cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.20285960.v1
title: Testing the efficacy of 3D-printed geologic models as tools for fostering spatial visualization abilities

description: Geoscience educators seek new technologies and teaching materials that will successfully foster their students’ spatial visualization skills. As 3D-printing technology becomes more readily accessible, there are endless opportunities to create new instructional products that can help improve students’ spatial rotation, spatial manipulation, and visual penetrative ability early in their geoscience coursework. We developed a set of eight 3D-printed geologic block models that can easily be incorporated into any 3-hr long geologic structures module of a physical geology laboratory course. Our main objective was to investigate their efficacy in fostering all three spatial visualization abilities. Our test results, based on 583 undergraduate participants at California State University, Fullerton, indicate that access to the 3D-printed geologic block models had insignificant effects on the development of spatial manipulation or visual penetrative abilities and a statistically significant negative impact on students’ spatial rotation skill development. In-class observations suggest that pattern-matching instead of actively practicing spatial rotation may have hindered the development of this skill, however, observations also suggest that the blocks generated discourse and improved explanations of geologic structures between students. We recommend that future adopters of 3D-printed educational products redesign their laboratory exercises that require active engagement and sketching using the models.
DOI: 10.3535/lke-azf-91z
title: Bryozoa

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/v04-htt-ztg
title: Bryozoa

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/4re-885-gat
title: Bryozoa

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/lqa-ydf-q38
title: Bioclaustration structures

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.6084/m9.figshare.13797851.v1
title: GWAS for somatic cell counts in sheep

description: phenotypes.txt : deregressed breeding values for somatic cell scorevdb.map and vdb.ped: genotyping with 50K Ovine Beadchip
DOI: 10.3535/deg-5jw-5fh
title: Bioerosional trace fossils

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/n89-rje-5lw
title: Climacoconus

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.17632/m7zgksh4vd
title: DIFFERENTIAL PRIVACY TECHNIQUES IN MACHINE LEARNING FOR ENHANCED PRIVACY PRESERVATION

description: The increasing reliance on machine learning models has prompted growing concerns regarding the privacy of sensitive information used in the training process. As a result, using differential privacy techniques has become a viable paradigm for attaining strong privacy preservation without sacrificing the models' usefulness. This study investigates and summarises important approaches in the field of machine learning differential privacy. Adding controlled noise at various points in the machine learning pipeline is the first class of approaches. To avoid unintentionally revealing private information, Laplace and Gaussian noise are deliberately added to training data, predictions, and model parameters. By employing strategies like randomised response mechanisms, data perturbation can enhance privacy for each individual without compromising the model's quality. Collaborative model training is made easier by privacy-preserving aggregation techniques like Secure Multi-Party Computation (SMPC), which protects raw data. By adding noise to gradients during training, Differential Privacy Stochastic Gradient Descent (DP-SGD) provides privacy guarantees during the optimization stage. When differential privacy is combined with federated learning, it allows for decentralized model training across devices while maintaining the security and localization of sensitive data. By allowing computations on encrypted data or safely aggregating model updates, advanced cryptographic approaches like homomorphic encryption and secure aggregation protocols give another degree of privacy. When taken as a whole, these methods add to a thorough framework for machine learning differential privacy that strikes a balance between the need to protect individual privacy and the drive to create accurate models
DOI: 10.3535/2c9-245-e8j
title: Sanctum isp.

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/cha-ftp-cqc
title: Sanctum isp.

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.6084/m9.figshare.28524641.v1
title: Ecological, economic and legal determinants of electricity production in the context of co-firing biomass with coal - an example of Poland

description: The article aims to indicate the potential of biomass as one of the elements of increasing the share of renewable energy sources while limiting the use of coal, which currently dominates the Polish energy sector. The use of biomass co-firing not only reduces coal consumption during electricity production but also reduces emissions, thus contributing to reducing energy production costs. The article characterizes the ecological and economic importance of developing the method of co-firing biomass with coal for electricity production and refers to previously published works on similar topics, which addressed other external conditions such as prices of energy raw materials and significantly lower CO<sub>2</sub> emission fees. The research conducted in the article confirms the impact of using biomass during co-combustion with coal on reducing the environmental impact in one of the largest Polish coal-fired power plants, i.e. the Dolna Odra Power Plant.
DOI: 10.3535/b43-2qx-kgc
title: Bryozoa

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/l7a-anm-zs9
title: †Dittopora colliculata (Eichwald, 1856)

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/126-rkl-ac1
title: Bryozoa

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/9pr-77s-amz
title: Platycladus Spach

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/fhq-xz2-hqw
title: Sanctum isp.

