Markerless Motion Capture in the Crowd

This work uses crowdsourcing to obtain motion capture data from video recordings. The data is obtained by information workers who click repeatedly to indicate body configurations in the frames of a video, resulting in a model of 2D structure over time. We discuss techniques to optimize the tracking task and strategies for maximizing accuracy and efficiency. We show visualizations of a variety of motions captured with our pipeline then apply reconstruction techniques to derive 3D structure.Comment: Presented at Collective Intelligence conference, 2012 (arXiv:1204.2991

Followback Clusters, Satellite Audiences, and Bridge Nodes: Coengagement Networks for the 2020 US Election

The 2020 United States presidential election was, and has continued to be, the focus of pervasive and persistent mis- and disinformation spreading through our media ecosystems, including social media. This event has driven the collection and analysis of large, directed social network datasets, but such datasets can resist intuitive understanding. In such large datasets, the overwhelming number of nodes and edges present in typical representations create visual artifacts, such as densely overlapping edges and tightly-packed formations of low-degree nodes, which obscure many features of more practical interest. We apply a method, coengagement transformations, to convert such networks of social data into tractable images. Intuitively, this approach allows for parameterized network visualizations that make shared audiences of engaged viewers salient to viewers. Using the interpretative capabilities of this method, we perform an extensive case study of the 2020 United States presidential election on Twitter, contributing an empirical analysis of coengagement. By creating and contrasting different networks at different parameter sets, we define and characterize several structures in this discourse network, including bridging accounts, satellite audiences, and followback communities. We discuss the importance and implications of these empirical network features in this context. In addition, we release open-source code for creating coengagement networks from Twitter and other structured interaction data.Comment: Accepted for publication at ICWSM '2

Commentary on "The Perception and Cognition of Time in Balinese Music" by Andrew Clay McGraw

We review the paper by Andrew Clay McGraw, noting that it represents an interesting and valuable contribution to the study of music in cognition in its informed exploration of non-western musical perceptions. We raise a number of concerns about the methods used, and make suggestions as to how the issues that were empirically addressed in the paper might have been tackled in ways that would have enhanced the interpretability of its findings

Role of sialidase in glycoprotein utilization by Tannerella forsythia

The major bacterial pathogens associated with periodontitis include Tannerella forsythia. We previously discovered that sialic acid stimulates biofilm growth of T. forsythia, and that sialidase activity is key to utilization of sialoconjugate sugars and is involved in host–pathogen interactions in vitro. The aim of this work was to assess the influence of the NanH sialidase on initial biofilm adhesion and growth in experiments where the only source of sialic acid was sialoglycoproteins or human oral secretions. After showing that T. forsythia can utilize sialoglycoproteins for biofilm growth, we showed that growth and initial adhesion with sialylated mucin and fetuin were inhibited two- to threefold by the sialidase inhibitor oseltamivir. A similar reduction (three- to fourfold) was observed with a nanH mutant compared with the wild-type. Importantly, these data were replicated using clinically relevant serum and saliva samples as substrates. In addition, the ability of the nanH mutant to form biofilms on glycoprotein-coated surfaces could be restored by the addition of purified NanH, which we show is able to cleave sialic acid from the model glycoprotein fetuin and, much less efficiently, 9-O-acetylated bovine submaxillary mucin. These data show for the first time that glycoprotein-associated sialic acid is likely to be a key in vivo nutrient source for T. forsythia when growing in a biofilm, and suggest that sialidase inhibitors might be useful adjuncts in periodontal therapy

Australian clinical practice guidelines for the diagnosis and management of Barrett's esophagus and early esophageal adenocarcinoma

