cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6993482
title: Database_Modelo de mediación

description: This information contains the database of the systematic literature review of mediation models for online learning and perspectives for open innovation period 2015 - 2021.
DOI: 10.5281/zenodo.6944134
title: Data files associated with the article entitled: "High-throughput behavioral phenotyping of tiny arthropods: chemosensory traits in a mesostigmatic hematophagous mite" (accepted in Journal of Experimental Zoology - part A))

description: Here are provided three groups of datasets, corresponding respectively to the data obtained from MiteMap bioassays (1) with the monomolecular reference substances (geraniol and NH<sub>3</sub>), (2) with the patented blend MIX1.0, (3) with the odors emitted by the mites' bodies. These datasets were analyzed using the script provided in RMarkdown format in the Zenodo repository DOI 10.5281/zenodo.6109388. A folder is also provided with the heatmaps associated with these data grouped in subfolders by farm x modality.
DOI: 10.5281/zenodo.6103005
title: Data files associated with the article entitled: "High-throughput behavioral phenotyping of tiny arthropods: chemosensory traits in a mesostigmatic hematophagous mite" (accepted in Journal of Experimental Zoology - part A))

description: Here are provided three groups of datasets, corresponding respectively to the data obtained from MiteMap bioassays (1) with the monomolecular reference substances (geraniol and NH<sub>3</sub>), (2) with the patented blend MIX1.0, (3) with the odors emitted by the mites' bodies. These datasets were analyzed using the script provided in RMarkdown format in the Zenodo repository DOI 10.5281/zenodo.6109388. A folder is also provided with the heatmaps associated with these data grouped in subfolders by farm x modality.
DOI: 10.5281/zenodo.6821576
title: Source Data for Xiao et al., Topological Superfluid Defects with Discrete Point Group Symmetries , Nature Communications 13, 4635 (2022).

description: Source data for Figures 2-5. Source data for Supplementary Figures S2-S5 available upon request to David Hall (dshall@amherst.edu).
DOI: 10.5281/zenodo.6821575
title: Source Data for Xiao et al., Topological Superfluid Defects with Discrete Point Group Symmetries , Nature Communications 13, 4635 (2022).

description: Source data for Figures 2-5. Source data for Supplementary Figures S2-S5 available upon request to David Hall (dshall@amherst.edu).
DOI: 10.48493/tm6j-fq61
title: Historical database of equines in Crete
DOI: 10.5517/ccdc.csd.cc260t35
title: CCDC 2026566: Experimental Crystal Structure Determination

description: Related Article: Lei-Lei Qian, Yan-Cheng Hu, Xiang-Ting Min, Sa-Na Yang, Bing-Xue Shen, Boshun Wan, Qing-An Chen|2022|Chem Cat.|2|2024|doi:10.1016/j.checat.2022.05.023
description: Related Article: leilei qian|2021|CSD Communication|||
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: 10.5066/p9qax4ei
title: Duplicate Stream Sample Analyses by Laboratories of the U.S. Geological Survey New York Water Science Center and Adirondack Lake Survey Corporation Applied to Adirondack Stream Monitoring Data, 2003-2017

description: This dataset contains a comparison of chemical analysis results obtained by the U.S. Geological Survey (USGS) New York Water Science Center Soil and Low-Ionic Strength Water Quality Laboratory and the Adirondack Lake Survey Corporation (ALSC) Laboratory. Duplicate samples were collected biweekly from Buck Creek and the North and South Tributaries of Buck Creek from September 5, 2006, through September 2, 2008, to be analyzed in each laboratory. The 155 pairs of samples collected over 2 years enabled comparisons to be made under a variety of flows and seasons, using the markedly different chemical characteristics of the three streams. An additional 6 duplicate samples collected in 2016-2017 from Buck Creek were analyzed in each laboratory [...]
DOI: 10.6084/m9.figshare.20490105
title: crax_fasciolata_decontaminated_FSCR

description: .......
DOI: 10.6084/m9.figshare.20490105.v1
title: crax_fasciolata_decontaminated_FSCR

description: .......
DOI: 10.21227/2w1y-cy57
title: Inner-body dataset

description: coming soon
DOI: 10.6084/m9.figshare.20490138
title: crax_fasciolata_decontaminated_gx

description: ......
DOI: 10.6084/m9.figshare.20490138.v1
title: crax_fasciolata_decontaminated_gx

description: ......
DOI: 10.6069/rje1-xf11
title: Plasma proteomic analysis to identify potential biomarkers of histologic chorioamnionitis in women with preterm premature rupture of membranes

description: Introduction: To identify potential biomarkers in the plasma that could predict histologic chorioamnionitis (HCA) in women with preterm premature rupture of membranes (PPROM), using shotgun and targeted proteomic analyses. 

