Representing Micro-Macro Linkages by Actor-Based Dynamic Network Models

PubMed Central

Snijders, Tom A.B.; Steglich, Christian E.G.

2014-01-01

Stochastic actor-based models for network dynamics have the primary aim of statistical inference about processes of network change, but may be regarded as a kind of agent-based models. Similar to many other agent-based models, they are based on local rules for actor behavior. Different from many other agent-based models, by including elements of generalized linear statistical models they aim to be realistic detailed representations of network dynamics in empirical data sets. Statistical parallels to micro-macro considerations can be found in the estimation of parameters determining local actor behavior from empirical data, and the assessment of goodness of fit from the correspondence with network-level descriptives. This article studies several network-level consequences of dynamic actor-based models applied to represent cross-sectional network data. Two examples illustrate how network-level characteristics can be obtained as emergent features implied by micro-specifications of actor-based models. PMID:25960578

Requirements Modeling with Agent Programming

NASA Astrophysics Data System (ADS)

Dasgupta, Aniruddha; Krishna, Aneesh; Ghose, Aditya K.

Agent-oriented conceptual modeling notations are highly effective in representing requirements from an intentional stance and answering questions such as what goals exist, how key actors depend on each other, and what alternatives must be considered. In this chapter, we review an approach to executing i* models by translating these into set of interacting agents implemented in the CASO language and suggest how we can perform reasoning with requirements modeled (both functional and non-functional) using i* models. In this chapter we particularly incorporate deliberation into the agent design. This allows us to benefit from the complementary representational capabilities of the two frameworks.

Promoting motivation with virtual agents and avatars: role of visual presence and appearance.

PubMed

Baylor, Amy L

2009-12-12

Anthropomorphic virtual agents can serve as powerful technological mediators to impact motivational outcomes such as self-efficacy and attitude change. Such anthropomorphic agents can be designed as simulated social models in the Bandurian sense, providing social influence as virtual 'role models'. Of particular value is the capacity for designing such agents as optimized social models for a target audience and context. Importantly, the visual presence and appearance of such agents can have a major impact on motivation and affect regardless of the underlying technical sophistication. Empirical results of different instantiations of agent presence and appearance are reviewed for both autonomous virtual agents and avatars that represent a user.

A hybrid agent-based approach for modeling microbiological systems.

PubMed

Guo, Zaiyi; Sloot, Peter M A; Tay, Joc Cing

2008-11-21

Models for systems biology commonly adopt Differential Equations or Agent-Based modeling approaches for simulating the processes as a whole. Models based on differential equations presuppose phenomenological intracellular behavioral mechanisms, while models based on Multi-Agent approach often use directly translated, and quantitatively less precise if-then logical rule constructs. We propose an extendible systems model based on a hybrid agent-based approach where biological cells are modeled as individuals (agents) while molecules are represented by quantities. This hybridization in entity representation entails a combined modeling strategy with agent-based behavioral rules and differential equations, thereby balancing the requirements of extendible model granularity with computational tractability. We demonstrate the efficacy of this approach with models of chemotaxis involving an assay of 10(3) cells and 1.2x10(6) molecules. The model produces cell migration patterns that are comparable to laboratory observations.

Modelling of robotic work cells using agent based-approach

NASA Astrophysics Data System (ADS)

Sękala, A.; Banaś, W.; Gwiazda, A.; Monica, Z.; Kost, G.; Hryniewicz, P.

2016-08-01

In the case of modern manufacturing systems the requirements, both according the scope and according characteristics of technical procedures are dynamically changing. This results in production system organization inability to keep up with changes in a market demand. Accordingly, there is a need for new design methods, characterized, on the one hand with a high efficiency and on the other with the adequate level of the generated organizational solutions. One of the tools that could be used for this purpose is the concept of agent systems. These systems are the tools of artificial intelligence. They allow assigning to agents the proper domains of procedures and knowledge so that they represent in a self-organizing system of an agent environment, components of a real system. The agent-based system for modelling robotic work cell should be designed taking into consideration many limitations considered with the characteristic of this production unit. It is possible to distinguish some grouped of structural components that constitute such a system. This confirms the structural complexity of a work cell as a specific production system. So it is necessary to develop agents depicting various aspects of the work cell structure. The main groups of agents that are used to model a robotic work cell should at least include next pattern representatives: machine tool agents, auxiliary equipment agents, robots agents, transport equipment agents, organizational agents as well as data and knowledge bases agents. In this way it is possible to create the holarchy of the agent-based system.

Ensuring congruency in multiscale modeling: towards linking agent based and continuum biomechanical models of arterial adaptation.

PubMed

Hayenga, Heather N; Thorne, Bryan C; Peirce, Shayn M; Humphrey, Jay D

2011-11-01

There is a need to develop multiscale models of vascular adaptations to understand tissue-level manifestations of cellular level mechanisms. Continuum-based biomechanical models are well suited for relating blood pressures and flows to stress-mediated changes in geometry and properties, but less so for describing underlying mechanobiological processes. Discrete stochastic agent-based models are well suited for representing biological processes at a cellular level, but not for describing tissue-level mechanical changes. We present here a conceptually new approach to facilitate the coupling of continuum and agent-based models. Because of ubiquitous limitations in both the tissue- and cell-level data from which one derives constitutive relations for continuum models and rule-sets for agent-based models, we suggest that model verification should enforce congruency across scales. That is, multiscale model parameters initially determined from data sets representing different scales should be refined, when possible, to ensure that common outputs are consistent. Potential advantages of this approach are illustrated by comparing simulated aortic responses to a sustained increase in blood pressure predicted by continuum and agent-based models both before and after instituting a genetic algorithm to refine 16 objectively bounded model parameters. We show that congruency-based parameter refinement not only yielded increased consistency across scales, it also yielded predictions that are closer to in vivo observations.

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.

Mathematical modeling of malaria infection with innate and adaptive immunity in individuals and agent-based communities.

PubMed

Gurarie, David; Karl, Stephan; Zimmerman, Peter A; King, Charles H; St Pierre, Timothy G; Davis, Timothy M E

2012-01-01

Agent-based modeling of Plasmodium falciparum infection offers an attractive alternative to the conventional Ross-Macdonald methodology, as it allows simulation of heterogeneous communities subjected to realistic transmission (inoculation patterns). We developed a new, agent based model that accounts for the essential in-host processes: parasite replication and its regulation by innate and adaptive immunity. The model also incorporates a simplified version of antigenic variation by Plasmodium falciparum. We calibrated the model using data from malaria-therapy (MT) studies, and developed a novel calibration procedure that accounts for a deterministic and a pseudo-random component in the observed parasite density patterns. Using the parasite density patterns of 122 MT patients, we generated a large number of calibrated parameters. The resulting data set served as a basis for constructing and simulating heterogeneous agent-based (AB) communities of MT-like hosts. We conducted several numerical experiments subjecting AB communities to realistic inoculation patterns reported from previous field studies, and compared the model output to the observed malaria prevalence in the field. There was overall consistency, supporting the potential of this agent-based methodology to represent transmission in realistic communities. Our approach represents a novel, convenient and versatile method to model Plasmodium falciparum infection.

An Agent-Based Modeling Template for a Cohort of Veterans with Diabetic Retinopathy.

PubMed

Day, Theodore Eugene; Ravi, Nathan; Xian, Hong; Brugh, Ann

2013-01-01

Agent-based models are valuable for examining systems where large numbers of discrete individuals interact with each other, or with some environment. Diabetic Veterans seeking eye care at a Veterans Administration hospital represent one such cohort. The objective of this study was to develop an agent-based template to be used as a model for a patient with diabetic retinopathy (DR). This template may be replicated arbitrarily many times in order to generate a large cohort which is representative of a real-world population, upon which in-silico experimentation may be conducted. Agent-based template development was performed in java-based computer simulation suite AnyLogic Professional 6.6. The model was informed by medical data abstracted from 535 patient records representing a retrospective cohort of current patients of the VA St. Louis Healthcare System Eye clinic. Logistic regression was performed to determine the predictors associated with advancing stages of DR. Predicted probabilities obtained from logistic regression were used to generate the stage of DR in the simulated cohort. The simulated cohort of DR patients exhibited no significant deviation from the test population of real-world patients in proportion of stage of DR, duration of diabetes mellitus (DM), or the other abstracted predictors. Simulated patients after 10 years were significantly more likely to exhibit proliferative DR (P<0.001). Agent-based modeling is an emerging platform, capable of simulating large cohorts of individuals based on manageable data abstraction efforts. The modeling method described may be useful in simulating many different conditions where course of disease is described in categorical stages.

Evolvable social agents for bacterial systems modeling.

PubMed

Paton, Ray; Gregory, Richard; Vlachos, Costas; Saunders, Jon; Wu, Henry

2004-09-01

We present two approaches to the individual-based modeling (IbM) of bacterial ecologies and evolution using computational tools. The IbM approach is introduced, and its important complementary role to biosystems modeling is discussed. A fine-grained model of bacterial evolution is then presented that is based on networks of interactivity between computational objects representing genes and proteins. This is followed by a coarser grained agent-based model, which is designed to explore the evolvability of adaptive behavioral strategies in artificial bacteria represented by learning classifier systems. The structure and implementation of the two proposed individual-based bacterial models are discussed, and some results from simulation experiments are presented, illustrating their adaptive properties.

Application of Psychological Theories in Agent-Based Modeling: The Case of the Theory of Planned Behavior.

PubMed

Scalco, Andrea; Ceschi, Andrea; Sartori, Riccardo

2018-01-01

It is likely that computer simulations will assume a greater role in the next future to investigate and understand reality (Rand & Rust, 2011). Particularly, agent-based models (ABMs) represent a method of investigation of social phenomena that blend the knowledge of social sciences with the advantages of virtual simulations. Within this context, the development of algorithms able to recreate the reasoning engine of autonomous virtual agents represents one of the most fragile aspects and it is indeed crucial to establish such models on well-supported psychological theoretical frameworks. For this reason, the present work discusses the application case of the theory of planned behavior (TPB; Ajzen, 1991) in the context of agent-based modeling: It is argued that this framework might be helpful more than others to develop a valid representation of human behavior in computer simulations. Accordingly, the current contribution considers issues related with the application of the model proposed by the TPB inside computer simulations and suggests potential solutions with the hope to contribute to shorten the distance between the fields of psychology and computer science.

Agent based modeling of the coevolution of hostility and pacifism

NASA Astrophysics Data System (ADS)

Dalmagro, Fermin; Jimenez, Juan

2015-01-01

We propose a model based on a population of agents whose states represent either hostile or peaceful behavior. Randomly selected pairs of agents interact according to a variation of the Prisoners Dilemma game, and the probabilities that the agents behave aggressively or not are constantly updated by the model so that the agents that remain in the game are those with the highest fitness. We show that the population of agents oscillate between generalized conflict and global peace, without either reaching a stable state. We then use this model to explain some of the emergent behaviors in collective conflicts, by comparing the simulated results with empirical data obtained from social systems. In particular, using public data reports we show how the model precisely reproduces interesting quantitative characteristics of diverse types of armed conflicts, public protests, riots and strikes.

An Agent-Based Data Mining System for Ontology Evolution

NASA Astrophysics Data System (ADS)

Hadzic, Maja; Dillon, Darshan

We have developed an evidence-based mental health ontological model that represents mental health in multiple dimensions. The ongoing addition of new mental health knowledge requires a continual update of the Mental Health Ontology. In this paper, we describe how the ontology evolution can be realized using a multi-agent system in combination with data mining algorithms. We use the TICSA methodology to design this multi-agent system which is composed of four different types of agents: Information agent, Data Warehouse agent, Data Mining agents and Ontology agent. We use UML 2.1 sequence diagrams to model the collaborative nature of the agents and a UML 2.1 composite structure diagram to model the structure of individual agents. The Mental Heath Ontology has the potential to underpin various mental health research experiments of a collaborative nature which are greatly needed in times of increasing mental distress and illness.

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 methodology for eliciting, representing, and analysing stakeholder knowledge for decision making on complex socio-ecological systems: from cognitive maps to agent-based models.

