cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14776556
title: Global Fully Automatic Coffee Machine Market 2024 To 2033

description: Fully Automatic Coffee Machine Market Size, Trends and Insights By Type (Drip, Espresso, Thermal, Others), By Maximum Cup Output (Less than 50 Cups Per Day, 51-100 Cups Per Day, 100-200 Cups Per Day, 200-500 Cups Per Day, More than 500 Cups Per Day), By Installation (Table Top, Floor Standing), By End Use (Residential, Commercial), By Distribution Channel (Online, Offline), and By Region - Global Industry Overview, Statistical Data, Competitive Analysis, Share, Outlook, and Forecast 2024–2033.

Reports Description

As per the current market research conducted by the CMI Team, the global Fully Automatic Coffee Machine Market is expected to record a CAGR of 4.06% from 2024 to 2033. In 2024, the market size is projected to reach a valuation of USD 4.95 Billion. By 2033, the valuation is anticipated to reach USD 7.08 Billion.

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DOI: 10.5281/zenodo.14776557
title: Global Fully Automatic Coffee Machine Market 2024 To 2033

description: Fully Automatic Coffee Machine Market Size, Trends and Insights By Type (Drip, Espresso, Thermal, Others), By Maximum Cup Output (Less than 50 Cups Per Day, 51-100 Cups Per Day, 100-200 Cups Per Day, 200-500 Cups Per Day, More than 500 Cups Per Day), By Installation (Table Top, Floor Standing), By End Use (Residential, Commercial), By Distribution Channel (Online, Offline), and By Region - Global Industry Overview, Statistical Data, Competitive Analysis, Share, Outlook, and Forecast 2024–2033.

Reports Description

As per the current market research conducted by the CMI Team, the global Fully Automatic Coffee Machine Market is expected to record a CAGR of 4.06% from 2024 to 2033. In 2024, the market size is projected to reach a valuation of USD 4.95 Billion. By 2033, the valuation is anticipated to reach USD 7.08 Billion.

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DOI: 10.5281/zenodo.14776577
title: US Food Truck Market 2024 To 2033

description: US Food Truck Market Size, Trends and Insights By Food Type (Barbecue & Snacks, Fast Food, Desserts & Confectionary, Bakery, Vegan & Meat Plant, Others), By Truck Type (Vans, Trailers, Trucks, Others), By Size (Small, Medium, Large), By Operating Model (Independent Operators, Fleet Operators, Franchise Models), and By Region - Industry Overview, Statistical Data, Competitive Analysis, Share, Outlook, and Forecast 2024–2033.

Reports Description

As per the current market research conducted by the CMI Team, the US Food Truck Market is expected to record a CAGR of 6.38% from 2024 to 2033. In 2024, the market size is projected to reach a valuation of USD 4.52 Billion. By 2033, the valuation is anticipated to reach USD 7.89 Billion.

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DOI: 10.5281/zenodo.14776578
title: US Food Truck Market 2024 To 2033

description: US Food Truck Market Size, Trends and Insights By Food Type (Barbecue & Snacks, Fast Food, Desserts & Confectionary, Bakery, Vegan & Meat Plant, Others), By Truck Type (Vans, Trailers, Trucks, Others), By Size (Small, Medium, Large), By Operating Model (Independent Operators, Fleet Operators, Franchise Models), and By Region - Industry Overview, Statistical Data, Competitive Analysis, Share, Outlook, and Forecast 2024–2033.

Reports Description

As per the current market research conducted by the CMI Team, the US Food Truck Market is expected to record a CAGR of 6.38% from 2024 to 2033. In 2024, the market size is projected to reach a valuation of USD 4.52 Billion. By 2033, the valuation is anticipated to reach USD 7.89 Billion.

