Optimizing Ground-based Observations of O2 in Earth Analogs

We present the result of calculations to optimize the search for molecular oxygen (O2) in Earth analogs transiting around nearby, low-mass stars using ground-based, high-resolution, Doppler shift techniques. We investigate a series of parameters, namely spectral resolution, wavelength coverage of the observations, and sky coordinates and systemic velocity of the exoplanetary systems, to find the values that optimize detectability of O2. We find that increasing the spectral resolution of observations to R = 300,000 - 400,000 from the typical R ~ 100,000, more than doubles the average depth of O2 lines in planets with atmospheres similar to Earth's. Resolutions higher than about 500,000 do not produce significant gains in the depths of the O2 lines. We confirm that observations in the O2 A-band are the most efficient except for M9V host stars, for which observations in the O2 NIR-band are more efficient. Combining observations in the O2 A, B, and NIR -bands can reduce the number of transits needed to produce a detection of O2 by about 1/3 in the case of white noise limited observations. However, that advantage disappears in the presence of typical levels of red noise. Therefore, combining observations in more than one band produces no significant gains versus observing only in the A-band, unless red-noise can be significantly reduced. Blending between the exoplanet's O2 lines and telluric O2 lines is a known problem. We find that problem can be alleviated by increasing the resolution of the observations, and by giving preference to targets near the ecliptic.Comment: 15 pages, 7 figures, accepted for publication in The Astronomical Journa

Understanding Spatial Ability through a Neural Efficiency EEG Study

The purpose of this research is to understand the neural efficiency of undergraduate engineers while they solve spatial ability and Statics (sophomore-level engineering) problems. Spatial ability is the measurement of one’s aptitude to reason and remember the spatial relations between objects or space. In engineering, spatial ability is found to be predictive of engineering success, but there is little information as to why or how spatial ability impacts engineers. The neural efficiency hypothesis states that individuals who excel in a given field will experience lower-energy related brain activity in that field whereas those who are unfamiliar with a given field experience higher-energy brain activity in certain frequency bands of neural activity. In this study, participants brain activity was observed using an electroencephalogram (EEG) while each of the participants completed spatial ability assessments (the PSVT:R and MCT) and Statics problems. The analysis of the EEG data provides insight into student expertise in spatial ability and basic engineering skills by comparing the neural efficiency levels of each participant with the results of the spatial and Statics assessments. This research will allow for greater understanding of the applicability of neural efficiency in engineering and aptitude research studies, which will be used in further studies to find ways of understanding and improving the spatial ability of engineers

Community-driven reconstruction in Colombia: An experimental study of collective action beyond program beneficiaries

Increased community cooperation is an important objective of Community-Driven Reconstruction (CDR) programs in post-conflict settings. While these programs typically work with a limited group of beneficiaries, little is known about the potential community impact beyond these beneficiaries. To investigate this, we empirically analyze how cooperative behavior develops in a lab-in-the-field experiment with mixed groups of CDR program beneficiaries and nonbeneficiaries, organized in 42 municipalities in Colombia with active CDR programs. In the experiment, we use two rounds of a binary public goods game with a communication stage between both rounds. The experimental data are complemented with information on pre-existing social proximity among the participants and whether they have participated in a CDR program. We find that cooperation increases after communication, and that it correlates positively with the proportion of cooperators before communication. This peer effect is mainly driven by the cooperative behavior of CDR program beneficiaries while the influence of non-beneficiaries is limited

Unconventional superconductivity near a flat band in organic and organometallic materials

We study electron correlation driven superconductivity on a decorated honeycomb lattice (DHL), which has a low-energy flat band. On doping, we find singlet superconductivity with extended-s, extended-d and f-wave symmetry mediated by magnetic exchange. f-wave singlet pairing is enabled by the lattice decoration. The critical temperature is predicted to be significantly higher than on similar lattices lacking flat bands. We discuss how high-temperature superconductivity could be realized in the DHL materials such as Rb3TT. 2 H2O and Mo3S7(dmit)3.Comment: 4 pages, 4 figures + Supplemental materia

