cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.21203239
title: Additional file 14 of Comparative analysis of transcriptome remodeling in plaque-associated and plaque-distant microglia during amyloid-β pathology progression in mice

description: Additional file 14: Table S2. List of the samples included in the study.
DOI: 10.6084/m9.figshare.21203239.v1
title: Additional file 14 of Comparative analysis of transcriptome remodeling in plaque-associated and plaque-distant microglia during amyloid-β pathology progression in mice

description: Additional file 14: Table S2. List of the samples included in the study.
DOI: 10.6084/m9.figshare.21203242
title: Additional file 15 of Comparative analysis of transcriptome remodeling in plaque-associated and plaque-distant microglia during amyloid-β pathology progression in mice

description: Additional file 15: Table S3. Expression values for all expressed genes (in pseudocounts), related to Fig. 2.
DOI: 10.6084/m9.figshare.21203242.v1
title: Additional file 15 of Comparative analysis of transcriptome remodeling in plaque-associated and plaque-distant microglia during amyloid-β pathology progression in mice

description: Additional file 15: Table S3. Expression values for all expressed genes (in pseudocounts), related to Fig. 2.
DOI: 10.6084/m9.figshare.21203245
title: Additional file 16 of Comparative analysis of transcriptome remodeling in plaque-associated and plaque-distant microglia during amyloid-β pathology progression in mice

description: Additional file 16: Table S4. Fold-change of typical microglial homeostatic genes in XO4+; DAM; ARM; MGnD and PAMs (NS: non significant; −: not reported).
DOI: 10.6084/m9.figshare.21203245.v1
title: Additional file 16 of Comparative analysis of transcriptome remodeling in plaque-associated and plaque-distant microglia during amyloid-β pathology progression in mice

description: Additional file 16: Table S4. Fold-change of typical microglial homeostatic genes in XO4+; DAM; ARM; MGnD and PAMs (NS: non significant; −: not reported).
DOI: 10.6084/m9.figshare.21203248
title: Additional file 17 of Comparative analysis of transcriptome remodeling in plaque-associated and plaque-distant microglia during amyloid-β pathology progression in mice

description: Additional file 17: Table S5. Differentially expressed genes in PAM vs CM, related to Fig. 2. Ta ble S5B: GO analysis of the PAM vs CM DEGs Turquoise module, related to Fig. 2C. Table S5C: GO analysis of the PAM vs CM DEGs Blue module, related to Fig. 2D.
DOI: 10.6084/m9.figshare.21203248.v1
title: Additional file 17 of Comparative analysis of transcriptome remodeling in plaque-associated and plaque-distant microglia during amyloid-β pathology progression in mice

description: Additional file 17: Table S5. Differentially expressed genes in PAM vs CM, related to Fig. 2. Ta ble S5B: GO analysis of the PAM vs CM DEGs Turquoise module, related to Fig. 2C. Table S5C: GO analysis of the PAM vs CM DEGs Blue module, related to Fig. 2D.
DOI: 10.6084/m9.figshare.21203251
title: Additional file 18 of Comparative analysis of transcriptome remodeling in plaque-associated and plaque-distant microglia during amyloid-β pathology progression in mice

description: Additional file 18: Table S6. PAM vs CM, Genes networks and subnetworks (highlighted in green: hub genes).
DOI: 10.6084/m9.figshare.21203251.v1
title: Additional file 18 of Comparative analysis of transcriptome remodeling in plaque-associated and plaque-distant microglia during amyloid-β pathology progression in mice

description: Additional file 18: Table S6. PAM vs CM, Genes networks and subnetworks (highlighted in green: hub genes).
DOI: 10.6084/m9.figshare.21203254
title: Additional file 19 of Comparative analysis of transcriptome remodeling in plaque-associated and plaque-distant microglia during amyloid-β pathology progression in mice

description: Additional file 19: Table S7. A. Differentially expressed genes in PCM vs CM, related to Fig. 3. Table S7B: GO analysis of the PCM vs CM DEGs, related to Fig. 3C.
DOI: 10.6084/m9.figshare.21203254.v1
title: Additional file 19 of Comparative analysis of transcriptome remodeling in plaque-associated and plaque-distant microglia during amyloid-β pathology progression in mice

description: Additional file 19: Table S7. A. Differentially expressed genes in PCM vs CM, related to Fig. 3. Table S7B: GO analysis of the PCM vs CM DEGs, related to Fig. 3C.
DOI: 10.6084/m9.figshare.21203260
title: Additional file 20 of Comparative analysis of transcriptome remodeling in plaque-associated and plaque-distant microglia during amyloid-β pathology progression in mice

