Storable Votes and Judicial Nominations in the U.S. Senate

We model a procedural reform aimed at restoring a proper role for the minority in the confirmation process of judicial nominations in the U.S. Senate. We propose that nominations to the same level court be collected in periodic lists and voted upon individually with Storable Votes, allowing each senator to allocate freely a fixed number of total votes. Although each nomination is decided by simple majority, storable votes make it possible for the minority to win occasionally, but only when the relative importance its members assign to a nomination is higher than the relative importance assigned by the majority. Numerical simulations, motivated by a game theoretic model, show that under plausible assumptions a minority of 45 senators would be able to block between 20 and 35 percent of nominees. For most parameter values, the possibility of minority victories increases aggregate welfare

Interfacial Dzyaloshinskii-Moriya interaction in epitaxial W/Co/Pt multilayers

Dzyaloshinskii-Moriya interaction (DMI) manifesting in asymmetric layered ferromagnetic films gives rise to non-colinear spin structures stabilizing magnetization configurations with nontrivial topology. In this work magnetization reversal, domain structure, and strength of DMI are related with the structure of W/Co/Pt multilayers grown by molecular beam epitaxy. Applied growth method enables fabrication of layered systems with higher crystalline quality than commonly applied sputtering techniques. As a result, a high value of D coefficient was determined from the aligned magnetic domain stripe structure, substantially exceeding 2 mJ/m2. The highest value of DMI value D$_{eff}$ = 2.64mj/m2 and strength of surface DMI parameter DS = 1.83pJ/m for N=10 has been observed. Experimental results coincide precisely with those obtained from structure based micromagnetic modelling and density functional theory calculations performed for well-defined layered stacks. This high value of DMI strength originates from dominating contributions of the interfacial atomic Co layers and additive character from both interface types

The SDO Education and Outreach (E/PO) Program: Changing Perceptions One Program at a Time

The Solar Dynamics Observatory (SDO) Education and Public Outreach (E/PO) program began as a series of discrete efforts implemented by each of the instrument teams and has evolved into a well-rounded program with a full suite of national and international programs. The SDO E/PO team has put forth much effort in the past few years to increase our cohesiveness by adopting common goals and increasing the amount of overlap between our programs. In this paper, we outline the context and overall philosophy for our combined programs, present a brief overview of all SDO E/PO programs along with more detailed highlight of a few key programs, followed by a review of our results up to date. Concluding is a summary of the successes, failures, and lessons learned that future missions can use as a guide, while further incorporating their own content to enhance the public's knowledge and appreciation of NASA?s science and technology as well as its benefit to society

The Solar Dynamics Observatory (SDO) Education and Outreach (E/PO) Program: Changing Perceptions One Program at a Time

We outline the context and overall philosophy for the combined Solar Dynamics Observatory (SDO) Education and Public Outreach (E/PO) program, present a brief overview of all SDO E/PO programs along with more detailed highlights of a few key programs, followed by a review of our results to date, conclude a summary of the successes, failures, and lessons learned, which future missions can use as a guide, while incorporating their own content to enhance the public's knowledge and appreciation of science and technology as well as its benefit to society

Study of ultrathin Pt/Co/Pt trilayers modified by nanosecond XUV pulses from laser-driven plasma source

We have studied the structural mechanisms responsible for the magnetic reorientation between in-plane and out-of-plane magnetization in the (25 nm Pt)/(3 and 10 nm Co)/(3 nm Pt) trilayer systems irradiated with nanosecond XUV pulses generated with laser-driven gas-puff target plasma source of a narrow continuous spectrum peaked at wavelength of 11 nm. The thickness of individual layers, their density, chemical composition and irradiation-induced lateral strain were deduced from symmetric and asymmetric X-ray diffraction (XRD) patterns, grazing-incidence X-ray reflectometry (GIXR), grazing incidence X-ray fluorescence (GIXRF), extended X-ray absorption fine structure (EXAFS) and transmission electron microscopy (TEM) measurements. In the as grown samples we found, that the Pt buffer layers are relaxed and that the layer interfaces are sharp. As a result of a quasi-uniform irradiation of the samples, the XRD, EXAFS, GIXR and GIXRF data reveal the formation of two distinct layers composed of Pt1-xCox alloys with different Co concentrations, dependent on the thickness of the as grown magnetic Co film but with similar ∼1% lateral tensile residual strain. For smaller exposure dose (lower number of accumulated pulses) only partial interdiffusion at the interfaces takes place with the formation of a tri-layer composed of Co-Pt alloy sandwiched between thinned Pt layers, as revealed by TEM. The structural modifications are accompanied by magnetization changes, evidenced by means of magneto-optical microscopy. The difference in magnetic properties of the irradiated samples can be related to their modification in Pt1-xCox alloy composition, as the other parameters (lateral strain and alloy thickness) remain almost unchanged. The out-of-plane magnetization observed for the sample with initially 3 nm Co layer can be due to a significant reduction of demagnetization factor resulting from a lower Co concentration

