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opencc-by-4.0Jul 2023View details →

Towards a real-world technical test battery for remote microphone systems used with hearing prostheses

Wav format audio files of both source and response for 5 different wireless remote microphone systems under various test conditions, as reported in the paper : Stone M.A., Lough M., Whiston H., Wilbraham K., Dillon H. (2023) Towards a real-world technical test battery for remote microphone systems used with hearing prostheses.      Trends in Hearing  DOI:   10.1177/23312165231182518 Also includes the MATLAB script used to analyse the recordings.

opencc-by-4.0Dec 2022View details →

Real life condition evaluation of Inoserp PAN-AFRICA antivenom effectiveness in Cameroon

ABSTRACT Background: Snakebites is a serious public health issue but remains a neglected tropical disease. Data on antivenom effectiveness are urgently needed in Africa. We assessed effectiveness of Inoserp PAN-AFRICA (IPA), the recommended antivenom available in Cameroon. Methodology/Principal Findings: We enrolled 447 patients presenting with snakebite in 14 health facilities across Cameroon. At presentation, cytotoxicity, coagulation troubles and neurotoxicity were graded. We administered two to four vials of antivenom to patients based on hemotoxic or neurotoxic signs. We renewed antivenom administration to patients with persistence of bleedings or neurotoxicity 2 hours after each injection. We defined early improvement as a reduction of the grade of envenomation symptoms 2 hours after first injection. Medium-term effectiveness was investigated looking at disappearance of symptoms during hospitalization. After hospital discharge, a home visit was planned to assess long-term outcomes. Between October 2019 and May 2021, we enrolled 447 (93.7%), including 72% from the savannah regions. The median [IQR] age was 25 [14-40]. Envenomation was diagnosed in 369 (82.6%) participants. The antivenom was administered to 356 patients (96.5%) of whom 256 (71.9%) received one administration. Among these patients, cytotoxic symptoms were observed in 336 (94.4%) participants, coagulation disorders in 234 (65.7%) participants and neurotoxicity in 23 (6.5%) participants. Two hours after the first administration of antivenom, we observed a decrease in coagulation disorders or neurotoxicity in 75.2% and 39.1% of patients, respectively. Complete cessation of bleedings and neurotoxicity occurred in 96% and 93% of patients within 24 hours, respectively. Sequelae have been observed in 9 (3%) patients at the home visit 15 days after hospital admission and 11 (3%) died including one before antivenom injection. Conclusions/Significance: We confirmed good effectiveness of the IPA and highlighted the rapid improvement in bleeding or neurotoxicity after the first administration. Sequential administrations of low doses of antivenom, rigorously assessed at short intervals for an eventual renewal, can preserve patient safety and save antivenom.

opencc-by-4.0Aug 2023View details →

Data for "ChickenSense: A low-cost deep learning-based solution for real-time poultry feed intake monitoring using sound technology"

The dataset includes two types of data: scale and audio. The scale data is recorded using a hanging scale and measures the feeders' weight with a 5 Hz frequency. The audio data contains 1824 hours of recorded audio using a piezo-electric sensor attached to a bucket feeder to capture vibrations as audio signals with a sampling rate of 48 kHz. Each .wav file contains 15 minutes of audio recording. Along with the raw data, a part of the dataset containing 36 30-second audio recordings was sampled and labeled in four classes, including pecking, singing, anomaly, and silence, resulting in 3319 labeled events.

openmit-licenseAug 2023View details →

Datasets of paper "Towards Assessing the Real-World Impact of Defects in Blockchain-based Smart Contracts"

Datasets of paper "Towards Assessing the Real-World Impact of Defects in Blockchain-based Smart Contracts" published on the 1st International Workshop on Software Defect Datasets (SDD 2023). The GitHub repository is available here: <a href="https://github.com/MichaelHettmer/sdd23">https://github.com/MichaelHettmer/sdd23</a>

opencc-by-4.0Sep 2023View details →

Data from: Automatic patient-level recognition of four Plasmodium species on thin blood smear by a Real Time Detector Transformer (RT-DETR) object detection algorithm: a proof-of-concept and evaluation

