cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.7710575.v1
title: Zooplankton community attributes in an oligo-mesotrophic reservoir: A comparative study of two sampling strategies

description: Abstract Studies of the limnetic zooplankton in Brazilian freshwater have been done using several sampling strategies which are frequently associated to personal preferences, system constraints and objectives of the studies. It is known that a better sampling technique exists for each group of investigated zooplankton. So, the challenge is to provide a good sampling method for all groups at once. Regarding this theme we are contributing by pointing out the merits and demerits of two collecting methods of zooplankton widely used in many studies in Brazilian reservoirs to clarify the information about communities’ structure in past published and non-published biological data and also find a more useful sampler for future studies. Two simultaneous strategies were used with a 68μm-plankton net: filtration of water collected at sub-surface by bucket and vertical hauls throughout the euphotic zone. A total of 133 taxa was found with both strategies. Rotifers (69 taxa) comprised the group with the highest richness, followed by protozoans (31 taxa), cladocerans (30 taxa) and copepods (5 taxa). Paired t-tests showed significant difference for richness despite none for density in whole period. Spatially, sampling strategies differed in abundance and composition of zooplankton at most sites sampled (except for L1- shallowest site and L4 – deepest site). Temporally, both samplers showed the highest mean abundances at thermal stratification period. In general, the extent of spatial data collected throughout the vertical gradient provided better estimations in the limnetic area for the attributes analyzed: zooplankton density, richness, specific diversity, equitability and cumulative richness. Zooplankton sampling by vertical hauls through the euphotic zone was more efficient, but in order to obtain integrated data and according to the collector’s curve it might be useful to adopt both methodologies.
DOI: 10.17632/wpb2f53r9r
title: Impact of COVID-19 on melanoma

description: The impact of COVID-19 in 2020 on the diagnosis, treatment, and outcomes of invasive cutaneous melanoma: a retrospective national cohort study
DOI: 10.15468/dl.sghp79
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Argentina Linnaeus, 1758",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((54.1341 -16.2111,54.4917 -16.3924,54.8913 -16.2339,54.9312 -16.1504,54.1138 -16.1504,54.1341 -16.2111))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012866-250525065834625/datasets/export for details.
DOI: 10.6084/m9.figshare.26047975.v1
title: Research data on changes in strength performance of highly trained athletes after COVID-19

description: The data in this database pertains to the basic information of athletes and their strength performance test data related to the study of "changes in strength performance of highly trained athletes after COVID-19."
DOI: 10.17632/r5sk6z3v9k
title: Data for: Microscopy-spectroscopy SI: high spatiotemporal resolution data from a custom magnetic tweezers instrument

description: The three-dimensional bead position was acquired using a MT setup interfaced using custom Labview 2016 routines. Frame numbers, time stamp and x,y,z positions of the beads were saved as a tab delimited .txt file (raw data). When force was applied during the measurement, two more .txt files were generated: one describing the magnet position and the residence time at each position and a second containing a time stamp of magnet movement. Data were analyzed and plotted using Python.
DOI: 10.17632/f3ftpd7xpg
title: MABSA: Malayalam Aspect Based Sentiment Analysis Dataset

description: MABSA is a curated aspect-based sentiment analysis dataset on the South Indian language Malayalam over the movie review domain. This dataset contains 4000 movie reviews in Malayalam and its sentiment labels for nine target aspects: direction, acting, songs, screenplay, story, casting, editing, cinematography, and BGM (background music). Each aspect in the review is mapped to one of the three sentiment classes, which are positive, negative, or neutral. These three sentiment classes are numerically represented as 1, 0, and 0.5, respectively. Movie reviews in Malayalam are collected through two methods, where the first method uses the Google survey tool to collect reviews from people, and the second method manually gathers movie reviews from various pages and groups on different social media platforms like Facebook, YouTube, and IMDb. The MABSA dataset consists of 4000 Malayalam movie reviews and a total of 5707 aspects manually annotated with its sentiment orientation. Dataset files include both with and without English translations of Malayalam movie reviews. A copy of the Google form file is attached along with the MABSA dataset.
DOI: 10.17632/pwm6cg2shj
title: In situ real-time dataset as compared to the predicted thermal wheel performance of an energy recovery system

description: The experimental dataset of a rotary desiccant wheel system in a Taoyuan hotel contains the ambient conditions and dehumidified process air outputs, as well as comparisons of experimental and numerical outputs under various operating conditions. Physical implementation of the experiments for numerical validation of transient responses included step changes to the regeneration air temperature, wheel speed, and airflow rate (i.e. fan speed). The related data article provides insights to optimal performance of thermal wheel operation for HVAC practitioners and academic researchers.


