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14 results for “GMM”
Hoofprints in the Sand Supplement S3: ADI & GMM datasheet, TPS and sliders for GMM analysis
<p>Datasheet: Provenience, dating, measurements (mm), astragalar index values, and catalogue numbers for the astragali used in the ADI and GMM analyses (.csv file); thin plate spline coordinates (.tps file) and sliders (.csv file) for use in the GMM analysis. As demonstrated in Harding, S. et al. Hoofprints in the Sand: A Metric Study of Livestock on the Southern Phoenician Coast. In preparation for <em>Quaternary International</em>. </p>
Hoofprints in the Sand Supplement S4: R Code for LSI, ADI, GMM Analyses
<p>R code to reproduce the statistics and graphic plots shown in our study on the maritime mobility of sheep in the Iron Age eastern Mediterranean, as demonstrated in Harding, S. et al. Hoofprints in the Sand: A Metric Study of Livestock on the Southern Phoenician Coast. In preparation for <em>Quaternary International</em>. </p>
Geopotential-based Multivariate MJO Index (GMM Index)
<p>This repository contains the data of the Geopotential-based Multivariate MJO Index (GMM Index).<br> </p> <p><strong>About the GMM Index</strong></p> <ul> <li>The GMM index is an RMM-like index, derived from outgoing longwave radiation (OLR), 200hPa and 850hPa zonal wind, that can be extended to the pre-satellite era where satellite-based OLR data is unavailable.</li> <li>The short record of OLR observation limits the data length of the RMM index (<a href="https://journals.ametsoc.org/view/journals/mwre/132/8/1520-0493_2004_132_1917_aarmmi_2.0.co_2.xml">Wheeler and Hendon, 2004</a>), hindering the research of long-term variability of the Madden-Julian Oscillation (MJO) in the past century. And, the GMM index, which can be extended to the early 20th century (and even to the 19th century), is proposed to solve the problem.</li> <li>The construction method of the GMM index is the same as the RMM index, except that: <ul> <li>the OLR input is derived from upper-tropospheric geopotential data, based on the intrinsic relationship between MJO convection and upper-level geopotential (see <a href="https://doi.org/10.1007/s00382-016-3431-x">Leung and Qian, 2017</a>);</li> <li>the OLR, 200hPa and 850hPa zonal wind input of the GMM index are bandpass-filtered anomalies.</li> </ul> </li> <li>Please refer to <a href="https://doi.org/10.1007/s00382-022-06142-2">Leung et al. (2022)</a> for more detail about the calculation procedure and the theory behind it.</li> </ul> <p> </p> <p><strong>Files</strong></p> <ul> <li>GMM index derived based on the ERA-Interim reanalysis <ul> <li>Location: <a href="https://github.com/jeremychleung/Geopotential-based-Multivariate-MJO-Index/blob/main/data/gmm_index_erai.csv">data/gmm_index_erai.csv</a></li> <li>Temporal coverage: 1979–2013</li> </ul> </li> <li>GMM index derived based on the ERA-20C reanalysis <ul> <li>Location: <a href="https://github.com/jeremychleung/Geopotential-based-Multivariate-MJO-Index/blob/main/data/gmm_index_era20c.csv">data/gmm_index_era20c.csv</a></li> <li>Temporal coverage: 1900–2010</li> </ul> </li> <li>GMM index derived based on the NOAA-20CRv3 reanalysis <ul> <li>Link: (to be uploaded)</li> <li>Temporal coverage: 1836–2015</li> </ul> </li> </ul> <p> </p> <p><strong>Citation</strong></p> <p>If you use the GMM index in a publication or for any other purposes, please cite</p> <ul> <li>Leung, J.CH., Qian, W., Zhang, P. et al. Geopotential-based Multivariate MJO Index: extending RMM-like indices to pre-satellite era. Clim Dyn (2022). <a href="https://doi.org/10.1007/s00382-022-06142-2">https://doi.org/10.1007/s00382-022-06142-2</a></li> <li>Zenodo archive: <a href="https://doi.org/10.5281/zenodo.6331379">https://doi.org/10.5281/zenodo.6331379</a></li> </ul> <p> </p> <p><strong>References</strong></p> <ul> <li>Leung, J.CH., Qian, W., Zhang, P. et al. Geopotential-based Multivariate MJO Index: extending RMM-like indices to pre-satellite era. Clim Dyn (2022). <a href="https://doi.org/10.1007/s00382-022-06142-2">https://doi.org/10.1007/s00382-022-06142-2</a></li> <li>Leung, J.CH., Qian, W. Monitoring the Madden–Julian oscillation with geopotential height. Clim Dyn 49, 1981–2006 (2017). <a href="https://doi.org/10.1007/s00382-016-3431-x">https://doi.org/10.1007/s00382-016-3431-x</a></li> <li>Wheeler, M.C., Hendon, H.H. An All-Season Real-Time Multivariate MJO Index: Development of an Index for Monitoring and Prediction. Mon Weather Rev 132:1917–1932 (2004). <a href="https://journals.ametsoc.org/view/journals/mwre/132/8/1520-0493_2004_132_1917_aarmmi_2.0.co_2.xml">https://journals.ametsoc.org/view/journals/mwre/132/8/1520-0493_2004_132_1917_aarmmi_2.0.co_2.xml</a></li> </ul> <p> </p> <p><strong>Contact</strong></p> <p>If you have any questions about the data, feel free to contact Dr. Jeremy Leung (<a href="mailto:chleung@pku.edu.cn">chleung@pku.edu.cn</a> or <a href="mailto:liangzx@gd121.cn">liangzx@gd121.cn</a>).</p>
Dataset: Global Mofy Metaverse Limited (GMM) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Text-fig. 6. The skeletal remains of the European bison from Gladbeck as reconstruction and presentation in the anatomical position. GMM A5.K 517. in Everything Is A Question Of Time - Age Of Important Quaternary Palaeontological Finds From Westphalia
Text-fig. 6. The skeletal remains of the European bison from Gladbeck as reconstruction and presentation in the anatomical position. GMM A5.K 517.
