Find research datasets worth reusing

opencc-by-nc-4.0Mar 2024View details →

Dataset of Recordings of Enteric Neural Activity using Implantable Bioelectronics (I)

Open the record for dataset details and reuse information.

opencc-by-4.0Oct 2021View details →

Active repair of a dinuclear photocatalyst for visible light-driven hydrogen production

The peer-reviewed publication for this dataset has been published in Nature Chemistry and can be accessed via <a href="https://doi.org/10.1038/s41557-021-00860-6"> DOI 10.1038/s41557-021-00860-6</a>. Please cite this when using the data.

opencc-zeroOct 2021View details →

Activation of autophagy during normothermic machine perfusion of discarded livers is associated with improved hepatocellular function

We demonstrate that ischemia-reperfusion injury occurs in all livers during NMP, though there are notable differences in gene expression between functional and nonfunctional livers. We further demonstrate that activation of the liver's repair and homeostasis mechanisms through autophagy plays a vital role in the graft's response to injury and may impact liver function. These findings indicate that liver autophagy might be a key therapeutic target for rehabilitating the function of severely injured or untransplantable livers.

opencc-by-4.0Dec 2020View details →

Long short-term memory (LSTM) recurrent neural network for muscle activity detection

Background: The accurate temporal analysis of muscle activation is of great interest in many research areas, spanning from neurorobotic systems to the assessment of altered locomotion patterns in orthopedic and neurological patients and the monitoring of their motor rehabilitation. The performance of the existing muscle activity detectors is strongly affected by both the SNR of the surface electromyography (sEMG) signals and the set of features used to detect the activation intervals. This work aims at introducing and validating a powerful approach to detect muscle activation intervals from sEMG signals, based on long short-term memory (LSTM) recurrent neural networks.   Methods: First, the applicability of the proposed LSTM-based muscle activity detector (LSTM-MAD) is studied through simulated sEMG signals, comparing the LSTM-MAD performance against other two widely used approaches, i.e., the standard approach based on Teager–Kaiser Energy Operator (TKEO) and the traditional approach, used in clinical gait analysis, based on a double-threshold statistical detector (Stat). Second, the effect of the Signal-to-Noise Ratio (SNR) on the performance of the LSTM-MAD is assessed considering simulated signals with nine different SNR values. Finally, the newly introduced approach is validated on real sEMG signals, acquired during both physiological and pathological gait. Electromyography recordings from a total of 20 subjects (8 healthy individuals, 6 orthopedic patients, and 6 neurological patients) were included in the analysis. Results: The proposed algorithm overcomes the main limitations of the other tested approaches and it works directly on sEMG signals, without the need for background-noise and SNR estimation (as in Stat). Results demonstrate that LSTM-MAD outperforms the other approaches, revealing higher values of F1-score (F1-score > 0.91) and Jaccard similarity index (Jaccard > 0.85), and lower values of onset/offset bias (average absolute bias < 6 ms), both on simulated and real sEMG signals. Moreover, the advantages of using the LSTM-MAD algorithm are particularly evident for signals featuring a low to medium SNR. Conclusions: The presented approach LSTM-MAD revealed excellent performances against TKEO and Stat. The validation carried out both on simulated and real signals, considering normal as well as pathological motor function during locomotion, demonstrated that it can be considered a powerful tool in the accurate and effective recognition/ distinction of muscle activity from background noise in sEMG signals.

opencc-by-2.0Nov 2021View details →

Personal Online Dosimetry Using Computational Methods: The PODIUM Project and the Future of Active Dosimetry

