The dual impact of ecology and management on social incentives in marine common-pool resource systems.

PubMed

Klein, E S; Barbier, M R; Watson, J R

2017-08-01

Understanding how and when cooperative human behaviour forms in common-pool resource systems is critical to illuminating social-ecological systems and designing governance institutions that promote sustainable resource use. Before assessing the full complexity of social dynamics, it is essential to understand, concretely and mechanistically, how resource dynamics and human actions interact to create incentives and pay-offs for social behaviours. Here, we investigated how such incentives for information sharing are affected by spatial dynamics and management in a common-pool resource system. Using interviews with fishermen to inform an agent-based model, we reveal generic mechanisms through which, for a given ecological setting characterized by the spatial dynamics of the resource, the two 'human factors' of information sharing and management may heterogeneously impact various members of a group for whom theory would otherwise predict the same strategy. When users can deplete the resource, these interactions are further affected by the management approach. Finally, we discuss the implications of alternative motivations, such as equity among fishermen and consistency of the fleet's output. Our results indicate that resource spatial dynamics, form of management and level of depletion can interact to alter the sociality of people in common-pool resource systems, providing necessary insight for future study of strategic decision processes.

You Look Human, But Act Like a Machine: Agent Appearance and Behavior Modulate Different Aspects of Human-Robot Interaction.

PubMed

Abubshait, Abdulaziz; Wiese, Eva

2017-01-01

Gaze following occurs automatically in social interactions, but the degree to which gaze is followed depends on whether an agent is perceived to have a mind, making its behavior socially more relevant for the interaction. Mind perception also modulates the attitudes we have toward others, and determines the degree of empathy, prosociality, and morality invested in social interactions. Seeing mind in others is not exclusive to human agents, but mind can also be ascribed to non-human agents like robots, as long as their appearance and/or behavior allows them to be perceived as intentional beings. Previous studies have shown that human appearance and reliable behavior induce mind perception to robot agents, and positively affect attitudes and performance in human-robot interaction. What has not been investigated so far is whether different triggers of mind perception have an independent or interactive effect on attitudes and performance in human-robot interaction. We examine this question by manipulating agent appearance (human vs. robot) and behavior (reliable vs. random) within the same paradigm and examine how congruent (human/reliable vs. robot/random) versus incongruent (human/random vs. robot/reliable) combinations of these triggers affect performance (i.e., gaze following) and attitudes (i.e., agent ratings) in human-robot interaction. The results show that both appearance and behavior affect human-robot interaction but that the two triggers seem to operate in isolation, with appearance more strongly impacting attitudes, and behavior more strongly affecting performance. The implications of these findings for human-robot interaction are discussed.

Evacuation simulation using Hybrid Space Discretisation and Application to Large Underground Rail Tunnel Station

NASA Astrophysics Data System (ADS)

Chooramun, N.; Lawrence, P. J.; Galea, E. R.

2017-08-01

In all evacuation simulation tools, the space through which agents navigate and interact is represented by one the following methods, namely Coarse regions, Fine nodes and Continuous regions. Each of the spatial representation methods has its benefits and limitations. For instance, the Coarse approach allows simulations to be processed very rapidly, but is unable to represent the interactions of the agents from an individual perspective; the Continuous approach provides a detailed representation of agent movement and interaction but suffers from relatively poor computational performance. The Fine nodal approach presents a compromise between the Continuous and Coarse approaches such that it allows agent interaction to be modelled while providing good computational performance. Our approach for representing space in an evacuation simulation tool differs such that it allows evacuation simulations to be run using a combination of Coarse regions, Fine nodes and Continuous regions. This approach, which we call Hybrid Spatial Discretisation (HSD), is implemented within the buildingEXODUS evacuation simulation software. The HSD incorporates the benefits of each of the spatial representation methods whilst providing an optimal environment for representing agent movement and interaction. In this work, we demonstrate the effectiveness of the HSD through its application to a moderately large case comprising of an underground rail tunnel station with a population of 2,000 agents.

I Reach Faster When I See You Look: Gaze Effects in Human-Human and Human-Robot Face-to-Face Cooperation.

PubMed

Boucher, Jean-David; Pattacini, Ugo; Lelong, Amelie; Bailly, Gerrard; Elisei, Frederic; Fagel, Sascha; Dominey, Peter Ford; Ventre-Dominey, Jocelyne

2012-01-01

Human-human interaction in natural environments relies on a variety of perceptual cues. Humanoid robots are becoming increasingly refined in their sensorimotor capabilities, and thus should now be able to manipulate and exploit these social cues in cooperation with their human partners. Previous studies have demonstrated that people follow human and robot gaze, and that it can help them to cope with spatially ambiguous language. Our goal is to extend these findings into the domain of action, to determine how human and robot gaze can influence the speed and accuracy of human action. We report on results from a human-human cooperation experiment demonstrating that an agent's vision of her/his partner's gaze can significantly improve that agent's performance in a cooperative task. We then implement a heuristic capability to generate such gaze cues by a humanoid robot that engages in the same cooperative interaction. The subsequent human-robot experiments demonstrate that a human agent can indeed exploit the predictive gaze of their robot partner in a cooperative task. This allows us to render the humanoid robot more human-like in its ability to communicate with humans. The long term objectives of the work are thus to identify social cooperation cues, and to validate their pertinence through implementation in a cooperative robot. The current research provides the robot with the capability to produce appropriate speech and gaze cues in the context of human-robot cooperation tasks. Gaze is manipulated in three conditions: Full gaze (coordinated eye and head), eyes hidden with sunglasses, and head fixed. We demonstrate the pertinence of these cues in terms of statistical measures of action times for humans in the context of a cooperative task, as gaze significantly facilitates cooperation as measured by human response times.

Mesoscopic Effects in an Agent-Based Bargaining Model in Regular Lattices

PubMed Central

Poza, David J.; Santos, José I.; Galán, José M.; López-Paredes, Adolfo

2011-01-01

The effect of spatial structure has been proved very relevant in repeated games. In this work we propose an agent based model where a fixed finite population of tagged agents play iteratively the Nash demand game in a regular lattice. The model extends the multiagent bargaining model by Axtell, Epstein and Young [1] modifying the assumption of global interaction. Each agent is endowed with a memory and plays the best reply against the opponent's most frequent demand. We focus our analysis on the transient dynamics of the system, studying by computer simulation the set of states in which the system spends a considerable fraction of the time. The results show that all the possible persistent regimes in the global interaction model can also be observed in this spatial version. We also find that the mesoscopic properties of the interaction networks that the spatial distribution induces in the model have a significant impact on the diffusion of strategies, and can lead to new persistent regimes different from those found in previous research. In particular, community structure in the intratype interaction networks may cause that communities reach different persistent regimes as a consequence of the hindering diffusion effect of fluctuating agents at their borders. PMID:21408019

Mesoscopic effects in an agent-based bargaining model in regular lattices.

PubMed

Poza, David J; Santos, José I; Galán, José M; López-Paredes, Adolfo

2011-03-09

The effect of spatial structure has been proved very relevant in repeated games. In this work we propose an agent based model where a fixed finite population of tagged agents play iteratively the Nash demand game in a regular lattice. The model extends the multiagent bargaining model by Axtell, Epstein and Young modifying the assumption of global interaction. Each agent is endowed with a memory and plays the best reply against the opponent's most frequent demand. We focus our analysis on the transient dynamics of the system, studying by computer simulation the set of states in which the system spends a considerable fraction of the time. The results show that all the possible persistent regimes in the global interaction model can also be observed in this spatial version. We also find that the mesoscopic properties of the interaction networks that the spatial distribution induces in the model have a significant impact on the diffusion of strategies, and can lead to new persistent regimes different from those found in previous research. In particular, community structure in the intratype interaction networks may cause that communities reach different persistent regimes as a consequence of the hindering diffusion effect of fluctuating agents at their borders.

A Framework to Describe, Analyze and Generate Interactive Motor Behaviors

PubMed Central

Jarrassé, Nathanaël; Charalambous, Themistoklis; Burdet, Etienne

2012-01-01

While motor interaction between a robot and a human, or between humans, has important implications for society as well as promising applications, little research has been devoted to its investigation. In particular, it is important to understand the different ways two agents can interact and generate suitable interactive behaviors. Towards this end, this paper introduces a framework for the description and implementation of interactive behaviors of two agents performing a joint motor task. A taxonomy of interactive behaviors is introduced, which can classify tasks and cost functions that represent the way each agent interacts. The role of an agent interacting during a motor task can be directly explained from the cost function this agent is minimizing and the task constraints. The novel framework is used to interpret and classify previous works on human-robot motor interaction. Its implementation power is demonstrated by simulating representative interactions of two humans. It also enables us to interpret and explain the role distribution and switching between roles when performing joint motor tasks. PMID:23226231

A framework to describe, analyze and generate interactive motor behaviors.

PubMed

Jarrassé, Nathanaël; Charalambous, Themistoklis; Burdet, Etienne

2012-01-01

While motor interaction between a robot and a human, or between humans, has important implications for society as well as promising applications, little research has been devoted to its investigation. In particular, it is important to understand the different ways two agents can interact and generate suitable interactive behaviors. Towards this end, this paper introduces a framework for the description and implementation of interactive behaviors of two agents performing a joint motor task. A taxonomy of interactive behaviors is introduced, which can classify tasks and cost functions that represent the way each agent interacts. The role of an agent interacting during a motor task can be directly explained from the cost function this agent is minimizing and the task constraints. The novel framework is used to interpret and classify previous works on human-robot motor interaction. Its implementation power is demonstrated by simulating representative interactions of two humans. It also enables us to interpret and explain the role distribution and switching between roles when performing joint motor tasks.

Demography-based adaptive network model reproduces the spatial organization of human linguistic groups

NASA Astrophysics Data System (ADS)

Capitán, José A.; Manrubia, Susanna

2015-12-01

The distribution of human linguistic groups presents a number of interesting and nontrivial patterns. The distributions of the number of speakers per language and the area each group covers follow log-normal distributions, while population and area fulfill an allometric relationship. The topology of networks of spatial contacts between different linguistic groups has been recently characterized, showing atypical properties of the degree distribution and clustering, among others. Human demography, spatial conflicts, and the construction of networks of contacts between linguistic groups are mutually dependent processes. Here we introduce an adaptive network model that takes all of them into account and successfully reproduces, using only four model parameters, not only those features of linguistic groups already described in the literature, but also correlations between demographic and topological properties uncovered in this work. Besides their relevance when modeling and understanding processes related to human biogeography, our adaptive network model admits a number of generalizations that broaden its scope and make it suitable to represent interactions between agents based on population dynamics and competition for space.

Demography-based adaptive network model reproduces the spatial organization of human linguistic groups.

PubMed

Capitán, José A; Manrubia, Susanna

2015-12-01

The distribution of human linguistic groups presents a number of interesting and nontrivial patterns. The distributions of the number of speakers per language and the area each group covers follow log-normal distributions, while population and area fulfill an allometric relationship. The topology of networks of spatial contacts between different linguistic groups has been recently characterized, showing atypical properties of the degree distribution and clustering, among others. Human demography, spatial conflicts, and the construction of networks of contacts between linguistic groups are mutually dependent processes. Here we introduce an adaptive network model that takes all of them into account and successfully reproduces, using only four model parameters, not only those features of linguistic groups already described in the literature, but also correlations between demographic and topological properties uncovered in this work. Besides their relevance when modeling and understanding processes related to human biogeography, our adaptive network model admits a number of generalizations that broaden its scope and make it suitable to represent interactions between agents based on population dynamics and competition for space.

A Microfluidics and Agent-Based Modeling Framework for Investigating Spatial Organization in Bacterial Colonies: The Case of Pseudomonas Aeruginosa and H1-Type VI Secretion Interactions.

PubMed

Wilmoth, Jared L; Doak, Peter W; Timm, Andrea; Halsted, Michelle; Anderson, John D; Ginovart, Marta; Prats, Clara; Portell, Xavier; Retterer, Scott T; Fuentes-Cabrera, Miguel

2018-01-01

The factors leading to changes in the organization of microbial assemblages at fine spatial scales are not well characterized or understood. However, they are expected to guide the succession of community development and function toward specific outcomes that could impact human health and the environment. In this study, we put forward a combined experimental and agent-based modeling framework and use it to interpret unique spatial organization patterns of H1-Type VI secretion system (T6SS) mutants of P . aeruginosa under spatial confinement. We find that key parameters, such as T6SS-mediated cell contact and lysis, spatial localization, relative species abundance, cell density and local concentrations of growth substrates and metabolites are influenced by spatial confinement. The model, written in the accessible programming language NetLogo, can be adapted to a variety of biological systems of interest and used to simulate experiments across a broad parameter space. It was implemented and run in a high-throughput mode by deploying it across multiple CPUs, with each simulation representing an individual well within a high-throughput microwell array experimental platform. The microfluidics and agent-based modeling framework we present in this paper provides an effective means by which to connect experimental studies in microbiology to model development. The work demonstrates progress in coupling experimental results to simulation while also highlighting potential sources of discrepancies between real-world experiments and idealized models.

A Microfluidics and Agent-Based Modeling Framework for Investigating Spatial Organization in Bacterial Colonies: The Case of Pseudomonas Aeruginosa and H1-Type VI Secretion Interactions

PubMed Central

Wilmoth, Jared L.; Doak, Peter W.; Timm, Andrea; Halsted, Michelle; Anderson, John D.; Ginovart, Marta; Prats, Clara; Portell, Xavier; Retterer, Scott T.; Fuentes-Cabrera, Miguel

2018-01-01

The factors leading to changes in the organization of microbial assemblages at fine spatial scales are not well characterized or understood. However, they are expected to guide the succession of community development and function toward specific outcomes that could impact human health and the environment. In this study, we put forward a combined experimental and agent-based modeling framework and use it to interpret unique spatial organization patterns of H1-Type VI secretion system (T6SS) mutants of P. aeruginosa under spatial confinement. We find that key parameters, such as T6SS-mediated cell contact and lysis, spatial localization, relative species abundance, cell density and local concentrations of growth substrates and metabolites are influenced by spatial confinement. The model, written in the accessible programming language NetLogo, can be adapted to a variety of biological systems of interest and used to simulate experiments across a broad parameter space. It was implemented and run in a high-throughput mode by deploying it across multiple CPUs, with each simulation representing an individual well within a high-throughput microwell array experimental platform. The microfluidics and agent-based modeling framework we present in this paper provides an effective means by which to connect experimental studies in microbiology to model development. The work demonstrates progress in coupling experimental results to simulation while also highlighting potential sources of discrepancies between real-world experiments and idealized models. PMID:29467721

Exploiting Human Resource Requirements to Infer Human Movement Patterns for Use in Modelling Disease Transmission Systems: An Example from Eastern Province, Zambia.

PubMed

Alderton, Simon; Noble, Jason; Schaten, Kathrin; Welburn, Susan C; Atkinson, Peter M

2015-01-01

In this research, an agent-based model (ABM) was developed to generate human movement routes between homes and water resources in a rural setting, given commonly available geospatial datasets on population distribution, land cover and landscape resources. ABMs are an object-oriented computational approach to modelling a system, focusing on the interactions of autonomous agents, and aiming to assess the impact of these agents and their interactions on the system as a whole. An A* pathfinding algorithm was implemented to produce walking routes, given data on the terrain in the area. A* is an extension of Dijkstra's algorithm with an enhanced time performance through the use of heuristics. In this example, it was possible to impute daily activity movement patterns to the water resource for all villages in a 75 km long study transect across the Luangwa Valley, Zambia, and the simulated human movements were statistically similar to empirical observations on travel times to the water resource (Chi-squared, 95% confidence interval). This indicates that it is possible to produce realistic data regarding human movements without costly measurement as is commonly achieved, for example, through GPS, or retrospective or real-time diaries. The approach is transferable between different geographical locations, and the product can be useful in providing an insight into human movement patterns, and therefore has use in many human exposure-related applications, specifically epidemiological research in rural areas, where spatial heterogeneity in the disease landscape, and space-time proximity of individuals, can play a crucial role in disease spread.

Visual analytics of geo-social interaction patterns for epidemic control.

PubMed

Luo, Wei

2016-08-10

Human interaction and population mobility determine the spatio-temporal course of the spread of an airborne disease. This research views such spreads as geo-social interaction problems, because population mobility connects different groups of people over geographical locations via which the viruses transmit. Previous research argued that geo-social interaction patterns identified from population movement data can provide great potential in designing effective pandemic mitigation. However, little work has been done to examine the effectiveness of designing control strategies taking into account geo-social interaction patterns. To address this gap, this research proposes a new framework for effective disease control; specifically this framework proposes that disease control strategies should start from identifying geo-social interaction patterns, designing effective control measures accordingly, and evaluating the efficacy of different control measures. This framework is used to structure design of a new visual analytic tool that consists of three components: a reorderable matrix for geo-social mixing patterns, agent-based epidemic models, and combined visualization methods. With real world human interaction data in a French primary school as a proof of concept, this research compares the efficacy of vaccination strategies between the spatial-social interaction patterns and the whole areas. The simulation results show that locally targeted vaccination has the potential to keep infection to a small number and prevent spread to other regions. At some small probability, the local control strategies will fail; in these cases other control strategies will be needed. This research further explores the impact of varying spatial-social scales on the success of local vaccination strategies. The results show that a proper spatial-social scale can help achieve the best control efficacy with a limited number of vaccines. The case study shows how GS-EpiViz does support the design and testing of advanced control scenarios in airborne disease (e.g., influenza). The geo-social patterns identified through exploring human interaction data can help target critical individuals, locations, and clusters of locations for disease control purposes. The varying spatial-social scales can help geographically and socially prioritize limited resources (e.g., vaccines).

Land Use Change on Household Farms in the Ecuadorian Amazon: Design and Implementation of an Agent-Based Model.

PubMed

Mena, Carlos F; Walsh, Stephen J; Frizzelle, Brian G; Xiaozheng, Yao; Malanson, George P

2011-01-01

This paper describes the design and implementation of an Agent-Based Model (ABM) used to simulate land use change on household farms in the Northern Ecuadorian Amazon (NEA). The ABM simulates decision-making processes at the household level that is examined through a longitudinal, socio-economic and demographic survey that was conducted in 1990 and 1999. Geographic Information Systems (GIS) are used to establish spatial relationships between farms and their environment, while classified Landsat Thematic Mapper (TM) imagery is used to set initial land use/land cover conditions for the spatial simulation, assess from-to land use/land cover change patterns, and describe trajectories of land use change at the farm and landscape levels. Results from prior studies in the NEA provide insights into the key social and ecological variables, describe human behavioral functions, and examine population-environment interactions that are linked to deforestation and agricultural extensification, population migration, and demographic change. Within the architecture of the model, agents are classified as active or passive. The model comprises four modules, i.e., initialization, demography, agriculture, and migration that operate individually, but are linked through key household processes. The main outputs of the model include a spatially-explicit representation of the land use/land cover on survey and non-survey farms and at the landscape level for each annual time-step, as well as simulated socio-economic and demographic characteristics of households and communities. The work describes the design and implementation of the model and how population-environment interactions can be addressed in a frontier setting. The paper contributes to land change science by examining important pattern-process relations, advocating a spatial modeling approach that is capable of synthesizing fundamental relationships at the farm level, and links people and environment in complex ways.

Pedagogical Agents as Learning Companions: The Impact of Agent Emotion and Gender

ERIC Educational Resources Information Center

Kim, Yanghee; Baylor, A. L.; Shen, E.

2007-01-01

The potential of emotional interaction between human and computer has recently interested researchers in human-computer interaction. The instructional impact of this interaction in learning environments has not been established, however. This study examined the impact of emotion and gender of a pedagogical agent as a learning companion (PAL) on…

Agent Based Modeling of Human Gut Microbiome Interactions and Perturbations.

PubMed

Shashkova, Tatiana; Popenko, Anna; Tyakht, Alexander; Peskov, Kirill; Kosinsky, Yuri; Bogolubsky, Lev; Raigorodskii, Andrei; Ischenko, Dmitry; Alexeev, Dmitry; Govorun, Vadim

2016-01-01

Intestinal microbiota plays an important role in the human health. It is involved in the digestion and protects the host against external pathogens. Examination of the intestinal microbiome interactions is required for understanding of the community influence on host health. Studies of the microbiome can provide insight on methods of improving health, including specific clinical procedures for individual microbial community composition modification and microbiota correction by colonizing with new bacterial species or dietary changes. In this work we report an agent-based model of interactions between two bacterial species and between species and the gut. The model is based on reactions describing bacterial fermentation of polysaccharides to acetate and propionate and fermentation of acetate to butyrate. Antibiotic treatment was chosen as disturbance factor and used to investigate stability of the system. System recovery after antibiotic treatment was analyzed as dependence on quantity of feedback interactions inside the community, therapy duration and amount of antibiotics. Bacterial species are known to mutate and acquire resistance to the antibiotics. The ability to mutate was considered to be a stochastic process, under this suggestion ratio of sensitive to resistant bacteria was calculated during antibiotic therapy and recovery. The model confirms a hypothesis of feedbacks mechanisms necessity for providing functionality and stability of the system after disturbance. High fraction of bacterial community was shown to mutate during antibiotic treatment, though sensitive strains could become dominating after recovery. The recovery of sensitive strains is explained by fitness cost of the resistance. The model demonstrates not only quantitative dynamics of bacterial species, but also gives an ability to observe the emergent spatial structure and its alteration, depending on various feedback mechanisms. Visual version of the model shows that spatial structure is a key factor, which helps bacteria to survive and to adapt to changed environmental conditions.

Modeling agent's preferences by its designer's social value orientation

NASA Astrophysics Data System (ADS)

Zuckerman, Inon; Cheng, Kan-Leung; Nau, Dana S.

2018-03-01

Human social preferences have been shown to play an important role in many areas of decision-making. There is evidence from the social science literature that human preferences in interpersonal interactions depend partly on a measurable personality trait called, Social Value Orientation (SVO). Automated agents are often written by humans to serve as their delegates when interacting with other agents. Thus, one might expect an agent's behaviour to be influenced by the SVO of its human designer. With that in mind, we present the following: first, we explore, discuss and provide a solution to the question of how SVO tests that were designed for humans can be used to evaluate agents' social preferences. Second, we show that in our example domain there is a medium-high positive correlation between the social preferences of agents and their human designers. Third, we exemplify how the SVO information of the designer can be used to improve the performance of some other agents playing against those agents, and lastly, we develop and exemplify the behavioural signature SVO model which allows us to better predict performances when interactions are repeated and behaviour is adapted.

A Microfluidics and Agent-Based Modeling Framework for Investigating Spatial Organization in Bacterial Colonies: The Case of Pseudomonas Aeruginosa and H1-Type VI Secretion Interactions

DOE PAGES

Wilmoth, Jared L.; Doak, Peter W.; Timm, Andrea; ...

2018-02-06

The factors leading to changes in the organization of microbial assemblages at fine spatial scales are not well characterized or understood. However, they are expected to guide the succession of community development and function toward specific outcomes that could impact human health and the environment. In this study, we put forward a combined experimental and agent-based modeling framework and use it to interpret unique spatial organization patterns of H1-Type VI secretion system (T6SS) mutants of P. aeruginosa under spatial confinement. We find that key parameters, such as T6SS-mediated cell contact and lysis, spatial localization, relative species abundance, cell density andmore » local concentrations of growth substrates and metabolites are influenced by spatial confinement. The model, written in the accessible programming language NetLogo, can be adapted to a variety of biological systems of interest and used to simulate experiments across a broad parameter space. It was implemented and run in a high-throughput mode by deploying it across multiple CPUs, with each simulation representing an individual well within a high-throughput microwell array experimental platform. The microfluidics and agent-based modeling framework we present in this paper provides an effective means by which to connect experimental studies in microbiology to model development. The work demonstrates progress in coupling experimental results to simulation while also highlighting potential sources of discrepancies between real-world experiments and idealized models.« less

A Microfluidics and Agent-Based Modeling Framework for Investigating Spatial Organization in Bacterial Colonies: The Case of Pseudomonas Aeruginosa and H1-Type VI Secretion Interactions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wilmoth, Jared L.; Doak, Peter W.; Timm, Andrea

The factors leading to changes in the organization of microbial assemblages at fine spatial scales are not well characterized or understood. However, they are expected to guide the succession of community development and function toward specific outcomes that could impact human health and the environment. In this study, we put forward a combined experimental and agent-based modeling framework and use it to interpret unique spatial organization patterns of H1-Type VI secretion system (T6SS) mutants of P. aeruginosa under spatial confinement. We find that key parameters, such as T6SS-mediated cell contact and lysis, spatial localization, relative species abundance, cell density andmore » local concentrations of growth substrates and metabolites are influenced by spatial confinement. The model, written in the accessible programming language NetLogo, can be adapted to a variety of biological systems of interest and used to simulate experiments across a broad parameter space. It was implemented and run in a high-throughput mode by deploying it across multiple CPUs, with each simulation representing an individual well within a high-throughput microwell array experimental platform. The microfluidics and agent-based modeling framework we present in this paper provides an effective means by which to connect experimental studies in microbiology to model development. The work demonstrates progress in coupling experimental results to simulation while also highlighting potential sources of discrepancies between real-world experiments and idealized models.« less

Cooperation in Human-Agent Systems to Support Resilience: A Microworld Experiment.

PubMed

Chiou, Erin K; Lee, John D

2016-09-01

This study uses a dyadic approach to understand human-agent cooperation and system resilience. Increasingly capable technology fundamentally changes human-machine relationships. Rather than reliance on or compliance with more or less reliable automation, we investigate interaction strategies with more or less cooperative agents. A joint-task microworld scenario was developed to explore the effects of agent cooperation on participant cooperation and system resilience. To assess the effects of agent cooperation on participant cooperation, 36 people coordinated with a more or less cooperative agent by requesting resources and responding to requests for resources in a dynamic task environment. Another 36 people were recruited to assess effects following a perturbation in their own hospital. Experiment 1 shows people reciprocated the cooperative behaviors of the agents; a low-cooperation agent led to less effective interactions and less resource sharing, whereas a high-cooperation agent led to more effective interactions and greater resource sharing. Experiment 2 shows that an initial fast-tempo perturbation undermined proactive cooperation-people tended to not request resources. However, the initial fast tempo had little effect on reactive cooperation-people tended to accept resource requests according to cooperation level. This study complements the supervisory control perspective of human-automation interaction by considering interdependence and cooperation rather than the more common focus on reliability and reliance. The cooperativeness of automated agents can influence the cooperativeness of human agents. Design and evaluation for resilience in teams involving increasingly autonomous agents should consider the cooperative behaviors of these agents. © 2016, Human Factors and Ergonomics Society.

Evolutionary Agent-Based Simulation of the Introduction of New Technologies in Air Traffic Management

NASA Technical Reports Server (NTRS)

Yliniemi, Logan; Agogino, Adrian K.; Tumer, Kagan

2014-01-01

Accurate simulation of the effects of integrating new technologies into a complex system is critical to the modernization of our antiquated air traffic system, where there exist many layers of interacting procedures, controls, and automation all designed to cooperate with human operators. Additions of even simple new technologies may result in unexpected emergent behavior due to complex human/ machine interactions. One approach is to create high-fidelity human models coming from the field of human factors that can simulate a rich set of behaviors. However, such models are difficult to produce, especially to show unexpected emergent behavior coming from many human operators interacting simultaneously within a complex system. Instead of engineering complex human models, we directly model the emergent behavior by evolving goal directed agents, representing human users. Using evolution we can predict how the agent representing the human user reacts given his/her goals. In this paradigm, each autonomous agent in a system pursues individual goals, and the behavior of the system emerges from the interactions, foreseen or unforeseen, between the agents/actors. We show that this method reflects the integration of new technologies in a historical case, and apply the same methodology for a possible future technology.

A real-time architecture for time-aware agents.

PubMed

Prouskas, Konstantinos-Vassileios; Pitt, Jeremy V

2004-06-01

This paper describes the specification and implementation of a new three-layer time-aware agent architecture. This architecture is designed for applications and environments where societies of humans and agents play equally active roles, but interact and operate in completely different time frames. The architecture consists of three layers: the April real-time run-time (ART) layer, the time aware layer (TAL), and the application agents layer (AAL). The ART layer forms the underlying real-time agent platform. An original online, real-time, dynamic priority-based scheduling algorithm is described for scheduling the computation time of agent processes, and it is shown that the algorithm's O(n) complexity and scalable performance are sufficient for application in real-time domains. The TAL layer forms an abstraction layer through which human and agent interactions are temporally unified, that is, handled in a common way irrespective of their temporal representation and scale. A novel O(n2) interaction scheduling algorithm is described for predicting and guaranteeing interactions' initiation and completion times. The time-aware predicting component of a workflow management system is also presented as an instance of the AAL layer. The described time-aware architecture addresses two key challenges in enabling agents to be effectively configured and applied in environments where humans and agents play equally active roles. It provides flexibility and adaptability in its real-time mechanisms while placing them under direct agent control, and it temporally unifies human and agent interactions.

Almost human: Anthropomorphism increases trust resilience in cognitive agents.

PubMed

de Visser, Ewart J; Monfort, Samuel S; McKendrick, Ryan; Smith, Melissa A B; McKnight, Patrick E; Krueger, Frank; Parasuraman, Raja

2016-09-01

We interact daily with computers that appear and behave like humans. Some researchers propose that people apply the same social norms to computers as they do to humans, suggesting that social psychological knowledge can be applied to our interactions with computers. In contrast, theories of human–automation interaction postulate that humans respond to machines in unique and specific ways. We believe that anthropomorphism—the degree to which an agent exhibits human characteristics—is the critical variable that may resolve this apparent contradiction across the formation, violation, and repair stages of trust. Three experiments were designed to examine these opposing viewpoints by varying the appearance and behavior of automated agents. Participants received advice that deteriorated gradually in reliability from a computer, avatar, or human agent. Our results showed (a) that anthropomorphic agents were associated with greater trust resilience , a higher resistance to breakdowns in trust; (b) that these effects were magnified by greater uncertainty; and c) that incorporating human-like trust repair behavior largely erased differences between the agents. Automation anthropomorphism is therefore a critical variable that should be carefully incorporated into any general theory of human–agent trust as well as novel automation design. PsycINFO Database Record (c) 2016 APA, all rights reserved

Learning by Communicating in Natural Language with Conversational Agents

ERIC Educational Resources Information Center

Graesser, Arthur; Li, Haiying; Forsyth, Carol

2014-01-01

Learning is facilitated by conversational interactions both with human tutors and with computer agents that simulate human tutoring and ideal pedagogical strategies. In this article, we describe some intelligent tutoring systems (e.g., AutoTutor) in which agents interact with students in natural language while being sensitive to their cognitive…

An agent-based model for water management and planning in the Lake Naivasha basin, Kenya

NASA Astrophysics Data System (ADS)

van Oel, Pieter; Mulatu, Dawit; Odongo, Vincent; Onyando, Japheth; Becht, Robert; van der Veen, Anne

2013-04-01

A variety of human and natural processes influence the ecological and economic state of the Lake Naivasha basin. The ecological wealth and recent economic developments in the area are strongly connected to Lake Naivasha which supports a rich variety of flora, mammal and bird species. Many human activities depend on clean freshwater from the lake whereas recently the freshwater availability of good quality is seriously influenced by water abstractions and the use of fertilizers in agriculture. Management alternatives include those aiming at limiting water abstractions and fertilizer use. A possible way to achieve reduced use of water and fertilizers is the introduction of Payment for Environmental Services (PES) schemes. As the Lake Naivasha basin and its population have experienced increasing pressures various disputes and disagreements have arisen about the processes responsible for the problems experienced, and the effectively of management alternatives. Beside conflicts of interest and disagreements on responsibilities there are serious factual disagreements. To share scientific knowledge on the effects of the socio-ecological system processes on the Lake Naivasha basin, tools may be used that expose information at temporal and spatial scales that are meaningful to stakeholders. In this study we use a spatially-explicit agent-based modelling (ABM) approach to depict the interactions between socio-economic and natural subsystems for supporting a more sustainable governance of the river basin resources. Agents consider alternative livelihood strategies and decide to go for the one they perceive as likely to be most profitable. Agents may predict and sense the availability of resources and also can observe economic performance achieved by neighbouring agents. Results are presented at the basin and subbasin level to provide relevant knowledge to Water Resources Users Associations which are important collective forums for water management through which PES schemes are managed.

Why we interact: on the functional role of the striatum in the subjective experience of social interaction.

PubMed

Pfeiffer, Ulrich J; Schilbach, Leonhard; Timmermans, Bert; Kuzmanovic, Bojana; Georgescu, Alexandra L; Bente, Gary; Vogeley, Kai

2014-11-01

There is ample evidence that human primates strive for social contact and experience interactions with conspecifics as intrinsically rewarding. Focusing on gaze behavior as a crucial means of human interaction, this study employed a unique combination of neuroimaging, eye-tracking, and computer-animated virtual agents to assess the neural mechanisms underlying this component of behavior. In the interaction task, participants believed that during each interaction the agent's gaze behavior could either be controlled by another participant or by a computer program. Their task was to indicate whether they experienced a given interaction as an interaction with another human participant or the computer program based on the agent's reaction. Unbeknownst to them, the agent was always controlled by a computer to enable a systematic manipulation of gaze reactions by varying the degree to which the agent engaged in joint attention. This allowed creating a tool to distinguish neural activity underlying the subjective experience of being engaged in social and non-social interaction. In contrast to previous research, this allows measuring neural activity while participants experience active engagement in real-time social interactions. Results demonstrate that gaze-based interactions with a perceived human partner are associated with activity in the ventral striatum, a core component of reward-related neurocircuitry. In contrast, interactions with a computer-driven agent activate attention networks. Comparisons of neural activity during interaction with behaviorally naïve and explicitly cooperative partners demonstrate different temporal dynamics of the reward system and indicate that the mere experience of engagement in social interaction is sufficient to recruit this system. Copyright © 2014 Elsevier Inc. All rights reserved.

How do we think machines think? An fMRI study of alleged competition with an artificial intelligence

PubMed Central

Chaminade, Thierry; Rosset, Delphine; Da Fonseca, David; Nazarian, Bruno; Lutcher, Ewald; Cheng, Gordon; Deruelle, Christine

2012-01-01

Mentalizing is defined as the inference of mental states of fellow humans, and is a particularly important skill for social interactions. Here we assessed whether activity in brain areas involved in mentalizing is specific to the processing of mental states or can be generalized to the inference of non-mental states by comparing brain responses during the interaction with an intentional and an artificial agent. Participants were scanned using fMRI during interactive rock-paper-scissors games while believing their opponent was a fellow human (Intentional agent, Int), a humanoid robot endowed with an artificial intelligence (Artificial agent, Art), or a computer playing randomly (Random agent, Rnd). Participants' subjective reports indicated that they adopted different stances against the three agents. The contrast of brain activity during interaction with the artificial and the random agents didn't yield any cluster at the threshold used, suggesting the absence of a reproducible stance when interacting with an artificial intelligence. We probed response to the artificial agent in regions of interest corresponding to clusters found in the contrast between the intentional and the random agents. In the precuneus involved in working memory, the posterior intraparietal suclus, in the control of attention and the dorsolateral prefrontal cortex, in executive functions, brain activity for Art was larger than for Rnd but lower than for Int, supporting the intrinsically engaging nature of social interactions. A similar pattern in the left premotor cortex and anterior intraparietal sulcus involved in motor resonance suggested that participants simulated human, and to a lesser extend humanoid robot actions, when playing the game. Finally, mentalizing regions, the medial prefrontal cortex and right temporoparietal junction, responded to the human only, supporting the specificity of mentalizing areas for interactions with intentional agents. PMID:22586381

How do we think machines think? An fMRI study of alleged competition with an artificial intelligence.

PubMed

Chaminade, Thierry; Rosset, Delphine; Da Fonseca, David; Nazarian, Bruno; Lutcher, Ewald; Cheng, Gordon; Deruelle, Christine

2012-01-01

Mentalizing is defined as the inference of mental states of fellow humans, and is a particularly important skill for social interactions. Here we assessed whether activity in brain areas involved in mentalizing is specific to the processing of mental states or can be generalized to the inference of non-mental states by comparing brain responses during the interaction with an intentional and an artificial agent. Participants were scanned using fMRI during interactive rock-paper-scissors games while believing their opponent was a fellow human (Intentional agent, Int), a humanoid robot endowed with an artificial intelligence (Artificial agent, Art), or a computer playing randomly (Random agent, Rnd). Participants' subjective reports indicated that they adopted different stances against the three agents. The contrast of brain activity during interaction with the artificial and the random agents didn't yield any cluster at the threshold used, suggesting the absence of a reproducible stance when interacting with an artificial intelligence. We probed response to the artificial agent in regions of interest corresponding to clusters found in the contrast between the intentional and the random agents. In the precuneus involved in working memory, the posterior intraparietal suclus, in the control of attention and the dorsolateral prefrontal cortex, in executive functions, brain activity for Art was larger than for Rnd but lower than for Int, supporting the intrinsically engaging nature of social interactions. A similar pattern in the left premotor cortex and anterior intraparietal sulcus involved in motor resonance suggested that participants simulated human, and to a lesser extend humanoid robot actions, when playing the game. Finally, mentalizing regions, the medial prefrontal cortex and right temporoparietal junction, responded to the human only, supporting the specificity of mentalizing areas for interactions with intentional agents.

Land Use Change on Household Farms in the Ecuadorian Amazon: Design and Implementation of an Agent-Based Model

PubMed Central

Mena, Carlos F.; Walsh, Stephen J.; Frizzelle, Brian G.; Xiaozheng, Yao; Malanson, George P.

2010-01-01

This paper describes the design and implementation of an Agent-Based Model (ABM) used to simulate land use change on household farms in the Northern Ecuadorian Amazon (NEA). The ABM simulates decision-making processes at the household level that is examined through a longitudinal, socio-economic and demographic survey that was conducted in 1990 and 1999. Geographic Information Systems (GIS) are used to establish spatial relationships between farms and their environment, while classified Landsat Thematic Mapper (TM) imagery is used to set initial land use/land cover conditions for the spatial simulation, assess from-to land use/land cover change patterns, and describe trajectories of land use change at the farm and landscape levels. Results from prior studies in the NEA provide insights into the key social and ecological variables, describe human behavioral functions, and examine population-environment interactions that are linked to deforestation and agricultural extensification, population migration, and demographic change. Within the architecture of the model, agents are classified as active or passive. The model comprises four modules, i.e., initialization, demography, agriculture, and migration that operate individually, but are linked through key household processes. The main outputs of the model include a spatially-explicit representation of the land use/land cover on survey and non-survey farms and at the landscape level for each annual time-step, as well as simulated socio-economic and demographic characteristics of households and communities. The work describes the design and implementation of the model and how population-environment interactions can be addressed in a frontier setting. The paper contributes to land change science by examining important pattern-process relations, advocating a spatial modeling approach that is capable of synthesizing fundamental relationships at the farm level, and links people and environment in complex ways. PMID:24436501

Embodied artificial agents for understanding human social cognition.

PubMed

Wykowska, Agnieszka; Chaminade, Thierry; Cheng, Gordon

2016-05-05

In this paper, we propose that experimental protocols involving artificial agents, in particular the embodied humanoid robots, provide insightful information regarding social cognitive mechanisms in the human brain. Using artificial agents allows for manipulation and control of various parameters of behaviour, appearance and expressiveness in one of the interaction partners (the artificial agent), and for examining effect of these parameters on the other interaction partner (the human). At the same time, using artificial agents means introducing the presence of artificial, yet human-like, systems into the human social sphere. This allows for testing in a controlled, but ecologically valid, manner human fundamental mechanisms of social cognition both at the behavioural and at the neural level. This paper will review existing literature that reports studies in which artificial embodied agents have been used to study social cognition and will address the question of whether various mechanisms of social cognition (ranging from lower- to higher-order cognitive processes) are evoked by artificial agents to the same extent as by natural agents, humans in particular. Increasing the understanding of how behavioural and neural mechanisms of social cognition respond to artificial anthropomorphic agents provides empirical answers to the conundrum 'What is a social agent?' © 2016 The Authors.

From automata to animate beings: the scope and limits of attributing socialness to artificial agents.

PubMed

Hortensius, Ruud; Cross, Emily S

2018-05-11

Understanding the mechanisms and consequences of attributing socialness to artificial agents has important implications for how we can use technology to lead more productive and fulfilling lives. Here, we integrate recent findings on the factors that shape behavioral and brain mechanisms that support social interactions between humans and artificial agents. We review how visual features of an agent, as well as knowledge factors within the human observer, shape attributions across dimensions of socialness. We explore how anthropomorphism and dehumanization further influence how we perceive and interact with artificial agents. Based on these findings, we argue that the cognitive reconstruction within the human observer is likely to be far more crucial in shaping our interactions with artificial agents than previously thought, while the artificial agent's visual features are possibly of lesser importance. We combine these findings to provide an integrative theoretical account based on the "like me" hypothesis, and discuss the key role played by the Theory-of-Mind network, especially the temporal parietal junction, in the shift from mechanistic to social attributions. We conclude by highlighting outstanding questions on the impact of long-term interactions with artificial agents on the behavioral and brain mechanisms of attributing socialness to these agents. © 2018 New York Academy of Sciences.

Emerging infectious diseases at the beginning of the 21st century.

PubMed

Lashley, Felissa R

2006-01-31

The emergence and re-emergence of infectious diseases involves many interrelated factors. Global interconnectedness continues to increase with international travel and trade; economic, political, and cultural interactions; and human-to-human and animal-to-human interactions. These interactions include the accidental and deliberate sharing of microbial agents and antimicrobial resistance and allow the emergence of new and unrecognized microbial disease agents. As the 21st century begins, already new agents have been identified, and new outbreaks have occurred. Solutions to limiting the spread of emerging infectious diseases will require cooperative efforts among many disciplines and entities worldwide. This article defines emerging infectious diseases, summarizes historical background, and discusses factors that contribute to emergence. Seven agents that have made a significant appearance, particularly in the 21st century, are reviewed, including: Ebola and Marburg hemorrhagic fevers, human monkeypox, bovine spongiform encephalopathy, severe acute respiratory syndrome (SARS), West Nile virus, and avian influenza. The article provides for each agent a brief historical background, case descriptions, and health care implications.

Research on mixed network architecture collaborative application model

NASA Astrophysics Data System (ADS)

Jing, Changfeng; Zhao, Xi'an; Liang, Song

2009-10-01

When facing complex requirements of city development, ever-growing spatial data, rapid development of geographical business and increasing business complexity, collaboration between multiple users and departments is needed urgently, however conventional GIS software (such as Client/Server model or Browser/Server model) are not support this well. Collaborative application is one of the good resolutions. Collaborative application has four main problems to resolve: consistency and co-edit conflict, real-time responsiveness, unconstrained operation, spatial data recoverability. In paper, application model called AMCM is put forward based on agent and multi-level cache. AMCM can be used in mixed network structure and supports distributed collaborative. Agent is an autonomous, interactive, initiative and reactive computing entity in a distributed environment. Agent has been used in many fields such as compute science and automation. Agent brings new methods for cooperation and the access for spatial data. Multi-level cache is a part of full data. It reduces the network load and improves the access and handle of spatial data, especially, in editing the spatial data. With agent technology, we make full use of its characteristics of intelligent for managing the cache and cooperative editing that brings a new method for distributed cooperation and improves the efficiency.

Agent-based modeling approach of immune defense against spores of opportunistic human pathogenic fungi.

PubMed

Tokarski, Christian; Hummert, Sabine; Mech, Franziska; Figge, Marc Thilo; Germerodt, Sebastian; Schroeter, Anja; Schuster, Stefan

2012-01-01

Opportunistic human pathogenic fungi like the ubiquitous fungus Aspergillus fumigatus are a major threat to immunocompromised patients. An impaired immune system renders the body vulnerable to invasive mycoses that often lead to the death of the patient. While the number of immunocompromised patients is rising with medical progress, the process, and dynamics of defense against invaded and ready to germinate fungal conidia are still insufficiently understood. Besides macrophages, neutrophil granulocytes form an important line of defense in that they clear conidia. Live imaging shows the interaction of those phagocytes and conidia as a dynamic process of touching, dragging, and phagocytosis. To unravel strategies of phagocytes on the hunt for conidia an agent-based modeling approach is used, implemented in NetLogo. Different modes of movement of phagocytes are tested regarding their clearing efficiency: random walk, short-term persistence in their recent direction, chemotaxis of chemokines excreted by conidia, and communication between phagocytes. While the short-term persistence hunting strategy turned out to be superior to the simple random walk, following a gradient of chemokines released by conidial agents is even better. The advantage of communication between neutrophilic agents showed a strong dependency on the spatial scale of the focused area and the distribution of the pathogens.

Integration agent-based models and GIS as a virtual urban dynamic laboratory

NASA Astrophysics Data System (ADS)

Chen, Peng; Liu, Miaolong

2007-06-01

Based on the Agent-based Model and spatial data model, a tight-coupling integrating method of GIS and Agent-based Model (ABM) is to be discussed in this paper. The use of object-orientation for both spatial data and spatial process models facilitates their integration, which can allow exploration and explanation of spatial-temporal phenomena such as urban dynamic. In order to better understand how tight coupling might proceed and to evaluate the possible functional and efficiency gains from such a tight coupling, the agent-based model and spatial data model are discussed, and then the relationships affecting spatial data model and agent-based process models interaction. After that, a realistic crowd flow simulation experiment is presented. Using some tools provided by general GIS systems and a few specific programming languages, a new software system integrating GIS and MAS as a virtual laboratory applicable for simulating pedestrian flows in a crowd activity centre has been developed successfully. Under the environment supported by the software system, as an applicable case, a dynamic evolution process of the pedestrian's flows (dispersed process for the spectators) in a crowds' activity center - The Shanghai Stadium has been simulated successfully. At the end of the paper, some new research problems have been pointed out for the future.

A Formal Investigation of Human Spatial Control Skills: Mathematical Formalization, Skill Development, and Skill Assessment

NASA Astrophysics Data System (ADS)

Li, Bin

Spatial control behaviors account for a large proportion of human everyday activities from normal daily tasks, such as reaching for objects, to specialized tasks, such as driving, surgery, or operating equipment. These behaviors involve intensive interactions within internal processes (i.e. cognitive, perceptual, and motor control) and with the physical world. This dissertation builds on a concept of interaction pattern and a hierarchical functional model. Interaction pattern represents a type of behavior synergy that humans coordinates cognitive, perceptual, and motor control processes. It contributes to the construction of the hierarchical functional model that delineates humans spatial control behaviors as the coordination of three functional subsystems: planning, guidance, and tracking/pursuit. This dissertation formalizes and validates these two theories and extends them for the investigation of human spatial control skills encompassing development and assessment. Specifically, this dissertation first presents an overview of studies in human spatial control skills encompassing definition, characteristic, development, and assessment, to provide theoretical evidence for the concept of interaction pattern and the hierarchical functional model. The following, the human experiments for collecting motion and gaze data and techniques to register and classify gaze data, are described. This dissertation then elaborates and mathematically formalizes the hierarchical functional model and the concept of interaction pattern. These theories then enables the construction of a succinct simulation model that can reproduce a variety of human performance with a minimal set of hypotheses. This validates the hierarchical functional model as a normative framework for interpreting human spatial control behaviors. The dissertation then investigates human skill development and captures the emergence of interaction pattern. The final part of the dissertation applies the hierarchical functional model for skill assessment and introduces techniques to capture interaction patterns both from the top down using their geometric features and from the bottom up using their dynamical characteristics. The validity and generality of the skill assessment is illustrated using two the remote-control flight and laparoscopic surgical training experiments.

A Spatial Cognitive Map and a Human-Like Memory Model Dedicated to Pedestrian Navigation in Virtual Urban Environments

NASA Astrophysics Data System (ADS)

Thomas, Romain; Donikian, Stéphane

Many articles dealing with agent navigation in an urban environment involve the use of various heuristics. Among them, one is prevalent: the search of the shortest path between two points. This strategy impairs the realism of the resulting behaviour. Indeed, psychological studies state that such a navigation behaviour is conditioned by the knowledge the subject has of its environment. Furthermore, the path a city dweller can follow may be influenced by many factors like his daily habits, or the path simplicity in term of minimum of direction changes. It appeared interesting to us to investigate how to mimic human navigation behavior with an autonomous agent. The solution we propose relies on an architecture based on a generic model of informed environment, a spatial cognitive map model merged with a human-like memory model, representing the agent's temporal knowledge of the environment, it gained along its experiences of navigation.

Emotional Multiagent Reinforcement Learning in Spatial Social Dilemmas.

PubMed

Yu, Chao; Zhang, Minjie; Ren, Fenghui; Tan, Guozhen

2015-12-01

Social dilemmas have attracted extensive interest in the research of multiagent systems in order to study the emergence of cooperative behaviors among selfish agents. Understanding how agents can achieve cooperation in social dilemmas through learning from local experience is a critical problem that has motivated researchers for decades. This paper investigates the possibility of exploiting emotions in agent learning in order to facilitate the emergence of cooperation in social dilemmas. In particular, the spatial version of social dilemmas is considered to study the impact of local interactions on the emergence of cooperation in the whole system. A double-layered emotional multiagent reinforcement learning framework is proposed to endow agents with internal cognitive and emotional capabilities that can drive these agents to learn cooperative behaviors. Experimental results reveal that various network topologies and agent heterogeneities have significant impacts on agent learning behaviors in the proposed framework, and under certain circumstances, high levels of cooperation can be achieved among the agents.

When Humanoid Robots Become Human-Like Interaction Partners: Corepresentation of Robotic Actions

ERIC Educational Resources Information Center

Stenzel, Anna; Chinellato, Eris; Bou, Maria A. Tirado; del Pobil, Angel P.; Lappe, Markus; Liepelt, Roman

2012-01-01

In human-human interactions, corepresenting a partner's actions is crucial to successfully adjust and coordinate actions with others. Current research suggests that action corepresentation is restricted to interactions between human agents facilitating social interaction with conspecifics. In this study, we investigated whether action…

Evaluation of water security in Jordan using a multi-agent, hydroeconomic model: Initial model results from the Jordan Water Project

NASA Astrophysics Data System (ADS)

Yoon, J.; Klassert, C. J. A.; Lachaut, T.; Selby, P. D.; Knox, S.; Gorelick, S.; Rajsekhar, D.; Tilmant, A.; Avisse, N.; Harou, J. J.; Medellin-Azuara, J.; Gawel, E.; Klauer, B.; Mustafa, D.; Talozi, S.; Sigel, K.; Zhang, H.

2016-12-01

Our work focuses on development of a multi-agent, hydroeconomic model for water policy evaluation in Jordan. Jordan ranks among the most water-scarce countries in the world, a situation exacerbated due to a recent influx of refugees escaping the ongoing civil war in neighboring Syria. The modular, multi-agent model is used to evaluate interventions for enhancing Jordan's water security, integrating biophysical modules that simulate natural and engineered phenomena with human modules that represent behavior at multiple levels of decision making. The hydrologic modules are developed using spatially-distributed groundwater and surface water models, which are translated into compact simulators for efficient integration into the multi-agent model. For the multi-agent model, we explicitly account for human agency at multiple levels of decision making, with agents representing riparian, management, supplier, and water user groups. Human agents are implemented as autonomous entities in the model that make decisions in relation to one another and in response to hydrologic and socioeconomic conditions. The integrated model is programmed in Python using Pynsim, a generalizable, open-source object-oriented software framework for modeling network-based water resource systems. The modeling time periods include historical (2006-2014) and future (present-2050) time spans. For the historical runs, the model performance is validated against historical data for several observations that reflect the interacting dynamics of both the hydrologic and human components of the system. A historical counterfactual scenario is also constructed to isolate and identify the impacts of the recent Syrian civil war and refugee crisis on Jordan's water system. For the future period, model runs are conducted to evaluate potential supply, demand, and institutional interventions over a wide range of plausible climate and socioeconomic scenarios. In addition, model sensitivity analysis is conducted revealing the hydrologic and human aspects of the system that most strongly influence water security outcomes, providing insight into coupled human-water system dynamics as well as priority areas of focus for continued model improvement.

Linking Spatial Structure and Community-Level Biotic Interactions through Cooccurrence and Time Series Modeling of the Human Intestinal Microbiota.

PubMed

de Muinck, Eric J; Lundin, Knut E A; Trosvik, Pål

2017-01-01

The gastrointestinal (GI) microbiome is a densely populated ecosystem where dynamics are determined by interactions between microbial community members, as well as host factors. The spatial organization of this system is thought to be important in human health, yet this aspect of our resident microbiome is still poorly understood. In this study, we report significant spatial structure of the GI microbiota, and we identify general categories of spatial patterning in the distribution of microbial taxa along a healthy human GI tract. We further estimate the biotic interaction structure in the GI microbiota, both through time series and cooccurrence modeling of microbial community data derived from a large number of sequentially collected fecal samples. Comparison of these two approaches showed that species pairs involved in significant negative interactions had strong positive contemporaneous correlations and vice versa, while for species pairs without significant interactions, contemporaneous correlations were distributed around zero. We observed similar patterns when comparing these models to the spatial correlations between taxa identified in the adherent microbiota. This suggests that colocalization of microbial taxon pairs, and thus the spatial organization of the GI microbiota, is driven, at least in part, by direct or indirect biotic interactions. Thus, our study can provide a basis for an ecological interpretation of the biogeography of the human gut. IMPORTANCE The human gut microbiome is the subject of intense study due to its importance in health and disease. The majority of these studies have been based on the analysis of feces. However, little is known about how the microbial composition in fecal samples relates to the spatial distribution of microbial taxa along the gastrointestinal tract. By characterizing the microbial content both in intestinal tissue samples and in fecal samples obtained daily, we provide a conceptual framework for how the spatial structure relates to biotic interactions on the community level. We further describe general categories of spatial distribution patterns and identify taxa conforming to these categories. To our knowledge, this is the first study combining spatial and temporal analyses of the human gut microbiome. This type of analysis can be used for identifying candidate probiotics and designing strategies for clinical intervention.

Agent Interaction with Human Systems in Complex Environments: Requirements for Automating the Function of CapCom in Apollo 17

NASA Technical Reports Server (NTRS)

Clancey, William J.

2003-01-01

A human-centered approach to computer systems design involves reframing analysis in terms of people interacting with each other, not only human-machine interaction. The primary concern is not how people can interact with computers, but how shall we design computers to help people work together? An analysis of astronaut interactions with CapCom on Earth during one traverse of Apollo 17 shows what kind of information was conveyed and what might be automated today. A variety of agent and robotic technologies are proposed that deal with recurrent problems in communication and coordination during the analyzed traverse.

A Formal Investigation of the Organization of Guidance Behavior: Implications for Humans and Autonomous Guidance

NASA Astrophysics Data System (ADS)

Kong, Zhaodan

Guidance behavior generated either by artificial agents or humans has been actively studied in the fields of both robotics and cognitive science. The goals of these two fields are different. The former is the automatic generation of appropriate or even optimal behavior, while the latter is the understanding of the underlying mechanism. Their challenges, though, are closely related, the most important one being the lack of a unified, formal and grounded framework where the guidance behavior can be modeled and studied. This dissertation presents such a framework. In this framework, guidance behavior is analyzed as the closed-loop dynamics of the whole agent-environment system. The resulting dynamics give rise to interaction patterns. The central points of this dissertation are that: first of all, these patterns, which can be explained in terms of symmetries that are inherent to the guidance behavior, provide building blocks for the organization of behavior; second, the existence of these patterns and humans' organization of their guidance behavior based on these patterns are the reasons that humans can generate successful behavior in spite of all the complexities involved in the planning and control. This dissertation first gives an overview of the challenges existing in both scientific endeavors, such as human and animal spatial behavior study, and engineering endeavors, such as autonomous guidance system design. It then lays out the foundation for our formal framework, which states that guidance behavior should be interpreted as the collection of the closed-loop dynamics resulting from the agent's interaction with the environment. The following, illustrated by examples of three different UAVs, shows that the study of the closed-loop dynamics should not be done without the consideration of vehicle dynamics, as is the common practice in some of the studies in both autonomous guidance and human behavior analysis. The framework, the core concepts of which are symmetries and interaction patterns, is then elaborated on with the example of Dubins' vehicle's guidance behavior. The dissertation then describes the details of the agile human guidance experiments using miniature helicopters, the technique that is developed for the analysis of the experimental data and the analysis results. The results confirm that human guidance behavior indeed exhibits invariance as defined by interaction patterns. Subsequently, the behavior in each interaction pattern is investigated using piecewise affine model identification. Combined, the results provide a natural and formal decomposition of the behavior that can be unified under a hierarchical hidden Markov model. By employing the languages of dynamical system and control and by adopting algorithms from system identification and machine learning, the framework presented in this dissertation provides a fertile ground where these different disciplines can meet. It also promises multiple potential directions where future research can be headed.

Robots As Intentional Agents: Using Neuroscientific Methods to Make Robots Appear More Social.

PubMed

Wiese, Eva; Metta, Giorgio; Wykowska, Agnieszka

2017-01-01

Robots are increasingly envisaged as our future cohabitants. However, while considerable progress has been made in recent years in terms of their technological realization, the ability of robots to interact with humans in an intuitive and social way is still quite limited. An important challenge for social robotics is to determine how to design robots that can perceive the user's needs, feelings, and intentions, and adapt to users over a broad range of cognitive abilities. It is conceivable that if robots were able to adequately demonstrate these skills, humans would eventually accept them as social companions. We argue that the best way to achieve this is using a systematic experimental approach based on behavioral and physiological neuroscience methods such as motion/eye-tracking, electroencephalography, or functional near-infrared spectroscopy embedded in interactive human-robot paradigms. This approach requires understanding how humans interact with each other, how they perform tasks together and how they develop feelings of social connection over time, and using these insights to formulate design principles that make social robots attuned to the workings of the human brain. In this review, we put forward the argument that the likelihood of artificial agents being perceived as social companions can be increased by designing them in a way that they are perceived as intentional agents that activate areas in the human brain involved in social-cognitive processing. We first review literature related to social-cognitive processes and mechanisms involved in human-human interactions, and highlight the importance of perceiving others as intentional agents to activate these social brain areas. We then discuss how attribution of intentionality can positively affect human-robot interaction by (a) fostering feelings of social connection, empathy and prosociality, and by (b) enhancing performance on joint human-robot tasks. Lastly, we describe circumstances under which attribution of intentionality to robot agents might be disadvantageous, and discuss challenges associated with designing social robots that are inspired by neuroscientific principles.

Dynamic Simulation of Crime Perpetration and Reporting to Examine Community Intervention Strategies

ERIC Educational Resources Information Center

Yonas, Michael A.; Burke, Jessica G.; Brown, Shawn T.; Borrebach, Jeffrey D.; Garland, Richard; Burke, Donald S.; Grefenstette, John J.

2013-01-01

Objective: To develop a conceptual computational agent-based model (ABM) to explore community-wide versus spatially focused crime reporting interventions to reduce community crime perpetrated by youth. Method: Agents within the model represent individual residents and interact on a two-dimensional grid representing an abstract nonempirically…

Autonomy in robots and other agents.

PubMed

Smithers, T

1997-06-01

The word "autonomous" has become widely used in artificial intelligence, robotics, and, more recently, artificial life and is typically used to qualify types of systems, agents, or robots: we see terms like "autonomous systems," "autonomous agents," and "autonomous robots." Its use in these fields is, however, both weak, with no distinctions being made that are not better and more precisely made with other existing terms, and varied, with no single underlying concept being involved. This ill-disciplined usage contrasts strongly with the use of the same term in other fields such as biology, philosophy, ethics, law, and human rights, for example. In all these quite different areas the concept of autonomy is essentially the same, though the language used and the aspects and issues of concern, of course, differ. In all these cases the underlying notion is one of self-law making and the closely related concept of self-identity. In this paper I argue that the loose and varied use of the term autonomous in artificial intelligence, robotics, and artificial life has effectively robbed these fields of an important concept. A concept essentially the same as we find it in biology, philosophy, ethics, and law, and one that is needed to distinguish a particular kind of agent or robot from those developed and built so far. I suggest that robots and other agents will have to be autonomous, i.e., self-law making, not just self-regulating, if they are to be able effectively to deal with the kinds of environments in which we live and work: environments which have significant large scale spatial and temporal invariant structure, but which also have large amounts of local spatial and temporal dynamic variation and unpredictability, and which lead to the frequent occurrence of previously unexperienced situations for the agents that interact with them.

New approaches in agent-based modeling of complex financial systems

NASA Astrophysics Data System (ADS)

Chen, Ting-Ting; Zheng, Bo; Li, Yan; Jiang, Xiong-Fei

2017-12-01

Agent-based modeling is a powerful simulation technique to understand the collective behavior and microscopic interaction in complex financial systems. Recently, the concept for determining the key parameters of agent-based models from empirical data instead of setting them artificially was suggested. We first review several agent-based models and the new approaches to determine the key model parameters from historical market data. Based on the agents' behaviors with heterogeneous personal preferences and interactions, these models are successful in explaining the microscopic origination of the temporal and spatial correlations of financial markets. We then present a novel paradigm combining big-data analysis with agent-based modeling. Specifically, from internet query and stock market data, we extract the information driving forces and develop an agent-based model to simulate the dynamic behaviors of complex financial systems.

Evolving learning rules and emergence of cooperation in spatial prisoner's dilemma.

PubMed

Moyano, Luis G; Sánchez, Angel

2009-07-07

In the evolutionary Prisoner's dilemma (PD) game, agents play with each other and update their strategies in every generation according to some microscopic dynamical rule. In its spatial version, agents do not play with every other but, instead, interact only with their neighbours, thus mimicking the existing of a social or contact network that defines who interacts with whom. In this work, we explore evolutionary, spatial PD systems consisting of two types of agents, each with a certain update (reproduction, learning) rule. We investigate two different scenarios: in the first case, update rules remain fixed for the entire evolution of the system; in the second case, agents update both strategy and update rule in every generation. We show that in a well-mixed population the evolutionary outcome is always full defection. We subsequently focus on two-strategy competition with nearest-neighbour interactions on the contact network and synchronised update of strategies. Our results show that, for an important range of the parameters of the game, the final state of the system is largely different from that arising from the usual setup of a single, fixed dynamical rule. Furthermore, the results are also very different if update rules are fixed or evolve with the strategies. In these respect, we have studied representative update rules, finding that some of them may become extinct while others prevail. We describe the new and rich variety of final outcomes that arise from this co-evolutionary dynamics. We include examples of other neighbourhoods and asynchronous updating that confirm the robustness of our conclusions. Our results pave the way to an evolutionary rationale for modelling social interactions through game theory with a preferred set of update rules.

Bottom-up modeling approach for the quantitative estimation of parameters in pathogen-host interactions

PubMed Central

Lehnert, Teresa; Timme, Sandra; Pollmächer, Johannes; Hünniger, Kerstin; Kurzai, Oliver; Figge, Marc Thilo

2015-01-01

Opportunistic fungal pathogens can cause bloodstream infection and severe sepsis upon entering the blood stream of the host. The early immune response in human blood comprises the elimination of pathogens by antimicrobial peptides and innate immune cells, such as neutrophils or monocytes. Mathematical modeling is a predictive method to examine these complex processes and to quantify the dynamics of pathogen-host interactions. Since model parameters are often not directly accessible from experiment, their estimation is required by calibrating model predictions with experimental data. Depending on the complexity of the mathematical model, parameter estimation can be associated with excessively high computational costs in terms of run time and memory. We apply a strategy for reliable parameter estimation where different modeling approaches with increasing complexity are used that build on one another. This bottom-up modeling approach is applied to an experimental human whole-blood infection assay for Candida albicans. Aiming for the quantification of the relative impact of different routes of the immune response against this human-pathogenic fungus, we start from a non-spatial state-based model (SBM), because this level of model complexity allows estimating a priori unknown transition rates between various system states by the global optimization method simulated annealing. Building on the non-spatial SBM, an agent-based model (ABM) is implemented that incorporates the migration of interacting cells in three-dimensional space. The ABM takes advantage of estimated parameters from the non-spatial SBM, leading to a decreased dimensionality of the parameter space. This space can be scanned using a local optimization approach, i.e., least-squares error estimation based on an adaptive regular grid search, to predict cell migration parameters that are not accessible in experiment. In the future, spatio-temporal simulations of whole-blood samples may enable timely stratification of sepsis patients by distinguishing hyper-inflammatory from paralytic phases in immune dysregulation. PMID:26150807

Bottom-up modeling approach for the quantitative estimation of parameters in pathogen-host interactions.

PubMed

Lehnert, Teresa; Timme, Sandra; Pollmächer, Johannes; Hünniger, Kerstin; Kurzai, Oliver; Figge, Marc Thilo

2015-01-01

Opportunistic fungal pathogens can cause bloodstream infection and severe sepsis upon entering the blood stream of the host. The early immune response in human blood comprises the elimination of pathogens by antimicrobial peptides and innate immune cells, such as neutrophils or monocytes. Mathematical modeling is a predictive method to examine these complex processes and to quantify the dynamics of pathogen-host interactions. Since model parameters are often not directly accessible from experiment, their estimation is required by calibrating model predictions with experimental data. Depending on the complexity of the mathematical model, parameter estimation can be associated with excessively high computational costs in terms of run time and memory. We apply a strategy for reliable parameter estimation where different modeling approaches with increasing complexity are used that build on one another. This bottom-up modeling approach is applied to an experimental human whole-blood infection assay for Candida albicans. Aiming for the quantification of the relative impact of different routes of the immune response against this human-pathogenic fungus, we start from a non-spatial state-based model (SBM), because this level of model complexity allows estimating a priori unknown transition rates between various system states by the global optimization method simulated annealing. Building on the non-spatial SBM, an agent-based model (ABM) is implemented that incorporates the migration of interacting cells in three-dimensional space. The ABM takes advantage of estimated parameters from the non-spatial SBM, leading to a decreased dimensionality of the parameter space. This space can be scanned using a local optimization approach, i.e., least-squares error estimation based on an adaptive regular grid search, to predict cell migration parameters that are not accessible in experiment. In the future, spatio-temporal simulations of whole-blood samples may enable timely stratification of sepsis patients by distinguishing hyper-inflammatory from paralytic phases in immune dysregulation.

Interactions across spatial scales among forest dieback, fire, and erosion in northern New Mexico landscapes

USGS Publications Warehouse

Allen, Craig D.

2007-01-01

Ecosystem patterns and disturbance processes at one spatial scale often interact with processes at another scale, and the result of such cross-scale interactions can be nonlinear dynamics with thresholds. Examples of cross-scale pattern-process relationships and interactions among forest dieback, fire, and erosion are illustrated from northern New Mexico (USA) landscapes, where long-term studies have recently documented all of these disturbance processes. For example, environmental stress, operating on individual trees, can cause tree death that is amplified by insect mortality agents to propagate to patch and then landscape or even regional-scale forest dieback. Severe drought and unusual warmth in the southwestern USA since the late 1990s apparently exceeded species-specific physiological thresholds for multiple tree species, resulting in substantial vegetation mortality across millions of hectares of woodlands and forests in recent years. Predictions of forest dieback across spatial scales are constrained by uncertainties associated with: limited knowledge of species-specific physiological thresholds; individual and site-specific variation in these mortality thresholds; and positive feedback loops between rapidly-responding insect herbivore populations and their stressed plant hosts, sometimes resulting in nonlinear “pest” outbreak dynamics. Fire behavior also exhibits nonlinearities across spatial scales, illustrated by changes in historic fire regimes where patch-scale grazing disturbance led to regional-scale collapse of surface fire activity and subsequent recent increases in the scale of extreme fire events in New Mexico. Vegetation dieback interacts with fire activity by modifying fuel amounts and configurations at multiple spatial scales. Runoff and erosion processes are also subject to scale-dependent threshold behaviors, exemplified by ecohydrological work in semiarid New Mexico watersheds showing how declines in ground surface cover lead to non-linear increases in bare patch connectivity and thereby accelerated runoff and erosion at hillslope and watershed scales. Vegetation dieback, grazing, and fire can change land surface properties and cross-scale hydrologic connectivities, directly altering ecohydrological patterns of runoff and erosion. The interactions among disturbance processes across spatial scales can be key drivers in ecosystem dynamics, as illustrated by these studies of recent landscape changes in northern New Mexico. To better anticipate and mitigate accelerating human impacts to the planetary ecosystem at all spatial scales, improvements are needed in our conceptual and quantitative understanding of cross-scale interactions among disturbance processes.

Social Intelligence in a Human-Machine Collaboration System

NASA Astrophysics Data System (ADS)

Nakajima, Hiroshi; Morishima, Yasunori; Yamada, Ryota; Brave, Scott; Maldonado, Heidy; Nass, Clifford; Kawaji, Shigeyasu

In this information society of today, it is often argued that it is necessary to create a new way of human-machine interaction. In this paper, an agent with social response capabilities has been developed to achieve this goal. There are two kinds of information that is exchanged by two entities: objective and functional information (e.g., facts, requests, states of matters, etc.) and subjective information (e.g., feelings, sense of relationship, etc.). Traditional interactive systems have been designed to handle the former kind of information. In contrast, in this study social agents handling the latter type of information are presented. The current study focuses on sociality of the agent from the view point of Media Equation theory. This article discusses the definition, importance, and benefits of social intelligence as agent technology and argues that social intelligence has a potential to enhance the user's perception of the system, which in turn can lead to improvements of the system's performance. In order to implement social intelligence in the agent, a mind model has been developed to render affective expressions and personality of the agent. The mind model has been implemented in a human-machine collaborative learning system. One differentiating feature of the collaborative learning system is that it has an agent that performs as a co-learner with which the user interacts during the learning session. The mind model controls the social behaviors of the agent, thus making it possible for the user to have more social interactions with the agent. The experiment with the system suggested that a greater degree of learning was achieved when the students worked with the co-learner agent and that the co-learner agent with the mind model that expressed emotions resulted in a more positive attitude toward the system.

Do infants perceive the social robot Keepon as a communicative partner?

PubMed

Peca, Andreea; Simut, Ramona; Cao, Hoang-Long; Vanderborght, Bram

2016-02-01

This study investigates if infants perceive an unfamiliar agent, such as the robot Keepon, as a social agent after observing an interaction between the robot and a human adult. 23 infants, aged 9-17 month, were exposed, in a first phase, to either a contingent interaction between the active robot and an active human adult, or to an interaction between an active human adult and the non-active robot, followed by a second phase, in which infants were offered the opportunity to initiate a turn-taking interaction with Keepon. The measured variables were: (1) the number of social initiations the infant directed toward the robot, and (2) the number of anticipatory orientations of attention to the agent that follows in the conversation. The results indicate a significant higher level of initiations in the interactive robot condition compared to the non-active robot condition, while the difference between the frequencies of anticipations of turn-taking behaviors was not significant. Copyright © 2015 Elsevier Inc. All rights reserved.

Kinetic Models for Topological Nearest-Neighbor Interactions

NASA Astrophysics Data System (ADS)

Blanchet, Adrien; Degond, Pierre

2017-12-01

We consider systems of agents interacting through topological interactions. These have been shown to play an important part in animal and human behavior. Precisely, the system consists of a finite number of particles characterized by their positions and velocities. At random times a randomly chosen particle, the follower, adopts the velocity of its closest neighbor, the leader. We study the limit of a system size going to infinity and, under the assumption of propagation of chaos, show that the limit kinetic equation is a non-standard spatial diffusion equation for the particle distribution function. We also study the case wherein the particles interact with their K closest neighbors and show that the corresponding kinetic equation is the same. Finally, we prove that these models can be seen as a singular limit of the smooth rank-based model previously studied in Blanchet and Degond (J Stat Phys 163:41-60, 2016). The proofs are based on a combinatorial interpretation of the rank as well as some concentration of measure arguments.

Quantitative Modeling of Human-Environment Interactions in Preindustrial Time

NASA Astrophysics Data System (ADS)

Sommer, Philipp S.; Kaplan, Jed O.

2017-04-01

Quantifying human-environment interactions and anthropogenic influences on the environment prior to the Industrial revolution is essential for understanding the current state of the earth system. This is particularly true for the terrestrial biosphere, but marine ecosystems and even climate were likely modified by human activities centuries to millennia ago. Direct observations are however very sparse in space and time, especially as one considers prehistory. Numerical models are therefore essential to produce a continuous picture of human-environment interactions in the past. Agent-based approaches, while widely applied to quantifying human influence on the environment in localized studies, are unsuitable for global spatial domains and Holocene timescales because of computational demands and large parameter uncertainty. Here we outline a new paradigm for the quantitative modeling of human-environment interactions in preindustrial time that is adapted to the global Holocene. Rather than attempting to simulate agency directly, the model is informed by a suite of characteristics describing those things about society that cannot be predicted on the basis of environment, e.g., diet, presence of agriculture, or range of animals exploited. These categorical data are combined with the properties of the physical environment in coupled human-environment model. The model is, at its core, a dynamic global vegetation model with a module for simulating crop growth that is adapted for preindustrial agriculture. This allows us to simulate yield and calories for feeding both humans and their domesticated animals. We couple this basic caloric availability with a simple demographic model to calculate potential population, and, constrained by labor requirements and land limitations, we create scenarios of land use and land cover on a moderate-resolution grid. We further implement a feedback loop where anthropogenic activities lead to changes in the properties of the physical environment, e.g., through soil erosion.

