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146 results for “agent based”
2,5-Furandicarboxaldehyde as a Bio-based Crosslinking Agent Replacing Glutaraldehyde for Covalent Enzyme Immobilization
<p>In the quest for a bio-based and safer substitute for glutaraldehyde, we have investigated 2,5 diformylfuran (DFF) as bifunctional crosslinking agent for the covalent immobilization of glucoamylase on amino-functionalized methacrylic resins. Immobilization experiments and systematic comparison with glutaraldehyde at four different concentrations for the activation step showed that DFF leads to comparable enzymatic activities at all tested concentrations. Continuous flow experiment confirms a similar long term stability of the immobilized formulations obtained with the two crosslinkers. The NMR study of DFF in aqueous solution evidenced a much simpler behaviour as compared to glutaraldehyde, since no enolic forms can form and only a mono-hydrated form was observed. Unlike in the case of glutaraldehyde, DFF reacts covalently with the primary amino groups <em>via</em> imine bond formation only. Nevertheless, the stability of the covalent immobilization was confirmed also at acidic pH (4.5), most probably because of the higher stability of the imine bonds formed with the aromatic aldehydes. In terms of toxicity DFF has the advantage of being poorly soluble in water and, more importantly, poorly volatile as compared to glutaraldehyde, which displays severe respiratory toxicity. We have performed preliminary ecotoxicity assays using <em>Aliivibrio fischeri</em>, a marine bacterium, evidencing comparable behaviour (below the toxicity threshold) for both dialdehydes at the tested concentrations.</p>
Alternative Covid-19 mitigation measures in school classrooms: Analysis using an agent-based model of SARS-CoV-2 transmission
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Agent-based Testing of Extended Reality Systems
<p>Testing for quality assurance (QA) is a crucial step in the development of Extended Reality (XR) systems that typically follow iterative design and development cycles. Bringing automation to these testing procedures will increase the productivity of XR developers. However, given the complexity of the XR environments and the User Experience (UX) demands, achieving this is highly challenging. We propose to address this issue through the creation of autonomous cognitive test agents that will have the ability to cope with the complexity of the interaction space by intelligently explore the most prominent interactions given a test goal and support the assessment of affective properties of the UX by playing the role of users.</p>
New leads for fragment based design of Re/Tc radiopharmaceutical agents: Raw Diffraction Images
<p>Multiple coordination possibilities of <em>fac</em>-[Re(CO)<sub>3</sub>]<sup>+</sup> to a protein, were found bound to the Asp, Glu, Arg and His amino acid residues as well as to the C-terminal carboxylate in the vicinity of Leu and Pro and are described in the publication titled " <em>New leads for fragment based design of Re/Tc radiopharmaceutical agents</em>" written by Brink & Helliwell, <em>IUCrJ</em>, 2017</p> <p>The raw diffraction images for the DLS and Cu Kalpha data sets are made available at the Zenodo research data archive, as specified in the publication.</p>
Agent-based model predicts that layered structure and 3D movement work synergistically to reduce bacterial load in 3D in vitro models of tuberculosis granuloma - Location Data
<p>This dataset is meant to be used with "Agent-based model predicts that layered structure and 3D movement work synergistically to reduce bacterial load in 3D in vitro models of tuberculosis granuloma - Results and Data". It provides spatial output data for 4 different setups (spheroid, traditional, 3d gravity, and traditional floating) of an agent-based model of <i>in vitro </i>tuberculosis infection models. </p>
Simulated results from an agent-based model examining inequality and innovation in social networks
<p>Theories of innovation often balance contrasting views that either smart people create smart things or smartly constructed institutions create smart things. While population models have shown factors including population size, connectivity, and agent behavior as crucial for innovation, few have taken the individual-central approach seriously by examining the role individuals play within their groups. To explore how network structures influence not only population-level innovation but also performance among individuals, we studied an agent-based model of the Potions Task, a paradigm developed to test how structure affects a group's ability to solve a difficult exploration task. We explore how size, connectivity, and rates of information sharing in a network influence innovation and how these have an impact on the emergence of inequality in terms of agent contributions. We find, in line with prior work, population size has a positive effect on innovation, but that large and small populations perform similarly per capita; that many small groups outperform fewer large groups; that random changes to structure have few effects on innovation; and that the highest performing agents tend to occupy more central network positions. Moreover, we show that every network factor which facilitates innovation leads to a proportional increase in inequality of performance, creating "genius effects" among otherwise "dumb" agents in both idealized and real-world networks.</p>
Supplemental Movie Files for "Agent-Based Modeling of a Nuclear Chromosome Ensemble Identifies Determinants of Homolog Pairing During Meiosis" by Chriss et al.
