Chemodynamical Simulations of Star-Forming Molecular Clouds

Stars are known to form from dense, dusty clumps and cores of molecular clouds. However, there is no consensus on a theory that can predict the rate of star formation, its clustering, and the conditions needed for massive stars to be born. A major challenge is how to observe and characterise the gas that is the fuel for star formation. One way is to take advantage of line emission from molecular species, a great variety of which have now been detected in the interstellar medium. However, interpreting the messages from these molecules necessitates an understanding and modeling of astrochemistry. In addition to this diagnostic power, astrochemistry is also expected to impact the physical evolution of the gas by influencing heating and cooling rates and controlling the degree of ionization, which mediates coupling to magnetic fields. To make progress in modeling the physical and chemical evolution of molecular clouds, we develop methods for chemodynamical simulations and carry out several studies combining magnetohydrodynamics (MHD) and astrochemistry. Our first investigation concerns the evolution of chemical abundances in massive pre-stellar cores, which are the initial conditions in some theories of massive star formation. A gas-phase chemical reaction network is applied to MHD simulations, with a focus on predicting the level of deuteration of key diagnostic species that are widely used in observational searches for such cores. We show how the abundances and kinematics of N2D+ and N2H+ can help disentangle the chemodynamical history of massive cores. Next we examine the formation of populations of cores from colliding and non-colliding giant molecular clouds (GMCs). We begin by carrying out high resolution MHD simulations to examine how core properties, especially the core mass function (CMF), are influenced by the dynamics of the GMCs. Synthetic observations of the simulated clouds are derived to enable a more direct comparison with observed CMFs. We then use a gas-grain chemical network to follow the evolution of key gas- and ice-phase species in these GMCs. One application is a study of the influence of the cosmic ray ionization rate on the abundances of CO, HCO+ and N2H+ in the colliding and non-colliding clouds and how observations of these species can help measure this key environmental property. Associated with the release of our astrochemical modeling tool, Naunet, we also discuss the computational performance of chemodynamical simulations and summarize methods to further improve their efficiency

Chemodynamics in Star-Forming Molecular Clouds

Stars are fundamental building blocks of galaxies. However, the answers to many basic questions about their formation remain elusive. There is no consensus on a theory that can predict the rate of star formation, its clustering properties, and the conditions needed for massive stars to be born. Although stars are known to form from dense regions of molecular clouds, measuring the physical properties in such regions is an outstanding challenge. Astrochemistry is the crucial set of processes that control the chemical evolution of the universe. It is important for controlling physical evolution, e.g., by setting heating and cooling rates and ionization fractions, but also for allowing predictions to be made for the emission from key diagnostic species to probe interstellar processes, such as star formation. To reconstruct the three-dimensional structures of galaxies and their interstellar media, chemodynamics, which is the combination of hydrodynamics and chemistry, is necessary.In this thesis, chemodynamical simulations are applied to star-forming regions to follow their combined physical and chemical evolution and make predictions for observations. In particular a gas phase deuterium fractionation network is applied to massive prestellar core simulations. Various chemical model parameters are investigated to understand whether fast collapse of a turbulent, magnetised prestellar core can achieve the high levels of deuteration that are commonly observed in such systems. The structure, kinematics and dynamics of the core, as traced by the rotational transitions of the key diagnostic species of $\rm N_2D^+$, are investigated. Another astrochemical network, including gas-grain processes, is constructed for simulations of larger-scale, generally lower density molecular clouds and applied to a simulation of giant molecular cloud collisions. We also discuss the computational performance of our chemodynamical simulations and summarize some methods to improve their efficiency

Denoising Diffusion Probabilistic Models to Predict the Density of Molecular Clouds

We introduce the state-of-the-art deep learning Denoising Diffusion Probabilistic Model (DDPM) as a method to infer the volume or number density of giant molecular clouds (GMCs) from projected mass surface density maps. We adopt magnetohydrodynamic simulations with different global magnetic field strengths and large-scale dynamics, i.e., noncolliding and colliding GMCs. We train a diffusion model on both mass surface density maps and their corresponding mass-weighted number density maps from different viewing angles for all the simulations. We compare the diffusion model performance with a more traditional empirical two-component and three-component power-law fitting method and with a more traditional neural network machine learning approach (CASI-2D). We conclude that the diffusion model achieves an order of magnitude improvement on the accuracy of predicting number density compared to that by other methods. We apply the diffusion method to some example astronomical column density maps of Taurus and the Infrared Dark Clouds (IRDCs) G28.37+0.07 and G35.39-0.33 to produce maps of their mean volume densities.Comment: ApJ accepte

GMC collisions as triggers of star formation – VIII. The core mass function

Compression in giant molecular cloud (GMC) collisions is a promising mechanism to trigger the formation of massive star clusters and OB associations. We simulate colliding and non-colliding magnetized GMCs and examine the properties of pre-stellar cores, selected from projected mass surface density maps, including after synthetic ALMA observations. We then examine core properties, including mass, size, density, velocity, velocity dispersion, temperature, and magnetic field strength. After 4 Myr, ∼1000 cores have formed in the GMC collision, and the high-mass end of the core mass function (CMF) can be fit by a power-law dN/dlogM ∝ M-α with α ≃ 0.7, i.e. relatively top heavy compared to a Salpeter mass function. Depending on how cores are identified, a break in the power law can appear around a few 710 M☉. The non-colliding GMCs form fewer cores with a CMF with α ≃ 0.8–1.2, i.e. closer to the Salpeter index. We compare the properties of these CMFs to those of several observed samples of cores. Considering other properties, cores formed from colliding clouds are typically warmer, have more disturbed internal kinematics, and are more likely to be gravitational unbound, than cores formed from non-colliding GMCs. The dynamical state of the protocluster of cores formed in the GMC–GMC collision is intrinsically subvirial but can appear to be supervirial if the total mass measurement is affected by observations that miss mass on large scales or at low densities

