cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.27078718.v1
title: <b>Social conditions alter the growth, metabolic rate, behavioral traits, and food-shelter preferences in the qingbo </b><b><i>Spinibarbus sinensis</i></b>

description: <b>Abstract</b>For social animals, conspecifics within a group can influence an individual’s physiology and behavior, but whether these group effects alter the trade-offs between foraging and defense remains unclear. In this study, we investigated the social fish species, the qingbo (<i>Spinibarbus sinensis</i>), to examine how group effects during both past social experiences (rearing conditions) and current social conditions (test environments) influence routine metabolic rate (RMR), behavioral traits (activity, boldness, and sociability), and preferences for food versus shelter, and how rearing conditions (isolation or group rearing) specifically affect growth. Our results revealed that the qingbo reared in social isolation exhibited both higher growth and RMR than did the individuals reared in groups, potentially through compensatory feeding. Group effects from conspecifics during rearing and testing led to increased activity and decreased sociability in qingbo, whereas the presence of conspecifics during testing increased boldness. Isolation-reared qingbo showed a preference for shelter over both an open field and food in the absence of conspecifics, whereas group-reared qingbo preferred food over shelter when conspecifics were present. These findings suggest that visual social isolation may not be a significant stressor for qingbo, as the isolation-reared qingbo exhibited improved growth. This could be because the presence of conspecific olfactory cues in the rearing environment mitigated the stress associated with visual isolation. Interactions with conspecifics and the associated reduction in predation risk with group effects may enhance activity and boldness. Additionally, the qingbo’s food and shelter preferences can dynamically adjust in response to group effects, reflecting high behavioral plasticity that allows social fishes to optimize foraging efficiency in risky situations.
DOI: 10.6084/m9.figshare.27087754.v1
title: PRISMA 2020 Checklist

description: PRISMA 2020 Checklist
DOI: 10.6084/m9.figshare.3695652.v2
title: Supplementary Material for: Whole-Exome Sequencing Identifies Two Novel TTN Mutations in Chinese Families with Dilated Cardiomyopathy

description: <b><i>Objectives:</i></b> Dilated cardiomyopathy (DCM) is a leading cause of sudden cardiac death. So far, only 127 mutations of <i>Titin</i><i>(TTN)</i> have been reported in patients with different phenotypes such as isolated cardiomyopathies, purely skeletal muscle phenotypes or complex overlapping disorders of muscles. <b><i>Methods:</i></b> We applied whole-exome sequencing (WES) to investigate cardiomyopathy patients and a cardiomyopathy-related gene-filtering strategy was used to analyze the disease-causing mutations. Sanger sequencing was applied to confirm the mutation cosegregation in the affected families. <b><i>Results:</i></b> A nonsense mutation (c.12325C&gt;T/p.R4109X) and a missense mutation (c.17755G&gt;C/p.G5919R) of <i>TTN</i> were identified in 2 Chinese DCM families, respectively. Both mutations were cosegregated in all affected members of both families. The nonsense mutation is predicted to result in a truncated TTN protein and the missense mutation leads to a substitution of glycine by arginine. Both variants may cause the structure changes of titin protein. <b><i>Conclusions:</i></b> We employed WES to detect the mutations of DCM patients and identified 2 novel mutations. Our study expands the spectrum of <i>TTN</i> mutations and offers accurate genetic testing information for DCM patients who are still clinically negative.
DOI: 10.17632/kvp23k439m
title: CD8+ T cells and fatty acids orchestrate tumor ferroptosis and immunity via ACSL4 

description: IFNgamma reprograms ACSL4 associated phospholipids to induce tumor ferroptosis
DOI: 10.6084/m9.figshare.12221984.v2
title: Replication data: The tip of the iceberg – Interest group behaviour in rule drafting and consultations during EU agency rulemaking

description: The replication data concerns two datasets: - A dataset on EASA rule drafting group access (dataset A)- A dataset on attempts of interest groups to influence EASA rules in consultations (dataset B) For more details, see corresponding article (to be published).
DOI: 10.6084/m9.figshare.4616080.v1
title: PowerPoint Slides for: History of Erythropoiesis-Stimulating Agents, the Development of Biosimilars, and the Future of Anemia Treatment in Nephrology

