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In recent years vehicle accident has become one of the most important problems in almost all over the globe. Drunk and drive, riding without adequate sleep and riding a car at faster speeds are the three significant reasons which lead to drastic increase in the number of accidents. Evidence Collection Car is a device used to record the driving history. This device is installed in a car which stores the readings of engine temperature, detection of obstacle and condition of seat belt. Thesnapshots inside a car and readings of engine temperature, detection of obstacle and condition of seat belt are collected. The collected information is notified through GSM to the concerned authorities. As a result rescue team will be informed automatically so that injured person will be assisted in a short span of time. The main aim of this paper is to reduce thepercentage of road accidents occurring in real time.

Convolutional Neural Networks and its contemporary variants have proven to be ruling benchmarks for most image processing tasks but resort to pooling techniques and routing mechanisms that affect classification accuracy and lose spatial relationship information between involved data points. Hence, Hinton et al, proposed a layered architecture called Capsule Networks (Capsnets) which outperform traditional systems by replacing pooling techniques with dynamic routing abilities. Capsnets are, thus, en-route to proving themselves as prospective future benchmarks in visual imagery tasks by surpassing existing state-of-theart results on the MNIST dataset. The two novel aspects inspected in this paper are: the enhancement of this performance on CIFAR-10 through regularization and hyperparameter optimization which, henceforth, augment applicability to stochastic numeric healthcare data helping uncover newer challenges of predictive neural networks.

Background: Meta-analysis and clinical studies suggest coronavirus disease-2019 (COVID-19) patients in ICU have a high mortality rate of 30-45%, which has evolved as a function of criteria of admission and the management modalities. Materials and methods: We conducted a retrospective evaluation for characteristics and outcomes in critical care set up across six months. Results: 514 patients (74.3% males and 25.6% females) were evaluated. 9.72% (n = 50) patients expired, 78% (n = 39) were males. Mean age (years) was 57 (±14, range 64, 95% CI 55-58). 65.7% (n = 338) were of age more than 50 years, of which 71.5% (n = 242) were males. Males at 20% higher risk for death than women. (RR = 1.2, 95% CI 0.66-2.31, p = 0.61 NS). There was 18% less risk of mortality in female vs male with comorbidities (RR 0.82, 95% CI 0.67-1.12, p = 0.32 NS). Risk for mortality in diabetics was significantly increased by 116% vs nondiabetics. (RR 2.16, p = 0.0055, 95% CI 1.28-3.67). Highly significant risk of mortality in age group >50 years (3.13 times higher) vs age ≤50 years. (RR 3.18, 95% CI 1.71-8.64, p = 0.0003). 50.2% had moderate ARDS at admission. High flow nasal cannula was used in 47.2%. There is 5.79 times more likelihood to be on the ventilator with moderate to severe ARDS vs mild ARDS (RR = 5.79, 95% CI 3.10-11.05, p <0.0001). Risk for death was six times higher for patients on ventilator vs not on ventilator (RR = 6.08, 95% CI 3.49-10.59, p <0.0001). The mean number of days on ventilator for patients who underwent tracheostomy (n = 49) was 14 days as compared to 6.6 days in patients who were extubated (n = 57) (p <0.0001). P/F ratio had negative correlation with number of days of hospitalisation (Pearson r -0.391, 95% CI -0.46- -0.31, p <0.0001). 67% less chances of mortality in patients on steroids (RR = 0.33, 95% CI 0.19-60, p = 0.0012). Mean duration of ICU stay (days) was 8 (± 5, range 29, 95% CI 7.5-8.4). Conclusions: We observed that a strict adherence to the basic principles of ARDS management resulted in a lower mortality in ICU setting. [ABSTRACT FROM AUTHOR]

The list of members of the Fibr Community Science Consortium in the original version of the paper incorrectly omitted consortium member Matthew D. Sacchet, Massachusetts General Hospital, Harvard Medical School, Boston, USA. The corrected membership list has replaced the incorrect version in the pdf and HTML versions of the article. [Extracted from the article]

The corrected membership list has replaced the incorrect version in the pdf and HTML versions of the article. Correction to: I Scientific Data i https://doi.org/10.1038/s41597-022-01695-7, published online 12 October 2022 The list of members of the Fibr Community Science Consortium in the original version of the paper incorrectly omitted consortium member Christian K. Tamnes, University of Oslo, Norway. [Extracted from the article]

Correction to: I Scientific Data i https://doi.org/10.1038/s41597-022-01695-7, published online 12 October 2022 In this article the affiliation details for Bárbara Avelar-Pereira were incorrectly given as "University of Zurich, Department of Child and Adolescent Psychiatry and Psychotherapy, University Hospital of Psychiatry Zurich, Zurich, 8032, Switzerland" but should have been "Stanford University, Department of Psychiatry and Behavioral Sciences, School of Medicine, Stanford, California, 94305, USA". These authors contributed equally: Adam Richie-Halford, Matthew Cieslak. [Extracted from the article]