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1,630 results for “Stepping”
Dataset for "Single-Step Selective Oxidation of Methane by Iron-Oxo Species in the Metal-Organic Framework MFU-4l"
<p>Dataset belonging to publication "Single-Step Selective Oxidation of Methane by Iron-Oxo Species in the Metal-Organic Framework MFU-4l"</p>
Supplementary Material for "Recursive Small-Step Multi-Agent A* for Dec-POMDPs"
<p>This artefact accompanies the IJCAI 2023 paper with the same name.<br> Please refer to the README for more information.</p>
Source data for "Regulation of replication origin licensing by ORC phosphorylation reveals a two-step mechanism for Mcm2-7 ring closing"
<p>Source data for "Regulation of replication origin licensing by ORC phosphorylation reveals a two-step mechanism for Mcm2-7 ring closing" </p> <p>The data is organized by Figure and associated Supp Figure(s). A README file is included in each figure folder to explain the files.</p> <p>(note: Data is included for Figs2-7 and SuppFigs 2-8. Fig.1 and SuppFig.1 did not have any associated data matrices, so there is no upload for them here). </p> <p>Briefly, the single molecule data is included in several different formats, all generated from single-molecule TIRF-microscopy video files using Matlab:</p> <p>Integrated trace files "traces" include integrated fluorescence intensity at individual DNA molecules over a 20 minute reaction.</p> <p>Background-corrected trace files normalize the integrated fluorescence intensity to a local-average background, as described in the Methods section of the paper-- these are used for EFRET calculations.</p> <p>"Intervals" files include the start, end time, and duration of protein-DNA interactions and were generated from the trace files and the raw videos using the Imscroll program (available at: https://github.com/gelles-brandeis/CoSMoS_Analysis).</p> <p>EFRET vectors are concatenated vectors of the EFRET vs time values of all protein-DNA interactions in the experiment-- these are used to generate EFRET heat maps. </p> <p>Matlab analysis scripts used in the paper are uploaded in a separate folder "ALA_scripts_used_final". Several of these scripts reference custom Matlab functions from the Gelles lab which are available here: https://github.com/gelles-brandeis/jganalyze and should be downloaded along with my attached scripts file. </p> <p>note: Raw single-molecule video files have not been uploaded here due to large sizes, but can be provided upon request. </p>
Data from: Biochemical, structural and dynamical characterizations of the lactate dehydrogenase from Selenomonas ruminantium provide information about an intermediate evolutionary step prior to complete allosteric regulation acquisition in the super family of lactate and malate dehydrogenases.
<p>This data accompanies the paper entitled <strong><em>Biochemical, structural and dynamical characterizations of the lactate dehydrogenase from Selenomonas ruminantium provide information about an intermediate evolutionary step prior to complete allosteric regulation acquisition in the super family of lactate and malate dehydrogenases.</em></strong></p> <p>The zip archive contains the results of molecular dynamics simulations of the 2 systems investigated in the paper: <em>S. rum</em> and <em>T. mar</em> LDHs. The systems have been simulated at 315 K for <em>S. rum </em>and 340 K for <em>T. mar</em>. Final configurations of the proteins after productions are provided for all the systems in GRO Gromos87 format. Trajectories with the positions of the proteins every 100 ps are provided for all the systems in XTC gromacs format.</p>
Database and Syntax for Analysis of the Paper: "Effects of introducing the WHO Labour Care Guide on Caesarean section: a pragmatic, stepped-wedge, cluster randomized trial in India"
<p>The following files contains the information used to analyze the trial “Implementing the WHO Labour Care Guide to reduce the use of Caesarean section in four hospitals in India: a pragmatic, stepped wedge, cluster randomized pilot trial” in which it was hypothesized that the intervention would promote correct LCG use by these providers, changing their labour monitoring and management practices to align with WHO’s intrapartum recommendations. In turn, this could reduce overuse of Caesarean section, improve maternal and newborn outcomes, and enhance women’s care experiences. </p> <p>Two datafiles with extension “csv” are uploaded. The databased named “LCG Trial Women Database (transition period included).csv” is the database which contains the data of the recruited women in the trial. There is one row per women. The databased named “LCG Trial Neonates Database (transition period included).csv” is the database which contains the data of the neonates born from the recruited women. There is one row per neonate.