Individual monitoring of workers exposed to external ionizing radiation is essential to allow application of the ALARA principle and follow up of the official dose limits. However, large uncertainties still exist in personal dosimetry. Also, many practical problems exist for personal dosimetry, with many dosemeters getting lost and the reluctance of many workers to wear one or more dosemeters. Most legal dosimetry is done with passive dosemeters, which are analyzed after the wearing period in an accredited lab. Active dosemeters are also widely used, although mostly only for ALARA purposes or for specific exposure situations. Although the active dosemeters are dosimetrically and technically at least equivalent to passive dosemeters, their higher cost limits their use as only legal dosemeters. In an attempt of reinventing dosimetry by using the modern evolutions in simulations, artificial intelligence and computer vision, the PODIUM project was set up. PODIUM was a short feasibility project, funded by the EC CONCERT programme. The objective of the PODIUM project was to improve personal dosimetry by an innovative approach: the development of an online dosimetry application based on computer simulations without the use of physical dosemeters. Operational quantities, protection quantities and radiosensitive organ doses (e.g. eye lens, brain, heart, extremities) can be calculated based on the use of modern technology such as personal tracking devices, flexible individualized phantoms and scanning of geometry set-up. When combined with fast simulation codes, the aim was to perform personal dosimetry in real-time. We applied and validated the methodology for two situations where improvements in dosimetry are urgently needed: neutron workplaces and interventional radiology. Several validation and test measurements were done in different hospitals, and in 2 workplace fields with significant neutron exposure. Personal doses could be calculated within acceptable simulation times, just based on captured movements of the workers and information of the radiation fields. These doses agreed with the results from physical dosemeters within the standard uncertainties that are accepted in personal dosimetry. This PODIUM dosimetry method can also be used to visualize the radiation in near real time. This will increase awareness of radiation protection among workers and will improve the application of the ALARA principle, and it can also be used in training modules. The use of neural networks and big data will help in further reducing simulation time, making real time simulations and dosimetry without physical dosemeters possible in the near future.

A dataset for tracking the activity of Bogong moths on transects of Mt Kosciuszko, NSW on the evening of 2021-02-18

This dataset contains video clips and stills captured using wildlife cameras on two transects on the slopes of Mt Kosciuszko, NSW. The images contain motion blurs from Bogong moths Agrotis infusa flying past the cameras, allowing for the measurement of Bogong moth activity using the Camfi software (<a href="https://doi.org/10.5281/zenodo.4971144">https://doi.org/10.5281/zenodo.4971144</a>).

opencc-by-4.0May 2021View details →

Dataset for "Reinforcement Learning reveals fundamental limits on the mixing of active particles"

Open access data set for manuscript "Reinforcement Learning reveals fundamental limits on the mixing of active particles" currently (2021) in preparation.

Code and data for 'Bacillus subtilis histidine kinase KinC activates biofilm formation by controlling heterogeneity of single-cell responses'

Code and data used in the paper 'Bacillus subtilis histidine  kinase KinC activates biofilm formation by controlling heterogeneity of single-cell responses'  https://doi.org/10.1128/mBio.01694-21

Active structural geometries and their correlation with moderate (M 5.5-7.0) earthquakes in the Jiashi-Keping region, Tian Shan southwestern front

This data set contains Figures S1-S5, which serve as supporting information for the paper titled "Active structural geometries and their correlation with moderate (M 5.5-7.0) earthquakes in the Jiashi-Keping region, Tian Shan southwestern front". Figure S1 shows locations of all seismic-reflection profiles used in this study. Figures S2-S5 provide uninterpreted and interpreted seismic-reflection profiles across the Bachu transpressional fault system, the western Keping Thrust and the blind Bashituopu Thrust.

Environmental and AIS data collected during the EUMarineRobots Trans-National Access activities experiments using the NATO STO-CMRE Littoral Ocean Observatory Network testbed (Release 2)

