrophy. We find that the weak winds during disturbed conditions block the vertical propagation of gravity waves into the mesosphere. The gravity wave activity is correlated with the altitudes where the winds are weakest. During periods of weak winds we find little correlation with ageostrophy. However, during periods of stronger winds we find the USLM gravity wave activity is correlated with the ageostrophy in the upper troposphere indicating that ageostrophy in this region is a source of the gravity waves. Inter-annually we find the wintertime gravity wave activity is correlated with the level of disturbance of the middle atmosphere, being reduced in those winters with a higher level of disturbance and weaker winds. We used rocket-borne ion gauges to measure turbulence in the wintertime middle atmosphere while documenting the larger meteorological context from Rayleigh lidar and satellites. This investigation of turbulence was called the Mesosphere-Lower Thermosphere Turbulence Experiment (MTeX). During MTeX we found a highly disturbed atmosphere associated with an SSW where winds were weak and gravity wave activity was low. We found low levels of turbulence in the upper mesosphere. The turbulence was primarily found in regions of convective instability in the topside of mesospheric inversion layers (MILs). The strongest and most persist turbulence was found in a MIL that is associated with the breaking of a monochromatic gravity wave. These MTeX observations indicate that turbulence is generated by gravity wave breaking as opposed to gravity wave saturation. These MTeX findings of low levels of turbulence are consistent with recent model studies of vertical transport during SSWs and support the view that eddy transport is not a dominant transport mechanism during SSWs.</p>

<p> In this thesis, we aim to systematically understand the relationship between cloud spatial structure and its radiation imprints, i.e., three-dimensional (3D) cloud effects, with the ultimate goal of deriving accurate radiative energy budget estimates from space, aircraft, or ground-based observations under spatially inhomogeneous conditions. By studying the full spectral information in the measured and modeled shortwave radiation fields of heterogeneous cloud scenes sampled during aircraft field experiments, we find evidence that cloud spatial structure reveals itself through spectral signatures in the associated irradiance and radiance fields in the near-ultraviolet and visible spectral range.</p><p> The spectral signature of 3D cloud effects in irradiances is apparent as a domain- wide, consistent correlation between the magnitude and spectral dependence of net horizontal photon transport. The physical mechanism of this phenomenon is molecular scattering in conjunction with cloud heterogeneity. A simple parameterization with a single parameter &epsiv; is developed, which holds for individual pixels and the domain as a whole. We then investigate the impact of scene parameters on the discovered correlation and find that it is upheld for a wide range of scene conditions, although the value of &epsiv; varies from scene to scene.</p><p> The spectral signature of 3D cloud effects in radiances manifests itself as a distinct relationship between the magnitude and spectral dependence of reflectance, which cannot be reproduced in the one-dimensional (1D) radiative transfer framework. Using the spectral signature in radiances and irradiances, it is possible to infer information on net horizontal photon transport from spectral radiance perturbations on the basis of pixel populations in sub-domains of a cloud scene.</p><p> We show that two different biases need to be considered when attempting radiative closure between measured and modeled irradiance fields below inhomogeneous cloud fields: the remote sensing bias (affecting cloud radiances and thus retrieved properties of the inhomogeneous scene) and the irradiance bias (ignoring 3D effects in the calculation of irradiance fields from imagery-based cloud retrievals). The newly established relationships between spatial and spectral structure lay the foundation for first-order corrections for these 3D biases within a 1D framework, once the correlations are explored on a more statistical basis.</p>

The concept of material dispersion is an important factor in analyzing the performance of an optical fiber system. The thesis presents an analysis of the material dispersion as a function of any pressure (in Mega Newton's per square meter) and temperature (in degrees Celsius). The pressure dependent and temperature dependent Sellmeier coefficients are considered for the analysis. The results obtained can be used in building a sensor that can be used for measuring dispersion as a function of pressure or temperature.

Populations of the least killifish, Heterandria formosa are found in a wide variety of habitats, including habitats that differ widely in average temperature and in range of seasonal temperatures. To determine whether this ability to exist in thermally different sites is owing to phenotypic plasticity or to population differentiation I raised fish from a spring site and a pond site under common laboratory conditions. Fish were raised at one of two temperatures during gestation and at one of two temperatures from birth to sexual maturity. Gestation temperature, rearing temperature, population of origin, and gender had complex, interacting effects on critical thermal maximum and minimum at sexual maturity, on offspring survival, and on time to maturity. In particular, the populations were strongly differentiated for offspring survival and time to maturity, although the magnitude of the differences depended on the environment. Females performed better than males when genders differed. / H. formosa also exhibit superfetation, the presence of embryos in different developmental stages in the ovary at one time. There have been few comparative studies of interspecific variation in superfetation, and there have been no surveys of population variation in reproductive traits within a superfetating species. In this study I followed seasonal changes in reproductive parameters of four populations of H. formosa for all or part of 4 years. / The four populations differed in breeding phenology, level of superfetation, total volume of embryos carried, and brood size. This variation does not correspond to either general habitat similarities among the populations (ponds versus rivers), or to habitat stability. I also discovered that first, females must hold back some same-stage embryos while advancing others and second, that size of females, as measured by standard length, clearly influences the total number of embryos, brood size, and number of embryos carried in each stage. Yet despite this relationship between body size and embryo capacity, brood size is not constrained by space available for late-stage embryos. / Source: Dissertation Abstracts International, Volume: 51-02, Section: B, page: 0549. / Major Professor: Joseph Travis. / Thesis (Ph.D.)--The Florida State University, 1989.

