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943 results for “play”
Data from: Seascape continuity plays an important role in determining patterns of spatial genetic structure in a coral reef fish
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Effects of chronic THC in adolescence on rat play behaviours
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If the tape were played again: Lineage evolution and the causes of phylogenetic similarity in two tropical assemblages of Coleoptera
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Figure 4 from: Prieß-Buchheit J, Aro AR, Demirova I, Lanzerath D, Stoev P, Wilder N (2020) Rotatory role-playing and role-models to enhance the research integrity culture. Research Ideas and Outcomes 6: e53921. https://doi.org/10.3897/rio.6.e53921
Figure 4 Quotes from Pierre Curie (2012) Marie Curie: With Autobiographical Notes by Marie Curie, Dover Publication: Mineola New York, p.70 and Russell, Bertrand (2004) History of Western Philosophy, London, p.864. Figures designed by Freepik from www.flaticon.com.
Experiments for "It's Time to Play Safe: Shield Synthesis for Timed Systems"
<p><strong>Prerequisite</strong></p> <p>The <em>conda</em> package manager for python</p> <p><strong>Setup</strong></p> <p>Navigate to <em>./Platoon</em> and execute following commands</p> <pre><code class="language-bash">conda env create -n your_env_name -f conda_env.yml conda activate your_env_name pip install -r pip_req.txt</code></pre> <p><strong>Usage</strong>:<br> <strong>Creating an Agent (platoon.py)</strong><br> First you need to create an environment</p> <pre><code class="language-java">gym.make(ENV_NAME, rendermode, numcars, startdist, startspeed, mindist, maxdist, accsteps, rendermode, seed, shield, shield_file)</code></pre> <p>All of these key word arguments already have default values and can be changed if needed.<br> <em>rendermode</em> can be set to <em>None</em>, <em>Minimal</em>, <em>Console</em>, <em>Viewer</em> or <em>Console_Viewer</em><em>.</em></p> <p>The weigths of the agent get saved in <em>./Platoon/weigths</em> <br> and checkpoints can be found in <em>./Platoon/weigths/checkpoints</em><em>.</em><br> The checkpoints can be disabled by not using a <em>callback</em> for the dqnAgent.<br> <br> All the agents have been trained by taking some amount of steps, saving the weights, reloading the weights and then start the training again. <br> The first training session should be between 60.000 and 80.000 steps. (here the <em>load_weigths</em> is not needed)<br> After that the session can be a larger amount of steps but should not be unreasonably large (80.000 - 200.000). <br> Larger amount of cars need more training sessions in order to achieve a good performance.</p> <p><strong>Using an Agent (test_agent.py)</strong><br> the gym should be initialized with the values <em>numcars</em>, <em>mindist</em>, <em>maxdist</em>, <em>accsteps</em> the agent has been trained on <br> <em>startspeed</em>, <em>startdis</em> can be changed, but might create situations where the agent has no way of preventing a crash<br> <em>rendermode</em> can be set to <em>None</em>, <em>Minimal</em>, <em>Console</em>, <em>Viewer</em> or <em>Console_Viewer</em></p> <p>the model, memory and policy need to be set according to the agent <br> now the weigths of the agent can be loaded</p> <pre><code class="language-java">dqn.load_weights('weights/agent_name')</code></pre> <p>Pre-trained agents from 2 - 10 cars can be found in <em>./Platoon/weigths</em></p> <p><strong>Environment</strong><br> the environment can be found in <em>./Platoon/custom_gym/envs/custom_env_dir</em> and consists of <em>platooning_env.py</em> and <em>car.py</em></p> <p><strong>Safestragey</strong></p> <p><strong>Creating a Safe Strategy</strong></p> <ol> <li>open UPPAAL and load the <em>./safe_stragety/cruise.xml</em> file </li> <li>edit it however you want,</li> <li>use these two commands in the Verifier in order to save the strategy <pre><code>strategy safe = control: A[] distance > 5 saveStrategy("filename.txt", safe)</code></pre> <p> </p> </li> </ol> <p><strong>Parser Usage</strong></p> <p>In <em>safe_strategy/</em></p> <pre><code class="language-bash">python parser.py -create in_file_name out_file_name python parser.py -test file_name</code></pre> <p> </p> <p><strong>Using the safestrategy</strong></p> <pre><code class="language-java">gym.make(ENV_NAME, rendermode, numcars, startdist, startspeed, mindist, maxdist, accsteps, rendermode, seed, shield, shield_file)</code></pre> <p>Enable the shield by setting <em>shield</em> to <em>True</em><br> <em>shield_file</em> should be the path to the previously created safestrategy</p>
Rats_Play
Drawing uploaded to scidraw.io on: 19 November 2019
Rats_Play
Drawing uploaded to scidraw.io on: 19 November 2019
Replication data for High-impact details of play and movements with higher trunk acceleration in female basketball game