Environmental and AIS data collected during the second phase of EUMR TNA experiments using the CMRE LOON testbed. Environmental data consists of temperature measured across the water column; sound velocity measured close to the surface and close to the sea bottom; meteorological data at the surface (i.e., pressure, temperature, wind speed and direction, humidity and rain). The environmental dataset is complemented with Automatic Identification System (AIS) data for the ships transiting close to  the LOON area (Gulf of La Spezia, Italy) Temperature measured across the water column in the LOON area (Gulf of La Spezia, Italy). The dataset includes measurements for: i) June 9-11, 17-18, 25-26 - 2021 ii) July 5-7, 21-27, 30-31 - 2021 iii) August 3-5, 10-14, 19-21, 23-24, 28-30 - 2021 Meteorological data at the surface (i.e., pressure, temperature, wind speed and direction, humidity and rain) in the LOON area (Gulf of La Spezia, Italy). The dataset includes measurements for: i) June 9-11, 17-18, 25-26 - 2021 ii) July 5-7, 21-27, 30-31 - 2021 iii) August 3-5, 10-14, 19-21, 23-24, 28-30 - 2021 Sound velocity measured close to the surface (SVP1) and close to the sea bottom (SVP2) in the LOON area (Gulf of La Spezia, Italy). The dataset includes measurements for: i) June 9-11, 17-18, 25-26 - 2021 ii) July 5-7, 21-27, 30-31 - 2021 iii) August 3-5, 10-14, 19-21, 23-24, 28-30 - 2021 SVP1 data  missing for  June 17-18 (2021) and July 5-7 (2021). Automatic Identification System (AIS) data for the ships transiting close to  the LOON area (Gulf of La Spezia, Italy). The dataset includes AIS data for: i) June 9-11 - 2021 AIS recorded data not available after June 11, 2021 For reference, see: "Environmental data collected on the CMRE LOON tested during the EUMR project: dataset description",  Petroccia, Roberto; Zappa, Giovanni; Cimino, Giampaolo; Grati, Alberto; Alves, João. CMRE-DA-2021-001. July 2021, available  at https://www.cmre.nato.int/research/publications/latest-techreports/1638-cmre-da-2021-001

Fink: early supernovae Ia classification using active learning

Data and code used to obtain results presented in <a href="https://arxiv.org/abs/2111.11438">Leoni et al., 2021, Fink: early supernovae Ia classification using active learning</a>

opencc-by-4.0Dec 2021View details →

Recordings of electrical activity of four species of fungi

Recordings of electrical activity of four species of fungi ghost fungi Omphalotus nidiformis, Enoki fungi Flammulina velutipes, split gill fungi Schizophyllum commune and  caterpillar fungi Cordyceps militari.    Electrical activity of the fungi was recorded using pairs of iridium-coated stainless steel sub-dermal needle electrodes (Spes Medica S.r.l., Italy), with twisted cables and  ADC-24 (Pico Technology, UK) high-resolution data logger with a 24-bit A/D converter, galvanic isolation and software-selectable sample rates all contribute to a superior noise-free resolution.  Each pair of electrodes  reported a potential difference between the electrodes. The pairs of electrodes were pierced into the substrates colonised by fungi or, as in case of \emph{S. commune}, in the sporocarps.  Distance between electrodes was 1-2~cm.  We recorded electrical activity one sample per second. We recorded 8 electrode pairs simultaneously. During the recording, the logger has been doing as many measurements as possible (typically up to 600 per second) and saving the average value. The acquisition voltage range was 78~mV. S. commune has been recorded for 1.5 days, other species for c. 5 days.

opencc-by-3.0-usDec 2021View details →

Medial prefrontal cortex and anteromedial thalamus interaction regulates motivation related behavior and dopaminergic neuron activity: Animal Behavior

The excel Source DATA file contains the data described in Figures 2c, 2d, 2f, and 3b and Supplementary Figure 3b and 3c. The fiber photometry data described in Supplementary Figure 9 are found in the CSV files. The CSV file names reflect animal IDs.

