Household food insecurity positively associated with increased hospital charges for infants

Objective: To test whether household food insecurity (HFI) was associated with total annual hospitalization charges, annual days hospitalized, and charges per day, among low-income infants (months) with any non-neonatal hospital stays. Methods: Administrative inpatient hospital charge data were matched to survey data from infants\u27 caregivers interviewed 1998-2005 in emergency departments in Boston and Little Rock. All study infants had been hospitalized at least once since birth; infants whose diagnoses were not plausibly related to nutrition were excluded from both groups. Log-transformed hospitalization charges were analyzed, controlling for site fixed effects. Results: 24% of infants from food-insecure households and 16% from food-secure households were hospitalized \u3e2 times (P=0.02). Mean annual inpatient hospital charges ($6,707 vs$5,735; P Conclusion: HFI was positively associated with annual inpatient charges among hospitalized low income infants. Average annual inpatient charges were almost $2,000 higher (inflation adjusted) for infants living in food-insecure households. Reducing or eliminating food insecurity could reduce health services utilization and expenditures for infants in low-income families, most of whom are covered by public health insurance

Microlensing Events in Five Years of Photometry from the Zwicky Transient Facility

Microlensing has a unique advantage for detecting dark objects in the Milky Way, such as free floating planets, neutron stars, and stellar-mass black holes. Most microlensing surveys focus towards the Galactic bulge, where higher stellar density leads to a higher event rate. However, microlensing events in the Galactic plane are closer, and take place over longer timescales. This enables a better measurement of the microlensing parallax, which serves as an independent constraint on the mass of the dark lens. In this work, we systematically searched for microlensing events in Zwicky Transient Facility (ZTF) Data Release 17 from 2018--2023 in the Galactic plane region $|b| < 20^\circ$. We find 124 high-confidence microlensing events and 54 possible events. In the event selection, we use the efficient \texttt{EventFinder} algorithm to detect microlensing signals, which could be used for large datasets such as future ZTF data releases or data from the Rubin Observatory Legacy Survey of Space and Time (LSST). With detection efficiencies of ZTF fields from catalog-level simulations, we calculate the mean Einstein timescale to be $\langle t_\mathrm{E}\rangle = 51.7 \pm 3.3$ days, smaller than previous results of the Galactic plane to within 1.5-$\sigma$. We calculate optical depths and event rates, which we interpret with caution due to the use of visual inspection in creating our final sample. With two years of additional ZTF data in DR17, we have more than doubled the amount of microlensing events (60) found in the three-year DR5 search and found events with longer Einstein timescales than before.Comment: 9 figures, 3 tables. Submitted to Ap

Antineutrino Geophysics with Liquid Scintillator Detectors

Detecting the antineutrinos emitted by the decay of radioactive elements in the mantle and crust could provide a direct measurement of the total abundance of uranium and thorium in the Earth. In calculating the antineutrino flux at specific sites, the local geology of the crust and the background from the world's nuclear power reactors are important considerations. Employing a global crustal map, with type and thickness data, and using recent estimates of the uranium and thorium distribution in the Earth, we calculate the antineutrino event rate for two new neutrino detectors. We show that spectral features allow terrestrial antineutrino events to be identified above reactor antineutrino backgrounds and that the uranium and thorium contributions can be separately determined.Comment: Published paper differs from original submitted preprint because reviewers suggested updated continental crust U/Th abundances. Kamioka geographical location error was in preprint, partially corrected in published version. This version is the same as the published paper, with Kamioka fully corrected. Because of recent interest in this topic, this version is being made available, despite this work being 8 years ol

Trends in Household and Child Food Insecurity Among Families with Young Children from 2007 to 2013

Background: 2007-2013 spanned an economic downturn with rising food costs. While Supplemental Nutrition Assistance Program (SNAP) benefits increased during those years by 13.6% from the 2009 American Recovery Reinvestment Act (ARRA), the impact of these competing conditions on household food insecurity (HFI, household food insecure but child food secure) and child food insecurity (CFI, household and child food insecure) in households with infants and toddlers has not been investigated. Objective: To describe HFI and CFI in households participating in SNAP vs. households likely eligible but not participating (No SNAP). Design: Repeat cross-sectional Participants/Setting: 19,999 caregivers of childrenChildren’s HealthWatch survey in emergency and primary care departments in 5 US cities. Main Outcome Measures: The 18-item U.S. Household Food Security Survey (HFSS) measured HFI (≥3 affirmative responses on non-child-specific questions) and CFI (≥2 affirmative responses to eight child-specific questions). Statistical analyses performed: The sample was stratified by SNAP/ No SNAP. Multinomial logistic regression analyses examined the association between SNAP receipt and HFI and CFI. Results: Across the study period, controlling for confounders including year, households with SNAP were 17% less likely to experience HFI (AOR 0.83; 95% CI,0 .75, 0.91; p Conclusions: Receipt of SNAP vs. No SNAP was associated with decreased prevalence of HFI and CFI during much of the economic downturn; this impact waned as the buying power of the boost in benefit amounts during the ARRA period eroded

