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Observations of teleseismic earthquakes using broadband seismometers on the Ross Ice Shelf (RIS) must contend with environmental and structural processes that do not exist for land-sited seismometers. Important considerations are: (1) a broadband, multi-mode ambient wavefield excited by ocean gravity wave interactions with the ice shelf; (2) body wave reverberations produced by seismic impedance contrasts at the ice/water and water/seafloor interfaces and (3) decoupling of the solid Earth horizontal wavefield by the sub-shelf water column. We analyze seasonal and geographic variations in signal-to-noise ratios for teleseismic P-wave (0.5–2.0 s), S-wave (10–15 s) and surface wave (13–25 s) arrivals relative to the RIS noise field. We use ice and water layer reverberations generated by teleseismic P-waves to accurately estimate the sub-station thicknesses of these layers. We present observations consistent with the theoretically predicted transition of the water column from compressible to incompressible mechanics, relevant for vertically incident solid Earth waves with periods longer than 3 s. Finally, we observe symmetric-mode Lamb waves generated by teleseismic S-waves incident on the grounding zones. Despite their complexity, we conclude that teleseismic coda can be utilized for passive imaging of sub-shelf Earth structure, although longer deployments relative to conventional land-sited seismometers will be necessary to acquire adequate data.
Can multicellular life be distinguished from single cellular life on an exoplanet? We hypothesize that abundant upright photosynthetic multicellular life (trees) will cast shadows at high sun angles that will distinguish them from single cellular life and test this using Earth as an exoplanet. We first test the concept using unmanned aerial vehicles at a replica moon-landing site near Flagstaff, Arizona and show trees have both a distinctive reflectance signature (red edge) and geometric signature (shadows at high sun angles) that can distinguish them from replica moon craters. Next, we calculate reflectance signatures for Earth at several phase angles with POLDER (Polarization and Directionality of Earth's reflectance) satellite directional reflectance measurements and then reduce Earth to a single pixel. We compare Earth to other planetary bodies (Mars, the Moon, Venus and Uranus) and hypothesize that Earth's directional reflectance will be between strongly backscattering rocky bodies with no weathering (like Mars and the Moon) and cloudy bodies with more isotropic scattering (like Venus and Uranus). Our modelling results put Earth in line with strongly backscattering Mars, while our empirical results put Earth in line with more isotropic scattering Venus. We identify potential weaknesses in both the modelled and empirical results and suggest additional steps to determine whether this technique could distinguish upright multicellular life on exoplanets.
Advanced imaging techniques are enhancing research capacity focussed on the developmental origins of adult health and disease (DOHaD) hypothesis, and consequently increasing awareness of future health risks across various subareas of DOHaD research themes. Understanding how these advanced imaging techniques in animal models and human population studies can be both additively and synergistically used alongside traditional techniques in DOHaD-focussed laboratories is therefore of great interest. Global experts in advanced imaging techniques congregated at the advanced imaging workshop at the 2019 DOHaD World Congress in Melbourne, Australia. This review summarizes the presentations of new imaging modalities and novel applications to DOHaD research and discussions had by DOHaD researchers that are currently utilizing advanced imaging techniques including MRI, hyperpolarized MRI, ultrasound, and synchrotron-based techniques to aid their DOHaD research focus.
Cognitive behavior therapy (CBT) is effective for most patients with a social anxiety disorder (SAD) but a substantial proportion fails to remit. Experimental and clinical research suggests that enhancing CBT using imagery-based techniques could improve outcomes. It was hypothesized that imagery-enhanced CBT (IE-CBT) would be superior to verbally-based CBT (VB-CBT) on pre-registered outcomes.
A randomized controlled trial of IE-CBT v. VB-CBT for social anxiety was completed in a community mental health clinic setting. Participants were randomized to IE (n = 53) or VB (n = 54) CBT, with 1-month (primary end point) and 6-month follow-up assessments. Participants completed 12, 2-hour, weekly sessions of IE-CBT or VB-CBT plus 1-month follow-up.
Intention to treat analyses showed very large within-treatment effect sizes on the social interaction anxiety at all time points (ds = 2.09–2.62), with no between-treatment differences on this outcome or clinician-rated severity [1-month OR = 1.45 (0.45, 4.62), p = 0.53; 6-month OR = 1.31 (0.42, 4.08), p = 0.65], SAD remission (1-month: IE = 61.04%, VB = 55.09%, p = 0.59); 6-month: IE = 58.73%, VB = 61.89%, p = 0.77), or secondary outcomes. Three adverse events were noted (substance abuse, n = 1 in IE-CBT; temporary increase in suicide risk, n = 1 in each condition, with one being withdrawn at 1-month follow-up).
Group IE-CBT and VB-CBT were safe and there were no significant differences in outcomes. Both treatments were associated with very large within-group effect sizes and the majority of patients remitted following treatment.
