With human influences driving populations of apex predators into decline, more information is required on how factors affect species at national and global scales. However, camera-trap studies are seldom executed at a broad spatial scale. We demonstrate how uniting fine-scale studies and utilizing camera-trap data of non-target species is an effective approach for broadscale assessments through a case study of the brown hyaena Parahyaena brunnea. We collated camera-trap data from 25 protected and unprotected sites across South Africa into the largest detection/non-detection dataset collected on the brown hyaena, and investigated the influence of biological and anthropogenic factors on brown hyaena occupancy. Spatial autocorrelation had a significant effect on the data, and was corrected using a Bayesian Gibbs sampler. We show that brown hyaena occupancy is driven by specific co-occurring apex predator species and human disturbance. The relative abundance of spotted hyaenas Crocuta crocuta and people on foot had a negative effect on brown hyaena occupancy, whereas the relative abundance of leopards Panthera pardus and vehicles had a positive influence. We estimated that brown hyaenas occur across 66% of the surveyed camera-trap station sites. Occupancy varied geographically, with lower estimates in eastern and southern South Africa. Our findings suggest that brown hyaena conservation is dependent upon a multi-species approach focussed on implementing conservation policies that better facilitate coexistence between people and hyaenas. We also validate the conservation value of pooling fine-scale datasets and utilizing bycatch data to examine species trends at broad spatial scales.

Each summer, surface melting of the margin of the Greenland Ice Sheet exposes a distinctive visible stratigraphy that is related to past variability in subaerial dust deposition across the accumulation zone and subsequent ice flow toward the margin. Here we map this surface stratigraphy along the northern margin of the ice sheet using mosaicked Sentinel-2 multispectral satellite imagery from the end of the 2019 melt season and finer-resolution WorldView-2/3 imagery for smaller regions of interest. We trace three distinct transitions in apparent dust concentration and the top of a darker basal layer. The three dust transitions have been identified previously as representing late-Pleistocene climatic transitions, allowing us to develop a coarse margin chronostratigraphy for northern Greenland. Substantial folding of late-Pleistocene stratigraphy is observed but uncommon. The oldest conformal surface-exposed ice in northern Greenland is likely located adjacent to Warming Land and may be up to ~55 thousand years old. Basal ice is commonly exposed hundreds of metres from the ice margin and may indicate a widespread frozen basal thermal state. We conclude that the ice margin across northern Greenland offers multiple opportunities to recover paleoclimatically distinct ice relative to previously studied regions in southwestern Greenland.

Clinical and Translational Science Award (CTSA) TL1 trainees and KL2 scholars were surveyed to determine the immediate impact of the COVID-19 pandemic on training and career development. The most negative impact was lack of access to research facilities, clinics, and human subjects, plus for KL2 scholars lack of access to team members and need for homeschooling. TL1 trainees reported having more time to think and write. Common strategies to maintain research productivity involved time management, virtual connections with colleagues, and shifting to research activities not requiring laboratory/clinic settings. Strategies for mitigating the impact of the COVID-19 pandemic on training and career development are described.

Bipartite networks represent pairwise relationships between nodes belonging to two distinct classes. While established methods exist for analyzing unipartite networks, those for bipartite network analysis are somewhat obscure and relatively less developed. Community detection in such instances is frequently approached by first projecting the network onto a unipartite network, a method where edges between node classes are encoded as edges within one class. Here we test seven different projection schemes by assessing the performance of community detection on both: (i) a real-world dataset from social media and (ii) an ensemble of artificial networks with prescribed community structure. A number of performance and accuracy issues become apparent from the experimental findings, especially in the case of long-tailed degree distributions. Of the methods tested, the “hyperbolic” projection scheme alleviates most of these difficulties and is thus the most robust scheme of those tested. We conclude that any interpretation of community detection algorithm performance on projected networks must be done with care as certain network configurations require strong community preference for the bipartite structure to be reflected in the unipartite communities. Our results have implications for the analysis of detected community structure in projected unipartite networks.

The functional Catechol-O-methyltransferase (COMT Val 108/158 Met) polymorphism has been shown to have an impact on tasks of executive function, memory and attention and recently, tasks with an affective component. As estrogen may downregulate COMT, we were interested in the effect of gender, COMT genotype and the interaction between these factors on brain activations during an affective processing task. We used functional MRI to record brain activations from 74 healthy subjects who engaged in a facial affect recognition task; subjects viewed and identified fearful faces compared to neutral faces. We found a significant effect of gender on brain activations in the left amygdala and right superior temporal gyrus, where females demonstrated increased activations over males. Within these regions, female val/val carriers showed greater activity compared to met/met carriers, while male participants with a met/met allele showed greater deactivations compared to val/val carriers. There was no main effect of the COMT polymorphism, gender or genotype by gender interaction on task performance. We propose that the observed effects of gender and COMT allele on brain activations arise from differences in dopamine levels in these groups and that the gender differences and gender genotype interaction may be due to the downregulation of COMT by estrogen.