<p>This set of Supplemental Information contains two movies made from the simulations from the model developed in the manuscript "<strong>Agent-Based Modeling of a Nuclear Chromosome Ensemble Identifies Determinants of Homolog Pairing During Meiosis</strong>" by A. Chriss, G. V. Börner, and S. D. Ryan. </p> <p> </p> <p>Supplemental Movie S1: <strong>WT Chromosome Trajectories during Prophase I. </strong>The first file "movie_WT..." contains the file for the results of simulations for the wild-type chromosomes and the exact parameter values can be found in Table 1 of the manuscript. The movie shows one realization of the agent-based model. The simulation movie covers the homology search process from <em>t = 3h </em>to <em>t = 9h</em>. Matching colors correspond to homologous pairs. True chromosome lengths are incorporated and scale the relevant interaction radii. The radius represents the attractive and non-homologous repulsive region.</p> <p> </p> <p>Supplemental Movie S2: <strong>WT Chromosome Trajectories during Prophase I with active dumbbell model. </strong> The second file "movie<em>WT</em>_activedumbbell..." contains the file for the results of the simulations for the modeling of chromosomes as active dumbbells (from polymers) to allow for the study of the effects of elongation, orientation, and flexibility. The movie shows one realization of the agent-based active dumbbell model which is closer to modeling a chromosome as a polymer. The simulation movie covers the homology search process from <em>t = 3h </em>to <em>t = 9h</em>. Matching colors correspond to homologous pairs. True chromosome lengths are incorporated and scale the relevant interaction radii, but are allowed to change in time as the two beads expand and contract. The radius represents the attractive and non-homologous repulsive region.</p> <p> </p> <p>Supplemental Movie S3: <strong><em>spo11</em> hypomorph (30% WT DSB levels) Chromosome Trajectories during Prophase I (parameters from Fig 7B)</strong>. The third file "movie_spo11..." contains the file for the results of the simulations for the spo-11 hypomorph and the associated parameter values can be found in Table 1 of the manuscript. The movie depicts one realization of the agent-based model for the {\it spo11} hypomorphic mutant. The simulation movie covers the homology search process from <em>t = 3h</em> to <em>t = 9h</em> where mutant <em>spo11</em> is associated with a weaker attractive and repulsive force (e.g., reduction to 77% of WT values). True chromosome lengths are incorporated and scale the relevant interaction radii. Matching colors correspond to homologous pairs. The radii represent the homologous attractive and the non-homologous repulsive region. Note that the reduction in interaction strength delays homologous pairing consistent with experimental observations in [13]. </p> <p> </p> <p> </p> <p>The codes that generated these movies were written in Matlab and freely available via GitHub: <a href="https://github.com/sdryan/ChromosomeDynamicsProphase1">https://github.com/sdryan/ChromosomeDynamicsProphase1</a></p> <p> </p> <p>For questions please contact the corresponding authors: G. Valentin Börner <a href="mailto:g.boerner@csuohio.edu">g.boerner@csuohio.edu</a> (Biology) or Shawn D. Ryan <a href="mailto:s.d.ryan@csuohio.edu">s.d.ryan@csuohio.edu</a> (Math).</p>
Data repository for study "Understanding agricultural market dynamics in times of crisis: the dynamic agent-based model Agrimate"
