09181 Abstracts Collection -- Sampling-based Optimization in the Presence of Uncertainty

This Dagstuhl seminar brought together researchers from statistical ranking and selection; experimental design and response-surface modeling; stochastic programming; approximate dynamic programming; optimal learning; and the design and analysis of computer experiments with the goal of attaining a much better mutual understanding of the commonalities and differences of the various approaches to sampling-based optimization, and to take first steps toward an overarching theory, encompassing many of the topics above

Gaussian Markov random fields for discrete optimization via simulation:framework and algorithms

We consider optimizing the expected value of some performance measure of a dynamic stochastic simulation with a statistical guarantee for optimality when the decision variables are discrete, in particular, integer-ordered; the number of feasible solutions is large; and the model execution is too slow to simulate even a substantial fraction of them. Our goal is to create algorithms that stop searching when they can provide inference about the remaining optimality gap similar to the correct-selection guarantee of ranking and selection when it simulates all solutions. Further, our algorithm remains competitive with fixed-budget algorithms that search efficiently but do not provide such inference. To accomplish this we learn and exploit spatial relationships among the decision variables and objective function values using a Gaussian Markov random field (GMRF). Gaussian random fields on continuous domains are already used in deterministic and stochastic optimization because they facilitate the computation of measures, such as expected improvement, that balance exploration and exploitation. We show that GMRFs are particularly well suited to the discrete decision–variable problem, from both a modeling and a computational perspective. Specifically, GMRFs permit the definition of a sensible neighborhood structure, and they are defined by their precision matrices, which can be constructed to be sparse. Using this framework, we create both single and multiresolution algorithms, prove the asymptotic convergence of both, and evaluate their finite-time performance empirically

Online Risk Monitoring Using Offline Simulation

Estimating portfolio risk measures and classifying portfolio risk levels in real time are important yet challenging tasks. In this paper, we propose to build a logistic regression model using data generated in past simulation experiments and to use the model to predict portfolio risk measures and classify risk levels at any time. We further explore regularization techniques, simulation model structure, and additional simulation budget to enhance the estimators of the logistic regression model to make its predictions more precise. Our numerical results show that the proposed methods work well. Our work may be viewed as an example of the recently proposed idea of simulation analytics, which treats a simulation model as a data generator and proposes to apply data analytics tools to the simulation outputs to uncover conditional statements. Our work shows that the simulation analytics idea is viable and promising in the field of financial risk management

X-ray and UV emission from the recurrent nova RS Ophiuchi in quiescence: Signatures of accretion and shocked gas

RS Ophiuchi is a recurrent nova system that experiences outbursts every ~20 years, implying accretion at a high rate onto a massive white dwarf. However, previous X-ray observations of the system in quiescence have detected only faint emission that is difficult to reconcile with the high accretion rate predicted by nova theory for such frequent outbursts. Here, we use new Chandra and XMM-Newton observations obtained 537 and 744 days after the 2006 outburst to constrain both the accretion rate onto the white dwarf and the properties of the nova ejecta at these times. We detect low level UV variability with the XMM-Newton Optical Monitor on day 744 that is consistent with accretion disk flickering, and use this to place a lower limit on the accretion rate. The X-ray spectra in both observations are well described by a two component thermal plasma model. The first component originates in the nova shell, which can emit X-rays for up to a decade after the outburst. The other component likely arises in the accretion disk boundary layer, and can be equally well fit by a single temperature plasma or a cooling flow model. Although the flux of the single temperature model implies an accretion rate that is 40 times lower than theoretical predictions for RS Oph, the best fit cooling flow model implies Mdot < 1.2x10^-8 M_sol/yr 537 days after the outburst, which is within a factor of 2 of the theoretical accretion rate required to power an outburst every 20 years. Furthermore, we place an upper limit on the accretion rate through an optically thick region of the boundary layer of 2.0x10^-8 M_sol/yr. Thus, the X-ray emission in quiescence is consistent with the accretion rate expectations of nova theory. Finally, we discuss the possible origins of the low temperature associated with the accretion component, which is a factor of 10 lower than in T CrB, an otherwise similar recurrent nova.Comment: 16 pages, 6 figures, accepted for publication in Ap

