Browsing by Subject "Morphology"

Utilizing the power of Monte Carlo simulations, a novel, semi-empirical method for investigating the performance of organic photovoltaics (OPVs) in resonant infrared, matrix-assisted pulsed laser evaporation (RIR-MAPLE) films is explored. Emulsion-based RIR-MAPLE offers a unique and powerful alternative to solution processing in depositing organic materials for use in solar cells: in particular, its usefulness in controlling the nanoscale morphology of organic thin films and the potential for creating novel hetero-structures make it a suitable experimental backdrop for investigating trends through simulation and gaining a better understanding of how different thin film characteristics impact OPV device performance.

The work presented in this dissertation explores the creation of a simulation tool that relies heavily on measureable properties of RIR-MAPLE films that impact efficiency and can be used to inform film deposition and dictate the paths for future improvements in OPV devices. The original nanoscale implementation of the Monte Carlo method for investigating OPV performance is transformed to enable direct comparison between simulation and experimental external quantum efficiency results. Next, a unique microscale formulation of the Dynamic Monte Carlo (DMC) model is developed based on the observable, fundamental differences between the morphologies of RIR-MAPLE and solution-processed bulk heterojunction (BHJ) films. This microscale model enables us to examine the sensitivity of device performance to various structural and electronic properties of the devices. Specifically, using confocal microscopy, we obtain an average microscale feature size for the RIR-MAPLE P3HT:PC61BM (1:1) BHJ system that represents a strategic starting point for utilizing the DMC as an empirical tool.

Building on this, the RIR-MAPLE P3HT:PC61BM OPV system is studied using input simulation parameters obtained from films with different material ratios and overall device structures based on characterization techniques such as grazing incidence-wide angle X-ray scattering (GI-WAXS) and X-ray photoelectron spectroscopy (XPS). The results from the microscale DMC simulation compare favorably to experimental data and allow us to articulate a well-informed critique on the strengths and limitations of the model as a predictive tool. The DMC is then used to analyze a different RIR-MAPLE BHJ system: PCPDTBT:PC71BM, where the deposition technique itself is investigated for differences in the primary solvents used during film deposition.

Finally, a multi-scale DMC model is introduced where morphology measurements taken at two different size scales, as well as structural and electrical characterization, provide a template that mimics the operation of OPVs. This final, semi-empirical tool presents a unique simulation opportunity for exploring the different properties of RIR-MAPLE deposited OPVs, their effects on OPV performance and potential design routes for improving device efficiencies.