</p> <p>The excel file “Data Dictionary LCG to Share.xlsx” is the data dictionary of the two databases. In the sheet named “Maternal Variables” a list and description of the variables included in the maternal database is included and, in the sheet, named “Neonatal Variables” a list and description of the variables included in the neonatal database is included.</p> <p>Three files of “R” extension and one “rmd” are included. The file named “RunningModelsFunctions.R” is the one use to run the models that are included in the analyses, the file named “2. Final Analysis LCG Trial.R” is the one in which the tables are prepared, and the file named “3. LCG Results Output Final.rmd” is used to export the tables with results. The R file named “funciones.tablas.R” is used in the analyses.</p>
Рис. 12–13. Биотопы новых виΔов Λистоверток. 12 – биотоп Phtheochroa tabasarana sp. n., степной скΛон к югу от с. Сиртыч, 7.05.2022; 13 – биотоп Celypha laminaria sp. n., горный скΛон к запаΔу от с. Àатуна, 8.06.2022. Figs 12–13. Habitats of new species of leaf-rollers. 12 – habitat of Phtheochroa tabasarana sp. n., stepped slope south of Sirtych village, 7.05V.2022; 13 – habitat of Celypha laminaria sp. n., mountain slope west of Datuna village, 8.06.2022. in Two new species of leaf-rollers (Lepidoptera: Tortricidae) from the East Caucasus
Рис. 12–13. Биотопы новых виΔов Λистоверток. 12 – биотоп Phtheochroa tabasarana sp. n., степной скΛон к югу от с. Сиртыч, 7.05.2022; 13 – биотоп Celypha laminaria sp. n., горный скΛон к запаΔу от с. Àатуна, 8.06.2022. Figs 12–13. Habitats of new species of leaf-rollers. 12 – habitat of Phtheochroa tabasarana sp. n., stepped slope south of Sirtych village, 7.05V.2022; 13 – habitat of Celypha laminaria sp. n., mountain slope west of Datuna village, 8.06.2022.
Strain Evolution in 2D-Digital Composites-T= 1-15 time steps.
<p>Strain Evolution in 2D - Digital Composites for first 15 time steps.</p> <p>Abaqus simulation script can be found <a href="https://github.com/M3RG-IITD/StrainEvolution">here</a></p>
"I was on vacation in Mala, living in a self-catering holiday cottage, together with my girlfriend (we're together for 11 years now), recovering from a heavy workload in the second half of 2008. We were sitting outside, probably sipping a beer, when we heard the sound of bells approaching. Stepping on the stones that enclose the little forecourt of the cottage, we could just see the goat herd being driven by. Idashed for my R09 (recording equipment) to get that impression – but too slowly too late, it seemed, the herd had disappeared and with it the sound. When Iwas about to pack my R09 again the sound appeared to come back, so Idashed down the driveway, just in time to see the herd pass, and then Ifollowed it a couple of hundred meters, walking behind the herd, trying not to breathe or make stepping sounds, eventually, when dogs started barking and a car approached from behind, I stopped and let the goats go on, the car passes, honks ... and Icut the recording and walk back to the cottage." [Peter/ptroxler]13 in Collecting Sounds. Online Sharing of Field Recordings as Cultural Practice
"I was on vacation in Mala, living in a self-catering holiday cottage, together with my girlfriend (we're together for 11 years now), recovering from a heavy workload in the second half of 2008. We were sitting outside, probably sipping a beer, when we heard the sound of bells approaching. Stepping on the stones that enclose the little forecourt of the cottage, we could just see the goat herd being driven by. Idashed for my R09 (recording equipment) to get that impression – but too slowly too late, it seemed, the herd had disappeared and with it the sound. When Iwas about to pack my R09 again the sound appeared to come back, so Idashed down the driveway, just in time to see the herd pass, and then Ifollowed it a couple of hundred meters, walking behind the herd, trying not to breathe or make stepping sounds, eventually, when dogs started barking and a car approached from behind, I stopped and let the goats go on, the car passes, honks ... and Icut the recording and walk back to the cottage." [Peter/ptroxler]13
Sleep Treatment Education Program-1 (STEP-1)
ClinicalTrials.gov study NCT05519982. IPD Sharing: YES. Countries: 1. Publications: 1.
COVID-19 Vaccine Hesitancy Counseling Intervention for Pharmacists: A Stepped-Wedge Trial
ClinicalTrials.gov study NCT06547814. IPD Sharing: YES. Countries: 1. Publications: 5.
