The potential of electromagnetic fields (EMFs) for disease treatment and health enhancement has been actively pursued over the recent decades. This review first provides a general introduction about natural EMFs and related biological effects. Then the recent progress on the EMF treatment of some common diseases (such as cancer, diabetes, wound healing and neurological diseases, etc.) has been carefully reviewed and summarized. Yet, the blindness on the selection of therapeutic EMF parameters still hinders the broad ap-plication of EMF therapy. Moreover, the unclear mechanism of EMF function and poor reproducibility of experimental results also remain big challenges in the field of bioelectromagnetics. Bionics is a useful methodology that gains inspiration from nature to serve human life and industry. We have discussed the feasibility of applying bionic approach on the selection of therapeutic EMFs, which is based on the findings of natural EMFs. Finally, we advocate that the detailed information of EMFs and biological samples should be thoroughly rec-orded in future research and reported in publications. In addition, the publication of studies with negative results should also be allowed.
Computer networks have increasingly been the focus of cyber attack, such as botnets, which have a variety of serious cybersecurity implications. As a consequence, understanding their behaviour is an important step towards the mitigation of such threat. In this paper, we propose a novel method based on network topology to assess the spreading and potential security impact of botnets. Our main motivation is to provide a toolbox to classify and analyse the security threats posed by botnets based on their dynamical and statistical behaviour. This would potentially lead to a better understanding and prediction of cybersecurity issues related to computer networks. Our initial validation shows the potential of our method providing relevant and accurate results.
The COVID-19 pandemic has brought to the fore a number of issues regarding digital technologies, including a heightened focus on cybersecurity and data privacy. This chapter examines two aspects of this phenomenon. First, as businesses explore creative approaches to operate in the “new normal,” the security implications of the deployment of new technologies are often not considered, especially in small businesses, which often possess limited IT knowledge and resources. Second, issues relating to security and data privacy in monitoring the pandemic are examined, and different privacy-preserving data-sharing techniques, including federated learning, secure multiparty computation, and blockchain-based techniques, are assessed. A new privacy-preserving data-sharing framework, which addresses current limitations of these techniques, is then put forward and discussed. The chapter concludes that although the worst of the pandemic may soon be over, issues regarding cybersecurity will be with us for far longer and require vigilant management and the development of creative solutions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.