cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.12237389
title: cateventnodes.csv from A natural catastrophic turnover event: individual sociality matters despite community resilience in wild house mice

description: Natural disasters can cause rapid demographic changes which disturb the social structure of a population as individuals may lose connections. These changes also have indirect effects as survivors alter their within-group connections or move between groups. As group membership and network position may influence individual fitness, indirect effects may affect how individuals and populations recover from catastrophic events. Here we study changes in the social structure after a large predation event in a population of wild house mice (<i>Mus musculus domesticus</i>), where a third of adults were lost. Using social network analysis, we examine how heterogeneity in sociality results in varied responses to losing connections. We then investigate how these differences influence the overall network structure. An individual's reaction to losing associates depended on its sociality prior to the event. Those that were less social before formed more weak connections afterwards, while more social individuals reduced the number of survivors they associated with. Otherwise, the number and size of social groups were highly robust. This indicates that social preferences can drive how individuals adjust their social behaviour after catastrophic turnover events, despite the population's resilience in social structure.
DOI: 10.6084/m9.figshare.12237389.v1
title: cateventnodes.csv from A natural catastrophic turnover event: individual sociality matters despite community resilience in wild house mice

description: Natural disasters can cause rapid demographic changes which disturb the social structure of a population as individuals may lose connections. These changes also have indirect effects as survivors alter their within-group connections or move between groups. As group membership and network position may influence individual fitness, indirect effects may affect how individuals and populations recover from catastrophic events. Here we study changes in the social structure after a large predation event in a population of wild house mice (<i>Mus musculus domesticus</i>), where a third of adults were lost. Using social network analysis, we examine how heterogeneity in sociality results in varied responses to losing connections. We then investigate how these differences influence the overall network structure. An individual's reaction to losing associates depended on its sociality prior to the event. Those that were less social before formed more weak connections afterwards, while more social individuals reduced the number of survivors they associated with. Otherwise, the number and size of social groups were highly robust. This indicates that social preferences can drive how individuals adjust their social behaviour after catastrophic turnover events, despite the population's resilience in social structure.
DOI: 10.6084/m9.figshare.12236969
title: IVIM Shepp Logan Phantom

description: D, D* and f values were assigned to the phantom, including normal tissue, tissue with infiltrating tumour, low-perfused tumour, high-perfused tumour, cavity and cerebrospinal fluid. Diffusion-weighted images (DWI) were simulated using the IVIM model at 54 b-values ranging from 0-1000, for five slices, each at a different noise level.
DOI: 10.6084/m9.figshare.12236963
title: Country Boundaries

description: This is a shapefile with country boundaries.
DOI: 10.6084/m9.figshare.12236966
title: EEG 128E example dataset ANT CNT

description: a raw EEG datase contaminated with a 16 2/3 Hz artefact
DOI: 10.6084/m9.figshare.12236957
title: Dataset for Modeling Climate Change and Health in Uganda-East Africa

description: Climate change, that is a threat to ecosystems and the livelihoods of those that depend on them, is increasingly manifesting as an increased frequency and intensity of severe weather events such as droughts and floods (Déqué et al., 2017). Climate change has created an urgent need for early warning aids or models to enhance the sub-Saharan African health systems ability to prepare for, and cope with escalations in treatment needs of climate sensitive diseases (Nhamo & Muchuru, 2019). This dataset was created from the health and weather data of nine purposively selected study districts in Uganda, whose health and weather data were available for the development of an early warning health model (https://github.com/CHAIUGA/chasa-model) and an accompanying prediction web app (https://github.com/CHAIUGA/chasa-webapp). The districts were selected based on the following criteria: (a) were experiencing climate change and variability, (b) represented different climatologic, and agro-ecological zones, (c) availability of climate information and health information from a health facility within a 40 kilometres radius of a functional weather station. Historical weather data was retrieved from the Uganda National Meteorological Association databases, as monthly averages. The weather variables in this data included: atmospheric pressure, rainfall, solar radiation, humidity, temperature (maximum, minimum and mean), and wind (gusts and average wind speed). The monthly health aggregated data for the period starting September 2018 to December 2019, was retrieved from the National Health Repository (DHIS2) for referral hospitals within the selected districts. Only data for a selection of climate-sensitive disease aggregates was obtained. The dataset contains 436 complete matched disease and weather records. Ethical issues: Both the de-identified aggregate monthly disease diagnosis count data and weather data in this dataset are from national data available to the public on request.
DOI: 10.6084/m9.figshare.12236960
title: Arabic Handwritten Characters Dataset