description: <b><i>Background:</i></b> Exogenous replacement of erythropoietin (EPO) by recombinant human EPO has been considered a standard of care for the treatment of anemia in patients with chronic kidney disease for more than 20 years. Genetically engineered biologic proteins derived from human, animal, or microorganism sources are a major area of growth in modern medical care, accounting for one-third of new drug approvals in the past decade. Despite benefit to patients, the use of biologics comes at a significant cost, representing one of the fastest growing segments of strained healthcare budgets around the world. <b><i>Summary:</i></b> Biosimilars, or biologic drugs that are designed to be highly similar to approved reference biologic drugs, have been available in Europe for more than 10 years with no unusual or unexpected effects compared to their reference biologics whose patents have expired. Given the success of the biosimilar approval pathway pioneered in Europe, it has served as a global reference for other regulatory authorities to establish and implement biosimilar licensure frameworks, including the United States (US), the largest pharmaceutical market in the world. Given 10 of the top 25 drugs sold in 2014 were biologics, and considering the rising costs of healthcare, biosimilars have the potential to become a significant part of the US market. <b><i>Key Messages:</i></b> For the nephrology community, the recent patent expiries for epoetin alfa (Epogen®, Amgen and Procrit®, Johnson & Johnson) have created the opportunity to develop biosimilar EPOs. And while no biosimilar in this therapeutic class is approved in the US, there are proposed biosimilars in development.
DOI: 10.17632/cgtnjyggtm
title: Datasets on CFRP specimens after low-velocity impact tests: 24-layer quasi-isotropic laminates

description: This dataset is developed to study carbon fiber reinforced plastics laminates after low-velocity impact tests. It is related to a Data in Brief article, which describes the experiment in detail, and the main article on how the authors used the datasets. The low-velocity impact test was conducted with various impact conditions, changing the impactor shape, the impact energy and the stacking sequence, which generates barely visible impact damage. This dataset is on 24 layer quasi-isotropic laminates. See the other Mendeley data URLs to find the data on the other stacking sequences. 

“impacted surface image” folder: The impacted surface image (78.933mm * 78.933mm)
“internal damage” folder: The c-scanning image after the impact. Each scale is on the image.
“non-impacted surface image” folder: The non-impacted surface image (78.933mm * 78.933mm)
“surface profile” folder: The surface profile of the impacted surface. (78.933mm * 78.933mm)
“impact condition_q24.xlsx”: The impact condition.
DOI: 10.17632/sghd8vbvbp
title: Dataset for Bitcoin arbitrage in different cryptocurrency exchanges

description: We present a high-frequency dataset of algorithmic trading. Given that, the dataset contains different time intervals depending on the timestamp when an arbitrage opportunity occurred. Our dataset has 9,799,130 tick-level records of the Bitcoin-to-Euro exchange rate starting from 2019-01-01 00:00:31 until 2020-03-30 23:59:48. Data covered information about different cryptocurrency pairs from 18 cryptocurrency exchanges. These pairs contained information about exchanges in which it was possible to buy and sell simultaneously. Each row presented the amount of arbitrage that it was possible to earn if a transaction would have been executed. The dataset contains information about the amount of arbitrage that could be earned after executing a transaction in given cryptocurrency exchanges, the quantity which had to be bought to earn arbitrage, the best sell, and the best buy prices, the balance of fiat currency in “Exchange 1” and the balance of cryptocurrency in “Exchange 2”. If there was enough fiat currency in “Exchange 1” and enough cryptocurrency in “Exchange 2” it means that the transaction was successfully executed and given arbitrage amount was earned. This information could be used by investors to discover potential earning capabilities, and create effective arbitrage trading strategies. Moreover, this dataset could serve academics for deeper analysis of efficiency and liquidity questions as well as it could be used to spot and evaluate risks in the market, identify patterns in the market.

Short description of the dataset:
ID - Unique ID
arb_timestamp - timestamp of arbitrage opportunity 
arb_exch1 - presents exchanges where one was able to successfully buy Bitcoin
arb_exch2 - presents exchanges where one was able to successfully sell Bitcoin
arb_ticker - BTCEUR exchange rate
arb_prc - percentage earned compared to the invested amount 
arb_amount - the amount of arbitrage that would be earned if a transaction had been executed 
arb_quantity - Bitcoin quantity that needed to be bought in order to execute a transaction and to earn arbitrage
best_sell_price - best price at which it was possible to sell Bitcoin in "Exchange 2"
best_buy_price -  best price at which it was possible to buy Bitcoin in "Exchange 1"
balance_fiat - the amount of Euros available in “Exchange 1”
balance_crypto - the amount of Bitcoin available in “Exchange 2”
DOI: 10.6084/m9.figshare.14339417.v1
title: Supplementary Material for: Kidney Injury Molecule-1 and Periostin Urinary Excretion and Tissue Expression Levels and Association with Glomerular Disease Outcomes

