cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/p8czktrz7k.1
title: Kaji_EICont

description: spike -- size: (1, N+2) 1st~Nth components: spike data (time stamps of spike happened) (N+2)th compoent: Number of cortical neurons and maximum time step time bin size: 1ms This raw data is stored for individual data samples. cellnum: number of neurons Sheet1: excitatory neurons Sheet2: inhibitory neurons FR: firings-rate histograms [log10] Sheet 1: frequency [log10] Sheet2: histograms of excitatory neurons (for 7 data set) Sheet3: histograms of inhibitory neurons (for 7 data set) Weights: histograms of connectivity intensities Sheet 1: weights (=intensities) [log10] Sheet2: histograms of excitatory neurons (for 7 data set) Sheet3: histograms of inhibitory neurons (for 7 data set) KC_layers: This data is a summary of K-core (KC) clusterings separately calculated from individual layers or all cortical layers. Individual sheets correspond with 7 data samples. A,B: excitatory neurons, D,E: inhibitory neurons A,D: labels of data, (layer1-3, layer4, layer5, layer6, all), B,E : their values All means KC values for all layers FVS_layers: The data format is same as KC_layers. The included data is Feedback Vertex Set. Degree: degree histograms Sheet1: values of x axis (degree [log10]) Sheet2: in-degree histograms for seven data samples Sheet3: out-degree histograms for seven data samples
DOI: 10.17632/dvtmn59xft.1
title: Simulated soil temperature and surface fluxes over the Tibetan Plateau using SSiB3-FSM

description: The dataset includes simulated soil temperature, albedo, and energy fluxes over the Tibetan Plateau, using a land surface model (SSiB3-FSM). Based on this dataset and other publicly archived observations, we found that: 1. Land surface temperature anomaly can sustain for seasons and is accompanied by persistent subsurface temperature, snow, and albedo anomalies. 2. With middle-layer subsurface temperature as a predictor, the land surface temperature is highly predictable, especially during the springtime. 3. Soil properties and soil column depth predominate subsurface temperature memory, which suggests the key processes to improve its prediction. More information can be found in the reference: Ye Liu, et al, 2020, Investigation of the variability of near-surface temperature anomaly and its causes over the Tibetan Plateau, Journal of Geophysical Research: Atmospheres.
DOI: 10.17632/724c998h9c.1
title: MoLa R8.7k InCar Dataset

description: This repository presents the dataset described in the article "A system for the generation of in-car human body pose datasets", published in Machine Vision and Applications (2019). The repository includes the complete real dataset used for training, validation and testing. To ease its use, a general README file is provided, explaining the structure of an individual sub-dataset. For evaluation indexing purposes, a .mat indexing file (MoLa R8.7K InCar Dataset) is provided for each of the sub-datasets (train, validation and test). For visualization purposes, a toolbox is provided in MATLAB code that reads the .mat indexing file, as well as the associated dataset folder (MoLa R8.7K InCar Dataset) and generates an animation with image and ground-truth.
DOI: 10.17632/b7z524pyhv.2
title: Data_PIBIC_3.556.646_UNIR_2019

description: Multiapproach of use and abuse of alcohol, licit and illicit drugs and similars (Legal opinion n. 3.556.646 - CEP/UNIR 2019). 1st Year (august 2019 - july 2020), excessive alcohol consumption at Porto Velho-RO: categorization by CAGE. [Multiabordagem do uso e abuso de álcool, drogas lícitas e ilícitas e afins (Parecer n°. 3.556.646 - CEP/UNIR 2019). Ano 1 (agosto de 2019 - julho de 2020), abuso do consumo de álcool em Porto Velho - RO: categorização pelo CAGE.]
DOI: 10.17632/jw44tcywfr.2
title: Comunicação no perioperatório: Perspectivas dos Profissionais da Saúde e Pacientes na construção da Cultura de Segurança

description: Produção de artigo título COMUNICAÇÃO NO PERIOPERATÓRIO: PERSPECTIVAS DOS PROFISSIONAIS DA SAÚDE E PACIENTES NA CONSTRUÇÃO DA CULTURA DE SEGURANÇA
DOI: 10.4125/pd0118th
title: Synthetic Approach to Fused Azasultams with 1,2,4-Thiadiazepine Framework

