High-vacuum-compatible high-power Faraday isolators for gravitational-wave interferometers

Faraday isolators play a key role in the operation of large-scale gravitational-wave detectors. Second-generation gravitational-wave interferometers such as the Advanced Laser Interferometer Gravitational-Wave Observatory (LIGO) and Advanced Virgo will use high-average-power cw lasers (up to 200 W) requiring specially designed Faraday isolators that are immune to the effects resulting from the laser beam absorption–degraded isolation ratio, thermal lensing, and thermally induced beam steering. In this paper, we present a comprehensive study of Faraday isolators designed specifically for high-performance operation in high-power gravitational-wave interferometers

Randomised controlled feasibility trial of a web-based weight management intervention with nurse support for obese patients in primary care

<b>Background</b><p></p> There is a need for cost-effective weight management interventions that primary care can deliver to reduce the morbidity caused by obesity. Automated web-based interventions might provide a solution, but evidence suggests that they may be ineffective without additional human support. The main aim of this study was to carry out a feasibility trial of a web-based weight management intervention in primary care, comparing different levels of nurse support, to determine the optimal combination of web-based and personal support to be tested in a full trial.<p></p> <b>Methods</b><p></p> This was an individually randomised four arm parallel non-blinded trial, recruiting obese patients in primary care. Following online registration, patients were randomly allocated by the automated intervention to either usual care, the web-based intervention only, or the web-based intervention with either basic nurse support (3 sessions in 3 months) or regular nurse support (7 sessions in 6 months). The main outcome measure (intended as the primary outcome for the main trial) was weight loss in kg at 12 months. As this was a feasibility trial no statistical analyses were carried out, but we present means, confidence intervals and effect sizes for weight loss in each group, uptake and retention, and completion of intervention components and outcome measures.<p></p> <b>Results</b><p></p> All randomised patients were included in the weight loss analyses (using Last Observation Carried Forward). At 12 months mean weight loss was: usual care group (n = 43) 2.44 kg; web-based only group (n = 45) 2.30 kg; basic nurse support group (n = 44) 4.31 kg; regular nurse support group (n = 47) 2.50 kg. Intervention effect sizes compared with usual care were: d = 0.01 web-based; d = 0.34 basic nurse support; d = 0.02 regular nurse support. Two practices deviated from protocol by providing considerable weight management support to their usual care patients.<p></p> <b>Conclusions</b><p></p> This study demonstrated the feasibility of delivering a web-based weight management intervention supported by practice nurses in primary care, and suggests that the combination of the web-based intervention with basic nurse support could provide an effective solution to weight management support in a primary care context

Labeling poststorm coastal imagery for machine learning: measurement of interrater agreement

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Goldstein, E. B., Buscombe, D., Lazarus, E. D., Mohanty, S. D., Rafique, S. N., Anarde, K. A., Ashton, A. D., Beuzen, T., Castagno, K. A., Cohn, N., Conlin, M. P., Ellenson, A., Gillen, M., Hovenga, P. A., Over, J.-S. R., Palermo, R., Ratliff, K. M., Reeves, I. R. B., Sanborn, L. H., Straub, J. A., Taylor, L. A., Wallace E. J., Warrick, J., Wernette, P., Williams, H. E. Labeling poststorm coastal imagery for machine learning: measurement of interrater agreement. Earth and Space Science, 8(9), (2021): e2021EA001896, https://doi.org/10.1029/2021EA001896.Classifying images using supervised machine learning (ML) relies on labeled training data—classes or text descriptions, for example, associated with each image. Data-driven models are only as good as the data used for training, and this points to the importance of high-quality labeled data for developing a ML model that has predictive skill. Labeling data is typically a time-consuming, manual process. Here, we investigate the process of labeling data, with a specific focus on coastal aerial imagery captured in the wake of hurricanes that affected the Atlantic and Gulf Coasts of the United States. The imagery data set is a rich observational record of storm impacts and coastal change, but the imagery requires labeling to render that information accessible. We created an online interface that served labelers a stream of images and a fixed set of questions. A total of 1,600 images were labeled by at least two or as many as seven coastal scientists. We used the resulting data set to investigate interrater agreement: the extent to which labelers labeled each image similarly. Interrater agreement scores, assessed with percent agreement and Krippendorff's alpha, are higher when the questions posed to labelers are relatively simple, when the labelers are provided with a user manual, and when images are smaller. Experiments in interrater agreement point toward the benefit of multiple labelers for understanding the uncertainty in labeling data for machine learning research.The authors gratefully acknowledge support from the U.S. Geological Survey (G20AC00403 to EBG and SDM), NSF (1953412 to EBG and SDM; 1939954 to EBG), Microsoft AI for Earth (to EBG and SDM), The Leverhulme Trust (RPG-2018-282 to EDL and EBG), and an Early Career Research Fellowship from the Gulf Research Program of the National Academies of Sciences, Engineering, and Medicine (to EBG). U.S. Geological Survey researchers (DB, J-SRO, JW, and PW) were supported by the U.S. Geological Survey Coastal and Marine Hazards and Resources Program as part of the response and recovery efforts under congressional appropriations through the Additional Supplemental Appropriations for Disaster Relief Act, 2019 (Public Law 116-20; 133 Stat. 871)