Sleep Treatment Education Program for Young Adult Cancer Survivors (STEP-YA)
ClinicalTrials.gov study NCT05358951. IPD Sharing: YES. Countries: 1. Publications: 1.
Integrating a Stepped Care Model of Screening and Treatment for Depression Into Malawi's National HIV Care Delivery Platform
ClinicalTrials.gov study NCT04777006. IPD Sharing: YES. Countries: 1. Publications: 11.
TechStep: Technology-based Stepped Care to Stem Transgender Adolescent Risk Transmission
ClinicalTrials.gov study NCT04000724. IPD Sharing: YES. Countries: 1. Publications: 2.
The RESTING Insomnia Study: Randomized Controlled Study on Effectiveness of Stepped-Care Sleep Therapy
ClinicalTrials.gov study NCT03532282. IPD Sharing: YES. Countries: 1. Publications: 3.
Data for Integrated Step Selection Analysis of translocated female greater sage-grouse in the 60 days post-release, North Dakota 2018-2020
Open the record for dataset details and reuse information.
Data from: Hydrodynamic analysis of bioinspired vortical cross-step filtration by computational modelling
Open the record for dataset details and reuse information.
Spreadsheets: step by step of data reconciliation
<p>Planilhas desenvolvidas para o artigo intitulado “Application of data reconciliation in a water balance as a tool for optimizing water use at a university in Brazil”. Ele foi submetido no 26th IJCIEOM – International Joint Conference on Industrial Engineering and Operations Management;</p> <p>1. Na planilha “Database_IJCIEOM_2020” estão todos os dados usados na pesquisa.</p> <p>2. A planilha denominada “Coverage test” refere-se ao teste estatistico feito com a media dos blocos MT e FS.</p> <p>3. Em “<a href="http://ijcieom_2020.mt/">IJCIEOM_2020.MT</a>” e “IJCIEOM_2020.FS” encontra-se o desenvolvimento da incerteza das medições de vazão de água do CJA-UFSB.</p> <p>4. As planilhas “nhemu_seiqué.MT” e “nhemu_seiqué.FS” são usadas no programa de KALID (2020). Para rodar no programa é necessário renomear para “nhemu_seiqué”.</p> <p> </p> <p>English:</p> <p>Spreadsheets developed for the article entitled “Application of data reconciliation in a water balance as a tool for optimizing water use at a university in Brazil”. He was submitted to the 26th IJCIEOM - International Joint Conference on Industrial Engineering and Operations Management;</p> <p>1. In the spreadsheet “Database_IJCIEOM_2020” are all the data used in the research.</p> <p>2. The spreadsheet called “Coverage test” refers to the statistical test done with the average of blocks MT and FS.</p> <p>3. In “IJCIEOM_2020.MT” and “IJCIEOM_2020.FS” there is the development of the uncertainty of water flow measurements from CJA-UFSB.</p> <p>4. The spreadsheets “nhemu_seiqué.MT” and “nhemu_seiqué.FS” are used in the KALID program (2020). To run the program it is necessary to rename it to “nhemu_seiqué”.</p>
Data from: Genome assembly of the ragweed leaf beetle, a step forward to better predict rapid evolution of a weed biocontrol agent to environmental novelties
<p><span>Rapid evolution of weed biological control agents (BCAs) to new biotic and abiotic conditions is poorly understood and so far, only little considered both in pre-release and post-release studies, despite potential major negative or positive implications for risks of non-targeted attacks or for colonizing yet unsuitable habitats, respectively. Provision of genetic resources, such as assembled and annotated genomes, is essential to assess potential adaptive processes by identifying underlying genetic mechanisms. Here, we provide the first sequenced genome of a phytophagous insect used as a BCA, <i>i.e.</i> the leaf beetle <i>Ophraella communa</i>, a promising BCA of common ragweed, recently and accidentally introduced into Europe. A total 33.98 Gb of raw DNA sequences, representing c. 43-fold coverage, were obtained using the PacBio SMRT-Cell sequencing approach. Among the five different assemblers tested, the SMARTdenovo assembly displaying the best scores was then corrected with Illumina short reads. A final genome of 774 Mb containing 7,003 scaffolds was obtained. The reliability of the final assembly was then assessed by benchmarking universal single-copy orthologous genes (> 96.0% of the 1,658 expected insect genes) and by remapping tests of Illumina short reads (average of 98.6% ± 0.7% without filtering). The number of protein-coding genes of 75,642, representing 82% of the published antennal transcriptome, and the phylogenetic analyses based on 825 orthologous genes placing <i>O. communa </i>in the monophyletic group of Chrysomelidae, confirm the relevance of our genome assembly. Overall, the genome provides a valuable resource for studying potential risks and benefits of this BCA facing environmental novelties.</span></p>