description: Synthetic approach to fused azasultams with 1,2,4-thiadi­azepine framework via base promoted protocols has been developed. 1H-Azole-2-carboxylates and N-(chloromethyl)-N-methylmethanesulfonamide were used as ambiphilic building blocks in the one-pot and two-step reaction sequences. Chemical behavior of the obtained azasultams in reactions with amines, hydrazine, DMFDMA, and NaBH4 was investigated. An enamino ketone derived from an azasultam was exploited in the synthesis of new pyrazole and pyrimidine heterocycles.
DOI: 10.4125/pd0119th
title: Facile Synthesis of β-Bromostyrenes by Direct Bromination of Styrenes with N-Bromosuccinimide and Sodium Persulfate

description: A new, direct, efficient, and transition-metal-free method is reported for the synthesis of β-bromostyrenes from styrenes by using N-bromosuccinimide as the brominating reagent and sodium persulfate (Na2S2O8) as the oxidant. This convenient and concise reaction is practical, operationally simple, and can be adapted for large-scale syntheses.
DOI: 10.17632/cvdnf723k5.1
title: Research data to: " Validation and calibration of soil δ2H and brGDGTs along (E-W) and strike (N-S) of the Himalayan climatic gradient"

description: Research data used in the manuscript
DOI: 10.17632/s4y6y7vz94.1
title: Raw spectrum data for untargeted metabolome of the rat mammary cancer model

description: Raw spectrum data for untargeted metabolomics of the fecal matters obtained from the rat mammary cancer model
DOI: 10.17632/nn442rvb8j.3
title: Whose tweets on COVID-19 gain the most attention: celebrities, politcal or scientific authorities?

description: Background Twitter has considerable capacity for health education and proves to be an efficient and popular communication tool in the COVID-19 pandemic. Although a number of stakeholders saturate Twitter with COVID-19-related information it remains unknown who disseminates information most efficaciously. Methods COVID-19-related tweets were obtained from Twitter accounts of health agencies, governmental authorities, universities, scientific journals, medical associations, and celebrities. The impact of posts was measured with the nominal and relative (%followers) number of likes and retweets. Sentiment analysis was conducted. Results We have identified 17,331 COVID-19-related tweets posted by 338 accounts in over four months since the virus began to spread. The largest number of likes was received by tweets of celebrities (median nominal, relative likes; 14,918, 0.036%), politicians (259, 0.174%), and health agencies (231, 0.007%). Most retweeted messages were also posted by celebrities (2,366, 0.005%), health agencies (130, 0.004%), and politicians (55, 0.041%). Retweets and likes peaked in March 2020 and the overall sentiment of the tweets was growing steadily. Whereas celebrities and politicians posted positive messages, the scientific and health authorities more often employed a negative vocabulary. The posts with positive sentiment gained more likes, and relative likes than non-positive. Conclusions During the pandemic, the tweets of celebrities, and politicians related to COVID-19 outperform those coming from health and scientific institutions. Active engagement of Twitter influencers may help key messages go viral.
DOI: 10.15482/usda.adc/1519359
title: Data From: Feasibility of Infiltration Galleries for Managed Aquifer Recharge in the Mississippi River Valley Alluvial Aquifer of Northeast Arkansas
DOI: 10.17632/h9vdjh8tk7.2
title: Data for measuring e-learning systems success during the COVID-19 pandemic: Case of the Higher Education Institutions in Morocco

description: E-learning systems success data.
DOI: 10.17632/wwjp2jzxmf.1
title: Dataset: Application of the larger-the-better signal-to-noise ratio model to portfolio optimization

