Find research datasets worth reusing

Credit Card Fraud Detection

The dataset from https://www.kaggle.com/datasets/mlg-ulb/creditcardfraud The dataset contains transactions made by credit cards in September 2013 by European cardholders. This dataset presents transactions that occurred in two days, where we have 492 frauds out of 284,807 transactions. The dataset is highly unbalanced, the positive class (frauds) account for 0.172% of all transactions.

opencc-zeroDec 2022View details →

Distinct latitudinal community patterns of Arctic marine vertebrates along the East Greenlandic coast detected by environmental DNA

Aim: Greenland is one of the places on Earth where the effects of climate change are most evident. The retreat of sea ice has made East Greenland more accessible for longer periods during the year. East Greenland fjords have been notoriously difficult to study due to their remoteness, dense sea ice conditions and lack of infrastructure. As a result, biological monitoring across latitudinal gradients is scarce in East Greenland and relies on sporadic research cruises and trawl data from commercial vessels. We here aim to investigate the transition in fish and marine mammal communities from South to Northeast Greenland using environmental DNA (eDNA). Location: South to Northeast Greenland. Methods: We investigated the transition in fish and marine mammal communities from South to Northeast Greenland using eDNA metabarcoding of seawater samples. We included both surface and mesopelagic samples, collected over approximately 2400 km waterway distance, by sampling from Cape Farewell to Ella Island in August 2021. Results: We demonstrate a clear transition in biological communities from south to northeast, with detected fish and mammal species matching known distributions. Samples from the southern areas were dominated by capelin (Mallotus villotus) and redfish (Sebastes), whereas northeastern samples were dominated by polar cod (Boreogadus saida), sculpins (Myoxocephalus) and ringed seal (Pusa hispida). We provide newly generated 12S rRNA barcodes from 72 fish species, bringing the public DNA database closer to full taxonomic coverage for Greenlandic fish species for this locus. Main conclusions: Our results demonstrate that eDNA sampling can detect latitudinal shifts in marine biological communities of the Arctic region, which can supplement traditional fish surveys in understanding species distributions and community compositions of marine vertebrates. Importantly, sampling of eDNA can be a feasible approach for detecting northward range expansions in remote areas as climate change progresses.

opencc-by-4.0Oct 2022View details →

A supramolecular cucurbit[8]uril-based rotaxane chemosensor for the optical tryptophan detection in human serum and urine

Dataset of the publication data. Raw and analyzed data included in each excel file.

opencc-by-4.0Dec 2021View details →

Scenarios used for the Validation of the Conflict Detection and Resolution Use Case (ARTIMATION )

This dataset contains the scenarios used for one of the validation of the ARTIMATION project: Conflict Detection and Resolution (CD&R) use case. It contains the validation exercice developped at ENAC using real flown data from 2016, and modifying it to respect our constraints. Inside, one can find: -The file "exo_artimation.txt" a file containing the whole scenario, that can be played using REJEU platform. -10 individual files, extracted from "exo_artimation.txt" containing conflicting aircrafts. Those files where used in other steps of the ARTIMATION project, notably in the solution dataset, the heatmatrix, heatmap, storyboard developped (all linked in related identifiers).

opencc-by-4.0Jun 2022View details →

Coccolithophore blooms days detected by MODIS Level-2 data in Algiers bay between 2003 and 2018

The figures illustrated in this document reflect the days where the coccolithophore blooms were detected for episodes shown in Figure 8 in Harid et al., (2023). The methodology used to produce these figures is described in Harid, (2022); Harid et al., (2023).   References: Harid, R. (2022). Étude par télédétection et mesures in-situ des efflorescences algales et de la matière en suspension dans le Bassin Algérien [PhD. thesis]. ENSSMAL, Algiers. Harid, R., Demarcq, H., Amanouche, S., Ait-Kaci, M., Bachari, N.-E.-I., & Houma, F. (2023). Detection of Coccolithophore Bloom Episodes in Algiers Bay Using Satellite and In Situ Analysis. In S. Niculescu (Éd.), European Spatial Data for Coastal and Marine Remote Sensing (p. 1‑15). Springer International Publishing. <a href="https://doi.org/10.1007/978-3-031-16213-8_1">https://doi.org/10.1007/978-3-031-16213-8_1</a>

