Real-time optical and electronic sensing with a β-amino enone linked, triazine-containing 2D covalent organic framework
Contributors: Kulkarni, Ranjit, Noda, Yu, Barange, Deepak K., Kochergin, Yaroslav S., Balcarova, Barbora, Lyu, Pengbo, Nachtigal, Petr, Bojdys, Michael J.
... [This repository contains the raw and source data for the manuscript "Real-time optical and electronic sensing with a β-amino enone linked, triazine-containing 2D covalent organic framework".] Fully-aromatic, two-dimensional covalent organic frameworks (2D COFs) are hailed as candidates for electronic and optical devices, yet to-date few applications emerged that make genuine use of their rational, predictive design principles and permanent pore structure. Here, we present a 2D COF made up of chemoresistant β-amino enone bridges and Lewis-basic triazine moieties that exhibits a dramatic real-time response in the visible spectrum and an increase in bulk conductivity by two orders of magnitude to a chemical trigger - corrosive HCl vapours. The optical and electronic response is fully reversible using a chemical switch (NH3 vapours) or physical triggers (temperature or vacuum). These findings demonstrate a useful application of fully-aromatic 2D COFs as real-time responsive chemosensors and switches.
Contributors: Bhandia, Rishabh, van der Meer, Arjen, Palensky, Peter, Widl, Edmund, Strasser, Thomas I., Akroud, Nabil, Heussen, Kai, Jensen, Tue Vissing, Nguyen, Van Hoa
... Work done in the ERIGrid project focuses on development of advanced simulation-based methods to test and validate smart grid scenarios. Smart Grid systems constitute of models interconnected across different domains. The unavailability of a single simulation platform to test these systems is overcome by co-simulation based assessment methods. Co-simulation requires development of necessary interfaces and couplings to integrate various domain specific specialized simulators, which are then coordinated by a master to orchestrate the simulation of the entire system. The webinar discusses the development and application of various models, tools and test systems developed to conduct co-simulation. The added complexity of simulator interactions with increase in system size is one of the main focus areas of the work done in the project. This webinar will give a live demonstration to showcase the workings of co-simulation models developed in ERIGrid. This webinar focused on the following topics: • Development of Co-simulation approach • Development of necessary interfaces, couplings, test systems etc. • Implementations in the ERIGrid project Additional information can be found at: • Project website • Project deliverables • Project publications • Project training material • Project open access tools Supported by: • IEEE IES Technical Committee on Smart Grids (TC-SG) • IEEE SMCs Technical Committee Cybernetics for Intelligent Industrial Systems (TC-IIS)
Contributors: Swoap, Steven, Levin, Charles
... This folder contains three files 1) a demonstration video for deep breathing 2) a demonstration video for alternate nostril breathing 3) a sample data set.
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Contributors: Wiese, Meike, Bannister, Andrew J., Basu, Srinjan, Boucher, Wayne, Wohlfahrt, Kai, Christophorou, Maria A., Nielsen, Michael L., Klenerman, David, Laue, Ernest D., Kouzarides, Tony
... Background: Stem cell differentiation involves major chromatin reorganisation, heterochromatin formation and genomic relocalisation of structural proteins, including heterochromatin protein 1 gamma (HP1γ). As the principal reader of the repressive histone marks H3K9me2/3, HP1 plays a key role in numerous processes including heterochromatin formation and maintenance.Results: We find that HP1γ is citrullinated in mouse embryonic stem cells (mESCs) and this diminishes when cells differentiate, indicating that it is a dynamically regulated post-translational modification during stem cell differentiation. Peptidylarginine deiminase 4, a known regulator of pluripotency, citrullinates HP1γ in vitro. This requires R38 and R39 within the HP1γ chromodomain, and the catalytic activity is enhanced by trimethylated H3K9 (H3K9me3) peptides. Mutation of R38 and R39, designed to mimic citrullination, affects HP1γ binding to H3K9me3-containing peptides. Using live-cell single-particle tracking, we demonstrate that R38 and R39 are important for HP1γ binding to chromatin in vivo. Furthermore, their mutation reduces the residence time of HP1γ on chromatin in differentiating mESCs.Conclusion: Citrullination is a novel post-translational modification of the structural heterochromatin protein HP1γ in mESCs that is dynamically regulated during mESC differentiation. The citrullinated residues lie within the HP1γ chromodomain and are important for H3K9me3 binding in vitro and chromatin association in vivo.
