cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc1nvkjl
title: CCDC 1544870: Experimental Crystal Structure Determination

description: Related Article: D.S. Cati, H. Stoeckli-Evans|2017|Acta Crystallogr.,Sect.E:Cryst.Commun.|73|729|doi:10.1107/S2056989017005898
DOI: 10.5517/ccdc.csd.cc1nvkkm
title: CCDC 1544871: Experimental Crystal Structure Determination

description: Related Article: D.S. Cati, H. Stoeckli-Evans|2017|Acta Crystallogr.,Sect.E:Cryst.Commun.|73|729|doi:10.1107/S2056989017005898
DOI: 10.5517/ccdc.csd.cc1nw36v
title: CCDC 1545387: Experimental Crystal Structure Determination

description: Related Article: V. Piccialli, A. Tuzi, R. Centore|2017|Acta Crystallogr.,Sect.E:Cryst.Commun.|73|780|doi:10.1107/S2056989017006065
DOI: 10.5517/ccdc.csd.cc1nw45v
title: CCDC 1545417: Experimental Crystal Structure Determination

description: Related Article: C. Liu, A.C. Felts, D. Takahashi, W.S. Kinden, K.A. Abboud|2017|Acta Crystallogr.,Sect.E:Cryst.Commun.|73|777|doi:10.1107/S2056989017006090
DOI: 10.5517/ccdc.csd.cc1nw4f3
title: CCDC 1545425: Experimental Crystal Structure Determination

description: Related Article: J.J. Bankeu Kezetas, S. Dietagoum Madjouka, R. Kumar, M.S. Ali, B. Lenta Njakou, S. Yousuf|2017|Acta Crystallogr.,Sect.E:Cryst.Commun.|73|763|doi:10.1107/S2056989017006077
DOI: 10.5517/ccdc.csd.cc1nw6zq
title: CSD 1545504: Experimental Crystal Structure Determination

description: Related Article: G. Alhakmi, A. Assani, M. Saadi, L. El Ammari|2017|Acta Crystallogr.,Sect.E:Cryst.Commun.|73|767|doi:10.1107/S2056989017006120
DOI: 10.5517/ccdc.csd.cc1nw70s
title: CSD 1545505: Experimental Crystal Structure Determination

description: Related Article: G. Alhakmi, A. Assani, M. Saadi, L. El Ammari|2017|Acta Crystallogr.,Sect.E:Cryst.Commun.|73|767|doi:10.1107/S2056989017006120
DOI: 10.5517/ccdc.csd.cc1nw85z
title: CCDC 1545541: Experimental Crystal Structure Determination

description: Related Article: A.K. Bauri, S. Foro, A.F.M.M. Rahman|2017|Acta Crystallogr.,Sect.E:Cryst.Commun.|73|774|doi:10.1107/S2056989017006132
DOI: 10.15468/pgaf2x
title: Two rare species of Danielsseniinae (Copepoda: Harpacticoida: Pseudotachidiidae) from the Kara and East Siberian Seas, with description of their previously unknown sexes

description: This dataset contains the digitized treatments in Plazi based on the original journal article Garlitska, Lesya, Chertoprud, Elena S. (2021): Two rare species of Danielsseniinae (Copepoda: Harpacticoida: Pseudotachidiidae) from the Kara and East Siberian Seas, with description of their previously unknown sexes. Zootaxa 5051 (1): 94-100, DOI: https://doi.org/10.11646/zootaxa.5051.1.8
DOI: 10.5281/zenodo.5576217
title: Dataset of: Macros to Quantify Exosome release and Autophagy at the Neuromuscular Junction of Drosophila Melanogaster

description: Dataset of the future paper "Macros to Quantify Exosome release and Autophagy at the Neuromuscular Junction of Drosophila Melanogaster". If you have any doubts I can be found in this email: irene.sanchez-mirasierra@u-bordeaux.fr
DOI: 10.5281/zenodo.5576216
title: Dataset of: Macros to Quantify Exosome release and Autophagy at the Neuromuscular Junction of Drosophila Melanogaster

