cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/2sfvbvjtg7.1
title: Critic: a new program for the topological analysis of solid-state electron densities

description: This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2018) Abstract In this paper we introduce critic, a new program for the topological analysis of the electron densities of crystalline solids. Two different versions of the code are provided, one adapted to the LAPW (Linear Augmented Plane Wave) density calculated by the WIEN2k package and the other to the ab initio Perturbed Ion (aiPI) density calculated with the pi7 code. Using the converged ground state densities, critic can locate their critical points, determine atomic basins and integrate properties wi... Title of program: CRITIC Catalogue Id: AECB_v1_0 Nature of problem Topological analysis of the electron density in periodic solids. Versions of this program held in the CPC repository in Mendeley Data AECB_v1_0; CRITIC; 10.1016/j.cpc.2008.07.018 AECB_v2_0; CRITIC2; 10.1016/j.cpc.2013.10.026
DOI: 10.17632/64gkbz8bdb.2
title: Data for: On Farm Sheep Breed Classification Using Deep Learning

description: Sheep from four sheep breeds were recorded while being drafted on farm. Individual frames capturing sheep are grouped by breed. There are two folders one for raw frames with all types of variations (illumination, posture etc) and one for aligned sheep images with less variations
DOI: 10.17632/h4n3gn93gz.3
title: CineScale2

description: Data consists of camera angle and camera level annotations for a total of 24,748 frames.
Specifically, 9,129 video frames are categorized according to their camera angle in the following five categories: Overhead, High, Neutral, Low, and Dutch angle.
The remaining 15,619 video frames are labelled into six different classes accounting for their camera level: Aerial, Eye, Shoulder, Hip, Knee, and Ground.
Both camera angle and camera level annotations were performed by a team of expert film scholars:  two independent coders and a third person who made decisions in cases of disagreement.
DOI: 10.17632/xhz8m74pp7.1
title: Kartal District of Istanbul

description: Kartal district of Istanbul data set is first discussed in "Locating temporary shelter areas after an earthquake: A case for Turkey" article of Kilci F, Kara BY, Bozkaya B, 2015. (Kılcı F, Kara BY, Bozkaya B, 2015 Locating temporary shelter areas after an earthquake: A case for Turkey. European Journal of Operational Research 243(1):323- 332.) Kartal is specified as the 11th most crowded district among the 39 districts of Istanbul and has nearly $425,000$ inhabitants. There are 20 sub-districts in Kartal and the population of each is assumed to be concentrated in its center. Moreover, there are 25 points of interests (POI) which are determined as emergency rallying points. These POIs include school yards, mall parking lots and some other appropriate points. The locations of 45 nodes are presented in the KARTAL.jpg. Rallying points are the first 25 nodes and the rest are sub-districts. Symmetric node to node distance matrix and a matrix describing ground transportation network existence are also defined.
DOI: 10.17632/9xyvy2njj3.1
title: Samsung INR21700 30T 3Ah Li-ion Battery Data