Supplementing to this data article are eight dataset files pertaining to ambient conditions and dehumidified process air outputs, as well as comparisons of experimental and numerical outputs under various operating conditions. Physical implementation of the experiments for numerical validation of transient responses included step changes to the regeneration air temperature, wheel speed, and airflow rate (i.e. fan speed). Finally, the data article provides insights to optimal performance of thermal wheel operation for HVAC practitioners and academic researchers.
DOI: 10.6084/m9.figshare.25105742.v1
title: Mean Data.xlsx

description: <b>Improving the Productivity of Common</b> <b>Bean</b><b> </b><b>(</b><i>Phaseolus Vulgaris</i> L<b>.)</b><b> </b><b>Using the Optimum Blended Inorganic Fertilizer Rate Recommendation</b>
DOI: 10.17632/m83zjmth44
title: Export Tax Rebates, Product Ranking, and Exports of Multi-Product Firms

description: This study relies predominantly on the following three datasets covering the 2002–2013 period: customs transaction-level data, firm-level information, and product-level data on export tax rebate rates. Customs transaction-level data collected by the General Administration of Customs of China are monthly data at the Harmonized System (HS) 8-digit level, which are aggregated into annual data and unified to the HS 6-digit level. Firm-level information is provided in detail by the ASIF. Following Brandt et al. (2012), we match customs and ASIF data using information such as the year, firm name, postal code, and telephone number. Product-level data on export tax rebate rates are available from the China Export Tax Rebate Advisory Network. In this study, we match product-level export tax rebate rates with customs trade data based on HS codes and city names.
DOI: 10.17632/hvwyz5yhh2
title: Four-channel radio-frequency signal generator programmed by an open-source Arduino-based control system via single or quad Serial Peripheral Interface

description: Radio-frequency (RF) signal generators are standard laboratory equipment and a wide-range of open-source and commercial devices exists to address their many applications. Nonetheless, only few expensive and proprietary solutions can be re-configured within a wide frequency band and triggered on a micro-second timescale. Such specifications are required for applications that leverage variable radio-frequencies to generate programmed mixed signals, to control processes or states and to precisely steer laser beams using acousto-optical devices, tasks often needed in industrial manufacturing, atomic and molecular physics or microscopy.
Here we present an open-source low-cost Arduino-based control system that can store up to millions of commands received from a computer and then perform reliable high-speed programming of an arbitrary device under its control (DUC) via a single or quad-wire Serial Peripheral Interface. The software architecture operates as a real-time state machine, making it easily extensible and adaptable to any DUC. Each configuration change can be triggered either externally or internally, reaching 1 MHz rates when using a Teensy 4.1 Arduino-compatible board. Leveraging this flexible system, we developed a programmable four-channel RF signal generator, based on an Analog Devices 9959 Evaluation board, and we demonstrated its capability and validated its performance.
DOI: 10.17632/6j8db5fmv9
title: Romanian BET index vs. USA, WE, CEE

description: The dataset contains index values for BET, and major indices from the USA (NASDAQ, S\&P500, DIJA), Western Europe (FTSE100, CAC40, DAX) and Central and Eastern Europe (ATX,BUX, WIG20).
DOI: 10.17632/mmstgynxcp
title: data forThe Changed Functional Status of the Brain was Involved in Patients with Post-stroke Aphasia: Coordinate-Based (ALE) Meta-Analysis

description: all focies were involved in comparison between HC &gt;PSA and HC
DOI: 10.6084/m9.figshare.4982618.v1
title: One-trial Memory Data from What makes specialized food-caching mountain chickadees successful city slickers?