Rationalizing spatial exploration patterns of wild animals and humans through a temporal discounting framework.

PubMed

Namboodiri, Vijay Mohan K; Levy, Joshua M; Mihalas, Stefan; Sims, David W; Hussain Shuler, Marshall G

2016-08-02

Understanding the exploration patterns of foragers in the wild provides fundamental insight into animal behavior. Recent experimental evidence has demonstrated that path lengths (distances between consecutive turns) taken by foragers are well fitted by a power law distribution. Numerous theoretical contributions have posited that "Lévy random walks"-which can produce power law path length distributions-are optimal for memoryless agents searching a sparse reward landscape. It is unclear, however, whether such a strategy is efficient for cognitively complex agents, from wild animals to humans. Here, we developed a model to explain the emergence of apparent power law path length distributions in animals that can learn about their environments. In our model, the agent's goal during search is to build an internal model of the distribution of rewards in space that takes into account the cost of time to reach distant locations (i.e., temporally discounting rewards). For an agent with such a goal, we find that an optimal model of exploration in fact produces hyperbolic path lengths, which are well approximated by power laws. We then provide support for our model by showing that humans in a laboratory spatial exploration task search space systematically and modify their search patterns under a cost of time. In addition, we find that path length distributions in a large dataset obtained from free-ranging marine vertebrates are well described by our hyperbolic model. Thus, we provide a general theoretical framework for understanding spatial exploration patterns of cognitively complex foragers.

Domain learning naming game for color categorization.

PubMed

Li, Doujie; Fan, Zhongyan; Tang, Wallace K S

2017-01-01

Naming game simulates the evolution of vocabulary in a population of agents. Through pairwise interactions in the games, agents acquire a set of vocabulary in their memory for object naming. The existing model confines to a one-to-one mapping between a name and an object. Focus is usually put onto name consensus in the population rather than knowledge learning in agents, and hence simple learning model is usually adopted. However, the cognition system of human being is much more complex and knowledge is usually presented in a complicated form. Therefore, in this work, we extend the agent learning model and design a new game to incorporate domain learning, which is essential for more complicated form of knowledge. In particular, we demonstrate the evolution of color categorization and naming in a population of agents. We incorporate the human perceptive model into the agents and introduce two new concepts, namely subjective perception and subliminal stimulation, in domain learning. Simulation results show that, even without any supervision or pre-requisition, a consensus of a color naming system can be reached in a population solely via the interactions. Our work confirms the importance of society interactions in color categorization, which is a long debate topic in human cognition. Moreover, our work also demonstrates the possibility of cognitive system development in autonomous intelligent agents.

Domain learning naming game for color categorization

PubMed Central

2017-01-01

Naming game simulates the evolution of vocabulary in a population of agents. Through pairwise interactions in the games, agents acquire a set of vocabulary in their memory for object naming. The existing model confines to a one-to-one mapping between a name and an object. Focus is usually put onto name consensus in the population rather than knowledge learning in agents, and hence simple learning model is usually adopted. However, the cognition system of human being is much more complex and knowledge is usually presented in a complicated form. Therefore, in this work, we extend the agent learning model and design a new game to incorporate domain learning, which is essential for more complicated form of knowledge. In particular, we demonstrate the evolution of color categorization and naming in a population of agents. We incorporate the human perceptive model into the agents and introduce two new concepts, namely subjective perception and subliminal stimulation, in domain learning. Simulation results show that, even without any supervision or pre-requisition, a consensus of a color naming system can be reached in a population solely via the interactions. Our work confirms the importance of society interactions in color categorization, which is a long debate topic in human cognition. Moreover, our work also demonstrates the possibility of cognitive system development in autonomous intelligent agents. PMID:29136661

A unifying framework for quantifying the nature of animal interactions.

PubMed

Potts, Jonathan R; Mokross, Karl; Lewis, Mark A

2014-07-06

Collective phenomena, whereby agent-agent interactions determine spatial patterns, are ubiquitous in the animal kingdom. On the other hand, movement and space use are also greatly influenced by the interactions between animals and their environment. Despite both types of interaction fundamentally influencing animal behaviour, there has hitherto been no unifying framework for the models proposed in both areas. Here, we construct a general method for inferring population-level spatial patterns from underlying individual movement and interaction processes, a key ingredient in building a statistical mechanics for ecological systems. We show that resource selection functions, as well as several examples of collective motion models, arise as special cases of our framework, thus bringing together resource selection analysis and collective animal behaviour into a single theory. In particular, we focus on combining the various mechanistic models of territorial interactions in the literature with step selection functions, by incorporating interactions into the step selection framework and demonstrating how to derive territorial patterns from the resulting models. We demonstrate the efficacy of our model by application to a population of insectivore birds in the Amazon rainforest. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Spatiotemporally synchronized cancer combination therapy using photo-activated nanoparticle drug delivery systems (Conference Presentation)

NASA Astrophysics Data System (ADS)

Hasan, Tayyaba

2016-03-01

This talk will introduce a new nanotechnology platform for cancer combination therapy that utilizes near infrared light activation not only for photodynamic damage but also as an extrinsic mechanism to initiate release of complimentary drugs to suppress dynamic bursts in molecular signaling networks that promote tumor cell survival and treatment escape. The goal is to achieve co-delivery with concomitant activity of photodynamic, molecular inhibitor and chemotherapeutic agents, selectively within the tumor. This approach overcomes challenges in achieving synergistic interactions using sequential drug delivery. Conventional drug delivery is compromised by the differential pharmacokinetics of individual agents and potentially antagonistic effects—such as vascular shutdown by one agent that limits delivery of the second. Here, photodynamic damage—which efficiently kills drug-resistant cells via damage of common proteins involved in drug-resistance (such as anti-apoptosis factors and drug-efflux transporters)—is synchronized spatially and temporally with the photo-initiated release of complimentary agents—to enable full interaction amongst the individual therapies. This spatiotemporal synchronization offers new prospects for exploiting time-sensitive synergistic interactions. Specific implementations of these concepts will be presented in preclinical models of cancer. Strategies to enable molecular-targeting of cancer cells via site-specific attachment of targeting moieties to the outer lipid shell of these nanovehicles will also be discussed. If successful in humans, this new paradigm for synchronized, tumor-focused combination therapy will ultimately supersede the present use of chronic drug injection by increasing efficacy per cycle whilst reducing systemic exposure to toxic drugs.

Intelligent judgements over health risks in a spatial agent-based model.

PubMed

Abdulkareem, Shaheen A; Augustijn, Ellen-Wien; Mustafa, Yaseen T; Filatova, Tatiana

2018-03-20

Millions of people worldwide are exposed to deadly infectious diseases on a regular basis. Breaking news of the Zika outbreak for instance, made it to the main media titles internationally. Perceiving disease risks motivate people to adapt their behavior toward a safer and more protective lifestyle. Computational science is instrumental in exploring patterns of disease spread emerging from many individual decisions and interactions among agents and their environment by means of agent-based models. Yet, current disease models rarely consider simulating dynamics in risk perception and its impact on the adaptive protective behavior. Social sciences offer insights into individual risk perception and corresponding protective actions, while machine learning provides algorithms and methods to capture these learning processes. This article presents an innovative approach to extend agent-based disease models by capturing behavioral aspects of decision-making in a risky context using machine learning techniques. We illustrate it with a case of cholera in Kumasi, Ghana, accounting for spatial and social risk factors that affect intelligent behavior and corresponding disease incidents. The results of computational experiments comparing intelligent with zero-intelligent representations of agents in a spatial disease agent-based model are discussed. We present a spatial disease agent-based model (ABM) with agents' behavior grounded in Protection Motivation Theory. Spatial and temporal patterns of disease diffusion among zero-intelligent agents are compared to those produced by a population of intelligent agents. Two Bayesian Networks (BNs) designed and coded using R and are further integrated with the NetLogo-based Cholera ABM. The first is a one-tier BN1 (only risk perception), the second is a two-tier BN2 (risk and coping behavior). We run three experiments (zero-intelligent agents, BN1 intelligence and BN2 intelligence) and report the results per experiment in terms of several macro metrics of interest: an epidemic curve, a risk perception curve, and a distribution of different types of coping strategies over time. Our results emphasize the importance of integrating behavioral aspects of decision making under risk into spatial disease ABMs using machine learning algorithms. This is especially relevant when studying cumulative impacts of behavioral changes and possible intervention strategies.

Exploring complex dynamics in multi agent-based intelligent systems: Theoretical and experimental approaches using the Multi Agent-based Behavioral Economic Landscape (MABEL) model

NASA Astrophysics Data System (ADS)

Alexandridis, Konstantinos T.

This dissertation adopts a holistic and detailed approach to modeling spatially explicit agent-based artificial intelligent systems, using the Multi Agent-based Behavioral Economic Landscape (MABEL) model. The research questions that addresses stem from the need to understand and analyze the real-world patterns and dynamics of land use change from a coupled human-environmental systems perspective. Describes the systemic, mathematical, statistical, socio-economic and spatial dynamics of the MABEL modeling framework, and provides a wide array of cross-disciplinary modeling applications within the research, decision-making and policy domains. Establishes the symbolic properties of the MABEL model as a Markov decision process, analyzes the decision-theoretic utility and optimization attributes of agents towards comprising statistically and spatially optimal policies and actions, and explores the probabilogic character of the agents' decision-making and inference mechanisms via the use of Bayesian belief and decision networks. Develops and describes a Monte Carlo methodology for experimental replications of agent's decisions regarding complex spatial parcel acquisition and learning. Recognizes the gap on spatially-explicit accuracy assessment techniques for complex spatial models, and proposes an ensemble of statistical tools designed to address this problem. Advanced information assessment techniques such as the Receiver-Operator Characteristic curve, the impurity entropy and Gini functions, and the Bayesian classification functions are proposed. The theoretical foundation for modular Bayesian inference in spatially-explicit multi-agent artificial intelligent systems, and the ensembles of cognitive and scenario assessment modular tools build for the MABEL model are provided. Emphasizes the modularity and robustness as valuable qualitative modeling attributes, and examines the role of robust intelligent modeling as a tool for improving policy-decisions related to land use change. Finally, the major contributions to the science are presented along with valuable directions for future research.

Statistical physics of the spatial Prisoner's Dilemma with memory-aware agents

NASA Astrophysics Data System (ADS)

Javarone, Marco Alberto

2016-02-01

We introduce an analytical model to study the evolution towards equilibrium in spatial games, with `memory-aware' agents, i.e., agents that accumulate their payoff over time. In particular, we focus our attention on the spatial Prisoner's Dilemma, as it constitutes an emblematic example of a game whose Nash equilibrium is defection. Previous investigations showed that, under opportune conditions, it is possible to reach, in the evolutionary Prisoner's Dilemma, an equilibrium of cooperation. Notably, it seems that mechanisms like motion may lead a population to become cooperative. In the proposed model, we map agents to particles of a gas so that, on varying the system temperature, they randomly move. In doing so, we are able to identify a relation between the temperature and the final equilibrium of the population, explaining how it is possible to break the classical Nash equilibrium in the spatial Prisoner's Dilemma when considering agents able to increase their payoff over time. Moreover, we introduce a formalism to study order-disorder phase transitions in these dynamics. As result, we highlight that the proposed model allows to explain analytically how a population, whose interactions are based on the Prisoner's Dilemma, can reach an equilibrium far from the expected one; opening also the way to define a direct link between evolutionary game theory and statistical physics.

Using Virtual Interactive Training Agents (ViTA) with Adults with Autism and Other Developmental Disabilities

ERIC Educational Resources Information Center

Burke, Shanna L.; Bresnahan, Tammy; Li, Tan; Epnere, Katrina; Rizzo, Albert; Partin, Mary; Ahlness, Robert M.; Trimmer, Matthew

2018-01-01

Conversational virtual human (VH) agents are increasingly used to support role-play experiential learning. This project examined whether a Virtual Interactive Training Agent (ViTA) system would improve job interviewing skills in individuals with autism and developmental disabilities (N = 32). A linear mixed model was employed to evaluate adjusted…

Incorporating BDI Agents into Human-Agent Decision Making Research

NASA Astrophysics Data System (ADS)

Kamphorst, Bart; van Wissen, Arlette; Dignum, Virginia

Artificial agents, people, institutes and societies all have the ability to make decisions. Decision making as a research area therefore involves a broad spectrum of sciences, ranging from Artificial Intelligence to economics to psychology. The Colored Trails (CT) framework is designed to aid researchers in all fields in examining decision making processes. It is developed both to study interaction between multiple actors (humans or software agents) in a dynamic environment, and to study and model the decision making of these actors. However, agents in the current implementation of CT lack the explanatory power to help understand the reasoning processes involved in decision making. The BDI paradigm that has been proposed in the agent research area to describe rational agents, enables the specification of agents that reason in abstract concepts such as beliefs, goals, plans and events. In this paper, we present CTAPL: an extension to CT that allows BDI software agents that are written in the practical agent programming language 2APL to reason about and interact with a CT environment.

Agent tracking: a psycho-historical theory of the identification of living and social agents.

PubMed

Bullot, Nicolas J

To explain agent-identification behaviours, universalist theories in the biological and cognitive sciences have posited mental mechanisms thought to be universal to all humans, such as agent detection and face recognition mechanisms. These universalist theories have paid little attention to how particular sociocultural or historical contexts interact with the psychobiological processes of agent-identification. In contrast to universalist theories, contextualist theories appeal to particular historical and sociocultural contexts for explaining agent-identification. Contextualist theories tend to adopt idiographic methods aimed at recording the heterogeneity of human behaviours across history, space, and cultures. Defenders of the universalist approach tend to criticise idiographic methods because such methods can lead to relativism or may lack generality. To overcome explanatory limitations of proposals that adopt either universalist or contextualist approaches in isolation, I propose a philosophical model that integrates contributions from both traditions: the psycho-historical theory of agent-identification. This theory investigates how the tracking processes that humans use for identifying agents interact with the unique socio-historical contexts that support agent-identification practices. In integrating hypotheses about the history of agents with psychological and epistemological principles regarding agent-identification, the theory can generate novel hypotheses regarding the distinction between recognition-based, heuristic-based, and explanation-based agent-identification.

An individual-based process model to simulate landscape-scale forest ecosystem dynamics

Treesearch

Rupert Seidl; Werner Rammer; Robert M. Scheller; Thomas Spies

2012-01-01

Forest ecosystem dynamics emerges from nonlinear interactions between adaptive biotic agents (i.e., individual trees) and their relationship with a spatially and temporally heterogeneous abiotic environment. Understanding and predicting the dynamics resulting from these complex interactions is crucial for the sustainable stewardship of ecosystems, particularly in the...

Particle-based simulations of self-motile suspensions

NASA Astrophysics Data System (ADS)

Hinz, Denis F.; Panchenko, Alexander; Kim, Tae-Yeon; Fried, Eliot

2015-11-01

A simple model for simulating flows of active suspensions is investigated. The approach is based on dissipative particle dynamics. While the model is potentially applicable to a wide range of self-propelled particle systems, the specific class of self-motile bacterial suspensions is considered as a modeling scenario. To mimic the rod-like geometry of a bacterium, two dissipative particle dynamics particles are connected by a stiff harmonic spring to form an aggregate dissipative particle dynamics molecule. Bacterial motility is modeled through a constant self-propulsion force applied along the axis of each such aggregate molecule. The model accounts for hydrodynamic interactions between self-propelled agents through the pairwise dissipative interactions conventional to dissipative particle dynamics. Numerical simulations are performed using a customized version of the open-source software package LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator) software package. Detailed studies of the influence of agent concentration, pairwise dissipative interactions, and Stokes friction on the statistics of the system are provided. The simulations are used to explore the influence of hydrodynamic interactions in active suspensions. For high agent concentrations in combination with dominating pairwise dissipative forces, strongly correlated motion patterns and a fluid-like spectral distributions of kinetic energy are found. In contrast, systems dominated by Stokes friction exhibit weaker spatial correlations of the velocity field. These results indicate that hydrodynamic interactions may play an important role in the formation of spatially extended structures in active suspensions.

Detection of human pathogenic Ehrlichia muris-like agent in Peromyscus leucopus.

PubMed

Castillo, Caroline G; Eremeeva, Marina E; Paskewitz, Susan M; Sloan, Lynne M; Lee, Xia; Irwin, William E; Tonsberg, Stefan; Pritt, Bobbi S

2015-03-01

An Ehrlichia muris-like (EML) bacterium was recently detected in humans and Ixodes scapularis ticks in Minnesota and Wisconsin. The reservoir for this agent is unknown. To investigate the occurrence of the EML agent, groEL PCR testing and sequencing was performed on blood from small mammals and white-tailed deer that were collected in areas where human and tick infections were previously demonstrated. DNA of the EML agent was detected in two Peromyscus leucopus of 146 small mammals (1.4%); while 181 O. virginianus tested negative. This report provides the first evidence that DNA from the EML agent is found in P. leucopus, the same animal that is a reservoir for Anaplasma phagocytophilum in this region. The role of white-tailed deer remains inconclusive. Further sampling is warranted to understand the spatial and temporal distribution, transmission and maintenance of this pathogen. Copyright © 2014 Elsevier GmbH. All rights reserved.

Fronto-parietal coding of goal-directed actions performed by artificial agents.

PubMed

Kupferberg, Aleksandra; Iacoboni, Marco; Flanagin, Virginia; Huber, Markus; Kasparbauer, Anna; Baumgartner, Thomas; Hasler, Gregor; Schmidt, Florian; Borst, Christoph; Glasauer, Stefan

2018-03-01

With advances in technology, artificial agents such as humanoid robots will soon become a part of our daily lives. For safe and intuitive collaboration, it is important to understand the goals behind their motor actions. In humans, this process is mediated by changes in activity in fronto-parietal brain areas. The extent to which these areas are activated when observing artificial agents indicates the naturalness and easiness of interaction. Previous studies indicated that fronto-parietal activity does not depend on whether the agent is human or artificial. However, it is unknown whether this activity is modulated by observing grasping (self-related action) and pointing actions (other-related action) performed by an artificial agent depending on the action goal. Therefore, we designed an experiment in which subjects observed human and artificial agents perform pointing and grasping actions aimed at two different object categories suggesting different goals. We found a signal increase in the bilateral inferior parietal lobule and the premotor cortex when tool versus food items were pointed to or grasped by both agents, probably reflecting the association of hand actions with the functional use of tools. Our results show that goal attribution engages the fronto-parietal network not only for observing a human but also a robotic agent for both self-related and social actions. The debriefing after the experiment has shown that actions of human-like artificial agents can be perceived as being goal-directed. Therefore, humans will be able to interact with service robots intuitively in various domains such as education, healthcare, public service, and entertainment. © 2017 Wiley Periodicals, Inc.

Multi-Agent Flight Simulation with Robust Situation Generation

NASA Technical Reports Server (NTRS)

Johnson, Eric N.; Hansman, R. John, Jr.

1994-01-01

A robust situation generation architecture has been developed that generates multi-agent situations for human subjects. An implementation of this architecture was developed to support flight simulation tests of air transport cockpit systems. This system maneuvers pseudo-aircraft relative to the human subject's aircraft, generating specific situations for the subject to respond to. These pseudo-aircraft maneuver within reasonable performance constraints, interact in a realistic manner, and make pre-recorded voice radio communications. Use of this system minimizes the need for human experimenters to control the pseudo-agents and provides consistent interactions between the subject and the pseudo-agents. The achieved robustness of this system to typical variations in the subject's flight path was explored. It was found to successfully generate specific situations within the performance limitations of the subject-aircraft, pseudo-aircraft, and the script used.

Can human-like Bots control collective mood: agent-based simulations of online chats

NASA Astrophysics Data System (ADS)

Tadić, Bosiljka; Šuvakov, Milovan

2013-10-01

Using an agent-based modeling approach, in this paper, we study self-organized dynamics of interacting agents in the presence of chat Bots. Different Bots with tunable ‘human-like’ attributes, which exchange emotional messages with agents, are considered, and the collective emotional behavior of agents is quantitatively analyzed. In particular, using detrended fractal analysis we determine persistent fluctuations and temporal correlations in time series of agent activity and statistics of avalanches carrying emotional messages of agents when Bots favoring positive/negative affects are active. We determine the impact of Bots and identify parameters that can modulate that impact. Our analysis suggests that, by these measures, the emotional Bots induce collective emotion among interacting agents by suitably altering the fractal characteristics of the underlying stochastic process. Positive emotion Bots are slightly more effective than negative emotion Bots. Moreover, Bots which periodically alternate between positive and negative emotion can enhance fluctuations in the system, leading to avalanches of agent messages that are reminiscent of self-organized critical states.

A validated agent-based model to study the spatial and temporal heterogeneities of malaria incidence in the rainforest environment.

PubMed

Pizzitutti, Francesco; Pan, William; Barbieri, Alisson; Miranda, J Jaime; Feingold, Beth; Guedes, Gilvan R; Alarcon-Valenzuela, Javiera; Mena, Carlos F

2015-12-22

The Amazon environment has been exposed in the last decades to radical changes that have been accompanied by a remarkable rise of both Plasmodium falciparum and Plasmodium vivax malaria. The malaria transmission process is highly influenced by factors such as spatial and temporal heterogeneities of the environment and individual-based characteristics of mosquitoes and humans populations. All these determinant factors can be simulated effectively trough agent-based models. This paper presents a validated agent-based model of local-scale malaria transmission. The model reproduces the environment of a typical riverine village in the northern Peruvian Amazon, where the malaria transmission is highly seasonal and apparently associated with flooding of large areas caused by the neighbouring river. Agents representing humans, mosquitoes and the two species of Plasmodium (P. falciparum and P. vivax) are simulated in a spatially explicit representation of the environment around the village. The model environment includes: climate, people houses positions and elevation. A representation of changes in the mosquito breeding areas extension caused by the river flooding is also included in the simulation environment. A calibration process was carried out to reproduce the variations of the malaria monthly incidence over a period of 3 years. The calibrated model is also able to reproduce the spatial heterogeneities of local scale malaria transmission. A "what if" eradication strategy scenario is proposed: if the mosquito breeding sites are eliminated through mosquito larva habitat management in a buffer area extended at least 200 m around the village, the malaria transmission is eradicated from the village. The use of agent-based models can reproduce effectively the spatiotemporal variations of the malaria transmission in a low endemicity environment dominated by river floodings like in the Amazon.

Robots As Intentional Agents: Using Neuroscientific Methods to Make Robots Appear More Social

PubMed Central

Wiese, Eva; Metta, Giorgio; Wykowska, Agnieszka

2017-01-01

Robots are increasingly envisaged as our future cohabitants. However, while considerable progress has been made in recent years in terms of their technological realization, the ability of robots to interact with humans in an intuitive and social way is still quite limited. An important challenge for social robotics is to determine how to design robots that can perceive the user’s needs, feelings, and intentions, and adapt to users over a broad range of cognitive abilities. It is conceivable that if robots were able to adequately demonstrate these skills, humans would eventually accept them as social companions. We argue that the best way to achieve this is using a systematic experimental approach based on behavioral and physiological neuroscience methods such as motion/eye-tracking, electroencephalography, or functional near-infrared spectroscopy embedded in interactive human–robot paradigms. This approach requires understanding how humans interact with each other, how they perform tasks together and how they develop feelings of social connection over time, and using these insights to formulate design principles that make social robots attuned to the workings of the human brain. In this review, we put forward the argument that the likelihood of artificial agents being perceived as social companions can be increased by designing them in a way that they are perceived as intentional agents that activate areas in the human brain involved in social-cognitive processing. We first review literature related to social-cognitive processes and mechanisms involved in human–human interactions, and highlight the importance of perceiving others as intentional agents to activate these social brain areas. We then discuss how attribution of intentionality can positively affect human–robot interaction by (a) fostering feelings of social connection, empathy and prosociality, and by (b) enhancing performance on joint human–robot tasks. Lastly, we describe circumstances under which attribution of intentionality to robot agents might be disadvantageous, and discuss challenges associated with designing social robots that are inspired by neuroscientific principles. PMID:29046651

How gestures affect students: A comparative experiment using class presentations conducted by an anthropomorphic agent

NASA Astrophysics Data System (ADS)

Shirakawa, Tomohiro; Sato, Hiroshi; Imao, Tomoya

2017-07-01

Recently, a variety of user interfaces have been developed based on human-robot and human-agent interaction, and anthropomorphic agents are used as one type of interface. However, the use of anthropomorphic agents is applied mainly to the medical and cognitive sciences, and there are few studies of their application to other fields. Therefore, we used an anthropomorphic agent of MMD in a virtual lecture to analyze the effect of gestures on students and search for ways to apply anthropomorphic agents to the field of educational technology.

Rhythm Patterns Interaction - Synchronization Behavior for Human-Robot Joint Action

PubMed Central

Mörtl, Alexander; Lorenz, Tamara; Hirche, Sandra

2014-01-01

Interactive behavior among humans is governed by the dynamics of movement synchronization in a variety of repetitive tasks. This requires the interaction partners to perform for example rhythmic limb swinging or even goal-directed arm movements. Inspired by that essential feature of human interaction, we present a novel concept and design methodology to synthesize goal-directed synchronization behavior for robotic agents in repetitive joint action tasks. The agents’ tasks are described by closed movement trajectories and interpreted as limit cycles, for which instantaneous phase variables are derived based on oscillator theory. Events segmenting the trajectories into multiple primitives are introduced as anchoring points for enhanced synchronization modes. Utilizing both continuous phases and discrete events in a unifying view, we design a continuous dynamical process synchronizing the derived modes. Inverse to the derivation of phases, we also address the generation of goal-directed movements from the behavioral dynamics. The developed concept is implemented to an anthropomorphic robot. For evaluation of the concept an experiment is designed and conducted in which the robot performs a prototypical pick-and-place task jointly with human partners. The effectiveness of the designed behavior is successfully evidenced by objective measures of phase and event synchronization. Feedback gathered from the participants of our exploratory study suggests a subjectively pleasant sense of interaction created by the interactive behavior. The results highlight potential applications of the synchronization concept both in motor coordination among robotic agents and in enhanced social interaction between humanoid agents and humans. PMID:24752212

Human-directed local autonomy for motion guidance and coordination in an intelligent manufacturing system

NASA Astrophysics Data System (ADS)

Alford, W. A.; Kawamura, Kazuhiko; Wilkes, Don M.

1997-12-01

This paper discusses the problem of integrating human intelligence and skills into an intelligent manufacturing system. Our center has jointed the Holonic Manufacturing Systems (HMS) Project, an international consortium dedicated to developing holonic systems technologies. One of our contributions to this effort is in Work Package 6: flexible human integration. This paper focuses on one activity, namely, human integration into motion guidance and coordination. Much research on intelligent systems focuses on creating totally autonomous agents. At the Center for Intelligent Systems (CIS), we design robots that interact directly with a human user. We focus on using the natural intelligence of the user to simplify the design of a robotic system. The problem is finding ways for the user to interact with the robot that are efficient and comfortable for the user. Manufacturing applications impose the additional constraint that the manufacturing process should not be disturbed; that is, frequent interacting with the user could degrade real-time performance. Our research in human-robot interaction is based on a concept called human directed local autonomy (HuDL). Under this paradigm, the intelligent agent selects and executes a behavior or skill, based upon directions from a human user. The user interacts with the robot via speech, gestures, or other media. Our control software is based on the intelligent machine architecture (IMA), an object-oriented architecture which facilitates cooperation and communication among intelligent agents. In this paper we describe our research testbed, a dual-arm humanoid robot and human user, and the use of this testbed for a human directed sorting task. We also discuss some proposed experiments for evaluating the integration of the human into the robot system. At the time of this writing, the experiments have not been completed.

Spatial Segregation between Invasive and Native Commensal Rodents in an Urban Environment: A Case Study in Niamey, Niger

PubMed Central

Garba, Madougou; Dalecky, Ambroise; Kadaoure, Ibrahima; Kane, Mamadou; Hima, Karmadine; Veran, Sophie; Gagare, Sama; Gauthier, Philippe; Tatard, Caroline; Rossi, Jean-Pierre; Dobigny, Gauthier

2014-01-01

Invasive rodents have been responsible for the diffusion worldwide of many zoonotic agents, thus representing major threats for public health. Cities are important hubs for people and goods exchange and are thus expected to play a pivotal role in invasive commensal rodent dissemination. Yet, data about urban rodents' ecology, especially invasive vs. native species interactions, are dramatically scarce. Here, we provide results of an extensive survey of urban rodents conducted in Niamey, Niger, depicting the early stages of rodent bioinvasions within a city. We explore the species-specific spatial distributions throughout the city using contrasted approaches, namely field sampling, co-occurrence analysis, occupancy modelling and indicator geostatistics. We show that (i) two species (i.e. rural-like vs. truly commensal) assemblages can be identified, and that (ii) within commensal rodents, invasive (Rattus rattus and Mus musculus) and native (Mastomys natalensis) species are spatially segregated. Moreover, several pieces of arguments tend to suggest that these exclusive distributions reflect an ongoing native-to-invasive species turn over. The underlying processes as well as the possible consequences for humans are discussed. PMID:25379785

Towards the Verification of Human-Robot Teams

NASA Technical Reports Server (NTRS)

Fisher, Michael; Pearce, Edward; Wooldridge, Mike; Sierhuis, Maarten; Visser, Willem; Bordini, Rafael H.

2005-01-01

Human-Agent collaboration is increasingly important. Not only do high-profile activities such as NASA missions to Mars intend to employ such teams, but our everyday activities involving interaction with computational devices falls into this category. In many of these scenarios, we are expected to trust that the agents will do what we expect and that the agents and humans will work together as expected. But how can we be sure? In this paper, we bring together previous work on the verification of multi-agent systems with work on the modelling of human-agent teamwork. Specifically, we target human-robot teamwork. This paper provides an outline of the way we are using formal verification techniques in order to analyse such collaborative activities. A particular application is the analysis of human-robot teams intended for use in future space exploration.

On the Utilization of Social Animals as a Model for Social Robotics

PubMed Central

Miklósi, Ádám; Gácsi, Márta

2012-01-01

Social robotics is a thriving field in building artificial agents. The possibility to construct agents that can engage in meaningful social interaction with humans presents new challenges for engineers. In general, social robotics has been inspired primarily by psychologists with the aim of building human-like robots. Only a small subcategory of “companion robots” (also referred to as robotic pets) was built to mimic animals. In this opinion essay we argue that all social robots should be seen as companions and more conceptual emphasis should be put on the inter-specific interaction between humans and social robots. This view is underlined by the means of an ethological analysis and critical evaluation of present day companion robots. We suggest that human–animal interaction provides a rich source of knowledge for designing social robots that are able to interact with humans under a wide range of conditions. PMID:22457658

Towards a conceptual multi-agent-based framework to simulate the spatial group decision-making process

NASA Astrophysics Data System (ADS)

Ghavami, Seyed Morsal; Taleai, Mohammad

2017-04-01

Most spatial problems are multi-actor, multi-issue and multi-phase in nature. In addition to their intrinsic complexity, spatial problems usually involve groups of actors from different organizational and cognitive backgrounds, all of whom participate in a social structure to resolve or reduce the complexity of a given problem. Hence, it is important to study and evaluate what different aspects influence the spatial problem resolution process. Recently, multi-agent systems consisting of groups of separate agent entities all interacting with each other have been put forward as appropriate tools to use to study and resolve such problems. In this study, then in order to generate a better level of understanding regarding the spatial problem group decision-making process, a conceptual multi-agent-based framework is used that represents and specifies all the necessary concepts and entities needed to aid group decision making, based on a simulation of the group decision-making process as well as the relationships that exist among the different concepts involved. The study uses five main influencing entities as concepts in the simulation process: spatial influence, individual-level influence, group-level influence, negotiation influence and group performance measures. Further, it explains the relationship among different concepts in a descriptive rather than explanatory manner. To illustrate the proposed framework, the approval process for an urban land use master plan in Zanjan—a provincial capital in Iran—is simulated using MAS, the results highlighting the effectiveness of applying an MAS-based framework when wishing to study the group decision-making process used to resolve spatial problems.

Building a responsive teacher: how temporal contingency of gaze interaction influences word learning with virtual tutors

PubMed Central

Lee, Hanju; Kanakogi, Yasuhiro; Hiraki, Kazuo

2015-01-01

Animated pedagogical agents are lifelike virtual characters designed to augment learning. A review of developmental psychology literature led to the hypothesis that the temporal contingency of such agents would promote human learning. We developed a Pedagogical Agent with Gaze Interaction (PAGI), an experimental animated pedagogical agent that engages in gaze interaction with students. In this study, university students learned words of a foreign language, with temporally contingent PAGI (live group) or recorded version of PAGI (recorded group), which played pre-recorded sequences from live sessions. The result revealed that students in the live group scored considerably better than those in the recorded group. The finding indicates that incorporating temporal contingency of gaze interaction from a pedagogical agent has positive effect on learning. PMID:26064584

The Evolution of Cooperation in Managed Groundwater Systems: An Agent-Based Modelling Approach

NASA Astrophysics Data System (ADS)

Castilla Rho, J. C.; Mariethoz, G.; Rojas, R. F.; Andersen, M. S.; Kelly, B. F.; Holley, C.

2014-12-01

Human interactions with groundwater systems often exhibit complex features that hinder the sustainable management of the resource. This leads to costly and persistent conflicts over groundwater at the catchment scale. One possible way to address these conflicts is by gaining a better understanding of how social and groundwater dynamics coevolve using agent-based models (ABM). Such models allow exploring 'bottom-up' solutions (i.e., self-organised governance systems), where the behaviour of individual agents (e.g., farmers) results in the emergence of mutual cooperation among groundwater users. There is significant empirical evidence indicating that this kind of 'bottom-up' approach may lead to more enduring and sustainable outcomes, compared to conventional 'top-down' strategies such as centralized control and water right schemes (Ostrom 1990). New modelling tools are needed to study these concepts systematically and efficiently. Our model uses a conceptual framework to study cooperation and the emergence of social norms as initially proposed by Axelrod (1986), which we adapted to groundwater management. We developed an ABM that integrates social mechanisms and the physics of subsurface flow. The model explicitly represents feedback between groundwater conditions and social dynamics, capturing the spatial structure of these interactions and the potential effects on cooperation levels in an agricultural setting. Using this model, we investigate a series of mechanisms that may trigger norms supporting cooperative strategies, which can be sustained and become stable over time. For example, farmers in a self-monitoring community can be more efficient at achieving the objective of sustainable groundwater use than government-imposed regulation. Our coupled model thus offers a platform for testing new schemes promoting cooperation and improved resource use, which can be used as a basis for policy design. Importantly, we hope to raise awareness of agent-based modelling as a new tool for studying complex human-groundwater systems.

A spatial socio-ecosystem approach to analyse human-environment interactions on climate change adaptation for water resources management

NASA Astrophysics Data System (ADS)

Giupponi, Carlo; Mojtahed, Vahid

2017-04-01

Global climate and socio-economic drivers determine the future patterns of the allocation and the trade of resources and commodities in all markets. The agricultural sector is an emblematic case in which natural (e.g. climate), social (e.g. demography) and economic (e.g. the market) drivers of change interact, determining the evolution of social and ecological systems (or simply socio-ecosystems; SES) over time. In order to analyse the dynamics and possible future evolutions of SES, the combination of local complex systems and global drivers and trends require the development of multiscale approaches. At global level, climatic general circulation models (CGM) and computable general equilibrium or partial equilibrium models have been used for many years to explore the effects of global trends and generate future climate and socio-economic scenarios. Al local level, the inherent complexity of SESs and their spatial and temporal variabilities require different modelling approaches of physical/environmental sub-systems (e.g. field scale crop modelling, GIS-based models, etc.) and of human agency decision makers (e.g. agent based models). Global and local models have different assumption, limitations, constrains, etc., but in some cases integration is possible and several attempts are in progress to couple different models within the so-called Integrated Assessment Models. This work explores an innovative proposal to integrate the global and local approaches, where agent-based models (ABM) are used to simulate spatial (i.e. grid-based) and temporal dynamics of land and water resource use spatial and temporal dynamics, under the effect of global drivers. We focus in particular on how global change may affect land-use allocation at the local to regional level, under the influence of limited natural resources, land and water in particular. We specifically explore how constrains and competition for natural resources may induce non-linearities and discontinuities in socio-ecosystems behaviour. Our general ambition is to explore the feasibility of an approach that could be implemented worldwide through the identification of representative cases described by means of spatially explicit integrated simulations in communication with global modelling. Our specific objective is to test how ABMs can support scenario analysis at regional scale, and in particular how this can facilitate understanding of the role of human agency and its behavioural characteristics in local to global dynamics. The SES of interest is the agro-ecosystem with its relationships with other land uses. In order to test the feasibility of application at global level, all the information about land uses, natural resources, local climate, crop potential productions, etc. were derived from freely available spatial data sets covering the whole planet, which provided the ABM model with spatial information as matrices of pixels. Input maps were extracted from the Global Agro-Ecological Zone (GAEZ) web site of the Food and Agriculture Organization of the United Nations and compiled in the local GIS from where they were then converted in a format compatible with Matlab. In this initial application, an ABM prototype was developed in three test areas around the Mediterranean Basin, in agricultural regions of Tunisia, Italy and Spain.

Least-cost transportation networks predict spatial interaction of invasion vectors.

PubMed

Drake, D Andrew R; Mandrak, Nicholas E

2010-12-01

Human-mediated dispersal among aquatic ecosystems often results in biotic transfer between drainage basins. Such activities may circumvent biogeographic factors, with considerable ecological, evolutionary, and economic implications. However, the efficacy of predictions concerning community changes following inter-basin movements are limited, often because the dispersal mechanism is poorly understood (e.g., quantified only partially). To date, spatial-interaction models that predict the movement of humans as vectors of biotic transfer have not incorporated patterns of human movement through transportation networks. As a necessary first step to determine the role of anglers as invasion vectors across a land-lake ecosystem, we investigate their movement potential within Ontario, Canada. To determine possible model improvements resulting from inclusion of network travel, spatial-interaction models were constructed using standard Euclidean (e.g., straight-line) distance measures and also with distances derived from least-cost routing of human transportation networks. Model comparisons determined that least-cost routing both provided the most parsimonious model and also excelled at forecasting spatial interactions, with a proportion of 0.477 total movement deviance explained. The distribution of movements was characterized by many relatively short to medium travel distances (median = 292.6 km) with fewer lengthier distances (75th percentile = 484.6 km, 95th percentile = 775.2 km); however, even the shortest movements were sufficient to overcome drainage-basin boundaries. Ranking of variables in order of their contribution within the most parsimonious model determined that distance traveled, origin outflow, lake attractiveness, and sportfish richness significantly influence movement patterns. Model improvements associated with least-cost routing of human transportation networks imply that patterns of human-mediated invasion are fundamentally linked to the spatial configuration and relative impedance of human transportation networks, placing increased importance on understanding their contribution to the invasion process.

A little anthropomorphism goes a long way: Effects of oxytocin on trust, compliance and team performance with automated agents

PubMed Central

de Visser, Ewart J.; Monfort, Samuel S.; Goodyear, Kimberly; Lu, Li; O’Hara, Martin; Lee, Mary R.; Parasuraman, Raja; Krueger, Frank

2017-01-01

Objective We investigated the effects of exogenous oxytocin on trust, compliance, and team decision making with agents varying in anthropomorphism (computer, avatar, human) and reliability (100%, 50%). Background Recent work has explored psychological similarities in how we trust human-like automation compared to how we trust other humans. Exogenous administration of oxytocin, a neuropeptide associated with trust among humans, offers a unique opportunity to probe the anthropomorphism continuum of automation to infer when agents are trusted like another human or merely a machine. Method Eighty-four healthy male participants collaborated with automated agents varying in anthropomorphism that provided recommendations in a pattern recognition task. Results Under placebo, participants exhibited less trust and compliance with automated aids as the anthropomorphism of those aids increased. Under oxytocin, participants interacted with aids on the extremes of the anthropomorphism continuum similarly to placebos, but increased their trust, compliance, and performance with the avatar, an agent on the midpoint of the anthropomorphism continuum. Conclusion This study provided the first evidence that administration of exogenous oxytocin affected trust, compliance, and team decision making with automated agents. These effects provide support for the premise that oxytocin increases affinity for social stimuli in automated aids. Application Designing automation to mimic basic human characteristics is sufficient to elicit behavioral trust outcomes that are driven by neurological processes typically observed in human-human interactions. Designers of automated systems should consider the task, the individual, and the level of anthropomorphism to achieve the desired outcome. PMID:28146673

Implementing Artificial Intelligence Behaviors in a Virtual World

NASA Technical Reports Server (NTRS)

Krisler, Brian; Thome, Michael

2012-01-01

In this paper, we will present a look at the current state of the art in human-computer interface technologies, including intelligent interactive agents, natural speech interaction and gestural based interfaces. We describe our use of these technologies to implement a cost effective, immersive experience on a public region in Second Life. We provision our Artificial Agents as a German Shepherd Dog avatar with an external rules engine controlling the behavior and movement. To interact with the avatar, we implemented a natural language and gesture system allowing the human avatars to use speech and physical gestures rather than interacting via a keyboard and mouse. The result is a system that allows multiple humans to interact naturally with AI avatars by playing games such as fetch with a flying disk and even practicing obedience exercises using voice and gesture, a natural seeming day in the park.

Identification of walking human model using agent-based modelling

NASA Astrophysics Data System (ADS)

Shahabpoor, Erfan; Pavic, Aleksandar; Racic, Vitomir

2018-03-01

The interaction of walking people with large vibrating structures, such as footbridges and floors, in the vertical direction is an important yet challenging phenomenon to describe mathematically. Several different models have been proposed in the literature to simulate interaction of stationary people with vibrating structures. However, the research on moving (walking) human models, explicitly identified for vibration serviceability assessment of civil structures, is still sparse. In this study, the results of a comprehensive set of FRF-based modal tests were used, in which, over a hundred test subjects walked in different group sizes and walking patterns on a test structure. An agent-based model was used to simulate discrete traffic-structure interactions. The occupied structure modal parameters found in tests were used to identify the parameters of the walking individual's single-degree-of-freedom (SDOF) mass-spring-damper model using 'reverse engineering' methodology. The analysis of the results suggested that the normal distribution with the average of μ = 2.85Hz and standard deviation of σ = 0.34Hz can describe human SDOF model natural frequency. Similarly, the normal distribution with μ = 0.295 and σ = 0.047 can describe the human model damping ratio. Compared to the previous studies, the agent-based modelling methodology proposed in this paper offers significant flexibility in simulating multi-pedestrian walking traffics, external forces and simulating different mechanisms of human-structure and human-environment interaction at the same time.

Reciprocity in computer-human interaction: source-based, norm-based, and affect-based explanations.

PubMed

Lee, Seungcheol Austin; Liang, Yuhua Jake

2015-04-01

Individuals often apply social rules when they interact with computers, and this is known as the Computers Are Social Actors (CASA) effect. Following previous work, one approach to understand the mechanism responsible for CASA is to utilize computer agents and have the agents attempt to gain human compliance (e.g., completing a pattern recognition task). The current study focuses on three key factors frequently cited to influence traditional notions of compliance: evaluations toward the source (competence and warmth), normative influence (reciprocity), and affective influence (mood). Structural equation modeling assessed the effects of these factors on human compliance with computer request. The final model shows that norm-based influence (reciprocity) increased the likelihood of compliance, while evaluations toward the computer agent did not significantly influence compliance.

Observing Fearful Faces Leads to Visuo-Spatial Perspective Taking

ERIC Educational Resources Information Center

Zwickel, Jan; Muller, Hermann J.

2010-01-01

A number of recent studies suggested that visuo-spatial perspective taking (VSPT) occurs spontaneously when viewing either a human body or an action by an agent. However, it remains unclear whether VSPT is caused by the observation of an (potential) action or occurs because the observer infers from certain cues that another mind is present…

A multi-agent architecture for geosimulation of moving agents

NASA Astrophysics Data System (ADS)

Vahidnia, Mohammad H.; Alesheikh, Ali A.; Alavipanah, Seyed Kazem

2015-10-01

In this paper, a novel architecture is proposed in which an axiomatic derivation system in the form of first-order logic facilitates declarative explanation and spatial reasoning. Simulation of environmental perception and interaction between autonomous agents is designed with a geographic belief-desire-intention and a request-inform-query model. The architecture has a complementary quantitative component that supports collaborative planning based on the concept of equilibrium and game theory. This new architecture presents a departure from current best practices geographic agent-based modelling. Implementation tasks are discussed in some detail, as well as scenarios for fleet management and disaster management.

Information for Successful Interaction with Autonomous Systems

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Johnson, Kathy A.

2003-01-01

Interaction in heterogeneous mission operations teams is not well matched to classical models of coordination with autonomous systems. We describe methods of loose coordination and information management in mission operations. We describe an information agent and information management tool suite for managing information from many sources, including autonomous agents. We present an integrated model of levels of complexity of agent and human behavior, which shows types of information processing and points of potential error in agent activities. We discuss the types of information needed for diagnosing problems and planning interactions with an autonomous system. We discuss types of coordination for which designs are needed for autonomous system functions.

Evolutionary game theory using agent-based methods.

PubMed

Adami, Christoph; Schossau, Jory; Hintze, Arend

2016-12-01

Evolutionary game theory is a successful mathematical framework geared towards understanding the selective pressures that affect the evolution of the strategies of agents engaged in interactions with potential conflicts. While a mathematical treatment of the costs and benefits of decisions can predict the optimal strategy in simple settings, more realistic settings such as finite populations, non-vanishing mutations rates, stochastic decisions, communication between agents, and spatial interactions, require agent-based methods where each agent is modeled as an individual, carries its own genes that determine its decisions, and where the evolutionary outcome can only be ascertained by evolving the population of agents forward in time. While highlighting standard mathematical results, we compare those to agent-based methods that can go beyond the limitations of equations and simulate the complexity of heterogeneous populations and an ever-changing set of interactors. We conclude that agent-based methods can predict evolutionary outcomes where purely mathematical treatments cannot tread (for example in the weak selection-strong mutation limit), but that mathematics is crucial to validate the computational simulations. Copyright © 2016 Elsevier B.V. All rights reserved.

Impact of Human like Cues on Human Trust in Machines: Brain Imaging and Modeling Studies for Human-Machine Interactions

DTIC Science & Technology

2018-01-05

research team recorded fMRI or event-related potentials while subjects were playing two cognitive games . At the first experiment, human subjects played a...theory-of-mind bilateral game with two types of computerized agents: with or without humanlike cues. At the second experiment, human subjects played...a unilateral game in which the human subjects played the role of the Coach (or supervisor) while a computer agent played as the Player

Different impressions of other agents obtained through social interaction uniquely modulate dorsal and ventral pathway activities in the social human brain.

PubMed

Takahashi, Hideyuki; Terada, Kazunori; Morita, Tomoyo; Suzuki, Shinsuke; Haji, Tomoki; Kozima, Hideki; Yoshikawa, Masahiro; Matsumoto, Yoshio; Omori, Takashi; Asada, Minoru; Naito, Eiichi

2014-09-01

Internal (neuronal) representations in the brain are modified by our experiences, and this phenomenon is not unique to sensory and motor systems. Here, we show that different impressions obtained through social interaction with a variety of agents uniquely modulate activity of dorsal and ventral pathways of the brain network that mediates human social behavior. We scanned brain activity with functional magnetic resonance imaging (fMRI) in 16 healthy volunteers when they performed a simple matching-pennies game with a human, human-like android, mechanical robot, interactive robot, and a computer. Before playing this game in the scanner, participants experienced social interactions with each opponent separately and scored their initial impressions using two questionnaires. We found that the participants perceived opponents in two mental dimensions: one represented "mind-holderness" in which participants attributed anthropomorphic impressions to some of the opponents that had mental functions, while the other dimension represented "mind-readerness" in which participants characterized opponents as intelligent. Interestingly, this "mind-readerness" dimension correlated to participants frequently changing their game tactic to prevent opponents from envisioning their strategy, and this was corroborated by increased entropy during the game. We also found that the two factors separately modulated activity in distinct social brain regions. Specifically, mind-holderness modulated activity in the dorsal aspect of the temporoparietal junction (TPJ) and medial prefrontal and posterior paracingulate cortices, while mind-readerness modulated activity in the ventral aspect of TPJ and the temporal pole. These results clearly demonstrate that activity in social brain networks is modulated through pre-scanning experiences of social interaction with a variety of agents. Furthermore, our findings elucidated the existence of two distinct functional networks in the social human brain. Social interaction with anthropomorphic or intelligent-looking agents may distinctly shape the internal representation of our social brain, which may in turn determine how we behave for various agents that we encounter in our society. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

The role of potential agents in making spatial perspective taking social

PubMed Central

Clements-Stephens, Amy M.; Vasiljevic, Katarina; Murray, Alexandra J.; Shelton, Amy L.

2013-01-01

A striking relationship between visual spatial perspective taking (VSPT) and social skills has been demonstrated for perspective-taking tasks in which the target of the imagined or inferred perspective is a potential agent, suggesting that the presence of a potential agent may create a social context for the seemingly spatial task of imagining a novel visual perspective. In a series of studies, we set out to investigate how and when a target might be viewed as sufficiently agent-like to incur a social influence on VSPT performance. By varying the perceptual and conceptual features that defined the targets as potential agents, we find that even something as simple as suggesting animacy for a simple wooden block may be sufficient. More critically, we found that experience with one potential agent influenced the performance with subsequent targets, either by inducing or eliminating the influence of social skills on VSPT performance. These carryover effects suggest that the relationship between social skills and VSPT performance is mediated by a complex relationship that includes the task, the target, and the context in which that target is perceived. These findings highlight potential problems that arise when identifying a task as belonging exclusively to a single cognitive domain and stress instead the highly interactive nature of cognitive domains and their susceptibility to cross-domain individual differences. PMID:24046735

Intelligent Context-Aware and Adaptive Interface for Mobile LBS

PubMed Central

Liu, Yanhong

2015-01-01

Context-aware user interface plays an important role in many human-computer Interaction tasks of location based services. Although spatial models for context-aware systems have been studied extensively, how to locate specific spatial information for users is still not well resolved, which is important in the mobile environment where location based services users are impeded by device limitations. Better context-aware human-computer interaction models of mobile location based services are needed not just to predict performance outcomes, such as whether people will be able to find the information needed to complete a human-computer interaction task, but to understand human processes that interact in spatial query, which will in turn inform the detailed design of better user interfaces in mobile location based services. In this study, a context-aware adaptive model for mobile location based services interface is proposed, which contains three major sections: purpose, adjustment, and adaptation. Based on this model we try to describe the process of user operation and interface adaptation clearly through the dynamic interaction between users and the interface. Then we show how the model applies users' demands in a complicated environment and suggested the feasibility by the experimental results. PMID:26457077

Quantifying the influences of various ecological factors on land surface temperature of urban forests.

PubMed

Ren, Yin; Deng, Lu-Ying; Zuo, Shu-Di; Song, Xiao-Dong; Liao, Yi-Lan; Xu, Cheng-Dong; Chen, Qi; Hua, Li-Zhong; Li, Zheng-Wei

2016-09-01

Identifying factors that influence the land surface temperature (LST) of urban forests can help improve simulations and predictions of spatial patterns of urban cool islands. This requires a quantitative analytical method that combines spatial statistical analysis with multi-source observational data. The purpose of this study was to reveal how human activities and ecological factors jointly influence LST in clustering regions (hot or cool spots) of urban forests. Using Xiamen City, China from 1996 to 2006 as a case study, we explored the interactions between human activities and ecological factors, as well as their influences on urban forest LST. Population density was selected as a proxy for human activity. We integrated multi-source data (forest inventory, digital elevation models (DEM), population, and remote sensing imagery) to develop a database on a unified urban scale. The driving mechanism of urban forest LST was revealed through a combination of multi-source spatial data and spatial statistical analysis of clustering regions. The results showed that the main factors contributing to urban forest LST were dominant tree species and elevation. The interactions between human activity and specific ecological factors linearly or nonlinearly increased LST in urban forests. Strong interactions between elevation and dominant species were generally observed and were prevalent in either hot or cold spots areas in different years. In conclusion, quantitative studies based on spatial statistics and GeogDetector models should be conducted in urban areas to reveal interactions between human activities, ecological factors, and LST. Copyright © 2016 Elsevier Ltd. All rights reserved.

Software agents and the route to the information economy.

PubMed

Kephart, Jeffrey O

2002-05-14

Humans are on the verge of losing their status as the sole economic species on the planet. In private laboratories and in the Internet laboratory, researchers and developers are creating a variety of autonomous economically motivated software agents endowed with algorithms for maximizing profit or utility. Many economic software agents will function as miniature businesses, purchasing information inputs from other agents, combining and refining them into information goods and services, and selling them to humans or other agents. Their mutual interactions will form the information economy: a complex economic web of information goods and services that will adapt to the ever-changing needs of people and agents. The information economy will be the largest multiagent system ever conceived and an integral part of the world's economy. I discuss a possible route toward this vision, beginning with present-day Internet trends suggesting that agents will charge one another for information goods and services. Then, to establish that agents can be competent price setters, I describe some laboratory experiments pitting software bidding agents against human bidders. The agents' superior performance suggests they will be used on a broad scale, which in turn suggests that interactions among agents will become frequent and significant. How will this affect macroscopic economic behavior? I describe some interesting phenomena that my colleagues and I have observed in simulations of large populations of automated buyers and sellers, such as price war cycles. I conclude by discussing fundamental scientific challenges that remain to be addressed as we journey toward the information economy.

A Gas Chromotographic-Mass Spectrometric Approach to Examining Stereoselective Interaction of Human Plasma Proteins with Soman

DTIC Science & Technology

2008-02-01

ABSTRACT See reprint. 15. SUBJECT TERMS Human plasma proteins, soman, nerve agent , bioscavenger, gas chromatography, mass spectrometry 16. SECURITY...usually referred to as nerve agents ) are tabun (ethyl dimethylamidocyanophosphate, or GA ), sarin (iso- propyl methylfluorophosphonate, or GB), soman...Pharmacology and toxicology of chemical warfare agents Ann. Acad. Med. Singapore 2&: 104-107 (1997). 11. C Macilwain. Study proves Iraq used nerve gas . Nature 3

Interactive machine learning for health informatics: when do we need the human-in-the-loop?

PubMed

Holzinger, Andreas

2016-06-01

Machine learning (ML) is the fastest growing field in computer science, and health informatics is among the greatest challenges. The goal of ML is to develop algorithms which can learn and improve over time and can be used for predictions. Most ML researchers concentrate on automatic machine learning (aML), where great advances have been made, for example, in speech recognition, recommender systems, or autonomous vehicles. Automatic approaches greatly benefit from big data with many training sets. However, in the health domain, sometimes we are confronted with a small number of data sets or rare events, where aML-approaches suffer of insufficient training samples. Here interactive machine learning (iML) may be of help, having its roots in reinforcement learning, preference learning, and active learning. The term iML is not yet well used, so we define it as "algorithms that can interact with agents and can optimize their learning behavior through these interactions, where the agents can also be human." This "human-in-the-loop" can be beneficial in solving computationally hard problems, e.g., subspace clustering, protein folding, or k-anonymization of health data, where human expertise can help to reduce an exponential search space through heuristic selection of samples. Therefore, what would otherwise be an NP-hard problem, reduces greatly in complexity through the input and the assistance of a human agent involved in the learning phase.

Brain Computer Interfaces for Enhanced Interaction with Mobile Robot Agents

DTIC Science & Technology

2016-07-27

synergistic and complementary way. This project focused on acquiring a mobile robotic agent platform that can be used to explore these interfaces...providing a test environment where the human control of a robot agent can be experimentally validated in 1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND...Distribution Unlimited UU UU UU UU 27-07-2016 17-Sep-2013 16-Sep-2014 Final Report: Brain Computer Interfaces for Enhanced Interactions with Mobile Robot

Pharmacomicrobiomics: the impact of human microbiome variations on systems pharmacology and personalized therapeutics.

PubMed

ElRakaiby, Marwa; Dutilh, Bas E; Rizkallah, Mariam R; Boleij, Annemarie; Cole, Jason N; Aziz, Ramy K

2014-07-01

The Human Microbiome Project (HMP) is a global initiative undertaken to identify and characterize the collection of human-associated microorganisms at multiple anatomic sites (skin, mouth, nose, colon, vagina), and to determine how intra-individual and inter-individual alterations in the microbiome influence human health, immunity, and different disease states. In this review article, we summarize the key findings and applications of the HMP that may impact pharmacology and personalized therapeutics. We propose a microbiome cloud model, reflecting the temporal and spatial uncertainty of defining an individual's microbiome composition, with examples of how intra-individual variations (such as age and mode of delivery) shape the microbiome structure. Additionally, we discuss how this microbiome cloud concept explains the difficulty to define a core human microbiome and to classify individuals according to their biome types. Detailed examples are presented on microbiome changes related to colorectal cancer, antibiotic administration, and pharmacomicrobiomics, or drug-microbiome interactions, highlighting how an improved understanding of the human microbiome, and alterations thereof, may lead to the development of novel therapeutic agents, the modification of antibiotic policies and implementation, and improved health outcomes. Finally, the prospects of a collaborative computational microbiome research initiative in Africa are discussed.

Pharmacomicrobiomics: The Impact of Human Microbiome Variations on Systems Pharmacology and Personalized Therapeutics

PubMed Central

ElRakaiby, Marwa; Dutilh, Bas E.; Rizkallah, Mariam R.; Boleij, Annemarie; Cole, Jason N.

2014-01-01

Abstract The Human Microbiome Project (HMP) is a global initiative undertaken to identify and characterize the collection of human-associated microorganisms at multiple anatomic sites (skin, mouth, nose, colon, vagina), and to determine how intra-individual and inter-individual alterations in the microbiome influence human health, immunity, and different disease states. In this review article, we summarize the key findings and applications of the HMP that may impact pharmacology and personalized therapeutics. We propose a microbiome cloud model, reflecting the temporal and spatial uncertainty of defining an individual's microbiome composition, with examples of how intra-individual variations (such as age and mode of delivery) shape the microbiome structure. Additionally, we discuss how this microbiome cloud concept explains the difficulty to define a core human microbiome and to classify individuals according to their biome types. Detailed examples are presented on microbiome changes related to colorectal cancer, antibiotic administration, and pharmacomicrobiomics, or drug–microbiome interactions, highlighting how an improved understanding of the human microbiome, and alterations thereof, may lead to the development of novel therapeutic agents, the modification of antibiotic policies and implementation, and improved health outcomes. Finally, the prospects of a collaborative computational microbiome research initiative in Africa are discussed. PMID:24785449

Seeing Minds in Others – Can Agents with Robotic Appearance Have Human-Like Preferences?

PubMed Central

Martini, Molly C.; Gonzalez, Christian A.; Wiese, Eva

2016-01-01

Ascribing mental states to non-human agents has been shown to increase their likeability and lead to better joint-task performance in human-robot interaction (HRI). However, it is currently unclear what physical features non-human agents need to possess in order to trigger mind attribution and whether different aspects of having a mind (e.g., feeling pain, being able to move) need different levels of human-likeness before they are readily ascribed to non-human agents. The current study addresses this issue by modeling how increasing the degree of human-like appearance (on a spectrum from mechanistic to humanoid to human) changes the likelihood by which mind is attributed towards non-human agents. We also test whether different internal states (e.g., being hungry, being alive) need different degrees of humanness before they are ascribed to non-human agents. The results suggest that the relationship between physical appearance and the degree to which mind is attributed to non-human agents is best described as a two-linear model with no change in mind attribution on the spectrum from mechanistic to humanoid robot, but a significant increase in mind attribution as soon as human features are included in the image. There seems to be a qualitative difference in the perception of mindful versus mindless agents given that increasing human-like appearance alone does not increase mind attribution until a certain threshold is reached, that is: agents need to be classified as having a mind first before the addition of more human-like features significantly increases the degree to which mind is attributed to that agent. PMID:26745500

Design and implementation of spatial knowledge grid for integrated spatial analysis

NASA Astrophysics Data System (ADS)

Liu, Xiangnan; Guan, Li; Wang, Ping

2006-10-01

Supported by spatial information grid(SIG), the spatial knowledge grid (SKG) for integrated spatial analysis utilizes the middleware technology in constructing the spatial information grid computation environment and spatial information service system, develops spatial entity oriented spatial data organization technology, carries out the profound computation of the spatial structure and spatial process pattern on the basis of Grid GIS infrastructure, spatial data grid and spatial information grid (specialized definition). At the same time, it realizes the complex spatial pattern expression and the spatial function process simulation by taking the spatial intelligent agent as the core to establish space initiative computation. Moreover through the establishment of virtual geographical environment with man-machine interactivity and blending, complex spatial modeling, network cooperation work and spatial community decision knowledge driven are achieved. The framework of SKG is discussed systematically in this paper. Its implement flow and the key technology with examples of overlay analysis are proposed as well.

Interacting with an artificial partner: modeling the role of emotional aspects.

PubMed

Cattinelli, Isabella; Goldwurm, Massimiliano; Borghese, N Alberto

2008-12-01

In this paper we introduce a simple model based on probabilistic finite state automata to describe an emotional interaction between a robot and a human user, or between simulated agents. Based on the agent's personality, attitude, and nature, and on the emotional inputs it receives, the model will determine the next emotional state displayed by the agent itself. The probabilistic and time-varying nature of the model yields rich and dynamic interactions, and an autonomous adaptation to the interlocutor. In addition, a reinforcement learning technique is applied to have one agent drive its partner's behavior toward desired states. The model may also be used as a tool for behavior analysis, by extracting high probability patterns of interaction and by resorting to the ergodic properties of Markov chains.

A truly human interface: interacting face-to-face with someone whose words are determined by a computer program

PubMed Central

Corti, Kevin; Gillespie, Alex

2015-01-01

We use speech shadowing to create situations wherein people converse in person with a human whose words are determined by a conversational agent computer program. Speech shadowing involves a person (the shadower) repeating vocal stimuli originating from a separate communication source in real-time. Humans shadowing for conversational agent sources (e.g., chat bots) become hybrid agents (“echoborgs”) capable of face-to-face interlocution. We report three studies that investigated people’s experiences interacting with echoborgs and the extent to which echoborgs pass as autonomous humans. First, participants in a Turing Test spoke with a chat bot via either a text interface or an echoborg. Human shadowing did not improve the chat bot’s chance of passing but did increase interrogators’ ratings of how human-like the chat bot seemed. In our second study, participants had to decide whether their interlocutor produced words generated by a chat bot or simply pretended to be one. Compared to those who engaged a text interface, participants who engaged an echoborg were more likely to perceive their interlocutor as pretending to be a chat bot. In our third study, participants were naïve to the fact that their interlocutor produced words generated by a chat bot. Unlike those who engaged a text interface, the vast majority of participants who engaged an echoborg did not sense a robotic interaction. These findings have implications for android science, the Turing Test paradigm, and human–computer interaction. The human body, as the delivery mechanism of communication, fundamentally alters the social psychological dynamics of interactions with machine intelligence. PMID:26042066

Chemical interaction: enhancement and inhibition of clastogenicity.

PubMed Central

Anwar, W A

1993-01-01

Most environmental exposures involve concurrent or sequential exposure to multiple chemicals in air, water, and food. Interactive effects in carcinogenesis have been described for certain combinations of agents. They are described in terms of enhancement or inhibition of carcinogenesis. Enhancement effects have been documented for cigarette smoking in combination with exposure to asbestos, radon, alcohol, or other exposures. A variety of inhibitors of carcinogenesis have also been described. They are classified into agents preventing formation of carcinogens; blocking agents; and suppressing agents. Assessment of risk from exposure to multiple agents can be derived either from epidemiological studies in relation to actual exposure or from laboratory studies after controlled exposure to different agents. Prediction of how toxic components of mixtures will interact should be based on an understanding of the mechanisms of such interactions. Compounds may interact chemically, yielding new toxic components or causing a change in the biological availability of the existing components or metabolites. In humans, great individual variability in response is to be expected because of genetic heterogeneity or acquired host susceptibility factors. Interaction is thus a key component in the risk assessment process. In this paper, the definition of interaction and the theoretical basis for different types of interaction in cancer causation are reviewed. Epidemiological and experimental studies showing interactive effects of two chemical carcinogens are also presented. PMID:8143617

An experimental-computational platform for investigating microbial interactions and dynamics in communities with two codependent species

NASA Astrophysics Data System (ADS)

Fuentes-Cabrera, Miguel; Anderson, John D.; Wilmoth, Jared; Ginovart, Marta; Prats, Clara; Portell-Canal, Xavier; Retterer, Scott

Microbial interactions are critical for governing community behavior and structure in natural environments. Examination of microbial interactions in the lab involves growth under ideal conditions in batch culture; conditions that occur in nature are, however, characterized by disequilibrium. Of particular interest is the role that system variables play in shaping cell-to-cell interactions and organization at ultrafine spatial scales. We seek to use experiments and agent-based modeling to help discover mechanisms relevant to microbial dynamics and interactions in the environment. Currently, we are using an agent-based model to simulate microbial growth, dynamics and interactions that occur on a microwell-array device developed in our lab. Bacterial cells growing in the microwells of this platform can be studied with high-throughput and high-content image analyses using brightfield and fluorescence microscopy. The agent-based model is written in the language Netlogo, which in turn is ''plugged into'' a computational framework that allows submitting many calculations in parallel for different initial parameters; visualizing the outcomes in an interactive phase-like diagram; and searching, with a genetic algorithm, for the parameters that lead to the most optimal simulation outcome.

Social Experiments in the Mesoscale: Humans Playing a Spatial Prisoner's Dilemma

PubMed Central

Grujić, Jelena; Fosco, Constanza; Araujo, Lourdes; Cuesta, José A.; Sánchez, Angel

2010-01-01

Background The evolutionary origin of cooperation among unrelated individuals remains a key unsolved issue across several disciplines. Prominent among the several mechanisms proposed to explain how cooperation can emerge is the existence of a population structure that determines the interactions among individuals. Many models have explored analytically and by simulation the effects of such a structure, particularly in the framework of the Prisoner's Dilemma, but the results of these models largely depend on details such as the type of spatial structure or the evolutionary dynamics. Therefore, experimental work suitably designed to address this question is needed to probe these issues. Methods and Findings We have designed an experiment to test the emergence of cooperation when humans play Prisoner's Dilemma on a network whose size is comparable to that of simulations. We find that the cooperation level declines to an asymptotic state with low but nonzero cooperation. Regarding players' behavior, we observe that the population is heterogeneous, consisting of a high percentage of defectors, a smaller one of cooperators, and a large group that shares features of the conditional cooperators of public goods games. We propose an agent-based model based on the coexistence of these different strategies that is in good agreement with all the experimental observations. Conclusions In our large experimental setup, cooperation was not promoted by the existence of a lattice beyond a residual level (around 20%) typical of public goods experiments. Our findings also indicate that both heterogeneity and a “moody” conditional cooperation strategy, in which the probability of cooperating also depends on the player's previous action, are required to understand the outcome of the experiment. These results could impact the way game theory on graphs is used to model human interactions in structured groups. PMID:21103058

Protein crystallization studies

NASA Technical Reports Server (NTRS)

Lyne, James Evans

1996-01-01

The Structural Biology laboratory at NASA Marshall Spaceflight Center uses x-ray crystallographic techniques to conduct research into the three-dimensional structure of a wide variety of proteins. A major effort in the laboratory involves an ongoing study of human serum albumin (the principal protein in human plasma) and its interaction with various endogenous substances and pharmaceutical agents. Another focus is on antigenic and functional proteins from several pathogenic organisms including the human immunodeficiency virus (HIV) and the widespread parasitic genus, Schistosoma. My efforts this summer have been twofold: first, to identify clinically significant drug interactions involving albumin binding displacement and to initiate studies of the three-dimensional structure of albumin complexed with these agents, and secondly, to establish collaborative efforts to extend the lab's work on human pathogens.

Interaction effects between sender and receiver processes in indirect transmission of Campylobacter jejuni between broilers.

PubMed

van Bunnik, Bram A D; Hagenaars, Thomas J; Bolder, Nico M; Nodelijk, Gonnie; de Jong, Mart C M

2012-07-25

Infectious diseases in plants, animals and humans are often transmitted indirectly between hosts (or between groups of hosts), i.e. via some route through the environment instead of via direct contacts between these hosts. Here we study indirect transmission experimentally, using transmission of Campylobacter jejuni (C. jejuni) between spatially separated broilers as a model system. We distinguish three stages in the process of indirect transmission; (1) an infectious "sender" excretes the agent, after which (2) the agent is transported via some route to a susceptible "receiver", and subsequently (3) the receiver becomes colonised by the agent. The role of the sender and receiver side (stage 1 and stage 3) was studied here by using acidification of the drinking water as a modulation mechanism. In the experiment one control group and three treatment groups were monitored for the presence of C. jejuni by taking daily cloacal swabs. The three treatments consisted of acidification of the drinking water of the inoculated animals (the senders), acidification of the drinking water of the susceptible animals (the receivers) or acidification of the drinking water of both inoculated and susceptible animals. In the control group 12 animals got colonised out of a possible 40, in each treatment groups 3 animals out of a possible 40 were found colonised with C. jejuni. The results of the experiments show a significant decrease in transmission rate (β) between the control groups and treatment groups (p < 0.01 for all groups) but not between different treatments; there is a significant negative interaction effect when both the sender and the receiver group receive acidified drinking water (p = 0.01). This negative interaction effect could be due to selection of bacteria already at the sender side thereby diminishing the effect of acidification at the receiver side.

An opinion formation based binary optimization approach for feature selection

NASA Astrophysics Data System (ADS)

Hamedmoghadam, Homayoun; Jalili, Mahdi; Yu, Xinghuo

2018-02-01

This paper proposed a novel optimization method based on opinion formation in complex network systems. The proposed optimization technique mimics human-human interaction mechanism based on a mathematical model derived from social sciences. Our method encodes a subset of selected features to the opinion of an artificial agent and simulates the opinion formation process among a population of agents to solve the feature selection problem. The agents interact using an underlying interaction network structure and get into consensus in their opinions, while finding better solutions to the problem. A number of mechanisms are employed to avoid getting trapped in local minima. We compare the performance of the proposed method with a number of classical population-based optimization methods and a state-of-the-art opinion formation based method. Our experiments on a number of high dimensional datasets reveal outperformance of the proposed algorithm over others.

Evaluating the effect of human activity patterns on air pollution exposure using an integrated field-based and agent-based modelling framework

NASA Astrophysics Data System (ADS)

Schmitz, Oliver; Beelen, Rob M. J.; de Bakker, Merijn P.; Karssenberg, Derek

2015-04-01

Constructing spatio-temporal numerical models to support risk assessment, such as assessing the exposure of humans to air pollution, often requires the integration of field-based and agent-based modelling approaches. Continuous environmental variables such as air pollution are best represented using the field-based approach which considers phenomena as continuous fields having attribute values at all locations. When calculating human exposure to such pollutants it is, however, preferable to consider the population as a set of individuals each with a particular activity pattern. This would allow to account for the spatio-temporal variation in a pollutant along the space-time paths travelled by individuals, determined, for example, by home and work locations, road network, and travel times. Modelling this activity pattern requires an agent-based or individual based modelling approach. In general, field- and agent-based models are constructed with the help of separate software tools, while both approaches should play together in an interacting way and preferably should be combined into one modelling framework, which would allow for efficient and effective implementation of models by domain specialists. To overcome this lack in integrated modelling frameworks, we aim at the development of concepts and software for an integrated field-based and agent-based modelling framework. Concepts merging field- and agent-based modelling were implemented by extending PCRaster (http://www.pcraster.eu), a field-based modelling library implemented in C++, with components for 1) representation of discrete, mobile, agents, 2) spatial networks and algorithms by integrating the NetworkX library (http://networkx.github.io), allowing therefore to calculate e.g. shortest routes or total transport costs between locations, and 3) functions for field-network interactions, allowing to assign field-based attribute values to networks (i.e. as edge weights), such as aggregated or averaged concentration values. We demonstrate the approach by using six land use regression (LUR) models developed in the ESCAPE (European Study of Cohorts for Air Pollution Effects) project. These models calculate several air pollutants (e.g. NO2, NOx, PM2.5) for the entire Netherlands at a high (5 m) resolution. Using these air pollution maps, we compare exposure of individuals calculated at their x, y location of their home, their work place, and aggregated over the close surroundings of these locations. In addition, total exposure is accumulated over daily activity patterns, summing exposure at home, at the work place, and while travelling between home and workplace, by routing individuals over the Dutch road network, using the shortest route. Finally, we illustrate how routes can be calculated with the minimum total exposure (instead of shortest distance).

Intelligent Agents for the Digital Battlefield

DTIC Science & Technology

1998-11-01

specific outcome of our long term research will be the development of a collaborative agent technology system, CATS , that will provide the underlying...software infrastructure needed to build large, heterogeneous, distributed agent applications. CATS will provide a software environment through which multiple...intelligent agents may interact with other agents, both human and computational. In addition, CATS will contain a number of intelligent agent components that will be useful for a wide variety of applications.

