cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/dkv6b3xj99.1
title: Single Point Corn Yield Data - Weather, Soil, Cultivation Area, and Yield for Precision Agriculture

description: This data comprises processed weather, soil, yield, and cultivation area for corn yield prediction in Sub-Sahara Africa, with emphasis on Nigeria. The data was collected to design a corn yield prediction model to help smallholder farmers make smart farming decisions. However, the data can serve several other purposes through analysis and interpretation.

The reference study region in Africa is Nigeria. The focuses on corn crop because there are over 211.4 million people, of which a large percentage of the population are smallholder farmers. Nigeria [9.0820° N, 8.6753° E] is within an arable land area of 34 million hectares located on the west coast of Africa. The region comprises of 36 states with the most and least number of districts being 214 and 10, respectively. For each state, the environment data are collected as follows. 
 
Grid map climate data – This data spans spatial resolutions between ~1 km2 to ~340 km2 from the high spatial resolution WorldClim global climate database22. Each grid point on the map is monthly data from January to December between 1970 and 2000 years and records 8 climate variables. The variables are average temperature C0, minimum temperature C0, maximum temperature C0, precipitation (mm), solar radiation (kJ m^(-2) day(-1), wind speed (m s(-1)), and water vapor (kPa) taken at 30 seconds (s), 2.5 minutes m, 5 m, and 10 m. 
 
Grid map soil data – This data is obtained from 250 minutes of spatial resolution AfSIS soil data23 from year 1960 to 2012. The variables are wet soil bulk density, dry bulk density (kg dm-3), clay percentage of plant available water content, hydraulic conductivity, the upper limit of plant available water content, the lower limit of, organic matter percentage, pH, sand percentage (g 100 g-1), silt percentage (g 100 g-1) and, clay percentage (g 100 g-1), and saturated volumetric water content variables measured at depths 0–5, 5–10, 10–15, 15–30, 30–45, 45–60, 60–80, 80–100, and 100–120 measured in centimeters (cm). 
 
Corn yield data – This data is available on Kneoma Corporation website24. It ranged from years 1995 to 2006 and consisted of a corn yield of 1000 metric tonnes and a cultivation area of 1000 hectares. 
 
Geolocation coordinates (latitude and longitude) – The geolocation of each of the 36 states with their districts is sampled from Google Maps. The output feds into the Esri-ArcGIS 2.5, a professional geographical software, for extracting the point-cloud values of each environmental variable (weather and soil) at specific geolocation of the 36 states of Nigeria.

Other Descriptions:
Data type - Continous and Categorical
Dataset Characteristics - Tabular
Associated Tasks - Regression
Feature Type - Real
Number of Instances - 1828
Number of Features: 12
DOI: 10.17632/crhpfz9cgt.2
title: Comparative data on aggressive biting behavior in mice of ddY strain measured by two independent devices

description: The Aggressive Response Meter (ARM) has been validated for measuring emotional aggression triggered by mental irritation in mice (Kuchiiwa and Kuchiiwa J. Neurosci. Methods, 2014; Kuchiiwa and Kuchiiwa J. Neurosci. Methods, 2016). It is used for revealing aggressive behavior of stressed animals and/or for investigating the effect of psychiatric drugs on aggression (Furukawa et al., Biochem. Biophys. Res. Com., 2017; Igarashi et al., Brain Res., 2021). We present data on whether the newly developed apparatus (PowerLab compatible-type ARM; pARM) is also valid to evaluate emotional (psychotic) aggressive biting behavior (ABB) of mice as the prior device (the ARM; Muromachi Kikai Co., Ltd.) has been. Mice (ddY strain) were singly-housed from 3 until 11 weeks after birth. In the experiment #1, a set of mice (10 males and 10 females) were measured with the pARM, then with the ARM at 9 weeks after birth. In the experiment #2, another set of mice (10 males and 10 females) were measured with the ARM, then with the p-ARM at 10 weeks after birth. In brief, these devices semi-automatically measured the average intensity and total number of bites in one 5-min session, which consisted of 30 presentations of two metal rods in front of each mouse, after an “irritation session” in which the hind paw of the mouse was stimulated 30 times in a 5-min session. The average intensity of one bite and the total number of bites within 30 presentations of metal rods in front of each mouse were recorded as ABB intensity and ABB frequency, respectively. Raw data from individual mice on ABB intensity and frequency (Table 1) is presented.
DOI: 10.15468/dl.yc75yy
title: Occurrence Download

description: A dataset containing 15706 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is Ecuador",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Mimus parvulus (Gould, 1837)",
 "Year 1868-2025"
 ]
}

