cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.21253/dmu.30146575.v1
title: Lowering of vapour pressure by solutes

description: Raoult’s law states that, for an ideal solution of volatile substances, the partial pressure exerted by each component in the gas above the solution is equal to the vapour pressure of the pure component multiplied by its mole fraction in the liquid mixture. The total vapour pressure of the solution is then given by the sum of these individual contributions, which is consistent with Dalton’s law of partial pressures.For a simple case of a two-component solution at room temperature, the total vapour pressure is the sum of the two pure component vapour pressures, each weighted by their mole fraction in the liquid. If one of the components is non-volatile, then it contributes nothing to the vapour above the solution. In this situation the vapour pressure of the solution is simply the vapour pressure of the pure volatile component multiplied by its mole fraction in the liquid.The reduction in vapour pressure compared with the pure liquid is therefore directly proportional to the mole fraction of the non-volatile solute. This means that adding a solute effectively dilutes the volatile solvent, lowering its vapour pressure in proportion to the fraction of solute present.For example, at 20 °C the vapour pressure of pure water is about 23 mbar. If a non-volatile solute is added, the vapour pressure decreases in a linear fashion with increasing solute mole fraction. When plotted against mole fraction, this produces a straight line that intercepts the y-axis at 23 mbar, with a slope of about −23.4 mbar. However, if the vapour pressure is replotted against solute weight percent, the relationship looks very different: instead of a straight line, the curve shows a sharp downturn at high solute concentrations, with the most precipitous drop occurring above roughly 80 wt%.For freeze-drying, the lowering of vapour pressure has important practical consequences. The presence of solutes in a frozen matrix reduces the effective vapour pressure of water compared with that of pure ice. As a result, the driving force for sublimation is diminished, which slows the rate of drying. In addition, because the vapour pressure depression is proportional to solute concentration, regions within the product that are richer in solute will dry more slowly than regions that are more dilute.This effect also underlies the concept of collapse temperature (). As ice is removed during primary drying, the unfrozen solute phase becomes more concentrated. The reduction in vapour pressure alters the balance between sublimation, glass transition behaviour, and structural stability. If the product temperature rises above the collapse temperature while vapour pressure is still depressed by concentrated solute, the dried structure can lose its rigidity and collapse.
DOI: 10.15468/dl.6ytw3c
title: Occurrence Download

description: A dataset containing 190 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is New Caledonia",
 "OccurrenceStatus is Present",
 "PublishingOrg is 2853c0e7-c758-4c9c-83a2-7c2d18967fb9",
 "TaxonKey is Cryptocarya"
 ]
}

 The dataset includes 190 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010696-250914085247600/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21253/dmu.30146170
title: Vapour pressure of ice calculated from the equations of Huang (2018)

description: The International Association for the Properties of Water and Steam<b> </b>(IAPWS, 2009) adopted a formulation based on the work of Wagner and co-workers, which provides the best fit to the authoritative experimental dataset. A key advance of this formulation is that it explicitly incorporates the temperature dependence of the latent heat of sublimation, thereby improving accuracy over a wide temperature range. The formulation was later published in detail by (Wagner <i>et al.</i>, 2011) ensuring broader dissemination and acceptance within the scientific community.Since then, a simpler equation to that proposed by Wagner was developed by Huang (Huang, 2018). It has a general exponential form in which the vapour pressure of the pure substance (expressed in pascals, Pa) is calculated from the temperature in degrees Celsius together with a set of empirical coefficients. The coefficients take different values depending on whether the equation is applied to the saturated vapour pressure of liquid water or to that of ice.For liquid water, the equation is valid above 0 °C, while for ice it is valid at 0 °C and below. In both cases, the structure of the equation is similar: it relates the natural logarithm of vapour pressure to a combination of constants and the reciprocal of a temperature term, adjusted by fitted parameters.In Huang’s formulation, the symbol <i>t</i> is used for temperature in degrees Celsius, while an upper-case <i>T</i> is reserved for temperatures in Kelvin. Using the liquid-water and ice versions of the equation, values for the vapour pressure can be tabulated and plotted as curves, as presented in the Excel workbook associated with this Figshare publication.Although less rigorous than the official IAPWS formulation, Huang’s equation offers a computationally efficient alternative, making it particularly useful for routine modelling and cycle design in freeze-drying applications.Huang, J. (2018) ‘A Simple Accurate Formula for Calculating Saturation Vapor Pressure of Water and Ice’, <i>J. Appl. Meteorol. Climatol.</i>, 57(6), pp. 1265–1272. Available at: https://doi.org/https://doi.org/10.1175/JAMC-D-17-0334.1.IAPWS (2009) Revised Release on the IAPWS Formulation 1995 for the Thermodynamic Properties of Ordinary Water Substance for General and Scientific Use, http://www.iapws.org. Available at: http://www.iapws.org.Wagner, W., Riethmann, T., Feistel, R. and Harvey, A.H. (2011) ‘New Equations for the Sublimation Pressure and Melting Pressure of H2O Ice Ih’, <i>J. Phys. Chem. Ref. Data</i>, 40(4), p. 043103. Available at: https://doi.org/https://doi.org/10.1063/1.3657937.
DOI: 10.21253/dmu.30146170.v2
title: Vapour pressure of ice calculated from the equations of Huang (2018)

