Novae -The study of the reactive flow

There is a wide consensus in the astrophysics community that the mechanism underlying the observed Classical Nova eruptions is a surface thermonuclear runaway. We start this short review with the main observational facts that lead to the theoretical model of a thermonuclear runaway that takes place in an accreted hydrogen rich envelope placed on top of a cool degenerate core of a white dwarf. According to the theory, the accreted envelope becomes unstable to convection days to weeks prior to the runaway. During the extreme stages of the runaway itself, when the burning is most efficient, the envelope is fully convective. Therefore, the elements processed under such extreme conditions are lifted to the outermost regions of the star. A significant fraction of the envelope is ejected during the outburst. The complicated combination of hydrodynamic instabilities and explosive hydrogen burning, close to the surface of the star, gives us a unique opportunity to study this complex reactive flow. The range of core masses, core temperatures and accretion rates introduce a whole range of burning temperatures and densities. Following the description of the "standard" cases, we then focus on rare, but still possible, portions of the relevant parameter space, in which "breakout" of the traditional CNO cycle can occur and lead to heavy element enrichment patterns caused only by breakout burning. We conclude our review with the main challenges that nova theorists face today, with special emphasis on problems related to the nucleosynthesis issues.Comment: Proceedings of: Nuclear Physics in Astrophysics-V,Eilat,April,201

From isolated subgroups to generic permutation representations

Let $G$ be a countable group, $\operatorname{Sub}(G)$ the (compact, metric) space of all subgroups of $G$ with the Chabauty topology and $\operatorname{Is}(G) \subset \operatorname{Sub}(G)$ the collection of isolated points. We denote by $X!$ the (Polish) group of all permutations of a countable set $X$. Then the following properties are equivalent: (i) $\operatorname{Is}(G)$ is dense in $\operatorname{Sub}(G)$, (ii) $G$ admits a "generic permutation representation". Namely there exists some $\tau^* \in \operatorname{Hom}(G,X!)$ such that the collection of permutation representations $\{\phi \in \operatorname{Hom}(G,X!) \ | \ \phi {\text{is permutation isomorphic to}} \tau^*\}$ is co-meager in $\operatorname{Hom}(G,X!)$. We call groups satisfying these properties solitary. Examples of solitary groups include finitely generated LERF groups and groups with countably many subgroups.Comment: 21 page

Strange Cepheids and RR Lyrae

Strange modes can occur in radiative classical Cepheids and RR Lyrae models. These are vibrational modes that are trapped near the surface as a result of a 'potential barrier' caused by the sharp hydrogen partial ionization region. Typically the modal number of the strange mode falls between the 7th and 12th overtone, depending on the astrophysical parameters of the equilibrium stellar models (L, M, \Teff, X, Z). Interestingly these modes can be linearly unstable outside the usual instability strip, in which case they should be observable as new kinds of variable stars, 'strange Cepheids' or 'strange RR Lyrae' stars. The present paper reexamines the linear stability properties of the strange modes by taking into account the effects of an isothermal atmosphere, and of turbulent convection. It is found that the linear vibrational instability of the strange modes is resistant to both of these effects. Nonlinear hydrodynamic calculations indicate that the pulsation amplitude of these modes is likely to saturate at the millimagnitude level. These modes should therefore be detectable albeit not without effort.Comment: 6 pages, 7 figures, submitted to Ap

Previsit Multidomain Psychosocial Screening Tools for Adolescents and Young Adults: A Systematic Review.

Adolescence and young adulthood constitute a period when exploratory behaviors can evolve into risky behaviors. Most causes of adolescent ill health are preventable; therefore, it is a priority to detect them early before they turn into health problems. Previsit multidomain psychosocial screening tools are used by professionals to detect and prioritize potentially problematic issues. In conjunction with appropriate clinician training, these tools have improved clinician screening rates in several areas of adolescent health. This article reviews existing multidomain previsit psychosocial screening tools developed in the 21st century and describes their characteristics using a systematic methodology. We reviewed 10,623 records to identify 15 different tools in use since 2000 and described their characteristics. Results show that all tools were developed in high-income countries. The tools provide sufficient coverage of many psychosocial domains relevant to young people's health. However, some psychosocial domains such as screen use and strengths are seldomly addressed. Furthermore, the tools rarely focus on young adults as a target population. Future research should assess the effectiveness, acceptability, and psychometric properties of validated psychosocial screening tools and examine how to expand their use in low- and middle-income countries

