Reproductive Effort and Lipid Dynamics of the Emerald Shiner (Notropis atherinoides) in the Upper Niagara River, New York

Life history theory predicts that reproductive characteristics of organisms will be shaped by biotic and abiotic factors to maximize their overall fitness. In this study, I investigated how growth, reproductive effort, and lipid dynamics vary ontogenetically and seasonally for emerald shiners (Notropis atherinoides) in the upper Niagara River. Growth rates were highest in age 2 shiners and lower in age 1 and age 3 individuals. Evidence of reproduction was found beginning at age 1, and reproductive investment as measured by ovarian lipid content was lowest in age 1 and age 2 individuals and greatest in age 3 fish. All age classes exhibited significant changes in somatic lipids across sampling seasons, with minima in spring and maxima in fall. Fulton’s condition factor K did not accurately represent variation in somatic lipid reserves that were found in this study, and therefore this index is not likely to be an accurate measure of overall health and robustness for this species. My findings suggest that emerald shiners exhibit a life history strategy where somatic growth is prioritized over reproduction until their third year of life when large investments into reproduction result in significantly reduced growth rates. Although prior studies have examined growth and reproductive traits of the emerald shiner, my study is the first to document significant changes in lipid dynamics across seasons and age groups in this native keystone species

New Clarification About Observation Billing May Improve Care for Behavioral Health Patients

Emergency Physicians provide ongoing care to psychiatric patients beyond the confines of a standard emergency room visit.  Often, when we identify patients who need specialty psychiatric care, patients board in the emergency department awaiting acceptance and transfer to an outside facility.  Even in cases where it has taken multiple days to complete the transfer, it has been unclear how to properly obtain reimbursement for this care.  We discuss a new coding clarification that may provide a pathway to improve part of this situation

RADYNVERSION: Learning to Invert a Solar Flare Atmosphere with Invertible Neural Networks

During a solar flare, it is believed that reconnection takes place in the corona followed by fast energy transport to the chromosphere. The resulting intense heating strongly disturbs the chromospheric structure, and induces complex radiation hydrodynamic effects. Interpreting the physics of the flaring solar atmosphere is one of the most challenging tasks in solar physics. Here we present a novel deep learning approach, an invertible neural network, to understanding the chromospheric physics of a flaring solar atmosphere via the inversion of observed solar line profiles in H{\alpha} and Ca II {\lambda}8542. Our network is trained using flare simulations from the 1D radiation hydrodynamics code RADYN as the expected atmosphere and line profile. This model is then applied to single pixels from an observation of an M1.1 solar flare taken with SST/CRISP instrument just after the flare onset. The inverted atmospheres obtained from observations provide physical information on the electron number density, temperature and bulk velocity flow of the plasma throughout the solar atmosphere ranging from 0-10 Mm in height. The density and temperature profiles appear consistent with the expected atmospheric response, and the bulk plasma velocity provides the gradients needed to produce the broad spectral lines whilst also predicting the expected chromospheric evaporation from flare heating. We conclude that we have taught our novel algorithm the physics of a solar flare according to RADYN and that this can be confidently used for the analysis of flare data taken in these two wavelengths. This algorithm can also be adapted for a menagerie of inverse problems providing extremely fast ($\sim$10 {\mu}s) inversion samples.Comment: Published in Ap

Seasonal variation and impact of waste-water lagoons as larval habitat on the population dynamics of Culicoides sonorensis (Diptera:Ceratpogonidae) at two dairy farms in northern California.

The Sacramento (northern Central) Valley of California (CA) has a hot Mediterranean climate and a diverse ecological landscape that is impacted extensively by human activities, which include the intensive farming of crops and livestock. Waste-water ponds, marshes, and irrigated fields associated with these agricultural activities provide abundant larval habitats for C. sonorensis midges, in addition to those sites that exist in the natural environment. Within this region, C. sonorensis is an important vector of bluetongue (BTV) and related viruses that adversely affect the international trade and movement of livestock, the economics of livestock production, and animal welfare. To characterize the seasonal dynamics of immature and adult C. sonorensis populations, abundance was monitored intensively on two dairy farms in the Sacramento Valley from August 2012- to July 2013. Adults were sampled every two weeks for 52 weeks by trapping (CDC style traps without light and baited with dry-ice) along N-S and E-W transects on each farm. One farm had large operational waste-water lagoons, whereas the lagoon on the other farm was drained and remained dry during the study. Spring emergence and seasonal abundance of adult C. sonorensis on both farms coincided with rising vernal temperature. Paradoxically, the abundance of midges on the farm without a functioning waste-water lagoon was increased as compared to abundance on the farm with a waste-water lagoon system, indicating that this infrastructure may not serve as the sole, or even the primary larval habitat. Adult midges disappeared from both farms from late November until May; however, low numbers of parous female midges were detected in traps set during daylight in the inter-seasonal winter period. This latter finding is especially critical as it provides a potential mechanism for the "overwintering" of BTV in temperate regions such as northern CA. Precise documentation of temporal changes in the annual abundance and dispersal of Culicoides midges is essential for the creation of models to predict BTV infection of livestock and to develop sound abatement strategies

Fuel poverty increases risk of mould contamination, regardless of adult risk perception & ventilation in social housing properties

