A Demonstration of Continuous Interaction with Elckerlyc

We discuss behavior planning in the style of the SAIBA framework for continuous (as opposed to turn-based) interaction. Such interaction requires the real-time application of minor shape or timing modifications of running behavior and anticipation of behavior of a (human) interaction partner. We discuss how behavior (re)planning and on-the-fly parameter modification fit into the current SAIBA framework, and what type of language or architecture extensions might be necessary. Our BML realizer Elckerlyc provides flexible mechanisms for both the specification and the execution of modifications to running behavior. We show how these mechanisms are used in a virtual trainer and two turn taking scenarios

Developing a Generic Debugger for Advanced-Dispatching Languages

Programming-language research has introduced a considerable number of advanced-dispatching mechanisms in order to improve modularity. Advanced-dispatching mechanisms allow changing the behavior of a function without modifying their call sites and thus make the local behavior of code less comprehensible. Debuggers are tools, thus needed, which can help a developer to comprehend program behavior but current debuggers do not provide inspection of advanced-\ud dispatching-related language constructs. In this paper, we present a debugger which extends a traditional Java debugger with the ability of debugging an advanced-dispatching language constructs and a user interface for inspecting this

Using a cognitive architecture to examine what develops

Different theories of development propose alternative mechanisms by which development occurs. Cognitive architectures can be used to examine the influence of each proposed mechanism of development while keeping all other mechanisms constant. An ACT-R computational model that matched adult behavior in solving a 21-block pyramid puzzle was created. The model was modified in three ways that corresponded to mechanisms of development proposed by developmental theories. The results showed that all the modifications (two of capacity and one of strategy choice) could approximate the behavior of 7-year-old children on the task. The strategy-choice modification provided the closest match on the two central measures of task behavior (time taken per layer, r = .99, and construction attempts per layer, r = .73). Modifying cognitive architectures is a fruitful way to compare and test potential developmental mechanisms, and can therefore help in specifying “what develops.

Anyone Can Become a Troll: Causes of Trolling Behavior in Online Discussions

In online communities, antisocial behavior such as trolling disrupts constructive discussion. While prior work suggests that trolling behavior is confined to a vocal and antisocial minority, we demonstrate that ordinary people can engage in such behavior as well. We propose two primary trigger mechanisms: the individual's mood, and the surrounding context of a discussion (e.g., exposure to prior trolling behavior). Through an experiment simulating an online discussion, we find that both negative mood and seeing troll posts by others significantly increases the probability of a user trolling, and together double this probability. To support and extend these results, we study how these same mechanisms play out in the wild via a data-driven, longitudinal analysis of a large online news discussion community. This analysis reveals temporal mood effects, and explores long range patterns of repeated exposure to trolling. A predictive model of trolling behavior shows that mood and discussion context together can explain trolling behavior better than an individual's history of trolling. These results combine to suggest that ordinary people can, under the right circumstances, behave like trolls.Comment: Best Paper Award at CSCW 201

Estrous behavior in dairy cows: identification of underlying mechanisms and gene functions

Selection in dairy cattle for a higher milk yield has coincided with declined fertility. One of the factors is reduced expression of estrous behavior. Changes in systems that regulate the estrous behavior could be manifested by altered gene expression. This literature review describes the current knowledge on mechanisms and genes involved in the regulation of estrous behavior. The endocrinological regulation of the estrous cycle in dairy cows is well described. Estradiol (E2) is assumed to be the key regulator that synchronizes endocrine and behavioral events. Other pivotal hormones are, for example, progesterone, gonadotropin releasing hormone and insulin-like growth factor-1. Interactions between the latter and E2 may play a role in the unfavorable effects of milk yield-related metabolic stress on fertility in high milk-producing dairy cows. However, a clear understanding of how endocrine mechanisms are tied to estrous behavior in cows is only starting to emerge. Recent studies on gene expression and signaling pathways in rodents and other animals contribute to our understanding of genes and mechanisms involved in estrous behavior. Studies in rodents, for example, show that estrogen-induced gene expression in specific brain areas such as the hypothalamus play an important role. Through these estrogen-induced gene expressions, E2 alters the functioning of neuronal networks that underlie estrous behavior, by affecting dendritic connections between cells, receptor populations and neurotransmitter releases. To improve the understanding of complex biological networks, like estrus regulation, and to deal with the increasing amount of genomic information that becomes available, mathematical models can be helpful. Systems biology combines physiological and genomic data with mathematical modeling. Possible applications of systems biology approaches in the field of female fertility and estrous behavior are discusse

Greening through schooling:Understanding the link between education and pro-environmental behavior in the Philippines

In recent years, changing lifestyle, consumption and mobility patterns have contributed to a global rise in greenhouse gases responsible for the warming of the planet. Despite its increasing relevance, there is a lack of understanding of factors influencing the environmental behavior of people from emerging economies. In this study, we focus on the role of formal education for pro-environmental behavior in the Philippines and study three potentially underlying mechanisms explaining the education effects: differential knowledge about climate change, risk perceptions, and awareness. Whilst there is some evidence showing that education is associated with pro-environmental behavior, little is known about the actual mechanisms through which it influences decision-making. Using propensity score methods, we find that an additional year of schooling significantly increases the probability of pro-environmental actions, e.g. planting trees, recycling, and proper waste management, by 3.3%. Further decomposing the education effects, it is found that education influences behavior mainly by increasing awareness about the anthropogenic causes of climate change, which may consequently affect the perception of self-efficacy in reducing human impacts on the environment. Knowledge and perceptions about climate risks also explain the education effect on pro-environmental behavior, but to a lesser extent

Cooja TimeLine: A Power Visualizer for Sensor Network Simulation

Power consumption is one of the most important factors in wireless sensor network research, but most simulators do not provide support for visualizing the power consumption of an entire sensor network. This makes it hard to develop, debug, and understand mechanisms and protocols based on power-saving mechanisms. We present Cooja TimeLine, an extension to Contiki’s Cooja network simulator, that visualizes radio traffic and radio usage of sensor networks. Cooja TimeLine makes is possible to visually see the behavior of low-power protocols and mechanisms thereby increasing the understanding of the behavior of sensor networks. We see this as an important tool for the field moving forward

Fragile-strong transitions and polyamorphism in glass former fluids

A simple model of a glass former fluid, consisting of a bidisperse mixture of penetrable spheres is studied. The model shows a transition from fragile to strong behavior as temperature is reduced. This transition is driven by the competition between the two mechanisms that contribute to diffusivity in the model: collective rearrangement of particles (responsible for the fragile behavior), and individual particle motion (which gives rise to the strong behavior at low temperature). We also observe a maximum of diffusivity as a function of pressure that can be interpreted within the same framework. The connection between this behavior and polyamorphism is addressed.Comment: 5 pages, 6 figure