description: The included tests were performed at McMaster University in Hamilton, Ontario, Canada by Dr. Phillip Kollmeyer (phillip.kollmeyer@gmail.com). If this data is utilized for any purpose, it should be appropriately referenced. See the Readme file for more details. A new 3Ah Samsung 3.0T cell was tested in an 8 cu.ft. thermal chamber with a 75amp, 5 volt Digatron Firing Circuits Universal Battery Tester channel with a voltage and current accuracy of 0.1% of full scale. /*************************************************/ A series of tests were performed at six different temperatures, and the battery was charged after each test at 1C rate to 4.2V, 10mA cut off charge current, at battery temperature of 25degC The tests were performed as follows: 1. Four pulse discharge HPPC test (1, 2, 6, and 12C discharge and 0.5, 1, 2, and 4C charge, with reduced values at lower temperatures) performed at 100, 95, 90, 80, 70..., 20, 15, 10, 5, 2.5 % SOC. ("..._HPPC.mat") 2. C/20 Discharge and Charge test. ("..._C20DisCh.mat") 3.0.5C ("..._Dis_0p5C.mat"), 2C ("..._Dis_2C.mat"), and two 1C ("..._Cap_1C.mat") discharge tests. The first 1C discharge test is performed before the UDDS cycle, and the second is performed before the Mix3 cycle. 4.Series of four drive cycles performed, in following order: UDDS(..._UDDS.mat), HWFET(..._HWFET.mat), LA92 (..._LA92.mat), US06 (..._US06.mat). 5. A series of eight drive cycles (mix 1-8) (..._Mixed#.mat) consist of random mix of UDDS, HWFET, LA92, US06. The drive cycle power profile is calculated for a single Turnigy cell in a compact electric vehicle. 6. The previous tests are repeated for ambient temperatures of 40degC, 25degC, 10degC, 0degC, -10degC, and -20degC, in that order. For tests with ambient temperature below 10degC, a reduced regen current limit is set to prevent premature aging of the cells. The drive cycle power profiles are repeated until 95% of the 1C discharge capacity at the respective temperature has been discharged from the cell 7. A series of 16 charges (charge 1-16) (..._Charge##.mat) store the cell charging before and after every drive cycle starting with an inital top up before doing the Cap_1C test /*************************************************/ Matlab (.mat) file naming convention: The file names begin with the date the test started, and are followed by the time the test started and a descriptive name, such as in the following example: "11-07-19_10.49 557_Cap_1C_40degC_IN21700_30T.mat? Date: "11-07-19" (November 7th, 2019) Time: "10.49" (10:49 am) Descriptor: "40degC_IN21700_30T" The naming convention allows for sorting by date and test time when all the files are placed in one folder. This may be useful when trying to determine which charge is associated with which drive cycle, for example, or when looking at aging.
DOI: 10.17632/xf5bv3hcvw.2
title: Seasonal McArthur Forest Fire Danger Index (FFDI) data for Australia: 1973-2017

description: McArthur FFDI for historical data at 39 high quality stations in Australia. Stations cover the entire continent, although spacing is sparse in some locations. Values of 95th,90th,75th,50th,25th and 10th percentile of daily FFDI estimated over standard meteorological seasons (i.e. DJF, MAM, JJA, SON). Top and Bottom value for each season are also provided. Reliable data presented here extend from JJA 1972 through MAM 2017. The data used in the paper focus on the 90th percentile. Seasonal statistics for components of FFDI (i.e. rainfall, KBDI, max temperature, relative humidity, drought factor, wind speed) also given. Latitude/longitude of the stations, number of individual observations in each season, and time indicators also provided. Sorry, station names not included...couldn't get the netCDF to contain a string variable!! The netCDF-3 file describes the format and variables included in more detail. The calculation of FFDI follows the methodology described in Lucas (2010). Station selection is as in Clarke et al (2013). Underlying meteorological data come from Bureau of Meteorology surface weather stations This version of the data set supports the submission/publication of Harris and Lucas (2019) in PLOS ONE
DOI: 10.17632/ckdvx3d3zc.1
title: Spatial decomposed concentrations of NO2 and PM2.5 air pollution in the United States at Census block group level

description: This dataset includes the yearly block group level decomposed concentrations of four spatial components ("long-range", "mid-range", "neighborhood", "near-source") for PM2.5 and NO2, from year-2000 to year-2015. The concentrations are at the census block group level. The unit of concentrations is ug/m3 for PM2.5 and ppb for NO2. Block group is identified by variable "blockgroup_id"; the longitude and latitude of each block group centroid are indicated by "longitude" and "latitude". Names of concentration variables follow the pattern as "COMPONENT_YEAR". "COMPONENT" represents four spatial components; "YEAR" represents the last two digits of year-2000 to year-2015. For example, "long-range_00" represents the "long-range" component concentrations for the year-2000. To use this dateset, please cite the following article: Wang, Y., Bechle, M.J., Kim, S.Y., Adams, P.J., Pandis, S.N., Pope III, C.A., Robinson, A.L., Sheppard, L., Szpiro, A.A. and Marshall, J.D., 2020. Spatial decomposition analysis of NO2 and PM2. 5 air pollution in the United States. Atmospheric Environment, p.117470. DOI: 10.1016/j.atmosenv.2020.117470
DOI: 10.17632/s62zm6djd2.1
title: A database of eight common tomato pest images