Zinc is now firmly established as an essential trace element in the human body. Whilst it has many key structural and catalytic fixed roles, it is also found in 'mobile' pools in many essential organs and organelles that are readily chelatable. The presence and trafficking of these zinc pools are thought to contribute in some form to many human disease states associated with these organs, for example, Type 2 diabetes in the pancreas, some forms of cancer in the prostate, and even ischemic stroke, epilepsy and Alzheimer's disease. The exact role however, remains largely unknown and this is due to our current limitations with the methods in which we monitor the movement of this important element in our body. This thesis presents our efforts to develop novel Zn2+ selective chemosensors that can meet contemporary criteria for successful and simple imaging. Many efforts are being made to develop simple fluorescent molecular probes to monitor the trafficking and progress of Zn2+ through these cells and organs in real time via these chelatable 'mobile' pools. Chapter 1 will outline some successful efforts towards these and discuss their relevance and mechanisms of action, as well as outlining 'click'-chemistry and its role in chemosensing to date. Chapter 2 describes a novel 'click'-chemistry approach designed to aid with the simple construction of novel zinc-chelating probes in a facile and high yielding manner. This methodology was taken forward to the synthesis of 6 novel Zn2+-selective small molecule fluorescent probes that incorporate a cell organelle targeting motif in their structure. These are described in Chapter 3, and their successful testing both in-vitro and in-cellulo in murine pancreatic islet cells is presented and discussed. Finally, Chapter 4 discusses the development of some modified fluorescent [2]rotaxanes as molecularly interlocked architectures capable of binding and sensing metals, and will specifically focus on how small structural changes led to vast differences in their fluorescence properties, ultimately resulting in a Zn2+-selective [2]rotaxane in organic media.

<p> This study implemented LiDAR (Light Detection and Ranging) remote sensing technology and applied ITD (Individual Tree Detection) methods as an approach to estimate some essential tree variables, such as DBH (Diameter at Breast Height), height, volume, and biomass for Ford Forest Research Center in Upper Peninsula, Michigan. There were 34 deciduous (1 bigtooth aspen, 9 red oaks, 20 sugar maples, 2 white birches, and 2 yellow birches) and 17 coniferous (2 eastern hemlocks, 11 red pines, and 4 white pines) subject tree species. There were two different available LiDAR datasets from the same area that were collected in 2011 and 2017. Height measurements were done at 96% and 97% accuracy for hardwood and softwood tree species, respectively. </p><p> Several other tree variables derived from LiDAR point cloud were used to estimate DBH by using regression analysis for both 2017 and 2011 datasets. Estimation equations were tested on the other dataset. The best-fitted formula was 2017&rsquo;s, with 0.55 adjusted R&sup2; and less than 0.0001 p-values on 2017 LiDAR data while 0.42 adjusted R&sup2; and less than 0.0001 p-values on 2011&rsquo;s dataset. Some additional analysis that includes calculating PRMSE (Predicted Root Mean Square Error), BIAS (Mean Error), and MAD (Mean Absolute Difference) have been applied. The equation that was generated by using data from 2017 has &ndash;0.57 BIAS for Hardwood and 1.13 BIAS for softwood. That result indicates that the equation has &ndash;0.57 centimeters (cm) estimation error for hardwood and 1.13 cm for softwood on DBH estimations. </p><p>

"This thesis presents an effective approach to study tactile based mobile robot navigation. A Matlab simulator, which can simulate the properties of the tactile sensors, the environment, and the motion of the robot, is developed. The simulator uses an abstraction model of a compliant tactile sensor to represent an array of sensors covering the robot. The tactile sensor can detect normal and shear forces. The simulator has been used by a set of human subjects to drive a robot in an indoor environment to capture data. The details of the implementation and the data collected are presented in this thesis. From the data, some contact features can be extracted. Regarding the features, this thesis uses the Gaussian classifier and Gaussian mixture model to classify the data and build the feature classification model. Comparing the classification results of these two methods, the Gaussian mixture model has better performance. Applying the feature classification model, some contact objects can be detected, such as wall and corner. Based on this classification tool, a simple navigation problem can be solved successfully."

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