Animals experience hydrodynamic forces (lift, drag, and side) and moments (pitching, yawing, and rolling) as a result of motion in an aqueous medium. Under selective pressure, most cetaceans, including porpoises, dolphins, and whales, developed a streamlined body shape and modified limbs, which delay the separation of flow, create lower drag when they swim, and therefore decrease their locomotor cost. In order to calculate the locomotor cost and propulsive efficiency of cetaceans, accurate estimates of drag on marine animals are required. However, extra momentum imparted into the fluid from lift and side forces as well as pitching, rolling, and yawing moments (here, the parasitic loads) results in extra drag force on the animal. Therefore, in addition to streaming and delaying flow separation, animals must also minimize excess fluid momentum resulting from parasitic loads. Given the endangered status of the North Atlantic right whale (Eubalaena glacialis; hereafter NARW), analyzing the hydrodynamic characteristics of the NARWs was the focus of this work. Additionally, previous studies showed that body shape of NARWs changes with life stages, reproduction status, nutritive conditions or prey abundance, and the effects of entanglement in fishing gear. Therefore, in this study, computational fluid dynamics (CFD) analysis was performed on multiple 10 m three-dimensional NARW models with different body shapes (e.g., normal condition, emaciated, and pregnant) to measure baseline measurements of flow regimes and hydrodynamic loads on the animal. Swimming speeds covering known right whale speed range (0.125 m/s to 8 m/s) were simulated in most scenarios. In addition to the hydrodynamic effects of different body shapes, drag was also considered a function of parasitic loads. The NARW models were embedded with bone segments that allowed one to manipulate the body pose of the model via adjusting the flippers or the spine of the animal before measuring hydrodynamic drag. By doing so, momentum from parasitic loads was expected to be eliminated. CFD simulations revealed that drag on NARWs is dictated by its irregular outline and that the drag coefficient (0.0071-0.0059; or dimensionless drag) of on NARWs is approximately twice that of many previous estimates for large cetaceans. It was also found that pregnant NARW model encounters the lowest drag coefficient due to delayed flow separation resulting from enlarged abdomen, whereas the emaciated NARW model experiences the highest drag coefficient possibly due to the concavity at the post-nuchal region. These results suggested that drag on NARWs and their thrust power requirements were indeed affected by its body shape but the differences between the three NARW models tested were small. Lastly, minimum drag, which corresponds to the elimination of the parasitic loads, can be obtained by adjusting the pose of the animal. Thus, minimum drag occurs at the neutral trim pose. For the static, normo-nourished NARW model, simulations revealed that by changing the angle of attack of the flippers by 4.03° (relative to the free-stream flow) and pitching the spine downward by 5° while maintaining fluke angle, the drag was lowered by approximately 11% across the flow speeds tested. This drag reduction was relative to the drag study conducted on the same animal model but without body pose adjustments. Together the studies included in the present work explored and highlighted the capability of numerical methods in investigating the hydrodynamics and energetics of cetaceans. Future studies should address how computer solutions can be used to solve problems from a wider aspect. For instance, extra parasitic loads caused by attached gear as well as possible injuries due to the encounter with fishing gear should also be considered while evaluating the energy budget of the North Atlantic right whales.

A major goal of biological studies is to understand how complex forms develop and evolve. Each form is the result of molecular developmental patterning, growth, and the accumulation of changes in these processes from internal and external perturbations in ancestral forms. This dissertation uses each of these lenses to investigate the complex forms in the insect family Membracidae, which arises from the pronotum. In most insects, the pronotum is a simple, domed structure just behind the head, but in membracids it has enlarged and elaborated to look like thorns, plant stipules, fungi, and ants, among other shapes. To investigate this diversity, I rely on landmark based geometric morphometrics to quantify pronotal shapes. The specimens I used included those from a laboratory colony, those collected in and around San Jose, Costa Rica, and those from the Smithsonian National Museum of Natural History collection. In Chapter 1, I examined 5th instar morphogenesis to elucidate the timing of developmental events during the transition from juvenile to adult. These findings informed Chapter 2, which revealed developmental mechanisms related to growth led to transcriptional similarity between the pronotum and wings. In Chapter 3, I identified ontogenetic changes in the patterning of membracid pronotal shape compared to that of a closely related outgroup. Finally, in Chapter 4, I used a phylogenetic framework to investigate developmental modules and the co-occurrence of pronotal shape with two life history characteristics.

Fossil taxa are crucial to studies of brain evolution, as they allow us to identify evolutionary trends in relative brain size and brain shape that may not otherwise be identifiable in comparative studies using only extant taxa, owing to multiple events of parallel encephalization among primate clades. This thesis combines indirect and direct approaches to understanding primate evolution, by evaluating variation in the endocranial morphology of extant primates and their fossil representatives. I use a comparative approach to examine the relationships between interspecific adult endocranial volume and shape, and brain evolution and cranial form among extant primate clades and their fossil representatives. The associations are evaluated via phylogenetically informed statistics perfomed on volumetric measurements and three-dimensional geometric morphometric analyses of virtual endocasts constructed from micro-CT scans of primate crania. Fossil taxa included in these analyses are: 1) anthropoids Parapithecus, Aegyptopithecus (Early Oligocene, Egypt), Homunculus and Tremacebus (Early Miocene, Argentina), and 2) Eocene euprimates Adapis and Leptadapis (Eocene adapoids, France), and the Rooneyia (Eocene omomyoid, Texas).

