cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6073/pasta/cf046a6e84bfbae9602182fcf57fb800
title: North Temperate Lakes LTER: Chemical Limnology of Primary Study Lakes: Nutrients, pH and Carbon 1981 - current

description: Parameters characterizing the nutrient chemistry of the eleven primary lakes (Allequash, Big Muskellunge, Crystal, Sparkling, and Trout lakes, unnamed lakes 27-02 [Crystal Bog] and 12-15 [Trout Bog], Mendota, Monona, Wingra, and Fish) are measured at one station in the deepest part of each lake at the top and bottom of the epilimnion, mid-thermocline, and top, middle, and bottom of the hypolimnion. These parameters include total nitrogen, total dissolved nitrogen (only in the northern lakes), nitrate, ammonia, total phosphorus, total dissolved phosphorus (only in the northern lakes), dissolved reactive phosphorus (only in the southern lakes and not in Wingra and Fish after 2003), bicarbonite-reactive filtered and unfiltered silica (both discontinued in 2003), dissolved reactive silica, field pH, air equilibrated pH, total alkalinity, total inorganic carbon, dissolved inorganic carbon, total organic carbon, dissolved organic carbon, and total particulate matter (only in the northern lakes in this data set. Total particulate matter in southern lakes starting in 2000 is available in a separate dataset). Sampling Frequency: monthly during ice-free season - every 6 weeks during ice-covered season for the northern lakes. The southern lakes are similar except that sampling occurs monthly during the fall and typically only once during the winter (depending on ice conditions). Number of sites: 11
DOI: 10.5517/ccdc.csd.cc2bl638
title: CCDC 2162439: Experimental Crystal Structure Determination

description: Related Article: Kechang Li, Qiao Chen, Pengchong Xue|2022|Tetrahedron|121|132924|doi:10.1016/j.tet.2022.132924
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.cc2bl6qw
title: CCDC 2162458: Experimental Crystal Structure Determination

description: Related Article: Kechang Li, Qiao Chen, Pengchong Xue|2022|Tetrahedron|121|132924|doi:10.1016/j.tet.2022.132924
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.cc2bsskh
title: CCDC 2168777: Experimental Crystal Structure Determination

description: Related Article: Qi-Wei Lang, Xiang-Yang Qian, Xiu-Lin He, Hui Geng, Jian-Feng Zheng, Pei-Qiang Huang|2022|Tetrahedron|122|132935|doi:10.1016/j.tet.2022.132935
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.cc2c4l37
title: CCDC 2179148: Experimental Crystal Structure Determination

description: Related Article: Yuan Gao, Jun-Su Zhou, Hong-Chun Liu, Yan Zhang, Wei-Hang Yin, Qun-Fang Liu, Guan-Wu Wang, Jin-Xin Zhao, Jian-Min Yue|2022|Tetrahedron|123|132955|doi:10.1016/j.tet.2022.132955
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.cc2c4pdm
title: CCDC 2179250: Experimental Crystal Structure Determination

description: Related Article: Yuan Gao, Jun-Su Zhou, Hong-Chun Liu, Yan Zhang, Wei-Hang Yin, Qun-Fang Liu, Guan-Wu Wang, Jin-Xin Zhao, Jian-Min Yue|2022|Tetrahedron|123|132955|doi:10.1016/j.tet.2022.132955
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.cc2c861x
title: CCDC 2182618: Experimental Crystal Structure Determination

description: Related Article: Constantine V. Milyutin, Andrey N. Komogortsev, Boris V. Lichitsky, Valerie G. Melekhina|2022|Tetrahedron|124|133012|doi:10.1016/j.tet.2022.133012
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.cc2c862y
title: CCDC 2182619: Experimental Crystal Structure Determination

description: Related Article: Constantine V. Milyutin, Andrey N. Komogortsev, Boris V. Lichitsky, Valerie G. Melekhina|2022|Tetrahedron|124|133012|doi:10.1016/j.tet.2022.133012
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: 10.5281/zenodo.7268417
title: Data files for "Stripe correlations in the two-dimensional Hubbard-Holstein model" by S. Karakuzu et al.

description: Data files for the manuscript "Stripe correlations in the two-dimensional Hubbard-Holstein model" by S. Karakuzu et al. To appear in Communications Physics. Preprint available at https://arxiv.org/abs/2205.15464 (2022). This work was supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, under Award Number<br> DE-SC0022311.
DOI: 10.5281/zenodo.7268416
title: Data files for "Stripe correlations in the two-dimensional Hubbard-Holstein model" by S. Karakuzu et al.