Newly characterized interaction stabilizes DNA structure: oligoethylene glycols stabilize G-quadruplexes CH–π interactions

Oligoethylene glycols are used as crowding agents in experiments that aim to understand the effects of intracellular environments on DNAs. Moreover, DNAs with covalently attached oligoethylene glycols are used as cargo carriers for drug delivery systems. To investigate how oligoethylene glycols interact with DNAs, we incorporated deoxythymidine modified with oligoethylene glycols of different lengths, such as tetraethylene glycol (TEG), into DNAs that form antiparallel G-quadruplex or hairpin structures such that the modified residues were incorporated into loop regions. Thermodynamic analysis showed that because of enthalpic differences, the modified G-quadruplexes were stable and the hairpin structures were slightly unstable relative to unmodified DNA. The stability of G-quadruplexes increased with increasing length of the ethylene oxides and the number of deoxythymidines modified with ethylene glycols in the G-quadruplex. Nuclear magnetic resonance analyses and molecular dynamics calculations suggest that TEG interacts with bases in the G-quartet and loop via CH-pi and lone pair-pi interactions, although it was previously assumed that oligoethylene glycols do not directly interact with DNAs. The results suggest that numerous cellular co-solutes likely affect DNA function through these CH-pi and lone pair-pi interactions

Comparison of Population-Based Association Study Methods Correcting for Population Stratification

Population stratification can cause spurious associations in population–based association studies. Several statistical methods have been proposed to reduce the impact of population stratification on population–based association studies. We simulated a set of stratified populations based on the real haplotype data from the HapMap ENCODE project, and compared the relative power, type I error rates, accuracy and positive prediction value of four prevailing population–based association study methods: traditional case-control tests, structured association (SA), genomic control (GC) and principal components analysis (PCA) under various population stratification levels. Additionally, we evaluated the effects of sample sizes and frequencies of disease susceptible allele on the performance of the four analytical methods in the presence of population stratification. We found that the performance of PCA was very stable under various scenarios. Our comparison results suggest that SA and PCA have comparable performance, if sufficient ancestral informative markers are used in SA analysis. GC appeared to be strongly conservative in significantly stratified populations. It may be better to apply GC in the stratified populations with low stratification level. Our study intends to provide a practical guideline for researchers to select proper study methods and make appropriate inference of the results in population-based association studies

Neural networks for modeling gene-gene interactions in association studies

<p>Abstract</p> <p>Background</p> <p>Our aim is to investigate the ability of neural networks to model different two-locus disease models. We conduct a simulation study to compare neural networks with two standard methods, namely logistic regression models and multifactor dimensionality reduction. One hundred data sets are generated for each of six two-locus disease models, which are considered in a low and in a high risk scenario. Two models represent independence, one is a multiplicative model, and three models are epistatic. For each data set, six neural networks (with up to five hidden neurons) and five logistic regression models (the null model, three main effect models, and the full model) with two different codings for the genotype information are fitted. Additionally, the multifactor dimensionality reduction approach is applied.</p> <p>Results</p> <p>The results show that neural networks are more successful in modeling the structure of the underlying disease model than logistic regression models in most of the investigated situations. In our simulation study, neither logistic regression nor multifactor dimensionality reduction are able to correctly identify biological interaction.</p> <p>Conclusions</p> <p>Neural networks are a promising tool to handle complex data situations. However, further research is necessary concerning the interpretation of their parameters.</p