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1,457 results for “feedback”
Data from: Feedback between environment and traits under selection in a seasonal environment: consequences for experimental evolution
Batch cultures are frequently used in experimental evolution. Even though they are generally considered to simply drive a growth rate increase, traits evolution can be more complex. Indeed, recurrent batches form a seasonal environment as different phases repeat periodically and different traits can be under selection in the different seasons. Moreover, during culture the impact of organisms on the environment is important since the system is closed. Thus, the study of adaptation should take into account the environment and eco-evolutionary feedbacks. Using the data of an experimental evolution on yeast Saccharomyces cerevisiae, we develop a mathematical model to understand which traits are under selection, and what is the role of the environment for selection in a batch culture. We show that two kinds of traits are under selection in seasonal environments: life-history traits, related to growth and mortality, and transition traits, related to the ability to maintain high growth rate when the environment changes. The impact of environmental conditions can be summarized by the length of the different seasons which weight the importance of selection on each trait: the longer a season is, the higher is selection on the associated traits. Since phenotypes drive the length of each season, eco-evolutionary feedbacks emerge. Such feedbacks are known to promote coexistence between different species or strains. Our results show that the design of the batch in an experimental evolution can affect which traits are most selected because of these feedbacks.
Data from: Interception by two predatory fly species is explained by a proportional navigation feedback controller
When aiming to capture a fast-moving target, animals can follow it until they catch up, or try to intercept it. In principle, interception is the more complicated strategy, but also more energy efficient. To study whether simple feedback controllers can explain interception behaviours by animals with miniature brains, we have reconstructed and studied the predatory flights of the robber fly Holcocephala fusca and killer fly Coenosia attenuata. Although both species catch other aerial arthropods out of the air, Holcocephala contrasts prey against the open sky, while Coenosia hunts against clutter and at much closer range. Thus, their solutions to this target catching task may differ significantly. We reconstructed in three dimensions the flight trajectories of these two species and those of the presented targets they were attempting to intercept. We then tested their recorded performances against simulations. We found that both species intercept targets on near time-optimal courses. To investigate the guidance laws that could underlie this behaviour, we tested three alternative control systems (pure pursuit, deviated pursuit and proportional navigation). Only proportional navigation explains the timing and magnitude of fly steering responses, but with differing gain constants and delays for each fly species. Holcocephala uses a dimensionless navigational constant of N ≈ 3 with a time delay of ≈28 ms to intercept targets over a comparatively long range. This constant is optimal, as it minimizes the control effort required to hit the target. In contrast, Coenosia uses a constant of N ≈ 1.5 with a time delay of ≈18 ms, this setting may allow Coenosia to cope with the extremely high line-of-sight rotation rates, which are due to close target proximity, and thus prevent overcompensation of steering. This is the first clear evidence of interception supported by proportional navigation in insects. This work also demonstrates how by setting different gains and delays, the same simple feedback controller can yield the necessary performance in two different environments.
Data from: Investigating the impact of feedback update interval on the efficacy of restorative brain–computer interfaces
Restorative brain–computer interfaces (BCIs) have been proposed to enhance stroke rehabilitation. Restorative BCIs are able to close the sensorimotor loop by rewarding motor imagery (MI) with sensory feedback. Despite the promising results from early studies, reaching clinically significant outcomes in a timely fashion is yet to be achieved. This lack of efficacy may be due to suboptimal feedback provision. To the best of our knowledge, the optimal feedback update interval (FUI) during MI remains unexplored. There is evidence that sensory feedback disinhibits the motor cortex. Thus, in this study, we explore how shorter than usual FUIs affect behavioural and neurophysiological measures following BCI training for stroke patients using a single-case proof-of-principle study design. The action research arm test was used as the primary behavioural measure and showed a clinically significant increase (36%) over the course of training. The neurophysiological measures including motor evoked potentials and maximum voluntary contraction showed distinctive changes in early and late phases of BCI training. Thus, this preliminary study may pave the way for running larger studies to further investigate the effect of FUI magnitude on the efficacy of restorative BCIs. It may also elucidate the role of early and late phases of motor learning along the course of BCI training.