Methods: This retrospective cohort study included 77 singleton pregnant women with PPROM (24–34 gestational weeks) who delivered within 96 h of blood sampling. Maternal plasma samples were analyzed by label-free liquid chromatography-tandem mass spectrometry for proteome profiling in a nested case-control study design (HCA cases vs. non-HCA controls [n=9 each]). Differential expression of 12 candidate proteins was assessed by multiple reaction monitoring-mass spectrometry (MRM-MS) analysis in individual plasma samples from cases and controls matched by gestational age at sampling (n=40, cohort 1). A validation study was further performed in an independent study group (n=39, cohort 2) using ELISA and turbidimetric immunoassay for three differentially expressed proteins.

Results: Shotgun proteomics analyses yielded 18 proteins that were differentially expressed (P < 0.05) between HCA cases and non-HCA controls. MRM-MS analysis of 12 differentially expressed proteins further revealed that the CRP, C4A, and SAA4 levels were significantly increased in women with HCA. A multi-marker panel comprising plasma SAA4 and C4A showed enhanced potential for differentiating HCA from non-HCA women (area under the curve=0.899). Additional validation of these findings by ELISA assays revealed that the CRP levels were significantly higher in women with HCA than in those without HCA, whereas the plasma levels of C4A and SAA4 did not significantly differ between the two groups.


Conclusions: Plasma C4A, SAA4, and CRP were identified as potential biomarkers for detecting HCA in women with PPROM, based on targeted and shotgun proteomic analyses, showing good accuracy when used as a combined dual-biomarker panel (C4A and SAA4). Nonetheless, ELISA validation of these proteins, except for CRP, may reflect clinically useful markers for predicting HCA
DOI: 10.25573/serc.20054420.v2
title: 2022 Water Quality Data, Upper Chesapeake Bay, MarineGEO, Smithsonian Environmental Research Center

description: 2022 water quality data collected on a YSI EXO2 multiparameter sonde at the MarineGEO Upper Chesapeake Bay observatory (Smithsonian Environmental Research Center, Edgewater, MD, USA). The figshare resource also contains quality control metadata to assist interpretation and analysis. Review the "readme.txt" file for more information. Location: 38.886928, -76.540172
DOI: 10.25573/serc.20054633.v1
title: 2022 Water Quality Data, Indian River Lagoon, MarineGEO, Smithsonian Marine Station

description: 2022 water quality data collected on a YSI EXO2 multiparameter sonde at the MarineGEO Indian River Lagoon observatory (Smithsonian Marine Station, Ft. Pierce, FL, USA). The figshare resource also contains quality control metadata to assist interpretation and analysis. Review the "readme.txt" file for more information. Location: 27.456000, -80.309480
DOI: 10.25573/serc.20060225.v1
title: 2022 Water Quality Data, Bocas del Toro, MarineGEO, Smithsonian Tropical Research Institute

description: 2022 water quality data collected on a YSI EXO2 multiparameter sonde at the MarineGEO Bocas del Toro observatory (Bocas del Toro Research Station, Smithsonian Tropical Research Institute, Panama). The figshare resource also contains quality control metadata to assist interpretation and analysis. Review the "readme.txt" file for more information. QAQC is on-going, and this resource will be updated monthly. Location: 9.350822, -82.257853
DOI: 10.25573/serc.20060585.v1
title: 2022 Water Level Data, Upper Chesapeake Bay, MarineGEO, Smithsonian Environmental Research Center

description: 2022 water level data collected on CS475A instrumentation at the MarineGEO Upper Chesapeake Bay observatory (Smithsonian Environmental Research Center, Edgewater, MD, USA). Location: 38.886928, -76.540172
DOI: 10.25573/serc.20060657.v1
title: 2022 Meteorological Data, Upper Chesapeake Bay, MarineGEO, Smithsonian Environmental Research Center