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/2n7-t2b-ga2
title: Platycladus Spach

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/ycl-6bh-gwa
title: Platycladus Spach

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.6084/m9.figshare.27683157.v1
title: R2 and F statistics for the 45 factors we studied (1 exposure and 44 intermediaries).

description: We calculated the F-statistics for 45 factors, including one exposure (ukb-b-1489) and 44 potential mediators ( ebi-a-GCST90013976-ebi-a-GCST90014019). Due to missing EAF values for the 44 potential mediators, we were unable to compute R²; therefore, we only calculated the F-statistic, which is the square of β divided by the square of the standard error (SE). For cheese intake (ukb-b-1489), we calculated both R² and the F-statistic, and also computed β²/SE² to derive the F-statistic based on this calculation.
DOI: 10.15468/dl.p4pb2f
title: Occurrence Download

description: A dataset containing 99 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ceropegia rhynchantha Schltr.",
 "Continent is Africa"
 ]
}

 The dataset includes 99 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009817-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3535/3z1-y5j-yjv
title: †Dittopora colliculata (Eichwald, 1856)

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/yv7-ygm-f3l
title: Planolites montanus

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.6084/m9.figshare.20022324.v1
title: Vocal warm-up and cool-down: systematic review

description: ABSTRACT For this literature review, we researched national and international scientific publications on vocal warm-up and cool-down of the speaking voice, through databases such as Lilacs, MedLine and Scielo, in order to identify and describe the methodological parameters and the effects of the vocal warm-up and cool-down proposals that are described in national and international literature. We performed the location and selection of studies through a survey of texts published on the theme from 1999 to 2013. We included original research articles; published in Portuguese or English; with emphasis on vocal warm-up and cool-down; associated or not. The recommended time of execution for warm-up ranged from 15 to 30 minutes or three sets of 15 repetitions, and the cool-down from 5 to 15min. The most used exercises for warm-up were voiced fricative sounds and vibrant of tongue or lips, in ascending scales, and for the vocal cool-down the nasal sounds, fricative sounds and vibrant of tongue or lips, in descending scales, were the most used exercises. The exercises showed positive vocal changes, observed by vocal acoustic and auditory-perceptual vocal and, self-evaluation and aerodynamic related to phonation. There was unanimity on the importance of completing the vocal warm-up and cool-down for voice professionals and on the positive results after carrying out the procedures. There was no agreement on the time of execution and on the exercises that were used.
DOI: 10.6084/m9.figshare.c.3831283_d19.v1
title: Additional file 8: of Hybrid assembly with long and short reads improves discovery of gene family expansions

description: Medicago repeat statistics. (XLSX 48Â kb)
DOI: 10.6084/m9.figshare.c.3930469_d3.v1
title: Additional file 3: Figure S2. of Molecular evolution of HIV-1 integrase during the 20Â years prior to the first approval of integrase inhibitors

description: Relation between significant coupling and frequency of single/pairwise substitutions. a) Relation between the relative frequencies of substitution pairs within the MSA and the strength of their coupling values (only significant couplings are considered). b) Relation between the relative frequencies of single substitutions within the MSA and their absolute frequency in significant couplings. (ZIP 133Â kb)
DOI: 10.17632/ky2bdpskpz
title: Supporting information for the article “Preliminary characterization of the spectral properties of marennine-like pigments from new Haslea strains”

description: Marennine is a bluish pigment excreted in the seawater by the microalga Haslea Ostrearia. It has interested researchers of different backgrounds such as marine biologists, phytochemists and biochemists because it fixes on the oysters gills and make them green, a phenomenon observed since centuries in the Atlantic French coast near Marenne-Oléron, where the tradition of cultivating oysters is old. Its biological activities have been and are currently studied and many applications are interesting because of its antioxidant, antiangiogenetic and antibacterial activities but also for being a blue natural pigment. During recent sampling campaigns all over the word, new blue diatoms have been discovered and ongoing investigation of genome and frustules appearance are carried out to classify them. A preliminary characterization of the marennine-like pigments that they produce has been carried out, and selected data concerning UV-visible spectrometry, Infrared spectrometry, cyclic voltammetry, elemental composition by Energy-dispersive X-ray spectroscopy (EDX), and proton nuclear magnetic resonance are presented and discussed in the research paper related to this supporting information. Therefore, the data presented in this data paper complete the full paper.
DOI: 10.3535/1yf-p1c-f25
title: Platycladus Spach

