Adolescent Sense of Belonging in Outdoor Adventure Education: The Influence of Conflict and Instructors

Outdoor adventure education programs are strategically positioned to provide a multitude of positive social outcomes for youth. The social connections adolescents develop with their peers are critically important for positive youth development. This study sought to understand how sense of belonging develops within a wilderness-based outdoor adventure education program while using a dynamical systems theory (DST) framework and analysis. The findings showed that group-based components, such as process conflict influenced the rate of change while instructor support increased the level of sense of belonging students felt. Implications for research and practice are discussed

Tethys and Annex IV Progress Report for FY 2012

The marine and hydrokinetic (MHK) environmental Impacts Knowledge Management System, dubbed “Tethys” after the mythical Greek titaness of the seas, is being developed by the Pacific Northwest National Laboratory (PNNL) to support the U.S. Department of Energy’s Wind and Water Power Program (WWPP). Functioning as a smart database, Tethys enables its users to identify key words or terms to help gather, organize and make available information and data pertaining to the environmental effects of MHK and offshore wind (OSW) energy development. By providing and categorizing relevant publications within a simple and searchable database, Tethys acts as a dissemination channel for information and data which can be utilized by regulators, project developers and researchers to minimize the environmental risks associated with offshore renewable energy developments and attempt to streamline the permitting process. Tethys also houses a separate content-related Annex IV data base with identical functionality to the Tethys knowledge base. Annex IV is a collaborative project among member nations of the International Energy Agency (IEA) Ocean Energy Systems – Implementing Agreement (OES-IA) that examines the environmental effects of ocean energy devices and projects. The U.S. Department of Energy leads the Annex IV working with federal partners such as the Federal Energy Regulatory Commission (FERC), the Bureau of Ocean Energy Management (BOEM), and the National Oceanic Atmospheric Administration (NOAA). While the Annex IV database contains technical reports and journal articles, it is primarily focused on the collection of project site and research study metadata forms (completed by MHK researchers and developers around the world, and collected by PNNL) which provide information on environmental studies and the current progress of the various international MHK developments in the Annex IV member nations. The purpose of this report is to provide a summary of the content, accessibility and functionality enhancements made to the Annex IV and Tethys knowledge bases in FY12

Stress Crossover in Intimate Relationships: A New Framework for Studying Dynamic Co-Regulation Patterns in Dyadic Interactions

It has been demonstrated that stress, experienced outside of a relationship, can spill into a relationship and cross over during interactions from one partner to the other. However, the mechanism of how stress cross over in real-time between partners is still unknown. To overcome this limitation, we invited 189 couples (N = 378 individuals) for two interactions and stressed either the man, the woman, or both partners between the interactions with a standardized stress-induction procedure. Vocally-encoded emotional arousal (i.e., fundamental frequency, indexed as fo) was extracted from both partners in 25,834 talk turns. Dynamical systems modeling revealed four patterns of dynamic influence prior to stress induction, which started to erode after the stress induction. This demonstrates that the initially unstressed mates become stressed during the behavioral exchange and stress crosses over from the unstressed partner to the stressed mates, interfering with their ability to down-regulate stress

The Dynamics of Stress and Fatigue Across Menopause: Attractors, Coupling, and Resilience

Objective: The objective of this study was to evaluate the regulatory dynamics between stress and fatigue experienced by women during the menopausal transition (MT) and early postmenopause (EPM). Fatigue and perceived stress are commonly experienced by women during the MT and EPM. We sought to discover relationships between these symptoms and to employ these symptoms as possible markers for resilience. Methods: Participants were drawn from the longitudinal Seattle Midlife Women\u27s Health Study. Eligible women completed questionnaires on 60+ occasions (annual health reports and monthly health diaries) (n = 56 women). The total number of observations across the sample was 4,224. STRAW+10 criteria were used to stage women in either in late reproductive, early or late transition, or EPM stage. Change values were generated for fatigue and stress and analyzed with a multilevel structural equation model; slopes indicate how quickly a person returns to homeostasis after a perturbation. Coupling of stress and fatigue was modeled to evaluate resilience, the notion of maintaining stability during change. Results: Eligible women were on average 35 years old (SD = 4.71), well educated, employed, married or partnered, and white. Fit indices suggested the model depicts the relationships of stress and fatigue (χ2(9 df) = 7.638, P = 0.57, correction factor = 4.9244; root mean square error of approximation (RMSEA) 90% CI = 0.000 ≤ 0.000 ≤ 0.032; comparative fit index (CFI) = 1.00). A loss in model fit across stages suggests that the four stages differed in their dynamics (χ2Δ(12 df) = 21.181, P = .048). All stages showed fixed-point attractor dynamics: fatigue became less stable over time; stress generally became more stable over time. Coupling relationships of stress on fatigue show evidence for shifts in regulatory relationships with one another across the MT. Conclusions: Results are suggestive of general dysregulation via disruptions to coupling relationships of stress and fatigue across the MT. Findings support a holistic approach to understanding symptoms and supporting women during the MT

