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The growth in the use of social media platforms such as Facebook and Twitter over the past decade has significantly facilitated and improved the way people communicate with each other. However, the information that is available and shared online is not always credible. These platforms provide a fertile ground for the rapid propagation of breaking news along with other misleading information. The enormous amounts of fake news present online have the potential to trigger serious problems at an individual level and in society at large. Detecting whether the given information is fake or not is a challenging problem and the traits of social media makes the task even more complicated as it eases the generation and spread of content to the masses leading to an enormous volume of content to analyze. The multimedia nature of fake news on online platforms has not been explored fully. This survey presents a comprehensive overview of the state-of-the-art techniques for combating fake news on online media with the prime focus on deep learning (DL) techniques keeping multimodality under consideration. Apart from this, various DL frameworks, pre-trained models, and transfer learning approaches are also underlined. As till date, there are only limited multimodal datasets that are available for this task, the paper highlights various data collection strategies that can be used along with a comparative analysis of available multimodal fake news datasets. The paper also highlights and discusses various open areas and challenges in this direction., Competing Interests: Conflict of interestThe authors declare that they have no conflict of interest., (© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022.)

Virus classification arranges viruses showing similar properties into groups and, even though this depends on choices of which specific properties have a value for classification, it does have certain important features. It aims to give a structured arrangement of viruses so that the human mind can comprehend them more easily. It helps with communication between virologists, and between virologists and non-virologists (e.g. regulators, advisers, other stakeholders etc.). It enables properties of new viruses to be predicted, and it could reveal possible evolutionary relationships. We need appropriate unambiguous names for virus species, which is the keystone taxon, howsoever these are defined. We react to the recent consultation paper [1] and suggest that, before deciding on a binomial (Latinized or non-Latinized) system for virus species names, the International Committee on Taxonomy of Viruses develops a 21 st century virus classification system that handles the large numbers of new virus species expected from metagenomic studies. This system should be user-friendly for easy communication, especially between virologists and non-virologist stakeholders.

The news of success in ether anesthesia on 16 October 1846 in Boston spread like wildfire through Europe. In the German-speaking countries, the national newspapers as conveyers of the development played a prominent role; this was especially the case for the Augsburger Allgemeine Zeitung whose correspondent, Aloys Martin [1], was a medical professional. The function of local newspapers has not yet been investigated. This was to be remedied by examining both of Bamberg's local papers. All issues from 01.01. to 31.04.1847 were surveyed with respect to relevant announcements. These were then catalogued according to date, extent and contents. Starting on 22.01.1847, the events outside of and in Bamberg were reported on in 26 notices and articles of just a few lines to half a page and in advertisements; Aloys Martin also appears on the scene. Thus, the local press in Bamberg also informed its readers early and regularly on the discovery of ether and the succeeding events.