description: Additional file 20: Table S8. A: Differentially expressed genes in PAM vs PCM, related to Fig. 4A. Table S8B: GO analysis of the PAM vs PCM DEGs Turquoise module, related to Fig. 4C.
DOI: 10.6084/m9.figshare.21203260.v1
title: Additional file 20 of Comparative analysis of transcriptome remodeling in plaque-associated and plaque-distant microglia during amyloid-β pathology progression in mice

description: Additional file 20: Table S8. A: Differentially expressed genes in PAM vs PCM, related to Fig. 4A. Table S8B: GO analysis of the PAM vs PCM DEGs Turquoise module, related to Fig. 4C.
DOI: 10.6084/m9.figshare.21203263
title: Additional file 21 of Comparative analysis of transcriptome remodeling in plaque-associated and plaque-distant microglia during amyloid-β pathology progression in mice

description: Additional file 21: Table S9. Differentially expressed genes in PCM vs CM excluding DEGs in PAM vs CM, related to Fig. 4D. Table S9B: Differentially expressed genes in PAM vs PCM excluding DEGs in PAM vs CM, related to Fig. 4D.
DOI: 10.6084/m9.figshare.21203263.v1
title: Additional file 21 of Comparative analysis of transcriptome remodeling in plaque-associated and plaque-distant microglia during amyloid-β pathology progression in mice

description: Additional file 21: Table S9. Differentially expressed genes in PCM vs CM excluding DEGs in PAM vs CM, related to Fig. 4D. Table S9B: Differentially expressed genes in PAM vs PCM excluding DEGs in PAM vs CM, related to Fig. 4D.
DOI: 10.6084/m9.figshare.21203266.v1
title: Additional file 22 of Comparative analysis of transcriptome remodeling in plaque-associated and plaque-distant microglia during amyloid-β pathology progression in mice

description: Additional file 22: Table S10. GO analysis of the PAM vs CM:Age DEGs Turquoise module, related to Figure S7B, C.
DOI: 10.6084/m9.figshare.21203266
title: Additional file 22 of Comparative analysis of transcriptome remodeling in plaque-associated and plaque-distant microglia during amyloid-β pathology progression in mice

description: Additional file 22: Table S10. GO analysis of the PAM vs CM:Age DEGs Turquoise module, related to Figure S7B, C.
DOI: 10.6084/m9.figshare.21203269
title: Additional file 23 of Comparative analysis of transcriptome remodeling in plaque-associated and plaque-distant microglia during amyloid-β pathology progression in mice

description: Additional file 23: Table S11. Human postmortem samples used in the study (Highlighted in grey, samples processed for RNAscope)
DOI: 10.6084/m9.figshare.21203269.v1
title: Additional file 23 of Comparative analysis of transcriptome remodeling in plaque-associated and plaque-distant microglia during amyloid-β pathology progression in mice

description: Additional file 23: Table S11. Human postmortem samples used in the study (Highlighted in grey, samples processed for RNAscope)
DOI: 10.6084/m9.figshare.21203355
title: Additional file 2 of A global overview of healthcare workers’ turnover intention amid COVID-19 pandemic: a systematic review with future directions

description: Additional file 2. Quality appraisal of included studies.
DOI: 10.6084/m9.figshare.21203355.v1
title: Additional file 2 of A global overview of healthcare workers’ turnover intention amid COVID-19 pandemic: a systematic review with future directions

description: Additional file 2. Quality appraisal of included studies.
DOI: 10.6084/m9.figshare.21203401.v1
title: Additional file 2 of Computer grading of lung disease severity in patients with lymphangioleiomyomatosis referred for transplantation

description: Additional file 2. Comparison of Clinical, Functional, and Cyst Score (%) between Patients referred for Lung Transplantation (n=41).
DOI: 10.6084/m9.figshare.21203401
title: Additional file 2 of Computer grading of lung disease severity in patients with lymphangioleiomyomatosis referred for transplantation

description: Additional file 2. Comparison of Clinical, Functional, and Cyst Score (%) between Patients referred for Lung Transplantation (n=41).
DOI: 10.5281/zenodo.7109184
title: Decoding the metabolic response of Escherichia coli for sensing trace heavy metals in water

description: As: Raman spectra from E. coli lysate sample after exposing to As in DI water Cr: Raman spectra from E. coli lysate sample after exposing to Cr in DI water As_TapWater: Raman spectra from E. coli lysate sample after exposing to As in tap water WasteWater_FineTune_Dataset: Raman spectra from E. coli lysate sample after exposing to As in waste water WasteWater 'Unknow' Dataset: Raman spectra from E. coli lysate sample after exposing to waste water
DOI: 10.5281/zenodo.7109183
title: Decoding the metabolic response of Escherichia coli for sensing trace heavy metals in water

