cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.23959251
title: Honey bee (<i>Apis mellifera</i> L.) and wild bee resource competition: how big is this problem?

description: The Western honey bee (<i>Apis mellifera</i> L.) has been managed by humans for centuries for honey, wax, and most recently, crop pollination. The deep history of human association with this species has enabled agricultural practices that reduce biodiversity of pollinating wild bees, largely through habitat modification. However, there is also interest in determining if <i>Apis mellifera</i> presence itself contributes significantly to wild bee population declines. Herein we review the evidence of <i>Apis mellifera</i> competitive impacts on wild bees, with a particular emphasis on the scope of effects associated with resource competition. Despite accelerated research in this area, only ~13% of resource competition studies evaluated fitness effects of <i>Apis mellifera</i> on wild bees, a research gap that has persisted for over 20 years. About three times as many studies have evaluated effects of <i>Apis mellifera</i> on wild bee community parameters, including wild bee abundance, which provides a measure of a landscape’s “bee carrying capacity”. Just over 20% of these studies show a negative correlation with <i>Apis mellifera</i> abundance. In a novel additional analysis of 68 studies measuring bee communities for other reasons found negative correlations between <i>Apis mellifera</i> abundance and any measure of the wild bee community for only 10; conversely, 10 studies show positive relationships between <i>Apis mellifera</i> and wild bee abundance, and most show no relationship at all. We found no pattern to explain which habitat types are more vulnerable to <i>Apis mellifera</i> competition, nor is the literature clear on impactful densities of managed hives in particular environment types. Overall, the data do not support a generalized and widespread negative relationship between <i>Apis mellifera</i> abundance and wild bee fitness and community health. Rather, conservation measures that reliably improve wild bee health (habitat preservation and restoration) will likely have positive effects on <i>Apis mellifera</i>, and <i>vice versa</i>.
DOI: 10.17632/hzbg2wyjxb.1
title: Mappings of Potential Sailing Mobility in the Mediterranean during Antiquity: Research Data

description: Merchant sailing ships in Antiquity possessed very limited upwind capabilities and their sailing mobility was very much at the mercy of the wind. Mapping of potential sailing mobility in Antiquity has eluded researchers who have attempted to derive sailing abilities of ancient ships from averaged climatic wind data. A PhD study underway at the University of Haifa, Department of Maritime Civilization has taken a different approach using Data Science methods.
The underlying premise is that (a) the variabilities typical to Mediterranean winds are the key drivers of sailing mobility especially when a sailing passage lies contrary to prevailing winds; (b) these variabilities can be resolved in a large modern meteorological data set at high spatiotemporal resolution but are lost in averaged climatic data sets; and (c) palaeoclimatological examination has shown that the wind patterns in the Mediterranean have not changed in the last 3000 years and more.
Sailing passages are reconstructed throughout the data set using regatta weather-routing software. This reduces the meteorological data, which is in the order of billions  of records, to millions of sailing records. These are further reduced by statistical methods to obtain metrics of potential sailing mobility and are published in the data sheets for both direct sailing passages and for breeze assisted coastal sailing.
DOI: 10.17632/hzbg2wyjxb.2
title: Mappings of Potential Sailing Mobility in the Mediterranean during Antiquity: Research Data

description: Merchant sailing ships in Antiquity possessed very limited upwind capabilities and their sailing mobility was very much at the mercy of the wind. Mapping of potential sailing mobility in Antiquity has eluded researchers who have attempted to derive sailing abilities of ancient ships from averaged climatic wind data. A PhD study underway at the University of Haifa, Department of Maritime Civilization has taken a different approach using Data Science methods.
The underlying premise is that (a) the variabilities typical to Mediterranean winds are the key drivers of sailing mobility especially when a sailing passage lies contrary to prevailing winds; (b) these variabilities can be resolved in a large modern meteorological data set at high spatiotemporal resolution but are lost in averaged climatic data sets; and (c) palaeoclimatological examination has shown that the wind patterns in the Mediterranean have not changed in the last 3000 years and more.
Sailing passages are reconstructed throughout the data set using regatta weather-routing software. This reduces the meteorological data, which is in the order of billions  of records, to millions of sailing records. These are further reduced by statistical methods to obtain metrics of potential sailing mobility and are published in the data sheets for both direct sailing passages and for breeze assisted coastal sailing.
DOI: 10.17632/hzbg2wyjxb.3
title: Mappings of Potential Sailing Mobility in the Mediterranean during Antiquity: Research Data