description: The database is based on eight common tomato pests, including (1) Tetranychus urticae, (2) Bemisia argentifolii, (3) Zeugodacus cucurbitae, (4) Thrips palmi, (5) Myzus persicae, (6) Spodoptera litura, (7) Spodoptera exigua, and (8) Helicoverpa armigera. The original images were collected from IPMImages database (https://www.ipmimages.org/index.cfm), National Bureau of Agricultural Insect Resources (NBAIR) (https://www.nbair.res.in /Databases/insectpests/index.php) and Google search. The image database contains 609 original images in 8 categories, and is amplified using image enhancement technology to have a total of 4263 images after enhancement. Image enhancement technologies include 90 degree rotation, 180 degree rotation, 270 degree rotation, horizontal flip, vertical flip and crop. Finally, the image size is unified in 299*299 and the image format is in .JPG file.
DOI: 10.17632/884ds27xc5.1
title: Data for "Shock-induced devolatilization of phlogopite"

description: This is the supporting material for the article "Shock-induced devolatilization of phlogopite". It includes datasets produced by ab initio molecular dynamics and post-processing software package UMD, such as self-diffusion coefficient, coordination, fluid composition, etc.
DOI: 10.17632/nm2gyjn8mc.1
title: Social Entrepreneurship Questionnaire

description: Dataset has answers of 135 responders. I. Demographic questions: 1. What is your age? 2. What is your highest education level? 3. Number of Work experience years? 4. To What Degree, you are interested to start a social entrepreneurship activity? II. The following questions are presented 1 Lack of involvement in Environmental policy making By Social Entrepreneurs 2 Lack of social impact recordings 3 Limiting performance measurements to financial performance 4 Lack of CSR Reporting or social auditing 5 Market Entry Barriers for Social Entrepreneurs 6 Lack of Opportunity Recognition By Social Entrepreneurs 7 Lack of Financial assistance for Social Entrepreneurs 8 Existence of Powerful Competitors 9 Lack of contribution to local environmental capital 10 Lack of Perception of involvement in community 11 Lack of Awareness about community assets 12 Lack of Social Purposes 13 Lack of Awareness about SE in Academic world 14 Lack of Theories in SE Field 15 Difficulties in paying attention to economic and social issues at the same time 16 Lack of Value Creation in current SE activities 17 Lack of Society involvement 18 Lack of Innovative thinking 19 Lack of interest in social Change 20 Lack of Support Networks for Social Entrepreneurs 21 Lack of Knowledge in Social Entrepreneurs 22 Lack of Framing Processes in order to do collective actions 23 Difficulties in Making a good Brand Image 24 Existence of Numerous Actors in Social issues 25 unsuitable Revenue Models 26 Lack of Social objectives 27 Lack of Economic, social and environmental values 28 Lack of Supportive regulations and laws and Tax Policies 29 Lack of Strategic Niche Markets for their activities 30 Lack of Partner Networks 31 Lack of Administrative Structures 32 Lack of local Capacity Building Activities 33 Lack of local movements 34 Local Norms 35 High Risks 36 Lack of Sense of accountability in Social Entrepreneurs 37 Complexity of Management in Social Enterprises 38 Cross Disciplinary nature of SE 39 lack of Social Entrepreneurial behavior 40 Lack of Social Entrepreneurship education 41 Lack of Ability to challenge traditional ways of thinking 42 Lack of Optimism 43 Lack of Empathy in Entrepreneurs 44 Lack of Cultural awareness 45 Lack of ability to Create and sustain social value 46 High Environmental dynamics 47 Lack of Entrepreneurial spirit 48 None-profit to for-profit competition 49 Lack of learning from failure 50 Focus on individual level of analysis
DOI: 10.17632/s3r4thpy95.1
title: Enhancing Legal Sentiment Analysis: A CNN-LSTM Document-Level Model

description: This research delves into the use of deep learning methods in analyzing sentiment within Canadian maritime case law. Its primary aim is to apply these advanced techniques to the fields of legal analytics and policy development. The study underscores the crucial role of Artificial Intelligence (AI) in both legal practices and policy formulation, drawing comparisons among various machine learning models. The results of this research indicate that AI has the capability to foster a more nuanced and well-informed legal landscape, underscoring its potential in legal practices.

