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1,719 results for “Making”
dhaw/fluCodeImperial: Using real-time data to guide decision-making during an influenza pandemic: a modelling analysis
<p><strong>All codes and data used for "Using real-time data to guide decision-making during an influenza pandemic: a modelling analysis" are included in this folder. The file "runExamples.m" contains a step-by-step method for reproducing figures and running model fits. Ensure that all data and code files are in the same directory, then a single execution of “runExamples” on the command line will generate all main and supplementary figures in the manuscript. There is one line of code per figure, clearly marked, that can be commented out as desired. In order to run the MCMC adaptive algorithm, a single line of code, also clearly marked, must be commented back in. Instructions to change the single-state example are given at the top of the file “runExamples.m”. The saved state selection of California (“state=1”) is consistent with all results presented in the manuscript. </strong></p> <p><strong> </strong></p> <p><strong>Plots make use of files from the following sources, with some modifications:</strong></p> <p><strong>Holger Hoffmann (2022). Violin Plot (https://www.mathworks.com/matlabcentral/fileexchange/45134-violin-plot);</strong></p> <p><strong>Evan (2022). Plot Groups of Stacked Bars (https://www.mathworks.com/matlabcentral/fileexchange/32884-plot-groups-of-stacked-bars);</strong></p> <p><strong>John Onofrey (2022). Shaded Plots and Statistical Distribution Visualizations (https://www.mathworks.com/matlabcentral/fileexchange/69203-shaded-plots-and-statistical-distribution-visualizations)</strong></p>
Real-time Alignments for Predicting Decision-Making Time for Diagnostics over NGS Cycles
<p>Input datasets for an interpretable learning approach to predict decision-making time for diagnostics over NGS cycles. The dataset contains alignment files of two clinical sputum samples sequenced with an Illumina MiSeq sequencing device, and following a real-time sequencing protocol.</p> <p>The datasets consist of real-time alignment files for specific sequencing cycle intervals. The alignment has been performed to a database of respiratory microbes. Data preprocessing, including the removal of human host DNA, is integrated into the real-time alignment approach that has been applied to generate the alignments.</p>
Charcoal-making on Urnarti (N19.55276° E30.41962°)
<p>Urnarti, Sudan.</p> <p>Use of fire: b) charcoal-making (mostly other trees, but date palm wood is used in brick-making and bakeries due to long heat retention).</p>
Making tea using dry leaves, with enclosure to prevent fire from spreading (Difoinarti, N19.94736° E30.49462°)
<p>Use of fire: c) making tea (using dry leaves, including date palms leaves, central part of sociability among farmers during day; here with metal enclosure to prevent fire from spreading) or heating food</p>
High species turnover and unique plant–pollinator interactions make a hyperdiverse mountain
<p>1. We studied α- and β-diversity of pollinators, flowering plants, and plant–pollinator interactions along the altitudinal gradient of Mt. Olympus, a legendary mountain and biodiversity hotspot in Central Greece.</p> <p>2. We explored ten study sites located on the north-eastern slope of the mountain, from 327 to 2,596 m a.s.l. Insect surveys were conducted once a month using hand netting (years 2013, 2014, and 2016), and they were combined with recordings of flowering plant diversity (species richness and flower cover). We then calculated α- and β-diversity of pollinators, plants in flower, and plant–pollinator interactions, and explored their demographic response along the altitudinal gradient.</p> <p>3. Alpha‐diversity of pollinators, plants, and plant–pollinator interactions were altitude-dependent; α‐diversity of all pollinators, bees, non-bumblebee bees, bee flies, and butterflies showed linear declines with altitude, whereas those of hoverflies and bumblebees showed unimodal patterns. Beta-diversity and its turnover component of all pollinators, hoverflies, bees, bumblebees, non-bumblebee bees, butterflies, and plants showed linear increases, whereas those of bee flies and of plant–pollinator interactions varied independently from the pairwise altitudinal difference.</p> <p>4. The high dissimilarity and uniqueness of pollination networks, which is probably a result of the high biodiversity and endemism of Mt. Olympus, is driven by species turnover and the formation of new interactions between new species. Contrasting to the monotonic decline of the remaining groups, the unimodal patterns of hoverfly and bumblebee α‐diversity are probably the effect of a higher tolerance of these groups to high-altitude environmental conditions. Our findings highlight that the high turnover of species and of pollination interactions along the altitudinal gradient is the mainstay of hyperdiverse mountains, a fact that conveys important historical, ecological, and conservational implications.</p>
