cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.18405756
title: Analyzing the Effectiveness of Macroeconomic Policies in Addressing Poverty in Iraq: An Econometric Study considering Digital Transformation and Artificial Intelligence for the Period (2004–2024)
DOI: 10.5281/zenodo.18405755
title: Analyzing the Effectiveness of Macroeconomic Policies in Addressing Poverty in Iraq: An Econometric Study considering Digital Transformation and Artificial Intelligence for the Period (2004–2024)
DOI: 10.5061/dryad.kwh70rzbz
title: Data from: Biogeographic patterns of Iranian Lepidoptera: A framework for conservation

description: The order Lepidoptera is one of the most diverse and species-rich insect
 groups in Iran, with at least 4,812 confirmed species, approximately 20%
 of which are endemic. Among them, the families Lycaenidae, Geometridae,
 and Zygaenidae have been extensively studied, each containing a
 significant number of documented species. Lycaenidae, with 215 species, is
 the largest family within Rhopalocera in Iran. Geometridae and Zygaenidae,
 representing diverse non-Papilionoidea families, comprise 539 and 73
 species, respectively. While Lycaenidae and Zygaenidae are primarily
 diurnal, Geometridae are nocturnal, making these families valuable models
 for studying species distribution patterns, bioregionalization, and
 Lepidoptera conservation in Iran. Given the country's unique position
 at the intersection of three zoogeographic realms—the Palearctic,
 Saharo-Arabian, and Oriental—these families contribute significantly to
 its high species richness and endemism.
description: As part of the Lepidoptera Iranica project, an extensive
 literature review was conducted on published studies covering various
 groups of Lepidoptera in Iran. Additionally, the dataset was supplemented
 with unpublished museum collection materials, resulting in a comprehensive
 compilation of species records. The collected data were carefully
 cross-checked taxonomically and phylogenetically by 70 specialists in
 different lepidopteran families. Finally, all records were georeferenced
 using Google Earth Pro v. 7.3.6.934 for further analysis. The occurrence
 dataset comprises 15,030 records for 797 species across three Lepidoptera
 families: Lycaenidae, Geometridae, and Zygaenidae. Additionally, it
 includes information on subspecies and the endemism status of each
 species.
description: # Data from: Biogeographic patterns of Iranian Lepidoptera: A framework
 for conservation
 [https://doi.org/10.5061/dryad.kwh70rzbz](https://doi.org/10.5061/dryad.kwh70rzbz) This dataset is the most comprehensive compilation of occurrence records for three families of Lepidoptera in Iran—Geometridae, Lycaenidae, and Zygaenidae—comprising 15,030 georeferenced records for 797 species. It integrates spatial data from both published literature and museum collections, covering records up to the end of 2022. ## Description of the data and file structure File: Iranian_Lepidoptera_Lycaenidae_Geometridae_Zygaenidae.csv The dataset includes occurrence records in decimal longitude/latitude format for 797 species across three families—Geometridae, Lycaenidae, and Zygaenidae—in Iran. Additionally, it provides information on subspecies and the endemism status of each species.
DOI: 10.15468/dl.jj9zvn
title: Occurrence Download

description: A dataset containing 570 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Amazona viridigenalis",
 "Year 1990-2026"
 ]
}

 The dataset includes 570 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003882-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7910/dvn/cxml8c
title: Validation of machine learning based scenario generators

description: We provide Matlab Code and interest data to reproduce the results in the paper
"Validation of machine learning based scenario generators", by Gero Junike, Solveig Flaig and Ralf Werner, Accepted by the Journal of Risk and Insurance.
DOI: 10.5061/dryad.98sf7m0rc
title: Data from: Pre- and post- treatment fold change plasma proteomics in metastatic NSCLC patients

