cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/67stkk57ht.1
title: Morphological and biomass dataset for combining ability of Padjadjaran Field Corn based on line × tester Analysis and GGE biplot

description: The data presented in this article consist of three tables and two figures derived from observations and measurements of plant height (PH), number of leaves (NL), stem diameter (SD) and biomass characters. The variance analysis of the line × tester model is shown in Table 1. The analysis showed that the coefficient of variance was 5.44% in PH, 10.07% in NL, 15.61% in SD and 13.75 in biomass. In PH and SD, all factors showed a highly significant effect (p&gt;0.01). Then in NL, the line × tester factor showed a highly significant effect, while the line and tester factors showed a significant factor (p&gt;0.05). Thus, in biomass all factors also showed a very significant effect except for the tester factor. The existence of a significant effect indicates that the selected material is diversified for all the traits studied. The highest percentage of total variance (%SS) in PH, NL, SD and biomass was shown by the effect of crossing factors with 49.9%, 49.4%, 49.6% and 49.6% respectively. Table 1 also shows the contribution values of lines, testers, and lines × testers. PH is 26.28%, 7.17% and 65.97% respectively. NL is 24.51%, 5.55% and 67.44%. Then the SD shows 33.34%, 4.92% and 60.09%; while, the biomass amounted to 22.51%, 1.2% and 74.57%. The results showed that lines × testers gave the highest contribution, indicating that lines × testers crosses showed a large variance in all characters tested. Estimation of additive and dominant variances showed that all characters had larger dominant variances than additive variances. The data also shows that the estimated broad heritability of all characters namely PH, NL, SD and biomass had high broad heritability (0.951, 0.776, 0.922 and 0.968, respectively). In contrast to these results, the estimation of the narrow sense heritability showed a variation of only 0 - 5%. The data in Table 2 shows GCA information. The best of GCA values for lines at PH is L7, then at NL is L9, then at SD is L3 and at biomass is L5. The GCA for the tester at PH is T3, then at NL is T4, then at SD is T4 and at biomass is T2. The data shows the SCA value. The assessment results show that the best at PH is T1×L7, then at NL is T2×L20, then at SD is T4×L3 and in biomass T2×L10. The figure shows a vector view of the biplot that reveals the combining power of the strains for all testers. In PH (Fig. 1a), L7 had the highest GCA. Then at NL shows that the L9 line is the strain that has the best GCA. Furthermore, in SD it is known that L3 is the line with the best GCA. And finally, the strains that have the best combining power for all testers in biomass is L5. The data in Fig shows a which won where biplot that reveals which strains are best to combine with a particular tester (SCA). Based on Figure, PH shows that line L7 is best when crossed with tester T1. In NL, it was found that L7 crossed well with T2. The SD shows that L3 and L1 are best crossed with T4 and T3. On biomass , it is known that L5 is best crossed with T2 and T1.
DOI: 10.34740/kaggle/dsv/7453822
title: Egypt Gold Prices | Daily Updated
DOI: 10.6084/m9.figshare.21995072.v5
title: Files for Main Figure 3

description: Quantified TEs in TPM counts in simulated short-read measured by 7 approaches. File used for main figure 3.
<br>
Information about column names

 TE_name: Name of TE individuals
 TE_label: Positions of TE individuals
 length: TE lengths
 Long: Long-read TE output
 org_tel: Telescope TE output
 mod_tel: LocusMasterTE TE output 
 squire: Squire TE output 
 uniq: Unique counts from Telescope TE output
 best: Best counts from Telescope TE output 
 rsem: RSEM TE output
 salmonTE: salmonTE TE output
DOI: 10.17632/x3jcd9n3vk.2
title: Replication-BusinessClosures-BarrotBonelliGrassiSauvagnat

description: Replication package of “Causal effects of closing businesses in a pandemic” by Jean-Noel Barrot, Maxime Bonelli, Basile Grassi and Julien Sauvagnat
DOI: 10.17632/x3jcd9n3vk.3
title: Replication-BusinessClosures-BarrotBonelliGrassiSauvagnat

description: Replication package of “Causal effects of closing businesses in a pandemic” by Jean-Noel Barrot, Maxime Bonelli, Basile Grassi and Julien Sauvagnat
DOI: 10.5281/zenodo.10548456
title: Dataset of the research project ID-UDIMA-2022-01
DOI: 10.5281/zenodo.10548457
title: Dataset of the research project ID-UDIMA-2022-01
DOI: 10.17632/xtcw6pt6tr.1
title: Passion, Perfectionism and Sports Commitment as Covariates of the Risk of Exercise Addiction