description: 2022 meteorological data collected on WXT536, PTB110, and LI-190R instrumentation at the MarineGEO Upper Chesapeake Bay observatory (Smithsonian Environmental Research Center, Edgewater, MD, USA). Location: 38.886928, -76.540172
DOI: 10.25573/serc.20060690.v1
title: 2022 Water Level Data, Bocas del Toro, MarineGEO, Smithsonian Tropical Research Institute

description: 2022 water level data collected on CS475A instrumentation at the MarineGEO Bocas del Toro observatory (Bocas del Toro Research Station, Smithsonian Tropical Research Institute, Panama). Location: 9.350822, -82.257853
DOI: 10.25573/serc.20060759.v1
title: 2022 Meteorological Data, Bocas del Toro, MarineGEO, Smithsonian Tropical Research Institute

description: 2022 meteorological data collected on WXT536 instrumentation at the MarineGEO Bocas del Toro observatory (Bocas del Toro Research Station, Smithsonian Tropical Research Institute, Panama). Location: 9.350822, -82.257853
DOI: 10.34740/kaggle/dsv/4075514
title: Elon Musk Tweets
DOI: 10.17909/m4gd-2x80
title: Na D

description: Supplementary UV spectral profiles for papter
DOI: 10.34740/kaggle/dsv/4075361
title: Rectangular Maze Dataset via Kruskal's
DOI: 10.21227/z7gb-np68
title: Paradox-free analysis for comparing the performance of optimization algorithms

description: Numerical comparison serves as a major tool in evaluating the performance of optimization algorithms, especially nondeterministic algorithms, but existing methods may suffer from a ‘cycle ranking’ paradox and/or a ‘survival of the nonfittest paradox. This paper searches for paradox-free data analysis methods for numerical comparison. It is discovered that a class of sufficient conditions exist for designing paradox-free analysis. Rigorous modeling and deduction are applied to a class of profile methods employing a filter. It is thus further discovered and proven that algorithm-independent filter conditions can prevent cycle ranking and survival of non-fittest paradoxes from occurring. By adopting an algorithm-independent filter, popular profile methods such as the ‘modified data profile method’, ‘the accuracy profile method’, and ‘the operational characteristics zones method’ can be paradox free in comparing or bench-marking the performance of optimization algorithms.
DOI: 10.34943/66237670-a983-45be-bfb5-ad20b590317d
title: Main Endeavour Field Sediment Trap Deployed 2021-08-22

description: The McLane Parflux MK78H-21 Sediment Trap (SN 12294-02) was deployed on 2021-08-22 at Main Endeavour Field. Main Endeavour Field is a vent field located at Endeavour Ridge, where hydrothermal vent systems are observed. This device is a Sediment Trap. Sediment traps use a conical-shaped trap to guide settling particles into a set of sample bottles. Separate bottle samples are collected as the instrument is rotated. Sediment traps can be remotely triggered by a user or on a set schedule. Sediment traps record operational conditions including the sample date, time, and temperature during each sampling event. Upon instrument recovery, the samples are analyzed in a lab for particle flux and composition over time. It was deployed on a fixed platform. Data from this deployment were archived and made available through Ocean Networks Canada's Oceans 3.0 digital infrastructure, with quality assurance and derived data products following established practices.
DOI: 10.5281/zenodo.6992686
title: Ukraine-related Disinformation Dataset

description: Ukraine-related disinformation dataset from "Comparative Analysis of Engagement, Themes, and Causality of Ukraine-Related Debunks and Disinformation" (accepted at SocInfo 2022).
DOI: 10.5281/zenodo.6992685
title: Ukraine-related Disinformation Dataset

description: Ukraine-related disinformation dataset from "Comparative Analysis of Engagement, Themes, and Causality of Ukraine-Related Debunks and Disinformation" (accepted at SocInfo 2022).
DOI: 10.17632/gvrwz5nr8d.1
title: LINF_310030700

description: 3-2-trans-enoyl-CoA isomerase - mitochondrial precursor | teCi.2
Leishmania infantum (strain JPCM5)
DOI: 10.17632/5rt5yzb2zt.1
title: LINF_310030600

