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31 results for “Avoidance strategies”
Opposing life history strategies allow grass shrimp parasites to avoid a conflict of interest
<p>A conflict of interest occurs when parasites manipulate the behavior of their host in contradictory ways to achieve different goals. In grass shrimp (<em>Palaemonetes pugio</em>), trematode parasites that use shrimp as an intermediate host cause the shrimp to be more active than usual around predators, whereas bopyrid isopod parasites that use shrimp as a final host elicit the opposite response. Since these parasites are altering the host's behavior in opposing directions, a conflict of interest would occur in co-infected shrimp. Natural selection should favor attempts to resolve this conflict through avoidance, killing, or sabotage. In a field survey of shrimp populations in four tidal creeks in the Cape Fear River, we found a significant negative association between the two parasites. Parasite abundance was negatively correlated in differently sized hosts, suggesting avoidance as a mechanism. Subsequent mortality experiments showed no evidence of early death of co-infected hosts. In behavior trials, co-infected shrimp did not show significantly different behavior from singly infected or uninfected shrimp, suggesting that neither parasite sabotages the manipulation of the other. Taken together, our results suggest that rather than sabotaging or killing one another, bopyrid and trematode parasites tend to infect differently sized hosts, thus avoiding a conflict and confirming the importance of testing assumptions in natural contexts.</p>
Opposing life history strategies allow grass shrimp parasites to avoid a conflict of interest
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Data archive for: Chain forming diatoms use different strategies to avoid diffusion limited N assimilation
<p>Data archive for: “Chain forming diatoms use different strategies to avoid diffusion limited N assimilation” published in <em><strong>Limnology and Oceanography (L&O), <a href="https://doi.org/10.1002/lno.12677">https://doi.org/10.1002/lno.12677</a></strong></em>.</p> <p> </p> <p>Dataset of single cell assimilation of DIC and NO<sub>3</sub><sup>-</sup> by <em>Skeletonema marinoi</em> in the exponential and stationary growth phase captured using secondary ion mass spectrometry (SIMS) and stable isotopic tracers. The data set contains the data used in the study and the outliers excluded from further analysis.</p> <p> </p> <p>Two strains (Strain 1 and Strain 2) were incubated during either the exponential or stationary growth phase over 24h with <sup>15</sup>N enriched NO<sub>3</sub><sup>-</sup> and <sup>13</sup>C enriched DIC. The cell specific DIC and NO<sub>3</sub><sup>-</sup> assimilation was measured using SIMS.</p> <p>See the main manuscript for a extensive experimental setup and more details.</p> <p><strong>Each file is uploaded as both a .CSV and .XLSX, so that you can choose which you prefer.</strong></p> <p> </p> <p><strong>Row description:</strong></p> <p>Each row represents one <em>Skeletonema marinoi cell</em>.</p> <p><strong>Column description: </strong></p> <p><em>Single.cell:</em> if the cell was a solitary cell (y) or not (n)</p> <p><em>End.cell:</em> if the cell was located at the end of a chain (y) or not (n)</p> <p><em>Chain_position:</em> a number assigned to identify every cell in a chain starting with 1 at one end of the chain</p> <p><em>Chain_length_numeric:</em> the total number of cells in the chain</p> <p><em>Chain_length_max_6: </em>the total number of cell in the chain, all numbers larger than 6 are pooled together and labelled >6</p> <p><em>Two_chain:</em> if the cell was in a chain consisting of only 2 cells (y) or not (n)</p> <p><em>Cell_information:</em> whether the cell was a solitary cell (Single cell), found in a two cell chain (Two cell chain), found at the end of a chain longer than 2 cell (End cell), or in the middle of a chain longer than 3 cells (Middle cell).</p> <p><em>Chain:</em> a identifying number assigned to differentiate the different chains</p> <p><em>C_fmol_per_cell_day:</em> DIC assimilated in fmol cell<sup>-1</sup> day<sup>-1</sup></p> <p><em>N_fmol_per_cell_day:</em> NO<sub>3</sub><sup>-</sup> assimilated in fmol cell<sup>-1</sup> day<sup>-1</sup></p> <p> </p> <p> </p>
