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The Voronoi model is a popular tool for studying confluent living tissues. It exhibits an anomalous glassy behavior even at very low temperatures or weak active self-propulsion, and at zero temperature the model exhibits a disordered solid structure with no evidence of a rigidity transition. Here we investigate the properties of the energy landscape in this limit. We find two disordered solid phases that have similar structural features but that differ in the ultrametricity of their energy landscapes; the crossover between these two states shares phenomenological properties with a Gardner transition. We further highlight how the metric used to calculate distances between configurations influences the ability to detect hierarchical arrangements of basins in the energy landscape.

© 2019 The Author(s) This study investigates, at the country level, the adverse effects of changes in metal inputs on the achievement of sustainable development goals (SDGs). It also highlights the relationships between metals use and various socio-economic consequences that urgently require decoupling in order to achieve the SDGs. We performed panel data analysis to evaluate, on a national scale and over a ten-year period (2004–2013), the impact of changes in the material flows of 11 metals on 96 SDG indicators corresponding to the 17 SDGs defined by the UN. On average, an increase in the material flow of the targeted metals was found to be correlated with a deterioration in approximately 10% of the 96 indicators. Among the affected SDGs, the adverse impact of metals on SDG 3 (Health), SDG 8 (Economic Growth), and SDG 16 (Peace, Justice, and Strong Institutions)was particularly noteworthy. More SDGs were negatively impacted in metal-mining countries than in metal-importing countries.

David Sussman, James E Paul Department of Anesthesia, McMaster University, Hamilton, ON, Canada Purpose: The primary objective of this study was to assess anesthesia residents' opinions and perceptions on wellness/burnout, fatigue, education, and patient safety after the initiation of a reduced call model (16-hour call). Methods: A prospective cohort study was conducted at three time points during the 2013–2014 academic year. A web-based questionnaire consisting of 23 questions was electronically distributed to all anesthesia residents from postgraduate years (PGY) 1 to 5 who were part of the active call roster (n=84) at McMaster University in Hamilton, Ontario. Descriptive summaries were calculated, counts and percentages were used for categorical variables, and answers to open text questions were reviewed for themes. Results: A response rate of 67% was obtained for this study. A majority of anesthesia residents (65%) approved of 16-hour call, felt that their overall quality of life as a senior resident (PGY3 or greater) or junior resident (PGY2 and below) had improved (73% and 55%, respectively), and reported overall feeling less fatigued. Most respondents indicated that the quality of education remained unchanged (47%), or had improved (31%). And most felt better prepared for the royal college exam (52%). Most felt patient safety had improved or was unchanged (both 48%). Conclusion: The study demonstrates that 16-hour call improved resident wellness, reduced burnout and fostered an environment where residents are less fatigued and more satisfied with their educational experience promoting an environment of patient safety. Overall, the anesthesia residency group demonstrated that not only is 16-hour call preferred but beneficial. Keywords: resident wellness, reduced call model, duty hours, patient safety, cohort study, fatigue&nbsp

The random dot product graph (RDPG) is an independent-edge random graph that is analytically tractable and, simultaneously, either encompasses or can successfully approximate a wide range of random graphs, from relatively simple stochastic block models to complex latent position graphs. In this survey paper, we describe a comprehensive paradigm for statistical inference on random dot product graphs, a paradigm centered on spectral embeddings of adjacency and Laplacian matrices. We examine the analogues, in graph inference, of several canonical tenets of classical Euclidean inference: in particular, we summarize a body of existing results on the consistency and asymptotic normality of the adjacency and Laplacian spectral embeddings, and the role these spectral embeddings can play in the construction of single- and multi-sample hypothesis tests for graph data. We investigate several real-world applications, including community detection and classification in large social networks and the determination of functional and biologically relevant network properties from an exploratory data analysis of the Drosophila connectome. We outline requisite background and current open problems in spectral graph inference., Comment: An expository survey paper on a comprehensive paradigm for inference for random dot product graphs, centered on graph adjacency and Laplacian spectral embeddings. Paper outlines requisite background; summarizes theory, methodology, and applications from previous and ongoing work; and closes with a discussion of several open problems