Seroprevalence of Zika virus in wild African green monkeys and baboons

ABSTRACT Zika virus (ZIKV) has recently spread through the Americas and has been associated with a range of health effects, including birth defects in children born to women infected during pregnancy. Although the natural reservoir of ZIKV remains poorly defined, the virus was first identified in a captive “sentinel” macaque monkey in Africa in 1947. However, the virus has not been reported in humans or nonhuman primates (NHPs) in Africa outside Gabon in over a decade. Here, we examine ZIKV infection in 239 wild baboons and African green monkeys from South Africa, the Gambia, Tanzania, and Zambia using combinations of unbiased deep sequencing, quantitative reverse transcription-PCR (qRT-PCR), and an antibody capture assay that we optimized using serum collected from captive macaque monkeys exposed to ZIKV, dengue virus, and yellow fever virus. While we did not find evidence of active ZIKV infection in wild NHPs in Africa, we found variable ZIKV seropositivity of up to 16% in some of the NHP populations sampled. We anticipate that these results and the methodology described within will help in continued efforts to determine the prevalence, natural reservoir, and transmission dynamics of ZIKV in Africa and elsewhere. IMPORTANCE Zika virus (ZIKV) is a mosquito-borne virus originally discovered in a captive monkey living in the Zika Forest of Uganda, Africa, in 1947. Recently, an outbreak in South America has shown that ZIKV infection can cause myriad health effects, including birth defects in the children of women infected during pregnancy. Here, we sought to investigate ZIKV infection in wild African primates to better understand its emergence and spread, looking for evidence of active or prior infection. Our results suggest that up to 16% of some populations of nonhuman primate were, at some point, exposed to ZIKV. We anticipate that this study will be useful for future studies that examine the spread of infections from wild animals to humans in general and those studying ZIKV in primates in particular. Podcast: A podcast concerning this article is available

Lack of a significant legacy effect of baseline blood pressure 'treatment naivety' on all-cause and cardiovascular mortality in the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial

Objectives: To investigate legacy effects at 14-year follow-up of all-cause and cardiovascular disease (CVD) mortality in 'treatment-naive' or 'previous treatment' groups based on blood pressure (BP)-lowering treatment status at baseline. Methods: A post-hoc observational study of the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial. We excluded participants with a previous history of CVD events. Cox proportional hazard model and 95% confidence interval were used to estimate the effects of treatment naive on mortality outcomes. Moreover, a subgroup analysis by estimated 10-year Framingham risk score was performed. Results: In multivariable models adjusting for baseline and in-trial characteristics (BP values and number of BP medications as time-dependent variables), there was no statistically significant difference in 5 and 14-year all-cause mortality with a hazard ratio of 0.93 (95% confidence interval 0.80-1.09) and hazard ratio 0.95 (0.88-1.03) and in 5 and 14-year CVD mortality hazard ratio 0.94 (0.72-1.23) and hazard ratio 0.93 (0.80-1.08). In subgroup by absolute CVD risk, no heterogeneity of the association between treatment naive and short-term or long-term all-cause or CVD mortality were found. All comparisons are between the treatment-naive and previous treatment groups. Conclusion: Physicians are concerned about 'legacy effects' of not treating individuals with a BP of 140 mmHg or over and low absolute risk. When treatment intensification was taken into consideration in the primary prevention population in this study, no adverse legacy effect as a result of baseline BP 'treatment naivety' was evident in 14 years of follow-up. The nonsignificant associations were consistent across the CVD risk subgroups. However, the results may be biased due to unobserved residual confounding and therefore should be interpreted with caution

Association of Blood Biomarkers With Acute Sport-Related Concussion in Collegiate Athletes: Findings From the NCAA and Department of Defense CARE Consortium

