Feet movement in desktop 3D interaction

In this paper we present an exploratory work on the use of foot movements to support fundamental 3D interaction tasks. Depth cameras such as the Microsoft Kinect are now able to track users' motion unobtrusively, making it possible to draw on the spatial context of gestures and movements to control 3D UIs. Whereas multitouch and mid-air hand gestures have been explored extensively for this purpose, little work has looked at how the same can be accomplished with the feet. We describe the interaction space of foot movements in a seated position and propose applications for such techniques in three-dimensional navigation, selection, manipulation and system control tasks in a 3D modelling context. We explore these applications in a user study and discuss the advantages and disadvantages of this modality for 3D UIs

pdCSM-GPCR: predicting potent GPCR ligands with graph-based signatures.

Funder: Newton Fund RCUK-CONFAPFunder: Victorian Government’s Operational Infrastructure Support ProgramMOTIVATION: G protein-coupled receptors (GPCRs) can selectively bind to many types of ligands, ranging from light-sensitive compounds, ions, hormones, pheromones and neurotransmitters, modulating cell physiology. Considering their role in many essential cellular processes, they are one of the most targeted protein families, with over a third of all approved drugs modulating GPCR signalling. Despite this, the large diversity of receptors and their multipass transmembrane architectures make the identification and development of novel specific, and safe GPCR ligands a challenge. While computational approaches have the potential to assist GPCR drug development, they have presented limited performance and generalization capabilities. Here, we explored the use of graph-based signatures to develop pdCSM-GPCR, a method capable of rapidly and accurately screening potential GPCR ligands. RESULTS: Bioactivity data (IC50, EC50, Ki and Kd) for individual GPCRs were curated. After curation, we used the data for developing predictive models for 36 major GPCR targets, across 4 classes (A, B, C and F). Our models compose the most comprehensive computational resource for GPCR bioactivity prediction to date. Across stratified 10-fold cross-validation and blind tests, our approach achieved Pearson's correlations of up to 0.89, significantly outperforming previous methods. Interpreting our results, we identified common important features of potent GPCRs ligands, which tend to have bicyclic rings, leading to higher levels of aromaticity. We believe pdCSM-GPCR will be an invaluable tool to assist screening efforts, enriching compound libraries and ranking candidates for further experimental validation. AVAILABILITY AND IMPLEMENTATION: pdCSM-GPCR predictive models and datasets used have been made available via a freely accessible and easy-to-use web server at http://biosig.unimelb.edu.au/pdcsm_gpcr/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics Advances online

Deconvolving the information from an imperfect spherical gravitational wave antenna

We have studied the effects of imperfections in spherical gravitational wave antenna on our ability to properly interpret the data it will produce. The results of a numerical simulation are reported that quantitatively describe the systematic errors resulting from imperfections in various components of the antenna. In addition, the results of measurements on a room-temperature prototype are presented that verify it is possible to accurately deconvolve the data in practice.Comment: 5 pages, 2 figures, to be published in Europhysics Letter

Modeling the Dashboard Provenance

Organizations of all kinds, whether public or private, profit-driven or non-profit, and across various industries and sectors, rely on dashboards for effective data visualization. However, the reliability and efficacy of these dashboards rely on the quality of the visual and data they present. Studies show that less than a quarter of dashboards provide information about their sources, which is just one of the expected metadata when provenance is seriously considered. Provenance is a record that describes people, organizations, entities, and activities that had a role in the production, influence, or delivery of a piece of data or an object. This paper aims to provide a provenance representation model, that entitles standardization, modeling, generation, capture, and visualization, specifically designed for dashboards and its visual and data components. The proposed model will offer a comprehensive set of essential provenance metadata that enables users to evaluate the quality, consistency, and reliability of the information presented on dashboards. This will allow a clear and precise understanding of the context in which a specific dashboard was developed, ultimately leading to better decision-making.Comment: 8 pages, 4 figures, one table, to be published in VIS 2023 (Vis + Prov) x Domai

Insulin Receptor Has Tyrosine Kinase Activity Toward Shc In Rat Liver.

Insulin induces tyrosine phosphorylation of Shc in cell cultures and in insulin-sensitive tissues of the intact rat. However, the ability of insulin receptor (IR) tyrosine kinase to phosphorylate Shc has not been previously demonstrated. In the present study, we investigated insulin-induced IR tyrosine kinase activity towards Shc. Insulin receptor was immunoprecipitated from liver extracts, before and after a very low dose of insulin into the portal vein, and incubated with immunopurified Shc from liver of untreated rats. The kinase assay was performed in vitro in the presence of exogenous ATP and the phosphorylation level was quantified by immunoblotting with antiphosphotyrosine antibody. The results demonstrate that Shc interacted with insulin receptor after infusion of insulin, and, more important, there was insulin receptor kinase activity towards immunopurified Shc. The description of this pathway in animal tissue may have an important role in insulin receptor tyrosine kinase activity toward mitogenic transduction pathways.311415-