cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.12851436
title: Semiparametric Estimation of the Distribution of Episodically Consumed Foods Measured With Error

description: Dietary data collected from 24-hour dietary recalls are observed with significant measurement errors. In the nonparametric curve estimation literature, much of the effort has been devoted to designing methods that are consistent under contamination by noise, and which have been traditionally applied for analyzing those data. However, some foods such as alcohol or fruits are consumed only episodically, and may not be consumed during the day when the 24-hour recall is administered. These so-called excess zeros make existing nonparametric estimators break down, and new techniques need to be developed for such data. We develop two new consistent semiparametric estimators of the distribution of such episodically consumed food data, making parametric assumptions only on some less important parts of the model. We establish its theoretical properties and illustrate the good performance of our fully data-driven method in simulated and real data. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.12851436.v2
title: Semiparametric Estimation of the Distribution of Episodically Consumed Foods Measured With Error

description: Dietary data collected from 24-hour dietary recalls are observed with significant measurement errors. In the nonparametric curve estimation literature, much of the effort has been devoted to designing methods that are consistent under contamination by noise, and which have been traditionally applied for analyzing those data. However, some foods such as alcohol or fruits are consumed only episodically, and may not be consumed during the day when the 24-hour recall is administered. These so-called excess zeros make existing nonparametric estimators break down, and new techniques need to be developed for such data. We develop two new consistent semiparametric estimators of the distribution of such episodically consumed food data, making parametric assumptions only on some less important parts of the model. We establish its theoretical properties and illustrate the good performance of our fully data-driven method in simulated and real data. Supplementary materials for this article are available online.
DOI: 10.17632/s6yj9t2rcy.2
title: China_Dry_wet_abrupt_alternation_hotspots_projections

description: This is the climate region model simulations cover China pertaining to the following research paper: "Projected changes in the abrupt alternation between dry and wet extremes over China through an ensemble of regional climate model simulations" . It includes the CRU( http://www.cru.uea.ac.uk/ ), APHRODITE datasets (http://aphrodite.st.hirosaki-u.ac.jp/), and the five multi-model ensemble simulations derived from CORDEX EAS datasets (https://cordex.org/) and RECIS datasets for gridded monthly precipitation and PET.
DOI: 10.17632/rskdtzfspy.1
title: pictures of research area for Penguin subcolonies abandonment in the late 19th century on Inexpressible Island, Antarctica

description: The pictures of Inexpressible Island surface penguin carcasses
DOI: 10.17632/5sx5k2cvwn.1
title: One Earth 2020_Horizon Scan Survey Results

description: Results from an online survey that was part of a modified (two-phase) horizon scan to determine the emerging topics in ecological drought. See Crausbay et al. 2020. Unfamiliar territory: emerging themes for ecological drought research and management. One Earth. We conducted a two-phase horizon scan that was co-produced with drought scientists, managers, and decision-makers to reveal emerging topics in ecological drought research and management. The pool of experts was defined as the list of attendees (n=180) from a series of eight regional Ecological Drought Workshops. These workshops were convened by the U.S. Geological Survey’s National Climate Adaptation Science Center and were held in each of the eight Regional Climate Adaptation Science Centers (CASCs) between September 2015 and March 2017. The Regional CASC network covers the entire continental U.S., Hawai’i, Alaska, the U.S. Affiliated Pacific Islands, and the U.S. Caribbean. Although these workshops and experts were centered in the U.S., they do encompass a wide range of ecosystem types and drought regimes represented globally. Each of the regional workshops sought to identify the most pressing ecological drought issues for their particular region and assess the current knowledge and research pertinent to these issues. We evaluated the synthesis outputs from each workshop, including summary documents and outreach materials, to generate a list of unique and emerging ecological drought topics across all eight regions (n=19). As a second phase to this horizon scanning approach, in May 2017, we distributed an anonymous online survey to the same attendees of all eight regional Ecological Drought Workshops (n=180). The survey requested that attendees assign each topic a rank based on its degree of ‘emergence’ (e.g., topics yet to be extensively reviewed/synthesized, that relate to novel scientific questions, and are increasingly important in the 21st century, and/or provide insight on innovative management approaches). We presented topics to rank within different aspects of vulnerability; in this case, either exposure, sensitivity / adaptive capacity, or the ecological impact itself. Then we asked attendees to provide up to five additional topics they considered to be emerging in ecological drought research or management (resulting in n=17 added topics), and to list their top three to five highest-ranked topics among those provided or added. In total, 52 of the 180 attendees responded.
DOI: 10.17632/7dxf3223dd.1
title: ev smith