The investigation into case adjudication in Canadian maritime law has unveiled significant insights, particularly in terms of trial outcomes related to the number of judges presiding. It was found that when a single judge was responsible for a case, the probability of a guilty verdict was 46%, with a not guilty verdict being slightly more likely at approximately 51%. This demonstrates an almost equal distribution of case outcomes, with around 3% of cases left unresolved. Interestingly, the occurrence of unresolved verdicts did not show a notable increase with the involvement of three judges, as it rose only slightly to 5%. This suggests that the addition of more judges to the trial does not significantly affect the rate of indecision in verdicts, pointing to a remarkable consistency in judgment outcomes across different judicial settings within the domain of Canadian maritime law.

The term 'accuracy' in this context refers to the rate at which a model correctly predicts outcomes.
DOI: 10.17632/hk77hj72xp.1
title: Average regression

description: Average regression
DOI: 10.17632/zkwgkjkjn9.2
title: MultimodalGasData: Multimodal Dataset for Gas Detection and Classification

description: The MultimodalGasData provides simultaneous measurements taken using seven different Gas Sensors and images taken using a Thermal Camera. Two different gases are considered, and a dataset is created for four classes – No Gas, Perfume, Smoke and Mixture of Perfume and Smoke.  The dataset is collected using the seven different metal oxide gas sensors, MQ2, MQ3, MQ5, MQ6, MQ7, MQ8, MQ135 and a thermal imaging camera. The dataset consists of numerical values taken from gas sensors and images taken using a thermal camera.
DOI: 10.17632/hbmk6srnrx.1
title: date

description: Fish
DOI: 10.17632/3pj9y3db25.1
title: The Effect of National Culture on Corporate Social Responsibility: Evidence from Chinese Red Culture

description: In this study, based on institution theory and social identity theory, we validate the normative role of national culture as an informal institution on corporate social responsibility (CSR) from the perspective of red culture. By analyzing the panel sample of Chinese listed companies from 2012 to 2020, we investigated the effect of red culture on CSR, and the changes in the influence of red culture on CSR under different institutional conditions. Based on the institutional background of China, we find that red culture atmosphere is positive and significantly affects CEO’s CSR behavior. We further find that the market intermediary organizations and legal system environment index and foreign culture shock weaken the positive relationship between red culture and CSR, and the transportation convenience enhances the influence of red culture on CSR, the results are largely confirmed by a series of robustness tests. Our research has contributed to propagandizing the national culture, enhancing cultural confidence, exalting the cohesion and centripetal force of the nation, and improving governance and CSR performance in theory and practice.
DOI: 10.17632/whb6rychpx.2
title: Nigeria's 2023 Presidential Election Dataset

description: This dataset contains tweets mined from August, 2022 to February, 2023 about Nigeria's 2023 presidential election. The data is based on the three major presidential aspirants in the 2023 presidential election. These aspirants are Atiku Abubakar, Bola Ahmed Tinubu and Peter Obi. The data was mined using the Twitter API and Tweepy Python library using the following hastags: #obi, #atiku, #bat, #ObiDatti, #Atikulate and #batified.
DOI: 10.17632/36hs538bm9.1
title: Sperm

description: Methotrexate (MTX ) is commonly used for the treatment of certain cancers including but not limited to leukemia, Hodgkin's disease and head and neck cancers and causes reproductive damage in mice. The aim of this research, is to study the effects of catechin aqueous extract on some parameters of sperms and histopathological changes in testis of mice treated with methotrexate. The results showed significant (P&lt;0.05) decrease in sperms motility , increased percentage of dead sperms and abnormalities of sperms in mice treated with MTX, there was significant (P&lt;0.05) decrease in diameters of seminiferous tubules, primary spermatocytes and spermatids, increased interstitial spaces as compared with control, while in the second group result showed significant (P&lt;0.05) increase in sperms motility , decreased percentage of dead and abnormalities of sperms and significant (P&lt;0.05) increase in diameters of seminiferous tubules, primary spermatocytes and spermatids and decrease interstitial spaces compared with first and third groups.
DOI: 10.17632/v8y9gp3kpn.1
title: A Ship-Construction Dataset for Resource Leveling Optimization in Large Project Management Problems 