What Makes Sentences Semantically Related? A Textual Relatedness Dataset and Empirical Study
<p><strong>What Makes Sentences Semantically Related? A Textual Relatedness Dataset and Empirical Study </strong></p> <p>This repository contains data and code for the paper <a href="https://arxiv.org/abs/2110.04845">What Makes Sentences Semantically Related: A Textual Relatedness Dataset and Empirical Study</a>.</p> <p>We hope that this work will spur further research on understanding sentence--sentence relatedness, methods of sentence representation, measures of semantic relatedness, and their applications.</p> <p><strong>Citing our work</strong><br> Please use the following BibTex entry to cite us if you use our dataset or any of the associated analyses:</p> <blockquote>@inproceedings{abdalla2023makes,<br> title={What Makes Sentences Semantically Related: A Textual Relatedness Dataset and Empirical Study},<br> author={Abdalla, Mohamed and Vishnubhotla, Krishnapriya and Mohammad, Saif M.},<br> year={2023},<br> address = {Dubrovnik, Croatia},<br> publisher = "Association for Computational Linguistics",<br> booktitle = "Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume"<br> }</blockquote> <p><strong>Dataset Description</strong></p> <p>The dataset consists of 5500 English sentence pairs that are scored and ranked on a relatedness scale ranging from 0 (least related) to 1 (most related).</p> <p><strong>Why Semantic Relatedness?</strong><br> Closeness of meaning can be of two kinds: semantic relatedness and semantic similarity. Two sentences are considered semantically similar when they have a paraphrasal or entailment relation, whereas relatedness accounts for all of the commonalities that can exist between two sentences. Semantic relatedness is central to textual coherence and narrative structure. Automatically determining semantic relatedness has many applications such as question answering, plagiarism detection, text generation (say in personal assistants and chat bots), and summarization.</p> <p>Prior NLP work has focused on semantic similarity (a small subset of semantic relatedness), largely because of a dearth of datasets. In this paper, we present the first manually annotated dataset of sentence--sentence semantic relatedness. It includes fine-grained scores of relatedness from 0 (least related) to 1 (most related) for 5,500 English sentence pairs. The sentences are taken from diverse sources and thus also have diverse sentence structures, varying amounts of lexical overlap, and varying formality.</p> <p><strong>Comparative Annotations and Best-Worst Scaling</strong><br> Most existing sentence-sentence similarity datasets were annotated, one item at a time, using coarse rating labels such as integer values between 1 and 5 @ representing coarse degrees of closeness. It is well documented that such approaches suffer from inter- and intra-annotator inconsistency, scale region bias, and issues arising due to the fixed granularity.</p> <p>The relatedness scores for our dataset were, instead, obtained using a <em>comparative</em> annotation schema. In comparative annotations, two (or more) items are presented together and the annotator has to determine which is greater with respect to the metric of interest.</p> <p>Specifically, we use Best-Worst Scaling, a comparative annotation method}, which has been shown to produce reliable scores with fewer annotations in other NLP tasks. We use scripts from https://saifmohammad.com/WebPages/BestWorst.html to obtain relatedness scores from our annotations.