description: hypothetical protein - conserved
Leishmania infantum (strain JPCM5)
DOI: 10.17632/276f33rg96.1
title: LINF_310029900

description: ARM-like helical domain-containing protein
Leishmania infantum (strain JPCM5)
DOI: 10.17632/89wkp9vdzr.1
title: LINF_310029800

description: hypothetical protein - conserved
Leishmania infantum (strain JPCM5)
DOI: 10.17632/s7wxgcccz2.1
title: LINF_310029700

description: prostaglandin f2-alpha synthase | PGF2S | glutathione-specific aldose reductase | D-arabinose dehydrogenase
Leishmania infantum (strain JPCM5)
DOI: 10.17632/rcnv3mvddp.1
title: Proteomic data of Biofilm responsive proteins of Candida albicans ATCC 10231

description: Data represents the raw proteomic data generated by SWATH-MS analysis of Candida albicans (ATCC 10231) biofilm.
DOI: 10.17632/2rr75x4wg4.1
title: EEG sensor system development (processed)

description: The processed data for the proposed manuscript titled: "EEG sensor system development consisting of solid polyvinyl alcohol-glycerol-NaCl contact gel and 3D printed, silver coated polylactic acid electrode for potential brain-computer interface use" can be found here. The appropriate sections cut from the whole datastreams, their Fourier transforms, as well as the signal-to-noise and alpha band's ratios are presented here. Since the conversion to voltage does not yield different ratio values, the calculations were made from the bit values.
DOI: 10.17632/2rr75x4wg4.2
title: EEG sensor system development (processed)

description: The processed data for the proposed manuscript titled: "EEG sensor system development consisting of solid polyvinyl alcohol-glycerol-NaCl contact gel and 3D printed, silver coated polylactic acid electrode for potential brain-computer interface use" can be found here. The appropriate sections cut from the whole datastreams, their Fourier transforms, as well as the signal-to-noise and alpha band's ratios are presented here. Since the conversion to voltage does not yield different ratio values, the calculations were made from the bit values.
DOI: 10.17632/66ndcswhr2.1
title: EEG sensor system development

description: The raw data for the published article titled: "EEG sensor system development consisting of solid polyvinyl alcohol-glycerol-NaCl contact gel and 3D printed, silver coated polylactic acid electrode for potential brain-computer interface use" can be found here. In the "Electrical properties" folder the results of the conductivity measurements of the proposed contact gel, the impedance spectroscopic measurements of the PVAgel-AgPLA and the electrode-skin interface are presented. The "EEG" folder contains the datastreams of the SSVEP and the alpha wave detection recordings in csv format. The sampling rate was 500 Hz and one bit is equal to 0,536 microV.
DOI: 10.17632/66ndcswhr2.2
title: EEG sensor system development

description: The raw data for the proposed manuscript titled: "EEG sensor system development consisting of solid polyvinyl alcohol-glycerol-NaCl contact gel and 3D printed, silver coated polylactic acid electrode for potential brain-computer interface use" can be found here. In the "Electrical properties" folder the results of the conductivity measurements of the proposed contact gel, the impedance spectroscopic measurements of the PVAgel-AgPLA and the electrode-skin interface are presented. The "EEG" folder contains the datastreams of the SSVEP and the alpha wave detection recordings in csv format. The sampling rate was 500 Hz and one bit is equal to 0,536 microV.
DOI: 10.17632/66ndcswhr2.3
title: EEG sensor system development

description: The raw data for the proposed manuscript titled: "EEG sensor system development consisting of solid polyvinyl alcohol-glycerol-NaCl contact gel and 3D printed, silver coated polylactic acid electrode for potential brain-computer interface use" can be found here. In the "Electrical properties" folder the results of the conductivity measurements of the proposed contact gel, the impedance spectroscopic measurements of the PVAgel-AgPLA and the electrode-skin interface are presented. The "EEG" folder contains the datastreams of the SSVEP and the alpha wave detection recordings in csv format. The sampling rate was 500 Hz and one bit is equal to 0,536 microV.
DOI: 10.17632/jggcgy93x8.1
title: Pinterest financial statements

description: This article will explain what advantages retail investors have over high salaried investment managers and institutions and why Warren Buffets bet that any investment manager cannot outperform the SNP500 was free money.