description: Exercise addiction is a behavioral addictions without diagnostic criteria due to incomparable antecedents, and research based on risk rather than dysfunctionality. The risk of exercise addiction (REA) shares substantial variance with passion, perfectionism, and commitment to sport. However, their contributionb to REA is unknown. Thus, this study researched this issue by consideriung gender, competition status, and individual vs. team sports. An international sample of 1,003 regular exercisers (46.86% males) completed instruments to assess REA, passion, perfectionism and sports commitment. All measures showed medium to strong correlations with the REA. A bootstrapped hierarchical regression yielded six statistically significant predictors (exercise volume and intensity, harmonious and obsessive passion, rigid perfectionism, and constrained commitment), sharing 42.7% of the variance with the REA. Three bootstrapped univariate tests yielded gender, competition status, and sports-form differences in REA when the predictors were not included in the model as covariates. However, all group differences vanished when the predictors were controlled-
DOI: 10.26182/48p7-7b06
title: Tracing microfinance's mobility
DOI: 10.17632/83by2y8rk4.1
title: Microbial functional groups

description: These are codes for generating figures in "Y. Zhao, O. X. Cordero and M. Tikhonov, Linear-regression-based algorithms can succeed at identifying microbial functional groups despite the nonlinearity of ecological function." One can obtain Fig. 2-4 and Fig. S2-5 of the paper by running "RunMe.m" with all the files in the same folder. Codes are written in MATLAB.
DOI: 10.17632/vwrrdmryd6.1
title: Simulating Land Cover Changes and It’s Impacts on Land Surface Temperature: A Case Study in Rajshahi, Bangladesh

description: Land Surface Temperature (LST) has been used to investigate the effects of changing land cover on climate. The importance of surface temperature in a range of earth science concerns and themes, such as urban climatology, human-environment interactions, and global environmental change, cannot be overstated. Its impact will be more in the monsoon areas, because the rainfall is unpredictable, failure of monsoon and there will be heavy down pour of rainfall. LST for Rajshahi division, Bangladesh, is derived using ArcGIS software from images of Landsat 8 Optical Land Imager (OLI) data of 30 m resolution and Thermal Infrared Sensor (TIR) data of 100 m resolution, as well as data from Landsat-5 Thematic MAPPER (TM) satellites. A total time span of 15 years, starting from 2005 to 2020 is selected. Land cover map, Land Surface temperature, Normalized Difference vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) are calculated at every 5 years interval starting from 2005. The digital number of thermal infrared band is converted into spectral radiance using the equation supplied by the Landsat user's guidebook. The effective at sensor brightness temperature is obtained from the spectral radiance using Plank's inverse function. The final LST is computed using surface emissivity based on NDVI classes. according to the study, LST is increasing with the passage of time. The northwest parts of the Rajshahi division have the highest LST values. LST and NDVI are found to have a considerable positive correlation. The study shows the increase in vegetation reduces LST and the decrease of vegetation is responsible for increased LST. Also, bare soil, built-up area, waterbody is responsible for controlling LST. From the land cover map, it is visible that, bare soil and water body has a slight effect on LST but on the other hand, LST increases with growing of built-up area. The spatial distribution statistics of Land cover map, LST, and NDVI can be used as a guideline for urban planning, methods for improving the quality of the urban environment and a possible solution for diminishing of LST.
DOI: 10.5281/zenodo.10208904
title: Induced polarization and hydraulic tomography joint inversion results on a synthetic model

description: These data are supplementary material for a publication currently under review. This paper will be referenced here after publication.
The data set presents induced polarization (IP) and hydraulic tomography (HT) inversion results for a simple synthetic model. In addition, a joint inversion approach for both data types was implemented, so that individual and joint inversion results can be compared. We also show how the joint inversion procedure has the potential to correct a petrophysical bias within the IP inversion by incorporating the hydraulic data. The effect of different HT setups is also assessed by implementing different source and receiver positions.
The file directory contains the original synthetic model, and subfolders for the individual HT and IP, as well as the joint inversion results. The HT results contain three different setups (1m, 2m-inside, 2m-outside). The IP results are shown for five different assumptions of petrophysical bias (-2, -1, 0, +1, +2). The joint inversion results contain all possible combinations of these test cases. For more information on the methodology, we refer to the paper (see above, currently under review).
DOI: 10.17632/z26j8k2t3r.1
title: Two-step evolution of HIV-1 budding system leading to pandemic in the human population