description: A 1282-day field study was conducted to provide data to assess the prediction of field soil water content time series θ(t). Volumetric water content was determined, typically once a week, by neutron thermalization at 20-, 40-, 60-, 80- and 100-cm depths. Soil samples were taken at 60 locations between 14- and 114-cm depths to determine soil properties, water retention, and saturated hydraulic conductivity. Soil properties include soil texture, bulk density, organic matter, and porosity.
DOI: 10.17632/y2h864xdhr.1
title: Data for: Joint optimization of container slot planning and truck scheduling for tandem quay cranes

description: Supplementary Raw Research Data
DOI: 10.17632/pvs2mmd3hs.1
title: Radioprotective efficacy of zinc oxide nanoparticles on γ-ray-induced nuclear DNA damage in Vicia faba L. as evaluated by DNA bioassays

description: This study aimed to assess the radioprotective efficacy of zinc oxide nanoparticles (nano-ZnO) against γ-radiation-induced DNA lesions in Vicia faba employing flow cytometry (FCM), comet assay, and RAPD-PCR bioassays. Each dose of γ-irradiated seeds was post-treated with three nano-ZnO concentrations. Exposure time pre- and post-ZnO treatments were 24 h. Dose-dependent nano-ZnO and γ-ray treatments showed specific interference with DNA. Three bioassays could successfully detect positive action of two nano-ZnO concentrations (500 and 2000 mg L-1) on DNA compared to control while high concentration nano-ZnO showed a negative interference with DNA. On the contrary, three doses of γ-ray induced major lesions in V. faba DNA. Data obtained illustrated that combination of 2000 mgL-1 nano-ZnO concentration with each γ-ray the dose had a good ability to protect DNA against their damaging when compared to the equivalent γ-ray doses prior to nano-ZnO treatment. This was evident through the significant amelioration of DNA parameters which manifested in increasing nuclear DNA content and genome size, reduction the DNA damage (tail length, Tailed DNA% and tail moment), and scoring new amplified DNA bands and increasing their number. This study concluded that nano-ZnO can be used as potent mutant and an efficient nano-radioprotector for the protection of crop plant DNA.
DOI: 10.6084/m9.figshare.12851388
title: Likelihood-Based Inference for Partially Observed Epidemics on Dynamic Networks

description: We propose a generative model and an inference scheme for epidemic processes on dynamic, adaptive contact networks. Network evolution is formulated as a link-Markovian process, which is then coupled to an individual-level stochastic susceptible-infectious-recovered model, to describe the interplay between the dynamics of the disease spread and the contact network underlying the epidemic. A Markov chain Monte Carlo framework is developed for likelihood-based inference from partial epidemic observations, with a novel data augmentation algorithm specifically designed to deal with missing individual recovery times under the dynamic network setting. Through a series of simulation experiments, we demonstrate the validity and flexibility of the model as well as the efficacy and efficiency of the data augmentation inference scheme. The model is also applied to a recent real-world dataset on influenza-like-illness transmission with high-resolution social contact tracking records. Supplementary materials for this article are available online.
DOI: 10.17632/3dpw885w4x.2
title: Greenhouse agricultural plastic waste mapping database