 The dataset includes 15706 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004479-250117142028555/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/cfhkhmk6rt.1
title: Analysis of the current tools for optimization of equilibrium constants from potentiometric data_dataset

description: Artificial dataset of six different titrations simulated for a hypothetical hexaprotic acid
DOI: 10.17632/dkz2zcm2d6
title: LDHU3_20.0370

description: Leucine-rich repeat-containing protein; Leishmania donovani (HU3 strain)
DOI: 10.17632/dkz2zcm2d6.1
title: LDHU3_20.0370

description: Leucine-rich repeat-containing protein; Leishmania donovani (HU3 strain)
DOI: 10.17632/km7vf3rnmb
title: LDHU3_20.0420

description: Protein of unknown function - conserved; Leishmania donovani (HU3 strain)
DOI: 10.17632/km7vf3rnmb.1
title: LDHU3_20.0420

description: Protein of unknown function - conserved; Leishmania donovani (HU3 strain)
DOI: 10.17632/3pcdpr9nrm.1
title: LINF_350052200

description: Cgr1-like protein; Leishmania infantum (strain JPCM5)
DOI: 10.17632/4sh6s766fj.1
title: Attributes that build Florianópolis Brand Identity in the Technological Context

description: This dataset explores the key attributes that contribute to the construction of the brand identity of Florianópolis within the technological context. It includes insights derived from documentary research and open data collected from interviews. The data is structured to support studies on regional branding, innovation ecosystems, and the role of technology in urban identity development.
DOI: 10.17632/65czz8x7ky.1
title: LINF_350046700

description: Hypothetical protein - conserved; Leishmania infantum (strain JPCM5)
DOI: 10.17632/26hc75jc5j.3
title: Data library of irradiated fuel salt and off-gas tank composition for a molten salt reactor concept produced with Serpent2 and SOURCES 4C codes

description: This dataset has been prepared for the Compact Molten Salt Reactor (CMSR) that is being developed as a floating-type/transportable Molten Salt Reactor (MSR) by Seaborg Technologies in Copenhagen, Denmark. The version of the reactor design used in the preparation of this dataset was set to operate as a FUNaK-fuelled (or NaF-KF-UF4) and Sodium Hydroxide-moderated, converter-type reactor. It also features some novel features such as removal of volatile and gaseous fission products from the primary fuel salt to the off-gas tank with the help of a designated system called the Off-Gas System (OGS). 

This dataset was created using the Monte-Carlo particle transport code, Serpent2 and the neutron source term calculation code, SOURCES 4C. The dataset contains compositions (as nuclide masses in g/cm3) of the primary fuel salt and that of the off-gas tank contents at various combinations of Burnup (BU), Enrichment (IE), and Cooling Time (CT). The dataset also includes this data at various (35) rates of material movement from the primary salt to the off-gas tank. A total of 42 nuclides are removed this way and their concentrations are tracked throughout the simulations. In addition to these quantities, the dataset contains the total gamma emission rate (in photons/sec), total decay heat (in Watts), and total activity (in Becquerel) (which were also computed using Serpent2) for both, primary salt and the off-gas tank contents. Lastly, the dataset includes total neutron emission rates from spontaneous fission and alpha, n reactions which were computed using the SOURCES 4C code. In summation, there are a total of 2850 columns of data and 861,000 rows (corresponding to combinations of BU, IE, and CT). The 2850 columns of data can be broken down as:
‘BU’: Burnup (in MWd/kgU) (1 column of data)
‘IE’: Initial enrichment (in wt. % U-235) (1 column of data)
‘CT’: Cooling time (in days) (1 column of data)
‘FMI’: Flow Multiplier Index (1 column of data) 
‘fuel_Isotope’: 1398 columns of isotopes (in g/cm3) (1398 columns of data) 
‘tank_Isotope’: 1398 columns of isotopes (in g/cm3) (1398 columns of data) 
‘fuel_TOT_DH’: Total decay heat (in Watts) for fuel salt (1 column of data) 
‘fuel_TOT_GS’: Total gamma emission rate (photons/second) for fuel salt (1 column of data) 
‘fuel_TOT_A’: Total activity (becquerel) for fuel salt (1 column of data) 
‘tank_TOT_DH’: Total decay heat (in Watts) for fuel salt (1 column of data) 
‘tank_TOT_GS’: Total gamma emission rate (photons/second) for fuel salt (1 column of data) 
‘tank_TOT_A’: Total activity (becquerel) for fuel salt (1 column of data) 
‘flow_isotope’: Removal rates of 42 nuclides in 1/s (42 columns of data)
‘SF’: Total neutron emissions from spontaneous fission for primary salt (1 column of data) 
‘AN’: Total neutron emissions from (ɑ, n) for irradiated primary salt (1 column of data) 

