cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2235gv
title: CCDC 1909676: Experimental Crystal Structure Determination

description: Related Article: Xue Zhang, Shuang Wang, Tingting Yan, Jun Zhang, Fang Luo|2020|Inorg.Chem.Commun.|111|107634|doi:10.1016/j.inoche.2019.107634
DOI: 10.5517/ccdc.csd.ccpkq86
title: CCDC 642638: Experimental Crystal Structure Determination

description: Related Article: Kang-Kai Du|2019|CSD Communication|||
description: Related Article: Kangkai Du, Shi-Xiong Liu, Bizhou Lin|2020|Inorg.Chem.Commun.|111|107606|doi:10.1016/j.inoche.2019.107606
DOI: 10.5517/ccdc.csd.cc231zms
title: CCDC 1938325: Experimental Crystal Structure Determination

description: Related Article: Chao Li, Hongqiang Gao, Linsui Li, Wenjuan Wei, Yuhui Tan|2020|Inorg.Chem.Commun.|111|107613|doi:10.1016/j.inoche.2019.107613
DOI: 10.5517/ccdc.csd.cc231znt
title: CCDC 1938326: Experimental Crystal Structure Determination

description: Related Article: Chao Li, Hongqiang Gao, Linsui Li, Wenjuan Wei, Yuhui Tan|2020|Inorg.Chem.Commun.|111|107613|doi:10.1016/j.inoche.2019.107613
DOI: 10.5517/ccdc.csd.cc212fwg
title: CCDC 1879185: Experimental Crystal Structure Determination

description: Related Article: Ru-Xia Zhao, Jing Wang, Da-wei Jing, Hui-jing Zhang, Chao Feng, Guang-yue Li|2020|Inorg.Chem.Commun.|111|107597|doi:10.1016/j.inoche.2019.107597
DOI: 10.5517/ccdc.csd.cc23bmbf
title: CCDC 1946624: Experimental Crystal Structure Determination

description: Related Article: Ying-Bing Lu, Shui-Hu Wang, Shui-Dong Zhu, Ya-Qi Zhuo, Xiang-Li Lin, Gen-Mei Yang, Yong-Rong Xie|2020|Inorg.Chem.Commun.|111|107667|doi:10.1016/j.inoche.2019.107667
DOI: 10.5517/ccdc.csd.cc1z0q6x
title: CCDC 1817939: Experimental Crystal Structure Determination

description: Related Article: Jun Ying, Haiyan Yu, Guiying Liu, Yubo Fu, Aixiang Tian|2020|Inorg.Chem.Commun.|111|107626|doi:10.1016/j.inoche.2019.107626
DOI: 10.5517/ccdc.csd.cc1z0q7y
title: CCDC 1817940: Experimental Crystal Structure Determination

description: Related Article: Jun Ying, Haiyan Yu, Guiying Liu, Yubo Fu, Aixiang Tian|2020|Inorg.Chem.Commun.|111|107626|doi:10.1016/j.inoche.2019.107626
DOI: 10.5517/ccdc.csd.cc21t085
title: CCDC 1900866: Experimental Crystal Structure Determination

description: Related Article: Jun Ying, Haiyan Yu, Guiying Liu, Yubo Fu, Aixiang Tian|2020|Inorg.Chem.Commun.|111|107626|doi:10.1016/j.inoche.2019.107626
DOI: 10.5517/ccdc.csd.cc23hhgl
title: CCDC 1951309: Experimental Crystal Structure Determination

description: Related Article: Xin Xu, Jun Jiang, Da Li, Saisai Xie, Lulu Liu, Baoxing Zeng, Lijuan Chen, Junwei Zhao|2020|Inorg.Chem.Commun.|111|107625|doi:10.1016/j.inoche.2019.107625
DOI: 10.5517/ccdc.csd.cc23jr4k
title: CCDC 1952508: Experimental Crystal Structure Determination

description: Related Article: Ping Ju|2019|CSD Communication|||
description: Related Article: Ping Ju, En-sheng Zhang, Xicheng Liu, Long Jiang|2020|Inorg.Chem.Commun.|111|107641|doi:10.1016/j.inoche.2019.107641
DOI: 10.5517/ccdc.csd.cc23jr5l
title: CCDC 1952509: Experimental Crystal Structure Determination

