Weather-it missions: a social network analysis perspective of an online citizen inquiry community

Citizen inquiry is an innovative informal science learning approach, which engages members of the general public in scientific investigations sparked by their personal experience of everyday science, and to which other members can contribute. This paper aims to describe the network of interactions and contributions of Weather-it, an online Citizen Inquiry community accommodated by the nQuire-it platform, which involves people in creating and maintaining their own weather missions (investigations). The interaction patterns within Weather-it are mainly explored through social network analysis of community members and missions. The results indicate the quiet and active members within the community, their splitting into sub-communities, and their contribution and data collection methods and preferences. These results provide in-sight into the behaviour of people in such public engagement projects

Learning Adaptive Regularization for Image Labeling Using Geometric Assignment

We study the inverse problem of model parameter learning for pixelwise image labeling, using the linear assignment flow and training data with ground truth. This is accomplished by a Riemannian gradient flow on the manifold of parameters that determine the regularization properties of the assignment flow. Using the symplectic partitioned Runge--Kutta method for numerical integration, it is shown that deriving the sensitivity conditions of the parameter learning problem and its discretization commute. A convenient property of our approach is that learning is based on exact inference. Carefully designed experiments demonstrate the performance of our approach, the expressiveness of the mathematical model as well as its limitations, from the viewpoint of statistical learning and optimal control

Polarization of coalitions in an agent-based model of political discourse

Political discourse is the verbal interaction between political actors in a policy domain. This article explains the formation of polarized advocacy or discourse coalitions in this complex phenomenon by presenting a dynamic, stochastic, and discrete agent-based model based on graph theory and local optimization. In a series of thought experiments, actors compute their utility of contributing a specific statement to the discourse by following ideological criteria, preferential attachment, agenda-setting strategies, governmental coherence, or other mechanisms. The evolving macro-level discourse is represented as a dynamic network and evaluated against arguments from the literature on the policy process. A simple combination of four theoretical mechanisms is already able to produce artificial policy debates with theoretically plausible properties. Any sufficiently realistic configuration must entail innovative and path-dependent elements as well as a blend of exogenous preferences and endogenous opinion formation mechanisms

Hot Streaks in Artistic, Cultural, and Scientific Careers

The hot streak, loosely defined as winning begets more winnings, highlights a specific period during which an individual's performance is substantially higher than her typical performance. While widely debated in sports, gambling, and financial markets over the past several decades, little is known if hot streaks apply to individual careers. Here, building on rich literature on lifecycle of creativity, we collected large-scale career histories of individual artists, movie directors and scientists, tracing the artworks, movies, and scientific publications they produced. We find that, across all three domains, hit works within a career show a high degree of temporal regularity, each career being characterized by bursts of high-impact works occurring in sequence. We demonstrate that these observations can be explained by a simple hot-streak model we developed, allowing us to probe quantitatively the hot streak phenomenon governing individual careers, which we find to be remarkably universal across diverse domains we analyzed: The hot streaks are ubiquitous yet unique across different careers. While the vast majority of individuals have at least one hot streak, hot streaks are most likely to occur only once. The hot streak emerges randomly within an individual's sequence of works, is temporally localized, and is unassociated with any detectable change in productivity. We show that, since works produced during hot streaks garner significantly more impact, the uncovered hot streaks fundamentally drives the collective impact of an individual, ignoring which leads us to systematically over- or under-estimate the future impact of a career. These results not only deepen our quantitative understanding of patterns governing individual ingenuity and success, they may also have implications for decisions and policies involving predicting and nurturing individuals with lasting impact