Globally, plant-soil feedbacks are weak predictors of plant abundance
Plant-soil feedbacks (PSFs) have been shown to strongly affect plant performance under controlled conditions, and PSFs are thought to have far reaching consequences for plant population dynamics and the structuring of plant communities. However, thus far the relationship between PSF and plant species abundance in the field is not consistent. Here, we synthesize PSF experiments from tropical forests to semiarid grasslands, and test for a positive relationship between plant abundance in the field and PSFs estimated from controlled bioassays. We meta-analyzed results from 22 PSF experiments and found an overall positive correlation (0.12 ≤ ▁(r ̅ ) ≤ 0.32) between plant abundance in the field and PSFs across plant functional types (herbaceous and woody plants) but also variation by plant functional type. Thus, our analysis provides quantitative support that plant abundance has a general albeit weak positive relationship with PSFs across ecosystems. Overall, our results suggest that harmful soil biota tend to accumulate around and disproportionately impact species that are rare. However, data for the herbaceous species, which are most common in the literature, had no significant abundance-PSFs relationship. Therefore, we conclude that further work is needed within and across biomes, succession stages and plant types, both under controlled and field conditions, while separating PSF effects from other drivers (e.g. herbivory, competition, disturbance) of plant abundance to tease apart the role of soil biota in causing patterns of plant rarity versus commonness.
When More is Not Merrier: The Effect of Feedback Frequency on Goal Performance
<p>Datasets for When More is Not Merrier: The Effect of Feedback Frequency on Goal Performance</p>
Reproduction data and code for "The social cost of carbon dioxide under climate-economy feedbacks and temperature variability"
<p>### Data for Kikstra et al. 2021, ERL, The social cost of carbon dioxide under climate-economy feedbacks and temperature variability</p> <p>This repository contains data and scripts for the main text figures in the article Kikstra, J.S., Waidelich, P., Rising J., Yumashev, D., Hope, C., Brierley, C.M. (2021) The social cost of carbon dioxide under climate-economy feedbacks and temperature variability, Environmental Research Letters. DOI <a href="https://doi.org/10.1088/1748-9326/ac1d0b">https://doi.org/10.1088/1748-9326/ac1d0b</a></p> <p>##### Authors<br> - Jarmo S. Kikstra<br> - Paul Waidelich<br> - James Rising<br> - Dmitry Yumashev<br> - Chris Hope<br> - Chris M. Brierly</p> <p>Correspondence: kikstra@iiasa.ac.at</p> <p>##### Data repository structure<br> - data # hosts all data that is used to produce the main text figures<br> - growth-effects # hosts model data for results from model runs with persistent damages, for figure 3 and figure 4<br> - PAGE-ANN-Growth_ModelResults_PersistenceDistribution # annual PAGE version, empirical persistence distribution<br> - PAGE-arVAR-Growth_ModelResults_PersistenceDistribution # annual PAGE version with temperature variability, empirical persistence distribution<br> - PAGE-Growth_ModelResults_FixedPersistence # main version, with 10 time steps, fixed persistence levels<br> - PAGE-Growth_ModelResults_LowPassFilterPersistenceDistribution # main version, with 10 time steps, low pass filter persistence distribution<br> - PAGE-Growth_ModelResults_PersistenceDistribution # main version, with 10 time steps, empirical persistence distribution<br> - page-ice # model data for results from PAGE-ICE base model runs<br> - scco2-montecarlo # for figure 6 data<br> - update-page # for figure 2 data<br> - variability # for figure 5 data<br> - extended data # hosts other data used in the manuscript or which we simply want to publish alongside. Example for naming convention for each variable in […] behind the files.<br> - economic-impact # model output variables “EquityWeighting_ te_totaleffect{_ann_yr}.csv” [PAGE-ICE_SSP1-1.9_discountedimpacts.csv]<br> - montecarlo-draws # model output variable “trialdata.csv” [PAGE-ICE_SSP1-1.9_trialdata.csv]<br> - sensitivity # hosts selected sensitivity analysis data used in the appendix<br> - temperature # model output variable “ClimateTemperature_rt_g_globaltemperature.csv” [PAGE-ICE_SSP1-1.9_globaltemperature.csv]<br> - scripts # has one script for each main text figure,<br> - figures # hosts main text figures as they come out of the scripts<br> - README.md # explanation for the repository</p>
When More is Not Merrier: The Effect of Feedback Frequency on Goal Performance
<p>Datasets for When More is Not Merrier: The Effect of Feedback Frequency on Goal Performance</p>