description: This dataset consists of the coordinates of plots and the area in square meters covered by agricultural greenhouses in the Republic of Cyprus, an EU member state. The collection of the data is included in sixteen tables separated per geographical area-cluster. The agricultural plastic waste (APW) detailed mapping was conducted with the use of up-to-date statistics from Cyprus Agricultural Payments Organization (CAPO), geographic information system (GIS) and satellite imagery.
DOI: 10.6084/m9.figshare.12851388.v2
title: Likelihood-Based Inference for Partially Observed Epidemics on Dynamic Networks

description: We propose a generative model and an inference scheme for epidemic processes on dynamic, adaptive contact networks. Network evolution is formulated as a link-Markovian process, which is then coupled to an individual-level stochastic susceptible-infectious-recovered model, to describe the interplay between the dynamics of the disease spread and the contact network underlying the epidemic. A Markov chain Monte Carlo framework is developed for likelihood-based inference from partial epidemic observations, with a novel data augmentation algorithm specifically designed to deal with missing individual recovery times under the dynamic network setting. Through a series of simulation experiments, we demonstrate the validity and flexibility of the model as well as the efficacy and efficiency of the data augmentation inference scheme. The model is also applied to a recent real-world dataset on influenza-like-illness transmission with high-resolution social contact tracking records. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.12782522
title: Fig4H.tif

description: Images from a timelapse point scanning confocal recording of an embryo expressing Tc-sqh-eGFP.
DOI: 10.6084/m9.figshare.12782522.v1
title: Fig4H.tif

description: Images from a timelapse point scanning confocal recording of an embryo expressing Tc-sqh-eGFP.
DOI: 10.17632/w5m8jf94m8.1
title: Suppl Tables

description: Supplementary Tables
DOI: 10.17632/x4mxnjmc76.1
title: Supplementary Tables and Methods

description: Supplemental Methods
DOI: 10.17632/djd7x3yh75.1
title: Records of recharge in transition metal concentrations of annually resolved stalagmites: An assessment from the arid Soutwest United States.

description: Geochemical (trace element concentrations) and principal component analysis data for Core 1 and Core 2.
DOI: 10.17632/ps94fp4ngn.1
title: Bacterial isolates cultured from various sampling sites in patients with chronic rhinosinusitis

description: This is a dataset that accompanies the paper "Challenging the gold standard: methods of sampling for microbial culture in patients with chronic rhinosinusitis". It contains the results of culture from samples obtained from 50 patients with chronic rhinosinusitis. The samples (swabs and tissue biopsies) were collected during endoscopic sinus surgery from the middle nasal meatus, maxillary sinus and frontal sinus. Additionally, swabs were taken from the nasal vestibule. The bacterial isolates were identified and tested for antibiotic susceptibility. The data shows that the results differ between sampling sites. The middle nasal meatus is not a representative sampling site for the sinuses as a whole. Multiple swabs were required to capture all culturable pathogens, while invasive biopsies usually do not provide additional information. Abbreviations: E - erythromycin DA - clindamycin NA - nalidixic acid IMP - imipenem MEM - meropenem ETP - ertapenem AK - amikacin CN - gentamicin NET - netilmicin TOB - tobramycin AMC - amoxicillin/clavulanic acid CXM - cefuroxime CTX - cefotaxime CAZ- ceftazidime FEP - cefepime CIP- ciprofloxacin TIC- ticarcillin TIM - ticarcillin/clavulanic acid PRL - piperacillin TZP - piperacillin/tazobactam SXT - trimethoprim sulfamethoxazole
DOI: 10.17632/ts9p355m3d.1
title: Solid state NMR spectra of FUS-LC-C, FUS-LC-N, and FUS-LC fibrils

description: 2D NCACX and C-C solid state NMR spectra of fibrils formed by the 214-residue low-complexity domain of the FUS protein (FUS-LC), by residues 111-214 (FUS-LC-C), and by residues 2-108 (FUS-LC-N). All samples were uniformly 15N and 13C labeled. Spectra are in Sparky format (*.ucsf files).
DOI: 10.17632/cff9fkwjp5.1
title: Growth Gains from Trade