description: This data includes the monthly closing net asset values of five different US portfolios as samples: the American Funds Bond Fund of America, the PIMCO Total Return Fund, the Vanguard Inflation-Protected Securities Fund, the S&P500 and the Dow Jones Industrial Average indexes. That is, three fixed income portfolios (with low return variances) and two stock portfolios (with high return variances). The data ranges from August 31st, 2015 to July 31st, 2020, which includes some stability periods as well as some abnormal volatility periods, such as the January 2020 – July 2020 period. Some calculations in this data include: monthly returns, average monthly returns, standard deviations, variances and average yearly return. This raw data is required to perform the Mean-Variance and the Larger-the-Better Signal-to-Noise Ratio analysis used in portfolio selection processes.
DOI: 10.17632/v992cb6bw7.1
title: HFRD: Human Face Recognition Datasets on COVID-2019 pandemic stage (v2020)

description: The HFRD (v2020) dataset includes 4835 images of masked human faces. Originally, the faces were taken from three different publicly available datasets: MUCT, FASSEG, and AT&T datasets. The collected subsets of the HFRD dataset contain standard images that are previously used in the field of facial recognition, and then we added masks to cover the nose, mouth, and chin area, as for what remains visible from the face are the eyes, forehead, and hair. Thus, we have introduced new standard images for use in the field of partial facial recognition (PFR) domain. The new structure of the current HFRD store inherits the structure of each original dataset, which means there are three main datasets: MaskedMUCT contains five folders, MaskedFASSEG contains four folders, and MaskedAT&T has organized in 40 folders. This store of HFRD masked face datasets are not only inheriting the structure of the original datasets, but also inheriting the varsity of them. Finally, all folders consist of facial images surrounded and covered by various shapes of masks. Consequently, the proposed new enhanced HFRD datasets have been developed based on the impact of the pandemic COVID-2019 stage. Our enhanced improved Human Face Recognition Datasets (HFRD) datasets could be used to test studies of FR algorithms for human identification. The obtained outcomes from this enhanced HFRD data can also be useful in providing more knowledge for the Artificial Intelligence (AI) tools, and decision support system for predicting the spread of COVID-2019.
DOI: 10.17632/tmp32v54ss.1
title: LIWC and n-gram counts of English and Dutch novels

description: This dataset consists of CSV files with word counts in several corpora: - 694 English language novels from different genders and orientations - 401 bestselling Dutch language novels - 50 novels nominated for Dutch literary prizes Each corpus comes with: - LIWC counts; this file also includes the available metadata for each novel. The English data was created with LIWC 2015. The Dutch data was created with the validated translation of LIWC 2001. - Word counts (unigrams) and bigram counts per novel. All text has been converted to lowercase. Contractions are tokenized into separate tokens, e.g., can't =&gt; ca n't Two restrictions are applied: - only unigrams or bigrams that occur in at least 10 texts are retained - only the 100k most frequent are retained - Overall word counts and bigram counts; i.e., the sum across all novels. All files are encoded in UTF-8.
DOI: 10.21227/mwjq-xd54
title: ExoNet Database: Wearable Camera Images of Human Locomotion Environments

description: Abstract: Recent advances in computer vision and artificial intelligence have allowed researchers to develop environment recognition systems for robotic lower-limb exoskeletons and prostheses. However, small-scale and private training datasets have impeded the widespread development and dissemination of image classification algorithms for human locomotion environment recognition. To address these shortcomings, we developed “ExoNet” - the first open-source, large-scale hierarchical database of high-resolution wearable camera images of human locomotion environments. Unparalleled in both scale and diversity, ExoNet comprises over 5.6 million images of different indoor and outdoor real-world walking environments, which were collected using a lightweight wearable smartphone camera during the summer, fall, and winter seasons. Approximately 923,000 images in ExoNet were human-annotated using a 12-class hierarchical labelling architecture. Available publicly through IEEE DataPort, ExoNet offers an unprecedented community platform to train, develop, and compare next-generation image classification algorithms for human locomotion environment recognition. Beyond the control of lower-limb exoskeletons and prostheses, potential applications of ExoNet extend to humanoid and autonomous legged robotics.Reference: Laschowski B, McNally W, Wong A, and McPhee J. (2020). ExoNet Database: Wearable Camera Images of Human Locomotion Environments. Under Review.
DOI: 10.6084/m9.figshare.12954512.v1
title: R0216_20180209a_videos

description: Rat 0216, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.3886/e120799v1
title: Data and Code for: Inventor Gender and the Direction of Invention

