cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.21213401.v1
title: Additional file 2 of Adapting field-mosquito collection techniques in a perspective of near-infrared spectroscopy implementation

description: Additional file 2. Dataset S2.
DOI: 10.6084/m9.figshare.21213401
title: Additional file 2 of Adapting field-mosquito collection techniques in a perspective of near-infrared spectroscopy implementation

description: Additional file 2. Dataset S2.
DOI: 10.6084/m9.figshare.21213441
title: Additional file 1 of MiR-34b/c play a role in early sex differentiation of Amur sturgeon, Acipenser schrenckii

description: Additional file 1: Table S1. Growth performance of Amur sturgeon individuals.
DOI: 10.6084/m9.figshare.21213441.v1
title: Additional file 1 of MiR-34b/c play a role in early sex differentiation of Amur sturgeon, Acipenser schrenckii

description: Additional file 1: Table S1. Growth performance of Amur sturgeon individuals.
DOI: 10.6084/m9.figshare.21213444
title: Additional file 2 of MiR-34b/c play a role in early sex differentiation of Amur sturgeon, Acipenser schrenckii

description: Additional file 2: Table S2. Stem-loop RT primers and amplification primers were used for real-time PCR.
DOI: 10.6084/m9.figshare.21213447
title: Additional file 3 of MiR-34b/c play a role in early sex differentiation of Amur sturgeon, Acipenser schrenckii

description: Additional file 3: Table S3. Germ-cell-specific gene primers used by RT-PCR.
DOI: 10.6084/m9.figshare.21213444.v1
title: Additional file 2 of MiR-34b/c play a role in early sex differentiation of Amur sturgeon, Acipenser schrenckii

description: Additional file 2: Table S2. Stem-loop RT primers and amplification primers were used for real-time PCR.
DOI: 10.6084/m9.figshare.21213447.v1
title: Additional file 3 of MiR-34b/c play a role in early sex differentiation of Amur sturgeon, Acipenser schrenckii

description: Additional file 3: Table S3. Germ-cell-specific gene primers used by RT-PCR.
DOI: 10.6084/m9.figshare.21213453
title: Additional file 4 of MiR-34b/c play a role in early sex differentiation of Amur sturgeon, Acipenser schrenckii

description: Additional file 4: Table S4. Primers information for 3'UTR region of ar containing Xho I and Not I restriction sites.
DOI: 10.6084/m9.figshare.21213453.v1
title: Additional file 4 of MiR-34b/c play a role in early sex differentiation of Amur sturgeon, Acipenser schrenckii

description: Additional file 4: Table S4. Primers information for 3'UTR region of ar containing Xho I and Not I restriction sites.
DOI: 10.6084/m9.figshare.21213492
title: Additional file 3 of Comparative genome analysis unravels pathogenicity of Xanthomonas albilineans causing sugarcane leaf scald disease

description: Additional file 3.
DOI: 10.6084/m9.figshare.21213492.v1
title: Additional file 3 of Comparative genome analysis unravels pathogenicity of Xanthomonas albilineans causing sugarcane leaf scald disease

description: Additional file 3.
DOI: 10.6084/m9.figshare.21213495
title: Additional file 1 of Profile of judicialization in access to antineoplastic drugs and their costs: a cross-sectional, descriptive study based on a set of all lawsuits filed between 2016 and 2018 in a state in the Northeast Region of Brazil

description: Additional file 1. Database.
DOI: 10.6084/m9.figshare.21213495.v1
title: Additional file 1 of Profile of judicialization in access to antineoplastic drugs and their costs: a cross-sectional, descriptive study based on a set of all lawsuits filed between 2016 and 2018 in a state in the Northeast Region of Brazil

description: Additional file 1. Database.
DOI: 10.6084/m9.figshare.21213503
title: Additional file 3 of Efficient compartmentalization in insect bacteriomes protects symbiotic bacteria from host immune system

description: Additional file 3: Table S1. Primer sequences. Table S2. Dual RNA-seq trimming and mapping statistics. Table S3. Count data of S. oryzae genes. Table S4. Differential expression analysis of S. oryzae genes. Table S5. Level of expression of S. pierantonius genes. Table S6. Differential expression of S. pierantonius genes. Table S7. Count data and differential expression analysis of S. pierantonius ISs. Table S8. Highly expressed bacterial genes in all conditions (TPM &gt; 1000) belonging to key biological functions in S. pierantonius. Table S9. Expression levels of genes related to the general stress response in S. pierantonius.
DOI: 10.6084/m9.figshare.21213503.v1
title: Additional file 3 of Efficient compartmentalization in insect bacteriomes protects symbiotic bacteria from host immune system