PubMed

Elsawah, Sondoss; Guillaume, Joseph H A; Filatova, Tatiana; Rook, Josefine; Jakeman, Anthony J

2015-03-15

This paper aims to contribute to developing better ways for incorporating essential human elements in decision making processes for modelling of complex socio-ecological systems. It presents a step-wise methodology for integrating perceptions of stakeholders (qualitative) into formal simulation models (quantitative) with the ultimate goal of improving understanding and communication about decision making in complex socio-ecological systems. The methodology integrates cognitive mapping and agent based modelling. It cascades through a sequence of qualitative/soft and numerical methods comprising: (1) Interviews to elicit mental models; (2) Cognitive maps to represent and analyse individual and group mental models; (3) Time-sequence diagrams to chronologically structure the decision making process; (4) All-encompassing conceptual model of decision making, and (5) computational (in this case agent-based) Model. We apply the proposed methodology (labelled ICTAM) in a case study of viticulture irrigation in South Australia. Finally, we use strengths-weakness-opportunities-threats (SWOT) analysis to reflect on the methodology. Results show that the methodology leverages the use of cognitive mapping to capture the richness of decision making and mental models, and provides a combination of divergent and convergent analysis methods leading to the construction of an Agent Based Model. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

Multi-Agent Strategic Modeling in a Specific Environment

NASA Astrophysics Data System (ADS)

Gams, Matjaz; Bezek, Andraz

Multi-agent modeling in ambient intelligence (AmI) is concerned with the following task [19]: How can external observations of multi-agent systems in the ambient be used to analyze, model, and direct agent behavior? The main purpose is to obtain knowledge about acts in the environment thus enabling proper actions of the AmI systems [1]. Analysis of such systems must thus capture complex world state representation and asynchronous agent activities. Instead of studying basic numerical data, researchers often use more complex data structures, such as rules and decision trees. Some methods are extremely useful when characterizing state space, but lack the ability to clearly represent temporal state changes occurred by agent actions. To comprehend simultaneous agent actions and complex changes of state space, most often a combination of graphical and symbolical representation performs better in terms of human understanding and performance.

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 modeling of the spread of influenza-like illness in an emergency department: a simulation study.

PubMed

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

2011-11-01

The objective of this paper was to develop an agent-based modeling framework in order to simulate the spread of influenza virus infection on a layout based on a representative hospital emergency department in Winnipeg, Canada. In doing so, the study complements mathematical modeling techniques for disease spread, as well as modeling applications focused on the spread of antibiotic-resistant nosocomial infections in hospitals. Twenty different emergency department scenarios were simulated, with further simulation of four infection control strategies. The agent-based modeling approach represents systems modeling, in which the emergency department was modeled as a collection of agents (patients and healthcare workers) and their individual characteristics, behaviors, and interactions. The framework was coded in C++ using Qt4 libraries running under the Linux operating system. A simple ordinary least squares (OLS) regression was used to analyze the data, in which the percentage of patients that became infected in one day within the simulation was the dependent variable. The results suggest that within the given instance context, patient-oriented infection control policies (alternate treatment streams, masking symptomatic patients) tend to have a larger effect than policies that target healthcare workers. The agent-based modeling framework is a flexible tool that can be made to reflect any given environment; it is also a decision support tool for practitioners and policymakers to assess the relative impact of infection control strategies. The framework illuminates scenarios worthy of further investigation, as well as counterintuitive findings.

Bruton's tyrosine kinase inhibitor BMS-986142 in experimental models of rheumatoid arthritis enhances efficacy of agents representing clinical standard-of-care.

PubMed

Gillooly, Kathleen M; Pulicicchio, Claudine; Pattoli, Mark A; Cheng, Lihong; Skala, Stacey; Heimrich, Elizabeth M; McIntyre, Kim W; Taylor, Tracy L; Kukral, Daniel W; Dudhgaonkar, Shailesh; Nagar, Jignesh; Banas, Dana; Watterson, Scott H; Tino, Joseph A; Fura, Aberra; Burke, James R

2017-01-01

Bruton's tyrosine kinase (BTK) regulates critical signal transduction pathways involved in the pathobiology of rheumatoid arthritis (RA) and other autoimmune disorders. BMS-986142 is a potent and highly selective reversible small molecule inhibitor of BTK currently being investigated in clinical trials for the treatment of both RA and primary Sjögren's syndrome. In the present report, we detail the in vitro and in vivo pharmacology of BMS-986142 and show this agent provides potent and selective inhibition of BTK (IC50 = 0.5 nM), blocks antigen receptor-dependent signaling and functional endpoints (cytokine production, co-stimulatory molecule expression, and proliferation) in human B cells (IC50 ≤ 5 nM), inhibits Fcγ receptor-dependent cytokine production from peripheral blood mononuclear cells, and blocks RANK-L-induced osteoclastogenesis. Through the benefits of impacting these important drivers of autoimmunity, BMS-986142 demonstrated robust efficacy in murine models of rheumatoid arthritis (RA), including collagen-induced arthritis (CIA) and collagen antibody-induced arthritis (CAIA). In both models, robust efficacy was observed without continuous, complete inhibition of BTK. When a suboptimal dose of BMS-986142 was combined with other agents representing the current standard of care for RA (e.g., methotrexate, the TNFα antagonist etanercept, or the murine form of CTLA4-Ig) in the CIA model, improved efficacy compared to either agent alone was observed. The results suggest BMS-986142 represents a potential therapeutic for clinical investigation in RA, as monotherapy or co-administered with agents with complementary mechanisms of action.

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.

Agent-based dynamic knowledge representation of Pseudomonas aeruginosa virulence activation in the stressed gut: Towards characterizing host-pathogen interactions in gut-derived sepsis.

PubMed

Seal, John B; Alverdy, John C; Zaborina, Olga; An, Gary

2011-09-19

There is a growing realization that alterations in host-pathogen interactions (HPI) can generate disease phenotypes without pathogen invasion. The gut represents a prime region where such HPI can arise and manifest. Under normal conditions intestinal microbial communities maintain a stable, mutually beneficial ecosystem. However, host stress can lead to changes in environmental conditions that shift the nature of the host-microbe dialogue, resulting in escalation of virulence expression, immune activation and ultimately systemic disease. Effective modulation of these dynamics requires the ability to characterize the complexity of the HPI, and dynamic computational modeling can aid in this task. Agent-based modeling is a computational method that is suited to representing spatially diverse, dynamical systems. We propose that dynamic knowledge representation of gut HPI with agent-based modeling will aid in the investigation of the pathogenesis of gut-derived sepsis. An agent-based model (ABM) of virulence regulation in Pseudomonas aeruginosa was developed by translating bacterial and host cell sense-and-response mechanisms into behavioral rules for computational agents and integrated into a virtual environment representing the host-microbe interface in the gut. The resulting gut milieu ABM (GMABM) was used to: 1) investigate a potential clinically relevant laboratory experimental condition not yet developed--i.e. non-lethal transient segmental intestinal ischemia, 2) examine the sufficiency of existing hypotheses to explain experimental data--i.e. lethality in a model of major surgical insult and stress, and 3) produce behavior to potentially guide future experimental design--i.e. suggested sample points for a potential laboratory model of non-lethal transient intestinal ischemia. Furthermore, hypotheses were generated to explain certain discrepancies between the behaviors of the GMABM and biological experiments, and new investigatory avenues proposed to test those hypotheses. Agent-based modeling can account for the spatio-temporal dynamics of an HPI, and, even when carried out with a relatively high degree of abstraction, can be useful in the investigation of system-level consequences of putative mechanisms operating at the individual agent level. We suggest that an integrated and iterative heuristic relationship between computational modeling and more traditional laboratory and clinical investigations, with a focus on identifying useful and sufficient degrees of abstraction, will enhance the efficiency and translational productivity of biomedical research.

Agent-based dynamic knowledge representation of Pseudomonas aeruginosa virulence activation in the stressed gut: Towards characterizing host-pathogen interactions in gut-derived sepsis

PubMed Central

2011-01-01

Background There is a growing realization that alterations in host-pathogen interactions (HPI) can generate disease phenotypes without pathogen invasion. The gut represents a prime region where such HPI can arise and manifest. Under normal conditions intestinal microbial communities maintain a stable, mutually beneficial ecosystem. However, host stress can lead to changes in environmental conditions that shift the nature of the host-microbe dialogue, resulting in escalation of virulence expression, immune activation and ultimately systemic disease. Effective modulation of these dynamics requires the ability to characterize the complexity of the HPI, and dynamic computational modeling can aid in this task. Agent-based modeling is a computational method that is suited to representing spatially diverse, dynamical systems. We propose that dynamic knowledge representation of gut HPI with agent-based modeling will aid in the investigation of the pathogenesis of gut-derived sepsis. Methodology/Principal Findings An agent-based model (ABM) of virulence regulation in Pseudomonas aeruginosa was developed by translating bacterial and host cell sense-and-response mechanisms into behavioral rules for computational agents and integrated into a virtual environment representing the host-microbe interface in the gut. The resulting gut milieu ABM (GMABM) was used to: 1) investigate a potential clinically relevant laboratory experimental condition not yet developed - i.e. non-lethal transient segmental intestinal ischemia, 2) examine the sufficiency of existing hypotheses to explain experimental data - i.e. lethality in a model of major surgical insult and stress, and 3) produce behavior to potentially guide future experimental design - i.e. suggested sample points for a potential laboratory model of non-lethal transient intestinal ischemia. Furthermore, hypotheses were generated to explain certain discrepancies between the behaviors of the GMABM and biological experiments, and new investigatory avenues proposed to test those hypotheses. Conclusions/Significance Agent-based modeling can account for the spatio-temporal dynamics of an HPI, and, even when carried out with a relatively high degree of abstraction, can be useful in the investigation of system-level consequences of putative mechanisms operating at the individual agent level. We suggest that an integrated and iterative heuristic relationship between computational modeling and more traditional laboratory and clinical investigations, with a focus on identifying useful and sufficient degrees of abstraction, will enhance the efficiency and translational productivity of biomedical research. PMID:21929759

Markov Tracking for Agent Coordination

NASA Technical Reports Server (NTRS)

Washington, Richard; Lau, Sonie (Technical Monitor)

1998-01-01

Partially observable Markov decision processes (POMDPs) axe an attractive representation for representing agent behavior, since they capture uncertainty in both the agent's state and its actions. However, finding an optimal policy for POMDPs in general is computationally difficult. In this paper we present Markov Tracking, a restricted problem of coordinating actions with an agent or process represented as a POMDP Because the actions coordinate with the agent rather than influence its behavior, the optimal solution to this problem can be computed locally and quickly. We also demonstrate the use of the technique on sequential POMDPs, which can be used to model a behavior that follows a linear, acyclic trajectory through a series of states. By imposing a "windowing" restriction that restricts the number of possible alternatives considered at any moment to a fixed size, a coordinating action can be calculated in constant time, making this amenable to coordination with complex agents.

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.

Towards an agent-oriented programming language based on Scala

NASA Astrophysics Data System (ADS)

Mitrović, Dejan; Ivanović, Mirjana; Budimac, Zoran

2012-09-01

Scala and its multi-threaded model based on actors represent an excellent framework for developing purely reactive agents. This paper presents an early research on extending Scala with declarative programming constructs, which would result in a new agent-oriented programming language suitable for developing more advanced, BDI agent architectures. The main advantage the new language over many other existing solutions for programming BDI agents is a natural and straightforward integration of imperative and declarative programming constructs, fitted under a single development framework.

Agents Play Mix-game

NASA Astrophysics Data System (ADS)

Gou, Chengling

In recent years, economics and finance see the shift of paradigm from representative agent models to heterogeneous agent models [1, 2]. More and more economists and physicists made efforts in research on heterogeneous agent models for financial markets. Minority game (MG) proposed by D. Challet, and Y. C. Zhang [3] is an example among such efforts. Challet and Zhang's MG model, together with the original bar model of Arthur, attracts a lot of following studies [4-6]. Given MG's richness and yet underlying simplicity, MG has also received much attention as a financial market model [4]. MG comprises an odd number of agents choosing repeatedly between the options of buying (1) and selling (0) a quantity of a risky asset. The agents continually try to make the minority decision, i.e. buy assets when the majority of other agents are selling, and sell when the majority of other agents are buying. Neil F. Johnson [4, 5] and coworkers extended MG by allowing a variable number of active traders at each timestep— they called their modified game as the Grand Canonical Minority Game (GCMG). GCMG, and to a lesser extent the basic MG itself, can reproduce the stylized facts of financial markets, such as volatility clustering and fat-tail distributions.

SPARK: A Framework for Multi-Scale Agent-Based Biomedical Modeling.

PubMed

Solovyev, Alexey; Mikheev, Maxim; Zhou, Leming; Dutta-Moscato, Joyeeta; Ziraldo, Cordelia; An, Gary; Vodovotz, Yoram; Mi, Qi

2010-01-01

Multi-scale modeling of complex biological systems remains a central challenge in the systems biology community. A method of dynamic knowledge representation known as agent-based modeling enables the study of higher level behavior emerging from discrete events performed by individual components. With the advancement of computer technology, agent-based modeling has emerged as an innovative technique to model the complexities of systems biology. In this work, the authors describe SPARK (Simple Platform for Agent-based Representation of Knowledge), a framework for agent-based modeling specifically designed for systems-level biomedical model development. SPARK is a stand-alone application written in Java. It provides a user-friendly interface, and a simple programming language for developing Agent-Based Models (ABMs). SPARK has the following features specialized for modeling biomedical systems: 1) continuous space that can simulate real physical space; 2) flexible agent size and shape that can represent the relative proportions of various cell types; 3) multiple spaces that can concurrently simulate and visualize multiple scales in biomedical models; 4) a convenient graphical user interface. Existing ABMs of diabetic foot ulcers and acute inflammation were implemented in SPARK. Models of identical complexity were run in both NetLogo and SPARK; the SPARK-based models ran two to three times faster.