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DOI: 10.5281/zenodo.14498499
title: Electric Field Mill Data over Balasore
DOI: 10.5281/zenodo.14499528
title: Electric Field Mill Data over Balasore
DOI: 10.5281/zenodo.14550347
title: Electric Field Mill Data over Balasore
DOI: 10.5281/zenodo.14776586
title: Global Facial Cleanser Market 2024 To 2033

description: Facial Cleanser Market Size, Trends and Insights By Skin Type (Normal Skin, Oily skin, Dry skin, Sensitive skin, Combination skin, Others), By Product Type (Gel cleanser, Cream & lotion cleanser, Foaming cleanser, Bar cleanser, Others), By Consumer Group (Male, Female, Unisex), By End-use (Individual, Commercial), By Distribution Channel (Online, Offline), and By Region - Global Industry Overview, Statistical Data, Competitive Analysis, Share, Outlook, and Forecast 2024–2033.

Reports Description

As per the current market research conducted by the CMI Team, the global Facial Cleanser Market is expected to record a CAGR of 5.80% from 2024 to 2033. In 2024, the market size is projected to reach a valuation of USD 13,860 Million. By 2033, the valuation is anticipated to reach USD 23,020 Million.

The growing adoption of e-commerce platforms is significantly supporting the growth of the facial cleanser market. E-commerce provides a convenient, accessible, and diverse shopping experience, which has increased consumer reach for facial cleansers. Online platforms allow customers to compare products, read reviews, and make informed decisions, thereby driving higher sales.

Additionally, e-commerce platforms often offer personalized recommendations and targeted marketing, enhancing product visibility and consumer interest in facial cleansers. The ease of international shipping through e-commerce has also opened new markets for facial cleanser brands, expanding their customer base globally.

Promotions, discounts, and subscription services available online further incentivize purchases. The COVID-19 pandemic accelerated e-commerce adoption, with more consumers preferring online shopping over traditional brick-and-mortar stores. This shift has led to increased sales of skincare products, including facial cleansers, as consumers seek to maintain their skincare routines at home.

Moreover, the integration of social media with e-commerce platforms allows brands to engage directly with consumers, driving brand loyalty and repeat purchases. Overall, e-commerce has become a crucial driver of growth in the facial cleanser market.

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DOI: 10.5281/zenodo.14776587
title: Global Facial Cleanser Market 2024 To 2033

description: Facial Cleanser Market Size, Trends and Insights By Skin Type (Normal Skin, Oily skin, Dry skin, Sensitive skin, Combination skin, Others), By Product Type (Gel cleanser, Cream & lotion cleanser, Foaming cleanser, Bar cleanser, Others), By Consumer Group (Male, Female, Unisex), By End-use (Individual, Commercial), By Distribution Channel (Online, Offline), and By Region - Global Industry Overview, Statistical Data, Competitive Analysis, Share, Outlook, and Forecast 2024–2033.

Reports Description

As per the current market research conducted by the CMI Team, the global Facial Cleanser Market is expected to record a CAGR of 5.80% from 2024 to 2033. In 2024, the market size is projected to reach a valuation of USD 13,860 Million. By 2033, the valuation is anticipated to reach USD 23,020 Million.

The growing adoption of e-commerce platforms is significantly supporting the growth of the facial cleanser market. E-commerce provides a convenient, accessible, and diverse shopping experience, which has increased consumer reach for facial cleansers. Online platforms allow customers to compare products, read reviews, and make informed decisions, thereby driving higher sales.

Additionally, e-commerce platforms often offer personalized recommendations and targeted marketing, enhancing product visibility and consumer interest in facial cleansers. The ease of international shipping through e-commerce has also opened new markets for facial cleanser brands, expanding their customer base globally.

Promotions, discounts, and subscription services available online further incentivize purchases. The COVID-19 pandemic accelerated e-commerce adoption, with more consumers preferring online shopping over traditional brick-and-mortar stores. This shift has led to increased sales of skincare products, including facial cleansers, as consumers seek to maintain their skincare routines at home.

Moreover, the integration of social media with e-commerce platforms allows brands to engage directly with consumers, driving brand loyalty and repeat purchases. Overall, e-commerce has become a crucial driver of growth in the facial cleanser market.