description: Dataset of the future paper "Macros to Quantify Exosome release and Autophagy at the Neuromuscular Junction of Drosophila Melanogaster". If you have any doubts I can be found in this email: irene.sanchez-mirasierra@u-bordeaux.fr
DOI: 10.21227/9s4y-e116
title: Thermal Sensation

description: This is a subset of the ASHRAE Global Comfort Database that we used in our study to prove that Deep learning methods performs better than shallow methods predicting the thermal sensation.
DOI: 10.15468/y2vx7t
title: A new species of Maraenobiotus Mrázek, 1893 (Copepoda: Harpacticoida Canthocamptidae) from Colombian Andean mosses, with an identification key for the American species

description: This dataset contains the digitized treatments in Plazi based on the original journal article Gaviria, Santiago, Defaye, Danielle (2021): A new species of Maraenobiotus Mrázek, 1893 (Copepoda: Harpacticoida Canthocamptidae) from Colombian Andean mosses, with an identification key for the American species. Zootaxa 5051 (1): 101-116, DOI: https://doi.org/10.11646/zootaxa.5051.1.9
DOI: 10.3886/e113685v1-99162
title: Replication data for: The Big Sort: College Reputation and Labor Market Outcomes

description: We explore how college reputation affects the "big sort," the process by which students choose colleges and find their first jobs. We incorporate a simple definition of college reputation—graduates' mean admission scores—into a competitive labor market model. This generates a clear prediction: if employers use reputation to set wages, then the introduction of a new measure of individual skill will decrease the return to reputation. Administrative data and a natural experiment from the country of Colombia confirm this. Finally, we show that college reputation is positively correlated with graduates' earnings growth, suggesting that reputation matters beyond signaling individual skill.
DOI: 10.5281/zenodo.4687979
title: ATLAS Enquête Coupons - enquête pilote

description: L'enquête Pilote Coupons Côte d'Ivoire vise à permettre une collecte de données auprès des utilisateurs finaux des kits<br> d'autodépistage du VIH (ADVIH) distribués dans le cadre du projet ATLAS. Elle repose sur l'anonymat et la participation<br> volontaire, à travers la mise en place d'une plateforme téléphonique anonyme et gratuite. Les objectifs principaux de l'enquête<br> Coupons sont de documenter le profil socio-comportemental et l'historique de dépistage des utilisatrices et utilisateurs de<br> l'ADVIH. L'enquête pilote s'est déroulées entre le 25 novembre 2019 et le 29 juin 2020 en Côte d'Ivoire et a abouti à 42<br> questionnaires complétés. <br> Le programme ATLAS (2019-2021) vise à promouvoir et à déployer l'autodépistage du VIH (ADVIH) en Côte d'Ivoire, au<br> Mali et au Sénégal et prévoit la distribution d'un demi millions d'autotests à travers différents canaux de dispensation, visant<br> en particulier les populations clés (travailleuses du sexe, hommes ayant des rapports sexuels avec des hommes, usager·e·s de<br> drogues), les partenaires des personnes vivant avec le VIH (PvVIH) et les patient·e·s atteint·e·s d'une infection sexuellement<br> transmissible. La dispensation des kits d'ADVIH est réalisée en soins courants, dans le cadre des stratégies nationales de<br> lutte contre le sida des trois pays et de manière intégrée aux politiques de dépistage déjà en place, à travers huit canaux de<br> dispensation combinant des stratégies fixes et des stratégies avancées, une distribution primaire et une distribution secondaire.
DOI: 10.6084/m9.figshare.16528446
title: Data used in Agronomy MDPI manuscript, Breeding for resilience to water deficit and its predicted effect on forage mass in tall fescue

description: This is the raw data used for analysis. This experiment examined the genetic parameters of a novel, direct measure of resilience to water deficit in tall fescue (<i>Lolium arundinaceum</i> [Schreb.] Darbysh.). Heritability, genetic correlations, and predicted gain from selection were estimated for average productivity, resilience, and stability based on forage mass of a tall fescue half-sib population grown under a linesource irrigation system with five different water levels (WL).
DOI: 10.6084/m9.figshare.16528446.v1
title: Data used in Agronomy MDPI manuscript, Breeding for resilience to water deficit and its predicted effect on forage mass in tall fescue

