cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.22297645
title: Supporting data: Microscopy images of FITC labeled G12 and no inhibitor control in cells, repeat 2.

description: Supporting data: Microscopy images of FITC labeled G12 and no inhibitor control in cells, repeat 2.
DOI: 10.5281/zenodo.7747411
title: Tetiaroa Vegetation Sampling

description: Measurement of seedling recruitment for four native woody species, the shade cover of four herbaceous plant species, and coconuts on the Motu Ahuroa in Tetiaroa were conducted by students with the UC Berkeley Island Sustainability Program. The four woody species we observed were Pisonia, Pandanus, Guettarda, and Ipomoea. For the herbaceous species, we observed Asplenium, Boerhavia, Microsorum, and Portulaca. Once we completed our data collection in each transect, we compiled our data to see the effect of rat eradication programs on plant growth.
DOI: 10.5281/zenodo.7747412
title: Tetiaroa Vegetation Sampling

description: Measurement of seedling recruitment for four native woody species, the shade cover of four herbaceous plant species, and coconuts on the Motu Ahuroa in Tetiaroa were conducted by students with the UC Berkeley Island Sustainability Program. The four woody species we observed were Pisonia, Pandanus, Guettarda, and Ipomoea. For the herbaceous species, we observed Asplenium, Boerhavia, Microsorum, and Portulaca. Once we completed our data collection in each transect, we compiled our data to see the effect of rat eradication programs on plant growth.
DOI: 10.5281/zenodo.7747226
title: Boats Coastal Monitoring 2023

description: Types and quantities of boats and marine vessels observed along the Mo'orea coastline on February 20, 2023, collected and organized by timestamp and including data on a group, observer, type of fishing vessel, number of fishers, and if vessel is navigating or anchoring.
DOI: 10.5281/zenodo.7747424
title: SEM EDS data for sediments in a crude oil contaminated aquifer

description: Mineralogic classification and weight percent data for Fe, O, C, Co, Ni, Ba, and Sr from sediments in a crude oil-contaminated aquifer near Bemidji, Minnesota.
DOI: 10.5281/zenodo.7747423
title: SEM EDS data for sediments in a crude oil contaminated aquifer

description: Mineralogic classification and weight percent data for Fe, O, C, Co, Ni, Ba, and Sr from sediments in a crude oil-contaminated aquifer near Bemidji, Minnesota.
DOI: 10.6084/m9.figshare.13227506
title: Comparative study of dietary fat: lard and sugar as a better obesity and metabolic syndrome mice model

description: Diet macronutrient heterogeneity hinders animal studies’ data extrapolation from metabolic disorders to human diseases. The present study aimed to evaluate different fat-diet compositions’ effect on inducing lipid/glucose metabolism alterations in mice. Swiss male mice were fed for 12 weeks with five different diets: Standard Diet (ST), American Institute of Nutrition 93 for growth (AIN93G) high-butter/high-sugar (HBHS), high-lard/high-sugar (HLHS), and high-oil/high-sugar diet (soybean oil) (HOHS). Several parameters, such as serum biochemistry, histology, and liver mRNA expression, were accessed. The main findings revealed that the HLHS diet dramatically altered liver metabolism inducing hepatic steatosis and increased total cholesterol, triglycerides, VLDL, increasing liver CCAAT/enhancer binding protein (CEBP-α), Acetyl-CoA carboxylase (ACC) and Catalase (CAT) mRNA expression. Moreover, the HLHS diet increased glucose intolerance and reduced insulin sensitivity. High-fat/high-sugar diets are efficient to induce obesity and metabolic syndrome-associated alterations, and diets enriched with lard and sugar showed more effective results.
DOI: 10.6084/m9.figshare.13227506.v1
title: Comparative study of dietary fat: lard and sugar as a better obesity and metabolic syndrome mice model