<p>Data for the study "Understanding agricultural market dynamics in times of crisis: the dynamic agent-based model Agrimate".</p> <p><strong>hindcasting_analysis</strong></p> <ul> <li>figures of the hindcasting exercise in the main text</li> <li>raw_data <ul> <li> raw model output data for <ul> <li>baseline scenario -- <em>agrimate_baseline=2007-2009_extra_regions=(Egypt=EGY)_regions=AgrimateEU28_start=2000-01-01.nc</em></li> <li>production failure scenario -- <em>agrimate_baseline=2007-2009_extra_regions=(Egypt=EGY)_production_anomalies=FAOsince-2005_regions=AgrimateEU28_start=2000-01-01.nc</em></li> <li>production failure and export restriction scenario -- <em>agrimate_baseline=2007-2009_export_restrictions=2007-2011_extra_regions=(Egypt=EGY)_production_anomalies=FAOsince-2005_regions=AgrimateEU28_start=2000-01-01.nc</em></li> </ul> </li> </ul> </li> </ul> <p><strong>multibreadbasket_analysis</strong></p> <ul> <li>figures of the multibreadbasket analysis in the main text</li> <li>raw_data <ul> <li> raw model output data for <ul> <li>simulations under historical climatic conditions with <number> as an identifier -- <em>agrimate_his-<number>.nc</em></li> <li>simulations under +2°C projection with <number> as an identifier -- <em>agrimate_2p0-<number>.nc</em></li> </ul> </li> </ul> </li> <li>processed_data <ul> <li>processed output data to easier/faster plot</li> </ul> </li> </ul> <p><strong>sensitivity_analysis</strong></p> <ul> <li>raw data and graphics as in <strong>main_output</strong> for different model parameters as given in Table F.1</li> </ul> <p> </p> <p> </p>
Supplementary material for an investigation of suitable healing agents for vascular-based self-healing in cementitious materials
<p>The data found here is related to the crack width measurements, capillary water absorption tests and mechanical tests performed in a study evaluating different types of healing agents for self-healing concrete.</p>
Supplementary data - "Learning Reduced Models for Large-Scale Agent-Based Systems"
<p>This repository contains supplementary data on my PhD thesis "Learning Reduced Models for Large-Scale Agent-Based Systems". Chapters 1-3, 7 and A do not have supplementary data.</p> <p><strong>Chapter 4</strong></p> <ul> <li><em>Large_deviation_example.zip</em> contains the trajectory for Figure 4.8.</li> <li><em>mean_exit_time*</em> contains the raw data to compute the mean exit time and standard deviation for the ABM process (JP) and SDE process (CLE). It contains additionally a precomputed mean and standard deviation as well as the corresponding numbers of agents.</li> <li><em>transition_matrix*</em> contain the computed box discretizations as MATLAB and Numpy files as used for Figures 4.2-4.4, 4.6 and Tables 4.1 and 4.2.</li> </ul> <p><strong>Chapter 5</strong></p> <ul> <li><em>CVM_2021-07-09-15-53_training_data.npz</em> contains the training data for Figure 5.7 a and b.</li> <li><em>CVM_2021-09-29-07-13_distribution.npz </em>contains the raw data for Figure 5.7 c.</li> <li>The remaining data for Chapter 5 can be found in the related dataset <a href="https://doi.org/10.5281/zenodo.4522119">doi.org/10.5281/zenodo.4522119</a>.</li> </ul> <p><strong>Chapter 6</strong></p> <ul> <li><em>CVM_pareto_estimate</em> contains trajectory data required for Figure 6.6 b to estimate points in the Pareto Front using the civil violence model. </li> <li><em>CVM_training_data</em> contains the training data to construct the surrogate model. Each data set consists of <em>CVM_*_cops_train.npz</em> as training set, <em>CVM_*_cops_trajectory.npz</em> as sample trajectory and <em>CVM_*_cops.pkl</em> to compute the training data.</li> <li><em>CVM_covering_iterations_8.mat</em> Pareto set covering after 8 iterations for the civil violence model. Required for Figure 6.6 a.</li> <li><em>CVM_pareto_set+front.npz</em> is required for Figure 6.6 b. </li> <li><em>CVM_surrogate_model.mat</em> contains the surrogate model for the civil violence model</li> <li><em>Expl_iterations_*</em> contains Pareto set coverings after 8 and 12 iterations for Example 6.1.4 and Figure 6.1.</li> <li><em>VM_covering_iterations_12.mat</em> contains the Pareto set covering depicted in Figure 6.4 a.</li> <li><em>VM_ODE_covering_iterations_12_subset_front.mat</em> contains the Pareto set covering depicted in Figure 6.5 and 6.5 c.</li> <li><em>VM_ODE_covering_iterations_12_subset.mat</em> contains the Pareto set covering depicted in Figure 6.5 and 6.5 d.</li> <li><em>VM_ODE_covering_iterations_12.mat</em> contains the Pareto set covering depicted in Figure 6.4 b.</li> <li><em>VM_surrogate_model.mat</em> contains the surrogate model for the extended voter model.</li> <li><em>VM_test_points_non_pareto.npz</em> contains Non-Pareto points in Figure 6.5 and 6.5 d.</li> <li><em>VM_test_points_pareto.npz</em> contains Pareto points in Figure 6.5 and 6.5 c.</li> </ul>