The first part of this work (Chapter 2) explores variation in residual mass of brain components (taken from the literature) among primates, and evaluates the correlated evolution of encephalization and brain proportions with endocast shape, quantified via three-dimensional geometric morphometric techniques. Analyses reveal a broad range of variation in endocast shape among primates. Endocast shape is influenced by a complex array of factors, including phylogeny, body size, encephalization, and brain proportions (residual mass of brain components). The analysis supports previous research, which concludes that anthropoids and tarsiers (Haplorhini) share the enlargement of several key brain regions including the neocortex and visual systems, and a reduction of the olfactory system. Anthropoids further differ from strepsirrhines in endocranial features associated with encephalization--a more flexed brain base, an inferiorly deflected olfactory fossa--and those associated with brain proportions--a small olfactory fossa, and a more caudally extended cerebrum that extends posteriorly past the cerebellar poles. Tarsiers are unique in having a mediolaterally broad and rostro-caudally short endocast with an attenuated anterior and middle cranial fossae. This morphology is likely related to the extreme orbital enlargement in this taxon, which limits anterior expansion of the endocranium. Finally, despite the correlation between residual endocranial volume and endocast shape among modern primates, early anthropoid fossils demonstrate a disconnect between these factors in sharing key features of endocast shape with extant anthropoids at a relatively small brain size.

The second part of this thesis (Chapter 3) explores the relationship between craniofacial organization--cranial base angle, facial size, facial hafting--and encephalization via the lens of the Spatial Constraints and Facial Packing Hypotheses. These hypotheses predict that interspecific adult variation in encephalization correlates with endocranial shape such that a larger brain for a given body size will be more "globular" or spherical in shape. These hypotheses futher predict that basicranial angle covaries with encephalization and that the relative size of the endocranium and facial skeleton will have an antagonistic effect on basicranial angle and facial hafting. Results show that various measures of globularity have inconsistent and weak relationships to phylogeny, encephalization, and basicranial flexion, owing to a diversity of clade-specific scaling patterns between the maximum length, breadth, and width of the endocast. Among extant primates, there is weak but significant evidence to suggest that both facial size and encephalization influence variation in basicranial flexion. Considering the fossil specimens in isolation, their relative ranks in encephalization, basicranial flexion, and midline facial size and shape follow the pattern expected from the Spatial and Facial Packing Hypotheses outlined above; however, relative to modern species, the early fossil anthropoids have more flexed cranial bases and shorter facial skeletons at much smaller level of encephalization than seen in modern anthropoids.

Together, the extant data suggest a moderately conserved pattern of correlated evolution among endocranial size, endocranial shape, brain proportions, and craniofacial organization, which may explain differences in endocranial and facial shape between extant strepsirrhine and anthropoid primates; however, the fossil record for early anthropoid evolution demonstrates that a shift towards key anthropoid-like traits of the endocranium, basicranium, and facial skeleton were initiated early in anthropoid evolution, with subsequent encephalization occurring within and among members of this clade. Thus, these anthropoid cranial traits evolved in tandem with changes in the relative size of brain components, rather than absolute or relative brain size alone. Basicranial flexion, facial length and orientation are influenced by both: 1) shifts in endocranial shape associated with changes in brain proportion--accounting for the initiation of the anthropoid-like craniofacial plan early in the evolution of the clade--and 2) encephalization, which influenced subsequent morphological divergence among extant anthropoid groups.

Not all ferns grow in moist and shaded habitats. One notable example is the ecologically unusual clade of notholaenids. With approximately 40 species, the notholaenids have adapted to and diversified within the deserts of Mexico and the southwestern United States. In my dissertation, I studied the evolution and diversification of notholaenid ferns, using an approach that integrates data from multiple sources: biochemistry, biogeography, cytology, ecological niche modeling, molecular phylogeny, morphology, and physiology.