Rationale and design of the Multicenter Medication Reconciliation Quality Improvement Study (MARQUIS)

Background: Unresolved medication discrepancies during hospitalization can contribute to adverse drug events, resulting in patient harm. Discrepancies can be reduced by performing medication reconciliation; however, effective implementation of medication reconciliation has proven to be challenging. The goals of the Multi-Center Medication Reconciliation Quality Improvement Study (MARQUIS) are to operationalize best practices for inpatient medication reconciliation, test their effect on potentially harmful unintentional medication discrepancies, and understand barriers and facilitators of successful implementation. Methods: Six U.S. hospitals are participating in this quality improvement mentored implementation study. Each hospital has collected baseline data on the primary outcome: the number of potentially harmful unintentional medication discrepancies per patient, as determined by a trained on-site pharmacist taking a “gold standard” medication history. With the guidance of their mentors, each site has also begun to implement one or more of 11 best practices to improve medication reconciliation. To understand the effect of the implemented interventions on hospital staff and culture, we are performing mixed methods program evaluation including surveys, interviews, and focus groups of front line staff and hospital leaders. Discussion At baseline the number of unintentional medication discrepancies in admission and discharge orders per patient varies by site from 2.35 to 4.67 (mean=3.35). Most discrepancies are due to history errors (mean 2.12 per patient) as opposed to reconciliation errors (mean 1.23 per patient). Potentially harmful medication discrepancies averages 0.45 per patient and varies by site from 0.13 to 0.82 per patient. We discuss several barriers to implementation encountered thus far. In the end, we anticipate that MARQUIS tools and lessons learned have the potential to decrease medication discrepancies and improve patient outcomes. Trial registration Clinicaltrials.gov identifier NCT0133706

Invasion of the Red Seaweed \u3cem\u3eHeterosiphonia japonica\u3c/em\u3e Spans Biogeographic Provinces in the Western North Atlantic Ocean

The recent invasion of the red alga Heterosiphonia japonica in the western North Atlantic Ocean has provided a unique opportunity to study invasion dynamics across a biogeographical barrier. Native to the western North Pacific Ocean, initial collections in 2007 and 2009 restricted the western North Atlantic range of this invader to Rhode Island, USA. However, through subtidal community surveys, we document the presence of Heterosiphonia in coastal waters from Maine to New York, USA, a distance of more than 700 km. This geographical distribution spans a well-known biogeographical barrier at Cape Cod, Massachusetts. Despite significant differences in subtidal community structure north and south of Cape Cod, Heterosiphonia was found at all but two sites surveyed in both biogeographic provinces, suggesting that this invader is capable of rapid expansion over broad geographic ranges. Across all sites surveyed, Heterosiphonia comprised 14% of the subtidal benthic community. However, average abundances of nearly 80% were found at some locations. As a drifting macrophyte, Heterosiphonia was found as intertidal wrack in abundances of up to 65% of the biomass washed up along beaches surveyed. Our surveys suggest that the high abundance of Heterosiphonia has already led to marked changes in subtidal community structure; we found significantly lower species richness in recipient communities with higher Heterosiphona abundances. Based on temperature and salinity tolerances of the European populations, we believe Heterosiphonia has the potential to invade and alter subtidal communities from Florida to Newfoundland in the western North Atlantic

Applying refinement to the use of mice and rats in rheumatoid arthritis research

Rheumatoid arthritis (RA) is a painful, chronic disorder and there is currently an unmet need for effective therapies that will benefit a wide range of patients. The research and development process for therapies and treatments currently involves in vivo studies, which have the potential to cause discomfort, pain or distress. This Working Group report focuses on identifying causes of suffering within commonly used mouse and rat ‘models’ of RA, describing practical refinements to help reduce suffering and improve welfare without compromising the scientific objectives. The report also discusses other, relevant topics including identifying and minimising sources of variation within in vivo RA studies, the potential to provide pain relief including analgesia, welfare assessment, humane endpoints, reporting standards and the potential to replace animals in RA research

An International Contrast of Rates of Placental Abruption : An Age-Period-Cohort Analysis