description: Data files for the manuscript "Stripe correlations in the two-dimensional Hubbard-Holstein model" by S. Karakuzu et al. To appear in Communications Physics. Preprint available at https://arxiv.org/abs/2205.15464 (2022). This work was supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, under Award Number<br> DE-SC0022311.
DOI: 10.17632/2hr96vkkfc.1
title: What determines root-sprouting ability: injury or phytohormones?

description: The file includes all the data presented in the manuscript:
Martínková et al. What determines root-sprouting ability: injury or phytohormones?
American Journal of 

There two sheets in the excel file:
1. a sheet with the data on phytohormones
2. a sheet with the data on biomass, buds and root respiration

Please see the Methods section of the manuscript for all abbreviations and parameters measured in this study.
DOI: 10.17632/xvyp2ph8jh.1
title: Behavioral and fMRS results of visual perceptual learning in children and adults

description: This dataset includes the results from a study in which mechanisms of visual perceptual learning (VPL) were investigated by training children (8 – 11 years old) and adults (18 – 35 years old) on a visual orientation detection task for VPL. The dataset includes visual orientation detection thresholds from (1) a behavioral pilot experiment to determine sample size, (2) an imaging experiment and (3) two behavioral experiments. In each experiment a total of 14 new participants per age group were tested (note that the results from one child in the imaging experiment were excluded due to insufficient imaging data quality). Furthermore, imaging results (i.e., concentrations of γ-aminobutyric acid and N-acetyl-aspartate and N-acetyl-aspartyl-glutamate) from measurements using functional magnetic resonance spectroscopy (fMRS) are included.
DOI: 10.17632/645m9kd7bm.1
title: Practically: Options trading

description: This article will discuss options trading which is a wide term and analysis of past 16 year of data, but here, an explanation for and past data analysis for the Israeli stock market will be explained in more detail. More over a sensitivity analysis will be done for past 16 years of data, based on that a success chance will be displayed. This is just a theoretical Analysis of past data. Some might relate to Option trading as complex and dangerous but the illustration here will try to relate to it as a simple and understandable matter.
DOI: 10.17632/645m9kd7bm.2
title: Practically: Options trading

description: This article will discuss options trading which is a wide term and analysis of past 16 year of data, but here, an explanation for and past data analysis for the Israeli stock market will be explained in more detail. More over a sensitivity analysis will be done for past 16 years of data, based on that a success chance will be displayed. This is just a theoretical Analysis of past data. Some might relate to Option trading as complex and dangerous but the illustration here will try to relate to it as a simple and understandable matter.
DOI: 10.17632/645m9kd7bm.3
title: Practically: Options trading

description: This article will discuss options trading which is a wide term and analysis of past 16 year of data, but here, an explanation for and past data analysis for the Israeli stock market will be explained in more detail. More over a sensitivity analysis will be done for past 16 years of data, based on that a success chance will be displayed. This is just a theoretical Analysis of past data. Some might relate to Option trading as complex and dangerous but the illustration here will try to relate to it as a simple and understandable matter.
DOI: 10.17632/645m9kd7bm.4
title: Practically: Options trading

description: This article will discuss options trading which is a wide term and analysis of past 16 year of data, but here, an explanation for and past data analysis for the Israeli stock market will be explained in more detail. More over a sensitivity analysis will be done for past 16 years of data, based on that a success chance will be displayed. This is just a theoretical Analysis of past data. Some might relate to Option trading as complex and dangerous but the illustration here will try to relate to it as a simple and understandable matter.
DOI: 10.17632/w3hgskv49m.1
title: Practically: Trendline for non statisticians

description: This article will discuss how to calculate and display  a trendline on a tabular using very simple linear regression, usage of very simple statistical methods for linear regression will be used and and it will be explained and demonstrated on a given data on a data grid. Although we have built in abilities into spreadsheets such as google sheets or microsoft excel, sometimes there is a need to create a trendline manually and for this purpose the methodology of creating trend lines will be explained here. Mainly this is used by programmers to use this method for creating a functionality to display trendlines on charts for some other type of usages to be used at Business intelligence platforms.
DOI: 10.17632/w3hgskv49m.2
title: Practically: Trendline for non statisticians

description: This article will discuss how to calculate and display  a trendline on a tabular using very simple linear regression, usage of very simple statistical methods for linear regression will be used and and it will be explained and demonstrated on a given data on a data grid. Although we have built in abilities into spreadsheets such as google sheets or microsoft excel, sometimes there is a need to create a trendline manually and for this purpose the methodology of creating trend lines will be explained here. Mainly this is used by programmers to use this method for creating a functionality to display trendlines on charts for some other type of usages to be used at Business intelligence platforms.
DOI: 10.17632/przhxygkkm.1
title: Gastrodia elata Blume extract improves high-fat diet-induced type 2 diabetes by regulating gut microbiota and bile acid metabolism