opencc-by-nc-4.0Dec 2021View details →

Overview of social informatics scientific activities (1985–2019): Three datasets

The dataset was created as part of the overview of social informatics scientific activities published from 1985 to 2019. The results of the overview are presented in the article Evolution of social informatics: Publications, research, and educational activities. Three files are included: <ol> <li>The file SI-dataset-SI-N.xslx lists all peer-reviewed scientific publications containing the term social informatics in the title, abstract or keywords. Each listed publication is coded according to ten variables.</li> <li>The file SI-dataset-SocInfo.xslx lists all papers published in the Proceedings of the international conference on Social Informatics (SocInfo conference). Each listed publication is coded according to seven variables.</li> <li>The file SI-dataset-Activities.xslx lists all research and educational activities as well as conferences, journals and blogs that contain the term social informatics in their title or name.</li> </ol> The methodology is detailed in the article. Vehovar, V., Smutny, Z., and Bartol, J. (2022). Evolution of social informatics: Publications, research, and educational activities. The Information Society, 38(5), 307–333. <a href="https://doi.org/10.1080/01972243.2022.2092570">https://doi.org/10.1080/01972243.2022.2092570</a>

Ripples reflect a spectrum of synchronous spiking activity in human anterior temporal lobe

Direct brain recordings have provided important insights into how high-frequency activity captured through intracranial EEG (iEEG) supports human memory retrieval. The extent to which such activity is comprised of transient fluctuations that reflect the dynamic coordination of underlying neurons, however, remains unclear. Here, we simultaneously record iEEG, local field potential (LFP), and single unit activity in the human temporal cortex. We demonstrate that fast oscillations within the previously identified 80–120 Hz ripple band contribute to broadband high-frequency activity in the human cortex. These ripple oscillations exhibit a spectrum of amplitudes and durations related to the amount of underlying neuronal spiking. Ripples in the macro-scale iEEG are related to the number and synchrony of ripples in the micro-scale LFP, which in turn are related to the synchrony of neuronal spiking. Our data suggest that neural activity in the human temporal lobe is organized into transient bouts of ripple oscillations that reflect underlying bursts of spiking activity.

Data from: Microbial metabolic activity in two basins of the Gulf of Mexico influenced by mesoscale structures

Information on microbial metabolic activity is essential for quantifying carbon and energy flows through marine food webs. We quantified community (Rcom) and prokaryotic (Rpro) respiration rates, bacterial production (BP), bacterial abundance (BA), and bacterial growth efficiencies (BGE) in the Perdido and Coatzacoalcos basins of the Gulf of Mexico (GOM) during summer and winter conditions in 2016. Our results showed seasonal, regional, and mesoscale eddy influences on those metabolic variables. Rpro accounted for more than 60% of total respiration in both regions, being three times higher in stations influenced by a cyclonic eddy (CE) in September (24.1 μM O2 d-1) than in stations affected by an anticyclonic eddy in March (7.2 μM O2 d-1) within the Coatzacoalcos basin where the eddy-trapping mechanism advected biomass-enriched waters from the Bay of Campeche. The eddy-stirring mechanism produced horizontal and vertical dipole patterns of metabolic variables increasing up to one order of magnitude Rcom and Rpro while decreasing BGE to 25-fold from the southeastern to the northwestern edges in CEs. This finding indicates that dissolved organic matter is more actively taken up to build bacterial biomass on the eastern edge of CEs in the GOM, while respiration rates increase on the western edges. Satellite integrated primary production was coupled with surface respiration rates at CEs and no eddies. Bacterial production was mainly regulated by CEs and was about 50% higher in the Coatzacoalcos basin (~0.03–0.14 µmol C L-1 d-1). BP increased in zones with high respiration rates, suggesting that Rcom is associated with heterotrophic prokaryote activity in both basins. Bacterial growth efficiency was lower than 25% within the upper 500 m during both cruises, but the highest values were quantified in the euphotic zone and during the September cruise. Metabolic variables integrated over the water column showed that 40–80% of the activity occurred between the base of the euphotic zone and 150 m depth. Our findings contribute to a better understanding of the metabolic activity of the microbial communities in two regions of the GOM influenced by mesoscale eddies.

