Analysis of wheat spike characteristics using image analysis, machine learning, and genomics

2022 Summer.Includes bibliographical references.Understanding genetics regulating yield component and spike traits can contribute to the development of new wheat cultivars. The flowering pathway in wheat is not entirely known, but spike architecture and its relationship with yield component traits could provide valuable information for crop improvement. Spikelets spike-1 (SPS) has previously been positively associated with kernel number spike (KNS) and negatively correlated with thousand kernel weight, meaning a further understanding of SPS could help unlock full yield potential. While genomics research has improved efficiency over time with the development of techniques such as genotyping by sequencing (GBS), phenotyping remains a labor and time intensive process, limiting the amount of phenomic data available for research. Recently, there has been more interest in generating high-throughput methods for collecting and analyzing phenotypic data. Imaging is a cheap and easily reproducible way to collect data at a specific maturity point or over time, and is a promising candidate for implementing deep learning algorithms to extract traits of interest. For this study, a population of 594 soft red winter wheat (SRWW) inbred lines were evaluated for wheat spike characteristics over two years. Images of wheat spikes were taken in a controlled environment and used to train deep learning algorithms to count SPS. A total of 12,717 images were prepared for analysis and used to train, test, and validate a basic classification and regression convolutional neural network (CNN), as well as a VGG16 and VGG19 regression model. Classification had a low accuracy and did not allow for an assessment of error margins. Regression models were more accurate. Of the regression models, VGG16 had the lowest mean absolute error (MAE) (MAE = 1.09) and mean squared error (MSE) (MSE = 2.08), and the highest coefficient of determination (R2) (R2 = 0.53) meaning it had the best fit of all models. The basic CNN was the next well fit model (MAE = 1.27, MSE = 2.61, r = 0.48) followed by the VGG19 (MAE = 1.32, MSE = 2.98, r = 0.45). With an average error of just above one spikelet, it is possible that counting methods could provide enough data with an accuracy high enough for use in statistical analyses such as genome wide association studies (GWAS), or genomic selection (GS). A GWAS was used to identify markers associated with SPS and yield component traits, while demonstrating the use of genomic selection (GS) for prediction and screening of individuals across multiple breeding programs. The GWAS results indicated similar markers and genotypic regions underpinning both KNS and SPS on chromosome 6A and spike length and SPS on chromosome 7A. It was observed that favorable alleles at each locus were associated with higher KNS and SPS on chromosome 6A and longer wheat spikes with higher SPS on chromosome 7A. Significant markers on 7A were observed in the region near WAPO1, the causal gene for SPS on the long arm of chromosome 7A, indicating they could be associated with that gene. GS results showed promise for whole genome selection, with the lowest prediction accuracy observed for heading date (rgs = 0.30) and the highest for spike area (rgs = 0.62). SPS showed prediction accuracies ranging from 0.33 to 0.42, high enough to aid in the selection process. These results indicate that knowledge of the flowering pathway and wheat spike architecture and how it relates to yield components could be beneficial for making selections and increasing grain yield

Accumulating culture: the collections of emperor Huizong

published_or_final_versio

DIGITAL IMAGE PROCESSING FOR ULTRASONIC THERAPY AND TENDINOUS INJURY

In this master\u27s thesis, several digital image processing techniques are explored for potential in evaluation of Brightness mode (B-mode) ultrasound images. Currently, many processing techniques are utilized during ultrasound visualization in cardiovascular applications, mammography, and three-dimensional ultrasound systems. However, approaches that serve to aid the clinician in diagnostic assessment of tendinous and ligamentous injuries are more limited. Consequently, the methods employed below are aimed at reducing the dependence on clinician judgment alone to assess the healing stage and mechanical properties of tendinous injuries. Initial focus concentrated on the use of entropy in texture analysis to relate a tendon\u27s appearance in an ultrasound image to its mechanical integrity. Confounding effects such as motion artifacts and region of interest selection by the user limited the applicability of small regions selected for analysis, but general trends were observed when the entire visualized tendon or superficial background region was selected. Entropy calculations suggested a significant change in texture pattern for tendinous regions compared to the selected background regions. In order to reduce the impact of motion artifacts and dependence of the texture analysis on manual identification of regions of interest, a Matlab® script was developed intended to isolate the tendinous regions of interest for further analysis. Methods for segmentation employed relied on a moving window Fourier Transform to compare local parameters in the image to a predefined window of tendinous tissue. Further assessment of each local region benefited from parameterization of the local window\u27s properties that focused on capturing indicators of mean pixel intensity, local variation in pixel intensity, and local directionality consistency derived from the spatial frequency patterns observed in the Fourier Transforms via comparison by the circular Earth Mover\u27s Distance. Results of the segmentation algorithm developed indicated the presence of directional consistency within the tendinous regions, and changes in the speckle pattern were observed for the image derived from mean intensity and local pixel intensity variation. However, non-tendinous regions were also identified for their directional consistency, limiting the applicability of the current process in tendinous region isolation. The results obtained for calculations of the circular Earth Mover\u27s Distance improved slightly with the inclusion of temporal averaging and image registration, but still require improvement before implementation in clinical applications can be realized

Advanced Conducting Project

Sure On This Shining Night by Morten Johannes Lauridsen Sicut Cervus by Giovanni Pierluigi da Palestrina Zigeunerleben, Op. 29, No. 3 by Robert Schumann Ubi Caritas by Ola Gjeilo Eatnemen Vuelie by Frode Fjeilheim, arranged by Emily Crocker Hatikva (Traditional Hebrew Melody) arranged by John Leavitt; lyrics by N.H. Imber Last Words of David by Randall Thompson How Lovely is Thy Dwelling Place by Johannes Brahms

