cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/m9b3bhzdhf.3
title: Rich sample dataset for assessing digital innovation: Data from digitally skilled teachers in Bisha Province, Saudi Arabia

description: In this study, we gathered low-level digital innovation datasets among digitally skilled teachers (DSTs) of Bisha Province, Saudi Arabia and recognize the need for 1) a real assessment to measure and identify the problem(s), 2) designing and introducing a DISs training program for such teachers.
A rich sample of 400 voluntary responses were conducted from the teacher’s community in Bisha, Saudi Arabia. Male and female general education teachers participated in the questionnaire, with 218 and 182 female (54.5 %) and male (45.5 %) teachers, respectively. The professional rank of practicing teachers was 286 male and female teachers (71.5 %), 66 male and female participants had the rank of a teacher, while the rest had other ranks. Herein, 94, 75, and 70 of them were majored in mathematics, Islamic education, and Arabic language, at a rate of 23.5, 18.8, and 17.5 %, respectively. Furthermore, 255 participants (63.7 %) had not received training in DISs.
DOI: 10.17632/zbd8wj942y.1
title: Effect of Parental Involvement on Students’ Achievement in Mathematics: Roles of Learning Engagement and Self-efficacy (data used for the analysis)

description: Data on junior secondary school students' perceived parental involvement, learning engagement, mathematics self-efficacy, and achievement in Mathematics
DOI: 10.17031/65d32b581d311.1
title: 2011 Marine Biological Association of the UK (MBA) Bovisand Surveying Habitats and Researching Coasts (SHARC) group and MBA members Alien Invaders timed survey

description: A SHARC and MBA members run timed species survey for non-native species at Bovisand, Devon.  Some native species were also recorded.
DOI: 10.15468/dl.acdaew
title: Occurrence Download

description: A dataset containing 45 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lilium gongshanense (Y.D.Gao & X.J.He) Y.D.Gao"
 ]
}

 The dataset includes 45 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043153-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.eadfpn
title: Occurrence Download

description: A dataset containing 428 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lithodora hispidula (Sm.) Griseb."
 ]
}

 The dataset includes 428 records from 55 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043155-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k5d2x2
title: Occurrence Download

description: A dataset containing 254 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Leptopus cordifolius Decne."
 ]
}

 The dataset includes 254 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043154-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/tcpj358sk2.1
title: Lack of Period1 accelerates colorectal tumorigeneses in APCmin/+ mice

description: Clock genes drive the circadian rhythm in each cell, and Period1 (Per1) is one of the core genes in mammals. When the clock genes lose their functions due to deficiency, various behavioral and physiological functions are altered. Although many pathological studies have been conducted on clock genes and cancers, the results could be more consistent. In the present study, we aimed to clarify how the lack of Per1 affects the development and progression of colorectal cancer. We recorded survival days and calculated survival rates, measured the number of polyps, performed histological evaluation, and measured β-catenin expression using ApcMin/+Per1-/- mice. The results showed that loss of Per1 caused variation in the survival rate of mice, increased the number of polyps, and increased β-catenin expression. These results suggest that Per1 plays a role in suppressing the development and progression of colorectal cancer.
DOI: 10.17632/3jdn6x32sg.1
title: Alternating Suture and Staple Placement for Linear High Tension Scalp Wounds: A Video Walkthrough

description: Video Walkthrough
DOI: 10.17632/kpj9gcnsz2.1
title: Java Application to Design, Develop and Execute Preventative Tests Based on Synthetic App Monitoring Outcome and GenAI