description: Blood plasma samples were collected from advanced-stage NSCLC patients as
 part of a clinical study (PROPHETIC; NCT04056247). All clinical sites
 received IRB approval for the study protocol. Patient blood samples were
 drawn at baseline (referred to as T0) and, on average, 4 weeks after the
 treatment commenced, prior to the second dose of treatment (referred to as
 T1). Blood samples were drawn into tubes containing EDTA as an
 anticoagulant, and plasma was separated from the whole blood. The protocol
 adheres to the Clinical and Laboratory Standards Institute (CLSI)
 guidelines.
description: # Pre- and Post- treatment fold change plasma proteomics in metastatic
 NSCLC patients This
 dataset contains fold-change values representing the ratio between
 on-treatment (T1) and pre-treatment (T0) plasma protein abundance levels
 in 225 non-small cell lung cancer (NSCLC) patients. The dataset was used
 to characterize early on-treatment proteomic changes in blood plasma and
 gain insights into treatment response and resistance in NSCLC patients
 treated with immunotherapy. **Description of the data and file structure**
 The dataset consists of the following file: fold_change.csv: Fold-change
 values representing the ratio of on-treatment (T1) to pre-treatment (T0)
 reads for each aptamer ID, which corresponds to a specific protein.
 Details regarding the measured proteins according to the aptamer ID are
 available at Somalogic website (). The
 fold_change.csv file contains fold-change values for each protein, with
 rows representing individual patients and columns representing the
 fold-change ratios for each protein. **Sharing/Access information**
 Additional details about patient recruitment, sample collection, and data
 analysis can be found in the accompanying paper titled "Biological
 insights from plasma proteomics of non-small cell lung cancer patients
 treated with immunotherapy" (doi:
DOI: 10.5683/sp3/dhxpqd
title: Rapport de panel

description: Ce rapport est lié au panel de discussion qui a eu lieu lors du 5ième colloque du RÉSEAU - pour un développement psychosocial par le sport et le plein air. Le panel de discussion, intitulé "Regards croisés sur l’offre de formation en intervention par la nature (et l’aventure) au Québec et au-delà : états des lieux et pistes d’action pour optimiser la formation au Québec", constitue une première étape collaborative visant à inclure les membres du RÉSEAU dans la réflexion et dans l’élaboration future de lignes directrices qui reflètent les postures axiologiques (valeurs), épistémologiques (types de savoirs et connaissances valorisés) et méthodologiques (approches et stratégies d’intervention) que nous souhaitons collectivement promouvoir en INA au Québec. À cet effet, il invite à réfléchir aux orientations et aux pratiques qui permettront d’aligner les interventions et les programmes INPA/INA à des valeurs partagées, pertinentes et durables qui répondent aux besoins réels personnes bénéficiant de tels services, mais également à ceux des êtres non-humains qui habitent les écosystèmes québécois et qui occupent une place centrale dans les processus d’intervention.

Le rapport présente les trois étapes liée au déroulement du panel de discussion. D’abord, il fait appel à des experts du milieu pour faire un état des lieux sur la formation au Québec selon trois niveaux de formation : universitaire, collégiale et privée. Ensuite, des données préliminaires d’une démarche visant à faire état de différents cursus de formation à l’échelle internationale sont présentées. Enfin, une réflexion sur les besoins émergents en INA/INPA et sur les enjeux liés à la formation actuelle est entamée avec les 49 membres du RÉSEAU participant à cet atelier. Le volet collaboratif vise ainsi à mobiliser les savoirs et les connaissances des personnes participantes afin de réfléchir et documenter collectivement les besoins émergents, les enjeux et les pistes d’action.
DOI: 10.5061/dryad.zcrjdfnm3
title: Ambient noise cross-correlation functions and three-dimensional S-wave velocity structure in the Noto Peninsula, Japan