Around a quarter of people suffering from psychotic conditions, like schizophrenia, continue to experience auditory hallucinations despite adequate drug treatment. In addition to medication, some help is also provided by psychological interventions, particularly cognitive behavioural therapy for psychosis (CBTp). AVATAR therapy is based on computer technology which enables each patient to create an avatar of the entity (human or non-human) that they believe is talking to them. The therapist promotes a dialogue between the patient and the avatar in which the avatar progressively comes under the patient's control. These sessions are audio recorded and provided to the patient on an MP3 player for continued use at home. In an initial pilot study, a maximum of 7 sessions lasting 30 minutes resulted in highly significant reductions in the patients’ hallucinations and the associated distress, enhancing the quality of their life (Leff et al., 2013). Our objective is to replicate the findings of this pilot study of the AVATAR therapy. We will carry out a randomised controlled evaluation of computer assisted voice therapy compared to supportive counselling to determine preliminary estimates of both effectiveness and cost-effectiveness. The study aims to recruit 142 people who have suffered from auditory hallucinations for at least 12 months despite taking medication regularly. Participants will complete a number of selfcompleted and interview based measures (on four assessment points: pre-treatment, post treatment, and then at 12 and 24 weeks follow-up) to assess the impact of interventions on outcomes and to explore potential mediators and modifiers of therapy.

This work focuses on understanding the formation of the first massive, passive galaxies in clusters, as a first step to the development of environmental trends seen at low redshift. Cl J1449 + 0856 is an excellent case to study this - a galaxy cluster at redshift z = 1.99 that already shows evidence of a virialised atmosphere. Here we highlight two recent results: the discovery of merger-driven star formation and highly-excited molecular gas in galaxies at the core of Cl J1449, along with the lowest-mass Sunyaev-Zel’dovich detection to date.

We present the latest data release of the Planetary Nebulae Spectrograph Survey (PNS) of ten lenticular galaxies and two spiral galaxies. With this data set we are able to recover the galaxies’ kinematics out to several effective radii. We use a maximum likelihood method to decompose the disk and spheroid kinematics and we compare it with the kinematics of spiral and elliptical galaxies. We build the Tully- Fisher (TF) relation for these galaxies and we compare with data from the literature and simulations. We find that the disks of lenticular galaxies are hotter than the disks of spiral galaxies at low redshifts, but still dominated by rotation velocity. The mechanism responsible for the formation of these lenticular galaxies is neither major mergers, nor a gentle quenching driven by stripping or Active Galactic Nuclei (AGN) feedback.

We present a machine learning methodology to separate quasars from galaxies and stars using data from S-PLUS in the Stripe-82 region. In terms of quasar classification, we achieved 95.49% for precision and 95.26% for recall using a Random Forest algorithm. For photometric redshift estimation, we obtained a precision of 6% using k-Nearest Neighbour.

We have analyzed Chandra/High Energy Transmission Grating spectra of the X-ray emission line gas in the Seyfert galaxy NGC 4151. The zeroth-order spectral images show extended H- and He-like O and Ne, up to a distance r ˜ 200 pc from the nucleus. Using the 1st-order spectra, we measure an average line velocity ˜230 km s–1, suggesting significant outflow of X-ray gas. We generated Cloudy photoionization models to fit the 1st-order spectra; the fit required three distinct emission-line components. To estimate the total mass of ionized gas (M) and the mass outflow rates, we applied the model parameters to fit the zeroth-order emission-line profiles of Ne IX and Ne X. We determined an M ≍ 5.4 × 105 Mʘ. Assuming the same kinematic profile as that for the [O III] gas, derived from our analysis of Hubble Space Telescope/Space Telescope Imaging Spectrograph spectra, the peak X-ray mass outflow rate is approximately 1.8 Mʘ yr–1, at r ˜ 150 pc. The total mass and mass outflow rates are similar to those determined using [O III], implying that the X-ray gas is a major outflow component. However, unlike the optical outflows, the X-ray emitting mass outflow rate does not drop off at r > 100pc, which suggests that it may have a greater impact on the host galaxy.