description: We used 16S rRNA sequencing with bile acid metabolomics to find that GEB extract (GEBE) improved the intestinal microbiota and increased serum secondary bile acid levels in high-fat diet (HFD)-induced mice, as well as GLUT4 expression on white adipose tissue (WAT) and improved insulin resistance in the organism.
DOI: 10.17632/przhxygkkm.2
title: Gastrodia elata Blume extract improves high-fat diet-induced type 2 diabetes by regulating gut microbiota and bile acid metabolism

description: We used 16S rRNA sequencing with bile acid metabolomics to find that GEB extract (GEBE) improved the intestinal microbiota and increased serum secondary bile acid levels in high-fat diet (HFD)-induced mice, as well as GLUT4 expression on white adipose tissue (WAT) and improved insulin resistance in the organism.
DOI: 10.17632/przhxygkkm.3
title: Gastrodia elata Blume extract improves high-fat diet-induced type 2 diabetes by regulating gut microbiota and bile acid metabolism

description: We used 16S rRNA sequencing with bile acid metabolomics to find that GEB extract (GEBE) improved the intestinal microbiota and increased serum secondary bile acid levels in high-fat diet (HFD)-induced mice, as well as GLUT4 expression on white adipose tissue (WAT) and improved insulin resistance in the organism.
DOI: 10.6084/m9.figshare.21440739
title: Example babyAFQ BIDS subject

description: Example subject in BIDS for use with babyAFQ. Includes tractography and other derivatives generated by MRtrix.
DOI: 10.17632/ydsswp72zr.5
title: Practically: Weighted Standard deviation for non statisticians

description: This article will discuss how to find weighted standard deviation of groups while there is no data about the individuals inside the groups. Sometimes we have partial information about averages values and groups with weight of the group but how can we find out the standard deviation of the whole groups without the measurements of each individual? a suggestion, verification and practical example will be shown.
DOI: 10.17632/ydsswp72zr.1
title: Weighted Standard deviation

description: his article will discuss how to find weighted standard deviation of a group of populations while there is no data about the individuals. Sometimes we have partial information about averages values and groups with weight of the group but how can we find out the standard deviation of the whole groups without the measurements of each individual? a suggestion, verification and practical example will be shown.
DOI: 10.17632/ydsswp72zr.2
title: Weighted Standard deviation

description: This article will discuss how to find weighted standard deviation of a group of populations while there is no data about the individuals. Sometimes we have partial information about averages values and groups with weight of the group but how can we find out the standard deviation of the whole groups without the measurements of each individual? a suggestion, verification and practical example will be shown.
DOI: 10.17632/ydsswp72zr.3
title: Weighted Standard deviation

description: This article will discuss how to find weighted standard deviation of groups while there is no data about the individuals inside the groups. Sometimes we have partial information about averages values and groups with weight of the group but how can we find out the standard deviation of the whole groups without the measurements of each individual? a suggestion, verification and practical example will be shown.
DOI: 10.17632/ydsswp72zr.4
title: Practically: Weighted Standard deviation for non statisticians

description: This article will discuss how to find weighted standard deviation of groups while there is no data about the individuals inside the groups. Sometimes we have partial information about averages values and groups with weight of the group but how can we find out the standard deviation of the whole groups without the measurements of each individual? a suggestion, verification and practical example will be shown.
DOI: 10.17632/ydsswp72zr.6
title: Practically: Weighted Standard deviation for non statisticians

description: This article will discuss how to find weighted standard deviation of groups while there is no data about the individuals inside the groups. Sometimes we have partial information about averages values and groups with weight of the group but how can we find out the standard deviation of the whole groups without the measurements of each individual? a suggestion, verification and practical example will be shown.
DOI: 10.17632/9jwffh873s.1
title: MICADO

description: Estimation data for the article: "Reducing ethnic discrimination through formal warning: evidence from two combined field experiments"
DOI: 10.17632/jznmb7mxpm.1
title: Solid state NMR spectra and molecular dynamics (MD) simulation trajectories of brain-derived Abeta42 fibrils

description: 2D NCACX, NCA, CC, and HC solid state NMR spectra of brain-derived Ab42 fibrils. Spectra are in Sparky format (*.ucsf files).  200 ns of molecular dynamics (MD) simulation trajectories of brain-derived type A and type B Ab42 fibrils. Eight Ab42 molecules with the type A and type B fibril structure were solvated and neutralized in 100 mM NaCl.  See README.txt file for additional details.
DOI: 10.17632/fpy65wn6gt.1
title: LINF_330028600

description: serine/threonine-protein kinase
Leishmania infantum (strain JPCM5)
DOI: 10.17632/n6rstzb6r6.1
title: LINF_330028900

description: calpain protease-like protein | CAL33.1
Leishmania infantum (strain JPCM5)
DOI: 10.17632/pz5z4629dg.1
title: LINF_330029300

