A fundamental test for stellar feedback recipes in galaxy simulations

Direct comparisons between galaxy simulations and observations that both reach scales < 100 pc are strong tools to investigate the cloud-scale physics of star formation and feedback in nearby galaxies. Here we carry out such a comparison for hydrodynamical simulations of a Milky Way-like galaxy, including stochastic star formation, HII region and supernova feedback, and chemical post-processing at 8 pc resolution. Our simulation shows excellent agreement with almost all kpc-scale and larger observables, including total star formation rates, radial profiles of CO, HI, and star formation through the galactic disc, mass ratios of the ISM components, both whole-galaxy and resolved Kennicutt-Schmidt relations, and giant molecular cloud properties. However, we find that our simulation does not reproduce the observed de-correlation between tracers of gas and star formation on < 100 pc scales, known as the star formation 'uncertainty principle', which indicates that observed clouds undergo rapid evolutionary lifecycles. We conclude that the discrepancy is driven by insufficiently-strong pre-supernova feedback in our simulation, which does not disperse the surrounding gas completely, leaving star formation tracer emission too strongly associated with molecular gas tracer emission, inconsistent with observations. This result implies that the cloud-scale de-correlation of gas and star formation is a fundamental test for feedback prescriptions in galaxy simulations, one that can fail even in simulations that reproduce all other macroscopic properties of star-forming galaxies.Comment: 13 pages, 10 figures, accepted for publication in MNRA

Innovative methods for observing and changing complex health behaviors: Four propositions

Precision health initiatives aim to progressively move from traditional, group-level approaches to health diagnostics and treatments toward ones that are individualized, contextualized, and timely. This article aims to provide an overview of key methods and approaches that can help facilitate this transition in the health behavior change domain. This article is a narrative review of the methods used to observe and change complex health behaviors. On the basis of the available literature, we argue that health behavior change researchers should progressively transition from (i) low- to high-resolution behavioral assessments, (ii) group-only to group- and individual-level statistical inference, (iii) narrative theoretical models to dynamic computational models, and (iv) static to adaptive and continuous tuning interventions. Rather than providing an exhaustive and technical presentation of each method and approach, this article articulates why and how researchers interested in health behavior change can apply these innovative methods. Practical examples contributing to these efforts are presented. If successfully adopted and implemented, the four propositions in this article have the potential to greatly improve our public health and behavior change practices in the near future

The effects of codon context on in vivo translation speed

pre-printWe developed a bacterial genetic system based on translation of the his operon leader peptide gene to determine the relative speed at which the ribosome reads single or multiple codons in vivo. Low frequency effects of so-called ‘‘silent'' codon changes and codon neighbor (context) effects could be measured using this assay. An advantage of this system is that translation speed is unaffected by the primary sequence of the His leader peptide. We show that the apparent speed at which ribosomes translate synonymous codons can vary substantially even for synonymous codons read by the same tRNA species. Assaying translation through codon pairs for the 59- and 39- side positioning of the 64 codons relative to a specific codon revealed that the codon-pair orientation significantly affected in vivo translation speed. Codon pairs with rare arginine codons and successive proline codons were among the slowest codon pairs translated in vivo. This system allowed us to determine the effects of different factors on in vivo translation speed including Shine-Dalgarno sequence, rate of dipeptide bond formation, codon context, and charged tRNA levels

An uncertainty principle for star formation -- III. The characteristic emission time-scales of star formation rate tracers

We recently presented a new statistical method to constrain the physics of star formation and feedback on the cloud scale by reconstructing the underlying evolutionary timeline. However, by itself this new method only recovers the relative durations of different evolutionary phases. To enable observational applications, it therefore requires knowledge of an absolute 'reference time-scale' to convert relative time-scales into absolute values. The logical choice for this reference time-scale is the duration over which the star formation rate (SFR) tracer is visible because it can be characterised using stellar population synthesis (SPS) models. In this paper, we calibrate this reference time-scale using synthetic emission maps of several SFR tracers, generated by combining the output from a hydrodynamical disc galaxy simulation with the SPS model SLUG2. We apply our statistical method to obtain self-consistent measurements of each tracer's reference time-scale. These include H${\alpha}$ and 12 ultraviolet (UV) filters (from GALEX, Swift, and HST), which cover a wavelength range 150-350 nm. At solar metallicity, the measured reference time-scales of H${\alpha}$ are ${4.32^{+0.09}_{-0.23}}$ Myr with continuum subtraction, and 6-16 Myr without, where the time-scale increases with filter width. For the UV filters we find 17-33 Myr, nearly monotonically increasing with wavelength. The characteristic time-scale decreases towards higher metallicities, as well as to lower star formation rate surface densities, owing to stellar initial mass function sampling effects. We provide fitting functions for the reference time-scale as a function of metallicity, filter width, or wavelength, to enable observational applications of our statistical method across a wide variety of galaxies.Comment: 24 pages, 18 figures, 7 tables (including Appendices); published in MNRA

Distributed Mathematical Model Simulation on a Parallel Architecture

The aim of this article is to discuss the design of distributed mathematical models and suitable parallel architecture of computers. The paper summarises the author’s experience with mathematical modelling of decomposed information systems of a simulator. Conclusions are based on the theory of the design of the computer control systems. The author describes computers that create a distributed computer system of a flight simulator. Modelling of a time precision of mathematical model of the speed of a simulator system is done by describing equations. The qualities of models depend on the architecture of computer systems. Some functions of other sections of POSIX are also analysed including semaphores and scheduling functions. An important part of this article is the implementation of computation speed of aircraft in multicore processor architecture

Metal-catalyzed asymmetric sulfoxidation, epoxidation and hydroxylation by hydrogen peroxide

International audienceThe development of environmentally benign reactions is an important goal in synthetic organic chemistry and chemical engineering. However, catalytic enantioselective oxidations using transition-metal complexes are limited when the oxidant is hydrogen peroxide. The two main difficulties of using hydrogen peroxide in the presence of transition metal complexes are the homolytic cleavage generating OH radicals and the catalase reaction with formation of dioxygen. The current applications of asymmetric sulfoxidation, epoxidation, dihydroxylation of alkenes and hydroxylation will be herein reported. Use of non-heme systems will be presented. The possibility of asymmetric oxidation catalyzed by metalloporphyrins will also be discussed