description: Related Article: Ping Ju|2019|CSD Communication|||
description: Related Article: Ping Ju, En-sheng Zhang, Xicheng Liu, Long Jiang|2020|Inorg.Chem.Commun.|111|107641|doi:10.1016/j.inoche.2019.107641
DOI: 10.5517/ccdc.csd.cc23lmhv
title: CCDC 1954317: Experimental Crystal Structure Determination

description: Related Article: Dan-Dan Liu, Xin-Hui Zhang, Qing-Yan Liu, Yu-Ling Wang|2020|Inorg.Chem.Commun.|111|107623|doi:10.1016/j.inoche.2019.107623
DOI: 10.5517/ccdc.csd.cc23pqcx
title: CCDC 1957289: Experimental Crystal Structure Determination

description: Related Article: Huali Jia, Yuanchun Qi, Xin Wang, Jianping Xie, Wenjing Yu|2020|Inorg.Chem.Commun.|111|107668|doi:10.1016/j.inoche.2019.107668
DOI: 10.5517/ccdc.csd.cc23q613
title: CCDC 1957744: Experimental Crystal Structure Determination

description: Related Article: Xiao-Quan Zhu, Tian-Lu Sheng|2020|Inorg.Chem.Commun.|111|107638|doi:10.1016/j.inoche.2019.107638
DOI: 10.5517/ccdc.csd.cc23q624
title: CCDC 1957745: Experimental Crystal Structure Determination

description: Related Article: Xiao-Quan Zhu, Tian-Lu Sheng|2020|Inorg.Chem.Commun.|111|107638|doi:10.1016/j.inoche.2019.107638
DOI: 10.5517/ccdc.csd.cc23q635
title: CCDC 1957746: Experimental Crystal Structure Determination

description: Related Article: Xiao-Quan Zhu, Tian-Lu Sheng|2020|Inorg.Chem.Commun.|111|107638|doi:10.1016/j.inoche.2019.107638
DOI: 10.5517/ccdc.csd.cc242hf5
title: CCDC 1968606: Experimental Crystal Structure Determination

description: Related Article: Sergei V. Voitekhovich, Alexander S. Lyakhov, Ludmila S. Ivashkevich, Oleg A. Ivashkevich|2020|Inorg.Chem.Commun.|114|107827|doi:10.1016/j.inoche.2020.107827
DOI: 10.5517/ccdc.csd.cc242hg6
title: CCDC 1968607: Experimental Crystal Structure Determination

description: Related Article: Sergei V. Voitekhovich, Alexander S. Lyakhov, Ludmila S. Ivashkevich, Oleg A. Ivashkevich|2020|Inorg.Chem.Commun.|114|107827|doi:10.1016/j.inoche.2020.107827
DOI: 10.5517/ccdc.csd.cc242hh7
title: CCDC 1968608: Experimental Crystal Structure Determination

description: Related Article: Sergei V. Voitekhovich, Alexander S. Lyakhov, Ludmila S. Ivashkevich, Oleg A. Ivashkevich|2020|Inorg.Chem.Commun.|114|107827|doi:10.1016/j.inoche.2020.107827
DOI: 10.6084/m9.figshare.19145951
title: Effects of haemosporidian co-infection and parasitemia on reproductive strategies in a polymorphic species

description: This data contains information on white-throated sparrow haemosporidian infection (co-infection <em>Plasmodium</em> and <em>Leucocytozoon</em> status (DINF) and the parasitemia fro <em>Plasmodium</em> & <em>Leucocytozoon</em>) combined with measures of reproductive success such as the number of nestlings, the number of fledges, and the ratio of genetic offspring belonging to the social father (G<sub>o</sub>/S<sub>f</sub>) and the nest mean growth rate and mean body condition. Each line corresponds to a nest from the 1st or 2nd clutch of a breeding season combined with the ID of the father and the mother of the nestling, combine with the parental haemosporidian infection status. <br> In addition, the second data file contains the adult morph, sex, the population density of the year, and body condition combined with the co-infection <em>Plasmodium</em> and <em>Leucocytozoon</em> status (DINF) and the parasitemia (<em>Plasmodium</em> & <em>Leucocytozoon</em>).
DOI: 10.6084/m9.figshare.19146008
title: pdxe_mut_and_cn2.txt.gz