Voters' Fickleness:. a Mathematical Model

NASA Astrophysics Data System (ADS)

Boccara, Nino

This paper presents a spatial agent-based model in order to study the evolution of voters' choice during the campaign of a two-candidate election. Each agent, represented by a point inside a two-dimensional square, is under the influence of its neighboring agents, located at a Euclidean distance less than or equal to d, and under the equal influence of both candidates seeking to win its support. Moreover, each agent located at time t at a given point moves at the next timestep to a randomly selected neighboring location distributed normally around its position at time t. Besides their location in space, agents are characterized by their level of awareness, a real a ∈ [0, 1], and their opinion ω ∈ {-1, 0, +1}, where -1 and +1 represent the respective intentions to cast a ballot in favor of one of the two candidates while 0 indicates either disinterest or refusal to vote. The essential purpose of the paper is qualitative; its aim is to show that voters' fickleness is strongly correlated to the level of voters' awareness and the efficiency of candidates' propaganda.

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.

Complex dynamics and empirical evidence (Invited Paper)

NASA Astrophysics Data System (ADS)

Delli Gatti, Domenico; Gaffeo, Edoardo; Giulioni, Gianfranco; Gallegati, Mauro; Kirman, Alan; Palestrini, Antonio; Russo, Alberto

2005-05-01

Standard macroeconomics, based on a reductionist approach centered on the representative agent, is badly equipped to explain the empirical evidence where heterogeneity and industrial dynamics are the rule. In this paper we show that a simple agent-based model of heterogeneous financially fragile agents is able to replicate a large number of scaling type stylized facts with a remarkable degree of statistical precision.

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

DOE PAGES

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

2015-10-30

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

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

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

A water market simulator considering pair-wise trades between agents

NASA Astrophysics Data System (ADS)

Huskova, I.; Erfani, T.; Harou, J. J.

2012-04-01

In many basins in England no further water abstraction licences are available. Trading water between water rights holders has been recognized as a potentially effective and economically efficient strategy to mitigate increasing scarcity. A screening tool that could assess the potential for trade through realistic simulation of individual water rights holders would help assess the solution's potential contribution to local water management. We propose an optimisation-driven water market simulator that predicts pair-wise trade in a catchment and represents its interaction with natural hydrology and engineered infrastructure. A model is used to emulate licence-holders' willingness to engage in short-term trade transactions. In their simplest form agents are represented using an economic benefit function. The working hypothesis is that trading behaviour can be partially predicted based on differences in marginal values of water over space and time and estimates of transaction costs on pair-wise trades. We discuss the further possibility of embedding rules, norms and preferences of the different water user sectors to more realistically represent the behaviours, motives and constraints of individual licence holders. The potential benefits and limitations of such a social simulation (agent-based) approach is contrasted with our simulator where agents are driven by economic optimization. A case study based on the Dove River Basin (UK) demonstrates model inputs and outputs. The ability of the model to suggest impacts of water rights policy reforms on trading is discussed.

IDEA: Planning at the Core of Autonomous Reactive Agents

NASA Technical Reports Server (NTRS)

Muscettola, Nicola; Dorais, Gregory A.; Fry, Chuck; Levinson, Richard; Plaunt, Christian; Clancy, Daniel (Technical Monitor)

2002-01-01

Several successful autonomous systems are separated into technologically diverse functional layers operating at different levels of abstraction. This diversity makes them difficult to implement and validate. In this paper, we present IDEA (Intelligent Distributed Execution Architecture), a unified planning and execution framework. In IDEA a layered system can be implemented as separate agents, one per layer, each representing its interactions with the world in a model. At all levels, the model representation primitives and their semantics is the same. Moreover, each agent relies on a single model, plan database, plan runner and on a variety of planners, both reactive and deliberative. The framework allows the specification of agents that operate, within a guaranteed reaction time and supports flexible specification of reactive vs. deliberative agent behavior. Within the IDEA framework we are working to fully duplicate the functionalities of the DS1 Remote Agent and extend it to domains of higher complexity than autonomous spacecraft control.

Agent-based model of fecal microbial transplant effect on bile acid metabolism on suppressing Clostridium difficile infection: an example of agent-based modeling of intestinal bacterial infection.

PubMed

Peer, Xavier; An, Gary

2014-10-01

Agent-based modeling is a computational modeling method that represents system-level behavior as arising from multiple interactions between the multiple components that make up a system. Biological systems are thus readily described using agent-based models (ABMs), as multi-cellular organisms can be viewed as populations of interacting cells, and microbial systems manifest as colonies of individual microbes. Intersections between these two domains underlie an increasing number of pathophysiological processes, and the intestinal tract represents one of the most significant locations for these inter-domain interactions, so much so that it can be considered an internal ecology of varying robustness and function. Intestinal infections represent significant disturbances of this internal ecology, and one of the most clinically relevant intestinal infections is Clostridium difficile infection (CDI). CDI is precipitated by the use of broad-spectrum antibiotics, involves the depletion of commensal microbiota, and alterations in bile acid composition in the intestinal lumen. We present an example ABM of CDI (the C. difficile Infection ABM, or CDIABM) to examine fundamental dynamics of the pathogenesis of CDI and its response to treatment with anti-CDI antibiotics and a newer treatment therapy, fecal microbial transplant. The CDIABM focuses on one specific mechanism of potential CDI suppression: commensal modulation of bile acid composition. Even given its abstraction, the CDIABM reproduces essential dynamics of CDI and its response to therapy, and identifies a paradoxical zone of behavior that provides insight into the role of intestinal nutritional status and the efficacy of anti-CDI therapies. It is hoped that this use case example of the CDIABM can demonstrate the usefulness of both agent-based modeling and the application of abstract functional representation as the biomedical community seeks to address the challenges of increasingly complex diseases with the goal of personalized medicine.

Agent-based model of Fecal Microbial Transplant effect on Bile Acid Metabolism on suppressing Clostridium difficile infection: an example of agent-based modeling of intestinal bacterial infection

PubMed Central

Peer, Xavier; An, Gary

2014-01-01

Agent-based modeling is a computational modeling method that represents system-level behavior as arising from multiple interactions between the multiple components that make up a system. Biological systems are thus readily described using agent-based models (ABMs), as multi-cellular organisms can be viewed as populations of interacting cells, and microbial systems manifest as colonies of individual microbes. Intersections between these two domains underlie an increasing number of pathophysiological processes, and the intestinal tract represents one of the most significant locations for these inter-domain interactions, so much so that it can be considered an internal ecology of varying robustness and function. Intestinal infections represent significant disturbances of this internal ecology, and one of the most clinically relevant intestinal infections is Clostridium difficile infection (CDI). CDI is precipitated by the use of broad-spectrum antibiotics, involves the depletion of commensal microbiota, and alterations in bile acid composition in the intestinal lumen. We present an example ABM of CDI (the Clostridium difficile Infection ABM, or CDIABM) to examine fundamental dynamics of the pathogenesis of CDI and its response to treatment with anti-CDI antibiotics and a newer treatment therapy, Fecal Microbial Transplant (FMT). The CDIABM focuses on one specific mechanism of potential CDI suppression: commensal modulation of bile acid composition. Even given its abstraction, the CDIABM reproduces essential dynamics of CDI and its response to therapy, and identifies a paradoxical zone of behavior that provides insight into the role of intestinal nutritional status and the efficacy of anti-CDI therapies. It is hoped that this use case example of the CDIABM can demonstrate the usefulness of both agent-based modeling and the application of abstract functional representation as the biomedical community seeks to address the challenges of increasingly complex diseases with the goal of personalized medicine. PMID:25168489

Addressing the translational dilemma: dynamic knowledge representation of inflammation using agent-based modeling.

PubMed

An, Gary; Christley, Scott

2012-01-01

Given the panoply of system-level diseases that result from disordered inflammation, such as sepsis, atherosclerosis, cancer, and autoimmune disorders, understanding and characterizing the inflammatory response is a key target of biomedical research. Untangling the complex behavioral configurations associated with a process as ubiquitous as inflammation represents a prototype of the translational dilemma: the ability to translate mechanistic knowledge into effective therapeutics. A critical failure point in the current research environment is a throughput bottleneck at the level of evaluating hypotheses of mechanistic causality; these hypotheses represent the key step toward the application of knowledge for therapy development and design. Addressing the translational dilemma will require utilizing the ever-increasing power of computers and computational modeling to increase the efficiency of the scientific method in the identification and evaluation of hypotheses of mechanistic causality. More specifically, development needs to focus on facilitating the ability of non-computer trained biomedical researchers to utilize and instantiate their knowledge in dynamic computational models. This is termed "dynamic knowledge representation." Agent-based modeling is an object-oriented, discrete-event, rule-based simulation method that is well suited for biomedical dynamic knowledge representation. Agent-based modeling has been used in the study of inflammation at multiple scales. The ability of agent-based modeling to encompass multiple scales of biological process as well as spatial considerations, coupled with an intuitive modeling paradigm, suggest that this modeling framework is well suited for addressing the translational dilemma. This review describes agent-based modeling, gives examples of its applications in the study of inflammation, and introduces a proposed general expansion of the use of modeling and simulation to augment the generation and evaluation of knowledge by the biomedical research community at large.

Action Understanding as Inverse Planning

ERIC Educational Resources Information Center

Baker, Chris L.; Saxe, Rebecca; Tenenbaum, Joshua B.

2009-01-01

Humans are adept at inferring the mental states underlying other agents' actions, such as goals, beliefs, desires, emotions and other thoughts. We propose a computational framework based on Bayesian inverse planning for modeling human action understanding. The framework represents an intuitive theory of intentional agents' behavior based on the…

A coupled modeling framework for sustainable watershed management in transboundary river basins

NASA Astrophysics Data System (ADS)

Furqan Khan, Hassaan; Yang, Y. C. Ethan; Xie, Hua; Ringler, Claudia

2017-12-01

There is a growing recognition among water resource managers that sustainable watershed management needs to not only account for the diverse ways humans benefit from the environment, but also incorporate the impact of human actions on the natural system. Coupled natural-human system modeling through explicit modeling of both natural and human behavior can help reveal the reciprocal interactions and co-evolution of the natural and human systems. This study develops a spatially scalable, generalized agent-based modeling (ABM) framework consisting of a process-based semi-distributed hydrologic model (SWAT) and a decentralized water system model to simulate the impacts of water resource management decisions that affect the food-water-energy-environment (FWEE) nexus at a watershed scale. Agents within a river basin are geographically delineated based on both political and watershed boundaries and represent key stakeholders of ecosystem services. Agents decide about the priority across three primary water uses: food production, hydropower generation and ecosystem health within their geographical domains. Agents interact with the environment (streamflow) through the SWAT model and interact with other agents through a parameter representing willingness to cooperate. The innovative two-way coupling between the water system model and SWAT enables this framework to fully explore the feedback of human decisions on the environmental dynamics and vice versa. To support non-technical stakeholder interactions, a web-based user interface has been developed that allows for role-play and participatory modeling. The generalized ABM framework is also tested in two key transboundary river basins, the Mekong River basin in Southeast Asia and the Niger River basin in West Africa, where water uses for ecosystem health compete with growing human demands on food and energy resources. We present modeling results for crop production, energy generation and violation of eco-hydrological indicators at both the agent and basin-wide levels to shed light on holistic FWEE management policies in these two basins.

Counter-terrorism threat prediction architecture

NASA Astrophysics Data System (ADS)

Lehman, Lynn A.; Krause, Lee S.

2004-09-01

This paper will evaluate the feasibility of constructing a system to support intelligence analysts engaged in counter-terrorism. It will discuss the use of emerging techniques to evaluate a large-scale threat data repository (or Infosphere) and comparing analyst developed models to identify and discover potential threat-related activity with a uncertainty metric used to evaluate the threat. This system will also employ the use of psychological (or intent) modeling to incorporate combatant (i.e. terrorist) beliefs and intent. The paper will explore the feasibility of constructing a hetero-hierarchical (a hierarchy of more than one kind or type characterized by loose connection/feedback among elements of the hierarchy) agent based framework or "family of agents" to support "evidence retrieval" defined as combing, or searching the threat data repository and returning information with an uncertainty metric. The counter-terrorism threat prediction architecture will be guided by a series of models, constructed to represent threat operational objectives, potential targets, or terrorist objectives. The approach would compare model representations against information retrieved by the agent family to isolate or identify patterns that match within reasonable measures of proximity. The central areas of discussion will be the construction of an agent framework to search the available threat related information repository, evaluation of results against models that will represent the cultural foundations, mindset, sociology and emotional drive of typical threat combatants (i.e. the mind and objectives of a terrorist), and the development of evaluation techniques to compare result sets with the models representing threat behavior and threat targets. The applicability of concepts surrounding Modeling Field Theory (MFT) will be discussed as the basis of this research into development of proximity measures between the models and result sets and to provide feedback in support of model adaptation (learning). The increasingly complex demands facing analysts evaluating activity threatening to the security of the United States make the family of agent-based data collection (fusion) a promising area. This paper will discuss a system to support the collection and evaluation of potential threat activity as well as an approach fro presentation of the information.

