Volatile Abundances, Extended Coma Sources, and Nucleus Ice Associations in Comet C/2014 Q2 (Lovejoy)

High-resolution infrared spectra of comet C/2014 Q2 Lovejoy were acquired with NIRSPEC at the W. M. Keck Observatory on two post-perihelion dates (UT 2015 February 2 and 3). H2O was measured simultaneously with CO, CH3OH, H2CO, CH4, C2H6, C2H4, C2H2, HCN, and NH3 on both dates, and rotational temperatures, production rates, relative abundances, H2O ortho-to-para ratios, and spatial distributions in the coma were determined. The first detection of C2H4 in a comet from ground-based observations is reported. Abundances relative to H2O for all species were found to be in the typical range compared with values for other comets in the overall population to date. There is evidence of variability in rotational temperatures and production rates on timescales that are small compared with the rotational period of the comet. Spatial distributions of volatiles in the coma suggest complex outgassing behavior. CH3OH, HCN, C2H6, and CH4 spatial distributions in the coma are consistent with direct release from associated ices in the nucleus and are peaked in a more sunward direction compared with co-measured dust. H2O spatial profiles are clearly distinct from these other four species, likely due to a sizable coma contribution from icy grain sublimation. Spatial distributions for C2H2, H2CO, and NH3 suggest substantial contributions from extended coma sources, providing further evidence for distinct origins and associations for these species in comets. CO shows a different spatial distribution compared with other volatiles, consistent with jet activity from discrete nucleus ice sources.

Heat capacity of dispersed rocks

Protection of automobile roads from negative cryogenic processes is a current issue to which significant attention is devoted in both scientific and engineering communities. In many cases important for practice, the the thermal factor determines the reliability and security of the use of the road in the cryolithic zone. The heat capacity of dispersed rocks is among the most important indicators of the physical properties determining the intensity of thermal processes in the road surfaces and road foundations. The precision of determination of the total heat capacity of the rocks in thawed and frozen state largely determines the precision of the forecast of the thermal regime of roads in the cryolithic zone. A complex assessment of the impact of ice content of the dispersed rocks on the value of total heat capacity was done. 2D and 3D charts which allow to assess the possible range of change in the heat capacity of the dispersed rocks in thawed and frozen state, in both a wide range and in the typical range of values, were produced. Among the main criteria determining the extent of the seasonal freezing and thawing of the soils of the active layer is the Stefan number, a dimensionless criterion. An overall assessment of the impact of ice content on the ground (rock) foundations of the roads and of the air temperature in the warm period of the year on the quantitative values of the Stefan number was done. Charts allowing to determine in both a wide and typical range the changes of values of the Stefan numbers, permitting to assess the possible range of changes of the Stefan number, were made. It was determined, in particular, that for the typical dispersed rocks of the road foundations in the cryolithic zone the range of change in the Stefan numbers is 2.1-6.5.

Matrix gas flow through ‘impermeable’ rocks – shales and tight sandstone

The effective pressure sensitivity of gas flow through two shales (Bowland and Haynesville shales) and a tight gas sandstone (Pennant sandstone) was measured over the typical range of reservoir pressure conditions. These are low permeability rocks such as can be exploited as caprocks above reservoirs that might be developed to store compressed air, methane, hydrogen or to bury waste carbon dioxide, all of which may become important components of the forthcoming major changes in methods of energy generation and storage. Knowledge of the petrophysical properties of such tight rocks will be of great importance in such developments. All three rocks display only a small range in log10 permeability at low pressures, but these decrease at dramatically different rates with increasing effective pressure, and the rate of decrease itself decreases with pressure, as the rocks stiffen. The pressure sensitivity of the bulk moduli of each of these rocks was also measured, and used to formulate a description of the permeability decrease in terms of the progressive closure of narrow, crack-like pores with increasing pressure. In the case of the shales in particular, only a very small proportion of the total porosity takes part in the flow of gases, particularly along the bedding layering.

Evidence for V363 Cas as a First Overtone Anomalous Cepheid

V363 Cassiopeiae was observed through 51 acquisitions of each of V, B, i and z filters, during a 15 day observation window. From the observations, folded light curves were generated using a PDM technique. It was my objective to provide further evidence for this star’s reclassification as a first overtone Anomalous Cepheid, as some past papers have proposed (Fernley, 1998). Based on our light curve characteristics (shape, and period), V363 Cas appeared to favor the anomalous Cepheid class over any RR Lyrae class. My observed period of 0.545 days is higher than the typical range of periods for RRd Lyrae, reported between 0.25 and 0.49 days (Soszynski et al., 2008). The RRab type Lyrae, as some have imposed on V363 Cas (Kholopov et al., 1985), was ruled out due to the evidence for overtone pulsation by Hajdu et al. (Hajdu, Jurcsik, et al., 2009) and Fernley (Fernley, 1998). Finally, a rough distance comparison to GAIA, using Nemec’s 1994 P-L-[Fe/H] for Anomalous Cepheids (Nemec, Nemec, & Lutz, 1994), estimated the distance of V363 Cas to be closer to the distance estimated by GAIA than estimates made with RRd class equations.

The Twenty Item Prosopagnosia Index (PI20) provides meaningful evidence of face recognition impairment

The Twenty Item Prosopagnosia Index (PI20) is a self-report questionnaire used for quantifying prosopagnosic traits. This scale is intended to help researchers identify cases of developmental prosopagnosia by providing standardized self-report evidence to complement diagnostic evidence obtained from objective computer-based tasks. In order to respond appropriately to items, prosopagnosics must have some insight that their face recognition is well below average, while non-prosopagnosics need to understand that their relative face recognition ability falls within the typical range. There has been considerable debate about whether participants have the necessary insight into their face recognition abilities to respond appropriately. In the present study, we sought to determine whether the PI20 provides meaningful evidence of face recognition impairment. In keeping with the intended use of the instrument, we used PI20 scores to identify two groups: high-PI20 scorers (those with self-reported face recognition difficulties) and low-PI20 scorers (those with no self-reported face recognition difficulties). We found that participant groups distinguished on the basis of PI20 scores clearly differed in terms of their mean performance on objective measures of face recognition ability. We also found that high-PI20 scorers were more likely to achieve levels of face recognition accuracy associated with developmental prosopagnosia.

White matter properties underlying reading abilities differ in 8-year-old children born full term and preterm

Diffusion magnetic resonance imaging (dMRI) studies find differences in associations between reading and white matter fractional anisotropy (FA) in children born full term (FT) versus preterm (PT). Use of complementary neuroimaging modalities may reveal neurobiological factors driving these associations. We used two MRI methods to interpret associations of reading abilities and white matter properties in FT and PT children. Participants (N=79; 36 FT; 43 PT) were administered Gray’s Oral Reading Test at age 8 years. We segmented two dorsal and two ventral white matter tracts associated with reading skills and quantified (1) FA from dMRI and (2) R1 from quantitative relaxometry, as a proxy for myelin content. We examined correlations between reading scores and imaging metrics, assessing trajectories along the tracts. Mean reading scores fell in the typical range in both groups. Reading positively correlated with FA in segments of the left arcuate and the left and right superior longitudinal fasciculi, but only in FT children, not in PT children. Reading positively correlated with R1 in segments of the left superior longitudinal, right uncinate, and left inferior longitudinal fasciculi, but only in PT children, not in FT children. The significantly different patterns of associations between reading abilities and white matter properties across FT and PT groups suggest variations in the neurobiology of typical reading abilities.

Intelligent Approach for GOSP Oil Recovery Enhancement

This study aims to propose an intelligent operational advisory solution that guides the plant operation team to optimal HPPT/LPPT pressure settings that compensate for the variation in ambient temperature effect to maximize plant revenue. Traditional industry practice is to operate a gas-oil-separation-plant (GOSP) at fixed operating conditions ignoring the variation in the ambient temperature (Ta) leading to a loss in oil recovery and associated revenue. The variation of ambient temperature (Ta) highly affects the separation process, where ambient temperature varies greatly from summer to winter. To develop a correlation, a GOSP model was constructed by OmegaLand dynamic simulator using a typical Saudi Aramco GOSP design. Oil recovery values were determined by running the process simulation for a typical range of high-pressure production trap (HPPT), low-pressure production trap (LPPT), and ambient temperature (Ta). Then, an intelligent approach was built to determine the optimum pressure of LPPT and HPPT units for each ambient temperature condition using an artificial intelligence technique. Results show that liquid recovery decreases with an increase in ambient temperature at constant HPPT and LPPT pressures, indicating adjustment in HPPT or LPPT pressure responding to the temperature variations can improve the oil recovery. At constant LPPT pressure and ambient temperature, the oil recovery increases with an increase in HPPT pressure until it reaches the optimum value and then decreases with further increase in the HPPTpressure suggesting that there is an optimum HPPT pressure at which oil recovery is maximum. At fixed ambient temperature and fixed HPPT pressure, liquid recovery increases with increasing LPPT pressure until it reaches the optimum value, and then it decreases with further increase in the LPPT pressure suggesting that there is an optimum LPPT pressure at which oil recovery is maximum.

CONTENT OF SUSPENDED SUBSTANCES IN MACROPRIENT ESTUARIES OF THE WHITE AND BARENTS SEA RIVERS

The statistical characteristics of the content of suspended matter in the macrotidal estuaries of the Kuloi River with a lateral tributary of the Pocha, the Pyya River (White Sea) and the Chesha River in the Barents Sea. Their maximum values in the surface layers of estuarine waters due to the roiling of bottom sediments by tidal currents can reach a level of 500–4000 mg/l and even more. The typical range of fluctuations in the concentration of suspended matter in such river mouths will be 90–720 mg/l for taiga rivers and 200–1830 mg/l for tundra rivers. The higher turbidity of the estuarine waters of the tundra zone is associated with the degradation of its permafrost soils against the background of the observed climate warming. The relationship between suspended solids and salinity distribution at the mouths of small rivers may differ markedly from the conditions observed at the mouths of medium and large rivers.

Inverse design of layered periodic wave barriers based on deep learning

This study presents an approach based on deep learning to design layered periodic wave barriers with consideration of typical range of soil parameters. Three cases are considered where P wave and S wave exist separately or simultaneously. The deep learning model is composed of an autoencoder with a pretrained decoder which has three branches to output frequency attenuation domains for three different cases. A periodic activation function is used to improve the design accuracy, and condition variables are applied in the code layer of the autoencoder to meet the requirements of practical multi working conditions. Forty thousand sets of data are generated to train, validate, and test the model, and the designed results are highly consistent with the targets. The presented approach has great generality, feasibility, rapidity, and accuracy on designing layered periodic wave barriers which exhibit good performance in wave suppression in targeted frequency range.