description: Diet macronutrient heterogeneity hinders animal studies’ data extrapolation from metabolic disorders to human diseases. The present study aimed to evaluate different fat-diet compositions’ effect on inducing lipid/glucose metabolism alterations in mice. Swiss male mice were fed for 12 weeks with five different diets: Standard Diet (ST), American Institute of Nutrition 93 for growth (AIN93G) high-butter/high-sugar (HBHS), high-lard/high-sugar (HLHS), and high-oil/high-sugar diet (soybean oil) (HOHS). Several parameters, such as serum biochemistry, histology, and liver mRNA expression, were accessed. The main findings revealed that the HLHS diet dramatically altered liver metabolism inducing hepatic steatosis and increased total cholesterol, triglycerides, VLDL, increasing liver CCAAT/enhancer binding protein (CEBP-α), Acetyl-CoA carboxylase (ACC) and Catalase (CAT) mRNA expression. Moreover, the HLHS diet increased glucose intolerance and reduced insulin sensitivity. High-fat/high-sugar diets are efficient to induce obesity and metabolic syndrome-associated alterations, and diets enriched with lard and sugar showed more effective results.
DOI: 10.6084/m9.figshare.22255873.v2
title: Labeled 17 Hardwood Species and 55 Genotypes of Populus Stomatal Images Datasets

description: Research has indicated the potential of using machine learning algorithms to detect and measure stomata automatically. However, the current limitation for further improving and fine-tuning machine learning-based stomatal study methods is due to the small, inconsistent, and monotypic nature of stomatal datasets, which are also not easily accessible. To address this issue, our collection comprises more than 11,000 unique images of hardwood leaf stomata gathered from projects conducted between 2015 and 2020-2022. The dataset includes over 7,000 images of 17 frequently encountered hardwood species, including oak, maple, ash, elm, and hickory, as well as over 3,000 images of 55 genotypes from seven Populus taxa (as detailed in Table 1). Each image has been labeled as either stomata (stomatal aperture only) or whole_stomata (stomatal aperture and guard cells) and has a corresponding YOLO label file that can be transformed to other annotation formats. These images and labels are publicly available, making it easier to train machine-learning models and examine leaf stomatal traits. By utilizing our dataset, users can (1) use state-of-the-art machine learning models to identify, count, and quantify leaf stomata; (2) investigate the diverse range of stomatal characteristics across different types of hardwood trees; and (3) create new indices for measuring stomata.
DOI: 10.6084/m9.figshare.22297213
title: Supporting data: EM micrographs of LCD+S2 vRNA Experiment_2, LCD:S2 1:1 molar ratio

description: Supporting data: EM micrographs of LCD+S2 vRNA Experiment_2, LCD:S2 1:1 molar ratio
DOI: 10.6084/m9.figshare.22297213.v2
title: Supporting data: EM micrographs of LCD+S2 vRNA Experiment_2, LCD:S2 1:1 molar ratio

description: Supporting data: EM micrographs of LCD+S2 vRNA Experiment_2, LCD:S2 1:1 molar ratio
DOI: 10.6084/m9.figshare.22297213.v1
title: Supportive data: EM micrographs of LCD+S2 vRNA Experiment_2, LCD:S2 1:1 molar ratio

description: Supportive data: EM micrographs of LCD+S2 vRNA Experiment_2, LCD:S2 1:1 molar ratio
DOI: 10.5517/ccdc.csd.cc2938zp
title: CCDC 2118322: Experimental Crystal Structure Determination

description: Related Article: Zhongqiu Zhao, Shuo Yang, Mingchang Zhu, Ying Zhang, Yaguang Sun, Shuangyan Wu|2023|Sens.Actuators,B|383|133593|doi:10.1016/j.snb.2023.133593
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc29390r
title: CCDC 2118323: Experimental Crystal Structure Determination

description: Related Article: Zhongqiu Zhao, Shuo Yang, Mingchang Zhu, Ying Zhang, Yaguang Sun, Shuangyan Wu|2023|Sens.Actuators,B|383|133593|doi:10.1016/j.snb.2023.133593
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.22256200
title: central nervous system infection of enterobacteriaceae