description: Software development is characterized by quick innovations, intricate designs, and changing customer requirements. Preventative testing finds and fixes flaws early in the development process, acting as a proactive approach to guarantee that software products fulfill quality requirements. Development teams may improve the user experience by drastically lowering the probability of faults making it into production by putting in place a strong preventive testing architecture.
Preventative testing's capacity to find security holes and vulnerabilities in software programmes is one of its main advantages. Integrating security-focused preventive testing contributes to the overall integrity of digital ecosystems by protecting sensitive data and ensuring that software systems are resilient to possible breaches in the face of growing cyber threats.
Cost-effectiveness is another crucial facet of preventative testing. Early detection and resolution of defects during the development phase lead to substantial cost savings compared to addressing issues post-deployment. By minimizing the need for emergency fixes and updates, preventative testing supports efficient resource allocation and reduces the economic burden associated with software maintenance.
Preventative testing is also essential to keeping project deadlines and delivery dates on track. Early problem-solving and identification throughout the development life cycle helps teams better stick to project schedules, which guarantees on-time product delivery and satisfied customers.
Preventative testing strategies, which incorporate automated testing, continuous integration, and other cutting-edge techniques, grow along with the complexity of software systems. Development teams may produce high-quality software more quickly, detect any bottlenecks, and optimize their testing procedures by using these breakthroughs.
The application jar included with this data collection offers the preventative test solutions based on synthetic app monitoring outcome, code coverage information, performing browser synthetic app monitoring and provide valuable recommendation based on gen AI. Providing a platform that will function as an engine and offer preventative tests to identify errors early in the software development life cycle is the main problem statement driving this approach. This is done with the understanding that no further time will be spent on the procedure because the primary reason for not doing the preventive test is a time crisis. In addition to saving your time, parallel testing ensures that you receive the highest amount of test coverage. Preventative testing based on synthetic app monitoring gives you the ability to answer to support tickets with the greatest amount of ground testing before issues are reported.
DOI: 10.17632/kpj9gcnsz2.2
title: Java Application to Design, Develop and Execute Preventative Tests Based on Synthetic App Monitoring Outcome and GenAI

description: Software development is characterized by quick innovations, intricate designs, and changing customer requirements. Preventative testing finds and fixes flaws early in the development process, acting as a proactive approach to guarantee that software products fulfill quality requirements. Development teams may improve the user experience by drastically lowering the probability of faults making it into production by putting in place a strong preventive testing architecture.
Preventative testing's capacity to find security holes and vulnerabilities in software programmes is one of its main advantages. Integrating security-focused preventive testing contributes to the overall integrity of digital ecosystems by protecting sensitive data and ensuring that software systems are resilient to possible breaches in the face of growing cyber threats.
Cost-effectiveness is another crucial facet of preventative testing. Early detection and resolution of defects during the development phase lead to substantial cost savings compared to addressing issues post-deployment. By minimizing the need for emergency fixes and updates, preventative testing supports efficient resource allocation and reduces the economic burden associated with software maintenance.
Preventative testing is also essential to keeping project deadlines and delivery dates on track. Early problem-solving and identification throughout the development life cycle helps teams better stick to project schedules, which guarantees on-time product delivery and satisfied customers.
Preventative testing strategies, which incorporate automated testing, continuous integration, and other cutting-edge techniques, grow along with the complexity of software systems. Development teams may produce high-quality software more quickly, detect any bottlenecks, and optimize their testing procedures by using these breakthroughs.
The application jar included with this data collection offers the preventative test solutions based on synthetic app monitoring outcome, code coverage information, performing browser synthetic app monitoring and provide valuable recommendation based on gen AI. Providing a platform that will function as an engine and offer preventative tests to identify errors early in the software development life cycle is the main problem statement driving this approach. This is done with the understanding that no further time will be spent on the procedure because the primary reason for not doing the preventive test is a time crisis. In addition to saving your time, parallel testing ensures that you receive the highest amount of test coverage. Preventative testing based on synthetic app monitoring gives you the ability to answer to support tickets with the greatest amount of ground testing before issues are reported.
Please do visit our github repo for more updated code and artifacts on https://github.com/sohambpatel/PreventativeTests
DOI: 10.17632/kpj9gcnsz2.3
title: Java Application to Design, Develop and Execute Preventative Tests Based on Synthetic App Monitoring Outcome and GenAI