description: Raw data table without excel gene name conversion issues in supplementary table 1 from Gao et al "High-throughput screening using patient-derived tumor xenografts to predict clinical trial drug response"
DOI: 10.5281/zenodo.5884485
title: SkyFinder Dataset

description: This dataset consists of images from 53 AMOS webcams (https://mvrl.github.io/AMOS). The image sequences were selected so that they were stable so that a single sky/ground mask could be used for all images in a given camera. <strong>Contents</strong> [integer camera ID].zip : contains images from each camera skyfinder_masks.zip : contains the sky/ground masks <strong>Additional Links</strong> Project Webpage: https://cs.valdosta.edu/~rpmihail/skyfinder/ Another Dataset Summary: https://mvrl.github.io/SkyFinder <strong>Citation</strong> If you use this dataset, please cite the following paper: Mihail RP, Workman S, Bessinger Z, Jacobs N. 2016. Sky Segmentation in the Wild: An Empirical Study. In: IEEE Winter Conference on Applications of Computer Vision (WACV). 1–6. DOI: 10.1109/WACV.2016.7477637. @inproceedings{mihail2016sky,<br> author = {Mihail, Radu Paul and Workman, Scott and Bessinger, Zach and Jacobs, Nathan},<br> booktitle = {IEEE Winter Conference on Applications of Computer Vision (WACV)},<br> pages = {1--6},<br> doi = {10.1109/WACV.2016.7477637},<br> title = {Sky Segmentation in the Wild: An Empirical Study},<br> year = {2016}<br> }
DOI: 10.5281/zenodo.5884484
title: SkyFinder Dataset

description: This dataset consists of images from 53 AMOS webcams (https://mvrl.github.io/AMOS). The image sequences were selected so that they were stable so that a single sky/ground mask could be used for all images in a given camera. <strong>Contents</strong> [integer camera ID].zip : contains images from each camera skyfinder_masks.zip : contains the sky/ground masks <strong>Additional Links</strong> Project Webpage: https://cs.valdosta.edu/~rpmihail/skyfinder/ Another Dataset Summary: https://mvrl.github.io/SkyFinder <strong>Citation</strong> If you use this dataset, please cite the following paper: Mihail RP, Workman S, Bessinger Z, Jacobs N. 2016. Sky Segmentation in the Wild: An Empirical Study. In: IEEE Winter Conference on Applications of Computer Vision (WACV). 1–6. DOI: 10.1109/WACV.2016.7477637. @inproceedings{mihail2016sky,<br> author = {Mihail, Radu Paul and Workman, Scott and Bessinger, Zach and Jacobs, Nathan},<br> booktitle = {IEEE Winter Conference on Applications of Computer Vision (WACV)},<br> pages = {1--6},<br> doi = {10.1109/WACV.2016.7477637},<br> title = {Sky Segmentation in the Wild: An Empirical Study},<br> year = {2016}<br> }
DOI: 10.6084/m9.figshare.19146032
title: anemia final.dta

description: This dataset is collected prospectvly form pregnant women to estimate the risk of anemia.
DOI: 10.5281/zenodo.5528088
title: Stable nickel production in Type Ia supernovae: A smoking gun for the progenitor mass?

description: Model spectra from Blondin et al. (2022). This second version includes spectra of the uniformly-mixed versions of model DDC15, which were accidentally omitted from the first version.
description: {"references": ["Blondin et al. (2022), preprint available at https://arxiv.org/abs/2109.13840"]}
DOI: 10.5281/zenodo.5528083
title: Stable nickel production in Type Ia supernovae: A smoking gun for the progenitor mass?

