Perspectives on self-managed abortion among providers in hospitals along the Texas– Mexico border

Background Following self-managed abortion (SMA), or a pregnancy termination attempt outside of the formal health system, some patients may seek care in an emergency department. Information about provider experiences treating these patients in hospital settings on the Texas-Mexico border is lacking. Methods The study team conducted semi-structured interviews with physicians, advanced practice clinicians, and nurses who had experience with patients presenting with early pregnancy complications in emergency and/or labor and delivery departments in five hospitals near the Texas-Mexico border. Interview questions focused on respondents’ roles at the hospital, knowledge of abortion services and laws, perspectives on SMA trends, experiences treating patients presenting after SMA, and potential gaps in training related to abortion. Researchers conducted interviews in person between October 2017 and January 2018, and analyzed transcripts using a thematic analysis approach. Results Most of the 54 participants interviewed said that the care provided to SMA patients was, and should be, the same as for patients presenting after miscarriage. The majority had treated a patient they suspected or confirmed had attempted SMA; typically, these cases required only expectant management and confirmation of pregnancy termination, or treatment for incomplete abortion. In rare cases, further clinical intervention was required. Many providers lacked clinical and legal knowledge about abortion, including local resources available. Conclusions Treatment provided to SMA patients is similar to that provided to patients presenting after early pregnancy loss. Lack of provider knowledge about abortion and SMA, despite their involvement with SMA patients, highlights a need for improved training

Volcanic Hazard Assessment for an Eruption Hiatus, or Post-eruption Unrest Context: Modeling Continued Dome Collapse Hazards for Soufrière Hills Volcano

Effective volcanic hazard management in regions where populations live in close proximity to persistent volcanic activity involves understanding the dynamic nature of hazards, and associated risk. Emphasis until now has been placed on identification and forecasting of the escalation phase of activity, in order to provide adequate warning of what might be to come. However, understanding eruption hiatus and post-eruption unrest hazards, or how to quantify residual hazard after the end of an eruption, is also important and often key to timely post-eruption recovery. Unfortunately, in many cases when the level of activity lessens, the hazards, although reduced, do not necessarily cease altogether. This is due to both the imprecise nature of determination of the “end” of an eruptive phase as well as to the possibility that post-eruption hazardous processes may continue to occur. An example of the latter is continued dome collapse hazard from lava domes which have ceased to grow, or sector collapse of parts of volcanic edifices, including lava dome complexes. We present a new probabilistic model for forecasting pyroclastic density currents (PDCs) from lava dome collapse that takes into account the heavy-tailed distribution of the lengths of eruptive phases, the periods of quiescence, and the forecast window of interest. In the hazard analysis, we also consider probabilistic scenario models describing the flow’s volume and initial direction. Further, with the use of statistical emulators, we combine these models with physics-based simulations of PDCs at Soufrière Hills Volcano to produce a series of probabilistic hazard maps for flow inundation over 5, 10, and 20 year periods. The development and application of this assessment approach is the first of its kind for the quantification of periods of diminished volcanic activity. As such, it offers evidence-based guidance for dome collapse hazards that can be used to inform decision-making around provisions of access and reoccupation in areas around volcanoes that are becoming less active over time

Pooling strength amongst limited datasets using hierarchical Bayesian analysis, with application to pyroclastic density current mobility metrics

In volcanology, the sparsity of datasets for individual volcanoes is an important problem, which, in many cases, compromises our ability to make robust judgments about future volcanic hazards. In this contribution we develop a method for using hierarchical Bayesian analysis of global datasets to combine information across different volcanoes and to thereby improve our knowledge at individual volcanoes. The method is applied to the assessment of mobility metrics for pyroclastic density currents in order to better constrain input parameters and their related uncertainties for forward modeling. Mitigation of risk associated with such flows depends upon accurate forecasting of possible inundation areas, often using empirical models that rely on mobility metrics measured from the deposits of past flows, or on the application of computational models, several of which take mobility metrics, either directly or indirectly, as input parameters. We use hierarchical Bayesian modeling to leverage the global record of mobility metrics from the FlowDat database, leading to considerable improvement in the assessment of flow mobility where the data for a particular volcano is sparse. We estimate the uncertainties involved and demonstrate how they are improved through this approach. The method has broad applicability across other areas of volcanology where relationships established from broader datasets can be used to better constrain more specific, sparser, datasets. Employing such methods allows us to use, rather than shy away from, limited datasets, and allows for transparency with regard to uncertainties, enabling more accountable decision-making