Estimation of Agricultural Groundwater Usage by Well Pumping Efficiency and Electric Consumption

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchive

Deuterium Chemodynamics of Massive Pre-Stellar Cores

High levels of deuterium fractionation of $\rm N_2H^+$ (i.e., $\rm D_{frac}^{N_2H^+} \gtrsim 0.1$) are often observed in pre-stellar cores (PSCs) and detection of $\rm N_2D^+$ is a promising method to identify elusive massive PSCs. However, the physical and chemical conditions required to reach such high levels of deuteration are still uncertain, as is the diagnostic utility of $\rm N_2H^+$ and $\rm N_2D^+$ observations of PSCs. We perform 3D magnetohydrodynamics simulations of a massive, turbulent, magnetised PSC, coupled with a sophisticated deuteration astrochemical network. Although the core has some magnetic/turbulent support, it collapses under gravity in about one freefall time, which marks the end of the simulations. Our fiducial model achieves relatively low $\rm D_{frac}^{N_2H^+} \sim 0.002$ during this time. We then investigate effects of initial ortho-para ratio of $\rm H_2$ ($\rm OPR^{H_2}$), temperature, cosmic ray (CR) ionization rate, CO and N-species depletion factors and prior PSC chemical evolution. We find that high CR ionization rates and high depletion factors allow the simulated $\rm D_{frac}^{N_2H^+}$ and absolute abundances to match observational values within one freefall time. For $\rm OPR^{H_2}$, while a lower initial value helps the growth of $\rm D_{frac}^{N_2H^+}$, the spatial structure of deuteration is too widespread compared to observed systems. For an example model with elevated CR ionization rates and significant heavy element depletion, we then study the kinematic and dynamic properties of the core as traced by its $\rm N_2D^+$ emission. The core, undergoing quite rapid collapse, exhibits disturbed kinematics in its average velocity map. Still, because of magnetic support, the core often appears kinematically sub-virial based on its $\rm N_2D^+$ velocity dispersion.Comment: 25 pages, 20 figures, 2 tables, accepted for publication in MNRAS, comments welcom

Risk factors and clinical significance of bacteremia caused by Pseudomonas aeruginosa resistant only to carbapenems

Background/purposeCarbapenem-resistant Pseudomonas aeruginosa infections have been a challenge and issue in hospital settings. However, the clinical impact of P. aeruginosa blood isolates resistant only to carbapenems has never been discussed previously.MethodsTo assess the risk factors and clinical significance of bacteremia caused by carbapenem resistance only P. aeruginosa (CROPA), a 6-year retrospective case–control study was conducted. The CROPA strains were defined as isolates susceptible to ciprofloxacin, antipseudomonal penicillins and cephalosporins, and aminoglycosides but resistant to one antipseudomonal carbapenem (imipenem or meropenem) or both. The controls were selected among patients with bacteremia due to P. aeruginosa susceptible to all above classes of antipseudomonal antibiotics, which was defined as all-susceptible P. aeruginosa.ResultsTwenty-five patients had at least one blood culture positive for CROPA, and 50 controls had all-susceptible P. aeruginosa bacteremia. CROPA bacteremia had a high 30-day mortality rate (72.0%), as compared to 26.0% for the controls (p < 0.001). Through multivariate analysis, carbapenem exposure was the only risk factor for developing CROPA bacteremia (p = 0.002). A comparison between the surviving and deceased patients with CROPA bacteremia showed that nine (50%) of those who died, but none of the survivors, received carbapenems as the initial empirical therapy (p = 0.027).ConclusionCarbapenem exposure was associated with emergence of CROPA infections. Repeated carbapenem use in such patients might increase rates of inappropriate initial empirical treatment and mortality. Prudent carbapenem use is important to reduce the emergence of CROPA

Interplay between Cell Migration and Neurite Outgrowth Determines SH2B1β-Enhanced Neurite Regeneration of Differentiated PC12 Cells

The regulation of neurite outgrowth is crucial in developing strategies to promote neurite regeneration after nerve injury and in degenerative diseases. In this study, we demonstrate that overexpression of an adaptor/scaffolding protein SH2B1β promotes neurite re-growth of differentiated PC12 cells, an established neuronal model, using wound healing (scraping) assays. Cell migration and the subsequent remodeling are crucial determinants during neurite regeneration. We provide evidence suggesting that overexpressing SH2B1β enhances protein kinase C (PKC)-dependent cell migration and phosphatidylinositol 3-kinase (PI3K)-AKT-, mitogen activated protein kinase (MAPK)/extracellular signal-regulated protein kinase (ERK) kinase (MEK)-ERK-dependent neurite re-growth. Our results further reveal a cross-talk between pathways involving PKC and ERK1/2 in regulating neurite re-growth and cell migration. We conclude that temporal regulation of cell migration and neurite outgrowth by SH2B1β contributes to the enhanced regeneration of differentiated PC12 cells