Young People’s Perceptions of the Influence of a Sport-for-Social-Change Program on Their Life Trajectories

Sport-for-social-change programs focusing on enhancing young people’s personal and social development emerged in the early to mid-2000s. Children and adolescents who participated in early programs are now adults, providing an opportunity to examine whether these programs have had any influence on their life trajectories. The Football United program has been operating in Sydney, Australia, since 2006 and is used as a case study in this article. This qualitative study draws on 20 interviews conducted in 2018 with a diverse sample of past participants of the program. Key findings were that participants perceived that the relationships they formed at Football United have had a substantial impact on their life trajectories, including influencing education and career decisions. These relationships were found to increase participants’ social capital, creating diverse connections with people and institutions within and external to their geographical communities. This study also found participants embraced a long-term commitment to ‘give back’ to their local geographical, cultural, and ethnic communities, which they attributed to their participation in the program

An Afternoon of Jazz in celebration of Black History Month

Program listing performers and works performe

Sharing and visualizing environmental data using Virtual Globes

Virtual globe technology holds many exciting possibilities for environmental science. These easy-to-use, intuitive systems provide means for simultaneously visualizing four-dimensional environmental data from many different sources, enabling the generation of new hypotheses and driving greater understanding of the Earth system. Through the use of simple markup languages, scientists can publish and consume data in interoperable formats without the need for technical assistance. In this paper we give, with examples from our own work, a number of scientific uses for virtual globes, demonstrating their particular advantages. We explain how we have used Web Services to connect virtual globes with diverse data sources and enable more sophisticated usage such as data analysis and collaborative visualization. We also discuss the current limitations of the technology, with particular regard to the visualization of subsurface data and vertical sections

Rapid social perception is flexible: approach and avoidance motivational states shape P100 responses to other-race faces

Research on person categorization suggests that people automatically and inflexibly categorize others according to group memberships, such as race. Consistent with this view, research using electroencephalography (EEG) has found that White participants tend to show an early difference in processing Black versus White faces. Yet, new research has shown that these ostensibly automatic biases may not be as inevitable as once thought and that motivational influences may be able to eliminate these biases. It is unclear, however, whether motivational influences shape the initial biases or whether these biases can only be modulated by later, controlled processes. Using EEG to examine the time course of biased processing, we manipulated approach and avoidance motivational states by having participants pull or push a joystick, respectively, while viewing White or Black faces. Consistent with previous work on own-race bias, we observed a greater P100 response to White than Black faces; however, this racial bias was attenuated in the approach condition. These data suggest that rapid social perception may be flexible and can be modulated by motivational states

Making data a first class scientific output : data citation and publication by NERC's Environmental Data Centres

The NERC Science Information Strategy Data Citation and Publication project aims to develop and formalise a method for formally citing and publishing the datasets stored in its environmental data centres. It is believed that this will act as an incentive for scientists, who often invest a great deal of effort in creating datasets, to submit their data to a suitable data repository where it can properly be archived and curated. Data citation and publication will also provide a mechanism for data producers to receive credit for their work, thereby encouraging them to share their data more freely

Considerations of Mutual Exchange in Prosocial Decision-Making

Research using economic decision-making tasks has established that direct reciprocity plays a role in prosocial decision-making: people are more likely to help those who have helped them in the past. However, less is known about how considerations of mutual exchange influence decisions even when the other party’s actions are unknown and direct reciprocity is therefore not possible. Using a two-party economic task in which the other’s actions are unknown, Study 1 shows that prosociality critically depends on the potential for mutual exchange; when the other person has no opportunity to help the participant, prosocial behavior is drastically reduced. In Study 2, we find that theories regarding the other person’s intentions influence the degree of prosociality that participants exhibit, even when no opportunity for direct reciprocity exists. Further, beliefs about the other’s intentions are closely related to one’s own motivations in the task. Together, the results support a model in which prosociality depends on both the social conditions for mutual exchange and a mental model of how others will behave within these conditions, which is closely related to knowledge of the self

ParticleMDI - Particle Monte Carlo methods for the cluster analysis of multiple datasets with applications to cancer subtype identification