description: Arabic Handwritten Characters DatasetAstractHandwritten Arabic character recognition systems face several challenges, including the unlimited variation in human handwriting and large public databases. In this work, we model a deep learning architecture that can be effectively apply to recognizing Arabic handwritten characters. A Convolutional Neural Network (CNN) is a special type of feed-forward multilayer trained in supervised mode. The CNN trained and tested our database that contain 16800 of handwritten Arabic characters. In this paper, the optimization methods implemented to increase the performance of CNN. Common machine learning methods usually apply a combination of feature extractor and trainable classifier. The use of CNN leads to significant improvements across different machine-learning classification algorithms. Our proposed CNN is giving an average 5.1% misclassification error on testing data.ContextThe motivation of this study is to use cross knowledge learned from multiple works to enhancement the performance of Arabic handwritten character recognition. In recent years, Arabic handwritten characters recognition with different handwriting styles as well, making it important to find and work on a new and advanced solution for handwriting recognition. A deep learning systems needs a huge number of data (images) to be able to make a good decisions.ContentThe data-set is composed of 16,800 characters written by 60 participants, the age range is between 19 to 40 years, and 90% of participants are right-hand. Each participant wrote each character (from ’alef’ to ’yeh’) ten times on two forms as shown in Fig. 7(a) & 7(b). The forms were scanned at the resolution of 300 dpi. Each block is segmented automatically using Matlab 2016a to determining the coordinates for each block. The database is partitioned into two sets: a training set (13,440 characters to 480 images per class) and a test set (3,360 characters to 120 images per class). Writers of training set and test set are exclusive. Ordering of including writers to test set are randomized to make sure that writers of test set are not from a single institution (to ensure variability of the test set).In an experimental section we showed that the results were promising with 94.9% classification accuracy rate on testing images. In future work, we plan to work on improving the performance of handwritten Arabic character recognition.AcknowledgementsAhmed El-Sawy, Mohamed Loey, Hazem EL-Bakry, Arabic Handwritten Characters Recognition using Convolutional Neural Network, WSEAS, 2017<br>Our proposed CNN is giving an average 5.1% misclassification error on testing data.InspirationCreating the proposed database presents more challenges because it deals with many issues such as style of writing, thickness, dots number and position. Some characters have different shapes while written in the same position. For example the teh character has different shapes in isolated position.Benha Universityhttp://bu.edu.eg/staff/mloeyhttps://mloey.github.io/
DOI: 10.6084/m9.figshare.12236948
title: Arabic Handwritten Digits Dataset

description: Arabic Handwritten Digits DatasetAbstractIn recent years, handwritten digits recognition has been an important area<br>due to its applications in several fields. This work is focusing on the recognition<br>part of handwritten Arabic digits recognition that face several challenges, including<br>the unlimited variation in human handwriting and the large public databases. The<br>paper provided a deep learning technique that can be effectively apply to recognizing Arabic handwritten digits. LeNet-5, a Convolutional Neural Network (CNN)<br>trained and tested MADBase database (Arabic handwritten digits images) that contain 60000 training and 10000 testing images. A comparison is held amongst the<br>results, and it is shown by the end that the use of CNN was leaded to significant<br>improvements across different machine-learning classification algorithms.The Convolutional Neural Network was trained and tested MADBase database (Arabic handwritten digits images) that contain 60000 training and 10000 testing images. Moreover, the CNN is giving an average recognition accuracy of 99.15%.ContextThe motivation of this study is to use cross knowledge learned from multiple works to enhancement the performance of Arabic handwritten digits recognition. In recent years, Arabic handwritten digits recognition with different handwriting styles as well, making it important to find and work on a new and advanced solution for handwriting recognition. A deep learning systems needs a huge number of data (images) to be able to make a good decisions.ContentThe MADBase is modified Arabic handwritten digits database contains 60,000 training images, and 10,000 test images. MADBase were written by 700 writers. Each writer wrote each digit (from 0 -9) ten times. To ensure including different writing styles, the database was gathered from different institutions: Colleges of Engineering and Law, School of Medicine, the Open University (whose students span a wide range of ages), a high school, and a governmental institution.<br>MADBase is available for free and can be downloaded from (http://datacenter.aucegypt.edu/shazeem/) .AcknowledgementsCNN for Handwritten Arabic Digits Recognition Based on LeNet-5<br>http://link.springer.com/chapter/10.1007/978-3-319-48308-5_54<br>Ahmed El-Sawy, Hazem El-Bakry, Mohamed Loey<br>Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2016<br>Volume 533 of the series Advances in Intelligent Systems and Computing pp 566-575InspirationCreating the proposed database presents more challenges because it deals with many issues such as style of writing, thickness, dots number and position. Some characters have different shapes while written in the same position. For example the teh character has different shapes in isolated position.Arabic Handwritten Characters Datasethttps://www.kaggle.com/mloey1/ahcd1Benha Universityhttp://bu.edu.eg/staff/mloeyhttps://mloey.github.io/
DOI: 10.6084/m9.figshare.12236966.v1
title: EEG 128E example dataset ANT CNT