description: The International Association for the Properties of Water and Steam<b> </b>(IAPWS, 2009) adopted a formulation based on the work of Wagner and co-workers, which provides the best fit to the authoritative experimental dataset. A key advance of this formulation is that it explicitly incorporates the temperature dependence of the latent heat of sublimation, thereby improving accuracy over a wide temperature range. The formulation was later published in detail by (Wagner <i>et al.</i>, 2011) ensuring broader dissemination and acceptance within the scientific community.Since then, a simpler equation to that proposed by Wagner was developed by Huang (Huang, 2018). It has a general exponential form in which the vapour pressure of the pure substance (expressed in pascals, Pa) is calculated from the temperature in degrees Celsius together with a set of empirical coefficients. The coefficients take different values depending on whether the equation is applied to the saturated vapour pressure of liquid water or to that of ice.For liquid water, the equation is valid above 0 °C, while for ice it is valid at 0 °C and below. In both cases, the structure of the equation is similar: it relates the natural logarithm of vapour pressure to a combination of constants and the reciprocal of a temperature term, adjusted by fitted parameters.In Huang’s formulation, the symbol <i>t</i> is used for temperature in degrees Celsius, while an upper-case <i>T</i> is reserved for temperatures in Kelvin. Using the liquid-water and ice versions of the equation, values for the vapour pressure can be tabulated and plotted as curves, as presented in the Excel workbook associated with this Figshare publication.Although less rigorous than the official IAPWS formulation, Huang’s equation offers a computationally efficient alternative, making it particularly useful for routine modelling and cycle design in freeze-drying applications.Huang, J. (2018) ‘A Simple Accurate Formula for Calculating Saturation Vapor Pressure of Water and Ice’, <i>J. Appl. Meteorol. Climatol.</i>, 57(6), pp. 1265–1272. Available at: https://doi.org/https://doi.org/10.1175/JAMC-D-17-0334.1.IAPWS (2009) Revised Release on the IAPWS Formulation 1995 for the Thermodynamic Properties of Ordinary Water Substance for General and Scientific Use, http://www.iapws.org. Available at: http://www.iapws.org.Wagner, W., Riethmann, T., Feistel, R. and Harvey, A.H. (2011) ‘New Equations for the Sublimation Pressure and Melting Pressure of H2O Ice Ih’, <i>J. Phys. Chem. Ref. Data</i>, 40(4), p. 043103. Available at: https://doi.org/https://doi.org/10.1063/1.3657937.
DOI: 10.21253/dmu.30146170.v1
title: Vapour pressure of ice calculated from the equations of Huang (2018)

