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20 results for “Information theory”
A Reputation Game Simulation: Emergent Social Phenomena from Information Theory
<p>Here, the data underlying the article "A Reputation Game Simulation: Emergent Social Phenomena from Information Theory" (<a href="https://doi.org/10.1002/andp.202100277">https://doi.org/10.1002/andp.202100277</a>) is provided.<br> <br> The data is structured according to the figures it has been used for. There are</p> <ul> <li>example simulations with basic communication strategies in the folder "single_simulations_3_agents" (Figures 4,5,8,D1)</li> <li>statistical simulations with 3 agents and special communication strategies in the folder "statistical_simulations_3_agents" (Figures 9-13, the upper panel of figure 15, figures 16-18, D2 and the left panels of figure D3)</li> <li>statistical simulations with 4 agents and special communication strategies in the folder "statistical_simulations_4_agents" (Figure 14, the middle panel of figure 15, the middle panels of figure D3 and the upper panels of figures D4, D5)</li> <li>statistical simulations with 5 agents and special communication strategies in the folder "statistical_simulations_5_agents" (The lower panel of figure 15, the right panels of figure D3 and the lower panels of figures D4,D5)</li> <li>propaganda simulations in the folder "propaganda_simulations" (Figure 7)</li> </ul> <p><br> Each simulation is represented by a .json file in which all events that happened during the simulation are collected. Generally, there are three types of events: communications, self-updates (information that the speaker gained about itself is processed) and updates (information that the receiver gained about the speaker and the topic is processed). Additionally, the first line specifies the parameters of each simulation, and the last few lines summarize the final status of the simulation. In the following all important abbreviations are explained:</p> <ul> <li>parameters <ul> <li>decpeting: whether or not agents in generally make dishonest statements</li> <li>listening: whether or not agents in listen to their communication partners</li> <li>disturbing: whether or not agents are particularly risk-taking when making dishonest statements</li> <li>x_est: intrinsic honesties of the agents</li> <li>RSeed: the used random seed</li> <li>NA: number of agents</li> <li>NR: number of rounds</li> </ul> </li> <li>communication <ul> <li>a: speaker</li> <li>b: receiver</li> <li>c: topic</li> <li>J: transmitted message in the form of</li> </ul> </li> <li>self_update <ul> <li>id: number of agent who is updating knowledge about itself</li> <li>Nl, Nt: number of dishonest/honest statements the agent has observed from itself so far</li> <li>I_<id>: knowledge that the agents has about itself after the update in the form of</li> </ul> </li> <li>update <ul> <li>id: number of agent who is updating its knowledge</li> <li>I_<id1>: knowledge that the updating agent has about agent <id1> in the form of</li> <li>Jothers_<id1>_<id2>: last statement that the updating agent heared agent <id1> make about agent <id2></li> <li>Iothers_<id1>_<id2>: what the updating agent believes that agent <id1> thinks about agent <id2> after the update</li> <li>Cothers_<id1>_<id2>: what the updating agent believes after the update that agent <id1> wants it to think about agent <id2></li> <li>new_friends/enemies: id of the agent, the updating agent after the update considers a friend/enemy</li> <li>new_K: normalized surprise the updating agent experienced in the last communication (used to calculate kappa)</li> <li>kappa: median of the last ten normalized surprises the updating agent experienced</li> </ul> </li> <li>final_status <ul> <li>id/name: number if the described agent</li> <li>x: the agent's honesty</li> <li>I: the agent's knowledge about all others</li> <li>Nc/Nt/Nl: total number of conversations/honest statements/dishonest statements the agent has made</li> <li>K: the last 10 normalized surprises the agent experienced</li> <li>kappa: the median of K</li> <li>friends/enemies: list of the agent's friends/enemies</li> <li>Jothers/Iothers/Cothers: same as above, now as full array, i.e. the combined information about all others</li> <li>openess/mind/decepting/strategic/egocentric/deceptive/flattering/aggressive/shameless/disturbing: the agent's character traits</li> </ul> </li> </ul>