description: This is the raw data used for analysis. This experiment examined the genetic parameters of a novel, direct measure of resilience to water deficit in tall fescue (<i>Lolium arundinaceum</i> [Schreb.] Darbysh.). Heritability, genetic correlations, and predicted gain from selection were estimated for average productivity, resilience, and stability based on forage mass of a tall fescue half-sib population grown under a linesource irrigation system with five different water levels (WL).
DOI: 10.6084/m9.figshare.16826615
title: Exploring potential inhibitors against Kyasanur forest disease by utilizing molecular dynamics simulations and ensemble docking

description: Kyasanur forest disease (KFD) is a tick-borne, neglected tropical disease, caused by KFD virus (KFDV) which belongs to <i>Flavivirus</i> (Flaviviridae family). This emerging viral disease is a major threat to humans. Currently, vaccination is the only controlling method against the KFDV, and its effectiveness is very low. An effective control strategy is required to combat this emerging tropical disease using the existing resources. In this regard, <i>in silico</i> drug repurposing method offers an effective strategy to find suitable antiviral drugs against KFDV proteins. Drug repurposing is an effective strategy to identify new use for approved or investigational drugs that are outside the scope of their initial usage and the repurposed drugs have lower risk and higher safety compared to <i>de novo</i> developed drugs, because their toxicity and safety issues are profoundly investigated during the preclinical trials in human/other models. In the present work, we evaluated the effectiveness of the FDA approved and natural compounds against KFDV proteins using <i>in silico</i> molecular docking and molecular simulations. At present, no experimentally solved 3D structures for the KFD viral proteins are available in Protein Data Bank and hence their homology model was developed and used for the analysis. The present analysis successfully developed the reliable homology model of NS3 of KFDV, in terms of geometry and energy contour. Further, <i>in silico</i> molecular docking and molecular dynamics simulations successfully presented four FDA approved drugs and one natural compound against the NS3 homology model of KFDV. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.16826615.v1
title: Exploring potential inhibitors against Kyasanur forest disease by utilizing molecular dynamics simulations and ensemble docking

description: Kyasanur forest disease (KFD) is a tick-borne, neglected tropical disease, caused by KFD virus (KFDV) which belongs to <i>Flavivirus</i> (Flaviviridae family). This emerging viral disease is a major threat to humans. Currently, vaccination is the only controlling method against the KFDV, and its effectiveness is very low. An effective control strategy is required to combat this emerging tropical disease using the existing resources. In this regard, <i>in silico</i> drug repurposing method offers an effective strategy to find suitable antiviral drugs against KFDV proteins. Drug repurposing is an effective strategy to identify new use for approved or investigational drugs that are outside the scope of their initial usage and the repurposed drugs have lower risk and higher safety compared to <i>de novo</i> developed drugs, because their toxicity and safety issues are profoundly investigated during the preclinical trials in human/other models. In the present work, we evaluated the effectiveness of the FDA approved and natural compounds against KFDV proteins using <i>in silico</i> molecular docking and molecular simulations. At present, no experimentally solved 3D structures for the KFD viral proteins are available in Protein Data Bank and hence their homology model was developed and used for the analysis. The present analysis successfully developed the reliable homology model of NS3 of KFDV, in terms of geometry and energy contour. Further, <i>in silico</i> molecular docking and molecular dynamics simulations successfully presented four FDA approved drugs and one natural compound against the NS3 homology model of KFDV. Communicated by Ramaswamy H. Sarma
DOI: 10.18112/openneuro.ds002731.v1.0.2
title: Multiple interactive memory representations underlie the induction of false memory
DOI: 10.5281/zenodo.5091136
title: High-precision Aftershock Locations and Fault Planes of the 2016-2017 Central Italy Sequence