Independence-Based Optimization of Epistemic Model Checking

DTIC Science & Technology

2017-02-22

favourite restaurant . Their waiter informs them that arrangements have been made with the maitre d’hotel for the bill to be paid anonymously. One of the...nondeterministically selecting a value of either 0 or 1. Each cryptographer is associated with a set of variables, whose values they are able to observe at each...slotsCi is used to represent which slot, if any, agent Ci has selected for its transmission; slotsCi[0] represents that the agent has nothing to transmit

Combining human and machine intelligence to derive agents' behavioral rules for groundwater irrigation

NASA Astrophysics Data System (ADS)

Hu, Yao; Quinn, Christopher J.; Cai, Ximing; Garfinkle, Noah W.

2017-11-01

For agent-based modeling, the major challenges in deriving agents' behavioral rules arise from agents' bounded rationality and data scarcity. This study proposes a "gray box" approach to address the challenge by incorporating expert domain knowledge (i.e., human intelligence) with machine learning techniques (i.e., machine intelligence). Specifically, we propose using directed information graph (DIG), boosted regression trees (BRT), and domain knowledge to infer causal factors and identify behavioral rules from data. A case study is conducted to investigate farmers' pumping behavior in the Midwest, U.S.A. Results show that four factors identified by the DIG algorithm- corn price, underlying groundwater level, monthly mean temperature and precipitation- have main causal influences on agents' decisions on monthly groundwater irrigation depth. The agent-based model is then developed based on the behavioral rules represented by three DIGs and modeled by BRTs, and coupled with a physically-based groundwater model to investigate the impacts of agents' pumping behavior on the underlying groundwater system in the context of coupled human and environmental systems.

Employment, Production and Consumption model: Patterns of phase transitions

NASA Astrophysics Data System (ADS)

Lavička, H.; Lin, L.; Novotný, J.

2010-04-01

We have simulated the model of Employment, Production and Consumption (EPC) using Monte Carlo. The EPC model is an agent based model that mimics very basic rules of industrial economy. From the perspective of physics, the nature of the interactions in the EPC model represents multi-agent interactions where the relations among agents follow the key laws for circulation of capital and money. Monte Carlo simulations of the stochastic model reveal phase transition in the model economy. The two phases are the phase with full unemployment and the phase with nearly full employment. The economy switches between these two states suddenly as a reaction to a slight variation in the exogenous parameter, thus the system exhibits strong non-linear behavior as a response to the change of the exogenous parameters.

Strategy Space Exploration of a Multi-Agent Model for the Labor Market

NASA Astrophysics Data System (ADS)

de Grande, Pablo; Eguia, Manuel

We present a multi-agent system where typical labor market mechanisms emerge. Based on a few simple rules, our model allows for different interpretative paradigms to be represented and for different scenarios to be tried out. We thoroughly explore the space of possible strategies both for those unemployed and for companies and analyze the trade-off between these strategies regarding global social and economical indicators.

Range of interaction in an opinion evolution model of ideological self-positioning: Contagion, hesitance and polarization

NASA Astrophysics Data System (ADS)

Gimenez, M. Cecilia; Paz García, Ana Pamela; Burgos Paci, Maxi A.; Reinaudi, Luis

2016-04-01

The evolution of public opinion using tools and concepts borrowed from Statistical Physics is an emerging area within the field of Sociophysics. In the present paper, a Statistical Physics model was developed to study the evolution of the ideological self-positioning of an ensemble of agents. The model consists of an array of L components, each one of which represents the ideology of an agent. The proposed mechanism is based on the ;voter model;, in which one agent can adopt the opinion of another one if the difference of their opinions lies within a certain range. The existence of ;undecided; agents (i.e. agents with no definite opinion) was implemented in the model. The possibility of radicalization of an agent's opinion upon interaction with another one was also implemented. The results of our simulations are compared to statistical data taken from the Latinobarómetro databank for the cases of Argentina, Chile, Brazil and Uruguay in the last decade. Among other results, the effect of taking into account the undecided agents is the formation of a single peak at the middle of the ideological spectrum (which corresponds to a centrist ideological position), in agreement with the real cases studied.

Using Model Replication to Improve the Reliability of Agent-Based Models

NASA Astrophysics Data System (ADS)

Zhong, Wei; Kim, Yushim

The basic presupposition of model replication activities for a computational model such as an agent-based model (ABM) is that, as a robust and reliable tool, it must be replicable in other computing settings. This assumption has recently gained attention in the community of artificial society and simulation due to the challenges of model verification and validation. Illustrating the replication of an ABM representing fraudulent behavior in a public service delivery system originally developed in the Java-based MASON toolkit for NetLogo by a different author, this paper exemplifies how model replication exercises provide unique opportunities for model verification and validation process. At the same time, it helps accumulate best practices and patterns of model replication and contributes to the agenda of developing a standard methodological protocol for agent-based social simulation.

`Models of' versus `Models for'. Toward an Agent-Based Conception of Modeling in the Science Classroom

NASA Astrophysics Data System (ADS)

Gouvea, Julia; Passmore, Cynthia

2017-03-01

The inclusion of the practice of "developing and using models" in the Framework for K-12 Science Education and in the Next Generation Science Standards provides an opportunity for educators to examine the role this practice plays in science and how it can be leveraged in a science classroom. Drawing on conceptions of models in the philosophy of science, we bring forward an agent-based account of models and discuss the implications of this view for enacting modeling in science classrooms. Models, according to this account, can only be understood with respect to the aims and intentions of a cognitive agent (models for), not solely in terms of how they represent phenomena in the world (models of). We present this contrast as a heuristic— models of versus models for—that can be used to help educators notice and interpret how models are positioned in standards, curriculum, and classrooms.

When more of the same is better

NASA Astrophysics Data System (ADS)

Fontanari, José F.

2016-01-01

Problem solving (e.g., drug design, traffic engineering, software development) by task forces represents a substantial portion of the economy of developed countries. Here we use an agent-based model of cooperative problem-solving systems to study the influence of diversity on the performance of a task force. We assume that agents cooperate by exchanging information on their partial success and use that information to imitate the more successful agent in the system —the model. The agents differ only in their propensities to copy the model. We find that, for easy tasks, the optimal organization is a homogeneous system composed of agents with the highest possible copy propensities. For difficult tasks, we find that diversity can prevent the system from being trapped in sub-optimal solutions. However, when the system size is adjusted to maximize the performance the homogeneous systems outperform the heterogeneous systems, i.e., for optimal performance, sameness should be preferred to diversity.

An agent-based method for simulating porous fluid-saturated structures with indistinguishable components

NASA Astrophysics Data System (ADS)

Kashani, Jamal; Pettet, Graeme John; Gu, YuanTong; Zhang, Lihai; Oloyede, Adekunle

2017-10-01

Single-phase porous materials contain multiple components that intermingle up to the ultramicroscopic level. Although the structures of the porous materials have been simulated with agent-based methods, the results of the available methods continue to provide patterns of distinguishable solid and fluid agents which do not represent materials with indistinguishable phases. This paper introduces a new agent (hybrid agent) and category of rules (intra-agent rule) that can be used to create emergent structures that would more accurately represent single-phase structures and materials. The novel hybrid agent carries the characteristics of system's elements and it is capable of changing within itself, while also responding to its neighbours as they also change. As an example, the hybrid agent under one-dimensional cellular automata formalism in a two-dimensional domain is used to generate patterns that demonstrate the striking morphological and characteristic similarities with the porous saturated single-phase structures where each agent of the ;structure; carries semi-permeability property and consists of both fluid and solid in space and at all times. We conclude that the ability of the hybrid agent to change locally provides an enhanced protocol to simulate complex porous structures such as biological tissues which could facilitate models for agent-based techniques and numerical methods.

Quantum machine learning with glow for episodic tasks and decision games

NASA Astrophysics Data System (ADS)

Clausen, Jens; Briegel, Hans J.

2018-02-01

We consider a general class of models, where a reinforcement learning (RL) agent learns from cyclic interactions with an external environment via classical signals. Perceptual inputs are encoded as quantum states, which are subsequently transformed by a quantum channel representing the agent's memory, while the outcomes of measurements performed at the channel's output determine the agent's actions. The learning takes place via stepwise modifications of the channel properties. They are described by an update rule that is inspired by the projective simulation (PS) model and equipped with a glow mechanism that allows for a backpropagation of policy changes, analogous to the eligibility traces in RL and edge glow in PS. In this way, the model combines features of PS with the ability for generalization, offered by its physical embodiment as a quantum system. We apply the agent to various setups of an invasion game and a grid world, which serve as elementary model tasks allowing a direct comparison with a basic classical PS agent.

Field validation of a free-agent cellular automata model of fire spread with fire–atmosphere coupling

Treesearch

Gary Achtemeier

2012-01-01

A cellular automata fire model represents ‘elements’ of fire by autonomous agents. A few simple algebraic expressions substituted for complex physical and meteorological processes and solved iteratively yield simulations for ‘super-diffusive’ fire spread and coupled surface-layer (2-m) fire–atmosphere processes. Pressure anomalies, which are integrals of the thermal...

A Novel Application of Agent-based Modeling: Projecting Water Access and Availability Using a Coupled Hydrologic Agent-based Model in the Nzoia Basin, Kenya

NASA Astrophysics Data System (ADS)

Le, A.; Pricope, N. G.

2015-12-01

Projections indicate that increasing population density, food production, and urbanization in conjunction with changing climate conditions will place stress on water resource availability. As a result, a holistic understanding of current and future water resource distribution is necessary for creating strategies to identify the most sustainable means of accessing this resource. Currently, most water resource management strategies rely on the application of global climate predictions to physically based hydrologic models to understand potential changes in water availability. However, the need to focus on understanding community-level social behaviors that determine individual water usage is becoming increasingly evident, as predictions derived only from hydrologic models cannot accurately represent the coevolution of basin hydrology and human water and land usage. Models that are better equipped to represent the complexity and heterogeneity of human systems and satellite-derived products in place of or in conjunction with historic data significantly improve preexisting hydrologic model accuracy and application outcomes. We used a novel agent-based sociotechnical model that combines the Soil and Water Assessment Tool (SWAT) and Agent Analyst and applied it in the Nzoia Basin, an area in western Kenya that is becoming rapidly urbanized and industrialized. Informed by a combination of satellite-derived products and over 150 household surveys, the combined sociotechnical model provided unique insight into how populations self-organize and make decisions based on water availability. In addition, the model depicted how population organization and current management alter water availability currently and in the future.

Identification of novel antitubulin agents by using a virtual screening approach based on a 7-point pharmacophore model of the tubulin colchi-site.

PubMed

Massarotti, Alberto; Theeramunkong, Sewan; Mesenzani, Ornella; Caldarelli, Antonio; Genazzani, Armando A; Tron, Gian Cesare

2011-12-01

Tubulin inhibition represents an established target in the field of anticancer research, and over the last 20 years, an intensive search for new antimicrotubule agents has occurred. Indeed, in silico models have been presented that might aid the discovery of novel agents. Among these, a 7-point pharmacophore model has been recently proposed. As a formal proof of this model, we carried out a ligand-based virtual screening on the colchicine-binding site. In vitro testing demonstrated that two compounds displayed a cytotoxic profile on neuroblastoma cancer cells (SH-SY5H) and one had an antitubulinic profile. © 2011 John Wiley & Sons A/S.

Kinetic theory of situated agents applied to pedestrian flow in a corridor

NASA Astrophysics Data System (ADS)

Rangel-Huerta, A.; Muñoz-Meléndez, A.

2010-03-01

A situated agent-based model for simulation of pedestrian flow in a corridor is presented. In this model, pedestrians choose their paths freely and make decisions based on local criteria for solving collision conflicts. The crowd consists of multiple walking agents equipped with a function of perception as well as a competitive rule-based strategy that enables pedestrians to reach free access areas. Pedestrians in our model are autonomous entities capable of perceiving and making decisions. They apply socially accepted conventions, such as avoidance rules, as well as individual preferences such as the use of specific exit points, or the execution of eventual comfort turns resulting in spontaneous changes of walking speed. Periodic boundary conditions were considered in order to determine the density-average walking speed, and the density-average activity with respect to specific parameters: comfort angle turn and frequency of angle turn of walking agents. The main contribution of this work is an agent-based model where each pedestrian is represented as an autonomous agent. At the same time the pedestrian crowd dynamics is framed by the kinetic theory of biological systems.

