cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.24105474.v2
title: VOC2012数据集、BDD100数据集

description: <pre>@misc{pascal-voc-2012,<br> author = "Everingham, M. and Van~Gool, L. and Williams, C. K. I. and Winn, J. and Zisserman, A.",<br> title = "The {PASCAL} {V}isual {O}bject {C}lasses {C}hallenge 2012 {(VOC2012)} {R}esults",<br> howpublished = "http://www.pascal-network.org/challenges/VOC/voc2012/workshop/index.html"}<br><br>BDD100K<br>Copyright ©2018. The Regents of the University of California (Regents). All Rights Reserved.<br><br>THIS SOFTWARE AND/OR DATA WAS DEPOSITED IN THE BAIR OPEN RESEARCH COMMONS REPOSITORY ON 1/1/2021<br><br>Permission to use, copy, modify, and distribute this software and its documentation for educational, research, and not-for-profit purposes, without fee and without a signed licensing agreement; and permission to use, copy, modify and distribute this software for commercial purposes (such rights not subject to transfer) to BDD and BAIR Commons members and their affiliates, is hereby granted, provided that the above copyright notice, this paragraph and the following two paragraphs appear in all copies, modifications, and distributions. Contact The Office of Technology Licensing, UC Berkeley, 2150 Shattuck Avenue, Suite 510, Berkeley, CA 94720-1620, (510) 643-7201, otl@berkeley.edu, http://ipira.berkeley.edu/industry-info for commercial licensing opportunities.<br><br>IN NO EVENT SHALL REGENTS BE LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF REGENTS HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.<br><br>REGENTS SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE AND ACCOMPANYING DOCUMENTATION, IF ANY, PROVIDED HEREUNDER IS PROVIDED "AS IS". REGENTS HAS NO OBLIGATION TO PROVIDE MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.<br><br></pre>
DOI: 10.6084/m9.figshare.25920016.v3
title: Perovskite_data

description: In this work, we demonstrated the role of shallow energy level defect states on the emission of CH<sub>3</sub>NH<sub>3</sub>PbBr<sub>3</sub> perovskite polycrystals under laser excitation. The perovskite polycrystals were synthesized by a simple, one-step, low-cost solution self-assembled method. By adjusting the sample preparation temperature, we could manipulate the shallow energy level defect states that can be recognized through low-temperature photoluminescence measurement. Depending on the shallow energy level defect states, the sample’s emission experienced an evolution from amplified spontaneous emission to random lasing emission. Notably, the most efficient lasing threshold of 4 μJ/mm<sup>2</sup> was achieved when the sample was prepared at 333 K. The surface morphologies and other optical properties of the perovskite polycrystals were also investigated by optical microscopy, X-ray diffractometer.<br>
DOI: 10.6084/m9.figshare.28245260.v1
title: Oryza australiensis haplotype assembly and annotation data

description: Haplotype assembly and annotation data for <i>Oryza australiensis.</i>Transposable element repeats were identified and masked using RepeatModeler2 v2.0.5 and RepeatMasker v4.1.5 using the soft masking option. Paired-end RNAseq files were adaptor-trimmed using TrimGalore! v0.6.10 and aligned to genomes using HISAT2. Gene prediction was performed with Braker3 v3.0.3.Functional annotation of the O. australiensis coding sequences (CDS) was performed in OmicsBox 3.1.11. Sequences were BLAST searched against a non-redundant protein sequence database using BLASTX with viridiplantae taxonomy and an e-value threshold of 1.0E-10. Sequences were run through InterProScan and Gene Ontology (GO) terms were retrieved from BLAST hits using Gene Ontology mapping with Blast2GO annotation. Blast2GO annotations were then combined with GO terms produced from InterProScan.
DOI: 10.6084/m9.figshare.28397210.v1
title: ZM4_haplotype genome