We describe a method to estimate background noise in atom probe tomography (APT) mass spectra and to use this information to enhance both background correction and quantification. Our approach is mathematically general in form for any detector exhibiting Poisson noise with a fixed data acquisition time window, at voltages varying through the experiment. We show that this accurately estimates the background observed in real experiments. The method requires, as a minimum, the z-coordinate and mass-to-charge-state data as input and can be applied retrospectively. Further improvements are obtained with additional information such as acquisition voltage. Using this method allows for improved estimation of variance in the background, and more robust quantification, with quantified count limits at parts-per-million concentrations. To demonstrate applications, we show a simple peak detection implementation, which quantitatively suppresses false positives arising from random noise sources. We additionally quantify the detectability of 121-Sb in a standardized-doped Si microtip as (1.5 × 10−5, 3.8 × 10−5) atomic fraction, α = 0.95. This technique is applicable to all modes of APT data acquisition and is highly general in nature, ultimately allowing for improvements in analyzing low ionic count species in datasets.
Healthcare workers (HCWs) have a theoretically increased risk of contracting severe acute respiratory coronavirus virus 2 (SARS-CoV-2) given their occupational exposure. We tested 2,167 HCWs in a London Acute Integrated Care Organisation for antibodies to SARS-CoV-2 in May and June 2020 to evaluate seroprevalence. We found a seropositivity rate of 31.6% among HCWs.
The growth in wirelessly enabled sensor network technologies has enabled the low cost deployment of sensor platforms with applications in a range of sectors and communities. In the agricultural domain such sensors have been the foundation for the creation of decision support tools that enhance farm operational efficiency. This Research Reflection illustrates how these advances are assisting dairy farmers to optimise performance and illustrates where emerging sensor technology can offer additional benefits. One of the early applications for sensor technology at an individual animal level was the accurate identification of cattle entering into heat (oestrus) to increase the rate of successful pregnancies and thus optimise milk yield per animal. This was achieved through the use of activity monitoring collars and leg tags. Additional information relating to the behaviour of the cattle, namely the time spent eating and ruminating, was subsequently derived from collars giving further insights of economic value into the wellbeing of the animal, thus an enhanced range of welfare related services have been provisioned. The integration of the information from neck-mounted collars with the compositional analysis data of milk measured at a robotic milking station facilitates the early diagnosis of specific illnesses such as mastitis. The combination of different data streams also serves to eliminate the generation of false alarms, improving the decision making capability. The principle of integrating more data streams from deployed on-farm systems, for example, with feed composition data measured at the point of delivery using instrumented feeding wagons, supports the optimisation of feeding strategies and identification of the most productive animals. Optimised feeding strategies reduce operational costs and minimise waste whilst ensuring high welfare standards. These IoT-inspired solutions, made possible through Internet-enabled cloud data exchange, have the potential to make a major impact within farming practices. This paper gives illustrative examples and considers where new sensor technology from the automotive industry may also have a role.
We evaluated the safety and feasibility of high-intensity interval training via a novel telemedicine ergometer (MedBIKE™) in children with Fontan physiology.
The MedBIKE™ is a custom telemedicine ergometer, incorporating a video game platform and live feed of patient video/audio, electrocardiography, pulse oximetry, and power output, for remote medical supervision and modulation of work. There were three study phases: (I) exercise workload comparison between the MedBIKE™ and a standard cardiopulmonary exercise ergometer in 10 healthy adults. (II) In-hospital safety, feasibility, and user experience (via questionnaire) assessment of a MedBIKE™ high-intensity interval training protocol in children with Fontan physiology. (III) Eight-week home-based high-intensity interval trial programme in two participants with Fontan physiology.
There was good agreement in oxygen consumption during graded exercise at matched work rates between the cardiopulmonary exercise ergometer and MedBIKE™ (1.1 ± 0.5 L/minute versus 1.1 ± 0.5 L/minute, p = 0.44). Ten youth with Fontan physiology (11.5 ± 1.8 years old) completed a MedBIKE™ high-intensity interval training session with no adverse events. The participants found the MedBIKE™ to be enjoyable and easy to navigate. In two participants, the 8-week home-based protocol was tolerated well with completion of 23/24 (96%) and 24/24 (100%) of sessions, respectively, and no adverse events across the 47 sessions in total.
The MedBIKE™ resulted in similar physiological responses as compared to a cardiopulmonary exercise test ergometer and the high-intensity interval training protocol was safe, feasible, and enjoyable in youth with Fontan physiology. A randomised-controlled trial of a home-based high-intensity interval training exercise intervention using the MedBIKE™ will next be undertaken.
Systematic monitoring of exanthema is largely absent from public health surveillance despite emerging diseases and threats of bioterrorism. Michigan Child Care Related Infections Surveillance Program (MCRISP) is the first online program in child care centers to report pediatric exanthema.