description: The three-year-lasting earthquake swarm in the Noto Peninsula, Japan, led
 to the 2024 Noto earthquake (moment magnitude 7.5). To reveal structural
 controls on the swarm evolution and the large earthquake generation, we
 imaged the three-dimensional S-wave velocity structure beneath the Noto
 Peninsula using ambient noise surface wave tomography with dense seismic
 observations. This dataset provides the cross-correlation functions of the
 densely observed ambient seismic noise and the estimated three-dimensional
 S-wave velocity structure model. We computed the multicomponent
 cross-correlation functions for the pairs of 22 seismic stations (composed
 of 12 seismic nodes and 10 short-period permanent stations). The
 observation data spanned 32 days, from October to November 2023. The
 cross-correlation functions in the vertical-vertical, vertical-radial,
 radial-radial, and transverse-transverse components yielded the estimates
 of dispersion curves of Rayleigh and Love waves. The dispersion curves of
 the fundamental-mode Rayleigh and Love waves in the frequency range of
 0.10–0.45 Hz were used to estimate isotropic S-wave velocity structure via
 two-dimensional phase velocity tomography and a series of local 1D
 inversions. Our results show a high-velocity body collocated with the
 major slip zone of the 2024 Noto earthquake, a region the preceding swarm
 avoided. This observation strongly suggests that the structural
 heterogeneity beneath the Noto Peninsula controlled the swarm evolution
 and the generation of the 2024 Noto earthquake.
description: # Ambient noise cross-correlation functions and three-dimensional S-wave
 velocity structure in the Noto Peninsula, Japan
 [https://doi.org/10.5061/dryad.zcrjdfnm3](https://doi.org/10.5061/dryad.zcrjdfnm3) ## Description of the data and file structure ccf.h5: The cross-correlation function (CCF) data are stored in the self-describing HDF5 format. The attributes of the HDF5 file describe the following parameters: * b: Starting lag time of CCFs in seconds (-204.7). * nc: Number of components of original seismograms (3). The number of CCF components is nc x nc (9). * ns: Number of stations (22). * npts: Number of CCF data samples (4096). * sr: Sampling rate in samples per second (10). * stnm1 & stnm2: Names of stations 1 & 2. * stla1 & stla2: Latitudes of stations 1 & 2. * stlo1 & stlo2: Longitudes of stations 1 & 2. * stel1 & stel2: Elevations of stations 1 & 2. * cmpnm: Name of CCF component. * nstack: Number of CCF stacks. vs3d.nc: The 3D S-wave velocity model is stored in the NetCDF format. This file contains three variables as follows: * Vs: Estimated S-wave velocity in km/s. * Ndata: Number of dispersion data used to estimate S-wave velocity. At grid points with zero Ndata, the S-wave velocity structures are the same as the initial model (Nishida et al. 2008; doi:10.1029/2007JB005395). * SD: Standard deviation of the estimated S-wave velocity in km/s.
DOI: 10.5061/dryad.37pvmcvsk
title: Unveiling the submerged secrets: bumblebee queens' resilience to flooding

description: In a previous study, an experimental oversight led to the accumulation of
 water filling a container housing diapausing bumblebee queens.
 Surprisingly, after draining the water, the queens were found to be alive.
 This observation raises a compelling question: can bumblebee queens endure
 periods of inundation while overwintering underground? To address this
 question, we conducted an experiment using 143 common eastern bumblebee
 (Bombus impatiens) queens placed in soil-filled tubes and subjected to
 artificially induced diapause in a refrigerated unit for seven days. Tap
 water was then added to the tubes and queens (n=21/treatment) were either
 maintained underwater using a plunger-like apparatus or left to float
 naturally on the water’s surface for varying durations (8h, 24h, or 7
 days) while remaining in overwintering conditions. Seventeen queens served
 as controls. After the submersion period, queens were removed from the
 water, transferred to new tubes with soil, and kept in cold storage for 8
 weeks. Overall queen survival remained consistently high (89.5 ± 6.4%)
 across all treatments and did not differ among submersion regimes and
 durations. These results demonstrate the remarkable ability of
 diapausing B. impatiens queens to withstand submersion underwater
 for up to one week, indicating their adaptations to survive periods of
 flooding in the wild.
description: # Unveiling the submerged secrets: bumblebee queens' resilience to
 flooding
 [https://doi.org/10.5061/dryad.37pvmcvsk](https://doi.org/10.5061/dryad.37pvmcvsk) This README file describes the data package accompanying the publication: Rondeau S, Raine NE. 2024. Unveiling the submerged secrets: bumblebee queens' resilience to flooding. *Biology Letters.* doi: 10.1098/rsbl.2023.0609 ## Description of the data and file structure The file "Data_flooding.csv" contains the dataset analyzed in the study. The description of each variable is as follows: * Bee_ID: unique bumblebee queen identifier * Maternal_colony: the parental colony of each queen * Weight: weight of the queens, in mg * Submersion: submersion regime (ctl = Control; floating = Left to float; underwater = Maintained underwater) * Duration: submersion duration (N/A = not applicable; 8 = 8 hours; 24 = 24 hours; 7 = 7 days) * Tx: Treatment (combination of 'Submersion' and 'Duration': e.g. floating_24 = Left to float during 24 hours) * Time: week of survival assessment (1 week, 4 weeks, or 8 weeks) * Survival: 1 = alive; 0 = dead ## Code/Software The file 'Code_flooding.R' reproduces the analyses of the article cited above.
DOI: 10.5061/dryad.fbg79cp33
title: First singing data of Graptopsaltria nigrofuscata and weather data