Automatic patient-level recognition of four Plasmodium species on thin blood smear by a Real Time Dectector Transformer (RT-DETR) object detection algorithm: a proof-of-concept and evaluation Emilie Guemas, Baptiste Routier, Théo Ghelfenstein-Ferreira, Camille Cordier, Sophie Hartuis, Bénédicte Marion, Sébastien Bertout, Emmanuelle Varlet-Marie, Damien Costa, Grégoire Pasquier Abstract: Malaria remains a global health problem with 247 million cases and 619,000 deaths in 2021. Diagnostic of Plasmodium species is important for administering the appropriate treatment. The gold-standard diagnosis from accurate species identification remains the thin blood smear. Nevertheless, this method is time-consuming and requires highly skilled and trained microscopists. To overcome these issues, new diagnostic tools based on deep learning are emerging. This study aimed to evaluate the performances of a RT-DETR (Real-Time Detection Transformer)object detection algorithm to discriminate Plasmodium species on thin blood smears images. The algorithm was trained and validated on a dataset consisting in 24,720 images from 475 thin blood smears corresponding to 2,002,597 labels. Performances were calculated with a test dataset of 4,508 images from 170 smears corresponding to 358,825labels coming from six French university hospital. At the patient level, the RT-DETR algorithm exhibited an overall accuracy of 79.4% (135/170) with a recall of 74% (40/54) and 81.9% (95/116) for negative and positive smears, respectively. Among Plasmodium positive smears, the global sensitivity was 82.7% (91/110) with a sensitivity of 90% (38/42), 81.8% (18/22) and 76.1% (35/46) for P. falciparum, P. malariae and P. ovale/vivax, respectively. The YOLOv5 model achieved a World Health Organization (WHO) competence level 2 for species identification. Besides, the RT-DETR algorithm may be run in real-time on low-cost devices such as a smartphone and could be suitable for deployment in low-resource setting areas where microscopy experts are lacking. Data collection: The training and validation dataset included 24,720 pictures taken from 475 manually May Grunwald-Giemsa (MGG)-stained thin blood smears from the Montpellier University Hospital collection and for a smaller part from the Toulouse University Hospital collection. In Montpellier, the pictures were taken with a Flexcam C1 microscope camera (Leica) attached to a Leica DM 2000 microscope and Leica DF450C microscope camera adapted with a Leica DM2500 microscope at X1000 magnification. Labelling of pictures was performed manually, and then automatically with manual correction with a Computer Visual Annotation Tools (CVAT) free software. Nine categories of labels were used: white blood cells (n=3,338), red blood cells (n=1,887,781), platelets (n=48,520), Trypanosoma brucei (n=2,773), and red blood cells infected by P. falciparum (n=43,545), P. ovale (n=4,651), P. vivax (n=4,115), P. malariae (n=2,849) and Babesia divergens (n=5,142). The test dataset included 4,508 pictures taken from 170 thin blood smears from the same number of patients from the Parasitology laboratories of University Hospitals of Montpellier, Toulouse, Rouen, Lille, Nantes and Saint-Louis in Paris (Table 1). Among these 170 patients, 54 were not infected, including two patients with Howell-Jolly bodies, and 116 were infected with hematozoa. For each patient, between 20 and 30 photos were taken from one thin blood smear with at least one hematozoan parasite per picture for infected patients. Accurate species diagnostic was made by a senior parasitologist, and for recent smears, it was confirmed by specific PCR, either performed locally (Toulouse) or at the Malaria French National Reference Center (Montpellier, Saint Louis, Rouen, Lille, Nantes).

opencc-by-4.0Sep 2023View details →

Interpretation results used in the paper "Real-Time Dual-Para FWI-Inv of GPR Data Based on Robust Deep Learning"

We provide the updated synthetic data and inversion results used for all interpretations presented in the paper "Real-Time Dual-Parameter FWI Inversion of GPR Data Based on Robust Deep Learning."

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Real-world human-robot interaction data with robotic pets in user homes in the United States and South Korea

Socially-assistive robots (SARs) hold significant potential to transform the management of chronic healthcare conditions (e.g. diabetes, Alzheimer's, dementia) outside the clinic walls. However doing so entails embedding such autonomous robots into people's daily lives and home living environments, which are deeply shaped by the cultural and geographic locations within which they are situated. That begs the question of whether we can design autonomous interactive behaviors between SARs and humans based on universal machine learning (ML) and deep learning (DL) models of robotic sensor data that would work across such diverse environments. To investigate this, we conducted a long-term user study with 26 participants across two diverse locations (the United States and South Korea) with SARs deployed in each user's home for several weeks. We collected robotic sensor data every second of every day, combined with sophisticated ecological momentary assessment (EMA) sampling techniques, to generate a large-scale dataset of over 270 million data points representing 173 hours of randomly-sampled naturalistic interaction data between the human and robot pet. Interaction behaviors included activities like playing, petting, talking, cooking, etc.

opencc-zeroOct 2023View details →

opencc-by-4.0Aug 2024View details →

Now or Never? Global Review of Reactive and Near Real-Time Conservation Actions For Cetaceans

Table S1: Information on resulting publications (n = 64) reviewed in this study.

Mobile Technology and Data Analytics to Identify Real-time Predictors of Caregiver Well-Being

ClinicalTrials.gov study NCT04556591. IPD Sharing: YES. Countries: 1. Publications: 4.

Log2Lose: Incenting Weight Loss and Dietary Self-monitoring in Real-time to Improve Weight Management Among Adults With Obesity

ClinicalTrials.gov study NCT04770909. IPD Sharing: YES. Countries: 1. Publications: 2.

A Study to Observe Vedolizumab and Anti-tumour Necrosis Factors (Anti-TNFs) Outcomes in Real-world Biologic Ulcerative Colitis (UC) and Crohn's Disease (CD) Participants

ClinicalTrials.gov study NCT03710486. IPD Sharing: YES. Countries: 2. Publications: 1.

restrictedIPD-UNDECIDEDFeb 2026View details →

Exposure to Gun Violence in Video Games Increases Interest in Real Guns

ClinicalTrials.gov study NCT03259139. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.

Clinical Effectiveness of Body Fat Distribution Imaging in Real-World Practice: The BODY-REAL Study

ClinicalTrials.gov study NCT04763772. IPD Sharing: YES. Countries: 1. Publications: 1.