<p>This study aimed to identify the high-impact details of play and movements with higher acceleration and their frequency during a female basketball match. Trunk acceleration was measured during a simulated basketball game with eight female players. We categorized the various actions as details of play and movements generated at >6 and 8G resultant accelerations using a video recording and an accelerometer attached to the players’ trunk. The frequency and ratio of the details of play and movements about all detected movements were calculated. A total of 1062 and 223 play actions were detected for the resultant acceleration thresholds of >6 and 8G, respectively. For these acceleration thresholds, in terms of details of play, positioning on the half-court was the most frequently observed (29.6% and 23.8%, respectively). In the terms of movements, deceleration was the most frequently detected movement (21.5% and 23.3%, respectively), followed by landing (7.6 and 15.7%, respectively). The results also showed that characteristics of movements or playing style and position of play might have an effect on acceleration patterns during a basketball game. Monitoring the frequency and intensity of these movements and details of play can help to quantify the biomechanical load experienced by basketball players.</p>
Alterations in gut microbiota do not play a causal role in diet-independent weight gain caused by ovariectomy
<p>These files are associated with the following publication:<a href="https://doi.org/10.1210/jendso/bvaa173">https://doi.org/10.1210/jendso/bvaa173</a></p> <p>And the sequence data are available at the European Nucleotide Archive: PRJEB40801</p> <p>This link contains the metadata, sequences reads, and analysis files used in the study "Alterations in gut microbiota do not play a causal role in diet-independent weight gain caused by ovariectomy."</p> <p>Alpha_diversity files:<br> File: AlphaDiversity_analysis_sham_ovex<br> Description: R statistical analysis file for Faith's Phylogenetic Diversity (Faith's PD) and Observed<br> Sequence Variant (SV) alpha diversity metrics<br> File: faith_pd_sham_ovex<br> Description: QIIME2 output file for Faith's PD alpha diversity measurements for sham/ovex samples<br> File: obserevd_svs_sham_ovex<br> Description: QIIME2 output file for Observed SVs alpha diversity measurements for sham/ovex samples<br> </p> <p>Beta_diversity files:<br> File: BetaDiversity_analysis_sham_ovex<br> Description: R statistical analysis file for beta diversiy metrics<br> File: merged.sv.sham.ovex<br> Description: Combined SV table and taxa table for sham/ovex samples <br> File: sv.sham.ovex<br> Description: SV table for sham/ovex samples<br> File: table.sham.ovex.biom<br> Description: BIOM formated file for combined SV and taxa data. (For import into Phyloseq)<br> File: tax.sham.ovex<br> Description: Taxa table for sham/ovex samples<br> File: tree.nwk<br> Description: Phylogentic tree for sham/ovex data (For import into Phyloseq)<br> <br> DeSeq2 Analysis files:<br> File: merged.sv.sham.ovex.trimmed<br> Description: Combined SV table and taxa table for sham/ovex samples. SVs found in 4 samples or less removed. <br> File: sv.table.sham.ovex.trimmed <br> Description: SV table for sham/ovex samples. SVs found in 4 samples or less removed.<br> File: sham.ovex.trimmed.biom<br> Description: BIOM formated file for combined SV and taxa data. SVs found in 4 samples or less removed.(For import into Phyloseq)<br> File: tax.sham.ovex.trimmed<br> Description: Taxa table for sham/ovex samples. SVs found in 4 samples or less removed.<br> File: tree.trimmed.nwk<br> Description: Phylogentic tree for sham/ovex data. SVs found in 4 samples or less removed. (For import into Phyloseq)<br> File: Phyloseq.DeSeq2.Ovex.Sham<br> Description: Log2 Fold change analysis (relative species abundance) done in DESeq2 for time points 1-5.<br> File: Phyloseq.DeSeq2.Ovex.Sham.week3<br> Description: Log2 Fold change analysis (relative species abundance) done in DESeq2 for time point 3.<br> File: Phyloseq.DeSeq2.Ovex.Sham.week4<br> Description: Log2 Fold change analysis (relative species abundance) done in DESeq2 for time point 4.<br> File: Phyloseq.DeSeq2.Ovex.Sham.week5<br> Description: Log2 Fold change analysis (relative species abundance) done in DESeq2 for time point 5.<br> <br> <br> Mapping_files including metadata (for use with sequences below):<br> File: ovex_mapping <br> Description: Mapping file - maps barcodes to samples<br> File: ovex_mapping_samples removed<br> Description: Mapping file - maps barcodes to reads. Two samples removed for low sequence count.<br> 1. Plate2 A08 806rcbc103 GCG AGC GAA GTA CCG GAC TAC HVG GGT WTC TAA T 8 870 (T2) Ovex F<br> 2. Plate2 C02 806rcbc121 GCA ATT AGG TAC CCG GAC TAC HVG GGT WTC TAA T 26 888 (T2) Co-Sham O<br> File: ovex_mapping_sham_ovex_samples removed<br> Description: Mapping file - maps barcodes to reads. Sham/ovex samples only. One sample removed for low sequence count.<br> 1. Plate2 A08 806rcbc103 GCG AGC GAA GTA CCG GAC TAC HVG GGT WTC TAA T 8 870 (T2) Ovex F<br> </p> <p>QIIME2 Script:</p> <p>File: QIIME2_sham_ovex<br> Description: This file includes the commands used in the QIIME2 pipeline.</p>