description: As: Raman spectra from E. coli lysate sample after exposing to As in DI water Cr: Raman spectra from E. coli lysate sample after exposing to Cr in DI water As_TapWater: Raman spectra from E. coli lysate sample after exposing to As in tap water WasteWater_FineTune_Dataset: Raman spectra from E. coli lysate sample after exposing to As in waste water WasteWater 'Unknow' Dataset: Raman spectra from E. coli lysate sample after exposing to waste water
DOI: 10.6084/m9.figshare.21203411
title: Tabular regression

description: tabular regression
DOI: 10.6084/m9.figshare.21203411.v1
title: Tabular regression

description: tabular regression
DOI: 10.6084/m9.figshare.19424699
title: Supplemental File 1.xlsx

description: Whole-genome allelic expression patterns in 749 sweet orange transcriptomes
DOI: 10.6084/m9.figshare.19424699.v1
title: Supplemental File 1.txt

description: Whole-genome allelic expression patterns in 740 sweet orange transcriptomes
DOI: 10.5519/qd.zlpf36m0
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (127 records)
DOI: 10.34820/fk2/zjd8bj/9lzzoa
title: tabeldatasiswasekolah.sql

description: :unav
DOI: 10.34820/fk2/zjd8bj
title: School admission dataset

description: Dataset regarding school admission system
DOI: 10.5281/zenodo.7086410
title: Breathing Rate and Heart Rate Dataset using Integrated mmWave FMCW Radar and Camera Steering System

description: The presented dataset consists of raw and transformed CWT images of the breathing and heart waveforms obtained from a radar<br> and IP camera setup. The setup is a self-proposed setup with a mmWave radar mounted over an IP camera and can capture<br> the breathing and heart waveforms of the person in the room in front of the system in any orientation. The dataset can be used to estimate the vital signs using any machine learning model and important information about the respiration rate and pulse rate<br> can then be obtained. The dataset is a total of 1280 images- 720 raw and 720 processed. The processed dataset is labeled in six different classes. The first bifurcation is between breath and heart, breath signal is classified as low, normal, and high whereas the heart signal is classified as low, normal, and slightly low. The subject is oriented in differently so that the setup can steer towards the person and capture the breath and heart signals accordingly.
DOI: 10.5281/zenodo.7086409
title: Breathing Rate and Heart Rate Dataset using Integrated mmWave FMCW Radar and Camera Steering System

description: The presented dataset consists of raw and transformed CWT images of the breathing and heart waveforms obtained from a radar<br> and IP camera setup. The setup is a self-proposed setup with a mmWave radar mounted over an IP camera and can capture<br> the breathing and heart waveforms of the person in the room in front of the system in any orientation. The dataset can be used to estimate the vital signs using any machine learning model and important information about the respiration rate and pulse rate<br> can then be obtained. The dataset is a total of 1280 images- 720 raw and 720 processed. The processed dataset is labeled in six different classes. The first bifurcation is between breath and heart, breath signal is classified as low, normal, and high whereas the heart signal is classified as low, normal, and slightly low. The subject is oriented in differently so that the setup can steer towards the person and capture the breath and heart signals accordingly.
DOI: 10.34820/fk2/qbtmwu/vjadpp
title: tabeldatataksivehicle.sql

description: vehicle dataset
DOI: 10.34820/fk2/qbtmwu/rls7pe
title: tabeldatataksicustomer.sql

description: customer dataset
DOI: 10.34820/fk2/qbtmwu
title: Dataset for Dispatching Model in Online Taxi System by Using Stable Marriage and First Price Sealed Bid Auction Models

description: This dataset is dataset for research regarding the dispatching model of the online taxi system.
DOI: 10.21227/zfb7-5e19
title: Expected Bitcoin Transaction Efficiency Under Dilithium and ECDSA

description: Calculations to compute the expected Bitcoin transaction efficiency (measured in transactions per block) using CRYSTALS-Dilithium vs using Elliptic Curve Digital Signature Algorithm (ECDSA).
DOI: 10.6084/m9.figshare.21203807
title: MnSi_manuscript_data_code

description: Data used for plotting main-text figures for manuscript entitled "Magnetic molecular orbitals in MnSi" <br>
DOI: 10.34820/fk2/nlvny4/do6gc2
title: IMFI_2022_03_Salim (1).pdf

description: :unav
DOI: 10.34820/fk2/nlvny4
title: Smart beta portfolio investment strategy during the COVID-19 pandemic in Indonesia