Opinions, Conflicts, and Consensus: Modeling Social Dynamics in a Collaborative Environment

NASA Astrophysics Data System (ADS)

Török, János; Iñiguez, Gerardo; Yasseri, Taha; San Miguel, Maxi; Kaski, Kimmo; Kertész, János

2013-02-01

Information-communication technology promotes collaborative environments like Wikipedia where, however, controversy and conflicts can appear. To describe the rise, persistence, and resolution of such conflicts, we devise an extended opinion dynamics model where agents with different opinions perform a single task to make a consensual product. As a function of the convergence parameter describing the influence of the product on the agents, the model shows spontaneous symmetry breaking of the final consensus opinion represented by the medium. In the case when agents are replaced with new ones at a certain rate, a transition from mainly consensus to a perpetual conflict occurs, which is in qualitative agreement with the scenarios observed in Wikipedia.

Opinions, conflicts, and consensus: modeling social dynamics in a collaborative environment.

PubMed

Török, János; Iñiguez, Gerardo; Yasseri, Taha; San Miguel, Maxi; Kaski, Kimmo; Kertész, János

2013-02-22

Information-communication technology promotes collaborative environments like Wikipedia where, however, controversy and conflicts can appear. To describe the rise, persistence, and resolution of such conflicts, we devise an extended opinion dynamics model where agents with different opinions perform a single task to make a consensual product. As a function of the convergence parameter describing the influence of the product on the agents, the model shows spontaneous symmetry breaking of the final consensus opinion represented by the medium. In the case when agents are replaced with new ones at a certain rate, a transition from mainly consensus to a perpetual conflict occurs, which is in qualitative agreement with the scenarios observed in Wikipedia.

21 CFR 1404.915 - Agent or representative.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 9 2010-04-01 2010-04-01 false Agent or representative. 1404.915 Section 1404.915 Food and Drugs OFFICE OF NATIONAL DRUG CONTROL POLICY GOVERNMENTWIDE DEBARMENT AND SUSPENSION (NONPROCUREMENT) Definitions § 1404.915 Agent or representative. Agent or representative means any person who acts...

A knowledge base architecture for distributed knowledge agents

NASA Technical Reports Server (NTRS)

Riedesel, Joel; Walls, Bryan

1990-01-01

A tuple space based object oriented model for knowledge base representation and interpretation is presented. An architecture for managing distributed knowledge agents is then implemented within the model. The general model is based upon a database implementation of a tuple space. Objects are then defined as an additional layer upon the database. The tuple space may or may not be distributed depending upon the database implementation. A language for representing knowledge and inference strategy is defined whose implementation takes advantage of the tuple space. The general model may then be instantiated in many different forms, each of which may be a distinct knowledge agent. Knowledge agents may communicate using tuple space mechanisms as in the LINDA model as well as using more well known message passing mechanisms. An implementation of the model is presented describing strategies used to keep inference tractable without giving up expressivity. An example applied to a power management and distribution network for Space Station Freedom is given.

Axelrod Model of Social Influence with Cultural Hybridization

NASA Astrophysics Data System (ADS)

Radillo-Díaz, Alejandro; Pérez, Luis A.; Del Castillo-Mussot, Marcelo

2012-10-01

Since cultural interactions between a pair of social agents involve changes in both individuals, we present simulations of a new model based on Axelrod's homogenization mechanism that includes hybridization or mixture of the agents' features. In this new hybridization model, once a cultural feature of a pair of agents has been chosen for the interaction, the average of the values for this feature is reassigned as the new value for both agents after interaction. Moreover, a parameter representing social tolerance is implemented in order to quantify whether agents are similar enough to engage in interaction, as well as to determine whether they belong to the same cluster of similar agents after the system has reached the frozen state. The transitions from a homogeneous state to a fragmented one decrease in abruptness as tolerance is increased. Additionally, the entropy associated to the system presents a maximum within the transition, the width of which increases as tolerance does. Moreover, a plateau was found inside the transition for a low-tolerance system of agents with only two cultural features.

Fame emerges as a result of small memory

NASA Astrophysics Data System (ADS)

Bingol, Haluk

2008-03-01

A dynamic memory model is proposed in which an agent “learns” a new agent by means of recommendation. The agents can also “remember” and “forget.” The memory size is decreased while the population size is kept constant. “Fame” emerged as a few agents become very well known in expense of the majority being completely forgotten. The minimum and the maximum of fame change linearly with the relative memory size. The network properties of the who-knows-who graph, which represents the state of the system, are investigated.

Seldon v.3.0

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

Berry, Nina; Ko, Teresa; Shneider, Max

Seldon is an agent-based social simulation framework that uniquely integrates concepts from a variety of different research areas including psychology, social science, and agent-based modeling. Development has been taking place for a number of years, previously focusing on gang and terrorist recruitment. The toolkit consists of simple agents (individuals) and abstract agents (groups of individuals representing social/institutional concepts) that interact according to exchangeable rule sets (i.e. linear attraction, linear reinforcement). Each agent has a set of customizable attributes that get modified during the interactions. Interactions create relationships between agents, and each agent has a maximum amount of relationship energy thatmore » it can expend. As relationships evolve, they form multiple levels of social networks (i.e. acquaintances, friends, cliques) that in turn drive future interactions. Agents can also interact randomly if they are not connected through a network, mimicking the chance interactions that real people have in everyday life. We are currently integrating Seldon with the cognitive framework (also developed at Sandia). Each individual agent has a lightweight cognitive model that is created automatically from textual sources. Cognitive information is exchanged during interactions, and can also be injected into a running simulation. The entire framework has been parallelized to allow for larger simulations in an HPC environment. We have also added more detail to the agents themselves (a"Big Five" personality model) and their interactions (an enhanced relationship model) for a more realistic representation.« less

Formalizing the Role of Agent-Based Modeling in Causal Inference and Epidemiology

PubMed Central

Marshall, Brandon D. L.; Galea, Sandro

2015-01-01

Calls for the adoption of complex systems approaches, including agent-based modeling, in the field of epidemiology have largely centered on the potential for such methods to examine complex disease etiologies, which are characterized by feedback behavior, interference, threshold dynamics, and multiple interacting causal effects. However, considerable theoretical and practical issues impede the capacity of agent-based methods to examine and evaluate causal effects and thus illuminate new areas for intervention. We build on this work by describing how agent-based models can be used to simulate counterfactual outcomes in the presence of complexity. We show that these models are of particular utility when the hypothesized causal mechanisms exhibit a high degree of interdependence between multiple causal effects and when interference (i.e., one person's exposure affects the outcome of others) is present and of intrinsic scientific interest. Although not without challenges, agent-based modeling (and complex systems methods broadly) represent a promising novel approach to identify and evaluate complex causal effects, and they are thus well suited to complement other modern epidemiologic methods of etiologic inquiry. PMID:25480821

Dynamic electronic institutions in agent oriented cloud robotic systems.

PubMed

Nagrath, Vineet; Morel, Olivier; Malik, Aamir; Saad, Naufal; Meriaudeau, Fabrice

2015-01-01

The dot-com bubble bursted in the year 2000 followed by a swift movement towards resource virtualization and cloud computing business model. Cloud computing emerged not as new form of computing or network technology but a mere remoulding of existing technologies to suit a new business model. Cloud robotics is understood as adaptation of cloud computing ideas for robotic applications. Current efforts in cloud robotics stress upon developing robots that utilize computing and service infrastructure of the cloud, without debating on the underlying business model. HTM5 is an OMG's MDA based Meta-model for agent oriented development of cloud robotic systems. The trade-view of HTM5 promotes peer-to-peer trade amongst software agents. HTM5 agents represent various cloud entities and implement their business logic on cloud interactions. Trade in a peer-to-peer cloud robotic system is based on relationships and contracts amongst several agent subsets. Electronic Institutions are associations of heterogeneous intelligent agents which interact with each other following predefined norms. In Dynamic Electronic Institutions, the process of formation, reformation and dissolution of institutions is automated leading to run time adaptations in groups of agents. DEIs in agent oriented cloud robotic ecosystems bring order and group intellect. This article presents DEI implementations through HTM5 methodology.

Using Improved Equation of State to Model Simultaneous Nucleation and Bubble Growth in Thermoplastic Foams

NASA Astrophysics Data System (ADS)

Khan, Irfan; Costeux, Stephane; Adrian, David; Cristancho, Diego

2013-11-01

Due to environmental regulations carbon-dioxide (CO2) is increasingly being used to replace traditional blowing agents in thermoplastic foams. CO2 is dissolved in the polymer matrix under supercritical conditions. In order to predict the effect of process parameters on foam properties using numerical modeling, the P-V-T relationship of the blowing agents should accurately be represented at the supercritical state. Previous studies in the area of foam modeling have all used ideal gas equation of state to predict the behavior of the blowing agent. In this work the Peng-Robinson equation of state is being used to model the blowing agent during its diffusion into the growing bubble. The model is based on the popular ``Influence Volume Approach,'' which assumes a growing boundary layer with depleted blowing agent surrounds each bubble. Classical nucleation theory is used to predict the rate of nucleation of bubbles. By solving the mass balance, momentum balance and species conservation equations for each bubble, the model is capable of predicting average bubble size, bubble size distribution and bulk porosity. The effect of the improved model on the bubble growth and foam properties are discussed.

Price dynamics of the financial markets using the stochastic differential equation for a potential double well

NASA Astrophysics Data System (ADS)

Lima, L. S.; Miranda, L. L. B.

2018-01-01

We have used the Itô's stochastic differential equation for the double well with additive white noise as a mathematical model for price dynamics of the financial market. We have presented a model which allows us to test within the same framework the comparative explanatory power of rational agents versus irrational agents, with respect to the facts of financial markets. We have obtained the mean price in terms of the β parameter that represents the force of the randomness term of the model.

Behavior believability in virtual worlds: agents acting when they need to.

PubMed

Avradinis, Nikos; Panayiotopoulos, Themis; Anastassakis, George

2013-12-01

Believability has been a perennial goal for the intelligent virtual agent community. One important aspect of believability largely consists in demonstrating autonomous behavior, consistent with the agent's personality and motivational state, as well as the world conditions. Autonomy, on behalf of the agent, implies the existence of an internal structure and mechanism that allows the agent to have its own needs and interests, based on which the agent will dynamically select and generate goals that will in turn lead to self-determined behavior. Intrinsic motivation allows the agent to function and demonstrate behavior, even when no external stimulus is present, due to the constant change of its internal emotional and physiological state. The concept of motivation has already been investigated by research works on intelligent agents, trying to achieve autonomy. The current work presents an architecture and model to represent and manage internal driving factors in intelligent virtual agents, using the concept of motivations. Based on Maslow and Alderfer's bio-psychological needs theories, we present a motivational approach to represent human needs and produce emergent behavior through motivation synthesis. Particular attention is given to basic, physiological level needs, which are the basis of behavior and can produce tendency to action even when there is no other interaction with the environment.

Generative Models of Segregation: Investigating Model-Generated Patterns of Residential Segregation by Ethnicity and Socioeconomic Status

PubMed Central

Fossett, Mark

2011-01-01

This paper considers the potential for using agent models to explore theories of residential segregation in urban areas. Results of generative experiments conducted using an agent-based simulation of segregation dynamics document that varying a small number of model parameters representing constructs from urban-ecological theories of segregation can generate a wide range of qualitatively distinct and substantively interesting segregation patterns. The results suggest how complex, macro-level patterns of residential segregation can arise from a small set of simple micro-level social dynamics operating within particular urban-demographic contexts. The promise and current limitations of agent simulation studies are noted and optimism is expressed regarding the potential for such studies to engage and contribute to the broader research literature on residential segregation. PMID:21379372

Novel Treatment of Staphylococcus aureus Device-Related Infections Using Fibrinolytic Agents.

PubMed

Hogan, S; O'Gara, J P; O'Neill, E

2018-02-01

Staphylococcal infections involving biofilms represent a significant challenge in the treatment of patients with device-related infections. Staphylococcus aureus biofilms have been shown to be SaeRS regulated and dependent on the coagulase-catalyzed conversion of fibrinogen into fibrin on surfaces coated with human plasma. Here we investigated the treatment of staphylococcal biofilm device-related infections by digesting the fibrin biofilm matrix with and without existing antimicrobials. The fibrinolytic agents plasmin, streptokinase, and nattokinase, and TrypLE, a recombinant trypsin-like protease, were used to digest and treat S. aureus biofilms grown in vitro using in vivo -like static biofilm assays with and without antimicrobials. Cytotoxicity, the potential to induce a cytokine response in whole human blood, and the risk of induction of tolerance to fibrinolytic agents were investigated. A rat model of intravascular catheter infection was established to investigate the efficacy of selected fibrinolytic agents in vivo Under biomimetic conditions, the fibrinolytic agents effectively dispersed established S. aureus biofilms and, in combination with common antistaphylococcal antimicrobials, effectively killed bacterial cells being released from the biofilm. These fibrinolytic agents were not cytotoxic and did not affect the host immune response. The rat model of infection successfully demonstrated the activity of the selected fibrinolytic agents alone and in combination with antimicrobials on established biofilms in vivo TrypLE and nattokinase most successfully removed adherent cells from plasma-coated surfaces and significantly improved the efficacy of existing antimicrobials against S. aureus biofilms in vitro and in vivo These biofilm dispersal agents represent a viable future treatment option for S. aureus device-related infections. Copyright © 2018 American Society for Microbiology.