Tensor Regression with Applications in Neuroimaging Data Analysis

Classical regression methods treat covariates as a vector and estimate a corresponding vector of regression coefficients. Modern applications in medical imaging generate covariates of more complex form such as multidimensional arrays (tensors). Traditional statistical and computational methods are proving insufficient for analysis of these high-throughput data due to their ultrahigh dimensionality as well as complex structure. In this article, we propose a new family of tensor regression models that efficiently exploit the special structure of tensor covariates. Under this framework, ultrahigh dimensionality is reduced to a manageable level, resulting in efficient estimation and prediction. A fast and highly scalable estimation algorithm is proposed for maximum likelihood estimation and its associated asymptotic properties are studied. Effectiveness of the new methods is demonstrated on both synthetic and real MRI imaging data.Comment: 27 pages, 4 figure

An ALMA survey of submillimetre galaxies in the COSMOS field: The extent of the radio-emitting region revealed by 3 GHz imaging with the Very Large Array

We determine the radio size distribution of a large sample of 152 SMGs in COSMOS that were detected with ALMA at 1.3 mm. For this purpose, we used the observations taken by the VLA-COSMOS 3 GHz Large Project. One hundred and fifteen of the 152 target SMGs were found to have a 3 GHz counterpart. The median value of the major axis FWHM at 3 GHz is derived to be $4.6\pm0.4$ kpc. The radio sizes show no evolutionary trend with redshift, or difference between different galaxy morphologies. We also derived the spectral indices between 1.4 and 3 GHz, and 3 GHz brightness temperatures for the sources, and the median values were found to be $\alpha=-0.67$ and $T_{\rm B}=12.6\pm2$ K. Three of the target SMGs, which are also detected with the VLBA, show clearly higher brightness temperatures than the typical values. Although the observed radio emission appears to be predominantly powered by star formation and supernova activity, our results provide a strong indication of the presence of an AGN in the VLBA and X-ray-detected SMG AzTEC/C61. The median radio-emitting size we have derived is 1.5-3 times larger than the typical FIR dust-emitting sizes of SMGs, but similar to that of the SMGs' molecular gas component traced through mid-$J$ line emission of CO. The physical conditions of SMGs probably render the diffusion of cosmic-ray electrons inefficient, and hence an unlikely process to lead to the observed extended radio sizes. Instead, our results point towards a scenario where SMGs are driven by galaxy interactions and mergers. Besides triggering vigorous starbursts, galaxy collisions can also pull out the magnetised fluids from the interacting disks, and give rise to a taffy-like synchrotron-emitting bridge. This provides an explanation for the spatially extended radio emission of SMGs, and can also cause a deviation from the well-known IR-radio correlation.Comment: 32 pages (incl. 5 appendices), 17 figures, 7 tables; accepted for publication in A&A; abstract abridged for arXi

The natural capital accounting opportunity: Let s really do the numbers

This work was conducted as a part of the “Accounting for U.S. Ecosystem Services at National and Subnational Scales” working group supported by the National Socio-Environmental Synthesis Center under funding received from the National Science Foundation (grant no. DBI-1052875) and the US Geological Survey John Wesley Powell Center for Analysis and Synthesis (grant no. GX16EW00ECSV00)

Text mining for biology - the way forward: opinions from leading scientists

This article collects opinions from leading scientists about how text mining can provide better access to the biological literature, how the scientific community can help with this process, what the next steps are, and what role future BioCreative evaluations can play. The responses identify several broad themes, including the possibility of fusing literature and biological databases through text mining; the need for user interfaces tailored to different classes of users and supporting community-based annotation; the importance of scaling text mining technology and inserting it into larger workflows; and suggestions for additional challenge evaluations, new applications, and additional resources needed to make progress