description: The information of the ZM4 haploid genome of alfalfa. The raw data was uploaded to NGDC (CRA005190) and NCBI (PRJNA685277).Related paper: Evolutionary genomics of climatic adaptation and resilience to climate change in alfalfa
DOI: 10.6084/m9.figshare.9849845.v2
title: Reproducible Analysis Workflow for Harrison et al (2019) Designing Probiotic Therapies with Broad-Spectrum Activity Against a Wildlife Pathogen

description: Reproducible analysis workflow for Harrison et al (2019) Designing Probiotic Therapies with Broad-Spectrum Activity Against a Wildlife Pathogen
DOI: 10.6084/m9.figshare.13274744.v1
title: State of Open Data survey 2020

description: Raw data and questionnaire from the Springer Nature - Digital Science collaboration of an annual survey of research authors on their attitudes and behaviour around research data.
DOI: 10.6084/m9.figshare.5044633.v3
title: Introduction to Statistical Philosophy

description: This video lecture and slide set presents a pragmatic statistical philosophy, including both frequentist and Bayesian ideas as well as providing careful definitions of inference, hypothesis testing, and P values.
DOI: 10.6084/m9.figshare.29170289.v1
title: EEG Emotion Recognition Dataset_GU

description: This dataset comprises EEG recordings collected from 10 healthy participants (9 male, 1 female) aged 18–23 years from the Department of Information Technology, Gauhati University, India, with the aim of analyzing brain activity associated with visually induced emotions—specifically happiness, sadness, and fear. Visual stimuli were drawn from the Open Images Dataset v7 and Extensions, with each emotion block consisting of three images (5 seconds each), separated by relaxation intervals. EEG data were recorded using a 32-channel Emotiv Epoc Flex gel-based system at a sampling rate of 128 Hz, following the international 10–20 electrode placement standard. Reference electrodes were placed at P3 (CMS) and P4 (DRL), as per Emotiv's default setup. Participants first viewed a “Relax” screen (10 seconds) before emotional stimuli were presented in two phases using different image sets to increase variability. Verbal feedback was collected after each phase to confirm the participants' emotional experiences; only data from those whose self-reported emotions matched the intended labels were retained. Participants were asked to minimize movement, and multiple relaxation periods were incorporated to maintain a calm baseline. All participants provided written informed consent.The raw EEG signals were preprocessed through a structured pipeline to ensure artifact-free data suitable for analysis. First, a bandpass filter (0.5–45 Hz) was applied using zero-phase forward-backward FIR filtering to preserve the integrity of frequency components relevant to emotional states. Next, Savitzky–Golay smoothing (frame length 127, order 5) was used to remove slow-varying trends by subtracting the smoothed reference from the EEG signals. Finally, Independent Component Analysis (ICA) via EEGLAB’s <code>runica</code> function was employed to identify and remove ocular artifacts, retaining only clean components for analysis.
DOI: 10.17632/2k3txbgn5n
title: CancerNextExpanded+RNAinsight multi-gene panel from Ambry Genetics Laboratories

description: This supplemental material contains the 77 genes tested in the Ambry Genetics multi-gene panel.
DOI: 10.6084/m9.figshare.12599783.v1
title: JVASP-15330 to JVASP-16585

description: JARVIS-DFT
DOI: 10.6084/m9.figshare.23736891.v2
title: A dataset for soil organic carbon in agricultural systems for the Southeast Asia region