When More is Not Merrier: The Effect of Feedback Frequency on Goal Performance
<p>Datasets for When More is Not Merrier: The Effect of Feedback Frequency on Goal Performance</p>
Evaluation of a Sound Quality Visual Feedback for Bow Learning Technique in Violin Beginners: An EEG Study
<p>Audio and EEG data obtained from beginner and expert violinists while performing a violin bowing exercise. </p>
A Dynamic MaxSAT-based Approach to Directed Feedback Vertex Sets - Results
<p>The Results for the paper of the same name, published at ALENEX 2023.</p>
AGN Feedback in the Survey era: Insights into large samples of Clusters and Groups through LOFAR, MeerKAT and eROSITA
<p>In the last two decades, significant improvements have been made in the understanding of how AGN feedback operates in galaxy clusters. However, the vast majority of these studies involved observations of small samples, mostly lying in the high mass (M> 5 x 10^14 Msun) regime. We will present recent works in which we make use of survey observations performed by VLA, LOFAR and MeerKAT in the radio band, as well as eROSITA, Chandra and XMM-Newton in the X-rays, to investigate AGN feedback on the macro scale in large (N>200) samples of galaxy clusters and groups, down to masses of 2 x 10^13 Msun. We find a close relation between the X-ray emission -estimated within the whole cluster/group extent- and the radio emission produced by the central AGN. Statistical tests show that this correlation is not dominated by biases or selection effects. After converting the radio power into kinetic luminosity, we find an even tighter relation which seemingly exists for both disturbed and relaxed objects. Exploiting a subsample composed by COSMOS spectroscopic galaxy members, we find that Brightest Cluster Galaxies hosting strong AGN radio emission always lie within 0.2 virial radii from the cluster centre, and that there is an higher probability of stronger AGN being hosted in more massive systems. All these observations support the picture of a strong connection between the ICM and radio galaxies hosted in BCGs, which is also predicted by Chaotic Cold Accretion (CCA) models.</p>
Local Monitoring of Photosensitizer Transient States Provides Feedback for Enhanced Efficiency and Targeting Selectivity in Photodynamic Therapy.
<p><strong>This folder contains all raw data underlying the results presented in a manuscript, accepted for publication in Scientifc Reports, entitled:</strong></p> <p><strong>Local Monitoring of Photosensitizer Transient States Provides Feedback for Enhanced Efficiency and Targeting Selectivity in Photodynamic Therapy.</strong></p> <p><strong>Authored by:</strong></p> <p>Elin Sandberg <sup>1</sup>, Chinmaya V Srambickal <sup>1</sup>, Joachim Piguet <sup>1</sup>, Haichun Liu <sup>1</sup> and Jerker Widengren <sup>1,</sup>*</p> <p><sup>1</sup> Experimental Biomolecular Physics, Department of Applied Physics, Royal Institute of Technology (KTH), Stockholm, Sweden</p> <p><sup>* </sup>To whom correspondence should be addressed. Email: jwideng@kth.se. Tel: +46-8-7907813</p> <p> </p> <p><strong>The data files are grouped with respect to the figures/tables in the manuscript where the extracted results are presented. </strong></p> <p><strong>ABSTRACT</strong></p> <p>Photodynamic therapy (PDT) fundamentally relies on local generation of PDT precursor states in added photosensitizers (PS), particularly triplet and photo-radical states. Monitoring these states <em>in situ</em> can provide important feedback but is difficult in practice. The states are strongly influenced by local oxygenation, pH and redox conditions, often varying significantly at PDT treatment sites. To overcome this problem, we followed local PDT precursor state populations of PS compounds, via their fluorescence intensity response to systematically varied excitation light modulation. Thereby, we could demonstrate local monitoring of PDT precursor states of methylene blue (MB) and IRdye700DX (IR700), and determined their transitions rates under different oxygenation, pH and redox conditions. By fiber-optics, using one fiber for both excitation and fluorescence detection, the triplet and photo-radical state kinetics of locally applied MB and IR700 could then be monitored in a tissue sample. Finally, potassium iodide and ascorbate were added as possible PDT adjuvants, enhancing intersystem crossing and photoreduction, respectively, and their effects on the PDT precursor states of MB and IR700 could be locally monitored. Taken together, the presented procedure overcomes current methodological limitations and can offer feedback, guiding both excitation and PDT adjuvant application, and thereby more efficient and targeted PDT treatments.</p>