description: Model spectra from Blondin et al. (2022). This second version includes spectra of the uniformly-mixed versions of model DDC15, which were accidentally omitted from the first version.
description: {"references": ["Blondin et al. (2022), preprint available at https://arxiv.org/abs/2109.13840"]}
DOI: 10.6084/m9.figshare.19145957.v1
title: C88.v1.pep.fa.gz

description: C88 v1 protein fasta
DOI: 10.6084/m9.figshare.19145957
title: C88.v1.pep.fa.gz

description: C88 v1 protein fasta
DOI: 10.6084/m9.figshare.19146017
title: C88.v1.fa.gz

description: C88 v1 assembly
DOI: 10.6084/m9.figshare.19146017.v1
title: C88.v1.fa.gz

description: C88 v1 assembly
DOI: 10.6084/m9.figshare.19145954
title: C88.v1.EDTA.TEanno.gff3.gz

description: C88 v1 TE annotation from EDTA pipeline
DOI: 10.6084/m9.figshare.19145960.v1
title: C88.v1.gene.gff3.gz

description: C88 v1 gene annotation gff3
DOI: 10.6084/m9.figshare.19145960
title: C88.v1.gene.gff3.gz

description: C88 v1 gene annotation gff3
DOI: 10.6084/m9.figshare.19145963
title: C88.v1.cds.fa.gz

description: C88 v1 cds fasta
DOI: 10.6084/m9.figshare.19145963.v1
title: C88.v1.cds.fa.gz

description: C88 v1 cds fasta
DOI: 10.6084/m9.figshare.19145966
title: C88.v1.cdna.fa.gz

description: C88 v1 cdna fasta
DOI: 10.6084/m9.figshare.19145966.v1
title: C88.v1.cdna.fa.gz

description: C88 v1 cdna fasta
DOI: 10.23729/9d30d494-e8f1-4aed-9053-1096c0017f8a
title: Zero Point Calibration

description: A calibration sample VTX18CE000 with a well measured distance of 7,9513 mm between the centers of the ruby balls, was measured at different Focus To Object - ratios to calibrate the position of the focus point in GE phoenix v|tome|x s located at Geological Survey of Finland, Espoo. Dataset contains ruby balls segmented using watershed segmentation in ThermoFisher PerGeos 2020.2. Voxel size required for distance calculation can be found in log files. Preview dataset found at https://doi.org/10.23729/e0993f57-1c76-4931-8470-57d29df8ad96 . To obtain data, please contact fairdata-pas@gtk.fi .
DOI: 10.34740/kaggle/dsv/3162101
title: Mahanagar Yatayat Dataset
DOI: 10.17632/2nfwrtc44s.1
title: Supplementary Figure S1 and S2 - JDS20782 - GreenFeed visits

description: Supplementary Figure S1. The average number of GreenFeed visits (per cow) over a 24 h period of the dairy cows receiving a grass silage-based diet (GS; green), a grass silage- and corn silage-mixed diet (GSCS; orange), and a corn silage-based diet (CS; blue) supplemented with a placebo (NOP0; circle as symbol) or with 60 mg 3-nitrooxypropanol / kg DM (NOP60; triangle as symbol).

Supplementary Figure S2. The average number of GreenFeed visits (per cow) over a 24 h period of the dairy cows receiving a grass silage-based diet (GS; green), a grass silage- and corn silage-mixed diet (GSCS; orange), and a corn silage-based diet (CS; blue) supplemented with a placebo (NOP0; circle as symbol) or with 80 mg 3-nitrooxypropanol / kg DM (NOP80; triangle as symbol).
DOI: 10.17632/ftvs8jwkmx.1
title: Supplementary Figure S2 - JDS20782 - GreenFeed visits NOP0 and NOP80

description: Supplementary Figure S2. The average number of GreenFeed visits (per cow) over a 24 h period of the dairy cows receiving a grass silage-based diet (GS; green), a grass silage- and corn silage-mixed diet (GSCS; orange), and a corn silage-based diet (CS; blue) supplemented with a placebo (NOP0; circle as symbol) or with 80 mg 3-nitrooxypropanol / kg DM (NOP80; triangle as symbol).
DOI: 10.17632/t9h6p943xy.2
title: BEASC: Bangla emotional audio-speech corpus - A speech emotion recognition corpus for the low-resource Bangla language