description: Nucleoporin | NUP89
Leishmania infantum (strain JPCM5)
DOI: 10.17632/762894kgyp.1
title: LINF_330029600

description: mitogen-activated protein kinase | MPK15
Leishmania infantum (strain JPCM5)
DOI: 10.17632/cwmnpbdx8n.1
title: SUBCONJUCTIVAL MOBILE MASS AFTER HYALUROINC ACID FILLER INJECTION

description: A rare phenomenon of freely movable subconjunctival mass that developed as a complication of HA filler spreading away from its original site of injection
DOI: 10.17632/6yknx5z7bx.1
title: LINF_330030000

description: phosphoglycerate mutase
Leishmania infantum (strain JPCM5)
DOI: 10.17632/j7sygcyswb.1
title: Nested Sampling of Materials' Potential Energy Surfaces: Case Study of Zirconium

description: The nested sampling (NS) method was originally proposed by John Skilling 
to calculate the evidence in Bayesian inference. The method has since been utilised in various research fields, and here we focus on how NS has been adapted to sample the Potential Energy Surface (PES) of atomistic systems, enabling the straightforward estimation of the partition function.
Using two interatomic potential models of zirconium, we demonstrate the workflow and advantages of using nested sampling to calculate pressure-temperature phase diagrams.
Without any prior knowledge of the stable phases or the phase transitions, we are able to identify the melting line, as well as the transition between the body-centred-cubic and hexagonal-close-packed structures.
Supporting data for Proceedings paper of MaxEnt Conference 2022.
DOI: 10.17632/89pj7z5br9.1
title: Air ion concentrations, aerosol size distribution and electric charge state, and potential gradient upwind and downwind of AC high-voltage powerlines

description: Data should be read in conjunction with associated paper (submitted for peer review as at 31-Oct-2022) where Materials and Methods are described.

"Time Series Data" file shows time series of ion concentrations and charge asymmetry values for each individual measurement obtained using ACIMS (described in Fews et al 2005, DOI:10.1016/j.atmosres.2004.11.008). Where additional analysis was undertaken (splitting raw data into separate negative and positive half-cycles, or determining concentration of intermediate ions) these are presented as additional columns. If no data is present in a column, no data was collected for that parameter during that measurement. Note that the times of data are not necessarily coincident with each other due to instrumental issues.

"Particle Data" file shows the particle number size distribution obtained using SMPS+C (Grimm Aerosol Technik) including statistical parameters (total number concentration, geometric mean diameter and geometric standard deviation of the size distribution (first table, headed Number Size Distribution), raw count data for the charge-conditioned SMPS+C (second table, headed 'NEUT'), raw count data for the ambient mobility SMPS+C (third table, headed 'NO NEUT') and the results of the fitting procedure described in Buckley et al., 2008 DOI:10.1080/02786820802400645 (fourth table, headed 'FIT') for each individual SMPS+C cycle on each measurement occasion.

"PG" files contain raw potential gradient (PG) data obtained using a JCI 131 electrostatic field mill meter at 1 s intervals for each of the case studies (5 measurement days) presented.

Throughout these files the following abbreviations are used:
2-letter site codes (e.g. HH) are described in Table 1 in the associated paper
UW = upwind of HVPL
DW = downwind of HVPL
BG = background site away from HVPL
PG = atmospheric potential gradient
DOI: 10.17632/mh9gjbw4yv.1
title: British Public Investment, Government Spending, Housing, and the Industrial Revolution

description: Data for paper of same name and drawn from other works.
DOI: 10.17632/txnvtdw2zs.1
title: GPI-Anchored Ligand-BioID2-Tagging System Identifies Galectin-1 Mediating Zika Virus Entry Gao et al

description: Identification of host factors facilitating pathogen entry is critical for preventing infectious diseases. Here, we report a tagging system consisting of a viral receptor-binding protein (RBP) linked to BioID2, which is expressed on the cell surface via a GPI anchor. Using VSV or Zika virus (ZIKV) RBP, the system (BioID2- RBP(V)-GPI; BioID2-RBP(Z)-GPI) faithfully identifies LDLR and AXL, the receptors of VSV and ZIKV, respectively. Being GPI-anchored is essential for the probe to function properly. Furthermore, BioID2-RBP(Z)-GPI expressed in human neuronal progenitor cells identifies galectin-1 on cell surface pivotal for ZIKV entry. This conclusion is further supported by antibody blocking and galectin-1 silencing in A549 and mouse neural cells. Importantly, Lgas1-/- mice are significantly more resistant to ZIKV infection than Lgas1+/+ littermates are, having significantly lower virus titers and fewer pathologies in various organs. This tagging system may have broad applications for identifying protein-protein interactions on the cell surface.