We present a novel nonparametric Bayesian approach for performing cluster analysis in a context where observational units have data arising from multiple sources. Our approach uses a particle Gibbs sampler for inference in which cluster allocations are jointly updated using a conditional particle filter within a Gibbs sampler, improving the mixing of the MCMC chain. We develop several approaches to improving the computational performance of our algorithm. These methods can achieve greater than an order-of-magnitude improvement in performance at no cost to accuracy and can be applied more broadly to Bayesian inference for mixture models with a single dataset. We apply our algorithm to the discovery of risk cohorts amongst 243 patients presenting with kidney renal clear cell carcinoma, using samples from the Cancer Genome Atlas, for which there are gene expression, copy number variation, DNA methylation, protein expression and microRNA data. We identify 4 distinct consensus subtypes and show they are prognostic for survival rate (p < 0.0001)

A computationally engineered RAS rheostat reveals RAS-ERK signaling dynamics.

Synthetic protein switches controlled with user-defined inputs are powerful tools for studying and controlling dynamic cellular processes. To date, these approaches have relied primarily on intermolecular regulation. Here we report a computationally guided framework for engineering intramolecular regulation of protein function. We utilize this framework to develop chemically inducible activator of RAS (CIAR), a single-component RAS rheostat that directly activates endogenous RAS in response to a small molecule. Using CIAR, we show that direct RAS activation elicits markedly different RAS-ERK signaling dynamics from growth factor stimulation, and that these dynamics differ among cell types. We also found that the clinically approved RAF inhibitor vemurafenib potently primes cells to respond to direct wild-type RAS activation. These results demonstrate the utility of CIAR for quantitatively interrogating RAS signaling. Finally, we demonstrate the general utility of our approach in design of intramolecularly regulated protein tools by applying it to the Rho family of guanine nucleotide exchange factors

Ideology and Predictive Processing: Coordination, Bias, and Polarization in Socially Constrained Error Minimization

Recent models of cognition suggest that the brain may implement predictive processing, in which top-down expectations constrain incoming sensory data. In this perspective, expectations are updated (error minimization) only if sensory data sufficiently deviate from these expectations (prediction error). Although originally applied to perception, predictive processing is thought to generally characterize cognitive architecture, including the social cognitive processes involved in ideological thinking. Scaling up these simple computational principles to the social sphere outlines a path by which group members may adopt shared ideologies and beliefs to predict behavior and cooperate with each other. Because ideological judgments are of specific interest to others in our political groups, we may increasingly regulate each other’s thinking, sharing the process of error minimization. In this paper, we outline how this process of shared error minimization may lead to shared ideologies and beliefs that allow group members to predict and cooperate with each other, and how, as a consequence, political polarization and extremism may result

Troubled Worlds: A Course Syllabus about Information Work and the Anthropocene

The goal of this syllabus is to interrogate the material, and socioeconomic processes which underpin our everyday information work. In particular, we examine the relationships developing between contemporary information practices and what problematically gets configured as “nature”—that messy world of non-human entanglements that often exists beyond the purview of innovation work, whether digital software development or industrial engineering. Much recent work on the environmental conditions of computing has sought to break down technology-nature dualisms in order to expose the implication of information technology in broader social and material ecologies. Library and information professionals and researchers are well poised to deepen this inquiry by presenting alternative nature-technology epistemologies grounded in longstanding analyses of information resources and their consumption. The “Troubled Worlds” syllabus starts with a discussion of concerns most obviously germane to the work of most library and information science professionals: practices at the intersection of structuring information and computing. Building on this attention, we turn to humanistic approaches to thinking through the era of dominant human activities widely known as the “Anthropocene” by introducing poetic, artistic, and activist lenses. We explore how artistic objects representing an increasingly troubled natural world raise awareness of the challenges facing it, as well as how they may incorporate and reshape information for aesthetic ends. We then look to questions of disability justice and how it works in blended built and natural spaces as well as the many different ways in which bodies respond to the toxic environments produced by information technologies. We next consider the newer design approaches to library and information research, specifically asking how design perspectives on digital information objects get inscribed in the Anthropocene. Lastly, we consider paradigms of repair and making and analyze the different valences through which information researchers and professionals categorize and contextualize what is possible with them. This compilation does not provide a comprehensive review of the literature on the environment within the information fields. Instead, it extends this literature to promote experimental research and practice. The modules construct an interdisciplinary and provisional path through the related literature in a form that we hope may be continually adjusted, rearranged, and augmented. Pre-print first published online 03/15/202