description: The pandemic HIV-1, HIV-1 group M, emerged from a single spillover event of its ancestral lentivirus from a chimpanzee. During human-to-human spread worldwide, HIV-1 diversified into multiple subtypes. Here, our interdisciplinary investigation mainly sheds light on the evolutionary scenario of viral budding system of HIV-1 subtype C (HIV-1C), a most successfully spread subtype. Of the two amino acid motifs for HIV-1 budding, the P(T/S)AP and YPxL motifs, HIV-1C loses the YPxL motif. Our data imply that HIV-1C might lose this motif to evade immune pressure. Additionally, the P(T/S)AP motif, is duplicated dependently of the level of HIV-1 spread in the human population, and &gt;20% of HIV-1C harbored duplicated P(T/S)AP motif. We further show that the duplication of the P(T/S)AP motif is caused by the expansion of the CTG triplet repeat. Altogether, our results suggest that HIV-1 has experienced two-step evolution of viral budding process during human-to-human spread worldwide.
DOI: 10.5281/zenodo.10511000
title: Input states for "Optimal sampling of tensor networks targeting wave function's fast decaying tails"

description: The dataset contains the input states for results presented in "Optimal sampling of tensor networks targeting wave function’s fast decaying tails" (https://arxiv.org/abs/2401.10330). The simulations for sampling the quantum Ising model (ground state and finite temperature) and GHZ state generated under noise depend on the tensor network state of this data set.
DOI: 10.5281/zenodo.10511001
title: Input states for "Optimal sampling of tensor networks targeting wave function's fast decaying tails"

description: The dataset contains the input states for results presented in "Optimal sampling of tensor networks targeting wave function’s fast decaying tails" (https://arxiv.org/abs/2401.10330). The simulations for sampling the quantum Ising model (ground state and finite temperature) and GHZ state generated under noise depend on the tensor network state of this data set.
DOI: 10.17632/4t73j3nnt5.1
title: Oroxylum indicum metabolomics

description: LCMS/MS and HRMS data sheet
DOI: 10.5281/zenodo.10213882
title: Hydraulic tomography and thermal tracer test data from a fractured-porous field site in Goettingen (Germany)

description: These data are supplementary material for:

Römhild, L., Ringel, L. M., Liu, Q., Hu, L., Ptak, T., & Bayer, P. (2024). Hybrid discrete fracture network inversion of hydraulic tomography data from a fractured-porous field site. Water Resources Research, 60, e2023WR036035. https://doi.org/10.1029/2023WR036035

The data set comprises hydraulic tomography and thermal tracer test field data from a porous-fractured site in Göttingen (Germany). The repository contains a schematic figure of the experimental setup and subfolders for the two different experiments. For more information about the data, we refer to the readme files in the repository, and the soon-to-be-published paper (see above).
DOI: 10.5281/zenodo.10213883
title: Hydraulic tomography and thermal tracer test data from a fractured-porous field site in Goettingen (Germany)

description: These data are supplementary material for:

Römhild, L., Ringel, L. M., Liu, Q., Hu, L., Ptak, T., & Bayer, P. (2024). Hybrid discrete fracture network inversion of hydraulic tomography data from a fractured-porous field site. Water Resources Research, 60, e2023WR036035. https://doi.org/10.1029/2023WR036035

The data set comprises hydraulic tomography and thermal tracer test field data from a porous-fractured site in Göttingen (Germany). The repository contains a schematic figure of the experimental setup and subfolders for the two different experiments. For more information about the data, we refer to the readme files in the repository, and the soon-to-be-published paper (see above).
DOI: 10.17632/9f2t8mmkyj.1
title: Soil Salinity prediction by different resolution data

description: Soil properties were measured in an approximately 17000 ha to examine the effects of different resolution data in accuracy of soil salinity prediction model.
DOI: 10.17632/r4v7gsvmsx.1
title: Semiparametric Least Squares Estimation of Binary Choice Panel Data Models with Endogeneity

description: The replication package accompanying
"Semiparametric Least Squares Estimation of Binary Choice Panel Data Models with Endogeneity",
by Anastasia Semykina, Yimeng Xie, Cynthia Fan Yang, and Qiankun Zhou,
January 2024
DOI: 10.17632/bfmpbx432k.2
title: Contrast based lesion segmentation on DermIS and DermQuest datasets.