description: Merchant sailing ships in Antiquity possessed very limited upwind capabilities and their sailing mobility was very much at the mercy of the wind. Mapping of potential sailing mobility in Antiquity has eluded researchers who have attempted to derive sailing abilities of ancient ships from averaged climatic wind data. A PhD study completed in 2022 at the University of Haifa, Department of Maritime Civilizations took a different approach using Data Science methods.

The underlying premise was that (a) the variabilities typical to Mediterranean winds are the key drivers of sailing mobility especially when a sailing passage lies contrary to prevailing winds; (b) these variabilities can be resolved in a large modern meteorological data set at high spatiotemporal resolution but are lost in averaged climatic data sets; and (c) palaeoclimatological examination has shown that the wind patterns in the Mediterranean have not changed in the last 3000 years and more.

Sailing passages are reconstructed throughout the data set using regatta weather-routing software. This reduces the meteorological data, which is in the order of billions  of records, to millions of sailing records. These are further reduced by statistical methods to obtain metrics of potential sailing mobility and are published in the data sheets for both direct sailing passages and for breeze assisted coastal sailing.

The tools to produce additional data remain in place and active. Additional measures of potential sailing mobility produced since the original research have been added to the repository.
DOI: 10.17632/hzbg2wyjxb.4
title: Mappings of Potential Sailing Mobility during Antiquity: Research Data

description: Merchant sailing ships in Antiquity possessed very limited upwind capabilities and their sailing mobility was predominantly determined by variability of the wind. Mapping of potential sailing mobility in Antiquity has eluded researchers who have attempted to derive sailing abilities of ancient ships from averaged climatic wind data. A PhD study completed in 2022 at the University of Haifa, Department of Maritime Civilizations took a different approach using Data Science methods.

The underlying premise was that (a) the variabilities typical to Mediterranean winds are the key drivers of sailing mobility especially when a sailing passage lies contrary to prevailing winds; (b) these variabilities can be resolved in a large modern meteorological data set at high spatiotemporal resolution but are lost in averaged climatic data sets; and (c) palaeoclimatological examination has shown that the wind patterns in the Mediterranean have not changed in the last 3000 years and more.

Sailing passages are reconstructed throughout the data set using regatta weather-routing software. This reduces the meteorological data, which is in the order of billions  of records, to millions of sailing records. These are further reduced by statistical methods to obtain metrics of potential sailing mobility and are published in the data sheets for both direct sailing passages and for breeze assisted coastal sailing. The ancient mariners' limits of reasonability are also modelled in the process of determining practical potential sailing mobility.

The tools to produce additional data remain in place and active. Additional measures of potential sailing mobility produced since the original research have been added to the repository.

Potential sailing mobility measures for the Red Sea have been added in Version 4 of the data repository. Sheets exist for both Roman single main square sail rigs and for Indian Ocean type vessels rigged with Lateen sails. This facilitates comparisons of practical windward sailing in the Red Sea environment.
DOI: 10.17632/hzbg2wyjxb.5
title: Mappings of Potential Sailing Mobility during Antiquity: Research Data