Detection of SARS-CoV-2 variants by genomic analysis of wastewater ampliconic samples (Galaxy Training Material)

The tutorial aims to train how to run workflows to analyze lineages abundances in SAR-CoV-2 wastewater ampliconic samples. (https://training.galaxyproject.org/training-material/)

Detection of SARS-CoV-2 variants by genomic analysis of wastewater metatranscriptomic samples (Galaxy Training Material)

The tutorial aims to train how to run workflows to analyze lineages abundances in SAR-CoV-2 wastewater metatranscriptomic samples. (https://training.galaxyproject.org/training-material/)

opencc-zeroDec 2021View details →

Data from: A surface acoustic wave (SAW)-based lab-on-chip for the detection of active α-glycosidase

Enzyme detection in liquid samples is a complex laboratory procedure, based on assays that are generally time- and cost-consuming, and require specialized personnel. Surface acoustic wave sensors can be used for this application, overcoming the cited limitations. To give our contribution, in this work we present the bottom-up development of a surface acoustic wave biosensor to detect active α-glycosidase in aqueous solutions. Our device, optimized to work at an ultra-high frequency (around 740 MHz), is functionalized with a newly synthesized probe 7-mercapto-1-eptyl-D-maltoside, bringing one maltoside terminal moiety. The probe is designed ad hoc for this application and tested in-cuvette to analyze the enzymatic conversion kinetics at different times, temperatures and enzyme concentrations. Preliminary data are used to optimize the detection protocol with the SAW device. In around 60 min, the SAW device is able to detect the enzymatic conversion of the maltoside unit into glucose in the presence of the active enzyme. We obtained successful α-glycosidase detection in the concentration range 0.15–150 U/mL, with an increasing signal in the range up to 15 U/mL. We also checked the sensor performance in the presence of an enzyme inhibitor as a control test, with a signal decrease of 80% in the presence of the inhibitor. The results demonstrate the synergic effect of our SAW Lab-on-a-Chip and probe design as a valid alternative to conventional laboratory tests.

Mode structure reconstruction by detected and undetected light: data sets

Data sets related to the multimode optical field reconstructions reported in manuscript <a href="https://arxiv.org/abs/2212.13873v1">arXiv:2212.13873v1</a>

Supplementary Materials for "An Automated Detection of Confusing Variable Pairs with Highly Similar Compound Names in Java and Python Programs"

This is a dataset contains the data collected through the empirical study in our paper "An Automated Detection of Confusing Variable Pairs with Highly Similar Compound Names in Java and Python Programs."

opencc-zeroDec 2021View details →

Data from: Surface Acoustic Wave-based Lab-On-a-Chip for the fast detection of Legionella pneumophila in water

Surface acoustic wave (SAW) -based immuno-biosensors are used for several applications, thanks to their versatility and faster response than conventional analytical methods. SAW immuno-biosensors can be usefully applied to promptly detect bacteria and prevent bacterial infections that can lead to severe diseases. Here, we present a SAW immuno-biosensor to detect Legionella pneumophila in water. Our device, working at ultra-high frequency (740 MHz), is functionalized with an anti-L. pneumophila antibody to maximize the specificity. We report the characteristic curve of the sensor, calculated measuring bacterial samples at known densities, and its related parameters. We also measure L. pneumophila samples contaminated with different Gram-positive and Gram-negative bacterial species (Escherichia coli and Enterococcus faecium) and samples diluted in mains waters. The proposed device is able to detect L. pneumophila in the range from 1×106 to 1×108 CFU/mL, with a limit of blank of 1.22×106 CFU/mL and a limit of detection of 2.01×106 CFU/mL. The nonspecific signal due to contaminant bacteria is very limited and measurements of L. pneumophila are not affected by contamination. We obtain a good detection also in mains water, representing a realistic matrix for L. pneumophila. Our results are encouraging and pave the way to the use of fast, easy-to-use, reliable and precise sensors to prevent bacterial infections in human activities.