description: We study whether increasing the share of female inventors leads to more biomedical inventions that focus on the needs of women. After accounting for detailed disease-technology, disease-year, and technology-year fixed effects, we find that a 10 percentage-point increase in the share of female inventors in a research area yields 1.2 percentage points more female-focused patents. Notably, this effect only holds for female-led invention teams. Areas with a greater share of female inventors in supporting roles do not produce more female-focused inventions. For gender to impact the direction of invention, it appears that women must occupy positions of power.
DOI: 10.3886/e120799
title: Data and Code for: Inventor Gender and the Direction of Invention

description: We study whether increasing the share of female inventors leads to more biomedical inventions that focus on the needs of women. After accounting for detailed disease-technology, disease-year, and technology-year fixed effects, we find that a 10 percentage-point increase in the share of female inventors in a research area yields 1.2 percentage points more female-focused patents. Notably, this effect only holds for female-led invention teams. Areas with a greater share of female inventors in supporting roles do not produce more female-focused inventions. For gender to impact the direction of invention, it appears that women must occupy positions of power.
DOI: 10.3886/e120387
title: Data and Code for: How often does active learning occur?

description: Substantial evidence suggests active learning pedagogies are superior to lecturing, but little evidence exists on the prevalence of such methods. Watts and Schaur (2011) find, based on self-reported data, the median instructor lectures 83% of the time. We analyze audio recordings of 535 total classes from 30 different instructors to show instructors greatly underestimate how often they use passive learning pedagogies such as lecturing. Survey results show instructors estimate they lecture approximately 78.5% of class time; our data reveals the true average is 89%. This gap between perception and reality is statistically significant.
description: College instructors.
DOI: 10.3886/e120387v1
title: Data and Code for: How often does active learning occur?

description: Substantial evidence suggests active learning pedagogies are superior to lecturing, but little evidence exists on the prevalence of such methods. Watts and Schaur (2011) find, based on self-reported data, the median instructor lectures 83% of the time. We analyze audio recordings of 535 total classes from 30 different instructors to show instructors greatly underestimate how often they use passive learning pedagogies such as lecturing. Survey results show instructors estimate they lecture approximately 78.5% of class time; our data reveals the true average is 89%. This gap between perception and reality is statistically significant.
description: College instructors.
DOI: 10.3886/e120347
title: Data and Code for: College Attainment, Income Inequality, and Economic Security: A Simulation Exercise

description: We conduct an empirical simulation exercise that gauges the plausible impact of increased rates of college attainment on a variety of measures of income inequality and economic insecurity. Using two different methodological approaches—a distributional approach and a causal parameter approach—we find that increased rates of bachelor’s and associate degree attainment would meaningfully increase economic security for lower-income individuals, reduce poverty and near-poverty, and shrink gaps between the 90th and lower percentiles of the earnings distribution. However, increases in college attainment would not significantly reduce inequality at the very top of the distribution.<br>
DOI: 10.3886/e120347v1
title: Data and Code for: College Attainment, Income Inequality, and Economic Security: A Simulation Exercise

description: We conduct an empirical simulation exercise that gauges the plausible impact of increased rates of college attainment on a variety of measures of income inequality and economic insecurity. Using two different methodological approaches—a distributional approach and a causal parameter approach—we find that increased rates of bachelor’s and associate degree attainment would meaningfully increase economic security for lower-income individuals, reduce poverty and near-poverty, and shrink gaps between the 90th and lower percentiles of the earnings distribution. However, increases in college attainment would not significantly reduce inequality at the very top of the distribution.<br>
DOI: 10.3886/e120825
title: Replication Data For: The Impact of School Finance Reforms on Local Tax Revenues