description: The International Association for the Properties of Water and Steam<b> </b>(IAPWS, 2009) adopted a formulation based on the work of Wagner and co-workers, which provides the best fit to the authoritative experimental dataset. A key advance of this formulation is that it explicitly incorporates the temperature dependence of the latent heat of sublimation, thereby improving accuracy over a wide temperature range. The formulation was later published in detail by (Wagner <i>et al.</i>, 2011) ensuring broader dissemination and acceptance within the scientific community.Since then, a simpler equation to that proposed by Wagner was developed by Huang (Huang, 2018). It has a general exponential form in which the vapour pressure of the pure substance (expressed in pascals, Pa) is calculated from the temperature in degrees Celsius together with a set of empirical coefficients. The coefficients take different values depending on whether the equation is applied to the saturated vapour pressure of liquid water or to that of ice.For liquid water, the equation is valid above 0 °C, while for ice it is valid at 0 °C and below. In both cases, the structure of the equation is similar: it relates the natural logarithm of vapour pressure to a combination of constants and the reciprocal of a temperature term, adjusted by fitted parameters.In Huang’s formulation, the symbol <i>t</i> is used for temperature in degrees Celsius, while an upper-case <i>T</i> is reserved for temperatures in Kelvin. Using the liquid-water and ice versions of the equation, values for the vapour pressure can be tabulated and plotted as curves, as presented in the Excel workbook associated with this Figshare publication.Although less rigorous than the official IAPWS formulation, Huang’s equation offers a computationally efficient alternative, making it particularly useful for routine modelling and cycle design in freeze-drying applications.Huang, J. (2018) ‘A Simple Accurate Formula for Calculating Saturation Vapor Pressure of Water and Ice’, <i>J. Appl. Meteorol. Climatol.</i>, 57(6), pp. 1265–1272. Available at: https://doi.org/https://doi.org/10.1175/JAMC-D-17-0334.1.IAPWS (2009) Revised Release on the IAPWS Formulation 1995 for the Thermodynamic Properties of Ordinary Water Substance for General and Scientific Use, http://www.iapws.org. Available at: http://www.iapws.org.Wagner, W., Riethmann, T., Feistel, R. and Harvey, A.H. (2011) ‘New Equations for the Sublimation Pressure and Melting Pressure of H2O Ice Ih’, <i>J. Phys. Chem. Ref. Data</i>, 40(4), p. 043103. Available at: https://doi.org/https://doi.org/10.1063/1.3657937.
DOI: 10.6084/m9.figshare.30147571
title: AAAAAA.xlsx

description: BackgroundAging poses challenges global health and social care systems, with obesity potentially being associated with this process. However, sex differences and the mediating mechanisms underlying this association remain poorly understood. This study investigated sex differences in the associations of visceral adiposity index (VAI) with biological aging (BA) assessed via the Klemera-Doubal method age (KDMAge) and the risk of KDMAge acceleration (KDMAgeAccel), and explored the mediating role of the homeostasis model assessment of insulin resistance (HOMA-IR).Methods According to the National Health and Nutrition Examination Survey (1999–2018), weighted data from 19486 adults were analyzed cross-sectionally. VAI–BA associations were analyzed in the overall population and sex-specific subgroups using multivariable linear and logistic regressions, with nonlinear patterns explored via restricted cubic splines (RCSs) and threshold analyses. Mediation analyses quantified the mediating effects of HOMA-IR.Results VAI correlated positively with BA overall. However, females showed stronger associations than males for each 1-unit VAI increase with KDMAge elevation (βfemale = 1.02, 95% CI: 0.81–1.23; βmale = 0.59, 95% CI: 0.42–0.75) and KDMAgeAccel risk (ORfemale = 1.22, 95% CI: 1.17–1.28; ORmale = 1.10, 95% CI: 1.07–1.13), with all associations remaining significant (P &lt; 0.001). RCSs demonstrated nonlinear positive associations in all cohorts (Pnonlinear &lt; 0.001). Threshold analyses identified that females exhibited a higher VAI threshold for the KDMAge association (3.52 vs. 2.60) despite comparable effect sizes, whereas similar VAI thresholds across sexes were associated with a greater KDMAgeAccel risk in females than in males (75% vs. 36%). HOMA-IR partially mediated VAI–BA associations, with a greater percentage in males than in females in both VAI–KDMAge (21.67% vs. 12.71%) and VAI–KDMAgeAccel risk (27.09% vs. 10.39%) relationships. Conclusion VAI showed a significant positive association with BA, with females demonstrating a stronger association strength and males showing a greater proportion of the association mediated through HOMA-IR.
DOI: 10.6084/m9.figshare.30147571.v1
title: AAAAAA.xlsx