Data supplementing the article "Diatom DNA metabarcoding for biomonitoring : strategies to avoid major taxonomical and bioinformatical biases limiting molecular indices capacities" K. Tapolczai, F. Keck, A. Bouchez, F. Rimet, M. Kahlert and V. Vasselon submitted to "Frontiers in Ecology and Evolution" journal
<p>These data supplement the article "Diatom DNA metabarcoding for biomonitoring : strategies to avoid major taxonomical and bioinformatical biases limiting molecular indices capacities" K. Tapolczai, F. Keck, A. Bouchez, F. Rimet, M. Kahlert and V. Vasselon submitted to "Frontiers in Ecology and Evolution" journal.</p> <p>The directory contains the following files:</p> <p><strong>464_samples_fastq_files_(mothur).rar </strong>- contains the 464 fastq files proceed together during the Mothur bioinformatics treatments to produce the OTUs and ISUs tables. As the contig and the demultiplexing steps were performed by the sequencing platform, there is 1 fastq file per sample. From this 464 samples OTU/ISU tables, only information regarding 76 samples were used in this study and are listed in the "<strong>76_samples_list_(mothur).xlsx" </strong>file<strong>.</strong></p> <p><strong>76_samples_list_(mothur).xlsx </strong>- contains the information regarding the 76 samples used to create the OTUs and ISUs tables presented in the paper.</p> <p><strong>76_samples_R1_R2_fastq_files(DADA2).rar - </strong>contains the raw demultiplexed fastq files (R1.fastq and R2.fastq) for each of the 76 samples used in this study to produce the ESVs table using the DADA2 bioinformatics pipeline.</p>
Simulation Dataset: Collective anti-predator escape manoeuvres through optimal attack and avoidance strategies
<p>This is a supplementary simulation dataset to reproduce Fig. 3C,D of the manuscript "Collective anti-predator escape manoeuvres through optimal attack and avoidance strategies" by Bartashevich et al.</p> <p>The zip folder contains the following 3 files in h5 format: front attack (out_Npred1_pred_angle0.0.h5), side attack (<span>out_Npred1_pred_angle1.5707963267948966.h5), </span><span>back attack (out_Npred1_pred_angle3.141592653589793.h5).</span></p> <p>Each file has the following "keys": KeysViewHDF5 ['circ_seg', 'end', 'endD', 'end_PosVel', 'fount', 'part', 'partD', 'pavas', 'pred', 'predD', 'start', 'start_fountain', 'start_pred', 'swarm', 'swarm_pred0', 'swarm_predD'].</p> <p>The key necessary to reproduce Fig. 3C,D of the aforementioned paper is "fount" (<HDF5 dataset "fount": shape (40, 1200, 100, 8), type "<f8">). Namely, "fount" data array consists of 40 simulation runs, 1200 time points, 100 agents, and 8 metrics. The metric with index "0" depicts the value of the Euclidean distance from the agent <em>i</em> to the simulated predator. The metric with index "1" depicts the value of the position angle (theta 1 in rad) of the agent <em>i</em> relative to the simulated predator. The metric with index "2" depicts the value of the flee angle (theta 2 in rad) of the agent <em>i</em> relative to the simulated predator.</p> <p>To estimate the start and the end of the fountain evasion, one can use the following script in Python:</p> <p>import numpy as np</p> <p>m = h5py.File(filename, "r")<br><br>for key in m.keys():<br> print(key)</p> <p>fount_runs = m[key]["fount"]</p> <p>for j in range(40):<br> fnt_start[j] = np.where(fount_runs[j, 0:1200, 0:100,5]==1)[0][0] <br> fnt_end[j] = np.where(fount_runs[j, 0:1200, 0:100,5]==1)[0][-1]</p>
