ABSTRACT'Galaxy groups' have hardly been realised as a separate class of objects with specific characteristics in the structural hierarchy. The presumption that the selfsimilarity of dark matter structures is a valid prescription for the baryonic universe at all scales has rendered smaller structures undetectable by current observational facilities, leading to lesser dedicated studies on them. Some recent reports that indicate a deviation from L x -T scaling in groups compared to clusters have motivated us to study their physical properties in depth. In this article, we report the extensive study on physical properties of groups in comparison to the clusters through cosmological hydrodynamic plus N-body simulations using ENZO 2.2 code. As additional physics, radiative cooling, heating due to supernova and star motions, star formation and stellar feedback has been implemented. We have produced a mock sample of 362 objects with mass ranging from 5 × 10 12 M to 2.5×10 15 M . Strikingly, we have found that objects with mass below ∼ 8 × 10 13 M do not follow any of the cluster self-similar laws in hydrostatics, not even in thermal and non-thermal energies. Two distinct scaling laws are observed to be followed with breaks at ∼ 8 × 10 13 M for mass, ∼1 keV for temperature and ∼1 Mpc for radius. This places groups as a distinct entity in the hierarchical structures, well demarcated from clusters. This study reveals that groups are mostly far away from virialization, suggesting the need for formulating new models for deciphering their physical parameters. They are also shown to have high turbulence and more non-thermal energy stored, indicating better visibility in the non-thermal regime.

Global changes in response to human encroachment into natural habitats and carbon emissions are driving the biodiversity extinction crisis and increasing disease emergence risk. Host distributions are one critical component to identify areas at risk of viral spillover, and bats act as reservoirs of diverse viruses. We developed a reproducible ecological niche modelling pipeline for bat hosts of SARS-like viruses (subgenus Sarbecovirus ), given that several closely related viruses have been discovered and sarbecovirus–host interactions have gained attention since SARS-CoV-2 emergence. We assessed sampling biases and modelled current distributions of bats based on climate and landscape relationships and project future scenarios for host hotspots. The most important predictors of species distributions were temperature seasonality and cave availability. We identified concentrated host hotspots in Myanmar and projected range contractions for most species by 2100. Our projections indicate hotspots will shift east in Southeast Asia in locations greater than 2°C hotter in a fossil-fuelled development future. Hotspot shifts have implications for conservation and public health, as loss of population connectivity can lead to local extinctions, and remaining hotspots may concentrate near human populations.

Infectious diseases that kill their hosts may persist locally only if transmission is appropriately balanced by susceptible recruitment. Great apes die of Ebola virus disease (EVD) and have transmitted ebolaviruses to people. However, understanding the role that apes and other non-human primates play in maintaining ebolaviruses in Nature is hampered by a lack of data. Recent serological findings suggest that few non-human primates have antibodies to EVD-causing viruses throughout tropical Africa, suggesting low transmission rates and/or high EVD mortality (Ayouba A et al. 2019 J. Infect. Dis. 220 , 1599–1608 ( doi:10.1093/infdis/jiz006 ); Mombo IM et al. 2020 Viruses 12 , 1347 ( doi:10.3390/v12121347 )). Here, stochastic transmission models of EVD in non-human primates assuming high case-fatality probabilities and experimentally observed or field-observed parameters did not allow viral persistence, suggesting that non-human primate populations are highly unlikely to sustain EVD-causing infection for prolonged periods. Repeated introductions led to declining population sizes, similar to field observations of apes, but not viral persistence.

Global changes in response to human encroachment into natural habitats and carbon emissions are driving the biodiversity extinction crisis and increasing disease emergence risk. Host distributions are one critical component to identify areas at risk of spillover, and bats act as reservoirs of diverse viruses. We developed a reproducible ecological niche modelling pipeline for bat hosts of SARS-like viruses (subgenus Sarbecovirus), given that since SARS-CoV-2 emergence several closely-related viruses have been discovered and sarbecovirus-host interactions have gained attention. We assess sampling biases and model bats’ current distributions based on climate and landscape relationships and project future scenarios. The most important predictors of species distribution were temperature seasonality and cave availability. We identified concentrated host hotspots in Myanmar and projected range contractions for most species by 2100. Our projections indicate hotspots will shift east in Southeast Asia in >2 °C hotter locations in a fossil-fueled development future. Hotspot shifts have implications for conservation and public health, as loss of population connectivity can lead to local extinctions, and remaining hotspots may concentrate near human populations.