Integrating adaptive behaviour in large-scale flood risk assessments: an Agent-Based Modelling approach

NASA Astrophysics Data System (ADS)

Haer, Toon; Aerts, Jeroen

2015-04-01

Between 1998 and 2009, Europe suffered over 213 major damaging floods, causing 1126 deaths, displacing around half a million people. In this period, floods caused at least 52 billion euro in insured economic losses making floods the most costly natural hazard faced in Europe. In many low-lying areas, the main strategy to cope with floods is to reduce the risk of the hazard through flood defence structures, like dikes and levees. However, it is suggested that part of the responsibility for flood protection needs to shift to households and businesses in areas at risk, and that governments and insurers can effectively stimulate the implementation of individual protective measures. However, adaptive behaviour towards flood risk reduction and the interaction between the government, insurers, and individuals has hardly been studied in large-scale flood risk assessments. In this study, an European Agent-Based Model is developed including agent representatives for the administrative stakeholders of European Member states, insurers and reinsurers markets, and individuals following complex behaviour models. The Agent-Based Modelling approach allows for an in-depth analysis of the interaction between heterogeneous autonomous agents and the resulting (non-)adaptive behaviour. Existing flood damage models are part of the European Agent-Based Model to allow for a dynamic response of both the agents and the environment to changing flood risk and protective efforts. By following an Agent-Based Modelling approach this study is a first contribution to overcome the limitations of traditional large-scale flood risk models in which the influence of individual adaptive behaviour towards flood risk reduction is often lacking.

Agent-based approach for generation of a money-centered star network

NASA Astrophysics Data System (ADS)

Yang, Jae-Suk; Kwon, Okyu; Jung, Woo-Sung; Kim, In-mook

2008-09-01

The history of trade is a progression from a pure barter system. A medium of exchange emerges autonomously in the market, a position currently occupied by money. We investigate an agent-based computational economics model consisting of interacting agents considering distinguishable properties of commodities which represent salability. We also analyze the properties of the commodity network using a spanning tree. We find that the “storage fee” is more crucial than “demand” in determining which commodity is used as a medium of exchange.

Chemotherapy-induced pulmonary hypertension: role of alkylating agents.

PubMed

Ranchoux, Benoît; Günther, Sven; Quarck, Rozenn; Chaumais, Marie-Camille; Dorfmüller, Peter; Antigny, Fabrice; Dumas, Sébastien J; Raymond, Nicolas; Lau, Edmund; Savale, Laurent; Jaïs, Xavier; Sitbon, Olivier; Simonneau, Gérald; Stenmark, Kurt; Cohen-Kaminsky, Sylvia; Humbert, Marc; Montani, David; Perros, Frédéric

2015-02-01

Pulmonary veno-occlusive disease (PVOD) is an uncommon form of pulmonary hypertension (PH) characterized by progressive obstruction of small pulmonary veins and a dismal prognosis. Limited case series have reported a possible association between different chemotherapeutic agents and PVOD. We evaluated the relationship between chemotherapeutic agents and PVOD. Cases of chemotherapy-induced PVOD from the French PH network and literature were reviewed. Consequences of chemotherapy exposure on the pulmonary vasculature and hemodynamics were investigated in three different animal models (mouse, rat, and rabbit). Thirty-seven cases of chemotherapy-associated PVOD were identified in the French PH network and systematic literature analysis. Exposure to alkylating agents was observed in 83.8% of cases, mostly represented by cyclophosphamide (43.2%). In three different animal models, cyclophosphamide was able to induce PH on the basis of hemodynamic, morphological, and biological parameters. In these models, histopathological assessment confirmed significant pulmonary venous involvement highly suggestive of PVOD. Together, clinical data and animal models demonstrated a plausible cause-effect relationship between alkylating agents and PVOD. Clinicians should be aware of this uncommon, but severe, pulmonary vascular complication of alkylating agents. Copyright © 2015 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Minimal agent based model for financial markets I. Origin and self-organization of stylized facts

NASA Astrophysics Data System (ADS)

Alfi, V.; Cristelli, M.; Pietronero, L.; Zaccaria, A.

2009-02-01

We introduce a minimal agent based model for financial markets to understand the nature and self-organization of the stylized facts. The model is minimal in the sense that we try to identify the essential ingredients to reproduce the most important deviations of price time series from a random walk behavior. We focus on four essential ingredients: fundamentalist agents which tend to stabilize the market; chartist agents which induce destabilization; analysis of price behavior for the two strategies; herding behavior which governs the possibility of changing strategy. Bubbles and crashes correspond to situations dominated by chartists, while fundamentalists provide a long time stability (on average). The stylized facts are shown to correspond to an intermittent behavior which occurs only for a finite value of the number of agents N. Therefore they correspond to finite size effects which, however, can occur at different time scales. We propose a new mechanism for the self-organization of this state which is linked to the existence of a threshold for the agents to be active or not active. The feedback between price fluctuations and number of active agents represents a crucial element for this state of self-organized intermittency. The model can be easily generalized to consider more realistic variants.

Agreement dynamics on interaction networks with diverse topologies

NASA Astrophysics Data System (ADS)

Barrat, Alain; Baronchelli, Andrea; Dall'Asta, Luca; Loreto, Vittorio

2007-06-01

We review the behavior of a recently introduced model of agreement dynamics, called the "Naming Game." This model describes the self-organized emergence of linguistic conventions and the establishment of simple communication systems in a population of agents with pairwise local interactions. The mechanisms of convergence towards agreement strongly depend on the network of possible interactions between the agents. In particular, the mean-field case in which all agents communicate with all the others is not efficient, since a large temporary memory is requested for the agents. On the other hand, regular lattice topologies lead to a fast local convergence but to a slow global dynamics similar to coarsening phenomena. The embedding of the agents in a small-world network represents an interesting tradeoff: a local consensus is easily reached, while the long-range links allow to bypass coarsening-like convergence. We also consider alternative adaptive strategies which can lead to faster global convergence.

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.

A hamster model for Marburg virus infection accurately recapitulates Marburg hemorrhagic fever

PubMed Central

Marzi, Andrea; Banadyga, Logan; Haddock, Elaine; Thomas, Tina; Shen, Kui; Horne, Eva J.; Scott, Dana P.; Feldmann, Heinz; Ebihara, Hideki

2016-01-01

Marburg virus (MARV), a close relative of Ebola virus, is the causative agent of a severe human disease known as Marburg hemorrhagic fever (MHF). No licensed vaccine or therapeutic exists to treat MHF, and MARV is therefore classified as a Tier 1 select agent and a category A bioterrorism agent. In order to develop countermeasures against this severe disease, animal models that accurately recapitulate human disease are required. Here we describe the development of a novel, uniformly lethal Syrian golden hamster model of MHF using a hamster-adapted MARV variant Angola. Remarkably, this model displayed almost all of the clinical features of MHF seen in humans and non-human primates, including coagulation abnormalities, hemorrhagic manifestations, petechial rash, and a severely dysregulated immune response. This MHF hamster model represents a powerful tool for further dissecting MARV pathogenesis and accelerating the development of effective medical countermeasures against human MHF. PMID:27976688

A hamster model for Marburg virus infection accurately recapitulates Marburg hemorrhagic fever.

PubMed

Marzi, Andrea; Banadyga, Logan; Haddock, Elaine; Thomas, Tina; Shen, Kui; Horne, Eva J; Scott, Dana P; Feldmann, Heinz; Ebihara, Hideki

2016-12-15

Marburg virus (MARV), a close relative of Ebola virus, is the causative agent of a severe human disease known as Marburg hemorrhagic fever (MHF). No licensed vaccine or therapeutic exists to treat MHF, and MARV is therefore classified as a Tier 1 select agent and a category A bioterrorism agent. In order to develop countermeasures against this severe disease, animal models that accurately recapitulate human disease are required. Here we describe the development of a novel, uniformly lethal Syrian golden hamster model of MHF using a hamster-adapted MARV variant Angola. Remarkably, this model displayed almost all of the clinical features of MHF seen in humans and non-human primates, including coagulation abnormalities, hemorrhagic manifestations, petechial rash, and a severely dysregulated immune response. This MHF hamster model represents a powerful tool for further dissecting MARV pathogenesis and accelerating the development of effective medical countermeasures against human MHF.

Understanding the complex dynamics of stock markets through cellular automata

NASA Astrophysics Data System (ADS)

Qiu, G.; Kandhai, D.; Sloot, P. M. A.

2007-04-01

We present a cellular automaton (CA) model for simulating the complex dynamics of stock markets. Within this model, a stock market is represented by a two-dimensional lattice, of which each vertex stands for a trader. According to typical trading behavior in real stock markets, agents of only two types are adopted: fundamentalists and imitators. Our CA model is based on local interactions, adopting simple rules for representing the behavior of traders and a simple rule for price updating. This model can reproduce, in a simple and robust manner, the main characteristics observed in empirical financial time series. Heavy-tailed return distributions due to large price variations can be generated through the imitating behavior of agents. In contrast to other microscopic simulation (MS) models, our results suggest that it is not necessary to assume a certain network topology in which agents group together, e.g., a random graph or a percolation network. That is, long-range interactions can emerge from local interactions. Volatility clustering, which also leads to heavy tails, seems to be related to the combined effect of a fast and a slow process: the evolution of the influence of news and the evolution of agents’ activity, respectively. In a general sense, these causes of heavy tails and volatility clustering appear to be common among some notable MS models that can confirm the main characteristics of financial markets.

Projecting Sexual and Injecting HIV Risks into Future Outcomes with Agent-Based Modeling

NASA Astrophysics Data System (ADS)

Bobashev, Georgiy V.; Morris, Robert J.; Zule, William A.

Longitudinal studies of health outcomes for HIV could be very costly cumbersome and not representative of the risk population. Conversely, cross-sectional approaches could be representative but rely on the retrospective information to estimate prevalence and incidence. We present an Agent-based Modeling (ABM) approach where we use behavioral data from a cross-sectional representative study and project the behavior into the future so that the risks of acquiring HIV could be studied in a dynamical/temporal sense. We show how the blend of behavior and contact network factors (sexual, injecting) play the role in the risk of future HIV acquisition and time till obtaining HIV. We show which subjects are the most likely persons to get HIV in the next year, and whom they are likely to infect. We examine how different behaviors are related to the increase or decrease of HIV risks and how to estimate the quantifiable risk measures such as survival HIV free.

The self-aware diabetic patient software agent model.

PubMed

Wang, Zhanle; Paranjape, Raman

2013-11-01

This work presents a self-aware diabetic patient software agent for representing a human diabetic patient. To develop a 24h, stochastic and self-aware patient agent, we extend the original seminal work of Ackerman et al. [1] in creating a mathematical model of human blood glucose levels in three aspects. (1) We incorporate the stochastic and unpredictable effects of daily living. (2) The Ackerman model is extended into the period of night-time. (3) Patients' awareness of their own conditions is incorporated. Simulation results are quantitatively assessed to demonstrate the effectiveness of lifestyle management, such as adjusting the amount of food consumed, meal schedule, intensity of exercise and level of medication. In this work we show through the simulation that the average blood glucose can be reduced by as much as 51% due to careful lifestyle management. Self monitoring blood glucose is also quantitatively evaluated. The simulation results show that the average blood glucose is further dropped by 25% with the assistance of blood glucose samples. In addition, the blood glucose is perfectly controlled in the target range during the simulation period as a result of joint efforts of lifestyle management and self monitoring blood glucose. This study focuses on demonstrating how human patients' behavior, specifically lifestyle and self monitoring of blood glucose, affects blood glucose controls on a daily basis. This work does not focus on the insulin-glucose interaction of an individual human patient. Our conclusion is that this self-aware patient agent model is capable of adequately representing diabetic patients and of evaluating their dynamic behaviors. It can also be incorporated into a multi-agent system by introducing other healthcare components so that more interesting insights such as the healthcare quality, cost and performance can be observed. © 2013 Published by Elsevier Ltd.

Introduction of an agent-based multi-scale modular architecture for dynamic knowledge representation of acute inflammation.