description: Additional file 3: Table S1. Primer sequences. Table S2. Dual RNA-seq trimming and mapping statistics. Table S3. Count data of S. oryzae genes. Table S4. Differential expression analysis of S. oryzae genes. Table S5. Level of expression of S. pierantonius genes. Table S6. Differential expression of S. pierantonius genes. Table S7. Count data and differential expression analysis of S. pierantonius ISs. Table S8. Highly expressed bacterial genes in all conditions (TPM &gt; 1000) belonging to key biological functions in S. pierantonius. Table S9. Expression levels of genes related to the general stress response in S. pierantonius.
DOI: 10.5281/zenodo.7115096
title: VladislavKaryukin/kk_en_corpora: The Kazakh - English parallel corpora

description: The full corpora of 380 thousand parallel sentences
DOI: 10.5281/zenodo.7115360
title: VladislavKaryukin/kk_en_corpora: The Kazakh - English parallel corpora

description: The full corpora of 380 thousand parallel sentences
DOI: 10.34740/kaggle/ds/2507071
title: Patient Survival Prediction model
DOI: 10.6084/m9.figshare.21213425
title: Additional file 1 of Environmental and maternal factors shaping tonsillar microbiota development in piglets

description: Additional file 1: Table S1. Metadata on the sows included in the study.
DOI: 10.6084/m9.figshare.21213528
title: Additional file 2 of Environmental and maternal factors shaping tonsillar microbiota development in piglets

description: Additional file 2: Table S2. Detailed content of the ingredients used in the different diets used in the study.
DOI: 10.6084/m9.figshare.21213528.v1
title: Additional file 2 of Environmental and maternal factors shaping tonsillar microbiota development in piglets

description: Additional file 2: Table S2. Detailed content of the ingredients used in the different diets used in the study.
DOI: 10.6084/m9.figshare.21213531
title: Additional file 3 of Environmental and maternal factors shaping tonsillar microbiota development in piglets

description: Additional file 3: Table S3. Metadata on the piglets included in the study.
DOI: 10.6084/m9.figshare.21213531.v1
title: Additional file 3 of Environmental and maternal factors shaping tonsillar microbiota development in piglets

description: Additional file 3: Table S3. Metadata on the piglets included in the study.
DOI: 10.6084/m9.figshare.21213534.v1
title: Additional file 4 of Environmental and maternal factors shaping tonsillar microbiota development in piglets

description: Additional file 4: Table S4. Overview of the 1000 most abundant ASVs, their sequence, taxonomy, and abundance at the different timepoints and in adult sows.
DOI: 10.6084/m9.figshare.21213537
title: Additional file 5 of Environmental and maternal factors shaping tonsillar microbiota development in piglets

description: Additional file 5: Table S5. ANOVA results for Shannon, InvSimpson, Chao1, and PD alpha diversity metrics.
DOI: 10.6084/m9.figshare.21213540
title: Additional file 6 of Environmental and maternal factors shaping tonsillar microbiota development in piglets

description: Additional file 6: Table S6. PERMANOVA results for Bray-Curtis, weighted and unweighted UniFrac, and Jaccard beta diversity metrics.
DOI: 10.6084/m9.figshare.21213537.v1
title: Additional file 5 of Environmental and maternal factors shaping tonsillar microbiota development in piglets

description: Additional file 5: Table S5. ANOVA results for Shannon, InvSimpson, Chao1, and PD alpha diversity metrics.
DOI: 10.6084/m9.figshare.21213540.v1
title: Additional file 6 of Environmental and maternal factors shaping tonsillar microbiota development in piglets

description: Additional file 6: Table S6. PERMANOVA results for Bray-Curtis, weighted and unweighted UniFrac, and Jaccard beta diversity metrics.
DOI: 10.6084/m9.figshare.21213534
title: Additional file 4 of Environmental and maternal factors shaping tonsillar microbiota development in piglets

description: Additional file 4: Table S4. Overview of the 1000 most abundant ASVs, their sequence, taxonomy, and abundance at the different timepoints and in adult sows.
DOI: 10.6084/m9.figshare.21213425.v1
title: Additional file 1 of Environmental and maternal factors shaping tonsillar microbiota development in piglets