A prototype system based on visual interactive SDM called VGC

NASA Astrophysics Data System (ADS)

Jia, Zelu; Liu, Yaolin; Liu, Yanfang

2009-10-01

In many application domains, data is collected and referenced by its geo-spatial location. Spatial data mining, or the discovery of interesting patterns in such databases, is an important capability in the development of database systems. Spatial data mining recently emerges from a number of real applications, such as real-estate marketing, urban planning, weather forecasting, medical image analysis, road traffic accident analysis, etc. It demands for efficient solutions for many new, expensive, and complicated problems. For spatial data mining of large data sets to be effective, it is also important to include humans in the data exploration process and combine their flexibility, creativity, and general knowledge with the enormous storage capacity and computational power of today's computers. Visual spatial data mining applies human visual perception to the exploration of large data sets. Presenting data in an interactive, graphical form often fosters new insights, encouraging the information and validation of new hypotheses to the end of better problem-solving and gaining deeper domain knowledge. In this paper a visual interactive spatial data mining prototype system (visual geo-classify) based on VC++6.0 and MapObject2.0 are designed and developed, the basic algorithms of the spatial data mining is used decision tree and Bayesian networks, and data classify are used training and learning and the integration of the two to realize. The result indicates it's a practical and extensible visual interactive spatial data mining tool.

Learning to make collective decisions: the impact of confidence escalation.

PubMed

Mahmoodi, Ali; Bang, Dan; Ahmadabadi, Majid Nili; Bahrami, Bahador

2013-01-01

Little is known about how people learn to take into account others' opinions in joint decisions. To address this question, we combined computational and empirical approaches. Human dyads made individual and joint visual perceptual decision and rated their confidence in those decisions (data previously published). We trained a reinforcement (temporal difference) learning agent to get the participants' confidence level and learn to arrive at a dyadic decision by finding the policy that either maximized the accuracy of the model decisions or maximally conformed to the empirical dyadic decisions. When confidences were shared visually without verbal interaction, RL agents successfully captured social learning. When participants exchanged confidences visually and interacted verbally, no collective benefit was achieved and the model failed to predict the dyadic behaviour. Behaviourally, dyad members' confidence increased progressively and verbal interaction accelerated this escalation. The success of the model in drawing collective benefit from dyad members was inversely related to confidence escalation rate. The findings show an automated learning agent can, in principle, combine individual opinions and achieve collective benefit but the same agent cannot discount the escalation suggesting that one cognitive component of collective decision making in human may involve discounting of overconfidence arising from interactions.

Software agents and the route to the information economy

PubMed Central

Kephart, Jeffrey O.

2002-01-01

Humans are on the verge of losing their status as the sole economic species on the planet. In private laboratories and in the Internet laboratory, researchers and developers are creating a variety of autonomous economically motivated software agents endowed with algorithms for maximizing profit or utility. Many economic software agents will function as miniature businesses, purchasing information inputs from other agents, combining and refining them into information goods and services, and selling them to humans or other agents. Their mutual interactions will form the information economy: a complex economic web of information goods and services that will adapt to the ever-changing needs of people and agents. The information economy will be the largest multiagent system ever conceived and an integral part of the world's economy. I discuss a possible route toward this vision, beginning with present-day Internet trends suggesting that agents will charge one another for information goods and services. Then, to establish that agents can be competent price setters, I describe some laboratory experiments pitting software bidding agents against human bidders. The agents' superior performance suggests they will be used on a broad scale, which in turn suggests that interactions among agents will become frequent and significant. How will this affect macroscopic economic behavior? I describe some interesting phenomena that my colleagues and I have observed in simulations of large populations of automated buyers and sellers, such as price war cycles. I conclude by discussing fundamental scientific challenges that remain to be addressed as we journey toward the information economy. PMID:12011399

Dynamic simulation of crime perpetration and reporting to examine community intervention strategies.

PubMed

Yonas, Michael A; Burke, Jessica G; Brown, Shawn T; Borrebach, Jeffrey D; Garland, Richard; Burke, Donald S; Grefenstette, John J

2013-10-01

To develop a conceptual computational agent-based model (ABM) to explore community-wide versus spatially focused crime reporting interventions to reduce community crime perpetrated by youth. Agents within the model represent individual residents and interact on a two-dimensional grid representing an abstract nonempirically grounded community setting. Juvenile agents are assigned initial random probabilities of perpetrating a crime and adults are assigned random probabilities of witnessing and reporting crimes. The agents' behavioral probabilities modify depending on the individual's experience with criminal behavior and punishment, and exposure to community crime interventions. Cost-effectiveness analyses assessed the impact of activating different percentages of adults to increase reporting and reduce community crime activity. Community-wide interventions were compared with spatially focused interventions, in which activated adults were focused in areas of highest crime prevalence. The ABM suggests that both community-wide and spatially focused interventions can be effective in reducing overall offenses, but their relative effectiveness may depend on the intensity and cost of the interventions. Although spatially focused intervention yielded localized reductions in crimes, such interventions were shown to move crime to nearby communities. Community-wide interventions can achieve larger reductions in overall community crime offenses than spatially focused interventions, as long as sufficient resources are available. The ABM demonstrates that community-wide and spatially focused crime strategies produce unique intervention dynamics influencing juvenile crime behaviors through the decisions and actions of community adults. It shows how such models might be used to investigate community-supported crime intervention programs by integrating community input and expertise and provides a simulated setting for assessing dimensions of cost comparison and intervention effect sustainability. ABM illustrates how intervention models might be used to investigate community-supported crime intervention programs.

The agent-based spatial information semantic grid

NASA Astrophysics Data System (ADS)

Cui, Wei; Zhu, YaQiong; Zhou, Yong; Li, Deren

2006-10-01

Analyzing the characteristic of multi-Agent and geographic Ontology, The concept of the Agent-based Spatial Information Semantic Grid (ASISG) is defined and the architecture of the ASISG is advanced. ASISG is composed with Multi-Agents and geographic Ontology. The Multi-Agent Systems are composed with User Agents, General Ontology Agent, Geo-Agents, Broker Agents, Resource Agents, Spatial Data Analysis Agents, Spatial Data Access Agents, Task Execution Agent and Monitor Agent. The architecture of ASISG have three layers, they are the fabric layer, the grid management layer and the application layer. The fabric layer what is composed with Data Access Agent, Resource Agent and Geo-Agent encapsulates the data of spatial information system so that exhibits a conceptual interface for the Grid management layer. The Grid management layer, which is composed with General Ontology Agent, Task Execution Agent and Monitor Agent and Data Analysis Agent, used a hybrid method to manage all resources that were registered in a General Ontology Agent that is described by a General Ontology System. The hybrid method is assembled by resource dissemination and resource discovery. The resource dissemination push resource from Local Ontology Agent to General Ontology Agent and the resource discovery pull resource from the General Ontology Agent to Local Ontology Agents. The Local Ontology Agent is derived from special domain and describes the semantic information of local GIS. The nature of the Local Ontology Agents can be filtrated to construct a virtual organization what could provides a global scheme. The virtual organization lightens the burdens of guests because they need not search information site by site manually. The application layer what is composed with User Agent, Geo-Agent and Task Execution Agent can apply a corresponding interface to a domain user. The functions that ASISG should provide are: 1) It integrates different spatial information systems on the semantic The Grid management layer establishes a virtual environment that integrates seamlessly all GIS notes. 2) When the resource management system searches data on different spatial information systems, it transfers the meaning of different Local Ontology Agents rather than access data directly. So the ability of search and query can be said to be on the semantic level. 3) The data access procedure is transparent to guests, that is, they could access the information from remote site as current disk because the General Ontology Agent could automatically link data by the Data Agents that link the Ontology concept to GIS data. 4) The capability of processing massive spatial data. Storing, accessing and managing massive spatial data from TB to PB; efficiently analyzing and processing spatial data to produce model, information and knowledge; and providing 3D and multimedia visualization services. 5) The capability of high performance computing and processing on spatial information. Solving spatial problems with high precision, high quality, and on a large scale; and process spatial information in real time or on time, with high-speed and high efficiency. 6) The capability of sharing spatial resources. The distributed heterogeneous spatial information resources are Shared and realizing integrated and inter-operated on semantic level, so as to make best use of spatial information resources,such as computing resources, storage devices, spatial data (integrating from GIS, RS and GPS), spatial applications and services, GIS platforms, 7) The capability of integrating legacy GIS system. A ASISG can not only be used to construct new advanced spatial application systems, but also integrate legacy GIS system, so as to keep extensibility and inheritance and guarantee investment of users. 8) The capability of collaboration. Large-scale spatial information applications and services always involve different departments in different geographic places, so remote and uniform services are needed. 9) The capability of supporting integration of heterogeneous systems. Large-scale spatial information systems are always synthetically applications, so ASISG should provide interoperation and consistency through adopting open and applied technology standards. 10) The capability of adapting dynamic changes. Business requirements, application patterns, management strategies, and IT products always change endlessly for any departments, so ASISG should be self-adaptive. Two examples are provided in this paper, those examples provide a detailed way on how you design your semantic grid based on Multi-Agent systems and Ontology. In conclusion, the semantic grid of spatial information system could improve the ability of the integration and interoperability of spatial information grid.

Uncovering Patterns of Inter-Urban Trip and Spatial Interaction from Social Media Check-In Data

PubMed Central

Liu, Yu; Sui, Zhengwei; Kang, Chaogui; Gao, Yong

2014-01-01

The article revisits spatial interaction and distance decay from the perspective of human mobility patterns and spatially-embedded networks based on an empirical data set. We extract nationwide inter-urban movements in China from a check-in data set that covers half a million individuals within 370 cities to analyze the underlying patterns of trips and spatial interactions. By fitting the gravity model, we find that the observed spatial interactions are governed by a power law distance decay effect. The obtained gravity model also closely reproduces the exponential trip displacement distribution. The movement of an individual, however, may not obey the same distance decay effect, leading to an ecological fallacy. We also construct a spatial network where the edge weights denote the interaction strengths. The communities detected from the network are spatially cohesive and roughly consistent with province boundaries. We attribute this pattern to different distance decay parameters between intra-province and inter-province trips. PMID:24465849

Uncovering patterns of inter-urban trip and spatial interaction from social media check-in data.

PubMed

Liu, Yu; Sui, Zhengwei; Kang, Chaogui; Gao, Yong

2014-01-01

The article revisits spatial interaction and distance decay from the perspective of human mobility patterns and spatially-embedded networks based on an empirical data set. We extract nationwide inter-urban movements in China from a check-in data set that covers half a million individuals within 370 cities to analyze the underlying patterns of trips and spatial interactions. By fitting the gravity model, we find that the observed spatial interactions are governed by a power law distance decay effect. The obtained gravity model also closely reproduces the exponential trip displacement distribution. The movement of an individual, however, may not obey the same distance decay effect, leading to an ecological fallacy. We also construct a spatial network where the edge weights denote the interaction strengths. The communities detected from the network are spatially cohesive and roughly consistent with province boundaries. We attribute this pattern to different distance decay parameters between intra-province and inter-province trips.

Global biogeography of human infectious diseases.

PubMed

Murray, Kris A; Preston, Nicholas; Allen, Toph; Zambrana-Torrelio, Carlos; Hosseini, Parviez R; Daszak, Peter

2015-10-13

The distributions of most infectious agents causing disease in humans are poorly resolved or unknown. However, poorly known and unknown agents contribute to the global burden of disease and will underlie many future disease risks. Existing patterns of infectious disease co-occurrence could thus play a critical role in resolving or anticipating current and future disease threats. We analyzed the global occurrence patterns of 187 human infectious diseases across 225 countries and seven epidemiological classes (human-specific, zoonotic, vector-borne, non-vector-borne, bacterial, viral, and parasitic) to show that human infectious diseases exhibit distinct spatial grouping patterns at a global scale. We demonstrate, using outbreaks of Ebola virus as a test case, that this spatial structuring provides an untapped source of prior information that could be used to tighten the focus of a range of health-related research and management activities at early stages or in data-poor settings, including disease surveillance, outbreak responses, or optimizing pathogen discovery. In examining the correlates of these spatial patterns, among a range of geographic, epidemiological, environmental, and social factors, mammalian biodiversity was the strongest predictor of infectious disease co-occurrence overall and for six of the seven disease classes examined, giving rise to a striking congruence between global pathogeographic and "Wallacean" zoogeographic patterns. This clear biogeographic signal suggests that infectious disease assemblages remain fundamentally constrained in their distributions by ecological barriers to dispersal or establishment, despite the homogenizing forces of globalization. Pathogeography thus provides an overarching context in which other factors promoting infectious disease emergence and spread are set.

Maintaining Engagement in Long-term Interventions with Relational Agents

PubMed Central

Bickmore, Timothy; Schulman, Daniel; Yin, Langxuan

2011-01-01

We discuss issues in designing virtual humans for applications which require long-term voluntary use, and the problem of maintaining engagement with users over time. Concepts and theories related to engagement from a variety of disciplines are reviewed. We describe a platform for conducting studies into long-term interactions between humans and virtual agents, and present the results of two longitudinal randomized controlled experiments in which the effect of manipulations of agent behavior on user engagement was assessed. PMID:21318052

Rationalizing spatial exploration patterns of wild animals and humans through a temporal discounting framework

PubMed Central

Namboodiri, Vijay Mohan K.; Levy, Joshua M.; Mihalas, Stefan; Sims, David W.; Hussain Shuler, Marshall G.

2016-01-01

Understanding the exploration patterns of foragers in the wild provides fundamental insight into animal behavior. Recent experimental evidence has demonstrated that path lengths (distances between consecutive turns) taken by foragers are well fitted by a power law distribution. Numerous theoretical contributions have posited that “Lévy random walks”—which can produce power law path length distributions—are optimal for memoryless agents searching a sparse reward landscape. It is unclear, however, whether such a strategy is efficient for cognitively complex agents, from wild animals to humans. Here, we developed a model to explain the emergence of apparent power law path length distributions in animals that can learn about their environments. In our model, the agent’s goal during search is to build an internal model of the distribution of rewards in space that takes into account the cost of time to reach distant locations (i.e., temporally discounting rewards). For an agent with such a goal, we find that an optimal model of exploration in fact produces hyperbolic path lengths, which are well approximated by power laws. We then provide support for our model by showing that humans in a laboratory spatial exploration task search space systematically and modify their search patterns under a cost of time. In addition, we find that path length distributions in a large dataset obtained from free-ranging marine vertebrates are well described by our hyperbolic model. Thus, we provide a general theoretical framework for understanding spatial exploration patterns of cognitively complex foragers. PMID:27385831

An Investigation on Social Representations: Inanimate Agent Can Mislead Dogs (Canis familiaris) in a Food Choice Task.

PubMed

Abdai, Judit; Gergely, Anna; Petró, Eszter; Topál, József; Miklósi, Ádám

2015-01-01

The nature of mental representation of others plays a crucial role in social interactions. Dogs present an ideal model species for the investigation of such mental representations because they develop social ties with both conspecifics and heterospecifics. Former studies found that dogs' preference for larger food quantity could be reversed by humans who indicate the smaller quantity. The question is whether this social bias is restricted to human partners. We suggest that after a short positive social experience, an unfamiliar moving inanimate agent (UMO) can also change dogs' choice between two food quantities. We tested four groups of dogs with different partners: In the (1) Helper UMO and (2) Helper UMO Control groups the partner was an interactive remote control car that helped the dog to obtain an otherwise unreachable food. In the (3) Non-helper UMO and (4) Human partner groups dogs had restricted interaction with the remote control car and the unfamiliar human partners. In the Human partner, Helper UMO and Helper UMO Control groups the partners were able to revert dogs' choice for the small amount by indicating the small one, but the Non-helper UMO was not. We suggest that dogs are able to generalize their wide range of experiences with humans to another type of agent as well, based on the recognition of similarities in simple behavioural patterns.

An Investigation on Social Representations: Inanimate Agent Can Mislead Dogs (Canis familiaris) in a Food Choice Task

PubMed Central

Abdai, Judit; Gergely, Anna; Petró, Eszter; Topál, József; Miklósi, Ádám

2015-01-01

The nature of mental representation of others plays a crucial role in social interactions. Dogs present an ideal model species for the investigation of such mental representations because they develop social ties with both conspecifics and heterospecifics. Former studies found that dogs’ preference for larger food quantity could be reversed by humans who indicate the smaller quantity. The question is whether this social bias is restricted to human partners. We suggest that after a short positive social experience, an unfamiliar moving inanimate agent (UMO) can also change dogs’ choice between two food quantities. We tested four groups of dogs with different partners: In the (1) Helper UMO and (2) Helper UMO Control groups the partner was an interactive remote control car that helped the dog to obtain an otherwise unreachable food. In the (3) Non-helper UMO and (4) Human partner groups dogs had restricted interaction with the remote control car and the unfamiliar human partners. In the Human partner, Helper UMO and Helper UMO Control groups the partners were able to revert dogs’ choice for the small amount by indicating the small one, but the Non-helper UMO was not. We suggest that dogs are able to generalize their wide range of experiences with humans to another type of agent as well, based on the recognition of similarities in simple behavioural patterns. PMID:26241747

A Novel Computer-Based Set-Up to Study Movement Coordination in Human Ensembles

PubMed Central

Alderisio, Francesco; Lombardi, Maria; Fiore, Gianfranco; di Bernardo, Mario

2017-01-01

Existing experimental works on movement coordination in human ensembles mostly investigate situations where each subject is connected to all the others through direct visual and auditory coupling, so that unavoidable social interaction affects their coordination level. Here, we present a novel computer-based set-up to study movement coordination in human groups so as to minimize the influence of social interaction among participants and implement different visual pairings between them. In so doing, players can only take into consideration the motion of a designated subset of the others. This allows the evaluation of the exclusive effects on coordination of the structure of interconnections among the players in the group and their own dynamics. In addition, our set-up enables the deployment of virtual computer players to investigate dyadic interaction between a human and a virtual agent, as well as group synchronization in mixed teams of human and virtual agents. We show how this novel set-up can be employed to study coordination both in dyads and in groups over different structures of interconnections, in the presence as well as in the absence of virtual agents acting as followers or leaders. Finally, in order to illustrate the capabilities of the architecture, we describe some preliminary results. The platform is available to any researcher who wishes to unfold the mechanisms underlying group synchronization in human ensembles and shed light on its socio-psychological aspects. PMID:28649217

Online Bahavior Aquisition of an Agent based on Coaching as Learning Assistance

NASA Astrophysics Data System (ADS)

Hirokawa, Masakazu; Suzuki, Kenji

This paper describes a novel methodology, namely ``Coaching'', which allows humans to give a subjective evaluation to an agent in an iterative manner. This is an interactive learning method to improve the reinforcement learning by modifying a reward function dynamically according to given evaluations by a trainer and the learning situation of the agent. We demonstrate that the agent can learn different reward functions by given instructions such as ``good or bad'' by human's observation, and can also obtain a set of behavior based on the learnt reward functions through several experiments.

A spatial web/agent-based model to support stakeholders' negotiation regarding land development.

PubMed

Pooyandeh, Majeed; Marceau, Danielle J

2013-11-15

Decision making in land management can be greatly enhanced if the perspectives of concerned stakeholders are taken into consideration. This often implies negotiation in order to reach an agreement based on the examination of multiple alternatives. This paper describes a spatial web/agent-based modeling system that was developed to support the negotiation process of stakeholders regarding land development in southern Alberta, Canada. This system integrates a fuzzy analytic hierarchy procedure within an agent-based model in an interactive visualization environment provided through a web interface to facilitate the learning and negotiation of the stakeholders. In the pre-negotiation phase, the stakeholders compare their evaluation criteria using linguistic expressions. Due to the uncertainty and fuzzy nature of such comparisons, a fuzzy Analytic Hierarchy Process is then used to prioritize the criteria. The negotiation starts by a development plan being submitted by a user (stakeholder) through the web interface. An agent called the proposer, which represents the proposer of the plan, receives this plan and starts negotiating with all other agents. The negotiation is conducted in a step-wise manner where the agents change their attitudes by assigning a new set of weights to their criteria. If an agreement is not achieved, a new location for development is proposed by the proposer agent. This process is repeated until a location is found that satisfies all agents to a certain predefined degree. To evaluate the performance of the model, the negotiation was simulated with four agents, one of which being the proposer agent, using two hypothetical development plans. The first plan was selected randomly; the other one was chosen in an area that is of high importance to one of the agents. While the agents managed to achieve an agreement about the location of the land development after three rounds of negotiation in the first scenario, seven rounds were required in the second scenario. The proposed web/agent-based model facilitates the interaction and learning among stakeholders when facing multiple alternatives. Copyright © 2013 Elsevier Ltd. All rights reserved.

The Effects of Animated Agents on Students' Achievement and Attitudes

ERIC Educational Resources Information Center

Unal-Colak, Figen; Ozan, Ozlem

2012-01-01

Animated agents are electronic agents that interact with learners through voice, visuals or text and that carry human-like characteristics such as gestures and facial expressions with the purpose of creating a social learning environment, and provide information and guidance and when required feedback and motivation to students during their…

Triggering social interactions: chimpanzees respond to imitation by a humanoid robot and request responses from it.

PubMed

Davila-Ross, Marina; Hutchinson, Johanna; Russell, Jamie L; Schaeffer, Jennifer; Billard, Aude; Hopkins, William D; Bard, Kim A

2014-05-01

Even the most rudimentary social cues may evoke affiliative responses in humans and promote social communication and cohesion. The present work tested whether such cues of an agent may also promote communicative interactions in a nonhuman primate species, by examining interaction-promoting behaviours in chimpanzees. Here, chimpanzees were tested during interactions with an interactive humanoid robot, which showed simple bodily movements and sent out calls. The results revealed that chimpanzees exhibited two types of interaction-promoting behaviours during relaxed or playful contexts. First, the chimpanzees showed prolonged active interest when they were imitated by the robot. Second, the subjects requested 'social' responses from the robot, i.e. by showing play invitations and offering toys or other objects. This study thus provides evidence that even rudimentary cues of a robotic agent may promote social interactions in chimpanzees, like in humans. Such simple and frequent social interactions most likely provided a foundation for sophisticated forms of affiliative communication to emerge.

Responses to alternative rainfall regimes and antipoaching in a migratory system.

PubMed

Holdo, Ricardo M; Galvin, Kathleen A; Knapp, Eli; Polasky, Stephen; Hilborn, Ray; Holt, Robert D

2010-03-01

Migratory ungulates may be particularly vulnerable to the challenges imposed by growing human populations and climate change. These species depend on vast areas to sustain their migratory behavior, and in many cases come into frequent contact with human populations outside protected areas. They may also act as spatial coupling agents allowing feedbacks between ecological systems and local economies, particularly in the agropastoral subsistence economies found in the African savanna biome. We used HUMENTS, a spatially realistic socioecological model of the Greater Serengeti Ecosystem in East Africa, to explore the potential impacts of changing climate and poaching on the migratory wildebeest (Connochaetes taurinus) population, the fire regime, and habitat structure in the ecosystem, as well as changes in the size and economic activities of the human population outside the protected area. Unlike earlier models, the HUMENTS model predicted only moderate declines in the wildebeest population associated with an increasing human population over the next century, with a gradual expansion of agriculture, more poaching, and increases in fire frequency and reduced tree density. Changes in rainfall were predicted to have strong asymmetric effects on the size and economic activity of the human population and on livestock, and more moderate effects on wildlife and other ecological indicators. Conversely, antipoaching had a stronger effect on the ecological portion of the system because of its effect on wildebeest (and therefore on fire and habitat structure), and a weaker effect on the socioeconomic component, except in areas directly adjacent to the protected-area boundary, which were affected by crop-raiding and the availability of wildlife as a source of income. The results highlight the strong direct and indirect effects of rainfall on the various components of socioecological systems in semiarid environments, and the key role of mobile wildlife populations as agents of spatial coupling between the human-dominated and natural portions of ecosystems. They also underscore the fundamental importance of considering the spatial configuration of hunting refuges across the landscape in relation to human populations.

Examining the Resilience of Crop Production, Livestock Carrying Capacity, and Woodland Density in a Rural Zimbabwean Socio-Ecological System Using Agent-Based Models Representing Human Management Decisions

NASA Astrophysics Data System (ADS)

Eitzel Solera, M. V.; Neves, K.; Veski, A.; Solera, J.; Omoju, O. E.; Mawere Ndlovu, A.; Wilson, K.

2016-12-01

As climate change increases the pressures on arid ecosystems by changing timing and amount of rainfall, understanding the ways in which human management choices affect the resilience of these systems becomes key to their sustainability. On marginal farmland in Mazvihwa, Midlands Province, the historical carrying capacity of livestock has been consistently surprisingly high. We explore this phenomenon by building an agent-based model in NetLogo from a wealth of long-term data generated by the community-based participatory research team of The Muonde Trust, a Zimbabwean non-governmental organization. We combine the accumulated results of 35 years of indigenous and local knowledge with national datasets such as rainfall records. What factors keep the carrying capacity high? What management choices can maintain crops, livestock, and woodland at levels necessary for the community's survival? How do these choices affect long-term sustainability, and does increasing resilience at one scale reduce resilience at another scale? We use our agent-based model to explore the feedbacks between crops, livestock, and woodland and the impacts of various human choices as well as temporal and spatial ecological variation. By testing different scenarios, we disentangle the complex interactions between these components. We find that some factors out of the community's control can strongly affect the sustainability of the system through times of drought, and that supplementary feed may maintain livestock potentially at the expense of other resources. The challenges to resilience encountered by the farmers in Mazvihwa are not unique - many indigenous and rural people face drought and the legacies of colonialism, which contribute to lowered resilience to external challenges such as climate change, epidemics, and political instability. Using the agent-based model as a tool for synthesis and exploration initiates discussion about resilience-enhancing management choices for Mazvihwa's farmer-researchers.

Tools to Assess Community-Based Cumulative Risk and Exposures

EPA Science Inventory

Multiple agents and stressors can interact in a given community to adversely affect human and ecological conditions. A cumulative risk assessment (CRA) analyzes, characterizes, and potentially quantifies the effects from multiple stressors, which include chemical agents (for exam...

The Effect of Shared Information on Pilot/Controller And Controller/Controller Interactions

NASA Technical Reports Server (NTRS)

Hansman, R. John

1999-01-01

In order to respond to the increasing demand on limited airspace system resources, a number of applications of information technology have been proposed, or are under investigation, to improve the efficiency, capacity and reliability of ATM (Asynchronous Transfer Mode) operations. Much of the attention in advanced ATM technology has focused on advanced automation systems or decision aiding systems to improve the performance of individual Pilots or Controllers. However, the most significant overall potential for information technology appears to he in increasing the shared information between human agents such as Pilots, Controllers or between interacting Controllers or traffic flow managers. Examples of proposed shared information systems in the US include; Controller Pilot Databank Communication (CPDLC), Traffic Management Advisor (TMA); Automatic Dependent Surveillance (ADS); Collaborative Decision Making (CDM) and NAS Level Common Information Exchange. Air Traffic Management is fundamentally a human centered process consisting of the negotiation, execution and monitoring of contracts between human agents for the allocation of limited airspace, runway and airport surface resources. The decision processes within ATM tend to be Semistructured. Many of the routine elements in ATM decision making on the part of the Controllers or Pilots are well Structured and can be represented by well defined rules or procedures. However in disrupted conditions, the ATM decision processes are often Unstructured and cannot be reduced to a set of discrete rules. As a consequence, the ability to automate ATM processes will be limited and ATM will continue to be a human centric process where the responsibility and the authority for the negotiation will continue to rest with human Controllers and Pilots. The use of information technology to support the human decision process will therefore be an important aspect of ATM modernization. The premise of many of the proposed shared information systems is that the performance of ATM operations will improve with an increase in Shared Situation Awareness between agents (Pilots, Controller, Dispatchers). This will allow better informed control decisions and an improved ability to negotiate between agents. A common information basis may reduce communication load and may increase the level of collaboration in the decision process. In general, information sharing is expected to have advantages for all agents within the system. However there are important questions which remain to be,addressed. For example: What shared information is most important for developing effective Shared Situation Awareness? Are there issues of information saturation? Does information parity create ambiguity in control authority? Will information sharing induce undesirable or unstable gaming behavior between agents? This paper will explore the effect of current and proposed information sharing between different ATM agents. The paper will primarily concentrate on bilateral tactical interactions between specific agents (Pilot/Controller; Controller/Controller; Pilot/Dispatcher; Controller/Dispatcher) however it will also briefly discuss multilateral interaction and more strategic interactions.

Design of a multi-agent hydroeconomic model to simulate a complex human-water system: Early insights from the Jordan Water Project

NASA Astrophysics Data System (ADS)

Yoon, J.; Klassert, C. J. A.; Lachaut, T.; Selby, P. D.; Knox, S.; Gorelick, S.; Rajsekhar, D.; Tilmant, A.; Avisse, N.; Harou, J. J.; Gawel, E.; Klauer, B.; Mustafa, D.; Talozi, S.; Sigel, K.

2015-12-01

Our work focuses on development of a multi-agent, hydroeconomic model for purposes of water policy evaluation in Jordan. The model adopts a modular approach, integrating biophysical modules that simulate natural and engineered phenomena with human modules that represent behavior at multiple levels of decision making. The hydrologic modules are developed using spatially-distributed groundwater and surface water models, which are translated into compact simulators for efficient integration into the multi-agent model. For the groundwater model, we adopt a response matrix method approach in which a 3-dimensional MODFLOW model of a complex regional groundwater system is converted into a linear simulator of groundwater response by pre-processing drawdown results from several hundred numerical simulation runs. Surface water models for each major surface water basin in the country are developed in SWAT and similarly translated into simple rainfall-runoff functions for integration with the multi-agent model. The approach balances physically-based, spatially-explicit representation of hydrologic systems with the efficiency required for integration into a complex multi-agent model that is computationally amenable to robust scenario analysis. For the multi-agent model, we explicitly represent human agency at multiple levels of decision making, with agents representing riparian, management, supplier, and water user groups. The agents' decision making models incorporate both rule-based heuristics as well as economic optimization. The model is programmed in Python using Pynsim, a generalizable, open-source object-oriented code framework for modeling network-based water resource systems. The Jordan model is one of the first applications of Pynsim to a real-world water management case study. Preliminary results from a tanker market scenario run through year 2050 are presented in which several salient features of the water system are investigated: competition between urban and private farmer agents, the emergence of a private tanker market, disparities in economic wellbeing to different user groups caused by unique supply conditions, and response of the complex system to various policy interventions.

Discovering spatio-temporal models of the spread of West Nile virus.

PubMed

Orme-Zavaleta, Jennifer; Jorgensen, Jane; D'Ambrosio, Bruce; Altendorf, Eric; Rossignol, Philippe A

2006-04-01

Emerging infectious diseases are characterized by complex interactions among disease agents, vectors, wildlife, humans, and the environment. Since the appearance of West Nile virus (WNV) in New York City in 1999, it has infected over 8,000 people in the United States, resulting in several hundred deaths in 46 contiguous states. The virus is transmitted by mosquitoes and maintained in various bird reservoir hosts. Its unexpected introduction, high morbidity, and rapid spread have left public health agencies facing severe time constraints in a theory-poor environment, dependent largely on observational data collected by independent survey efforts and much uncertainty. Current knowledge may be expressed as a priori constraints on models learned from data. Accordingly, we applied a Bayesian probabilistic relational approach to generate spatially and temporally linked models from heterogeneous data sources. Using data collected from multiple independent sources in Maryland, we discovered the integrated context in which infected birds are plausible indicators for positive mosquito pools and human cases for 2001 and 2002.

Advice Taking from Humans and Machines: An fMRI and Effective Connectivity Study.

PubMed

Goodyear, Kimberly; Parasuraman, Raja; Chernyak, Sergey; Madhavan, Poornima; Deshpande, Gopikrishna; Krueger, Frank

2016-01-01

With new technological advances, advice can come from different sources such as machines or humans, but how individuals respond to such advice and the neural correlates involved need to be better understood. We combined functional MRI and multivariate Granger causality analysis with an X-ray luggage-screening task to investigate the neural basis and corresponding effective connectivity involved with advice utilization from agents framed as experts. Participants were asked to accept or reject good or bad advice from a human or machine agent with low reliability (high false alarm rate). We showed that unreliable advice decreased performance overall and participants interacting with the human agent had a greater depreciation of advice utilization during bad advice compared to the machine agent. These differences in advice utilization can be perceivably due to reevaluation of expectations arising from association of dispositional credibility for each agent. We demonstrated that differences in advice utilization engaged brain regions that may be associated with evaluation of personal characteristics and traits (precuneus, posterior cingulate cortex, temporoparietal junction) and interoception (posterior insula). We found that the right posterior insula and left precuneus were the drivers of the advice utilization network that were reciprocally connected to each other and also projected to all other regions. Our behavioral and neuroimaging results have significant implications for society because of progressions in technology and increased interactions with machines.

An agent-based hydroeconomic model to evaluate water policies in Jordan

NASA Astrophysics Data System (ADS)

Yoon, J.; Gorelick, S.

2014-12-01

Modern water systems can be characterized by a complex network of institutional and private actors that represent competing sectors and interests. Identifying solutions to enhance water security in such systems calls for analysis that can adequately account for this level of complexity and interaction. Our work focuses on the development of a hierarchical, multi-agent, hydroeconomic model that attempts to realistically represent complex interactions between hydrologic and multi-faceted human systems. The model is applied to Jordan, one of the most water-poor countries in the world. In recent years, the water crisis in Jordan has escalated due to an ongoing drought and influx of refugees from regional conflicts. We adopt a modular approach in which biophysical modules simulate natural and engineering phenomena, and human modules represent behavior at multiple scales of decision making. The human modules employ agent-based modeling, in which agents act as autonomous decision makers at the transboundary, state, organizational, and user levels. A systematic nomenclature and conceptual framework is used to characterize model agents and modules. Concepts from the Unified Modeling Language (UML) are adopted to promote clear conceptualization of model classes and process sequencing, establishing a foundation for full deployment of the integrated model in a scalable object-oriented programming environment. Although the framework is applied to the Jordanian water context, it is generalizable to other regional human-natural freshwater supply systems.

Advice Taking from Humans and Machines: An fMRI and Effective Connectivity Study

PubMed Central

Goodyear, Kimberly; Parasuraman, Raja; Chernyak, Sergey; Madhavan, Poornima; Deshpande, Gopikrishna; Krueger, Frank

2016-01-01

With new technological advances, advice can come from different sources such as machines or humans, but how individuals respond to such advice and the neural correlates involved need to be better understood. We combined functional MRI and multivariate Granger causality analysis with an X-ray luggage-screening task to investigate the neural basis and corresponding effective connectivity involved with advice utilization from agents framed as experts. Participants were asked to accept or reject good or bad advice from a human or machine agent with low reliability (high false alarm rate). We showed that unreliable advice decreased performance overall and participants interacting with the human agent had a greater depreciation of advice utilization during bad advice compared to the machine agent. These differences in advice utilization can be perceivably due to reevaluation of expectations arising from association of dispositional credibility for each agent. We demonstrated that differences in advice utilization engaged brain regions that may be associated with evaluation of personal characteristics and traits (precuneus, posterior cingulate cortex, temporoparietal junction) and interoception (posterior insula). We found that the right posterior insula and left precuneus were the drivers of the advice utilization network that were reciprocally connected to each other and also projected to all other regions. Our behavioral and neuroimaging results have significant implications for society because of progressions in technology and increased interactions with machines. PMID:27867351

Emergence of cooperation as a non-equilibrium transition in noisy spatial games

NASA Astrophysics Data System (ADS)

Menon, Shakti N.; Sasidevan, V.; Sinha, Sitabhra

2018-04-01

The emergence of cooperation among selfish agents that have no incentive to cooperate is a non-trivial phenomenon that has long intrigued biologists, social scientists and physicists. The iterated Prisoner's Dilemma (IPD) game provides a natural framework for investigating this phenomenon. Here, agents repeatedly interact with their opponents, and their choice to either cooperate or defect is determined at each round by knowledge of the previous outcomes. The spatial version of IPD, where each agent interacts only with their nearest neighbors on a specified connection topology, has been used to study the evolution of cooperation under conditions of bounded rationality. In this paper we study how the collective behavior that arises from the simultaneous actions of the agents (implemented by synchronous update) is affected by (i) uncertainty, measured as noise intensity K, (ii) the payoff b, quantifying the temptation to defect and (iii) the nature of the underlying connection topology. In particular, we study the phase transitions between states characterized by distinct collective dynamics as the connection topology is gradually altered from a two-dimensional lattice to a random network. This is achieved by rewiring links between agents with a probability p following the small-world network construction paradigm. On crossing a specified threshold value of b, the game switches from being Prisoner's Dilemma, characterized by a unique equilibrium, to Stag Hunt, a well-known coordination game having multiple equilibria. We observe that the system can exhibit three collective states corresponding to a pair of absorbing states (viz., all agents cooperating or defecting) and a fluctuating state characterized by agents switching intermittently between cooperation and defection. As noise and temptation can be interpreted as temperature and an external field respectively, a strong analogy can be drawn between the phase diagrams of such games with that of interacting spin systems. Considering the 3-dimensional p-K-b parameter space allows us to investigate the different phase transitions that occur between these collective states and characterize them using finite-size scaling. We find that the values of the critical exponents depend on the connection topology and are different from the Directed Percolation (DP) universality class.

Building an adaptive agent to monitor and repair the electrical power system of an orbital satellite

NASA Technical Reports Server (NTRS)

Tecuci, Gheorghe; Hieb, Michael R.; Dybala, Tomasz

1995-01-01

Over several years we have developed a multistrategy apprenticeship learning methodology for building knowledge-based systems. Recently we have developed and applied our methodology to building intelligent agents. This methodology allows a subject matter expert to build an agent in the same way in which the expert would teach a human apprentice. The expert will give the agent specific examples of problems and solutions, explanations of these solutions, or supervise the agent as it solves new problems. During such interactions, the agent learns general rules and concepts, continuously extending and improving its knowledge base. In this paper we present initial results on applying this methodology to build an intelligent adaptive agent for monitoring and repair of the electrical power system of an orbital satellite, stressing the interaction with the expert during apprenticeship learning.

Semantic Interaction for Sensemaking: Inferring Analytical Reasoning for Model Steering.

PubMed

Endert, A; Fiaux, P; North, C

2012-12-01

Visual analytic tools aim to support the cognitively demanding task of sensemaking. Their success often depends on the ability to leverage capabilities of mathematical models, visualization, and human intuition through flexible, usable, and expressive interactions. Spatially clustering data is one effective metaphor for users to explore similarity and relationships between information, adjusting the weighting of dimensions or characteristics of the dataset to observe the change in the spatial layout. Semantic interaction is an approach to user interaction in such spatializations that couples these parametric modifications of the clustering model with users' analytic operations on the data (e.g., direct document movement in the spatialization, highlighting text, search, etc.). In this paper, we present results of a user study exploring the ability of semantic interaction in a visual analytic prototype, ForceSPIRE, to support sensemaking. We found that semantic interaction captures the analytical reasoning of the user through keyword weighting, and aids the user in co-creating a spatialization based on the user's reasoning and intuition.

Rigorous Results for the Distribution of Money on Connected Graphs

NASA Astrophysics Data System (ADS)

Lanchier, Nicolas; Reed, Stephanie

2018-05-01

This paper is concerned with general spatially explicit versions of three stochastic models for the dynamics of money that have been introduced and studied numerically by statistical physicists: the uniform reshuffling model, the immediate exchange model and the model with saving propensity. All three models consist of systems of economical agents that consecutively engage in pairwise monetary transactions. Computer simulations performed in the physics literature suggest that, when the number of agents and the average amount of money per agent are large, the limiting distribution of money as time goes to infinity approaches the exponential distribution for the first model, the gamma distribution with shape parameter two for the second model and a distribution similar but not exactly equal to a gamma distribution whose shape parameter depends on the saving propensity for the third model. The main objective of this paper is to give rigorous proofs of these conjectures and also extend these conjectures to generalizations of the first two models and a variant of the third model that include local rather than global interactions, i.e., instead of choosing the two interacting agents uniformly at random from the system, the agents are located on the vertex set of a general connected graph and can only interact with their neighbors.

Analyzing Human-Landscape Interactions: Tools That Integrate

NASA Astrophysics Data System (ADS)

Zvoleff, Alex; An, Li

2014-01-01

Humans have transformed much of Earth's land surface, giving rise to loss of biodiversity, climate change, and a host of other environmental issues that are affecting human and biophysical systems in unexpected ways. To confront these problems, environmental managers must consider human and landscape systems in integrated ways. This means making use of data obtained from a broad range of methods (e.g., sensors, surveys), while taking into account new findings from the social and biophysical science literatures. New integrative methods (including data fusion, simulation modeling, and participatory approaches) have emerged in recent years to address these challenges, and to allow analysts to provide information that links qualitative and quantitative elements for policymakers. This paper brings attention to these emergent tools while providing an overview of the tools currently in use for analysis of human-landscape interactions. Analysts are now faced with a staggering array of approaches in the human-landscape literature—in an attempt to bring increased clarity to the field, we identify the relative strengths of each tool, and provide guidance to analysts on the areas to which each tool is best applied. We discuss four broad categories of tools: statistical methods (including survival analysis, multi-level modeling, and Bayesian approaches), GIS and spatial analysis methods, simulation approaches (including cellular automata, agent-based modeling, and participatory modeling), and mixed-method techniques (such as alternative futures modeling and integrated assessment). For each tool, we offer an example from the literature of its application in human-landscape research. Among these tools, participatory approaches are gaining prominence for analysts to make the broadest possible array of information available to researchers, environmental managers, and policymakers. Further development of new approaches of data fusion and integration across sites or disciplines pose an important challenge for future work in integrating human and landscape components.

New activity pattern in human interactive dynamics

NASA Astrophysics Data System (ADS)

Formentin, Marco; Lovison, Alberto; Maritan, Amos; Zanzotto, Giovanni

2015-09-01

We investigate the response function of human agents as demonstrated by written correspondence, uncovering a new pattern for how the reactive dynamics of individuals is distributed across the set of each agent’s contacts. In long-term empirical data on email, we find that the set of response times considered separately for the messages to each different correspondent of a given writer, generate a family of heavy-tailed distributions, which have largely the same features for all agents, and whose characteristic times grow exponentially with the rank of each correspondent. We furthermore show that this new behavioral pattern emerges robustly by considering weighted moving averages of the priority-conditioned response-time probabilities generated by a basic prioritization model. Our findings clarify how the range of priorities in the inputs from one’s environment underpin and shape the dynamics of agents embedded in a net of reactive relations. These newly revealed activity patterns might be universal, being present in other general interactive environments, and constrain future models of communication and interaction networks, affecting their architecture and evolution.

Visually induced plasticity of auditory spatial perception in macaques.

PubMed

Woods, Timothy M; Recanzone, Gregg H

2004-09-07

When experiencing spatially disparate visual and auditory stimuli, a common percept is that the sound originates from the location of the visual stimulus, an illusion known as the ventriloquism effect. This illusion can persist for tens of minutes, a phenomenon termed the ventriloquism aftereffect. The underlying neuronal mechanisms of this rapidly induced plasticity remain unclear; indeed, it remains untested whether similar multimodal interactions occur in other species. We therefore tested whether macaque monkeys experience the ventriloquism aftereffect similar to the way humans do. The ability of two monkeys to determine which side of the midline a sound was presented from was tested before and after a period of 20-60 min in which the monkeys experienced either spatially identical or spatially disparate auditory and visual stimuli. In agreement with human studies, the monkeys did experience a shift in their auditory spatial perception in the direction of the spatially disparate visual stimulus, and the aftereffect did not transfer across sounds that differed in frequency by two octaves. These results show that macaque monkeys experience the ventriloquism aftereffect similar to the way humans do in all tested respects, indicating that these multimodal interactions are a basic phenomenon of the central nervous system.

Top-down modulation of motor priming by belief about animacy.

PubMed

Liepelt, Roman; Brass, Marcel

2010-01-01

There is recent evidence that we directly map observed actions of other agents onto our own motor repertoire, referred to as direct matching (Iacoboni et al., 1999). This was shown when we are actively engaged in joint action with others' (Sebanz et al. 2003) and also when observing irrelevant movements while executing congruent or incongruent movements (Brass et al., 2000). However, an open question is whether direct matching in human beings is limited to the perception of intentional agents. Recent research provides contradictory evidence with respect to the question whether the direct matching system has a biological bias possibly emerging from perceptual differences of the stimulus display. In this study all participants performed a motor priming task observing the identical animation showing finger lifting movements of a hand in a leather glove. Before running the experiment we presented either a human hand or a wooden analog hand wearing the leather glove. We found a motor priming effect for both human and wooden hands. However, motor priming was larger when participants believed that they interacted with a human hand than when they believed to interact with a wooden hand. The stronger motor priming effect for the biological agent suggests that the "direct matching system" is tuned to represent actions of animate agents.

BDNF and TNF-α polymorphisms in memory.

PubMed

Yogeetha, B S; Haupt, L M; McKenzie, K; Sutherland, H G; Okolicsyani, R K; Lea, R A; Maher, B H; Chan, R C K; Shum, D H K; Griffiths, L R

2013-09-01

Here, we investigate the genetic basis of human memory in healthy individuals and the potential role of two polymorphisms, previously implicated in memory function. We have explored aspects of retrospective and prospective memory including semantic, short term, working and long-term memory in conjunction with brain derived neurotrophic factor (BDNF) and tumor necrosis factor-alpha (TNF-α). The memory scores for healthy individuals in the population were obtained for each memory type and the population was genotyped via restriction fragment length polymorphism for the BDNF rs6265 (Val66Met) SNP and via pyrosequencing for the TNF-α rs113325588 SNP. Using univariate ANOVA, a significant association of the BDNF polymorphism with visual and spatial memory retention and a significant association of the TNF-α polymorphism was observed with spatial memory retention. In addition, a significant interactive effect between BDNF and TNF-α polymorphisms was observed in spatial memory retention. In practice visual memory involves spatial information and the two memory systems work together, however our data demonstrate that individuals with the Val/Val BDNF genotype have poorer visual memory but higher spatial memory retention, indicating a level of interaction between TNF-α and BDNF in spatial memory retention. This is the first study to use genetic analysis to determine the interaction between BDNF and TNF-α in relation to memory in normal adults and provides important information regarding the effect of genetic determinants and gene interactions on human memory.

Interacting With Robots to Investigate the Bases of Social Interaction.

PubMed

Sciutti, Alessandra; Sandini, Giulio

2017-12-01

Humans show a great natural ability at interacting with each other. Such efficiency in joint actions depends on a synergy between planned collaboration and emergent coordination, a subconscious mechanism based on a tight link between action execution and perception. This link supports phenomena as mutual adaptation, synchronization, and anticipation, which cut drastically the delays in the interaction and the need of complex verbal instructions and result in the establishment of joint intentions, the backbone of social interaction. From a neurophysiological perspective, this is possible, because the same neural system supporting action execution is responsible of the understanding and the anticipation of the observed action of others. Defining which human motion features allow for such emergent coordination with another agent would be crucial to establish more natural and efficient interaction paradigms with artificial devices, ranging from assistive and rehabilitative technology to companion robots. However, investigating the behavioral and neural mechanisms supporting natural interaction poses substantial problems. In particular, the unconscious processes at the basis of emergent coordination (e.g., unintentional movements or gazing) are very difficult-if not impossible-to restrain or control in a quantitative way for a human agent. Moreover, during an interaction, participants influence each other continuously in a complex way, resulting in behaviors that go beyond experimental control. In this paper, we propose robotics technology as a potential solution to this methodological problem. Robots indeed can establish an interaction with a human partner, contingently reacting to his actions without losing the controllability of the experiment or the naturalness of the interactive scenario. A robot could represent an "interactive probe" to assess the sensory and motor mechanisms underlying human-human interaction. We discuss this proposal with examples from our research with the humanoid robot iCub, showing how an interactive humanoid robot could be a key tool to serve the investigation of the psychological and neuroscientific bases of social interaction.

Brain-Computer Interfaces: A Neuroscience Paradigm of Social Interaction? A Matter of Perspective

PubMed Central

Mattout, Jérémie

2012-01-01

A number of recent studies have put human subjects in true social interactions, with the aim of better identifying the psychophysiological processes underlying social cognition. Interestingly, this emerging Neuroscience of Social Interactions (NSI) field brings up challenges which resemble important ones in the field of Brain-Computer Interfaces (BCI). Importantly, these challenges go beyond common objectives such as the eventual use of BCI and NSI protocols in the clinical domain or common interests pertaining to the use of online neurophysiological techniques and algorithms. Common fundamental challenges are now apparent and one can argue that a crucial one is to develop computational models of brain processes relevant to human interactions with an adaptive agent, whether human or artificial. Coupled with neuroimaging data, such models have proved promising in revealing the neural basis and mental processes behind social interactions. Similar models could help BCI to move from well-performing but offline static machines to reliable online adaptive agents. This emphasizes a social perspective to BCI, which is not limited to a computational challenge but extends to all questions that arise when studying the brain in interaction with its environment. PMID:22675291

Using a cellular model to explore human-facilitated spread of risk of EAB in Minnesota

Treesearch

Anantha Prasad; Louis Iverson; Matthew Peters; Steve Matthews

2011-01-01

The Emerald Ash Borer has made inroads to Minnesota in the past two years, killing ash trees. We use our spatially explicit cell based model called EAB-SHIFT to calculate the risk of infestation owing to flight characteristics and short distance movement of the insect (insect flight model, IFM), and the human facilitated agents like roads, campgrounds etc. (insect ride...

Climate Predictors of the Spatial Distribution of Human Plague Cases in the West Nile Region of Uganda

PubMed Central

MacMillan, Katherine; Monaghan, Andrew J.; Apangu, Titus; Griffith, Kevin S.; Mead, Paul S.; Acayo, Sarah; Acidri, Rogers; Moore, Sean M.; Mpanga, Joseph Tendo; Enscore, Russel E.; Gage, Kenneth L.; Eisen, Rebecca J.

2012-01-01

East Africa has been identified as a region where vector-borne and zoonotic diseases are most likely to emerge or re-emerge and where morbidity and mortality from these diseases is significant. Understanding when and where humans are most likely to be exposed to vector-borne and zoonotic disease agents in this region can aid in targeting limited prevention and control resources. Often, spatial and temporal distributions of vectors and vector-borne disease agents are predictable based on climatic variables. However, because of coarse meteorological observation networks, appropriately scaled and accurate climate data are often lacking for Africa. Here, we use a recently developed 10-year gridded meteorological dataset from the Advanced Weather Research and Forecasting Model to identify climatic variables predictive of the spatial distribution of human plague cases in the West Nile region of Uganda. Our logistic regression model revealed that within high elevation sites (above 1,300 m), plague risk was positively associated with rainfall during the months of February, October, and November and negatively associated with rainfall during the month of June. These findings suggest that areas that receive increased but not continuous rainfall provide ecologically conducive conditions for Yersinia pestis transmission in this region. This study serves as a foundation for similar modeling efforts of other vector-borne and zoonotic disease in regions with sparse observational meteorologic networks. PMID:22403328

Ticks and Tick-Borne Infections: Complex Ecology, Agents, and Host Interactions.

PubMed

Wikel, Stephen K

2018-06-20

Ticks transmit the most diverse array of infectious agents of any arthropod vector. Both ticks and the microbes they transmit are recognized as significant threats to human and veterinary public health. This article examines the potential impacts of climate change on the distribution of ticks and the infections they transmit; the emergence of novel tick-borne pathogens, increasing geographic range and incidence of tick-borne infections; and advances in the characterization of tick saliva mediated modulation of host defenses and the implications of those interactions for transmission, establishment, and control of tick infestation and tick-borne infectious agents.

The Hologram in My Hand: How Effective is Interactive Exploration of 3D Visualizations in Immersive Tangible Augmented Reality?

PubMed

Bach, Benjamin; Sicat, Ronell; Beyer, Johanna; Cordeil, Maxime; Pfister, Hanspeter

2018-01-01

We report on a controlled user study comparing three visualization environments for common 3D exploration. Our environments differ in how they exploit natural human perception and interaction capabilities. We compare an augmented-reality head-mounted display (Microsoft HoloLens), a handheld tablet, and a desktop setup. The novel head-mounted HoloLens display projects stereoscopic images of virtual content into a user's real world and allows for interaction in-situ at the spatial position of the 3D hologram. The tablet is able to interact with 3D content through touch, spatial positioning, and tangible markers, however, 3D content is still presented on a 2D surface. Our hypothesis is that visualization environments that match human perceptual and interaction capabilities better to the task at hand improve understanding of 3D visualizations. To better understand the space of display and interaction modalities in visualization environments, we first propose a classification based on three dimensions: perception, interaction, and the spatial and cognitive proximity of the two. Each technique in our study is located at a different position along these three dimensions. We asked 15 participants to perform four tasks, each task having different levels of difficulty for both spatial perception and degrees of freedom for interaction. Our results show that each of the tested environments is more effective for certain tasks, but that generally the desktop environment is still fastest and most precise in almost all cases.

THE EVOLUTION OF RESTRAINT IN BACTERIAL BIOFILMS UNDER NONTRANSITIVE COMPETITION

PubMed Central

Prado, Federico; Kerr, Benjamin

2009-01-01

Theoretical and empirical evidence indicates that competing species can coexist if dispersal, migration, and competitive interactions occur over relatively small spatial scales. In particular, spatial structure appears to be critical to certain communities with nontransitive competition. A typical nontransitive system involves three competing species that satisfy a relationship similar to the children’s game of rock–paper–scissors. Although the ecological dynamics of nontransitive systems in spatially structured communities have received some attention, fewer studies have incorporated evolutionary change. Here we investigate evolution within toxic bacterial biofilms using an agent-based simulation that represents a nontransitive community containing three populations of Escherichia coli. In structured, nontransitive communities, strains evolve that do not maximize their competitive ability: They do not reduce their probability of death to a minimum or increase their toxicity to a maximum. That is, types evolve that exercise restraint. We show that nontransitivity and spatial structure (in the form of localized interactions) are both necessary for the evolution of restraint in these biofilms. PMID:18039324

The evolution of restraint in bacterial biofilms under nontransitive competition.

PubMed

Prado, Federico; Kerr, Benjamin

2008-03-01

Theoretical and empirical evidence indicates that competing species can coexist if dispersal, migration, and competitive interactions occur over relatively small spatial scales. In particular, spatial structure appears to be critical to certain communities with nontransitive competition. A typical nontransitive system involves three competing species that satisfy a relationship similar to the children's game of rock-paper-scissors. Although the ecological dynamics of nontransitive systems in spatially structured communities have received some attention, fewer studies have incorporated evolutionary change. Here we investigate evolution within toxic bacterial biofilms using an agent-based simulation that represents a nontransitive community containing three populations of Escherichia coli. In structured, nontransitive communities, strains evolve that do not maximize their competitive ability: They do not reduce their probability of death to a minimum or increase their toxicity to a maximum. That is, types evolve that exercise restraint. We show that nontransitivity and spatial structure (in the form of localized interactions) are both necessary for the evolution of restraint in these biofilms.

Research on monocentric model of urbanization by agent-based simulation

NASA Astrophysics Data System (ADS)

Xue, Ling; Yang, Kaizhong

2008-10-01

Over the past years, GIS have been widely used for modeling urbanization from a variety of perspectives such as digital terrain representation and overlay analysis using cell-based data platform. Similarly, simulation of urban dynamics has been achieved with the use of Cellular Automata. In contrast to these approaches, agent-based simulation provides a much more powerful set of tools. This allows researchers to set up a counterpart for real environmental and urban systems in computer for experimentation and scenario analysis. This Paper basically reviews the research on the economic mechanism of urbanization and an agent-based monocentric model is setup for further understanding the urbanization process and mechanism in China. We build an endogenous growth model with dynamic interactions between spatial agglomeration and urban development by using agent-based simulation. It simulates the migration decisions of two main types of agents, namely rural and urban households between rural and urban area. The model contains multiple economic interactions that are crucial in understanding urbanization and industrial process in China. These adaptive agents can adjust their supply and demand according to the market situation by a learning algorithm. The simulation result shows this agent-based urban model is able to perform the regeneration and to produce likely-to-occur projections of reality.

Malarial pathocoenosis: beneficial and deleterious interactions between malaria and other human diseases

PubMed Central

Faure, Eric

2014-01-01

In nature, organisms are commonly infected by an assemblage of different parasite species or by genetically distinct parasite strains that interact in complex ways. Linked to co-infections, pathocoenosis, a term proposed by M. Grmek in 1969, refers to a pathological state arising from the interactions of diseases within a population and to the temporal and spatial dynamics of all of the diseases. In the long run, malaria was certainly one of the most important component of past pathocoenoses. Today this disease, which affects hundreds of millions of individuals and results in approximately one million deaths each year, is always highly endemic in over 20% of the world and is thus co-endemic with many other diseases. Therefore, the incidences of co-infections and possible direct and indirect interactions with Plasmodium parasites are very high. Both positive and negative interactions between malaria and other diseases caused by parasites belonging to numerous taxa have been described and in some cases, malaria may modify the process of another disease without being affected itself. Interactions include those observed during voluntary malarial infections intended to cure neuro-syphilis or during the enhanced activations of bacterial gastro-intestinal diseases and HIV infections. Complex relationships with multiple effects should also be considered, such as those observed during helminth infections. Moreover, reports dating back over 2000 years suggested that co- and multiple infections have generally deleterious consequences and analyses of historical texts indicated that malaria might exacerbate both plague and cholera, among other diseases. Possible biases affecting the research of etiological agents caused by the protean manifestations of malaria are discussed. A better understanding of the manner by which pathogens, particularly Plasmodium, modulate immune responses is particularly important for the diagnosis, cure, and control of diseases in human populations. PMID:25484866

Using Landsat time series for characterizing forest disturbance dynamics in the coupled human and natural systems of Central Europe.

PubMed

Senf, Cornelius; Pflugmacher, Dirk; Hostert, Patrick; Seidl, Rupert

2017-08-01

Remote sensing is a key information source for improving the spatiotemporal understanding of forest ecosystem dynamics. Yet, the mapping and attribution of forest change remains challenging, particularly in areas where a number of interacting disturbance agents simultaneously affect forest development. The forest ecosystems of Central Europe are coupled human and natural systems, with natural and human disturbances affecting forests both individually and in combination. To better understand the complex forest disturbance dynamics in such systems, we utilize 32-year Landsat time series to map forest disturbances in five sites across Austria, the Czech Republic, Germany, Poland, and Slovakia. All sites consisted of a National Park and the surrounding forests, reflecting three management zones of different levels of human influence (managed, protected, strictly protected). This allowed for a comparison of spectral, temporal, and spatial disturbance patterns across a gradient from natural to coupled human and natural disturbances. Disturbance maps achieved overall accuracies ranging from 81% to 93%. Disturbance patches were generally small, with 95% of the disturbances being smaller than 10 ha. Disturbance rates ranged from 0.29% yr -1 to 0.95% yr -1 , and differed substantially among management zones and study sites. Natural disturbances in strictly protected areas were longer in duration (median of 8 years) and slightly less variable in magnitude compared to human-dominated disturbances in managed forests (median duration of 1 year). However, temporal dynamics between natural and human-dominated disturbances showed strong synchrony, suggesting that disturbance peaks are driven by natural events affecting managed and unmanaged areas simultaneously. Our study demonstrates the potential of remote sensing for mapping forest disturbances in coupled human and natural systems, such as the forests of Central Europe. Yet, we also highlight the complexity of such systems in terms of agent attribution, as many natural disturbances are modified by management responding to them outside protected areas.

Using Landsat time series for characterizing forest disturbance dynamics in the coupled human and natural systems of Central Europe

NASA Astrophysics Data System (ADS)

Senf, Cornelius; Pflugmacher, Dirk; Hostert, Patrick; Seidl, Rupert

2017-08-01

Remote sensing is a key information source for improving the spatiotemporal understanding of forest ecosystem dynamics. Yet, the mapping and attribution of forest change remains challenging, particularly in areas where a number of interacting disturbance agents simultaneously affect forest development. The forest ecosystems of Central Europe are coupled human and natural systems, with natural and human disturbances affecting forests both individually and in combination. To better understand the complex forest disturbance dynamics in such systems, we utilize 32-year Landsat time series to map forest disturbances in five sites across Austria, the Czech Republic, Germany, Poland, and Slovakia. All sites consisted of a National Park and the surrounding forests, reflecting three management zones of different levels of human influence (managed, protected, strictly protected). This allowed for a comparison of spectral, temporal, and spatial disturbance patterns across a gradient from natural to coupled human and natural disturbances. Disturbance maps achieved overall accuracies ranging from 81% to 93%. Disturbance patches were generally small, with 95% of the disturbances being smaller than 10 ha. Disturbance rates ranged from 0.29% yr-1 to 0.95% yr-1, and differed substantially among management zones and study sites. Natural disturbances in strictly protected areas were longer in duration (median of 8 years) and slightly less variable in magnitude compared to human-dominated disturbances in managed forests (median duration of 1 year). However, temporal dynamics between natural and human-dominated disturbances showed strong synchrony, suggesting that disturbance peaks are driven by natural events affecting managed and unmanaged areas simultaneously. Our study demonstrates the potential of remote sensing for mapping forest disturbances in coupled human and natural systems, such as the forests of Central Europe. Yet, we also highlight the complexity of such systems in terms of agent attribution, as many natural disturbances are modified by management responding to them outside protected areas.

A Life-Cycle Model of Human Social Groups Produces a U-Shaped Distribution in Group Size.

PubMed

Salali, Gul Deniz; Whitehouse, Harvey; Hochberg, Michael E

2015-01-01

One of the central puzzles in the study of sociocultural evolution is how and why transitions from small-scale human groups to large-scale, hierarchically more complex ones occurred. Here we develop a spatially explicit agent-based model as a first step towards understanding the ecological dynamics of small and large-scale human groups. By analogy with the interactions between single-celled and multicellular organisms, we build a theory of group lifecycles as an emergent property of single cell demographic and expansion behaviours. We find that once the transition from small-scale to large-scale groups occurs, a few large-scale groups continue expanding while small-scale groups gradually become scarcer, and large-scale groups become larger in size and fewer in number over time. Demographic and expansion behaviours of groups are largely influenced by the distribution and availability of resources. Our results conform to a pattern of human political change in which religions and nation states come to be represented by a few large units and many smaller ones. Future enhancements of the model should include decision-making rules and probabilities of fragmentation for large-scale societies. We suggest that the synthesis of population ecology and social evolution will generate increasingly plausible models of human group dynamics.

A Life-Cycle Model of Human Social Groups Produces a U-Shaped Distribution in Group Size

PubMed Central

Salali, Gul Deniz; Whitehouse, Harvey; Hochberg, Michael E.

2015-01-01

One of the central puzzles in the study of sociocultural evolution is how and why transitions from small-scale human groups to large-scale, hierarchically more complex ones occurred. Here we develop a spatially explicit agent-based model as a first step towards understanding the ecological dynamics of small and large-scale human groups. By analogy with the interactions between single-celled and multicellular organisms, we build a theory of group lifecycles as an emergent property of single cell demographic and expansion behaviours. We find that once the transition from small-scale to large-scale groups occurs, a few large-scale groups continue expanding while small-scale groups gradually become scarcer, and large-scale groups become larger in size and fewer in number over time. Demographic and expansion behaviours of groups are largely influenced by the distribution and availability of resources. Our results conform to a pattern of human political change in which religions and nation states come to be represented by a few large units and many smaller ones. Future enhancements of the model should include decision-making rules and probabilities of fragmentation for large-scale societies. We suggest that the synthesis of population ecology and social evolution will generate increasingly plausible models of human group dynamics. PMID:26381745

Evaluating Spatial Interaction Models for Regional Mobility in Sub-Saharan Africa

PubMed Central

Wesolowski, Amy; O’Meara, Wendy Prudhomme; Eagle, Nathan; Tatem, Andrew J.; Buckee, Caroline O.

2015-01-01

Simple spatial interaction models of human mobility based on physical laws have been used extensively in the social, biological, and physical sciences, and in the study of the human dynamics underlying the spread of disease. Recent analyses of commuting patterns and travel behavior in high-income countries have led to the suggestion that these models are highly generalizable, and as a result, gravity and radiation models have become standard tools for describing population mobility dynamics for infectious disease epidemiology. Communities in Sub-Saharan Africa may not conform to these models, however; physical accessibility, availability of transport, and cost of travel between locations may be variable and severely constrained compared to high-income settings, informal labor movements rather than regular commuting patterns are often the norm, and the rise of mega-cities across the continent has important implications for travel between rural and urban areas. Here, we first review how infectious disease frameworks incorporate human mobility on different spatial scales and use anonymous mobile phone data from nearly 15 million individuals to analyze the spatiotemporal dynamics of the Kenyan population. We find that gravity and radiation models fail in systematic ways to capture human mobility measured by mobile phones; both severely overestimate the spatial spread of travel and perform poorly in rural areas, but each exhibits different characteristic patterns of failure with respect to routes and volumes of travel. Thus, infectious disease frameworks that rely on spatial interaction models are likely to misrepresent population dynamics important for the spread of disease in many African populations. PMID:26158274

Motor contagion during human-human and human-robot interaction.

PubMed

Bisio, Ambra; Sciutti, Alessandra; Nori, Francesco; Metta, Giorgio; Fadiga, Luciano; Sandini, Giulio; Pozzo, Thierry

2014-01-01

Motor resonance mechanisms are known to affect humans' ability to interact with others, yielding the kind of "mutual understanding" that is the basis of social interaction. However, it remains unclear how the partner's action features combine or compete to promote or prevent motor resonance during interaction. To clarify this point, the present study tested whether and how the nature of the visual stimulus and the properties of the observed actions influence observer's motor response, being motor contagion one of the behavioral manifestations of motor resonance. Participants observed a humanoid robot and a human agent move their hands into a pre-specified final position or put an object into a container at various velocities. Their movements, both in the object- and non-object- directed conditions, were characterized by either a smooth/curvilinear or a jerky/segmented trajectory. These trajectories were covered with biological or non-biological kinematics (the latter only by the humanoid robot). After action observation, participants were requested to either reach the indicated final position or to transport a similar object into another container. Results showed that motor contagion appeared for both the interactive partner except when the humanoid robot violated the biological laws of motion. These findings suggest that the observer may transiently match his/her own motor repertoire to that of the observed agent. This matching might mediate the activation of motor resonance, and modulate the spontaneity and the pleasantness of the interaction, whatever the nature of the communication partner.

Motor Contagion during Human-Human and Human-Robot Interaction

PubMed Central

Bisio, Ambra; Sciutti, Alessandra; Nori, Francesco; Metta, Giorgio; Fadiga, Luciano; Sandini, Giulio; Pozzo, Thierry

2014-01-01

Motor resonance mechanisms are known to affect humans' ability to interact with others, yielding the kind of “mutual understanding” that is the basis of social interaction. However, it remains unclear how the partner's action features combine or compete to promote or prevent motor resonance during interaction. To clarify this point, the present study tested whether and how the nature of the visual stimulus and the properties of the observed actions influence observer's motor response, being motor contagion one of the behavioral manifestations of motor resonance. Participants observed a humanoid robot and a human agent move their hands into a pre-specified final position or put an object into a container at various velocities. Their movements, both in the object- and non-object- directed conditions, were characterized by either a smooth/curvilinear or a jerky/segmented trajectory. These trajectories were covered with biological or non-biological kinematics (the latter only by the humanoid robot). After action observation, participants were requested to either reach the indicated final position or to transport a similar object into another container. Results showed that motor contagion appeared for both the interactive partner except when the humanoid robot violated the biological laws of motion. These findings suggest that the observer may transiently match his/her own motor repertoire to that of the observed agent. This matching might mediate the activation of motor resonance, and modulate the spontaneity and the pleasantness of the interaction, whatever the nature of the communication partner. PMID:25153990

Learning by Observing, Pitching in, and Being in Relations in the Natural World.

PubMed

Bang, Megan; Marin, Ananda; Medin, Douglas; Washinawatok, Karen

2015-01-01

This chapter describes a central tenet of Indigenous American social interaction, which emphasizes mutuality in collaboration and caring in Indigenous communities. This includes interactions with an agentive natural world, in which more-than-human beings act as participants in the lives of humans and vice versa. We argue that research on children's learning should take a broader view of interactional partners to include the natural world. © 2015 Elsevier Inc. All rights reserved.

Ecogeographic Genetic Epidemiology

PubMed Central

Sloan, Chantel D.; Duell, Eric J.; Shi, Xun; Irwin, Rebecca; Andrew, Angeline S.; Williams, Scott M.; Moore, Jason H.

2009-01-01

Complex diseases such as cancer and heart disease result from interactions between an individual's genetics and environment, i.e. their human ecology. Rates of complex diseases have consistently demonstrated geographic patterns of incidence, or spatial “clusters” of increased incidence relative to the general population. Likewise, genetic subpopulations and environmental influences are not evenly distributed across space. Merging appropriate methods from genetic epidemiology, ecology and geography will provide a more complete understanding of the spatial interactions between genetics and environment that result in spatial patterning of disease rates. Geographic Information Systems (GIS), which are tools designed specifically for dealing with geographic data and performing spatial analyses to determine their relationship, are key to this kind of data integration. Here the authors introduce a new interdisciplinary paradigm, ecogeographic genetic epidemiology, which uses GIS and spatial statistical analyses to layer genetic subpopulation and environmental data with disease rates and thereby discern the complex gene-environment interactions which result in spatial patterns of incidence. PMID:19025788

Synergy of irofulven in combination with other DNA damaging agents: synergistic interaction with altretamine, alkylating, and platinum-derived agents in the MV522 lung tumor model.

PubMed

Kelner, Michael J; McMorris, Trevor C; Rojas, Rafael J; Estes, Leita A; Suthipinijtham, Pharnuk

2008-12-01

Irofulven (MGI 114, NSC 683863) is a semisynthetic derivative of illudin S, a natural product present in the Omphalotus illudins (Jack O'Lantern) mushroom. This novel agent produces DNA damage, that in contrast to other agents, is predominately ignored by the global genome repair pathway of the nucleotide excision repair (NER)(2) system. The aim of this study was to determine the antitumor activity of irofulven when administered in combination with 44 different DNA damaging agents, whose damage is in general detected and repaired by the genome repair pathway. The human lung carcinoma MV522 cell line and its corresponding xenograft model were used to evaluate the activity of irofulven in combination with different DNA damaging agents. Two main classes of DNA damaging agents, platinum-derived agents, and select bifunctional alkylating agents, demonstrated in vivo synergistic or super-additive interaction with irofulven. DNA helicase inhibiting agents also demonstrated synergy in vitro, but an enhanced interaction with irofulven could not be demonstrated in vivo. There was no detectable synergistic activity between irofulven and agents capable of inducing DNA cleavage or intercalating into DNA. These results indicate that the antitumor activity of irofulven is enhanced when combined with platinum-derived agents, altretamine, and select alkylating agents such as melphalan or chlorambucil. A common factor between these agents appears to be the production of intrastrand DNA crosslinks. The synergistic interaction between irofulven and other agents may stem from the nucleotide excision repair system being selectively overwhelmed at two distinct points in the pathway, resulting in prolonged stalling of transcription forks, and subsequent initiation of apoptosis.

PLANNING AND RESPONSE IN THE AFTERMATH OF A LARGE CRISIS: AN AGENT-BASED INFORMATICS FRAMEWORK*

PubMed Central

Barrett, Christopher; Bisset, Keith; Chandan, Shridhar; Chen, Jiangzhuo; Chungbaek, Youngyun; Eubank, Stephen; Evrenosoğlu, Yaman; Lewis, Bryan; Lum, Kristian; Marathe, Achla; Marathe, Madhav; Mortveit, Henning; Parikh, Nidhi; Phadke, Arun; Reed, Jeffrey; Rivers, Caitlin; Saha, Sudip; Stretz, Paula; Swarup, Samarth; Thorp, James; Vullikanti, Anil; Xie, Dawen

2014-01-01

We present a synthetic information and modeling environment that can allow policy makers to study various counter-factual experiments in the event of a large human-initiated crisis. The specific scenario we consider is a ground detonation caused by an improvised nuclear device in a large urban region. In contrast to earlier work in this area that focuses largely on the prompt effects on human health and injury, we focus on co-evolution of individual and collective behavior and its interaction with the differentially damaged infrastructure. This allows us to study short term secondary and tertiary effects. The present environment is suitable for studying the dynamical outcomes over a two week period after the initial blast. A novel computing and data processing architecture is described; the architecture allows us to represent multiple co-evolving infrastructures and social networks at a highly resolved temporal, spatial, and individual scale. The representation allows us to study the emergent behavior of individuals as well as specific strategies to reduce casualties and injuries that exploit the spatial and temporal nature of the secondary and tertiary effects. A number of important conclusions are obtained using the modeling environment. For example, the studies decisively show that deploying ad hoc communication networks to reach individuals in the affected area is likely to have a significant impact on the overall casualties and injuries. PMID:25580055

PLANNING AND RESPONSE IN THE AFTERMATH OF A LARGE CRISIS: AN AGENT-BASED INFORMATICS FRAMEWORK*

PubMed

Barrett, Christopher; Bisset, Keith; Chandan, Shridhar; Chen, Jiangzhuo; Chungbaek, Youngyun; Eubank, Stephen; Evrenosoğlu, Yaman; Lewis, Bryan; Lum, Kristian; Marathe, Achla; Marathe, Madhav; Mortveit, Henning; Parikh, Nidhi; Phadke, Arun; Reed, Jeffrey; Rivers, Caitlin; Saha, Sudip; Stretz, Paula; Swarup, Samarth; Thorp, James; Vullikanti, Anil; Xie, Dawen

2013-01-01

We present a synthetic information and modeling environment that can allow policy makers to study various counter-factual experiments in the event of a large human-initiated crisis. The specific scenario we consider is a ground detonation caused by an improvised nuclear device in a large urban region. In contrast to earlier work in this area that focuses largely on the prompt effects on human health and injury, we focus on co-evolution of individual and collective behavior and its interaction with the differentially damaged infrastructure. This allows us to study short term secondary and tertiary effects. The present environment is suitable for studying the dynamical outcomes over a two week period after the initial blast. A novel computing and data processing architecture is described; the architecture allows us to represent multiple co-evolving infrastructures and social networks at a highly resolved temporal, spatial, and individual scale. The representation allows us to study the emergent behavior of individuals as well as specific strategies to reduce casualties and injuries that exploit the spatial and temporal nature of the secondary and tertiary effects. A number of important conclusions are obtained using the modeling environment. For example, the studies decisively show that deploying ad hoc communication networks to reach individuals in the affected area is likely to have a significant impact on the overall casualties and injuries.