PubMed

An, Gary

2008-05-27

One of the greatest challenges facing biomedical research is the integration and sharing of vast amounts of information, not only for individual researchers, but also for the community at large. Agent Based Modeling (ABM) can provide a means of addressing this challenge via a unifying translational architecture for dynamic knowledge representation. This paper presents a series of linked ABMs representing multiple levels of biological organization. They are intended to translate the knowledge derived from in vitro models of acute inflammation to clinically relevant phenomenon such as multiple organ failure. ABM development followed a sequence starting with relatively direct translation from in-vitro derived rules into a cell-as-agent level ABM, leading on to concatenated ABMs into multi-tissue models, eventually resulting in topologically linked aggregate multi-tissue ABMs modeling organ-organ crosstalk. As an underlying design principle organs were considered to be functionally composed of an epithelial surface, which determined organ integrity, and an endothelial/blood interface, representing the reaction surface for the initiation and propagation of inflammation. The development of the epithelial ABM derived from an in-vitro model of gut epithelial permeability is described. Next, the epithelial ABM was concatenated with the endothelial/inflammatory cell ABM to produce an organ model of the gut. This model was validated against in-vivo models of the inflammatory response of the gut to ischemia. Finally, the gut ABM was linked to a similarly constructed pulmonary ABM to simulate the gut-pulmonary axis in the pathogenesis of multiple organ failure. The behavior of this model was validated against in-vivo and clinical observations on the cross-talk between these two organ systems. A series of ABMs are presented extending from the level of intracellular mechanism to clinically observed behavior in the intensive care setting. The ABMs all utilize cell-level agents that encapsulate specific mechanistic knowledge extracted from in vitro experiments. The execution of the ABMs results in a dynamic representation of the multi-scale conceptual models derived from those experiments. These models represent a qualitative means of integrating basic scientific information on acute inflammation in a multi-scale, modular architecture as a means of conceptual model verification that can potentially be used to concatenate, communicate and advance community-wide knowledge.

Role of noise and agents’ convictions on opinion spreading in a three-state voter-like model

NASA Astrophysics Data System (ADS)

Crokidakis, Nuno

2013-07-01

In this work we study opinion formation in a voter-like model defined on a square lattice of linear size L. The agents may be in three different states, representing any public debate with three choices (yes, no, undecided). We consider heterogeneous agents that have different convictions about their opinions. These convictions limit the capacity of persuasion of the individuals during the interactions. Moreover, there is a noise p that represents the probability of an individual spontaneously changing his opinion to the undecided state. Our simulations suggest that the system reaches stationary states for all values of p, with consensus states occurring only for the noiseless case p = 0. In this case, the relaxation times are distributed according to a log-normal function, with the average value τ growing with the lattice size as τ ∼ Lα, where α ≈ 0.9. We found a threshold value p* ≈ 0.9 above which the stationary fraction of undecided agents is greater than the fraction of decided ones. We also study the consequences of the presence of external effects in the system, which models the influence of mass media on opinion formation.

Complexity of life via collective mind

NASA Technical Reports Server (NTRS)

Zak, Michail

2004-01-01

e mind is introduced as a set of simple intelligent units (say, neurons, or interacting agents), which can communicate by exchange of information without explicit global control. Incomplete information is compensated by a sequence of random guesses symmetrically distributed around expectations with prescribed variances. Both the expectations and variances are the invariants characterizing the whole class of agents. These invariants are stored as parameters of the collective mind, while they contribute into dynamical formalism of the agents' evolution, and in particular, into the reflective chains of their nested abstract images of the selves and non-selves. The proposed model consists of the system of stochastic differential equations in the Langevin form representing the motor dynamics, and the corresponding Fokker-Planck equation representing the mental dynamics (Motor dynamics describes the motion in physical space, while mental dynamics simulates the evolution of initial errors in terms of the probability density). The main departure of this model from Newtonian and statistical physics is due to a feedback from the mental to the motor dynamics which makes the Fokker-Planck equation nonlinear. Interpretation of this model from mathematical and physical viewpoints, as well as possible interpretation from biological, psychological, and social viewpoints are discussed. The model is illustrated by the dynamics of a dialog.

29 CFR 453.5 - Officers, agents, shop stewards, or other representatives or employees of a labor organization.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 29 Labor 2 2010-07-01 2010-07-01 false Officers, agents, shop stewards, or other representatives... Determining Who Must Be Bonded § 453.5 Officers, agents, shop stewards, or other representatives or employees of a labor organization. With respect to labor organizations, the term “officer, agent, shop steward...

29 CFR 453.5 - Officers, agents, shop stewards, or other representatives or employees of a labor organization.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 29 Labor 2 2014-07-01 2014-07-01 false Officers, agents, shop stewards, or other representatives... Determining Who Must Be Bonded § 453.5 Officers, agents, shop stewards, or other representatives or employees of a labor organization. With respect to labor organizations, the term “officer, agent, shop steward...

29 CFR 453.5 - Officers, agents, shop stewards, or other representatives or employees of a labor organization.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 29 Labor 2 2011-07-01 2011-07-01 false Officers, agents, shop stewards, or other representatives... Determining Who Must Be Bonded § 453.5 Officers, agents, shop stewards, or other representatives or employees of a labor organization. With respect to labor organizations, the term “officer, agent, shop steward...

29 CFR 453.5 - Officers, agents, shop stewards, or other representatives or employees of a labor organization.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 29 Labor 2 2013-07-01 2013-07-01 false Officers, agents, shop stewards, or other representatives... Determining Who Must Be Bonded § 453.5 Officers, agents, shop stewards, or other representatives or employees of a labor organization. With respect to labor organizations, the term “officer, agent, shop steward...

29 CFR 453.5 - Officers, agents, shop stewards, or other representatives or employees of a labor organization.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 29 Labor 2 2012-07-01 2012-07-01 false Officers, agents, shop stewards, or other representatives... Determining Who Must Be Bonded § 453.5 Officers, agents, shop stewards, or other representatives or employees of a labor organization. With respect to labor organizations, the term “officer, agent, shop steward...

Coevolutionary, coexisting learning and teaching agents model for prisoner’s dilemma games enhancing cooperation with assortative heterogeneous networks

NASA Astrophysics Data System (ADS)

Tanimoto, Jun

2013-07-01

Unlike other natural network systems, assortativity can be observed in most human social networks, although it has been reported that a social dilemma situation represented by the prisoner’s dilemma favors dissortativity to enhance cooperation. We established a new coevolutionary model for both agents’ strategy and network topology, where teaching and learning agents coexist. Remarkably, this model enables agents’ enhancing cooperation more than a learners-only model on a time-frozen scale-free network and produces an underlying assortative network with a fair degree of power-law distribution. The model may imply how and why assortative networks are adaptive in human society.

Simulation of Tasks Distribution in Horizontally Scalable Management System

NASA Astrophysics Data System (ADS)

Kustov, D.; Sherstneva, A.; Botygin, I.

2016-08-01

This paper presents an imitational model of the task distribution system for the components of territorially-distributed automated management system with a dynamically changing topology. Each resource of the distributed automated management system is represented with an agent, which allows to set behavior of every resource in the best possible way and ensure their interaction. The agent work load imitation was done via service query imitation formed in a system dynamics style using a stream diagram. The query generation took place in the abstract-represented center - afterwards, they were sent to the drive to be distributed to management system resources according to a ranking table.

The dynamics of financial stability in complex networks

NASA Astrophysics Data System (ADS)

da Cruz, J. P.; Lind, P. G.

2012-08-01

We address the problem of banking system resilience by applying off-equilibrium statistical physics to a system of particles, representing the economic agents, modelled according to the theoretical foundation of the current banking regulation, the so called Merton-Vasicek model. Economic agents are attracted to each other to exchange `economic energy', forming a network of trades. When the capital level of one economic agent drops below a minimum, the economic agent becomes insolvent. The insolvency of one single economic agent affects the economic energy of all its neighbours which thus become susceptible to insolvency, being able to trigger a chain of insolvencies (avalanche). We show that the distribution of avalanche sizes follows a power-law whose exponent depends on the minimum capital level. Furthermore, we present evidence that under an increase in the minimum capital level, large crashes will be avoided only if one assumes that agents will accept a drop in business levels, while keeping their trading attitudes and policies unchanged. The alternative assumption, that agents will try to restore their business levels, may lead to the unexpected consequence that large crises occur with higher probability.

Agent-based modeling in ecological economics.

PubMed

Heckbert, Scott; Baynes, Tim; Reeson, Andrew

2010-01-01

Interconnected social and environmental systems are the domain of ecological economics, and models can be used to explore feedbacks and adaptations inherent in these systems. Agent-based modeling (ABM) represents autonomous entities, each with dynamic behavior and heterogeneous characteristics. Agents interact with each other and their environment, resulting in emergent outcomes at the macroscale that can be used to quantitatively analyze complex systems. ABM is contributing to research questions in ecological economics in the areas of natural resource management and land-use change, urban systems modeling, market dynamics, changes in consumer attitudes, innovation, and diffusion of technology and management practices, commons dilemmas and self-governance, and psychological aspects to human decision making and behavior change. Frontiers for ABM research in ecological economics involve advancing the empirical calibration and validation of models through mixed methods, including surveys, interviews, participatory modeling, and, notably, experimental economics to test specific decision-making hypotheses. Linking ABM with other modeling techniques at the level of emergent properties will further advance efforts to understand dynamics of social-environmental systems.

Biological agents for controlling excessive scarring.

PubMed

Berman, Brian

2010-01-01

The potential of various biological agents to reduce or prevent excessive scar formation has now been evaluated in numerous in-vitro studies, experimental animal models and preliminary clinical trials, in some cases with particularly promising results. Perhaps prominent among this group of biological agents, and, to some degree, possibly representing marketed compounds already being used 'off label' to manage excessive scarring, are the tumor necrosis factor alpha antagonist etanercept, and immune-response modifiers such as IFNalpha2b and imiquimod. Additional assessment of these novel agents is now justified with a view to reducing or preventing hypertrophic scars, keloid scars and the recurrence of post-excision keloid lesions.

An agent-based model identifies MRI regions of probable tumor invasion in a patient with glioblastoma

NASA Astrophysics Data System (ADS)

Chen, L. Leon; Ulmer, Stephan; Deisboeck, Thomas S.

2010-01-01

We present an application of a previously developed agent-based glioma model (Chen et al 2009 Biosystems 95 234-42) for predicting spatio-temporal tumor progression using a patient-specific MRI lattice derived from apparent diffusion coefficient (ADC) data. Agents representing collections of migrating glioma cells are initialized based upon voxels at the outer border of the tumor identified on T1-weighted (Gd+) MRI at an initial time point. These simulated migratory cells exhibit a specific biologically inspired spatial search paradigm, representing a weighting of the differential contribution from haptotactic permission and biomechanical resistance on the migration decision process. ADC data from 9 months after the initial tumor resection were used to select the best search paradigm for the simulation, which was initiated using data from 6 months after the initial operation. Using this search paradigm, 100 simulations were performed to derive a probabilistic map of tumor invasion locations. The simulation was able to successfully predict a recurrence in the dorsal/posterior aspect long before it was depicted on T1-weighted MRI, 18 months after the initial operation.

An agent-based model identifies MRI regions of probable tumor invasion in a patient with glioblastoma.

PubMed

Chen, L Leon; Ulmer, Stephan; Deisboeck, Thomas S

2010-01-21

We present an application of a previously developed agent-based glioma model (Chen et al 2009 Biosystems 95 234-42) for predicting spatio-temporal tumor progression using a patient-specific MRI lattice derived from apparent diffusion coefficient (ADC) data. Agents representing collections of migrating glioma cells are initialized based upon voxels at the outer border of the tumor identified on T1-weighted (Gd+) MRI at an initial time point. These simulated migratory cells exhibit a specific biologically inspired spatial search paradigm, representing a weighting of the differential contribution from haptotactic permission and biomechanical resistance on the migration decision process. ADC data from 9 months after the initial tumor resection were used to select the best search paradigm for the simulation, which was initiated using data from 6 months after the initial operation. Using this search paradigm, 100 simulations were performed to derive a probabilistic map of tumor invasion locations. The simulation was able to successfully predict a recurrence in the dorsal/posterior aspect long before it was depicted on T1-weighted MRI, 18 months after the initial operation.

Modelling of Robotized Manufacturing Systems Using MultiAgent Formalism

NASA Astrophysics Data System (ADS)

Foit, K.; Gwiazda, A.; Banaś, W.

2016-08-01

The evolution of manufacturing systems has greatly accelerated due to development of sophisticated control systems. On top of determined, one way production flow the need of decision making has arisen as a result of growing product range that are manufactured simultaneously, using the same resources. On the other hand, the intelligent flow control could address the “bottleneck” problem caused by the machine failure. This sort of manufacturing systems uses advanced control algorithms that are introduced by the use of logic controllers. The complex algorithms used in the control systems requires to employ appropriate methods during the modelling process, like the agent-based one, which is the subject of this paper. The concept of an agent is derived from the object-based methodology of modelling, so it meets the requirements of representing the physical properties of the machines as well as the logical form of control systems. Each agent has a high level of autonomy and could be considered separately. The multi-agent system consists of minimum two agents that can interact and modify the environment, where they act. This may lead to the creation of self-organizing structure, what could be interesting feature during design and test of manufacturing system.

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.