description: Additional file 1: Table S1. Metadata on the sows included in the study.
DOI: 10.5281/zenodo.7115387
title: Music tracks from Lakh with different instrument bodies

description: The current demo of the dataset contains 10 audio multi-tracks generated with three different sound bodies from the Lakh MIDIs (https://colinraffel.com/projects/lmd/) . The full version contains 3599 tracks. E1.tar.gz The first corpus of 10 multi-tracks E2.tar.gz The second corpus of 10 multi-tracks E3.tar.gz The third corpus of 10 multi-tracks mix1.flac Track 1 from E1 (example) mix2.flac Track 1 from E2 (example) mix3.flac Track 1 from E3 (example)
DOI: 10.5281/zenodo.7115386
title: Music tracks from Lakh with different instrument bodies

description: The current demo of the dataset contains 10 audio multi-tracks generated with three different sound bodies from the Lakh MIDIs (https://colinraffel.com/projects/lmd/) . The full version contains 3599 tracks. E1.tar.gz The first corpus of 10 multi-tracks E2.tar.gz The second corpus of 10 multi-tracks E3.tar.gz The third corpus of 10 multi-tracks mix1.flac Track 1 from E1 (example) mix2.flac Track 1 from E2 (example) mix3.flac Track 1 from E3 (example)
DOI: 10.6084/m9.figshare.19228611.v1
title: Supplementary Material for: Three-dimensional interactive graphical model of the hindlimb muscles of the rat

description: Many questions in human movement sciences are addressed by exploiting the advantages of animal models. However, a 3D model of the musculoskeletal system of the frequently used rat model that includes a sufficient level of detail does not exist. Therefore, the aim of the present work was to develop an freely accessible 3D model of the rat hindlimb. Using the anatomical data of the Wistar rat (Mus norveqicus albinus) published by Green [Greene, 1935], a 3D representation of 34 muscles of the hindlimb was drawn. Two models were created, one using muscle like appearances and one using different colors. Each muscle can be viewed separately or within the context of its synergistic and antagonistic muscles. This model can serve to train new students before starting their experiments, but also for producing illustrations of experimental conditions or results. Further development of the model will be needed to equip it with the same advanced functionalities of some of the human anatomy atlases.
DOI: 10.5281/zenodo.7115464
title: Energy Efficient Portfolio Scheduling for Business-Critical Workloads

description: Results and data needed for reproducing the experiments run in https://github.com/Timovanmilligen/opendc defined in the folder 'opendc-experiments-timo'
DOI: 10.5281/zenodo.7115463
title: Energy Efficient Portfolio Scheduling for Business-Critical Workloads

description: Results and data needed for reproducing the experiments run in https://github.com/Timovanmilligen/opendc defined in the folder 'opendc-experiments-timo'
DOI: 10.5281/zenodo.7115166
title: Spectroscopic ellipsometry mapping of PAAO:Au (AJ-3-04-20-Au sample)

description: Spectroscopic ellipsometry measurement data obtained from the porous anodized aluminum oxide covered with gold nanoparticles (PAAO:Au). The sample was made by anodization of aluminum monocrystal in 0.3 mol/L oxalic acid at 40 V for 4 minutes and 8 seconds. Then it was dip-coated in 60 nm diameter gold nanoparticles suspension. Extraction speed was 500 nm/s. The measurements were carried out at 20 × 20 locations covering all of the sample surface (approximately 4.8 × 4.8 mm<sup>2</sup>). The coordinates of each of 400 locations are available in "mapping_points.csv" file. All measurement data is also included in a single "AJ-3-04-20-Au Ellipsometry Mapping Measurements.rar" file. Ellipsometer: rotating compensator GES5-E (Semilab). Light source: 75 W xenon short arc lamp with 185-2000 nm wavelength spectrum. Detector: UV-Vis CCD with 0.8 nm resolution. Spectral range: approximately 230-960 nm. Light incidence angles: 50°, 55°, 60°, 65°, 70°, 75°. Light beam size: microspot (365 × 470 μm<sup>2</sup> at 75° angle of incidence). The same sample was also measured using the same spectroscopic ellipsometry method before being covered with gold nanoparticles. The data can be found here: https://doi.org/10.5281/zenodo.5718424
description: The research was carried out under postdoctoral project "Patterned hybrid multilayer films for optical sensors", No. 1.1.1.2/VIAA/4/20/615.
DOI: 10.5281/zenodo.7115165
title: Spectroscopic ellipsometry mapping of PAAO:Au (AJ-3-04-20-Au sample)