description: <b><i>Introductions:</i></b> Kidney injury molecule-1 (KIM-1) and periostin (POSTN) are proximal and distal tubule injury biomarkers. We tested whether baseline urine KIM-1/Cr (uKIM-1/Cr) and/or uPOSTN/Cr correlated with disease severity or improved a remission prediction model. <b><i>Methods:</i></b> Baseline uKIM-1/Cr and uPOSTN/Cr were measured on spot urine samples from immunosuppression-free patients enrolled in Nephrotic Syndrome Study Network until December 15, 2014. Urine protein/Cr (UPCR) and albumin/Cr (UACR) were measured at baseline, 4 months, and until last follow-up. Glomerular and tubulointerstitial (TI) expression arrays were analyzed from a baseline research renal biopsy core collected during a clinically indicated biopsy. Renal diagnoses were centrally confirmed, sections scanned, and measured morphometrically. Correlations between baseline uKIM-1/Cr and uPOSTN/Cr and UPCR, UACR, histopathologic features, glomerular and TI KIM-1 and POSTN expression levels, and renal outcomes were assessed. <b><i>Results:</i></b> Baseline uKIM-1/cr correlated with UPCR and UACR and were associated with complete remission (CR) after adjustment for proteinuria, histopathologic diagnosis, and treatment. Baseline uKIM-1/Cr also correlated with degree of foot process effacement and acute tubular injury. Glomerular and TI KIM-1 expression levels correlated with UPCR and UACR. Higher TI KIM-1 expression levels correlated with interstitial fibrosis, tubular atrophy, and global glomerulosclerosis, while glomerular KIM-1 expression correlated with time to remission. Findings for POSTN were of lesser statistical strength. <b><i>Discussion/Conclusion:</i></b> Lower baseline uKIM-1/Cr values were associated with more rapid time to CR after adjusting for proteinuria, histopathologic diagnosis, and treatment. Increased TI KIM-1 expression levels in proteinuric states were associated with chronic morphological injury; lower glomerular expression levels were associated with a greater potential for proteinuria reversibility.
DOI: 10.6084/m9.figshare.29149181.v1
title: <b>Growing completeness of multi-taxon biodiversity occurrence information is associated with long-term socioeconomic advance in China</b>

description: The absence of comprehensive species distribution data may hinder our understanding of biogeographic patterns and the development of effective conservation strategies. Although citizen science data on biodiversity present opportunities to address these data deficiencies, it also introduces various biases. Here, we conducted an analysis of the completeness of citizen science data and its driving factors in China to address existing knowledge gaps and offer new insights for biodiversity conservation research and practice.
DOI: 10.6084/m9.figshare.3563751.v1
title: Supplement 1. The raw data on pollen morphology and climate variables of the collection sites used in the analysis.

description: File List data.txt -- (MD5: a82e69f2e3cab98107c9ae2557ce613f) Description The data.txt is a tab-separated file. It contains the raw data on pollen morphology (polar axis, equatorial axis, surface area, and volume) and climate variables (Temperature, PET, and altitude) of the collection sites. Column definitions are given in the file. Missing values are represented as “-9999”. Checksum values are: Column 3 (Collection site – Latitude): SUM = 3786.63; 16 missing values (rows with data: 74) Column 4 (Collection site – Longitude): SUM = 1410.62; 16 missing values (rows with data: 74) Column 5 (Altitude provided by collector [m]): SUM = 16531.00; 74 missing values (rows with data: 16) Column 6 (Altitude SRTM 250x250m [m]): SUM = 16931.00; 16 missing values (rows with data: 74) Column 7 (Temperature May [deg.C]): SUM = 429.20; 56 missing values (rows with data: 34) Column 8 (Temperature June [deg.C]): SUM = 989.70; 29 missing values (rows with data: 61) Column 9 (Temperature July [deg.C]): SUM = 635.40; 55 missing values (rows with data: 35) Column 10 (Mean temperature in flowering period [deg.C]): SUM = 9867.12; 16 missing values (rows with data: 74) Column 11 (PET May [mm]): SUM = 3766.00; 56 missing values (rows with data: 34) Column 12 (PET June [mm]): SUM = 7920.00; 29 missing values (rows with data: 61) Column 13 (PET July [mm]): SUM = 4826.00; 55 missing values (rows with data: 35) Column 14 (Mean PET in flowering period [mm]): SUM = 9354.58; 16 missing values (rows with data: 74) Column 15 (Polar axis [um]): SUM = 2862.63; 0 missing values (rows with data: 90) Column 16 (Equatorial axis [um]): SUM = 2501.41; 0 missing values (rows with data: 90) Column 17 (Volume of an ellipsoid for a given P and E [um^3]): SUM = 1284905.60; 0 missing values (rows with data: 90) Column 18 (Surface of an elipsoid for a given P and E [um^2]): SUM = 247975.40; 0 missing values (rows with data: 90)
DOI: 10.17632/f6vty3wkwj
title: Massively parallel implementation and approaches to simulate quantum dynamics using Krylov subspace techniques

