Unsupervised machine learning for detection of phase transitions in off-lattice systems I. Foundations

We demonstrate the utility of an unsupervised machine learning tool for the detection of phase transitions in off-lattice systems. We focus on the application of principal component analysis (PCA) to detect the freezing transitions of two-dimensional hard-disk and three-dimensional hard-sphere systems as well as liquid-gas phase separation in a patchy colloid model. As we demonstrate, PCA autonomously discovers order-parameter-like quantities that report on phase transitions, mitigating the need for a priori construction or identification of a suitable order parameter--thus streamlining the routine analysis of phase behavior. In a companion paper, we further develop the method established here to explore the detection of phase transitions in various model systems controlled by compositional demixing, liquid crystalline ordering, and non-equilibrium active forces

1952 Steel Seizure Revisited - Systematic Study In Presidential Decision-Making

Managemen

Subunit interactions influence the biochemical and biological properties of Hsp104

Point mutations in either of the two nucleotide-binding domains (NBD) of Hsp104 (NBD1 and NBD2) eliminate its thermotolerance function in vivo. In vitro, NBD1 mutations virtually eliminate ATP hydrolysis with little effect on hexamerization; analogous NBD2 mutations reduce ATPase activity and severely impair hexamerization. We report that high protein concentrations overcome the assembly defects of NBD2 mutants and increase ATP hydrolysis severalfold, changing V(max) with little effect on K(m). In a complementary fashion, the detergent 3-[(3-cholamidopropyl)dimethylammonio]-1-propanesulfonate inhibits hexamerization of wild-type (WT) Hsp104, lowering V(max) with little effect on K(m). ATP hydrolysis exhibits a Hill coefficient between 1.5 and 2, indicating that it is influenced by cooperative subunit interactions. To further analyze the effects of subunit interactions on Hsp104, we assessed the effects of mutant Hsp104 proteins on WT Hsp104 activities. An NBD1 mutant that hexamerizes but does not hydrolyze ATP reduces the ATPase activity of WT Hsp104 in vitro. In vivo, this mutant is not toxic but specifically inhibits the thermotolerance function of WT Hsp104. Thus, interactions between subunits influence the ATPase activity of Hsp104, play a vital role in its biological functions, and provide a mechanism for conditionally inactivating Hsp104 function in vivo

Unsupervised machine learning for detection of phase transitions in off-lattice systems II. Applications

We outline how principal component analysis (PCA) can be applied to particle configuration data to detect a variety of phase transitions in off-lattice systems, both in and out of equilibrium. Specifically, we discuss its application to study 1) the nonequilibrium random organization (RandOrg) model that exhibits a phase transition from quiescent to steady-state behavior as a function of density, 2) orientationally and positionally driven equilibrium phase transitions for hard ellipses, and 3) compositionally driven demixing transitions in the non-additive binary Widom-Rowlinson mixture

The journey and destination need to be intentional: Perceptions of success in community-academic research partnerships

Research partnerships between community members and academics are dynamic microsystems that aim to increase community wellbeing within complex environments. Efforts to improve health and social outcomes in communities are challenging in their own right, but even the most experienced researchers or engaged community members can have difficulty navigating the collaborative terrain of community-academic research partnerships. Proponents of participatory research models that engage community members as co-researchers are still examining how the collaborative process interacts with, and impacts, both short- and long-term outcomes. As a result, there has been a call for additional studies that employ qualitative and quantitative methods to contribute to a holistic understanding of this approach to research. This pilot study utilized the participatory tenets of co-researcher models to explore how members of community-academic research partnerships think about partnership processes and outcomes, including how they delineate between the two. Web-based concept mapping methodology was combined with individual interviews in an innovative mixed methods research study to further the field’s understanding of how community and academic members define partnership success and evaluate the impact of their work. Our findings suggest that in the early stages of a partnership members rely on informal and intuitive evaluation of success based on how the partnership is functioning. These partnership processes, which serve as intermediate outcomes, largely influence member engagement in the work, but partnerships are ultimately deemed successful if intended community-based research outcomes are achieved.Keywords: community-academic research partnerships, participatory research, concept mapping methodology, mixed methods, partnership process, outcomes  

From 3D landscape visualization to environmental simulation: The contribution of sound to the perception of virtual environments

This research investigated the perceptual interaction of combining sound with 3D landscape visualizations. Images sourced from Google Earth at St. James's Park, London, UK, showing terrain only, terrain with built form or terrain with primarily vegetation were paired with four sound conditions using recordings from the park (i.e. ‘no sound’, anthropogenic, mechanical and natural). Perceived realism and preference were evaluated using a survey delivered via the Internet and in a controlled laboratory environment (N = 199 total). Analysis using repeated measures ANOVA indicated the interaction of sound and 3D visualizations significantly alters environmental perception both positively and negatively. Sounds and visuals that are congruent receive higher realism and preference ratings while the more incongruent the combination is, the lower the corresponding ratings. The lowest realism and preference ratings are given to visualizations showing terrain only combined with speech. The highest realism ratings overall correspond to visualization with built form combined with speech, and visualizations showing primarily vegetation paired with a birdcall. The absolute highest realism rating was for the visualization with primarily vegetation and some built form paired with speech, while the highest preference ratings correspond to visualizations showing vegetation paired with birdcall or no sound. Aural-visual data collected via the web-based survey was comparable to data collected in the laboratory and overall realism ratings for the Google Earth visualizations were low (e.g. below 3 on a 1–5 likert type scale). The results suggest there is an opportunity to increase experiential authenticity of 3D landscape visualizations with sound

Horizontal Educational Inequalities and Civil Conflict: The Nexus of Ethnicity, Inequality, and Violent Conflict

Development economists have long questioned the relationship between civil conflict, inequality, and ethnic heterogeneity. While most quantitative literature has focused on inequality between individuals, this study analyzes the relationship of horizontal inequality – between groups of individuals sharing a common identity – and propensity for the onset of civil conflict, focusing on horizontal educational inequality (HEI). Findings from Demographic and Health Survey data for 44 countries from 1986 to 2005 show that measures of both female and male HEI are marginally or not significant in predicting civil conflict but strongly significant in predicting ethnic civil conflict