description: https://www.businessperspectives.org/index.php/journals/investment-management-and-financial-innovations/issue-413/smart-beta-portfolio-investment-strategy-during-the-covid-19-pandemic-in-indonesia
DOI: 10.5281/zenodo.7111282
title: Profile data of the ADMIRE project use case applications

description: HPC application traces from the use cases in the ADMIRE project. They were collected with TAU monitoring tools. Applications traced are described at: https://www.admire-eurohpc.eu/UseCases/ - <em>Application 1: Monitoring and Modelling Marine, weather and Air quality </em> - <em>Application 2: Car-Parrinello molecular dynamic simulation of large molecules and small proteins </em> <em>- Application 3: Simulation of large scale turbulent flow.</em> <em>- Application 4: Continental-scale land cover mapping with scalable and automatic deep learning frameworks.</em> <em>- Application 5: Super-resolution imaging using Opera microscopy and SRRF/ImageJ software. </em> <em>- Application 6: Software Heritage Management & Indexing.</em>
DOI: 10.5281/zenodo.7111281
title: Profile data of the ADMIRE project use case applications

description: HPC application traces from the use cases in the ADMIRE project. They were collected with TAU monitoring tools. Applications traced are described at: https://www.admire-eurohpc.eu/UseCases/ - <em>Application 1: Monitoring and Modelling Marine, weather and Air quality </em> - <em>Application 2: Car-Parrinello molecular dynamic simulation of large molecules and small proteins </em> <em>- Application 3: Simulation of large scale turbulent flow.</em> <em>- Application 4: Continental-scale land cover mapping with scalable and automatic deep learning frameworks.</em> <em>- Application 5: Super-resolution imaging using Opera microscopy and SRRF/ImageJ software. </em> <em>- Application 6: Software Heritage Management & Indexing.</em>
DOI: 10.5281/zenodo.7039937
title: JSV1 VCF

description: JSV1, a structural variation panel utilizing long-read sequencing technology of 333 individuals composing 111 trios.
DOI: 10.5281/zenodo.7039938
title: JSV1 VCF

description: JSV1, a structural variation panel utilizing long-read sequencing technology of 333 individuals composing 111 trios.
DOI: 10.34820/fk2/5hfi08/65sso6
title: 822-Article-4979-3-10-20220605.pdf

description: :unav
DOI: 10.34820/fk2/5hfi08
title: A STOCK PORTFOLIO STRATEGY IN THE MIDST OF THE COVID-19: CASE OF INDONESIA

description: https://ieeca.org/journal/index.php/JEECAR/article/view/822
DOI: 10.5281/zenodo.7039927
title: JSV1-paper-dataset

description: Datasets and software for "Construction of a trio-based structural variation panel utilizing activated T lymphocytes and long-read sequencing technologyConstruction of a trio-based structural variation panel utilizing activated T lymphocytes and long-read sequencing technology" Otsuki, Okamura, et al.
DOI: 10.5281/zenodo.7039928
title: JSV1-paper-dataset

description: Datasets and software for "Construction of a trio-based structural variation panel utilizing activated T lymphocytes and long-read sequencing technologyConstruction of a trio-based structural variation panel utilizing activated T lymphocytes and long-read sequencing technology" Otsuki, Okamura, et al.
DOI: 10.5281/zenodo.7039977
title: JSV1-paper-dataset

description: Datasets and software for "Construction of a trio-based structural variation panel utilizing activated T lymphocytes and long-read sequencing technologyConstruction of a trio-based structural variation panel utilizing activated T lymphocytes and long-read sequencing technology" Otsuki, Okamura, et al.
DOI: 10.5281/zenodo.7049276
title: JSV1-paper-dataset

description: Datasets and software for "Construction of a trio-based structural variation panel utilizing activated T lymphocytes and long-read sequencing technologyConstruction of a trio-based structural variation panel utilizing activated T lymphocytes and long-read sequencing technology" Otsuki, Okamura, et al.
DOI: 10.5445/ir/1000150821
title: Surfaced and suspended plastic: Cup_PP_98_def_V5 (videos)
DOI: 10.5281/zenodo.6792917
title: soil nutrient balance(NPK) dataset of Rwanda