description: The earthquake catalog includes high-precision hypocenter relocations for 390,334<br> earthquakes recorded during the 2016-2017 Amatrice (Central Italy) <br> earthquake sequence. The relative locations were computed by double-difference inversion of a <br> combination of INGV phase picks and cross-correlation differential <br> times measured from correlated seismograms with correlation coefficients &gt; 0.7. Planes of normal faults (idx=1-5) are derived from PCA analysis of 2 months of aftershock <br> locations in the CAT4 catalog following large events. Surfaces of detachment faults (idx=7-10) are derived from mapping out the location of correlated earthquakes. Citation: Waldhauser, F., Michele, M., Chiaraluce, L., Di Stefano, R., & Schaff, D. P. (2021). Fault planes, fault zone structure and detachment fragmentation resolved with highprecision aftershock locations of the 2016-2017 central Italy sequence. Geophysical Research Letters, 48, e2021GL092918. https://doi.org/10.1029/2021GL092918
description: {"references": ["Waldhauser, F., Michele, M., Chiaraluce, L., Di Stefano, R., & Schaff, D. P. (2021). Fault planes, fault zone structure and detachment fragmentation resolved with high-precision aftershock locations of the 2016-2017 central Italy sequence. Geophysical Research Letters, 48, e2021GL092918. https://doi. org/10.1029/2021GL092918"]}
DOI: 10.5517/ccdc.csd.cc21fyjz
title: CCDC 1890241: Experimental Crystal Structure Determination

description: Related Article: Mingjuan Zhang|2019|CSD Communication|||
description: Related Article: Yunmei Du, Hongdong Li, Zuochao Wang, Mingjuan Zhang, Kang Liu, Yongjun Liu, Ruixin Chen, Lei Wang|2019|J.Mol.Struct.|1196|828|doi:10.1016/j.molstruc.2019.07.028
DOI: 10.5517/ccdc.csd.cc21fyk0
title: CCDC 1890242: Experimental Crystal Structure Determination

description: Related Article: Mingjuan Zhang|2019|CSD Communication|||
description: Related Article: Yunmei Du, Hongdong Li, Zuochao Wang, Mingjuan Zhang, Kang Liu, Yongjun Liu, Ruixin Chen, Lei Wang|2019|J.Mol.Struct.|1196|828|doi:10.1016/j.molstruc.2019.07.028
DOI: 10.5517/ccdc.csd.cc21fyl1
title: CCDC 1890243: Experimental Crystal Structure Determination

description: Related Article: Mingjuan Zhang|2019|CSD Communication|||
description: Related Article: Yunmei Du, Hongdong Li, Zuochao Wang, Mingjuan Zhang, Kang Liu, Yongjun Liu, Ruixin Chen, Lei Wang|2019|J.Mol.Struct.|1196|828|doi:10.1016/j.molstruc.2019.07.028
DOI: 10.5517/ccdc.csd.cc21gkdh
title: CCDC 1890826: Experimental Crystal Structure Determination

description: Related Article: Munisamy Manjunathan, Krishnamoorthy Anbalagan|2019|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc21gkfj
title: CCDC 1890827: Experimental Crystal Structure Determination

description: Related Article: Munisamy Manjunathan, Krishnamoorthy Anbalagan|2019|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc24h0k7
title: CCDC 1980638: Experimental Crystal Structure Determination

description: Related Article: Yang Bai|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc24h0j6
title: CCDC 1980637: Experimental Crystal Structure Determination

description: Related Article: Yang Bai|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc25fzm7
title: CCDC 2009439: Experimental Crystal Structure Determination

description: Related Article: Guang-Jian Mei, Jonathan J. Wong, Wenrui Zheng, Anjanay A. Nangia, K.N. Houk, Yixin Lu|2021|Cell Press: Chem|7|2743|doi:10.1016/j.chempr.2021.07.013
DOI: 10.5517/ccdc.csd.cc25kdv0
title: CCDC 2012732: Experimental Crystal Structure Determination

description: Related Article: Guang-Jian Mei, Jonathan J. Wong, Wenrui Zheng, Anjanay A. Nangia, K.N. Houk, Yixin Lu|2021|Cell Press: Chem|7|2743|doi:10.1016/j.chempr.2021.07.013
DOI: 10.5517/ccdc.csd.cc25s4ch
title: CCDC 2019196: Experimental Crystal Structure Determination

description: Related Article: Andrey Ilyukhin|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26h7kj
title: CCDC 2040437: Experimental Crystal Structure Determination

