Exploring Networks of Lexical Variation in Russian Sign Language

When describing variation at the lexical level in sign languages, researchers often distinguish between phonological and lexical variants, using the following principle: if two signs differ in only one of the major phonological components (handshape, orientation, movement, location), then they are considered phonological variants, otherwise they are considered separate lexemes. We demonstrate that this principle leads to contradictions in some simple and more complex cases of variation. We argue that it is useful to visualize the relations between variants as graphs, and we describe possible networks of variants that can arise using this visualization tool. We further demonstrate that these scenarios in fact arise in the case of variation in color terms and kinship terms in Russian Sign Language (RSL), using a newly created database of lexical variation in RSL. We show that it is possible to develop a set of formal rules that can help distinguish phonological and lexical variation also in the problematic scenarios. However, we argue that it might be a mistake to dismiss the actual patterns of variant relations in order to arrive at the binary lexical vs. phonological variant opposition.

Knowledge Visualization for Research Design

This chapter presents a case of information and communication technology use in doctoral research processes. In particular, it presents the use of the Idea Puzzle software as a knowledge visualization tool for research design at the University of Auckland. The chapter begins with a review of previous contributions on knowledge visualization and research design. It then presents the Idea Puzzle software and its application at the University of Auckland. In addition, the chapter discusses the results of a large-scale survey conducted on the Idea Puzzle software in 71 higher education institutions as well as its first usability testing at the University of Auckland. The chapter concludes that the Idea Puzzle software stimulates visual integrative thinking for coherent research design in the light of Philosophy of Science.

Durable Civic Technology

Minecraft is a video game that allows players to interact with a 3D environment. Launched in 2009, Minecraft has surprisingly durable popularity. Users report that Minecraft is easy to learn and understand, engaging and immersive, and adaptable. Outside North America it has been piloted for urban planning public consultation processes. Five years ago, authors conducted research using key informant interviews. This study asked practicing urban planners in Canada to assess Minecraft's potential. Key findings address Minecraft's usefulness as a visualization tool, its role in building public trust in local planning processes, the place of play in planning, and the challenges associated with its use in public consultation. This chapter explores Minecraft's ongoing use, offers reflections as to how this game could effectively be used for public consultation, and concludes with key lessons for urban planners whose practice intersects with our digitally-enabled world, with a particular focus on new application possibilities in smart city planning projects.

RASE: Modeling cumulative disadvantage due to marginalized group status in academia

We propose a framework of Resources, Achievement, Status, and Events (RASE) that allows the many disparate but well-documented phenomena affecting underrepresented groups in STEM to be assembled into a story of career trajectories, illuminating the possible cumulative impact of many small inequities. Our framework contains a three-component deterministic cycle of (1) production of Achievements from Resources, (2) updated community Status due to Achievements, and (3) accrual of additional Resources based on community Status. A fourth component, stochastic Events, can influence an individual’s level of Resources or Achievements at each time step of the cycle. We build a specific mathematical model within the RASE framework and use it to investigate the impact of accumulated disadvantages from multiple compounding variables. We demonstrate that the model can reproduce data of observed disparities in academia. Finally, we use a publicly available visualization and networking tool to provide a sandbox for exploring career outcomes within the model. The modeling exercise, results, and visualization tool may be useful in the context of training STEM faculty to recognize and reduce effects of bias.

An Improved Timed Elastic Band (TEB) Algorithm of Autonomous Ground Vehicle (AGV) in Complex Environment

In recent decades, the Timed Elastic Band (TEB) algorithm is widely used for the AGV local path panning because of its convenient and efficiency. However, it may make a local detour when encountering a curve turn and cause excessive energy consumption. To solve this problem, this paper proposed an improved TEB algorithm to make the AGV walk along the wall when turning, which shortens the planning time and saves energy. Experiments were implemented in the Rviz visualization tool platform of the robot operating system (ROS). Simulated experiment results reflect that an amount of 5% reduction in the planning time has been achieved and the velocity curve implies that the operation was relatively smooth. Practical experiment results demonstrate the effectiveness and feasibility of the proposed method that the robots can avoid obstacles smoothly in the unknown static and dynamic obstacle environment.

Nitrogen metabolism in Pseudomonas putida: functional analysis using random barcode transposon sequencing

Pseudomonas putida KT2440 has long been studied for its diverse and robust metabolisms, yet many genes and proteins imparting these growth capacities remain uncharacterized. Using pooled mutant fitness assays, we identified genes and proteins involved in the assimilation of 52 different nitrogen containing compounds. To assay amino acid biosynthesis, 19 amino acid drop-out conditions were also tested. From these 71 conditions, significant fitness phenotypes were elicited in 672 different genes including 100 transcriptional regulators and 112 transport-related proteins. We divide these conditions into 6 classes, and propose assimilatory pathways for the compounds based on this wealth of genetic data. To complement these data, we characterize the substrate range of three promiscuous aminotransferases relevant to metabolic engineering efforts in vitro. Furthermore, we examine the specificity of five transcriptional regulators, explaining some fitness data results and exploring their potential to be developed into useful synthetic biology tools. In addition, we use manifold learning to create an interactive visualization tool for interpreting our BarSeq data, which will improve the accessibility and utility of this work to other researchers.

ChemInformatics Model Explorer (CIME): Exploratory analysis of chemical model explanations

The introduction of machine learning to small molecule research – an inherently multidisciplinary field in which chemists and data scientists combine their expertise and collaborate – has been vital to making screening processes more efficient. In recent years, numerous models that predict pharmacokinetic properties or bioactivity have been published, and these are used on a daily basis by chemists to make decisions and prioritize ideas. The emerging field of explainable artificial intelligence is opening up new possibilities for understanding the reasoning that underlies a model. In small molecule research, this means relating contributions of substructures of compounds to their predicted properties, which in turn also allows the areas of the compounds that have the greatest influence on the outcome to be identified. However, there is no interactive visualization tool that facilitates such interdisciplinary collaborations towards interpretability of machine learning models for small molecules. To fill this gap, we present CIME (ChemInformatics Model Explorer), an interactive web-based system that allows users to inspect chemical data sets, visualize model explanations, compare interpretability techniques, and explore subgroups of compounds. The tool is model-agnostic and can be run on a server or a workstation.