Datasets for "Characterization of a DC glow discharge in N2-H2 with electrical measurements and neutral and ion mass spectrometry" and "Interaction dust – plasma in Titan's ionosphere: feedbacks on the gas phase composition"
<p>Dataset for the two following papers:</p> <p>-Audrey Chatain, Ana-Sofia Morillo Candas, Ludovic Vettier, Nathalie Carrasco, Guy Cernogora, and Olivier Guaitella, Characterization of a DC glow discharge in N<sub>2</sub>-H<sub>2</sub> with electrical measurements and neutral and ion mass spectrometry, Plasma Sources Science and Technology (2023), vol. 32, 035002. DOI: <a href="https://doi.org/10.1088/1361-6595/acc132">10.1088/1361-6595/acc132</a>. Open access: <a href="http://arxiv.org/abs/2303.01883">arXiv:2303.01883</a>.</p> <p>-Audrey Chatain, Nathalie Carrasco, Ludovic Vettier, and Olivier Guaitella, Interaction dust – plasma in Titan’s ionosphere: feedbacks on the gas phase composition, Icarus (2023), vol. 396, 115502. DOI: <a href="https://doi.org/10.1016/j.icarus.2023.115502">10.1016/j.icarus.2023.115502</a>. Open access: <a href="https://arxiv.org/abs/2303.00062">arXiv:2303.00062</a>.</p> <p>It contains raw data (from electric and mass spectrometry measurements), Matlab codes to process the data, processed Matlab variables, Matlab codes to plot the data and Matlab figures corresponding to the figures in the papers.</p> <p> </p>
An audit and feedback experience: qualitative analysis of personal and contextual dynamics.
<p>Dataset</p>
D6.6 - White goods pilot report - Test user feedback
<p>During the pilot phase, usage and consumption data is generated during the use of the appliance and sent to the ConnectLife app. The logged data consists of, among others, store time stamps, program choice, program duration, washing temperature, and error codes, this provided a continuous stream of raw data. As a result of these insights, individual user consumption data can be compared to the average user consumption data of users (reference data). This allows for providing details feedback to users regarding their program choices and the timing of conducting washing cycles. In addition, average consumption values are included (in grey) in order to create a reference for evaluation and recommendation. The green and red smileys indicate if the test user is below or above the average value, resulting in a note on how to improve the environmental burden.</p>
Data for "Visual feedback modulates the 1/f structure of movement amplitude time series"
<p>The spreadsheet "Time-series, power-spectra, ANOVA, and figure data.xlsx" contains data relevant to the article "Visual feedback modulates the 1/<em>f</em> structure of movement amplitude time series." The file contains movement amplitude time series and the corresponding power spectra for all participants in all conditions. In addition, the file includes data submitted to ANOVA and data used to plot all article figures.</p>
Key data used in "Western North Pacific tropical cyclone activity modulated by phytoplankton feedback under global warming" submitted to Nature Climate Change
<p>Key data</p>
Alpha-frequency feedback to early visual cortex orchestrates coherent naturalistic vision
<p>During naturalistic vision, the brain generates coherent percepts by integrating sensory inputs scattered across the visual field. Here, we asked whether this integration process is mediated by rhythmic cortical feedback. In EEG and fMRI experiments, we experimentally manipulated integrative processing by changing the spatiotemporal coherence of naturalistic videos presented across visual hemifields. Our EEG data revealed that information about incoherent videos is coded in feedforward-related gamma activity while information about coherent videos is coded in feedback-related alpha activity, indicating that integration is indeed mediated by rhythmic activity. Our fMRI data identified scene-selective cortex and hMT as likely sources of this feedback. Analytically combining our EEG and fMRI data further revealed that feedback-related representations in the alpha band shape the earliest stages of visual processing in cortex. Together, our findings indicate that the construction of coherent visual experiences relies on cortical feedback rhythms that fully traverse the visual hierarchy.</p>
Investigating the Use of User Feedback from a Crowd in Requirements Management in Software Ecosystems
<p>Supplementary material.</p>
Investigating the Use of User Feedback from a Crowd in Requirements Management in Software Ecosystems
<p>Supplementary material.</p>
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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.
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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.
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