In Chapter 1, I infer a species phylogeny for notholaenid ferns using both nuclear and plastid DNA sequences, and reconstruct the evolutionary history of “farina” (powdery exudates of lipophilic flavonoid aglycones), a characteristic drought-adapted trait, that occurs on both the gametophytic and sporophytic phases of members of the the clade. Forty-nine notholaenid and twelve outgroup samples were selected for these analyses. Long (ca. 1 kb) low-copy nuclear sequences for four loci were retrieved using a recently developed amplicon sequencing protocol on the PacBio Sequel platform and a bioinformatics pipeline PURC; plastid sequences from three loci were retrieved using Sanger sequencing. Each nuclear/plastid dataset was first analyzed individually using maximum likelihood and Bayesian inference, and the species phylogeny was inferred using *BEAST. Ancestral states were reconstructed using likelihood (re-rooting method) and MCMC (stochastic mapping method) approaches. Ploidy levels were inferred using chromosome counts corroborated by spore diameter measurements. My phylogenetic analyses results are roughly congruent with previous phylogenies inferred using only plastid data; however, several incongruences were observed between them. Hybridization events among recognized species of the notholaenid clade appear to be relatively rare, compared to what is observed in other well-studied fern genera. All characters associated with farina production in the group appear to be homoplastic and have complex evolutionary histories.

In Chapter 2, I focus on the infraspecific diversification of Notholaena standleyi, a species that thrives in the deserts of the southwestern United States and Mexico and has several “chemotypes” that express differences in farina color and chemistry. Forty-eight samples were selected from across the geographic distribution of N. standleyi. Phylogenetic relationships were inferred using four plastid makers and five single/low-copy nuclear markers. Sequences were retrieved using PacBio and the PURC pipeline. Ploidy levels were inferred from relative spore size measurements calibrated with chromosome counts, and farina chemistry was compared using thin-layer chromatography (TLC). My studies of Notholaena standleyi reveal a complex history of infraspecific diversification traceable to a variety of evolutionary drivers including classic allopatry, parapatry with or without changes in geologic substrate, and sympatric divergence through polyploidization. Four divergent clades were recognized within the species. Three roughly correspond to previously recognized chemotypes: gold (G), yellow (Y), and pallid/yellow-green (P/YG). The fourth clade, cryptic (C), is newly reported here. The diploid clades G and Y are found in the Sonoran and Chihuahuan Deserts, respectively; they co-occur (and hybridize) in the Pinaleño Mts. of eastern Arizona. Clades G and Y are estimated to have diverged in the Pleistocene, congruent with the postulated timing of climatological events that divide these two deserts. Clade P/YG is tetraploid and partially overlaps the distribution of clade Y in the eastern parts of the Chihuahuan Desert. However, PY/G is apparently confined to limestone, a geologic substrate rarely occupied by members of the other clades. The newly discovered diploid clade, cryptic (C), is distributed in the southern Mexican states of Oaxaca and Puebla and is highly disjunct from the other three clades.

In Chapter 3, I study the ecological niche differentiation among the three major chemotypes––G, Y, and P/YG. Using both ordination and species distribution modelling techniques, the ecological niches for each chemotype were characterized and compared. The main environmental drivers for their distributions were identified, their suitable habitats in both geographic and environmental spaces were predicted, and their niche equivalencies and similarities were tested. My ecological niche analyses results suggest that all three chemotypes are ecologically diverged. The ecological niches of the two parapatric, sister diploid chemotypes, G and Y, are significantly different from one another. Chemotype G occupies a very extreme niche with higher solar radiation, and lower rainfall and higher temperatures in the wettest quarter. The niche space of tetraploid chemotype P/YG is similar but not equivalent to the other two chemotypes. Its distribution model is highly influenced by the high percentage of Calcids and warmer temperatures in the wet season, reflecting the fact that it is confined to limestone in areas of lower elevation/latitude.