Empirical Dataset: Collective anti-predator escape manoeuvres through optimal attack and avoidance strategies
<h3>Description of the data and file structure</h3> <p>The files contain the source data for Fig. 1 and Fig. 3A,B of the manuscript "Collective anti-predator escape manoeuvres through optimal attack and avoidance strategies" by Bartashevich et al.</p> <h4>Files and variables</h4> <h5>File: Fountain_Fish_coordinates.zip</h5> <p><strong>Description:</strong> </p> <p>The zip file contains 30 folders, each containing information on one predator attack and respective prey evasion. Each folder is named according to the drone ID used for the filming (e.g., DJI _1, DJI _2, DJI _3) and the respective frame number (e.g., f930) from the video recording. </p> <h5>File naming</h5> <p>Each folder contains JPG and CSV files. </p> <p>The JPG files show the image from the footage at the corresponding frame indicated in the files' name (e.g., frame_001_im).</p> <p>There are 2 types of CSV files. Files with the name 'polygon.csv' contain coordinates (in pixels) of points (x, y) defining the polygon outlining the prey school at the particular frame as indicated in the files' name (e.g., frame001) and corresponding to the image in the JPG file with the same frame number. Files with the name 'sardines_and_marlin.csv' contain coordinates (in pixels) of points (x, y), defining the head (columns 1 and 2) and the dorsal fin (columns 3 and 4) of single sardine individuals (by rows), and of the respective attacking marlin: marlin's head (columns 5 and 6), marlin's dorsal fin (columns 7 and 8), and marlin's tip of the bill (columns 9 and 10). These coordinates correspond to the respective image with the same frame number.</p>
Nonaggressive behavior: A strategy employed by an obligate nest invader to avoid conflict with its host species
<p>In addition to its builders, termite nests are known to house a variety of secondary opportunistic termite species so‐called inquilines, but little is known about the mechanisms governing the maintenance of these symbioses. In a single nest, host and inquiline colonies are likely to engage in conflict due to nestmate discrimination, and an intriguing question is how both species cope with each other in the long term. Evasive behaviour has been suggested as one of the mechanisms reducing the frequency of host‐inquiline encounters, yet, the confinement imposed by the nests' physical boundaries suggests that cohabiting species would eventually come across each other. Under these circumstances, it is plausible that inquilines would be required to behave accordingly to secure their housing. Here, we show that once inevitably exposed to hosts individuals, inquilines exhibit nonthreatening behaviours, displaying hence a less threatening profile and preventing conflict escalation with their hosts. By exploring the behavioural dynamics of the encounter between both cohabitants, we find empirical evidence for a lack of aggressiveness by inquilines towards their hosts. Such a nonaggressive behaviour, somewhat uncommon among termites, is characterised by evasive manoeuvres that include reversing direction, bypassing and a defensive mechanism using defecation to repel the host. The behavioural adaptations we describe may play an important role in the stability of cohabitations between host and inquiline termite species: by preventing conflict escalation, inquilines may improve considerably their chances of establishing a stable cohabitation with their hosts.</p>
Strategies Using Darbepoetin Alfa to Avoid Transfusions in Chronic Kidney Disease
ClinicalTrials.gov study NCT01652872. IPD Sharing: Not stated. Countries: 2. Publications: 1.