Contributors: McLean, Alex
... Video demonstration of Live Loom, a prototype device for hand-weaving with the support of a programming language.
Data for paper "Using synthetic semiochemicals to train canines to detect bark beetle-infested trees" in Ann For Sci
Contributors: Johansson, Annette, Birgersson, Göran, Schlyter, Fredrik
... ESM_1 Fig. Educational scent platform. (PDF) ESM_2 Fig. Training platform stimuli layout and decline in response to no target scent. (PDF) ESM_3 Table. Evaluation of the dog detection performance as number of indications with decreasing amounts of scent molecules over time. (PDF) ESM_4_V1 Video. Educational scent platform in operation. (AVI) ESM_4_V2 Video. Placement of cotton scent pad and the location of the scent by dog on a pine (a non-host tree of the beetle). (AVI) ESM_4_V3 Video. The search, GPS tracking, and location of natural attacks. (AVI) ESM_4_V4 Video. The search, location of two adjacent natural attacks, and rewarding. (AVI) The dog detection allows timely removal by sanitation logging of first beetle-attacked trees before offspring emergence, preventing local beetle increases. Detection dogs rapidly learned responding to synthetic bark beetle pheromone components, with known chemical titres, allowing search training during winter in laboratory and field. Dogs trained on synthetics detected naturally attacked trees in summer at a distance of >100 m.
Dog training Videos for paper "Using synthetic semiochemicals to train canines to detect bark beetle-infested trees" in Ann For Sci
Contributors: Schlyter, Fredrik, Birgersson, Göran, Johansson, Annette
... ESM_4_V1 Video. Educational scent platform in operation. (AVI) ESM_4_V2 Video. Placement of cotton scent pad and the location of the scent by dog on a pine (a non-host tree of the beetle). (AVI) ESM_4_V3 Video. The search, GPS tracking, and location of natural attacks. (AVI) ESM_4_V4 Video. The search, location of two adjacent natural attacks, and rewarding. (AVI) The dog detection allows timely removal by sanitation logging of first beetle-attacked trees before offspring emergence, preventing local beetle increases. Detection dogs rapidly learned responding to synthetic bark beetle pheromone components, with known chemical titres, allowing search training during winter in laboratory and field. Dogs trained on synthetics detected naturally attacked trees in summer at a distance of >100 m.
Contributors: Samuel Tuhkanen, Jami Pekkanen, Paavo Rinkkala, Callum Mole, Richard M. Wilkie, Otto Lappi
... Supplementary movies for the article Humans use Predictive Gaze Strategies to Target Waypoints During Steering
Contributors: Ahmed, Nafiz Ishtiaque
... Mid term seminar presentation
Collective Change Detection: Adaptivity to Dynamic Swarm Densities and Light Conditions in Robot Swarms
Contributors: Wahby, Mostafa, Petzold, Julian, Eschke, Catriona, Schmickl, Thomas, Hamann, Heiko
... Robot swarms are known to be robust to individual robot failures. However, a reduced swarm size causes a reduced swarm density. A too low swarm density may then decrease swarm performance, that should be compensated by adapting the individual behavior. Similarly, swarm behaviors can also be adapted to changes in the environment, such as dynamic light conditions. We study aggregation of swarm robots controlled by an extended variant of the BEECLUST algorithm. The robots are asked to aggregate at the brightest spot in their environment. Our approach efficiently adapts this swarm aggregation behavior to variability in swarm density and light conditions. First, each robot individually monitors its environment continuously by sampling its local swarm density and perceived light condition. Second, we exploit the collaboration of robots by letting them share features of these measurements with their neighbors by communication. In extensive robot swarm experiments with ten robots we validate our approach with dynamically changing swarm densities and under dynamic light conditions. We find an improved performance compared to robot swarms without communication and without awareness of the swarm density.