Thermal Remote Sensing for Global Volcano Monitoring: Experiences From the MIROVA System

Volcanic activity is always accompanied by the transfer of heat from the Earth’s crust to the atmosphere. This heat can be measured from space and its measurement is a very useful tool for detecting volcanic activity on a global scale. MIROVA (Middle Infrared Observation of Volcanic Activity) is an automatic volcano hot spot detection system, based on the analysis of MODIS data (Moderate Resolution Imaging Spectroradiometer). The system is able to detect, locate and quantify thermal anomalies in near real-time, by providing, on a dedicated website (www.mirovaweb.it), infrared images and thermal flux time-series on over 200 volcanoes worldwide. Thanks to its simple interface and intuitive representation of the data, MIROVA is currently used by several volcano observatories for daily monitoring activities and reporting. In this paper, we present the architecture of the system and we provide a state of the art on satellite thermal data usage for operational volcano monitoring and research. In particular, we describe the contribution that the thermal data have provided in order to detect volcanic unrest, to forecast eruptions and to depict trends and patterns during eruptive crisis. The current limits and requirements to improve the quality of the data, their distribution and interpretation are also discussed, in the light of the experience gained in recent years within the volcanological community. The results presented clearly demonstrate how the open access of satellite thermal data and the sharing of derived products allow a better understanding of ongoing volcanic phenomena, and therefore constitute an essential requirement for the assessment of volcanic hazards

Thermal Remote Sensing for Global Volcano Monitoring: Experiences From the MIROVA System

Volcanic activity is always accompanied by the transfer of heat from the Earth's crust to the atmosphere. This heat can be measured from space and its measurement is a very useful tool for detecting volcanic activity on a global scale. MIROVA (Middle Infrared Observation of Volcanic Activity) is an automatic volcano hot spot detection system, based on the analysis of MODIS data (Moderate Resolution Imaging Spectroradiometer). The system is able to detect, locate and quantify thermal anomalies in near real-time, by providing, on a dedicated website (www.mirovaweb.it), infrared images and thermal flux time-series on over 200 volcanoes worldwide. Thanks to its simple interface and intuitive representation of the data, MIROVA is currently used by several volcano observatories for daily monitoring activities and reporting. In this paper, we present the architecture of the system and we provide a state of the art on satellite thermal data usage for operational volcano monitoring and research. In particular, we describe the contribution that the thermal data have provided in order to detect volcanic unrest, to forecast eruptions and to depict trends and patterns during eruptive crisis. The current limits and requirements to improve the quality of the data, their distribution and interpretation are also discussed, in the light of the experience gained in recent years within the volcanological community. The results presented clearly demonstrate how the open access of satellite thermal data and the sharing of derived products allow a better understanding of ongoing volcanic phenomena, and therefore constitute an essential requirement for the assessment of volcanic hazards. Peer reviewe

Experimental warming differentially affects vegetative and reproductive phenology of tundra plants

Rapid climate warming is altering Arctic and alpine tundra ecosystem structure and function, including shifts in plant phenology. While the advancement of green up and flowering are well-documented, it remains unclear whether all phenophases, particularly those later in the season, will shift in unison or respond divergently to warming. Here, we present the largest synthesis to our knowledge of experimental warming effects on tundra plant phenology from the International Tundra Experiment. We examine the effect of warming on a suite of season-wide plant phenophases. Results challenge the expectation that all phenophases will advance in unison to warming. Instead, we find that experimental warming caused: (1) larger phenological shifts in reproductive versus vegetative phenophases and (2) advanced reproductive phenophases and green up but delayed leaf senescence which translated to a lengthening of the growing season by approximately 3%. Patterns were consistent across sites, plant species and over time. The advancement of reproductive seasons and lengthening of growing seasons may have significant consequences for trophic interactions and ecosystem function across the tundra.publishedVersio