description: Data set used in a study that used long-term phenology data to explore key
 weather factors that affect the emergence of the Graptopsaltria
 nigrofuscata and detect the effects of climate change. This study showed
 that the emergence of Graptopsaltria nigrofuscata was influenced by higher
 temperatures during the summer to winter of the previous year. The effects
 of other climate factors such as precipitation and humidity were small.
 The annual increase in temperature caused by climate change was causing
 the advancement of cicada emergence patterns. The data consisted of
 long-term observations by the Japan Meteorological Agency, the last three
 years of data from citizen scientists, and weather data at the respective
 observation sites.
description: # First singing data of *Graptopsaltria nigrofuscata* and weather data
 [https://doi.org/10.5061/dryad.fbg79cp33](https://doi.org/10.5061/dryad.fbg79cp33) ## Description of the data and file structure "JMA_Data.csv" is long-term phenological data of the first singing date of *Graptopsaltria nigrofuscata* recorded by the Japan Meteorological Agency. Site means local meteorological observatories. DOY means the number of days from January 1. "Citizen_Data.csv" is phenological data of the first singing date of *Graptopsaltria nigrofuscata* between 2021 to 2023 recorded by citizen scientists. DOY means the number of days from January 1. Lat means latitude, and Lon means longitude. Cit_Site means the site ID of citizen scientists. "JMA_Weather_Data.csv" is the weather data of each local meteorological observatory. "NA" indicates that records were missing or not measured. Site means local meteorological observatories. DOY means the number of days from January 1. Temperature, humidity, wind_speed, precipitation, and solar_radiation mean daily average air temperature (°C), humidity (%), wind speed (m/s), cumulative precipitation (mm), and solar radiation (MJ/m^2), respectively. Site means local meteorological observatories. "Citizen_Weather_Data.csv" is the weather data for citizen scientists' sites. “Temp”, “Hum”, “Wind”, “Prec”, and “Solar” means daily average air temperature (°C), humidity (%), wind speed (m/s), and cumulative precipitation (mm) and solar radiation (MJ/m^2), respectively. Lat means latitude, and Lon means longitude. Cit_Site means the site ID of citizen scientists.
DOI: 10.5061/dryad.hx3ffbgmz
title: The effect of attendance over performance in higher education

description: The COVID-19 pandemic disrupted higher education, leading to shifts in
 attendance patterns. This study investigates the relationship between
 compulsory class attendance and academic achievement across a diverse
 array of course-content subjects at Universidad Europea de Canarias,
 Spain, focusing on two subject groups within the degree programs of the
 Social Science Faculty. Specifically, our analysis delves into subjects
 characterized by a substantial quantitative component and more
 conceptually oriented subjects. The findings show a robust positive
 connection between attendance and academic performance, with a more
 pronounced impact observed in courses with a quantitative emphasis.
 Additionally, semester-specific effects emerge as influential determinants
 in shaping students' academic outcomes. This study underscores the
 significance of attendance policies in enhancing the learning experience
 of university students and advocates for tailored instructional approaches
 that acknowledge the unique context of each student.
description: The authors picked up the data from their own students and other
 colleagues' students during an academic year. There was a previous
 informed consent from the students and we also received the approval of
 the European University Ethical Comittee with reference code
 2024-493.
description: # The attendance effect over performance in higher education
 Our database contains data
 from 137 students at the European University of the Canary Islands during
 the course 2022-23. Each row corresponds to a student, they are numbered
 anonymously and consecutively (column 1). Data is collected for six
 subjects: Subject 1 (columns B-E), Subject 2 (columns F-I), Subject 3
 (columns J-M), Subject 4 (columns N-Q), Subject 5 (columns R-U), Subject 6
 (columns V-Y). Each subject occupies 4 columns corresponding to each of
 the variables collected. For each subject, the variables collected are:
 Semester [1 (1st Semester) or 2 (2nd semester)]; Theoretical (0) or
 quantitative (1) subject; Attendance (%); and Final qualification (out of
 10 points). The variables name appear in file 1. Attendance shows
 percentage of in-person attendance during the semester. Final
 qualification shows the final mark obtained in the subject for that
 individual. There are students who took all subjects, whilst there are
 others who took only some of them. In the event that a student had not
 taken a subject, all related data for that student is scored with n/a.
DOI: 10.5281/zenodo.18140866
title: Luminescence characteristics of surface sediments from southern South America