description: BEASC is an audio-speech emotion recognition corpus for the Bangla language. The developed dataset consists of voice data from 34 speakers from diverse age groups between 19 to 57 (mean = 28.75 and Standard deviation = 9.346), equally balanced with 17 males and 17 females. This dataset contains 1224 speech-audio data of four emotional states. There are four emotional states recorded for three sentences. The three sentences are i. ‘১২ টা বেজে গেছে,’ ii. ‘আমি জানতাম এমন কিছু হবে’, and iii. ‘এ কেমন উপহার’. These emotional states include four basic human emotions: Angry, Happy, Sad, and Surprise. Three trials were preserved for each emotional expression. Hence, the total number of utterances involves three sentences × three repetitions × four emotions × 34 speakers = 1224 recordings. The format of the audio file is a . WAV format. We consider that happy and sad emotional speech has normal intensity and angry and surprise emotional states have a strong intensity. The data files are divided into 34 individual folders. Each folder contains 36 audio recordings of each participating actor. BEASC is a balanced dataset with 306 recordings of each individual emotion. The size of the BEASC dataset is 619 MB. While most of the existing datasets of different languages are recorded inside a closed studio or cover a single sentence, this dataset is collected by recording through smartphones, hence preserving the slightly noisy real-life environment. BEASC is compatible with various shallow machine learning and deep learning architectures such CNN, LSTM, HMM, Transformer, etc. Each data file has a unique filename. We followed the same procedure as the famous RAVDESS dataset for the naming. The filename consists of seven two-digit numerical identifiers, separated by hyphens (e.g., 03-01-01-01-02-02-02.wav). Each two-digit numerical identifier defines the level of a different experimental factor. The identifiers are ordered: Modality - Statement type - Emotion - Emotion Intensity - Statement - Repetition - Actor.wav. For example, the filename “03-01-01-01-02-02-02.wav” refers to: Audio only (03) - Scripted (01) - Happy (01) - Normal intensity (01) - 2nd Statement (02) - 2nd Repetition (02) - 2nd Actor, Female (02).
DOI: 10.17632/5zyft5ky8s.1
title: Supplementary Figure S1 - JDS20782 - GreenFeed visits NOP0 and NOP60

description: Supplementary Figure S1. The average number of GreenFeed visits (per cow) over a 24 h period of the dairy cows receiving a grass silage-based diet (GS; green), a grass silage- and corn silage-mixed diet (GSCS; orange), and a corn silage-based diet (CS; blue) supplemented with a placebo (NOP0; circle as symbol) or with 60 mg 3-nitrooxypropanol / kg DM (NOP60; triangle as symbol).
DOI: 10.17632/k7rmrjvz2p.3
title: Doing the Right Thing?  The Voting Power Effect and Institutional Shareholder Voting 

description: Through a combination of a controlled experiment and a survey, we examine the effect of voting power on shareholders’ voting behavior at general meetings. To avoid a selection bias, common in archival voting data, we exogenously manipulate shareholders’ power to affect the outcome. Our findings suggest that, when it comes to corporate decisions involving conflicts of interest, voting power nudges shareholders to oppose management and to choose the “right” alternative, that is, vote against a proposal which prima facie does not serve the company’s best interest. This effect obtained even when the dissenting vote contravened the choices of all other voters or self-interest. Furthermore, the drive “to do the right thing” was established as significant, above and beyond the size of the economic stake. We also demonstrate that strategic voting among institutional investors is contingent on voting power: When in a position to affect the outcome of a vote, institutional investors tend to eschew strategic considerations and display fewer consistent patterns in their voting, compared to situations in which their ability to make a difference is limited. In anticipation of a “bad” proposal to be put to vote at the general shareholder meeting, institutional investors prefer to negotiate terms with management beforehand, and vote against it only after such negotiations fail. Our results shed new light on the “behind the scenes” processes in shareholder voting and underscore the importance of institutional investor agency to corporate governance, accountability, and minority shareholder representation.

The data include:  i)First Phase: M-Turk Experiment (3 studies); ii) First Phase: Prolific Study; iii) Second Phase: Institutional Investor Employee Survey; iv) Research Instrument (Appendix A1: M-Turk questionnaire; Appendix A2: Prolific questionnaire (Study 4); Appendix B: The survey questionnaire for institutional investors’ employees).
DOI: 10.17632/r89gjb658r.2
title: Annual School Closures and Standardized Test Scores in California, 2003-2019

description: File includes demographic, socioeconomic, and academic data on public schools in California with school closures listed by individual cause per academic year. Demographic, socioeconomic, and academic data come from the California Department of Education. Data on school closures come from CalMatters’ Disaster Days dataset.
DOI: 10.17632/8jbfz89rbp.1
title: Numerical simulation data of bubble-structure interactions in near-field underwater explosion