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DOI: 10.6084/m9.figshare.28320134.v1
title: Logic Syllogistic Algorithms Fedorchenko MV.txt

description: Logic Syllogistic Algorithms
DOI: 10.5281/zenodo.14776598
title: Global Face Scrub Market 2024 To 2033

description: Face Scrub Market Size, Trends and Insights By Type (Normal Skin, Oily Skin, Dry Skin, Sensitive Skin, Combination Skin), By Consumer Group (Men, Women, Unisex), By Product (Organic, Inorganic), By Packaging (Plastic Containers, Tubes, Pouches), By Distribution Channel (Online, Offline), and By Region - Global Industry Overview, Statistical Data, Competitive Analysis, Share, Outlook, and Forecast 2024–2033.

Reports Description

As per the current market research conducted by the CMI Team, the global Face Scrub Market is expected to record a CAGR of 5.1% from 2024 to 2033. In 2024, the market size is projected to reach a valuation of USD 2,340.00 Million. By 2033, the valuation is anticipated to reach USD 3,490 Million.

The growing adoption of e-commerce platforms is significantly supporting the growth of the face scrub market. Online shopping offers consumers convenience, a wider variety of products, and the ability to compare prices and reviews easily. E-commerce platforms also enable face scrub brands to reach a broader audience beyond their geographical constraints.

Additionally, personalized marketing, targeted ads, and influencer collaborations on social media further boost visibility and sales. The direct-to-consumer model facilitated by e-commerce allows brands to gather customer feedback and swiftly adapt to trends, driving innovation and enhancing customer satisfaction in the face scrub market.

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DOI: 10.5281/zenodo.14776599
title: Global Face Scrub Market 2024 To 2033

description: Face Scrub Market Size, Trends and Insights By Type (Normal Skin, Oily Skin, Dry Skin, Sensitive Skin, Combination Skin), By Consumer Group (Men, Women, Unisex), By Product (Organic, Inorganic), By Packaging (Plastic Containers, Tubes, Pouches), By Distribution Channel (Online, Offline), and By Region - Global Industry Overview, Statistical Data, Competitive Analysis, Share, Outlook, and Forecast 2024–2033.

Reports Description

As per the current market research conducted by the CMI Team, the global Face Scrub Market is expected to record a CAGR of 5.1% from 2024 to 2033. In 2024, the market size is projected to reach a valuation of USD 2,340.00 Million. By 2033, the valuation is anticipated to reach USD 3,490 Million.

The growing adoption of e-commerce platforms is significantly supporting the growth of the face scrub market. Online shopping offers consumers convenience, a wider variety of products, and the ability to compare prices and reviews easily. E-commerce platforms also enable face scrub brands to reach a broader audience beyond their geographical constraints.

Additionally, personalized marketing, targeted ads, and influencer collaborations on social media further boost visibility and sales. The direct-to-consumer model facilitated by e-commerce allows brands to gather customer feedback and swiftly adapt to trends, driving innovation and enhancing customer satisfaction in the face scrub market.

For more information, DOWNLOAD FREE SAMPLE Now at https://www.custommarketinsights.com/request-for-free-sample/?reportid=54781
DOI: 10.6073/pasta/7e0e3a32771e9002f0f3dcaa08e4e28f
title: Time series of high-frequency sensor data measuring water temperature, dissolved oxygen, conductivity, specific conductance, total dissolved solids, chlorophyll a, phycocyanin, and fluorescent dissolved organic matter at discrete depths in Carvins Cove Reservoir, Virginia, USA in 2020-2024