In Chapter 4, I gather together all my other studies related to Notholaena standleyi, including: 1) morphological and anatomical observations of its desiccation-tolerant leaf, with special focus on the farina; 2) two cases of hybridization between the chemotypes, one between the diploid chemotype Y and tetraploid chemotype YG, and another between diploid chemotypes Y and G; and 3) morphological and physiological comparisons between the two diploid chemotypes Y and G. My plan is to finalize these studies and submit them for publication in the near future.

In Chapter 5, I summarize collaborative contributions that I made to other fern studies during my Ph.D.

Increasingly, drone-based photogrammetry has been used to measure size and body condition changes in marine megafauna. A broad range of platforms, sensors, and altimeters are being applied for these purposes, but there is no unified way to predict photogrammetric uncertainty across this methodological spectrum. As such, it is difficult to make robust comparisons across studies, disrupting collaborations amongst researchers using platforms with varying levels of measurement accuracy.

In this dissertation, I evaluate the major drivers of photogrammetric error and develop a framework to easily quantify and incorporate uncertainty associated with different UAS platforms. To do this, I take an experimental approach to train a Bayesian statistical model using a known-sized object floating at the water’s surface to quantify how measurement error scales with altitude for several different drones equipped with different cameras, focal length lenses, and altimeters. I then use the fitted model to predict the length distributions of unknown-sized humpback whales and assess how predicted uncertainty can affect quantities derived from photogrammetric measurements such as the age class of an animal (Chapter 1). I also use the fitted model to predict body condition of blue whales, humpback whales, and Antarctic minke whales, providing the first comparison of how uncertainty scales across commonly used 1-, 2-, and 3-dimensional (1D, 2D, and 3D, respectively) body condition measurements (Chapter 2). This statistical framework jointly estimates errors from altitude and length measurements and accounts for altitudes measured with both barometers and laser altimeters while incorporating errors specific to each. This Bayesian statistical model outputs a posterior predictive distribution of measurement uncertainty around length and body condition measurements and allows for the construction of highest posterior density intervals to define measurement uncertainty, which allows one to make probabilistic statements and stronger inferences pertaining to morphometric features critical for understanding life history patterns and potential impacts from anthropogenically altered habitats. From these studies, I find that altimeters can greatly influence measurement predictions, with measurements using a barometer producing larger and greater uncertainty compared to using a laser altimeter, which can influence age classifications. I also find that while the different body condition measurements are highly correlated with one another, uncertainty does not scale linearly across 1D, 2D, and 3D body condition measurements, with 2D and 3D uncertainty increasing by a factor of 1.44 and 2.14 compared to 1D measurements, respectively. I find that body area index (BAI) accounts for potential variation along the body for each species and was the most precise body condition measurement.

I then use the model to incorporate uncertainty associated with different drone platforms to measure how body condition (as BAI) changes over the course of the foraging season for humpback whales along the Western Antarctic Peninsula (Chapter 3). I find that BAI increases curvilinearly for each reproductive class, with rapid increases in body condition early in the season compared to later in the season. Lactating females had the lowest BAI, reflecting the high energetic costs of reproduction, whereas mature whales had the largest BAI, reflecting their high energy stores for financing the costs of reproduction on the breeding grounds. Calves also increased BAI opposed to strictly increasing length, while immature whales may increase their BAI and commence an early migration by mid-season. These results set a baseline for monitoring this healthy population in the future as they face potential impacts from climate change and anthropogenic stresses. This dissertation concludes with a best practices guide for minimizing, quantifying, and incorporating uncertainty associated with photogrammetry data. This work provides novel insights into how to obtain more accurate morphological measurements to help increase our understanding of how animals perform and function in their environment, as well as better track the health of populations over time and space.

Dietary adaptation appears to have driven many aspects of the high-level diversification of primates. Dental topography metrics provide a means of quantifying morphological correlates of dietary adaptation and can be used to reconstruct dietary adaptation in extinct taxa, model ecospace occupation, and capture macroevolutionary trends across deep time. However, difficulties may arise in the interpretation of dental topography metrics from A) their sensitivity to digital mesh processing choices; B) their tendency to average morphological information across tooth surfaces; and C) potential mismatches between the material properties understood theoretically to drive tooth shape and the measured properties of categorically defined primate diets. The full potential of pairing dental topography metrics with modern phylogenetic comparative methods, which would allow the evolutionary history of diet in large clades to be explored statistically, has yet to be explored.