INTRODUCTION: Fuel poverty affects 2.4 million UK homes leading to poor hygrothermal conditions and risk of mould and house dust mite contaminations, which in turn increases risk of asthma exacerbation. For the first time we assess how fuel poverty, occupants' risk perception and use of mechanical ventilation mediate the risk of mould contamination in social housing. METHODS: Postal questionnaires were sent to 3867 social housing properties to collect adult risk perception, and demographic and environmental information on occupants. Participant details were linked to data pertaining to the individual properties. Multiple logistic regression was used to calculate odds ratios and confidence intervals while allowing for clustering of individuals coming from the same housing estate. We used Structured Equation Modelling and Goodness of Fit analysis in mediation analyses to examine the role of fuel poverty, risk perception, use of ventilation and energy efficiency. RESULTS: Eighteen percent of our target social housing populations (671 households) were included into our study. High risk perception (score of 8-10) was associated with reduced risk of mould contamination in the bedrooms of children (OR 0.5 95% CI; 0.3-0.9) and adults (OR 0.4 95% CI; 0.3-0.7). High risk perception of living with inadequate heating and ventilation reduced the risk of mould contamination (OR 0.5 95% CI; 0.3-0.8 and OR 0.5 95% CI; 0.3-0.7, respectively). Participants living with inadequate heating and not heating due to the cost of fuel had an increased risk of mould contamination (OR 3.4 95% CI; 2.0-5.8 and OR 2.2 95% CI; 1.5-3.2, respectively). Increased risk perception and use of extractor fans did not mediate the association between fuel poverty behaviours and increased risk of mould contamination. DISCUSSION: Fuel poverty behaviours increased the risk of mould contamination, which corresponds with existing literature. For the first time we used mediation analysis to assess how this association maybe modified by occupant behaviours. Increased risk perception and use of extractor fans did not modify the association between fuel poverty and mould contamination. This suggests that fuel poor populations may not benefit from energy efficiency interventions due to ineffective heating and ventilation practices of those occupants residing participating households. Our findings may be modified by a complex interaction between occupant behaviours and the built environment. We found that participant age, occupancy, SES, pets, drying washing indoors, geographic location, architectural design/age of the property, levels of insulation and type of heating regulated risk of mould contamination. CONCLUSION: Fuel poverty behaviours affected around a third of participating households and represent a risk factor for increased exposures to damp and mouldy conditions, regardless of adult risk perception, heating and ventilation practices. This requires multidisciplinary approach to assess the complex interaction between occupant behaviours, risk perception, the built environment and the effective use of heating and ventilation practices. STUDY IMPLICATIONS: Our findings have implications for housing policies and future housing interventions. Effective communication strategies focusing on awareness and perception of risk may help address indoor air quality issues. This must be supported by improved household energy efficiency with the provision of more effective heating and ventilation strategies, specifically to help alleviate those suffering from fuel poverty.European Regional Development Fund Programme  202497 50002

A practical scheme for quantum computation with any two-qubit entangling gate

Which gates are universal for quantum computation? Although it is well known that certain gates on two-level quantum systems (qubits), such as the controlled-not (CNOT), are universal when assisted by arbitrary one-qubit gates, it has only recently become clear precisely what class of two-qubit gates is universal in this sense. Here we present an elementary proof that any entangling two-qubit gate is universal for quantum computation, when assisted by one-qubit gates. A proof of this important result for systems of arbitrary finite dimension has been provided by J. L. and R. Brylinski [arXiv:quant-ph/0108062, 2001]; however, their proof relies upon a long argument using advanced mathematics. In contrast, our proof provides a simple constructive procedure which is close to optimal and experimentally practical [C. M. Dawson and A. Gilchrist, online implementation of the procedure described herein (2002), http://www.physics.uq.edu.au/gqc/].Comment: 3 pages, online implementation of procedure described can be found at http://www.physics.uq.edu.au/gqc

Deep learning for the Sun

Abstract John A Armstrong, Christopher M J Osborne and Lyndsay Fletcher examine how neural networks can be used to explore the nature and location of solar activity

Increasing influence of heat stress on French maize yields from the 1960s to the 2030s

Improved crop yield forecasts could enable more effective adaptation to climate variability and change. Here, we explore how to combine historical observations of crop yields and weather with climate model simulations to produce crop yield projections for decision relevant timescales. Firstly, the effects on historical crop yields of improved technology, precipitation and daily maximum temperatures are modelled empirically, accounting for a nonlinear technology trend and interactions between temperature and precipitation, and applied specifically for a case study of maize in France. The relative importance of precipitation variability for maize yields in France has decreased significantly since the 1960s, likely due to increased irrigation. In addition, heat stress is found to be as important for yield as precipitation since around 2000. A significant reduction in maize yield is found for each day with a maximum temperature above 32 °C, in broad agreement with previous estimates. The recent increase in such hot days has likely contributed to the observed yield stagnation. Furthermore, a general method for producing near-term crop yield projections, based on climate model simulations, is developed and utilized. We use projections of future daily maximum temperatures to assess the likely change in yields due to variations in climate. Importantly, we calibrate the climate model projections using observed data to ensure both reliable temperature mean and daily variability characteristics, and demonstrate that these methods work using retrospective predictions. We conclude that, to offset the projected increased daily maximum temperatures over France, improved technology will need to increase base level yields by 12% to be confident about maintaining current levels of yield for the period 2016–2035; the current rate of yield technology increase is not sufficient to meet this target