Platform adaptive trial of novel antivirals for early treatment of COVID-19 In the community (PANORAMIC): protocol for a randomised, controlled, open-label, adaptive platform trial of community novel antiviral treatment of COVID-19 in people at increased risk of more severe disease

Introduction: There is an urgent need to determine the safety, effectiveness and cost-effectiveness of novel antiviral treatments for COVID-19 in vaccinated patients in the community at increased risk of morbidity and mortality from COVID-19. // Methods and analysis: PANORAMIC is a UK-wide, open-label, prospective, adaptive, multiarm platform, randomised clinical trial that evaluates antiviral treatments for COVID-19 in the community. A master protocol governs the addition of new antiviral treatments as they become available, and the introduction and cessation of existing interventions via interim analyses. The first two interventions to be evaluated are molnupiravir (Lagevrio) and nirmatrelvir/ritonavir (Paxlovid). Eligibility criteria: community-dwelling within 5 days of onset of symptomatic COVID-19 (confirmed by PCR or lateral flow test), and either (1) aged 50 years and over, or (2) aged 18–49 years with qualifying comorbidities. Registration occurs via the trial website and by telephone. Recruitment occurs remotely through the central trial team, or in person through clinical sites. Participants are randomised to receive either usual care or a trial drug plus usual care. Outcomes are collected via a participant-completed daily electronic symptom diary for 28 days post randomisation. Participants and/or their Trial Partner are contacted by the research team after days 7, 14 and 28 if the diary is not completed, or if the participant is unable to access the diary. The primary efficacy endpoint is all-cause, non-elective hospitalisation and/or death within 28 days of randomisation. Multiple prespecified interim analyses allow interventions to be stopped for futility or superiority based on prespecified decision criteria. A prospective economic evaluation is embedded within the trial. // Ethics and dissemination: Ethical approval granted by South Central–Berkshire REC number: 21/SC/0393; IRAS project ID: 1004274. Results will be presented to policymakers and at conferences, and published in peer-reviewed journals. // Trial registration number: ISRCTN30448031; EudraCT number: 2021-005748-31

Analysis of Temperature-to-Polarization Leakage in BICEP3 and Keck CMB Data from 2016 to 2018

The Bicep/Keck Array experiment is a series of small-aperture refracting telescopes observing degree-scale Cosmic Microwave Background polarization from the South Pole in search of a primordial B-mode signature. As a pair differencing experiment, an important systematic that must be controlled is the differential beam response between the co-located, orthogonally polarized detectors. We use high-fidelity, in-situ measurements of the beam response to estimate the temperature-to-polarization (T → P) leakage in our latest data including observations from 2016 through 2018. This includes three years of Bicep3 observing at 95 GHz, and multifrequency data from Keck Array. Here we present band-averaged far-field beam maps, differential beam mismatch, and residual beam power (after filtering out the leading difference modes via deprojection) for these receivers. We show preliminary results of "beam map simulations," which use these beam maps to observe a simulated temperature (no Q/U) sky to estimate T → P leakage in our real data

Polarization calibration of the BICEP3 CMB polarimeter at the South Pole

The BICEP3 CMB Polarimeter is a small-aperture refracting telescope located at the South Pole and is specifically designed to search for the possible signature of inflationary gravitational waves in the Cosmic Microwave Background (CMB). The experiment measures polarization on the sky by differencing the signal of co-located, orthogonally polarized antennas coupled to Transition Edge Sensor (TES) detectors. We present precise measurements of the absolute polarization response angles and polarization efficiencies for nearly all of BICEP3's ~800 functioning polarization-sensitive detector pairs from calibration data taken in January 2018. Using a Rotating Polarized Source (RPS), we mapped polarization response for each detector over a full 360 degrees of source rotation and at multiple telescope boresight rotations from which per-pair polarization properties were estimated. In future work, these results will be used to constrain signals predicted by exotic physical models such as Cosmic Birefringence