description: Related Article: Yan-Feng Deng, Li-Ping Cui, Jing-Hua Lv, Yuan Guan, Yuhang Liu, Xingzhi Liu, Kai Yu|2021|J.Solid State Chem.|295|121941|doi:10.1016/j.jssc.2020.121941
DOI: 10.5517/ccdc.csd.cc26r4bg
title: CCDC 2048025: Experimental Crystal Structure Determination

description: Related Article: Rama Krishna Gamidi, Monica Dandawate, Srinu Tothadi, Rahul Choudhury, Ashwini K. Nangia, D. Srinivasa Reddy|2021|CrystEngComm|23|7056|doi:10.1039/D1CE01055G
DOI: 10.5517/ccdc.csd.cc27zf2r
title: CCDC 2084814: Experimental Crystal Structure Determination

description: Related Article: Arkalekha Mandal, Youngmee Kim, Sung-Jin Kim, JaeHong Park|2021|CrystEngComm|23|7132|doi:10.1039/D1CE00741F
DOI: 10.5517/ccdc.csd.cc27zzw3
title: CCDC 2085366: Experimental Crystal Structure Determination

description: Related Article: Jie Huang, Shaofa Sun, Ping Ma, Jian Wang, Kevin Lee, Yalan Xing, Yang Wu, Gangqiang Wang|2021|New J.Chem.|45|18776|doi:10.1039/D1NJ02886C
DOI: 10.5517/ccdc.csd.cc2821l0
title: CCDC 2087341: Experimental Crystal Structure Determination

description: Related Article: Chu-Xing Hu, Ya-Hui Xuan, Zi-Hao Jiang, Tao Lu, Jie Yang, Hui Yuan, You-Ping Tian, Zheng-Guang Sun, Xuan-Feng Jiang|2021|CrystEngComm|23|7179|doi:10.1039/D1CE01069G
DOI: 10.5063/f1gt5km2
title: A GBIF reptile and amphibian analysis of burn sites in Southwestern, USA

description: The purpose of this dataset is to evaluate the impact of fires on reptile and amphibian biodiversity in California's southwest desert. Species data was downloaded from the Global Diversity Information Facility (GBIF).GBIF.org (28 July 2021) GBIF Occurrence Download https://doi.org/10.15468/dl.6kvrr7
DOI: 10.6084/m9.figshare.16676656
title: Data

description: The modelled concentrations with different vegetation flux inputs and background concentrations are added in the modeldata.csv. Regional sensitivity index for 2017 and 2018 are added seperately. The regions definition used in the ms is given as a csv file, regmap
DOI: 10.6084/m9.figshare.16676656.v3
title: Data

description: The modelled concentrations with different vegetation flux inputs and background concentrations are added in the modeldata.csv. Regional sensitivity index for 2017 and 2018 are added seperately. The regions definition used in the ms is given as a csv file, regmap
DOI: 10.6084/m9.figshare.16676656.v2
title: Data

description: The modelled concentrations with different vegetation flux inputs and background concentrations are added in the modeldata.csv. Regional sensitivity index for 2017 and 2018 are added seperately. The regions definition used in the ms is given as a csv file, regmap
DOI: 10.5066/p9m64cd1
title: Data used to model and map manganese in the Northern Atlantic Coastal Plain aquifer system, eastern USA