In this dissertation, I attempt to address issues in the application of dental topography metrics, and extend them to new questions, using strepsirrhine primates as a model. The effectiveness of a recently described dental topography metric, ariaDNE, which is robust to details of mesh processing, in describing dietary adaptation in lower second molars is assessed. It is found that it performs at least as well as metrics more sensitive to mesh processing decisions. ariaDNE is then applied to segmented regions of lower second molars in order to assess the effect of averaging together potentially adaptively distinct tooth structures. I found no evidence that the aggregation of tooth structures significantly impairs dietary classification. These studies employ explicit methods for measuring overfitting risk, which has not previously been emphasized in applications of dental topography metrics.

Tooth shape is believed to reflect differences in the underlying material properties of the foods consumed by mammals, but the categories used to classify taxa to diets have inconsistent relationships with these food material properties. I attempt to address this inconsistency by relating tooth shape to expected geographic gradients in food material properties, an approach known as ecometrics. Dry, seasonal environments are expected to be associated with dental topography metrics associated with processing tougher foods. I find that ariaDNE is highest in highly seasonal but wet environments, supporting a role for the seasonal exploitation of fallback foods and that the availability of new leaves during wet periods may be important in driving community tooth sharpness. Tooth complexity is primarily driven by a stepwise increase in rainforest environments.

Dental topography metrics are then applied to several questions concerning the evolutionary history of lemurs. They are used to reconstruct the diets of seven genera of recently extinct, giant, subfossil lemurs, and find many of them to have exploited fruits and hard objects. Ecometric models are also applied to the reconstruction of paleoclimate at the ~500 year-old subfossil cave site of Ankilitelo, which records the last appearance of many subfossil lemur taxa. Models reconstruct a moister climate for Ankilitelo at the time of the accumulation of its subfossil fauna, supporting a role for climate alteration in the extirpation of the giant lemurs.

Finally, Dental topography metrics are combined with phylogenetic comparative methods to model the dietary evolution of lemurs in the context of adaptive radiation theory. Dental topography metrics do not show an early burst in rates of change or a pattern of early partitioning of subclade disparity in lemurs. However, rates of transition toward folivory were highest during the Oligocene, an interval of possible forest expansion on the island and of the dispersal of non-chiromyiform lemurs to Madagascar. Reconstruction of the ancestral molar morphology of ancestral nodes of the lemur tree suggest that the diversification of large bodied lemurs may have been driven by a shift toward the exploitation of defended plant resources.

Primates span incredible behavioral and ecological diversity, and this diversity is reflected in the shape of the skull. This dissertation asks two questions surrounding the evolution of primate skull shape: 1) what are the macroevolutionary correlates of primate skull shape? And 2) what is the pattern of phenotypic integration in the primate skull at a macroevolutionary scale? To address these questions, I compiled a broad comparative dataset of anatomical landmarks identified from 3D scans of primate skulls and analyzed this data using statistical methods that combine geometric morphometrics and phylogenetic comparative methods. To investigate the macroevolutionary correlates of skull shape, I used multivariate phylogenetic generalized linear models to test for relationships between skull shape and several variables that are predicted to be correlated with skull shape: allometry, typical diet, tree gouging behavior, activity pattern, and sexual dimorphism. I found strong phylogenetic signal for primate skull shape, confirming the need for phylogenetic comparative methods. Allometry was a significant predictor of skull shape, with larger primates having relatively small, convergent orbits, and anteroposteriorly short skulls compared to small primates. Sexual dimorphism was associated with a dramatically lengthened rostrum, probably to facilitate a large gape in aggressive displays. Folivory was associated with deeper mandibles, which may improve mechanical advantage and strain resistance. To investigate patterns of phenotypic integration in the skull, I performed hierarchical clustering analyses on phylogenetically corrected inter-landmark covariance matrices. In contrast to previous research, I did not find evidence for distinct phenotypic modules in the primate skull, and I argue that this discrepancy is due to methodological shortcomings of past research that biased results towards identifying different anatomical regions as discrete modules. This dissertation represents one of the first investigations of primate skull shape at a macroevolutionary scale, and demonstrates that the combination of geometric morphometrics and phylogenetic comparative methods can yield novel insights into evolutionary morphology.