description: Starting with the California State Supreme Court decision in Serrano v. Priest (1971), state supreme courts in the United States have invalidated school finance systems that relied primarily on locally funded property taxes, holding that such schemes deny low-income students’ constitutional rights to equal protection under the law (Sullivan 1977).<br>To comply with these court rulings, state legislatures enacted new policies for funding school districts that prioritized equity in school funding across districts, during the first wave of reforms, with later reforms requiring adequate levels of funding across school districts (Lafortune,Rothstein, and Schanzenbach 2018). <br><br>Whereas the effect of these reforms on equalizing school spending has been widely studied—for example, Jackson, Johnson, and Persico (2016); Card and Payne (2002); and Hyman (2017)—less attention in the literature is devoted to understanding how they affected both the tax base and the incentives of local school districts to increase property taxes to fund schools. Notable exceptions are Hoxby (2001) and Hoxby and Kuziemko (2004).<br><br>In this paper we show how these reforms can be used to generate plausibly exogenousvariation in local property taxes. Our hope is that other scholars can use these instruments to answer important research and policy questions at the intersection of public finance and education in economics, where having an instrumentfor local taxes is advantageous.
DOI: 10.3886/e120825v1
title: Replication Data For: The Impact of School Finance Reforms on Local Tax Revenues

description: Starting with the California State Supreme Court decision in Serrano v. Priest (1971), state supreme courts in the United States have invalidated school finance systems that relied primarily on locally funded property taxes, holding that such schemes deny low-income students’ constitutional rights to equal protection under the law (Sullivan 1977).<br>To comply with these court rulings, state legislatures enacted new policies for funding school districts that prioritized equity in school funding across districts, during the first wave of reforms, with later reforms requiring adequate levels of funding across school districts (Lafortune,Rothstein, and Schanzenbach 2018). <br><br>Whereas the effect of these reforms on equalizing school spending has been widely studied—for example, Jackson, Johnson, and Persico (2016); Card and Payne (2002); and Hyman (2017)—less attention in the literature is devoted to understanding how they affected both the tax base and the incentives of local school districts to increase property taxes to fund schools. Notable exceptions are Hoxby (2001) and Hoxby and Kuziemko (2004).<br><br>In this paper we show how these reforms can be used to generate plausibly exogenousvariation in local property taxes. Our hope is that other scholars can use these instruments to answer important research and policy questions at the intersection of public finance and education in economics, where having an instrumentfor local taxes is advantageous.
DOI: 10.3886/e120599
title: Replication Files for: The Cost-effectiveness Implications of Carbon Price Certainty

description: While a firm knows the carbon price with certainty under a tax, it must form an expectation about future allowance prices to identify its cost-effective abatement investment under a cap-and-trade program. We illustrate graphically how errors in forming this expectation increase the costs of irreversible pollution abatement investment under cap-and-trade relative to a tax. We describe empirical “cost-effectiveness anomalies” in allowance markets that may be attributed to cap-and-trade’s inherent uncertainty. We model investment under simulated U.S. carbon tax and cap-and-trade policies and find that allowance price uncertainty can increase resource costs 20 percent for a given quantity of emission abatement.
DOI: 10.3886/e120599v1
title: Replication Files for: The Cost-effectiveness Implications of Carbon Price Certainty

description: While a firm knows the carbon price with certainty under a tax, it must form an expectation about future allowance prices to identify its cost-effective abatement investment under a cap-and-trade program. We illustrate graphically how errors in forming this expectation increase the costs of irreversible pollution abatement investment under cap-and-trade relative to a tax. We describe empirical “cost-effectiveness anomalies” in allowance markets that may be attributed to cap-and-trade’s inherent uncertainty. We model investment under simulated U.S. carbon tax and cap-and-trade policies and find that allowance price uncertainty can increase resource costs 20 percent for a given quantity of emission abatement.
DOI: 10.3886/e120840
title: Data and code for: Split Apart: Differentiation, Diversion, and Coordination in the Market for Superpremium Ice Cream

description: I explore recent behavior in the market for superpremium ice cream. I first document that the flavors offered in supermarkets by Ben & Jerry's and Haagen-Dazs became increasingly differentiated from 2006–2013. Using an estimated model of demand, I show that this differentiation increased profits for both firms. Also, unilateral deviation from the set of products offered in 2013 would have increased variable profits for the deviating firm. These facts, when coupled with anecdotal evidence, suggest that these firms tacitly coordinated their choice of flavors. A companion piece, Sullivan (2019), formalizes this result and quantifies the implications for outcomes and welfare.