description: In this companion paper, we present the results obtained by our contrast based approach for lesion segmentation on two datasets used by amelard et al. (Amelard, J. Glaister, A. Wong and D. A. Clausi, High-Level Intuitive Features (HLIFs) for Intuitive Skin Lesion Description, IEEE Transactions on Biomedical Engineering, 62(3) (2015), 820-831). The first is a subset of a DermIS database (Dermatology Information System, available online: http://www.dermis.net) that contains 43 macroscopic photographs with lesion diagnosed as melanoma and 26 diagnosed as non melanoma. The second is a subset of the DermQuest database (Available online: http://www.dermquest.com) that contains 76 images of melanoma lesions and 61 images of non melanoma lesions. The images are subject to various artifacts like drastic shadow effect and the variation of illumination. We also provide the ground truth segmentation to evaluate visually the accuracy of our results.
DOI: 10.21335/nmdc-482758181
title: Nutrient Biogeochemistry in the Nordic Seas (Norwegian, Greenland, Iceland Seas), 1990 - 2019

description: This dataset contains biogeochemical samples analyzed by the Plankton Chemistry Laboratory at the Institute of Marine Research (IMR), mainly from the Norwegian Sea but also including the Iceland and Greenland Seas. Number of surveys and stations visited has varied greatly over the last 3 decades. One major effort by the IMR is the annual Ecosystem Survey in summer, with multiple trawl surveys, net tows and CTD water sampling over the course of a month. This month-long exercise also include companion vessels from Iceland and the Faroe Islands surveying their own territorial waters (only trawl surveys and net tows). Two transects are also visited multiple times each year by the IMR (Svinøy-NorthWest and Gimsøy-NorthWest), in addition to other water sample collections from short-term projects visiting the region. Each CTD cast is sampled for dissolved inorganic nutrients (nitrate, nitrite, phosphate, silicate) and phytoplankton pigments (ChlA, Phaeo) at predetermined depths and for later analysis at IMR. On occasion, short-term projects have performed Winkler DO titrations (DOW) and particulate organic carbon and nitrogen (POC, PN) determinations. This unique data set has seen limited use over the years, but the entire time-series is a great contribution towards global ocean research and climate change investigations. A description of analytical methods is available (Appendix-1).
DOI: 10.5281/zenodo.4441254
title: Dataset: Characterizing Smart Contracts Vulnerabilities and Bugs: An Empirical Study

description: Dataset: Characterizing Smart Contracts Vulnerabilities and Bugs: An Empirical Study This Dataset includes the following: 1. "Vulnerabilities categories card labeling.xml" file that represents the data for Categories of vulnerabilities in Smart Contracts (RQ1).<br> 2. "Impact cards labeling.xml" file that represents the data for Impact of Vulnerabilities and Bugs in smart contracts(RQ2).<br> 3. "Fix Time Duration.xml" file that shows the Vulnerabilities Fixing Duration in smart contracts(RQ3).<br> 4. "Defined 34 Vulnerabilities.pdf" this file shows the 34 vulnerabilities and bugs that we defined and identify from real-world smart contracts<br> on Stack Overflow and developers are facing in their smart contracts' source codes. ------<br> XML files structure:<br> The XML files can be opened used any text editor (e.g. notepad++) or any code editor (e.g. Visual Studio Code). 1. Each file has a root that is &lt;Card_Table&gt;&lt;/Card_Table&gt; which contains all the cards we labeled. <br> 2. Each card is represented by the &lt;Card&gt;&lt;/Card&gt; and contains the following:<br> - The main Tag marked by &lt;Tag&gt; that was used to search and collect the card from StackOverflow. <br> - The URL marked by &lt;URL&gt; of the post on StackOverflow which contains all the information of the post (i.e., the question information, the answers, comments, votes, post and answer times)<br> - The other tages marked by &lt;OtherTags&gt; that shows all the tags used in the post. <br> - The first expert labeling for the categories of vulnerabilities in each card is represented by &lt;FirstExpertCategoryLabel&gt;.<br> - The second expert labeling for the categories of vulnerabilities in each card is represented by &lt;SecondExpertCategoryLabel&gt;.<br> - The &lt;CategoryAgreement&gt; used to calculate the inter-rater agreement between the two labelers. <br> - The first expert labeling for the impact of vulnerabilities in each card is represented by &lt;FirstExpertImpactLabel&gt;.<br> - The second expert labeling for the impact of vulnerabilities in each card is represented by &lt;/SecondExpertImpactLabel&gt;.<br> - The &lt;PostTime&gt; shows the time at which the post was created on StackOverflow.<br> - The &lt;CorrectAnswerTime&gt; shows the time at which the correct answer of the card was posted on StackOverflow.<br> - Finally, the &lt;FixTimeDurationDAYS&gt; shows the fix time duration of each card in days, we calculated it based on the differnce between the &lt;CorrectAnswerTime&gt; and the &lt;PostTime&gt;. <br>
DOI: 10.5281/zenodo.7923866
title: CNBH-10 m: A first Chinese building height at 10 m resolution