description: Software development is characterized by quick innovations, intricate designs, and changing customer requirements. Preventative testing finds and fixes flaws early in the development process, acting as a proactive approach to guarantee that software products fulfill quality requirements. Development teams may improve the user experience by drastically lowering the probability of faults making it into production by putting in place a strong preventive testing architecture.
Preventative testing's capacity to find security holes and vulnerabilities in software programmes is one of its main advantages. Integrating security-focused preventive testing contributes to the overall integrity of digital ecosystems by protecting sensitive data and ensuring that software systems are resilient to possible breaches in the face of growing cyber threats.
Cost-effectiveness is another crucial facet of preventative testing. Early detection and resolution of defects during the development phase lead to substantial cost savings compared to addressing issues post-deployment. By minimizing the need for emergency fixes and updates, preventative testing supports efficient resource allocation and reduces the economic burden associated with software maintenance.
Preventative testing is also essential to keeping project deadlines and delivery dates on track. Early problem-solving and identification throughout the development life cycle helps teams better stick to project schedules, which guarantees on-time product delivery and satisfied customers.
Preventative testing strategies, which incorporate automated testing, continuous integration, and other cutting-edge techniques, grow along with the complexity of software systems. Development teams may produce high-quality software more quickly, detect any bottlenecks, and optimize their testing procedures by using these breakthroughs.
The application jar included with this data collection offers the preventative test solutions based on synthetic app monitoring outcome, code coverage information, performing browser synthetic app monitoring and provide valuable recommendation based on gen AI. Providing a platform that will function as an engine and offer preventative tests to identify errors early in the software development life cycle is the main problem statement driving this approach. This is done with the understanding that no further time will be spent on the procedure because the primary reason for not doing the preventive test is a time crisis. In addition to saving your time, parallel testing ensures that you receive the highest amount of test coverage. Preventative testing based on synthetic app monitoring gives you the ability to answer to support tickets with the greatest amount of ground testing before issues are reported.
Please do visit our github repo for more updated code and artifacts on https://github.com/sohambpatel/PreventativeTests
DOI: 10.15468/dl.cxs5nx
title: Occurrence Download

description: A dataset containing 14 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Linderniella horombensis (Eb.Fisch.) Eb.Fisch., Schäferh. & Kai Müll."
 ]
}

 The dataset includes 14 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043157-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bpx7mn
title: Occurrence Download

description: A dataset containing 142 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lepidium desertorum Eckl. & Zeyh."
 ]
}

 The dataset includes 142 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043156-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kdwjt8
title: Occurrence Download

description: A dataset containing 559447 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is one of (Rumex acetosella L.)"
 ]
}

 The dataset includes 559447 records from 2653 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043127-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5061/dryad.4kp4r/9
title: Supplementary Table 6 (Domingo et al.)
DOI: 10.5061/dryad.4p502/1
title: Simulation of adaptive walks on correlated fitness landscapes

description: In our simulations, the initial fitness of each block is chosen independently such that their average equals f_0. From then on, the adaptive proceeds until the fitness of all blocks reach local fitness peaks. Over 10^5 iterations, various quantities like average fitness difference between steps and the selection coefficient are calculated for the every step of the adaptive walk.
DOI: 10.5061/dryad.4p502/2
title: Simulation of adaptive walks on uncorrelated fitness landscapes

description: Starting from fitness f_0, the adaptive walk proceeds as per the transition probability (4) in the manuscript until it reaches a local fitness peak. The average fitness difference, selection co-efficient and the walk length are averaged over 10^6 iterations.
DOI: 10.5061/dryad.4r4r6/1
title: µSat Data

description: In this file the microsatellite data for each individual (ID) and its group is given in the first two columns. The following 22 columns are organized in pairs with both allels of one loci each. Values -9 indicate missing data.
DOI: 10.5061/dryad.4r4r6/2
title: IMa input file

description: Input file for Isolation-with-Migration analyses. Data is arranged locuswise, giving also locus-specific mutation rates (95% confidence interval). far = individuals originated from Farasan Islands; main = individuals originated from the south-western part of the Arabian Peninsula
DOI: 10.5061/dryad.4r4r6/3
title: skull measurements