description: Spectroscopic ellipsometry measurement data obtained from the porous anodized aluminum oxide covered with gold nanoparticles (PAAO:Au). The sample was made by anodization of aluminum monocrystal in 0.3 mol/L oxalic acid at 40 V for 4 minutes and 8 seconds. Then it was dip-coated in 60 nm diameter gold nanoparticles suspension. Extraction speed was 500 nm/s. The measurements were carried out at 20 × 20 locations covering all of the sample surface (approximately 4.8 × 4.8 mm<sup>2</sup>). The coordinates of each of 400 locations are available in "mapping_points.csv" file. All measurement data is also included in a single "AJ-3-04-20-Au Ellipsometry Mapping Measurements.rar" file. Ellipsometer: rotating compensator GES5-E (Semilab). Light source: 75 W xenon short arc lamp with 185-2000 nm wavelength spectrum. Detector: UV-Vis CCD with 0.8 nm resolution. Spectral range: approximately 230-960 nm. Light incidence angles: 50°, 55°, 60°, 65°, 70°, 75°. Light beam size: microspot (365 × 470 μm<sup>2</sup> at 75° angle of incidence). The same sample was also measured using the same spectroscopic ellipsometry method before being covered with gold nanoparticles. The data can be found here: https://doi.org/10.5281/zenodo.5718424
description: The research was carried out under postdoctoral project "Patterned hybrid multilayer films for optical sensors", No. 1.1.1.2/VIAA/4/20/615.
DOI: 10.6084/m9.figshare.21213527
title: Lab data Yuhuan Hu

description: These data belonged to AG Röszer, University of Ulm, Germany. They served as backup and records.
DOI: 10.6084/m9.figshare.21213527.v1
title: Lab data Yuhuan Hu

description: These data belonged to AG Röszer, University of Ulm, Germany. They served as backup and records.
DOI: 10.5281/zenodo.6458266
title: Per-Run Algorithm Selection with Warm-starting using Trajectory-based Features - Data

description: This repository contains the code and data for reproducing the results in the paper 'Per-Run Algorithm Selection with<br> Warm-starting using Trajectory-based Features' The file 'figure_generation.ipnb' contains the code used to create the heatmaps shown in the paper. The file 'Raw_data' contains the raw performance data, for both running A1 and recording all relevant features and for running the switching algorithms for each of the 6 algorithms in the portfolio while recording only performance. The processed version of the A2 data into relative performance is available in 'perf_relative'. The file 'data-collection' contains the code used to run the switching algorithms with the used warmstarting procedures. The file 'compute_features.ipnyb' contains the code used to extract the timeseries features, and those features themselves are included in 'TS_Features'. The file 'AlgorithmSelector' contains the scripts and data used to create the algorithm selector. The files 'selector_5_as_f' and 'selector_ng_f' contain the results of running the final models on the test-instances and nevergrad functions respectively.
DOI: 10.5281/zenodo.6458265
title: Per-Run Algorithm Selection with Warm-starting using Trajectory-based Features - Data

description: This repository contains the code and data for reproducing the results in the paper 'Per-Run Algorithm Selection with<br> Warm-starting using Trajectory-based Features' The file 'figure_generation.ipnb' contains the code used to create the heatmaps shown in the paper. The file 'Raw_data' contains the raw performance data, for both running A1 and recording all relevant features and for running the switching algorithms for each of the 6 algorithms in the portfolio while recording only performance. The processed version of the A2 data into relative performance is available in 'perf_relative'. The file 'data-collection' contains the code used to run the switching algorithms with the used warmstarting procedures. The file 'compute_features.ipnyb' contains the code used to extract the timeseries features, and those features themselves are included in 'TS_Features'. The file 'AlgorithmSelector' contains the scripts and data used to create the algorithm selector. The files 'selector_5_as_f' and 'selector_ng_f' contain the results of running the final models on the test-instances and nevergrad functions respectively.
DOI: 10.6084/m9.figshare.20285808.v1
title: Dataset of Urban Hotels Reviews