Background Although rare, placental abruption is implicated in disproportionately high rates of perinatal morbidity and mortality. Understanding geographic and temporal variations may provide in-sights into possible amenable factors of abruption. We examined abruption frequencies by maternal age, delivery year, and maternal birth cohorts over three decades across seven countries. Methods Women that delivered in the US (n = 863,879; 1979-10), Canada (4 provinces, n = 5,407,463; 1982-11), Sweden (n = 3,266,742; 1978-10), Denmark (n = 1,773,895; 197808), Norway (n = 1,780,271, 1978-09), Finland (n = 1,411,867; 1987-10), and Spain (n = 6,151,508; 1999-12) were analyzed. Abruption diagnosis was based on ICD coding. Rates were modeled using Poisson regression within the framework of an age-period-cohort analysis, and multi-level models to examine the contribution of smoking in four countries. Results Abruption rates varied across the seven countries (3-10 per 1000), Maternal age showed a consistent J-shaped pattern with increased rates at the extremes of the age distribution. In comparison to births in 2000, births after 2000 in European countries had lower abruption rates; in the US there was an increase in rate up to 2000 and a plateau thereafter. No birth cohort effects were evident. Changes in smoking prevalence partially explained the period effect in the US (P = 0.01) and Sweden (P <0.01). Conclusions There is a strong maternal age effect on abruption. While the abruption rate has plateaued since 2000 in the US, all other countries show declining rates. These findings suggest considerable variation in abruption frequencies across countries; differences in the distribution of risk factors, especially smoking, may help guide policy to reduce abruption rates.Peer reviewe

First spectroscopic observations of the galaxies that reionized the Universe

Low-mass galaxies in the early universe are believed to be the building blocks of present-day galaxies. These fledgling systems likely played a pivotal role in cosmic reionization, a major phase transition from neutral Hydrogen to ionized plasma around 600-800 Myr after the Big Bang. However, these galaxies have eluded comprehensive spectroscopic studies owing to their extreme faintness. Here we report the first spectroscopic analysis of 8 ultra-faint galaxies during the epoch of reionization with absolute magnitudes between M$_{\rm UV}$ $\sim -17$ to $-15$ mag (down to 0.005 $L^{\star}$). The combination of ultra-deep NIRSpec (Near-Infrared Spectrograph) observations and the strong gravitational lensing boost of Abell~2744 allow us to derive the first spectroscopic constraints on the prevalence of faint galaxies and their ionizing properties during the Universe's first billion years. We find that faint galaxies are prodigious producers of ionizing photons with log($\xi_{\rm ion}$/ Hz erg$^{-1}$) =$25.8\pm 0.05$, a factor of 4 larger than canonical values. This means that the total rate of ionizing photons produced by galaxies exceeds that needed for reionization, even for modest values of escape fraction ($f_{\rm esc}$ =5%). These findings provide robust evidence that faint galaxies were the main drivers of cosmic reionization at $z\sim7$.Comment: 29 pages, 7 figures, 2 table

Genome sequence of an Australian kangaroo, Macropus eugenii, provides insight into the evolution of mammalian reproduction and development.

BACKGROUND: We present the genome sequence of the tammar wallaby, Macropus eugenii, which is a member of the kangaroo family and the first representative of the iconic hopping mammals that symbolize Australia to be sequenced. The tammar has many unusual biological characteristics, including the longest period of embryonic diapause of any mammal, extremely synchronized seasonal breeding and prolonged and sophisticated lactation within a well-defined pouch. Like other marsupials, it gives birth to highly altricial young, and has a small number of very large chromosomes, making it a valuable model for genomics, reproduction and development. RESULTS: The genome has been sequenced to 2 × coverage using Sanger sequencing, enhanced with additional next generation sequencing and the integration of extensive physical and linkage maps to build the genome assembly. We also sequenced the tammar transcriptome across many tissues and developmental time points. Our analyses of these data shed light on mammalian reproduction, development and genome evolution: there is innovation in reproductive and lactational genes, rapid evolution of germ cell genes, and incomplete, locus-specific X inactivation. We also observe novel retrotransposons and a highly rearranged major histocompatibility complex, with many class I genes located outside the complex. Novel microRNAs in the tammar HOX clusters uncover new potential mammalian HOX regulatory elements. CONCLUSIONS: Analyses of these resources enhance our understanding of marsupial gene evolution, identify marsupial-specific conserved non-coding elements and critical genes across a range of biological systems, including reproduction, development and immunity, and provide new insight into marsupial and mammalian biology and genome evolution

Determination of intrinsic switching field distributions in perpendicular recording media: numerical study of the ΔH(M,ΔM)\Delta H(M, \Delta M) method

We present a numerical study of the $\Delta H(M,\Delta M)$ method and its ability to accurately determine intrinsic switching field distributions in interacting granular magnetic materials such as perpendicular recording media. In particular, we study how this methodology fails for large ferromagnetic inter-granular interactions, at which point the associated strongly correlated magnetization reversal cannot be properly represented by the mean-field approximation, upon which the $\Delta H(M,\Delta M)$ method is based. In this study, we use a 2-dimensional array of symmetric hysterons that have an intrinsic switching field distribution of standard deviation $\sigma$ and ferromagnetic nearest-neighbor interactions $J$. We find the $\Delta H(M,\Delta M)$ method to be very accurate for small $J/\sigma$ values, while substantial errors develop once the effective exchange field becomes comparable with $\sigma$, corroborating earlier results from micromagnetic simulations. We furthermore demonstrate that this failure is correlated with deviations from data set redundancy, which is a key property of the mean-field approximation. Thus, the $\Delta H(M,\Delta M)$ method fails in a well defined and quantifiable manner that can be easily assessed from the data sets alone.Comment: 13 pages, 9 figure