description: Raw data for the one-trial spatial memory acquisition experiment
DOI: 10.17632/tc5tnchrs2
title: Semaphore Flag Signaling Dataset

description: This is a Semaphore Flag Signaling Dataset prepared by Midshipmen of Naval Academy. It includes 20 samples for each semaphore flag in the English alphabet, taken by 4 different persons
DOI: 10.17632/jb7w4452pg
title: Lychee Leaf Disease Dataset: Advancing Agriculture and Sustainability through Machine Learning-Based Diagnosis

description: The Lychee Leaf Disease Detection Dataset is a carefully collected dataset aiming to promote research, exploration and application in agriculture. This diagnostic mini-tool enables researchers, agricultural experts, and stakeholders to precisely identify and manage lychee leaf diseases. This dataset facilitates early and accurate detection, allowing farmers to take timely action, optimize crop management practices, and improve agricultural productivity. Also, it provides a reference point for comparisons of existing and new machine learning models to inspire and motivate new methods for disease detection. This dataset comprises 3,768 original lychee leaf images labelled as one of the following condition classes: Anthrax Leaf, Bituminous Leaf, Curl Leaf, Deficiency Leaf, Dry Leaf, Felt Leaf, Fungal Leaf Spot, Healthy Leaf, Leaf Blight, and Leaf Gall.

The images were captured during field surveys conducted between June 2024 and December 2024 in Melandaha, Jamalpur, and Gazaria, Munshiganj. Using Redmi Note 11s and iPhone 14 Plus smartphones, the dataset reflects diverse environmental conditions, including variations in lighting and field settings. Expert guidance ensured the collection of high-quality images that authentically represent real-world scenarios, addressing potential challenges such as environmental variability.

To enhance its utility for machine learning applications, data augmentation techniques—including flipping, brightening, and rotation—were applied, expanding the dataset to 10,000 augmented images. These augmented samples significantly strengthen the dataset's robustness, facilitating the development of accurate and reliable models for disease detection and classification.

Key Features of the Dataset

Original Dataset:
Number of Images: 3,768
Format: .jpg

Augmented Dataset:
Number of Images: 10,000
Format: .jpg

This dataset offers a foundational resource for agricultural research, serving as a reliable benchmark for machine learning-based disease classification systems. It provides an unparalleled opportunity to enhance precision in lychee leaf disease detection and advance the field of agricultural informatics.
DOI: 10.17632/42z8st838w
title: Corn ear images of five varieties

description: There are a total of 6529 corn ear images, from 5 different corn varieties, with a pixel size of 500*500, PNG format, and RGB three channels. They were taken in a laboratory environment, using a Canon 80D camera, and then processed using Python's PIL library. All images have a black background. This data set can be used to study corn variety classification and identification.
DOI: 10.17632/k2gj4pssyr
title: Cyberattacks Patterns in Blockchain-Based Communication Networks for Distributed Renewable Energy Systems: A study on datasets

description: The data presented in the article provides various types of cyberattacks in blockchain-based communication networks for distributed renewable energy systems, including
• The scientific community in the field of cybersecurity, more specifically cybersecurity in the distributed renewable energy systems can benefit from these datasets by using them in various smart grid applications. 
• The scientific community by using the rarely available cybersecurity datasets can classify the normal and abnormal behavior of systems involved in the power generation, transmission, and distribution process. 
• The cybersecurity datasets analysis could help researchers to predict various types of cyberattack patterns in terms of frequency and continuity in the micro renewable energy systems. This definitely will help anomaly detection and mitigation in the system. 
• The cybersecurity and smart grid agencies with other stakeholders can in particular use these data to develop a more smart and resilient communication network to prevent various kinds of cyberattacks to protect employees, organizations, or customers’ privacy. 
• The datasets can be enriched with semantics annotated by cybersecurity experts to maintain the trust, credibility, and access control of the remote systems from cyberattacks in various fields such as e-health, e-transportation, e-agriculture, and many others.
DOI: 10.5061/dryad.72h4m
title: Data from: Repeated trans-watershed hybridisation among haplochromine cichlids (Cichlidae) was triggered by Neogene landscape evolution
DOI: 10.17632/xgxtz635mx
title: Top++: A program for the calculation of the top-pair cross-section at hadron colliders