The defining characteristic of the subphylum Vertebrata is the vertebral column, which is comprised of alternating vertebral bodies and intervertebral discs. In spite of being a highly conserved structure, the morphogenetic events that culminate in building the vertebral column remain poorly understood. In particular, patterning mechanisms underlying how segmentation of the spine is precisely established have not been examined at post-embryonic stages. For several years, vertebral column patterning was thought to hinge upon proper segmentation of the embryo, while the notochord served as a transient scaffold for the vertebral bodies and intervertebral discs. Using genetic, live-imaging, and quantitative approaches, this work illustrates that the notochord sheath in zebrafish, provides a template for osteoblast recruitment and vertebral bone formation in the developing spine. Furthermore, we show that notochord segmentation is influenced by the adjacent muscle segments and connective tissue, which may provide mechanical patterning cues. Insights from this work will better inform how adolescent idiopathic scoliosis and congenital scoliosis arise.

Tip growth in fungi involves highly polarized secretion and modification of the cell wall at the growing tip. The genetic requirements for initiating polarized growth are perhaps best understood for the model budding yeast, Saccharomyces cerevisiae. Once the cell is committed to enter the cell cycle by activation of G1 cyclin/cyclin-dependent kinase (CDK) complexes, the polarity regulator Cdc42 becomes concentrated at the presumptive bud site, actin cables are oriented towards that site, and septin filaments assemble into a ring around the polarity site. Several minutes later, the bud emerges. Here, we investigated the mechanisms that regulate the timing of these events at the single cell level and the role of polarisome during pheromone-induced polarized growth. We employed genetics and live cell microscopy to characterize cellular events. Septin recruitment was delayed relative to polarity establishment, and our findings suggest that a CDK-dependent septin “priming” facilitates septin recruitment by Cdc42. Bud emergence was delayed relative to the initiation of polarized secretion, and our findings suggest that the delay reflects the time needed to weaken the cell wall sufficiently to bud. Rho1 activation by Rom2 occurred at around the time of bud emergence, perhaps in response to local cell wall weakening. This report reveals regulatory mechanisms underlying the morphogenetic events in the budding yeast.

Scallops, a family of swimming bivalve mollusks, have dozens of eyes arrayed along the edges of their valves. Relatively little is known about the form and function of these unusual eyes. To learn more about them, we studied the visually influenced behavior of scallops, as well as the morphology and spectral sensitivity of their eyes. Of particular interest was whether or not the simple neural architecture of these animals constrains the number of visually-influenced behaviors they can perform. We were also interested to learn whether scallop eyes, despite providing relatively poor visual acuity, show optical refinements, such as corrections for spherical and chromatic aberration, that are known from the eyes of animals with better vision. In the following dissertation, Chapter 2 discusses the visually-influenced behaviors of scallops. It has been argued that bivalve mantle eyes only act as predator-detectors, but the behavioral trials described in this chapter suggest that vision may serve additional purposes in scallops. For example, it was found that visual cues relating to flow conditions may influence scallop feeding behavior. Chapter 3 presents a comparative study of scallop eye morphology. Here, it is found that eye morphology varies considerably between scallop species and that highly mobile scallops have better vision than less mobile or immobile species. Evidence is also presented that one of the two scallop retinas may perform tasks of similar importance to all species, such as predator detection, while the other retina may perform tasks more important to mobile species, such as those associated with the visual detection of preferred habitats. Chapter 4 investigates the spectral sensitivity of the two retinas in the mantle eyes of two scallop species. It is found that there is both inter- and intra-specific variation in scallop spectral sensitivity and that color perception in scallops may be influenced by both environmental light conditions and chromatic aberration caused by their lens. The research in this dissertation provides insight into how vision functions in animals that, like scallops, have a vast number of eyes, but a limited capacity for neural processing. Despite such limitations, it is evident that scallops display a wide range of visual behaviors and have eyes with highly-refined optics.