Serratamolide is a hemolytic factor produced by Serratia marcescens

Serratia marcescens is a common contaminant of contact lens cases and lenses. Hemolytic factors of S. marcescens contribute to the virulence of this opportunistic bacterial pathogen. We took advantage of an observed hyper-hemolytic phenotype of crp mutants to investigate mechanisms of hemolysis. A genetic screen revealed that swrW is necessary for the hyper-hemolysis phenotype of crp mutants. The swrW gene is required for biosynthesis of the biosurfactant serratamolide, previously shown to be a broad-spectrum antibiotic and to contribute to swarming motility. Multicopy expression of swrW or mutation of the hexS transcription factor gene, a known inhibitor of swrW expression, led to an increase in hemolysis. Surfactant zones and expression from an swrW-transcriptional reporter were elevated in a crp mutant compared to the wild type. Purified serratamolide was hemolytic to sheep and murine red blood cells and cytotoxic to human airway and corneal limbal epithelial cells in vitro. The swrW gene was found in the majority of contact lens isolates tested. Genetic and biochemical analysis implicate the biosurfactant serratamolide as a hemolysin. This novel hemolysin may contribute to irritation and infections associated with contact lens use. © 2012 Shanks et al

Enhanced mitochondrial superoxide scavenging does not Improve muscle insulin action in the high fat-fed mouse

Improving mitochondrial oxidant scavenging may be a viable strategy for the treatment of insulin resistance and diabetes. Mice overexpressing the mitochondrial matrix isoform of superoxide dismutase (sod2(tg) mice) and/or transgenically expressing catalase within the mitochondrial matrix (mcat(tg) mice) have increased scavenging of O2(˙-) and H2O2, respectively. Furthermore, muscle insulin action is partially preserved in high fat (HF)-fed mcat(tg) mice. The goal of the current study was to test the hypothesis that increased O2(˙-) scavenging alone or in combination with increased H2O2 scavenging (mtAO mice) enhances in vivo muscle insulin action in the HF-fed mouse. Insulin action was examined in conscious, unrestrained and unstressed wild type (WT), sod2(tg), mcat(tg) and mtAO mice using hyperinsulinemic-euglycemic clamps (insulin clamps) combined with radioactive glucose tracers following sixteen weeks of normal chow or HF (60% calories from fat) feeding. Glucose infusion rates, whole body glucose disappearance, and muscle glucose uptake during the insulin clamp were similar in chow- and HF-fed WT and sod2(tg) mice. Consistent with our previous work, HF-fed mcat(tg) mice had improved muscle insulin action, however, an additive effect was not seen in mtAO mice. Insulin-stimulated Akt phosphorylation in muscle from clamped mice was consistent with glucose flux measurements. These results demonstrate that increased O2(˙-) scavenging does not improve muscle insulin action in the HF-fed mouse alone or when coupled to increased H2O2 scavenging

Does Presentation Format Influence Visual Size Discrimination in Tufted Capuchin Monkeys (Sapajus spp.)?

Most experimental paradigms to study visual cognition in humans and non-human species are based on discrimination tasks involving the choice between two or more visual stimuli. To this end, different types of stimuli and procedures for stimuli presentation are used, which highlights the necessity to compare data obtained with different methods. The present study assessed whether, and to what extent, capuchin monkeys\u27 ability to solve a size discrimination problem is influenced by the type of procedure used to present the problem. Capuchins\u27 ability to generalise knowledge across different tasks was also evaluated. We trained eight adult tufted capuchin monkeys to select the larger of two stimuli of the same shape and different sizes by using pairs of food items (Experiment 1), computer images (Experiment 1) and objects (Experiment 2). Our results indicated that monkeys achieved the learning criterion faster with food stimuli compared to both images and objects. They also required consistently fewer trials with objects than with images. Moreover, female capuchins had higher levels of acquisition accuracy with food stimuli than with images. Finally, capuchins did not immediately transfer the solution of the problem acquired in one task condition to the other conditions. Overall, these findings suggest that - even in relatively simple visual discrimination problems where a single perceptual dimension (i.e., size) has to be judged - learning speed strongly depends on the mode of presentation

A statistical approach to quantitative data validation focused on the assessment of students' perceptions about biotechnology