Task-induced modulations of neuronal activity along the auditory pathway

Sensory processing varies depending on behavioral context. Here, we ask how task-engagement modulates neurons in the auditory system. We train mice in a simple tone-detection task, and compare their neuronal activity during passive hearing and active listening. Electrophysiological extracellular recordings in the inferior colliculus, medial geniculate body, primary auditory cortex and anterior auditory field reveals widespread modulations across all regions and cortical layers, and in both putative regular and fast-spiking cortical neurons. Clustering analysis unveils ten distinct modulation patterns that can either enhance or suppress neuronal activity. Task-engagement changes the tone-onset response in most neurons. Such modulations first emerge in subcortical areas, ruling out cortical feedback as the only mechanism underlying subcortical modulations. Half the neurons additionally display late modulations associated with licking, arousal or reward. Our results reveal the presence of functionally distinct subclasses of neurons, differentially sensitive to specific task-related variables but anatomically distributed along the auditory pathway.

Activity of individual neurons in the Aplysia buccal ganglion before and after in vitro operant conditioning

Dataset for Costa RM, Baxter DA, Byrne JH (2021) Neuronal population activity dynamics reveal a low-dimensional signature of operant learning in Aplysia. Commun Biol. BioRxiv preprint 2021.12.06.471434 Data collected by using voltage-sensitive dye imaging to capture population-wide, single neuron resolution activity in the isolated Aplysia buccal ganglion before and after in vitro operant conditioning. Data for 7 contingently trained and 7 yoked control animals includes population spike trains, timing of buccal motor patterns, ganglia images, and pixel coordinates for each neuron (kernels). In addition, the data includes results of the non-negative matrix factorization analyses described in the article. The dataset is organized as a Matlab structure variable.

opencc-by-4.0Dec 2021View details →

Harnessing single cell RNA sequencing to identify dendritic cell types, characterize their biological states and infer their activation trajectory

Summary: Dendritic cells (DCs) orchestrate innate and adaptive immunity, by translating the sensing of distinct danger signals into the induction of different effector lymphocyte responses, to induce different defense mechanisms suited to face distinct types of threats. Hence, DCs are very plastic, which results from two key characteristics. First, DCs encompass distinct cell types specialized in different functions. Second, each DC type can undergo different activation states, fine-tuning its functions depending on its tissue microenvironment and the pathophysiological context, by adapting the output signals it delivers to the input signals it receives. Hence, to better understand DC biology and harness it in the clinic, we must determine which combinations of DC types and activation states mediate which functions, and how. To decipher the nature, functions and regulation of DC types and their physiological activation states, one of the methods that can be harnessed most successfully is ex vivo single cell RNA sequencing (scRNAseq). However, for new users of this approach, determining which analytics strategy and computational tools to choose can be quite challenging, considering the rapid evolution and broad burgeoning of the field. In addition, awareness must be raised on the need for specific, robust and tractable strategies to annotate cells for cell type identity and activation states. It is also important to emphasize the necessity of examining whether similar cell activation trajectories are inferred by using different, complementary methods. In this chapter, we take these issues into account for providing a pipeline for scRNAseq analysis and illustrating it with a tutorial reanalyzing a public dataset of mononuclear phagocytes isolated from the lungs of naïve or tumor-bearing mice. We describe this pipeline step-by-step, including data quality controls, dimensionality reduction, cell clustering, cell cluster annotation, inference of the cell activation trajectories and investigation of the underpinning molecular regulation. It is accompanied with a more complete tutorial on Github. We anticipate that this method will be helpful for both wet lab and bioinformatics researchers interested in harnessing scRNAseq data for deciphering the biology of DCs or other cell types, and that it will contribute to establishing high standards in the field. Data : 1. Table1_full_version.docx : Marker genes for cell clusters of global Seurat analysis 2. Table2_full_version.docx : List of the Immgen samples used to generate the reference compendium for CMAP signature generation 3. Table5_full_version.docx : Top 20 marker genes for cell clusters of the Seurat analysis on selected cDC1s