description: Enterobacteriaceae bacterial strains in central nervous system infections after craniocerebral surgery
DOI: 10.6084/m9.figshare.22256200.v2
title: central nervous system infection of enterobacteriaceae

description: Enterobacteriaceae bacterial strains in central nervous system infections after craniocerebral surgery
DOI: 10.6084/m9.figshare.22256200.v1
title: NS16.fasta

description: Enterobacteriaceae bacterial strains in central nervous system infections after craniocerebral surgery
DOI: 10.5281/zenodo.7747456
title: Supplementary Table S1 and Supplementary Table S2 - Part of "Next generation leishmanization: revisiting molecular targets for selecting genetically engineered live-attenuated Leishmania"

description: Supplementary Table S1 and Supplementary Table S2 - Part of "Next generation leishmanization: revisiting molecular targets for selecting genetically engineered live-attenuated Leishmania"
DOI: 10.5281/zenodo.7747455
title: Supplementary Table S1 and Supplementary Table S2 - Part of "Next generation leishmanization: revisiting molecular targets for selecting genetically engineered live-attenuated Leishmania"

description: Supplementary Table S1 and Supplementary Table S2 - Part of "Next generation leishmanization: revisiting molecular targets for selecting genetically engineered live-attenuated Leishmania"
DOI: 10.6084/m9.figshare.22297702
title: Microscopy images of G12 in SARS -CoV-2 infected cells. Full antiviral dose-response and single dose-response. Used for analysis in Figures 5d and Supplementary Figure 8.

description: Microscopy images of G12 in SARS -CoV-2 infected cells. Full antiviral dose-response and single dose-response. Used for analysis in Figures 5d and Supplementary Figure 8.
DOI: 10.6084/m9.figshare.22297702.v1
title: Microscopy images of G12 in SARS -CoV-2 infected cells. Full antiviral dose-response and single dose-response. Used for analysis in Figures 5d and Supplementary Figure 8.

description: Microscopy images of G12 in SARS -CoV-2 infected cells. Full antiviral dose-response and single dose-response. Used for analysis in Figures 5d and Supplementary Figure 8.
DOI: 10.6084/m9.figshare.22297729
title: X-ray fiber diffraction source files. Collected on fibers of LCD only, LCD+S2hp vRNA and LCD+non-specific RNA. Used in Figure 2a.

description: X-ray fiber diffraction source files. Collected on fibers of LCD only, LCD+S2hp vRNA and LCD+non-specific RNA. Used in Figure 2a.
DOI: 10.6084/m9.figshare.22297729.v1
title: X-ray fiber diffraction source files. Collected on fibers of LCD only, LCD+S2hp vRNA and LCD+non-specific RNA. Used in Figure 2a.

description: X-ray fiber diffraction source files. Collected on fibers of LCD only, LCD+S2hp vRNA and LCD+non-specific RNA. Used in Figure 2a.
DOI: 10.6084/m9.figshare.22297735
title: A Novel collaborative electric location routing problem with battery-swapping stations considering range anxiety

description: This is the experimental data of the manuscript entitled “A novel collaborative electric location routing problem with battery-swapping stations considering range anxiety”. Problem sets A, B and P are modified from a classical capacitated vehicle routing problem dataset which was proposed by Augerat according to the characteristics of this study. Problem set C is generated by computation simulation.In each data set, the maximum distance and maximum weight of the electric vehicles, the number and coordinates of the depots, the coordinates and demands of the customers and the coordinates of the alternative battery-swapping stations are given.
DOI: 10.6084/m9.figshare.22297735.v1
title: A Novel collaborative electric location routing problem with battery-swapping stations considering range anxiety

description: This is the experimental data of the manuscript entitled “A novel collaborative electric location routing problem with battery-swapping stations considering range anxiety”. Problem sets A, B and P are modified from a classical capacitated vehicle routing problem dataset which was proposed by Augerat according to the characteristics of this study. Problem set C is generated by computation simulation.In each data set, the maximum distance and maximum weight of the electric vehicles, the number and coordinates of the depots, the coordinates and demands of the customers and the coordinates of the alternative battery-swapping stations are given.
DOI: 10.6084/m9.figshare.22297741
title: A Novel collaborative electric location routing problem with battery-swapping stations considering range anxiety