</p> <p><br> <strong>Loading the Dataset</strong><br> - The sentence pairs, and associated scores, are in the file sem_text_rel_ranked.csv in the root directory. The CSV file can be read using:</p> <pre><code class="language-python">python import pandas as pd str = pd.read_csv('sem_text_rel_ranked.csv') row = str.loc[0] sent1, sent2 = row['Text'].split("\n") score = row['Score']</code></pre> <p>- Relevant columns:</p> <p> - Text: Sentence pair, separated by the newline character.<br> - Score: The semantic relatedness score between 0 and 1.</p> <p>- Additionally:<br> - the SourceID column indicates the source dataset from which the sentence pair was drawn (see Table 2 of our paper)<br> - The SubsetID column indicates the sampling strategy used for the source dataset<br> - and the PairID is a unique identifier for each pair that also indicates its Source and Subset.</p> <p><br> <strong>Raw Annotations from Amazon Mechanical Turk</strong></p> <p>- The `mturk_data/` subdirectory provides the raw MTurk annotations obtained with our comparative annotation setup.<br> - Each row of `mturk_data/bws_annotations.csv` consists of four sentence pairs along with human annotations for the most related (column `BestItem`) and the least related (column `WorstItem`) pair.<br> - File `mturk_data/id2sents.csv` pairs each sentence pair with the corresponding SourceID, SubsetID, and PairID that indicates the source dataset (see Table 2 of our paper).<br> - See file `mturk_data/task_intructions.txt` for the instructions provided to annotators for our task.</p> <p><br> <strong>Datasheet for STR-2022</strong><br> The datasheet for our dataset is in the document `STR2022-datastatement.pdf` in the root folder of this repository.</p> <p><strong>Ethics Statement</strong><br> Any dataset of semantic relatedness entails several ethical considerations. We talk about this in Section 8 of our paper.</p> <p><strong>Creators</strong><br> - <a href="https://www.cs.toronto.edu/~msa/index.html">Mohamed Abdalla</a> (University of Toronto)<br> - <a href="https://priya22.github.io/">Krishnapriya Vishnubhotla</a> (University of Toronto)<br> - <a href="http://saifmohammad.com/">Saif M. Mohammad</a> (National Research Council Canada)</p> <p><strong>Contact:</strong> msa@cs.toronto.edu, vkpriya@cs.toronto.edu, saif.mohammad@nrc-cnrc.gc.ca</p> <p> </p>
Data and code for "Representing storylines with causal networks to support decision making: framework and example"
<p>Data and code for the paper "Representing storylines with causal networks to support decision making: framework and example", along with the Shiny webapp code accompanying the paper. The paper has been submitted to the journal of Climate Risk Management and is currently under review.</p>
Optimal policy for uncertainty estimation concurrent with decision making
<p>Dataset for "Optimal policy for uncertainty estimation concurrent with decision making".</p> <p>The dataset should be merged into the code folder, thus the program can work.</p>
Information integration for decision-making in desert locusts
<p>Locust swarms can extend over hundred kilometers, and starvation compels this ancient pest to devour everything in its path. Theory suggests that gregarious behavior benefits foraging efficiency, yet the role of social cohesion remains elusive. To this end, we collected high-resolution trajectories of individual and grouped gregarious desert locusts in a 2-choice assay with patches of either similar or different quality. Carefully maintaining animals' identities allowed us to monitor each individual's experience and estimate the leaky accumulation process of personally-acquired and socially-derived evidence. We fitted data to a Bayesian model to gain insight into the decision-making system for patch selection. By disentangling the relative contribution of each information class, our study suggests that locusts balance incongruent evidence but reinforce congruent ones. We provide insight into the collective foraging decisions of social (but non-eusocial) insects and present locusts as a powerful empirical system to study individual choices and consequent collective dynamics.</p>
Making virtual species less virtual by reverse engineering of spatiotemporal ecological models v3
<p>The most up-to-date version of the archive that contains all the necessary data to perform analyses supporting the paper <em>Making virtual species less virtual by reverse engineering of spatiotemporal ecological models </em>(<a href="https://doi.org/10.1111/2041-210X.14176">https://doi.org/10.1111/2041-210X.14176</a>) .</p> <p>The research was supported by the National Science Centre, Poland (grant no. 2018/29/B/NZ8/00066) and Poznań Supercomputing and Networking Centre (grant no. 403). </p> <p> </p>