description: We monitored water quality in Carvins Cove Reservoir (Roanoke, Virginia, USA) with high-frequency (10-minute) sensors in 2020-2024. Carvins Cove Reservoir is owned and managed by the Western Virginia Water Authority as a primary drinking water source. This data package consists of datasets from two separate deployments. First, from July 2020 - August 2021, depth profiles of water temperature were measured on 1-meter intervals using HOBO temperature pendant loggers deployed from 0.1 m below the surface of the reservoir to 10 m depth, and also at 15 and 20 m depth. Additionally, water temperature was measured in the Sawmill Branch inflow at 0.5 m depth using HOBO temperature pendant loggers. Second, from 9 April 2021 - 31 December 2024, depth profiles of water temperature were measured on 1-meter intervals from 0.1 m below the surface of the reservoir to 11 m depth and additionally at 15 and 19 m. A YSI EXO2 sonde measured water temperature, conductivity, specific conductance, chlorophyll a, phycocyanin, total dissolved solids, dissolved oxygen, and fluorescent dissolved organic matter at ~1.5 m depth. A YSI EXO3 sonde measured water temperature, conductivity, specific conductance, total dissolved solids, dissolved oxygen, and fluorescent dissolved organic matter at 9 m depth, which corresponds to the depth of a water outtake valve. The thermistors, EXO3 sonde, and pressure sensor were deployed at stationary, fixed elevations (referred to as positions) deployed off of the dam near the water outtake valves. Due to variable water levels in the reservoir, the depths of these sensors varied over time. In contrast, the EXO2 was deployed on a buoy from 2021-2022 and remained at 1.5 m depth as the water level fluctuated. However, in 2023, the buoy disappeared in a storm, and after that the EOX2 was deployed at a stationary elevation as the water level fluctuated around the sensor. The EXO2 was redeployed on the buoy in 2024. At the monitoring site, the reservoir is approximately 19 m deep (reservoir maximum depth is 23 m).
DOI: 10.34740/kaggle/dsv/10623234
title: Egypt Gold Prices | Daily Updated
DOI: 10.15468/dl.ebf2rd
title: Occurrence Download

description: A dataset containing 251 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "Geometry POLYGON((67.02334 27.52259,141.97666 27.52259,141.97666 57.47741,67.02334 57.47741,67.02334 27.52259))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Peganum nigellastrum Bunge"
 ]
}

 The dataset includes 251 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005934-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14776365
title: Local FLake simulations of lake temperature profiles for "Subsurface heatwaves in lakes"

description: This dataset provides daily temperature profiles for six lakes from 1981 to 2099, generated using the calibrated FLake model. Historical simulations (1981–2020) were driven by the ERA5-Land dataset, while future simulations (2021–2099) use forcing from ISIMIP2b. For more information on the underlying datasets and the calibration method, please refer to the paper “Subsurface heatwaves in lakes” (Woolway et al., 2025, Nature Climate Change).
DOI: 10.5281/zenodo.14776366
title: Local FLake simulations of lake temperature profiles for "Subsurface heatwaves in lakes"

description: This dataset provides daily temperature profiles for six lakes from 1981 to 2099, generated using the calibrated FLake model. Historical simulations (1981–2020) were driven by the ERA5-Land dataset, while future simulations (2021–2099) use forcing from ISIMIP2b. For more information on the underlying datasets and the calibration method, please refer to the paper “Subsurface heatwaves in lakes” (Woolway et al., 2025, Nature Climate Change).
DOI: 10.15468/dl.c3ekj8
title: Occurrence Download

description: A dataset containing 2630 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Lontra longicaudis (Olfers, 1818)"
 ]
}

 The dataset includes 2630 records from 178 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005935-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14354805
title: Data and code for "Improvements in Prediction Performance of Ensemble Approaches for Genomic Prediction in Crop Breeding"

description: The preprocessed data of the TeoNAM dataset by Chen et al. (2019) and code for the ensemble approach used in the manuscript "Improvements in Prediction Performance of Ensemble Approaches for Genomic Prediction in Crop Breeding"
DOI: 10.5281/zenodo.14354804
title: Data and code for "Improved Genomic Prediction Performance with Ensembles of Diverse Models"

description: The preprocessed data of the TeoNAM dataset by Chen et al. (2019) and code for the ensemble approach used in the manuscript "Improved Genomic Prediction Performance with Ensembles of Diverse Models".
DOI: 10.5281/zenodo.14776591
title: Data and code for "Improved Genomic Prediction Performance with Ensembles of Diverse Models"

