The genomics of neonatal abstinence syndrome

Significant variability has been observed in the development and severity of neonatal abstinence syndrome (NAS) among neonates exposed to prenatal opioids. Since maternal opioid dose does not appear to correlate directly with neonatal outcome, maternal, placental, and fetal genomic variants may play important roles in NAS. Previous studies in small cohorts have demonstrated associations of variants in maternal and infant genes that encode the μ-opioid receptor (OPRM1), catechol-O-methyltransferase (COMT), and prepronociceptin (PNOC) with a shorter length of hospital stay and less need for treatment in neonates exposed to opioids in utero. Consistently falling genomic sequencing costs and computational approaches to predict variant function will permit unbiased discovery of genomic variants and gene pathways associated with differences in maternal and fetal opioid pharmacokinetics and pharmacodynamics and with placental opioid transport and metabolism. Discovery of pathogenic variants should permit better delineation of the risk of developing more severe forms of NAS. This review provides a summary of the current role of genomic factors in the development of NAS and suggests strategies for further genomic discovery

The characteristics and limitations of the MPS/MMS battery charging system

A series of tests was conducted on two 12 ampere hour nickel cadmium batteries under a simulated cycle regime using the multiple voltage versus temperature levels designed into the modular power system (MPS). These tests included: battery recharge as a function of voltage control level; temperature imbalance between two parallel batteries; a shorted or partially shorted cell in one of the two parallel batteries; impedance imbalance of one of the parallel battery circuits; and disabling and enabling one of the batteries from the bus at various charge and discharge states. The results demonstrate that the eight commandable voltage versus temperature levels designed into the MPS provide a very flexible system that not only can accommodate a wide range of normal power system operation, but also provides a high degree of flexibility in responding to abnormal operating conditions

Propositional Encoding of Constraints over Tree-Shaped Data

We present a functional programming language for specifying constraints over tree-shaped data. The language allows for Haskell-like algebraic data types and pattern matching. Our constraint compiler CO4 translates these programs into satisfiability problems in propositional logic. We present an application from the area of automated analysis of (non-)termination of rewrite systems

Research and development of high temperature resistant polymeric film forming material final summary report, 1 mar. 1961 - 17 apr. 1962

Preparation of poly-organometallosiloxane polymers from reactions between bis-dialkylamino metal derivatives and silanediol

On Network Science and Mutual Information for Explaining Deep Neural Networks

In this paper, we present a new approach to interpret deep learning models. By coupling mutual information with network science, we explore how information flows through feedforward networks. We show that efficiently approximating mutual information allows us to create an information measure that quantifies how much information flows between any two neurons of a deep learning model. To that end, we propose NIF, Neural Information Flow, a technique for codifying information flow that exposes deep learning model internals and provides feature attributions.Comment: ICASSP 2020 (shorter version appeared at AAAI-19 Workshop on Network Interpretability for Deep Learning

Predicting space climate change

The recent decline in the open magnetic flux of the Sun heralds the end of the Grand Solar Maximum (GSM) that has persisted throughout the space age, during which the largest‐fluence Solar Energetic Particle (SEP) events have been rare and Galactic Cosmic Ray (GCR) fluxes have been relatively low. In the absence of a predictive model of the solar dynamo, we here make analogue forecasts by studying past variations of solar activity in order to evaluate how long‐term change in space climate may influence the hazardous energetic particle environment of the Earth in the future. We predict the probable future variations in GCR flux, near‐Earth interplanetary magnetic field (IMF), sunspot number, and the probability of large SEP events, all deduced from cosmogenic isotope abundance changes following 24 GSMs in a 9300‐year record