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/8ye-fyx-3fy
title: Porifera Grant, 1836

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.6084/m9.figshare.24796171.v2
title: Conditional and Unconditional Treatment Effects in Randomized Clinical Trials: Estimands, Estimation, and Interpretation

description: ICH E9(R1) specifies the importance of precisely defining the treatment effect for clinical trials—to inform patient choices and facilitate evidence-based decision-making. FDA’s guidance on covariate adjustment encourages the judicious use of baseline covariates to enhance efficiency. Careful consideration is required when adjusting for covariates in nonlinear models such as logistic regression and Cox regression. For these nonlinear models, including baseline covariates can change the targeted treatment effect (estimand). It is also crucial that the proposed statistical analyses align with the estimand of interest. Covariate-adjusted estimators used for unconditional treatment effect are typically robust to misspecification of the used regression models. Despite extensive literature and recommendations by the FDA on the statistical theory and properties of these methods, the real-life application of such methodologies is still limited. Moreover, a few open questions require further discussion, especially for time-to-event outcomes. In this article, we present causal estimands definition of conditional and unconditional treatment effects in randomized clinical trials. We also evaluate different estimation methods for estimating conditional and unconditional treatment effects for the binary and time-to-event endpoints. We also discuss practical considerations in choosing the conditional versus unconditional effect, implementing the estimation methods, and interpreting results.
DOI: 10.3535/8z0-79g-9nd
title: Trypanites sozialis

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/qed-0kb-38k
title: Bioerosional trace fossils

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.48420/22550149.v2
title: Code and Data from Lewis et al 2023 Animal Behavior

description: This data set contains the temporal data from Java sparrow songs studied in Lewis et al 2023 <em>Animal Behavior</em>, and all of the code used to analyse that data and make figures for the paper. <br> (The manuscript is currently pending publication. This record will be updated as appropriate when the paper is published.)
DOI: 10.6084/m9.figshare.14332364.v1
title: FR697 supertranscriptome files

description: The original de novo transcriptome assembly fasta file generated by the Necklace pipeline with the unmodified headers along with 128 protein coding transcripts, their GO annotation and the merged transcriptome data.
DOI: 10.3535/777-zgw-60t
title: Kukersite oil shale

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/9gl-vqf-wjx
title: Gastropoda Cuvier, 1795

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/6fj-f3v-kx4
title: Heliolitina

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/cxm-dmz-1wh
title: Trypanites isp.

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.17632/db9pd7ns6d
title: Code – A new computational approach to Henderson’s method for computing the inverse of a numerator relationship matrix

description: A new algorithm for computing the inverse of the numerator relationship matrix (A^-1) is presented in several (R, Julia, Python, and Awk) programming languages, and the code is shared.
The algorithm is based on the method of Henderson (1976) (doi: 10.2307/2529339) on each animal's contribution to the A^-1 matrix.

In the Jupyter notebook Example.ipynb (also Example.html), the procedure is presented using example data (example_ped.txt and example_inb.txt) and the 4 programming languages.

The algorithm was benchmarked on a pedigree of 20000 animals (PED2) and a pedigree of 180000 animals (PED4) with the corresponding files (ped.csv and PED4.csv) retrieved from doi:10.6084/m9.figshare.13497939.v1.
In BENCHMARKING.md (also BENCHMARKING.html), the benchmarking procedure for different programming languages, and the description of the files in this repository are given.
DOI: 10.3535/83r-14m-m29
title: Bryozoa

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/d4b-rp9-1wl
title: †Dictyoconus Blanckenhorn, 1900

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/4hp-vb8-9qd
title: Climacoconus

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/xvy-p5b-j2f
title: Bryozoa

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/kza-j3n-617
title: sedimentary rocks

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/p7t-fjs-6be
title: Anoigmaichnus? sp.

