Application of Acclerometer Data to Atmospheric Modeling During Mars Aerobraking Operations

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/77186/1/AIAA-28472-302.pd

DACOTA: The dense array for cosmological transitions

The Epoch of Reionization (EoR) heralded the advent of the Universe we recognize today, containing stars, galaxies and super-massive black holes. A number of experiments to detect the red-shifted hydrogen signature of the atomic component of the intergalactic medium (IGM) are on-going (e.g. PAPER, MWA, LOFAR). Due to the faintness of the signal, the bright foregrounds, and the challenge of instrumental systematics, multiple techniques are essential to create a more robust detection and to provide the complete picture on the evolution of early galaxies

Cross-correlating Carbon Monoxide Line-intensity Maps with Spectroscopic and Photometric Galaxy Surveys

Line-intensity mapping (LIM or IM) is an emerging field of observational work, with strong potential to fit into a larger effort to probe large-scale structure and small-scale astrophysical phenomena using multiple complementary tracers. Taking full advantage of such complementarity means, in part, undertaking line-intensity surveys with galaxy surveys in mind. We consider the potential for detection of a cross-correlation signal between COMAP and blind surveys based on photometric redshifts (as in COSMOS) or based on spectroscopic data (as with the HETDEX survey of Lyman-$\alpha$ emitters). We find that obtaining $\sigma_z/(1+z)\lesssim0.003$ accuracy in redshifts and $\gtrsim10^{-4}$ sources per Mpc$^3$ with spectroscopic redshift determination should enable a CO-galaxy cross spectrum detection significance at least twice that of the CO auto spectrum. Either a future targeted spectroscopic survey or a blind survey like HETDEX may be able to meet both of these requirements.Comment: 19 pages + appendix (31 pages total), 16 figures, 6 tables; accepted for publication in Ap

Social interactions through the eyes of macaques and humans

Group-living primates frequently interact with each other to maintain social bonds as well as to compete for valuable resources. Observing such social interactions between group members provides individuals with essential information (e.g. on the fighting ability or altruistic attitude of group companions) to guide their social tactics and choice of social partners. This process requires individuals to selectively attend to the most informative content within a social scene. It is unclear how non-human primates allocate attention to social interactions in different contexts, and whether they share similar patterns of social attention to humans. Here we compared the gaze behaviour of rhesus macaques and humans when free-viewing the same set of naturalistic images. The images contained positive or negative social interactions between two conspecifics of different phylogenetic distance from the observer; i.e. affiliation or aggression exchanged by two humans, rhesus macaques, Barbary macaques, baboons or lions. Monkeys directed a variable amount of gaze at the two conspecific individuals in the images according to their roles in the interaction (i.e. giver or receiver of affiliation/aggression). Their gaze distribution to non-conspecific individuals was systematically varied according to the viewed species and the nature of interactions, suggesting a contribution of both prior experience and innate bias in guiding social attention. Furthermore, the monkeys’ gaze behavior was qualitatively similar to that of humans, especially when viewing negative interactions. Detailed analysis revealed that both species directed more gaze at the face than the body region when inspecting individuals, and attended more to the body region in negative than in positive social interactions. Our study suggests that monkeys and humans share a similar pattern of role-sensitive, species- and context-dependent social attention, implying a homologous cognitive mechanism of social attention between rhesus macaques and humans

Relationships within the Araceae: comparison of morphological patterns with molecular phylogenies.

Premise of the study: The first family-wide molecular phylogeny of the Araceae, a family of about 3800 published species in 120 genera, became available in 1995, followed by a cladistic analysis of morpho-anatomical data in 1997. The most recent and comprehensive family-wide molecular phylogeny was published in 2008 and included species from 102 genera. We reanalyzed the molecular data with a more complete genus sampling and compared the resulting phylogeny with morphological and anatomical data, with a view to contributing to a new formal classification of the Araceae. • Methods: We analyzed 113 aroid genera and 4494 aligned nucleotides that resulted from adding 11 genera to the 2008 molecular matrix. We also analyzed 81 morphological characters in the context of the molecular phylogeny, using an extended version of the 1997 morpho-anatomical data set. • Key results: The resulting maximum-likelihood phylogeny is well resolved and supported, and most of the 44 larger clades also have morphological or anatomical synapomorphies as well as ecological or geographic cohesion. Of the 44 clades, 16 are here newly circumscribed and informally named. However, some relationships remain poorly supported within the Aroideae subfamily. The most problematic placement is Calla within Aroideae, which conflicts with the distribution of morphological, anatomical, and palynological character states. • Conclusions: The comparison of the molecular analysis with morphological and anatomical data presented here represents an important basis for a new formal classification for the Araceae and for the understanding of the evolution of this ancient family, a monocot group known in the fossil record from the early Cretaceous

COMAP Early Science: VIII. A Joint Stacking Analysis with eBOSS Quasars

We present a new upper limit on the cosmic molecular gas density at z = 2.4 − 3.4 obtained using the first year of observations from the CO Mapping Array Project (COMAP). COMAP data cubes are stacked on the 3D positions of 243 quasars selected from the Extended Baryon Oscillation SpectroscopicSurvey (eBOSS) catalog, yielding a 95% upper limit for flux from CO(1-0) line emission of 0.129 Jykm/s. Depending on the balance of the emission between the quasar host and its environment, this value can be interpreted as an average CO line luminosity L′CO of eBOSS quasars of ≤ 1.26 × 1011 K km pc2s−1, or an average molecular gas density ρH2 in regions of the universe containing a quasar of ≤ 1.52 × 108 M⊙ cMpc−3. The L′ CO upper limit falls among CO line luminosities obtained fromindividually-targeted quasars in the COMAP redshift range, and the ρH2 value is comparable to upper limits obtained from other Line Intensity Mapping (LIM) surveys and their joint analyses. Further, we forecast the values obtainable with the COMAP/eBOSS stack after the full 5-year COMAP Pathfinder survey. We predict that a detection is probable with this method, depending on the CO properties of the quasar sample. Based on the achieved sensitivity, we believe that this technique of stacking LIM data on the positions of traditional galaxy or quasar catalogs is extremely promising, both asa technique for investigating large galaxy catalogs efficiently at high redshift and as a technique for bolstering the sensitivity of LIM experiments, even with a fraction of their total expected survey data

COMAP Early Science: VIII. A Joint Stacking Analysis with eBOSS Quasars

We present a new upper limit on the cosmic molecular gas density at $z=2.4-3.4$ obtained using the first year of observations from the CO Mapping Array Project (COMAP). COMAP data cubes are stacked on the 3D positions of 282 quasars selected from the Extended Baryon Oscillation Spectroscopic Survey (eBOSS) catalog, yielding a 95% upper limit for flux from CO(1-0) line emission of 0.210 Jy km/s. Depending on the assumptions made, this value can be interpreted as either an average CO line luminosity $L'_\mathrm{CO}$ of eBOSS quasars of $\leq 7.30\times10^{10}$ K km pc$^2$ s$^{-1}$, or an average molecular gas density $\rho_\mathrm{H_2}$ in regions of the universe containing a quasar of $\leq 2.02\times10^8$ M$_\odot$ cMpc$^{-3}$. The $L'_\mathrm{CO}$ upper limit falls among CO line luminosities obtained from individually-targeted quasars in the COMAP redshift range, and the $\rho_\mathrm{H_2}$ value is comparable to upper limits obtained from other Line Intensity Mapping (LIM) surveys and their joint analyses. Further, we forecast the values obtainable with the COMAP/eBOSS stack after the full 5-year COMAP Pathfinder survey. We predict that a detection is probable with this method, depending on the CO properties of the quasar sample. Based on these achieved sensitivities, we believe that this technique of stacking LIM data on the positions of traditional galaxy or quasar catalogs is extremely promising, both as a technique for investigating large galaxy catalogs efficiently at high redshift and as a technique for bolstering the sensitivity of LIM experiments, even with a fraction of their total expected survey data.Comment: 15 pages, 8 figures. To be submitted to Ap

What Is a Representative Brain? Neuroscience Meets Population Science

The last decades of neuroscience research have produced immense progress in the methods available to understand brain structure and function. Social, cognitive, clinical, affective, economic, communication, and developmental neurosciences have begun to map the relationships between neuro-psychological processes and behavioral outcomes, yielding a new understanding of human behavior and promising interventions. However, a limitation of this fast moving research is that most findings are based on small samples of convenience. Furthermore, our understanding of individual differences may be distorted by unrepresentative samples, undermining findings regarding brain–behavior mechanisms. These limitations are issues that social demographers, epidemiologists, and other population scientists have tackled, with solutions that can be applied to neuroscience. By contrast, nearly all social science disciplines, including social demography, sociology, political science, economics, communication science, and psychology, make assumptions about processes that involve the brain, but have incorporated neural measures to differing, and often limited, degrees; many still treat the brain as a black box. In this article, we describe and promote a perspective—population neuroscience—that leverages interdisciplinary expertise to (i) emphasize the importance of sampling to more clearly define the relevant populations and sampling strategies needed when using neuroscience methods to address such questions; and (ii) deepen understanding of mechanisms within population science by providing insight regarding underlying neural mechanisms. Doing so will increase our confidence in the generalizability of the findings. We provide examples to illustrate the population neuroscience approach for specific types of research questions and discuss the potential for theoretical and applied advances from this approach across areas