The purpose of this dissertation was to improve CT-based radiomics characterization by assessing and accounting for its systematic and stochastic variability due to variations in the imaging method. The anatomically informed methodologies developed in this dissertation enable radiomics studies to retrospectively correct for the effects CT imaging protocols and prospectively inform CT protocol choices. This project was conducted in three parts of 1) assessing of the bias and variability of morphologic radiomics features across a wide range of CT imaging protocols and segmentation algorithms, 2) assessing the applicability, sensitivity, and usefulness of applying bias correction factors retrospectively to patient data acquired with heterogenous CT imaging protocols, and 3) developing analytical techniques to reduce the variability of radiomics features by prospectively optimizing the CT imaging protocols.

In part 1 (chapters 2-4), the measurability of bias and variability of morphologic radiomcis features was assessed. In chapter 2, a theoretical framework was developed to guide the process of analyzing and utilizing quantitative features, including radiomics, derived from CT images. The framework outlined the key qualities necessary for successful quantification including biological and clinical relevance, objectivity, robustness, and implementability. In chapter 3, a method was developed to use anatomically informed lung lesion models to assess the bias and variability of morphology radiomics features as a function of CT imaging protocols and segmentation algorithms. The results showed that bias and variability of radiomics features are dependent on a complicated interplay of anatomical, imaging protocol, and segmentation effects. In chapter 4, the bias and variability of radiomics due to segmentation algorithms was explored in-depth for three segmentation algorithms across a range of image noise magnitudes. The segmentation algorithms were assessed by comparing their performance to an ideal radiomics estimator for a range of image quality characteristics. The results showed that the optimal segmentation algorithm was function of the specific noise magnitude and the radiomics features of interest.

In part 2 (chapter 5), an analysis was carried out using a Non-Small Cell Lung Cancer patient dataset to assess the applicability, sensitivity, and usefulness of correcting radiomics features for imaging protocol effects. The applicability was assessed by calculating bias correction factors from one set of anatomically informed lesion models and applying the correction factors to another set of anatomically informed lesion models. The sensitivity was assessed by applying idealized bias correction factors to the patient dataset with increasing bias correction magnitudes to determine the sensitivity of predictive models to the magnitude of the bias correction factors. Finally, the usefulness was assessed by applying the anatomically informed protocol-specific bias correction factors to the patient dataset and quantifying the change in the performance predictive model. The results showed that the bias correction factors are applicable when the bias correction factors are derived from and applied to lesion models with similar anatomical characteristics. The feature-specific sensitivity of prediction to bias correction factors was found to be as low as 1-5% and was typically in the range of 20-50%. The bias correction factors were applied to a patient population and were found to result in a small statistically significant improvement in the performance.

In part 3 (chapter 6), a method was developed and implemented to assess the minimum detectable difference of morphologic radiomics features as a function of protocol and anatomical characteristics. The analysis of the data was carried out to allow for evaluating and informing the recommendations of the Quantitative Imaging Biomarkers Alliance (QIBA) for lung nodule volumetry. The results showed that the minimum detectable difference for QIBA compliant protocols was a lower median value than the minimum detectable difference among all possible CT protocols. The techniques developed in this analysis can be used to prospectively optimize CT imaging protocols for improved quantitative characterization of radiomics features.

In conclusion, this dissertation developed methods to assess and account for the variability of radiomics features across CT imaging protocols and segmentation algorithms using anatomically informed lesion models.