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.17632/rrmkf32v5p
title: R code used to analyze the data for the paper "Evaluating sustainable practices for certification schemes: herding practices in Mongolia"

description: This is the R code used to analyze the data for the paper "Evaluating sustainable practices for certification schemes: herding practices in Mongolia", which was submitted to Nature Sustainability. 
Specifically, app.r is the R code of the R Shiny app, which allows users to apply our models developed in this study to produce a sustainability score and certification advice for their real herding scenarios.
BP_analysis_models_used_in_app.r is the R code to build the models used in the above R Shiny app.
BP_analysis_overall_final.r is the R code to do the overall assessment of different models using accuracy indices.
BP_analysis_pred_VS_obs_final.r is the R code to compare predicted scores and the observed scores using five-fold cross-validation.
BP_analysis_plotting.r is the R code to plot the results from the above program BP_analysis_overall_final.r.
See the paper for more details.
DOI: 10.3535/wb9-e4r-al2
title: Brachiopoda Duméril, 1805

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/0fc-8jf-zry
title: Brachiopoda Duméril, 1805

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/wsd-qkx-5z6
title: †Mesotrypa Ulrich, 1893

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.25405/data.ncl.14357345.v1
title: Network and Substation Loading Data

description: 1) Network demand data.2) Network branch data.3) Substation loading data.<br>
DOI: 10.3535/vzn-251-6aj
title: Trypanites sozialis

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/yav-c19-ntq
title: Brachiopoda Duméril, 1805

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.6084/m9.figshare.20222181.v1
title: Polyp-canal reconstruction reveals evolution towards complexity in corals (Dataset Part 118)

description: There are 17 files in this dataset. This is the 118th part of this dataset. The <em>A. millepora</em>, <em>A. muricata</em>,<em> C. vaughani</em>,<em> M. capricornis</em>, <em>M. foliosa</em>,<em> P. damicornis</em>, <em>P. meandrina</em>,<em> P. verrucosa</em>, and<em> S. pistillata</em> samples were collected from the Xisha Islands (2018); the <em>A. digitifera</em>, <em>F. speciosa </em>(2008), and<em> M. turgescens</em> (2017) samples were collected from the Nansha Islands; the <em>P. lutea</em> samples were collected from the Weizhou Islands (2017); the <em>G. fascicularis</em>, and<em> M. stellata </em>samples were collected from the Gaven Reef (2017); the <em>A. myriophthalma</em> samples were collected from the Reed Tablemount (2017); the <em>P. sinensis</em> samples were collected from the Subi Reef (2017). All samples, which occurred in large arborescent colonies forming thickets, were found in tropical shallow reefs of the marine neritic zone, from depths of about 5 to 10 m. The daily mean temperature was between 23.2 and 29.2°C. The coral samples were kept whole and housed in our laboratory coral tank, where all conditions were simulated to reflect those of their habitat in the South China Sea. These samples were kept in the tank for about one to three months before HRCT analysis.
DOI: 10.3535/0fl-apd-0sc
title: Arthropoda

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.6084/m9.figshare.3554130.v1
title: Appendix C. Individual species variances.

description: Individual species variances.
DOI: 10.15468/dl.khfcwj
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Acalypha pendula C.Wright ex Griseb."
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009818-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3535/25e-8db-bxz
title: Trypanites sozialis

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/hve-2aq-cn3
title: Ostracoda Latreille, 1802

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.6084/m9.figshare.12622826.v2
title: SEAM IMS data

description: image and ASCII data used by SEAM paper
DOI: 10.6084/m9.figshare.19044446.v1
title: Processed DepMap CCLE mutation data

description: CCLE 21Q3 processed DepMap mutation data
DOI: 10.3535/aj3-vle-7d1
title: limestone

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/lnz-71g-hca
title: Ostracoda Latreille, 1802

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/bxl-sp9-lzg
title: Ostracoda Latreille, 1802

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/x8s-akr-mbg
title: Ostracoda Latreille, 1802

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.6084/m9.figshare.24076485.v1
title: Figure 3

description: Prism files of the primary data
DOI: 10.3535/e41-jfq-plr
title: Ostracoda Latreille, 1802

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/wr6-7lv-st3
title: Matourea Aubl.

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.