Corticosteroids in septic shock:a systematic review and network meta-analysis

Abstract Background Multiple corticosteroids and treatment regimens have been used as adjuncts in the treatment of septic shock. Qualitative and quantitative differences exist at cellular and tissular levels between the different drugs and their patterns of delivery. The objective of this study was to elucidate any differences between the drugs and their treatment regimens regarding outcomes for corticosteroid use in adult patients with septic shock. Methods Network meta-analysis of the data used for the recently conducted Cochrane review was performed. Studies that included children and were designed to assess respiratory function in pneumonia and acute respiratory distress syndrome, as well as cross-over studies, were excluded. Network plots were created for each outcome, and all analyses were conducted using a frequentist approach assuming a random-effects model. Results Complete data from 22 studies and partial data from 1 study were included. Network meta-analysis provided no clear evidence that any intervention or treatment regimen is better than any other across the spectrum of outcomes. There was strong evidence of differential efficacy in only one area: shock reversal. Hydrocortisone boluses and infusions were more likely than methylprednisolone boluses and placebo to result in shock reversal. Conclusions There was no clear evidence that any one corticosteroid drug or treatment regimen is more likely to be effective in reducing mortality or reducing the incidence of gastrointestinal bleeding or superinfection in septic shock. Hydrocortisone delivered as a bolus or as an infusion was more likely than placebo and methylprednisolone to result in shock reversal

Prospectus, March 18, 1998

https://spark.parkland.edu/prospectus_1998/1009/thumbnail.jp

Direct Selective Laser Synthesis of CuCrFeNiTiAl High Entropy Alloy from Elemental Powders through Selective Laser Melting

This study investigated the synthesis of CuCrFeNiTiAl high entropy alloy (HEA) from pure elements using selective laser melting (SLM). The objectives are to validate the feasibility of the HEA fabrication from elemental powder materials, and to examine the effect of various process conditions in SLM, such as laser power, point distance and laser exposure time, on the microstructures formed. The as-built samples under high, medium and low energy densities were characterized by X-ray diffraction (XRD), and the microstructures were observed using scanning electron microscopy (SEM). The XRD results showed that five major crystal structure phases (hexagonal, monoclinic, orthorhombic, body-centered cubic and rhombohedral) were present in all samples. Fine-grained phases were noticed on the sample surface with non-uniform microstructural distribution. Such phases in high and low energy density samples were observed polygonal while round-shaped microstructures were observed for samples prepared under medium energy density conditions. Also, the grain size was proportional to energy levels of the fabrication process. Large size and clustered structures are prominent in samples produced under high energy density

Relationships of Perfluorooctanoate and Perfluorooctane Sulfonate Serum Concentrations between Mother–Child Pairs in a Population with Perfluorooctanoate Exposure from Drinking Water

Background: There are limited data on the associations between maternal or newborn and child exposure to perfluoroalkyl acids (PFAAs), including perfluorooctanoate (PFOA) and perfluorooctane sulfonate (PFOS). This study provides an opportunity to assess the association between PFAA concentrations in mother–child pairs in a population exposed to PFOA via drinking water

Nesterov-aided Stochastic Gradient Methods using Laplace Approximation for Bayesian Design Optimization

Finding the best setup for experiments is the primary concern for Optimal Experimental Design (OED). Here, we focus on the Bayesian experimental design problem of finding the setup that maximizes the Shannon expected information gain. We use the stochastic gradient descent and its accelerated counterpart, which employs Nesterov's method, to solve the optimization problem in OED. We adapt a restart technique, originally proposed for the acceleration in deterministic optimization, to improve stochastic optimization methods. We combine these optimization methods with three estimators of the objective function: the double-loop Monte Carlo estimator (DLMC), the Monte Carlo estimator using the Laplace approximation for the posterior distribution (MCLA) and the double-loop Monte Carlo estimator with Laplace-based importance sampling (DLMCIS). Using stochastic gradient methods and Laplace-based estimators together allows us to use expensive and complex models, such as those that require solving partial differential equations (PDEs). From a theoretical viewpoint, we derive an explicit formula to compute the gradient estimator of the Monte Carlo methods, including MCLA and DLMCIS. From a computational standpoint, we study four examples: three based on analytical functions and one using the finite element method. The last example is an electrical impedance tomography experiment based on the complete electrode model. In these examples, the accelerated stochastic gradient descent method using MCLA converges to local maxima with up to five orders of magnitude fewer model evaluations than gradient descent with DLMC.Comment: 36 pages, 14 figure