Dataset describing presence or absence of stone tool making techniques in assemblages spanning the past 3 million years
<p>This repository contains a data-set describing the presence or absence of stone tool making techniques reported in the literature across archaeological assemblages, as well as among extant primates, and among the technologies produced in controlled flintknapping experiments. These data were incorporated into Jonathan Paige's dissertation focused on comparative studies of stone tool traditions published in 2022, though that version of the dataset had fewer entries. </p> <p>This dataset is available for development on github: https://github.com/jnpaige/Procedural.unit.dataset. Version 1.0.0 of that repository is what we have deposited here on Zenodo.</p> <p>The codebook used to generate the dataset is hosted on github here: https://github.com/jnpaige/Procedural.unit.codebookVersion 1.0.0 of that codebook was used in the coding process. </p> <p>The repository is stored here as a .tar.gz file, which is both compressed (gz) and packaged like a zip file (.tar). To open it, you need to first extract the files using something like 7zip, then open the archive also using something like 7zip. I might update this to be more user friendly in the future...</p> <p>Data collection for this study was funded through generous support from the Leakey Foundation, GPSA at Arizona State University, and the School of Human Evolution and Social Change, at Arizona State University.</p>
[DATA LINK] Clearing the way to the external world: do ants make optimal decisions when removing obstacles from their subterranean galleries?
<p>Data repository of the submitted paper:</p> <p>“Clearing the way to the external world: do ants make optimal decisions when removing obstacles from their subterranean galleries?”</p> <p>Authors : Louis Devers (0009-0001-3726-1891), Clémentine Cléradin, Zoé Bescond-Michel, Gérard Latil and Vincent Fourcassié (0000-0002-3605-6351).</p> <p>Contains :</p> <ul> <li>Extraction.csv [database] : the observed orientations of the obstacle extraction</li> <li>Traction.csv [database] : censing the orientation of mandibular grasps and effective pulls observed</li> <li>Model_traction.csv [database] : censing the orientation of virtual pulls</li> <li>Model_extraction.csv [database] : censing the orientation of virtual extraction, resulting from sequential tractions presented in model_traction.csv</li> <li>TreatmentAndGraphs [R script] : script including statistical analysis, and survival analysis graphs</li> </ul>
Dataset for Preferred and actual involvement of caregivers in oncologic treatment decision-making: A systematic review
<p>This dataset shows the search that was done for the publication Preferred and actual involvement of caregivers in oncologic treatment decision-making: A systematic review, which can be found at <a href="https://doi.org/10.1016/j.jgo.2023.101525">https://doi.org/10.1016/j.jgo.2023.101525</a>. </p>
Making andesite through shallow hybridization of magmas derived from variably enriched lithospheric mantle
<p>We integrate textural and in situ compositional information from plagioclase and clinopyroxene (Cpx) phenocrysts together with groundmass compositions in early Cretaceous andesite dykes within the Sulu belt of China to propose a new petrogenetic model for andesite. Plagioclase phenocrysts are mostly andesine; they are depleted in high field strength elements (HFSE). However, clinopyroxene (Cpx) phenocrysts are either reversely-zoned (type I) or homogeneous (type II), with the zoned Cpx divided into subtypes IA and IB. All Cpx has high Mg#, low Na<sub>2</sub>O and generally low Al<sub>2</sub>O<sub>3</sub>, with depletions in HFSE and variably high <sup>87</sup>Sr/<sup>86</sup>Sr ratios, suggesting crystallization above the Moho from magmas derived from enriched lithospheric mantle. The cores of type IA/IB and type II Cpx have normal major- and trace-element compositional variations and similar <sup>87</sup>Sr/<sup>86</sup>Sr ratios to each other and to plagioclase, consistent with fractional crystallization from a common magma (magma 1). The rims of type IA and IB Cpx also have normal major- and trace-element compositional variations, but these are not as evolved as the cores, and the rims have lower <sup>87</sup>Sr/<sup>86</sup>Sr ratios, demonstrating crystallization from an isotopically-distinct magma (magma 2). Based on modelled major and rare earth element compositions of magmas inferred to have been in equilibrium with different Cpx (± plagioclase) domains, the measured groundmass compositions can be reproduced by variable mixing between the two magmas. Our study demonstrates for the first time that andesite magma can be made through fractionation and shallow hybridization of magmas derived from variably enriched lithospheric mantle.</p>