description: Authors:<br>Federico Gomez<sup>1</sup>*, Ana Carcedo<sup>1</sup>, Chan Makara Mean<sup>2</sup>, Manuel Reyes<sup>3</sup>, Lyda Hok<sup>4</sup>, Florent Tivet<sup>5</sup>, Vang Seng<sup>6</sup>, P. V. Vara Prasad<sup>1</sup>, Shopie Manson<sup>7</sup>, K. A. I. Nekaris<sup>7</sup>, Eva Lehndorff<sup>8</sup>, Thilde Bech Bruun<sup>9</sup>, Catherine M. Hepp<sup>10</sup>, Ryusuke Hatano<sup>11</sup>, Auldry Chaddy<sup>12</sup>, Pham Thi Thu Huong<sup>13</sup>, Selva Dhandapani<sup>14</sup>, Katharina Maria Keiblinger<sup>15</sup>, Rizki Maftukhah<sup>16</sup>, Zar Ni Zaw<sup>17</sup>, Sota Tanaka<sup>18</sup>, and Ignacio Ciampitti<sup>1</sup>*<br><sup>1</sup>. Department of Agronomy, Kansas State University, Manhattan, Kansas, US.<br><sup>2</sup>. Faculty of Agricultural Biosystems Engineering, Royal University of Agriculture, Phnom Penh, Cambodia.<sup>3</sup>. Sustainable Intensification Innovation Lab, and Department of Agronomy, Kansas State University, Manhattan, Kansas, US.<br><sup>4</sup>. Center of Excellence on Sustainable Agricultural Intensification and Nutrition, Royal University of Agriculture, Phnom Penh, Cambodia.<sup>5</sup>. CIRAD, UPR AIDA, Univ Montpellier, Montpellier, France. Agroecology for South-East Asia.<br><sup>6</sup>. Department of Agricultural Land Resources Management, Phnom Penh, Cambodia.<br><sup>7</sup>. School of Humanities and Social Sciences, Oxford Brookes University, Oxford, United Kingdom.<br><sup>8</sup>. Soil Ecology, Universität Bayreuth, Bayreuth, Germany.<br><sup>9</sup>. Department of Geosciences and Natural Resource Management, Section for Geography, University of Copenhagen, Copenhagen, Denmark.<br><sup>10</sup>. Lethbridge, AB, Canada.<br><sup>11</sup>. Research Faculty of Agriculture, Hokkaido University, Hokkaido, Japan.<br><sup>12</sup>. Sarawak Tropical Peat Research Institute, Sarawak, Malaysia.<br><sup>13</sup>. Horticulture Department, Field Crops Research Institute, Hai Duong, Vietnam.<br><sup>14</sup>. Department of Geography and Environmental Science, School of Archaeology, Geography and Environmental Sciences (SAGES), University of Reading, Reading, United Kingdom.<br><sup>15</sup>. Department of Forest and Soil Sciences, Institute of Soil Research, University of Natural Resources and Life Sciences, Vienna, Austria.<br><sup>16</sup>. Department of Agricultural and Biosystem Engineering, Faculty of Agricultural Technology, Universitas Gadjah Mada, Indonesia.<br><sup>17</sup>. Faculty of Natural Resources, Prince of Songkla University, Thailand.<br><sup>18</sup>. Faculty of Agriculture and Marine Sciences, Kochi University, Kochi, Japan.<br><br>For more information about the dataset or the scripts, please contact the corresponding authors at: fmgomez@ksu.edu, ciampitti@ksu.edu.
DOI: 10.6084/m9.figshare.25838170.v1
title: raw LC-MS/MS data of GPR156

description: <b></b>The samples of GPR156 were prepared in three independent replicates. Additionally, two well-established class A GPCRs (including GPR34 and GPR174), each with two replicates, were employed as control groups where no two-chain phospholipids were present.
DOI: 10.6084/m9.figshare.28578131.v1
title: Hinderer_CMR_data_Ranaluteiventris.csv