description: Merchant sailing ships in Antiquity possessed very limited upwind capabilities and their sailing mobility was predominantly determined by variability of the wind. Mapping of potential sailing mobility in Antiquity has eluded researchers who have attempted to derive sailing abilities of ancient ships from averaged climatic wind data. A PhD study completed in 2022 at the University of Haifa, Department of Maritime Civilizations took a different approach using Data Science methods. The underlying premise was that (a) the variabilities typical to Mediterranean winds are the key drivers of sailing mobility especially when a sailing passage lies contrary to prevailing winds; (b) these variabilities can be resolved in a large modern meteorological data set at high spatiotemporal resolution but are lost in averaged climatic data sets; and (c) palaeoclimatological examination has shown that the wind patterns in the Mediterranean have not changed in the last 3000 years and more. Sailing passages are reconstructed throughout the data set using regatta weather-routing software. This reduces the meteorological data, which is in the order of billions of records, to millions of sailing records. These are further reduced by statistical methods to obtain metrics of potential sailing mobility and are published in the data sheets for both direct sailing passages and for breeze assisted coastal sailing. The ancient mariners' limits of reasonability are also modelled in the process of determining practical potential sailing mobility. The tools to produce additional data remain in place and active. Additional measures of potential sailing mobility produced since the original research have been added to the repository. Potential sailing mobility measures for the Red Sea have been added in Version 4 of the data repository. Sheets exist for both Roman single main square sail rigs and for Indian Ocean type vessels rigged with Lateen sails. This facilitates comparisons of practical windward sailing in the Red Sea environment.
DOI: 10.17632/hzbg2wyjxb.6
title: Mappings of Potential Sailing Mobility during Antiquity: Research Data

description: Merchant sailing ships in Antiquity possessed very limited upwind capabilities and their sailing mobility was predominantly determined by variability of the wind. Mapping of potential sailing mobility in Antiquity has eluded researchers who have attempted to derive sailing abilities of ancient ships from averaged climatic wind data. A PhD study completed in 2022 at the University of Haifa, Department of Maritime Civilizations took a different approach using Data Science methods. The underlying premise was that (a) the variabilities typical to Mediterranean winds are the key drivers of sailing mobility especially when a sailing passage lies contrary to prevailing winds; (b) these variabilities can be resolved in a large modern meteorological data set at high spatiotemporal resolution but are lost in averaged climatic data sets; and (c) palaeoclimatological examination has shown that the wind patterns in the Mediterranean have not changed in the last 3000 years and more. Sailing passages are reconstructed throughout the data set using regatta weather-routing software. This reduces the meteorological data, which is in the order of billions of records, to millions of sailing records. These are further reduced by statistical methods to obtain metrics of potential sailing mobility and are published in the data sheets for both direct sailing passages and for breeze assisted coastal sailing. The ancient mariners' limits of reasonability are also modelled in the process of determining practical potential sailing mobility. The tools to produce additional data remain in place and active. Additional measures of potential sailing mobility produced since the original research have been added to the repository. Changes in version 6: Sailing mobility mappings have been added for the Adriatic, the Black Sea, the Atlantic coasts, the Balearic Islands and initial mappings in the western Mediterranean basin.
DOI: 10.17632/hzbg2wyjxb.7
title: Atlas of Potential Sailing Mobility Mappings from the Neolithic Period to Late Antiquity: Research Data

description: Merchant sailing ships prior to Late Antiquity possessed limited upwind capabilities and their sailing mobility was predominantly determined by variability of the wind. Effective mapping potential sailing mobility has eluded researchers who have attempted to derive sailing abilities of ancient sailing vessels from averaged climatic wind data. A PhD study completed in 2022 at the University of Haifa, Department of Maritime Civilizations took a different approach using Data Science and simulation methods.

The underlying premise was that (a) the variabilities typical to Mediterranean winds are the key drivers of sailing mobility especially when a sailing passage lies contrary to prevailing winds; (b) these variabilities can be resolved by using a large modern meteorological data set (15 years) at high spatio-temporal resolution, but they are lost in averaged climatic data sets; and (c) palaeoclimatological examination has shown that the wind patterns in the Mediterranean have not changed in the last 3000 years and more.