Socio-economic factors and the journey to work: A case study of AT&T GIS employees

Individuals who must commute to work are often concerned with the spatial separation of their home and job site. In many of these cases the socio-economic characteristics of these individual\u27s lives play an important part in deciding how long this commute is, in terms of both time and distance. The following study seeks to identify the relationships between several selected socio-economic characteristics and the journey to work distances for employees at AT&T GIS. The factors being examined in this study are age, education level, number of dependents, income, length of service to the company, occupation type and gender. Significant differences in commuting distances were identified for the subgroups of employees being compared for five of the above factors. Only income and number of dependents were found to have no significant effect on commuting distances. However, when maximum commuting distances were compared for men and women separately, the number of dependents claimed by the individuals in the subgroups was found to affect the spatial separation of home and work for many of these individuals. Crosstabulations, difference of means t-tests and regression analyses were conducted to identify patterns and relationships inherent in the dataset provided by AT&T GIS. Unless stated otherwise, the confidence level selected for all statistical tests was 95%

Virtual Engineering Sciences Learning Lab: Giving STEM Education a Second Life

Engineering education in the 21st century faces multiple obstacles including limited accessibility of course resources due, in part, to the costs associated with acquiring and maintaining equipment and staffing laboratories. Another continuing challenge is the low level of participation of women and other groups historically underrepresented in STEM disciplines. As a partial remedy for these issues, we established a Virtual Engineering Sciences Learning Lab (VESLL) that provides interactive objects and learning activities, multimedia displays, and instant feedback procedures in a virtual environment to guide students through a series of key quantitative skills and concepts. Developed in the online virtual world Second LifeTM, VESLL is an interactive environment that supports STEM education, with potential to help reach women and other underrepresented groups. VESLL exposes students to various quantitative skills and concepts through visualization, collaborative games, and problem solving with realistic learning activities. Initial assessments have demonstrated high student interest in VESLL\u27s potential as a supplementary instructional tool and show that student learning experiences were improved by use of VESLL. Ultimately, the VESLL project contributes to the ongoing body of evidence suggesting that online delivery of course content has remarkable potential when properly deployed by STEM educators

Evaluation of atlas-based segmentation of hippocampi in healthy humans

Introduction and aim: Region of interest (ROI)-based functional magnetic resonance imaging (fMRI) data analysis relies on extracting signals from a specific area which is presumed to be involved in the brain activity being studied. The hippocampus is of interest in many functional connectivity studies for example in epilepsy as it plays an important role in epileptogenesis. In this context, ROI may be defined using different techniques. Our study aims at evaluating the spatial correspondence of hippocampal ROIs obtained using three brain atlases with hippocampal ROI obtained using an automatic segmentation algorithm dedicated to the hippocampus. Material and methods: High-resolution volumetric T1-weighted MR images of 18 healthy volunteers (five females) were acquired on a 3T scanner. Individual ROIs for both hippocampi of each subject were segmented from the MR images using an automatic hippocampus and amygdala segmentation software called SACHA providing the gold standard ROI for comparison with the atlas-derived results. For each subject, hippocampal ROIs were also obtained using three brain atlases: PickAtlas available as a commonly used software toolbox; automated anatomical labeling (AAL) atlas included as a subset of ROI into PickAtlas toolbox and a frequency-based brain atlas by Hammers et al. The levels of agreement between the SACHA results and those obtained using the atlases were assessed based on quantitative indices measuring volume differences and spatial overlap. The comparison was performed in standard Montreal Neurological Institute space, the registration being obtained with SPM5 (http://www.fil.ion.ucl.ac.uk/spm/). Results: The mean volumetric error across all subjects was 73% for hippocampal ROIs derived from AAL atlas; 20% in case of ROIs derived from the Hammers atlas and 107% for ROIs derived from PickAtlas. The mean false-positive and false-negative classification rates were 60% and 10% respectively for the AAL atlas; 16% and 32% for the Hammers atlas and 6% and 72% for the PickAtlas. Conclusion: Though atlas-based ROI definition may be convenient, the resulting ROIs may be poor representations of the hippocampus in some studies critical to under- or oversampling. Performance of the AAL atlas was inferior to that of the Hammers atlas. Hippocampal ROIs derived from PickAtlas are highly significantly smaller, and this results in the worst performance out of three atlases. It is advisable that the defined ROIs should be verified with knowledge of neuroanatomy before using it for further data analysis

Not for men only: The (de)-construction of lesbian/queer public sexualities.

This research study is an exploration of women's sexuality in general and lesbian/queer women's sexuality in particular. There has been little done in terms of examining women's sexuality and sexual practices, especially those sexualities that are considered subversive, taboo and/or immoral for various social, cultural and ethical reasons. That this study examines lesbian/queer sexual practices and sexual cultures at two events, Dinah Shore and Pussy Palace, using face-to-face interviews and participant observation techniques, I was able to uncover the various ways in which space, agency and desire foster and facilitate a range of sexual behaviors not typically associated with women's sexuality and expectations society has regarding appropriate standards of femininity. Findings indicate that not only is sexuality highly malleable, but that women's sexuality and sexual desires are much more complicated and diverse than previously imagined