description: a raw EEG datase contaminated with a 16 2/3 Hz artefact
DOI: 10.6084/m9.figshare.12236933
title: Guia para trabalho de campo UFSM/UFPEL

description: Guia elaborado para trabalho de campo na Quarta Colônia-RS (2019)
DOI: 10.6084/m9.figshare.12236933.v1
title: Guia para trabalho de campo UFSM/UFPEL

description: Guia elaborado para trabalho de campo na Quarta Colônia-RS (2019)
DOI: 10.6084/m9.figshare.12236918
title: Roteiro para visitação-Quarta Colônia 2020

description: Roteiro de visitação para a Quarta Colônia-RS, elaborado para o XII SBPV.
DOI: 10.6084/m9.figshare.12236918.v1
title: Roteiro para visitação-Quarta Colônia 2020

description: Roteiro de visitação para a Quarta Colônia-RS, elaborado para o XII SBPV.
DOI: 10.6084/m9.figshare.12236810
title: IVIM Dataset

description: IVIM Acquisition: 149x149x84x49
DOI: 10.6084/m9.figshare.12236807
title: Data for Dianthus Analyses

description: This zip package holds all of the data used in creating a suite of analyses related to the distributional ecology of an endemic species of <i>Dianthus</i> in the mountains of Iran.
DOI: 10.6084/m9.figshare.12236807.v1
title: Data for Dianthus Analyses

description: This zip package holds all of the data used in creating a suite of analyses related to the distributional ecology of an endemic species of <i>Dianthus</i> in the mountains of Iran.
DOI: 10.6084/m9.figshare.12236789
title: Dataset used to assess relationship between millet cultivation and malnutrition patterns in India at district level

description: This dataset draws data from 2011 Census of India, district level malnutrition data from the National Family Health Survey 4th round and district-wise area under cultivation by cereal type from web-based land-use data from Indian Ministry of Agriculture and is used to analyse the relationship between staple cereal cultivation and particular patterns of malnutrition. An explanatory note is attached explaining how the dataset was created.
DOI: 10.6084/m9.figshare.12236789.v1
title: Dataset used to assess relationship between millet cultivation and malnutrition patterns in India at district level

description: This dataset draws data from 2011 Census of India, district level malnutrition data from the National Family Health Survey 4th round and district-wise area under cultivation by cereal type from web-based land-use data from Indian Ministry of Agriculture and is used to analyse the relationship between staple cereal cultivation and particular patterns of malnutrition. An explanatory note is attached explaining how the dataset was created.
DOI: 10.6084/m9.figshare.12236588
title: Laporan kahoot: Berkenalan dengan Kahoot

description: Berikut ini merupakan contoh hasil laporan kahoot setelah dimainkan. Untuk melihat atau meninjau kahoot asli silakan cek tautan di bawah ini.
DOI: 10.6084/m9.figshare.12236423
title: CLBR-e-FETvsFresh.xlsx

description: This data set is sourced from our clinical computer based data set
DOI: 10.6084/m9.figshare.12236423.v1
title: CLBR-e-FETvsFresh.xlsx

description: This data set is sourced from our clinical computer based data set
DOI: 10.6084/m9.figshare.12236300
title: Gabungan rataan beberapa pengukuran utk publikasi.xlsx

description: Darunavir data
DOI: 10.6084/m9.figshare.12236303
title: Copy of JH3 utk publikasi revised.xlsx