description: This soil nutrient balance dataset contains raw, processed and analyzed data of soil nutrient depletion workflow developed by Uwiragiye et al.[1]. Soil nutrient (NPK) balance were predicted only in covers cropland of Rwanda (Fig.1). This dataset was developed from freely available data from different sources (Table 1). The main folder which contain all data is called ’’Data”. This main folder has five sub folders (soil nutrient flows, soil erosion and sediments, environmental covariates, NPK balance modelling results and code used for soil nutrient balance modelling) This is a dataset developed from available data for soil nutrient modelling in humid areas : A published paper Y. Uwiragiye, M. Junior Yannick Ngaba, M. Zhao, A.S. Elrys, G.B.M. Heuvelink, J. Zhou, Modelling and mapping soil nutrient depletion in humid highlands of East Africa using ensemble machine learning: A case study from Rwanda, CATENA. 217 (2022) 106499. https://doi.org/https://doi.org/10.1016/j.catena.2022.106499.
DOI: 10.5281/zenodo.6792918
title: soil nutrient depletion dataset of Rwanda

description: This is a dataset developed from available data for soil nutrient modelling in humid areas : a case study from Rwanda. A paper was published in CATENA https://doi.org/10.1016/j.catena.2022.106499
DOI: 10.5281/zenodo.7112371
title: soil nutrient balance(NPK) dataset of Rwanda

description: This soil nutrient balance dataset contains raw, processed and analyzed data of soil nutrient depletion workflow developed by Uwiragiye et al.[1]. Soil nutrient (NPK) balance were predicted only in covers cropland of Rwanda (Fig.1). This dataset was developed from freely available data from different sources (Table 1). The main folder which contain all data is called ’’Data”. This main folder has five sub folders (soil nutrient flows, soil erosion and sediments, environmental covariates, NPK balance modelling results and code used for soil nutrient balance modelling) This is a dataset developed from available data for soil nutrient modelling in humid areas : A published paper Y. Uwiragiye, M. Junior Yannick Ngaba, M. Zhao, A.S. Elrys, G.B.M. Heuvelink, J. Zhou, Modelling and mapping soil nutrient depletion in humid highlands of East Africa using ensemble machine learning: A case study from Rwanda, CATENA. 217 (2022) 106499. https://doi.org/https://doi.org/10.1016/j.catena.2022.106499.
DOI: 10.6084/m9.figshare.21202193
title: Supplementary files.zip

description: Supplementary files for DDQR Supplementary file 1: FASTA sequence for marker rbcL.<br> Supplementary file 2: FASTA sequence for marker matK.<br> Supplementary file 3: FASTA sequence for marker psbA-trnH.<br> Supplementary file 4: FASTA sequence for marker ITS2.<br> Supplementary file 5: FASTA sequence for marker COI.<br> Supplementary file 6: source code for DDQR and GeCo3 compression rate calculation.<br> Supplementary file 7: source code for DDQR compression rate calculation using simulated data.<br> Supplementary file 8: source code for GeCo3 compression rate calculation using simulated data.<br> Supplementary file 9: source code for DDQR compression rate calculation using real data.<br> Supplementary file 10: source code for GeCo3 compression rate calculation using real data.
DOI: 10.6084/m9.figshare.21203423.v1
title: The impact of absorptive capacity on the FDI-growth relationship

description: This dataset contains information on 78 underdeveloped and developing economies for the period 2000 to 2018.
DOI: 10.6084/m9.figshare.21203423
title: The impact of absorptive capacity on the FDI-growth relationship

description: This dataset contains information on 78 underdeveloped and developing economies for the period 2000 to 2018.
DOI: 10.5519/qd.e4hn64vu
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (23719 records)
DOI: 10.6084/m9.figshare.21204758
title: Data Citation 3.docx

description: Comparison of different analysis programs to measure the thickness of GO flakes.
DOI: 10.6084/m9.figshare.21204758.v1
title: Data Citation 3.docx

description: Comparison of different analysis programs to measure the thickness of GO flakes.
DOI: 10.6084/m9.figshare.20726392.v1
title: Incidence, risk and impact of unplanned ICU readmission on patient outcomes and resource utilisation in tertiary level ICUs in Nepal.

description: The study assesses the determinants of risk attributable to unplanned ICU readmission in four ICUs in Kathmandu, Nepal. Despite growing literature on this topic, most of the evidence on incidence, characteristics, associated risk factors and attributable outcomes of unplanned readmission to ICU are from studies performed in high-income countries. In this study, the registry-embedded eCRF reported data on case mix, severity of illness, in-ICU interventions (including organ support), ICU outcome, and readmission characteristics. Data were captured in all adult patients admitted between September 2019 and February 2021. Population and ICU encounter characteristics were compared between those with and without readmission. Independent risk factors for readmission were assessed using univariate analysis. Unplanned ICU readmission rates were adversely associated with significantly poorer outcomes, increased ICU resource utilisation. Clinical and organisational characteristics influenced risk of readmission and outcome.