Galaxy clusters are known to be reservoirs of cosmic rays (CRs), as inferred from theoretical calculations or detection of CR-derived observables. CR acceleration in clusters is mostly attributed to the dynamical activity that produces shocks. Shocks in clusters emerge out of merger or accretion, but which one is more effective in producing CRs? at which dynamical phase? and why? To this aim, we study the production or injection of CRs through shocks and its evolution in the galaxy clusters using cosmological simulations with the enzo code. Particle acceleration model considered here is primarily the Diffusive Shock Acceleration (DSA) of thermal particles, but we also report a tentative study with pre-existing CRs. Defining appropriate dynamical states using the concept of virialization, we studied a sample of merging and non-merging clusters. We report that the merger shocks (with Mach number $\mathcal {M}\sim 2-5$) are the most effective CR producers, while high-Mach peripheral shocks (i.e. $\mathcal {M}\gt 5$) are mainly responsible for the brightest phase of CR injection in clusters. Clusters once merged, permanently deviate from CR and X-ray mass scaling of non-merging systems, enabling us to use it as a tool to determine the state of merger. Through a temporal and spatial evolution study, we found a strong correlation between cluster merger dynamics and CR injection. We observed that the brightest phase of X-ray and CR injection from clusters occurs, respectively, at about 1.0 and 1.5 Gyr after every mergers, and CR injection peaks near to the cluster virial radius (i.e r200). Delayed CR injection peaks found in this study deserve further investigation for possible impact on the evolution of CR-derived observables from galaxy clusters.

The speed of spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during the coronavirus disease 2019 (COVID-19) pandemic highlights the importance of understanding how infections are transmitted in a highly connected world. Prior to vaccination, changes in human mobility patterns were used as non-pharmaceutical interventions to eliminate or suppress viral transmission. The rapid spread of respiratory viruses, various intervention approaches, and the global dissemination of SARS-CoV-2 underscore the necessity for epidemiological models that incorporate mobility to comprehend the spread of the virus. Here, we introduce a metapopulation susceptible exposed infectious recovered (SEIR) model parameterised with human movement data from 340 cities in China. Our model replicates the early case trajectory in the COVID-19 pandemic. We then use machine learning algorithms to determine which network properties best predict spread between cities and find travel time to be most important, followed by the human movement Weighted Personalised PageRank. However, we show that travel time is most influential locally, after which the high connectivity between cities reduces the impact of travel time between individual cities on transmission speed. Additionally, we demonstrate that only significantly reduced movement substantially impacts infection spread times throughout the network.

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Galaxy groups are the intermediate structures in hierarchy of cosmic objects. Usually, galaxy clusters emerge out of mergers of groups of galaxies, but, no study confirms that groups are just the scaled down version of the clusters. In this work we have studied the thermal and non-thermal characteristics of galaxy groups from observational (SDSS catalogue) and theoretical (ENZO hydrodynamic simulations) point of view and compared them with the cluster properties. Our study shows that the mass scaling of both thermal and non-thermal properties of galaxy groups are deviating from cluster scale below 5 × 10 13 M. A prominent break in the scaling laws at 5 × 10 13 M has been observed in computed radio emission as well. We have also estimated the cosmic magnetic field using turbulent dynamo model for these objects and found to be at a level of sub-micro Gauss. Possible radio synchrotron emission from groups have been calculated using both Diffusive Shock Acceleration and Turbulent Re-acceleration models. It is observed that the total emission from some of the groups are much higher than what is expected from existing scaling laws. Such groups must be away from virialization and are at a highly dynamic state. Finally, we have predicted the expected radio flux from these highly active groups for possible detection by future telescopes (e.g. SKA, Upgraded GMRT etc.).