description: We have developed an application and implemented parallel algorithms in order to provide a computational framework suitable for massively parallel supercomputers to study the unitary dynamics of quantum systems. We use renowned parallel libraries such as PETSc/SLEPc combined with high-performance computing approaches in order to overcome the large memory requirements to be able to study systems whose Hilbert space dimension comprises over 9 billion independent quantum states. Moreover, we provide descriptions of the parallel approach used for the three most important stages of the simulation: handling the Hilbert subspace basis, constructing a matrix representation for a generic Hamiltonian operator and the time evolution of the system by means of the Krylov subspace methods. We employ our setup to study the evolution of quasidisordered and clean many-body systems, focussing on the return probability and related dynamical exponents: the large system sizes accessible provide novel insights into their thermalization properties.
DOI: 10.6084/m9.figshare.14120894.v1
title: Timor Sea Benthic Type Reference Sample

description: This benthic reference data is intended for use as a calibration and/or validation data for global scale remote sensing image based classification of coral reef areas. The data is in a vector shapefile format consisting of polygons labelled with one of seven coral reef benthic classes that include Microalgal Mats, Coral/Algae, Rubble, Rock, Seagrass Dense, Seagrass Sparse, Sand. <b>Please cite data as:</b> Tudman, P., Borrego-Acevedo, R., Canto, R., Harris, D., Kennedy, E., Kovacs, E., Lyons, M., Markey, K., Murray, N., Ordonez Alvarez, A., Phinn, S., Roe, M., Roelfsema, C., Say, C., Wolff, J., Yuwono, D., Bambric, B., Fox, H., Lieb, Z., Asner , G., Knapp , D., Li, J., Harris, B., Larsen, K. & Rice, K. 2021. Timor Sea Benthic Type Reference Sample. University of Queensland. DOI: https://doi.org/10.6084/m9.figshare.14120894 <b>Links to supplementary information:</b> Mapping methods overview (https://allencoralatlas.org/methods/) UQ mapping team web site (https://www.rsrc.org.au/globalreef) Detailed mapping methods description by Lyons et al. (https://doi.org/10.1002/rse2.157) Detailed classification scheme description by Kennedy et al. (https://doi.org/10.1038/s41597-021-00958-z) Detailed reference creation description workflow by Roelfsema et al. (https://doi.org/10.3389/fmars.2021.643381) <b>Funding:</b> Vulcan Inc., (https://vulcan.com) Great Barrier Reef Foundation (https://www.barrierreef.org/) <b>Acknowledgement:</b> This work was initiated and funded primarily through Paul Allen Philanthropies and Vulcan Inc. as part of the Allen Coral Atlas. We acknowledge the late Paul Allen and Ruth Gates for their fundamental vision and drive to enable us to work together on this critical reef mapping problem. Project partners providing financial, service and personnel include: Planet Inc., National Geographic, University of Queensland, Arizona State University, and University of Hawai'i. Significant support has also been provided by Google Inc., Great Barrier Reef Foundation, and Trimble (Ecognition). Contributors to establishing and running the project include: Vulcan Inc. [James Deutsch, Lauren Kickam, Paulina Gerstner, Charlie Whiton, Kirk Larsen, Sarah Frias Torres, Kyle Rice, Eldan Goldenberg, Janet Greenlee]; Planet Inc. [Andrew Zolli, Trevor McDonald, Joe Mascaro, Joe Kington]; University of Queensland [Chris Roelfsema, Stuart Phinn, Emma Kennedy, Mitch Lyons, Nicholas Murray, Doddy Yuwono, Dan Harris, Eva Kovacs, Rodney Borrego, Meredith Roe, Jeremy Wolff, Kathryn Markey, Alexandra Ordonez, Chantal Say, Paul Tudman]; Arizona State University [Greg Asner, Dave Knapp, Jiwei Li, Yaping Xu, Nick Fabina, Heather D'Angelo]; and National Geographic [Helen Fox, Brianna Bambic, Brian Free, Zoe Lieb] and Great Barrier Reef Foundation [Petra Lundgren, Kirsty Bevan, Sarah Castine]. Attributions of contributed field data or maps for the reference sample creation are available at: https://allencoralatlas.org/attribution/
DOI: 10.6084/m9.figshare.22708162.v1
title: Raw data in LC-MS metabolomics sequencing