description: This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2018) Abstract We present the program Top++ for the numerical evaluation of the total inclusive cross-section for producing top quark pairs at hadron colliders. The program calculates the cross-section in (a) fixed order approach with exact next-to-next-to leading order (NNLO) accuracy and (b) by including soft-gluon resummation for the hadronic cross-section in Mellin space with full next-to-next-to-leading logarithmic (NNLL) accuracy. The program offers the user significant flexibility through the large n... Title of program: Top++ (ver. 2.0) Catalogue Id: AETR_v1_0 Nature of problem Computation of the total cross-section in perturbative QCD. Versions of this program held in the CPC repository in Mendeley Data AETR_v1_0; Top++ (ver. 2.0); 10.1016/j.cpc.2014.06.021
DOI: 10.17632/ncvfr2trwb
title: Covid-19 Go Away 2020 (C-19GA20)

description: The C-19GA20 dataset was gathered online in April 2020 from school and university students between 14 to 24 years of age. It provides insightful information about the students’ mental health, social lives, attitude towards Covid-19, impact of the Covid-19 Pandemic on students’ education, and their experience with online learning. The data includes 5 major groups of variables: 1) Socio-demographic data - age group, gender, current place of stay, study level in their institution 2) 4 items for information regarding connectivity to the internet during the lockdown - device availability for exclusive use, internet bandwidth, top 5 online tools used most commonly, and screen time. 3) 9 items measured the impact of Covid-19 on the students’ social lives - their current situation of living, number of people around them where they live, their feelings towards meeting their friends, visiting their institution of study, events that would have been held offline. Students were asked about their top 5 past time activities during the lockdown and the amount of time they spend on social media online. 4) 6 items to gauge their experience with online learning during the lockdown - questions about feeling connected to their peers, maintaining discipline, structured learning, and the stress/burden felt by them due to online learning in the lockdown 5) 11 items to comprehensively gather information about the students’ mental health - how well have they adapted to stay-at-home instructions, their overall mood in the lockdown, feelings towards Covid 19, their prime concerns regarding their academic schedule, being updated and informed about Covid 19, the impact of social media on their beliefs. Finally, the students were asked to write about how they feel the pandemic has changed them as a person and affected their thinking process, and the students were asked to share a one-line message for the world during the lockdown.
DOI: 10.17632/drx5nc3hr4
title: Automating the GDPR Compliance Assessment for Cross-border Personal Data Transfers in Android Applications

description: This repository contains data supporting the study on automation of GDPR Compliance Assessment for Cross-border Personal Data Transfers in Android Applications. Please read the associated paper for a full understanding of this data.
DOI: 10.17632/r7tjn68rmw
title: Soil data Grevena

description: In this dataset there are soil data analyses with properties such as pH, organic matter (OM), salinity (EC), etc., major elements (N, P, K, Mg) as well as some microelements (Fe, Zn, Mn, Cu, B) with significant impact on plant nutrition.
DOI: 10.17632/7nz28t26p5
title: Coulomb wave functions in momentum space

description: Abstract An algorithm to calculate non-relativistic partial-wave Coulomb functions in momentum space is presented. The arguments are the Sommerfeld parameter η, the angular momentum l, the asymptotic momentum q and the 'running' momentum p, where both momenta are real. Since the partial-wave Coulomb functions exhibit singular behavior when p→q, different representations of the Legendre functions of the 2nd kind need to be implemented in computing the functions for the values of p close to the singular... Title of program: libcwfn Catalogue Id: AEUQ_v1_0 Nature of problem The calculation of partial wave Coulomb functions with integer l and all other arguments real. Versions of this program held in the CPC repository in Mendeley Data AEUQ_v1_0; libcwfn; 10.1016/j.cpc.2014.10.002 This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2018)
DOI: 10.6084/m9.figshare.14054861.v1
title: Social anxiety, maladaptive cognition, mobile phone addiction, and perceived social support：A moderated mediation model.sav