description: Resource leveling is a highly complex optimization problem corresponding to adjusting a project’s timeline (start and end dates) with the aim of matching resource allocation demands. The problem is particularly complex when a project is large and involves hundreds or even thousands of activities. Its successful solution is equivalent to considerable profits for the involved construction groups through the efficient management of their resources. In literature usually can be found only small-size benchmark problems consisting of a few activities (ten to twenty) mainly aiming to demonstrate that a new proposed method can operate correctly identifying the optimum (or a near-optimum) solution. In this data article, resource leveling data suitable for testing are provided, corresponding to a very large real-world problem of ship construction (consisting of 1178 activities). According to recent literature, the majority of the proposed methods for solving resource leveling optimization problems are based on algorithmic approaches, usually artificial intelligence-oriented (evolutionary programming). The reason is that intelligent approaches manage to solve complex problems, producing approximate solutions of high accuracy and thus attractive (profitable) for practical application. The provided data have been tested in the past with intelligent techniques using different evaluation functions. Nevertheless, the specific dataset has never been published before elsewhere and now there is a clear opportunity to provide these data for testing and benchmark experimentation to interested researchers.
DOI: 10.17632/jx3bfy94hh.1
title: Data for: Application of abscisic acid at veraison improves red pigmentation and accumulation of dietary antioxidants in red table grapes cv. Red Globe at harvest
DOI: 10.15468/dl.krkvpp
title: Occurrence Download

description: A dataset containing 471 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Psoralea pinnata L.",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is Specimen"
 ]
}

 The dataset includes 471 records from 38 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009362-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/brrgt645bh.3
title: VOFTools 5: An extension to non-convex geometries of calculation tools for volume of fluid methods

description: The VOFTools library includes useful tools for performing the geometrical operations that typically arise in volume of fluid (VOF) methods. We present a major improvement of VOFTools to extend its use to non-convex geometries without the need for costly convex-decomposition techniques. A thorough adaptation of the different routines has been carried out to meet the challenges of the new geometries and to maintain, and even improve, the efficiency and robustness of the previous tools. Specifically, we upgraded the routines for (1) truncating a polyhedron with a half space, (2) computing the interface position to cut off a certain volume fraction from a cell in PLIC (piecewise linear interface calculation) reconstruction and (3) computing the volume of a material body, defined by an implicit function, that is contained inside a mesh cell. To assess the performance of the supplied routines, different tests, which are provided in FORTRAN and C, were implemented for several 2D and 3D non-convex geometries.
DOI: 10.15468/dl.ukgnss
title: Occurrence Download

description: A dataset containing 1486 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation)",
 "GadmGid is CAN.1_1",
 "TaxonKey is Castor canadensis Kuhl, 1820"
 ]
}

 The dataset includes 1486 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009363-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/5bxw69mzht.1
title: CWTS Leiden Ranking 2017 website

description: Data set of visits to the website of the 2017 edition of the CWTS Leiden Ranking (www.leidenranking.com/ranking/2017) in the period between May 17, 2017 and February 28, 2018.
DOI: 10.17632/ppcwcm3cv9.1
title: Climate Change Exposure and Diversification

description: We use the CNRDS database to extract information from firms’ conference calls to construct the variable of interest, firm-level climate change exposure (CCExposure). We rely on local statistical yearbooks for regional investments in environmental pollution control and GDP figures. Firm- and industry-specific financial variables are obtained from the CSMAR database.
The study hypothesized that climate change exposure (CCE) would increase the degree of corporate diversification (DIV). We verified the mechanisms of capacity utilization (CU/OC), return risk (ROA volatility/Daily (and Monthly) yield volatility) and cash flow risk (Cash Risk) of the research by means of subgroup testing.
We hold a series of robustness tests such as instrumental variables method(with three instrument variables, eg. Chinese Low-carbon Policy/Regional Temperature & Ventilation Coefficient/Lewbel way), PSM, entropy balance, Oster test, Permutation test, etc..
We claritfy the difference effects of the sentiments(positive/negative) and properties(physical/regulatary) of CCE on DIV.
Heterogeneity tests on regional and industry characteristics(Regional Green Investment/Industrial Proitability), corporate green governance characteristics(Executive Green Cognition/Environment Score) and performance characteristics(Performance/Retain), etc..
Finally a two-stage model is used to test the impact of diversification increment driven by climate change exposure on corporate financing constraints (SA) and value (MB).
DOI: 10.17632/9n6rhvmjjn.1
title: Abaqus code for phase field fracture in elasto-plastic solids

description: Abaqus code for phase field fracture in elasto-plastic solids