An agent-based approach for modeling dynamics of contagious disease spread

PubMed Central

Perez, Liliana; Dragicevic, Suzana

2009-01-01

Background The propagation of communicable diseases through a population is an inherent spatial and temporal process of great importance for modern society. For this reason a spatially explicit epidemiologic model of infectious disease is proposed for a greater understanding of the disease's spatial diffusion through a network of human contacts. Objective The objective of this study is to develop an agent-based modelling approach the integrates geographic information systems (GIS) to simulate the spread of a communicable disease in an urban environment, as a result of individuals' interactions in a geospatial context. Methods The methodology for simulating spatiotemporal dynamics of communicable disease propagation is presented and the model is implemented using measles outbreak in an urban environment as a case study. Individuals in a closed population are explicitly represented by agents associated to places where they interact with other agents. They are endowed with mobility, through a transportation network allowing them to move between places within the urban environment, in order to represent the spatial heterogeneity and the complexity involved in infectious diseases diffusion. The model is implemented on georeferenced land use dataset from Metro Vancouver and makes use of census data sets from Statistics Canada for the municipality of Burnaby, BC, Canada study site. Results The results provide insights into the application of the model to calculate ratios of susceptible/infected in specific time frames and urban environments, due to its ability to depict the disease progression based on individuals' interactions. It is demonstrated that the dynamic spatial interactions within the population lead to high numbers of exposed individuals who perform stationary activities in areas after they have finished commuting. As a result, the sick individuals are concentrated in geographical locations like schools and universities. Conclusion The GIS-agent based model designed for this study can be easily customized to study the disease spread dynamics of any other communicable disease by simply adjusting the modeled disease timeline and/or the infection model and modifying the transmission process. This type of simulations can help to improve comprehension of disease spread dynamics and to take better steps towards the prevention and control of an epidemic outbreak. PMID:19656403

Agent-based modeling of the immune system: NetLogo, a promising framework.

PubMed

Chiacchio, Ferdinando; Pennisi, Marzio; Russo, Giulia; Motta, Santo; Pappalardo, Francesco

2014-01-01

Several components that interact with each other to evolve a complex, and, in some cases, unexpected behavior, represents one of the main and fascinating features of the mammalian immune system. Agent-based modeling and cellular automata belong to a class of discrete mathematical approaches in which entities (agents) sense local information and undertake actions over time according to predefined rules. The strength of this approach is characterized by the appearance of a global behavior that emerges from interactions among agents. This behavior is unpredictable, as it does not follow linear rules. There are a lot of works that investigates the immune system with agent-based modeling and cellular automata. They have shown the ability to see clearly and intuitively into the nature of immunological processes. NetLogo is a multiagent programming language and modeling environment for simulating complex phenomena. It is designed for both research and education and is used across a wide range of disciplines and education levels. In this paper, we summarize NetLogo applications to immunology and, particularly, how this framework can help in the development and formulation of hypotheses that might drive further experimental investigations of disease mechanisms.

Characterizing segregation in the Schelling-Voter model

NASA Astrophysics Data System (ADS)

Caridi, I.; Pinasco, J. P.; Saintier, N.; Schiaffino, P.

2017-12-01

In this work we analyze several aspects related with segregation patterns appearing in the Schelling-Voter model in which an unhappy agent can change her location or her state in order to live in a neighborhood where she is happy. Briefly, agents may be in two possible states, each one represents an individually-chosen feature, such as the language she speaks or the opinion she supports; and an individual is happy in a neighborhood if she has, at least, some proportion of agents of her own type, defined in terms of a fixed parameter T. We study the model in a regular two dimensional lattice. The parameters of the model are ρ, the density of empty sites, and p, the probability of changing locations. The stationary states reached in a system of N agents as a function of the model parameters entail the extinction of one of the states, the coexistence of both, segregated patterns with conglomerated clusters of agents of the same state, and a diluted region. Using indicators as the energy and perimeter of the populations of agents in the same state, the inner radius of their locations (i.e., the side of the maximum square which could fit with empty spaces or agents of only one type), and the Shannon Information of the empty sites, we measure the segregation phenomena. We have found that there is a region within the coexistence phase where both populations take advantage of space in an equitable way, which is sustained by the role of the empty sites.

Modeling the Information Age Combat Model: An Agent-Based Simulation of Network Centric Operations

NASA Technical Reports Server (NTRS)

Deller, Sean; Rabadi, Ghaith A.; Bell, Michael I.; Bowling, Shannon R.; Tolk, Andreas

2010-01-01

The Information Age Combat Model (IACM) was introduced by Cares in 2005 to contribute to the development of an understanding of the influence of connectivity on force effectiveness that can eventually lead to quantitative prediction and guidelines for design and employment. The structure of the IACM makes it clear that the Perron-Frobenius Eigenvalue is a quantifiable metric with which to measure the organization of a networked force. The results of recent experiments presented in Deller, et aI., (2009) indicate that the value of the Perron-Frobenius Eigenvalue is a significant measurement of the performance of an Information Age combat force. This was accomplished through the innovative use of an agent-based simulation to model the IACM and represents an initial contribution towards a new generation of combat models that are net-centric instead of using the current platform-centric approach. This paper describes the intent, challenges, design, and initial results of this agent-based simulation model.

Effective organizational transformation in psychiatric rehabilitation and recovery.

PubMed

Clossey, Laurene; Rowlett, Al

2008-01-01

The recovery model represents a new paradigm in the treatment of psychiatric disability. Many states have mandated the model's adoption by their public mental health agencies. As organizational transformation toward this new approach is rapidly occurring, guidance to make successful change is necessary. The recovery model is readily misunderstood and may be resisted by professional occupational cultures that perceive it as a threat to their expertise. Successful change agents need to understand likely sources of resistance to agency transformation, and be knowledgeable and skilled in organizational development to facilitate service conversion to the recovery model. Change agents need to carefully consider how to transform agency structure and culture and how to develop committed leadership that empowers staff. Recovery values and principles must infuse the entire organization. Guidelines to assist change agents are discussed and distilled through the example of a successful northern California recovery model mental health agency called Turning Point Community Programs. The guidance provided seeks to help make the recovery model portable across many types of mental health settings.

29 CFR 453.6 - Officers, agents, shop stewards or other representatives or employees of a trust in which a labor...

Code of Federal Regulations, 2013 CFR

2013-07-01

... 29 Labor 2 2013-07-01 2013-07-01 false Officers, agents, shop stewards or other representatives or... OF 1959 Criteria for Determining Who Must Be Bonded § 453.6 Officers, agents, shop stewards or other representatives or employees of a trust in which a labor organization is interested. (a) Officers, agents, shop...

29 CFR 453.6 - Officers, agents, shop stewards or other representatives or employees of a trust in which a labor...

Code of Federal Regulations, 2014 CFR

2014-07-01

... 29 Labor 2 2014-07-01 2014-07-01 false Officers, agents, shop stewards or other representatives or... OF 1959 Criteria for Determining Who Must Be Bonded § 453.6 Officers, agents, shop stewards or other representatives or employees of a trust in which a labor organization is interested. (a) Officers, agents, shop...

29 CFR 453.6 - Officers, agents, shop stewards or other representatives or employees of a trust in which a labor...

Code of Federal Regulations, 2012 CFR

2012-07-01

... 29 Labor 2 2012-07-01 2012-07-01 false Officers, agents, shop stewards or other representatives or... OF 1959 Criteria for Determining Who Must Be Bonded § 453.6 Officers, agents, shop stewards or other representatives or employees of a trust in which a labor organization is interested. (a) Officers, agents, shop...

29 CFR 453.6 - Officers, agents, shop stewards or other representatives or employees of a trust in which a labor...

Code of Federal Regulations, 2011 CFR

2011-07-01

... 29 Labor 2 2011-07-01 2011-07-01 false Officers, agents, shop stewards or other representatives or... OF 1959 Criteria for Determining Who Must Be Bonded § 453.6 Officers, agents, shop stewards or other representatives or employees of a trust in which a labor organization is interested. (a) Officers, agents, shop...

29 CFR 453.6 - Officers, agents, shop stewards or other representatives or employees of a trust in which a labor...

Code of Federal Regulations, 2010 CFR

2010-07-01

... 29 Labor 2 2010-07-01 2010-07-01 false Officers, agents, shop stewards or other representatives or... OF 1959 Criteria for Determining Who Must Be Bonded § 453.6 Officers, agents, shop stewards or other representatives or employees of a trust in which a labor organization is interested. (a) Officers, agents, shop...

Impact of different policies on unhealthy dietary behaviors in an urban adult population: an agent-based simulation model.

PubMed

Zhang, Donglan; Giabbanelli, Philippe J; Arah, Onyebuchi A; Zimmerman, Frederick J

2014-07-01

Unhealthy eating is a complex-system problem. We used agent-based modeling to examine the effects of different policies on unhealthy eating behaviors. We developed an agent-based simulation model to represent a synthetic population of adults in Pasadena, CA, and how they make dietary decisions. Data from the 2007 Food Attitudes and Behaviors Survey and other empirical studies were used to calibrate the parameters of the model. Simulations were performed to contrast the potential effects of various policies on the evolution of dietary decisions. Our model showed that a 20% increase in taxes on fast foods would lower the probability of fast-food consumption by 3 percentage points, whereas improving the visibility of positive social norms by 10%, either through community-based or mass-media campaigns, could improve the consumption of fruits and vegetables by 7 percentage points and lower fast-food consumption by 6 percentage points. Zoning policies had no significant impact. Interventions emphasizing healthy eating norms may be more effective than directly targeting food prices or regulating local food outlets. Agent-based modeling may be a useful tool for testing the population-level effects of various policies within complex systems.

Formalizing the role of agent-based modeling in causal inference and epidemiology.

PubMed

Marshall, Brandon D L; Galea, Sandro

2015-01-15

Calls for the adoption of complex systems approaches, including agent-based modeling, in the field of epidemiology have largely centered on the potential for such methods to examine complex disease etiologies, which are characterized by feedback behavior, interference, threshold dynamics, and multiple interacting causal effects. However, considerable theoretical and practical issues impede the capacity of agent-based methods to examine and evaluate causal effects and thus illuminate new areas for intervention. We build on this work by describing how agent-based models can be used to simulate counterfactual outcomes in the presence of complexity. We show that these models are of particular utility when the hypothesized causal mechanisms exhibit a high degree of interdependence between multiple causal effects and when interference (i.e., one person's exposure affects the outcome of others) is present and of intrinsic scientific interest. Although not without challenges, agent-based modeling (and complex systems methods broadly) represent a promising novel approach to identify and evaluate complex causal effects, and they are thus well suited to complement other modern epidemiologic methods of etiologic inquiry. © The Author 2014. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Migration statistics relevant for malaria transmission in Senegal derived from mobile phone data and used in an agent-based migration model.

PubMed

Tompkins, Adrian M; McCreesh, Nicky

2016-03-31

One year of mobile phone location data from Senegal is analysed to determine the characteristics of journeys that result in an overnight stay, and are thus relevant for malaria transmission. Defining the home location of each person as the place of most frequent calls, it is found that approximately 60% of people who spend nights away from home have regular destinations that are repeatedly visited, although only 10% have 3 or more regular destinations. The number of journeys involving overnight stays peaks at a distance of 50 km, although roughly half of such journeys exceed 100 km. Most visits only involve a stay of one or two nights away from home, with just 4% exceeding one week. A new agent-based migration model is introduced, based on a gravity model adapted to represent overnight journeys. Each agent makes journeys involving overnight stays to either regular or random locations, with journey and destination probabilities taken from the mobile phone dataset. Preliminary simulations show that the agent-based model can approximately reproduce the patterns of migration involving overnight stays.

The coevolution of partner switching and strategy updating in non-excludable public goods game

NASA Astrophysics Data System (ADS)

Li, Yixiao; Shen, Bin

2013-10-01

Spatial public goods game is a popular metaphor to model the dilemma of collective cooperation on graphs, yet the non-excludable property of public goods has seldom been considered in previous models. Based upon a coevolutionary model where agents play public goods games and adjust their partnerships, the present model incorporates the non-excludable property of public goods: agents are able to adjust their participation in the games hosted by others, whereas they cannot exclude others from their own games. In the coevolution, a directed and dynamical network which represents partnerships among autonomous agents is evolved. We find that non-excludable property counteracts the positive effect of partner switching, i.e., the equilibrium level of cooperation is lower than that in the situation of excludable public goods game. Therefore, we study the effect of individual punishment that cooperative agents pay a personal cost to decrease benefits of those defective neighbors who participate in their hosted games. It is found that the cooperation level in the whole population is heightened in the presence of such a costly behavior.

Prostate Cancer Chemoprevention Targeting Men with High-Grade Prostatic Intraepithelial Neoplasia (HGPIN) and Atypical Small Acinar Proliferation (ASAP): Model for Trial Design and Outcome Measures.

PubMed

Kumar, Nagi; Crocker, Theresa; Smith, Tiffany; Connors, Shahnjayla; Pow-Sang, Julio; Spiess, Philippe E; Egan, Kathleen; Quinn, Gwen; