Dark cloud cores and gravitational decoupling from turbulent flows

We test the hypothesis that the starless cores may be gravitationally bound clouds supported largely by thermal pressure by comparing observed molecular line spectra to theoretical spectra produced by a simulation that includes hydrodynamics, radiative cooling, variable molecular abundance, and radiative transfer in a simple one-dimensional model. The results suggest that the starless cores can be divided into two categories: stable starless cores that are in approximate equilibrium and will not evolve to form protostars, and unstable pre-stellar cores that are proceeding toward gravitational collapse and the formation of protostars. The starless cores might be formed from the interstellar medium as objects at the lower end of the inertial cascade of interstellar turbulence. Additionally, we identify a thermal instability in the starless cores. Under par ticular conditions of density and mass, a core may be unstable to expansion if the density is just above the critical density for the collisional coupling of the gas and dust so that as the core expands the gas-dust coupling that cools the gas is reduced and the gas warms, further driving the expansion.Comment: Submitted to Ap

The Different Structures of the Two Classes of Starless Cores

We describe a model for the thermal and dynamical equilibrium of starless cores that includes the radiative transfer of the gas and dust and simple CO chemistry. The model shows that the structure and behavior of the cores is significantly different depending on whether the central density is either above or below about 10^5 cm-3. This density is significant as the critical density for gas cooling by gas-dust collisions and also as the critical density for dynamical stability, given the typical properties of the starless cores. The starless cores thus divide into two classes that we refer to as thermally super-critical and thermally sub-critical.This two-class distinction allows an improved interpretation of the different observational data of starless cores within a single model.Comment: ApJ in pres

Designing a Photonic Physically Unclonable Function Having Resilience to Machine Learning Attacks

Physically unclonable functions (PUFs) are designed to act as device 'fingerprints.' Given an input challenge, the PUF circuit should produce an unpredictable response for use in situations such as root-of-trust applications and other hardware-level cybersecurity applications. PUFs are typically subcircuits present within integrated circuits (ICs), and while conventional IC PUFs are well-understood, several implementations have proven vulnerable to malicious exploits, including those perpetrated by machine learning (ML)-based attacks. Such attacks can be difficult to prevent because they are often designed to work even when relatively few challenge-response pairs are known in advance. Hence the need for both more resilient PUF designs and analysis of ML-attack susceptibility. Previous work has developed a PUF for photonic integrated circuits (PICs). A PIC PUF not only produces unpredictable responses given manufacturing-introduced tolerances, but is also less prone to electromagnetic radiation eavesdropping attacks than a purely electronic IC PUF. In this work, we analyze the resilience of the proposed photonic PUF when subjected to ML-based attacks. Specifically, we describe a computational PUF model for producing the large datasets required for training ML attacks; we analyze the quality of the model; and we discuss the modeled PUF's susceptibility to ML-based attacks. We find that the modeled PUF generates distributions that resemble uniform white noise, explaining the exhibited resilience to neural-network-based attacks designed to exploit latent relationships between challenges and responses. Preliminary analysis suggests that the PUF exhibits similar resilience to generative adversarial networks, and continued development will show whether more-sophisticated ML approaches better compromise the PUF and -- if so -- how design modifications might improve resilience.Comment: 14 pages, 8 figure

Molecular Evolution in Collapsing Prestellar Cores

We have investigated the evolution and distribution of molecules in collapsing prestellar cores via numerical chemical models, adopting the Larson-Penston solution and its delayed analogues to study collapse. Molecular abundances and distributions in a collapsing core are determined by the balance among the dynamical, chemical and adsorption time scales. When the central density n_H of a prestellar core with the Larson-Penston flow rises to 3 10^6 cm^{-3}, the CCS and CO column densities are calculated to show central holes of radius 7000 AU and 4000 AU, respectively, while the column density of N2H+ is centrally peaked. These predictions are consistent with observations of L1544. If the dynamical time scale of the core is larger than that of the Larson-Penston solution owing to magnetic fields, rotation, or turbulence, the column densities of CO and CCS are smaller, and their holes are larger than in the Larson-Penston core with the same central gas density. On the other hand, N2H+ and NH3 are more abundant in the more slowly collapsing core. Therefore, molecular distributions can probe the collapse time scale of prestellar cores. Deuterium fractionation has also been studied via numerical calculations. The deuterium fraction in molecules increases as a core evolves and molecular depletion onto grains proceeds. When the central density of the core is n_H=3 10^6 cm^{-3}, the ratio DCO+/HCO+ at the center is in the range 0.06-0.27, depending on the collapse time scale and adsorption energy; this range is in reasonable agreement with the observed value in L1544.Comment: 21 pages, 17 figure

Using built environment characteristics to predict walking for exercise

Background: Environments conducive to walking may help people avoid sedentary lifestyles and associated diseases. Recent studies developed walkability models combining several built environment characteristics to optimally predict walking. Developing and testing such models with the same data could lead to overestimating one's ability to predict walking in an independent sample of the population. More accurate estimates of model fit can be obtained by splitting a single study population into training and validation sets (holdout approach) or through developing and evaluating models in different populations. We used these two approaches to test whether built environment characteristics near the home predict walking for exercise. Study participants lived in western Washington State and were adult members of a health maintenance organization. The physical activity data used in this study were collected by telephone interview and were selected for their relevance to cardiovascular disease. In order to limit confounding by prior health conditions, the sample was restricted to participants in good self-reported health and without a documented history of cardiovascular disease. Results: For 1,608 participants meeting the inclusion criteria, the mean age was 64 years, 90 percent were white, 37 percent had a college degree, and 62 percent of participants reported that they walked for exercise. Single built environment characteristics, such as residential density or connectivity, did not significantly predict walking for exercise. Regression models using multiple built environment characteristics to predict walking were not successful at predicting walking for exercise in an independent population sample. In the validation set, none of the logistic models had a C-statistic confidence interval excluding the null value of 0.5, and none of the linear models explained more than one percent of the variance in time spent walking for exercise. We did not detect significant differences in walking for exercise among census areas or postal codes, which were used as proxies for neighborhoods. Conclusion: None of the built environment characteristics significantly predicted walking for exercise, nor did combinations of these characteristics predict walking for exercise when tested using a holdout approach. These results reflect a lack of neighborhood-level variation in walking for exercise for the population studied.University of Washington Royalty Research fund award; by contracts R01-HL043201, R01-HL068639, and T32-HL07902 from the National Heart, Lung, and Blood Institute; and by grant R01-AG09556 from the National Institute on Aging

A faux hawk fullerene with PCBM-like properties

Reaction of C60, C6F5CF2I, and SnH(n-Bu)3 produced, among other unidentified fullerene derivatives, the two new compounds 1,9-C60(CF2C6F5)H (1) and 1,9-C60(cyclo-CF2(2-C6F4)) (2). The highest isolated yield of 1 was 35% based on C60. Depending on the reaction conditions, the relative amounts of 1 and 2 generated in situ were as high as 85% and 71%, respectively, based on HPLC peak integration and summing over all fullerene species present other than unreacted C60. Compound 1 is thermally stable in 1,2-dichlorobenzene (oDCB) at 160 °C but was rapidly converted to 2 upon addition of Sn2(n-Bu)6 at this temperature. In contrast, complete conversion of 1 to 2 occurred within minutes, or hours, at 25 °C in 90/10 (v/v) PhCN/C6D6 by addition of stoichiometric, or sub-stoichiometric, amounts of proton sponge (PS) or cobaltocene (CoCp2). DFT calculations indicate that when 1 is deprotonated, the anion C60(CF2C6F5)− can undergo facile intramolecular SNAr annulation to form 2 with concomitant loss of F−. To our knowledge this is the first observation of a fullerene-cage carbanion acting as an SNAr nucleophile towards an aromatic C–F bond. The gas-phase electron affinity (EA) of 2 was determined to be 2.805(10) eV by low-temperature PES, higher by 0.12(1) eV than the EA of C60 and higher by 0.18(1) eV than the EA of phenyl-C61-butyric acid methyl ester (PCBM). In contrast, the relative E1/2(0/−) values of 2 and C60, −0.01(1) and 0.00(1) V, respectively, are virtually the same (on this scale, and under the same conditions, the E1/2(0/−) of PCBM is −0.09 V). Time-resolved microwave conductivity charge-carrier yield × mobility values for organic photovoltaic active-layer-type blends of 2 and poly-3-hexylthiophene (P3HT) were comparable to those for equimolar blends of PCBM and P3HT. The structure of solvent-free crystals of 2 was determined by single-crystal X-ray diffraction. The number of nearest-neighbor fullerene–fullerene interactions with centroid⋯centroid (⊙⋯⊙) distances of ≤10.34 Å is significantly greater, and the average ⊙⋯⊙ distance is shorter, for 2 (10 nearest neighbors; ave. ⊙⋯⊙ distance = 10.09 Å) than for solvent-free crystals of PCBM (7 nearest neighbors; ave. ⊙⋯⊙ distance = 10.17 Å). Finally, the thermal stability of 2 was found to be far greater than that of PCBM

Radiative Transfer and Starless Cores

We develop a method of analyzing radio frequency spectral line observations to derive data on the temperature, density, velocity, and molecular abundance of the emitting gas. The method incorporates a radiative transfer code with a new technique for handling overlapping hyperfine emission lines within the accelerated lambda iteration algorithm and a heuristic search algorithm based on simulated annnealing. We apply this method to new observations of N_2H^+ in three Lynds clouds thought to be starless cores in the first stages of star formation and determine their density structure. A comparison of the gas densities derived from the molecular line emission and the millimeter dust emission suggests that the required dust mass opacity is about kappa_{1.3mm}=0.04 cm^2/g, consistent with models of dust grains that have opacities enhanced by ice mantles and fluffy aggregrates.Comment: 42 pages, 17 figures, to appear in Ap

Molecular Evolution in Collapsing Prestellar Cores II: The Effect of Grain-surface Reactions

The molecular evolution that occurs in collapsing prestellar cores is investigated. To model the dynamics, we adopt the Larson-Penston (L-P) solution and analogues with slower rates of collapse. For the chemistry, we utilize the new standard model (NSM) with the addition of deuterium fractionation and grain-surface reactions treated via the modified rate approach. The use of surface reactions distinguishes the present work from our previous model. We find that these reactions efficiently produce H2O, H2CO, CH3OH, N2, and NH3 ices. In addition, the surface chemistry influences the gas-phase abundances in a variety of ways. The current reaction network along with the L-P solution allows us to reproduce satisfactorily most of the molecular column densities and their radial distributions observed in L1544. The agreement tends to worsen with models that include strongly delayed collapse rates. Inferred radial distributions in terms of fractional abundances are somewhat harder to reproduce. In addition to our standard chemical model, we have also run a model with the UMIST gas-phase chemical network. The abundances of gas-phase S-bearing molecules such as CS and CCS are significantly affected by uncertainties in the gas-phase chemical network. In all of our models, the column density of N2H+ monotonically increases as the central density of the core increases during collapse from 3 10^4 cm-3 to 3 10^7 cm-3. Thus, the abundance of this ion can be a probe of evolutionary stage. Molecular D/H ratios in assorted cores are best reproduced in the L-P picture with the conventional rate coefficients for fractionation reactions. If we adopt the newly measured and calculated rate coefficients, the D/H ratios, especially N2D+/N2H+, become significantly lower than the observed values.Comment: 23 pages, 10 figures, accepted to Ap

Sources and Secondary Production of Organic Aerosols in the Northeastern United States during WINTER

Most intensive field studies investigating aerosols have been conducted in summer, and thus, wintertime aerosol sources and chemistry are comparatively poorly understood. An aerosol mass spectrometer was flown on the National Science Foundation/National Center for Atmospheric Research C‐130 during the Wintertime INvestigation of Transport, Emissions, and Reactivity (WINTER) 2015 campaign in the northeast United States. The fraction of boundary layer submicron aerosol that was organic aerosol (OA) was about a factor of 2 smaller than during a 2011 summertime study in a similar region. However, the OA measured in WINTER was almost as oxidized as OA measured in several other studies in warmer months of the year. Fifty‐eight percent of the OA was oxygenated (secondary), and 42% was primary (POA). Biomass burning OA (likely from residential heating) was ubiquitous and accounted for 33% of the OA mass. Using nonvolatile POA, one of two default secondary OA (SOA) formulations in GEOS‐Chem (v10‐01) shows very large underpredictions of SOA and O/C (5×) and overprediction of POA (2×). We strongly recommend against using that formulation in future studies. Semivolatile POA, an alternative default in GEOS‐Chem, or a simplified parameterization (SIMPLE) were closer to the observations, although still with substantial differences. A case study of urban outflow from metropolitan New York City showed a consistent amount and normalized rate of added OA mass (due to SOA formation) compared to summer studies, although proceeding more slowly due to lower OH concentrations. A box model and SIMPLE perform similarly for WINTER as for Los Angeles, with an underprediction at ages \u3c6 hr, suggesting that fast chemistry might be missing from the models