I Reach Faster When I See You Look: Gaze Effects in Human–Human and Human–Robot Face-to-Face Cooperation

PubMed Central

Boucher, Jean-David; Pattacini, Ugo; Lelong, Amelie; Bailly, Gerard; Elisei, Frederic; Fagel, Sascha; Dominey, Peter Ford; Ventre-Dominey, Jocelyne

2012-01-01

Human–human interaction in natural environments relies on a variety of perceptual cues. Humanoid robots are becoming increasingly refined in their sensorimotor capabilities, and thus should now be able to manipulate and exploit these social cues in cooperation with their human partners. Previous studies have demonstrated that people follow human and robot gaze, and that it can help them to cope with spatially ambiguous language. Our goal is to extend these findings into the domain of action, to determine how human and robot gaze can influence the speed and accuracy of human action. We report on results from a human–human cooperation experiment demonstrating that an agent’s vision of her/his partner’s gaze can significantly improve that agent’s performance in a cooperative task. We then implement a heuristic capability to generate such gaze cues by a humanoid robot that engages in the same cooperative interaction. The subsequent human–robot experiments demonstrate that a human agent can indeed exploit the predictive gaze of their robot partner in a cooperative task. This allows us to render the humanoid robot more human-like in its ability to communicate with humans. The long term objectives of the work are thus to identify social cooperation cues, and to validate their pertinence through implementation in a cooperative robot. The current research provides the robot with the capability to produce appropriate speech and gaze cues in the context of human–robot cooperation tasks. Gaze is manipulated in three conditions: Full gaze (coordinated eye and head), eyes hidden with sunglasses, and head fixed. We demonstrate the pertinence of these cues in terms of statistical measures of action times for humans in the context of a cooperative task, as gaze significantly facilitates cooperation as measured by human response times. PMID:22563315

Spatial vs. non-spatial eco-evolutionary dynamics in a tumor growth model.

PubMed

You, Li; Brown, Joel S; Thuijsman, Frank; Cunningham, Jessica J; Gatenby, Robert A; Zhang, Jingsong; Staňková, Kateřina

2017-12-21

Metastatic prostate cancer is initially treated with androgen deprivation therapy (ADT). However, resistance typically develops in about 1 year - a clinical condition termed metastatic castrate-resistant prostate cancer (mCRPC). We develop and investigate a spatial game (agent based continuous space) of mCRPC that considers three distinct cancer cell types: (1) those dependent on exogenous testosterone (T + ), (2) those with increased CYP17A expression that produce testosterone and provide it to the environment as a public good (T P ), and (3) those independent of testosterone (T - ). The interactions within and between cancer cell types can be represented by a 3 × 3 matrix. Based on the known biology of this cancer there are 22 potential matrices that give roughly three major outcomes depending upon the absence (good prognosis), near absence or high frequency (poor prognosis) of T -  cells at the evolutionarily stable strategy (ESS). When just two cell types coexist the spatial game faithfully reproduces the ESS of the corresponding matrix game. With three cell types divergences occur, in some cases just two strategies coexist in the spatial game even as a non-spatial matrix game supports all three. Discrepancies between the spatial game and non-spatial ESS happen because different cell types become more or less clumped in the spatial game - leading to non-random assortative interactions between cell types. Three key spatial scales influence the distribution and abundance of cell types in the spatial game: i. Increasing the radius at which cells interact with each other can lead to higher clumping of each type, ii. Increasing the radius at which cells experience limits to population growth can cause densely packed tumor clusters in space, iii. Increasing the dispersal radius of daughter cells promotes increased mixing of cell types. To our knowledge the effects of these spatial scales on eco-evolutionary dynamics have not been explored in cancer models. The fact that cancer interactions are spatially explicit and that our spatial game of mCRPC provides in general different outcomes than the non-spatial game might suggest that non-spatial models are insufficient for capturing key elements of tumorigenesis. Copyright © 2017 Elsevier Ltd. All rights reserved.

Landscape Context and Regional Patterns in Arkansas' Forests

Treesearch

Victor A. Rudis

2001-01-01

Abstract - Recent results from Forest Inventory and Analysis (FIA) surveys provided an opportunity to explore the spatial and temporal context for Arkansas’ forests, including associated range, recreation, water, and wildlife habitat resources. Noted were damage agents and multipurpose resource indicators: evidence of human-associated activities (...

Effects of climate change on ecological disturbances [Chapter 8

Treesearch

Danielle M. Malesky; Barbara J. Bentz; Gary R. Brown; Andrea R. Brunelle; John M. Buffington; Linda M. Chappell; R. Justin DeRose; John C. Guyon; Carl L. Jorgensen; Rachel A. Loehman; Laura L. Lowrey; Ann M. Lynch; Marek Matyjasik; Joel D. McMillin; Javier E. Mercado; Jesse L. Morris; Jose F. Negron; Wayne G. Padgett; Robert A. Progar; Carol B. Randall

2018-01-01

This chapter describes disturbance regimes in the Intermountain Adaptation Partnership (IAP) region, and potential shifts in these regimes as a consequence of observed and projected climate change. The term "disturbance regime" describes the general temporal and spatial characteristics of a disturbance agent (e.g., insects, disease, fire, weather, human...

Embodied Interactions in Human-Machine Decision Making for Situation Awareness Enhancement Systems

DTIC Science & Technology

2016-06-09

characterize differences in spatial navigation strategies in a complex task, the Traveling Salesman Problem (TSP). For the second year, we developed...visual processing, leading to better solutions for spatial optimization problems . I will develop a framework to determine which body expressions best...methods include systematic characterization of gestures during complex problem solving. 15. SUBJECT TERMS Embodied interaction, gestures, one-shot

Agent-Based Modeling in Molecular Systems Biology.

PubMed

Soheilypour, Mohammad; Mofrad, Mohammad R K

2018-07-01

Molecular systems orchestrating the biology of the cell typically involve a complex web of interactions among various components and span a vast range of spatial and temporal scales. Computational methods have advanced our understanding of the behavior of molecular systems by enabling us to test assumptions and hypotheses, explore the effect of different parameters on the outcome, and eventually guide experiments. While several different mathematical and computational methods are developed to study molecular systems at different spatiotemporal scales, there is still a need for methods that bridge the gap between spatially-detailed and computationally-efficient approaches. In this review, we summarize the capabilities of agent-based modeling (ABM) as an emerging molecular systems biology technique that provides researchers with a new tool in exploring the dynamics of molecular systems/pathways in health and disease. © 2018 WILEY Periodicals, Inc.

Design for interaction between humans and intelligent systems during real-time fault management

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Schreckenghost, Debra L.; Thronesbery, Carroll G.

1992-01-01

Initial results are reported to provide guidance and assistance for designers of intelligent systems and their human interfaces. The objective is to achieve more effective human-computer interaction (HCI) for real time fault management support systems. Studies of the development of intelligent fault management systems within NASA have resulted in a new perspective of the user. If the user is viewed as one of the subsystems in a heterogeneous, distributed system, system design becomes the design of a flexible architecture for accomplishing system tasks with both human and computer agents. HCI requirements and design should be distinguished from user interface (displays and controls) requirements and design. Effective HCI design for multi-agent systems requires explicit identification of activities and information that support coordination and communication between agents. The effects are characterized of HCI design on overall system design and approaches are identified to addressing HCI requirements in system design. The results include definition of (1) guidance based on information level requirements analysis of HCI, (2) high level requirements for a design methodology that integrates the HCI perspective into system design, and (3) requirements for embedding HCI design tools into intelligent system development environments.

Interaction effects between sender and receiver processes in indirect transmission of Campylobacter jejuni between broilers

PubMed Central

2012-01-01

Background Infectious diseases in plants, animals and humans are often transmitted indirectly between hosts (or between groups of hosts), i.e. via some route through the environment instead of via direct contacts between these hosts. Here we study indirect transmission experimentally, using transmission of Campylobacter jejuni (C. jejuni) between spatially separated broilers as a model system. We distinguish three stages in the process of indirect transmission; (1) an infectious “sender” excretes the agent, after which (2) the agent is transported via some route to a susceptible “receiver”, and subsequently (3) the receiver becomes colonised by the agent. The role of the sender and receiver side (stage 1 and stage 3) was studied here by using acidification of the drinking water as a modulation mechanism. Results In the experiment one control group and three treatment groups were monitored for the presence of C. jejuni by taking daily cloacal swabs. The three treatments consisted of acidification of the drinking water of the inoculated animals (the senders), acidification of the drinking water of the susceptible animals (the receivers) or acidification of the drinking water of both inoculated and susceptible animals. In the control group 12 animals got colonised out of a possible 40, in each treatment groups 3 animals out of a possible 40 were found colonised with C. jejuni. Conclusions The results of the experiments show a significant decrease in transmission rate (β) between the control groups and treatment groups (p < 0.01 for all groups) but not between different treatments; there is a significant negative interaction effect when both the sender and the receiver group receive acidified drinking water (p = 0.01). This negative interaction effect could be due to selection of bacteria already at the sender side thereby diminishing the effect of acidification at the receiver side. PMID:22831274

Blended Interaction Design: A Spatial Workspace Supporting HCI and Design Practice

NASA Astrophysics Data System (ADS)

Geyer, Florian

This research investigates novel methods and techniques along with tool support that result from a conceptual blend of human-computer interaction with design practice. Using blending theory with material anchors as a theoretical framework, we frame both input spaces and explore emerging structures within technical, cognitive, and social aspects. Based on our results, we will describe a framework of the emerging structures and will design and evaluate tool support within a spatial, studio-like workspace to support collaborative creativity in interaction design.

APPLYING THE PATUXENT LANDSCAPE UNIT MODEL TO HUMAN DOMINATED ECOSYSTEMS: THE CASE OF AGRICULTURE. (R827169)

EPA Science Inventory

Non-spatial dynamics are core to landscape simulations. Unit models simulate system interactions aggregated within one space unit of resolution used within a spatial model. For unit models to be applicable to spatial simulations they have to be formulated in a general enough w...

Cognitive Network Modeling as a Basis for Characterizing Human Communication Dynamics and Belief Contagion in Technology Adoption

NASA Technical Reports Server (NTRS)

Hutto, Clayton; Briscoe, Erica; Trewhitt, Ethan

2012-01-01

Societal level macro models of social behavior do not sufficiently capture nuances needed to adequately represent the dynamics of person-to-person interactions. Likewise, individual agent level micro models have limited scalability - even minute parameter changes can drastically affect a model's response characteristics. This work presents an approach that uses agent-based modeling to represent detailed intra- and inter-personal interactions, as well as a system dynamics model to integrate societal-level influences via reciprocating functions. A Cognitive Network Model (CNM) is proposed as a method of quantitatively characterizing cognitive mechanisms at the intra-individual level. To capture the rich dynamics of interpersonal communication for the propagation of beliefs and attitudes, a Socio-Cognitive Network Model (SCNM) is presented. The SCNM uses socio-cognitive tie strength to regulate how agents influence--and are influenced by--one another's beliefs during social interactions. We then present experimental results which support the use of this network analytical approach, and we discuss its applicability towards characterizing and understanding human information processing.

Agent-based modelling of consumer energy choices

NASA Astrophysics Data System (ADS)

Rai, Varun; Henry, Adam Douglas

2016-06-01

Strategies to mitigate global climate change should be grounded in a rigorous understanding of energy systems, particularly the factors that drive energy demand. Agent-based modelling (ABM) is a powerful tool for representing the complexities of energy demand, such as social interactions and spatial constraints. Unlike other approaches for modelling energy demand, ABM is not limited to studying perfectly rational agents or to abstracting micro details into system-level equations. Instead, ABM provides the ability to represent behaviours of energy consumers -- such as individual households -- using a range of theories, and to examine how the interaction of heterogeneous agents at the micro-level produces macro outcomes of importance to the global climate, such as the adoption of low-carbon behaviours and technologies over space and time. We provide an overview of ABM work in the area of consumer energy choices, with a focus on identifying specific ways in which ABM can improve understanding of both fundamental scientific and applied aspects of the demand side of energy to aid the design of better policies and programmes. Future research needs for improving the practice of ABM to better understand energy demand are also discussed.

A Watershed-Scale Agent-Based Model Incorporating Agent Learning and Interaction of Farmers' Decisions Subject to Carbon and Miscanthus Prices

NASA Astrophysics Data System (ADS)

Ng, T.; Eheart, J.; Cai, X.; Braden, J. B.

2010-12-01

Agricultural watersheds are coupled human-natural systems where the land use decisions of human agents (farmers) affect surface water quality, and in turn, are affected by the weather and yields. The reliable modeling of such systems requires an approach that considers both the human and natural aspects. Agent-based modeling (ABM), representing the human aspect, coupled with hydrologic modeling, representing the natural aspect, is one such approach. ABM is a relatively new modeling paradigm that formulates the system from the perspectives of the individual agents, i.e., each agent is modeled as a discrete autonomous entity with distinct goals and actions. The primary objective of this study is to demonstrate the applicability of this approach to agricultural watershed management. This is done using a semi-hypothetical case study of farmers in the Salt Creek watershed in East-Central Illinois under the influence markets for carbon and second-generation bioenergy crop (specifically, miscanthus). An agent-based model of the system is developed and linked to a hydrologic model of the watershed. The former is based on fundamental economic and mathematical programming principles, while the latter is based on the Soil and Water Assessment Tool (SWAT). Carbon and second-generation bioenergy crop markets are of interest here due to climate change and energy independence concerns. The agent-based model is applied to fifty hypothetical heterogeneous farmers. The farmers' decisions depend on their perceptions of future conditions. Those perceptions are updated, according to a pre-defined algorithm, as the farmers make new observations of prices, costs, yields and the weather with time. The perceptions are also updated as the farmers interact with each other as they share new information on initially unfamiliar activities (e.g., carbon trading, miscanthus cultivation). The updating algorithm is set differently for different farmers such that each is unique in his processing of new information. The results provide insights on how differences in the way farmers learn and adapt affect their forecasts of the future, and hence, decisions. Farmers who are interacting, less risk averse, quick to adjust their expectations with new observations, and slow to reduce their forecast confidence when there are unexpected changes are more likely to practice conservation tillage (farmers may claim carbon credits for sale when practicing conservation tillage), and switch from conventional crops to miscanthus. The results, though empirically untested, appear plausible and consistent with general behavior by farmers. All this demonstrates the ability and potential of ABM to capture, at least partially, the complexities of human decision-making.

Interaction between hippocampal serotonin and cannabinoid systems in reactivity to spatial and object novelty detection.

PubMed

Nasehi, Mohammad; Rostam-Nezhad, Elnaz; Ebrahimi-Ghiri, Mohaddeseh; Zarrindast, Mohammad-Reza

2017-01-15

Functional interaction between cannabinoid and serotonin neuronal systems have been reported in different tasks related to memory assessment. The present study investigated the effect of serotonin 5-HT4 agents into the dorsal hippocampus (the CA1 region) on spatial and object novelty detection deficits induced by activation of cannabinoid CB1 receptors (CB1Rs) using arachidonylcyclopropylamide (ACPA) in a non-associative behavioral task designed to forecast the ability of rodents to encode spatial and non-spatial relationships between distinct stimuli. Post-training, intra-CA1 microinjection of 5-HT4 receptor agonist RS67333 or 5-HT4 receptor antagonist RS23597 both at the dose of 0.016μg/mouse impaired spatial memory, while cannabinoid CB1R antagonist AM251 (0.1μg/mouse) facilitated object novelty memory. Also, post-training, intraperitoneal administration of CB1R agonist ACPA (0.005-0.05mg/kg) impaired both memories. However, a subthreshold dose of RS67333 restored ACPA response on both memories. Moreover, a subthreshold dose of RS23597 potentiated ACPA (0.01mg/kg) and reversed ACPA (0.05mg/kg) responses on spatial memory, while it potentiated ACPA response at the dose of 0.005 or 0.05mg/kg on object novelty memory. Furthermore, effective dose of AM251 restored ACPA response at the higher dose. AM251 blocked response induced by combination of RS67333 or RS23597 and the higher dose of ACPA on both memories. Our results highlight that hippocampal 5-HT4 receptors differently affect cannabinoid signaling in spatial and object novelty memories. The inactivation of CB1 receptors blocks the effect of 5-HT4 agents into the CA1 region on memory deficits induced by activation of CB1Rs via ACPA. Copyright © 2016. Published by Elsevier B.V.

What should I do next? Using shared representations to solve interaction problems.

PubMed

Pezzulo, Giovanni; Dindo, Haris

2011-06-01

Studies on how "the social mind" works reveal that cognitive agents engaged in joint actions actively estimate and influence another's cognitive variables and form shared representations with them. (How) do shared representations enhance coordination? In this paper, we provide a probabilistic model of joint action that emphasizes how shared representations help solving interaction problems. We focus on two aspects of the model. First, we discuss how shared representations permit to coordinate at the level of cognitive variables (beliefs, intentions, and actions) and determine a coherent unfolding of action execution and predictive processes in the brains of two agents. Second, we discuss the importance of signaling actions as part of a strategy for sharing representations and the active guidance of another's actions toward the achievement of a joint goal. Furthermore, we present data from a human-computer experiment (the Tower Game) in which two agents (human and computer) have to build together a tower made of colored blocks, but only the human knows the constellation of the tower to be built (e.g., red-blue-red-blue-…). We report evidence that humans use signaling strategies that take another's uncertainty into consideration, and that in turn our model is able to use humans' actions as cues to "align" its representations and to select complementary actions.

Structural aspects of catalytic mechanisms of endonucleases and their binding to nucleic acids

NASA Astrophysics Data System (ADS)

Zhukhlistova, N. E.; Balaev, V. V.; Lyashenko, A. V.; Lashkov, A. A.

2012-05-01

Endonucleases (EC 3.1) are enzymes of the hydrolase class that catalyze the hydrolytic cleavage of deoxyribonucleic and ribonucleic acids at any region of the polynucleotide chain. Endonucleases are widely used both in biotechnological processes and in veterinary medicine as antiviral agents. Medical applications of endonucleases in human cancer therapy hold promise. The results of X-ray diffraction studies of the spatial organization of endonucleases and their complexes and the mechanism of their action are analyzed and generalized. An analysis of the structural studies of this class of enzymes showed that the specific binding of enzymes to nucleic acids is characterized by interactions with nitrogen bases and the nucleotide backbone, whereas the nonspecific binding of enzymes is generally characterized by interactions only with the nucleic-acid backbone. It should be taken into account that the specificity can be modulated by metal ions and certain low-molecular-weight organic compounds. To test the hypotheses about specific and nonspecific nucleic-acid-binding proteins, it is necessary to perform additional studies of atomic-resolution three-dimensional structures of enzyme-nucleic-acid complexes by methods of structural biology.

CTCF-Mediated Human 3D Genome Architecture Reveals Chromatin Topology for Transcription.

PubMed

Tang, Zhonghui; Luo, Oscar Junhong; Li, Xingwang; Zheng, Meizhen; Zhu, Jacqueline Jufen; Szalaj, Przemyslaw; Trzaskoma, Pawel; Magalska, Adriana; Wlodarczyk, Jakub; Ruszczycki, Blazej; Michalski, Paul; Piecuch, Emaly; Wang, Ping; Wang, Danjuan; Tian, Simon Zhongyuan; Penrad-Mobayed, May; Sachs, Laurent M; Ruan, Xiaoan; Wei, Chia-Lin; Liu, Edison T; Wilczynski, Grzegorz M; Plewczynski, Dariusz; Li, Guoliang; Ruan, Yijun

2015-12-17

Spatial genome organization and its effect on transcription remains a fundamental question. We applied an advanced chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) strategy to comprehensively map higher-order chromosome folding and specific chromatin interactions mediated by CCCTC-binding factor (CTCF) and RNA polymerase II (RNAPII) with haplotype specificity and nucleotide resolution in different human cell lineages. We find that CTCF/cohesin-mediated interaction anchors serve as structural foci for spatial organization of constitutive genes concordant with CTCF-motif orientation, whereas RNAPII interacts within these structures by selectively drawing cell-type-specific genes toward CTCF foci for coordinated transcription. Furthermore, we show that haplotype variants and allelic interactions have differential effects on chromosome configuration, influencing gene expression, and may provide mechanistic insights into functions associated with disease susceptibility. 3D genome simulation suggests a model of chromatin folding around chromosomal axes, where CTCF is involved in defining the interface between condensed and open compartments for structural regulation. Our 3D genome strategy thus provides unique insights in the topological mechanism of human variations and diseases. Copyright © 2015 Elsevier Inc. All rights reserved.

Interactions of forests, climate, water resources, and humans in a changing environment: research needs

Treesearch

Ge Sun; Catalina Segura

2013-01-01

The aim of the special issue “Interactions of Forests, Climate, Water Resources, and Humans in a Changing Environment” is to present case studies on the influences of natural and human disturbances on forest water resources under a changing climate. Studies in this collection of six papers cover a wide range of geographic regions from Australia to Nigeria with spatial...

Human agency in social cognitive theory.

PubMed

Bandura, A

1989-09-01

The present article examines the nature and function of human agency within the conceptual model of triadic reciprocal causation. In analyzing the operation of human agency in this interactional causal structure, social cognitive theory accords a central role to cognitive, vicarious, self-reflective, and self-regulatory processes. The issues addressed concern the psychological mechanisms through which personal agency is exercised, the hierarchical structure of self-regulatory systems, eschewal of the dichotomous construal of self as agent and self as object, and the properties of a nondualistic but nonreductional conception of human agency. The relation of agent causality to the fundamental issues of freedom and determinism is also analyzed.

Towards a framework for agent-based image analysis of remote-sensing data

PubMed Central

Hofmann, Peter; Lettmayer, Paul; Blaschke, Thomas; Belgiu, Mariana; Wegenkittl, Stefan; Graf, Roland; Lampoltshammer, Thomas Josef; Andrejchenko, Vera

2015-01-01

Object-based image analysis (OBIA) as a paradigm for analysing remotely sensed image data has in many cases led to spatially and thematically improved classification results in comparison to pixel-based approaches. Nevertheless, robust and transferable object-based solutions for automated image analysis capable of analysing sets of images or even large image archives without any human interaction are still rare. A major reason for this lack of robustness and transferability is the high complexity of image contents: Especially in very high resolution (VHR) remote-sensing data with varying imaging conditions or sensor characteristics, the variability of the objects’ properties in these varying images is hardly predictable. The work described in this article builds on so-called rule sets. While earlier work has demonstrated that OBIA rule sets bear a high potential of transferability, they need to be adapted manually, or classification results need to be adjusted manually in a post-processing step. In order to automate these adaptation and adjustment procedures, we investigate the coupling, extension and integration of OBIA with the agent-based paradigm, which is exhaustively investigated in software engineering. The aims of such integration are (a) autonomously adapting rule sets and (b) image objects that can adopt and adjust themselves according to different imaging conditions and sensor characteristics. This article focuses on self-adapting image objects and therefore introduces a framework for agent-based image analysis (ABIA). PMID:27721916

Towards a framework for agent-based image analysis of remote-sensing data.

PubMed

Hofmann, Peter; Lettmayer, Paul; Blaschke, Thomas; Belgiu, Mariana; Wegenkittl, Stefan; Graf, Roland; Lampoltshammer, Thomas Josef; Andrejchenko, Vera

2015-04-03

Object-based image analysis (OBIA) as a paradigm for analysing remotely sensed image data has in many cases led to spatially and thematically improved classification results in comparison to pixel-based approaches. Nevertheless, robust and transferable object-based solutions for automated image analysis capable of analysing sets of images or even large image archives without any human interaction are still rare. A major reason for this lack of robustness and transferability is the high complexity of image contents: Especially in very high resolution (VHR) remote-sensing data with varying imaging conditions or sensor characteristics, the variability of the objects' properties in these varying images is hardly predictable. The work described in this article builds on so-called rule sets. While earlier work has demonstrated that OBIA rule sets bear a high potential of transferability, they need to be adapted manually, or classification results need to be adjusted manually in a post-processing step. In order to automate these adaptation and adjustment procedures, we investigate the coupling, extension and integration of OBIA with the agent-based paradigm, which is exhaustively investigated in software engineering. The aims of such integration are (a) autonomously adapting rule sets and (b) image objects that can adopt and adjust themselves according to different imaging conditions and sensor characteristics. This article focuses on self-adapting image objects and therefore introduces a framework for agent-based image analysis (ABIA).

Coordinated Speed Oscillations in Schooling Killifish Enrich Social Communication

NASA Astrophysics Data System (ADS)

Swain, Daniel T.; Couzin, Iain D.; Leonard, Naomi Ehrich

2015-10-01

We examine the spatial dynamics of individuals in small schools of banded killifish ( Fundulus diaphanus) that exhibit rhythmic, oscillating speed, typically with sustained, coordinated, out-of-phase speed oscillations as they move around a shallow water tank. We show that the relative motion among the fish yields a periodically time-varying network of social interactions that enriches visually driven social communication. The oscillations lead to the regular making and breaking of occlusions, which we term "switching." We show that the rate of convergence to consensus (biologically, the capacity for individuals in groups to achieve effective coordinated motion) governed by the switching outperforms static alternatives, and performs as well as the less practical case of every fish sensing every other fish. We show further that the oscillations in speed yield oscillations in relative bearing between fish over a range that includes the angles previously predicted to be optimal for a fish to detect changes in heading and speed of its neighbors. To investigate systematically, we derive and analyze a dynamic model of interacting agents that move with oscillatory speed. We show that coordinated circular motion of the school leads to systematic cycling of spatial ordering of agents and possibilities for enriched spatial density of measurements of the external environment. Our results highlight the potential benefits of dynamic communication topologies in collective animal behavior, and suggest new, useful control laws for the distributed coordination of mobile robotic networks.

State-of-the-Art Materials for Ultrasound-Triggered Drug Delivery

PubMed Central

Sirsi, Shashank; Borden, Mark

2014-01-01

Ultrasound is a unique and exciting theranostic modality that can be used to track drug carriers, trigger drug release and improve drug deposition with high spatial precision. In this review, we briefly describe the mechanisms of interaction between drug carriers and ultrasound waves, including cavitation, streaming and hyperthermia, and how those interactions can promote drug release and tissue uptake. We then discuss the rational design of some state-of-the-art materials for ultrasound-triggered drug delivery and review recent progress for each drug carrier, focusing on the delivery of chemotherapeutic agents such as doxorubicin. These materials include nanocarrier formulations, such as liposomes and micelles, designed specifically for ultrasound-triggered drug release, as well as microbubbles, microbubble-nanocarrier hybrids, microbubble-seeded hydrogels and phase-change agents. PMID:24389162

Agent-Based Models and Optimal Control in Biology: A Discrete Approach

DTIC Science & Technology

2012-01-01

different parts of the human body to cure diseases such as hypertension, cancer, or heart disease. And we need to control microbes for the efficient...antelope herd interacts with an aggregated prey agent such as cheetahs or lions, the size of each may expand or contract accordingly). Of course, such

Sensitivity to the Sampling Process Emerges From the Principle of Efficiency.

PubMed

Jara-Ettinger, Julian; Sun, Felix; Schulz, Laura; Tenenbaum, Joshua B

2018-05-01

Humans can seamlessly infer other people's preferences, based on what they do. Broadly, two types of accounts have been proposed to explain different aspects of this ability. The first account focuses on spatial information: Agents' efficient navigation in space reveals what they like. The second account focuses on statistical information: Uncommon choices reveal stronger preferences. Together, these two lines of research suggest that we have two distinct capacities for inferring preferences. Here we propose that this is not the case, and that spatial-based and statistical-based preference inferences can be explained by the assumption that agents are efficient alone. We show that people's sensitivity to spatial and statistical information when they infer preferences is best predicted by a computational model of the principle of efficiency, and that this model outperforms dual-system models, even when the latter are fit to participant judgments. Our results suggest that, as adults, a unified understanding of agency under the principle of efficiency underlies our ability to infer preferences. Copyright © 2018 Cognitive Science Society, Inc.

Twentieth century turnover of Mexican endemic avifaunas: Landscape change versus climate drivers.

PubMed

Peterson, A Townsend; Navarro-Sigüenza, Adolfo G; Martínez-Meyer, Enrique; Cuervo-Robayo, Angela P; Berlanga, Humberto; Soberón, Jorge

2015-05-01

Numerous climate change effects on biodiversity have been anticipated and documented, including extinctions, range shifts, phenological shifts, and breakdown of interactions in ecological communities, yet the relative balance of different climate drivers and their relationships to other agents of global change (for example, land use and land-use change) remains relatively poorly understood. This study integrated historical and current biodiversity data on distributions of 115 Mexican endemic bird species to document areas of concentrated gains and losses of species in local communities, and then related those changes to climate and land-use drivers. Of all drivers examined, at this relatively coarse spatial resolution, only temperature change had significant impacts on avifaunal turnover; neither precipitation change nor human impact on landscapes had detectable effects. This study, conducted across species' geographic distributions, and covering all of Mexico, thanks to two large-scale biodiversity data sets, could discern relative importance of specific climatic drivers of biodiversity change.

Visualizing High-Efficiency HIV Transfer | Center for Cancer Research

Cancer.gov

The Human Immunodeficiency Virus (HIV), the causative agent of Acquired Immunodeficiency Syndrome (AIDS), infects and eventually kills CD4 receptor-expressing T cells, which are critical for proper immune system function. The gp120 protein on the surface of HIV particles is known to bind CD4 and a co-receptor, either CCR5 or CXCR4, leading to fusion of the virus and T cell membranes and infection of the cell. The most efficient means of viral infection occurs when an uninfected T cell interacts with a dendritic cell (DC) that has previously come in contact with HIV. Antigen presenting cells, such as DCs, normally circulate throughout the body binding or engulfing foreign material and presenting it to T cells to initiate an immune response. HIV takes advantage of this close cell-cell association to propagate, so knowing the cells’ spatial arrangement during viral transmission could elucidate novel modes of treatment.

Human recreation affects spatio-temporal habitat use patterns in red deer (Cervus elaphus)

PubMed Central

Coppes, Joy; Burghardt, Friedrich; Hagen, Robert; Suchant, Rudi; Braunisch, Veronika

2017-01-01

The rapid spread and diversification of outdoor recreation can impact on wildlife in various ways, often leading to the avoidance of disturbed habitats. To mitigate human-wildlife conflicts, spatial zonation schemes can be implemented to separate human activities from key wildlife habitats, e.g., by designating undisturbed wildlife refuges or areas with some level of restriction to human recreation and land use. However, mitigation practice rarely considers temporal differences in human-wildlife interactions. We used GPS telemetry data from 15 red deer to study the seasonal (winter vs. summer) and diurnal (day vs. night) variation in recreation effects on habitat use in a study region in south-western Germany where a spatial zonation scheme has been established. Our study aimed to determine if recreation infrastructure and spatial zonation affected red deer habitat use and whether these effects varied daily or seasonally. Recreation infrastructure did not affect home range selection in the study area, but strongly determined habitat use within the home range. The spatial zonation scheme was reflected in both of these two levels of habitat selection, with refuges and core areas being more frequently used than the border zones. Habitat use differed significantly between day and night in both seasons. Both summer and winter recreation trails, and nearby foraging habitats, were avoided during day, whereas a positive association was found during night. We conclude that human recreation has an effect on red deer habitat use, and when designing mitigation measures daily and seasonal variation in human-wildlife interactions should be taken into account. We advocate using spatial zonation in conjunction with temporal restrictions (i.e., banning nocturnal recreation activities) and the creation of suitable foraging habitats away from recreation trails. PMID:28467429

Anthropogenic habitat disturbance and the dynamics of hantavirus using remote sensing, GIS, and a spatially explicit agent-based model

NASA Astrophysics Data System (ADS)

Cao, Lina

Sin Nombre virus (SNV), a strain of hantavirus, causes hantavirus pulmonary syndrome (HPS) in humans, a deadly disease with high mortality rate (>50%). The primary virus host is deer mice, and greater deer mice abundance has been shown to increase the human risk of HPS. There is a great need in understanding the nature of the virus host, its temporal and spatial dynamics, and its relation to the human population with the purpose of predicting human risk of the disease. This research studies SNV dynamics in deer mice in the Great Basin Desert of central Utah, USA using multiyear field data and integrated geospatial approaches including remote sensing, Geographic Information System (GIS), and a spatially explicit agent-based model. The goal is to advance our understanding of the important ecological and demographic factors that affect the dynamics of deer mouse population and SNV prevalence. The primary research question is how climate, habitat disturbance, and deer mouse demographics affect deer mouse population density, its movement, and SNV prevalence in the sagebrush habitat. The results show that the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI) can be good predictors of deer mouse density and the number of infected deer mice with a time lag of 1.0 to 1.3 years. This information can be very useful in predicting mouse abundance and SNV risk. The results also showed that climate, mouse density, sex, mass, and SNV infection had significant effects on deer mouse movement. The effect of habitat disturbance on mouse movement varies according to climate conditions with positive relationship in predrought condition and negative association in postdrought condition. The heavier infected deer mice moved the most. Season and disturbance alone had no significant effects. The spatial agent-based model (SABM) simulation results show that prevalence was negatively related to the disturbance levels and the sensitivity analysis showed that population density was one of the most important parameters affecting the SNV dynamics. The results also indicated that habitat disturbance could increase hantavirus transmission likely by increasing the movement and consequently contact rates. However, the model suggested that habitat disturbance had a much stronger effect on prevalence by decreasing population density than by increasing mice movement. Therefore, overall habitat disturbance reduces SNV prevalence.

Understanding coupled natural and human systems on fire prone landscapes: integrating wildfire simulation into an agent based planning system.

NASA Astrophysics Data System (ADS)

Barros, Ana; Ager, Alan; Preisler, Haiganoush; Day, Michelle; Spies, Tom; Bolte, John

2015-04-01

Agent-based models (ABM) allow users to examine the long-term effects of agent decisions in complex systems where multiple agents and processes interact. This framework has potential application to study the dynamics of coupled natural and human systems where multiple stimuli determine trajectories over both space and time. We used Envision, a landscape based ABM, to analyze long-term wildfire dynamics in a heterogeneous, multi-owner landscape in Oregon, USA. Landscape dynamics are affected by land management policies, actors decisions, and autonomous processes such as vegetation succession, wildfire, or at a broader scale, climate change. Key questions include: 1) How are landscape dynamics influenced by policies and institutions, and 2) How do land management policies and actor decisions interact to produce intended and unintended consequences with respect to wildfire on fire-prone landscapes. Applying Envision to address these questions required the development of a wildfire module that could accurately simulate wildfires on the heterogeneous landscapes within the study area in terms of replicating historical fire size distribution, spatial distribution and fire intensity. In this paper we describe the development and testing of a mechanistic fire simulation system within Envision and application of the model on a 3.2 million fire prone landscape in central Oregon USA. The core fire spread equations use the Minimum Travel Time algorithm developed by M Finney. The model operates on a daily time step and uses a fire prediction system based on the relationship between energy release component and historical fires. Specifically, daily wildfire probabilities and sizes are generated from statistical analyses of historical fires in relation to daily ERC values. The MTT was coupled with the vegetation dynamics module in Envision to allow communication between the respective subsystem and effectively model fire effects and vegetation dynamics after a wildfire. Canopy and surface fuels are modeled in a state and transition framework that accounts for succession, fire effects, and fuels management. Fire effects are modeled using simulated fire intensity (flame length) to calculate expected vegetation impacts for each vegetation state. This talk will describe the mechanics of the simulation system along with initial results of Envision simulations for the Central Oregon study area that explore the dynamics of wildfire, fuel management, and succession over time.

Detection of rheumatoid arthritis in humans by fluorescence imaging

NASA Astrophysics Data System (ADS)

Ebert, Bernd; Dziekan, Thomas; Weissbach, Carmen; Mahler, Marianne; Schirner, Michael; Berliner, Birgitt; Bauer, Daniel; Voigt, Jan; Berliner, Michael; Bahner, Malte L.; Macdonald, Rainer

2010-02-01

The blood pool agent indo-cyanine green (ICG) has been investigated in a prospective clinical study for detection of rheumatoid arthritis using fluorescence imaging. Temporal behavior as well as spatial distribution of fluorescence intensity are suited to differentiate healthy and inflamed finger joints after i.v. injection of an ICG bolus.

Spatial Positioning of All 24 Chromosomes in the Lymphocytes of Six Subjects: Evidence of Reproducible Positioning and Spatial Repositioning following DNA Damage with Hydrogen Peroxide and Ultraviolet B

PubMed Central

Kandukuri, Lakshmi; Quadri, Ameer; Becerra, Victor; Simpson, Joe Leigh

2015-01-01

The higher-order organization of chromatin is well-established, with chromosomes occupying distinct positions within the interphase nucleus. Chromatin is susceptible to, and constantly assaulted by both endogenous and exogenous threats. However, the effects of DNA damage on the spatial topology of chromosomes are hitherto, poorly understood. This study investigates the organization of all 24 human chromosomes in lymphocytes from six individuals prior to- and following in-vitro exposure to genotoxic agents: hydrogen peroxide and ultraviolet B. This study is the first to report reproducible distinct hierarchical radial organization of chromosomes with little inter-individual differences between subjects. Perturbed nuclear organization was observed following genotoxic exposure for both agents; however a greater effect was observed for hydrogen peroxide including: 1) More peripheral radial organization; 2) Alterations in the global distribution of chromosomes; and 3) More events of chromosome repositioning (18 events involving 10 chromosomes vs. 11 events involving 9 chromosomes for hydrogen peroxide and ultraviolet B respectively). Evidence is provided of chromosome repositioning and altered nuclear organization following in-vitro exposure to genotoxic agents, with notable differences observed between the two investigated agents. Repositioning of chromosomes following genotoxicity involved recurrent chromosomes and is most likely part of the genomes inherent response to DNA damage. The variances in nuclear organization observed between the two agents likely reflects differences in mobility and/or decondensation of chromatin as a result of differences in the type of DNA damage induced, chromatin regions targeted, and DNA repair mechanisms. PMID:25756782

Spatial positioning of all 24 chromosomes in the lymphocytes of six subjects: evidence of reproducible positioning and spatial repositioning following DNA damage with hydrogen peroxide and ultraviolet B.

PubMed

Ioannou, Dimitrios; Kandukuri, Lakshmi; Quadri, Ameer; Becerra, Victor; Simpson, Joe Leigh; Tempest, Helen G

2015-01-01

The higher-order organization of chromatin is well-established, with chromosomes occupying distinct positions within the interphase nucleus. Chromatin is susceptible to, and constantly assaulted by both endogenous and exogenous threats. However, the effects of DNA damage on the spatial topology of chromosomes are hitherto, poorly understood. This study investigates the organization of all 24 human chromosomes in lymphocytes from six individuals prior to- and following in-vitro exposure to genotoxic agents: hydrogen peroxide and ultraviolet B. This study is the first to report reproducible distinct hierarchical radial organization of chromosomes with little inter-individual differences between subjects. Perturbed nuclear organization was observed following genotoxic exposure for both agents; however a greater effect was observed for hydrogen peroxide including: 1) More peripheral radial organization; 2) Alterations in the global distribution of chromosomes; and 3) More events of chromosome repositioning (18 events involving 10 chromosomes vs. 11 events involving 9 chromosomes for hydrogen peroxide and ultraviolet B respectively). Evidence is provided of chromosome repositioning and altered nuclear organization following in-vitro exposure to genotoxic agents, with notable differences observed between the two investigated agents. Repositioning of chromosomes following genotoxicity involved recurrent chromosomes and is most likely part of the genomes inherent response to DNA damage. The variances in nuclear organization observed between the two agents likely reflects differences in mobility and/or decondensation of chromatin as a result of differences in the type of DNA damage induced, chromatin regions targeted, and DNA repair mechanisms.

Combining Multiple Forms Of Visual Information To Specify Contact Relations In Spatial Layout

NASA Astrophysics Data System (ADS)

Sedgwick, Hal A.

1990-03-01

An expert system, called Layout2, has been described, which models a subset of available visual information for spatial layout. The system is used to examine detailed interactions between multiple, partially redundant forms of information in an environment-centered geometrical model of an environment obeying certain rather general constraints. This paper discusses the extension of Layout2 to include generalized contact relations between surfaces. In an environment-centered model, the representation of viewer-centered distance is replaced by the representation of environmental location. This location information is propagated through the representation of the environment by a network of contact relations between contiguous surfaces. Perspective information interacts with other forms of information to specify these contact relations. The experimental study of human perception of contact relations in extended spatial layouts is also discussed. Differences between human results and Layout2 results reveal limitations in the human ability to register available information; they also point to the existence of certain forms of information not yet formalized in Layout2.

Human-Vehicle Interface for Semi-Autonomous Operation of Uninhabited Aero Vehicles

NASA Technical Reports Server (NTRS)

Jones, Henry L.; Frew, Eric W.; Woodley, Bruce R.; Rock, Stephen M.

2001-01-01

The robustness of autonomous robotic systems to unanticipated circumstances is typically insufficient for use in the field. The many skills of human user often fill this gap in robotic capability. To incorporate the human into the system, a useful interaction between man and machine must exist. This interaction should enable useful communication to be exchanged in a natural way between human and robot on a variety of levels. This report describes the current human-robot interaction for the Stanford HUMMINGBIRD autonomous helicopter. In particular, the report discusses the elements of the system that enable multiple levels of communication. An intelligent system agent manages the different inputs given to the helicopter. An advanced user interface gives the user and helicopter a method for exchanging useful information. Using this human-robot interaction, the HUMMINGBIRD has carried out various autonomous search, tracking, and retrieval missions.

Interactions between the spatial and temporal stimulus factors that influence multisensory integration in human performance.

PubMed

Stevenson, Ryan A; Fister, Juliane Krueger; Barnett, Zachary P; Nidiffer, Aaron R; Wallace, Mark T

2012-05-01

In natural environments, human sensory systems work in a coordinated and integrated manner to perceive and respond to external events. Previous research has shown that the spatial and temporal relationships of sensory signals are paramount in determining how information is integrated across sensory modalities, but in ecologically plausible settings, these factors are not independent. In the current study, we provide a novel exploration of the impact on behavioral performance for systematic manipulations of the spatial location and temporal synchrony of a visual-auditory stimulus pair. Simple auditory and visual stimuli were presented across a range of spatial locations and stimulus onset asynchronies (SOAs), and participants performed both a spatial localization and simultaneity judgment task. Response times in localizing paired visual-auditory stimuli were slower in the periphery and at larger SOAs, but most importantly, an interaction was found between the two factors, in which the effect of SOA was greater in peripheral as opposed to central locations. Simultaneity judgments also revealed a novel interaction between space and time: individuals were more likely to judge stimuli as synchronous when occurring in the periphery at large SOAs. The results of this study provide novel insights into (a) how the speed of spatial localization of an audiovisual stimulus is affected by location and temporal coincidence and the interaction between these two factors and (b) how the location of a multisensory stimulus impacts judgments concerning the temporal relationship of the paired stimuli. These findings provide strong evidence for a complex interdependency between spatial location and temporal structure in determining the ultimate behavioral and perceptual outcome associated with a paired multisensory (i.e., visual-auditory) stimulus.

Designing for Humans in Autonomous Systems: Military Applications

DTIC Science & Technology

2014-01-01

attentional control, and gaming experience are important determinants of how well humans interact with agents supervising multiple assets . 6 4...mission performance, operator workload, trust, SA, and, most important , how they affected human safety. The initial experiments were conducted in a...that humans can also play an important role by being able to identify these objects (perception by proxy). Therefore, human involvement is useful

Computational Models of Human Performance: Validation of Memory and Procedural Representation in Advanced Air/Ground Simulation

NASA Technical Reports Server (NTRS)

Corker, Kevin M.; Labacqz, J. Victor (Technical Monitor)

1997-01-01

The Man-Machine Interaction Design and Analysis System (MIDAS) under joint U.S. Army and NASA cooperative is intended to assist designers of complex human/automation systems in successfully incorporating human performance capabilities and limitations into decision and action support systems. MIDAS is a computational representation of multiple human operators, selected perceptual, cognitive, and physical functions of those operators, and the physical/functional representation of the equipment with which they operate. MIDAS has been used as an integrated predictive framework for the investigation of human/machine systems, particularly in situations with high demands on the operators. We have extended the human performance models to include representation of both human operators and intelligent aiding systems in flight management, and air traffic service. The focus of this development is to predict human performance in response to aiding system developed to identify aircraft conflict and to assist in the shared authority for resolution. The demands of this application requires representation of many intelligent agents sharing world-models, coordinating action/intention, and cooperative scheduling of goals and action in an somewhat unpredictable world of operations. In recent applications to airborne systems development, MIDAS has demonstrated an ability to predict flight crew decision-making and procedural behavior when interacting with automated flight management systems and Air Traffic Control. In this paper, we describe two enhancements to MIDAS. The first involves the addition of working memory in the form of an articulatory buffer for verbal communication protocols and a visuo-spatial buffer for communications via digital datalink. The second enhancement is a representation of multiple operators working as a team. This enhanced model was used to predict the performance of human flight crews and their level of compliance with commercial aviation communication procedures. We show how the data produced by MIDAS compares with flight crew performance data from full mission simulations. Finally, we discuss the use of these features to study communication issues connected with aircraft-based separation assurance.

Distinct Neurocognitive Strategies for Comprehensions of Human and Artificial Intelligence

PubMed Central

Ge, Jianqiao; Han, Shihui

2008-01-01

Although humans have inevitably interacted with both human and artificial intelligence in real life situations, it is unknown whether the human brain engages homologous neurocognitive strategies to cope with both forms of intelligence. To investigate this, we scanned subjects, using functional MRI, while they inferred the reasoning processes conducted by human agents or by computers. We found that the inference of reasoning processes conducted by human agents but not by computers induced increased activity in the precuneus but decreased activity in the ventral medial prefrontal cortex and enhanced functional connectivity between the two brain areas. The findings provide evidence for distinct neurocognitive strategies of taking others' perspective and inhibiting the process referenced to the self that are specific to the comprehension of human intelligence. PMID:18665211

Deliberate or unintended: Intentions modulate empathic responses to others' economic payoffs in social interactions.

PubMed

Ma, Qingguo; Meng, Liang; Shen, Qiang

2017-12-01

Previous studies examining empathy have revealed the neural substrates of how the physical pain of others is represented in the human brain. However, little is known about the empathic modulation of behavioral and neural responses to others' economic payoffs, especially in the social context. In the present study, we engaged participants in a revised Dictator Game as observers who observe the powerless players receiving varied offers proposed by the dominant players, establishing the link between empathy and fairness perception. Results showed that unfair division schemes elicited a more pronounced FRN than fair ones only if a human agent proposed the initial offer. In addition, observers sacrificed their own payments to adjust unfair proposals, especially when a human agent proposed the offer. Thus, results of the current study demonstrated that perceived intention modulates behavioral and neural responses to others' economic payoffs in social interactions.

Research and Development for an Operational Information Ecology: The User-System Interface Agent Project

NASA Technical Reports Server (NTRS)

Srivastava, Sadanand; deLamadrid, James

1998-01-01

The User System Interface Agent (USIA) is a special type of software agent which acts as the "middle man" between a human user and an information processing environment. USIA consists of a group of cooperating agents which are responsible for assisting users in obtaining information processing services intuitively and efficiently. Some of the main features of USIA include: (1) multiple interaction modes and (2) user-specific and stereotype modeling and adaptation. This prototype system provides us with a development platform towards the realization of an operational information ecology. In the first phase of this project we focus on the design and implementation of prototype system of the User-System Interface Agent (USIA). The second face of USIA allows user interaction via a restricted query language as well as through a taxonomy of windows. In third phase the USIA system architecture was revised.

Integrating Household Risk Mitigation Behavior in Flood Risk Analysis: An Agent-Based Model Approach.

PubMed

Haer, Toon; Botzen, W J Wouter; de Moel, Hans; Aerts, Jeroen C J H

2017-10-01

Recent studies showed that climate change and socioeconomic trends are expected to increase flood risks in many regions. However, in these studies, human behavior is commonly assumed to be constant, which neglects interaction and feedback loops between human and environmental systems. This neglect of human adaptation leads to a misrepresentation of flood risk. This article presents an agent-based model that incorporates human decision making in flood risk analysis. In particular, household investments in loss-reducing measures are examined under three economic decision models: (1) expected utility theory, which is the traditional economic model of rational agents; (2) prospect theory, which takes account of bounded rationality; and (3) a prospect theory model, which accounts for changing risk perceptions and social interactions through a process of Bayesian updating. We show that neglecting human behavior in flood risk assessment studies can result in a considerable misestimation of future flood risk, which is in our case study an overestimation of a factor two. Furthermore, we show how behavior models can support flood risk analysis under different behavioral assumptions, illustrating the need to include the dynamic adaptive human behavior of, for instance, households, insurers, and governments. The method presented here provides a solid basis for exploring human behavior and the resulting flood risk with respect to low-probability/high-impact risks. © 2016 The Authors Risk Analysis published by Wiley Periodicals, Inc. on behalf of Society for Risk Analysis.

Global Sensitivity Analysis for Large-scale Socio-hydrological Models using the Cloud

NASA Astrophysics Data System (ADS)

Hu, Y.; Garcia-Cabrejo, O.; Cai, X.; Valocchi, A. J.; Dupont, B.

2014-12-01

In the context of coupled human and natural system (CHNS), incorporating human factors into water resource management provides us with the opportunity to understand the interactions between human and environmental systems. A multi-agent system (MAS) model is designed to couple with the physically-based Republican River Compact Administration (RRCA) groundwater model, in an attempt to understand the declining water table and base flow in the heavily irrigated Republican River basin. For MAS modelling, we defined five behavioral parameters (κ_pr, ν_pr, κ_prep, ν_prep and λ) to characterize the agent's pumping behavior given the uncertainties of the future crop prices and precipitation. κ and ν describe agent's beliefs in their prior knowledge of the mean and variance of crop prices (κ_pr, ν_pr) and precipitation (κ_prep, ν_prep), and λ is used to describe the agent's attitude towards the fluctuation of crop profits. Notice that these human behavioral parameters as inputs to the MAS model are highly uncertain and even not measurable. Thus, we estimate the influences of these behavioral parameters on the coupled models using Global Sensitivity Analysis (GSA). In this paper, we address two main challenges arising from GSA with such a large-scale socio-hydrological model by using Hadoop-based Cloud Computing techniques and Polynomial Chaos Expansion (PCE) based variance decomposition approach. As a result, 1,000 scenarios of the coupled models are completed within two hours with the Hadoop framework, rather than about 28days if we run those scenarios sequentially. Based on the model results, GSA using PCE is able to measure the impacts of the spatial and temporal variations of these behavioral parameters on crop profits and water table, and thus identifies two influential parameters, κ_pr and λ. The major contribution of this work is a methodological framework for the application of GSA in large-scale socio-hydrological models. This framework attempts to find a balance between the heavy computational burden regarding model execution and the number of model evaluations required in the GSA analysis, particularly through an organic combination of Hadoop-based Cloud Computing to efficiently evaluate the socio-hydrological model and PCE where the sensitivity indices are efficiently estimated from its coefficients.

Pest and Disease Management: Why We Shouldn't Go against the Grain

PubMed Central

Skelsey, Peter; With, Kimberly A.; Garrett, Karen A.

2013-01-01

Given the wide range of scales and mechanisms by which pest or disease agents disperse, it is unclear whether there might exist a general relationship between scale of host heterogeneity and spatial spread that could be exploited by available management options. In this model-based study, we investigate the interaction between host distributions and the spread of pests and diseases using an array of models that encompass the dispersal and spread of a diverse range of economically important species: a major insect pest of coniferous forests in western North America, the mountain pine beetle (Dendroctonus ponderosae); the bacterium Pseudomonas syringae, one of the most-widespread and best-studied bacterial plant pathogens; the mosquito Culex erraticus, an important vector for many human and animal pathogens, including West Nile Virus; and the oomycete Phytophthora infestans, the causal agent of potato late blight. Our model results reveal an interesting general phenomenon: a unimodal (‘humpbacked’) relationship in the magnitude of infestation (an index of dispersal or population spread) with increasing grain size (i.e., the finest scale of patchiness) in the host distribution. Pest and disease management strategies targeting different aspects of host pattern (e.g., abundance, aggregation, isolation, quality) modified the shape of this relationship, but not the general unimodal form. This is a previously unreported effect that provides insight into the spatial scale at which management interventions are most likely to be successful, which, notably, do not always match the scale corresponding to maximum infestation. Our findings could provide a new basis for explaining historical outbreak events, and have implications for biosecurity and public health preparedness. PMID:24098739

Pest and disease management: why we shouldn't go against the grain.

PubMed

Skelsey, Peter; With, Kimberly A; Garrett, Karen A

2013-01-01

Given the wide range of scales and mechanisms by which pest or disease agents disperse, it is unclear whether there might exist a general relationship between scale of host heterogeneity and spatial spread that could be exploited by available management options. In this model-based study, we investigate the interaction between host distributions and the spread of pests and diseases using an array of models that encompass the dispersal and spread of a diverse range of economically important species: a major insect pest of coniferous forests in western North America, the mountain pine beetle (Dendroctonus ponderosae); the bacterium Pseudomonas syringae, one of the most-widespread and best-studied bacterial plant pathogens; the mosquito Culex erraticus, an important vector for many human and animal pathogens, including West Nile Virus; and the oomycete Phytophthora infestans, the causal agent of potato late blight. Our model results reveal an interesting general phenomenon: a unimodal ('humpbacked') relationship in the magnitude of infestation (an index of dispersal or population spread) with increasing grain size (i.e., the finest scale of patchiness) in the host distribution. Pest and disease management strategies targeting different aspects of host pattern (e.g., abundance, aggregation, isolation, quality) modified the shape of this relationship, but not the general unimodal form. This is a previously unreported effect that provides insight into the spatial scale at which management interventions are most likely to be successful, which, notably, do not always match the scale corresponding to maximum infestation. Our findings could provide a new basis for explaining historical outbreak events, and have implications for biosecurity and public health preparedness.

Applying Spatial Audio to Human Interfaces: 25 Years of NASA Experience

NASA Technical Reports Server (NTRS)

Begault, Durand R.; Wenzel, Elizabeth M.; Godfrey, Martine; Miller, Joel D.; Anderson, Mark R.

2010-01-01

From the perspective of human factors engineering, the inclusion of spatial audio within a human-machine interface is advantageous from several perspectives. Demonstrated benefits include the ability to monitor multiple streams of speech and non-speech warning tones using a cocktail party advantage, and for aurally-guided visual search. Other potential benefits include the spatial coordination and interaction of multimodal events, and evaluation of new communication technologies and alerting systems using virtual simulation. Many of these technologies were developed at NASA Ames Research Center, beginning in 1985. This paper reviews examples and describes the advantages of spatial sound in NASA-related technologies, including space operations, aeronautics, and search and rescue. The work has involved hardware and software development as well as basic and applied research.

Agent-based human-robot interaction of a combat bulldozer

NASA Astrophysics Data System (ADS)

Granot, Reuven; Feldman, Maxim

2004-09-01

A small-scale supervised autonomous bulldozer in a remote site was developed to experience agent based human intervention. The model is based on Lego Mindstorms kit and represents combat equipment, whose job performance does not require high accuracy. The model enables evaluation of system response for different operator interventions, as well as for a small colony of semiautonomous dozers. The supervising human may better react than a fully autonomous system to unexpected contingent events, which are a major barrier to implement full autonomy. The automation is introduced as improved Man Machine Interface (MMI) by developing control agents as intelligent tools to negotiate between human requests and task level controllers as well as negotiate with other elements of the software environment. Current UGVs demand significant communication resources and constant human operation. Therefore they will be replaced by semi-autonomous human supervisory controlled systems (telerobotic). For human intervention at the low layers of the control hierarchy we suggest a task oriented control agent to take care of the fluent transition between the state in which the robot operates and the one imposed by the human. This transition should take care about the imperfections, which are responsible for the improper operation of the robot, by disconnecting or adapting them to the new situation. Preliminary conclusions from the small-scale experiments are presented.

A topological multilayer model of the human body.

PubMed

Barbeito, Antonio; Painho, Marco; Cabral, Pedro; O'Neill, João

2015-11-04

Geographical information systems deal with spatial databases in which topological models are described with alphanumeric information. Its graphical interfaces implement the multilayer concept and provide powerful interaction tools. In this study, we apply these concepts to the human body creating a representation that would allow an interactive, precise, and detailed anatomical study. A vector surface component of the human body is built using a three-dimensional (3-D) reconstruction methodology. This multilayer concept is implemented by associating raster components with the corresponding vector surfaces, which include neighbourhood topology enabling spatial analysis. A root mean square error of 0.18 mm validated the three-dimensional reconstruction technique of internal anatomical structures. The expansion of the identification and the development of a neighbourhood analysis function are the new tools provided in this model.

Student Use of Animated Pedagogical Agents in a Middle School Science Inquiry Program

ERIC Educational Resources Information Center

Bowman, Catherine D. D.

2012-01-01

Animated pedagogical agents (APAs) have the potential to provide one-on-one, just-in-time instruction, guidance or mentoring in classrooms where such individualized human interactions may be infeasible. Much current APA research focuses on a wide range of design variables tested with small samples or in laboratory settings, while overlooking…

Self-Regulated Learning in Learning Environments with Pedagogical Agents that Interact in Natural Language

ERIC Educational Resources Information Center

Graesser, Arthur; McNamara, Danielle

2010-01-01

This article discusses the occurrence and measurement of self-regulated learning (SRL) both in human tutoring and in computer tutors with agents that hold conversations with students in natural language and help them learn at deeper levels. One challenge in building these computer tutors is to accommodate, encourage, and scaffold SRL because these…

Knowing Who Dunnit: Infants Identify the Causal Agent in an Unseen Causal Interaction

ERIC Educational Resources Information Center

Saxe, Rebecca; Tzelnic, Tania; Carey, Susan

2007-01-01

Preverbal infants can represent the causal structure of events, including distinguishing the agentive and receptive roles and categorizing entities according to stable causal dispositions. This study investigated how infants combine these 2 kinds of causal inference. In Experiments 1 and 2, 9.5-month-olds used the position of a human hand or a…

Combining Human and Machine Intelligence to Derive Agents' Behavioral Rules for Groundwater Irrigation

NASA Astrophysics Data System (ADS)

Hu, Y.; Quinn, C.; Cai, X.

2015-12-01

One major challenge of agent-based modeling is to derive agents' behavioral rules due to behavioral uncertainty and data scarcity. This study proposes a new approach to combine a data-driven modeling based on the directed information (i.e., machine intelligence) with expert domain knowledge (i.e., human intelligence) to derive the behavioral rules of agents considering behavioral uncertainty. A directed information graph algorithm is applied to identifying the causal relationships between agents' decisions (i.e., groundwater irrigation depth) and time-series of environmental, socio-economical and institutional factors. A case study is conducted for the High Plains aquifer hydrological observatory (HO) area, U.S. Preliminary results show that four factors, corn price (CP), underlying groundwater level (GWL), monthly mean temperature (T) and precipitation (P) have causal influences on agents' decisions on groundwater irrigation depth (GWID) to various extents. Based on the similarity of the directed information graph for each agent, five clusters of graphs are further identified to represent all the agents' behaviors in the study area as shown in Figure 1. Using these five representative graphs, agents' monthly optimal groundwater pumping rates are derived through the probabilistic inference. Such data-driven relationships and probabilistic quantifications are then coupled with a physically-based groundwater model to investigate the interactions between agents' pumping behaviors and the underlying groundwater system in the context of coupled human and natural systems.

Fundamental properties of cooperative contagion processes

NASA Astrophysics Data System (ADS)

Chen, Li; Ghanbarnejad, Fakhteh; Brockmann, Dirk

2017-10-01

We investigate the effects of cooperativity between contagion processes that spread and persist in a host population. We propose and analyze a dynamical model in which individuals that are affected by one transmissible agent A exhibit a higher than baseline propensity of being affected by a second agent B and vice versa. The model is a natural extension of the traditional susceptible-infected-susceptible model used for modeling single contagion processes. We show that cooperativity changes the dynamics of the system considerably when cooperativity is strong. The system exhibits discontinuous phase transitions not observed in single agent contagion, multi-stability, a separation of the traditional epidemic threshold into different thresholds for inception and extinction as well as hysteresis. These properties are robust and are corroborated by stochastic simulations on lattices and generic network topologies. Finally, we investigate wave propagation and transients in a spatially extended version of the model and show that especially for intermediate values of baseline reproduction ratios the system is characterized by various types of wave-front speeds. The system can exhibit spatially heterogeneous stationary states for some parameters and negative front speeds (receding wave fronts). The two agent model can be employed as a starting point for more complex contagion processes, involving several interacting agents, a model framework particularly suitable for modeling the spread and dynamics of microbiological ecosystems in host populations.

Human Activity Helps Prey Win the Predator-Prey Space Race

PubMed Central

Muhly, Tyler B.; Semeniuk, Christina; Massolo, Alessandro; Hickman, Laura; Musiani, Marco

2011-01-01

Predator-prey interactions, including between large mammalian wildlife species, can be represented as a “space race”, where prey try to minimize and predators maximize spatial overlap. Human activity can also influence the distribution of wildlife species. In particular, high-human disturbance can displace large carnivore predators, a trait-mediated direct effect. Predator displacement by humans could then indirectly benefit prey species by reducing predation risk, a trait-mediated indirect effect of humans that spatially decouples predators from prey. The purpose of this research was to test the hypothesis that high-human activity was displacing predators and thus indirectly creating spatial refuge for prey species, helping prey win the “space race”. We measured the occurrence of eleven large mammal species (including humans and cattle) at 43 camera traps deployed on roads and trails in southwest Alberta, Canada. We tested species co-occurrence at camera sites using hierarchical cluster and nonmetric multidimensional scaling (NMS) analyses; and tested whether human activity, food and/or habitat influenced predator and prey species counts at camera sites using regression tree analysis. Cluster and NMS analysis indicated that at camera sites humans co-occurred with prey species more than predator species and predator species had relatively low co-occurrence with prey species. Regression tree analysis indicated that prey species were three times more abundant on roads and trails with >32 humans/day. However, predators were less abundant on roads and trails that exceeded 18 humans/day. Our results support the hypothesis that high-human activity displaced predators but not prey species, creating spatial refuge from predation. High-human activity on roads and trails (i.e., >18 humans/day) has the potential to interfere with predator-prey interactions via trait-mediated direct and indirect effects. We urge scientist and managers to carefully consider and quantify the trait-mediated indirect effects of humans, in addition to direct effects, when assessing human impacts on wildlife and ecosystems. PMID:21399682

Do young toddlers act on their social preferences?

PubMed

Dahl, Audun; Schuck, Rachel K; Campos, Joseph J

2013-10-01

From preschool age to adulthood, most humans prefer to help someone who has treated others well over helping someone who has treated others badly. Researchers have recently made opposing predictions about whether such observation-based preferential helping is present when children begin to help in the second year of life. In the present study, 84 toddlers (16-27 months) observed 1 experimenter (antisocial) take a ball from, and 1 experimenter (prosocial) return a ball to, a neutral experimenter. In subsequent tests, children could help either the antisocial or the prosocial experimenter. Only the oldest children showed a significant preference for helping the prosocial agent first. Most children in all age groups were willing to help both experimenters when given multiple opportunities to help. Across age groups, children who looked longer at the continuation of the antisocial interaction were more likely to help the prosocial agent. These findings suggest that social evaluations do affect toddlers' helping behavior but that interactions between human agents may be difficult to evaluate for very young children.

The influence of a bystander agent's beliefs on children's and adults' decision-making process.

PubMed

Buttelmann, Frances; Buttelmann, David

2017-01-01

The ability to attribute and represent others' mental states (e.g., beliefs; so-called "theory of mind") is essential for participation in human social interaction. Despite a considerable body of research using tasks in which protagonists in the participants' attentional focus held false or true beliefs, the question of automatic belief attribution to bystander agents has received little attention. In the current study, we presented adults and 6-year-olds (N=92) with an implicit computer-based avoidance false-belief task in which participants were asked to place an object into one of three boxes. While doing so, we manipulated the beliefs of an irrelevant human-like or non-human-like bystander agent who was visible on the screen. Importantly, the bystander agent's beliefs were irrelevant for solving the task. Still, children's decision making was significantly influenced by the bystander agent's beliefs even if this was a non-human-like self-propelled object. Such an influence did not become obvious in adults' deliberate decisions but occurred only in their reaction times, which suggests that they also processed the bystander agent's beliefs but were able to suppress the influence of such beliefs on their behavior regulation. The results of a control study (N=53) ruled out low-level explanations and confirmed that self-propelledness of agents is a necessary factor for belief attribution to occur. Thus, not only do humans spontaneously ascribe beliefs to self-propelled bystander agents, but those beliefs even influence meaningful decisions in children. Copyright © 2016 Elsevier Inc. All rights reserved.

Punctuated equilibrium dynamics in human communications

NASA Astrophysics Data System (ADS)

Peng, Dan; Han, Xiao-Pu; Wei, Zong-Wen; Wang, Bing-Hong

2015-10-01

A minimal model based on network incorporating individual interactions is proposed to study the non-Poisson statistical properties of human behavior: individuals in system interact with their neighbors, the probability of an individual acting correlates to its activity, and all the individuals involved in action will change their activities randomly. The model reproduces varieties of spatial-temporal patterns observed in empirical studies of human daily communications, providing insight into various human activities and embracing a range of realistic social interacting systems, particularly, intriguing bimodal phenomenon. This model bridges priority queueing theory and punctuated equilibrium dynamics, and our modeling and analysis is likely to shed light on non-Poisson phenomena in many complex systems.

Infants' Understanding of False Labeling Events: The Referential Roles of Words and the Speakers Who Use Them.

ERIC Educational Resources Information Center

Koenig, Melissa A.; Echols, Catharine H.

2003-01-01

Four studies examined whether 16-month-olds' responses to true/false utterances interacted with their knowledge of human agents. Findings suggested that infants are developing a critical conception of human speakers as truthful communicators and that infants understand that human speakers may provide uniquely useful information when a word fails…

Cholinergic, But Not Dopaminergic or Noradrenergic, Enhancement Sharpens Visual Spatial Perception in Humans

PubMed Central

Wallace, Deanna L.

2017-01-01

The neuromodulator acetylcholine modulates spatial integration in visual cortex by altering the balance of inputs that generate neuronal receptive fields. These cholinergic effects may provide a neurobiological mechanism underlying the modulation of visual representations by visual spatial attention. However, the consequences of cholinergic enhancement on visuospatial perception in humans are unknown. We conducted two experiments to test whether enhancing cholinergic signaling selectively alters perceptual measures of visuospatial interactions in human subjects. In Experiment 1, a double-blind placebo-controlled pharmacology study, we measured how flanking distractors influenced detection of a small contrast decrement of a peripheral target, as a function of target-flanker distance. We found that cholinergic enhancement with the cholinesterase inhibitor donepezil improved target detection, and modeling suggested that this was mainly due to a narrowing of the extent of facilitatory perceptual spatial interactions. In Experiment 2, we tested whether these effects were selective to the cholinergic system or would also be observed following enhancements of related neuromodulators dopamine or norepinephrine. Unlike cholinergic enhancement, dopamine (bromocriptine) and norepinephrine (guanfacine) manipulations did not improve performance or systematically alter the spatial profile of perceptual interactions between targets and distractors. These findings reveal mechanisms by which cholinergic signaling influences visual spatial interactions in perception and improves processing of a visual target among distractors, effects that are notably similar to those of spatial selective attention. SIGNIFICANCE STATEMENT Acetylcholine influences how visual cortical neurons integrate signals across space, perhaps providing a neurobiological mechanism for the effects of visual selective attention. However, the influence of cholinergic enhancement on visuospatial perception remains unknown. Here we demonstrate that cholinergic enhancement improves detection of a target flanked by distractors, consistent with sharpened visuospatial perceptual representations. Furthermore, whereas most pharmacological studies focus on a single neurotransmitter, many neuromodulators can have related effects on cognition and perception. Thus, we also demonstrate that enhancing noradrenergic and dopaminergic systems does not systematically improve visuospatial perception or alter its tuning. Our results link visuospatial tuning effects of acetylcholine at the neuronal and perceptual levels and provide insights into the connection between cholinergic signaling and visual attention. PMID:28336568

Change Process in Organizations [in HRD].

ERIC Educational Resources Information Center

1995

These four papers are from a symposium that was facilitated by Toni Powell on the change process in organizations at the 1995 Academy of Human Resource Development (HRD) conference. "The Effectiveness of Change Agents as Affected by Strategic Interactions" (Marie A. George) explores the nature of strategic interactions exhibited by a chief…

Modeling Human Dynamics of Face-to-Face Interaction Networks

NASA Astrophysics Data System (ADS)

Starnini, Michele; Baronchelli, Andrea; Pastor-Satorras, Romualdo

2013-04-01

Face-to-face interaction networks describe social interactions in human gatherings, and are the substrate for processes such as epidemic spreading and gossip propagation. The bursty nature of human behavior characterizes many aspects of empirical data, such as the distribution of conversation lengths, of conversations per person, or of interconversation times. Despite several recent attempts, a general theoretical understanding of the global picture emerging from data is still lacking. Here we present a simple model that reproduces quantitatively most of the relevant features of empirical face-to-face interaction networks. The model describes agents that perform a random walk in a two-dimensional space and are characterized by an attractiveness whose effect is to slow down the motion of people around them. The proposed framework sheds light on the dynamics of human interactions and can improve the modeling of dynamical processes taking place on the ensuing dynamical social networks.

Charecterisation and Modelling Urbanisation Pattern in Sillicon Valley of India

NASA Astrophysics Data System (ADS)

Aithal, B. H.

2015-12-01

Urbanisation and Urban sprawl has led to environmental problems and large losses of arable land in India. In this study, we characterise pattern of urban growth and model urban sprawl by means of a combination of remote sensing, geographical information system, spatial metrics and CA based modelling. This analysis uses time-series data to explore and derive the potential political-socio-economic- land based driving forces behind urbanisation and urban sprawl, and spatial models in different scenarios to explore the spatio-temporal interactions and development. The study area applied is Greater Bangalore, for the period from 1973 to 2015. Further water bodies depletion, vegetation depletion, tree cover were also analysed to obtain specific region based results effecting global climate and regional balance. Agents were integrated successfully into modelling aspects to understand and foresee the landscape pattern change in urban morphology. The results reveal built-up paved surfaces has expanded towards the outskirts and have expanded into the buffer regions around the city. Population growth, economic, industrial developments in the city core and transportation development are still the main causes of urban sprawl in the region. Agent based model are considered to be to the traditional models. Agent Based modelling approach as seen in this paper clearly shown its effectiveness in capturing the micro dynamics and influence in its neighbourhood mapping. Greenhouse gas emission inventory has shown important aspects such as domestic sector to be one of the major impact categories in the region. Further tree cover reduced drastically and is evident from the statistics and determines that if city is in verge of creating a chaos in terms of human health and desertification. Study concludes that integration of remote sensing, GIS, and agent based modelling offers an excellent opportunity to explore the spatio-temporal variation and visulaisation of sprawling metropolitan region. This study give a complete overview of urbanisation and effects being caused due to urban sprawl in the region and help planners and city managers in understanding the future pockets and scenarios of urban growth.

Toward Shared Working Space of Human and Robotic Agents Through Dipole Flow Field for Dependable Path Planning.