Cystargolide-based amide and ester Pz analogs as proteasome inhibitors and anticancer agents
<p>A series of cystargolide-based beta-lactone analogs containing nitrogen atoms at the Pz portion of the scaffold were prepared and evaluated as proteasome inhibitors and for their cytotoxicity profile towards several cancer cell lines. Inclusion of one, two or even three nitrogen atoms at the Pz portion of the cystargolide scaffold is well-tolerated, producing analogs with low nanomolar proteasome inhibition activity, in many cases superior to carfilzomib. Additionally, analog 8g, containing an ester and pyrazine group at Pz, was shown to possess significant activity towards RPMI 8226 cells (IC50 = 21 nM) and to be less cytotoxic towards the normal tissue model MCF10A cells than carfilzomib.</p>
Data, models, and outputs for an agent-based hydro-economic modeling study in an intensively irrigated region of the U.S. High Plains
<p>In this dataset, we include all the models developed for the study "An integrated modeling approach to simulate human-crop-groundwater interactions in intensively irrigated regions", which is published in Environmental Modelling & Software (<a href="https://doi.org/10.1016/j.envsoft.2024.106120">https://doi.org/10.1016/j.envsoft.2024.106120</a>). Additionally, we provide all the data used in this study. Below, you will find a description of the contents of each file:</p> <ul> <li>abm_modflow.zip: This file includes the agent-based hydro-economic model (ABM-MODFLOW), including model inputs and outputs, Python post-processing scripts, and the Windows batch script for the integration process.</li> <li>modflow.zip: This file contains the standalone MODFLOW model files. Each folder includes files for individual simulation periods, starting with a steady-state model for the predevelopment period, followed by seven transient models.</li> <li>modflow_rs.zip: This file contains the MODFLOW-RS model files. Given that remote sensing data is provided for years from 1984 onwards, only models for the post-1980 simulation periods are included. For model files corresponding to years prior to 1980, refer to modflow.zip.</li> <li>Figurers.zip: This file includes all data and Python scripts used to produce the figures in the main text.</li> <li>Tables.zip: This file contains all tables and the associated data included in the main text.</li> <li>Supporting_Info_Figures: This file includes all data and Python scripts used to produce the figures in the Supporting Information.</li> <li>Supporting_Info_Tables: This file contains all tables and the associated data included in the Supporting Information.</li> <li>Supporting_Info_Videos: This file stores Videos S1 and S2 of the Supporting Information, displaying the historical development of irrigation wells and groundwater-fed irrigated lands in the study area from 1946 to 2018.</li> </ul>
Supplementary data for the paper: "Self-healing concrete with a bacteria-based or crystalline admixture as healing agent to prevent chloride ingress and corrosion in a marine environment'"
<div> <p>Supplementary data for the paper: "Self-healing concrete with a bacteria-based or crystalline admixture as healing agent to prevent chloride ingress and corrosion in a marine environment"<br><br>Open data concerning experimental work. Bacteria-based agents (BAS) and crystalline admixtures (CA) are explored as healing agents to enhance chloride resistance and prevent corrosion. Healing of 100 µm and 300 µm wide cracks was investigated, in combination with two conditioning methods. Either the samples were subjected to wet/dry cycles for 3 months before exposure (“healed”), or they were directly exposed to artificial seawater after crack creation (“unhealed”). </p> </div> <h2>Files</h2>