description: The preprocessed data of the TeoNAM dataset by Chen et al. (2019) and code for the ensemble approach used in the manuscript "Improved Genomic Prediction Performance with Ensembles of Diverse Models".
DOI: 10.5281/zenodo.14776622
title: Supplementary code and data for "More stringent adaptation solutions are needed to alleviate future groundwater stress over China"

description: This is the supplementary code and data for “More stringent adaptation solutions are needed to alleviate future groundwater stress over China”. The dataset contains groundwater stress index (GWSI) over mainland China during future period (2006-2050) at a spatial resolution of 0.25°×0.25° grid scale. The GWSI is calculated as the ratio of groundwater withdrawal to natural recharge with consideration of irrigation return flow and environmental flow requirement. The future GWSI projection consider three different experiments setting (namely without adaptation, under existing measures and potential solutions) under two shared socioeconomic pathways (SSPs) and representative concentration pathways (RCPs) combinations: SSP1-RCP2.6 and SSP2-RCP6.0. Code for GWSI calculation is produced with MATLAB R2021a. The detailed descriptions for the methods and dataset are presented in the paper (Huang et al., 2015).

Contact: For further questions please contact Zhongwei Huang (huangzw@nuist.edu.cn).
DOI: 10.5281/zenodo.14776623
title: Supplementary code and data for "More stringent adaptation solutions are needed to alleviate future groundwater stress over China"

description: This is the supplementary code and data for “More stringent adaptation solutions are needed to alleviate future groundwater stress over China”. The dataset contains groundwater stress index (GWSI) over mainland China during future period (2006-2050) at a spatial resolution of 0.25°×0.25° grid scale. The GWSI is calculated as the ratio of groundwater withdrawal to natural recharge with consideration of irrigation return flow and environmental flow requirement. The future GWSI projection consider three different experiments setting (namely without adaptation, under existing measures and potential solutions) under two shared socioeconomic pathways (SSPs) and representative concentration pathways (RCPs) combinations: SSP1-RCP2.6 and SSP2-RCP6.0. Code for GWSI calculation is produced with MATLAB R2021a. The detailed descriptions for the methods and dataset are presented in the paper (Huang et al., 2015).

Contact: For further questions please contact Zhongwei Huang (huangzw@nuist.edu.cn).
DOI: 10.15468/dl.aer2p7
title: Occurrence Download

description: A dataset containing 739 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Lontra longicaudis (Olfers, 1818)"
 ]
}

 The dataset includes 739 records from 32 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005936-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7mzm8y
title: Occurrence Download

description: A dataset listing the 4 species recorded in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "TaxonKey is Hygrocybe substrangulata (P.D.Orton) P.D.Orton & Watling"
 ]
}

 The dataset's 4 records were derived from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005933-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28320519.v1
title: Additional file 4 of Restoring riparian habitats for benefits to biodiversity and human livelihoods: a systematic map protocol for riparian restoration approaches in the tropics

description: Additional file 4: Pre-designed data coding form
DOI: 10.15468/dl.eahgf7
title: Occurrence Download

description: A dataset containing 28 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "GadmGid is MEX.25_1",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Lontra longicaudis (Olfers, 1818)"
 ]
}

 The dataset includes 28 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005937-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/e217221
title: Preservice Elementary Teacher STEM Teaching Self-efficacy

description: This project is on preservice elementary teachers' integrated STEM teaching self-efficacy. Data were collected via a survey instrument SETIS (Mobley, 2015), and interviews.
description: Random sampling
DOI: 10.3886/e217221v1
title: Preservice Elementary Teacher STEM Teaching Self-efficacy

description: This project is on preservice elementary teachers' integrated STEM teaching self-efficacy. Data were collected via a survey instrument SETIS (Mobley, 2015), and interviews.
description: Random sampling
DOI: 10.15468/dl.ah6533
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "GadmGid is MEX.26_1",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Lontra longicaudis (Olfers, 1818)"
 ]
}

 The dataset includes 16 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005939-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28320797
title: PJBL 773.csv

description: The data provides responses from 773 engineering students of Indonesian University related to their satisfaction