Double Robust Inference for Continuous Updating GMM
<p>Overview<br>The codes and data in the replication package are for replicating Figures 1-12, Table I in the paper “Double Robust Inference for Continuous Updating GMM” and Figures A1-A6 in the Online Appendix to the paper. Thus, the replication package reproduces: All tables and figures in the paper and its online appendix.<br>Computational requirements (software and hardware)<br>•<br>MATLAB (codes were run with MATLAB R2023a).<br>•<br>Dell Latitude 5501 Notebook (codes were run with Windows 10), or MacBook Pro (codes were run with macOS Sonoma).<br>Instructions to replicators<br>•<br>Step 1: Save all the codes and data to the same folder.<br>•<br>Step 2: Run “master_file.m” in MATLAB for replication. The resulting figures and table will be saved to the “output” folder, using the same names as in the paper/appendix.<br>Content of the replication package<br>Figure/Table<br>Expected Running Time<br>Comments<br>master_file.m<br>200 minutes<br>A master file that generates all results.<br>Figure_1_2.m<br>1 second<br>Simulated contour lines might slightly differ.<br>Figure_3_4_5_6.m<br>12 seconds<br>Figure_7.m<br>5 minutes<br>Data in “app_LLM.xls”<br>Figure_8.m<br>15 minutes<br>Data in “app_LLM_He.xls”<br>Figure_9.m<br>3 minutes<br>Data in “app_LLM.xls”<br>Figure_10.m<br>65 minutes<br>Figure_11.m<br>10 minutes<br>Data in “data_KZ2019.xls”<br>Figure_12.m<br>1 second<br>Data in “data_CRRA.xls”<br>Table_I.m<br>65 minutes<br>Data in “app_LLM.xls”, “app_LLM_He.xls”<br>Output is also saved in “output/Table_I.txt”.<br>Figure_A1.m<br>1 minute<br>Figure_A2.m<br>10 minutes<br>Data in “data_KZ2019.xls”<br>Figure_A3.m<br>4 minutes<br>Figure_A4.m<br>15 minutes<br>Data in “data_CRRA.xls”<br>Figure_A5.m<br>1 second<br>Data in “school1.dat” “school2.dat” “school3.dat”<br>Figure_A6.m<br>1 second<br>Simulated contour lines might slightly differ.<br>Notes: The other programs in the package are used by the programs listed above.</p>
Text-fig. 4. The Ahlen mammoth in its new mount of 2016. GMM A5N.383 (photo: Oliver Kunze). in Everything Is A Question Of Time - Age Of Important Quaternary Palaeontological Finds From Westphalia
Text-fig. 4. The Ahlen mammoth in its new mount of 2016. GMM A5N.383 (photo: Oliver Kunze).
Text-fig. 5. Fragment of the musk-ox skull from Herne-Crange. GMM A5.53. Scale bar 5 cm. in Everything Is A Question Of Time - Age Of Important Quaternary Palaeontological Finds From Westphalia
Text-fig. 5. Fragment of the musk-ox skull from Herne-Crange. GMM A5.53. Scale bar 5 cm.
Text-fig. 3. Third definite molar of the Ahlen mammoth. GMM A5N.412. Scale bar 5 cm. in Everything Is A Question Of Time - Age Of Important Quaternary Palaeontological Finds From Westphalia
Text-fig. 3. Third definite molar of the Ahlen mammoth. GMM A5N.412. Scale bar 5 cm.
Deep Learning Methods for Unsupervised Acoustic Modeling using GMM posteriograms (system #1)
<p>System combination of autoencoder and GMM-DNN features. </p>
Supplementary material from: Ashurov S, Othman AHA, Bin Rosman R, Bin Haron R (2020) The determinants of foreign direct investment in Central Asian region: A case study of Tajikistan, Kazakhstan, Kyrgyzstan, Turkmenistan and Uzbekistan (A quantitative analysis using GMM). Russian Journal of Economics 6(2): 162-176. https://doi.org/10.32609/j.ruje.6.48556
Arellano–Bond dynamic panel-data estimation
High-throughput Fitness Experiments Reveal Specific Vulnerabilities of Human-Adapted Salmonella During Stress and Infection- Barseq6 (anaerobic LB, GMM, zinc, Nmedia, protamine- second set)
GEO Series GSE261873. Salmonella enterica subsp. enterica serovar Paratyphi A str. ATCC 9150; Salmonella enterica subsp. enterica serovar Typhi str. Ty2; Salmonella enterica subsp. enterica serovar Typhimurium str. D23580; Salmonella enterica subsp. enterica serovar Typhimurium str. ST4/74. 28 samples. Type: Other.
GMM-Demux: sample demultiplexing, multiplet detection, experiment planning and novel cell type verification in single cell sequencing.
GEO Series GSE152981. Homo sapiens. 5 samples. Type: Expression profiling by high throughput sequencing.
High-throughput Fitness Experiments Reveal Specific Vulnerabilities of Human-Adapted Salmonella During Stress and Infection- Barseq5 (anaerobic LB, GMM, zinc, Nmedia, protamine)
GEO Series GSE261867. Salmonella enterica subsp. enterica serovar Typhi str. Ty2; Salmonella enterica subsp. enterica serovar Typhimurium str. D23580; Salmonella enterica subsp. enterica serovar Typhimurium str. ST4/74; Salmonella enterica subsp. enterica serovar Paratyphi A str. ATCC 9150. 24 samples. Type: Other.
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OpenNeuro
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