opencc-zeroJan 2023View details →

A longitudinal study of DNA and RNA viruses plasma detection in allogeneic hematopoietic stem cell transplant recipients

Background: Viral infections are among the most common complications after allogeneic hematopoietic stem cell transplantation (allo-HSCT) and can be associated with transient or sustained viremia. Besides viruses that are common causes of infection, metagenomics revealed the presence of several novel viruses and variants that are overlooked in clinical routine and represent potential sources of unrecognized systemic infections. Our aim was to describe the prevalence and the dynamics of 17 DNA and 3 RNA viral infections using (r(RT-)PCR) assays on plasma samples of adult allo-HSCT recipients over a one-year period after HSCT. Methods: 109 adult patients that received a first allo-HSCT from 1st March 2017 to 31st January 2019 we included in this longitudinal observational monocentric cohort study. 17 DNA and 3 RNA viral species were screened with qualitative and/or quantitative r(RT)-PCR assays performed on plasma samples collected at five time-points (day 0 and 30 days, 3 months, 6 months and one year after HSCT). Results: TTV was the most prevalent with an increasing prevalence to 96% of patients at 3 months. HPgV-1 prevalence ranged from 26 to 36% of patients. TTV and HPgV-1 plasma viral load peaked at month 3 (TTV: median 3.29E5 copies/ml [range, 3.37E2 to 4.06E9 copies/ml]; HPgV-1: median 1.18E6 copies/ml [range, 2.61E3 to 4.49E7 copies/ml]). Among Polyomaviridae, BKPyV, JCPyV, MCPyV, HPyV6 and 7 were detected in ≥10% of patients at ≥1 time-point. HPyV6 and HPyV7 prevalence reached 27% and 12% of patients at month 3. Among those, 41% and 63% had quantifiable viral loads, with median viral loads above 1E3copies/ml and results may suggest HPyV6 sustained viremia. Co-detections were frequent, in particular at 3 months with ≥2 viruses detected in 72% of patients. Conclusion: Our study confirms that TTV and HPgV-1 infections are highly prevalent and that infection may be sustained up to one year after allo-HSCT. Our systematic and large strategy of screening also revealed diverse and numerous co-detections, and that several novel Polyomaviridae (MCPyV, HPyV6/7) that are overlooked in clinical routine are as or more frequently detected compared to classical culprits. Our results underscores the need for further studies investigating the clinical impact of classical culprits together with other viruses in particular novel Polyomaviridae and HPgV-1.

opencc-by-4.0Sep 2022View details →

Impact ionization dust detection with compact, hollow and fluffy dust analogs

Datasets for the Planetary and Space Science article "Impact ionization dust detection with compact, hollow and fluffy dust analogs" (DOI: 10.1016/j.pss.2022.105536). The data contains two folders for dust impacts on the IIT and CAT targets of CDA. The folders contain separate tables with data for each run. Each table shows the registered CDA impacts for the corresponding run with impact time in UTC (determined by CDA) and all additional information about the impact that could be reconstructed from the measurements of CDA and other detectors (impact velocity, dust mass, ...). Data that could not be reconstructed are represented by NAN values in the tables.

opencc-by-nc-4.0Jan 2023View details →

CottonWeedDet12: a 12-class weed dataset of cotton production systems for benchmarking AI models for weed detection

