Simultaneous estimation by partial totals for compartmental models

Simultaneous estimation procedure for parameters in multiple equation regression mode

Spearman simultaneous estimation for a compartmental model Technical report no. 9

Compartmental model, represented as system of linear combination of exponentials with common exponential parameters, for tracer experiment

Multiwavelength Observations of the Hot DB Star PG 0112+104

We present a comprehensive multiwavelength analysis of the hot DB white dwarf PG 0112+104. Our analysis relies on newly-acquired FUSE observations, on medium-resolution FOS and GHRS data, on archival high-resolution GHRS observations, on optical spectrophotometry both in the blue and around Halpha, as well as on time-resolved photometry. From the optical data, we derive a self-consistent effective temperature of 31,300+-500 K, a surface gravity of log g = 7.8 +- 0.1 (M=0.52 Msun), and a hydrogen abundance of log N(H)/N(He) < -4.0. The FUSE spectra reveal the presence of CII and CIII lines that complement the previous detection of CII transitions with the GHRS. The improved carbon abundance in this hot object is log N(C)/N(He) = -6.15 +- 0.23. No photospheric features associated with other heavy elements are detected. We reconsider the role of PG 0112+104 in the definition of the blue edge of the V777 Her instability strip in light of our high-speed photometry, and contrast our results with those of previous observations carried out at the McDonald Observatory.Comment: 10 pages in emulateapj, 9 figures, accepted for publication in Ap

Time and energy constraints and the relationships between currencies in foraging theory

Measured foraging strategies often cluster around values that maximize the ratio of energy gained over energy spent while foraging (efficiency), rather than values that would maximize the long-term net rate of energy gain (rate). The reasons for this are not understood. This paper focuses on time and energy constraints while foraging to illustrate the relationship between efficiency and rate-maximizing strategies and develops models that provide a simple framework to analyze foraging strategies in two distinct foraging contexts. We assume that while capturing and ingesting food for their own use (which we term feeding), foragers behave so as to maximize the total net daily energetic gain. When gathering food for others or for storage (which we term provisioning), we assume that foragers behave so as to maximize the total daily delivery, subject to meeting their own energetic requirements. In feeding contexts, the behavior maximizing total net daily gain also maximizes efficiency when daily intake is limited by the assimilation capacity. In contrast, when time available to forage sets the limit to gross intake, the behavior maximizing total net daily gain also maximizes rate. In provisioning contexts, when daily delivery is constrained by the energy needed to power self-feeding, maximizing efficiency ensures the highest total daily delivery. When time needed to recoup energetic expenditure limits total delivery, a low self-feeding rate relative to the rate of energy expenditure favors efficient strategies. However, as the rate of self-feeding increases, foraging behavior deviates from efficiency maximization in the direction predicted by rate maximization. Experimental manipulations of the rate of self-feeding in provisioning contexts could be a powerful tool to explore the relationship between rate and efficiency-maximizing behavio

Poisonings Associated with Intubation: US National Poison Data System Exposures 2000-2013.

Patients may be intubated after exposure to a variety of substances because of respiratory failure, CNS sedation, pulmonary pathology, or cardiovascular instability. However, there is little data describing the types of substances that are associated with endotracheal intubation or the rates of intubation after these exposures. Evaluation of this association may inform future research on intubation after exposures to specific substances and guide poison prevention education. Our objective was to determine which exposures were commonly associated with intubation using the data from National Poison Data System (NPDS). The NPDS tracks data from potential exposures to substances reported to all American Association of Poison Control Centers. We performed a retrospective analysis of NPDS data from January 1st, 2000 to December 31st, 2013 to identify human exposures to substances that were associated with endotracheal intubation. Descriptive statistics were used to analyze the data. There were 93,474 single substance exposures and 228,507 multiple substance exposures that were associated with intubation. The most common exposures to substances that were associated with intubation were atypical antipsychotics (7.4 %) for single exposures and benzodiazepines (27.4 %) for multiple exposures. Within each age group, the most common known exposures to substances were for patients under 6 years, clonidine for single and multiple exposures; for patients aged 6-12 years, clonidine for single exposures and atypical antipsychotics for multiple exposures; for patients aged 13-19 years, atypical antipsychotics for single and multiple exposures; and for patients over 19 years, atypical antipsychotics for single exposures and benzodiazepines for multiple exposures. From 2000-2013, the exposures to substances most commonly associated with intubation varied by single versus multiple exposures and by age. This study helps clarify the exposures to substances that are associated with intubation reported to poison centers in the USA

Multitask Learning on Graph Neural Networks: Learning Multiple Graph Centrality Measures with a Unified Network