An information theory-based machine learning approach to detecting functionally conserved and coordinated protein dynamics
<p>The application of machine learning classification to the molecular dynamics of the functional states of protein allows for application of an information theoretic framework familiar to traditional bioinformatics. The functional states of proteins involving binding interactions with partners comprised of protein, DNA or small molecules can first be defined in a binary fashion (i.e. bound vs unbound), subsequently simulated in molecular dynamics software, and then employed as a comparative training set for a binary machine learning classifier capable of discerning the complex dynamical consequences of binding interaction. This learner can subsequently be deployed on new simulations of the functionally bound state to validate its ability to recognize the molecular motions that are supporting binding function. Regions of proteins with functionally conserved dynamics will induce significant local correlations in learning performance across independent validation runs. Through case studies of Rbp subunit 4/7 interaction in RNA Pol II and DNA-protein interactions of TATA binding protein, we demonstrate this method of detecting functionally conserved protein dynamics. We also demonstrate how Shannon information, relative entropy and mutual information can be applied to these binary classification states of dynamic simulations in order to compare dynamics and identify concerted motions involved in dynamic interactions across sites.</p>
Replication package for Shishkin ® Ortoleva "Ambiguous Information and Dilation: An Experiment" (Journal of Economic Theory)
<p>Replication package for Shishkin ® Ortoleva "Ambiguous Information and Dilation: An Experiment" (Journal of Economic Theory).</p> <p>It contains raw experimental data and code producing tables and figures from the paper.</p>
An information theory framework for movement path segmentation and analysis
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data for article "Theory informed, experiment based, constraint on the rate of autoxidation chemistry – An analytical approach"
<p>The files contain the data from simulations shown in plots for main manuscript figures and SI figures. Further, a preliminary autoCONSTRAINT verion to reproduce the results shown is attached and the PyCHAM model used to create CIMS-like inputs to autoCONSTRAINT referenced (model inputs are attached). For any questions on the data contact: office@pi-numerics.com</p> <p>Detailed information on the file content is provided in file "SI_data_description"</p>
Raw Data to 'Experimental verification of the area law of mutual information in quantum field theory', arXiv:2206.10563
<p><strong>Absorption images representing the raw data for arXiv:2206.10563</strong></p> <p>'scan5722.zip' contains the raw data for figures 2 and 3.</p> <p>'scan5831.zip' and 'scan9617.zip' contain the raw data for figure 5, right and left, respectively.</p> <p>All three datasets, 9617, 5722, and 5831, are used to obtain the data points in figure 4, from low to high temperatures.</p> <p> </p> <p><strong>Scans 5722 & 5831</strong></p> <p>The absorption images are numbered consecutively.</p> <p>The first image for scans 5722 and 5831 is taken along the axial (longitudinal) direction with our 'longitudinal' imaging system after 10 ms time of flight (TOF) to measure the atom number balance between the two wells. The measurement is performed before ramping up the DW barrier. Two images are taken in each cycle: One shot with atoms ('1-atomcloud.tif') and a second image to record the intensity of the imaging beam without atoms ('1-withoutatoms.tif'). These two pictures are used to extract the atomic density (see the Matlab script).</p> <p>The second image for scans 5722 and 5831 is taken in the direction of the double-well (DW) separation with our 'transverse' imaging system. The measurement is performed before ramping up the DW barrier. The image is taken after 11.2 ms TOF.</p> <p>The subsequent images record the interference fringes for the different evolution times (again, always pairs '-atomcloud.tif' and '-withoutatoms.tif'). They are taken with our 'vertical' imaging system after 15.6 ms TOF. The imaging direction is perpendicular to the weakly confined direction of the clouds and the DW separation.</p> <p>The recorded evolution times for scan 5722 are -1.9 ms (right before ramping up the DW barrier), 0 ms (right after the DW barrier is ramped up), and then in steps of 2.5 ms until 65 ms. This means that '3-atomcloud.tif' corresponds to -1.9 ms, and '30-atomcloud.tif' corresponds to 65 ms. This completes the 'first repeat'. The next two shots, '31-atomcloud.tif' and '32-atomcloud.tif', belong to the 'second repeat' and are again taken with the 'longitudinal' & 'transverse' imaging systems, respectively. The picture '33-atomcloud.tif' is again taken with the 'vertical' imaging and corresponds to -1.9 ms. And so forth.</p> <p>In the same way, the pictures scan 5831 are ordered. The evolution times (in ms) for these two scans are:</p> <p>scan 5722: -1.9 from 0 to 65 (in steps of 2.5)</p> <p>scan 5831: -1.8, from 0 to 65 (in steps of 2.5)</p> <p>The first time always corresponds to the instant right before the DW barrier is ramped up. 0 is always right after the barrier was ramped up.</p> <p> </p> <p><strong>Scan 9617</strong></p> <p>This scan only contains images with the 'vertical' imaging system with 15.6 ms TOF. The evolution times (in ms) are as follows:</p> <p>scan 9617: -2.8, from 0 to 15 (in steps of 1.5), 22, 25, 28</p> <p>The first time always corresponds to the instant right before the DW barrier is ramped up. 0 is always right after the barrier was ramped up.</p> <p>This means, that '1-atomcloud.tif', '16-atomcloud.tif', '31-atomcloud.tif' and so on correspond to -2.8 ms, and '15-atomcloud.tif', '30-atomcloud.tif', '45-atomcloud.tif' and so on correspond to 28 ms.</p> <p> </p> <p><strong>Matlab script</strong></p> <p>In addition to the data, a Matlab script (calc_atomic_density.m) illustrates how to extract the two-dimensional atomic density from the absorption images. It contains all relevant parameters of the imaging systems.</p>
Complexity or complexities? A simulation study on lexical complexity in expert and learner texts through the lens of information theory
<p>Measures dataset for the work presented at LCR 2024 (the Learner Corpus Research Conference), held in Tartu on 26th-28th September 2024.</p>
Replication package for: "Information Aggregation Under Ambiguity: Theory and Experimental Evidence"
<p>The package contains the data and code to replicate all figures and tables in Galanis, Ioannou, and Kotronis (forthcoming), "Information Aggregation Under Ambiguity: Theory and Experimental Evidence", Review of Economic Studies.</p>
Use of Construal Level Theory to Inform Messaging to Increase Vaccination Against COVID-19
ClinicalTrials.gov study NCT04871776. IPD Sharing: NO. Countries: 1. Publications: 1.
Data and code for the manuscript "Internal vs Forced Variability Metrics for General Circulation Models Using Information Theory"
<p>Data and code for the manuscript "Internal vs Forced Variability Metrics for General Circulation Models Using Information Theory" published in the Journal of Geophysical Research Oceans. <br>URL of the manuscript: https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JC020101<br>DOI of the manuscript: https://doi.org/10.1029/2023JC020101</p>
Raw neural codes and binsizes for the paper 'Robust and consistent measures of pattern separation based on information theory and demonstrated in the dentate gyrus'
<p>Raw optimal spiking codes and binsizes that maximise information theoretic quantities for the figures of the paper 'Robust and consistent measures of pattern separation based on information theory and demonstrated in the dentate gyrus' (PLoS Comput Biol. 2024 Feb 20;20(2):e1010706) . Additional data will be added in the coming months.</p>
Efficacy of a Health Empowerment Theory Based Health Information Literacy Promotion Intervention in Individuals With Metabolic Syndrome
ClinicalTrials.gov study NCT07096102. IPD Sharing: NO. Countries: 1. Publications: 5.
Self-Determination Theory-informed Occupational Therapy Program to Increase Physical Activity Among Survivors of Breast Cancer
ClinicalTrials.gov study NCT06671730. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Project files provided as supporting information to the manuscript "An information theory-based approach for optimal model reduction of biomolecules"
<p>The dataset contains the following files:</p> <ul> <li>- adenylate.zip</li> <li>- antitrypsin.zip</li> <li>- tamapin.zip</li> <li>- analysis_notebooks.zip</li> </ul> <p>Each of these refers to one of three proteins. For each CG sites number N, each compressed folder contains the following files:</p> <ul> <li>random mappings (random_mappings_${N}.txt) </li> <li>random mapping entropies (random_smaps_${N}.txt) [fig1]</li> <li>optimal mappings (lowest_mappings_${N}.txt) [fig3, fig4, figS2]</li> <li>optimal mapping entropies (lowest_smaps_${N}.txt) [fig1]</li> <li>pdb files with conservations probabilities in the beta factor column (${N}_probs.pdb) [fig4, figs2]</li> <li>SASA values (${protein_name}_SASA_residues.xvg </li> <li>transition mapping entropies (${protein_name}_transition_smaps.txt) [fig2]</li> <li>additional transition mapping entropies (${protein_name}_transition_smaps*) [figs3]</li> </ul> <p>The file analysis_notebooks.zip contains the python3 notebooks employed to perform all the analysis present in the paper:</p> <ul> <li>paper_analysis_adenylate.ipynb</li> <li>paper_analysis_antitrypsin.ipynb</li> <li>paper_analysis_tamapin.ipynb</li> </ul> <p>Packages required for the usage of these python 3 scripts:</p> <p>- numpy<br> - pandas<br> - matplotlib<br> - seaborn<br> </p>
Data from: When to monitor and when to act: value of information theory for multiple management units and limited budgets
1.The question of when to monitor and when to act is fundamental to applied ecology, and notoriously difficult to answer. Value of information (VOI) theory holds great promise to help answer this question for many management problems. However, VOI theory in applied ecology has only been demonstrated in single-decision problems, and has lacked explicit links between monitoring and management costs. 2.Here, we present an extension of VOI theory for solving multi-unit decisions of whether to monitor before managing, while explicitly accounting for monitoring costs. Our formulation helps to choose the optimal monitoring/management strategy among groups of management units (e.g. species, habitat patches), and can be used to examine the benefits of partial and repeat monitoring. 3.To demonstrate our approach, we use case simulated studies of single-species protection that must choose among potential habitat areas, and classification and management of multiple species threatened with extinction. We provide spreadsheets and code to illustrate the calculations and facilitate application. Our case studies demonstrate the utility of predicting the number of units with a given outcome for problems with probabilities of discrete states, and the efficiency of having a flexible approach to manage according to monitoring outcomes. 4.Synthesis and applications. The decision to act or gather more information can have serious consequences for management. No decision, including the decision to monitor, is risk-free. Our multi-unit expansion of Value of Information (VOI) theory can reduce the risk in monitoring/acting decisions for many applied ecology problems. While our approach cannot account for the potential value of discovering previously unknown threats or ecological processes via monitoring programs, it can provide quantitative guidance on whether to monitor before acting, and which monitoring/management actions are most likely to meet management objectives.
Information theory-based direct causality measure to assess cardiac fibrillation dynamics
<p>This repository contains the optical imaging data used in the article "Information theory-based direct causality measure to assess cardiac fibrillation dynamics"</p>
Data from: When to monitor and when to act: value of information theory for multiple management units and limited budgets
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Dataset_submission_Prospecting_behaviours_of_immature_eagles_support_the_theory_of_informed_dispersal
<p>This dataset is the one used to produce all the figures and models presented in the submitted paper entitled : <span>Prospecting behaviours of immature eagles support the theory of informed dispersal </span></p>
The Study of the Quasi-periodicity Observed on Plasma Density and Magnetic Field on Saturn's Magnetosphere: An Information Theory Approach
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Information_theory
<p>Information Theory, Code Msg</p>
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