Analysis of an Interplanetary Coronal Mass Ejection by a spacecraft radio signal: A case study

Tracking radio communication signals from planetary spacecraft with ground-based telescopes offers the possibility to study the electron density and the interplanetary scintillation of the solar wind. Observations of the telemetry link of planetary spacecraft have been conducted regularly with ground antennae from the European Very Long Baseline Interferometry Network, aiming to study the propagation of radio signals in the solar wind at different solar elongations and distances from the Sun. We have analyzed the Mars Express spacecraft radio signal phase fluctuations while, based on a 3-D heliosphere plasma simulation, an interplanetary coronal mass ejection (ICME) crossed the radio path during one of our observations on 6 April 2015. Our measurements showed that the phase scintillation indices increased by a factor of 4 during the passage of the ICME. The method presented here confirms that the phase scintillation technique based on spacecraft signals provides information of the properties and propagation of the ICMEs in the heliosphere

The AUSTRAL VLBI Observing Program

The AUSTRAL observing program was started in 2011, performing geodetic and astrometric very long baseline interferometry (VLBI) sessions using the new Australian AuScope VLBI antennas at Hobart, Katherine, and Yarragadee, with contribution from the Warkworth (New Zealand) 12 m and Hartebeesthoek (South Africa) 15 m antennas to make a southern hemisphere array of telescopes with similar design and capability. Designed in the style of the next-generation VLBI system, these small and fast antennas allow for a new way of observing, comprising higher data rates and more observations than the standard observing sessions coordinated by the International VLBI Service for Geodesy and Astrometry (IVS). In this contribution, the continuous development of the AUSTRAL sessions is described, leading to an improvement of the results in terms of baseline length repeatabilities by a factor of two since the start of this program. The focus is on the scheduling strategy and increased number of observations, aspects of automated operation, and data logistics, as well as results of the 151 AUSTRAL sessions performed so far. The high number of the AUSTRAL sessions makes them an important contributor to VLBI end-products, such as the terrestrial and celestial reference frames and Earth orientation parameters. We compare AUSTRAL results with other IVS sessions and discuss their suitability for the determination of baselines, station coordinates, source coordinates, and Earth orientation parameters

Abortion attitudes: An overview of demographic and ideological differences

Despite being a defining issue in the culture war, the relative importance of the psychological predictors of abortion attitudes are poorly understood. We address this oversight here by reviewing existing findings and providing new evidence for the demographic and ideological correlates of abortion support. Throughout our review, we integrate new analyses of several large-scale, cross-sectional, and longitudinal datasets to provide the most complete empirical examination of abortion attitudes to date. Our review and new analyses indicate that abortion support is increasing (modestly) over time in both the US and New Zealand. We also show that a plurality of respondents (43.8%) in the US indicate that they are “pro-choice” across various elective and traumatic scenarios, whereas only 14.8% report being consistently “pro-life” regardless of why an abortion is sought. Our review and new integrative analyses then demonstrate that age, religiosity, and conservatism correlate negatively, whereas Openness to Experience correlates positively, with abortion support. New analyses of heterosexual couples also reveal that women’s and men’s religiosity uniquely decreases their romantic partner’s abortion support. Finally, noting inconsistent gender differences in abortion support, we review evidence for the impact of traditional gender role attitudes and sexism on abortion support. Our review and theoretical analyses illustrate that, rather than misogyny, benevolent sexism—the belief that women should be cherished and protected—best explains abortion opposition. We conclude that demographic and ideological variables, along with attitudes that revere women and motherhood, continue to undermine women’s interpersonal, intergroup, and societal rights

Machine learning uncovers the most robust self-report predictors of relationship quality across 43 longitudinal couples studies

Given the powerful implications of relationship quality for health and well-being, a central mission of relationship science is explaining why some romantic relationships thrive more than others. This large-scale project used machine learning (i.e., Random Forests) to 1) quantify the extent to which relationship quality is predictable and 2) identify which constructs reliably predict relationship quality. Across 43 dyadic longitudinal datasets from 29 laboratories, the top relationship-specific predictors of relationship quality were perceived-partner commitment, appreciation, sexual satisfaction, perceived-partner satisfaction, and conflict. The top individual-difference predictors were life satisfaction, negative affect, depression, attachment avoidance, and attachment anxiety. Overall, relationship-specific variables predicted up to 45% of variance at baseline, and up to 18% of variance at the end of each study. Individual differences also performed well (21% and 12%, respectively). Actor-reported variables (i.e., own relationship-specific and individual-difference variables) predicted two to four times more variance than partner-reported variables (i.e., the partner’s ratings on those variables). Importantly, individual differences and partner reports had no predictive effects beyond actor-reported relationship-specific variables alone. These findings imply that the sum of all individual differences and partner experiences exert their influence on relationship quality via a person’s own relationship-specific experiences, and effects due to moderation by individual differences and moderation by partner-reports may be quite small. Finally, relationship-quality change (i.e., increases or decreases in relationship quality over the course of a study) was largely unpredictable from any combination of self-report variables. This collective effort should guide future models of relationships

Revising working models across time: Relationship situations that enhance attachment security

We propose the Attachment Security Enhancement Model (ASEM) to suggest how romantic relationships can promote chronic attachment security. One part of the ASEM examines partner responses that protect relationships from the erosive effects of immediate insecurity, but such responses may not necessarily address underlying insecurities in a person’s mental models. Therefore, a second part of the ASEM examines relationship situations that foster more secure mental models. Both parts may work in tandem. We posit that attachment anxiety should decline most in situations that foster greater personal confidence and more secure mental models of the self. In contrast, attachment avoidance should decline most in situations that involve positive dependence and foster more secure models of close others. The ASEM integrates research and theory, suggests novel directions for future research, and has practical implications, all of which center on the idea that adult attachment orientations are an emergent property of close relationships