description: JH3 data
DOI: 10.6084/m9.figshare.12236300.v1
title: Gabungan rataan beberapa pengukuran utk publikasi.xlsx

description: Darunavir data
DOI: 10.6084/m9.figshare.12236258
title: TMA-RAW DATA.xlsx

description: A total of 73 colorectal cancer tissues and normal colorectal mucosa tissues were collected from different selected patients in each tissue microarray slide. The tissue microarrays (TMA) were scored blindly by a clinical pathologist. Total and nuclear PLA signals were evaluated for both IGF-1R/NuMA and 53BP1/NuMA. Tumors were arbitrary classified for statistical comparisons: tumor with no or very few signals were scored as 0-1 (negative / weak); tumors with moderate signals (5-10 per cell/nuclei in the majority of cells) were scored as 2 (intermediate), and tumors with abundant signals (&gt;10 signals per cell / nuclei in the majority of cells) were scored as 3 (strong).
DOI: 10.6084/m9.figshare.12236303.v1
title: Copy of JH3 utk publikasi revised.xlsx

description: JH3 data
DOI: 10.6084/m9.figshare.12236078
title: JGROceans_IO

description: data sets used for the analysis of seasonal and inter annul variability of chlorophyll in the North India Ocean.All the satellite data are public free available at http://www.science.oregonstate.eduthe nutrients data used in the calculation are from https://www.nodc.noaa.gov/OC5/woa18/.<br>The wind and net heat flux are from:https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/sea surface height are from:AVISO, http://www.aviso.oceanobs.com/)<br>Here, we upload the cruise data used for the comparison with the satellite derived vertical Chl.
DOI: 10.6084/m9.figshare.12236078.v1
title: JGROceans_IO

description: data sets used for the analysis of seasonal and inter annul variability of chlorophyll in the North India Ocean.All the satellite data are public free available at http://www.science.oregonstate.eduthe nutrients data used in the calculation are from https://www.nodc.noaa.gov/OC5/woa18/.<br>The wind and net heat flux are from:https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/sea surface height are from:AVISO, http://www.aviso.oceanobs.com/)<br>Here, we upload the cruise data used for the comparison with the satellite derived vertical Chl.
DOI: 10.6084/m9.figshare.12235910
title: AdaptiveComparisonMatrixData.zip

description: This data set consists of :<br>(1) Excel file that includes original data used in plots of simulation and psychophysical experiments.<br>(2) A series of images that show trial-by-trial development of comparision matrix, sorted comparison matrix, and fitted comparison matrix (100 trials). This was obtained from a simulation with parameters of N=50, M=8, Sigma=0.05.<br><br>
DOI: 10.6084/m9.figshare.12235886
title: Fabrication of extended-dissolution divalproex tablets: a green solvent-free granulation technique

description: <b>Objective:</b> Divalproex sodium (DVS) is a challenging drug owing to its hygroscopicity, bitter taste, and short <i>in vivo</i> half-life. This study aims to produce stable taste masked DVS once daily tablets using solvent free hot melt granulation (HMG) process. <b>Methods:</b> A lab scale high shear mixer granulator employing six meltable lipid binders (compritol<sup>®</sup>888 ATO, beeswax, gelucire<sup>®</sup>50/13, precirol<sup>®</sup> ATO5, stearyl alcohol, and geleol<sup>®</sup>) was used for the preparation of tablets. Quality control tests were performed on granules and tablets, and Box–Behnken’s design was adopted to investigate the effect of binder concentration, impeller speed, and granulation time on the drug dissolution. Shelf and accelerated stability evaluation, taste assessment, and <i>in vivo</i> pharmacokinetic study were conducted on the selected batches. <b>Results:</b> Results revealed that DVS tablets were successfully prepared, and that the <i>in vitro</i> dissolution of the drug was inversely proportional to the binder concentration. Beeswax and compritol<sup>®</sup> tablets showed similar dissolution profiles to the marketed product Depakote<sup>®</sup> 500 ER tablets (F1 50). The selected batches showed lower moisture content (&lt;2%) and successfully masked the bitter taste compared to uncoated tablets based on a hydrophilic matrix. The <i>in vivo</i> pharmacokinetic study delineated relative bioavailability values for Beeswax and Compritol<sup>®</sup> tablets of 95.6% and 118%, respectively, compared to the marketed product. <b>Conclusion:</b> The solvent free HMG process can be employed to formulate 24 h extended dissolution DVS tablets with masked bitter taste and high stability, and comparable or higher bioavailability than the marketed product.
DOI: 10.6084/m9.figshare.12235886.v2
title: Fabrication of extended-dissolution divalproex tablets: a green solvent-free granulation technique