The Gravity Collective: A Search for the Electromagnetic Counterpart to the Neutron Star-Black Hole Merger GW190814

We present optical follow-up imaging obtained with the Katzman Automatic Imaging Telescope, Las Cumbres Observatory Global Telescope Network, Nickel Telescope, Swope Telescope, and Thacher Telescope of the LIGO/Virgo gravitational wave (GW) signal from the neutron star-black hole (NSBH) merger GW190814. We searched the GW190814 localization region (19 deg$^{2}$ for the 90th percentile best localization), covering a total of 51 deg$^{2}$ and 94.6% of the two-dimensional localization region. Analyzing the properties of 189 transients that we consider as candidate counterparts to the NSBH merger, including their localizations, discovery times from merger, optical spectra, likely host-galaxy redshifts, and photometric evolution, we conclude that none of these objects are likely to be associated with GW190814. Based on this finding, we consider the likely optical properties of an electromagnetic counterpart to GW190814, including possible kilonovae and short gamma-ray burst afterglows. Using the joint limits from our follow-up imaging, we conclude that a counterpart with an $r$-band decline rate of 0.68 mag day$^{-1}$, similar to the kilonova AT 2017gfo, could peak at an absolute magnitude of at most $-17.8$ mag (50% confidence). Our data are not constraining for ''red'' kilonovae and rule out ''blue'' kilonovae with $M>0.5 M_{\odot}$ (30% confidence). We strongly rule out all known types of short gamma-ray burst afterglows with viewing angles $<$17$^{\circ}$ assuming an initial jet opening angle of $\sim$$5.2^{\circ}$ and explosion energies and circumburst densities similar to afterglows explored in the literature. Finally, we explore the possibility that GW190814 merged in the disk of an active galactic nucleus, of which we find four in the localization region, but we do not find any candidate counterparts among these sources.Comment: 86 pages, 9 figure

Fearless-Evolution on Boolean Landscapes: Boolean Phase Portraits Reveal a New Navigation Strategy Based on Fearful Symmetry

We present two important developments for understanding nk Boolean landscapes: First, a discrete analogue to the continuous phase portrait for analyzing Boolean landscapes and, second, an evolutionary alternative to mutation and recombination. Applications include evolution in biological systems, social networks, electrical flow on power grids, business organizations. The Curie Principle states that symmetry in causes will be seen, transformed, in effects. Using our discrete phase portrait we found that ring symmetry in network structure can be found as symmetry groups among the attractors on a Boolean landscape. The transforms which define these symmetry groups constitute a new way to move among groups of attractors (fitness peaks). A system, using only information from its current peak and a locally-generated symmetry transform, can move directly to another peak. Among the implications for theories of adaptation is our proposal of a cogent definition of fitness that goes beyond the 0 to 1 fitness metric

Ghost hunting in the nonlinear dynamic machine.

Integrating dynamic systems modeling and machine learning generates an exploratory nonlinear solution for analyzing dynamical systems-based data. Applying dynamical systems theory to the machine learning solution further provides a pathway to interpret the results. Using random forest models as an illustrative example, these models were able to recover the temporal dynamics of time series data simulated using a modified Cusp Catastrophe Monte Carlo. By extracting the points of no change (set points) and the predicted changes surrounding the set points, it is possible to characterize the topology of the system, both for systems governed by global equation forms and complex adaptive systems. RESULTS: The model for the simulation was able to recover the cusp catastrophe (i.e. the qualitative changes in the dynamics of the system) even when applied to data that have a significant amount of error variance. To further illustrate the approach, a real-world accelerometer example was examined, where the model differentiated between movement dynamics patterns by identifying set points related to cyclic motion during walking and attraction during stair climbing. These example findings suggest that integrating machine learning with dynamical systems modeling provides a viable means for classifying distinct temporal patterns, even when there is no governing equation for the nonlinear dynamics. Results of these integrated models yield solutions with both a prediction of where the system is going next and a decomposition of the topological features implied by the temporal dynamics