description: In this study, we employed immunomagnetic enrichment and fluorescence-activated cell sorting (FACS) to isolate 15 hematopoietic cell types containing over 9×108 hematopoietic cells from 200 young and 150 aged mice, ranging from HSCs, committed progenitors, to mature lineage cells. Ultra-performance liquid chromatography mass spectroscopy (UPLC-MS/MS) untargeted analysis identified about 2000 metabolites in each cell population, which contributed to defining cell-specific signatures and depicting the landscape of aged blood cells.
DOI: 10.6084/m9.figshare.6905324.v1
title: Chipmunk phylosymbiosis

description: Metadata and 16S rRNA sequence data from feces from 8 species of chipmunk.
DOI: 10.17632/hr3tds2znj
title: Data for: "Supply Chain Risk: Changes in Supplier Composition and Vertical Integration"

description: Replication pacakge for: "Supply Chain Risk: Changes in Supplier Composition and Vertical Integration"
DOI: 10.6084/m9.figshare.16656808.v1
title: mutasi gen KKR indonesia 100621.xlsm

description: This is VCF files of high putative impact with pathogenic classification of mutation in Indonesian colorectal cancer patients.
DOI: 10.6084/m9.figshare.878253_d50
title: substrate_temperature_degC_soil_25_shade.zip

description: Substrate temperature (deg C) at depths of 0, 2.5, 5, 10, 15, 20, 30, 50 and 100 cm under ground assuming a soil substrate and 25% shade from vegetation. Each netCDF file contains 24 layers of global extent, one for each hour of the day (starting at 0:00 hrs) for a given month of the year, at ~15km resolution.
 
Fileset description:
The microclim dataset provides microclimate estimates of conditions above and below ground for each hour of the day for the middle day of each month based on a long-term average climatology. Details of this dataset are presented in [Kearney et al. 2014].
The dataset comprises a set of NetCDF files with one file per variable per month, each file comprising 24 layers (one for each hour of the day from 0:00 hrs to 23:00 hrs, so layer 13 is 12:00 midday) for the globe (852 rows, 2159 columns, latitudinal extents -58.57 to 83.43 degrees, longitudinal extents -180.00 to 180.00 degrees). For the naming convention, mon is month of the year (1 to 12, where 1 = Jan, 12 = Dec), shd is shade level in % (0, 25, 50, 75, 90, 100), and sub is substrate (soil, rock, sand).
To facilitate downloading the data, the NetCDF files are grouped into compressed (zipped) files, one per variable per shade and substrate type, each comprising all monthly values and, for the substrate temperatures, all depths. Note that not all variables are shade or substrate specific, specifically zenith angle, wind speeds, solar radiation, and 120 cm air temperature and relative humidity.
DOI: 10.17632/xfv7z6jzcm
title: BCN_OA_SourceApportionment_20142015_20172018

description: These files contain NR-PM1 time series, OA matrices and source apportionment results obtained from an ACSM deployed in the urban background station of Palau Reial in Barcelona in the periods May 2014 - May 2015 and September 2017- October 2018. Other co-located measurements are also included: PM1, black carbon, gases, meteorological variables and episodes.
DOI: 10.6084/m9.figshare.12235199.v1
title: Oral_samples

description: Pitfalls and Opportunities in Benchmarking Metagenomic Classifiers
DOI: 10.6084/m9.figshare.24315517.v1
title: <b>Gridded Material Stocks in China based on Geographical and Geometric Configurations of the Built-Environment</b>

description: This database contains 12 different materials stocks (i.e., steel, aluminum, copper, cement, gravel, sand, glass, wood, brick, asphalt, plastic, and rubber) in five end-use sectors (i.e., buildings, infrastructure, transportation, machinery, and domestic appliances) in China in Year 2000 and 2020 , with a spatial resolution of 1km.