description: Skull measurements for morphologcial analyses. Given is individual (ID), group (main = originated from the mainland of the Arabian Peninsula; far = originated from Farasan Islands), Sex (0 = males; 1 = females), wildcaptive (0 = individual originated from the wild; 1 = individual were bred in captivity) and data for 32 linear, log10-transformed skull measurements (for abbreviations see Fig. S2).
DOI: 10.5061/dryad.52c2h/1
title: Drepanotrema depressissimum microsatellite genotypes (GenAlEx)

description: Drepanotrema depressissimum microsatellite genotypes as GenAlEx format. For more information on sampling locations see the corresponding habitat characteristics data file.
DOI: 10.5061/dryad.52c2h/2
title: Drepanotrema depressissimum microsatellite genotypes (Genepop)

description: Drepanotrema depressissimum microsatellite genotypes as genepop format. For more information on sampling locations see the corresponding habitat characteristics data file.
DOI: 10.5061/dryad.52c2h/3
title: Drepanotrema depressissimum microsatellite genotypes (Rmes)

description: Drepanotrema depressissimum microsatellite genotypes as Rmes format. Rmes estimates unbiased selfing rates from population genetic data, for more information or to download the Rmes sofware see :http://www.cefe.cnrs.fr/en/genetique-et-ecologie-evolutive/patrice-david.
DOI: 10.5061/dryad.58ss8/10
title: RabV-L

description: Rabies virus - non-structural gene
DOI: 10.5061/dryad.58ss8/11
title: RVA-G2-S

description: Rotavirus A G2 - structural gene
DOI: 10.5061/dryad.58ss8/12
title: RVA-G3-S

description: Rotavirus A G3 - structural gene
DOI: 10.5061/dryad.58ss8/13
title: EAV-S

description: Equine arteritis virus - structural gene
DOI: 10.5061/dryad.58ss8/3
title: HAV-NS

description: Hepatitis A virus - non-structural gene
DOI: 10.5061/dryad.58ss8/5
title: RVA-NS

description: Rotavirus A - non-structural gene
DOI: 10.5061/dryad.58ss8/6
title: RVC-NS

description: Rotavirus C - non-structural gene
DOI: 10.5061/dryad.58ss8/7
title: RVC-S

description: Rotavirus C - structural gene
DOI: 10.5061/dryad.58ss8/8
title: CCHFV-NS

description: Crimean-Congo hemorrhagic fever virus - non-structural gene
DOI: 10.5061/dryad.58ss8/9
title: BDV-N

description: Borna disease virus - structural gene
DOI: 10.5061/dryad.610dd/1
title: IUPACAlignmentLessThan4SNPsPhylipFormat

description: This is a Phylip file alignment (not interleaved) of RAD-seq assembled data from pooled DNA samples from Nucella lapillus populations along the Northwestern Atlantic. For more information, please contact Nathaniel Chu (nathanieldchu@gmail.com).
DOI: 10.5061/dryad.63fp5/1
title: Pollen-transport networks

description: Quantitative matrices of interactions among insect pollinators and plant pollen types for species-species and individuals-species networks at two study sites.
DOI: 10.5061/dryad.63fp5/2
title: Pollinator and plant pollen type nodes

description: Files with information on network nodes identity.
DOI: 10.5061/dryad.63fp5/3
title: Summary results

description: Table with specialization indices, abundance and phenology data for 21 selected species from the networks.
DOI: 10.5061/dryad.63fp5/4
title: R script for analyses

description: R code to perform all the analyses included in Tur et al. 2013.
DOI: 10.5061/dryad.82j1g/1
title: Fig. 2a
DOI: 10.5061/dryad.82j1g/2
title: Fig. 2b
DOI: 10.5061/dryad.9q510/1
title: Lega_et_al_2014_Aquilegia_thalictrifolia_SSR_Genotypes

description: This file contains the genotypes of 9 SSR loci for 295 A. thalictrifolia individuals from 11 sampling localities. Missing data are indicated by '?'.
DOI: 10.5061/dryad.bh23t/1
title: hq_SNPs_and_estimation_error_calculations