The dataset is formatted as a HDF5 (Hierarchical Data Format) file that can be parsed using python libraries such as Pandas.
DOI: 10.17632/pycv47nk3p.1
title: An Integrated Dataset Providing a Landscape of the Italian Universities

description: We provide data describing the 78 largest Italian Universities from several perspectives, including scientific research, administrative and economic point of view. In particular, associated with each University, we have the following data.
 (a) The list of the 30 most representative research keywords, automatically extracted from titles, abstracts and other possible metadata of all the research publications available for that University in Scopus database at October 2022.
 (b) The Extended_name of the University, Status, University_Type, State_status, number of Managerial and Administrative Staff, Teaching Staff and Researchers, Phd Diplomas, Phd Enrollments, Enrolled Undergraduates, Enrolled Graduates, Graduates, Master I Lv Graduates, Enrolled Master's Degree I Lv, Master II Lv, Graduates Enrolled, Master II Lv, Graduates Specialistic Schools and Enrolled Specialistic Schools were extracted from USTAT database for the years 2016-2018.
 (c) The data of educational income, Income from Commissioned Research and Technology Transfer, Income from Research with competitive funding, Own Income, Contributions from others (private), Contributions from others (public), Contributions from universities, Contributions from the European Union and the Rest of the World, Contributions from other local governments, Contributions Regions and Autonomous Provinces, MIUR and other central government grants, Operating Costs, Current Management Costs, Managerial and administrative personnel costs, Research and teaching staff cost, Cost of Lecturers and Researchers, Cost Scientific Collaborators, Cost of Contract Teachers, Cost of Language Experts, Other research and teaching personnel costs, Personnel Costs, Scientific equipment, Concessions, licenses and trademarks, Patent rights are extracted from the unique University Balance Sheet of each university for the years 2016-2018.
 These data were of difficult availability; they have been extracted from several heterogeneous sources and have been automatically checked, cleaned from errors, integrated, missing values have been imputed as much as possible. However, due to large missing portions in the sources, they still contain several missing parts. 
 Nonetheless, they represent a powerful snapshot of the Italian Universities, and can be of interest to researchers for many analyses of the Italian academic world. All the sources of the openly available data are provided.
DOI: 10.17632/pycv47nk3p.2
title: An Integrated Dataset Providing a Landscape of the Italian Universities

description: We provide data describing the 78 largest Italian Universities from several perspectives, including scientific research, administrative and economic point of view. In particular, associated with each University, we have the following data.
 (a) The list of the 30 most representative research keywords, automatically extracted from titles, abstracts and other possible metadata of all the research publications available for that University in Scopus database at October 2022.
 (b) The Extended_name of the University, Status, University_Type, State_status, number of Managerial and Administrative Staff, Teaching Staff and Researchers, Phd Diplomas, Phd Enrollments, Enrolled Undergraduates, Enrolled Graduates, Graduates, Master I Lv Graduates, Enrolled Master's Degree I Lv, Master II Lv, Graduates Enrolled, Master II Lv, Graduates Specialistic Schools and Enrolled Specialistic Schools were extracted from USTAT database for the years 2016-2018.
 (c) The data of educational income, Income from Commissioned Research and Technology Transfer, Income from Research with competitive funding, Own Income, Contributions from others (private), Contributions from others (public), Contributions from universities, Contributions from the European Union and the Rest of the World, Contributions from other local governments, Contributions Regions and Autonomous Provinces, MIUR and other central government grants, Operating Costs, Current Management Costs, Managerial and administrative personnel costs, Research and teaching staff cost, Cost of Lecturers and Researchers, Cost Scientific Collaborators, Cost of Contract Teachers, Cost of Language Experts, Other research and teaching personnel costs, Personnel Costs, Scientific equipment, Concessions, licenses and trademarks, Patent rights are extracted from the unique University Balance Sheet of each university for the years 2016-2018.
 These data were of difficult availability; they have been extracted from several heterogeneous sources and have been automatically checked, cleaned from errors, integrated, missing values have been imputed as much as possible. However, due to large missing portions in the sources, they still contain several missing parts. 
 Nonetheless, they represent a powerful snapshot of the Italian Universities, and can be of interest to researchers for many analyses of the Italian academic world. All the sources of the openly available data are provided.
DOI: 10.17632/9gmhxx5t2g.4
title: Non-Pollen palynomorphs: Fungal spores and tissue of Caribbean mangroves, Southeastern Mexico