Data from: A trade-off between oxidative stress resistance and DNA repair plays a role in the evolution of elevated mutation rates in bacteria
The dominant paradigm for the evolution of mutator alleles in bacterial populations is that they spread by indirect selection for linked beneficial mutations when bacteria are poorly adapted. In this paper, we challenge the ubiquity of this paradigm by demonstrating that a clinically important stressor, hydrogen peroxide, generates direct selection for an elevated mutation rate in the pathogenic bacterium Pseudomonas aeruginosa as a consequence of a trade-off between the fidelity of DNA repair and hydrogen peroxide resistance. We demonstrate that the biochemical mechanism underlying this trade-off in the case of mutS is the elevated secretion of catalase by the mutator strain. Our results provide the first experimental evidence that direct selection can favour mutator alleles in bacterial populations, and pave the way for future studies to understand how mutation and DNA repair are linked to stress responses and how this impacts the evolution of bacterial mutation rates.
Data from: Playing 20 Questions with the mind: collaborative problem solving by humans using a brain-to-brain interface
We present, to our knowledge, the first demonstration that a non-invasive brain-to-brain interface (BBI) can be used to allow one human to guess what is on the mind of another human through an interactive question-and-answering paradigm similar to the "20 Questions" game. As in previous non-invasive BBI studies in humans, our interface uses electroencephalography (EEG) to detect specific patterns of brain activity from one participant (the "respondent"), and transcranial magnetic stimulation (TMS) to deliver functionally-relevant information to the brain of a second participant (the "inquirer"). Our results extend previous BBI research by (1) using stimulation of the visual cortex to convey visual stimuli that are privately experienced and consciously perceived by the inquirer; (2) exploiting real-time rather than off-line communication of information from one brain to another; and (3) employing an interactive task, in which the inquirer and respondent must exchange information bi-directionally to collaboratively solve the task. The results demonstrate that using the BBI, ten participants (five inquirer-respondent pairs) can successfully identify a "mystery item" using a true/false question-answering protocol similar to the "20 Questions" game, with high levels of accuracy that are significantly greater than a control condition in which participants were connected through a sham BBI.
Data from: Fungal specificity and selectivity for algae play a major role in determining lichen partnerships across diverse ecogeographic regions in the lichen-forming family Parmeliaceae
Microbial symbionts are instrumental to the ecological and long-term evolutionary success of their hosts, and the central role of symbiotic interactions is increasingly recognized across the vast majority of life. Lichens provide an iconic group for investigating patterns in species interactions; however, relationships among lichen symbionts are often masked by uncertain species boundaries or an inability to reliably identify symbionts. The species-rich lichen-forming fungal family Parmeliaceae provides a diverse group for assessing patterns of interactions of algal symbionts, and our study addresses patterns of lichen symbiont interactions at the largest geographic and taxonomic scales attempted to date. We analysed a total of 2356 algal internal transcribed spacer (ITS) region sequences collected from lichens representing ten mycobiont genera in Parmeliaceae, two genera in Lecanoraceae and 26 cultured Trebouxia strains. Algal ITS sequences were grouped into operational taxonomic units (OTUs); we attempted to validate the evolutionary independence of a subset of the inferred OTUs using chloroplast and mitochondrial loci. We explored the patterns of symbiont interactions in these lichens based on ecogeographic distributions and mycobiont taxonomy. We found high levels of undescribed diversity in Trebouxia, broad distributions across distinct ecoregions for many photobiont OTUs and varying levels of mycobiont selectivity and specificity towards the photobiont. Based on these results, we conclude that fungal specificity and selectivity for algal partners play a major role in determining lichen partnerships, potentially superseding ecology, at least at the ecogeographic scale investigated here. To facilitate effective communication and consistency across future studies, we propose a provisional naming system for Trebouxia photobionts and provide representative sequences for each OTU circumscribed in this study.