Two-step mixed model approach to analyzing differential alternative RNA splicing: Datasets and R scripts for analysis of alternative splicing
<p>Changes in gene expression can correlate with poor disease outcomes in two ways: through changes in relative transcript levels or through alternative RNA splicing leading to changes in relative abundance of individual transcript isoforms. The objective of this research is to develop new statistical methods in detecting and analyzing both differentially expressed and spliced isoforms, which appropriately account for the dependence between isoforms and multiple testing corrections for the multi-dimensional structure of at both the gene- and isoform- level. We developed a linear mixed effects model-based approach for analyzing the complex alternative RNA splicing regulation patterns detected by whole-transcriptome RNA-sequencing technologies. This approach thoroughly characterizes and differentiates three types of genes related to alternative RNA splicing events with distinct differential expression/splicing patterns. We applied the concept of appropriately controlling for the gene-level overall false discovery rate (OFDR) in this multi-dimensional alternative RNA splicing analysis utilizing a two-step hierarchical hypothesis testing framework. In the initial screening test we identify genes that have differentially expressed or spliced isoforms; in the subsequent confirmatory testing stage we examine only the isoforms for genes that have passed the screening tests. Comparisons with other methods through application to a whole transcriptome RNA-Seq study of adenoid cystic carcinoma and extensive simulation studies have demonstrated the advantages and improved performances of our method. Our proposed method appropriately controls the gene-level OFDR, maintains statistical power, and is flexible to incorporate advanced experimental designs.</p>
Python code for Monte Carlo Simulation of dynein stepping
<p>This project is described in: Three-color single-molecule imaging reveals conformational dynamics of dynein undergoing motility (2020) and can be found on BioRxiv: (link to follow)</p> <p>Here, we provide the custom python code that is used simulate the stepping of dynein based on experimental data. Details on how the code works are given in the script itself. Moreover, we provided a pdf, which shows plots of all the input data.</p> <p>There are three different python scripts:</p> <ul> <li>Monte-Carlo-simulation_Dynein-stepping.py</li> <li>Monte-Carlo-simulation_Dynein-stepping_flexible-ring-position.py</li> <li>Monte-Carlo-simulation_Dynein-stepping_fixed-ring-angle.py</li> </ul> <p>And six folders with different experimental input data:</p> <ol> <li>Experimental-data-to-run-simulation_MT</li> <li>Experimental-data-to-run-simulation_MT_MTBD-distance-independent-angle</li> <li>Experimental-data-to-run-simulation_MT_no-forward-bias</li> <li>Experimental-data-to-run-simulation_MT_no-leading-trailing</li> <li>Experimental-data-to-run-simulation_MT_no-left-right</li> <li>Experimental-data-to-run-simulation_MT_no-stepping-bias</li> </ol> <p>The first python script can be used to generate the stepping movies (Supplementary Movies 3-10). The second python script is used to generate stepping traces and all other plots. The last python script is a special version of number one and two as it simulates the stepping of dynein for a fixed stalk-microtubule angle. It can generate stepping movies as well as stepping traces and all other plots.</p> <p>In order to simulate stepping of dynein for a wild-type condition, the first experimental dataset should be used as input (this dataset is also used for the fixed angle simulation). The other five datasets are used to simulate stepping of dynein when specific rules are ignored:</p> <ul> <li>for an on-axis distance-dependent bias to take more forward than backward steps (dataset #3),</li> <li>a distance-dependent bias to close the gap between the motor domains along the on- and off-axis when taking a step (dataset #4 and 5, respectively), </li> <li>a higher probability for the trailing domain instead of the leading domain to take the next step (dataset #6), and </li> <li>the relative movement between AAA ring and MTBD (for fixed angle see comments above and for MTBD on-axis distance independent angle changes dataset #2)</li> </ul>
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Allen Brain Atlas
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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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