If humanity is obliterated by climate change, how will we even know it's happened? That's the question being answered by Australian scientists, who are building Earth's Black Box – a 32-foot-long steel monolith that captures data about our planet. It'll be filled with hard drives that constantly document climate change, giving an'unbiased account of events' that lead to Earth's demise. In the event of a climate apocalypse, it will provide a document of how humanity failed to avoid the disaster – as long as there's someone or something around to access it. Artist impressions suggest it will have a similar aura to the mysterious monolith in Stanley Kubrick's sci-fi film '2001: A Space Odyssey'.

Online reviews have a significant influence on customers' purchasing decisions for any products or services. Several models have been developed to detect fake reviews using machine learning approaches. Many of these models have some limitations resulting in low accuracy in distinguishing between fake and genuine reviews. These models focused only on linguistic features to detect fake reviews and failed to capture the semantic meaning of the reviews. To deal with this, this paper proposes a new ensemble model that employs transformer architecture to discover the hidden patterns in a sequence of fake reviews and detect them precisely. The proposed approach combines three transformer models to improve the robustness of fake and genuine behaviour profiling and modelling to detect fake reviews. The experimental results using semi-real benchmark datasets showed the superiority of the proposed model over state-of-the-art models. NTRODUCTION The Internet's size and importance has exploded in recent years, and it exerts a significant and growing influence on people's daily lives. Customers usually spend a substantial amount of time online, searching for information on a variety of products, communicating with others, and reading reviews.

The emergence of a devastating transmissible facial cancer among Tasmanian devils over the past few decades has caused substantial concern for their future because these animals are already threatened by a regional distribution and other stressors. Little is known about the overall history and trajectory of this disease. Patton et al. used an epidemiological phylodynamic approach to reveal the pattern of disease emergence and spread. They found that low Tasmanian devil densities appear to be contributing to slower disease growth and spread, which is good news for Tasmanian devil persistence and suggests that care should be taken when considering options for increasing devil populations. Science , this issue p. [eabb9772][1] ### INTRODUCTION Emerging infectious diseases pose one of the greatest threats to human health and biodiversity. Phylodynamics is an effective tool for inferring epidemiological parameters to guide intervention strategies, particularly for human viruses such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, phylodynamic analysis has historically been limited to the study of rapidly evolving viruses and, in rare cases, bacteria. Nonetheless, application of phylodynamics to nonviral pathogens has immense potential, such as for predicting disease spread and informing the management of wildlife diseases. We conducted a phylodynamics analysis of devil facial tumor disease (DFTD), a transmissible cancer that has spread across nearly the entire geographic range of Tasmanian devils and threatens the species with extinction. DFTD is transmitted as an allograft through biting during common social interactions, susceptibility is nearly universal, and case fatality rates approach 100%. The goals of our study were to (i) characterize the geographic spread of DFTD, (ii) identify whether there are different circulating tumor lineages, and (iii) quantify rates of transmission among lineages. ### RATIONALE In principle, phylodynamics should be readily extended to the study of slowly evolving pathogens with large genomes through careful interrogation of genes to identify those that are measurably evolving. By testing individual genes for a clocklike signal, these genes may then be used for phylodynamic analysis. We demonstrate this proof of concept in DFTD. ### RESULTS We screened >11,000 genes across the DFTD genome, identifying 28 that exhibited a strong, clocklike signal, and performed the first phylodynamic analysis of a genome larger than a bacterium. We demonstrate here, contrary to field observations, that DFTD spread omnidirectionally throughout the epizootic, leaving little signal of geographic structuring of tumor lineages across Tasmania. Despite predictions of devil extinction, we found that the effective reproduction number ( R E), a summary of the rate at which disease spreads, has declined precipitously after the initial epidemic spread of DFTD. Specifically, R E peaked at a high of ~3.5 shortly after the discovery of DFTD in 1996 and is now ~1 in both extant tumor lineages. This is consistent with a shift from emergence to endemism. Except for a single gene, we found little evidence for convergent molecular evolution among tumor lineages. ### CONCLUSION We have demonstrated that phylodynamics can be applied to virtually any pathogen. In doing so, we show that through careful interrogation of the pathogen genome, a measurably evolving set of genes can be identified to characterize epidemiological dynamics of nonviral pathogens with large genomes. By applying this approach to DFTD, we have shown that the disease appears to be transitioning from emergence to endemism. Consistent with recent models, our inference that R E ~1 predicts that coexistence between devils and DFTD is a more likely outcome than devil extinction. Therefore, our findings present cautious optimism for the continued survival of the iconic Tasmanian devil but emphasize the need for evolutionarily informed conservation management to ensure their persistence. ![Figure][2] Tasmanian devils and their transmissible cancer. Healthy (top) and DFTD-infected (bottom) Tasmanian devils. Photos: David G. Hamilton (top), Alexandra K. Fraik (bottom). Emerging infectious diseases pose one of the greatest threats to human health and biodiversity. Phylodynamics is often used to infer epidemiological parameters essential for guiding intervention strategies for human viruses such as severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2). Here, we applied phylodynamics to elucidate the epidemiological dynamics of Tasmanian devil facial tumor disease (DFTD), a fatal, transmissible cancer with a genome thousands of times larger than that of any virus. Despite prior predictions of devil extinction, transmission rates have declined precipitously from ~3.5 secondary infections per infected individual to ~1 at present. Thus, DFTD appears to be transitioning from emergence to endemism, lending hope for the continued survival of the endangered Tasmanian devil. More generally, our study demonstrates a new phylodynamic analytical framework that can be applied to virtually any pathogen. [1]: /lookup/doi/10.1126/science.abb9772 [2]: pending:yes

Drone operators are being warned about rules for flying after a drone forced the grounding of firefighting aircraft battling a blaze on Tasmania's Bruny Island. Tasmania police said the aircraft had to be grounded because firefighting efforts at Conleys Point, south Bruny, were being hampered by a drone flown in the area, putting community safety at risk. "This is a reminder to all operators of drones to not fly near aircraft at any time," police said. "This puts the safety of people in aircraft at risk and also impacts on the safety of the community." Flying drones near public safety or emergency operations, such as bushfires, can be an offence under Civil Aviation Safety Authority rules.