Software Development for Genome Sequence Analysis

The cost of genome sequencing has decreased rapidly, expanding availability for many biological applications (Muir 2016). For example, researchers can now obtain genome sequences from multiple populations under different types of selection. Comparison of these sequences allows for identification of chromosome regions and specific genes associated with adaptive evolution (Kelly 2013). As an increasing number of researchers engage in this type of inquiry, many have created in-house computer scripts to analyze the raw sequence data (e.g., Kelly 2013), creating a gap in both continuity and standardization. Using a test dataset and preliminary results from an ongoing artificial selection experiment in Mimulus guttatus (Yellow Monkeyflower), I translated, verified, and expanded five software programs representing stages of a single analysis into one software package written in the C# programming language. This program is helping researchers to streamline their analysis and increase precision, while remaining dynamic enough that it can be expanded to any like-set of data, regardless of species

Programmable Pulse-Position-Modulation Encoder

A programmable pulse-position-modulation (PPM) encoder has been designed for use in testing an optical communication link. The encoder includes a programmable state machine and an electronic code book that can be updated to accommodate different PPM coding schemes. The encoder includes a field-programmable gate array (FPGA) that is programmed to step through the stored state machine and code book and that drives a custom high-speed serializer circuit board that is capable of generating subnanosecond pulses. The stored state machine and code book can be updated by means of a simple text interface through the serial port of a personal computer

Social Fringe Dwellers: Can chat-bots combat bullies to improve participation for children with autism?

Autism Spectrum Disorder (ASD) can cause a gulf in communication that casts children with autism to the fringes of social and family life, despite the best efforts of their carers. These children often struggle with social interaction, lack of interest and empathy, and require intensive therapy to improve their ability to communicate with others. Improvements in social interaction are often hampered by experiences in which children with autism are more susceptible to being bullied. Social and communication technologies (e.g. smartphones and tablets), which children with autism tend to gravitate toward, and to which many families have access, may play a significant future role in building resilience and improving social interaction. Based on technology reviews and stakeholder interviews, we are developing modules for a machine learning artificial intelligence platform (a chat-bot) that assists children attending an Australian mainstream school to recognise and respond to social bullying and sarcasm, allowing bullied autistic children to develop the social prowess to withstand their aggressors. &nbsp

Forty years of graduate study in history at Carleton University

In November 1996, Carleton University celebrated forty years of graduate study in History. For a university only fifty-four years old, the event demonstrated the central place History has occupied in Carleton’s curriculum in the arts and social sciences. As a university in the national capital, the home of rich library and archival resources, Carleton’s interest in promoting Canadian studies is appropriate

DNA Methylation and Genetic Divergence Associated with an Inducible Defensive Response in Mimulus guttatus

Phenotypic plasticity allows many organisms to respond to their environment by changing their phenotype, but the mechanisms to do so are not well understood. Yellow Monkeyflower (formerly Mimulus guttatus; now Erythranthe guttata) is one such organism that can serve as a model to promote our understanding of these mechanisms due to its striking response to insect herbivory. Monkeyflower responds to leaf damage by increasing the number of hair-like glandular trichomes, a putative defensive trait that reduces the magnitude of damage by insects. This plastic response is transgenerationally inherited in a way that is sensitive to genome-wide demethylation when transmitted through the maternal but not the paternal germline. Investigation of this phenomenon has been hampered by a lack of computational tools to analyze pooled methylome and genome sequence data. In this study, two distinct software pipelines were developed and tested on data from Monkeyflower. The first pipeline detects regions that are differentially methylated and identifies adjacent candidate genes, using Nanopore data. This was tested on data from a Monkeyflower recombinant inbred line (RIL) subject to either parental damage or control conditions. The second pipeline uses pooled DNA sequence data to identify genomic regions that exhibit statistically significant divergence in allele frequencies. This was tested on genome sequence data from an experiment involving artificial selection for increased trichome production. Results indicate that epigenetic inheritance of the damage response in a particular RIL is associated with 59 differentially methylated regions. Relevant functions, including anatomical structure development and response to abscisic acid, are significantly overrepresented in the set of genes that lie closest to these DMRs. Artificial selection for high trichome production produced one highly divergent region adjacent to a gene associated with seed coat mucilage development. These findings identify candidate epigenetic and genetic factors associated with glandular trichome development while providing an effective test case for the development of two new software pipelines

Investigation of strategic capacity issues in the aerospace sector

The business environment is changing fast and radically. Traditional capacity planning has limitations in today’s dynamic environments, particularly from a strategic perspective in the aerospace sector. This document sets out to identify the unique characteristics of the aerospace industry and compare the traditional views of capacity planning and modern concepts in SCP relevant to the sector. Key findings are summarised from an analysis of the literature on strategic capacity planning. The importance of considering demand uncertainty, technology uncertainty and supply uncertainty is highlighted. Two case studies in the aero- engine sector are presented. A collaborative virtual organisation requires Strategic Capacity Planning (SCP) that focuses not only on economies of scale but also on coordination, flexibility and responsiveness. An integrated framework for addressing SCP in the aerospace industry is presented

Uncertainty in marine weather routing

Weather routing methods are essential for planning routes for commercial shipping and recreational craft. This paper provides a methodology for quantifying the significance of numerical error and performance model uncertainty on the predictions returned from a weather routing algorithm. The numerical error of the routing algorithm is estimated by solving the optimum path over different discretizations of the environment. The uncertainty associated with the performance model is linearly varied in order to quantify its significance. The methodology is applied to a sailing craft routing problem: the prediction of the voyaging time for an ethnographic voyaging canoe across long distance voyages in Polynesia. We find that the average numerical error is $0.396\%$, corresponding to $1.05$ hours for an average voyage length of $266.40$ hours. An uncertainty level of $2.5 \%$ in the performance model is seen to correspond to a standard deviation of $\pm 2.41-3.08\%$ of the voyaging time. These results illustrate the significance of considering the influence of numerical error and performance uncertainty when performing a weather routing study