The role of common ancestry and gene flow in the evolution of human-directed play behavior in dogs
<p><span>Among-population variance of phenotypic traits is of high relevance for understanding evolutionary mechanisms that operate in relatively short timescales, but various sources of non-independence, such as common ancestry and gene flow can hamper the interpretations. In this comparative analysis of 138 dog breeds, we demonstrate how such confounders can independently shape the evolution of a behavioral trait (human-directed play behavior from the Dog Mentality Assessment project). We combined information on genetic relatedness and haplotype sharing to reflect common ancestry and gene flow, respectively, and entered these into a phylogenetic mixed model to partition the among-breed variance of human-directed play behavior while also accounting for within-breed variance. We found that 75% of the among-breed variance was explained by overall genetic relatedness among breeds, while 15% could be attributed to haplotype sharing that arises from gene flow. Therefore, most of the differences in human-directed play behavior among breeds have likely been caused by constraints of common ancestry as a likely consequence of past selection regimes. On the other hand, gene flow caused by crosses among breeds has played a minor, but not negligible role. Our study serves as an example of an analytical approach that can be applied to comparative situations where the effects of shared origin and gene flow require quantification and appropriate statistical control in a within-species/among-population framework. Altogether, our results suggest that the evolutionary history of dog breeds have left remarkable signatures on the among-breed variation of a behavioral phenotype.</span></p>
Comparative genomic analysis reveals cellulase plays an important role in the pathogenicity of Setosphaeria turcica f. sp. Zeae
<p><i><span>Setosphaeria turcica</span></i><span> f. sp. <i>sorghi</i> and <i>S. turcica</i> f. sp. <i>zeae</i>, the two formae speciales of <i>S. turcica</i>, cause northern leaf blight disease of sorghum and corn, respectively, and often cause serious economic losses. They show obvious host specialization and have a close evolutionary relationship. Genomic sequencing can provide more information for understanding the virulence mechanisms of pathogens. However, the complete genomic sequence of <i>S. turcica</i> f. sp. <i>sorghi</i> has not yet been reported, and no comparative genomic information is available for the two formae speciales. In this study, based on the analysis of genomic structure, there were more protein-coding genes in <i>S. turcica</i> f. sp. <i>sorghi</i> than <i>S. turcica</i> f. sp. <i>zeae</i></span><span>, </span><span>showing positive selection in the evolution of <i>S. turcica</i>. The results of genomic functional analysis showed that the two formae speciales had a large number of identical protein-coding genes, while there were also specific protein families, including metabolic pathway proteins, transport proteins, </span><span>CAZy</span><span>s, pathogen and host interaction proteins. We also investigated the expression of specific effector-coding genes in <i>S. turcica</i> f. sp. <i>zeae</i>, and found that the endo-1, 4-β-D-glucanase coding gene </span><i><span>CEL</span><span>2</span></i><span>, an important component of cellulase, was significantly up-regulated during the interaction process. Finally, gluconolactone inhibited cellulase activity and decreased infection rate and pathogenicity, which indicates that cellulase is essential for maintaining virulence. These findings demonstrate that cellulase plays an important role in the pathogenicity of <i>S. turcica</i> f. sp. <i>zeae</i>. </span></p>
Data from: Historical biogeography of endemic seed plant genera in the Caribbean: did GAARlandia play a role?