Data from: What makes a good pollinator? Abundant and specialized insects with long flight periods transport the most strawberry pollen
<ol> <li>Despite the importance of insect pollination to produce marketable fruits, insect pollination management is limited by insufficient knowledge about key crop pollinator species. This lack of knowledge is due in part to: 1) the extensive labour involved in collecting direct observations of pollen-transport, 2) the variability of insect assemblages over space and time, and 3) the possibility that pollinators may need access to wild plants as well as crop floral resources.</li> <li>We address these problems using strawberry in the UK as a case study. First, we compare two proxies for estimating pollinator importance: flower visits and pollen transport. Pollen-transport data might provide a closer approximation of pollination service, but visitation data are less time-consuming to collect. Second, we identify insect parameters that are associated with high importance as pollinators, estimated using each of the proxies above. Third, we estimated insects' use of wild plants as well as the strawberry crop.</li> <li>Overall, pollinator importances estimated based on easier-to-collect visitation data were strongly correlated with importances estimated based on pollen loads. Both frameworks suggest that bees <em>Apis</em> and <em>Bombus</em> and hoverflies <em>Eristalis</em> are likely to be key pollinators of strawberries, although visitation data underestimate the importance of bees.</li> <li>Moving beyond species identities, abundant, relatively specialised insects with long active periods are likely to provide more pollination service. </li> <li>Most insects visiting strawberry plants also carried pollen from wild plants, suggesting that pollinators need diverse floral resources.</li> <li>Identifying essential pollinators or pollinator parameters based on visitation data will reach the same general conclusions as those using pollen transport data, at least in monoculture crop systems. Managers may be able to enhance pollination service by preserving habitats surrounding crop fields to complement pollinators' diets and provide habitats for diverse life stages of wild pollinators.</li> </ol>
Code and Datasets for "A simple mechanism for collective decision-making in the absence of payoff information"
<p>This repository contains R code and datasets used for analyses in the paper:</p> <p>"A simple mechanism for collective decision-making in the absence of payoff information"</p> <p>Published in <em>Proceedings of the National Academy of Sciences of the United States of America</em> (PNAS) in 2023</p> <p>by Daniele Carlesso, Justin M. McNab, Christopher J. Lustri, Simon Garnier, and Chris. R. Reid.</p> <pre><code>✓ Ensure that all files are in the same folder for the code to run properly. ✓ the repository also includes a summary HTML file for easier visualisation. </code></pre> <p>Datasets:</p> <pre><code>• chain_growth.csv • cumsum_df.csv • growth_data.csv • GrowthMP.csv • JL_chaingrowth.csv • joining_distance.csv • leave_10.csv • leaving_positions.csv • timespent.csv • traffic_mean.csv </code></pre> <p>Code:</p> <pre><code>• Code.Rmd </code></pre> <p>Markdown summary:</p> <pre><code>• Code.html </code></pre>
Dataset: Recruitment responses of shade-tolerant and heliophilous trees in human-degraded areas: the necessity of knowing the recruitment autecology of species for making reforestation decisions