Sailing passages are reconstructed throughout the data set using regatta weather-routing software. This reduces the meteorological data from the order of billions of records to millions of sailing records. These are further reduced by statistical methods to obtain metrics of potential sailing mobility for each passage. These metrics appear in data sheets for both direct sailing passages and for breeze assisted coastal sailing. The ancient mariners' limits of reasonability are also modelled in the process of determining practical potential sailing mobility.

Each data sheet summarises 5,479 individual simulated sailings on each direct passages. The data is presented in sections for mobility, sailing characteristics including distribution of points-of-sail, and for the environment encountered in the simulated sailings. 

The tools to produce additional mappings are continuously maintained. Additional measures of potential sailing mobility, produced since the original research, have been added to the repository. This atlas of mappings is constantly growing and is updated several time a year.

Changes in version 7: 
1. Sailing mobility data sheets have been added in a new section for the the Arabian Sea (both for vessels with square sails and vessels with Lateen sails).
2. Sailing mobility data sheets have been added in a new section for the late Beaker period in the western Mediterranean.
3. New direct passage data sheets have been added for all Mediterranean basins.
4. The folder structure organising the data sheets has been modified and it now contains multilevel folders.
5. All direct passage data sheets now include a table (Table 4) indicating the average number of days, in a given month, in which severe wind and/or waves might have been encountered for each passage.
DOI: 10.17632/hzbg2wyjxb.8
title: Atlas of Potential Sailing Mobility from the Neolithic Period to Late Antiquity: Research Data

description: The data sets in this repository are measures of potential sailing mobility for merchant ships, primarily of the period between the Middle Bronze Age and Late Antiquity. Two mappings of Neolithic Period sailing mobility are also included. The measures of sailing mobility are the product of a toolkit and methods developed at the University of Haifa, and they serve to assist researchers in the analysis of ancient maritime connectivity, including provision of quantitative inputs needed for network analyses and historic economic modelling.

The underlying premise was that (a) period ships had limited windward sailing ability (b) the variabilities typical to Mediterranean winds were the key drivers of sailing mobility primarily when a sailing passage lies contrary to prevailing winds; (c) these variabilities can be resolved by using a large modern meteorological data set (15 years) at high spatio-temporal resolution, but they are lost if averaged climatic data sets are used; and (d) palaeoclimatological examination has shown that the wind patterns in the Mediterranean have not changed in the last 3000 years and more.

Sailing passages are reconstructed throughout the meteorological data set using regatta weather-routing software reducing the meteorological data from the order of billions of records to millions of sailing records. These are further reduced by statistical methods to obtain metrics of potential sailing mobility for each passage. These metrics appear in data sheets for both direct sailing passages and for breeze-assisted coastal sailing. The ancient mariners' limits of reasonability are also modelled in the process of determining practical potential sailing mobility.

Each of the direct passage data sheets summarises 5,479 simulated daily sailings performed on each direct passage. The data sections include measures of mobility, sailing characteristics, including distribution of points-of-sail, and the environment encountered in the simulated sailing passages. 

The tools to produce additional mappings are continuously maintained. This atlas of sailing mobility mappings is constantly growing and is updated several times a year.

Changes in version 8: 
1. Additional potential mobility mappings have been added to the data, now totalling 1030 direct passages representing more than five million simulated sailings.
2. New index maps and lists of passages have been created.
3. There are changes to the folder structure. All datasets are in 11 top level folders without any subfolders.
DOI: 10.15468/dl.qfwkmu
title: Occurrence Download

description: A dataset containing 414738 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((20.89141 35.92802,23.75385 35.92802,23.75385 38.36912,20.89141 38.36912,20.89141 35.92802))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 414738 records from 517 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011860-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.eu7zmg
title: Occurrence Download

description: A dataset containing 345719 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Machine Observation, Material sample, Material citation, Human Observation, Specimen)",
 "CoordinateUncertaintyInMeters 0.0-959.0",
 "Country is one of (China, Hong Kong, Macao, Chinese Taipei)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "IucnRedListCategory is one of (CR, EN, VU, NT, LC, DD, NE)",
 "License is one of (CC0 1.0, CC-BY 4.0, CC-BY-NC 4.0)",
 "OccurrenceStatus is Present",
 "TaxonKey is Insecta",
 "Year 1876-2025"
 ]
}