description: BackgroundAging poses challenges global health and social care systems, with obesity potentially being associated with this process. However, sex differences and the mediating mechanisms underlying this association remain poorly understood. This study investigated sex differences in the associations of visceral adiposity index (VAI) with biological aging (BA) assessed via the Klemera-Doubal method age (KDMAge) and the risk of KDMAge acceleration (KDMAgeAccel), and explored the mediating role of the homeostasis model assessment of insulin resistance (HOMA-IR).Methods According to the National Health and Nutrition Examination Survey (1999–2018), weighted data from 19486 adults were analyzed cross-sectionally. VAI–BA associations were analyzed in the overall population and sex-specific subgroups using multivariable linear and logistic regressions, with nonlinear patterns explored via restricted cubic splines (RCSs) and threshold analyses. Mediation analyses quantified the mediating effects of HOMA-IR.Results VAI correlated positively with BA overall. However, females showed stronger associations than males for each 1-unit VAI increase with KDMAge elevation (βfemale = 1.02, 95% CI: 0.81–1.23; βmale = 0.59, 95% CI: 0.42–0.75) and KDMAgeAccel risk (ORfemale = 1.22, 95% CI: 1.17–1.28; ORmale = 1.10, 95% CI: 1.07–1.13), with all associations remaining significant (P &lt; 0.001). RCSs demonstrated nonlinear positive associations in all cohorts (Pnonlinear &lt; 0.001). Threshold analyses identified that females exhibited a higher VAI threshold for the KDMAge association (3.52 vs. 2.60) despite comparable effect sizes, whereas similar VAI thresholds across sexes were associated with a greater KDMAgeAccel risk in females than in males (75% vs. 36%). HOMA-IR partially mediated VAI–BA associations, with a greater percentage in males than in females in both VAI–KDMAge (21.67% vs. 12.71%) and VAI–KDMAgeAccel risk (27.09% vs. 10.39%) relationships. Conclusion VAI showed a significant positive association with BA, with females demonstrating a stronger association strength and males showing a greater proportion of the association mediated through HOMA-IR.
DOI: 10.7910/dvn/zbf669
title: Results of Knowledge, Attitude and Practices of PPR Kampung Limau on Dengue (August 2025)

description: Contains the questionnaire that was used, alongside the answers, as well as certain transformation of data like age, working status, etc...
DOI: 10.5281/zenodo.14222361
title: Physiological stem measurements of three wheat cultivars ranging in drought stress

description: In this study, several physiological variables were measured in three different wheat (Triticum aestivum L.) cultivars. One drought sensitive cultivar (Viking) and two resistant cultivars (Impala and Servus) were subjected to different levels of drought stress. Variables such as the water potential, osmotic potential and water content are important to assess the hydraulic properties of drought responses in a plant. These variables were measured in the stems of the different cultivars because the stem water potential (SWP) is assumed to be a more stable measure of drought stress than the leaf water potential. We also measured the different variables in the wrapped leaves, as they should represent stem conditions. Soil water content and water potential were measured to quantify the drought stress. A total of nine pots were measured for each cultivar, and five plants per pot (n=5) were measured.Different levels of drought stress were induced at the booting phase, when stem mobilization was ongoing, while measurements took place a few days after anthesis, ensuring presence of carbohydrate storage in the stem.
DOI: 10.5281/zenodo.14222362
title: Physiological stem measurements of three wheat cultivars ranging in drought stress

