Community-level characteristics of high infant mortality: A tool to identify at-risk communities

Infant mortality (IM) rate is a key indicator of population health and has been gradually improving in the United States. However, it is still a public health problem among minority and low-income communities. Maternal factors explain some of the variation, but community-level factors may also be a contributor. This study examines measures to identify a set of indicators that explain variations in IM at the community-level. Data for 77 communities in a city were obtained from local health databases. We used multivariable linear regression models to examine the strength of the association between IM and maternal, population, community wealth, and social capital characteristics. Community-level IM rates ranged from 2.1 – 25.6 deaths per 1,000 live births in 2000-2002. The final model explained 75% of the variation in IM rates at the community-level (R2=0.75). The model included a high percentage of low birth weight babies, a decline in mothers who began prenatal care in the second trimester, an increase in the percentage of Hispanics, increased unemployment rates, an increase in the percentage of veterans, an increased rate of foreign-born residents, and smaller average family sizes. Social capital variables, homicide rate and vacant housing, were also significant in the final model. Identifying communities at risk for high IM rates is imperative to improve maternal and child health outcomes because of shortages in public health resources. The development of a parsimonious set of community-level indicators can assist public health practitioners in targeting their resources to prevent infant mortality in high-risk communities

Bogged Down Trying to Define Federal Wetlands

This article examines these cases as well as the history, policies, and rationales behind identifying and conserving wetlands. It proposes a unique analytical method for valuation of wetlands. Under the proposed analysis, government agencies and landowners would be required to prepare economic impact statements containing cost/benefit analyses measuring the effects of wetlands delineations upon land values. These analyses would provide the basis for determining the value of preserving wetlands ecosystems as well as the basis for determining fair compensation payable to landowners in the event they suffer land use or income loss as a result of wetlands delineations

Quantum cosmic models and thermodynamics

The current accelerating phase of the evolution of the universe is considered by constructing most economical cosmic models that use just general relativity and some dominating quantum effects associated with the probabilistic description of quantum physics. Two of such models are explicitly analyzed. They are based on the existence of a sub-quantum potential and correspond to a generalization of the spatially flat exponential model of de Sitter space. The thermodynamics of these two cosmic solutions is discussed, using the second principle as a guide to choose which among the two is more feasible. The paper also discusses the relativistic physics on which the models are based, their holographic description, some implications from the classical energy conditions, and an interpretation of dark energy in terms of the entangled energy of the universe.Comment: 15 pages, 1 figure, accepted for publication in Class. Quantum Gra

A method to improve protein subcellular localization prediction by integrating various biological data sources

<p>Abstract</p> <p>Background</p> <p>Protein subcellular localization is crucial information to elucidate protein functions. Owing to the need for large-scale genome analysis, computational method for efficiently predicting protein subcellular localization is highly required. Although many previous works have been done for this task, the problem is still challenging due to several reasons: the number of subcellular locations in practice is large; distribution of protein in locations is imbalanced, that is the number of protein in each location remarkably different; and there are many proteins located in multiple locations. Thus it is necessary to explore new features and appropriate classification methods to improve the prediction performance.</p> <p>Results</p> <p>In this paper we propose a new predicting method which combines two key ideas: 1) Information of neighbour proteins in a probabilistic gene network is integrated to enrich the prediction features. 2) Fuzzy k-NN, a classification method based on fuzzy set theory is applied to predict protein locating in multiple sites. Experiment was conducted on a dataset consisting of 22 locations from Budding yeast proteins and significant improvement was observed.</p> <p>Conclusion</p> <p>Our results suggest that the neighbourhood information from functional gene networks is predictive to subcellular localization. The proposed method thus can be integrated and complementary to other available prediction methods.</p

Estimating global mean sea-level rise and its uncertainties by 2100 and 2300 from an expert survey

Sea-level rise projections and knowledge of their uncertainties are vital to make informed mitigation and adaptation decisions. To elicit projections from members of the scientific community regarding future global mean sea-level (GMSL) rise, we repeated a survey originally conducted five years ago. Under Representative Concentration Pathway (RCP) 2.6, 106 experts projected a likely (central 66% probability) GMSL rise of 0.30–0.65 m by 2100, and 0.54–2.15 m by 2300, relative to 1986–2005. Under RCP 8.5, the same experts projected a likely GMSL rise of 0.63–1.32 m by 2100, and 1.67–5.61 m by 2300. Expert projections for 2100 are similar to those from the original survey, although the projection for 2300 has extended tails and is higher than the original survey. Experts give a likelihood of 42% (original survey) and 45% (current survey) that under the high-emissions scenario GMSL rise will exceed the upper bound (0.98 m) of the likely range estimated by the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, which is considered to have an exceedance likelihood of 17%. Responses to open-ended questions suggest that the increases in upper-end estimates and uncertainties arose from recent influential studies about the impact of marine ice cliff instability on the meltwater contribution to GMSL rise from the Antarctic Ice Sheet. © 2020, The Author(s)

Tuning supersymmetric models at the LHC: A comparative analysis at two-loop level