set of exploration data and parameters for h24/5ad agent based model
<p>Different set of data used for exploration, used for reproductibility, updated with HigherProp parameters</p>
Agent-based simulation
<p>This datasaet comprises the results of the agent-based simulation study described in: Mazurkiewicz, Bartosz and Kattenbeck, Markus and Giannopoulos, Ioannis, <strong>Navigating Your Way! Increasing the Freedom of Choice during Wayfinding, </strong>11th International Conference on Geographic Information Science (GIScience 2021) - Part II</p>
When should bees be flower constant? An agent-based model highlights the importance of social information and foraging conditions
<p>1. Many bee species show flower constancy, i.e. a tendency to visit flowers of one type during a foraging trip. Flower constancy is important for plant reproduction, but the benefits of constancy to bees are unclear. Social bees, which often use communication about food sources, show particularly strong flower constancy.</p> <p>2. We aimed to better understand the benefits of flower constancy in social bees and how these benefits depend on foraging conditions. We hypothesised that sharing social information increases the benefits of flower constancy because social foragers share information selectively about high-quality food sources, thereby reducing the need to sample alternatives.</p> <p>3. We developed an agent-based model that allowed us to simulate bee colonies with and without communication and flower constancy in different foraging environments. By varying key environmental parameters, such as food source numbers and reward size, we explored how the costs and benefits of flower constancy depend on the foraging landscape.</p> <p>4. Flower constancy alone performed poorly in all environments, while indiscriminate flower choice was often the most successful strategy. However, communication improved the performance of flower constant colonies considerably in most environments. This combination was particularly successful when high-quality food sources were abundant and competition was weak.</p> <p>5. Our findings help explain why social bees tend to be more flower constant than solitary bees and suggest that flower constancy can be an adaptive strategy in social bees. Simulations suggest that anthropogenic changes of foraging landscapes will have different effects on the foraging performance of bees that vary in flower constancy.</p>
Wildlife response to disturbances in agent-based models: synthesis on current development and challenges (Systematic Review)
<p>This dataset was obtained from a systematic screening of 124 articles presenting agent-based models of wildlife response to disturbances. It is part of a manuscript for submission to the journal Methods in Ecology and Evolution. The manuscript is entitled: Wildlife response to disturbances in agent-based models: synthesis on current development and challenges.</p>
Shear bond strength of three universal adhesives to three CAD-CAM resin-based composites with and without a silane coupling agent
<p>i) The dataset acquired and analyzed in a laboratory study assessing the effect of three universal adhesives and a two-component silane coupling agent on the shear bond strength to three CAD-CAM resin-based composites with dispersed fillers (CCRBCs). </p> <p>ii) Data on the randomized allocation of specimens using computer-generated sequences created with free online software. </p>
First in Human Study of RVP-001, a New Manganese Based MRI Contrast Agent
ClinicalTrials.gov study NCT05413668. IPD Sharing: NO. Countries: 1. Publications: 0.
Data from: Agent-based versus correlative models of species distributions: Evaluation of predictive performance with real and simulated data
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.