description: These data were collected as part of a study of the relationship between body condition, as measured from length and mass of an animal, body composition, as measured by the mass of different tissues within an animal, and growth in amphibians. There were two main questions of this study: 1) which of some common body condition indices were most effective at describing the amount of fat or lean mass of a several amphibians and 2) whether body condition was related to the potential for growth in one amphibian species.The QMR data is output from quantitative magnetic resonance scans of three species of amphibians (<i>Rana luteiventris, Pseudacris sierra, *and *Ambystoma macrodactylum</i>) to determine body composition, as represented by amounts of fat and lean mass in an individual at the time of scanning. These outputs were then compared to traditional condition indices developed from length and mass measurements. The CMR data is capture-mark-recapture information from a population of individually marked <i>Rana luteiventris</i>, which covered multiple years and was used to study the effects of body condition on individual growth.Description: VariablesSite: Site of animal capture. LubrechtJonesPond = Jones Pond, Lubrecht Forest, MT 46.90°N; -113.44°W.Species: Species of the individual. RALU = Rana luteiventrisCaptureDate: Date of captureYear: Year of captureMonth: Month (1–12) of capturePitTagCode: Passive integrated transponder unique identifier of the animal in the mark-recapture study.OSex: Original sex, as recorded in the field. In rare cases this sex was edited based on sex calls by more experienced experts or previous and/or subsequent sex calls.Sex: Sex of the animal. M = male, F = female, U = unknown sex, typically juvenile &lt;45mm snout-vent length.SVLmm: Snout-vent length of the individual at time of capture (mm)MassG: Mass (g) at time of captureNotes: User input notesComments: User input comments
DOI: 10.6084/m9.figshare.9937859.v1
title: Supplementary Material for: Trends in the Incidence and Mortality of Stroke in Matão, Brazil: The Matão Preventing Stroke (MAPS) Study

description: <b><i>Background:</i></b> Stroke population-based studies in the same setting comparing time trends of rates are a gold standard method to determine the primary prevention status of stroke. Twelve years ago, we measured the stroke incidence and mortality in Matão city, Southeast of Brazil. <b><i>Objective:</i></b> This second Matão stroke registry study aimed to determine the time trends in the incidence, mortality, case fatality, and functional status of patients with stroke. <b><i>Methods:</i></b> This was a prospective, population-based study known as the Matão Preventing Stroke (MAPS). We determined all incident stroke events that occurred between August 1, 2015, and July 31, 2016. Between the periods of November 1, 2003, to October 31, 2004, and August 1, 2015, to July 31, 2016, the rates were age adjusted to the Brazilian and world population. Functional status was measured by Barthel scale 1 year after the index event. <b><i>Results:</i></b> We registered 81 cases of incident stroke. Demographic and cardiovascular risk factors were similar in both periods. The mean age increased by 9%, from 65.2 (95% CI 62.6–67.8) to 71.0 (95% CI 68.1–73.8) years. Between 2003–2004 and 2015–2016, the age-adjusted incidence decreased by 39% (incidence rate ratio [IRR] 0.61; 95% CI 0.46–0.79) and mortality by 50% (IRR 0.50; 95% CI 0.31–0.94). The 1-year case fatality was 26%; approximately 56% of the patients were functionally independent, while 7% had a recurrent stroke. Compared with the results of our first registry study, these outcomes did not differ significantly. <b><i>Conclusion:</i></b> Our findings agree with those of previous studies, showing a decline in the incidence and mortality of stroke in Brazil. Improvements in local public health care might explain these declines.
DOI: 10.17605/osf.io/ncka8
title: Usando R

description: Repositório com materiais de apoio do livro "Usando R"
DOI: 10.15468/dl.sh5xh2
title: Occurrence Download

description: A dataset containing 3098 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Platycarya strobilacea Siebold & Zucc."
 ]
}