description: Data were collected from a hotel reservation website (2,562 reviews extracted from Booking.com)
DOI: 10.57841/casdc.0000022
title: 中国超算任务负载资料库
DOI: 10.6084/m9.figshare.21213572.v1
title: Urine sample measurement

description: These data belonged to AG Röszer, University of Ulm, Germany. They serve as backup and records.
DOI: 10.6084/m9.figshare.21213572
title: Urine sample measurement

description: These data belonged to AG Röszer, University of Ulm, Germany. They serve as backup and records.
DOI: 10.6084/m9.figshare.19228611.v2
title: Supplementary Material for: Three-dimensional interactive graphical model of the hindlimb muscles of the rat

description: Many questions in human movement sciences are addressed by exploiting the advantages of animal models. However, a 3D model of the musculoskeletal system of the frequently used rat model that includes a sufficient level of detail does not exist. Therefore, the aim of the present work was to develop an freely accessible 3D model of the rat hindlimb. Using the anatomical data of the Wistar rat (Mus norveqicus albinus) published by Green [Greene, 1935], a 3D representation of 34 muscles of the hindlimb was drawn. Two models were created, one using muscle like appearances and one using different colors. Each muscle can be viewed separately or within the context of its synergistic and antagonistic muscles. This model can serve to train new students before starting their experiments, but also for producing illustrations of experimental conditions or results. Further development of the model will be needed to equip it with the same advanced functionalities of some of the human anatomy atlases.
DOI: 10.14457/rmutk.doc.2022.1
title: การทำแบบตัดและตัดเย็บชุดไทยพระราชนิยม
DOI: 10.14457/nida.the.2013.1
title: สิทธิของประชาชนในการมีส่วนร่วมในการจัดการทรัพยากรธรรมชาติและสิ่งแวดล้อมตามรัฐธรรมนูญ : ศึกษากรณีการทำเกลือสินเธาว์ในพื้นที่จังหวัดสกลนคร
DOI: 10.5281/zenodo.7104402
title: An analogue based forecasting system for Mediterranean marine litter concentration - Code and simulations dataset

description: This dataset contains the files and codes required to perform the computations described in "An analogue based forecasting system for Mediterranean marine litter concentration" by Gabriel Jordà and Javier Soto-Navarro, to be published in Ocean Science 2022 <strong>Summary</strong> This dataset comprises the files and code necessary to implement a statistical forecasting system for marine litter (ML) concentration in the Mediterranean Sea based on the analogues method. The system uses a historical database of ML concentration simulated by a high resolution realistic model and is trained to identify meteorological situations in the past that are similar to the forecasted ones. Then, the corresponding ML concentrations of the past analog days are used to construct the ML concentration forecast. Due to the scarcity of observations, the forecasting system has been validated against a synthetic reality (i.e. the outputs from a ML modelling system). Different approaches can be tested to refine the system. The analysis of the results show that using integral definitions for the similarity function, based on the history of the meteorological situation, improves the system performance. The system accuracy depends on the region of application being better for larger regions. The method performs well to capture the spatial patterns but performs worse to capture the temporal variability, specially the extreme values. Despite the inherent limitations of using a synthetic reality to validate the system. <strong>Dataset</strong> The dataset is developed in Matlab format, and is comprised by: Matlab files with ML concentration maps derived from the dispersion simulations performed by Soto-Navarro et al. (2020). See the reference for a detailed description of the model and simulations. Matlab files with atmospheric fields from ERA5 dataset (sea level pressure (SLP) and wind speed (U<sub>10</sub>, V<sub>10. </sub>https://climate.copernicus.eu/climate-reanalysis). Matlab files with the grid information for the different regions and sub-regions of the Mediterranean Sea analyzed. Matlab scripts needed for the implementation and running of the analogs based model. A document describing the implementation procedure. <strong>References</strong> Soto-Navarro, J., Jordà, G., Deudero, S., Alomar, C., Amores, Á., and Compa, M.: 3D hotspots of marine litter in the Mediterranean: A modeling study, Mar. Pollut. Bull., 155, 111159, https://doi.org/10.1016/j.marpolbul.2020.111159, 2020.
description: {"references": ["Soto-Navarro, J., Jord\u00e0, G., Deudero, S., Alomar, C., Amores, \u00c1., and Compa, M.: 3D hotspots of marine litter in the Mediterranean: A modeling study, Mar. Pollut. Bull., 155, 111159, https://doi.org/10.1016/j.marpolbul.2020.111159, 2020."]}