<p>This repository contains the files associated with the following article:</p> <p>Johanna Croce, Ernesto I. Badano, Andrés Tálamo. Recruitment responses of shade-tolerant and heliophilous trees in human-degraded areas: the necessity of knowing the recruitment autecology of species for making reforestation decisions Submitted to <em>Land Degradation & Development</em>.</p> <p>The first Microsoft Excel file (Dataset 01 - Microclimate.xlsx) contains two sheets with the microclimatic data (average, maximum and minimum soil temperatures, and volumetric soil water content) measured in Cerro Chachapoyas and Cerro Fachacano. These measurements were performed on three plots of each trearment, including shrub-protected treatment with high shade, shrub-protected treatment with medium shade, sunny treatment with high herbaceous cover, sunny treatment with medium herbaceous cover and controls. The second Microsoft Excel file (Dataset 02 -Plant responses.xlsx Dataset 02 - Plant responses.xlsx) contains three sheets with the data used to estimate the seedling emergence rates, plant survival rates and net aboveground growth rates of the tree species, including <em>Anadenanthera colubrina</em> and <em>Ceiba chodatii</em> in Cerro Chachapoyas, and <em>Jacaranda mimosifolia</em> in Cerro Fachacano.</p>
The essential-use concept: a valuable tool to guide decision-making on applications for authorisation under REACH?
<p>Supporting Information from The essential-use concept: a valuable tool to guide decision-making on applications for authorisation under REACH?</p>
Signal detection theory applied to giant pandas: Do pandas go out of their way to make sure their scent marks are found?
<p><span>Inter-animal communication allows signals released by an animal to be perceived by others. Scent-marking is the primary mode of such communication in giant pandas </span><span>(<em>Ailuropoda melanoleuca</em>)</span><span>. Signal detection theory propounds that animals choose the substrate and location of their scent marks so that the signals released are transmitted more widely and last longer. We believe that pandas trade off scent-marking because they are an energetically marginal species and it is costly to generate and mark chemical signals. Existing studies only indicate where pandas mark more frequently, but their selection preferences remain unknown. This study investigates whether the marking behavior of pandas is consistent with signal detection theory. Feces count, reflecting habitat use intensity, was combined with mark count to determine the selection preference for marking. The results showed that pandas preferred to mark ridges with animal trails and that most marked tree species were locally dominant. In addition, marked plots and species were selected for lower energy consumption and a higher chance of being detected. Over 90% of the marks used were the longest-surviving anogenital gland secretion marks, and over 80% of the marks were oriented toward animal trails. Our research demonstrates that pandas go out of their way to make sure their marks are found. This study not only sheds light on the mechanisms of scent-marking by pandas but also guides us toward more precise conservation of the panda habitat.</span></p>
Free Open Source Communities Sustainability: Does It Make a Difference in Software Quality?
<p> Free and Open Source Software (FOSS) communities' sustainability is important to maintain and promote access to technology and innovation. While considerable effort has been invested on the topic of FOSS sustainability, limited attention has been given to its impact on community outcomes, e.g., software quality. We conducted an empirical study to examine the influence of FOSS sustainability on software quality. We used projects' data sourced from the Apache Software Foundation Incubator. A total of 236 projects were originally selected. Our final list included a total of 217 projects after applying our exclusion criteria. We used Bayesian data analysis, which incorporates probability distributions to represent the regression coefficients and intercepts. Our findings suggest that our selected sustainability metrics do not significantly affect defect density or code coverage. However, we observed a positive impact of community age on specific code quality metrics, such as risk complexity, number of very large files, and code duplication percentage. Interestingly, our findings show that even when communities are experiencing sustainability, certain code quality metrics are negatively impacted. This implies that code quality practices are not consistently linked to sustainability, and defect management and prevention may be prioritized over the former.</p>
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OpenNeuro
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