PubMed

Trinh, Lan Anh; Ekström, Mikael; Cürüklü, Baran

2018-01-01

Recent industrial developments in autonomous systems, or agents, which assume that humans and the agents share the same space or even work in close proximity, open for new challenges in robotics, especially in motion planning and control. In these settings, the control system should be able to provide these agents a reliable path following control when they are working in a group or in collaboration with one or several humans in complex and dynamic environments. In such scenarios, these agents are not only moving to reach their goals, i.e., locations, they are also aware of the movements of other entities to find a collision-free path. Thus, this paper proposes a dependable, i.e., safe, reliable and effective, path planning algorithm for a group of agents that share their working space with humans. Firstly, the method employs the Theta * algorithm to initialize the paths from a starting point to a goal for a set of agents. As Theta * algorithm is computationally heavy, it only reruns when there is a significant change of the environment. To deal with the movements of the agents, a static flow field along the configured path is defined. This field is used by the agents to navigate and reach their goals even if the planned trajectories are changed. Secondly, a dipole field is calculated to avoid the collision of agents with other agents and human subjects. In this approach, each agent is assumed to be a source of a magnetic dipole field in which the magnetic moment is aligned with the moving direction of the agent. The magnetic dipole-dipole interactions between these agents generate repulsive forces to help them to avoid collision. The effectiveness of the proposed approach has been evaluated with extensive simulations. The results show that the static flow field is able to drive agents to the goals with a small number of requirements to update the path of agents. Meanwhile, the dipole flow field plays an important role to prevent collisions. The combination of these two fields results in a safe path planning algorithm, with a deterministic outcome, to navigate agents to their desired goals.

Brain activation related to the perception of minimal agency cues: the role of the mirror system.

PubMed

Stosic, Marina; Brass, Marcel; Van Hoeck, Nicole; Ma, Ning; Van Overwalle, Frank

2014-02-01

Recent fMRI studies indicate that the posterior superior temporal sulcus (pSTS) and the mirror system are involved in analyzing goal-directed actions performed by non-human objects. However, these studies have some limitations: the animations showed moving shapes that resemble humans and human movement, or showed the interaction of two moving shapes rather than one alone. This may have prompted participants to assume a human agent instead of an object. To avoid this potential confound, in this study, animations showed a small circular shape (agent) jumping toward a bigger circular shape (goal) with an obstacle separating them. We manipulated agency of the small circular shape by showing its movements as self-propelled (Agent condition) or as launched by a lever mechanism (Non-agent condition). The small shape succeeded in avoiding an obstacle and reaching the goal object or failed to do so. Our results showed that goal-directed actions performed by an agentic shape recruited the mirror system (the inferior parietal lobe and the premotor cortex) in comparison with shapes that were launched. Success or failure to avoid the obstacle had no effect on these areas. These results complement and further extend previous findings indicating that the mirror system does not appear to be selective for biological actions and their goals, nor does it require the presence of a human, human body parts or human-made objects. Instead, it seems to play a general role in representing goal-directed actions of agents regardless of their form. © 2013.

Risk, individual differences, and environment: an Agent-Based Modeling approach to sexual risk-taking.

PubMed

Nagoski, Emily; Janssen, Erick; Lohrmann, David; Nichols, Eric

2012-08-01

Risky sexual behaviors, including the decision to have unprotected sex, result from interactions between individuals and their environment. The current study explored the use of Agent-Based Modeling (ABM)-a methodological approach in which computer-generated artificial societies simulate human sexual networks-to assess the influence of heterogeneity of sexual motivation on the risk of contracting HIV. The models successfully simulated some characteristics of human sexual systems, such as the relationship between individual differences in sexual motivation (sexual excitation and inhibition) and sexual risk, but failed to reproduce the scale-free distribution of number of partners observed in the real world. ABM has the potential to inform intervention strategies that target the interaction between an individual and his or her social environment.

Intrinsically motivated reinforcement learning for human-robot interaction in the real-world.

PubMed

Qureshi, Ahmed Hussain; Nakamura, Yutaka; Yoshikawa, Yuichiro; Ishiguro, Hiroshi

2018-03-26

For a natural social human-robot interaction, it is essential for a robot to learn the human-like social skills. However, learning such skills is notoriously hard due to the limited availability of direct instructions from people to teach a robot. In this paper, we propose an intrinsically motivated reinforcement learning framework in which an agent gets the intrinsic motivation-based rewards through the action-conditional predictive model. By using the proposed method, the robot learned the social skills from the human-robot interaction experiences gathered in the real uncontrolled environments. The results indicate that the robot not only acquired human-like social skills but also took more human-like decisions, on a test dataset, than a robot which received direct rewards for the task achievement. Copyright © 2018 Elsevier Ltd. All rights reserved.

Nonverbal components of Theory of Mind in typical and atypical development.

PubMed

Kampis, Dora; Fogd, Dóra; Kovács, Ágnes Melinda

2017-08-01

To successfully navigate the human social world one needs to realize that behavior is guided by mental states such as goals and beliefs. Humans are highly proficient in using mental states to explain and predict their conspecific's behavior, which enables adjusting one's own behavior in online social interactions. Whereas according to recent studies even young infants seem to integrate others' beliefs into their own behavior, it is unclear what processes contribute to such competencies and how they may develop. Here we analyze a set of possible nonverbal components of theory of mind that may be involved in taking into account others' mental states, and discuss findings from typical and atypical development. To track an agent's belief one needs to (i) pay attention to agents that might be potential belief holders, and identify their focus of attention and their potential belief contents; (ii) keep track of their different experiences and their consequent beliefs, and (iii) to make behavioral predictions based on such beliefs. If an individual fails to predict an agent's behavior depending on the agent's beliefs, this may be due to a problem at any stage in the above processes. An analysis of the possible nonverbal processes contributing to belief tracking and their functioning in typical and atypical development aims to provide new insights into the possible mechanisms that make human social interactions uniquely rich. Copyright © 2016 Elsevier Inc. All rights reserved.

Modelling Adaptive Learning Behaviours for Consensus Formation in Human Societies

NASA Astrophysics Data System (ADS)

Yu, Chao; Tan, Guozhen; Lv, Hongtao; Wang, Zhen; Meng, Jun; Hao, Jianye; Ren, Fenghui

2016-06-01

Learning is an important capability of humans and plays a vital role in human society for forming beliefs and opinions. In this paper, we investigate how learning affects the dynamics of opinion formation in social networks. A novel learning model is proposed, in which agents can dynamically adapt their learning behaviours in order to facilitate the formation of consensus among them, and thus establish a consistent social norm in the whole population more efficiently. In the model, agents adapt their opinions through trail-and-error interactions with others. By exploiting historical interaction experience, a guiding opinion, which is considered to be the most successful opinion in the neighbourhood, can be generated based on the principle of evolutionary game theory. Then, depending on the consistency between its own opinion and the guiding opinion, a focal agent can realize whether its opinion complies with the social norm (i.e., the majority opinion that has been adopted) in the population, and adapt its behaviours accordingly. The highlight of the model lies in that it captures the essential features of people’s adaptive learning behaviours during the evolution and formation of opinions. Experimental results show that the proposed model can facilitate the formation of consensus among agents, and some critical factors such as size of opinion space and network topology can have significant influences on opinion dynamics.

Modelling Adaptive Learning Behaviours for Consensus Formation in Human Societies.

PubMed

Yu, Chao; Tan, Guozhen; Lv, Hongtao; Wang, Zhen; Meng, Jun; Hao, Jianye; Ren, Fenghui

2016-06-10

Learning is an important capability of humans and plays a vital role in human society for forming beliefs and opinions. In this paper, we investigate how learning affects the dynamics of opinion formation in social networks. A novel learning model is proposed, in which agents can dynamically adapt their learning behaviours in order to facilitate the formation of consensus among them, and thus establish a consistent social norm in the whole population more efficiently. In the model, agents adapt their opinions through trail-and-error interactions with others. By exploiting historical interaction experience, a guiding opinion, which is considered to be the most successful opinion in the neighbourhood, can be generated based on the principle of evolutionary game theory. Then, depending on the consistency between its own opinion and the guiding opinion, a focal agent can realize whether its opinion complies with the social norm (i.e., the majority opinion that has been adopted) in the population, and adapt its behaviours accordingly. The highlight of the model lies in that it captures the essential features of people's adaptive learning behaviours during the evolution and formation of opinions. Experimental results show that the proposed model can facilitate the formation of consensus among agents, and some critical factors such as size of opinion space and network topology can have significant influences on opinion dynamics.

Modelling Adaptive Learning Behaviours for Consensus Formation in Human Societies

PubMed Central

Yu, Chao; Tan, Guozhen; Lv, Hongtao; Wang, Zhen; Meng, Jun; Hao, Jianye; Ren, Fenghui

2016-01-01

Learning is an important capability of humans and plays a vital role in human society for forming beliefs and opinions. In this paper, we investigate how learning affects the dynamics of opinion formation in social networks. A novel learning model is proposed, in which agents can dynamically adapt their learning behaviours in order to facilitate the formation of consensus among them, and thus establish a consistent social norm in the whole population more efficiently. In the model, agents adapt their opinions through trail-and-error interactions with others. By exploiting historical interaction experience, a guiding opinion, which is considered to be the most successful opinion in the neighbourhood, can be generated based on the principle of evolutionary game theory. Then, depending on the consistency between its own opinion and the guiding opinion, a focal agent can realize whether its opinion complies with the social norm (i.e., the majority opinion that has been adopted) in the population, and adapt its behaviours accordingly. The highlight of the model lies in that it captures the essential features of people’s adaptive learning behaviours during the evolution and formation of opinions. Experimental results show that the proposed model can facilitate the formation of consensus among agents, and some critical factors such as size of opinion space and network topology can have significant influences on opinion dynamics. PMID:27282089

Review of the systems biology of the immune system using agent-based models.

PubMed

Shinde, Snehal B; Kurhekar, Manish P

2018-06-01

The immune system is an inherent protection system in vertebrate animals including human beings that exhibit properties such as self-organisation, self-adaptation, learning, and recognition. It interacts with the other allied systems such as the gut and lymph nodes. There is a need for immune system modelling to know about its complex internal mechanism, to understand how it maintains the homoeostasis, and how it interacts with the other systems. There are two types of modelling techniques used for the simulation of features of the immune system: equation-based modelling (EBM) and agent-based modelling. Owing to certain shortcomings of the EBM, agent-based modelling techniques are being widely used. This technique provides various predictions for disease causes and treatments; it also helps in hypothesis verification. This study presents a review of agent-based modelling of the immune system and its interactions with the gut and lymph nodes. The authors also review the modelling of immune system interactions during tuberculosis and cancer. In addition, they also outline the future research directions for the immune system simulation through agent-based techniques such as the effects of stress on the immune system, evolution of the immune system, and identification of the parameters for a healthy immune system.

Scaling identity connects human mobility and social interactions.

PubMed

Deville, Pierre; Song, Chaoming; Eagle, Nathan; Blondel, Vincent D; Barabási, Albert-László; Wang, Dashun

2016-06-28

Massive datasets that capture human movements and social interactions have catalyzed rapid advances in our quantitative understanding of human behavior during the past years. One important aspect affecting both areas is the critical role space plays. Indeed, growing evidence suggests both our movements and communication patterns are associated with spatial costs that follow reproducible scaling laws, each characterized by its specific critical exponents. Although human mobility and social networks develop concomitantly as two prolific yet largely separated fields, we lack any known relationships between the critical exponents explored by them, despite the fact that they often study the same datasets. Here, by exploiting three different mobile phone datasets that capture simultaneously these two aspects, we discovered a new scaling relationship, mediated by a universal flux distribution, which links the critical exponents characterizing the spatial dependencies in human mobility and social networks. Therefore, the widely studied scaling laws uncovered in these two areas are not independent but connected through a deeper underlying reality.

Scaling identity connects human mobility and social interactions

PubMed Central

Deville, Pierre; Song, Chaoming; Eagle, Nathan; Blondel, Vincent D.; Barabási, Albert-László; Wang, Dashun

2016-01-01

Massive datasets that capture human movements and social interactions have catalyzed rapid advances in our quantitative understanding of human behavior during the past years. One important aspect affecting both areas is the critical role space plays. Indeed, growing evidence suggests both our movements and communication patterns are associated with spatial costs that follow reproducible scaling laws, each characterized by its specific critical exponents. Although human mobility and social networks develop concomitantly as two prolific yet largely separated fields, we lack any known relationships between the critical exponents explored by them, despite the fact that they often study the same datasets. Here, by exploiting three different mobile phone datasets that capture simultaneously these two aspects, we discovered a new scaling relationship, mediated by a universal flux distribution, which links the critical exponents characterizing the spatial dependencies in human mobility and social networks. Therefore, the widely studied scaling laws uncovered in these two areas are not independent but connected through a deeper underlying reality. PMID:27274050

Model-based Utility Functions

NASA Astrophysics Data System (ADS)

Hibbard, Bill

2012-05-01

Orseau and Ring, as well as Dewey, have recently described problems, including self-delusion, with the behavior of agents using various definitions of utility functions. An agent's utility function is defined in terms of the agent's history of interactions with its environment. This paper argues, via two examples, that the behavior problems can be avoided by formulating the utility function in two steps: 1) inferring a model of the environment from interactions, and 2) computing utility as a function of the environment model. Basing a utility function on a model that the agent must learn implies that the utility function must initially be expressed in terms of specifications to be matched to structures in the learned model. These specifications constitute prior assumptions about the environment so this approach will not work with arbitrary environments. But the approach should work for agents designed by humans to act in the physical world. The paper also addresses the issue of self-modifying agents and shows that if provided with the possibility to modify their utility functions agents will not choose to do so, under some usual assumptions.

Human Metabolism and Interactions of Deployment-Related Chemicals

DTIC Science & Technology

2003-08-01

with individual test compounds (final concentration, 100 PM), agent pyridostigmine bromide to protect against possible nerve gas NADPH-generating system...an insect repellent (N,N-diethyl-m- toluamide) a nerve gas prophyllactic (pyridostigmine bromide) did not cause the inhibition of trans-permethrin...mechanism of organophosphorus anticholinesterase agents , namely; covalent modification of the active site of the esterases in question. Carbaryl, another

Simulating forest landscape disturbances as coupled human and natural systems

USGS Publications Warehouse

Wimberly, Michael; Sohl, Terry L.; Liu, Zhihua; Lamsal, Aashis

2015-01-01

Anthropogenic disturbances resulting from human land use affect forest landscapes over a range of spatial and temporal scales, with diverse influences on vegetation patterns and dynamics. These processes fall within the scope of the coupled human and natural systems (CHANS) concept, which has emerged as an important framework for understanding the reciprocal interactions and feedbacks that connect human activities and ecosystem responses. Spatial simulation modeling of forest landscape change is an important technique for exploring the dynamics of CHANS over large areas and long time periods. Landscape models for simulating interactions between human activities and forest landscape dynamics can be grouped into two main categories. Forest landscape models (FLMs) focus on landscapes where forests are the dominant land cover and simulate succession and natural disturbances along with forest management activities. In contrast, land change models (LCMs) simulate mosaics of different land cover and land use classes that include forests in addition to other land uses such as developed areas and agricultural lands. There are also several examples of coupled models that combine elements of FLMs and LCMs. These integrated models are particularly useful for simulating human–natural interactions in landscapes where human settlement and agriculture are expanding into forested areas. Despite important differences in spatial scale and disciplinary scope, FLMs and LCMs have many commonalities in conceptual design and technical implementation that can facilitate continued integration. The ultimate goal will be to implement forest landscape disturbance modeling in a CHANS framework that recognizes the contextual effects of regional land use and other human activities on the forest ecosystem while capturing the reciprocal influences of forests and their disturbances on the broader land use mosaic.

Tick-Borne Zoonoses in the United States: Persistent and Emerging Threats to Human Health

PubMed Central

Eisen, Rebecca J.; Kugeler, Kiersten J.; Eisen, Lars; Beard, Charles B.; Paddock, Christopher D.

2017-01-01

In the United States, ticks transmit the greatest diversity of arthropod-borne pathogens and are responsible for the most cases of all vector-borne diseases. In recent decades, the number of reported cases of notifiable tick-borne diseases has steadily increased, geographic distributions of many ticks and tick-borne diseases have expanded, and new tick-borne disease agents have been recognized. In this review, we (1) describe the known disease agents associated with the most commonly human-biting ixodid ticks, (2) review the natural histories of these ticks and their associated pathogens, (3) highlight spatial and temporal changes in vector tick distributions and tick-borne disease occurrence in recent decades, and (4) identify knowledge gaps and barriers to more effective prevention of tick-borne diseases. We describe 12 major tick-borne diseases caused by 15 distinct disease agents that are transmitted by the 8 most commonly human-biting ixodid ticks in the United States. Notably, 40% of these pathogens were described within the last two decades. Our assessment highlights the importance of animal studies to elucidate how tick-borne pathogens are maintained in nature, as well as advances in molecular detection of pathogens which has led to the discovery of several new tick-borne disease agents. PMID:28369515

Effects of a Pedagogical Agent's Emotional Expressiveness on Learner Perceptions

NASA Technical Reports Server (NTRS)

Romero, Enilda J.; Watson, Ginger S.

2012-01-01

The use of animated pedagogical agents or avatars in instruction has lagged behind their use in entertainment. This is due in part to the cost and complexity of development and implementation of agents in educational settings, but also results from a lack of research to understand how emotions from animated agents influence instructional effectiveness. The phenomenological study presented here assesses the perceptions of eight learners interacting with low and high intensity emotionally expressive pedagogical agents in a computer-mediated environment. Research methods include maximum variation and snowball sampling with random assignment to treatment. The resulting themes incorporate perceptions of importance, agent humanness, enjoyment, implementation barriers, and suggested improvements. Design recommendations and implications for future research are presented.

Situation Awareness of Onboard System Autonomy

NASA Technical Reports Server (NTRS)

Schreckenghost, Debra; Thronesbery, Carroll; Hudson, Mary Beth

2005-01-01

We have developed intelligent agent software for onboard system autonomy. Our approach is to provide control agents that automate crew and vehicle systems, and operations assistants that aid humans in working with these autonomous systems. We use the 3 Tier control architecture to develop the control agent software that automates system reconfiguration and routine fault management. We use the Distributed Collaboration and Interaction (DCI) System to develop the operations assistants that provide human services, including situation summarization, event notification, activity management, and support for manual commanding of autonomous system. In this paper we describe how the operations assistants aid situation awareness of the autonomous control agents. We also describe our evaluation of the DCI System to support control engineers during a ground test at Johnson Space Center (JSC) of the Post Processing System (PPS) for regenerative water recovery.

Urban land use decouples plant-herbivore-parasitoid interactions at multiple spatial scales.

PubMed

Nelson, Amanda E; Forbes, Andrew A

2014-01-01

Intense urban and agricultural development alters habitats, increases fragmentation, and may decouple trophic interactions if plants or animals cannot disperse to needed resources. Specialist insects represent a substantial proportion of global biodiversity and their fidelity to discrete microhabitats provides a powerful framework for investigating organismal responses to human land use. We sampled site occupancy and densities for two plant-herbivore-parasitoid systems from 250 sites across a 360 km2 urban/agricultural landscape to ask whether and how human development decouples interactions between trophic levels. We compared patterns of site occupancy, host plant density, herbivory and parasitism rates of insects at two trophic levels with respect to landcover at multiple spatial scales. Geospatial analyses were used to identify landcover characters predictive of insect distributions. We found that herbivorous insect densities were decoupled from host tree densities in urban landcover types at several spatial scales. This effect was amplified for the third trophic level in one of the two insect systems: despite being abundant regionally, a parasitoid species was absent from all urban/suburban landcover even where its herbivore host was common. Our results indicate that human land use patterns limit distributions of specialist insects. Dispersal constraints associated with urban built development are specifically implicated as a limiting factor.

Urban Land Use Decouples Plant-Herbivore-Parasitoid Interactions at Multiple Spatial Scales

PubMed Central

Nelson, Amanda E.; Forbes, Andrew A.

2014-01-01

Intense urban and agricultural development alters habitats, increases fragmentation, and may decouple trophic interactions if plants or animals cannot disperse to needed resources. Specialist insects represent a substantial proportion of global biodiversity and their fidelity to discrete microhabitats provides a powerful framework for investigating organismal responses to human land use. We sampled site occupancy and densities for two plant-herbivore-parasitoid systems from 250 sites across a 360 km2 urban/agricultural landscape to ask whether and how human development decouples interactions between trophic levels. We compared patterns of site occupancy, host plant density, herbivory and parasitism rates of insects at two trophic levels with respect to landcover at multiple spatial scales. Geospatial analyses were used to identify landcover characters predictive of insect distributions. We found that herbivorous insect densities were decoupled from host tree densities in urban landcover types at several spatial scales. This effect was amplified for the third trophic level in one of the two insect systems: despite being abundant regionally, a parasitoid species was absent from all urban/suburban landcover even where its herbivore host was common. Our results indicate that human land use patterns limit distributions of specialist insects. Dispersal constraints associated with urban built development are specifically implicated as a limiting factor. PMID:25019962

Human-environment interactions and sustainable urban development: Spatial modeling and landscape prediction the case of Nang Rong town, Thailand

NASA Astrophysics Data System (ADS)

Varnakovida, Pariwate

It is now well-recognized that, at local, regional, and global scales, land use changes are significantly altering land cover, perhaps at an accelerating pace. Further, the world's scientific community is increasingly recognizing what, in retrospect, should have been obvious, that human behavior and agency is a critical driver of Land Cover and Land Use Change. In this research, using recently developed computer modeling procedures and a rich case study, I develop spatially-explicit model-based simulations of LULCC scenarios within the rubric of sustainability science for Nang Rong town, Thailand. The research draws heavily on recent work in geography and complexity theory. A series of scenarios were built to explore different development trajectories based upon empirically observed relationships. The development models incorporate a) history and spatial pattern of village settlement; b) road development and changing geographic accessibility; c) population; d) biophysical characteristics and e) social drivers. This research uses multi-temporal and spatially-explicit data, analytic results, and dynamic modeling approaches combined with to describe, explain, and explore LULCC as the consequences of different production theories for rural, small town urbanization in the South East Asian context. Two Agent Based models were built: 1) Settlement model and 2) Land-use model. The Settlement model suggests that new development will emerge along the existing road network especially along the major highway and in close proximity to the urban center. If the population doubles in 2021, the settlement process may inhibit development along some corridors creating low density sprawl. The Land-use model under the urban expansion scenario suggests that new settlements will occur in close proximity to the town center and roads; even though, the area is suitable for rice farming or located on a flood plain. The Land-use model under the cash-crop expansion scenario captures that new agriculture will occur on the flood plain and other areas suitable for rice farming. The Land-use model under the King's Theory scenario suggests that agriculture agents occupied more disperse lands than the cash-crops scenario. In addition, the King's Theory scenario provided more access to water surface than other scenarios and was the most sustainable development plan. These products offer a better understanding of the urban growth and LULCC at a regional scale and will potentially guide more systematic and effective resource management and policy decisions. Although this research focuses on a specific site, the methods employed are applicable to other rural regions with similar characteristics.

Final Report: PAGE: Policy Analytics Generation Engine

DTIC Science & Technology

2016-08-12

develop a parallel framework for it. We also developed policies and methods by which a group of defensive resources (e.g. checkpoints) could be...Sarit Kraus. Learning to Reveal Information in Repeated Human -Computer Negotiation, Human -Agent Interaction Design and Models Workshop 2012. 04-JUN...Joseph Keshet, Sarit Kraus. Predicting Human Strategic Decisions Using Facial Expressions, International Joint Conference on Artificial

Interaction with Machine Improvisation

NASA Astrophysics Data System (ADS)

Assayag, Gerard; Bloch, George; Cont, Arshia; Dubnov, Shlomo

We describe two multi-agent architectures for an improvisation oriented musician-machine interaction systems that learn in real time from human performers. The improvisation kernel is based on sequence modeling and statistical learning. We present two frameworks of interaction with this kernel. In the first, the stylistic interaction is guided by a human operator in front of an interactive computer environment. In the second framework, the stylistic interaction is delegated to machine intelligence and therefore, knowledge propagation and decision are taken care of by the computer alone. The first framework involves a hybrid architecture using two popular composition/performance environments, Max and OpenMusic, that are put to work and communicate together, each one handling the process at a different time/memory scale. The second framework shares the same representational schemes with the first but uses an Active Learning architecture based on collaborative, competitive and memory-based learning to handle stylistic interactions. Both systems are capable of processing real-time audio/video as well as MIDI. After discussing the general cognitive background of improvisation practices, the statistical modelling tools and the concurrent agent architecture are presented. Then, an Active Learning scheme is described and considered in terms of using different improvisation regimes for improvisation planning. Finally, we provide more details about the different system implementations and describe several performances with the system.

Spatiochromatic Interactions between Individual Cone Photoreceptors in the Human Retina

PubMed Central

Sabesan, Ramkumar; Sincich, Lawrence C.

2017-01-01

A remarkable feature of human vision is that the retina and brain have evolved circuitry to extract useful spatial and spectral information from signals originating in a photoreceptor mosaic with trichromatic constituents that vary widely in their relative numbers and local spatial configurations. A critical early transformation applied to cone signals is horizontal-cell-mediated lateral inhibition, which imparts a spatially antagonistic surround to individual cone receptive fields, a signature inherited by downstream neurons and implicated in color signaling. In the peripheral retina, the functional connectivity of cone inputs to the circuitry that mediates lateral inhibition is not cone-type specific, but whether these wiring schemes are maintained closer to the fovea remains unsettled, in part because central retinal anatomy is not easily amenable to direct physiological assessment. Here, we demonstrate how the precise topography of the long (L)-, middle (M)-, and short (S)-wavelength-sensitive cones in the human parafovea (1.5° eccentricity) shapes perceptual sensitivity. We used adaptive optics microstimulation to measure psychophysical detection thresholds from individual cones with spectral types that had been classified independently by absorptance imaging. Measured against chromatic adapting backgrounds, the sensitivities of L and M cones were, on average, receptor-type specific, but individual cone thresholds varied systematically with the number of preferentially activated cones in the immediate neighborhood. The spatial and spectral patterns of these interactions suggest that interneurons mediating lateral inhibition in the central retina, likely horizontal cells, establish functional connections with L and M cones indiscriminately, implying that the cone-selective circuitry supporting red–green color vision emerges after the first retinal synapse. SIGNIFICANCE STATEMENT We present evidence for spatially antagonistic interactions between individual, spectrally typed cones in the central retina of human observers using adaptive optics. Using chromatic adapting fields to modulate the relative steady-state activity of long (L)- and middle (M)-wavelength-sensitive cones, we found that single-cone detection thresholds varied predictably with the spectral demographics of the surrounding cones. The spatial scale and spectral pattern of these photoreceptor interactions were consistent with lateral inhibition mediated by retinal horizontal cells that receive nonselective input from L and M cones. These results demonstrate a clear link between the neural architecture of the visual system inputs—cone photoreceptors—and visual perception and have implications for the neural locus of the cone-specific circuitry supporting color vision. PMID:28871030

Front-Presented Looming Sound Selectively Alters the Perceived Size of a Visual Looming Object.

PubMed

Yamasaki, Daiki; Miyoshi, Kiyofumi; Altmann, Christian F; Ashida, Hiroshi

2018-07-01

In spite of accumulating evidence for the spatial rule governing cross-modal interaction according to the spatial consistency of stimuli, it is still unclear whether 3D spatial consistency (i.e., front/rear of the body) of stimuli also regulates audiovisual interaction. We investigated how sounds with increasing/decreasing intensity (looming/receding sound) presented from the front and rear space of the body impact the size perception of a dynamic visual object. Participants performed a size-matching task (Experiments 1 and 2) and a size adjustment task (Experiment 3) of visual stimuli with increasing/decreasing diameter, while being exposed to a front- or rear-presented sound with increasing/decreasing intensity. Throughout these experiments, we demonstrated that only the front-presented looming sound caused overestimation of the spatially consistent looming visual stimulus in size, but not of the spatially inconsistent and the receding visual stimulus. The receding sound had no significant effect on vision. Our results revealed that looming sound alters dynamic visual size perception depending on the consistency in the approaching quality and the front-rear spatial location of audiovisual stimuli, suggesting that the human brain differently processes audiovisual inputs based on their 3D spatial consistency. This selective interaction between looming signals should contribute to faster detection of approaching threats. Our findings extend the spatial rule governing audiovisual interaction into 3D space.

Using the Gravity Model to Estimate the Spatial Spread of Vector-Borne Diseases

PubMed Central

Barrios, José Miguel; Verstraeten, Willem W.; Maes, Piet; Aerts, Jean-Marie; Farifteh, Jamshid; Coppin, Pol

2012-01-01

The gravity models are commonly used spatial interaction models. They have been widely applied in a large set of domains dealing with interactions amongst spatial entities. The spread of vector-borne diseases is also related to the intensity of interaction between spatial entities, namely, the physical habitat of pathogens’ vectors and/or hosts, and urban areas, thus humans. This study implements the concept behind gravity models in the spatial spread of two vector-borne diseases, nephropathia epidemica and Lyme borreliosis, based on current knowledge on the transmission mechanism of these diseases. Two sources of information on vegetated systems were tested: the CORINE land cover map and MODIS NDVI. The size of vegetated areas near urban centers and a local indicator of occupation-related exposure were found significant predictors of disease risk. Both the land cover map and the space-borne dataset were suited yet not equivalent input sources to locate and measure vegetated areas of importance for disease spread. The overall results point at the compatibility of the gravity model concept and the spatial spread of vector-borne diseases. PMID:23202882

Using the gravity model to estimate the spatial spread of vector-borne diseases.

PubMed

Barrios, José Miguel; Verstraeten, Willem W; Maes, Piet; Aerts, Jean-Marie; Farifteh, Jamshid; Coppin, Pol

2012-11-30

The gravity models are commonly used spatial interaction models. They have been widely applied in a large set of domains dealing with interactions amongst spatial entities. The spread of vector-borne diseases is also related to the intensity of interaction between spatial entities, namely, the physical habitat of pathogens’ vectors and/or hosts, and urban areas, thus humans. This study implements the concept behind gravity models in the spatial spread of two vector-borne diseases, nephropathia epidemica and Lyme borreliosis, based on current knowledge on the transmission mechanism of these diseases. Two sources of information on vegetated systems were tested: the CORINE land cover map and MODIS NDVI. The size of vegetated areas near urban centers and a local indicator of occupation-related exposure were found significant predictors of disease risk. Both the land cover map and the space-borne dataset were suited yet not equivalent input sources to locate and measure vegetated areas of importance for disease spread. The overall results point at the compatibility of the gravity model concept and the spatial spread of vector-borne diseases.

Emotional recognition from the speech signal for a virtual education agent

NASA Astrophysics Data System (ADS)

Tickle, A.; Raghu, S.; Elshaw, M.

2013-06-01

This paper explores the extraction of features from the speech wave to perform intelligent emotion recognition. A feature extract tool (openSmile) was used to obtain a baseline set of 998 acoustic features from a set of emotional speech recordings from a microphone. The initial features were reduced to the most important ones so recognition of emotions using a supervised neural network could be performed. Given that the future use of virtual education agents lies with making the agents more interactive, developing agents with the capability to recognise and adapt to the emotional state of humans is an important step.

Future Oil Spills and Possibilities for Intervention: A Model for the Coupled Human-Environmental Resource Extraction System

NASA Astrophysics Data System (ADS)

Shughrue, C. M.; Werner, B.; Nugnug, P. T.

2010-12-01

The catastrophic Deepwater Horizon oil spill highlights the risks for widespread environmental damage resulting from petroleum resource extraction. Possibilities for amelioration of these risks depend critically on understanding the dynamics and nonlinear interactions between various components of the coupled human-environmental resource extraction system. We use a complexity analysis to identify the levels of description and time scales at which these interactions are strongest, and then use the analysis as the basis for an agent-based numerical model with which decadal trends can be analyzed. Oil industry economic and technological activity and associated oil spills are components of a complex system that is coupled to natural environment, legislation, regulation, media, and resistance systems over annual to decadal time scales. In the model, oil spills are produced stochastically with a range of magnitudes depending on a reliability-engineering-based assessment of failure for the technology employed, human factors including compliance with operating procedures, and risks associated with the drilling environment. Oil industry agents determine drilling location and technological investment using a cost-benefit analysis relating projected revenue from added production to technology cost and government regulation. Media outlet agents reporting on the oil industry and environmental damage from oil spills assess the impacts of aggressively covering a story on circulation increases, advertiser concerns and potential loss of information sources. Environmental advocacy group agents increase public awareness of environmental damage (through media and public contact), solicit memberships and donations, and apply direct pressure on legislators for policy change. Heterogeneous general public agents adjust their desire for change in the level of regulation, contact their representatives or participate in resistance via protest by considering media sources, personal experiences with oil spills and individual predispositions toward the industry. Legislator agents pass legislation and influence regulator agents based on interaction with oil industry, media and general public agents. Regulator agents generate and enforce regulations by responding to pressure from legislator and oil industry agents. Oil spill impacts on the natural environment are related to number and magnitude of spills, drilling locations, and spill response methodology, determined collaboratively by government and oil company agents. Agents at the corporate and government levels use heterogeneous prediction models combined with a constant absolute risk aversion utility for wealth. This model simulates a nonlinear adaptive system with mechanisms to self-regulate oil industry activity, environmental damage and public response. A comparison of model output with historical oil industry development and environmental damage; the sensitivity of oil spill damage to economic, political and social factors; the potential for the emergence of new and possibly unstable behaviors; and opportunities for intervening in system dynamics to alter expected outcomes will be discussed. Supported by NSF: Geomorphology and Land Use Dynamics Program

Agile development of ontologies through conversation

NASA Astrophysics Data System (ADS)

Braines, Dave; Bhattal, Amardeep; Preece, Alun D.; de Mel, Geeth

2016-05-01

Ontologies and semantic systems are necessarily complex but offer great potential in terms of their ability to fuse information from multiple sources in support of situation awareness. Current approaches do not place the ontologies directly into the hands of the end user in the field but instead hide them away behind traditional applications. We have been experimenting with human-friendly ontologies and conversational interactions to enable non-technical business users to interact with and extend these dynamically. In this paper we outline our approach via a worked example, covering: OWL ontologies, ITA Controlled English, Sensor/mission matching and conversational interactions between human and machine agents.

New tools for linking human and earth system models: The Toolbox for Human-Earth System Interaction & Scaling (THESIS)

NASA Astrophysics Data System (ADS)

O'Neill, B. C.; Kauffman, B.; Lawrence, P.

2016-12-01

Integrated analysis of questions regarding land, water, and energy resources often requires integration of models of different types. One type of integration is between human and earth system models, since both societal and physical processes influence these resources. For example, human processes such as changes in population, economic conditions, and policies govern the demand for land, water and energy, while the interactions of these resources with physical systems determine their availability and environmental consequences. We have begun to develop and use a toolkit for linking human and earth system models called the Toolbox for Human-Earth System Integration and Scaling (THESIS). THESIS consists of models and software tools to translate, scale, and synthesize information from and between human system models and earth system models (ESMs), with initial application to linking the NCAR integrated assessment model, iPETS, with the NCAR earth system model, CESM. Initial development is focused on urban areas and agriculture, sectors that are both explicitly represented in both CESM and iPETS. Tools are being made available to the community as they are completed (see https://www2.cgd.ucar.edu/sections/tss/iam/THESIS_tools). We discuss four general types of functions that THESIS tools serve (Spatial Distribution, Spatial Properties, Consistency, and Outcome Evaluation). Tools are designed to be modular and can be combined in order to carry out more complex analyses. We illustrate their application to both the exposure of population to climate extremes and to the evaluation of climate impacts on the agriculture sector. For example, projecting exposure to climate extremes involves use of THESIS tools for spatial population, spatial urban land cover, the characteristics of both, and a tool to bring urban climate information together with spatial population information. Development of THESIS tools is continuing and open to the research community.

Intermediate Levels of Autonomy within the SSM/PMAD Breadboard

NASA Technical Reports Server (NTRS)

Dugal-Whitehead, Norma R.; Walls, Bryan

1995-01-01

The Space Station Module Power Management and Distribution (SSM/PMAD) bread-board is a test bed for the development of advanced power system control and automation. Software control in the SSM/PMAD breadboard is through co-operating systems, called Autonomous Agents. Agents can be a mixture of algorithmic software and expert systems. The early SSM/PMAD system was envisioned as being completely autonomous. It soon became apparent, though, that there would always be a need for human intervention, at least as long as a human interacts with the system in any way. In a system designed only for autonomous operation, manual intervention meant taking full control of the whole system, and loosing whatever expertise was in the system. Several methods for allowing humans to interact at an appropriate level of control were developed. This paper examines some of these intermediate modes of autonomy. The least humanly intrusive mode is simple monitoring. The ability to modify future behavior by altering a schedule involves high-level interaction. Modification of operating activities comes next. The coarsest mode of control is individual, unplanned operation of individual Power System components. Each of these levels is integrated into the SSM/PMAD breadboard, with support for the user (such as warnings of the consequences of control decisions) at every level.

Structural aspects of catalytic mechanisms of endonucleases and their binding to nucleic acids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhukhlistova, N. E.; Balaev, V. V.; Lyashenko, A. V.

2012-05-15

Endonucleases (EC 3.1) are enzymes of the hydrolase class that catalyze the hydrolytic cleavage of deoxyribonucleic and ribonucleic acids at any region of the polynucleotide chain. Endonucleases are widely used both in biotechnological processes and in veterinary medicine as antiviral agents. Medical applications of endonucleases in human cancer therapy hold promise. The results of X-ray diffraction studies of the spatial organization of endonucleases and their complexes and the mechanism of their action are analyzed and generalized. An analysis of the structural studies of this class of enzymes showed that the specific binding of enzymes to nucleic acids is characterized bymore » interactions with nitrogen bases and the nucleotide backbone, whereas the nonspecific binding of enzymes is generally characterized by interactions only with the nucleic-acid backbone. It should be taken into account that the specificity can be modulated by metal ions and certain low-molecular-weight organic compounds. To test the hypotheses about specific and nonspecific nucleic-acid-binding proteins, it is necessary to perform additional studies of atomic-resolution three-dimensional structures of enzyme-nucleic-acid complexes by methods of structural biology.« less

Brands as Intentional Agents Framework: How Perceived Intentions and Ability Can Map Brand Perception.

PubMed

Kervyn, Nicolas; Fiske, Susan T; Malone, Chris

2012-04-01

Building on the Stereotype Content Model, this paper introduces and tests the Brands as Intentional Agents Framework. A growing body of research suggests that consumers have relationships with brands that resemble relations between people. We propose that consumers perceive brands in the same way they perceive people. This approach allows us to explore how social perception theories and processes can predict brand purchase interest and loyalty. Brands as Intentional Agents Framework is based on a well-established social perception approach: the Stereotype Content Model. Two studies support the Brands as Intentional Agents Framework prediction that consumers assess a brand's perceived intentions and ability and that these perceptions elicit distinct emotions and drive differential brand behaviors. The research shows that human social interaction relationships translate to consumer-brand interactions in ways that are useful to inform brand positioning and brand communications.

Brands as Intentional Agents Framework: How Perceived Intentions and Ability Can Map Brand Perception

PubMed Central

Kervyn, Nicolas; Fiske, Susan T.; Malone, Chris

2013-01-01

Building on the Stereotype Content Model, this paper introduces and tests the Brands as Intentional Agents Framework. A growing body of research suggests that consumers have relationships with brands that resemble relations between people. We propose that consumers perceive brands in the same way they perceive people. This approach allows us to explore how social perception theories and processes can predict brand purchase interest and loyalty. Brands as Intentional Agents Framework is based on a well-established social perception approach: the Stereotype Content Model. Two studies support the Brands as Intentional Agents Framework prediction that consumers assess a brand’s perceived intentions and ability and that these perceptions elicit distinct emotions and drive differential brand behaviors. The research shows that human social interaction relationships translate to consumer-brand interactions in ways that are useful to inform brand positioning and brand communications. PMID:24403815

The Effects of Humans and Topography on Wildland Fire, Forests, and Species Abundance

Treesearch

Richard P. Guyette; Daniel Dey

2004-01-01

Ignitions, fuels, topography, and climate interact through time to create temporal and spatial differences in the frequency of fire, which, in turn, affects ecosystem structure and function. In many ecosystems non-human ignitions are overwhelmed by anthropogenic ignitions. Human population density, culture, and topographic factors are quantitatively related to fire...

Economic reasoning and artificial intelligence.

PubMed

Parkes, David C; Wellman, Michael P

2015-07-17

The field of artificial intelligence (AI) strives to build rational agents capable of perceiving the world around them and taking actions to advance specified goals. Put another way, AI researchers aim to construct a synthetic homo economicus, the mythical perfectly rational agent of neoclassical economics. We review progress toward creating this new species of machine, machina economicus, and discuss some challenges in designing AIs that can reason effectively in economic contexts. Supposing that AI succeeds in this quest, or at least comes close enough that it is useful to think about AIs in rationalistic terms, we ask how to design the rules of interaction in multi-agent systems that come to represent an economy of AIs. Theories of normative design from economics may prove more relevant for artificial agents than human agents, with AIs that better respect idealized assumptions of rationality than people, interacting through novel rules and incentive systems quite distinct from those tailored for people. Copyright © 2015, American Association for the Advancement of Science.

A framework for learning and planning against switching strategies in repeated games

NASA Astrophysics Data System (ADS)

Hernandez-Leal, Pablo; Munoz de Cote, Enrique; Sucar, L. Enrique

2014-04-01

Intelligent agents, human or artificial, often change their behaviour as they interact with other agents. For an agent to optimise its performance when interacting with such agents, it must be capable of detecting and adapting according to such changes. This work presents an approach on how to effectively deal with non-stationary switching opponents in a repeated game context. Our main contribution is a framework for online learning and planning against opponents that switch strategies. We present how two opponent modelling techniques work within the framework and prove the usefulness of the approach experimentally in the iterated prisoner's dilemma, when the opponent is modelled as an agent that switches between different strategies (e.g. TFT, Pavlov and Bully). The results of both models were compared against each other and against a state-of-the-art non-stationary reinforcement learning technique. Results reflect that our approach obtains competitive results without needing an offline training phase, as opposed to the state-of-the-art techniques.

A Multi-Level Approach to Modeling Rapidly Growing Mega-Regions as a Coupled Human-Natural System

NASA Astrophysics Data System (ADS)

Koch, J. A.; Tang, W.; Meentemeyer, R. K.

2013-12-01

The FUTure Urban-Regional Environment Simulation (FUTURES) integrates information on nonstationary drivers of land change (per capita land area demand, site suitability, and spatial structure of conversion events) into spatial-temporal projections of changes in landscape patterns (Meentemeyer et al., 2013). One striking feature of FUTURES is its patch-growth algorithm that includes feedback effects of former development events across several temporal and spatial scales: cell-level transition events are aggregated into patches of land change and their further growth is based on empirically derived parameters controlling its size, shape, and dispersion. Here, we augment the FUTURES modeling framework by expanding its multilevel structure and its representation of human decision making. The new modeling framework is hierarchically organized as nested subsystems including the latest theory on telecouplings in coupled human-natural systems (Liu et al., 2013). Each subsystem represents a specific level of spatial scale and embraces agents that have decision making authority at a particular level. The subsystems are characterized with regard to their spatial representation and are connected via flows of information (e.g. regulations and policies) or material (e.g. population migration). To provide a modeling framework that is applicable to a wide range of settings and geographical regions and to keep it computationally manageable, we implement a 'zooming factor' that allows to enable or disable subsystems (and hence the represented processes), based on the extent of the study region. The implementation of the FUTURES modeling framework for a specific case study follows the observational modeling approach described in Grimm et al. (2005), starting from the analysis of empirical data in order to capture the processes relevant for specific scales and to allow a rigorous calibration and validation of the model application. In this paper, we give an introduction to the basic concept of our modeling approach and describe its strengths and weaknesses. We furthermore use empirical data for the states of North and South Carolina to demonstrate how the modeling framework can be applied to a large, heterogeneous study system with diverse decision-making agents. Grimm et al. (2005) Pattern-Oriented Modeling of Agent-Based Complex Systems: Lessons from Ecology. Science 310, 987-991. Liu et al. (2013) Framing Sustainability in a Telecoupled World. Ecology and Society 18(2), 26. Meentemeyer et al. (2013) FUTURES: Multilevel Simulations of Merging Urban-Rural Landscape Structure Using a Stochastic Patch-Growing Algorithm. Annals of the Association of American Geographers 103(4), 785-807.

Agent Based Modeling: Fine-Scale Spatio-Temporal Analysis of Pertussis

NASA Astrophysics Data System (ADS)

Mills, D. A.

2017-10-01

In epidemiology, spatial and temporal variables are used to compute vaccination efficacy and effectiveness. The chosen resolution and scale of a spatial or spatio-temporal analysis will affect the results. When calculating vaccination efficacy, for example, a simple environment that offers various ideal outcomes is often modeled using coarse scale data aggregated on an annual basis. In contrast to the inadequacy of this aggregated method, this research uses agent based modeling of fine-scale neighborhood data centered around the interactions of infants in daycare and their families to demonstrate an accurate reflection of vaccination capabilities. Despite being able to prevent major symptoms, recent studies suggest that acellular Pertussis does not prevent the colonization and transmission of Bordetella Pertussis bacteria. After vaccination, a treated individual becomes a potential asymptomatic carrier of the Pertussis bacteria, rather than an immune individual. Agent based modeling enables the measurable depiction of asymptomatic carriers that are otherwise unaccounted for when calculating vaccination efficacy and effectiveness. Using empirical data from a Florida Pertussis outbreak case study, the results of this model demonstrate that asymptomatic carriers bias the calculated vaccination efficacy and reveal a need for reconsidering current methods that are widely used for calculating vaccination efficacy and effectiveness.

DOE Office of Scientific and Technical Information (OSTI.GOV)

LaHann, T.

ISU`s Center for Toxicology Research has been conducting toxicity testing of borocaptate sodium (BSH) to aid in assessing if proposed human studies of BSH are likely to be acceptably safe. This report describes BSH interactions with other biological agents.

Animated Agents Teaching Helping Skills in an Online Environment: A Pilot Study

ERIC Educational Resources Information Center

Duggan, Molly H.; Adcock, Amy B.

2007-01-01

Human service educators constantly struggle with how to best teach students the communication skills required of entry-level human service professionals. While teaching such skills is easier in a traditional face-to-face environment, teaching communication skills via distance learning presents its own challenges. Developing interactive web-based…

Natural Speech Toward Humans and Intelligent Agents During a Simulated Search and Rescue Mission

DTIC Science & Technology

2008-12-01

Eklundh, 2006). Research has been done on giving directions to robots, and the point of view that teammates normally attribute to them (Imai, Hiraki ...Bystander intervention as a resource in human-robot collaboration. Interaction Studies, 7(3), 455-477. Imai, M., Hiraki , K., Miyasato, T., Nakatsu, R

Devious Chatbots - Interactive Malware with a Plot

NASA Astrophysics Data System (ADS)

Jonathan, Pan Juin Yang; Fung, Chun Che; Wong, Kok Wai

Many social robots in the forms of conversation agents or Chatbots have been put to practical use in recent years. Their typical roles are online help or acting as a cyber agent representing an organisation. However, there exists a new form of devious chatbots lurking in the Internet. It is effectively an interactive malware seeking to lure its prey not through vicious assault, but with seductive conversation. It talks to its prey through the same channel that is normally used for human-to-human communication. These devious chatbots are using social engineering to attack the uninformed and unprepared victims. This type of attacks is becoming more pervasive with the advent of Web 2.0. This survey paper presents results from a research on how this breed of devious Malware is spreading, and what could be done to stop it.

Spatial interactions reveal inhibitory cortical networks in human amblyopia.

PubMed

Wong, Erwin H; Levi, Dennis M; McGraw, Paul V

2005-10-01

Humans with amblyopia have a well-documented loss of sensitivity for first-order, or luminance defined, visual information. Recent studies show that they also display a specific loss of sensitivity for second-order, or contrast defined, visual information; a type of image structure encoded by neurons found predominantly in visual area A18/V2. In the present study, we investigate whether amblyopia disrupts the normal architecture of spatial interactions in V2 by determining the contrast detection threshold of a second-order target in the presence of second-order flanking stimuli. Adjacent flanks facilitated second-order detectability in normal observers. However, in marked contrast, they suppressed detection in each eye of the majority of amblyopic observers. Furthermore, strabismic observers with no loss of visual acuity show a similar pattern of detection suppression. We speculate that amblyopia results in predominantly inhibitory cortical interactions between second-order neurons.

Vector-based navigation using grid-like representations in artificial agents.

PubMed

Banino, Andrea; Barry, Caswell; Uria, Benigno; Blundell, Charles; Lillicrap, Timothy; Mirowski, Piotr; Pritzel, Alexander; Chadwick, Martin J; Degris, Thomas; Modayil, Joseph; Wayne, Greg; Soyer, Hubert; Viola, Fabio; Zhang, Brian; Goroshin, Ross; Rabinowitz, Neil; Pascanu, Razvan; Beattie, Charlie; Petersen, Stig; Sadik, Amir; Gaffney, Stephen; King, Helen; Kavukcuoglu, Koray; Hassabis, Demis; Hadsell, Raia; Kumaran, Dharshan

2018-05-01

Deep neural networks have achieved impressive successes in fields ranging from object recognition to complex games such as Go 1,2 . Navigation, however, remains a substantial challenge for artificial agents, with deep neural networks trained by reinforcement learning 3-5 failing to rival the proficiency of mammalian spatial behaviour, which is underpinned by grid cells in the entorhinal cortex 6 . Grid cells are thought to provide a multi-scale periodic representation that functions as a metric for coding space 7,8 and is critical for integrating self-motion (path integration) 6,7,9 and planning direct trajectories to goals (vector-based navigation) 7,10,11 . Here we set out to leverage the computational functions of grid cells to develop a deep reinforcement learning agent with mammal-like navigational abilities. We first trained a recurrent network to perform path integration, leading to the emergence of representations resembling grid cells, as well as other entorhinal cell types 12 . We then showed that this representation provided an effective basis for an agent to locate goals in challenging, unfamiliar, and changeable environments-optimizing the primary objective of navigation through deep reinforcement learning. The performance of agents endowed with grid-like representations surpassed that of an expert human and comparison agents, with the metric quantities necessary for vector-based navigation derived from grid-like units within the network. Furthermore, grid-like representations enabled agents to conduct shortcut behaviours reminiscent of those performed by mammals. Our findings show that emergent grid-like representations furnish agents with a Euclidean spatial metric and associated vector operations, providing a foundation for proficient navigation. As such, our results support neuroscientific theories that see grid cells as critical for vector-based navigation 7,10,11 , demonstrating that the latter can be combined with path-based strategies to support navigation in challenging environments.

Interactions of landscape disturbances and climate change dictate ecological pattern and process: spatial modeling of wildfire, insect, and disease dynamics under future climates

Treesearch

Rachel A. Loehman; Robert E. Keane; Lisa M. Holsinger; Zhiwei Wu

2017-01-01

Context: Interactions among disturbances, climate, and vegetation influence landscape patterns and ecosystem processes. Climate changes, exotic invasions, beetle outbreaks, altered fire regimes, and human activities may interact to produce landscapes that appear and function beyond historical analogs. Objectives We used the mechanistic...

Augmenting team cognition in human-automation teams performing in complex operational environments.

PubMed

Cuevas, Haydee M; Fiore, Stephen M; Caldwell, Barrett S; Strater, Laura

2007-05-01

There is a growing reliance on automation (e.g., intelligent agents, semi-autonomous robotic systems) to effectively execute increasingly cognitively complex tasks. Successful team performance for such tasks has become even more dependent on team cognition, addressing both human-human and human-automation teams. Team cognition can be viewed as the binding mechanism that produces coordinated behavior within experienced teams, emerging from the interplay between each team member's individual cognition and team process behaviors (e.g., coordination, communication). In order to better understand team cognition in human-automation teams, team performance models need to address issues surrounding the effect of human-agent and human-robot interaction on critical team processes such as coordination and communication. Toward this end, we present a preliminary theoretical framework illustrating how the design and implementation of automation technology may influence team cognition and team coordination in complex operational environments. Integrating constructs from organizational and cognitive science, our proposed framework outlines how information exchange and updating between humans and automation technology may affect lower-level (e.g., working memory) and higher-level (e.g., sense making) cognitive processes as well as teams' higher-order "metacognitive" processes (e.g., performance monitoring). Issues surrounding human-automation interaction are discussed and implications are presented within the context of designing automation technology to improve task performance in human-automation teams.

Younger and Older Users’ Recognition of Virtual Agent Facial Expressions

PubMed Central

Beer, Jenay M.; Smarr, Cory-Ann; Fisk, Arthur D.; Rogers, Wendy A.

2015-01-01

As technology advances, robots and virtual agents will be introduced into the home and healthcare settings to assist individuals, both young and old, with everyday living tasks. Understanding how users recognize an agent’s social cues is therefore imperative, especially in social interactions. Facial expression, in particular, is one of the most common non-verbal cues used to display and communicate emotion in on-screen agents (Cassell, Sullivan, Prevost, & Churchill, 2000). Age is important to consider because age-related differences in emotion recognition of human facial expression have been supported (Ruffman et al., 2008), with older adults showing a deficit for recognition of negative facial expressions. Previous work has shown that younger adults can effectively recognize facial emotions displayed by agents (Bartneck & Reichenbach, 2005; Courgeon et al. 2009; 2011; Breazeal, 2003); however, little research has compared in-depth younger and older adults’ ability to label a virtual agent’s facial emotions, an import consideration because social agents will be required to interact with users of varying ages. If such age-related differences exist for recognition of virtual agent facial expressions, we aim to understand if those age-related differences are influenced by the intensity of the emotion, dynamic formation of emotion (i.e., a neutral expression developing into an expression of emotion through motion), or the type of virtual character differing by human-likeness. Study 1 investigated the relationship between age-related differences, the implication of dynamic formation of emotion, and the role of emotion intensity in emotion recognition of the facial expressions of a virtual agent (iCat). Study 2 examined age-related differences in recognition expressed by three types of virtual characters differing by human-likeness (non-humanoid iCat, synthetic human, and human). Study 2 also investigated the role of configural and featural processing as a possible explanation for age-related differences in emotion recognition. First, our findings show age-related differences in the recognition of emotions expressed by a virtual agent, with older adults showing lower recognition for the emotions of anger, disgust, fear, happiness, sadness, and neutral. These age-related difference might be explained by older adults having difficulty discriminating similarity in configural arrangement of facial features for certain emotions; for example, older adults often mislabeled the similar emotions of fear as surprise. Second, our results did not provide evidence for the dynamic formation improving emotion recognition; but, in general, the intensity of the emotion improved recognition. Lastly, we learned that emotion recognition, for older and younger adults, differed by character type, from best to worst: human, synthetic human, and then iCat. Our findings provide guidance for design, as well as the development of a framework of age-related differences in emotion recognition. PMID:25705105

Macroecological factors shape local-scale spatial patterns in agriculturalist settlements.

PubMed

Tao, Tingting; Abades, Sebastián; Teng, Shuqing; Huang, Zheng Y X; Reino, Luís; Chen, Bin J W; Zhang, Yong; Xu, Chi; Svenning, Jens-Christian

2017-11-15

Macro-scale patterns of human systems ranging from population distribution to linguistic diversity have attracted recent attention, giving rise to the suggestion that macroecological rules shape the assembly of human societies. However, in which aspects the geography of our own species is shaped by macroecological factors remains poorly understood. Here, we provide a first demonstration that macroecological factors shape strong local-scale spatial patterns in human settlement systems, through an analysis of spatial patterns in agriculturalist settlements in eastern mainland China based on high-resolution Google Earth images. We used spatial point pattern analysis to show that settlement spatial patterns are characterized by over-dispersion at fine spatial scales (0.05-1.4 km), consistent with territory segregation, and clumping at coarser spatial scales beyond the over-dispersion signals, indicating territorial clustering. Statistical modelling shows that, at macroscales, potential evapotranspiration and topographic heterogeneity have negative effects on territory size, but positive effects on territorial clustering. These relationships are in line with predictions from territory theory for hunter-gatherers as well as for many animal species. Our results help to disentangle the complex interactions between intrinsic spatial processes in agriculturalist societies and external forcing by macroecological factors. While one may speculate that humans can escape ecological constraints because of unique abilities for environmental modification and globalized resource transportation, our work highlights that universal macroecological principles still shape the geography of current human agricultural societies. © 2017 The Author(s).

Out of the net: An agent-based model to study human movements influence on local-scale malaria transmission.

PubMed

Pizzitutti, Francesco; Pan, William; Feingold, Beth; Zaitchik, Ben; Álvarez, Carlos A; Mena, Carlos F

2018-01-01

Though malaria control initiatives have markedly reduced malaria prevalence in recent decades, global eradication is far from actuality. Recent studies show that environmental and social heterogeneities in low-transmission settings have an increased weight in shaping malaria micro-epidemiology. New integrated and more localized control strategies should be developed and tested. Here we present a set of agent-based models designed to study the influence of local scale human movements on local scale malaria transmission in a typical Amazon environment, where malaria is transmission is low and strongly connected with seasonal riverine flooding. The agent-based simulations show that the overall malaria incidence is essentially not influenced by local scale human movements. In contrast, the locations of malaria high risk spatial hotspots heavily depend on human movements because simulated malaria hotspots are mainly centered on farms, were laborers work during the day. The agent-based models are then used to test the effectiveness of two different malaria control strategies both designed to reduce local scale malaria incidence by targeting hotspots. The first control scenario consists in treat against mosquito bites people that, during the simulation, enter at least once inside hotspots revealed considering the actual sites where human individuals were infected. The second scenario involves the treatment of people entering in hotspots calculated assuming that the infection sites of every infected individual is located in the household where the individual lives. Simulations show that both considered scenarios perform better in controlling malaria than a randomized treatment, although targeting household hotspots shows slightly better performance.

Using Motivational Interviewing to reduce threats in conversations about environmental behavior.

PubMed

Klonek, Florian E; Güntner, Amelie V; Lehmann-Willenbrock, Nale; Kauffeld, Simone

2015-01-01

Human behavior contributes to a waste of environmental resources and our society is looking for ways to reduce this problem. However, humans may perceive feedback about their environmental behavior as threatening. According to self-determination theory (SDT), threats decrease intrinsic motivation for behavior change. According to self-affirmation theory (SAT), threats can harm individuals' self-integrity. Therefore, individuals should show self-defensive biases, e.g., in terms of presenting counter-arguments when presented with environmental behavior change. The current study examines how change recipients respond to threats from change agents in interactions about environmental behavior change. Moreover, we investigate how Motivational Interviewing (MI) - an intervention aimed at increasing intrinsic motivation - can reduce threats at both the social and cognitive level. We videotaped 68 dyadic interactions with change agents who either did or did not use MI (control group). We coded agents verbal threats and recipients' verbal expressions of motivation. Recipients also rated agents' level of confrontation and empathy (i.e., cognitive reactions). As hypothesized, threats were significantly lower when change agents used MI. Perceived confrontations converged with observable social behavior of change agents in both groups. Moreover, behavioral threats showed a negative association with change recipients' expressed motivation (i.e., reasons to change). Contrary to our expectations, we found no relation between change agents' verbal threats and change recipients' verbally expressed self-defenses (i.e., sustain talk). Our results imply that MI reduces the adverse impact of threats in conversations about environmental behavior change on both the social and cognitive level. We discuss theoretical implications of our study in the context of SAT and SDT and suggest practical implications for environmental change agents in organizations.

Sensitivity to synchronicity of biological motion in normal and amblyopic vision

PubMed Central

Luu, Jennifer Y.; Levi, Dennis M.

2017-01-01

Amblyopia is a developmental disorder of spatial vision that results from abnormal early visual experience usually due to the presence of strabismus, anisometropia, or both strabismus and anisometropia. Amblyopia results in a range of visual deficits that cannot be corrected by optics because the deficits reflect neural abnormalities. Biological motion refers to the motion patterns of living organisms, and is normally displayed as points of lights positioned at the major joints of the body. In this experiment, our goal was twofold. We wished to examine whether the human visual system in people with amblyopia retained the higher-level processing capabilities to extract visual information from the synchronized actions of others, therefore retaining the ability to detect biological motion. Specifically, we wanted to determine if the synchronized interaction of two agents performing a dancing routine allowed the amblyopic observer to use the actions of one agent to predict the expected actions of a second agent. We also wished to establish whether synchronicity sensitivity (detection of synchronized versus desynchronized interactions) is impaired in amblyopic observers relative to normal observers. The two aims are differentiated in that the first aim looks at whether synchronized actions result in improved expected action predictions while the second aim quantitatively compares synchronicity sensitivity, or the ratio of desynchronized to synchronized detection sensitivities, to determine if there is a difference between normal and amblyopic observers. Our results show that the ability to detect biological motion requires more samples in both eyes of amblyopes than in normal control observers. The increased sample threshold is not the result of low-level losses but may reflect losses in feature integration due to undersampling in the amblyopic visual system. However, like normal observers, amblyopes are more sensitive to synchronized versus desynchronized interactions, indicating that higher-level processing of biological motion remains intact. We also found no impairment in synchronicity sensitivity in the amblyopic visual system relative to the normal visual system. Since there is no impairment in synchronicity sensitivity in either the nonamblyopic or amblyopic eye of amblyopes, our results suggest that the higher order processing of biological motion is intact. PMID:23474301

Human-specific features of spatial gene expression and regulation in eight brain regions.

PubMed

Xu, Chuan; Li, Qian; Efimova, Olga; He, Liu; Tatsumoto, Shoji; Stepanova, Vita; Oishi, Takao; Udono, Toshifumi; Yamaguchi, Katsushi; Shigenobu, Shuji; Kakita, Akiyoshi; Nawa, Hiroyuki; Khaitovich, Philipp; Go, Yasuhiro

2018-06-13

Molecular maps of the human brain alone do not inform us of the features unique to humans. Yet, the identification of these features is important for understanding both the evolution and nature of human cognition. Here, we approached this question by analyzing gene expression and H3K27ac chromatin modification data collected in eight brain regions of humans, chimpanzees, gorillas, a gibbon and macaques. An analysis of spatial transcriptome trajectories across eight brain regions in four primate species revealed 1,851 genes showing human-specific transcriptome differences in one or multiple brain regions, in contrast to 240 chimpanzee-specific ones. More than half of these human-specific differences represented elevated expression of genes enriched in neuronal and astrocytic markers in the human hippocampus, while the rest were enriched in microglial markers and displayed human-specific expression in several frontal cortical regions and the cerebellum. An analysis of the predicted regulatory interactions driving these differences revealed the role of transcription factors in species-specific transcriptome changes, while epigenetic modifications were linked to spatial expression differences conserved across species. Published by Cold Spring Harbor Laboratory Press.

Multiagent Work Practice Simulation: Progress and Challenges

NASA Technical Reports Server (NTRS)

Clancey, William J.; Sierhuis, Maarten; Shaffe, Michael G. (Technical Monitor)

2001-01-01

Modeling and simulating complex human-system interactions requires going beyond formal procedures and information flows to analyze how people interact with each other. Such work practices include conversations, modes of communication, informal assistance, impromptu meetings, workarounds, and so on. To make these social processes visible, we have developed a multiagent simulation tool, called Brahms, for modeling the activities of people belonging to multiple groups, situated in a physical environment (geographic regions, buildings, transport vehicles, etc.) consisting of tools, documents, and a computer system. We are finding many useful applications of Brahms for system requirements analysis, instruction, implementing software agents, and as a workbench for relating cognitive and social theories of human behavior. Many challenges remain for representing work practices, including modeling: memory over multiple days, scheduled activities combining physical objects, groups, and locations on a timeline (such as a Space Shuttle mission), habitat vehicles with trajectories (such as the Shuttle), agent movement in 3D space (e.g., inside the International Space Station), agent posture and line of sight, coupled movements (such as carrying objects), and learning (mimicry, forming habits, detecting repetition, etc.).

Multiagent Work Practice Simulation: Progress and Challenges

NASA Technical Reports Server (NTRS)

Clancey, William J.; Sierhuis, Maarten

2002-01-01

Modeling and simulating complex human-system interactions requires going beyond formal procedures and information flows to analyze how people interact with each other. Such work practices include conversations, modes of communication, informal assistance, impromptu meetings, workarounds, and so on. To make these social processes visible, we have developed a multiagent simulation tool, called Brahms, for modeling the activities of people belonging to multiple groups, situated in a physical environment (geographic regions, buildings, transport vehicles, etc.) consisting of tools, documents, and computer systems. We are finding many useful applications of Brahms for system requirements analysis, instruction, implementing software agents, and as a workbench for relating cognitive and social theories of human behavior. Many challenges remain for representing work practices, including modeling: memory over multiple days, scheduled activities combining physical objects, groups, and locations on a timeline (such as a Space Shuttle mission), habitat vehicles with trajectories (such as the Shuttle), agent movement in 3d space (e.g., inside the International Space Station), agent posture and line of sight, coupled movements (such as carrying objects), and learning (mimicry, forming habits, detecting repetition, etc.).

Integrating GIS and ABM to Explore Spatiotemporal Dynamics

NASA Astrophysics Data System (ADS)

Sun, M.; Jiang, Y.; Yang, C.

2013-12-01

Agent-based modeling as a methodology for the bottom-up exploration with the account of adaptive behavior and heterogeneity of system components can help discover the development and pattern of the complex social and environmental system. However, ABM is a computationally intensive process especially when the number of system components becomes large and the agent-agent/agent-environmental interaction is modeled very complex. Most of traditional ABM frameworks developed based on CPU do not have a satisfying computing capacity. To address the problem and as the emergence of advanced techniques, GPU computing with CUDA can provide powerful parallel structure to enable the complex simulation of spatiotemporal dynamics. In this study, we first develop a GPU-based ABM system. Secondly, in order to visualize the dynamics generated from the movement of agent and the change of agent/environmental attributes during the simulation, we integrate GIS into the ABM system. Advanced geovisualization technologies can be utilized for representing the spatiotemporal change events, such as proper 2D/3D maps with state-of-the-art symbols, space-time cube and multiple layers each of which presents pattern in one time-stamp, etc. Thirdly, visual analytics which include interactive tools (e.g. grouping, filtering, linking, etc.) is included in our ABM-GIS system to help users conduct real-time data exploration during the progress of simulation. Analysis like flow analysis and spatial cluster analysis can be integrated according to the geographical problem we want to explore.

Dogs (Canis familiaris) adjust their social behaviour to the differential role of inanimate interactive agents.

PubMed

Petró, Eszter; Abdai, Judit; Gergely, Anna; Topál, József; Miklósi, Ádám

2016-03-01

Dogs are able to flexibly adjust their social behaviour to situation-specific characteristics of their human partner's behaviour in problem situations. However, dogs do not necessarily detect the specific role played by the human in a particular situation: they may form expectations about their partners' behaviour based on previous experiences with them. Utilising inanimate objects (UMO-unidentified moving object) as interacting agents offers new possibilities for investigating social behaviour, because in this way we can remove or control the influence of previous experience with the partner. The aim of the present study was to investigate whether dogs are able to recognise the different roles of two UMOs and are able to adjust their communicative behaviour towards them. In the learning phase of the experiment, dogs were presented with a two-way food-retrieval problem in which two UMOs, which differed in their physical appearance and abilities, helped the dog obtain a piece of food in their own particular manner. After a short experience with both UMOs, dogs in the test phase faced one of the problems in the presence of both inanimate agents. Overall, dogs displayed similar levels of gazing behaviour towards the UMOs, but in the first test they looked, approached and touched the relevant partner first. This rapid adjustment of social behaviour towards UMOs suggests that dogs may generalise their experiences with humans to unfamiliar agents and are able to select the appropriate partner when facing a problem situation.

Quantifying multiple telecouplings using an integrated suite of spatially-explicit tools

NASA Astrophysics Data System (ADS)

Tonini, F.; Liu, J.

2016-12-01

Telecoupling is an interdisciplinary research umbrella concept that enables natural and social scientists to understand and generate information for managing how humans and nature can sustainably coexist worldwide. To systematically study telecoupling, it is essential to build a comprehensive set of spatially-explicit tools for describing and quantifying multiple reciprocal socioeconomic and environmental interactions between a focal area and other areas. Here we introduce the Telecoupling Toolbox, a new free and open-source set of tools developed to map and identify the five major interrelated components of the telecoupling framework: systems, flows, agents, causes, and effects. The modular design of the toolbox allows the integration of existing tools and software (e.g. InVEST) to assess synergies and tradeoffs associated with policies and other local to global interventions. We show applications of the toolbox using a number of representative studies that address a variety of scientific and management issues related to telecouplings throughout the world. The results suggest that the toolbox can thoroughly map and quantify multiple telecouplings under various contexts while providing users with an easy-to-use interface. It provides a powerful platform to address globally important issues, such as land use and land cover change, species invasion, migration, flows of ecosystem services, and international trade of goods and products.

Chemical Computer Man: Chemical Agent Response Simulation (CARS). Technical report, January 1983-September 1985

DOE Office of Scientific and Technical Information (OSTI.GOV)

Davis, E.G.; Mioduszewski, R.J.

The Chemical Computer Man: Chemical Agent Response Simulation (CARS) is a computer model and simulation program for estimating the dynamic changes in human physiological dysfunction resulting from exposures to chemical-threat nerve agents. The newly developed CARS methodology simulates agent exposure effects on the following five indices of human physiological function: mental, vision, cardio-respiratory, visceral, and limbs. Mathematical models and the application of basic pharmacokinetic principles were incorporated into the simulation so that for each chemical exposure, the relationship between exposure dosage, absorbed dosage (agent blood plasma concentration), and level of physiological response are computed as a function of time. CARS,more » as a simulation tool, is designed for the users with little or no computer-related experience. The model combines maximum flexibility with a comprehensive user-friendly interactive menu-driven system. Users define an exposure problem and obtain immediate results displayed in tabular, graphical, and image formats. CARS has broad scientific and engineering applications, not only in technology for the soldier in the area of Chemical Defense, but also in minimizing animal testing in biomedical and toxicological research and the development of a modeling system for human exposure to hazardous-waste chemicals.« less

Socio-Ecohydrologic Agents And Services: Integrating Human And Natural Components To Address Coupled System Resilience

NASA Astrophysics Data System (ADS)

Pavao-zuckerman, M.; Pope, A.; Chan, D.; Curl, K.; Gimblett, H. R.; Hough, M.; House-Peters, L.; Lee, R.; Scott, C. A.

2012-12-01

Riparian corridors in arid regions are highly valued for their relative scarcity, and because healthy riparian systems support high levels of biodiversity, can meet human demand for water and water-related resources and functions. Our team is taking a transdiciplinary social-ecological systems approach to assessing riparian corridor resilience in two watersheds (the San Pedro River in USA and Mexico, and the Rio San Miguel in Mexico) through a project funded by the NSF CNH program ("Strengthening Resilience of Arid Region Riparian Corridors"). Multiple perspectives are integrated in the project, including hydrology, ecology, institutional dynamics, and decision making (at the level of both policy and individual choice), as well as the perspectives of various stakeholder groups and individuals in the watersheds. Here we discuss initial findings that center around linking changes in ecohydrology and livelihoods related to decisions in response to climatic, ecological, and social change. The research team is implementing two approaches to integrate the disparate disciplines participating in the research (and the varied perspectives among the stakeholders in this binational riparian context): (1) ecosystem service assessment, and (2) agent based model simulation. We are developing an ecosystem service perspective that provides a bridge between ecological dynamics in the landscape and varied stakeholder perspectives on the implications of ecohydrology for well-being (economic, cultural, ecological). Services are linked on one hand to the spatial patterns of traits of individuals within species (allowing a more predictive application of ecosystem services as they vary with community change in time), and to stakeholder perspectives (facilitating integration of ecosystem services into our understanding of decision making processes) in a case study in the San Pedro River National Conservation Area. The agent- based model (ABM) approach incorporates the influence of human decision-making on spatially-explicit landscapes in a mechanistic way, taking into account social interaction, adaptation, and decision-making at different levels, allowing individual stakeholders to make decisions based on their unique perceptions of their environment, be it economic, social, or ecological awareness. Initial parameterization of the ABM proceeds from a case study centered in the town of Rayón, Sonora, Mexico, where semi-structured interviews were used to elicit perceptions by water resource users of CNH function, change, and solutions relating to livelihood changes in response to several drivers. In both case studies, we see the potential and limitations for an approach to adaptive management and decision support related to water resources that links ecosystem services and agent-based modeling. Methodologically, synthetic approaches such as these may allow coupling of systems for improved assessment and analysis, while at the same time lack a connection to the perspectives of water users and managers on the ground. There is thus potential for a either a loss of system resilience in the face of external change, or an opportunity to increase system resilience by building off perspectives already in place within these coupled socio-ecohydrologic systems.

Beliefs about human agency influence the neural processing of gaze during joint attention.