description: This is the experimental data of the manuscript entitled “A novel collaborative electric location routing problem with battery-swapping stations considering range anxiety”. Problem sets A, B and P are modified from a classical capacitated vehicle routing problem dataset which was proposed by Augerat according to the characteristics of this study. Problem set C is generated by computation simulation.In each data set, the maximum distance and maximum weight of the electric vehicles, the number and coordinates of the depots, the coordinates and demands of the customers and the coordinates of the alternative battery-swapping stations are given.
DOI: 10.6084/m9.figshare.22297741.v1
title: A Novel collaborative electric location routing problem with battery-swapping stations considering range anxiety

description: This is the experimental data of the manuscript entitled “A novel collaborative electric location routing problem with battery-swapping stations considering range anxiety”. Problem sets A, B and P are modified from a classical capacitated vehicle routing problem dataset which was proposed by Augerat according to the characteristics of this study. Problem set C is generated by computation simulation.In each data set, the maximum distance and maximum weight of the electric vehicles, the number and coordinates of the depots, the coordinates and demands of the customers and the coordinates of the alternative battery-swapping stations are given.
DOI: 10.6084/m9.figshare.22297717
title: Inverse of Rensch’s rule of allometry for sexual size dimorphism in Bufo andrewsi

description: Difference in body size between males and females (sexual size dimorphism: SSD) and its variation are a common phenomenon in animal kingdom. Rensch’s rule predicts that the degree of SSD variation increases with the enlarged mean body size when males are larger than females and decreases when females are larger than males. Here, whether the patterns of variations in SSD in the Andrew’s toad (<em>Bufo andrewsi</em>) follow Rensch’s rule was tested using unpublished data from 14 populations and published data from 17 populations. Results show the reduced major axis regression of log<sub>10</sub> (male size) on log<sub>10</sub> (female size) across all populations displayed a significant hyperallometric relationship, which was consistent with inverse Rensch’s rule (the degree of SSD increased with enlarged mean body size). SSD could also be explained by sexual age difference (SAD) due to a positive SSD–SAD relationship among all populations. The findings suggest that the occurrence of inverse Rensch’s rule in <em>B. andrewsi</em> is likely to be a result of fecundity selection on increased reproductive investments in larger females. This table is descriptive information about the study sites of Andrew’s toad (<em>B. andrewsi</em>), together with mean (± SD) body size and age of males and females.
DOI: 10.6084/m9.figshare.22297717.v1
title: Inverse of Rensch’s rule of allometry for sexual size dimorphism in Bufo andrewsi

description: Difference in body size between males and females (sexual size dimorphism: SSD) and its variation are a common phenomenon in animal kingdom. Rensch’s rule predicts that the degree of SSD variation increases with the enlarged mean body size when males are larger than females and decreases when females are larger than males. Here, whether the patterns of variations in SSD in the Andrew’s toad (<em>Bufo andrewsi</em>) follow Rensch’s rule was tested using unpublished data from 14 populations and published data from 17 populations. Results show the reduced major axis regression of log<sub>10</sub> (male size) on log<sub>10</sub> (female size) across all populations displayed a significant hyperallometric relationship, which was consistent with inverse Rensch’s rule (the degree of SSD increased with enlarged mean body size). SSD could also be explained by sexual age difference (SAD) due to a positive SSD–SAD relationship among all populations. The findings suggest that the occurrence of inverse Rensch’s rule in <em>B. andrewsi</em> is likely to be a result of fecundity selection on increased reproductive investments in larger females. This table is descriptive information about the study sites of Andrew’s toad (<em>B. andrewsi</em>), together with mean (± SD) body size and age of males and females.
DOI: 10.25582/data.2022-03.2457781/1910310
title: Data for EMSL Project 51134 from March 2022
DOI: 10.25582/data.2022-03.2457704/1910357
title: Data for EMSL Project 51134 from March 2022
DOI: 10.25582/data.2022-03.2457791/1910377
title: Data for EMSL Project 51134 from March 2022
DOI: 10.25582/data.2022-03.2457723/1910419
title: Data for EMSL Project 51134 from March 2022
DOI: 10.5517/ccdc.csd.cc299dcd
title: CCDC 2124193: Experimental Crystal Structure Determination