Author version made available following 12 month embargo from date of publication according to publisher copyright policy.Barrett's esophagus (BE), a common condition, is the only known precursor to esophageal adenocarcinoma (EAC). There is uncertainty about the best way to manage BE as most people with BE never develop EAC and most patients diagnosed with EAC have no preceding diagnosis of BE. Moreover, there have been recent advances in knowledge and practice about the management of BE and early EAC. To aid clinical decision making in this rapidly moving field, Cancer Council Australia convened an expert working party to identify pertinent clinical questions. The questions covered a wide range of topics including endoscopic and histological definitions of BE and early EAC; prevalence, incidence, natural history, and risk factors for BE; and methods for managing BE and early EAC. The latter considered modification of lifestyle factors; screening and surveillance strategies; and medical, endoscopic, and surgical interventions. To answer each question, the working party systematically reviewed the literature and developed a set of recommendations through consensus. Evidence underpinning each recommendation was rated according to quality and applicability

Keys for architectural history research in the digital era

This handbook gathers a selection of texts by the speakers at the Training School “Architectural Research in the Digital Era” (Ghent, 2-6 April 2013) and the workshop “GIS, data visualization an open community” (Paris, 27-28 January 2014). The aims of these two events organised in the framework of the COST ISO904 Action European architecture beyond Europe: Sharing Research and Knowledge on Dissemination Processes, Historical Data and Material Legacy (19th-20th centuries), was to familiarize the participants, architectural historians with a variety of aspects related to conducting research in a digital era: Architectural history research in the digital era Copyrights; Standards, metadata, interoperability and sustainability; Data visualisation; Creating a digital research environment, GIS and Open communities

Genome Analysis Linking Recent European and African Influenza (H5N1) Viruses

Although linked, these viruses are distinct from earlier outbreak strains

Trajectories of Big Five Personality Traits: A Coordinated Analysis of 16 Longitudinal Samples

This study assessed change in self‐reported Big Five personality traits. We conducted a coordinated integrative data analysis using data from 16 longitudinal samples, comprising a total sample of over 60 000 participants. We coordinated models across multiple datasets and fit identical multi‐level growth models to assess and compare the extent of trait change over time. Quadratic change was assessed in a subset of samples with four or more measurement occasions. Across studies, the linear trajectory models revealed declines in conscientiousness, extraversion, and openness. Non‐linear models suggested late‐life increases in neuroticism. Meta‐analytic summaries indicated that the fixed effects of personality change are somewhat heterogeneous and that the variability in trait change is partially explained by sample age, country of origin, and personality measurement method. We also found mixed evidence for predictors of change, specifically for sex and baseline age. This study demonstrates the importance of coordinated conceptual replications for accelerating the accumulation of robust and reliable findings in the lifespan developmental psychological sciences. © 2020 European Association of Personality PsychologyPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/156004/1/per2259.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/156004/2/per2259-sup-0001-Data_S1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/156004/3/per2259-sup-0002-Open_Practices_Disclosure_Form.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/156004/4/per2259_am.pd

Is healthy neuroticism associated with health behaviors? A coordinated integrative data analysis

Current literature suggests that neuroticism is positively associated with maladaptive life choices, likelihood of disease, and mortality. However, recent research has identified circumstances under which neuroticism is associated with positive outcomes. The current project examined whether “healthy neuroticism”, defined as the interaction of neuroticism and conscientiousness, was associated with the following health behaviors: smoking, alcohol consumption, and physical activity. Using a pre-registered multi-study coordinated integrative data analysis (IDA) approach, we investigated whether “healthy neuroticism” predicted the odds of engaging in each of the aforementioned activities. Each study estimated identical models, using the same covariates and data transformations, enabling optimal comparability of results. These results were then meta-analyzed in order to estimate an average (N-weighted) effect and to ascertain the extent of heterogeneity in the effects. Overall, these results suggest that neuroticism alone was not related to health behaviors, while individuals higher in conscientiousness were less likely to be smokers or drinkers, and more likely to engage in physical activity. In terms of the healthy neuroticism interaction of neuroticism and conscientiousness, significant interactions for smoking and physical activity suggest that the association between neuroticism and health behaviors was smaller among those high in conscientiousness. These findings lend credence to the idea that healthy neuroticism may be linked to certain health behaviors and that these effects are generalizable across several heterogeneous samples