PubMed

Caruana, Nathan; de Lissa, Peter; McArthur, Genevieve

2017-04-01

The current study measured adults' P350 and N170 ERPs while they interacted with a character in a virtual reality paradigm. Some participants believed the character was controlled by a human ("avatar" condition, n = 19); others believed it was controlled by a computer program ("agent" condition, n = 19). In each trial, participants initiated joint attention in order to direct the character's gaze toward a target. In 50% of trials, the character gazed toward the target (congruent responses), and in 50% of trials the character gazed to a different location (incongruent response). In the avatar condition, the character's incongruent gaze responses generated significantly larger P350 peaks at centro-parietal sites than congruent gaze responses. In the agent condition, the P350 effect was strikingly absent. Left occipitotemporal N170 responses were significantly smaller in the agent condition compared to the avatar condition for both congruent and incongruent gaze shifts. These data suggest that beliefs about human agency may recruit mechanisms that discriminate the social outcome of a gaze shift after approximately 350 ms, and that these mechanisms may modulate the early perceptual processing of gaze. These findings also suggest that the ecologically valid measurement of social cognition may depend upon paradigms that simulate genuine social interactions.

A Human-Robot Co-Manipulation Approach Based on Human Sensorimotor Information.

PubMed

Peternel, Luka; Tsagarakis, Nikos; Ajoudani, Arash

2017-07-01

This paper aims to improve the interaction and coordination between the human and the robot in cooperative execution of complex, powerful, and dynamic tasks. We propose a novel approach that integrates online information about the human motor function and manipulability properties into the hybrid controller of the assistive robot. Through this human-in-the-loop framework, the robot can adapt to the human motor behavior and provide the appropriate assistive response in different phases of the cooperative task. We experimentally evaluate the proposed approach in two human-robot co-manipulation tasks that require specific complementary behavior from the two agents. Results suggest that the proposed technique, which relies on a minimum degree of task-level pre-programming, can achieve an enhanced physical human-robot interaction performance and deliver appropriate level of assistance to the human operator.

Learn good from bad: Effects of good and bad neighbors in spatial prisoners' dilemma games

NASA Astrophysics Data System (ADS)

Lu, Peng

2015-10-01

Cooperation is vital for the human society and this study focuses on how to promote cooperation. In our stratification model, there exist three classes: two minorities are elites who are prone to cooperate and scoundrels who are born to defect; one majority is the class of common people. Agents of these three classes interact with each other on a square lattice. Commons' cooperation and its factors are investigated. Contradicting our common sense, it indicates that elites play a negative role while scoundrels play a positive one in promoting commons' cooperation. Besides, effects of good and bad neighbors vary with temptation. When the temptation is smaller the positive effect is able to overcome the negative effect, but the later prevails when the temptation is larger. It concludes that common people are more prone to cooperate in harsh environment with bad neighbors, and a better environment with good neighbors merely leads to laziness and free riding of commons.

Incorporating human-water dynamics in a hyper-resolution land surface model

NASA Astrophysics Data System (ADS)

Vergopolan, N.; Chaney, N.; Wanders, N.; Sheffield, J.; Wood, E. F.

2017-12-01

The increasing demand for water, energy, and food is leading to unsustainable groundwater and surface water exploitation. As a result, the human interactions with the environment, through alteration of land and water resources dynamics, need to be reflected in hydrologic and land surface models (LSMs). Advancements in representing human-water dynamics still leave challenges related to the lack of water use data, water allocation algorithms, and modeling scales. This leads to an over-simplistic representation of human water use in large-scale models; this is in turn leads to an inability to capture extreme events signatures and to provide reliable information at stakeholder-level spatial scales. The emergence of hyper-resolution models allows one to address these challenges by simulating the hydrological processes and interactions with the human impacts at field scales. We integrated human-water dynamics into HydroBlocks - a hyper-resolution, field-scale resolving LSM. HydroBlocks explicitly solves the field-scale spatial heterogeneity of land surface processes through interacting hydrologic response units (HRUs); and its HRU-based model parallelization allows computationally efficient long-term simulations as well as ensemble predictions. The implemented human-water dynamics include groundwater and surface water abstraction to meet agricultural, domestic and industrial water demands. Furthermore, a supply-demand water allocation scheme based on relative costs helps to determine sectoral water use requirements and tradeoffs. A set of HydroBlocks simulations over the Midwest United States (daily, at 30-m spatial resolution for 30 years) are used to quantify the irrigation impacts on water availability. The model captures large reductions in total soil moisture and water table levels, as well as spatiotemporal changes in evapotranspiration and runoff peaks, with their intensity related to the adopted water management strategy. By incorporating human-water dynamics in a hyper-resolution LSM this work allows for progress on hydrological monitoring and predictions, as well as drought preparedness and water impact assessments at relevant decision-making scales.

Novel Burkholderia mallei Virulence Factors Linked to Specific Host-Pathogen Protein Interactions

DTIC Science & Technology

2013-06-23

Wallqvist‡ Burkholderia mallei is an infectious intracellular pathogen whose virulence and resistance to antibiotics makes it a potential bioterrorism agent ...experimental Burkholderia data to ini- tially select a small number of proteins as putative viru- lence factors. We then used yeast two-hybrid assays...causative agent of glan- ders, a disease primarily affecting horses but transmittable to humans; and Burkholderia pseudomallei, which is responsible for

[Formation of endogenous pyrogen by mononuclear phagocytes].

PubMed

Agasarov, L G; Sorokin, A V; Ukhanova, I K

1984-07-01

Production of endogenous pyrogen by human and rabbit blood monocytes in response to stimulation with agents of different origin was studied by inhibitory analysis under comparable conditions. Actinomycin D and cytochalasin B were applied. New evidence was obtained about an important role in the mechanism of activation of mononuclear phagocytes of initial interaction between a stimulating agent and the leukocyte membrane and of the biphasic process of endogenous pyrogen production.

Improving Agent Based Models and Validation through Data Fusion

PubMed Central

Laskowski, Marek; Demianyk, Bryan C.P.; Friesen, Marcia R.; McLeod, Robert D.; Mukhi, Shamir N.

2011-01-01

This work is contextualized in research in modeling and simulation of infection spread within a community or population, with the objective to provide a public health and policy tool in assessing the dynamics of infection spread and the qualitative impacts of public health interventions. This work uses the integration of real data sources into an Agent Based Model (ABM) to simulate respiratory infection spread within a small municipality. Novelty is derived in that the data sources are not necessarily obvious within ABM infection spread models. The ABM is a spatial-temporal model inclusive of behavioral and interaction patterns between individual agents on a real topography. The agent behaviours (movements and interactions) are fed by census / demographic data, integrated with real data from a telecommunication service provider (cellular records) and person-person contact data obtained via a custom 3G Smartphone application that logs Bluetooth connectivity between devices. Each source provides data of varying type and granularity, thereby enhancing the robustness of the model. The work demonstrates opportunities in data mining and fusion that can be used by policy and decision makers. The data become real-world inputs into individual SIR disease spread models and variants, thereby building credible and non-intrusive models to qualitatively simulate and assess public health interventions at the population level. PMID:23569606

Improving Agent Based Models and Validation through Data Fusion.

PubMed

Laskowski, Marek; Demianyk, Bryan C P; Friesen, Marcia R; McLeod, Robert D; Mukhi, Shamir N

2011-01-01

This work is contextualized in research in modeling and simulation of infection spread within a community or population, with the objective to provide a public health and policy tool in assessing the dynamics of infection spread and the qualitative impacts of public health interventions. This work uses the integration of real data sources into an Agent Based Model (ABM) to simulate respiratory infection spread within a small municipality. Novelty is derived in that the data sources are not necessarily obvious within ABM infection spread models. The ABM is a spatial-temporal model inclusive of behavioral and interaction patterns between individual agents on a real topography. The agent behaviours (movements and interactions) are fed by census / demographic data, integrated with real data from a telecommunication service provider (cellular records) and person-person contact data obtained via a custom 3G Smartphone application that logs Bluetooth connectivity between devices. Each source provides data of varying type and granularity, thereby enhancing the robustness of the model. The work demonstrates opportunities in data mining and fusion that can be used by policy and decision makers. The data become real-world inputs into individual SIR disease spread models and variants, thereby building credible and non-intrusive models to qualitatively simulate and assess public health interventions at the population level.

Lipopolysaccharides of Rhizobium etli strain G12 act in potato roots as an inducing agent of systemic resistance to infection by the cyst nematode Globodera pallida.

PubMed

Reitz, M; Rudolph, K; Schröder, I; Hoffmann-Hergarten, S; Hallmann, J; Sikora, R A

2000-08-01

Recent studies have shown that living and heat-killed cells of the rhizobacterium Rhizobium etli strain G12 induce in potato roots systemic resistance to infection by the potato cyst nematode Globodera pallida. To better understand the mechanisms of induced resistance, we focused on identifying the inducing agent. Since heat-stable bacterial surface carbohydrates such as exopolysaccharides (EPS) and lipopolysaccharides (LPS) are essential for recognition in the symbiotic interaction between Rhizobium and legumes, their role in the R. etli-potato interaction was studied. EPS and LPS were extracted from bacterial cultures, applied to potato roots, and tested for activity as an inducer of plant resistance to the plant-parasitic nematode. Whereas EPS did not affect G. pallida infection, LPS reduced nematode infection significantly in concentrations as low as 1 and 0.1 mg ml(-1). Split-root experiments, guaranteeing a spatial separation of inducing agent and challenging pathogen, showed that soil treatments of one half of the root system with LPS resulted in a highly significant (up to 37%) systemic induced reduction of G. pallida infection of potato roots in the other half. The results clearly showed that LPS of R. etli G12 act as the inducing agent of systemic resistance in potato roots.

Mutual and asynchronous anticipation and action in sports as globally competitive and locally coordinative dynamics

PubMed Central

Fujii, Keisuke; Isaka, Tadao; Kouzaki, Motoki; Yamamoto, Yuji

2015-01-01

Humans interact by changing their actions, perceiving other’s actions and executing solutions in conflicting situations. Using oscillator models, nonlinear dynamics have been considered for describing these complex human movements as an emergence of self-organisation. However, these frameworks cannot explain the hierarchical structures of complex behaviours between conflicting inter-agent and adapting intra-agent systems, especially in sport competitions wherein mutually quick decision making and execution are required. Here we adopt a hybrid multiscale approach to model an attack-and-defend game during which both players predict the opponent’s movement and move with a delay. From both simulated and measured data, one synchronous outcome between two-agent (i.e. successful defence) can be described as one attractor. In contrast, the other coordination-breaking outcome (i.e. successful attack) cannot be explained using gradient dynamics because the asymmetric interaction cannot always assume a conserved physical quantity. Instead, we provide the asymmetric and asynchronous hierarchical dynamical models to discuss two-agent competition. Our framework suggests that possessing information about an opponent and oneself in local-coordinative and global-competitive scale enables us to gain a deeper understanding of sports competitions. We anticipate developments in the scientific fields of complex movement adapting to such uncontrolled environments. PMID:26538452

Mutual and asynchronous anticipation and action in sports as globally competitive and locally coordinative dynamics

NASA Astrophysics Data System (ADS)

Fujii, Keisuke; Isaka, Tadao; Kouzaki, Motoki; Yamamoto, Yuji

2015-11-01

Humans interact by changing their actions, perceiving other’s actions and executing solutions in conflicting situations. Using oscillator models, nonlinear dynamics have been considered for describing these complex human movements as an emergence of self-organisation. However, these frameworks cannot explain the hierarchical structures of complex behaviours between conflicting inter-agent and adapting intra-agent systems, especially in sport competitions wherein mutually quick decision making and execution are required. Here we adopt a hybrid multiscale approach to model an attack-and-defend game during which both players predict the opponent’s movement and move with a delay. From both simulated and measured data, one synchronous outcome between two-agent (i.e. successful defence) can be described as one attractor. In contrast, the other coordination-breaking outcome (i.e. successful attack) cannot be explained using gradient dynamics because the asymmetric interaction cannot always assume a conserved physical quantity. Instead, we provide the asymmetric and asynchronous hierarchical dynamical models to discuss two-agent competition. Our framework suggests that possessing information about an opponent and oneself in local-coordinative and global-competitive scale enables us to gain a deeper understanding of sports competitions. We anticipate developments in the scientific fields of complex movement adapting to such uncontrolled environments.

Compartmental and Spatial Rule-Based Modeling with Virtual Cell.

PubMed

Blinov, Michael L; Schaff, James C; Vasilescu, Dan; Moraru, Ion I; Bloom, Judy E; Loew, Leslie M

2017-10-03

In rule-based modeling, molecular interactions are systematically specified in the form of reaction rules that serve as generators of reactions. This provides a way to account for all the potential molecular complexes and interactions among multivalent or multistate molecules. Recently, we introduced rule-based modeling into the Virtual Cell (VCell) modeling framework, permitting graphical specification of rules and merger of networks generated automatically (using the BioNetGen modeling engine) with hand-specified reaction networks. VCell provides a number of ordinary differential equation and stochastic numerical solvers for single-compartment simulations of the kinetic systems derived from these networks, and agent-based network-free simulation of the rules. In this work, compartmental and spatial modeling of rule-based models has been implemented within VCell. To enable rule-based deterministic and stochastic spatial simulations and network-free agent-based compartmental simulations, the BioNetGen and NFSim engines were each modified to support compartments. In the new rule-based formalism, every reactant and product pattern and every reaction rule are assigned locations. We also introduce the rule-based concept of molecular anchors. This assures that any species that has a molecule anchored to a predefined compartment will remain in this compartment. Importantly, in addition to formulation of compartmental models, this now permits VCell users to seamlessly connect reaction networks derived from rules to explicit geometries to automatically generate a system of reaction-diffusion equations. These may then be simulated using either the VCell partial differential equations deterministic solvers or the Smoldyn stochastic simulator. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

A Dynamic Dialog System Using Semantic Web Technologies

ERIC Educational Resources Information Center

Ababneh, Mohammad

2014-01-01

A dialog system or a conversational agent provides a means for a human to interact with a computer system. Dialog systems use text, voice and other means to carry out conversations with humans in order to achieve some objective. Most dialog systems are created with specific objectives in mind and consist of preprogrammed conversations. The primary…

The photo-colorimetric space as a medium for the representation of spatial data

NASA Technical Reports Server (NTRS)

Kraiss, K. Friedrich; Widdel, Heino

1989-01-01

Spatial displays and instruments are usually used in the context of vehicle guidance, but it is hard to find applicable spatial formats in information retrieval and interaction systems. Human interaction with spatial data structures and the applicability of the CIE color space to improve dialogue transparency is discussed. A proposal is made to use the color space to code spatially represented data. The semantic distances of the categories of dialogue structures or, more general, of database structures, are determined empirically. Subsequently the distances are transformed and depicted into the color space. The concept is demonstrated for a car diagnosis system, where the category cooling system could, e.g., be coded in blue, the category ignition system in red. Hereby a correspondence between color and semantic distances is achieved. Subcategories can be coded as luminance differences within the color space.

Roles for Agent Assistants in Field Science: Understanding Personal Projects and Collaboration

NASA Technical Reports Server (NTRS)

Clancey, William J.

2003-01-01

A human-centered approach to computer systems design involves reframing analysis in terms of the people interacting with each other. The primary concern is not how people can interact with computers, but how shall we design work systems (facilities, tools, roles, and procedures) to help people pursue their personal projects, as they work independently and collaboratively? Two case studies provide empirical requirements. First, an analysis of astronaut interactions with CapCom on Earth during one traverse of Apollo 17 shows what kind of information was conveyed and what might be automated today. A variety of agent and robotic technologies are proposed that deal with recurrent problems in communication and coordination during the analyzed traverse. Second, an analysis of biologists and a geologist working at Haughton Crater in the High Canadian Arctic reveals how work interactions between people involve independent personal projects, sensitively coordinated for mutual benefit. In both cases, an agent or robotic system's role would be to assist people, rather than collaborating, because today's computer systems lack the identity and purpose that consciousness provides.

Strategies of offspring investment and dispersal in a spatially structured environment: a theoretical study using ants.

PubMed

Cronin, Adam L; Loeuille, Nicolas; Monnin, Thibaud

2016-02-05

Offspring investment strategies vary markedly between and within taxa, and much of this variation is thought to stem from the trade-off between offspring size and number. While producing larger offspring can increase their competitive ability, this often comes at a cost to their colonization ability. This competition-colonization trade-off (CCTO) is thought to be an important mechanism supporting coexistence of alternative strategies in a wide range of taxa. However, the relative importance of an alternative and possibly synergistic mechanism-spatial structuring of the environment-remains the topic of some debate. In this study, we explore the influence of these mechanisms on metacommunity structure using an agent-based model built around variable life-history traits. Our model combines explicit resource competition and spatial dynamics, allowing us to tease-apart the influence of, and explore the interaction between, the CCTO and the spatial structure of the environment. We test our model using two reproductive strategies which represent extremes of the CCTO and are common in ants. Our simulations show that colonisers outperform competitors in environments subject to higher temporal and spatial heterogeneity and are favoured when agents mature late and invest heavily in reproduction, whereas competitors dominate in low-disturbance, high resource environments and when maintenance costs are low. Varying life-history parameters has a marked influence on coexistence conditions and yields evolutionary stable strategies for both modes of reproduction. Nonetheless, we show that these strategies can coexist over a wide range of life-history and environmental parameter values, and that coexistence can in most cases be explained by a CCTO. By explicitly considering space, we are also able to demonstrate the importance of the interaction between dispersal and landscape structure. The CCTO permits species employing different reproductive strategies to coexist over a wide range of life-history and environmental parameters, and is likely to be an important factor in structuring ant communities. Our consideration of space highlights the importance of dispersal, which can limit the success of low-dispersers through kin competition, and enhance coexistence conditions for different strategies in spatially structured environments.

An agent-based computational model of the spread of tuberculosis

NASA Astrophysics Data System (ADS)

de Espíndola, Aquino L.; Bauch, Chris T.; Troca Cabella, Brenno C.; Souto Martinez, Alexandre

2011-05-01

In this work we propose an alternative model of the spread of tuberculosis (TB) and the emergence of drug resistance due to the treatment with antibiotics. We implement the simulations by an agent-based model computational approach where the spatial structure is taken into account. The spread of tuberculosis occurs according to probabilities defined by the interactions among individuals. The model was validated by reproducing results already known from the literature in which different treatment regimes yield the emergence of drug resistance. The different patterns of TB spread can be visualized at any time of the system evolution. The implementation details as well as some results of this alternative approach are discussed.

Leopard in a tea-cup: A study of leopard habitat-use and human-leopard interactions in north-eastern India.

PubMed

Kshettry, Aritra; Vaidyanathan, Srinivas; Athreya, Vidya

2017-01-01

There is increasing evidence of the importance of multi-use landscapes for the conservation of large carnivores. However, when carnivore ranges overlap with high density of humans, there are often serious conservation challenges. This is especially true in countries like India where loss of peoples' lives and property to large wildlife are not uncommon. The leopard (Panthera pardus) is a large felid that is widespread in India, often sharing landscapes with high human densities. In order to understand the ecology of leopards in a human use landscape and the nature of human-leopard interactions, we studied (i) the spatial and temporal distribution and the characteristics of leopard attacks on people, (ii) the spatial variability in the pattern of habitat use by the leopard, and (iii) the spatial relationship between attack locations and habitat use by leopards. The study site, located in northern West Bengal, India, is a densely populated mixed-use landscape of 630 km2, comprising of forests, tea plantations, agriculture fields, and human settlements. A total of 171 leopard attacks on humans were reported between January 2009 and March 2016, most of which occurred within the tea-gardens. None of the attacks was fatal. We found significant spatial clustering of locations of leopard attacks on humans. However, most of the attacks were restricted to certain tea estates and occurred mostly between January and May. Analysis of habitat use by leopards showed that the probability of use of areas with more ground vegetation cover was high while that of areas with high density of buildings was low. However, locations of leopard attacks on people did not coincide with areas that showed a higher probability of use by leopards. This indicates that an increased use of an area by leopards, by itself, does not necessarily imply an increase in attacks on people. The spatial and temporal clustering of attack locations allowed us to use this information to prioritize areas to focus mitigation activities in order reduce negative encounters between people and leopards in this landscape which has had a long history of conflict.

Leopard in a tea-cup: A study of leopard habitat-use and human-leopard interactions in north-eastern India

PubMed Central

2017-01-01

There is increasing evidence of the importance of multi-use landscapes for the conservation of large carnivores. However, when carnivore ranges overlap with high density of humans, there are often serious conservation challenges. This is especially true in countries like India where loss of peoples’ lives and property to large wildlife are not uncommon. The leopard (Panthera pardus) is a large felid that is widespread in India, often sharing landscapes with high human densities. In order to understand the ecology of leopards in a human use landscape and the nature of human-leopard interactions, we studied (i) the spatial and temporal distribution and the characteristics of leopard attacks on people, (ii) the spatial variability in the pattern of habitat use by the leopard, and (iii) the spatial relationship between attack locations and habitat use by leopards. The study site, located in northern West Bengal, India, is a densely populated mixed-use landscape of 630 km2, comprising of forests, tea plantations, agriculture fields, and human settlements. A total of 171 leopard attacks on humans were reported between January 2009 and March 2016, most of which occurred within the tea-gardens. None of the attacks was fatal. We found significant spatial clustering of locations of leopard attacks on humans. However, most of the attacks were restricted to certain tea estates and occurred mostly between January and May. Analysis of habitat use by leopards showed that the probability of use of areas with more ground vegetation cover was high while that of areas with high density of buildings was low. However, locations of leopard attacks on people did not coincide with areas that showed a higher probability of use by leopards. This indicates that an increased use of an area by leopards, by itself, does not necessarily imply an increase in attacks on people. The spatial and temporal clustering of attack locations allowed us to use this information to prioritize areas to focus mitigation activities in order reduce negative encounters between people and leopards in this landscape which has had a long history of conflict. PMID:28493999

Elucidating the druggable interface of protein-protein interactions using fragment docking and coevolutionary analysis.

PubMed

Bai, Fang; Morcos, Faruck; Cheng, Ryan R; Jiang, Hualiang; Onuchic, José N

2016-12-13

Protein-protein interactions play a central role in cellular function. Improving the understanding of complex formation has many practical applications, including the rational design of new therapeutic agents and the mechanisms governing signal transduction networks. The generally large, flat, and relatively featureless binding sites of protein complexes pose many challenges for drug design. Fragment docking and direct coupling analysis are used in an integrated computational method to estimate druggable protein-protein interfaces. (i) This method explores the binding of fragment-sized molecular probes on the protein surface using a molecular docking-based screen. (ii) The energetically favorable binding sites of the probes, called hot spots, are spatially clustered to map out candidate binding sites on the protein surface. (iii) A coevolution-based interface interaction score is used to discriminate between different candidate binding sites, yielding potential interfacial targets for therapeutic drug design. This approach is validated for important, well-studied disease-related proteins with known pharmaceutical targets, and also identifies targets that have yet to be studied. Moreover, therapeutic agents are proposed by chemically connecting the fragments that are strongly bound to the hot spots.

Exploring the Human-Nipah Virus Protein-Protein Interactome

PubMed Central

Vera-Velasco, Natalia M.; Mingarro, Ismael

2017-01-01

ABSTRACT Nipah virus is an emerging, highly pathogenic, zoonotic virus of the Paramyxoviridae family. Human transmission occurs by close contact with infected animals, the consumption of contaminated food, or, occasionally, via other infected individuals. Currently, we lack therapeutic or prophylactic treatments for Nipah virus. To develop these agents we must now improve our understanding of the host-virus interactions that underpin a productive infection. This aim led us to perform the present work, in which we identified 101 human-Nipah virus protein-protein interactions (PPIs), most of which (88) are novel. This data set provides a comprehensive view of the host complexes that are manipulated by viral proteins. Host targets include the PRP19 complex and the microRNA (miRNA) processing machinery. Furthermore, we explored the biologic consequences of the interaction with the PRP19 complex and found that the Nipah virus W protein is capable of altering p53 control and gene expression. We anticipate that these data will help in guiding the development of novel interventional strategies to counter this emerging viral threat. IMPORTANCE Nipah virus is a recently discovered virus that infects a wide range of mammals, including humans. Since its discovery there have been yearly outbreaks, and in some of them the mortality rate has reached 100% of the confirmed cases. However, the study of Nipah virus has been largely neglected, and currently we lack treatments for this infection. To develop these agents we must now improve our understanding of the host-virus interactions that underpin a productive infection. In the present work, we identified 101 human-Nipah virus protein-protein interactions using an affinity purification approach coupled with mass spectrometry. Additionally, we explored the cellular consequences of some of these interactions. Globally, this data set offers a comprehensive and detailed view of the host machinery's contribution to the Nipah virus's life cycle. Furthermore, our data present a large number of putative drug targets that could be exploited for the treatment of this infection. PMID:28904190

Exploring the Human-Nipah Virus Protein-Protein Interactome.

PubMed

Martinez-Gil, Luis; Vera-Velasco, Natalia M; Mingarro, Ismael

2017-12-01

Nipah virus is an emerging, highly pathogenic, zoonotic virus of the Paramyxoviridae family. Human transmission occurs by close contact with infected animals, the consumption of contaminated food, or, occasionally, via other infected individuals. Currently, we lack therapeutic or prophylactic treatments for Nipah virus. To develop these agents we must now improve our understanding of the host-virus interactions that underpin a productive infection. This aim led us to perform the present work, in which we identified 101 human-Nipah virus protein-protein interactions (PPIs), most of which (88) are novel. This data set provides a comprehensive view of the host complexes that are manipulated by viral proteins. Host targets include the PRP19 complex and the microRNA (miRNA) processing machinery. Furthermore, we explored the biologic consequences of the interaction with the PRP19 complex and found that the Nipah virus W protein is capable of altering p53 control and gene expression. We anticipate that these data will help in guiding the development of novel interventional strategies to counter this emerging viral threat. IMPORTANCE Nipah virus is a recently discovered virus that infects a wide range of mammals, including humans. Since its discovery there have been yearly outbreaks, and in some of them the mortality rate has reached 100% of the confirmed cases. However, the study of Nipah virus has been largely neglected, and currently we lack treatments for this infection. To develop these agents we must now improve our understanding of the host-virus interactions that underpin a productive infection. In the present work, we identified 101 human-Nipah virus protein-protein interactions using an affinity purification approach coupled with mass spectrometry. Additionally, we explored the cellular consequences of some of these interactions. Globally, this data set offers a comprehensive and detailed view of the host machinery's contribution to the Nipah virus's life cycle. Furthermore, our data present a large number of putative drug targets that could be exploited for the treatment of this infection. Copyright © 2017 American Society for Microbiology.

Two Equals One: Two Human Actions During Social Interaction Are Grouped as One Unit in Working Memory.

PubMed

Ding, Xiaowei; Gao, Zaifeng; Shen, Mowei

2017-09-01

Every day, people perceive other people performing interactive actions. Retaining these actions of human agents in working memory (WM) plays a pivotal role in a normal social life. However, whether the semantic knowledge embedded in the interactive actions has a pervasive impact on the storage of the actions in WM remains unknown. In the current study, we investigated two opposing hypotheses: (a) that WM stores the interactions individually (the individual-storage hypothesis) and (b) that WM stores the interactions as chunks (the chunk-storage hypothesis). We required participants to memorize a set of individual actions while ignoring the underlying social interactions. We found that although the social-interaction aspect was task irrelevant, the interactive actions were stored in WM as chunks that were not affected by memory load (Experiments 1 and 2); however, inverting the human actions vertically abolished this chunking effect (Experiment 3). These results suggest that WM automatically and efficiently used semantic knowledge about interactive actions to store them and support the chunk-storage hypothesis.

The dynamics of perception and action.

PubMed

Warren, William H

2006-04-01

How might one account for the organization in behavior without attributing it to an internal control structure? The present article develops a theoretical framework called behavioral dynamics that integrates an information-based approach to perception with a dynamical systems approach to action. For a given task, the agent and its environment are treated as a pair of dynamical systems that are coupled mechanically and informationally. Their interactions give rise to the behavioral dynamics, a vector field with attractors that correspond to stable task solutions, repellers that correspond to avoided states, and bifurcations that correspond to behavioral transitions. The framework is used to develop theories of several tasks in which a human agent interacts with the physical environment, including bouncing a ball on a racquet, balancing an object, braking a vehicle, and guiding locomotion. Stable, adaptive behavior emerges from the dynamics of the interaction between a structured environment and an agent with simple control laws, under physical and informational constraints. ((c) 2006 APA, all rights reserved).

Feedbacks in human-landscape systems

NASA Astrophysics Data System (ADS)

Chin, Anne

2015-04-01

As human interactions with Earth systems intensify in the "Anthropocene", understanding the complex relationships among human activity, landscape change, and societal responses to those changes is increasingly important. Interdisciplinary research centered on the theme of "feedbacks" in human-landscape systems serves as a promising focus for unraveling these interactions. Deciphering interacting human-landscape feedbacks extends our traditional approach of considering humans as unidirectional drivers of change. Enormous challenges exist, however, in quantifying impact-feedback loops in landscapes with significant human alterations. This paper illustrates an example of human-landscape interactions following a wildfire in Colorado (USA) that elicited feedback responses. After the 2012 Waldo Canyon Fire, concerns for heightened flood potential and debris flows associated with post-fire hydrologic changes prompted local landowners to construct tall fences at the base of a burned watershed. These actions changed the sediment transport regime and promoted further landscape change and human responses in a positive feedback cycle. The interactions ultimately increase flood and sediment hazards, rather than dampening the effects of fire. A simple agent-based model, capable of integrating social and hydro-geomorphological data, demonstrates how such interacting impacts and feedbacks could be simulated. Challenges for fully capturing human-landscape feedback interactions include the identification of diffuse and subtle feedbacks at a range of scales, the availability of data linking impact with response, the identification of multiple thresholds that trigger feedback mechanisms, and the varied metrics and data needed to represent both the physical and human systems. By collaborating with social scientists with expertise in the human causes of landscape change, as well as the human responses to those changes, geoscientists could more fully recognize and anticipate the coupled human-landscape interactions that will drive the evolution of Earth systems into the future.

Residential expansion as a continental threat to U.S. coastal ecosystems

Treesearch

J.G. Bartlett; D.M. Mageean; R.J. O' Connor

2000-01-01

Spatially extensive analysis of satellite, climate, and census data reveals human-environment interactions of regional or continental concern in the United States. A grid-based principal components analysis of Bureau of Census variables revealed two independent demographic phenomena, a-settlement reflecting traditional human settlement patterns and p-settlement...

Systematic detection of positive selection in the human-pathogen interactome and lasting effects on infectious disease susceptibility.

PubMed

Corona, Erik; Wang, Liuyang; Ko, Dennis; Patel, Chirag J

2018-01-01

Infectious disease has shaped the natural genetic diversity of humans throughout the world. A new approach to capture positive selection driven by pathogens would provide information regarding pathogen exposure in distinct human populations and the constantly evolving arms race between host and disease-causing agents. We created a human pathogen interaction database and used the integrated haplotype score (iHS) to detect recent positive selection in genes that interact with proteins from 26 different pathogens. We used the Human Genome Diversity Panel to identify specific populations harboring pathogen-interacting genes that have undergone positive selection. We found that human genes that interact with 9 pathogen species show evidence of recent positive selection. These pathogens are Yersenia pestis, human immunodeficiency virus (HIV) 1, Zaire ebolavirus, Francisella tularensis, dengue virus, human respiratory syncytial virus, measles virus, Rubella virus, and Bacillus anthracis. For HIV-1, GWAS demonstrate that some naturally selected variants in the host-pathogen protein interaction networks continue to have functional consequences for susceptibility to these pathogens. We show that selected human genes were enriched for HIV susceptibility variants (identified through GWAS), providing further support for the hypothesis that ancient humans were exposed to lentivirus pandemics. Human genes in the Italian, Miao, and Biaka Pygmy populations that interact with Y. pestis show significant signs of selection. These results reveal some of the genetic footprints created by pathogens in the human genome that may have left lasting marks on susceptibility to infectious disease.

Simulating an emergency department: the importance of modeling the interactions between physicians and delegates in a discrete event simulation.

PubMed

Lim, Morgan E; Worster, Andrew; Goeree, Ron; Tarride, Jean-Éric

2013-05-22

Computer simulation studies of the emergency department (ED) are often patient driven and consider the physician as a human resource whose primary activity is interacting directly with the patient. In many EDs, physicians supervise delegates such as residents, physician assistants and nurse practitioners each with different skill sets and levels of independence. The purpose of this study is to present an alternative approach where physicians and their delegates in the ED are modeled as interacting pseudo-agents in a discrete event simulation (DES) and to compare it with the traditional approach ignoring such interactions. The new approach models a hierarchy of heterogeneous interacting pseudo-agents in a DES, where pseudo-agents are entities with embedded decision logic. The pseudo-agents represent a physician and delegate, where the physician plays a senior role to the delegate (i.e. treats high acuity patients and acts as a consult for the delegate). A simple model without the complexity of the ED is first created in order to validate the building blocks (programming) used to create the pseudo-agents and their interaction (i.e. consultation). Following validation, the new approach is implemented in an ED model using data from an Ontario hospital. Outputs from this model are compared with outputs from the ED model without the interacting pseudo-agents. They are compared based on physician and delegate utilization, patient waiting time for treatment, and average length of stay. Additionally, we conduct sensitivity analyses on key parameters in the model. In the hospital ED model, comparisons between the approach with interaction and without showed physician utilization increase from 23% to 41% and delegate utilization increase from 56% to 71%. Results show statistically significant mean time differences for low acuity patients between models. Interaction time between physician and delegate results in increased ED length of stay and longer waits for beds. This example shows the importance of accurately modeling physician relationships and the roles in which they treat patients. Neglecting these relationships could lead to inefficient resource allocation due to inaccurate estimates of physician and delegate time spent on patient related activities and length of stay.

LAPSUS: soil erosion - landscape evolution model

NASA Astrophysics Data System (ADS)

van Gorp, Wouter; Temme, Arnaud; Schoorl, Jeroen

2015-04-01

LAPSUS is a soil erosion - landscape evolution model which is capable of simulating landscape evolution of a gridded DEM by using multiple water, mass movement and human driven processes on multiple temporal and spatial scales. It is able to deal with a variety of human landscape interventions such as landuse management and tillage and it can model their interactions with natural processes. The complex spatially explicit feedbacks the model simulates demonstrate the importance of spatial interaction of human activity and erosion deposition patterns. In addition LAPSUS can model shallow landsliding, slope collapse, creep, solifluction, biological and frost weathering, fluvial behaviour. Furthermore, an algorithm to deal with natural depressions has been added and event-based modelling with an improved infiltration description and dust deposition has been pursued. LAPSUS has been used for case studies in many parts of the world and is continuously developing and expanding. it is now available for third-party and educational use. It has a comprehensive user interface and it is accompanied by a manual and exercises. The LAPSUS model is highly suitable to quantify and understand catchment-scale erosion processes. More information and a download link is available on www.lapsusmodel.nl.

Origins and early development of human body knowledge.

PubMed

Slaughter, Virginia; Heron, Michelle

2004-01-01

As a knowable object, the human body is highly complex. Evidence from several converging lines of research, including psychological studies, neuroimaging and clinical neuropsychology, indicates that human body knowledge is widely distributed in the adult brain, and is instantiated in at least three partially independent levels of representation. Sensorimotor body knowledge is responsible for on-line control and movement of one's own body and may also contribute to the perception of others' moving bodies; visuo-spatial body knowledge specifies detailed structural descriptions of the spatial attributes of the human body; and lexical-semantic body knowledge contains language-based knowledge about the human body. In the first chapter of this Monograph, we outline the evidence for these three hypothesized levels of human body knowledge, then review relevant literature on infants' and young children's human body knowledge in terms of the three-level framework. In Chapters II and III, we report two complimentary series of studies that specifically investigate the emergence of visuo-spatial body knowledge in infancy. Our technique is to compare infants'responses to typical and scrambled human bodies, in order to evaluate when and how infants acquire knowledge about the canonical spatial layout of the human body. Data from a series of visual habituation studies indicate that infants first discriminate scrambled from typical human body picture sat 15 to 18 months of age. Data from object examination studies similarly indicate that infants are sensitive to violations of three-dimensional human body stimuli starting at 15-18 months of age. The overall pattern of data supports several conclusions about the early development of human body knowledge: (a) detailed visuo-spatial knowledge about the human body is first evident in the second year of life, (b) visuo-spatial knowledge of human faces and human bodies are at least partially independent in infancy and (c) infants' initial visuo-spatial human body representations appear to be highly schematic, becoming more detailed and specific with development. In the final chapter, we explore these conclusions and discuss how levels of body knowledge may interact in early development.

The shaping of social perception by stimulus and knowledge cues to human animacy

PubMed Central

Ramsey, Richard; Liepelt, Roman; Prinz, Wolfgang; Hamilton, Antonia F. de C.

2016-01-01

Although robots are becoming an ever-growing presence in society, we do not hold the same expectations for robots as we do for humans, nor do we treat them the same. As such, the ability to recognize cues to human animacy is fundamental for guiding social interactions. We review literature that demonstrates cortical networks associated with person perception, action observation and mentalizing are sensitive to human animacy information. In addition, we show that most prior research has explored stimulus properties of artificial agents (humanness of appearance or motion), with less investigation into knowledge cues (whether an agent is believed to have human or artificial origins). Therefore, currently little is known about the relationship between stimulus and knowledge cues to human animacy in terms of cognitive and brain mechanisms. Using fMRI, an elaborate belief manipulation, and human and robot avatars, we found that knowledge cues to human animacy modulate engagement of person perception and mentalizing networks, while stimulus cues to human animacy had less impact on social brain networks. These findings demonstrate that self–other similarities are not only grounded in physical features but are also shaped by prior knowledge. More broadly, as artificial agents fulfil increasingly social roles, a challenge for roboticists will be to manage the impact of pre-conceived beliefs while optimizing human-like design. PMID:26644594

The shaping of social perception by stimulus and knowledge cues to human animacy.

PubMed

Cross, Emily S; Ramsey, Richard; Liepelt, Roman; Prinz, Wolfgang; de C Hamilton, Antonia F

2016-01-19

Although robots are becoming an ever-growing presence in society, we do not hold the same expectations for robots as we do for humans, nor do we treat them the same. As such, the ability to recognize cues to human animacy is fundamental for guiding social interactions. We review literature that demonstrates cortical networks associated with person perception, action observation and mentalizing are sensitive to human animacy information. In addition, we show that most prior research has explored stimulus properties of artificial agents (humanness of appearance or motion), with less investigation into knowledge cues (whether an agent is believed to have human or artificial origins). Therefore, currently little is known about the relationship between stimulus and knowledge cues to human animacy in terms of cognitive and brain mechanisms. Using fMRI, an elaborate belief manipulation, and human and robot avatars, we found that knowledge cues to human animacy modulate engagement of person perception and mentalizing networks, while stimulus cues to human animacy had less impact on social brain networks. These findings demonstrate that self-other similarities are not only grounded in physical features but are also shaped by prior knowledge. More broadly, as artificial agents fulfil increasingly social roles, a challenge for roboticists will be to manage the impact of pre-conceived beliefs while optimizing human-like design. © 2015 The Authors.

A Face Attention Technique for a Robot Able to Interpret Facial Expressions

NASA Astrophysics Data System (ADS)

Simplício, Carlos; Prado, José; Dias, Jorge

Automatic facial expressions recognition using vision is an important subject towards human-robot interaction. Here is proposed a human face focus of attention technique and a facial expressions classifier (a Dynamic Bayesian Network) to incorporate in an autonomous mobile agent whose hardware is composed by a robotic platform and a robotic head. The focus of attention technique is based on the symmetry presented by human faces. By using the output of this module the autonomous agent keeps always targeting the human face frontally. In order to accomplish this, the robot platform performs an arc centered at the human; thus the robotic head, when necessary, moves synchronized. In the proposed probabilistic classifier the information is propagated, from the previous instant, in a lower level of the network, to the current instant. Moreover, to recognize facial expressions are used not only positive evidences but also negative.

Dietary Levels of Pure Flavonoids Improve Spatial Memory Performance and Increase Hippocampal Brain-Derived Neurotrophic Factor

PubMed Central

Rendeiro, Catarina; Vauzour, David; Rattray, Marcus; Waffo-Téguo, Pierre; Mérillon, Jean Michel; Butler, Laurie T.; Williams, Claire M.; Spencer, Jeremy P. E.

2013-01-01

Evidence suggests that flavonoid-rich foods are capable of inducing improvements in memory and cognition in animals and humans. However, there is a lack of clarity concerning whether flavonoids are the causal agents in inducing such behavioral responses. Here we show that supplementation with pure anthocyanins or pure flavanols for 6 weeks, at levels similar to that found in blueberry (2% w/w), results in an enhancement of spatial memory in 18 month old rats. Pure flavanols and pure anthocyanins were observed to induce significant improvements in spatial working memory (p = 0.002 and p = 0.006 respectively), to a similar extent to that following blueberry supplementation (p = 0.002). These behavioral changes were paralleled by increases in hippocampal brain-derived neurotrophic factor (R = 0.46, p<0.01), suggesting a common mechanism for the enhancement of memory. However, unlike protein levels of BDNF, the regional enhancement of BDNF mRNA expression in the hippocampus appeared to be predominantly enhanced by anthocyanins. Our data support the claim that flavonoids are likely causal agents in mediating the cognitive effects of flavonoid-rich foods. PMID:23723987

Brain Response to a Humanoid Robot in Areas Implicated in the Perception of Human Emotional Gestures

PubMed Central

Chaminade, Thierry; Zecca, Massimiliano; Blakemore, Sarah-Jayne; Takanishi, Atsuo; Frith, Chris D.; Micera, Silvestro; Dario, Paolo; Rizzolatti, Giacomo; Gallese, Vittorio; Umiltà, Maria Alessandra

2010-01-01

Background The humanoid robot WE4-RII was designed to express human emotions in order to improve human-robot interaction. We can read the emotions depicted in its gestures, yet might utilize different neural processes than those used for reading the emotions in human agents. Methodology Here, fMRI was used to assess how brain areas activated by the perception of human basic emotions (facial expression of Anger, Joy, Disgust) and silent speech respond to a humanoid robot impersonating the same emotions, while participants were instructed to attend either to the emotion or to the motion depicted. Principal Findings Increased responses to robot compared to human stimuli in the occipital and posterior temporal cortices suggest additional visual processing when perceiving a mechanical anthropomorphic agent. In contrast, activity in cortical areas endowed with mirror properties, like left Broca's area for the perception of speech, and in the processing of emotions like the left anterior insula for the perception of disgust and the orbitofrontal cortex for the perception of anger, is reduced for robot stimuli, suggesting lesser resonance with the mechanical agent. Finally, instructions to explicitly attend to the emotion significantly increased response to robot, but not human facial expressions in the anterior part of the left inferior frontal gyrus, a neural marker of motor resonance. Conclusions Motor resonance towards a humanoid robot, but not a human, display of facial emotion is increased when attention is directed towards judging emotions. Significance Artificial agents can be used to assess how factors like anthropomorphism affect neural response to the perception of human actions. PMID:20657777

MyGeneFriends: A Social Network Linking Genes, Genetic Diseases, and Researchers

PubMed Central

Allot, Alexis; Chennen, Kirsley; Nevers, Yannis; Poidevin, Laetitia; Kress, Arnaud; Ripp, Raymond; Thompson, Julie Dawn; Poch, Olivier

2017-01-01

Background The constant and massive increase of biological data offers unprecedented opportunities to decipher the function and evolution of genes and their roles in human diseases. However, the multiplicity of sources and flow of data mean that efficient access to useful information and knowledge production has become a major challenge. This challenge can be addressed by taking inspiration from Web 2.0 and particularly social networks, which are at the forefront of big data exploration and human-data interaction. Objective MyGeneFriends is a Web platform inspired by social networks, devoted to genetic disease analysis, and organized around three types of proactive agents: genes, humans, and genetic diseases. The aim of this study was to improve exploration and exploitation of biological, postgenomic era big data. Methods MyGeneFriends leverages conventions popularized by top social networks (Facebook, LinkedIn, etc), such as networks of friends, profile pages, friendship recommendations, affinity scores, news feeds, content recommendation, and data visualization. Results MyGeneFriends provides simple and intuitive interactions with data through evaluation and visualization of connections (friendships) between genes, humans, and diseases. The platform suggests new friends and publications and allows agents to follow the activity of their friends. It dynamically personalizes information depending on the user’s specific interests and provides an efficient way to share information with collaborators. Furthermore, the user’s behavior itself generates new information that constitutes an added value integrated in the network, which can be used to discover new connections between biological agents. Conclusions We have developed MyGeneFriends, a Web platform leveraging conventions from popular social networks to redefine the relationship between humans and biological big data and improve human processing of biomedical data. MyGeneFriends is available at lbgi.fr/mygenefriends. PMID:28623182

Language competition in a population of migrating agents.

PubMed

Lipowska, Dorota; Lipowski, Adam

2017-05-01

Influencing various aspects of human activity, migration is associated also with language formation. To examine the mutual interaction of these processes, we study a Naming Game with migrating agents. The dynamics of the model leads to formation of low-mobility clusters, which turns out to break the symmetry of the model: although the Naming Game remains symmetric, low-mobility languages are favored. High-mobility languages are gradually eliminated from the system, and the dynamics of language formation considerably slows down. Our model is too simple to explain in detail language competition of migrating human communities, but it certainly shows that languages of settlers are favored over nomadic ones.

Language competition in a population of migrating agents

NASA Astrophysics Data System (ADS)

Lipowska, Dorota; Lipowski, Adam

2017-05-01

Influencing various aspects of human activity, migration is associated also with language formation. To examine the mutual interaction of these processes, we study a Naming Game with migrating agents. The dynamics of the model leads to formation of low-mobility clusters, which turns out to break the symmetry of the model: although the Naming Game remains symmetric, low-mobility languages are favored. High-mobility languages are gradually eliminated from the system, and the dynamics of language formation considerably slows down. Our model is too simple to explain in detail language competition of migrating human communities, but it certainly shows that languages of settlers are favored over nomadic ones.

Quantitation of five organophosphorus nerve agent metabolites in serum using hydrophilic interaction liquid chromatography and tandem mass spectrometry

PubMed Central

Hamelin, Elizabeth I.; Schulze, Nicholas D.; Shaner, Rebecca L.; Coleman, Rebecca M.; Lawrence, Richard J.; Crow, Brian S.; Jakubowski, E. M.; Johnson, Rudolph C.

2015-01-01

Although nerve agent use is prohibited, concerns remain for human exposure to nerve agents during decommissioning, research, and warfare. Exposure can be detected through the analysis of the hydrolysis products in urine as well as blood. An analytical method to detect exposure to five nerve agents, including VX, VR (Russian VX), GB (sarin), GD (soman) and GF (cyclosarin), through the analysis of the hydrolysis products, which are the primary metabolites, in serum has been developed and characterized. This method uses solid phase extraction coupled with high performance liquid chromatography for separation and isotopic dilution tandem mass spectrometry for detection. An uncommon buffer of ammonium fluoride was used to enhance ionization and improve sensitivity when coupled with hydrophilic interaction liquid chromatography resulting in detection limits from 0.3–0.5 ng/mL. The assessment of two quality control samples demonstrated high accuracy (101–105%) and high precision (5–8%) for the detection of these five nerve agent hydrolysis products in serum. PMID:24633507

Characterization of New Zealand White Rabbit Gut-Associated Lymphoid Tissues and Use as Viral Oncology Animal Model.

PubMed

Haines, Robyn A; Urbiztondo, Rebeccah A; Haynes, Rashade A H; Simpson, Elaine; Niewiesk, Stefan; Lairmore, Michael D

2016-01-01

Rabbits have served as a valuable animal model for the pathogenesis of various human diseases, including those related to agents that gain entry through the gastrointestinal tract such as human T cell leukemia virus type 1. However, limited information is available regarding the spatial distribution and phenotypic characterization of major rabbit leukocyte populations in mucosa-associated lymphoid tissues. Herein, we describe the spatial distribution and phenotypic characterization of leukocytes from gut-associated lymphoid tissues (GALT) from 12-week-old New Zealand White rabbits. Our data indicate that rabbits have similar distribution of leukocyte subsets as humans, both in the GALT inductive and effector sites and in mesenteric lymph nodes, spleen, and peripheral blood. GALT inductive sites, including appendix, cecal tonsil, Peyer's patches, and ileocecal plaque, had variable B cell/T cell ratios (ranging from 4.0 to 0.8) with a predominance of CD4 T cells within the T cell population in all four tissues. Intraepithelial and lamina propria compartments contained mostly T cells, with CD4 T cells predominating in the lamina propria compartment and CD8 T cells predominating in the intraepithelial compartment. Mesenteric lymph node, peripheral blood, and splenic samples contained approximately equal percentages of B cells and T cells, with a high proportion of CD4 T cells compared with CD8 T cells. Collectively, our data indicate that New Zealand White rabbits are comparable with humans throughout their GALT and support future studies that use the rabbit model to study human gut-associated disease or infectious agents that gain entry by the oral route. © The Author 2016. Published by Oxford University Press on behalf of the Institute for Laboratory Animal Research. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Landscape-scale accessibility of livestock to tigers: implications of spatial grain for modeling predation risk to mitigate human-carnivore conflict.

PubMed

Miller, Jennifer R B; Jhala, Yadvendradev V; Jena, Jyotirmay; Schmitz, Oswald J

2015-03-01

Innovative conservation tools are greatly needed to reduce livelihood losses and wildlife declines resulting from human-carnivore conflict. Spatial risk modeling is an emerging method for assessing the spatial patterns of predator-prey interactions, with applications for mitigating carnivore attacks on livestock. Large carnivores that ambush prey attack and kill over small areas, requiring models at fine spatial grains to predict livestock depredation hot spots. To detect the best resolution for predicting where carnivores access livestock, we examined the spatial attributes associated with livestock killed by tigers in Kanha Tiger Reserve, India, using risk models generated at 20, 100, and 200-m spatial grains. We analyzed land-use, human presence, and vegetation structure variables at 138 kill sites and 439 random sites to identify key landscape attributes where livestock were vulnerable to tigers. Land-use and human presence variables contributed strongly to predation risk models, with most variables showing high relative importance (≥0.85) at all spatial grains. The risk of a tiger killing livestock increased near dense forests and near the boundary of the park core zone where human presence is restricted. Risk was nonlinearly related to human infrastructure and open vegetation, with the greatest risk occurring 1.2 km from roads, 1.1 km from villages, and 8.0 km from scrubland. Kill sites were characterized by denser, patchier, and more complex vegetation with lower visibility than random sites. Risk maps revealed high-risk hot spots inside of the core zone boundary and in several patches in the human-dominated buffer zone. Validation against known kills revealed predictive accuracy for only the 20 m model, the resolution best representing the kill stage of hunting for large carnivores that ambush prey, like the tiger. Results demonstrate that risk models developed at fine spatial grains can offer accurate guidance on landscape attributes livestock should avoid to minimize human-carnivore conflict.

Feedback-Based, System-Level Properties of Vertebrate-Microbial Interactions

PubMed Central

Rivas, Ariel L.; Jankowski, Mark D.; Piccinini, Renata; Leitner, Gabriel; Schwarz, Daniel; Anderson, Kevin L.; Fair, Jeanne M.; Hoogesteijn, Almira L.; Wolter, Wilfried; Chaffer, Marcelo; Blum, Shlomo; Were, Tom; Konah, Stephen N.; Kempaiah, Prakash; Ong’echa, John M.; Diesterbeck, Ulrike S.; Pilla, Rachel; Czerny, Claus-Peter; Hittner, James B.; Hyman, James M.; Perkins, Douglas J.

2013-01-01

Background Improved characterization of infectious disease dynamics is required. To that end, three-dimensional (3D) data analysis of feedback-like processes may be considered. Methods To detect infectious disease data patterns, a systems biology (SB) and evolutionary biology (EB) approach was evaluated, which utilizes leukocyte data structures designed to diminish data variability and enhance discrimination. Using data collected from one avian and two mammalian (human and bovine) species infected with viral, parasite, or bacterial agents (both sensitive and resistant to antimicrobials), four data structures were explored: (i) counts or percentages of a single leukocyte type, such as lymphocytes, neutrophils, or macrophages (the classic approach), and three levels of the SB/EB approach, which assessed (ii) 2D, (iii) 3D, and (iv) multi-dimensional (rotating 3D) host-microbial interactions. Results In all studies, no classic data structure discriminated disease-positive (D+, or observations in which a microbe was isolated) from disease-negative (D–, or microbial-negative) groups: D+ and D– data distributions overlapped. In contrast, multi-dimensional analysis of indicators designed to possess desirable features, such as a single line of observations, displayed a continuous, circular data structure, whose abrupt inflections facilitated partitioning into subsets statistically significantly different from one another. In all studies, the 3D, SB/EB approach distinguished three (steady, positive, and negative) feedback phases, in which D– data characterized the steady state phase, and D+ data were found in the positive and negative phases. In humans, spatial patterns revealed false-negative observations and three malaria-positive data classes. In both humans and bovines, methicillin-resistant Staphylococcus aureus (MRSA) infections were discriminated from non-MRSA infections. Conclusions More information can be extracted, from the same data, provided that data are structured, their 3D relationships are considered, and well-conserved (feedback-like) functions are estimated. Patterns emerging from such structures may distinguish well-conserved from recently developed host-microbial interactions. Applications include diagnosis, error detection, and modeling. PMID:23437039

Feedback-based, system-level properties of vertebrate-microbial interactions.

PubMed

Rivas, Ariel L; Jankowski, Mark D; Piccinini, Renata; Leitner, Gabriel; Schwarz, Daniel; Anderson, Kevin L; Fair, Jeanne M; Hoogesteijn, Almira L; Wolter, Wilfried; Chaffer, Marcelo; Blum, Shlomo; Were, Tom; Konah, Stephen N; Kempaiah, Prakash; Ong'echa, John M; Diesterbeck, Ulrike S; Pilla, Rachel; Czerny, Claus-Peter; Hittner, James B; Hyman, James M; Perkins, Douglas J

2013-01-01

Improved characterization of infectious disease dynamics is required. To that end, three-dimensional (3D) data analysis of feedback-like processes may be considered. To detect infectious disease data patterns, a systems biology (SB) and evolutionary biology (EB) approach was evaluated, which utilizes leukocyte data structures designed to diminish data variability and enhance discrimination. Using data collected from one avian and two mammalian (human and bovine) species infected with viral, parasite, or bacterial agents (both sensitive and resistant to antimicrobials), four data structures were explored: (i) counts or percentages of a single leukocyte type, such as lymphocytes, neutrophils, or macrophages (the classic approach), and three levels of the SB/EB approach, which assessed (ii) 2D, (iii) 3D, and (iv) multi-dimensional (rotating 3D) host-microbial interactions. In all studies, no classic data structure discriminated disease-positive (D+, or observations in which a microbe was isolated) from disease-negative (D-, or microbial-negative) groups: D+ and D- data distributions overlapped. In contrast, multi-dimensional analysis of indicators designed to possess desirable features, such as a single line of observations, displayed a continuous, circular data structure, whose abrupt inflections facilitated partitioning into subsets statistically significantly different from one another. In all studies, the 3D, SB/EB approach distinguished three (steady, positive, and negative) feedback phases, in which D- data characterized the steady state phase, and D+ data were found in the positive and negative phases. In humans, spatial patterns revealed false-negative observations and three malaria-positive data classes. In both humans and bovines, methicillin-resistant Staphylococcus aureus (MRSA) infections were discriminated from non-MRSA infections. More information can be extracted, from the same data, provided that data are structured, their 3D relationships are considered, and well-conserved (feedback-like) functions are estimated. Patterns emerging from such structures may distinguish well-conserved from recently developed host-microbial interactions. Applications include diagnosis, error detection, and modeling.

Exploiting Motion Capture to Enhance Avoidance Behaviour in Games

NASA Astrophysics Data System (ADS)

van Basten, Ben J. H.; Jansen, Sander E. M.; Karamouzas, Ioannis

Realistic simulation of interacting virtual characters is essential in computer games, training and simulation applications. The problem is very challenging since people are accustomed to real-world situations and thus, they can easily detect inconsistencies and artifacts in the simulations. Over the past twenty years several models have been proposed for simulating individuals, groups and crowds of characters. However, little effort has been made to actually understand how humans solve interactions and avoid inter-collisions in real-life. In this paper, we exploit motion capture data to gain more insights into human-human interactions. We propose four measures to describe the collision-avoidance behavior. Based on these measures, we extract simple rules that can be applied on top of existing agent and force based approaches, increasing the realism of the resulting simulations.

Restoration of the Mississippi Delta: Lessons from Hurricanes Katrina and Rita

NASA Astrophysics Data System (ADS)

Day, John W.; Boesch, Donald F.; Clairain, Ellis J.; Kemp, G. Paul; Laska, Shirley B.; Mitsch, William J.; Orth, Kenneth; Mashriqui, Hassan; Reed, Denise J.; Shabman, Leonard; Simenstad, Charles A.; Streever, Bill J.; Twilley, Robert R.; Watson, Chester C.; Wells, John T.; Whigham, Dennis F.

2007-03-01

Hurricanes Katrina and Rita showed the vulnerability of coastal communities and how human activities that caused deterioration of the Mississippi Deltaic Plain (MDP) exacerbated this vulnerability. The MDP formed by dynamic interactions between river and coast at various temporal and spatial scales, and human activity has reduced these interactions at all scales. Restoration efforts aim to re-establish this dynamic interaction, with emphasis on reconnecting the river to the deltaic plain. Science must guide MDP restoration, which will provide insights into delta restoration elsewhere and generally into coasts facing climate change in times of resource scarcity.

Spatial and temporal dynamics of disturbance interactions along an ecological gradient

Treesearch

Christopher D. O' Connor

2013-01-01

Interactions among site conditions, disturbance events, and climate determine the patterns of forest species recruitment and mortality across landscapes. Forests of the American Southwest have undergone significant changes over a century of altered disturbance regimes, human land uses, and changing environmental conditions. Along steep vertical gradients such as those...

Using landscape disturbance and succession models to support forest management

Treesearch

Eric J. Gustafson; Brian R. Sturtevant; Anatoly S. Shvidenko; Robert M. Scheller

2010-01-01

Managers of forested landscapes must account for multiple, interacting ecological processes operating at broad spatial and temporal scales. These interactions can be of such complexity that predictions of future forest ecosystem states are beyond the analytical capability of the human mind. Landscape disturbance and succession models (LDSM) are predictive and...

Bushmeat Hunting, Deforestation, and Prediction of Zoonotic Disease

PubMed Central

Daszak, Peter; Kilpatrick, A. Marm; Burke, Donald S.

2005-01-01

Understanding the emergence of new zoonotic agents requires knowledge of pathogen biodiversity in wildlife, human-wildlife interactions, anthropogenic pressures on wildlife populations, and changes in society and human behavior. We discuss an interdisciplinary approach combining virology, wildlife biology, disease ecology, and anthropology that enables better understanding of how deforestation and associated hunting leads to the emergence of novel zoonotic pathogens. PMID:16485465

Collective ordering of microscale matters in natural analogy

PubMed Central

Ahn, Sungsook; Joon Lee, Sang

2015-01-01

Collective interaction occurs in many natural and artificial matters in broad scales. In a biological system, collective spatial organization of live individuals in a colony is important for their viability determination. Interactive motions between a single individual and an agglomerate are critical for whole procedure of the collective behaviors, but few has been clarified for these intermediate range behaviors. Here, collective interactions of microscale matters are investigated with human cells, plant seeds and artificial microspheres in terms of commonly occurring spatial arrangements. Human cancer cells are inherently attractive to form an agglomerate by cohesive motion, while plant chia seeds are repulsive by excreting mucilage. Microsphere model is employed to investigate the dynamic assembly equilibrated by an attraction and repulsion. There is a fundamental analogy in terms of an onset of regular pattern formation even without physical contact of individuals. The collective interactions are suggested to start before the individual components become physically agglomerated. This study contributes to fundamental understanding on the microscale particulate matters and natural pattern formation which are further useful for various applications both in academic and industrial areas. PMID:26027819

Human DNA polymerase ε is phosphorylated at serine-1940 after DNA damage and interacts with the iron-sulfur complex chaperones CIAO1 and MMS19

PubMed Central

Moiseeva, Tatiana; Gamper, Armin M.; Hood, Brian; Conrads, Thomas P.; Bakkenist, Christopher J.

2016-01-01

We describe a dynamic phosphorylation on serine-1940 of the catalytic subunit of human Pol ε, POLE1, following DNA damage. We also describe novel interactions between POLE1 and the iron-sulfur cluster assembly complex CIA proteins CIAO1 and MMS19. We show that serine-1940 is essential for the interaction between POLE1 and MMS19, but not POLE1 and CIAO1. No defect in either proliferation or survival was identified when POLE1 serine-1940 was mutated to alanine in human cells, even following treatment with DNA damaging agents. We conclude that serine-1940 phosphorylation and the interaction between serine-1940 and MMS19 are not essential functions in the C terminal domain of the catalytic subunit of DNA polymerase ε. PMID:27235625

p53-Mdm2 interaction inhibitors as novel nongenotoxic anticancer agents.

PubMed

Nayak, Surendra Kumar; Khatik, Gopal L; Narang, Rakesh; Monga, Vikramdeep; Chopra, Harish Kumar

2017-06-23

Cancer is a major global health problem with high mortality rate. Most of clinically used anticancer agents induce apoptosis through genotoxic stress at various stages of cell cycle and activation of p53. Acting as a tumor suppressor p53 plays a vital role in preventing tumor development. Tumor suppressor function of p53 is effectively antagonized by its direct interaction with murine double minute 2 (Mdm2) proteins via multiple mechanisms. Thus, p53-Mdm2 interaction has been found to be an important target for the development of novel anticancer agents. Currently, nutlin, spirooxindole, isoquilinone and piperidinone analogues inhibiting p53-Mdm2 interaction are found to be promising in the treatment of cancer. The current review focused to scrutinize the structural aspects of p53-Mdm2 interaction inhibitors. The present study provides a detailed collection of published information on different classes of inhibitors of p53-Mdm2 interaction as potential anticancer agents. The review highlighted the structural aspects of various reported p53-Mdm2 inhibitor for optimization. In the last few years, different classes of inhibitors of p53-Mdm2 have been designed and developed, and seven such compounds are being evaluated in clinical trials as new anticancer drugs. Further, to explore the role of p53 protein as a potential target for anticancer drug development, in this review, the mechanism of Mdm2 mediated inactivation of p53 and recent developments on p53-Mdm2 interactions inhibitors are discussed. Agents designed to block the p53-Mdm2 interaction may have a therapeutic potential for treatment of a subset of human cancers retaining wild-type p53. We review herein the recent advances in the design and development of potent small molecules as p53-Mdm2 inhibitors. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Revealing Spatial Variation and Correlation of Urban Travels from Big Trajectory Data

NASA Astrophysics Data System (ADS)

Li, X.; Tu, W.; Shen, S.; Yue, Y.; Luo, N.; Li, Q.

2017-09-01

With the development of information and communication technology, spatial-temporal data that contain rich human mobility information are growing rapidly. However, the consistency of multi-mode human travel behind multi-source spatial-temporal data is not clear. To this aim, we utilized a week of taxies' and buses' GPS trajectory data and smart card data in Shenzhen, China to extract city-wide travel information of taxi, bus and metro and tested the correlation of multi-mode travel characteristics. Both the global correlation and local correlation of typical travel indicator were examined. The results show that: (1) Significant differences exist in of urban multi-mode travels. The correlation between bus travels and taxi travels, metro travel and taxi travels are globally low but locally high. (2) There are spatial differences of the correlation relationship between bus, metro and taxi travel. These findings help us understanding urban travels deeply therefore facilitate both the transport policy making and human-space interaction research.

Shear Forces during Blast, Not Abrupt Changes in Pressure Alone, Generate Calcium Activity in Human Brain Cells

DTIC Science & Technology

2012-06-29

the tissue-force interaction(s) and the cellular damage properties remain unresolved. Studies on a mechanical head model demonstrated high transient...that pressure transient. In vitro models of primary blast injury [5,18,19] are likewise limited by an absence of real-time, high spatial and temporal... models , as well as with human injuries in which expression of bTBI symptoms among different individuals that are exposed to the same blast is

Auditory peripersonal space in humans.

PubMed

Farnè, Alessandro; Làdavas, Elisabetta

2002-10-01

In the present study we report neuropsychological evidence of the existence of an auditory peripersonal space representation around the head in humans and its characteristics. In a group of right brain-damaged patients with tactile extinction, we found that a sound delivered near the ipsilesional side of the head (20 cm) strongly extinguished a tactile stimulus delivered to the contralesional side of the head (cross-modal auditory-tactile extinction). By contrast, when an auditory stimulus was presented far from the head (70 cm), cross-modal extinction was dramatically reduced. This spatially specific cross-modal extinction was most consistently found (i.e., both in the front and back spaces) when a complex sound was presented, like a white noise burst. Pure tones produced spatially specific cross-modal extinction when presented in the back space, but not in the front space. In addition, the most severe cross-modal extinction emerged when sounds came from behind the head, thus showing that the back space is more sensitive than the front space to the sensory interaction of auditory-tactile inputs. Finally, when cross-modal effects were investigated by reversing the spatial arrangement of cross-modal stimuli (i.e., touch on the right and sound on the left), we found that an ipsilesional tactile stimulus, although inducing a small amount of cross-modal tactile-auditory extinction, did not produce any spatial-specific effect. Therefore, the selective aspects of cross-modal interaction found near the head cannot be explained by a competition between a damaged left spatial representation and an intact right spatial representation. Thus, consistent with neurophysiological evidence from monkeys, our findings strongly support the existence, in humans, of an integrated cross-modal system coding auditory and tactile stimuli near the body, that is, in the peripersonal space.

A high resolution agent-based model to support walk-bicycle infrastructure investment decisions: A case study with New York City

DOE PAGES

Aziz, H. M. Abdul; Park, Byung H.; Morton, April M.; ...

2017-11-24

Active transportation modes--walk and bicycle--are central for low carbon transport, healthy living, and complete streets initiative. Building a community with amenable walk and bicycle facilities asks for smart planning and investments. It is critical to investigate the impact of infrastructure building or expansion on the overall walk and bicycle mode usage prior to making investment choices utilizing public tax money. This research developed an agent-based model to support investment decisions that allows to assess the impact of changes in walk-bike infrastructures at a high spatial resolution (e.g., block group level). The agent-based model (ABM) utilizes data from a synthetic populationmore » simulator generating agents with corresponding socio-demographic characteristics, and integrates facility attributes regarding walking and bicycling (e.g., sidewalk width, bike lane length) into the mode choice decision making process. Moreover, the ABM accounts for the effect of social interactions among agents who live and work at the same geographic locations. Finally, GIS-based maps are developed at block group resolution that allows exploring the effect of walk-bike infrastructure related investments. The results from New York City case study indicate that infrastructure investments such as widening sidewalk and increasing bike lane network can positively influence the active transportation mode choices. In addition, the level of impact varies with geographic locations--different boroughs of New York City will have different impacts. Lastly, social promotions resulting in higher social interaction among agents can reinforce the impacts of infrastructure changes.« less

A high resolution agent-based model to support walk-bicycle infrastructure investment decisions: A case study with New York City

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aziz, H. M. Abdul; Park, Byung H.; Morton, April M.

Active transportation modes--walk and bicycle--are central for low carbon transport, healthy living, and complete streets initiative. Building a community with amenable walk and bicycle facilities asks for smart planning and investments. It is critical to investigate the impact of infrastructure building or expansion on the overall walk and bicycle mode usage prior to making investment choices utilizing public tax money. This research developed an agent-based model to support investment decisions that allows to assess the impact of changes in walk-bike infrastructures at a high spatial resolution (e.g., block group level). The agent-based model (ABM) utilizes data from a synthetic populationmore » simulator generating agents with corresponding socio-demographic characteristics, and integrates facility attributes regarding walking and bicycling (e.g., sidewalk width, bike lane length) into the mode choice decision making process. Moreover, the ABM accounts for the effect of social interactions among agents who live and work at the same geographic locations. Finally, GIS-based maps are developed at block group resolution that allows exploring the effect of walk-bike infrastructure related investments. The results from New York City case study indicate that infrastructure investments such as widening sidewalk and increasing bike lane network can positively influence the active transportation mode choices. In addition, the level of impact varies with geographic locations--different boroughs of New York City will have different impacts. Lastly, social promotions resulting in higher social interaction among agents can reinforce the impacts of infrastructure changes.« less

Agent-based modeling for the landuse change of hunter-gather societies and the impacts on biodiversity in Guyana

NASA Astrophysics Data System (ADS)

Iwamura, T.; Fragoso, J.; Lambin, E.

2012-12-01

The interactions with animals are vital to the Amerindian, indigenous people, of Rupunini savannah-forest in Guyana. Their connections extend from basic energy and protein resource to spiritual bonding through "paring" to a certain animal in the forest. We collected extensive dataset of 23 indigenous communities for 3.5 years, consisting 9900 individuals from 1307 households, as well as animal observation data in 8 transects per communities (47,000 data entries). In this presentation, our research interest is to model the driver of land use change of the indigenous communities and its impacts on the ecosystem in the Rupunini area under global change. Overarching question we would like to answer with this program is to find how and why "tipping-point" from hunting gathering society to the agricultural society occurs in the future. Secondary question is what is the implication of the change to agricultural society in terms of biodiversity and carbon stock in the area, and eventually the well-being of Rupunini people. To answer the questions regarding the society shift in agriculture activities, we built as simulation with Agent-Based Modeling (Multi Agents Simulation). We developed this simulation by using Netlogo, the programming environment specialized for spatially explicit agent-based modeling (ABM). This simulation consists of four different process in the Rupunini landscape; forest succession, animal population growth, hunting of animals, and land clearing for agriculture. All of these processes are carried out by a set of computational unit, called "agents". In this program, there are four types of agents - patches, villages, households, and animals. Here, we describe the impacts of hunting on the biodiversity based on actual demographic data from one village named Crush Water. Animal population within the hunting territory of the village stabilized but Agouti/Paca dominates the landscape with little population of armadillos and peccaries. White-tailed deers, Tapirs, Capybara exist but very low. This finding is well aligned with the hunting dataset - Agouti/Paca consists 27% of total hunting. Based on our simulation, it seems the dominance of Agouti/Paca among hunted animals shown in the field data can be explained solely by their high carrying capacity against human extraction (population density of the Paca/Agouti = 60 per square km, whereas other animals ranges 0.63 to 7). When we incorporate agriculture, the "rodentation" of the animal population toward Agouti/Paca becomes more obvious. This simulation shows the interactions of people and animals through land change and hunting, which were observed in our fields.

Attraction of position preference by spatial attention throughout human visual cortex.

PubMed

Klein, Barrie P; Harvey, Ben M; Dumoulin, Serge O

2014-10-01

Voluntary spatial attention concentrates neural resources at the attended location. Here, we examined the effects of spatial attention on spatial position selectivity in humans. We measured population receptive fields (pRFs) using high-field functional MRI (fMRI) (7T) while subjects performed an attention-demanding task at different locations. We show that spatial attention attracts pRF preferred positions across the entire visual field, not just at the attended location. This global change in pRF preferred positions systematically increases up the visual hierarchy. We model these pRF preferred position changes as an interaction between two components: an attention field and a pRF without the influence of attention. This computational model suggests that increasing effects of attention up the hierarchy result primarily from differences in pRF size and that the attention field is similar across the visual hierarchy. A similar attention field suggests that spatial attention transforms different neural response selectivities throughout the visual hierarchy in a similar manner. Copyright © 2014 Elsevier Inc. All rights reserved.

Agent-based model with multi-level herding for complex financial systems

NASA Astrophysics Data System (ADS)

Chen, Jun-Jie; Tan, Lei; Zheng, Bo

2015-02-01

In complex financial systems, the sector structure and volatility clustering are respectively important features of the spatial and temporal correlations. However, the microscopic generation mechanism of the sector structure is not yet understood. Especially, how to produce these two features in one model remains challenging. We introduce a novel interaction mechanism, i.e., the multi-level herding, in constructing an agent-based model to investigate the sector structure combined with volatility clustering. According to the previous market performance, agents trade in groups, and their herding behavior comprises the herding at stock, sector and market levels. Further, we propose methods to determine the key model parameters from historical market data, rather than from statistical fitting of the results. From the simulation, we obtain the sector structure and volatility clustering, as well as the eigenvalue distribution of the cross-correlation matrix, for the New York and Hong Kong stock exchanges. These properties are in agreement with the empirical ones. Our results quantitatively reveal that the multi-level herding is the microscopic generation mechanism of the sector structure, and provide new insight into the spatio-temporal interactions in financial systems at the microscopic level.

Agent-based model with multi-level herding for complex financial systems

PubMed Central

Chen, Jun-Jie; Tan, Lei; Zheng, Bo

2015-01-01

In complex financial systems, the sector structure and volatility clustering are respectively important features of the spatial and temporal correlations. However, the microscopic generation mechanism of the sector structure is not yet understood. Especially, how to produce these two features in one model remains challenging. We introduce a novel interaction mechanism, i.e., the multi-level herding, in constructing an agent-based model to investigate the sector structure combined with volatility clustering. According to the previous market performance, agents trade in groups, and their herding behavior comprises the herding at stock, sector and market levels. Further, we propose methods to determine the key model parameters from historical market data, rather than from statistical fitting of the results. From the simulation, we obtain the sector structure and volatility clustering, as well as the eigenvalue distribution of the cross-correlation matrix, for the New York and Hong Kong stock exchanges. These properties are in agreement with the empirical ones. Our results quantitatively reveal that the multi-level herding is the microscopic generation mechanism of the sector structure, and provide new insight into the spatio-temporal interactions in financial systems at the microscopic level. PMID:25669427

Neonatal brainstem dysfunction risks infant social engagement

PubMed Central

Sopher, Koreen; Kurtzman, Lea; Galili, Giora; Feldman, Ruth; Kuint, Jacob

2013-01-01

The role of the brainstem in mediating social signaling in phylogenetic ancestral organisms has been demonstrated. Evidence for its involvement in social engagement in human infants may deepen the understanding of the evolutionary pathway of humans as social beings. In this longitudinal study, neonatal brainstem functioning was measured by auditory brainstem-evoked responses (ABRs) in 125 healthy neonates born prematurely before 35 weeks’ gestational age. At 4 months, infants were tested in a set of structured vignettes that required varying levels of social engagement and cardiac vagal tone was assessed. Data show that neonates with a disrupted I–V waveform, evident mostly by delayed wave V, exhibit shorter latencies to gaze averts in episodes involving direct face-to-face interactions but engage gaze as controls when interacting with masked agents or with agents whose faces are partly veiled by toys. Analysis of variance of infants’ social engagement with ABR, neonatal risk, maternal stress and cardiac vagal tone showed a main effect for ABR and an ABR by gestational age interaction. The integrity of brainstem transmission of sensory information during the final weeks of gestation may scaffold the development of social disengagement, thereby attesting to the brainstem's preserved evolutionary role in developing humans as social organisms prior to engaging in social encounters. PMID:22146141

The Interactive Minority Game: a Web-based investigation of human market interactions

NASA Astrophysics Data System (ADS)

Laureti, Paolo; Ruch, Peter; Wakeling, Joseph; Zhang, Yi-Cheng

2004-01-01

The unprecedented access offered by the World Wide Web brings with it the potential to gather huge amounts of data on human activities. Here we exploit this by using a toy model of financial markets, the Minority Game (MG), to investigate human speculative trading behaviour and information capacity. Hundreds of individuals have played a total of tens of thousands of game turns against computer-controlled agents in the Web-based Interactive Minority Game. The analytical understanding of the MG permits fine-tuning of the market situations encountered, allowing for investigation of human behaviour in a variety of controlled environments. In particular, our results indicate a transition in players’ decision-making, as the markets become more difficult, between deductive behaviour making use of short-term trends in the market, and highly repetitive behaviour that ignores entirely the market history, yet outperforms random decision-making.

Dynamic inverse models in human-cyber-physical systems

NASA Astrophysics Data System (ADS)

Robinson, Ryan M.; Scobee, Dexter R. R.; Burden, Samuel A.; Sastry, S. Shankar

2016-05-01

Human interaction with the physical world is increasingly mediated by automation. This interaction is characterized by dynamic coupling between robotic (i.e. cyber) and neuromechanical (i.e. human) decision-making agents. Guaranteeing performance of such human-cyber-physical systems will require predictive mathematical models of this dynamic coupling. Toward this end, we propose a rapprochement between robotics and neuromechanics premised on the existence of internal forward and inverse models in the human agent. We hypothesize that, in tele-robotic applications of interest, a human operator learns to invert automation dynamics, directly translating from desired task to required control input. By formulating the model inversion problem in the context of a tracking task for a nonlinear control system in control-a_ne form, we derive criteria for exponential tracking and show that the resulting dynamic inverse model generally renders a portion of the physical system state (i.e., the internal dynamics) unobservable from the human operator's perspective. Under stability conditions, we show that the human can achieve exponential tracking without formulating an estimate of the system's state so long as they possess an accurate model of the system's dynamics. These theoretical results are illustrated using a planar quadrotor example. We then demonstrate that the automation can intervene to improve performance of the tracking task by solving an optimal control problem. Performance is guaranteed to improve under the assumption that the human learns and inverts the dynamic model of the altered system. We conclude with a discussion of practical limitations that may hinder exact dynamic model inversion.

Exploring Agricultural Livelihood Transitions with an Agent-Based Virtual Laboratory: Global Forces to Local Decision-Making

PubMed Central

Magliocca, Nicholas R.; Brown, Daniel G.; Ellis, Erle C.

2013-01-01

Rural populations are undergoing rapid changes in both their livelihoods and land uses, with associated impacts on ecosystems, global biogeochemistry, and climate change. A primary challenge is, thus, to explain these shifts in terms of the actors and processes operating within a variety of land systems in order to understand how land users might respond locally to future changes in broader-scale environmental and economic conditions. Using ‘induced intensification’ theory as a benchmark, we develop a generalized agent-based model to investigate mechanistic explanations of relationships between agricultural intensity and population density, environmental suitability, and market influence. Land-use and livelihood decisions modeled from basic micro-economic theories generated spatial and temporal patterns of agricultural intensification consistent with predictions of induced intensification theory. Further, agent actions in response to conditions beyond those described by induced intensification theory were explored, revealing that interactions among environmental constraints, population pressure, and market influence may produce transitions to multiple livelihood regimes of varying market integration. The result is new hypotheses that could modify and enrich understanding of the classic relationship between agricultural intensity and population density. The strength of this agent-based model and the experimental results is the generalized form of the decision-making processes underlying land-use and livelihood transitions, creating the prospect of a virtual laboratory for systematically generating hypotheses of how agent decisions and interactions relate to observed land-use and livelihood patterns across diverse land systems. PMID:24039892

Developmental and Evolutionary Lexicon Acquisition in Cognitive Agents/Robots with Grounding Principle: A Short Review.

PubMed

Rasheed, Nadia; Amin, Shamsudin H M

2016-01-01

Grounded language acquisition is an important issue, particularly to facilitate human-robot interactions in an intelligent and effective way. The evolutionary and developmental language acquisition are two innovative and important methodologies for the grounding of language in cognitive agents or robots, the aim of which is to address current limitations in robot design. This paper concentrates on these two main modelling methods with the grounding principle for the acquisition of linguistic ability in cognitive agents or robots. This review not only presents a survey of the methodologies and relevant computational cognitive agents or robotic models, but also highlights the advantages and progress of these approaches for the language grounding issue.

Developmental and Evolutionary Lexicon Acquisition in Cognitive Agents/Robots with Grounding Principle: A Short Review

PubMed Central

Rasheed, Nadia; Amin, Shamsudin H. M.

2016-01-01

Grounded language acquisition is an important issue, particularly to facilitate human-robot interactions in an intelligent and effective way. The evolutionary and developmental language acquisition are two innovative and important methodologies for the grounding of language in cognitive agents or robots, the aim of which is to address current limitations in robot design. This paper concentrates on these two main modelling methods with the grounding principle for the acquisition of linguistic ability in cognitive agents or robots. This review not only presents a survey of the methodologies and relevant computational cognitive agents or robotic models, but also highlights the advantages and progress of these approaches for the language grounding issue. PMID:27069470

User Localization During Human-Robot Interaction

PubMed Central

Alonso-Martín, F.; Gorostiza, Javi F.; Malfaz, María; Salichs, Miguel A.

2012-01-01

This paper presents a user localization system based on the fusion of visual information and sound source localization, implemented on a social robot called Maggie. One of the main requisites to obtain a natural interaction between human-human and human-robot is an adequate spatial situation between the interlocutors, that is, to be orientated and situated at the right distance during the conversation in order to have a satisfactory communicative process. Our social robot uses a complete multimodal dialog system which manages the user-robot interaction during the communicative process. One of its main components is the presented user localization system. To determine the most suitable allocation of the robot in relation to the user, a proxemic study of the human-robot interaction is required, which is described in this paper. The study has been made with two groups of users: children, aged between 8 and 17, and adults. Finally, at the end of the paper, experimental results with the proposed multimodal dialog system are presented. PMID:23012577

Identifying and modeling the structural discontinuities of human interactions

NASA Astrophysics Data System (ADS)

Grauwin, Sebastian; Szell, Michael; Sobolevsky, Stanislav; Hövel, Philipp; Simini, Filippo; Vanhoof, Maarten; Smoreda, Zbigniew; Barabási, Albert-László; Ratti, Carlo

2017-04-01

The idea of a hierarchical spatial organization of society lies at the core of seminal theories in human geography that have strongly influenced our understanding of social organization. Along the same line, the recent availability of large-scale human mobility and communication data has offered novel quantitative insights hinting at a strong geographical confinement of human interactions within neighboring regions, extending to local levels within countries. However, models of human interaction largely ignore this effect. Here, we analyze several country-wide networks of telephone calls - both, mobile and landline - and in either case uncover a systematic decrease of communication induced by borders which we identify as the missing variable in state-of-the-art models. Using this empirical evidence, we propose an alternative modeling framework that naturally stylizes the damping effect of borders. We show that this new notion substantially improves the predictive power of widely used interaction models. This increases our ability to understand, model and predict social activities and to plan the development of infrastructures across multiple scales.

User localization during human-robot interaction.

PubMed

Alonso-Martín, F; Gorostiza, Javi F; Malfaz, María; Salichs, Miguel A

2012-01-01

This paper presents a user localization system based on the fusion of visual information and sound source localization, implemented on a social robot called Maggie. One of the main requisites to obtain a natural interaction between human-human and human-robot is an adequate spatial situation between the interlocutors, that is, to be orientated and situated at the right distance during the conversation in order to have a satisfactory communicative process. Our social robot uses a complete multimodal dialog system which manages the user-robot interaction during the communicative process. One of its main components is the presented user localization system. To determine the most suitable allocation of the robot in relation to the user, a proxemic study of the human-robot interaction is required, which is described in this paper. The study has been made with two groups of users: children, aged between 8 and 17, and adults. Finally, at the end of the paper, experimental results with the proposed multimodal dialog system are presented.

Identifying and modeling the structural discontinuities of human interactions

PubMed Central

Grauwin, Sebastian; Szell, Michael; Sobolevsky, Stanislav; Hövel, Philipp; Simini, Filippo; Vanhoof, Maarten; Smoreda, Zbigniew; Barabási, Albert-László; Ratti, Carlo

2017-01-01

The idea of a hierarchical spatial organization of society lies at the core of seminal theories in human geography that have strongly influenced our understanding of social organization. Along the same line, the recent availability of large-scale human mobility and communication data has offered novel quantitative insights hinting at a strong geographical confinement of human interactions within neighboring regions, extending to local levels within countries. However, models of human interaction largely ignore this effect. Here, we analyze several country-wide networks of telephone calls - both, mobile and landline - and in either case uncover a systematic decrease of communication induced by borders which we identify as the missing variable in state-of-the-art models. Using this empirical evidence, we propose an alternative modeling framework that naturally stylizes the damping effect of borders. We show that this new notion substantially improves the predictive power of widely used interaction models. This increases our ability to understand, model and predict social activities and to plan the development of infrastructures across multiple scales. PMID:28443647

Identifying and modeling the structural discontinuities of human interactions.

PubMed

Grauwin, Sebastian; Szell, Michael; Sobolevsky, Stanislav; Hövel, Philipp; Simini, Filippo; Vanhoof, Maarten; Smoreda, Zbigniew; Barabási, Albert-László; Ratti, Carlo

2017-04-26

The idea of a hierarchical spatial organization of society lies at the core of seminal theories in human geography that have strongly influenced our understanding of social organization. Along the same line, the recent availability of large-scale human mobility and communication data has offered novel quantitative insights hinting at a strong geographical confinement of human interactions within neighboring regions, extending to local levels within countries. However, models of human interaction largely ignore this effect. Here, we analyze several country-wide networks of telephone calls - both, mobile and landline - and in either case uncover a systematic decrease of communication induced by borders which we identify as the missing variable in state-of-the-art models. Using this empirical evidence, we propose an alternative modeling framework that naturally stylizes the damping effect of borders. We show that this new notion substantially improves the predictive power of widely used interaction models. This increases our ability to understand, model and predict social activities and to plan the development of infrastructures across multiple scales.

Spatial Hyperschematia without Spatial Neglect after Insulo-Thalamic Disconnection

PubMed Central

Saj, Arnaud; Wilcke, Juliane C.; Gschwind, Markus; Emond, Héloïse; Assal, Frédéric

2013-01-01

Different spatial representations are not stored as a single multipurpose map in the brain. Right brain-damaged patients can show a distortion, a compression of peripersonal and extrapersonal space. Here we report the case of a patient with a right insulo-thalamic disconnection without spatial neglect. The patient, compared with 10 healthy control subjects, showed a constant and reliable increase of her peripersonal and extrapersonal egocentric space representations - that we named spatial hyperschematia - yet left her allocentric space representations intact. This striking dissociation shows that our interactions with the surrounding world are represented and processed modularly in the human brain, depending on their frame of reference. PMID:24302992

The Influence of Spatial Configuration of Residential Area and Vector Populations on Dengue Incidence Patterns in an Individual-Level Transmission Model.

PubMed

Kang, Jeon-Young; Aldstadt, Jared

2017-07-15

Dengue is a mosquito-borne infectious disease that is endemic in tropical and subtropical countries. Many individual-level simulation models have been developed to test hypotheses about dengue virus transmission. Often these efforts assume that human host and mosquito vector populations are randomly or uniformly distributed in the environment. Although, the movement of mosquitoes is affected by spatial configuration of buildings and mosquito populations are highly clustered in key buildings, little research has focused on the influence of the local built environment in dengue transmission models. We developed an agent-based model of dengue transmission in a village setting to test the importance of using realistic environments in individual-level models of dengue transmission. The results from one-way ANOVA analysis of simulations indicated that the differences between scenarios in terms of infection rates as well as serotype-specific dominance are statistically significant. Specifically, the infection rates in scenarios of a realistic environment are more variable than those of a synthetic spatial configuration. With respect to dengue serotype-specific cases, we found that a single dengue serotype is more often dominant in realistic environments than in synthetic environments. An agent-based approach allows a fine-scaled analysis of simulated dengue incidence patterns. The results provide a better understanding of the influence of spatial heterogeneity on dengue transmission at a local scale.

[Chemical weapons and chemical terrorism].

PubMed

Nakamura, Katsumi

2005-10-01

Chemical Weapons are kind of Weapons of Mass Destruction (WMD). They were used large quantities in WWI. Historically, large quantities usage like WWI was not recorded, but small usage has appeared now and then. Chemical weapons are so called "Nuclear weapon for poor countrys" because it's very easy to produce/possession being possible. They are categorized (1) Nerve Agents, (2) Blister Agents, (3) Cyanide (blood) Agents, (4) Pulmonary Agents, (5) Incapacitating Agents (6) Tear Agents from the viewpoint of human body interaction. In 1997 the Chemical Weapons Convention has taken effect. It prohibits chemical weapons development/production, and Organization for the Prohibition of Chemical Weapons (OPCW) verification regime contributes to the chemical weapons disposal. But possibility of possession/use of weapons of mass destruction by terrorist group represented in one by Matsumoto and Tokyo Subway Sarin Attack, So new chemical terrorism countermeasures are necessary.

Social interaction enhances motor resonance for observed human actions.

PubMed

Hogeveen, Jeremy; Obhi, Sukhvinder S

2012-04-25

Understanding the neural basis of social behavior has become an important goal for cognitive neuroscience and a key aim is to link neural processes observed in the laboratory to more naturalistic social behaviors in real-world contexts. Although it is accepted that mirror mechanisms contribute to the occurrence of motor resonance (MR) and are common to action execution, observation, and imitation, questions remain about mirror (and MR) involvement in real social behavior and in processing nonhuman actions. To determine whether social interaction primes the MR system, groups of participants engaged or did not engage in a social interaction before observing human or robotic actions. During observation, MR was assessed via motor-evoked potentials elicited with transcranial magnetic stimulation. Compared with participants who did not engage in a prior social interaction, participants who engaged in the social interaction showed a significant increase in MR for human actions. In contrast, social interaction did not increase MR for robot actions. Thus, naturalistic social interaction and laboratory action observation tasks appear to involve common MR mechanisms, and recent experience tunes the system to particular agent types.

Agent-based model of diffusion of N-acyl homoserine lactones in a multicellular environment of Pseudomonas aeruginosa and Candida albicans.

PubMed

Pérez-Rodríguez, Gael; Dias, Sónia; Pérez-Pérez, Martín; Fdez-Riverola, Florentino; Azevedo, Nuno F; Lourenço, Anália

2018-03-08

Experimental incapacity to track microbe-microbe interactions in structures like biofilms, and the complexity inherent to the mathematical modelling of those interactions, raises the need for feasible, alternative modelling approaches. This work proposes an agent-based representation of the diffusion of N-acyl homoserine lactones (AHL) in a multicellular environment formed by Pseudomonas aeruginosa and Candida albicans. Depending on the spatial location, C. albicans cells were variably exposed to AHLs, an observation that might help explain why phenotypic switching of individual cells in biofilms occurred at different time points. The simulation and algebraic results were similar for simpler scenarios, although some statistical differences could be observed (p < 0.05). The model was also successfully applied to a more complex scenario representing a small multicellular environment containing C. albicans and P. aeruginosa cells encased in a 3-D matrix. Further development of this model may help create a predictive tool to depict biofilm heterogeneity at the single-cell level.

A qualitative method for collecting spatial data on important places for recreation, livelihoods, and ecological meanings: Integrating focus groups with public participation geographic information systems

Treesearch

Damon R. Lowery; Wayde C. Morse

2013-01-01

The association between humans and their environments is highly interactive, with humans bound to the landscapes and landscapes subject to the actions of humans. Sense of place is a concept used to describe the relationships that exist, bonds that form, and the meanings that humans ascribe to landscapes. This article builds on pre- vious qualitative research using...

Exploration of Metaphorical and Contextual Affect Sensing in a Virtual Improvisational Drama

NASA Astrophysics Data System (ADS)

Zhang, Li

Real-time affect detection from open-ended text-based dialogue is challenging but essential for the building of effective intelligent user interfaces. In this paper, we report updated developments of an affect detection model from text, including affect detection from one particular type of metaphorical affective expression (cooking metaphor) and affect detection based on context. The overall affect detection model has been embedded in an intelligent conversational AI agent interacting with human users under loose scenarios. Evaluation for the updated affect detection component is also provided. Our work contributes to the conference themes on engagement and emotion, interactions in games, storytelling and narrative in education, and virtual characters/agents development.

In Silico Identification of Proteins Associated with Drug-induced Liver Injury Based on the Prediction of Drug-target Interactions.

PubMed

Ivanov, Sergey; Semin, Maxim; Lagunin, Alexey; Filimonov, Dmitry; Poroikov, Vladimir

2017-07-01

Drug-induced liver injury (DILI) is the leading cause of acute liver failure as well as one of the major reasons for drug withdrawal from clinical trials and the market. Elucidation of molecular interactions associated with DILI may help to detect potentially hazardous pharmacological agents at the early stages of drug development. The purpose of our study is to investigate which interactions with specific human protein targets may cause DILI. Prediction of interactions with 1534 human proteins was performed for the dataset with information about 699 drugs, which were divided into three categories of DILI: severe (178 drugs), moderate (310 drugs) and without DILI (211 drugs). Based on the comparison of drug-target interactions predicted for different drugs' categories and interpretation of those results using clustering, Gene Ontology, pathway and gene expression analysis, we identified 61 protein targets associated with DILI. Most of the revealed proteins were linked with hepatocytes' death caused by disruption of vital cellular processes, as well as the emergence of inflammation in the liver. It was found that interaction of a drug with the identified targets is the essential molecular mechanism of the severe DILI for the most of the considered pharmaceuticals. Thus, pharmaceutical agents interacting with many of the identified targets may be considered as candidates for filtering out at the early stages of drug research. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Conversational sensing

NASA Astrophysics Data System (ADS)

Preece, Alun; Gwilliams, Chris; Parizas, Christos; Pizzocaro, Diego; Bakdash, Jonathan Z.; Braines, Dave

2014-05-01

Recent developments in sensing technologies, mobile devices and context-aware user interfaces have made it pos- sible to represent information fusion and situational awareness for Intelligence, Surveillance and Reconnaissance (ISR) activities as a conversational process among actors at or near the tactical edges of a network. Motivated by use cases in the domain of Company Intelligence Support Team (CoIST) tasks, this paper presents an approach to information collection, fusion and sense-making based on the use of natural language (NL) and controlled nat- ural language (CNL) to support richer forms of human-machine interaction. The approach uses a conversational protocol to facilitate a ow of collaborative messages from NL to CNL and back again in support of interactions such as: turning eyewitness reports from human observers into actionable information (from both soldier and civilian sources); fusing information from humans and physical sensors (with associated quality metadata); and assisting human analysts to make the best use of available sensing assets in an area of interest (governed by man- agement and security policies). CNL is used as a common formal knowledge representation for both machine and human agents to support reasoning, semantic information fusion and generation of rationale for inferences, in ways that remain transparent to human users. Examples are provided of various alternative styles for user feedback, including NL, CNL and graphical feedback. A pilot experiment with human subjects shows that a prototype conversational agent is able to gather usable CNL information from untrained human subjects.

Persistent and High-Level Expression of Human Liver Prolidase in Vivo in Mice Using Adenovirus

DTIC Science & Technology

2013-01-01

types of nerve agents and pesticide compounds, is mostly exported into the circulation [11]. Similarly, human paraoxonase1, a promising enzyme in the...of human butyrylcholinesetrase results in persistent high-level transgene expression in vivo, Chem. Biol. Interact. 175 (2008) 327– 331. [11] K...paraoxonase1 gene transfer to provide protection against the toxicity of the organophosphorus pesticide toxicant diazoxon, Gene Ther. 18 (2011) 250–257. [14

Cognitive Model of Trust Dynamics Predicts Human Behavior within and between Two Games of Strategic Interaction with Computerized Confederate Agents

PubMed Central

Collins, Michael G.; Juvina, Ion; Gluck, Kevin A.

2016-01-01

When playing games of strategic interaction, such as iterated Prisoner's Dilemma and iterated Chicken Game, people exhibit specific within-game learning (e.g., learning a game's optimal outcome) as well as transfer of learning between games (e.g., a game's optimal outcome occurring at a higher proportion when played after another game). The reciprocal trust players develop during the first game is thought to mediate transfer of learning effects. Recently, a computational cognitive model using a novel trust mechanism has been shown to account for human behavior in both games, including the transfer between games. We present the results of a study in which we evaluate the model's a priori predictions of human learning and transfer in 16 different conditions. The model's predictive validity is compared against five model variants that lacked a trust mechanism. The results suggest that a trust mechanism is necessary to explain human behavior across multiple conditions, even when a human plays against a non-human agent. The addition of a trust mechanism to the other learning mechanisms within the cognitive architecture, such as sequence learning, instance-based learning, and utility learning, leads to better prediction of the empirical data. It is argued that computational cognitive modeling is a useful tool for studying trust development, calibration, and repair. PMID:26903892

Modelling the perennial energy crop market: the role of spatial diffusion

PubMed Central

Alexander, Peter; Moran, Dominic; Rounsevell, Mark D. A.; Smith, Pete

2013-01-01

Biomass produced from energy crops, such as Miscanthus and short rotation coppice is expected to contribute to renewable energy targets, but the slower than anticipated development of the UK market implies the need for greater understanding of the factors that govern adoption. Here, we apply an agent-based model of the UK perennial energy crop market, including the contingent interaction of supply and demand, to understand the spatial and temporal dynamics of energy crop adoption. Results indicate that perennial energy crop supply will be between six and nine times lower than previously published, because of time lags in adoption arising from a spatial diffusion process. The model simulates time lags of at least 20 years, which is supported empirically by the analogue of oilseed rape adoption in the UK from the 1970s. This implies the need to account for time lags arising from spatial diffusion in evaluating land-use change, climate change (mitigation or adaptation) or the adoption of novel technologies. PMID:24026474

Modelling the perennial energy crop market: the role of spatial diffusion.

PubMed

Alexander, Peter; Moran, Dominic; Rounsevell, Mark D A; Smith, Pete

2013-11-06

Biomass produced from energy crops, such as Miscanthus and short rotation coppice is expected to contribute to renewable energy targets, but the slower than anticipated development of the UK market implies the need for greater understanding of the factors that govern adoption. Here, we apply an agent-based model of the UK perennial energy crop market, including the contingent interaction of supply and demand, to understand the spatial and temporal dynamics of energy crop adoption. Results indicate that perennial energy crop supply will be between six and nine times lower than previously published, because of time lags in adoption arising from a spatial diffusion process. The model simulates time lags of at least 20 years, which is supported empirically by the analogue of oilseed rape adoption in the UK from the 1970s. This implies the need to account for time lags arising from spatial diffusion in evaluating land-use change, climate change (mitigation or adaptation) or the adoption of novel technologies.

Aptazyme-embedded guide RNAs enable ligand-responsive genome editing and transcriptional activation

PubMed Central

Tang, Weixin; Hu, Johnny H.; Liu, David R.

2017-01-01

Programmable sequence-specific genome editing agents such as CRISPR-Cas9 have greatly advanced our ability to manipulate the human genome. Although canonical forms of genome-editing agents and programmable transcriptional regulators are constitutively active, precise temporal and spatial control over genome editing and transcriptional regulation activities would enable the more selective and potentially safer use of these powerful technologies. Here, by incorporating ligand-responsive self-cleaving catalytic RNAs (aptazymes) into guide RNAs, we developed a set of aptazyme-embedded guide RNAs that enable small molecule-controlled nuclease-mediated genome editing and small molecule-controlled base editing, as well as small molecule-dependent transcriptional activation in mammalian cells. PMID:28656978

Dissecting the chromatin interactome of microRNA genes.

PubMed

Chen, Dijun; Fu, Liang-Yu; Zhang, Zhao; Li, Guoliang; Zhang, Hang; Jiang, Li; Harrison, Andrew P; Shanahan, Hugh P; Klukas, Christian; Zhang, Hong-Yu; Ruan, Yijun; Chen, Ling-Ling; Chen, Ming

2014-03-01

Our knowledge of the role of higher-order chromatin structures in transcription of microRNA genes (MIRs) is evolving rapidly. Here we investigate the effect of 3D architecture of chromatin on the transcriptional regulation of MIRs. We demonstrate that MIRs have transcriptional features that are similar to protein-coding genes. RNA polymerase II-associated ChIA-PET data reveal that many groups of MIRs and protein-coding genes are organized into functionally compartmentalized chromatin communities and undergo coordinated expression when their genomic loci are spatially colocated. We observe that MIRs display widespread communication in those transcriptionally active communities. Moreover, miRNA-target interactions are significantly enriched among communities with functional homogeneity while depleted from the same community from which they originated, suggesting MIRs coordinating function-related pathways at posttranscriptional level. Further investigation demonstrates the existence of spatial MIR-MIR chromatin interacting networks. We show that groups of spatially coordinated MIRs are frequently from the same family and involved in the same disease category. The spatial interaction network possesses both common and cell-specific subnetwork modules that result from the spatial organization of chromatin within different cell types. Together, our study unveils an entirely unexplored layer of MIR regulation throughout the human genome that links the spatial coordination of MIRs to their co-expression and function.

Interaction of Experiential and Neurological Factors in the Patterning of Human Abilities: The Question of Sex Differences in 'Right Hemisphere' Skills.

ERIC Educational Resources Information Center

Harris, Lauren Jay

Sex differences in cerebral organization and functioning, and the apparent superiority of males in spatial ability are examined in this paper. Attention is given to several kinds of cognitive and perceptual tasks in which sex differences in spatial ability have been shown to exist; among these are tasks involving: (1) recall and detection of…

Evolution of direct reciprocity under uncertainty can explain human generosity in one-shot encounters

PubMed Central

Delton, Andrew W.; Krasnow, Max M.; Cosmides, Leda; Tooby, John

2011-01-01

Are humans too generous? The discovery that subjects choose to incur costs to allocate benefits to others in anonymous, one-shot economic games has posed an unsolved challenge to models of economic and evolutionary rationality. Using agent-based simulations, we show that such generosity is the necessary byproduct of selection on decision systems for regulating dyadic reciprocity under conditions of uncertainty. In deciding whether to engage in dyadic reciprocity, these systems must balance (i) the costs of mistaking a one-shot interaction for a repeated interaction (hence, risking a single chance of being exploited) with (ii) the far greater costs of mistaking a repeated interaction for a one-shot interaction (thereby precluding benefits from multiple future cooperative interactions). This asymmetry builds organisms naturally selected to cooperate even when exposed to cues that they are in one-shot interactions. PMID:21788489

Evolution of direct reciprocity under uncertainty can explain human generosity in one-shot encounters.

PubMed

Delton, Andrew W; Krasnow, Max M; Cosmides, Leda; Tooby, John

2011-08-09

Are humans too generous? The discovery that subjects choose to incur costs to allocate benefits to others in anonymous, one-shot economic games has posed an unsolved challenge to models of economic and evolutionary rationality. Using agent-based simulations, we show that such generosity is the necessary byproduct of selection on decision systems for regulating dyadic reciprocity under conditions of uncertainty. In deciding whether to engage in dyadic reciprocity, these systems must balance (i) the costs of mistaking a one-shot interaction for a repeated interaction (hence, risking a single chance of being exploited) with (ii) the far greater costs of mistaking a repeated interaction for a one-shot interaction (thereby precluding benefits from multiple future cooperative interactions). This asymmetry builds organisms naturally selected to cooperate even when exposed to cues that they are in one-shot interactions.

Simple spatial scaling rules behind complex cities.

PubMed

Li, Ruiqi; Dong, Lei; Zhang, Jiang; Wang, Xinran; Wang, Wen-Xu; Di, Zengru; Stanley, H Eugene

2017-11-28

Although most of wealth and innovation have been the result of human interaction and cooperation, we are not yet able to quantitatively predict the spatial distributions of three main elements of cities: population, roads, and socioeconomic interactions. By a simple model mainly based on spatial attraction and matching growth mechanisms, we reveal that the spatial scaling rules of these three elements are in a consistent framework, which allows us to use any single observation to infer the others. All numerical and theoretical results are consistent with empirical data from ten representative cities. In addition, our model can also provide a general explanation of the origins of the universal super- and sub-linear aggregate scaling laws and accurately predict kilometre-level socioeconomic activity. Our work opens a new avenue for uncovering the evolution of cities in terms of the interplay among urban elements, and it has a broad range of applications.

Interacting Social and Environmental Predictors for the Spatial Distribution of Conservation Lands

PubMed Central

Baldwin, Robert F.; Leonard, Paul B.

2015-01-01

Conservation decisions should be evaluated for how they meet conservation goals at multiple spatial extents. Conservation easements are land use decisions resulting from a combination of social and environmental conditions. An emerging area of research is the evaluation of spatial distribution of easements and their spatial correlates. We tested the relative influence of interacting social and environmental variables on the spatial distribution of conservation easements by ownership category and conservation status. For the Appalachian region of the United States, an area with a long history of human occupation and complex land uses including public-private conservation, we found that settlement, economic, topographic, and environmental data associated with spatial distribution of easements (N = 4813). Compared to random locations, easements were more likely to be found in lower elevations, in areas of greater agricultural productivity, farther from public protected areas, and nearer other human features. Analysis of ownership and conservation status revealed sources of variation, with important differences between local and state government ownerships relative to non-governmental organizations (NGOs), and among U.S. Geological Survey (USGS) GAP program status levels. NGOs were more likely to have easements nearer protected areas, and higher conservation status, while local governments held easements closer to settlement, and on lands of greater agricultural potential. Logistic interactions revealed environmental variables having effects modified by social correlates, and the strongest predictors overall were social (distance to urban area, median household income, housing density, distance to land trust office). Spatial distribution of conservation lands may be affected by geographic area of influence of conservation groups, suggesting that multi-scale conservation planning strategies may be necessary to satisfy local and regional needs for reserve networks. Our results support previous findings and provide an ecoregion-scale view that conservation easements may provide, at local scales, conservation functions on productive, more developable lands. Conservation easements may complement functions of public protected areas but more research should examine relative landscape-level ecological functions of both forms of protection. PMID:26465155

Interacting Social and Environmental Predictors for the Spatial Distribution of Conservation Lands.

PubMed

Baldwin, Robert F; Leonard, Paul B

2015-01-01

Conservation decisions should be evaluated for how they meet conservation goals at multiple spatial extents. Conservation easements are land use decisions resulting from a combination of social and environmental conditions. An emerging area of research is the evaluation of spatial distribution of easements and their spatial correlates. We tested the relative influence of interacting social and environmental variables on the spatial distribution of conservation easements by ownership category and conservation status. For the Appalachian region of the United States, an area with a long history of human occupation and complex land uses including public-private conservation, we found that settlement, economic, topographic, and environmental data associated with spatial distribution of easements (N = 4813). Compared to random locations, easements were more likely to be found in lower elevations, in areas of greater agricultural productivity, farther from public protected areas, and nearer other human features. Analysis of ownership and conservation status revealed sources of variation, with important differences between local and state government ownerships relative to non-governmental organizations (NGOs), and among U.S. Geological Survey (USGS) GAP program status levels. NGOs were more likely to have easements nearer protected areas, and higher conservation status, while local governments held easements closer to settlement, and on lands of greater agricultural potential. Logistic interactions revealed environmental variables having effects modified by social correlates, and the strongest predictors overall were social (distance to urban area, median household income, housing density, distance to land trust office). Spatial distribution of conservation lands may be affected by geographic area of influence of conservation groups, suggesting that multi-scale conservation planning strategies may be necessary to satisfy local and regional needs for reserve networks. Our results support previous findings and provide an ecoregion-scale view that conservation easements may provide, at local scales, conservation functions on productive, more developable lands. Conservation easements may complement functions of public protected areas but more research should examine relative landscape-level ecological functions of both forms of protection.

Invisible excess of sense in social interaction

PubMed Central

Koubová, Alice

2014-01-01

The question of visibility and invisibility in social understanding is examined here. First, the phenomenological account of expressive phenomena and key ideas of the participatory sense-making theory are presented with regard to the issue of visibility. These accounts plead for the principal visibility of agents in interaction. Although participatory sense-making does not completely rule out the existence of opacity and invisible aspects of agents in interaction, it assumes the capacity of agents to integrate disruptions, opacity and misunderstandings in mutual modulation. Invisibility is classified as the dialectical counterpart of visibility, i.e., as a lack of sense whereby the dynamics of perpetual asking, of coping with each other and of improvements in interpretation are brought into play. By means of empirical exemplification this article aims at demonstrating aspects of invisibility in social interaction which complement the enactive interpretation. Without falling back into Cartesianism, it shows through dramaturgical analysis of a practice called “(Inter)acting with the inner partner” that social interaction includes elements of opacity and invisibility whose role is performative. This means that opacity is neither an obstacle to be overcome with more precise understanding nor a lack of meaning, but rather an excess of sense, a “hiddenness” of something real that has an “active power” (Merleau-Ponty). In this way it contributes to on-going social understanding as a hidden potentiality that naturally enriches, amplifies and in part constitutes human participation in social interactions. It is also shown here that this invisible excess of sense already functions on the level of self-relationship due to the essential self-opacity and self-alterity of each agent of social interaction. The analysis consequently raises two issues: the question of the enactive ethical stance toward the alterity of the other and the question of the autonomy of the self-opaque agent. PMID:25324798

Using Motivational Interviewing to reduce threats in conversations about environmental behavior

PubMed Central

Klonek, Florian E.; Güntner, Amelie V.; Lehmann-Willenbrock, Nale; Kauffeld, Simone

2015-01-01

Human behavior contributes to a waste of environmental resources and our society is looking for ways to reduce this problem. However, humans may perceive feedback about their environmental behavior as threatening. According to self-determination theory (SDT), threats decrease intrinsic motivation for behavior change. According to self-affirmation theory (SAT), threats can harm individuals’ self-integrity. Therefore, individuals should show self-defensive biases, e.g., in terms of presenting counter-arguments when presented with environmental behavior change. The current study examines how change recipients respond to threats from change agents in interactions about environmental behavior change. Moreover, we investigate how Motivational Interviewing (MI) — an intervention aimed at increasing intrinsic motivation — can reduce threats at both the social and cognitive level. We videotaped 68 dyadic interactions with change agents who either did or did not use MI (control group). We coded agents verbal threats and recipients’ verbal expressions of motivation. Recipients also rated agents’ level of confrontation and empathy (i.e., cognitive reactions). As hypothesized, threats were significantly lower when change agents used MI. Perceived confrontations converged with observable social behavior of change agents in both groups. Moreover, behavioral threats showed a negative association with change recipients’ expressed motivation (i.e., reasons to change). Contrary to our expectations, we found no relation between change agents’ verbal threats and change recipients’ verbally expressed self-defenses (i.e., sustain talk). Our results imply that MI reduces the adverse impact of threats in conversations about environmental behavior change on both the social and cognitive level. We discuss theoretical implications of our study in the context of SAT and SDT and suggest practical implications for environmental change agents in organizations. PMID:26257676

Numerical Relations and Skill Level Constrain Co-Adaptive Behaviors of Agents in Sports Teams

PubMed Central

Silva, Pedro; Travassos, Bruno; Vilar, Luís; Aguiar, Paulo; Davids, Keith; Araújo, Duarte; Garganta, Júlio

2014-01-01

Similar to other complex systems in nature (e.g., a hunting pack, flocks of birds), sports teams have been modeled as social neurobiological systems in which interpersonal coordination tendencies of agents underpin team swarming behaviors. Swarming is seen as the result of agent co-adaptation to ecological constraints of performance environments by collectively perceiving specific possibilities for action (affordances for self and shared affordances). A major principle of invasion team sports assumed to promote effective performance is to outnumber the opposition (creation of numerical overloads) during different performance phases (attack and defense) in spatial regions adjacent to the ball. Such performance principles are assimilated by system agents through manipulation of numerical relations between teams during training in order to create artificially asymmetrical performance contexts to simulate overloaded and underloaded situations. Here we evaluated effects of different numerical relations differentiated by agent skill level, examining emergent inter-individual, intra- and inter-team coordination. Groups of association football players (national – NLP and regional-level – RLP) participated in small-sided and conditioned games in which numerical relations between system agents were manipulated (5v5, 5v4 and 5v3). Typical grouping tendencies in sports teams (major ranges, stretch indices, distances of team centers to goals and distances between the teams' opposing line-forces in specific team sectors) were recorded by plotting positional coordinates of individual agents through continuous GPS tracking. Results showed that creation of numerical asymmetries during training constrained agents' individual dominant regions, the underloaded teams' compactness and each team's relative position on-field, as well as distances between specific team sectors. We also observed how skill level impacted individual and team coordination tendencies. Data revealed emergence of co-adaptive behaviors between interacting neurobiological social system agents in the context of sport performance. Such observations have broader implications for training design involving manipulations of numerical relations between interacting members of social collectives. PMID:25191870

Numerical relations and skill level constrain co-adaptive behaviors of agents in sports teams.

PubMed

Silva, Pedro; Travassos, Bruno; Vilar, Luís; Aguiar, Paulo; Davids, Keith; Araújo, Duarte; Garganta, Júlio

2014-01-01

Similar to other complex systems in nature (e.g., a hunting pack, flocks of birds), sports teams have been modeled as social neurobiological systems in which interpersonal coordination tendencies of agents underpin team swarming behaviors. Swarming is seen as the result of agent co-adaptation to ecological constraints of performance environments by collectively perceiving specific possibilities for action (affordances for self and shared affordances). A major principle of invasion team sports assumed to promote effective performance is to outnumber the opposition (creation of numerical overloads) during different performance phases (attack and defense) in spatial regions adjacent to the ball. Such performance principles are assimilated by system agents through manipulation of numerical relations between teams during training in order to create artificially asymmetrical performance contexts to simulate overloaded and underloaded situations. Here we evaluated effects of different numerical relations differentiated by agent skill level, examining emergent inter-individual, intra- and inter-team coordination. Groups of association football players (national--NLP and regional-level--RLP) participated in small-sided and conditioned games in which numerical relations between system agents were manipulated (5v5, 5v4 and 5v3). Typical grouping tendencies in sports teams (major ranges, stretch indices, distances of team centers to goals and distances between the teams' opposing line-forces in specific team sectors) were recorded by plotting positional coordinates of individual agents through continuous GPS tracking. Results showed that creation of numerical asymmetries during training constrained agents' individual dominant regions, the underloaded teams' compactness and each team's relative position on-field, as well as distances between specific team sectors. We also observed how skill level impacted individual and team coordination tendencies. Data revealed emergence of co-adaptive behaviors between interacting neurobiological social system agents in the context of sport performance. Such observations have broader implications for training design involving manipulations of numerical relations between interacting members of social collectives.

Intelligent automated surface grid generation

NASA Technical Reports Server (NTRS)

Yao, Ke-Thia; Gelsey, Andrew

1995-01-01

The goal of our research is to produce a flexible, general grid generator for automated use by other programs, such as numerical optimizers. The current trend in the gridding field is toward interactive gridding. Interactive gridding more readily taps into the spatial reasoning abilities of the human user through the use of a graphical interface with a mouse. However, a sometimes fruitful approach to generating new designs is to apply an optimizer with shape modification operators to improve an initial design. In order for this approach to be useful, the optimizer must be able to automatically grid and evaluate the candidate designs. This paper describes and intelligent gridder that is capable of analyzing the topology of the spatial domain and predicting approximate physical behaviors based on the geometry of the spatial domain to automatically generate grids for computational fluid dynamics simulators. Typically gridding programs are given a partitioning of the spatial domain to assist the gridder. Our gridder is capable of performing this partitioning. This enables the gridder to automatically grid spatial domains of wide range of configurations.

Efficacy of Antiretroviral Agents against Murine Replication-Competent Retrovirus Infection in Human Cells

PubMed Central

Powell, Sharon K.; Artlip, Moria; Kaloss, Michele; Brazinski, Scott; Lyons, Russette; McGarrity, Gerard J.; Otto, Edward

1999-01-01

Retroviral vectors for gene therapy are designed to minimize the occurrence of replication-competent retrovirus (RCR); nonetheless, it is possible that a vector-derived RCR could establish an infection in a patient. Since the efficacy of antiretroviral agents can be impacted by interactions between virus, host cell, and drug, five commonly used antiretroviral drugs were evaluated for their abilities to inhibit the replication of a murine leukemia virus (MLV)-derived RCR in human cells. The results obtained indicate that the combination of nucleoside analogs zidovudine and dideoxyinosine with the protease inhibitor indinavir effectively inhibits MLV-derived RCR replication in three human cell lines. In addition, MLV-derived RCR was found to be inherently resistant to the nucleoside analogs lamivudine and stavudine, suggesting that mutations conferring resistance to nucleoside analogs in human immunodeficiency virus type 1 have the same effect even in an alternative viral backbone. PMID:10482636

Experimental econophysics: Complexity, self-organization, and emergent properties

NASA Astrophysics Data System (ADS)

Huang, J. P.

2015-03-01

Experimental econophysics is concerned with statistical physics of humans in the laboratory, and it is based on controlled human experiments developed by physicists to study some problems related to economics or finance. It relies on controlled human experiments in the laboratory together with agent-based modeling (for computer simulations and/or analytical theory), with an attempt to reveal the general cause-effect relationship between specific conditions and emergent properties of real economic/financial markets (a kind of complex adaptive systems). Here I review the latest progress in the field, namely, stylized facts, herd behavior, contrarian behavior, spontaneous cooperation, partial information, and risk management. Also, I highlight the connections between such progress and other topics of traditional statistical physics. The main theme of the review is to show diverse emergent properties of the laboratory markets, originating from self-organization due to the nonlinear interactions among heterogeneous humans or agents (complexity).

Molecular interaction of novel benzothiazolyl triazolium analogues with calf thymus DNA and HSA-their biological investigation as potent antimicrobial agents.

PubMed

Maddili, Swetha K; Katla, Ramesh; Kannekanti, Vijaya Kumar; Bejjanki, Naveen Kumar; Tuniki, Balaraju; Zhou, Cheng-He; Gandham, Himabindu

2018-04-25

The binding behaviour between calf thymus DNA and synthesized benzothiazolyl triazolium derivatives as potent antimicrobial agents was explored by means of spectroscopic applications together with molecular docking study at the sub-domain IIA, binding site I of human serum albumin (HSA). Most of the synthesized derivatives presented significant antimicrobial inhibition when compared with the clinical Norfloxacin, Chloromycin, and Fluconazole. In particular, compound 5q presented efficient anti-Bacillus subtilis, anti-Escherichia coli, anti-Salmonella typhi, and anti-Psuedomonas aeruginosa activity with low MIC values of 2-8 μg/mL which were relatively superior to the reference drugs. The preliminarily investigation of interaction studies with calf thymus DNA demonstrated that the most active compound 5q could effectively intercalate into DNA to form 5q-DNA complex. Further investigations revealed that human serum albumin could effectively transport compound 5q while molecular modelling studies with good docking score showed that hydrophobic interactions as well as hydrogen bonds played a significant role in the interaction of compound 5q with HSA. In addition, the cytotoxic investigation carried out on four different cancerous cell lines (3 human cell lines and 1 murine cell lines) by MTT assay presented that compound 5n is active against MDA cell lines with IC 50 values less than 100 μg/mL. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

Laura Jackson, Ph.D.

EPA Pesticide Factsheets

Research Biologist with the EPA. Her current work involves linking natural and built infrastructure to human health and well-being at multiple spatial scales, in order to develop interpretive maps and analytical tools for an interactive, web-based Atlas.

Approximate spatial reasoning

NASA Technical Reports Server (NTRS)

Dutta, Soumitra

1988-01-01

Much of human reasoning is approximate in nature. Formal models of reasoning traditionally try to be precise and reject the fuzziness of concepts in natural use and replace them with non-fuzzy scientific explicata by a process of precisiation. As an alternate to this approach, it has been suggested that rather than regard human reasoning processes as themselves approximating to some more refined and exact logical process that can be carried out with mathematical precision, the essence and power of human reasoning is in its capability to grasp and use inexact concepts directly. This view is supported by the widespread fuzziness of simple everyday terms (e.g., near tall) and the complexity of ordinary tasks (e.g., cleaning a room). Spatial reasoning is an area where humans consistently reason approximately with demonstrably good results. Consider the case of crossing a traffic intersection. We have only an approximate idea of the locations and speeds of various obstacles (e.g., persons and vehicles), but we nevertheless manage to cross such traffic intersections without any harm. The details of our mental processes which enable us to carry out such intricate tasks in such apparently simple manner are not well understood. However, it is that we try to incorporate such approximate reasoning techniques in our computer systems. Approximate spatial reasoning is very important for intelligent mobile agents (e.g., robots), specially for those operating in uncertain or unknown or dynamic domains.

Advancing the integration of spatial data to map human and natural drivers on coral reefs

PubMed Central

Gove, Jamison M.; Walecka, Hilary R.; Donovan, Mary K.; Williams, Gareth J.; Jouffray, Jean-Baptiste; Crowder, Larry B.; Erickson, Ashley; Falinski, Kim; Friedlander, Alan M.; Kappel, Carrie V.; Kittinger, John N.; McCoy, Kaylyn; Norström, Albert; Nyström, Magnus; Oleson, Kirsten L. L.; Stamoulis, Kostantinos A.; White, Crow; Selkoe, Kimberly A.

2018-01-01

A major challenge for coral reef conservation and management is understanding how a wide range of interacting human and natural drivers cumulatively impact and shape these ecosystems. Despite the importance of understanding these interactions, a methodological framework to synthesize spatially explicit data of such drivers is lacking. To fill this gap, we established a transferable data synthesis methodology to integrate spatial data on environmental and anthropogenic drivers of coral reefs, and applied this methodology to a case study location–the Main Hawaiian Islands (MHI). Environmental drivers were derived from time series (2002–2013) of climatological ranges and anomalies of remotely sensed sea surface temperature, chlorophyll-a, irradiance, and wave power. Anthropogenic drivers were characterized using empirically derived and modeled datasets of spatial fisheries catch, sedimentation, nutrient input, new development, habitat modification, and invasive species. Within our case study system, resulting driver maps showed high spatial heterogeneity across the MHI, with anthropogenic drivers generally greatest and most widespread on O‘ahu, where 70% of the state’s population resides, while sedimentation and nutrients were dominant in less populated islands. Together, the spatial integration of environmental and anthropogenic driver data described here provides a first-ever synthetic approach to visualize how the drivers of coral reef state vary in space and demonstrates a methodological framework for implementation of this approach in other regions of the world. By quantifying and synthesizing spatial drivers of change on coral reefs, we provide an avenue for further research to understand how drivers determine reef diversity and resilience, which can ultimately inform policies to protect coral reefs. PMID:29494613

Integrin Targeted MR Imaging

PubMed Central

Tan, Mingqian; Lu, Zheng-Rong

2011-01-01

Magnetic resonance imaging (MRI) is a powerful medical diagnostic imaging modality for integrin targeted imaging, which uses the magnetic resonance of tissue water protons to display tissue anatomic structures with high spatial resolution. Contrast agents are often used in MRI to highlight specific regions of the body and make them easier to visualize. There are four main classes of MRI contrast agents based on their different contrast mechanisms, including T1, T2, chemical exchange saturation transfer (CEST) agents, and heteronuclear contrast agents. Integrins are an important family of heterodimeric transmembrane glycoproteins that function as mediators of cell-cell and cell-extracellular matrix interactions. The overexpressed integrins can be used as the molecular targets for designing suitable integrin targeted contrast agents for MR molecular imaging. Integrin targeted contrast agent includes a targeting agent specific to a target integrin, a paramagnetic agent and a linker connecting the targeting agent with the paramagnetic agent. Proper selection of targeting agents is critical for targeted MRI contrast agents to effectively bind to integrins for in vivo imaging. An ideal integrin targeted MR contrast agent should be non-toxic, provide strong contrast enhancement at the target sites and can be completely excreted from the body after MR imaging. An overview of integrin targeted MR contrast agents based on small molecular and macromolecular Gd(III) complexes, lipid nanoparticles and superparamagnetic nanoparticles is provided for MR molecular imaging. By using proper delivery systems for loading sufficient Gd(III) chelates or superparamagnetic nanoparticles, effective molecular imaging of integrins with MRI has been demonstrated in animal models. PMID:21547154

How Deep Is Your SNARC? Interactions Between Numerical Magnitude, Response Hands, and Reachability in Peripersonal Space.

PubMed

Lohmann, Johannes; Schroeder, Philipp A; Nuerk, Hans-Christoph; Plewnia, Christian; Butz, Martin V

2018-01-01

Spatial, physical, and semantic magnitude dimensions can influence action decisions in human cognitive processing and interact with each other. For example, in the spatial-numerical associations of response code (SNARC) effect, semantic numerical magnitude facilitates left-hand or right-hand responding dependent on the small or large magnitude of number symbols. SNARC-like interactions of numerical magnitudes with the radial spatial dimension (depth) were postulated from early on. Usually, the SNARC effect in any direction is investigated using fronto-parallel computer monitors for presentation of stimuli. In such 2D setups, however, the metaphorical and literal interpretation of the radial depth axis with seemingly close/far stimuli or responses are not distinct. Hence, it is difficult to draw clear conclusions with respect to the contribution of different spatial mappings to the SNARC effect. In order to disentangle the different mappings in a natural way, we studied parametrical interactions between semantic numerical magnitude, horizontal directional responses, and perceptual distance by means of stereoscopic depth in an immersive virtual reality (VR). Two VR experiments show horizontal SNARC effects across all spatial displacements in traditional latency measures and kinematic response parameters. No indications of a SNARC effect along the depth axis, as it would be predicted by a direct mapping account, were observed, but the results show a non-linear relationship between horizontal SNARC slopes and physical distance. Steepest SNARC slopes were observed for digits presented close to the hands. We conclude that spatial-numerical processing is susceptible to effector-based processes but relatively resilient to task-irrelevant variations of radial-spatial magnitudes.

Concepts and models of coupled systems

NASA Astrophysics Data System (ADS)

Ertsen, Maurits

2017-04-01

In this paper, I will especially focus on the question of the position of human agency, social networks and complex co-evolutionary interactions in socio-hydrological models. The long term perspective of complex systems' modeling typically focuses on regional or global spatial scales and century/millennium time scales. It is still a challenge to relate correlations in outcomes defined at those longer and larger scales to the causalities at the shorter and smaller scales. How do we move today to the next 1000 years in the same way that our ancestors did move from their today to our present, in the small steps that produce reality? Please note, I am not arguing long term work is not interesting or the like. I just pose the question how to deal with the problem that we employ relations with hindsight that matter to us, but not necessarily to the agents that produced the relations we think we have observed. I would like to push the socio-hydrological community a little into rethinking how to deal with complexity, with the aim to bring together the timescales of humans and complexity. I will provide one or two examples of how larger-scale and longer-term observations on water flows and environmental loads can be broken down into smaller-scale and shorter-term production processes of these same loads.

Simulating irrational human behavior to prevent resource depletion.

PubMed

Sircova, Anna; Karimi, Fariba; Osin, Evgeny N; Lee, Sungmin; Holme, Petter; Strömbom, Daniel

2015-01-01

In a situation with a limited common resource, cooperation between individuals sharing the resource is essential. However, people often act upon self-interest in irrational ways that threaten the long-term survival of the whole group. A lack of sustainable or environmentally responsible behavior is often observed. In this study, we examine how the maximization of benefits principle works in a wider social interactive context of personality preferences in order to gain a more realistic insight into the evolution of cooperation. We used time perspective (TP), a concept reflecting individual differences in orientation towards past, present, or future, and relevant for making sustainable choices. We developed a personality-driven agent-based model that explores the role of personality in the outcomes of social dilemmas and includes multiple facets of diversity: (1) The agents have different behavior strategies: individual differences derived by applying cluster analysis to survey data from 22 countries (N = 10,940) and resulting in 7 cross-cultural profiles of TP; (2) The non-uniform distribution of the types of agents across countries; (3) The diverse interactions between the agents; and (4) diverse responses to those interactions in a well-mixed population. As one of the results, we introduced an index of overall cooperation for each of the 22 countries, which was validated against cultural, economic, and sustainability indicators (HDI, dimensions of national culture, and Environment Performance Index). It was associated with higher human development, higher individualism, lower power distance, and better environmental performance. The findings illustrate how individual differences in TP can be simulated to predict the ways people in different countries solve the personal vs. common gain dilemma in the global limited-resource situation. This interdisciplinary approach to social simulation can be adopted to explain the possible causes of global environmental issues and to predict their possible outcomes.

Simulating Irrational Human Behavior to Prevent Resource Depletion

PubMed Central

Sircova, Anna; Karimi, Fariba; Osin, Evgeny N.; Lee, Sungmin; Holme, Petter; Strömbom, Daniel

2015-01-01

In a situation with a limited common resource, cooperation between individuals sharing the resource is essential. However, people often act upon self-interest in irrational ways that threaten the long-term survival of the whole group. A lack of sustainable or environmentally responsible behavior is often observed. In this study, we examine how the maximization of benefits principle works in a wider social interactive context of personality preferences in order to gain a more realistic insight into the evolution of cooperation. We used time perspective (TP), a concept reflecting individual differences in orientation towards past, present, or future, and relevant for making sustainable choices. We developed a personality-driven agent-based model that explores the role of personality in the outcomes of social dilemmas and includes multiple facets of diversity: (1) The agents have different behavior strategies: individual differences derived by applying cluster analysis to survey data from 22 countries (N = 10,940) and resulting in 7 cross-cultural profiles of TP; (2) The non-uniform distribution of the types of agents across countries; (3) The diverse interactions between the agents; and (4) diverse responses to those interactions in a well-mixed population. As one of the results, we introduced an index of overall cooperation for each of the 22 countries, which was validated against cultural, economic, and sustainability indicators (HDI, dimensions of national culture, and Environment Performance Index). It was associated with higher human development, higher individualism, lower power distance, and better environmental performance. The findings illustrate how individual differences in TP can be simulated to predict the ways people in different countries solve the personal vs. common gain dilemma in the global limited-resource situation. This interdisciplinary approach to social simulation can be adopted to explain the possible causes of global environmental issues and to predict their possible outcomes. PMID:25760635

Opinion strength influences the spatial dynamics of opinion formation

PubMed Central

Baumgaertner, Bert O.; Tyson, Rebecca T.; Krone, Stephen M.

2016-01-01

Opinions are rarely binary; they can be held with different degrees of conviction, and this expanded attitude spectrum can affect the influence one opinion has on others. Our goal is to understand how different aspects of influence lead to recognizable spatio-temporal patterns of opinions and their strengths. To do this, we introduce a stochastic spatial agent-based model of opinion dynamics that includes a spectrum of opinion strengths and various possible rules for how the opinion strength of one individual affects the influence that this individual has on others. Through simulations, we find that even a small amount of amplification of opinion strength through interaction with like-minded neighbors can tip the scales in favor of polarization and deadlock. PMID:28529381

In vitro susceptibility of Scedosporium isolates to N-acetyl-L-cysteine alone and in combination with conventional antifungal agents.

PubMed

Homa, Mónika; Galgóczy, László; Tóth, Eszter; Virágh, Máté; Chandrasekaran, Muthusamy; Vágvölgyi, Csaba; Papp, Tamás

2016-10-01

In recent years, Scedosporium species have been more commonly recognized from severe, difficult-to-treat human infections, such as upper respiratory tract and pulmonary infections. To select an appropriate therapeutic approach for these infections is challenging, because of the commonly observed resistance of the causative agents to several antifungal drugs. Therefore, to find a novel strategy for the treatment of pulmonary Scedosporium infections the in vitro antifungal effect of a mucolytic agent, N-acetyl-L-cysteine and its in vitro combinations with conventional antifungals were investigated. Synergistic and indifferent interactions were registered in 23 and 13 cases, respectively. Antagonism was not revealed between the compounds. © The Author 2016. Published by Oxford University Press on behalf of The International Society for Human and Animal Mycology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

EEG source reconstruction reveals frontal-parietal dynamics of spatial conflict processing.

PubMed

Cohen, Michael X; Ridderinkhof, K Richard

2013-01-01

Cognitive control requires the suppression of distracting information in order to focus on task-relevant information. We applied EEG source reconstruction via time-frequency linear constrained minimum variance beamforming to help elucidate the neural mechanisms involved in spatial conflict processing. Human subjects performed a Simon task, in which conflict was induced by incongruence between spatial location and response hand. We found an early (∼200 ms post-stimulus) conflict modulation in stimulus-contralateral parietal gamma (30-50 Hz), followed by a later alpha-band (8-12 Hz) conflict modulation, suggesting an early detection of spatial conflict and inhibition of spatial location processing. Inter-regional connectivity analyses assessed via cross-frequency coupling of theta (4-8 Hz), alpha, and gamma power revealed conflict-induced shifts in cortical network interactions: Congruent trials (relative to incongruent trials) had stronger coupling between frontal theta and stimulus-contrahemifield parietal alpha/gamma power, whereas incongruent trials had increased theta coupling between medial frontal and lateral frontal regions. These findings shed new light into the large-scale network dynamics of spatial conflict processing, and how those networks are shaped by oscillatory interactions.

Human-Swarm Interactions Based on Managing Attractors

DTIC Science & Technology

2014-03-01

means that agent j is visible to agent i at time t. Each aij(t) is determined at time t according to a Bernoulli random vari- able with parameter pij(t...angu- lar momentum , mgroup, and group polarization, pgroup [9, 17]. The mgroup is a measure of the degree of rotation of the group about its centroid...0.1 seconds. 91 (a) (b) Figure 2: The group momentum and polarization as the radius of orientation is increased and decreased. 3. ATTRACTORS AND

Incorporating time and spatial-temporal reasoning into situation management

NASA Astrophysics Data System (ADS)

Jakobson, Gabriel

2010-04-01

Spatio-temporal reasoning plays a significant role in situation management that is performed by intelligent agents (human or machine) by affecting how the situations are recognized, interpreted, acted upon or predicted. Many definitions and formalisms for the notion of spatio-temporal reasoning have emerged in various research fields including psychology, economics and computer science (computational linguistics, data management, control theory, artificial intelligence and others). In this paper we examine the role of spatio-temporal reasoning in situation management, particularly how to resolve situations that are described by using spatio-temporal relations among events and situations. We discuss a model for describing context sensitive temporal relations and show have the model can be extended for spatial relations.

The human factors of workstation telepresence

NASA Technical Reports Server (NTRS)

Smith, Thomas J.; Smith, Karl U.

1990-01-01

The term workstation telepresence has been introduced to describe human-telerobot compliance, which enables the human operator to effectively project his/her body image and behavioral skills to control of the telerobot itself. Major human-factors considerations for establishing high fidelity workstation telepresence during human-telerobot operation are discussed. Telerobot workstation telepresence is defined by the proficiency and skill with which the operator is able to control sensory feedback from direct interaction with the workstation itself, and from workstation-mediated interaction with the telerobot. Numerous conditions influencing such control have been identified. This raises the question as to what specific factors most critically influence the realization of high fidelity workstation telepresence. The thesis advanced here is that perturbations in sensory feedback represent a major source of variability in human performance during interactive telerobot operation. Perturbed sensory feedback research over the past three decades has established that spatial transformations or temporal delays in sensory feedback engender substantial decrements in interactive task performance, which training does not completely overcome. A recently developed social cybernetic model of human-computer interaction can be used to guide this approach, based on computer-mediated tracking and control of sensory feedback. How the social cybernetic model can be employed for evaluating the various modes, patterns, and integrations of interpersonal, team, and human-computer interactions which play a central role is workstation telepresence are discussed.

Low is large: spatial location and pitch interact in voice-based body size estimation.

PubMed

Pisanski, Katarzyna; Isenstein, Sari G E; Montano, Kelyn J; O'Connor, Jillian J M; Feinberg, David R

2017-05-01

The binding of incongruent cues poses a challenge for multimodal perception. Indeed, although taller objects emit sounds from higher elevations, low-pitched sounds are perceptually mapped both to large size and to low elevation. In the present study, we examined how these incongruent vertical spatial cues (up is more) and pitch cues (low is large) to size interact, and whether similar biases influence size perception along the horizontal axis. In Experiment 1, we measured listeners' voice-based judgments of human body size using pitch-manipulated voices projected from a high versus a low, and a right versus a left, spatial location. Listeners associated low spatial locations with largeness for lowered-pitch but not for raised-pitch voices, demonstrating that pitch overrode vertical-elevation cues. Listeners associated rightward spatial locations with largeness, regardless of voice pitch. In Experiment 2, listeners performed the task while sitting or standing, allowing us to examine self-referential cues to elevation in size estimation. Listeners associated vertically low and rightward spatial cues with largeness more for lowered- than for raised-pitch voices. These correspondences were robust to sex (of both the voice and the listener) and head elevation (standing or sitting); however, horizontal correspondences were amplified when participants stood. Moreover, when participants were standing, their judgments of how much larger men's voices sounded than women's increased when the voices were projected from the low speaker. Our results provide novel evidence for a multidimensional spatial mapping of pitch that is generalizable to human voices and that affects performance in an indirect, ecologically relevant spatial task (body size estimation). These findings suggest that crossmodal pitch correspondences evoke both low-level and higher-level cognitive processes.

A Modern Aristotelian Rhetorical Theory.

ERIC Educational Resources Information Center

Douglass, Rodney Blaine

This study proposes a modern Aristotelian rhetorical theory--that rhetorical communication is that human communication within which persons deliberatively interact. A number of corollaries follow from the fundamental postulate and include: (1) persons function as the essential agents of the rhetorical communicative process; (2) a person's…

Identification of a candidate therapeutic autophagy–inducing peptide

PubMed Central

Shoji-Kawata, Sanae; Sumpter, Rhea; Leveno, Matthew; Campbell, Grant R.; Zou, Zhongju; Kinch, Lisa; Wilkins, Angela D.; Sun, Qihua; Pallauf, Kathrin; MacDuff, Donna; Huerta, Carlos; Virgin, Herbert W.; Helms, J. Bernd; Eerland, Ruud; Tooze, Sharon A.; Xavier, Ramnik; Lenschow, Deborah J.; Yamamoto, Ai; King, David; Lichtarge, Olivier; Grishin, Nick V.; Spector, Stephen A.; Kaloyanova, Dora V.; Levine, Beth

2013-01-01

The lysosomal degradation pathway of autophagy has a crucial role in defence against infection, neurodegenerative disorders, cancer and ageing. Accordingly, agents that induce autophagy may have broad therapeutic applications. One approach to developing such agents is to exploit autophagy manipulation strategies used by microbial virulence factors. Here we show that a peptide, Tat–beclin 1—derived from a region of the autophagy protein, beclin 1, which binds human immunodeficiency virus (HIV)-1 Nef—is a potent inducer of autophagy, and interacts with a newly identified negative regulator of autophagy, GAPR-1 (also called GLIPR2). Tat–beclin 1 decreases the accumulation of polyglutamine expansion protein aggregates and the replication of several pathogens (including HIV-1) in vitro, and reduces mortality in mice infected with chikungunya or West Nile virus. Thus, through the characterization of a domain of beclin 1 that interacts with HIV-1 Nef, we have developed an autophagy-inducing peptide that has potential efficacy in the treatment of human diseases. PMID:23364696

An intelligent virtual human system for providing healthcare information and support.

PubMed

Rizzo, Albert A; Lange, Belinda; Buckwalter, John G; Forbell, Eric; Kim, Julia; Sagae, Kenji; Williams, Josh; Rothbaum, Barbara O; Difede, JoAnn; Reger, Greg; Parsons, Thomas; Kenny, Patrick

2011-01-01

Over the last 15 years, a virtual revolution has taken place in the use of Virtual Reality simulation technology for clinical purposes. Shifts in the social and scientific landscape have now set the stage for the next major movement in Clinical Virtual Reality with the "birth" of intelligent virtual humans. Seminal research and development has appeared in the creation of highly interactive, artificially intelligent and natural language capable virtual human agents that can engage real human users in a credible fashion. No longer at the level of a prop to add context or minimal faux interaction in a virtual world, virtual humans can be designed to perceive and act in a 3D virtual world, engage in spoken dialogues with real users and can be capable of exhibiting human-like emotional reactions. This paper will present an overview of the SimCoach project that aims to develop virtual human support agents to serve as online guides for promoting access to psychological healthcare information and for assisting military personnel and family members in breaking down barriers to initiating care. The SimCoach experience is being designed to attract and engage military Service Members, Veterans and their significant others who might not otherwise seek help with a live healthcare provider. It is expected that this experience will motivate users to take the first step--to empower themselves to seek advice and information regarding their healthcare and general personal welfare and encourage them to take the next step towards seeking more formal resources if needed.

Using Spatial Subsidies to Account for Telecoupling in the Ecosystem Services of Transboundary Migratory Species in North America

NASA Astrophysics Data System (ADS)

Lopez-Hoffman, L.; Semmens, D. J.; Diffendorfer, J.; Thogmartin, W.

2016-12-01

In complex coupled natural-human systems, drivers of change in one location can have profound effects on human well-being in distant locations, often across international borders. While the conceptual framework of telecoupling describes these interactions across space, the ability to quantify feedbacks between ecosystem change in one area and societal benefits in other areas requires quantitative analytical approaches. We use a new approach—spatial subsidies—to operationalize the concept of telecoupling by measuring the degree to which a migratory species' ability to provide services in one location depends on habitat in another location. Spatial subsidies can be use identify critical features of telecoupled systems such as sending and receiving areas and to measure the strength of coupling between areas. We present spatial subsidies analyses for the telecoupled natural-human systems of three North American migratory species: Monarch butterflies, Mexican free-tailed bats and Northern Pintails (a dabbling duck). Spatial subsidies and the telecoupling conceptual framework have potential to be the foundation for new policies related to migratory species, such as the strategic direction of Duck Stamp revenues and the development of similar programs for other migratory species.

The balance between adaptation to catalysts and competition radius shapes the total wealth, time variability and inequality

NASA Astrophysics Data System (ADS)

Davidovich, Hadar; Louzoun, Yoram

2013-05-01

The globalization of modern markets has led to the emergence of competition between producers in ever growing distances. This opens the interesting question in population dynamics of the effect of long-range competition. We here study a model of non-local competition to test the effect of the competition radius on the wealth distribution, using the framework of a stochastic birth-death process, with non-local interactions. We show that this model leads to non-trivial dynamics that can have implications in other domains of physics. Competition is studied in the context of the catalyst induced growth of autocatalytic agents, representing the growth of capital in the presence of investment opportunities. These agents are competing with all other agents in a given radius on growth possibilities. We show that a large scale competition leads to an extreme localization of the agents, where typically a single aggregate of agents can survive within a given competition radius. The survival of these aggregates is determined by the diffusion rates of the agents and the catalysts. For high and low agent diffusion rates, the agent population is always annihilated, while for intermediate diffusion rates, a finite agent population persists. Increasing the catalyst diffusion rate always leads to a decrease in the average agent population density. The extreme localization of the agents leads to the emergence of intermittent fluctuations, when a large aggregate of agents disappear. As the competition radius increases, so does the average agent density and its spatial variance as well as the volatility.

Disentangling endogenous versus exogenous pattern formation in spatial ecology: a case study of the ant Azteca sericeasur in southern Mexico.

PubMed

Li, Kevin; Vandermeer, John H; Perfecto, Ivette

2016-05-01

Spatial patterns in ecology can be described as reflective of environmental heterogeneity (exogenous), or emergent from dynamic relationships between interacting species (endogenous), but few empirical studies focus on the combination. The spatial distribution of the nests of Azteca sericeasur, a keystone tropical arboreal ant, is thought to form endogenous spatial patterns among the shade trees of a coffee plantation through self-regulating interactions with controlling agents (i.e. natural enemies). Using inhomogeneous point process models, we found evidence for both types of processes in the spatial distribution of A. sericeasur. Each year's nest distribution was determined mainly by a density-dependent relationship with the previous year's lagged nest density; but using a novel application of a Thomas cluster process to account for the effects of nest clustering, we found that nest distribution also correlated significantly with tree density in the later years of the study. This coincided with the initiation of agricultural intensification and tree felling on the coffee farm. The emergence of this significant exogenous effect, along with the changing character of the density-dependent effect of lagged nest density, provides clues to the mechanism behind a unique phenomenon observed in the plot, that of an increase in nest population despite resource limitation in nest sites. Our results have implications in coffee agroecological management, as this system provides important biocontrol ecosystem services. Further research is needed, however, to understand the effective scales at which these relationships occur.

Agent-Based Models in Social Physics

NASA Astrophysics Data System (ADS)

Quang, Le Anh; Jung, Nam; Cho, Eun Sung; Choi, Jae Han; Lee, Jae Woo

2018-06-01

We review the agent-based models (ABM) on social physics including econophysics. The ABM consists of agent, system space, and external environment. The agent is autonomous and decides his/her behavior by interacting with the neighbors or the external environment with the rules of behavior. Agents are irrational because they have only limited information when they make decisions. They adapt using learning from past memories. Agents have various attributes and are heterogeneous. ABM is a non-equilibrium complex system that exhibits various emergence phenomena. The social complexity ABM describes human behavioral characteristics. In ABMs of econophysics, we introduce the Sugarscape model and the artificial market models. We review minority games and majority games in ABMs of game theory. Social flow ABM introduces crowding, evacuation, traffic congestion, and pedestrian dynamics. We also review ABM for opinion dynamics and voter model. We discuss features and advantages and disadvantages of Netlogo, Repast, Swarm, and Mason, which are representative platforms for implementing ABM.

BTFS: The Border Trade Facilitation System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Phillips, L.R.

The author demonstrates the Border Trade Facilitation System (BTFS), an agent-based bilingual e-commerce system built to expedite the regulation, control, and execution of commercial trans-border shipments during the delivery phase. The system was built to serve maquila industries at the US/Mexican border. The BTFS uses foundation technology developed here at Sandia Laboratories' Advanced Information Systems Lab (AISL), including a distributed object substrate, a general-purpose agent development framework, dynamically generated agent-human interaction via the World-Wide Web, and a collaborative agent architecture. This technology is also the substrate for the Multi-Agent Simulation Management System (MASMAS) proposed for demonstration at this conference. Themore » BTFS executes authenticated transactions among agents performing open trading over the Internet. With the BTFS in place, one could conduct secure international transactions from any site with an Internet connection and a web browser. The BTFS is currently being evaluated for commercialization.« less

Space versus Place in Complex Human-Natural Systems: Spatial and Multi-level Models of Tropical Land Use and Cover Change (LUCC) in Guatemala

PubMed Central

López-Carr, David; Davis, Jason; Jankowska, Marta; Grant, Laura; López-Carr, Anna Carla; Clark, Matthew

2013-01-01

The relative role of space and place has long been debated in geography. Yet modeling efforts applied to coupled human-natural systems seemingly favor models assuming continuous spatial relationships. We examine the relative importance of placebased hierarchical versus spatial clustering influences in tropical land use/cover change (LUCC). Guatemala was chosen as our study site given its high rural population growth and deforestation in recent decades. We test predictors of 2009 forest cover and forest cover change from 2001-2009 across Guatemala's 331 municipalities and 22 departments using spatial and multi-level statistical models. Our results indicate the emergence of several socio-economic predictors of LUCC regardless of model choice. Hierarchical model results suggest that significant differences exist at the municipal and departmental levels but largely maintain the magnitude and direction of single-level model coefficient estimates. They are also intervention-relevant since policies tend to be applicable to distinct political units rather than to continuous space. Spatial models complement hierarchical approaches by indicating where and to what magnitude significant negative and positive clustering associations emerge. Appreciating the comparative advantages and limitations of spatial and nested models enhances a holistic approach to geographical analysis of tropical LUCC and human-environment interactions. PMID:24013908

The Synthetic Antimicrobial Peptide 19-2.5 Interacts with Heparanase and Heparan Sulfate in Murine and Human Sepsis.