description: This data set has been used to estimate the growth effect of trade. We bifurcate trade openness into openness with respect to intermediate inputs and openness with respect to final goods and find that it is the former which matters for sectoral productivity growth. Data sources used : KLEMS, World Input Output Database (WIOD) , UNCTAD TRAINS (accessed through WITS) , World Bank Database, UN COMTRADE (accessed through WITS), World Governance Indicators (WGI) project, World Bank, World development Indicators (WDI), World Bank, Penn World Table (PWT) version 9.1
DOI: 10.17632/zfnn844kvg.1
title: Senior Management’s Academic Experience and Corporate Green Innovation

description: The data of executives and other financial data are from CSMAR database. Corporate green innovation data is from Green List of International Patent Classification (Green List) published by the World Intellectual Property Organization (WIPO) in 2010. We took A-share listed companies on the Shanghai and Shenzhen stock exchanges from 2008 to 2017 as initial samples, by: (1) deleting firms in financial and insurance industry; (2) removing abnormal companies, such as “specially treated firms” and “particular transfer firms”; (3) deleting firms with asset-liability ratio greater than 1 and firms with missing values of other variables; (4) winsorising continuous variables at the 1st and 99th percentiles, in order to eliminate potential outlier effects. F
DOI: 10.1285/i9788883051616
title: Imparare a insegnare. Formazione e didattica per la scuola. Atti del Convegno GEO 2017
DOI: 10.17632/zdzg6vg8ty.2
title: Maternal characteristics and neonatal outcomes of emergency repeat caesarean deliveries due to early-term spontaneous labour onset

description: Raw data of the participants.
DOI: 10.17632/vsm9xwbcwh.1
title: Structural and Immunogenicity Analysis of Reconstructed Ancestral and Consensus P48/45 for cross-species Antimalaria Vaccine

description: The development of the antimalaria vaccine holds a promising future in malaria control. One of the antimalaria vaccine strategies known as the transmission-blocking vaccine is designed to inhibit the parasite transmission between human and mosquito by targeting parasite gametocyte. Previously, we found that P48/45 that include in the 6-Cysteine protein family shared by Plasmodium sp. We also detected vaccine properties that possess by all human-infecting Plasmodium and could be used as a cross-species antimalaria vaccine. In this study, we investigated the efficacy of P48/45 through the ancestral and consensus reconstruction approach. P48/45 phylogenetic and time tree analysis was done by RAXML and BEAST2. GRASP server and Ugene software were used to reconstructed ancestral and consensus sequences, respectively. The protein structural prediction was done by using inspired and Rosetta program. Each protein characteristic of P48/45 was analyzed by assessing hydrophobicity and Post-Translational Modification sites. Meanwhile, the Epitope sequence for B-cell, T-cell, and MHC was determined using an immunoinformatic approach. Lastly, molecular docking simulation was done to determine native binding interactions of P48/45-P230. The result showed a distinct protein characteristic of ancestral and consensus sequences. The immunogenicity analysis revealed the number of epitopes in the ancestral sequence is greater. The study also found a conserved epitope located in the binding site and consists of specific Post-Translational Modification sites. Hence, our research provides detailed insight into ancestral and consensus P48/45 efficacy.
DOI: 10.17632/m2xjxtsmxb.1
title: Online teaching during the quarantine of the COVID 19 from Brazilian and Vietnamese teachers' perspectives: A qualitative study

description: The data shows teachers' experience of online teaching during the quarantine of the COVID 19. The data aims to find out both challenges that teachers face and successes that they have achieved when shifting to online education during the pandemic of the COVID 19. Using a survey with 107 teachers from Brazil and Vietnam (57 Vietnamese teachers and 50 Brazilian teachers), the data finds out some key challenges of online teaching, including: (i) the interaction inside and outside the classroom, (ii) physical access to technology, (iii) health issues (especially in terms of mentality), (iv) and adaptation of methodologies. Regarding the successes, the data identifies some achievements that teachers have succeeded related to professional improvement, including: (i) technology skills, (ii) adaptation of teaching methods, and (iii) interaction with students.
DOI: 10.17632/8cp52kynh6.1
title: Spatio-temporal dataset of nitrogen dioxide levels during COVID-19 lockdown in Cairo, Egypt