We provide a comparative study of the fine tuning amount (Delta) at the two-loop leading log level in supersymmetric models commonly used in SUSY searches at the LHC. These are the constrained MSSM (CMSSM), non-universal Higgs masses models (NUHM1, NUHM2), non-universal gaugino masses model (NUGM) and GUT related gaugino masses models (NUGMd). Two definitions of the fine tuning are used, the first (Delta_{max}) measures maximal fine-tuning wrt individual parameters while the second (Delta_q) adds their contribution in "quadrature". As a direct result of two theoretical constraints (the EW minimum conditions), fine tuning (Delta_q) emerges as a suppressing factor (effective prior) of the averaged likelihood (under the priors), under the integral of the global probability of measuring the data (Bayesian evidence p(D)). For each model, there is little difference between Delta_q, Delta_{max} in the region allowed by the data, with similar behaviour as functions of the Higgs, gluino, stop mass or SUSY scale (m_{susy}=(m_{\tilde t_1} m_{\tilde t_2})^{1/2}) or dark matter and g-2 constraints. The analysis has the advantage that by replacing any of these mass scales or constraints by their latest bounds one easily infers for each model the value of Delta_q, Delta_{max} or vice versa. For all models, minimal fine tuning is achieved for M_{higgs} near 115 GeV with a Delta_q\approx Delta_{max}\approx 10 to 100 depending on the model, and in the CMSSM this is actually a global minimum. Due to a strong ($\approx$ exponential) dependence of Delta on M_{higgs}, for a Higgs mass near 125 GeV, the above values of Delta_q\approx Delta_{max} increase to between 500 and 1000. Possible corrections to these values are briefly discussed.Comment: 23 pages, 46 figures; references added; some clarifications (section 2

Author Correction: Estimating global mean sea-level rise and its uncertainties by 2100 and 2300 from an expert survey

Correction to: NPJ Climate and Atmospheric Science https://doi.org/10.1038/s41612-020-0121-5, published online 08 May 202

GNOSIS: the first instrument to use fibre Bragg gratings for OH suppression

GNOSIS is a prototype astrophotonic instrument that utilizes OH suppression fibres consisting of fibre Bragg gratings and photonic lanterns to suppress the 103 brightest atmospheric emission doublets between 1.47-1.7 microns. GNOSIS was commissioned at the 3.9-meter Anglo-Australian Telescope with the IRIS2 spectrograph to demonstrate the potential of OH suppression fibres, but may be potentially used with any telescope and spectrograph combination. Unlike previous atmospheric suppression techniques GNOSIS suppresses the lines before dispersion and in a manner that depends purely on wavelength. We present the instrument design and report the results of laboratory and on-sky tests from commissioning. While these tests demonstrated high throughput and excellent suppression of the skylines by the OH suppression fibres, surprisingly GNOSIS produced no significant reduction in the interline background and the sensitivity of GNOSIS and IRIS2 is about the same as IRIS2. It is unclear whether the lack of reduction in the interline background is due to physical sources or systematic errors as the observations are detector noise-dominated. OH suppression fibres could potentially impact ground-based astronomy at the level of adaptive optics or greater. However, until a clear reduction in the interline background and the corresponding increasing in sensitivity is demonstrated optimized OH suppression fibres paired with a fibre-fed spectrograph will at least provide a real benefits at low resolving powers.Comment: 15 pages, 13 figures, accepted to A

Suppression of the near-infrared OH night sky lines with fibre Bragg gratings - first results

The background noise between 1 and 1.8 microns in ground-based instruments is dominated by atmospheric emission from hydroxyl molecules. We have built and commissioned a new instrument, GNOSIS, which suppresses 103 OH doublets between 1.47 - 1.7 microns by a factor of ~1000 with a resolving power of ~10,000. We present the first results from the commissioning of GNOSIS using the IRIS2 spectrograph at the AAT. The combined throughput of the GNOSIS fore-optics, grating unit and relay optics is ~36 per cent, but this could be improved to ~46 per cent with a more optimal design. We measure strong suppression of the OH lines, confirming that OH suppression with fibre Bragg gratings will be a powerful technology for low resolution spectroscopy. The integrated OH suppressed background between 1.5 and 1.7 microns is reduced by a factor of 9 compared to a control spectrum using the same system without suppression. The potential of low resolution OH suppressed spectroscopy is illustrated with example observations. The GNOSIS background is dominated by detector dark current below 1.67 microns and by thermal emission above 1.67 microns. After subtracting these we detect an unidentified residual interline component of ~ 860 +/ 210 ph/s/m^2/micron/arcsec^2. This component is equally bright in the suppressed and control spectra. We have investigated the possible source of the interline component, but were unable to discriminate between a possible instrumental artifact and intrinsic atmospheric emission. Resolving the source of this emission is crucial for the design of fully optimised OH suppression spectrographs. The next generation OH suppression spectrograph will be focussed on resolving the source of the interline component, taking advantage of better optimisation for a FBG feed. We quantify the necessary improvements for an optimal OH suppressing fibre spectrograph design.Comment: Accepted for publication in MNRAS. 15 pages, 18 figure

The Sydney-AAO Multi-object Integral field spectrograph (SAMI)

We demonstrate a novel technology that combines the power of the multi-object spectrograph with the spatial multiplex advantage of an integral field spectrograph (IFS). The Sydney-AAO Multi-object IFS (SAMI) is a prototype wide-field system at the Anglo-Australian Telescope (AAT) that allows 13 imaging fibre bundles ("hexabundles") to be deployed over a 1-degree diameter field of view. Each hexabundle comprises 61 lightly-fused multimode fibres with reduced cladding and yields a 75 percent filling factor. Each fibre core diameter subtends 1.6 arcseconds on the sky and each hexabundle has a field of view of 15 arcseconds diameter. The fibres are fed to the flexible AAOmega double-beam spectrograph, which can be used at a range of spectral resolutions (R=lambda/delta(lambda) ~ 1700-13000) over the optical spectrum (3700-9500A). We present the first spectroscopic results obtained with SAMI for a sample of galaxies at z~0.05. We discuss the prospects of implementing hexabundles at a much higher multiplex over wider fields of view in order to carry out spatially--resolved spectroscopic surveys of 10^4 to 10^5 galaxies.Comment: 24 pages, 16 figures. Accepted by MNRA