description: Social anxiety, maladaptive cognition, mobile phone addiction, and perceived social support：A moderated mediation model
DOI: 10.17632/czhfj4g6vb
title: Markov chain models for tissue regulatory T cell cellular kinetics and dwell times

description: CD45.1 mice were parabiosed to CD45.2 mice. Pairs of parabiotic animals were sacrificed and perfused at weeks 1, 2, 4, 8, and 12 for tissue analysis by flow cytometry (n=11,12,18,16,14). Markov chains were built to model the changes in cell state and tissue exchange, with each tissue built using a model containing the tissue, blood, and combined other tissues. Full code for analysis: https://github.com/gergelits/markov_chain_tissue_treg
DOI: 10.17632/f7g3w4z8jn
title: The Dataset of Drug Addictors of Dinajpur Town of Bangladesh

description: Of the 200 participants, 158 (79%) were male and 42 (21%) were female. The mean age of these people is about 14.97 years. The minimum age is 13 years, and the highest age is 17 years. 22 students (11%) had a history of Bangla addiction; 34 students (17%) had a cannabis addiction, 78 fencidyle (39%) and 66 students (33%) had a YaBa addiction. Of the 200 students, 30 (15%) were from class seven, 48 (24%) from class eight, 53 (26.5%) from class nine, and 69 (34.5%) from class ten. 10% are danger zones
DOI: 10.17632/2nwp98mt5n
title: Data for: Stable isotopes verify geographical origin of Yak meat from Qinghai-Tibet Plateau

description: Supplementary Data
DOI: 10.17632/62rw2j25gx
title: Accelerating forest tree breeding by integrating genomic selection and greenhouse phenotyping

description: The dataset is in a R file containing the adjusted phenotypes and the genomic relationship of 473 Populus deltoides genotypes
DOI: 10.17632/6h4gtrzgdc
title: Supplemental Data

description: Efficacy and safety of switching from dupilumab to upadacitinib versus continuous upadacitinib in moderate-to-severe atopic dermatitis: results from an open-label extension of the phase 3, randomized, controlled trial (Heads Up)
DOI: 10.17632/kn3x9rz3kd
title: Air Quality dataset for ADL classification

description: The variation in indoor gas concentration over time is monitored and data is stored in order to use this information to evaluate the type of activity carried out in the room. Thanks to the use of artificial intelligence, a quantitative approach in determining the gas concentration was avoided, which would have required careful calibration of the sensors. The dataset contains the values ​​acquired by an array of 6 low cost sensors in successive instants of time, and the stored values ​​are associated with the particular action that generated them. Through an appropriate data processing, based on machine learning algorithms, after an initial training phase it is possible to recognize the actions that are carried out inside the home. The presence of chemicals in the air is determined through a series of electrochemical gas sensors that have been selected based on the stated technical specifications on the ability to detect classes of compounds. The sensor set can be grouped into two main categories: - MQ sensors (MQ2, MQ9, MQ135, MQ137, MQ138) which have great sensitivity, low latency and low cost; each sensor can respond to different gases; - Analog CO2 gas sensor (MG-811) which has excellent sensitivity to carbon dioxide and is scarcely affected by the temperature and humidity of the air. The dataset contains 1845 collected samples describing 4 target situations: 1 - Normal situation - Activity: clean air, a person sleeping or studying or resting - Samples: 595; 2 - Preparing meals - Activities: cooking meat or pasta, fried vegetables. One or two people in the room, forced air circulation - Samples: 515. 3 - Presence of smoke - Activity: burning paper and wood for a short period of time in a room with closed windows and doors - Example: 195. 4 - Cleaning - Activity: use of spray and liquid detergents with ammonia and / or alcohol. Forced air circulation can be activated or deactivated - Samples: 540. Each sample is made up of 7 values; the first six values ​​are the sensor outputs, while the last is the index of the action that generated the values ​​acquired by the sensors. The four different situations are associated with a fairly different composition of the air, taking into account that any activity produces chemical substances due, that is, to human respiration, to the exhalations of metabolic processes, to the release of volatiles by combustion and / or oxidation, and evaporation of household detergents.