description: This file contains high quality SNPs selected for allele frequency estimation and comparison between individual genotypes and pool frequencies. We present here numbers of reads of reference and alternative variants and calculations of relative estimation errors.
DOI: 10.5061/dryad.bh23t/2
title: Bank_vole_reference_transcriptome_liver

description: The bank vole liver reference transcriptome
DOI: 10.5061/dryad.bh23t/3
title: Contigs_9het

description: Contigs probably representing pairs of paralogs
DOI: 10.5061/dryad.ck44d/1
title: genotype data, three species of Rhododendron

description: "genotype_data" contains genotypes of three species of Rhododendrons. This data was used in the paper entitled "Patterns of geographic distribution have a considerable influence on population genetic structure in one common and two rare species of Rhododendron (Ericaceae)" which is published from Tree Genetics and Genomes. Population number is corresponding to Figure 1 and Table 1 in the article.
DOI: 10.5061/dryad.d03qr/1
title: Supplemental Data 1

description: Animation based on segmented or thresholded features from a full-body CT-scan of Lyuba, a woolly mammoth neonate from the Yamal Peninsula, Siberia
DOI: 10.5061/dryad.dc394/1
title: Teste FunctionalEcology RawData FE-2013-00901_R1

description: Raw data from FE-2013-00901.R1 includes: plant growth, colonisation by mycorrhizal fungi, root intermingling in pots, and foliar nutrient levels.
DOI: 10.5061/dryad.gd031k26/12
title: Supplemental Dataset 13
DOI: 10.5061/dryad.gd031k26/13
title: Supplemental Dataset 14
DOI: 10.5061/dryad.gd031k26/14
title: Supplemental Dataset 15
DOI: 10.5061/dryad.gd031k26/15
title: Supplemental Dataset 16
DOI: 10.5061/dryad.gd031k26/16
title: Supplemental Dataset 17
DOI: 10.5061/dryad.gd031k26/17
title: Supplemental Dataset 18
DOI: 10.5061/dryad.gd031k26/18
title: Supplemental Dataset 19
DOI: 10.5061/dryad.gf1fp/1
title: Simulation data and code

description: Please see README.txt for full description of files.
DOI: 10.5061/dryad.j2718/1
title: Bombyx huttoni assembly

description: Final Bombyx huttoni assembly. Fasta format.
DOI: 10.5061/dryad.j2718/2
title: Unfiltered B. mori alignments

description: Compressed tarball containing alignments between each B. mori gene (1st sequence) and the B. huttoni sequence (2nd sequence), the B. mandarina major allele (3rd sequence), and the B. mandarina minor allele (4th sequence). These alignments include all B. mandarina polymorphic sites detected at Q30 or above. Note that these are consensus chromosomes that do not capture phase information among B. mandarina alleles; rather, they simply represent the major and minor allele at each polymorphic site.
DOI: 10.5061/dryad.kq6kh/1
title: Table1
DOI: 10.5061/dryad.mk8p7/1
title: DellAmpio_et_al_2013: Supplementary Data

description: Supplementary File Archives of "Decisive Datasets in Phylogenomics: Lessons from Studies on the Phylogenetic Relationships of Primarily Wingless Insects"
DOI: 10.5061/dryad.mt0j5/1
title: nettows_info
DOI: 10.5061/dryad.mt6m4/1
title: Data used in meta-analysis of cost of parental effort on adult survival in birds.

description: This file contains all species and studies used in our meta-analysis, along with sample sizes, effect sizes (converted to Odds Ratio), and references to the original studies.
DOI: 10.5061/dryad.n0310/1
title: Pterosaur wingspans data - DRYAD
DOI: 10.5061/dryad.p2r8r/1
title: Priol et al. 2014. Ecology and Evolution

description: R script and data for analyses
DOI: 10.5061/dryad.pd76f/1
title: Misregulation of spermatogenesis genes in Drosophila hybrids

description: Sperm motility, fecundity and gene expression
DOI: 10.5061/dryad.rb5hr/1
title: Chernobyl2010_Dryad