Importance: There is potential scientific and clinical value in validation of objective biomarkers for sport-related concussion (SRC). Objective: To investigate the association of acute-phase blood biomarker levels with SRC in collegiate athletes. Design, Setting, and Participants: This multicenter, prospective, case-control study was conducted by the National Collegiate Athletic Association (NCAA) and the US Department of Defense Concussion Assessment, Research, and Education (CARE) Consortium from February 20, 2015, to May 31, 2018, at 6 CARE Advanced Research Core sites. A total of 504 collegiate athletes with concussion, contact sport control athletes, and non-contact sport control athletes completed clinical testing and blood collection at preseason baseline, the acute postinjury period, 24 to 48 hours after injury, the point of reporting being asymptomatic, and 7 days after return to play. Data analysis was conducted from March 1 to November 30, 2019. Main Outcomes and Measures: Glial fibrillary acidic protein (GFAP), ubiquitin C-terminal hydrolase-L1 (UCH-L1), neurofilament light chain, and tau were quantified using the Quanterix Simoa multiplex assay. Clinical outcome measures included the Sport Concussion Assessment Tool-Third Edition (SCAT-3) symptom evaluation, Standardized Assessment of Concussion, Balance Error Scoring System, and Brief Symptom Inventory 18. Results: A total of 264 athletes with concussion (mean [SD] age, 19.08 [1.24] years; 211 [79.9%] male), 138 contact sport controls (mean [SD] age, 19.03 [1.27] years; 107 [77.5%] male), and 102 non-contact sport controls (mean [SD] age, 19.39 [1.25] years; 82 [80.4%] male) were included in the study. Athletes with concussion had significant elevation in GFAP (mean difference, 0.430 pg/mL; 95% CI, 0.339-0.521 pg/mL; P < .001), UCH-L1 (mean difference, 0.449 pg/mL; 95% CI, 0.167-0.732 pg/mL; P < .001), and tau levels (mean difference, 0.221 pg/mL; 95% CI, 0.046-0.396 pg/mL; P = .004) at the acute postinjury time point compared with preseason baseline. Longitudinally, a significant interaction (group × visit) was found for GFAP (F7,1507.36 = 16.18, P < .001), UCH-L1 (F7,1153.09 = 5.71, P < .001), and tau (F7,1480.55 = 6.81, P < .001); the interaction for neurofilament light chain was not significant (F7,1506.90 = 1.33, P = .23). The area under the curve for the combination of GFAP and UCH-L1 in differentiating athletes with concussion from contact sport controls at the acute postinjury period was 0.71 (95% CI, 0.64-0.78; P < .001); the acute postinjury area under the curve for all 4 biomarkers combined was 0.72 (95% CI, 0.65-0.79; P < .001). Beyond SCAT-3 symptom score, GFAP at the acute postinjury time point was associated with the classification of athletes with concussion from contact controls (β = 12.298; 95% CI, 2.776-54.481; P = .001) and non-contact sport controls (β = 5.438; 95% CI, 1.676-17.645; P = .005). Athletes with concussion with loss of consciousness or posttraumatic amnesia had significantly higher levels of GFAP than athletes with concussion with neither loss of consciousness nor posttraumatic amnesia at the acute postinjury time point (mean difference, 0.583 pg/mL; 95% CI, 0.369-0.797 pg/mL; P < .001). Conclusions and Relevance: The results suggest that blood biomarkers can be used as research tools to inform the underlying pathophysiological mechanism of concussion and provide additional support for future studies to optimize and validate biomarkers for potential clinical use in SRC

Lactation and neonatal nutrition: defining and refining the critical questions.

This paper resulted from a conference entitled "Lactation and Milk: Defining and refining the critical questions" held at the University of Colorado School of Medicine from January 18-20, 2012. The mission of the conference was to identify unresolved questions and set future goals for research into human milk composition, mammary development and lactation. We first outline the unanswered questions regarding the composition of human milk (Section I) and the mechanisms by which milk components affect neonatal development, growth and health and recommend models for future research. Emerging questions about how milk components affect cognitive development and behavioral phenotype of the offspring are presented in Section II. In Section III we outline the important unanswered questions about regulation of mammary gland development, the heritability of defects, the effects of maternal nutrition, disease, metabolic status, and therapeutic drugs upon the subsequent lactation. Questions surrounding breastfeeding practice are also highlighted. In Section IV we describe the specific nutritional challenges faced by three different populations, namely preterm infants, infants born to obese mothers who may or may not have gestational diabetes, and infants born to undernourished mothers. The recognition that multidisciplinary training is critical to advancing the field led us to formulate specific training recommendations in Section V. Our recommendations for research emphasis are summarized in Section VI. In sum, we present a roadmap for multidisciplinary research into all aspects of human lactation, milk and its role in infant nutrition for the next decade and beyond