description: This data set is associated with the numerical simulation of the interactions between a high-pressure gas bubble and a thin-walled aluminum cylinder, in the context of near-field underwater explosion.  The fluid dynamics is simulated using finite volume method implemented in the AERO-F solver.  The structural dynamics is simulated using finite element method implemented in the AERO-S solver.  The two solvers are coupled using an embedded boundary method and the FInite Volume method with Exact two-material Riemann problems (FIVER).  The input files to perform this simulation are also provided. Researchers can repeat this simulation, and use it as a starting point to study related problems involving cavitation bubbles, underwater explosion, and fluid-structure interaction in general.
DOI: 10.17632/hss8z5ksbk.1
title: Simulated waveforms for validation of seismic velocity models in southern California

description: The dataset includes synthetic waveforms used in the paper "Validation of seismic velocity models in southern California with full-waveform simulations, GJI, https://doi.org/10.1093/gji/ggab534". Please refer to the paper for further information regarding its usage.
DOI: 10.5281/zenodo.6023880
title: How efficient is symbiont-mediated protection to heat under daily fluctuating thermal environments? A study on an aphid-bacterium mutualism

description: These are the two datasets for the article "<strong>How efficient is symbiont-mediated protection to heat under daily fluctuating thermal environments? A study on an aphid-bacterium mutualism</strong>". We examined the effects of four thermal regimes defined by their combination of mean temperature (18 or 25°C) and diurnal thermal range (day-night fluctuations: 5 or 10°C) on the interaction between the aphid <em>Acyrthosiphon pisum</em>, its obligate symbiont <em>Buchnera aphidicola </em>and the facultative heat-protective symbiont <em>Serratia symbiotica</em>. We used two clonal lines of <em>A. pisum </em>uninfected (5A) or infected with <em>S. symbiotica </em>(5AR). Thermal treatments were applied form aphid birth to death. We recorded both aphid traits (immature survival rate, longevity, immature development time, total fecundity, body size) and symbiont titres at the onset of reproduction (for both <em>B. aphidicola </em>and <em>S. symbiotica</em>), expressed relatively to aphid gene copy number through quantitative PCRs (qPCRs). <strong>Aphid traits</strong> . Individual = identification of the individual . Line = aphid clonal line, either deprived of (5A) or infected with <em>S. symbiotica </em>(5AR) . MT = Mean Temperature, either 18°C or 25°C . DTR = Diurnal Temperature Range (day-night fluctuations), either 5°C or 10°C . surv.adult = whether (Y) or not (N) the individual survived until reaching reproduction (immature survival rate) . adulthood = time elapsed between birth and first reproduction (in days) . lifespan = time elapsed between birth and death (in days) . offspring = total number of larvae produced by each aphid throughout lifetime . tibia = hind tibia length as a proxy of body size (in mm) . wing = whether (Y) or not (N) the individual developed wings following imaginal moult <strong>Symbiont titres</strong> . Individual = identification of the individual . Line = aphid clonal line, either deprived of (A) or infected with <em>S. symbiotica </em>(AR) . MT = Mean Temperature, either 18°C or 25°C . DTR = Diurnal Temperature Range (day-night fluctuations), either 5°C or 10°C . QPCR = identification of the microplate used during qPCR analyses (to handle pseudoreplication) . EfAlph = number of copies of aphid housekeeping gene elongation factor 1-alpha (<em>EF1-α</em>) . SdEfAlph = standard deviation of the aphid gene copy number, calculated over three technical replicates . DnaKBa = number of copies of <em>B. aphidicola </em>gene <em>dnaK</em> . SdDnaKBa = standard deviation of <em>B. aphidicola </em>gene copy number, calculated over three technical replicates . DnakSs = number of copies of <em>S. symbiotica </em>gene <em>dnaK</em> . SdDnaKSs = standard deviation of <em>S. symbiotica </em>gene copy number, calculated over three technical replicates . RappBa = ratio between DnaKBa and EfAlph to calculate relative titre of <em>B. aphidicola</em> . RappSs = ratio between DnaKSs and EfAlph to calculate relative titre of <em>S. symbiotica</em>