PubMed

Martin, Lukas; De Santis, Rebecca; Koczera, Patrick; Simons, Nadine; Haase, Hajo; Heinbockel, Lena; Brandenburg, Klaus; Marx, Gernot; Schuerholz, Tobias

2015-01-01

Heparanase is an endo-β-glucuronidase that cleaves heparan sulfate side chains from their proteoglycans. Thereby, heparanase liberates highly potent circulating heparan sulfate-fragments (HS-fragments) and triggers the fatal and excessive inflammatory response in sepsis. As a potential anti-inflammatory agent for sepsis therapy, peptide 19-2.5 belongs to the class of synthetic anti-lipopolysaccharide peptides; however, its activity is not restricted to Gram-negative bacterial infection. We hypothesized that peptide 19-2.5 interacts with heparanase and/or HS, thereby reducing the levels of circulating HS-fragments in murine and human sepsis. Our data indicate that the treatment of septic mice with peptide 19-2.5 compared to untreated control animals lowers levels of plasma heparanase and circulating HS-fragments and reduces heparanase activity. Additionally, mRNA levels of heparanase in heart, liver, lung, kidney and spleen are downregulated in septic mice treated with peptide 19-2.5 compared to untreated control animals. In humans, plasma heparanase level and activity are elevated in septic shock. The ex vivo addition of peptide 19-2.5 to plasma of septic shock patients decreases heparanase activity but not heparanase level. Isothermal titration calorimetry revealed a strong exothermic reaction between peptide 19-2.5 and heparanase and HS-fragments. However, a saturation character has been identified only in the peptide 19-2.5 and HS interaction. In conclusion, the findings of our current study indicate that peptide 19-2.5 interacts with heparanase, which is elevated in murine and human sepsis and consecutively attenuates the generation of circulating HS-fragments in systemic inflammation. Thus, peptide 19-2.5 seems to be a potential anti-inflammatory agent in sepsis.

Stoichiometric and catalytic scavengers as protection against nerve agent toxicity: a mini review.

PubMed

Lenz, David E; Yeung, David; Smith, J Richard; Sweeney, Richard E; Lumley, Lucille A; Cerasoli, Douglas M

2007-04-20

Currently fielded treatments for nerve agent intoxication promote survival, but do not afford complete protection against either nerve agent-induced motor and cognitive deficits or neuronal pathology. The use of human plasma-derived butyrylcholinesterase (HuBuChE) to neutralize the toxic effects of nerve agents in vivo has been shown to both aid survival and protect against decreased cognitive function after nerve agent exposure. Recently, a commercially produced recombinant form of human butyrylcholinesterase (r-HuBuChE; PharmAthene Inc.) expressed in the milk of transgenic goats has become available. This material is biochemically similar to plasma-derived HuBuChE in in vitro assays. The pharmacokinetic characteristics of a polyethylene glycol coated (pegylated) form of r-HuBuChE were determined in guinea pigs; the enzyme was rapidly bioavailable with a half-life (t(1/2)) and pharmacokinetic profile that resembled that of plasma-derived huBuChE. Guinea pigs were injected with 140mg/kg (i.m.) of pegylated r-HuBuChE 18h prior to exposure (sc) to 5.5xLD(50) VX or soman. VX and soman were administered in a series of three injections of 1.5xLD(50), 2.0xLD(50), and 2.0xLD(50), respectively, with injections separated by 2h. Pretreatment with pegylated r-HuBuChE provided 100% survival against multiple lethal doses of VX and soman. Guinea pigs displayed no signs of nerve agent toxicity following exposure. Assessments of motor activity, coordination, and acquisition of spatial memory were performed for 2 weeks following nerve agent exposure. There were no measurable decreases in motor or cognitive function during this period. In contrast, animals receiving 1.5xLD(50) challenges of soman or VX and treated with standard atropine, 2-PAM, and diazepam therapy showed 50 and 100% survival, respectively, but exhibited marked decrements in motor function and, in the case of GD, impaired spatial memory acquisition. The advances in this field have resulted in the decision to select both the plasma-derived and the recombinant form of BuChE for advanced development and transition to clinical trials. Efforts have now been expanded to identify a catalytic protein capable of not only binding, but also rapidly hydrolyzing the standard threat nerve agents. Recent work has focused on paraoxonase-1 (PON1), a naturally occurring human serum enzyme with the capacity to catalyze the hydrolysis of nerve agents, albeit too slowly to afford dramatic protection. Using rational design, several amino acids involved in substrate binding have been identified and site-directed mutations have revealed that residue H115 plays an important role in binding. In addition, the stereospecificity of PON1 for the catalytic hydrolysis of soman has been examined. The enzyme exhibits a slight stereospecificity for the C+P+ isomer of soman, which is due more to preferential binding than to selective hydrolysis of this isomer. The results suggest that it may be possible to engineer a mutant form of PON1 with enhanced activity and stereospecificity for the most toxic nerve agent isoforms.

Co-culturing of Fungal Strains Against Botrytis cinerea as a Model for the Induction of Chemical Diversity and Therapeutic Agents.

PubMed

Serrano, Rachel; González-Menéndez, Víctor; Rodríguez, Lorena; Martín, Jesús; Tormo, José R; Genilloud, Olga

2017-01-01

New fungal SMs (SMs) have been successfully described to be produced by means of in vitro -simulated microbial community interactions. Co-culturing of fungi has proved to be an efficient way to induce cell-cell interactions that can promote the activation of cryptic pathways, frequently silent when the strains are grown in laboratory conditions. Filamentous fungi represent one of the most diverse microbial groups known to produce bioactive natural products. Triggering the production of novel antifungal compounds in fungi could respond to the current needs to fight health compromising pathogens and provide new therapeutic solutions. In this study, we have selected the fungus Botrytis cinerea as a model to establish microbial interactions with a large set of fungal strains related to ecosystems where they can coexist with this phytopathogen, and to generate a collection of extracts, obtained from their antagonic microbial interactions and potentially containing new bioactive compounds. The antifungal specificity of the extracts containing compounds induced after B. cinerea interaction was determined against two human fungal pathogens ( Candida albicans and Aspergillus fumigatus ) and three phytopathogens ( Colletotrichum acutatum , Fusarium proliferatum , and Magnaporthe grisea ). In addition, their cytotoxicity was also evaluated against the human hepatocellular carcinoma cell line (HepG2). We have identified by LC-MS the production of a wide variety of known compounds induced from these fungal interactions, as well as novel molecules that support the potential of this approach to generate new chemical diversity and possible new therapeutic agents.

Ocular exposure to blue-enriched light has an asymmetric influence on neural activity and spatial attention.

PubMed

Newman, Daniel P; Lockley, Steven W; Loughnane, Gerard M; Martins, Ana Carina P; Abe, Rafael; Zoratti, Marco T R; Kelly, Simon P; O'Neill, Megan H; Rajaratnam, Shantha M W; O'Connell, Redmond G; Bellgrove, Mark A

2016-06-13

Brain networks subserving alertness in humans interact with those for spatial attention orienting. We employed blue-enriched light to directly manipulate alertness in healthy volunteers. We show for the first time that prior exposure to higher, relative to lower, intensities of blue-enriched light speeds response times to left, but not right, hemifield visual stimuli, via an asymmetric effect on right-hemisphere parieto-occipital α-power. Our data give rise to the tantalising possibility of light-based interventions for right hemisphere disorders of spatial attention.

Ocular exposure to blue-enriched light has an asymmetric influence on neural activity and spatial attention

PubMed Central

Newman, Daniel P.; Lockley, Steven W.; Loughnane, Gerard M.; Martins, Ana Carina P.; Abe, Rafael; Zoratti, Marco T. R.; Kelly, Simon P.; O’Neill, Megan H.; Rajaratnam, Shantha M. W.; O’Connell, Redmond G.; Bellgrove, Mark A.

2016-01-01

Brain networks subserving alertness in humans interact with those for spatial attention orienting. We employed blue-enriched light to directly manipulate alertness in healthy volunteers. We show for the first time that prior exposure to higher, relative to lower, intensities of blue-enriched light speeds response times to left, but not right, hemifield visual stimuli, via an asymmetric effect on right-hemisphere parieto-occipital α-power. Our data give rise to the tantalising possibility of light-based interventions for right hemisphere disorders of spatial attention. PMID:27291291

Human Metabolism and Interactions of Deployment-Related Chemicals

DTIC Science & Technology

2008-08-01

metabolic detoxification pathway for permethrin. Other deployment related compounds, an insect repellent (N,N-diethyl-m- toluamide) a nerve gas ...Leo, K. U. 1997. Metabolism of proposed nerve agent pretreatment, pyridostigmine bromine. Walter Reed Army Institute of Research Report No. NTIS/AD...against possible nerve gas attack. It has been reported that chlorpyrifos and DEET are metabo- lized by human P450s (Tang et al., 2001; Usmani et al., 2002

Wildlife reservoirs for vector-borne canine, feline and zoonotic infections in Austria

PubMed Central

Duscher, Georg G.; Leschnik, Michael; Fuehrer, Hans-Peter; Joachim, Anja

2014-01-01

Austria's mammalian wildlife comprises a large variety of species, acting and interacting in different ways as reservoir and intermediate and definitive hosts for different pathogens that can be transmitted to pets and/or humans. Foxes and other wild canids are responsible for maintaining zoonotic agents, e.g. Echinococcus multilocularis, as well as pet-relevant pathogens, e.g. Hepatozoon canis. Together with the canids, and less commonly felids, rodents play a major role as intermediate and paratenic hosts. They carry viruses such as tick-borne encephalitis virus (TBEV), bacteria including Borrelia spp., protozoa such as Toxoplasma gondii, and helminths such as Toxocara canis. The role of wild ungulates, especially ruminants, as reservoirs for zoonotic disease on the other hand seems to be negligible, although the deer filaroid Onchocerca jakutensis has been described to infect humans. Deer may also harbour certain Anaplasma phagocytophilum strains with so far unclear potential to infect humans. The major role of deer as reservoirs is for ticks, mainly adults, thus maintaining the life cycle of these vectors and their distribution. Wild boar seem to be an exception among the ungulates as, in their interaction with the fox, they can introduce food-borne zoonotic agents such as Trichinella britovi and Alaria alata into the human food chain. PMID:25830102

Environmental Sustainability and Effects on Urban Micro Region using Agent-Based Modeling of Urbanisation in Select Major Indian Cities

NASA Astrophysics Data System (ADS)

Aithal, B. H.

2015-12-01

Abstract: Urbanisation has gained momentum with globalization in India. Policy decisions to set up commercial, industrial hubs have fuelled large scale migration, added with population upsurge has contributed to the fast growing urban region that needs to be monitored in order to design sustainable urban cities. Unplanned urbanization have resulted in the growth of peri-urban region referred to as urban sprawl, are often devoid of basic amenities and infrastructure leading to large scale environmental problems that are evident. Remote sensing data acquired through space borne sensors at regular interval helps in understanding urban dynamics aided by Geoinformatics which has proved very effective in mapping and monitoring for sustainable urban planning. Cellular automata (CA) is a robust approach for the spatially explicit simulation of land-use land cover dynamics. CA uses rules, states, conditions that are vital factors in modelling urbanisation. This communication effectively introduces simulation assistances of CA with the agent based modelling supported by its fuzzy characteristics and weightages through analytical hierarchal process (AHP). This has been done considering perceived agents such as industries, natural resource etc. Respective agent's role in development of a particular regions into an urban area has been examined with weights and its influence of each of these agents based on its characteristics functions. Validation was performed obtaining a high kappa coefficient indicating the quality and the allocation performance of the model & validity of the model to predict future projections. The prediction using the proposed model was performed for 2030. Further environmental sustainability of each of these cities are explored such as water features, environment, greenhouse gas emissions, effects on human human health etc., Modeling suggests trend of various land use classes transformation with the spurt in urban expansions based on specific regions and policies providing a visual spatial information to both urban planners and city managers. Further environmental sustainability assessment indicates dwindling natural resources and increase in thermal discomfort to the living population thereby indicating need for balanced and planned development.

Historical distribution and host-vector diversity of Francisella tularensis, the causative agent of tularemia, in Ukraine.

PubMed

Hightower, Jake; Kracalik, Ian T; Vydayko, Nataliya; Goodin, Douglas; Glass, Gregory; Blackburn, Jason K

2014-10-16

Francisella tularensis, the causative agent of tularemia, is a zoonotic agent that remains across much of the northern hemisphere, where it exists in enzootic cycles. In Ukraine, tularemia has a long history that suggests a need for sustained surveillance in natural foci. To better characterize the host-vector diversity and spatial distribution of tularemia, we analyzed historical data from field collections carried out from 1941 to 2008. We analyzed the spatial-temporal distribution of bacterial isolates collected from field samples. Isolates were characterized by source and dominant land cover type. To identify environmental persistence and spatial variation in the source of isolation, we used the space-time permutation and multinomial models in SaTScan. A total of 3,086 positive isolates were taken from 1,084 geographic locations. Isolation of F. tularensis was more frequent among arthropods [n = 2,045 (66.3%)] followed by mammals [n = 619 (20.1%)], water [n = 393 (12.7%)], and farm produce [n = 29 (0.94%)], respectively. Four areas of persistent bacterial isolation were identified. Water and farm produce as sources of bacterial isolation were clustered. Our findings confirm the presence of long-standing natural foci of F. tularensis in Ukraine. Given the history of tularemia as well as its environmental persistence there exists a possibility of (re)emergence in human populations. Heterogeneity in the distribution of tularemia isolate recovery related to land cover type supports the theory of natural nidality and clusters identify areas to target potential sources of the pathogen and improve surveillance.

An agent based architecture for high-risk neonate management at neonatal intensive care unit.

PubMed

Malak, Jaleh Shoshtarian; Safdari, Reza; Zeraati, Hojjat; Nayeri, Fatemeh Sadat; Mohammadzadeh, Niloofar; Farajollah, Seide Sedighe Seied

2018-01-01

In recent years, the use of new tools and technologies has decreased the neonatal mortality rate. Despite the positive effect of using these technologies, the decisions are complex and uncertain in critical conditions when the neonate is preterm or has a low birth weight or malformations. There is a need to automate the high-risk neonate management process by creating real-time and more precise decision support tools. To create a collaborative and real-time environment to manage neonates with critical conditions at the NICU (Neonatal Intensive Care Unit) and to overcome high-risk neonate management weaknesses by applying a multi agent based analysis and design methodology as a new solution for NICU management. This study was a basic research for medical informatics method development that was carried out in 2017. The requirement analysis was done by reviewing articles on NICU Decision Support Systems. PubMed, Science Direct, and IEEE databases were searched. Only English articles published after 1990 were included; also, a needs assessment was done by reviewing the extracted features and current processes at the NICU environment where the research was conducted. We analyzed the requirements and identified the main system roles (agents) and interactions by a comparative study of existing NICU decision support systems. The Universal Multi Agent Platform (UMAP) was applied to implement a prototype of our multi agent based high-risk neonate management architecture. Local environment agents interacted inside a container and each container interacted with external resources, including other NICU systems and consultation centers. In the NICU container, the main identified agents were reception, monitoring, NICU registry, and outcome prediction, which interacted with human agents including nurses and physicians. Managing patients at the NICU units requires online data collection, real-time collaboration, and management of many components. Multi agent systems are applied as a well-known solution for management, coordination, modeling, and control of NICU processes. We are currently working on an outcome prediction module using artificial intelligence techniques for neonatal mortality risk prediction. The full implementation of the proposed architecture and evaluation is considered the future work.

Structural elucidation of the hormonal inhibition mechanism of the bile acid cholate on human carbonic anhydrase II

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boone, Christopher D.; Tu, Chingkuang; McKenna, Robert, E-mail: rmckenna@ufl.edu

The structure of human carbonic anhydrase II in complex with cholate has been determined to 1.54 Å resolution. Elucidation of the novel inhibition mechanism of cholate will aid in the development of a nonsulfur-containing, isoform-specific therapeutic agent. The carbonic anhydrases (CAs) are a family of mostly zinc metalloenzymes that catalyze the reversible hydration/dehydration of CO{sub 2} into bicarbonate and a proton. Human isoform CA II (HCA II) is abundant in the surface epithelial cells of the gastric mucosa, where it serves an important role in cytoprotection through bicarbonate secretion. Physiological inhibition of HCA II via the bile acids contributes tomore » mucosal injury in ulcerogenic conditions. This study details the weak biophysical interactions associated with the binding of a primary bile acid, cholate, to HCA II. The X-ray crystallographic structure determined to 1.54 Å resolution revealed that cholate does not make any direct hydrogen-bond interactions with HCA II, but instead reconfigures the well ordered water network within the active site to promote indirect binding to the enzyme. Structural knowledge of the binding interactions of this nonsulfur-containing inhibitor with HCA II could provide the template design for high-affinity, isoform-specific therapeutic agents for a variety of diseases/pathological states, including cancer, glaucoma, epilepsy and osteoporosis.« less

Method for photo-altering a biological system to improve biological effect

DOEpatents

Hill, Richard A.; Doiron, Daniel R.; Crean, David H.

2000-08-01

Photodynamic therapy is a new adjunctive therapy for filtration surgery that does not use chemotherapy agents or radiation, but uses pharmacologically-active sensitizing compounds to produce a titratable, localized, transient, post operative avascular conjunctiva. A photosensitizing agent in a biological system is selectively activated by delivering the photosensitive agent to the biological system and laser activating only a spatially selected portion of the delivered photosensitive agent. The activated portion of the photosensitive agent reacts with the biological system to obtain a predetermined biological effect. As a result, an improved spatial disposition and effectuation of the biological effect by the photosensitive agent in the biological system is achieved.

Modeling physiological resistance in bacterial biofilms.

PubMed

Cogan, N G; Cortez, Ricardo; Fauci, Lisa

2005-07-01

A mathematical model of the action of antimicrobial agents on bacterial biofilms is presented. The model includes the fluid dynamics in and around the biofilm, advective and diffusive transport of two chemical constituents and the mechanism of physiological resistance. Although the mathematical model applies in three dimensions, we present two-dimensional simulations for arbitrary biofilm domains and various dosing strategies. The model allows the prediction of the spatial evolution of bacterial population and chemical constituents as well as different dosing strategies based on the fluid motion. We find that the interaction between the nutrient and the antimicrobial agent can reproduce survival curves which are comparable to other model predictions as well as experimental results. The model predicts that exposing the biofilm to low concentration doses of antimicrobial agent for longer time is more effective than short time dosing with high antimicrobial agent concentration. The effects of flow reversal and the roughness of the fluid/biofilm are also investigated. We find that reversing the flow increases the effectiveness of dosing. In addition, we show that overall survival decreases with increasing surface roughness.

Metabolic interaction between ethanol, high-dose alprazolam and its two main metabolites using human liver microsomes in vitro.

PubMed

Tanaka, Einosuke; Nakamura, Takako; Terada, Masaru; Shinozuka, Tatsuo; Honda, Katsuya

2007-08-01

Alprazolam is widely used as a short-acting antidepressant and anxiolytic agent and its effect appears at very low doses while ethanol is used as a social drug worldwide. Sometimes, toxic interactions occur following combined administration of these two drugs. In this study we have investigated the interaction between ethanol and high-dose alprazolam using human liver microsomes in vitro. The interaction effects between ethanol and alprazolam were examined by a mixed-function oxidation reaction using a human liver microsomal preparation. Alprazolam and its two main metabolites (alpha-hydroxyalprazolam: alpha-OH alprazolam, 4-hydroxyalprazolam: 4-OH alprazolam) were measured by HPLC/UV. The production of 4-OH alprazolam, one main metabolite of alprazolam, was weakly inhibited by higher dose of ethanol, but not alpha-OH alprazolam. These results using a human liver microsomal preparation show that the production of 4-OH alprazolam is weakly inhibited by ethanol but not alpha-OH alprazolam. Toxic levels may be reached by simultaneous administration of ethanol and high-dose alprazolam.

Punish and voice: punishment enhances cooperation when combined with norm-signalling.

PubMed

Andrighetto, Giulia; Brandts, Jordi; Conte, Rosaria; Sabater-Mir, Jordi; Solaz, Hector; Villatoro, Daniel

2013-01-01

Material punishment has been suggested to play a key role in sustaining human cooperation. Experimental findings, however, show that inflicting mere material costs does not always increase cooperation and may even have detrimental effects. Indeed, ethnographic evidence suggests that the most typical punishing strategies in human ecologies (e.g., gossip, derision, blame and criticism) naturally combine normative information with material punishment. Using laboratory experiments with humans, we show that the interaction of norm communication and material punishment leads to higher and more stable cooperation at a lower cost for the group than when used separately. In this work, we argue and provide experimental evidence that successful human cooperation is the outcome of the interaction between instrumental decision-making and the norm psychology humans are provided with. Norm psychology is a cognitive machinery to detect and reason upon norms that is characterized by a salience mechanism devoted to track how much a norm is prominent within a group. We test our hypothesis both in the laboratory and with an agent-based model. The agent-based model incorporates fundamental aspects of norm psychology absent from previous work. The combination of these methods allows us to provide an explanation for the proximate mechanisms behind the observed cooperative behaviour. The consistency between the two sources of data supports our hypothesis that cooperation is a product of norm psychology solicited by norm-signalling and coercive devices.

Punish and Voice: Punishment Enhances Cooperation when Combined with Norm-Signalling

PubMed Central

Andrighetto, Giulia; Brandts, Jordi; Conte, Rosaria; Sabater-Mir, Jordi; Solaz, Hector; Villatoro, Daniel

2013-01-01

Material punishment has been suggested to play a key role in sustaining human cooperation. Experimental findings, however, show that inflicting mere material costs does not always increase cooperation and may even have detrimental effects. Indeed, ethnographic evidence suggests that the most typical punishing strategies in human ecologies (e.g., gossip, derision, blame and criticism) naturally combine normative information with material punishment. Using laboratory experiments with humans, we show that the interaction of norm communication and material punishment leads to higher and more stable cooperation at a lower cost for the group than when used separately. In this work, we argue and provide experimental evidence that successful human cooperation is the outcome of the interaction between instrumental decision-making and the norm psychology humans are provided with. Norm psychology is a cognitive machinery to detect and reason upon norms that is characterized by a salience mechanism devoted to track how much a norm is prominent within a group. We test our hypothesis both in the laboratory and with an agent-based model. The agent-based model incorporates fundamental aspects of norm psychology absent from previous work. The combination of these methods allows us to provide an explanation for the proximate mechanisms behind the observed cooperative behaviour. The consistency between the two sources of data supports our hypothesis that cooperation is a product of norm psychology solicited by norm-signalling and coercive devices. PMID:23776441

Towards representing human behavior and decision making in Earth system models - an overview of techniques and approaches

NASA Astrophysics Data System (ADS)

Müller-Hansen, Finn; Schlüter, Maja; Mäs, Michael; Donges, Jonathan F.; Kolb, Jakob J.; Thonicke, Kirsten; Heitzig, Jobst

2017-11-01

Today, humans have a critical impact on the Earth system and vice versa, which can generate complex feedback processes between social and ecological dynamics. Integrating human behavior into formal Earth system models (ESMs), however, requires crucial modeling assumptions about actors and their goals, behavioral options, and decision rules, as well as modeling decisions regarding human social interactions and the aggregation of individuals' behavior. Here, we review existing modeling approaches and techniques from various disciplines and schools of thought dealing with human behavior at different levels of decision making. We demonstrate modelers' often vast degrees of freedom but also seek to make modelers aware of the often crucial consequences of seemingly innocent modeling assumptions. After discussing which socioeconomic units are potentially important for ESMs, we compare models of individual decision making that correspond to alternative behavioral theories and that make diverse modeling assumptions about individuals' preferences, beliefs, decision rules, and foresight. We review approaches to model social interaction, covering game theoretic frameworks, models of social influence, and network models. Finally, we discuss approaches to studying how the behavior of individuals, groups, and organizations can aggregate to complex collective phenomena, discussing agent-based, statistical, and representative-agent modeling and economic macro-dynamics. We illustrate the main ingredients of modeling techniques with examples from land-use dynamics as one of the main drivers of environmental change bridging local to global scales.

Modeling of cell signaling pathways in macrophages by semantic networks

PubMed Central

Hsing, Michael; Bellenson, Joel L; Shankey, Conor; Cherkasov, Artem

2004-01-01

Background Substantial amounts of data on cell signaling, metabolic, gene regulatory and other biological pathways have been accumulated in literature and electronic databases. Conventionally, this information is stored in the form of pathway diagrams and can be characterized as highly "compartmental" (i.e. individual pathways are not connected into more general networks). Current approaches for representing pathways are limited in their capacity to model molecular interactions in their spatial and temporal context. Moreover, the critical knowledge of cause-effect relationships among signaling events is not reflected by most conventional approaches for manipulating pathways. Results We have applied a semantic network (SN) approach to develop and implement a model for cell signaling pathways. The semantic model has mapped biological concepts to a set of semantic agents and relationships, and characterized cell signaling events and their participants in the hierarchical and spatial context. In particular, the available information on the behaviors and interactions of the PI3K enzyme family has been integrated into the SN environment and a cell signaling network in human macrophages has been constructed. A SN-application has been developed to manipulate the locations and the states of molecules and to observe their actions under different biological scenarios. The approach allowed qualitative simulation of cell signaling events involving PI3Ks and identified pathways of molecular interactions that led to known cellular responses as well as other potential responses during bacterial invasions in macrophages. Conclusions We concluded from our results that the semantic network is an effective method to model cell signaling pathways. The semantic model allows proper representation and integration of information on biological structures and their interactions at different levels. The reconstruction of the cell signaling network in the macrophage allowed detailed investigation of connections among various essential molecules and reflected the cause-effect relationships among signaling events. The simulation demonstrated the dynamics of the semantic network, where a change of states on a molecule can alter its function and potentially cause a chain-reaction effect in the system. PMID:15494071

The experience of agency in human-computer interactions: a review

PubMed Central

Limerick, Hannah; Coyle, David; Moore, James W.

2014-01-01

The sense of agency is the experience of controlling both one’s body and the external environment. Although the sense of agency has been studied extensively, there is a paucity of studies in applied “real-life” situations. One applied domain that seems highly relevant is human-computer-interaction (HCI), as an increasing number of our everyday agentive interactions involve technology. Indeed, HCI has long recognized the feeling of control as a key factor in how people experience interactions with technology. The aim of this review is to summarize and examine the possible links between sense of agency and understanding control in HCI. We explore the overlap between HCI and sense of agency for computer input modalities and system feedback, computer assistance, and joint actions between humans and computers. An overarching consideration is how agency research can inform HCI and vice versa. Finally, we discuss the potential ethical implications of personal responsibility in an ever-increasing society of technology users and intelligent machine interfaces. PMID:25191256

Endogenous lipid- and peptide-derived anti-inflammatory pathways generated with glucocorticoid and aspirin treatment activate the lipoxin A4 receptor

PubMed Central

Perretti, Mauro; Chiang, Nan; La, Mylinh; Fierro, Iolanda M.; Marullo, Stefano; Getting, Stephen J; Solito, Egle; Serhan, Charles N.

2009-01-01

Aspirin (ASA) and dexamethasone (DEX) are widely used anti-inflammatory agents yet their mechanism(s) for blocking polymorphonuclear neutrophil (PMN) accumulation at sites of inflammation remains unclear. Here, we report that inhibition of PMN infiltration by ASA and DEX is a property shared by aspirin-triggered lipoxins (ATL) and the glucocorticoid-induced annexin 1 (ANXA1)-derived peptides that are both generated in vivo and act at the lipoxin A4 receptor (ALXR/FPRL1) to halt PMN diapedesis. These structurally diverse ligands specifically interact directly with recombinant human ALXR demonstrated by specific radioligand binding and function as well as immunoprecipitation of PMN receptors. In addition, the combination of both ATL and ANXA1-derived peptides limited PMN infiltration and reduced production of inflammatory mediators (that is, prostaglandins and chemokines) in vivo. Together, these results indicate functional redundancies in endogenous lipid and peptide anti-inflammatory circuits that are spatially and temporally separate, where both ATL and specific ANXA1-derived peptides act in concert at ALXR to downregulate PMN recruitment to inflammatory loci. PMID:12368905

Searching for effective forces in laboratory insect swarms

NASA Astrophysics Data System (ADS)

Puckett, James G.; Kelley, Douglas H.; Ouellette, Nicholas T.

2014-04-01

Collective animal behaviour is often modeled by systems of agents that interact via effective social forces, including short-range repulsion and long-range attraction. We search for evidence of such effective forces by studying laboratory swarms of the flying midge Chironomus riparius. Using multi-camera stereoimaging and particle-tracking techniques, we record three-dimensional trajectories for all the individuals in the swarm. Acceleration measurements show a clear short-range repulsion, which we confirm by considering the spatial statistics of the midges, but no conclusive long-range interactions. Measurements of the mean free path of the insects also suggest that individuals are on average very weakly coupled, but that they are also tightly bound to the swarm itself. Our results therefore suggest that some attractive interaction maintains cohesion of the swarms, but that this interaction is not as simple as an attraction to nearest neighbours.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schweizer, M.

This report summarizes progress during the past year on maturing Boron-11 magnetic resonance imaging (MRI) methodology for noninvasive determination of BNCT agents (BSH) spatially in time. Three major areas are excerpted: (1) Boron-11 MRI of BSH distributions in a canine intracranial tumor model and the first human glioblastoma patient, (2) whole body Boron-11 MRI of BSH pharmacokinetics in a rat flank tumor model, and (3) penetration of gadolinium salts through the BBB as a function of tumor growth in the canine brain.

Predictive Mechanisms Are Not Involved the Same Way during Human-Human vs. Human-Machine Interactions: A Review

PubMed Central

Sahaï, Aïsha; Pacherie, Elisabeth; Grynszpan, Ouriel; Berberian, Bruno

2017-01-01

Nowadays, interactions with others do not only involve human peers but also automated systems. Many studies suggest that the motor predictive systems that are engaged during action execution are also involved during joint actions with peers and during other human generated action observation. Indeed, the comparator model hypothesis suggests that the comparison between a predicted state and an estimated real state enables motor control, and by a similar functioning, understanding and anticipating observed actions. Such a mechanism allows making predictions about an ongoing action, and is essential to action regulation, especially during joint actions with peers. Interestingly, the same comparison process has been shown to be involved in the construction of an individual's sense of agency, both for self-generated and observed other human generated actions. However, the implication of such predictive mechanisms during interactions with machines is not consensual, probably due to the high heterogeneousness of the automata used in the experimentations, from very simplistic devices to full humanoid robots. The discrepancies that are observed during human/machine interactions could arise from the absence of action/observation matching abilities when interacting with traditional low-level automata. Consistently, the difficulties to build a joint agency with this kind of machines could stem from the same problem. In this context, we aim to review the studies investigating predictive mechanisms during social interactions with humans and with automated artificial systems. We will start by presenting human data that show the involvement of predictions in action control and in the sense of agency during social interactions. Thereafter, we will confront this literature with data from the robotic field. Finally, we will address the upcoming issues in the field of robotics related to automated systems aimed at acting as collaborative agents. PMID:29081744

Biology and clinical relevance of chemokines and chemokine receptors CXCR4 and CCR5 in human diseases

PubMed Central

Choi, Won-Tak; An, Jing

2014-01-01

Chemokines and their receptors are implicated in a wide range of human diseases, including acquired immune deficiency syndrome (AIDS). The entry of human immunodeficiency virus type 1 (HIV-1) into a cell is initiated by the interaction of the virus’s surface envelope proteins with two cell surface components of the target cell, namely CD4 and a chemokine co-receptor, usually CXCR4 or CCR5. Typical anti-HIV-1 agents include protease and reverse transcriptase inhibitors, but the targets of these agents tend to show rapid mutation rates. As such, strategies based on HIV-1 co-receptors have appeal because they target invariant host determinants. Chemokines and their receptors are also of general interest since they play important roles in numerous physiological and pathological processes in addition to AIDS. Therefore, intensive basic and translational research is ongoing for the dissection of their structure – function relationships in an effort to understand the molecular mechanism of chemokine – receptor interactions and signal transductions across cellular membranes. This paper reviews and discusses recent advances and the translation of new knowledge and discoveries into novel interventional strategies for clinical application. PMID:21565895

Solving Multiple Isolated, Interleaved, and Blended Tasks through Modular Neuroevolution.

PubMed

Schrum, Jacob; Miikkulainen, Risto

2016-01-01

Many challenging sequential decision-making problems require agents to master multiple tasks. For instance, game agents may need to gather resources, attack opponents, and defend against attacks. Learning algorithms can thus benefit from having separate policies for these tasks, and from knowing when each one is appropriate. How well this approach works depends on how tightly coupled the tasks are. Three cases are identified: Isolated tasks have distinct semantics and do not interact, interleaved tasks have distinct semantics but do interact, and blended tasks have regions where semantics from multiple tasks overlap. Learning across multiple tasks is studied in this article with Modular Multiobjective NEAT, a neuroevolution framework applied to three variants of the challenging Ms. Pac-Man video game. In the standard blended version of the game, a surprising, highly effective machine-discovered task division surpasses human-specified divisions, achieving the best scores to date in this game. In isolated and interleaved versions of the game, human-specified task divisions are also successful, though the best scores are surprisingly still achieved by machine discovery. Modular neuroevolution is thus shown to be capable of finding useful, unexpected task divisions better than those apparent to a human designer.

Identification of cytotoxic agents disrupting synovial sarcoma oncoprotein interactions by proximity ligation assay.

PubMed

Laporte, Aimée N; Ji, Jennifer X; Ma, Limin; Nielsen, Torsten O; Brodin, Bertha A

2016-06-07

Conventional cytotoxic therapies for synovial sarcoma provide limited benefit. Drugs specifically targeting the product of its driver translocation are currently unavailable, in part because the SS18-SSX oncoprotein functions via aberrant interactions within multiprotein complexes. Proximity ligation assay is a recently-developed method that assesses protein-protein interactions in situ. Here we report use of the proximity ligation assay to confirm the oncogenic association of SS18-SSX with its co-factor TLE1 in multiple human synovial sarcoma cell lines and in surgically-excised human tumor tissue. SS18-SSX/TLE1 interactions are disrupted by class I HDAC inhibitors and novel small molecule inhibitors. This assay can be applied in a high-throughput format for drug discovery in fusion-oncoprotein associated cancers where key effector partners are known.

A quantitative chemotherapy genetic interaction map reveals new factors associated with PARP inhibitor resistance | Office of Cancer Genomics

Cancer.gov

Nearly every cancer patient is treated with chemotherapy yet our understanding of factors that dictate response and resistance to such agents remains limited. We report the generation of a quantitative chemical-genetic interaction map in human mammary epithelial cells that charts the impact of knockdown of 625 cancer and DNA repair related genes on sensitivity to 29 drugs, covering all classes of cancer chemotherapeutics.

Humans, Topograpghy, and Wildland Fire: The Ingredients for Long-term Patterns in Ecosystems

Treesearch

Richard P. Guyette; Daniel C. Dey

2000-01-01

Three factors, human population density, topography, and culture interact to create temporal and spatial differences in the frequency of fire at the landscape level. These factors can be quantitatively related to fire frequency. The fire model can be used to reconstruct historic and to predict future frequency of fire in ecosystems, as well as to identify long-term...

Humans, topography, and wildland fire: The ingredients for long-term patterns in ecosystems

Treesearch

Richard P. Guyette; Daniel C. Dey

2000-01-01

Three factors, human population density, topography,and culture interact to create temporal and spatial differences in the frequency of fire at the landscape level. These facters can be quantitatively related to fire frequency. The fire model can be used to reconstruct historic and to predict future frequency of fire in ecosystems, as well as to identify long-term...

Toward a formal definition of water scarcity in natural human systems

Treesearch

W.K. Jaeger; A.J. Plantinga; H. Chang; K. Dello; G. Grant; D. Hulse; J.J. McDonnell; S. Lancaster; H. Moradkhani; A.T. Morzillo; P. Mote; A. Nolin; M. Santlemann; J. Wu

2013-01-01

Water scarcity may appear to be a simple concept, but it can be difficult to apply to complex natural-human systems. While aggregate scarcity indices are straightforward to compute, they do not adequately represent the spatial and temporal variations in water scarcity that arise from complex systems interactions. The uncertain effects of future climate change on water...

Spatial Control of Cell Transfection Using Soluble or Solid-Phase Redox Agents and a Redox-Active Ferrocenyl Lipid

PubMed Central

Aytar, Burcu S.; Muller, John P. E.; Kondo, Yukishige; Abbott, Nicholas L.; Lynn, David M.

2013-01-01

We report principles for active, user-defined control over the locations and timing with which DNA is expressed in cells. Our approach exploits unique properties of a ferrocenyl cationic lipid that is inactive when oxidized, but active when chemically reduced. We show that methods that exert spatial control over the administration of reducing agents can lead to local activation of lipoplexes and spatial control over gene expression. The versatility of this approach is demonstrated using both soluble and solid-phase reducing agents. These methods provide control over cell transfection, including methods for remote activation and the patterning of expression using solid-phase redox agents, that are difficult to achieve using conventional lipoplexes. PMID:23965341

Spatial control of cell transfection using soluble or solid-phase redox agents and a redox-active ferrocenyl lipid.

PubMed

Aytar, Burcu S; Muller, John P E; Kondo, Yukishige; Abbott, Nicholas L; Lynn, David M

2013-09-11

We report principles for active, user-defined control over the locations and timing with which DNA is expressed in cells. Our approach exploits unique properties of a ferrocenyl cationic lipid that is inactive when oxidized, but active when chemically reduced. We show that methods that exert spatial control over the administration of reducing agents can lead to local activation of lipoplexes and spatial control over gene expression. The versatility of this approach is demonstrated using both soluble and solid-phase reducing agents. These methods provide control over cell transfection, including methods for remote activation and the patterning of expression using solid-phase redox agents, that are difficult to achieve using conventional lipoplexes.

The role of noise in the spatial public goods game

NASA Astrophysics Data System (ADS)

Javarone, Marco Alberto; Battiston, Federico

2016-07-01

In this work we aim to analyze the role of noise in the spatial public goods game, one of the most famous games in evolutionary game theory. The dynamics of this game is affected by a number of parameters and processes, namely the topology of interactions among the agents, the synergy factor, and the strategy revision phase. The latter is a process that allows agents to change their strategy. Notably, rational agents tend to imitate richer neighbors, in order to increase the probability to maximize their payoff. By implementing a stochastic revision process, it is possible to control the level of noise in the system, so that even irrational updates may occur. In particular, in this work we study the effect of noise on the macroscopic behavior of a finite structured population playing the public goods game. We consider both the case of a homogeneous population, where the noise in the system is controlled by tuning a parameter representing the level of stochasticity in the strategy revision phase, and a heterogeneous population composed of a variable proportion of rational and irrational agents. In both cases numerical investigations show that the public goods game has a very rich behavior which strongly depends on the amount of noise in the system and on the value of the synergy factor. To conclude, our study sheds a new light on the relations between the microscopic dynamics of the public goods game and its macroscopic behavior, strengthening the link between the field of evolutionary game theory and statistical physics.

Tracking the establishment of local endemic populations of an emergent enteric pathogen

PubMed Central

Holt, Kathryn E.; Thieu Nga, Tran Vu; Thanh, Duy Pham; Vinh, Ha; Kim, Dong Wook; Vu Tra, My Phan; Campbell, James I.; Hoang, Nguyen Van Minh; Vinh, Nguyen Thanh; Minh, Pham Van; Thuy, Cao Thu; Nga, Tran Thi Thu; Thompson, Corinne; Dung, Tran Thi Ngoc; Nhu, Nguyen Thi Khanh; Vinh, Phat Voong; Tuyet, Pham Thi Ngoc; Phuc, Hoang Le; Lien, Nguyen Thi Nam; Phu, Bui Duc; Ai, Nguyen Thi Thuy; Tien, Nguyen Manh; Dong, Nguyen; Parry, Christopher M.; Hien, Tran Tinh; Farrar, Jeremy J.; Parkhill, Julian; Dougan, Gordon; Thomson, Nicholas R.; Baker, Stephen

2013-01-01

Shigella sonnei is a human-adapted pathogen that is emerging globally as the dominant agent of bacterial dysentery. To investigate local establishment, we sequenced the genomes of 263 Vietnamese S. sonnei isolated over 15 y. Our data show that S. sonnei was introduced into Vietnam in the 1980s and has undergone localized clonal expansion, punctuated by genomic fixation events through periodic selective sweeps. We uncover geographical spread, spatially restricted frontier populations, and convergent evolution through local gene pool sampling. This work provides a unique, high-resolution insight into the microevolution of a pioneering human pathogen during its establishment in a new host population. PMID:24082120

[Dinitrosyl iron complexes are endogenous signaling agents in animal and human cells and tissues (a hypothesis)].

PubMed

Vanin, A F

2004-01-01

The hypothesis was advanced that dinitrosyl iron complexes generated in animal and human cells and tissues producing nitric oxide can function as endogenous universal regulators of biochemical and physiological processes. This function is realized by the ability of dinitrosyl iron complexes to act as donors of free nitric oxide molecules interacting with the heme groups of proteins, nitrosonium ions, or Fe+(NO+)2 interacting with the thiol groups of proteins. The effect of dinitrosyl iron complexes on the activity of some enzymes and the expression of the genome at the translation and transcription levels was considered.

Host-pathogen interactions between the human innate immune system and Candida albicans—understanding and modeling defense and evasion strategies

PubMed Central

Dühring, Sybille; Germerodt, Sebastian; Skerka, Christine; Zipfel, Peter F.; Dandekar, Thomas; Schuster, Stefan

2015-01-01

The diploid, polymorphic yeast Candida albicans is one of the most important human pathogenic fungi. C. albicans can grow, proliferate and coexist as a commensal on or within the human host for a long time. However, alterations in the host environment can render C. albicans virulent. In this review, we describe the immunological cross-talk between C. albicans and the human innate immune system. We give an overview in form of pairs of human defense strategies including immunological mechanisms as well as general stressors such as nutrient limitation, pH, fever etc. and the corresponding fungal response and evasion mechanisms. Furthermore, Computational Systems Biology approaches to model and investigate these complex interactions are highlighted with a special focus on game-theoretical methods and agent-based models. An outlook on interesting questions to be tackled by Systems Biology regarding entangled defense and evasion mechanisms is given. PMID:26175718

Modelling human decision-making in coupled human and natural systems

NASA Astrophysics Data System (ADS)

Feola, G.

2012-12-01

A solid understanding of human decision-making is essential to analyze the complexity of coupled human and natural systems (CHANS) and inform policies to promote resilience in the face of environmental change. Human decisions drive and/or mediate the interactions and feedbacks, and contribute to the heterogeneity and non-linearity that characterize CHANS. However, human decision-making is usually over-simplistically modeled, whereby human agents are represented deterministically either as dumb or clairvoyant decision-makers. Decision-making models fall short in the integration of both environmental and human behavioral drivers, and concerning the latter, tend to focus on only one category, e.g. economic, cultural, or psychological. Furthermore, these models render a linear decision-making process and therefore fail to account for the recursive co-evolutionary dynamics in CHANS. As a result, these models constitute only a weak basis for policy-making. There is therefore scope and an urgent need for better approaches to human decision-making, to produce the knowledge that can inform vulnerability reduction policies in the face of environmental change. This presentation synthesizes the current state-of-the-art of modelling human decision-making in CHANS, with particular reference to agricultural systems, and delineates how the above mentioned shortcomings can be overcome. Through examples from research on pesticide use and adaptation to climate change, both based on the integrative agent-centered framework (Feola and Binder, 2010), the approach for an improved understanding of human agents in CHANS are illustrated. This entails: integrative approach, focus on behavioral dynamics more than states, feedbacks between individual and system levels, and openness to heterogeneity.

Human-scale interaction for virtual model displays: a clear case for real tools

NASA Astrophysics Data System (ADS)

Williams, George C.; McDowall, Ian E.; Bolas, Mark T.

1998-04-01

We describe a hand-held user interface for interacting with virtual environments displayed on a Virtual Model Display. The tool, constructed entirely of transparent materials, is see-through. We render a graphical counterpart of the tool on the display and map it one-to-one with the real tool. This feature, combined with a capability for touch- sensitive, discrete input, results in a useful spatial input device that is visually versatile. We discuss the tool's design and interaction techniques it supports. Briefly, we look at the human factors issues and engineering challenges presented by this tool and, in general, by the class of hand-held user interfaces that are see-through.

MyGeneFriends: A Social Network Linking Genes, Genetic Diseases, and Researchers.

PubMed

Allot, Alexis; Chennen, Kirsley; Nevers, Yannis; Poidevin, Laetitia; Kress, Arnaud; Ripp, Raymond; Thompson, Julie Dawn; Poch, Olivier; Lecompte, Odile

2017-06-16

The constant and massive increase of biological data offers unprecedented opportunities to decipher the function and evolution of genes and their roles in human diseases. However, the multiplicity of sources and flow of data mean that efficient access to useful information and knowledge production has become a major challenge. This challenge can be addressed by taking inspiration from Web 2.0 and particularly social networks, which are at the forefront of big data exploration and human-data interaction. MyGeneFriends is a Web platform inspired by social networks, devoted to genetic disease analysis, and organized around three types of proactive agents: genes, humans, and genetic diseases. The aim of this study was to improve exploration and exploitation of biological, postgenomic era big data. MyGeneFriends leverages conventions popularized by top social networks (Facebook, LinkedIn, etc), such as networks of friends, profile pages, friendship recommendations, affinity scores, news feeds, content recommendation, and data visualization. MyGeneFriends provides simple and intuitive interactions with data through evaluation and visualization of connections (friendships) between genes, humans, and diseases. The platform suggests new friends and publications and allows agents to follow the activity of their friends. It dynamically personalizes information depending on the user's specific interests and provides an efficient way to share information with collaborators. Furthermore, the user's behavior itself generates new information that constitutes an added value integrated in the network, which can be used to discover new connections between biological agents. We have developed MyGeneFriends, a Web platform leveraging conventions from popular social networks to redefine the relationship between humans and biological big data and improve human processing of biomedical data. MyGeneFriends is available at lbgi.fr/mygenefriends. ©Alexis Allot, Kirsley Chennen, Yannis Nevers, Laetitia Poidevin, Arnaud Kress, Raymond Ripp, Julie Dawn Thompson, Olivier Poch, Odile Lecompte. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 16.06.2017.

Dynamics of deceptive interactions in social networks.

PubMed

Barrio, Rafael A; Govezensky, Tzipe; Dunbar, Robin; Iñiguez, Gerardo; Kaski, Kimmo

2015-11-06

In this paper, we examine the role of lies in human social relations by implementing some salient characteristics of deceptive interactions into an opinion formation model, so as to describe the dynamical behaviour of a social network more realistically. In this model, we take into account such basic properties of social networks as the dynamics of the intensity of interactions, the influence of public opinion and the fact that in every human interaction it might be convenient to deceive or withhold information depending on the instantaneous situation of each individual in the network. We find that lies shape the topology of social networks, especially the formation of tightly linked, small communities with loose connections between them. We also find that agents with a larger proportion of deceptive interactions are the ones that connect communities of different opinion, and, in this sense, they have substantial centrality in the network. We then discuss the consequences of these results for the social behaviour of humans and predict the changes that could arise due to a varying tolerance for lies in society. © 2015 The Author(s).

Modeling Being "Lost": Imperfect Situation Awareness

NASA Technical Reports Server (NTRS)

Middleton, Victor E.

2011-01-01

Being "lost" is an exemplar of imperfect Situation Awareness/Situation Understanding (SA/SU) -- information/knowledge that is uncertain, incomplete, and/or just wrong. Being "lost" may be a geo-spatial condition - not knowing/being wrong about where to go or how to get there. More broadly, being "lost" can serve as a metaphor for uncertainty and/or inaccuracy - not knowing/being wrong about how one fits into a larger world view, what one wants to do, or how to do it. This paper discusses using agent based modeling (ABM) to explore imperfect SA/SU, simulating geo-spatially "lost" intelligent agents trying to navigate in a virtual world. Each agent has a unique "mental map" -- its idiosyncratic view of its geo-spatial environment. Its decisions are based on this idiosyncratic view, but behavior outcomes are based on ground truth. Consequently, the rate and degree to which an agent's expectations diverge from ground truth provide measures of that agent's SA/SU.

Age-Related Inducibility of Carboxylesterases by the Antiepileptic Agent Phenobarbital and Implications in Drug Metabolism and Lipid Accumulation 1, 2

PubMed Central

Xiao, Da; Chen, Yi-Tzai; Yang, Dongfang; Yan, Bingfang

2014-01-01

Carboxylesterases (CES) constitute a class of hydrolytic enzymes that play critical roles in drug metabolism and lipid mobilization. Previous studies with a large number of human liver samples have suggested that the inducibility of carboxylesterases is inversely related with age. To directly test this possibility, neonatal (10 days of age) and adult mice were treated with the antiepileptic agent phenobarbital. The expression and hydrolytic activity were determined on six major carboxylesterases including ces1d, the ortholog of human CES1. Without exception, all carboxylesterases tested were induced to a greater extent in neonatal than adult mice. The induction was detected at mRNA, protein and catalytic levels. Ces1d was greatly induced and found to rapidly hydrolyze the antiplatelet agent clopidogrel and support the accumulation of neutral lipids. Phenobarbital represents a large number of therapeutic agents that induce drug metabolizing enzymes and transporters in a species-conserved manner. The higher inducibility of carboxylesterases in the developmental age likely represents a general phenomenon cross species including human. Consequently, individuals in the developmental age may experience greater drug-drug interactions. The greater induction of ces1d also provides a molecular explanation to the clinical observation that children on antiepileptic drugs increase plasma lipids. PMID:22513142

Human Robotic Swarm Interaction Using an Artificial Physics Approach

DTIC Science & Technology

2014-12-01

calculates virtual forces that are summed and translated into velocity commands. The virtual forces are modeled after real physical forces such as...results from the physical experiments show that an artificial physics-based framework is an effective way to allow multiple agents to follow a human... modeled after real physical forces such as gravitational and Coulomb, forces but are not restricted to them, for example, the force magnitude may not be

Co-Binding of Pharmaceutical Compounds at Mineral Surfaces: Molecular Investigations of Dimer Formation at Goethite/Water Interfaces.

PubMed

Xu, Jing; Marsac, Rémi; Costa, Dominique; Cheng, Wei; Wu, Feng; Boily, Jean-François; Hanna, Khalil

2017-08-01

The emergence of antibiotic and anti-inflammatory agents in aquatic and terrestrial systems is becoming a serious threat to human and animal health worldwide. Because pharmaceutical compounds rarely exist individually in nature, interactions between various compounds can have unforeseen effects on their binding to mineral surfaces. This work demonstrates this important possibility for the case of two typical antibiotic and anti-inflammatory agents (nalidixic acid (NA) and niflumic acid (NFA)) bound at goethite (α-FeOOH) used as a model mineral surface. Our multidisciplinary study, which makes use of batch sorption experiments, vibration spectroscopy and periodic density functional theory calculations, reveals enhanced binding of the otherwise weakly bound NFA caused by unforeseen intermolecular interactions with mineral-bound NA. This enhancement is ascribed to the formation of a NFA-NA dimer whose energetically favored formation (-0.5 eV compared to free molecules) is predominantly driven by van der Waals interactions. A parallel set of efforts also showed that no cobinding occurred with sulfamethoxazole (SMX) because of the lack of molecular interactions with coexisting contaminants. As such, this article raises the importance of recognizing drug cobinding, and lack of cobinding, for predicting and developing policies on the fate of complex mixtures of antibiotics and anti-inflammatory agents in nature.

Bimolecular interaction of argpyrimidine (a Maillard reaction product) in in vitro non-enzymatic protein glycation model and its potential role as an antiglycating agent.

PubMed

Bhattacherjee, Abhishek; Dhara, Kaliprasanna; Chakraborti, Abhay Sankar

2017-09-01

Non- enzymatic glycation, also known as Maillard reaction, is one of the most important and investigated reactions in biochemistry. Maillard reaction products (MRPs) like protein-derived advanced glycation end products (AGEs) are often referred to cause pathophysiological complications in human systems. On contrary, several MRPs are exogenously used as antioxidant, antimicrobial and flavouring agents. In the preset study, we have shown that argpyrimidine, a well-established AGE, interacts with bovine serum albumin (BSA) and glucose individually in standard BSA-glucose model system and successfully inhibits glycation of the protein. Bimolecular interaction of argpyrimidine with glucose or BSA has been studied independently. Chromatographic purification, different spectroscopic studies and molecular modeling have been used to evaluate the nature and pattern of interactions. Binding of argpyrimidine with BSA prevents incorporation of glucose inside the native protein. Argpyrimidine can also directly entrap glucose. Both these interactions may be associated with the antiglycation potential of argpyrimidine, indicating a beneficial function of an AGE. Copyright © 2017 Elsevier B.V. All rights reserved.

Hippocampal structure and human cognition: key role of spatial processing and evidence supporting the efficiency hypothesis in females

PubMed Central

Colom, Roberto; Stein, Jason L.; Rajagopalan, Priya; Martínez, Kenia; Hermel, David; Wang, Yalin; Álvarez-Linera, Juan; Burgaleta, Miguel; Quiroga, MªÁngeles; Shih, Pei Chun; Thompson, Paul M.

2014-01-01

Here we apply a method for automated segmentation of the hippocampus in 3D high-resolution structural brain MRI scans. One hundred and four healthy young adults completed twenty one tasks measuring abstract, verbal, and spatial intelligence, along with working memory, executive control, attention, and processing speed. After permutation tests corrected for multiple comparisons across vertices (p < .05) significant relationships were found for spatial intelligence, spatial working memory, and spatial executive control. Interactions with sex revealed significant relationships with the general factor of intelligence (g), along with abstract and spatial intelligence. These correlations were mainly positive for males but negative for females, which might support the efficiency hypothesis in women. Verbal intelligence, attention, and processing speed were not related to hippocampal structural differences. PMID:25632167

Moving attractive virtual agent improves interpersonal coordination stability.

PubMed

Zhao, Zhong; Salesse, Robin N; Gueugnon, Mathieu; Schmidt, Richard C; Marin, Ludovic; Bardy, Benoît G

2015-06-01

Interpersonal motor coordination is influenced not only by biomechanical factors such as coordination pattern, oscillating frequency, and individual differences, but also by psychosocial factor such as likability and social competences. Based on the social stereotype of "what is beautiful is good", the present study aimed at investigating whether people coordinate differently with physically attractive people compared to less attractive people. 34 participants were engaged in an interpersonal coordination task with different looking (virtual) agents while performing at the same time a reaction time task. Results showed that participants had more stable motor coordination with the moving attractive than with the less attractive agent, and that the difference in motor coordination could not be interpreted by a specific attention allocation strategy. Our findings provide the evidence that physical attractiveness genuinely affects how people interact with another person, and that the temporal-spatial coordinated movement varies with the partner's psychosocial characteristics. The study broadens the perspective of exploring the effect of additional psychosocial factors on social motor coordination. Copyright © 2015 Elsevier B.V. All rights reserved.

Pharmacological validation of Trypanosoma brucei phosphodiesterases B1 and B2 as druggable targets for African sleeping sickness.

PubMed

Bland, Nicholas D; Wang, Cuihua; Tallman, Craig; Gustafson, Alden E; Wang, Zhouxi; Ashton, Trent D; Ochiana, Stefan O; McAllister, Gregory; Cotter, Kristina; Fang, Anna P; Gechijian, Lara; Garceau, Norman; Gangurde, Rajiv; Ortenberg, Ron; Ondrechen, Mary Jo; Campbell, Robert K; Pollastri, Michael P

2011-12-08

Neglected tropical disease drug discovery requires application of pragmatic and efficient methods for development of new therapeutic agents. In this report, we describe our target repurposing efforts for the essential phosphodiesterase (PDE) enzymes TbrPDEB1 and TbrPDEB2 of Trypanosoma brucei , the causative agent for human African trypanosomiasis (HAT). We describe protein expression and purification, assay development, and benchmark screening of a collection of 20 established human PDE inhibitors. We disclose that the human PDE4 inhibitor piclamilast, and some of its analogues, show modest inhibition of TbrPDEB1 and B2 and quickly kill the bloodstream form of the subspecies T. brucei brucei . We also report the development of a homology model of TbrPDEB1 that is useful for understanding the compound-enzyme interactions and for comparing the parasitic and human enzymes. Our profiling and early medicinal chemistry results strongly suggest that human PDE4 chemotypes represent a better starting point for optimization of TbrPDEB inhibitors than those that target any other human PDEs.

Graceful Failure and Societal Resilience Analysis Via Agent-Based Modeling and Simulation

NASA Astrophysics Data System (ADS)

Schopf, P. S.; Cioffi-Revilla, C.; Rogers, J. D.; Bassett, J.; Hailegiorgis, A. B.

2014-12-01

Agent-based social modeling is opening up new methodologies for the study of societal response to weather and climate hazards, and providing measures of resiliency that can be studied in many contexts, particularly in coupled human and natural-technological systems (CHANTS). Since CHANTS are complex adaptive systems, societal resiliency may or may not occur, depending on dynamics that lack closed form solutions. Agent-based modeling has been shown to provide a viable theoretical and methodological approach for analyzing and understanding disasters and societal resiliency in CHANTS. Our approach advances the science of societal resilience through computational modeling and simulation methods that complement earlier statistical and mathematical approaches. We present three case studies of social dynamics modeling that demonstrate the use of these agent based models. In Central Asia, we exmaine mutltiple ensemble simulations with varying climate statistics to see how droughts and zuds affect populations, transmission of wealth across generations, and the overall structure of the social system. In Eastern Africa, we explore how successive episodes of drought events affect the adaptive capacity of rural households. Human displacement, mainly, rural to urban migration, and livelihood transition particularly from pastoral to farming are observed as rural households interacting dynamically with the biophysical environment and continually adjust their behavior to accommodate changes in climate. In the far north case we demonstrate one of the first successful attempts to model the complete climate-permafrost-infrastructure-societal interaction network as a complex adaptive system/CHANTS implemented as a ``federated'' agent-based model using evolutionary computation. Analysis of population changes resulting from extreme weather across these and other cases provides evidence for the emergence of new steady states and shifting patterns of resilience.

Smile! Social reward drives attention.

PubMed

Hayward, Dana A; Pereira, Effie J; Otto, A Ross; Ristic, Jelena

2018-02-01

Human social behavior is fine-tuned by interactions between individuals and their environments. Here we show that social motivation plays an important role in this process. Using a novel manipulation of social reward that included elements of real-life social exchanges, we demonstrate the emergence of attentional orienting for coincidental spatial associations that received positive social reward. After an interaction with the experimenter, participants completed a computerized task in which they received positive, negative, or no social reward for their performance to spatially congruent, spatially incongruent, and neutral cue-target pairings, respectively. Even though cue-target spatial correspondences remained at chance, attentional benefits emerged and persisted a day later for targets that received positive social reward. Our data further revealed that participants' level of social competence, as measured by the Autism-Spectrum Quotient scale, was predictably related to the magnitude of their reward-driven attentional benefits. No attentional effects emerged when the social interaction and social reward manipulations were removed. These results show that motivational incentives available during social exchanges affect later individual cognitive functioning, providing one of the first insights into why seemingly ambiguous social signals produce reliable and persistent attentional effects. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Spatial and temporal coherence in perceptual binding

PubMed Central

Blake, Randolph; Yang, Yuede

1997-01-01

Component visual features of objects are registered by distributed patterns of activity among neurons comprising multiple pathways and visual areas. How these distributed patterns of activity give rise to unified representations of objects remains unresolved, although one recent, controversial view posits temporal coherence of neural activity as a binding agent. Motivated by the possible role of temporal coherence in feature binding, we devised a novel psychophysical task that requires the detection of temporal coherence among features comprising complex visual images. Results show that human observers can more easily detect synchronized patterns of temporal contrast modulation within hybrid visual images composed of two components when those components are drawn from the same original picture. Evidently, time-varying changes within spatially coherent features produce more salient neural signals. PMID:9192701

Reinforcement Learning Multi-Agent Modeling of Decision-Making Agents for the Study of Transboundary Surface Water Conflicts with Application to the Syr Darya River Basin

NASA Astrophysics Data System (ADS)

Riegels, N.; Siegfried, T.; Pereira Cardenal, S. J.; Jensen, R. A.; Bauer-Gottwein, P.

2008-12-01

In most economics--driven approaches to optimizing water use at the river basin scale, the system is modelled deterministically with the goal of maximizing overall benefits. However, actual operation and allocation decisions must be made under hydrologic and economic uncertainty. In addition, river basins often cross political boundaries, and different states may not be motivated to cooperate so as to maximize basin- scale benefits. Even within states, competing agents such as irrigation districts, municipal water agencies, and large industrial users may not have incentives to cooperate to realize efficiency gains identified in basin- level studies. More traditional simulation--optimization approaches assume pre-commitment by individual agents and stakeholders and unconditional compliance on each side. While this can help determine attainable gains and tradeoffs from efficient management, such hardwired policies do not account for dynamic feedback between agents themselves or between agents and their environments (e.g. due to climate change etc.). In reality however, we are dealing with an out-of-equilibrium multi-agent system, where there is neither global knowledge nor global control, but rather continuous strategic interaction between decision making agents. Based on the theory of stochastic games, we present a computational framework that allows for studying the dynamic feedback between decision--making agents themselves and an inherently uncertain environment in a spatially and temporally distributed manner. Agents with decision-making control over water allocation such as countries, irrigation districts, and municipalities are represented by reinforcement learning agents and coupled to a detailed hydrologic--economic model. This approach emphasizes learning by agents from their continuous interaction with other agents and the environment. It provides a convenient framework for the solution of the problem of dynamic decision-making in a mixed cooperative / non-cooperative environment with which different institutional setups and incentive systems can be studied so to identify reasonable ways to reach desirable, Pareto--optimal allocation outcomes. Preliminary results from an application to the Syr Darya river basin in Central Asia will be presented and discussed. The Syr Darya River is a classic example of a transboundary river basin in which basin-wide efficiency gains identified in optimization studies have not been sufficient to induce cooperative management of the river by the riparian states.

Tissue Distribution of the Ehrlichia muris-Like Agent in a Tick Vector

PubMed Central

Lynn, Geoffrey E.; Oliver, Jonathan D.; Nelson, Curtis M.; Felsheim, Roderick F.; Kurtti, Timothy J.; Munderloh, Ulrike G.

2015-01-01

Human pathogens transmitted by ticks undergo complex life cycles alternating between the arthropod vector and a mammalian host. While the latter has been investigated to a greater extent, examination of the biological interactions between microbes and the ticks that carry them presents an equally important opportunity for disruption of the disease cycle. In this study, we used in situ hybridization to demonstrate infection by the Ehrlichia muris-like organism, a newly recognized human pathogen, of Ixodes scapularis ticks, a primary vector for several important human disease agents. This allowed us to assess whole sectioned ticks for the patterns of tissue invasion, and demonstrate generalized dissemination of ehrlichiae in a variety of cell types and organs within ticks infected naturally via blood feeding. Electron microscopy was used to confirm these results. Here we describe a strong ehrlichial affinity for epithelial cells, neuronal cells of the synganglion, salivary glands, and male accessory glands. PMID:25781930

Communicative mind-reading in preverbal infants.

PubMed

Tauzin, Tibor; Gergely, György

2018-06-22

Pragmatic theories of communication assume that humans evolved a species-unique inferential capacity to express and recognize intentions via communicative actions. We show that 13-month-old non-verbal infants can interpret the turn-taking exchange of variable tone sequences between unfamiliar agents as indicative of communicative transfer of goal-relevant information from a knowledgeable to a naïve agent pursuing the goal. No such inference of information transfer was drawn by the infants, however, when a) the agents exchanged fully predictable identical signal sequences, which does not enable transmission of new information, or b) when no goal-relevant contextual change was observed that would motivate its communicative transmission. These results demonstrate that young infants can recognize communicative interactions between third-party agents and possess an evolved capacity for communicative mind-reading that enables them to infer what contextually relevant information has been transmitted between the agents even without language.

Faithful teleportation of multi-particle states involving multi spatially remote agents via probabilistic channels

NASA Astrophysics Data System (ADS)

Jiang, Min; Li, Hui; Zhang, Zeng-ke; Zeng, Jia

2011-02-01

We present an approach to faithfully teleport an unknown quantum state of entangled particles in a multi-particle system involving multi spatially remote agents via probabilistic channels. In our scheme, the integrity of an entangled multi-particle state can be maintained even when the construction of a faithful channel fails. Furthermore, in a quantum teleportation network, there are generally multi spatially remote agents which play the role of relay nodes between a sender and a distant receiver. Hence, we propose two schemes for directly and indirectly constructing a faithful channel between the sender and the distant receiver with the assistance of relay agents, respectively. Our results show that the required auxiliary particle resources, local operations and classical communications are considerably reduced for the present purpose.

EEG Source Reconstruction Reveals Frontal-Parietal Dynamics of Spatial Conflict Processing

PubMed Central

Cohen, Michael X; Ridderinkhof, K. Richard

2013-01-01

Cognitive control requires the suppression of distracting information in order to focus on task-relevant information. We applied EEG source reconstruction via time-frequency linear constrained minimum variance beamforming to help elucidate the neural mechanisms involved in spatial conflict processing. Human subjects performed a Simon task, in which conflict was induced by incongruence between spatial location and response hand. We found an early (∼200 ms post-stimulus) conflict modulation in stimulus-contralateral parietal gamma (30–50 Hz), followed by a later alpha-band (8–12 Hz) conflict modulation, suggesting an early detection of spatial conflict and inhibition of spatial location processing. Inter-regional connectivity analyses assessed via cross-frequency coupling of theta (4–8 Hz), alpha, and gamma power revealed conflict-induced shifts in cortical network interactions: Congruent trials (relative to incongruent trials) had stronger coupling between frontal theta and stimulus-contrahemifield parietal alpha/gamma power, whereas incongruent trials had increased theta coupling between medial frontal and lateral frontal regions. These findings shed new light into the large-scale network dynamics of spatial conflict processing, and how those networks are shaped by oscillatory interactions. PMID:23451201

Towards optimization of an organotypic assay system that imitates human hair follicle-like epithelial-mesenchymal interactions.

PubMed

Havlickova, B; Bíró, T; Mescalchin, A; Arenberger, P; Paus, R

2004-10-01

Human hair growth can currently be studied in vitro by the use of organ-cultured scalp hair follicles (HFs). However, simplified organotypic systems are needed for dissecting the underlying epithelial-mesenchymal interactions and as screening tools for candidate hair growth-modulatory agents. To optimize the design and culture conditions of previously published organotypic systems that imitate epithelial-mesenchymal interactions in the human HF as closely as possible. Continuous submerged organotypic 'sandwich' cultures were established. These consist of a pseudodermis (collagen I mixed with and contracted by human interfollicular dermal fibroblasts) on which one of two upper layers is placed: either a mixture of Matrigel basement membrane matrix (BD Biosciences, Bedford, MA, U.S.A.) and follicular dermal papilla fibroblasts (DPC), with outer root sheath keratinocytes (ORSK) layered on the top ('layered' system), or a mixture of Matrigel, DPC and ORSK ('mixed' system). Morphological and functional characteristics of these 'folliculoid sandwiches' were then assessed by routine histology, histomorphometry and immunohistochemistry. In both 'layered' and 'mixed' systems, the ORSK formed spheroid epithelial cell aggregates, which retained their characteristic keratin expression pattern (i.e. cytokeratin 6). In the 'mixed' sandwich model the size of the epithelial cell aggregates was smaller, but the numbers of ORSK were significantly higher than in the 'layered' model at day 14 in the culture. ORSK proliferated better in the 'mixed' than in the 'layered' sandwich system, regardless of the calcium or serum content of the media, whereas apoptosis of ORSK was lowest in the 'mixed' system in serum-free, low calcium medium. The kinetics of proliferation and apoptosis of DPC, which retained their characteristic expression of versican, were similar in both systems. However, proliferation and apoptosis of DPC were higher in the presence of serum and/or under high calcium conditions. Our results underscore the importance of structural design and medium composition for epithelial-mesenchymal interactions as they occur in the human HF. Specifically, we report a new organotypic submerged 'folliculoid sandwich' system with serum-free, low calcium medium and a mixture of interacting human DPC and ORSK, which offers several advantages over previously available assays. This system allows the standardized assessment of the effects of a test agent on the proliferation, apoptosis and key marker expression of human ORSK and DPC under substantially simplified in vitro conditions which approximate the in vivo situation.

Synchronization of multi-agent systems with metric-topological interactions.

PubMed

Wang, Lin; Chen, Guanrong

2016-09-01

A hybrid multi-agent systems model integrating the advantages of both metric interaction and topological interaction rules, called the metric-topological model, is developed. This model describes planar motions of mobile agents, where each agent can interact with all the agents within a circle of a constant radius, and can furthermore interact with some distant agents to reach a pre-assigned number of neighbors, if needed. Some sufficient conditions imposed only on system parameters and agent initial states are presented, which ensure achieving synchronization of the whole group of agents. It reveals the intrinsic relationships among the interaction range, the speed, the initial heading, and the density of the group. Moreover, robustness against variations of interaction range, density, and speed are investigated by comparing the motion patterns and performances of the hybrid metric-topological interaction model with the conventional metric-only and topological-only interaction models. Practically in all cases, the hybrid metric-topological interaction model has the best performance in the sense of achieving highest frequency of synchronization, fastest convergent rate, and smallest heading difference.

Cumulative human impacts on marine predators.

PubMed

Maxwell, Sara M; Hazen, Elliott L; Bograd, Steven J; Halpern, Benjamin S; Breed, Greg A; Nickel, Barry; Teutschel, Nicole M; Crowder, Larry B; Benson, Scott; Dutton, Peter H; Bailey, Helen; Kappes, Michelle A; Kuhn, Carey E; Weise, Michael J; Mate, Bruce; Shaffer, Scott A; Hassrick, Jason L; Henry, Robert W; Irvine, Ladd; McDonald, Birgitte I; Robinson, Patrick W; Block, Barbara A; Costa, Daniel P

2013-01-01

Stressors associated with human activities interact in complex ways to affect marine ecosystems, yet we lack spatially explicit assessments of cumulative impacts on ecologically and economically key components such as marine predators. Here we develop a metric of cumulative utilization and impact (CUI) on marine predators by combining electronic tracking data of eight protected predator species (n=685 individuals) in the California Current Ecosystem with data on 24 anthropogenic stressors. We show significant variation in CUI with some of the highest impacts within US National Marine Sanctuaries. High variation in underlying species and cumulative impact distributions means that neither alone is sufficient for effective spatial management. Instead, comprehensive management approaches accounting for both cumulative human impacts and trade-offs among multiple stressors must be applied in planning the use of marine resources.

Co-culturing of Fungal Strains Against Botrytis cinerea as a Model for the Induction of Chemical Diversity and Therapeutic Agents

PubMed Central

Serrano, Rachel; González-Menéndez, Víctor; Rodríguez, Lorena; Martín, Jesús; Tormo, José R.; Genilloud, Olga

2017-01-01

New fungal SMs (SMs) have been successfully described to be produced by means of in vitro-simulated microbial community interactions. Co-culturing of fungi has proved to be an efficient way to induce cell–cell interactions that can promote the activation of cryptic pathways, frequently silent when the strains are grown in laboratory conditions. Filamentous fungi represent one of the most diverse microbial groups known to produce bioactive natural products. Triggering the production of novel antifungal compounds in fungi could respond to the current needs to fight health compromising pathogens and provide new therapeutic solutions. In this study, we have selected the fungus Botrytis cinerea as a model to establish microbial interactions with a large set of fungal strains related to ecosystems where they can coexist with this phytopathogen, and to generate a collection of extracts, obtained from their antagonic microbial interactions and potentially containing new bioactive compounds. The antifungal specificity of the extracts containing compounds induced after B. cinerea interaction was determined against two human fungal pathogens (Candida albicans and Aspergillus fumigatus) and three phytopathogens (Colletotrichum acutatum, Fusarium proliferatum, and Magnaporthe grisea). In addition, their cytotoxicity was also evaluated against the human hepatocellular carcinoma cell line (HepG2). We have identified by LC-MS the production of a wide variety of known compounds induced from these fungal interactions, as well as novel molecules that support the potential of this approach to generate new chemical diversity and possible new therapeutic agents. PMID:28469610