 The dataset includes 3098 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013209-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/6vbyfyhd7y
title: Influence of the sample preparation on the multi scale texture of sand clay simplified soils for geotechnical applications - MIP and X-ray Tomography raw data

description: 1-Raw results of porosimetry on S1, S2 and S3 samples. 2-Raw X-ray scans of S1, S2, S3 samples.
DOI: 10.17632/939g5nyjnm
title: Portevin-Le Chatelier (PLC)

description: PLC effect observed in a heterogeneous stress field
DOI: 10.6084/m9.figshare.23918667.v1
title: <b>Self-administration medication errors at home and its predictors among older adults</b>

description: Older adults with polypharmacy are more prone to medication errors. Medication errors can occur at any stage of the medication use cycle. Medication errors are a major concern for health systems because they reduce treatment effectiveness and increase costs. The present cross‑sectional descriptive-analytical study was conducted to identify the extent of medication self-administration errors (MSEs) and the contributing factors among illiterate and low-literate community-dwelling older adults with polypharmacy.
DOI: 10.6084/m9.figshare.24316417.v2
title: Wood decomposition and nutrient dynamics in burnt Mediterranean pine reforestations across an elevational gradient: a 15-year study.

description: The rate of wood decomposition after a forest fire was analyzed over a period of 15 years and six sampling periods (initial, and after 2, 4, 8, 10 and 15 years). 75 cm long pieces of logs were experimentally arranged along an elevation gradient (ca. 1400, 1700, 2000 and 2200 m a.s.l.) with contrasting climatic conditions. The concentration of C, N and P was also determined for four of the sampling periods (including the beginning and after 15 years) as well as the concentration of K, Ca, Mg, Na, Fe, Cu, Mn and Zn at the beginning and after 15 years. Nutrient analyses were carried out in 2006, 2008, 2010 and 2021. In 2006, the P content was determined by the molybdovanadate method and the rest of the nutrients (Ca, Mg, K, Na, Fe, Mn, Zn and Cu) by atomic absorption of the vegetal ash solution with a Perkin Elmer 5100 spectrometer (Waltham, MA, USA) (Marañón-Jiménez et al. 2013). In 2008 and 2010, the P content was determined by the molybdovanadate method with a Perkin Elmer 2400 spectrophotometer (Waltham, MA, USA) (Marañón-Jiménez and Castro 2013). In 2021, nutrient content (P, K, Na, Ca, Mg, Fe, Cu, Mn and Zn) was determined by inductively coupled plasma mass spectrometry (ICP-MS) with a Perkin Elmer Avio 500 spectrometer. For all sampling years, total C and N were determined with a CN Gas Analyzer by using an induction furnace and thermal conductivity (LECO TruSpec CN). Log volume was estimated by the conic-parabolic formula proposed by Fraver et al. (2007). Wood density was calculated by dividing wood dry weight by its volume. To check the accuracy of the 2021 data, nutrient analyses were repeated for 53 samples. The repeated samples showed consistency for all the nutrients except for Fe and Na, that gave random values without any correlation between the two trials of analysis. Therefore the values for these nutrients for 2021 were eliminated from the data set.
DOI: 10.6084/m9.figshare.24418144.v2
title: UAV DOM image; 2021-05-22

description: UAV DOM image; 2021-05-22
DOI: 10.17632/2423jdt345
title: DIC_noise_bias

description: The data set contains various rigid body translation tests at different noise levels, and the motion is known at sub-pixel accuracy. Illumination ranges from good to very weak, thus limiting the spatial gradient of gray tones.
DOI: 10.17632/7nwdgmsvwp
title: Chlorophyllins

description: Chlorophyllins are components of green food colorants and coloring foodstuff. However, in spite of its common consumption, the knowledge regarding these compounds is scarce, among other factors due to the complexity of identification. It is frequent to find groups of 2-4 chlorophyll derivatives, potentially present in green natural food colorants, with the same elemental composition, but different functional groups. This significantly increases the difficulty of correct identification, while the unintended misidentification is likely if the occurrence of structural isomers is not noted. We made use of data-dependent MS2 experiments on individual molecular ions to identify new chlorophyll derivatives, which structural arrangement was predictable on the basis of the chemical reactions taking place during the production of food green colorants; to provide qualifier ions by which structural isomers that differ at the sort of branched functional group(s), arising after the hydrolysis of the isocyclic ring, can be distinguished; and to increase our knowledge in chemical behavior of chlorophyll derivatives during MS experiments.
To the best of our knowledge, there is no current existing proposal to discern among structural isomers of chlorophyll derivatives present in marketed green food colorants and coloring foodstuff products. The data we compiled showed the identification of qualifier ions to distinguish among structural isomers of non-coppered chlorophylls. In addition, taking advantage of the capacity of the powerful post-processing software, the fragmentation patterns and structural configuration of each qualifier ions are also ascertained.
DOI: 10.17632/858bwy7rdj
title: Effect of Flatfoot on Rearfoot Eversion Moment During the Support Phase of Walking