description: <b>Objective:</b> Divalproex sodium (DVS) is a challenging drug owing to its hygroscopicity, bitter taste, and short <i>in vivo</i> half-life. This study aims to produce stable taste masked DVS once daily tablets using solvent free hot melt granulation (HMG) process. <b>Methods:</b> A lab scale high shear mixer granulator employing six meltable lipid binders (compritol<sup>®</sup>888 ATO, beeswax, gelucire<sup>®</sup>50/13, precirol<sup>®</sup> ATO5, stearyl alcohol, and geleol<sup>®</sup>) was used for the preparation of tablets. Quality control tests were performed on granules and tablets, and Box–Behnken’s design was adopted to investigate the effect of binder concentration, impeller speed, and granulation time on the drug dissolution. Shelf and accelerated stability evaluation, taste assessment, and <i>in vivo</i> pharmacokinetic study were conducted on the selected batches. <b>Results:</b> Results revealed that DVS tablets were successfully prepared, and that the <i>in vitro</i> dissolution of the drug was inversely proportional to the binder concentration. Beeswax and compritol<sup>®</sup> tablets showed similar dissolution profiles to the marketed product Depakote<sup>®</sup> 500 ER tablets (F1 50). The selected batches showed lower moisture content (&lt;2%) and successfully masked the bitter taste compared to uncoated tablets based on a hydrophilic matrix. The <i>in vivo</i> pharmacokinetic study delineated relative bioavailability values for Beeswax and Compritol<sup>®</sup> tablets of 95.6% and 118%, respectively, compared to the marketed product. <b>Conclusion:</b> The solvent free HMG process can be employed to formulate 24 h extended dissolution DVS tablets with masked bitter taste and high stability, and comparable or higher bioavailability than the marketed product.
DOI: 10.6084/m9.figshare.12235751
title: Supplementary data for IDR in coupled TN and PDN

description: 1) Supplementary data for the IDR in coupled TN and PDN is included.2) Refer to my paper "Integrated Demand Response for Congestion Alleviation in Coupled Power and Transportation Networks" if published online.
DOI: 10.6084/m9.figshare.12235751.v1
title: Supplementary data for IDR in coupled TN and PDN

description: 1) Supplementary data for the IDR in coupled TN and PDN is included.2) Refer to my paper "Integrated Demand Response for Congestion Alleviation in Coupled Power and Transportation Networks" if published online.
DOI: 10.6084/m9.figshare.12235733
title: Advantages and limits of metagenomic assembly and binning of a giant virus

description: Metagenome assemblies, reference genome assemblies and metagenome assembled genomes from the study "Advantages and limits of metagenomic assembly and binning of a giant virus" by Schulz et al., 2020
DOI: 10.6084/m9.figshare.12235412
title: Anxiety Tasks

description: These tasks were formulated to help patients with anxiety, for my final year project
DOI: 10.6084/m9.figshare.12235406
title: VG_samples

description: Pitfalls and Opportunities in Benchmarking Metagenomic Classifiers
DOI: 10.6084/m9.figshare.12235409
title: Depression Tasks.xlsx

description: These tasks were formulated to help people suffering from depression, as a part of my final year research project.
DOI: 10.6084/m9.figshare.12235403
title: Data File for "Income Tax Data Adoption and Spatial Diffusion"

description: Data file for:<br>Hall, J., Lacombe, D. & Tackett, M. Income Tax Adoption and Spatial Diffusion. <i>Atl Econ J</i> (2020). https://doi.org/10.1007/s11293-020-09669-z
DOI: 10.25392/leicester.data.12235397
title: Appendix II: SNP Genotyping

description: PhD thesis: PRDM9 Diversity, Recombination Landscapes and Childhood Leukaemia by Ihthisham Ali <br>This appendix contains SNP genotyping data from complete SNP genotyping results from studies on DNA3 and AA hotspots, and the childhood ALL study. For recombination hotspot analysis, these data formed the basis of the crossover analysis design. SNP genotyping data from the British ALL cohort was classified by major subtypes and compared with health control groups.<br>A. DNA3 and AA hotspotsB. ALL study