description: This dataset contains locations and luminescence measurements for individual surface sediment samples collected across southern South America, including corresponding relative standard errors for each sample. The measurements comprise feldspar luminescence signals used to characterize signal properties and variability among samples. Sampling locations span a range of geomorphological and climatic settings in southern South America. The purpose of the dataset is to support the analysis of sediment provenance and transport processes using luminescence characteristics of surface sediments.
DOI: 10.5061/dryad.83bk3jb0h
title: Land use and land cover scenarios for the Maurienne valley (French Alps) at 2085 horizon produced using CLUMPY model

description: We built three contrasted future LULC scenarios from 2020 to 2085 with the
 CLUMPY model (Mazy and Longaretti, 2022). The CLUMPY model is an
 innovative model of land use and land cover change comprising a
 calibration-estimation module separate from a non-biased allocation
 module. It is calibrated by using time series of past LULC maps (Mazy and
 Longaretti, 2022). The model then calculates transition probabilities for
 each LULC class according to relevant spatial explanatory variables. Next,
 the model can produce maps of future LULC distributions according to
 information it learned during the calibration-estimation phase. This model
 has the benefits of being easy to use, proposing nonbiased allocation
 methods and producing scenarios of future LULC change either by adjusting
 manually the matrix of LULC transitions probabilities (used for the
 Conservation and Tourism scenarios) or by training the model on specific
 areas of the past time series (only used for the Conservation scenario).
description: The scenarios were based on the “Montagne 2040” report that
 explore potential future for specific alpine region and their associated
 narratives (Claveranne, 2013). The “Business As Usual” scenario (BAU)
 extended the 2006-2016 observed trends. The “Conservation” scenario
 assumed: the expansion of protected areas, reduced support for agriculture
 and livestock farming, and LULC transitions, i.e., from grassland to shrub
 or forest, and from shrubland to forest (aka landscape encroachment). The
 “Tourism” scenario assumed the development of ski resorts and mass tourism
 in the valley, growing urbanization at low and middle altitude, and
 associated LULC transitions from grassland or shrubland to urban (see
 Supplementary Material D). Scenarios of LULC change only considered broad
 categories of LULC: urban, forest, shrub and grassland.
description: # Land use and land cover scenarios for the Maurienne valley (French Alps)
 at 2100 horizon produced using CLUMPY model
 [https://doi.org/10.5061/dryad.83bk3jb0h](https://doi.org/10.5061/dryad.83bk3jb0h) This datasets comprised several maps in .asc format for the Maurienne valley in the french alps. ## Description of the data and file structure Data are in EPSG: 4326. Three scenarios of future change are provided (Buisiness as Usual - S1, Conservation - S2, Tourism - S3). For each of those scenarios two data are provided : 2050 and 2085. Only the S1 have a map for 2020. LULC code description | Code | LULC | | :--- | :------------------------------ | | 1 | Permanent snow and glaciers | | 2 | Mineral surfaces and bare soils | | 3 | Grassland | | 4 | Shrub | | 5 | Open forest | | 6 | Closed forest | | 7 | Crops | | 8 | Urban | | 9 | Water | | 10 | Roads | ## Sharing/Access information Data are derived from the CLUMPY model (Mazy and Longaretti, 2022) and Montagnes 2040 reports that provided naratives for the scenarios (Claveranne, 2013).