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https://www.selleckchem.com/products/elamipretide-mtp-131.html Deepfakes may refer to algorithmically synthesized material wherein the face of a person is superimposed onto another body. To date, most deepfakes found online are pornographic, with the people depicted in them rarely consenting to their creation and publicization. Deepfakes leave anyone with an online presence vulnerable to victimization. As a testament to policy often being reactionary to antisocial behavior, current Canadian legislation offers no clear recourse to those who are victimized by deepfake pornography. We aim to provide a critical review of the legal mechanisms and remedies in place, including criminal charges, defamation, copyright infringement laws, and injunctive relief that could be applied in deepfake pornography cases. To combat deepfake pornography, we suggest current laws to be expanded to include language specific to falsely created pornography without the explicit consent of all depicted persons. We also discuss the extent to which host websites are responsible for vetting the uploaded content on their platforms. Finally, we present a call for action on a societal and research level to deal with deepfakes and better support victims of deepfake pornography.Biosensor data have the potential to improve disease control and detection. However, the analysis of these data under free-living conditions is not feasible with current statistical techniques. To address this challenge, we introduce a new functional representation of biosensor data, termed the glucodensity, together with a data analysis framework based on distances between them. The new data analysis procedure is illustrated through an application in diabetes with continuous-time glucose monitoring (CGM) data. In this domain, we show marked improvement with respect to state-of-the-art analysis methods. In particular, our findings demonstrate that (i) the glucodensity possesses an extraordinary clinical sensitivity to capture th

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