description: Excessive eversion of the talus and calcaneus (i.e., the rearfoot) during the support phase of walking occurs as a result of excessive moments about the ankle caused by ground reaction forces (GRF) and may eventually lead to chronic lower limb injuries. In this study, I investigated whether individuals with flatfoot are susceptible to excessive rearfoot eversion during walking. Healthy adult male participants (n = 29) were divided, by normalized truncated navicular height, into 2 groups—individuals with flatfoot (n = 14, low values) and individuals with normal foot characteristics (n = 14, high values; the participant with the median value was excluded). Rearfoot eversion moments and the factors generating moments (ankle height, mediolateral GRF, mediolateral distance of COP, mediolateral distance of center of the ankle, vertical GRF) were calculated. These variables were compared between groups. Participants with flatfoot had significantly larger eversion moments than those in the control group after foot contact and during the loading phase; ankle joint centers in participants with flatfoot were located significantly medial to those of participants in the control group, and as a result, the mediolateral distance between the COP and the ankle (the eversion moment arm of vertical GRF) was significantly larger. Because individuals with flatfoot have ankle joint centers located medial to those with normal foot characteristics during the support phase of walking, and consequently, have an increased mediolateral distance between COP and the center of the ankle, individuals with flatfoot are susceptible to large rearfoot eversion moments.
DOI: 10.6084/m9.figshare.25374583.v1
title: Data in "Heterogeneous integration of spin-photon interfaces with a scalable CMOS platform"

description: <b>Manuscript: </b>Heterogeneous integration of spin-photon interfaces with a scalable CMOS platform<b>Authors:</b> <b>Linsen Li*</b>, Lorenzo De Santis, Isaac Harris, Kevin C. Chen, Yihuai Gao, Ian Christen, Matthew Trusheim, Hyeongrak Choi, Yixuan Song, Carlos Errando-Herranz, Jiahui Du, Yong Hu, Genevieve Clark, Mohamed I. Ibrahim, Gerald Gilbert, Ruonan Han, <b>Dirk Englund*</b>* linsenli@mit,edu; englund@mit.edu<b>Manuscript Data for</b><br>Figure 3: https://doi.org/10.6084/m9.figshare.25374550.v1 <br>Figure 4: https://doi.org/10.6084/m9.figshare.25374559.v1Figure 5: https://doi.org/10.6084/m9.figshare.25374571.v1
DOI: 10.6084/m9.figshare.25729248.v6
title: A global 150-m dataset of urban building heights around 2020 (GBH2020)

description: Here, we provide a 150-m global urban building heights dataset around 2020 by combining the spaceborne lidar (Global Ecosystem Dynamics Investigation, GEDI), multi-sourced data (Landsat-8, Sentinel-2, and Sentinel-1), and topographic data. The validation results revealed that the GEDI-estimated building height samples were effective in comparison to the reference data (Pearson's r = 0.81, RMSE = 3.58 m). The mapping product also demonstrated good performance, as indicated by its strong correlation with the reference data (Pearson's r = 0.71, RMSE = 4.73 m).The global dataset of our urban building heights is availably visible by following the website (https://nju-eco-lidar.projects.earthengine.app/view/gbh2020), powered by the Google Earth Engine (GEE).<br><br>