description: Related Article: Kento Yasumoto, Noritaka Kunitomo, Taichi Kano|2023|Org.Lett.|25|1497|doi:10.1021/acs.orglett.3c00262
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.13026/ga7g-1614
title: MS-CXR-T: Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing

description: MS-CXR-T is a multi-modal benchmark dataset for evaluating biomedical vision-
language processing (VLP) models on two distinct temporal tasks in radiology:
image classification and sentence similarity. The former comprises multi-image
frontal chest X-rays with ground-truth labels (N=1326) across 5 findings, with
classes corresponding to 3 states of disease progression for each finding:
{'Improving', 'Stable', 'Worsening'}, expanding on the Chest ImaGenome
progression dataset. The latter quantifies the temporal-semantic similarity of
text embeddings extracted from pairs of sentences (N=361). The pairs can be
either paraphrases or contradictions in terms of disease progression. The data
for both tasks was manually annotated and reviewed by a board-certified
radiologist. The dataset provides researchers an opportunity to evaluate both
image and text models on these biomedical temporal tasks and reproduce
experiments reported in the corresponding literature.
DOI: 10.13026/pg10-j984
title: MS-CXR-T: Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing

description: MS-CXR-T is a multi-modal benchmark dataset for evaluating biomedical vision-
language processing (VLP) models on two distinct temporal tasks in radiology:
image classification and sentence similarity. The former comprises multi-image
frontal chest X-rays with ground-truth labels (N=1326) across 5 findings, with
classes corresponding to 3 states of disease progression for each finding:
{'Improving', 'Stable', 'Worsening'}, expanding on the Chest ImaGenome
progression dataset. The latter quantifies the temporal-semantic similarity of
text embeddings extracted from pairs of sentences (N=361). The pairs can be
either paraphrases or contradictions in terms of disease progression. The data
for both tasks was manually annotated and reviewed by a board-certified
radiologist. The dataset provides researchers an opportunity to evaluate both
image and text models on these biomedical temporal tasks and reproduce
experiments reported in the corresponding literature.
DOI: 10.25582/data.2023-03.2769303/1961836
title: Data for EMSL Project 51332 from March 2023
DOI: 10.6084/m9.figshare.22255873.v3
title: Labeled 17 Hardwood Species and 55 Genotypes of Populus Stomatal Images Datasets

description: Research has indicated the potential of using machine learning algorithms to detect and measure stomata automatically. However, the current limitation for further improving and fine-tuning machine learning-based stomatal study methods is due to the small, inconsistent, and monotypic nature of stomatal datasets, which are also not easily accessible. To address this issue, our collection comprises more than 11,000 unique images of hardwood leaf stomata gathered from projects conducted between 2015 and 2020-2022. The dataset includes over 7,000 images of 17 frequently encountered hardwood species, including oak, maple, ash, elm, and hickory, as well as over 3,000 images of 55 genotypes from seven Populus taxa (as detailed in Table 1). Each image has been labeled as either stomata (stomatal aperture only) or whole_stomata (stomatal aperture and guard cells) and has a corresponding YOLO label file that can be transformed to other annotation formats. These images and labels are publicly available, making it easier to train machine-learning models and examine leaf stomatal traits. By utilizing our dataset, users can (1) use state-of-the-art machine learning models to identify, count, and quantify leaf stomata; (2) investigate the diverse range of stomatal characteristics across different types of hardwood trees; and (3) create new indices for measuring stomata.
DOI: 10.34740/kaggle/dsv/5186662
title: 💥📰 Daily Breaking News Twitter Dataset