Two-fluid Physical Modeling of Superconducting Resonators in the ARTEMIS Framework

In this work, we implement a new London equation module for superconductivity in the GPU-enabled ARTEMIS framework, and couple it to a finite-difference time-domain solver for Maxwell's equations. We apply this two-fluid approach to model a superconducting coplanar waveguide (CPW) resonator. We validate our implementation by verifying that the theoretical skin depth and reflection coefficients can be obtained for several superconductive materials, with different London penetration depths, over a range of frequencies. Our convergence studies show that the algorithm is second-order accurate in both space and time, except at superconducting interfaces where the approach is spatially first-order. In our CPW simulations, we leverage the GPU scalability of our code to compare the two-fluid model to more traditional approaches that approximate superconducting behavior and demonstrate that superconducting physics can show comparable performance to the assumption of quasi-infinite conductivity as measured by the Q-factor

Do birds of a feather flock together? Comparing habitat preferences of piscivorous waterbirds in a lowland river catchment

Waterbirds can move into and exploit new areas of suitable habitat outside of their native range. One such example is the little egret (Egretta garzetta), a piscivorous bird which has colonised southern Britain within the last 30 years. Yet, habitat use by little egrets within Britain, and how such patterns of habitat exploitation compare with native piscivores, remains unknown. We examine overlap in habitat preferences within a river catchment between the little egret and two native species, the grey heron (Ardea cinerea) and great cormorant (Phalacrocorax carbo). All species showed strong preferences for river habitat in all seasons, with other habitat types used as auxiliary feeding areas. Seasonal use of multiple habitat types is consistent with egret habitat use within its native range. We found strong egret preference for aquatic habitats, in particular freshwaters, compared with pasture and arable agricultural habitat. Egrets showed greater shared habitat preferences with herons, the native species to which egrets are most morphologically and functionally similar. This is the first study to quantify little egret habitat preferences outside of its native range

Remote assessment of disease and relapse in major depressive disorder (RADAR-MDD): recruitment, retention, and data availability in a longitudinal remote measurement study

BACKGROUND: Major Depressive Disorder (MDD) is prevalent, often chronic, and requires ongoing monitoring of symptoms to track response to treatment and identify early indicators of relapse. Remote Measurement Technologies (RMT) provide an opportunity to transform the measurement and management of MDD, via data collected from inbuilt smartphone sensors and wearable devices alongside app-based questionnaires and tasks. A key question for the field is the extent to which participants can adhere to research protocols and the completeness of data collected. We aimed to describe drop out and data completeness in a naturalistic multimodal longitudinal RMT study, in people with a history of recurrent MDD. We further aimed to determine whether those experiencing a depressive relapse at baseline contributed less complete data. METHODS: Remote Assessment of Disease and Relapse – Major Depressive Disorder (RADAR-MDD) is a multi-centre, prospective observational cohort study conducted as part of the Remote Assessment of Disease and Relapse – Central Nervous System (RADAR-CNS) program. People with a history of MDD were provided with a wrist-worn wearable device, and smartphone apps designed to: a) collect data from smartphone sensors; and b) deliver questionnaires, speech tasks, and cognitive assessments. Participants were followed-up for a minimum of 11 months and maximum of 24 months. RESULTS: Individuals with a history of MDD (n = 623) were enrolled in the study,. We report 80% completion rates for primary outcome assessments across all follow-up timepoints. 79.8% of people participated for the maximum amount of time available and 20.2% withdrew prematurely. We found no evidence of an association between the severity of depression symptoms at baseline and the availability of data. In total, 110 participants had > 50% data available across all data types. CONCLUSIONS: RADAR-MDD is the largest multimodal RMT study in the field of mental health. Here, we have shown that collecting RMT data from a clinical population is feasible. We found comparable levels of data availability in active and passive forms of data collection, demonstrating that both are feasible in this patient group. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12888-022-03753-1