description: Data used to model and map manganese concentrations in groundwater in the Northern Atlantic Coastal Plain (NACP) aquifer system, eastern USA, are documented in this data release. The model predicts manganese concentration within four classes and is based on concentration data from 4492 wells. The well data were compiled from U.S. Geological Survey, U.S. Environmental Protection Agency, Suffolk County Water Authority (Suffolk County, New York), and state agency sources. The four concentration classes are based on guidelines for drinking water quality: below detection (class 1, less than 10 micrograms per liter (ug/L)); detected but less than the aesthetic guideline of 50 ug/L (class 2); greater than the aesthetic guideline but less than the health guideline of 300 ug/L (class 3); and greater than the health guideline of 300 ug/L (class 4). The thresholds of 50 ug/L and 300 ug/L are a Secondary Maximum Contaminant Level and a lifetime health advisory, respectively, from the U.S. Environmental Protection Agency for public water supplies. The model is built with the XGboost machine learning method. Explanatory variables (predictors) include well depth, soil characteristics, hydrologic variables, groundwater residence time, and predicted values of pH and of the probability of low dissolved oxygen from previous machine learning models of the aquifer system. The data are provided in data tables, raster files, and model files, organized as follows. One data table describes the 27 explanatory variables used in the model (NACP_Mn_explanatory_variables.csv). There is a data table for the well data used to develop the models, which includes the manganese concentrations, concentration classes, regional aquifer, explanatory variables, and predicted concentration class for the wells (NACP_Mn_well_data.csv). There is a compressed group (zip file) of 10 files (one for each regional aquifer) for explanatory variable data used to make predictions for the regional aquifers (NACP_Mn_prediction_input_aquifers.zip). There are two zip files providing model output, one for predictions made for each aquifer in text format and one for tif-format rasters of predictions for each aquifer. The data release also contains a tif-format raster file of the prediction grid and a zip file with the model object file (R data format) and a script that can be used to run the model to produce the predictions provided in this data release. Filenames for prediction input and for model output are distinguished by codes abbreviating the aquifer name and position in the vertical stack of 19 regional aquifers and confining units, as follows: Surficial aquifer, 1surf; Upper Chesapeake aquifer, 3upch; Lower Chesapeake aquifer, 5loch; Piney Point aquifer, 7pipt; Aquia aquifer, 9aqia; Monmouth - Mt. Laurel Aquifer, 11moml; Matawan aquifer, 13mtwn; Magothy Aquifer, 15mgty; Potomac-Patapsco aquifer, 17popt; Potomac-Patuxent aquifer, 19popx. The nine confining units are not represented in the model or predictions.
DOI: 10.5519/qd.2020b3fx
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (40 records)
DOI: 10.6084/m9.figshare.16821361
title: Integrating occupancy models - Data and Novel Code

description: Supplemental information for the Ecosphere manuscript "Integrating multi-method surveys and recovery trajectories into occupancy models". Includes detection-non detection data for <i>Pekania pennanti</i> in Oregon from cameras and detection dogs, a spatial extent model using reaction-diffusion equations, and novel occupancy code.
DOI: 10.15468/u64bbr
title: New records of Pseudotachidiidae from South Korea, including a key to species of the Pseudomesochrinae (Copepoda: Harpacticoida)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Kim, Jong Guk, Lee, Jimin, Huys, Rony (2021): New records of Pseudotachidiidae from South Korea, including a key to species of the Pseudomesochrinae (Copepoda: Harpacticoida). Zootaxa 5051 (1): 387-422, DOI: https://doi.org/10.11646/zootaxa.5051.1.16
DOI: 10.6084/m9.figshare.16826740
title: Data for the "Coupling traction force patterns and actomyosin wave dynamics reveals mechanics of cell motion"

description: Data for the "Coupling traction force patterns and actomyosin wave dynamics reveals mechanics of cell motion", Elisabeth Ghabache, Yuansheng Cao, Yuchuan Miao, Alex Groisman, Peter N. Devreotes, Wouter-Jan RappelThe data is presented in .mat files and corresponds to Figs. 2-6 in the study.
DOI: 10.6084/m9.figshare.14192102
title: Supplementary Material of the article "Flora of Ceará, Brazil: Loranthaceae"

description: Supplementary Material of the article "Flora of Ceará, Brazil: Loranthaceae"<br>Contains<br>- a shapefile (*.shp) with the distrbution of Loranthaceae in Ceará- a spreadsheet (*.xlsx) with raw data
DOI: 10.5281/zenodo.5576233
title: Rotating shallow water flow under location uncertainty with a structure-preserving discretization -- Data set

description: With this data set one can reproduce the figures in the manuscript "Rotating shallow water flow under location uncertainty with a structure-preserving discretization". The figures can be created with the following MATLAB scripts: Figure 3 - plot_contour_plane.m Figure 4 and 5 - plot_Energy_convergence.m Figure 6 - plot_sphere_snapshot.m Figure 7 - plot_contour_sphere.m Figure 8 - plot_specs.m Figure 9 - plot_spread.m Figure 10 - createhist.m Figure 11 - plot_MSB_MEV.m