description: Fungal spores and tissue counts in Laguna Cementerio, Caribbean Sea Southeastern Mexico. Morphotypes named with ECO (El Colegio de la Frontera Sur) and numbering
DOI: 10.17632/k26f8rh58k.1
title: Reducing socioeconomic health inequalities? A questionnaire study of majorization and invariance conditions

description: This data accompanies the paper Rohde KIM, Van Ourti T, Soebhag A (2023). "Reducing socioeconomic health inequalities? A questionnaire study of majorization and invariance conditions", Journal of Health Economics, DOI: 10.1016/j.jhealeco.2023.102773. This paper runs a lab experiment in order to study the appeal of basic preference conditions that underpin health inequality indices, including the widely used concentration index. We provide the data and code that allow for replication of the results in the paper. The file Readmefirst.pdf provides more details of the raw source data Final_Data.xlsx. The file replication.do can be run in STATA and replicates all results presented in the paper. Please let us know if you intend to use our data or STATA code.
DOI: 10.17632/d66w74nzw8
title: LDHU3_20.0540

description: Cell cycle checkpoint protein RAD1-like
Leishmania donovani (HU3 strain)
DOI: 10.17632/d66w74nzw8.1
title: LDHU3_20.0540

description: Cell cycle checkpoint protein RAD1-like
Leishmania donovani (HU3 strain)
DOI: 10.17632/pnhcnk9thr
title: LDHU3_20.0530

description: NUDIX domain containing protein
Leishmania donovani (HU3 strain)
DOI: 10.17632/pnhcnk9thr.1
title: LDHU3_20.0530

description: NUDIX domain containing protein
Leishmania donovani (HU3 strain)
DOI: 10.17632/f6y5m7skz5.2
title: Predator's paradise

description: Large predators typically hunt relatively large prey with high failure rates and at high costs. In contrast, small predators generally hunt relatively small, abundant prey at lower failure rates, incurring relatively lower costs. Bats are small predators with high metabolic rates during flight and most species hunt large numbers of abundant, small insects. However, nine different bat species have evolved true carnivory, targeting large, less abundant vertebrate prey. This rare hunting style among bats raises the fundamental conundrum of how these very small predators with limited energy stores and high absolute energy requirements can successfully employ a hunting strategy that usually involves prolonged searching and high-energy chasing at low success rates. Here, we address this question by quantifying the hunting behavior of 20 wild carnivorous fringe-lipped bats (Trachops cirrhosus) with sound and movement biologging tags. We equipped 20 Trachops cirrhosus bats (8 females, 12 males) with sound- and movement- tags in March 2023 and in October 2023. The tags used in this study recorded continuous data for ~5.5 hrs during one night of foraging, amounting to the first half of the bats’ nightly activity periods. Recordings generally started with the bats’ activity period, either at emergence time (via a timer) when bats had been captured and tagged in their day roosts (9 bats) or at time of release, when bats had been captured and tagged during emergence (11 bats), therefore all recording intervals covered the onset of the foraging period. Audio data was recorded with an ultrasonic microphone (FG-3329; Knowles Electronics, Itaska, IL, USA) at a sampling rate of 187.5 kHz, with 16-bit resolution, a 10 kHz 1-pole analog high-pass filter, and a clipping level of 121 dB re 20 μPa pk. Movement data was recorded with triaxial accelerometers sampling at 1000 Hz with a clipping level of 8 g. All accelerometer data was calibrated, converted into acceleration units (m/s2), and decimated to 100 Hz. The orientation of the bats was recorded with triaxial magnetometers sampling at 50 Hz. 
Long mastication times of up to 84 minutes after a kill show that these bats can target prey as large as their own body size. Unlike much larger predators, they do so with extreme efficiency: the bats spent only a fraction of the night in flight (median 11%, quartiles 7-14%) and complemented short search and pursuit times with high rates of hunting success (50%, 35-62%), capitalizing on a combination of eavesdropping on prey sounds and hang-and-wait ambush predation. The unusual low-risk/high-gain strategy of these predatory bats critically relies on high prey densities in pristine ecosystems. The dwindling sizes of intact ecosystems and dramatic decline in biodiversity raise great concern for the Anthropocene fate of these specialized predators.
DOI: 10.17632/y6g5spmgrf
title: LDHU3_20.0720