Rebalancing

Take a simple example of 2 companies: Apple and IBM. Over the last 5 years Apple is up almost 5x while IBM has done practically nothing. Had you started with a portfolio equally weighted with both companies 5 years ago and rebalanced monthly you would have to sell/Trim Apple regularly and use the funds to purchase additional IBM stock.

Now scale that up to 10, or 100 companies. Over the long run most will go up, some will go down and a select few will explode upwards. With rigid rules like “no company can represent more than 3% of the portfolio. As one company goes parabolic (AMD, NVDA, Apple, Tesla etc..) if you let it ride it will ultimately represent 10%+ of the portfolio. however with rebalancing you are taking from the winners and giving to the losers, in many cases stocks that have no business in any portfolio.

Bond Allocation

Disclosure: I work in the insurance industry as an actuary creating insurance policies, most of the policies are hedged by bonds (we buy in billions). However the value and total return of a bond index actually does better in a decreasing interest rate environment than a rising one.

Older bonds yielding 4-10% have multiplied in value as interest rates have decreased since 1982, the last 38 years. Just for some context the interest / bond yield was 15% in 1982, and has decreased to almost 0% today. Over the last 38 years bonds h…
Older bonds yielding 4-10% have multiplied in value as interest rates have decreased since 1982, the last 38 years. Just for some context the interest / bond yield was 15% in 1982, and has decreased to almost 0% today. Over the last 38 years bonds have done very well, however investing them today is like looking in the rear view mirror to drive forward, this performance will not be repeated unless we get into negatives as shown above.Source : I made this
As seen above any portfolio containing bonds since 1982 has delivered what seems to be risk free excess returns. However now that we are at the end of the cycle, the famous 60/40 Stock/Bond or 50/50 etc.. will all significantly underperform historic…
DOI: 10.17632/hn8zjc59vf.1
title: Data description & Do file "Regional Integration, Exchange Rate Volatility and Overseas Investment of Chinese Enterprises"

description: Accessing the restricted-use data:
We took the sample data form three main sources. 

1. To sum up the greenfield investment project of each Chinese enterprise according to the destination country, the global greenfield investment data is collected from “FDI Markets”. Total 1350 observations are obtained from the database, which contains information on 123 countries.  The dataset is an unbalanced panel for the years 2004 to 2015. In order to obtain data please access the below link to get the data, and audience will be able to access the data by purchasing according to their desired package.
 
URL: https://www.fdimarkets.com 

2. We aggregated the data of nominal exchange rate and trade volume from World Bank, and the data of consumer price level from World Development Indicators (WDI) database. The target country's GDP, per capita GDP, and GDP growth rate in the control variables are also obtained from the World Development Indicators (WDI). In order to obtain data please access the below link.

URL: https://databank.worldbank.org/source/world-development-indicators 

3. Data on control of corruption, regulatory quality, government effectiveness, and the rule of law are collected from the Worldwide Governance Indicators (WGI) database of World Bank.

URL: http://info.worldbank.org/governance/WGI/
DOI: 10.17632/x8wwf3hzxb.1
title: Yellow Anaconda Management 

description: Data from managed yellow anacondas in Argentina.
DOI: 10.17632/tk4f76sxn4.1
title: Viral metagenomics reveals distinct composition of plasma virome with increase abundance of Human gammaherpesvirus 4 in HIV-infected subjects on suppressive antiretroviral therapy compared to healthy controls

description: Plasma virome-based study aimed at identifying viral sequences in HIV-infected adults on therapy and uninfected healthy controls. The dataset consists of 6 healthy controls and 6 HIV- infected adults. A, B, C, D, E and F  are healthy controls whereas G, H, I, J, K and L are HIV-infected adults.
DOI: 10.17632/tk4f76sxn4.2
title: Viral metagenomics reveals distinct composition of plasma virome with increased abundance of Human gammaherpesvirus 4 in HIV-infected subjects on suppressive antiretroviral therapy compared to healthy controls

description: Plasma virome-based study aimed at identifying viral sequences in HIV-infected adults on therapy and uninfected healthy controls. The dataset consists of 6 healthy controls and 6 HIV- infected adults. A, B, C, D, E and F  are healthy controls whereas G, H, I, J, K and L are HIV-infected adults.