description: The World Health Organization (WHO) declared COVID-19 as a pandemic in March 2020. Lockdown measures were forced throughout the whole world. Egyptian governorate announced a partial curfew across the entire country on 25th March 2020. This dataset was created to monitor the changes in nitrogen dioxides (NO2) concentration due to the lockdown measures of COVID-19 pandemic in Cairo, Egypt. The daily data was collected and from the Sentinel 5P remote sensing platform for April 2019 and 2020. The daily data were processed using Matlab and ARC/GIS, then the monthly means of April 2019 and 2020 were created and used to calculate the changes in NO2 concentration. The data is publicly available, and it is beneficial for researchers and policymakers.
DOI: 10.17632/jfpj77vs9k.1
title: Tongue Cancer Survival Data

description: Oral Tongue Cancer Survival from a low socioeconomic area, this contains the spss data sheet file
DOI: 10.17632/68c4c77f4s.3
title: Industrial Pipelines Data Generator

description: The uniqueness and the complexity of industrial construction project data have always been a challenge in research. The confidentiality of the data also contributes to the difficulty of avail data to researchers and the public, especially those projects related to industrial projects such as oil and gas facility projects. Therefore, data generators capable of generating a large number of simulated data have been a pressing demand by the research communities. This data describes a data generator that is capable of producing simulated industrial pipelines data. The industrial pipelines data are complex in nature and the data generator is capable of generating a set of pipelines that preserves the topological and physical properties of the pipeline formation components. Each generated component has eight components. These are: 1. Line number 2. The type of pipeline branch 3. Component location (seq_in_branch) 4. The id of the previously connected component 5. Component type 6. Component diameter 7. Component length 8. The running direction (x, y, z) of the component The data is a Python program code. It runs in a simple Python Integrated Development Environment (IDLE) and saves the generated data in a text file within the program code folder directory. The generated data can be used in studies related to the optimization of industrial pipelines fabrication, transportation, and on-site installation processes. The industrial pipelines data generator can allow different optimization algorithms to be tested under a large number of instance of problems. Also, the availability of the generator program code will enable the researchers to extend the development in the industrial pipeline data.
DOI: 10.1285/i9788883051616p1
title: Frontespizio e pagine iniziali
DOI: 10.17632/24mnk4tv7r.1
title: Clinical Correlates of Early IgG Response in Patients with Mild COVID-19

description: The dataset includes the temporal pattern of early SARS-CoV-2 IgG response in patients with mild COVID-19 and tries to identify predictive clinical and laboratory features.
DOI: 10.1285/i9788883051616p3
title: Indice
DOI: 10.6084/m9.figshare.12851445
title: Causal Inference With Interference and Noncompliance in Two-Stage Randomized Experiments

description: In many social science experiments, subjects often interact with each other and as a result one unit’s treatment influences the outcome of another unit. Over the last decade, a significant progress has been made toward causal inference in the presence of such interference between units. Researchers have shown that the two-stage randomization of treatment assignment enables the identification of average direct and spillover effects. However, much of the literature has assumed perfect compliance with treatment assignment. In this article, we establish the nonparametric identification of the complier average direct and spillover effects in two-stage randomized experiments with interference and noncompliance. In particular, we consider the spillover effect of the treatment assignment on the treatment receipt as well as the spillover effect of the treatment receipt on the outcome. We propose consistent estimators and derive their randomization-based variances under the stratified interference assumption. We also prove the exact relationships between the proposed randomization-based estimators and the popular two-stage least squares estimators. The proposed methodology is motivated by and applied to our own randomized evaluation of India’s National Health Insurance Program (RSBY), where we find some evidence of spillover effects. The proposed methods are implemented via an open-source software package. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.