description: Building height is a crucial variable in the study of urban environments, regional climates, and human-environment interactions. However, high-resolution data on building height, especially at the national scale, are limited. Fortunately, high spatial-temporal resolution earth observations, harnessed using a cloud-based platform, offer an opportunity to fill this gap. We describe an approach to estimate 2020 building height for China at 10 m spatial resolution based on all-weather earth observations (radar, optical, and night light images) using the Random Forest (RF) model. Results show that our building height simulation has a strong correlation with real observations at the national scale (RMSE of 6.1 m, MAE = 5.2 m, <em>R</em> = 0.77). The Combinational Shadow Index (CSI) is the most important contributor (15.1%) to building height simulation. Analysis of the distribution of building morphology reveals significant differences in building volume and average building height at the city scale across China. Macau has the tallest buildings (22.3 m) among Chinese cities, while Shanghai has the largest building volume (298.4 10<sup>8</sup> m<sup>3</sup>). The strong correlation between modelled building volume and socio-economic parameters indicates the potential application of building height products. The building height map developed in this study with a resolution of 10 m is open access, provides insights into the 3D morphological characteristics of cities and serves as an important contribution to future urban studies in China.
description: {"references": ["Wu W B, Ma J, Banzhaf E, et al. A first Chinese building height estimate at 10 m resolution (CNBH-10 m) using multi-source earth observations and machine learning[J]. Remote Sensing of Environment, 2023, 291: 113578."]}
DOI: 10.5281/zenodo.8182851
title: Cell-to-Cell-Variations of a Panasonic NCR18650B

description: Cell-to-Cell-Variations of Panasonic NCR18650B 
This dataset contains raw characterization data from 92 Panasonic NCR-18650B cells at the beginn of life. Information on the measurements performed can be taken in part from this readme file. Further details can be found in https://doi.org/10.1016/j.jpowsour.2023.233677 . Pulse measurements, pseudo-open circuit measurements, and impedance measurements are recorded. All measurements are performed in a Binder MK 155 climate chamber at 25°C.
Pseudo Open Circuit Voltage
POCV is recorded with a constant current of 0.05C in the charge and discharge direction. The measurements are performed with an Arbin LBT 5V-25A cell tester. The data is stored as a Matlab struct containing the following entries:
pocv.ch  % POCV of during charging
pocv.dc  % POCV of during discharging
pocv.soc % SoC of the pocv curves
The POCVs are interpolated to 5000 equidistant SOC points and sorted in the direction of the SOC vector.
Impedance
Impedance measurements are at 50% SOC(actual measured discharge C/20 capacity as reference) after 4h of relaxation. The measurements are conducted with a Zahner Zenium Pro spectroscope with an amplitude of 250 mA in a frequency range between 0.01 Hz and 10 kHz with 10 steps per decade. The data is stored as a Matlab struct containing the following entries:
impedance.f      % Frequency in Hz
impedance.Z_imag % Imaginary Part of the impedance in Ohm
impedance.Z_real % Real part of the impedance in Ohm
impedance.Z      % Complex valued impedance in Ohm
Each row corresponds to a dataset of an individual cell and each column corresponds to a measurement frequency. The same applies to the .csv files.
Pulse Test
Pulse measurements are performed at 50% SOC (actual measured discharge C/20 capacity as reference) after 2h of relaxation. The measurements are performed with an Arbin LBT 5V-25A cell tester. The pulse test is performed with a current of 0.5C for 10s followed by a relaxation of 30 minutes. The discharge pulse follows the charge pulse. The data is stored as a Matlab struct containing the following entries:
pulse.neg_time    % Time of the discharge pulse sequence 
pulse.neg_voltage % Voltage of the discharge pulse sequence
pulse.pos_time    % Time of the charge pulse sequence
pulse.pos_voltage % Voltage of the charge pulse sequence