MCRISP aggregated daily counts of children sick, absent, or reported ill by parents. We extracted all MCRISP exanthema cases from October 1, 2014 through June 30, 2019. Cases were assessed with descriptive statistics and counts were used to construct epidemic curves.
360 exanthema cases were reported from 12,233 illnesses over 4.5 seasons. Children ages 13-35 months had the highest rash occurrence (45%, n = 162), followed by 36-59 months (41.7%, n = 150), 0-12 months (12.5%, n = 45), and kindergarten (0.8%, n = 3). Centers reported rashes of hand-foot-mouth disease (50%, n = 180), nonspecific rash without fever (15.3%, n = 55), hives (8.1%, n = 29), fever with nonspecific rash (6.9%, n = 25), roseola (3.3%, n = 12), scabies (2.5%, n = 9), scarlet fever (2.5%, n = 9), impetigo (2.2%, n = 8), abscess (1.95, n = 7), viral exanthema without fever (1.7%, n = 6), varicella (1.7%, n = 6), pinworms (0.8%, n = 3), molluscum (0.6%, n = 2), cellulitis (0.6%, n = 2), ringworm (0.6%, n = 2), and shingles (0.2%, n = 1).
Child care surveillance networks have the potential to act as sentinel public health tools for surveillance of pediatric exanthema outbreaks.
The coronavirus disease 2019 (COVID-19) has greatly impacted health-care systems worldwide, leading to an unprecedented rise in demand for health-care resources. In anticipation of an acute strain on established medical facilities in Dallas, Texas, federal officials worked in conjunction with local medical personnel to convert a convention center into a Federal Medical Station capable of caring for patients affected by COVID-19. A 200,000 square foot event space was designated as a direct patient care area, with surrounding spaces repurposed to house ancillary services. Given the highly transmissible nature of the novel coronavirus, the donning and doffing of personal protective equipment (PPE) was of particular importance for personnel staffing the facility. Furthermore, nationwide shortages in the availability of PPE necessitated the reuse of certain protective materials. This article seeks to delineate the procedures implemented regarding PPE in the setting of a COVID-19 disaster response shelter, including workspace flow, donning and doffing procedures, PPE conservation, and exposure event protocols.
This paper describes a collaborative approach to professional learning that has provided an opportunity for refreshed practices and growth in capacity in schools supporting students with various learning needs in several schools that are part of the Association of Independent Schools in the Australian Capital Territory. An action research approach to professional learning for school staff was facilitated with the participating schools in 2018/2019, centred on the Nationally Consistent Collection of Data on School Students with Disability.
Resident education in emergency medicine (EM) relies upon a variety of teaching platforms and mediums, including real-life clinical scenarios, simulation, academic day (lectures, small group sessions), journal clubs, and teaching learners. However, the coronavirus disease 2019 (COVID-19) pandemic has disrupted teaching and learning, forcing programs to adapt to ensure residents can progress in their training.1 Suddenly, academic days cannot be held in person, emergency department (ED) volumes are dynamically changing, and the role of residents in ED procedures has been questioned. Furthermore, medical student rotations through the ED have been cancelled, decreasing resident exposure to undergraduate teaching. These changes to resident education threaten resident wellness and will have downstream effects on training and personal professional development. In response, programs must develop strategies to ensure that residents continue receiving high-quality training in a safe learning environment. In this review, we will cover recommended strategies put forth by two large EM programs in Ontario (Table 1).
It is increasingly recognized that existing diagnostic approaches do not capture the underlying heterogeneity and complexity of psychiatric disorders such as depression. This study uses a data-driven approach to define fluid depressive states and explore how patients transition between these states in response to cognitive behavioural therapy (CBT).
Item-level Patient Health Questionnaire (PHQ-9) data were collected from 9891 patients with a diagnosis of depression, at each CBT treatment session. Latent Markov modelling was used on these data to define depressive states and explore transition probabilities between states. Clinical outcomes and patient demographics were compared between patients starting at different depressive states.
A model with seven depressive states emerged as the best compromise between optimal fit and interpretability. States loading preferentially on cognitive/affective v. somatic symptoms of depression were identified. Analysis of transition probabilities revealed that patients in cognitive/affective states do not typically transition towards somatic states and vice-versa. Post-hoc analyses also showed that patients who start in a somatic depressive state are less likely to engage with or improve with therapy. These patients are also more likely to be female, suffer from a comorbid long-term physical condition and be taking psychotropic medication.
This study presents a novel approach for depression sub-typing, defining fluid depressive states and exploring transitions between states in response to CBT. Understanding how different symptom profiles respond to therapy will inform the development and delivery of stratified treatment protocols, improving clinical outcomes and cost-effectiveness of psychological therapies for patients with depression.