Nonaggressive behavior: A strategy employed by an obligate nest invader to avoid conflict with its host species
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Data from: Frequency masking drives species-specific temporal avoidance strategies in boreal songbirds
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Pedestrian movement trajectories and collision avoidance strategies in interweaving pedestrian flow experiment
<p>The mechanisms of Collision Avoidance(CA) behaviors in interweaving pedestrian flow movements are important for pedestrian space planning and emergency management but not well understood yet. A series of controlled interweaving pedestrian flow experiments with different pedestrian flow densities are carried out to investigate the CA behaviors, especially CA strategy choices. This dataset consists the movement trajectory and the CA strategy choices information of the participants in the experiment and was provided as a supplementary material of a journal paper submitted to "Royal Society Open Science".</p> <p>All these experiments were conducted in an outdoor public square in the campus of Wuhan University of Technology. A total of 40 students aged 18-23 years participated these experiments. The experiment includes three "groups", representing low, medium and high density levels of interweaving pedestrian flow. Each group of experiment was repeated three times to increase the reliability of the observations. Therefore, there are totally 9 data files in this dataset, each file contains the data of one experiment.</p> <p>After the experiment, the PeTrack software was used to extract pedestrians' trajectories by identifying and tracking the coordinates of participants' heads in the video records. This dataset provides the extracted trajectories of all the pedestrians in each experiment. Trajectory of each RP is marked as Collision Avoidance Segment (CAS) and Normal Walking Segment (NWS). During the CAS, pedestrians have shown collision avoidance strategies. Four types of CA strategies, including "deceleration", "acceleration", "detour", and "stop" are manually identified in these experiments and marked in the dataset. More details of the data and the results of the study could be found in the associated journal paper. This dataset could be useful for researchers in this field.</p>
Supporting data for "Assessing GFDL-ESM4.1 Climate Responses to a Stratospheric Aerosol Injection Strategy Intented to Avoid Overshoot 2.0°C Warming"
<p>Supporting data for our work on GRL. You will find:</p> <p> - Post-processed data from GFDL-ESM4.1 ssp534os and ssp534os-sai experiments,</p> <p> - python codes for generating the plots in the manuscript.</p>
Divergent strategies in faeces avoidance between two cercopithecoid primates
<p class="p1"><span>Parasites constitute a major selective pressure which has shaped animal behaviour through evolutionary time. One adaption to parasites consists of recognizing and avoiding substrates or cues that indicate their presence. Among substrates harbouring infectious agents, faeces are known to elicit avoidance behaviour in numerous animal species. However, the function and mechanisms of faeces avoidance in non-human primates has been largely overlooked by scientists. In this study, we used an experimental approach to investigate whether aversion to faeces in a foraging context is mediated by visual and olfactory cues in two cercopithecoid<i> </i>primates: mandrills (<i>Mandrillus sphinx</i>) and long-tailed macaques (<i>Macaca fascicularis</i>). Visual and olfactory cues of faeces elicited lower food consumption rates in mandrills and higher food manipulation rates in long-tailed macaques. Both results support the infection avoidance hypothesis and confirm similar tendencies observed in other primate species. More studies are now needed to investigate the divergence of avoidance strategies observed in non-human primates regarding food contamination.</span></p>
Strategies to Avoid Returning to Smoking
ClinicalTrials.gov study NCT00757068. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Avoid and Resist Strategies for Weight Management
ClinicalTrials.gov study NCT05143931. IPD Sharing: NO. Countries: 1. Publications: 2.
Strategy to Avoid Excessive Oxygen Using an Autonomous Oxygen Titration Intervention
ClinicalTrials.gov study NCT06374225. IPD Sharing: NO. Countries: 1. Publications: 1.
Resuscitation Enhancement to Avoid Rearrest Through Evidence-based Strategies in Prehospital Post-resuscitation Care
ClinicalTrials.gov study NCT07239908. IPD Sharing: YES. Countries: 0. Publications: 11.
Strategy to Avoid Excessive Oxygen in Major Burn Patients
ClinicalTrials.gov study NCT04534972. IPD Sharing: NO. Countries: 1. Publications: 38.
Strategy to Avoid Excessive Oxygen for Critically Ill Trauma Patients
ClinicalTrials.gov study NCT04534959. IPD Sharing: NO. Countries: 1. Publications: 40.
Treating Hepatitis C in Pakistan. Strategies to Avoid Resistance to Antiviral Drugs
ClinicalTrials.gov study NCT04943588. IPD Sharing: NO. Countries: 1. Publications: 9.
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