The dataset CottonWeedDet12 consists of 5648 RGB images of 12-class weeds that are common in cotton fields in the southern U.S. states, with a total of 9370 bounding boxes. These images were acquired by either smartphones or hand-held digital cameras, under natural field light condition and throughout June to September of 2021. The images were manually labeled by qualified personnel for weed identification, and the labeling process was done using the VGG Image Annotator (version 2.10). The dataset, at the time of publication, is the largest publicly available multi-class dataset dedicated to weed detection. It expects to facilitate communicate efforts to exploit state-of-the-art deep learning method to push weed recognition to the next level. With the WeedDet12 dataset, a performance benchmark of a suite of YOLO object detectors has been built for weed detection. Detailed documentation of the dataset, model benchmarking and performance results is given in an accompanying journal paper: <a href="https://www.sciencedirect.com/science/article/pii/S0168169923000431">Dang, F., Chen, D., Lu, Y., Li, Z., 2023. YOLOWeeds: A novel benchmark of YOLO object detectors for multi-class weed detection in cotton production systems. Computers and Electronics in Agriculture 205, 107655. https://doi.org/10.1016/j.compag.2023.107655</a><a href="https://doi.org/10.1016/j.compag.2023.107655"> </a> If you use the dataset on a published publication, please cite the dataset or the <a href="https://doi.org/10.1016/j.compag.2023.107655">journal article</a> above.

opencc-zeroJan 2023View details →

Parasite detection and quantification in avian blood is dependent on storage medium and duration

Studies of parasites in wild animal populations often rely on molecular methods to both detect and quantify infections. However, method accuracy is likely to be influenced by the sampling approach taken prior to nucleic acid extraction. Avian Haemosporidia are studied primarily through the screening of host blood, and a range of storage mediums are available for the short- to long-term preservation of samples. Previous research has suggested that storage medium choice may impact the accuracy of PCR-based parasite detection, however, this relationship has never been explicitly tested and may be exacerbated by the duration of sample storage. These considerations could also be especially critical for sensitive molecular methods used to quantify infection (qPCR). To test the effect of storage medium and duration on Plasmodium detection and quantification, we split blood samples collected from wild birds across three medium types (filter paper, Queen's lysis buffer, and 96% ethanol) and carried out DNA extractions at five time-points (1, 6, 12, 24 and 36 months post-sampling). First, we found variation in DNA yield obtained from blood samples dependent on storage medium which had subsequent negative impacts on both detection and estimates of Plasmodium copy number. Second, we found that detection accuracy (incidence of true-positives) was highest for filter paper stored samples (97%), while accuracy for ethanol and Queen's lysis buffer-stored samples was influenced by either storage duration or extraction yield respectively. Lastly, longer storage durations were associated with decreased copy number estimates across all storage mediums; equating a 58% reduction between the first- and third-year post-sampling for lysis-stored samples. These results raise questions regarding the utility of standardising samples by dilution, while also illustrating the critical importance of considering storage approaches in studies of Haemosporidia comparing samples subjected to different storage regimes and/or stored for varying lengths of time.

Mass spectrometry- based biomarkers to detect prostate cancer: A multicentric study based on non- invasive urine collection without prior intervention

These are datasets related to mass spectrometry proteomics analysis, in particular Capillary Electrophoresis coupled to Mass Spectrometery (CE-MS). CE-MS was employed to acquire proteomics profiles from 970 patients from two different clinical centers. with the aim to develop a biomarker model to detect Prostate Cancer.

opencc-by-4.0Feb 2023View details →

Records used to compare duplicate detection of three systematic review screener tools

This upload contains records obtained from PubMed, Scopus and Web of Science that were used to compare the sensitivity of the duplicate detection systems of three systematic review screening tools, as well as a custom-made dataset to evaluate the detection of duplicates under various scenarios.

opencc-by-4.0Oct 2022View details →

3D sympathetic cooling and detection of levitated nanoparticles

Dataset for the paper 3D sympathetic cooling and detection of levitated nanoparticles

opencc-by-4.0Feb 2023View details →

data from "Temperate bats may alter calls to partially compensate for weather-induced changes in detection distance"

Echolocation call parameters of three species of European bats collected between 2017-2019, recorded with a microphone array. This dataset is associated to the manuscript "Temperate bats may alter calls to partially compensate for weather-induced changes in detection distance". Included is the R script used for statistical analyses, as well as the R script used to model detection distances of different targets by bats across weather conditions.