 The dataset includes 345719 records from 49 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000001-250402095845217/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/mdnz77znf5.1
title: Zoospore diversity and sexual reproduction in the lichen-forming genus Trebouxia: from neglected evidence to new facts (Additional Data)

description: The data here provided are the dataset of the measurements for the morphological characterisation of flagellate cells of the 4 Trebouxia species investigated; the videos (obtained at light microscopy) showing the release of flagellate cells of different morphotypes (Videos 1-4); and the videos (obtained at light microscopy) showing the fusion of sexual gametes (Videos 5-8).
DOI: 10.17632/9vcs96tt4j
title: Data for Urban Heat stress Assessment in Delhi-National Capital Region

description: The Land Surface Temperature (LST) datasets were acquired at a 16-day interval from the MODIS Aqua satellite from the openly available Google Earth Engine (GEE) platform. The given datasets are the monthly composites for summer (April, May, June) and winter (Nov, Dec, Jan) from 2003 to 2022 for assessing long-term LST dynamics, UHI, intensity, and anomalies in the study area on a seasonal, diurnal, and nocturnal basis. The LST datasets were resampled at 100m spatial resolution using the nearest neighbor resampling technique.
DOI: 10.17632/9vcs96tt4j.1
title: Data for Urban Heat stress Assessment in Delhi-National Capital Region

description: The Land Surface Temperature (LST) datasets were acquired at a 16-day interval from the MODIS Aqua satellite from the openly available Google Earth Engine (GEE) platform. The given datasets are the monthly composites for summer (April, May, June) and winter (Nov, Dec, Jan) from 2003 to 2022 for assessing long-term LST dynamics, UHI, intensity, and anomalies in the study area on a seasonal, diurnal, and nocturnal basis. The LST datasets were resampled at 100m spatial resolution using the nearest neighbor resampling technique.
DOI: 10.17632/f2bvsmc2nw.1
title: Revenue-Sharing

description: This dataset is collected for an experiment examining how decision support recommendations (order quantity range) and revenue-sharing contract parameters—such as wholesale price and revenue share—affect the pull-to-center effect in retailer ordering behavior. To assess the impact of range recommendations on retailers’ ordering behavior, we compare the ordering behavior of subjects who receive recommendation R1: [220, 300] with those who are not given a specific range and instead base their orders on the demand distribution, R2: [100, 300]. Each subject was presented with two revenue-sharing contracts, C1 and C2 with different parameters: C1: (w = 1, λ = 0.25) and C2: (w = 1.8, λ = 0.45) .
DOI: 10.17632/d2sggc4txm.1
title: Heat Flow Visualization and Thermal Anomaly Detection in Metals via Phase Measuring Deflectometry

description: This data contains a Word document that includes a flow chart for the algorithm used for phase extraction using Fourier Transform and a discussion of simulation results that demonstrate how thermal signatures vary due to different material inhomogeneity. It also contains three video files V1, V2, and V3 capturing the spatiotemporal evaluation of thermal signatures for three different thermal anomalies.
DOI: 10.17632/d2sggc4txm.2
title: Defect Detection in Metals by Mapping Thermal Anomalies Using Heat Flow Visualization with Phase Measuring Deflectometry

description: This data contains a Word document that includes a flow chart for the algorithm used for phase extraction using Fourier Transform and a discussion of simulation results that demonstrate how thermal signatures vary due to different material inhomogeneity. It also contains three video files V1, V2, and V3 capturing the spatiotemporal evaluation of thermal signatures for three different thermal anomalies.