The application of deep learning to symbolic domains remains an active research endeavour. Graph neural networks (GNN), consisting of trained neural modules which can be arranged in different topologies at run time, are sound alternatives to tackle relational problems which lend themselves to graph representations. In this paper, we show that GNNs are capable of multitask learning, which can be naturally enforced by training the model to refine a single set of multidimensional embeddings $\in \mathbb{R}^d$ and decode them into multiple outputs by connecting MLPs at the end of the pipeline. We demonstrate the multitask learning capability of the model in the relevant relational problem of estimating network centrality measures, focusing primarily on producing rankings based on these measures, i.e. is vertex $v_1$ more central than vertex $v_2$ given centrality $c$?. We then show that a GNN can be trained to develop a \emph{lingua franca} of vertex embeddings from which all relevant information about any of the trained centrality measures can be decoded. The proposed model achieves $89\%$ accuracy on a test dataset of random instances with up to 128 vertices and is shown to generalise to larger problem sizes. The model is also shown to obtain reasonable accuracy on a dataset of real world instances with up to 4k vertices, vastly surpassing the sizes of the largest instances with which the model was trained ($n=128$). Finally, we believe that our contributions attest to the potential of GNNs in symbolic domains in general and in relational learning in particular.Comment: Published at ICANN2019. 10 pages, 3 Figure

The stellar populations of spiral disks.II Measuring and modeling the radial distribution of absorption spectral indices

The radial distributions of the Mg2 and Fe5270 Lick spectral indices have been measured to large radial distances on the disks of NGC 4303 and NGC 4535 using an imaging technique based on interference filters. These data, added to those of NGC 4321 previously published in Paper I of this series are used to constraint chemical (multiphase) evolutionary models for these galaxies. Because the integrated light of a stellar disk is a time average over the history of the galaxy weighted by the star formation rate, these constraints complement the information on chemical gradients provided by the study of HII regions which, by themselves, can only provide the alpha-elements abundance accumulate over the life of the galaxy. The agreement between the observations and the model predictions shown here lends confidence to the models which are then used to describe the time evolution of galaxy parameters such as star formation rates, chemical gradients, and gradients in the mean age of the stellar population.Comment: to be published in Astrophysical Journa

Hydroacoustic Assessment of Abundance and Diel Distribution of Sockeye Salmon and Kokanee in the Sawtooth Valley Lakes, Idaho

We used dual-beam hydroacoustics and echo integration techniques, combined with midwater trawling and gillnetting, to assess the abundance and distribution of the endangered Snake River juvenile sockeye salmon and resident kokanee (both Oncorhynchus nerka) in Sawtooth Valley lakes of Idaho during September 1991 and 1992. Abundance of O. nerka varied among the four lakes containing this species (12,500–257,000) and varied between years in Redfish Lake (86,400 in 1994 and 241,000 in 1992) and Alturas Lake (230,000 in 1991 and 257,000 in 1992). In Alturas Lake, where piscivore densities were high and zooplankton densities were low, small acoustic targets (≤18 cm long) were nearly absent from the limnetic zone during daylight, and high densities remained in colder intermediate depths (15–30 m) during crepuscular and nocturnal periods. In Redfish Lake, where predator density was much lower and zooplankton density was higher, targets concentrated in schools at 25–30 m during daylight, dispersed into the upper 10 m at dusk, then were broadly distributed over the upper 30 m at night. In Pettit and Stanley lakes, nocturnal distributions of smaller (3–7 cm) and intermediate (7–18 cm) target sizes were skewed toward the epilimnion, and larger targets remained in the metalimnion or upper hypolimnion. The different diel vertical distribution patterns suggested that juvenile O. nerka exposed to limited food and high predation risk consumed smaller rations and maximized bioenergetic efficiency. Populations with higher food supplies and exposed to lower piscivore densities exploited the higher epilimnetic prey densities and temperatures at night and crepuscular periods to maximize growth but deviated further from bioenergetic efficiency. Populations responded differently to the unique combination of constraints that limit potential sockeye salmon smolt production at each lake. Consequently, different management strategies may be needed in each lake

A Preliminary Study Investigating Maternal Neurocognitive Mechanisms Underlying a Child-Supportive Parenting Intervention

Although interventions that promote child-supportive parenting for children have been shown to positively impact caregiving behaviors as well as child behavioral and neurobiological functioning, less is known about which aspects of maternal brain functioning are affected by such interventions. In the present study, we conducted a preliminary evaluation of the impact of the Filming Interactions to Nurture Development (FIND) video coaching program on mothers with at least one child age four or younger. We employed a waitlist control design with pre-post data. Compared to mothers in the control condition (n = 16), mothers who received FIND (n = 16) showed changes in neural measures of inhibitory control and behavioral measures of parenting self-evaluation during a series of functional neuroimaging tasks. Specifically, we found a group by time interaction in clusters in the left inferior frontal gyrus (IFG) and insula for the Correct Stop &gt; Correct Go contrast of the stop signal task (SST), where FIND increased brain activity associated with inhibitory control compared to mothers in the control condition; and FIND increased mothers’ endorsement of child-supportive parenting traits in the parenting self-evaluation task (PSET). Exploratory moderators, study limitations, and the implications of these findings for strength-based parenting programs are discussed