description: In this study, several physiological variables were measured in three different wheat (Triticum aestivum L.) cultivars. One drought sensitive cultivar (Viking) and two resistant cultivars (Impala and Servus) were subjected to different levels of drought stress. Variables such as the water potential, osmotic potential and water content are important to assess the hydraulic properties of drought responses in a plant. These variables were measured in the stems of the different cultivars because the stem water potential (SWP) is assumed to be a more stable measure of drought stress than the leaf water potential. We also measured the different variables in the wrapped leaves, as they should represent stem conditions. Soil water content and water potential were measured to quantify the drought stress. A total of nine pots were measured for each cultivar, and five plants per pot (n=5) were measured.Different levels of drought stress were induced at the booting phase, when stem mobilization was ongoing, while measurements took place a few days after anthesis, ensuring presence of carbohydrate storage in the stem.
DOI: 10.15468/dl.vgj9ec
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Aubrieta columnae",
 "Country is Austria",
 "HasCoordinate is true"
 ]
}

 The dataset includes 6 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010699-250914085247600/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5pxheh
title: Occurrence Download

description: A dataset containing 58 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Aubrieta columnae",
 "Country is Belgium",
 "HasCoordinate is true"
 ]
}

 The dataset includes 58 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010700-250914085247600/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7d2qr3
title: Occurrence Download

description: A dataset containing 1359 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tagelus plebeius",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Occurrence evidence)",
 {
 "not" : {
 "OccurrenceStatus" : [
 "is one of (Absent)"
 ]
 }
 }
 ]
}

 The dataset includes 1359 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010698-250914085247600/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17142745
title: Multiple DJI drone flights with hyperspectral camera over forests in Lithuania #14

description: ## Hyperspectral

Hyperspectral data in all of the datasets consist of processed hyperspectral data cubes to radiance values.all data cubes with _radiance.dat and ._radiance.hdr files are for ENVI format data file. While _rect.dat and _rect.hdr files are ENVI files with georectification applied.

Hyperspectral data also contain calculated RGB and NDVI png and tiff images. PNG images are generated from _radiance.dat files and tiff images are generated from _rect.dat files that have georectification.

All hyperspectral data was collected using the Specim hyperspectral pushbroom camera.

### Hyper 14

https://art21-icaerus.s3.eu-central-1.amazonaws.com/Hyper_14.zip

Dataset consists of 14 flight lines filmed over a forest patch.

Each flight folder denoted by fl# contains processed hyperspectral data cubes and "processed" folder with RGB and NDVI images. 

Dataset zip size: 34 GB
DOI: 10.5281/zenodo.17142746
title: Multiple DJI drone flights with hyperspectral camera over forests in Lithuania #14

description: ## Hyperspectral

Hyperspectral data in all of the datasets consist of processed hyperspectral data cubes to radiance values.all data cubes with _radiance.dat and ._radiance.hdr files are for ENVI format data file. While _rect.dat and _rect.hdr files are ENVI files with georectification applied.

Hyperspectral data also contain calculated RGB and NDVI png and tiff images. PNG images are generated from _radiance.dat files and tiff images are generated from _rect.dat files that have georectification.

All hyperspectral data was collected using the Specim hyperspectral pushbroom camera.

### Hyper 14

https://art21-icaerus.s3.eu-central-1.amazonaws.com/Hyper_14.zip

Dataset consists of 14 flight lines filmed over a forest patch.

Each flight folder denoted by fl# contains processed hyperspectral data cubes and "processed" folder with RGB and NDVI images. 

Dataset zip size: 34 GB
DOI: 10.6084/m9.figshare.30147481.v1
title: <b>Data for "Unveiling the Conserved Mechanism of Microsporidian Vertical Transmission: A Comparative Study of Nosema Infection Across Host Species"</b>

description: This dataset contains all the raw data for the original article "Unveiling the Conserved Mechanism of Microsporidian Vertical Transmission: A Comparative Study of Nosema Infection Across Host Species".
DOI: 10.6084/m9.figshare.30147481
title: <b>Data for "Unveiling the Conserved Mechanism of Microsporidian Vertical Transmission: A Comparative Study of Nosema Infection Across Host Species"</b>

description: This dataset contains all the raw data for the original article "Unveiling the Conserved Mechanism of Microsporidian Vertical Transmission: A Comparative Study of Nosema Infection Across Host Species".