The Caribbean archipelago is a region with an extremely complex geological history and an outstanding plant diversity with high levels of endemism. The aim of this study is to better understand the historical assembly and evolution of endemic seed plant genera in the Caribbean, by first determining divergence times of endemic genera to test whether the hypothesized Greater Antilles and Aves Ridge (GAARlandia) land bridge played a role in the archipelago colonization, and second by testing South America as the main colonization source as expected by the position of landmasses and recent evidence of an asymmetrical biotic interchange. We reconstructed a dated molecular phylogenetic tree for 625 seed plants including 32 Caribbean endemic genera using Bayesian inference and ten calibrations. To estimate the geographic range of the ancestors of endemic genera we performed a model selection between a null and 2 complex biogeographical models that included timeframes based on geological information, dispersal probabilities and directionality among regions. Crown ages for endemic genera ranged from Early Eocene (53.1 Ma) to Late Pliocene (3.4 Ma). Confidence intervals for divergence times (crown and/or stem ages) of 22 endemic genera occurred within the GAARlandia time frame. Contrary to expectations, the Antilles appears as the main ancestral area for endemic seed plant genera and only five genera had a South American origin. In contrast with patterns shown for vertebrates and other organisms and based on our sampling we conclude that GAARlandia did not act as a colonization route for plants between South America and the Antilles. Further studies on Caribbean plant dispersal at the species and population levels will be required to reveal finer-scale biogeographic patterns and mechanisms.
Data from: Bird species diversity in Altai riparian landscapes: wood cover plays a key role for avian abundance
Aims: We aim to understand bird richness and variation in species composition (beta diversity) along a 630 km riparian landscape in the Altai Mountains of China, and to test whether vegetation cover is the main explanation of species diversity. Methods: We selected nine regions along a gradient of natural vegetation change. Bird surveys and environmental measurements were conducted at 10 points in each of the nine regions. We collected environmental land cover variables such as wood cover (area proportion of trees and shrubs with saplings in habitats; here trees are woody plant with a single trunk and higher than 3m, shrubs and saplings are distinguished from trees by their multiple trunks and shorter height) and tree cover, and two climate factors which were Annual Mean Temperature (AMT) and Annual Precipitation (AP). We used Liner Regression Models to explore the correlation between bird species richness and environmental variables. We used Sørensen's dissimilarity index to measure birds' beta diversity, and quantified the contribution of environmental variables to this pattern using a Canonical Correspondence Analysis (CCA). Results: Wood cover was the strongest predictor of overall, insectivore and omnivore bird richness. Regions with wood cover contained more bird species. Beta diversity was overall high in the studied regions, and turnover components occupied a major part of beta diversity. Wood cover and AP were significant predictors of bird species composition explaining 33.24% of bird beta diversity together. Conclusions: Wood vegetation including trees, shrubs and saplings, rather than only trees, contains high bird richness. High beta diversity suggests that expansion of the existing nature reserves is needed in the riparian landscapes to capture the variation in bird species composition. Thus all wood cover in the overall riparian landscapes of Altai Mountains should be protected from farming and grazing to improve bird conservation outcomes.
Assessing Iterative Practical Software Engineering Courses with Play Money (Raw data of survey)
<p>This is the raw data of the surveys conducted for a paper / poster " Assessing Iterative Practical Software Engineering Courses with Play Money" at the ICSE 2016.</p>
Dataset of Israeli-Jews, Palestinians, Israeli-Arabs, Americans and Cypriot students' knowledge about the Israeli-Palestinian conflict before and after playing the PeaceMaker game
<p>The dataset includes data from 168 undergraduate students from five different ethnic groups (31 Israeli Jews, 30 Palestinians, 35 Israeli-Arabs, 42 Americans, and 30 Cypriots) who participated in a quasi-experimental pre-test post-test research design and played the games PeaceMaker. Their knowledge about the Israeli-Palestinian conflict was measured before and after playing the game.</p><p> </p>
Gameful experience and student engagement: A Comparative Study of Role-Playing and Puzzle Games in Higher Education
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Plug and play stability for intracortical brain-computer interfaces: A one-year demonstration of seamless brain-to-text communication
<p>Intracortical brain-computer interfaces (iBCIs) have shown promise for restoring rapid communication to people with neurological disorders such as amyotrophic lateral sclerosis (ALS). However, to maintain high performance over time, iBCIs typically need frequent recalibration to combat changes in the neural recordings that accrue over days. In this study, we propose a method: Continual Online Recalibration with Pseudo-labels (CORP), that enables self-recalibration of communication iBCIs without interrupting the user. We evaluated CORP with one clinical trial participant. CORP achieved a stable decoding accuracy of 93.84% in an online handwriting iBCI task, significantly outperforming other baseline methods.</p> <p>This dataset contains 21 sessions of recorded neural activities used for the evaluation. It has been formatted for developing and evaluating machine learning models. There 5 more sessions heldout for a planned iBCI stability competition. They will be released in the future.</p> <p>We also provide a pretrained RNN seed model and a laugnage model to preproduce the results in our paper.</p>
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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.