description: Mitoribosomal protein bL19m
Leishmania donovani (HU3 strain)
DOI: 10.17632/y6g5spmgrf.1
title: LDHU3_20.0720

description: Mitoribosomal protein bL19m
Leishmania donovani (HU3 strain)
DOI: 10.17632/d5bcptxx83.1
title: The application of cell-free DNA methylation patterns in critical illnesses protocol

description: Raw data for Fig B
DOI: 10.17632/xnt7cn8mtp.1
title: Complete_database_microbiota_nematofauna_Heliconia

description: Data for the manuscript entitled "The microbiota and nematofauna associated with the rhizosphere of a tropical herb growing in conserved and altered forests"
DOI: 10.17632/j39dx362p3.1
title: VRRO User Engagement Survey Data

description: A sustainable smart tourism ecosystem relies on building digital networks that link tourists to destinations. This study explores how web and immersive technologies, such as the VRRO platform, can improve tourism by offering interactive experiences to augment traditional travel. An empirical study investigates user engagement and highlights how it promotes social interaction and user participation while adapting to the evolving tourism landscape.

Participants were provided with access to the VRRO platform and asked to interact with it for a comfortable duration. Post-interaction, participants completed the feedback questionnaire consisting of the demographic questions (age, prior engagement with such technologies, interest, platform of use), the short form of the UES, module-specific rating of platform functionalities, self-rating of users’ activity, future engagement prospects, and impressions (open-ended questions).

Rating or self-scoring questions’ answers are in the form of 5-point Likert scales, with values corresponding to the context. For example, ‘How often did you upload virtual tours’ would have the answers ‘Never’, ‘Once’, ‘Twice or thrice’, ‘Multiple times’, or ‘Often’. Their feedback is recorded and analyzed to draw insights.

The User Experience Survey can be accessed here: https://forms.gle/SZHCydVkhqfSk4yw6 
The VRRO platform can be accesed here: https://vrro.azurewebsites.net/ 
Raw, uninterpreted, clean answer data gathered from the VRRO User Experience Survey.
The survey contains: 6 demographic questions, 12 questions offering an overall rating of the platform with the short form of the User Engagement Scale (5-point Likert scale), 6 questions rating user satisfaction using specific modules of the platform (5-point Likert scale); 8 self-rating questions of the activity and interactions within the VRRO platform (equivalents of 5-point Likert scale); 4 questions on the preferred technological access of the platform and of the Virtual Tours module; 6 questions self-rating possible future engagement; and 5 open-ended questions focusing on VRRO's key functionalities and scope.

Description of the data and file structure:
The data is available in .XLSX and .CSV formats.
The first column header represents the timestamp of the submitted answer, and the following columns contain the survey questions and answers.
Each row corresponds to a different user entry.
DOI: 10.6084/m9.figshare.24619713
title: 04/11/2021 - Cheltenham Ladies College

description: 04/11/2021 - Cheltenham Ladies CollegeDelivery:x1 1 hour lecture on 'Colonialism and African Literature: Peter Abrahams' Mine Boy (1946)' plus Q&A (Jade Munslow Ong)15 students, 1 teacher.Data:Teacher Questionnaire
DOI: 10.17632/23ppcdbmhc.1
title: Dataset about VNU students

description: The dataset was constructed to manage students and factors affecting the learning outcomes of students at the University of Education - Vietnam National University, Hanoi, to meet the research needs. In this article, we present the value of the data, data description, design, materials and methods. We conducted a survey of students and alumni of the University of Education, Vietnam National University, Hanoi, from March to June 2023. There were 2170 students and alumni who responded to the link to answer the survey. Furthermore, in this article, we also mention the appendix, supplementary materials and research data. This dataset offers significant insights into the elements that drive student learning outcomes.