The Effect of Composition on Nova Ignitions

The accretion of hydrogen-rich matter onto C/O and O/Ne white dwarfs in binary systems leads to unstable thermonuclear ignition of the accreted envelope, triggering a convective thermonuclear runaway and a subsequent classical, recurrent, or symbiotic nova. Prompted by uncertainties in the composition at the base of the accreted envelope at the onset of convection, as well as the range of abundances detected in nova ejecta, we examine the effects of varying the composition of the accreted material. For high accretion rates and carbon mass fractions < 0.002, we find that carbon, which is usually assumed to trigger the runaway via proton captures, is instead depleted and converted to 14N. Additionally, we quantify the importance of 3He, finding that convection is triggered by 3He+3He reactions for 3He mass fractions > 0.002. These different triggering mechanisms, which occur for critical abundances relevant to many nova systems, alter the amount of mass that is accreted prior to a nova, causing the nova rate to depend on accreted composition. Upcoming deep optical surveys such as Pan-STARRS-1, Pan-STARRS-4, and the Large Synoptic Survey Telescope may allow us to detect the dependence of nova rates on accreted composition. Furthermore, the burning and depletion of 3He with a mass fraction of 0.001, which is lower than necessary for triggering convection, still has an observable effect, resulting in a pre-outburst brightening in disk quiescence to > Lsun and an increase in effective temperature to 6.5e4 K for a 1.0 Msun white dwarf accreting at 1e-8 Msun/yr.Comment: Submitted to The Astrophysical Journal, 11 pages, 11 figure

MAESTRO: An Adaptive Low Mach Number Hydrodynamics Algorithm for Stellar Flows

Many astrophysical phenomena are highly subsonic, requiring specialized numerical methods suitable for long-time integration. In a series of earlier papers we described the development of MAESTRO, a low Mach number stellar hydrodynamics code that can be used to simulate long-time, low-speed flows that would be prohibitively expensive to model using traditional compressible codes. MAESTRO is based on an equation set derived using low Mach number asymptotics; this equation set does not explicitly track acoustic waves and thus allows a significant increase in the time step. MAESTRO is suitable for two- and three-dimensional local atmospheric flows as well as three-dimensional full-star flows. Here, we continue the development of MAESTRO by incorporating adaptive mesh refinement (AMR). The primary difference between MAESTRO and other structured grid AMR approaches for incompressible and low Mach number flows is the presence of the time-dependent base state, whose evolution is coupled to the evolution of the full solution. We also describe how to incorporate the expansion of the base state for full-star flows, which involves a novel mapping technique between the one-dimensional base state and the Cartesian grid, as well as a number of overall improvements to the algorithm. We examine the efficiency and accuracy of our adaptive code, and demonstrate that it is suitable for further study of our initial scientific application, the convective phase of Type Ia supernovae.Comment: Accepted to Astrophysical Journal Suppliment (http://iop.org). 56 pages, 15 figures

Machine learning in infection management using routine electronic health records:tools, techniques, and reporting of future technologies

Background: Machine learning (ML) is increasingly being used in many areas of health care. Its use in infection management is catching up as identified in a recent review in this journal. We present here a complementary review to this work. Objectives: To support clinicians and researchers in navigating through the methodological aspects of ML approaches in the field of infection management. Sources: A Medline search was performed with the keywords artificial intelligence, machine learning, infection∗, and infectious disease∗ for the years 2014–2019. Studies using routinely available electronic hospital record data from an inpatient setting with a focus on bacterial and fungal infections were included. Content: Fifty-two studies were included and divided into six groups based on their focus. These studies covered detection/prediction of sepsis (n = 19), hospital-acquired infections (n = 11), surgical site infections and other postoperative infections (n = 11), microbiological test results (n = 4), infections in general (n = 2), musculoskeletal infections (n = 2), and other topics (urinary tract infections, deep fungal infections, antimicrobial prescriptions; n = 1 each). In total, 35 different ML techniques were used. Logistic regression was applied in 18 studies followed by random forest, support vector machines, and artificial neural networks in 18, 12, and seven studies, respectively. Overall, the studies were very heterogeneous in their approach and their reporting. Detailed information on data handling and software code was often missing. Validation on new datasets and/or in other institutions was rarely done. Clinical studies on the impact of ML in infection management were lacking. Implications: Promising approaches for ML use in infectious diseases were identified. But building trust in these new technologies will require improved reporting. Explainability and interpretability of the models used were rarely addressed and should be further explored. Independent model validation and clinical studies evaluating the added value of ML approaches are needed