Student awareness levels are frequently used to evaluate the effectiveness of educational policies to promote scientific literacy. Over the last years several studies have been developed to assess students' perceptions towards science and technology, which usually rely on quantitative methods to achieve broad characterizations, and obtain quantifiable and comparable data. Although the usefulness of this information depends on its validity and reliability, validation is frequently neglected by researchers with limited background in statistics. In this context, we propose a guideline to implement a statistical approach to questionnaire validation, combining exploratory factor analysis and reliability analysis. The work focuses on the psychometric analysis of data provided by a questionnaire assessing 1196 elementary and high school students' perceptions about biotechnology. Procedural guidelines to enhance the efficiency of quantitative inquiry surveys are given, by discussing essential methodological aspects and relevant criteria to integrate theory into practice.The authors are grateful to all the participant teachers and students that contributed to gather the data presented and to Catarina L. Santos for useful comments and suggestions on the manuscript. Maria Joao Fonseca was supported by the FCT fellowship SFRH/BD/37389/2007 and this work was sponsored by a research grant (PTDC/AGR-PRO/111857/2009) from Fundacao para a Ciencia e Tecnologia (FCT, Portugal)

Reduced functional measure of cardiovascular reserve predicts admission to critical care unit following kidney transplantation

Background: There is currently no effective preoperative assessment for patients undergoing kidney transplantation that is able to identify those at high perioperative risk requiring admission to critical care unit (CCU). We sought to determine if functional measures of cardiovascular reserve, in particular the anaerobic threshold (VO2AT) could identify these patients. Methods: Adult patients were assessed within 4 weeks prior to kidney transplantation in a University hospital with a 37-bed CCU, between April 2010 and June 2012. Cardiopulmonary exercise testing (CPET), echocardiography and arterial applanation tonometry were performed. Results: There were 70 participants (age 41.7614.5 years, 60% male, 91.4% living donor kidney recipients, 23.4% were desensitized). 14 patients (20%) required escalation of care from the ward to CCU following transplantation. Reduced anaerobic threshold (VO2AT) was the most significant predictor, independently (OR = 0.43; 95% CI 0.27–0.68; p,0.001) and in the multivariate logistic regression analysis (adjusted OR = 0.26; 95% CI 0.12–0.59; p = 0.001). The area under the receiveroperating- characteristic curve was 0.93, based on a risk prediction model that incorporated VO2AT, body mass index and desensitization status. Neither echocardiographic nor measures of aortic compliance were significantly associated with CCU admission. Conclusions: To our knowledge, this is the first prospective observational study to demonstrate the usefulness of CPET as a preoperative risk stratification tool for patients undergoing kidney transplantation. The study suggests that VO2AT has the potential to predict perioperative morbidity in kidney transplant recipients

Temporal networks of face-to-face human interactions

The ever increasing adoption of mobile technologies and ubiquitous services allows to sense human behavior at unprecedented levels of details and scale. Wearable sensors are opening up a new window on human mobility and proximity at the finest resolution of face-to-face proximity. As a consequence, empirical data describing social and behavioral networks are acquiring a longitudinal dimension that brings forth new challenges for analysis and modeling. Here we review recent work on the representation and analysis of temporal networks of face-to-face human proximity, based on large-scale datasets collected in the context of the SocioPatterns collaboration. We show that the raw behavioral data can be studied at various levels of coarse-graining, which turn out to be complementary to one another, with each level exposing different features of the underlying system. We briefly review a generative model of temporal contact networks that reproduces some statistical observables. Then, we shift our focus from surface statistical features to dynamical processes on empirical temporal networks. We discuss how simple dynamical processes can be used as probes to expose important features of the interaction patterns, such as burstiness and causal constraints. We show that simulating dynamical processes on empirical temporal networks can unveil differences between datasets that would otherwise look statistically similar. Moreover, we argue that, due to the temporal heterogeneity of human dynamics, in order to investigate the temporal properties of spreading processes it may be necessary to abandon the notion of wall-clock time in favour of an intrinsic notion of time for each individual node, defined in terms of its activity level. We conclude highlighting several open research questions raised by the nature of the data at hand.Comment: Chapter of the book "Temporal Networks", Springer, 2013. Series: Understanding Complex Systems. Holme, Petter; Saram\"aki, Jari (Eds.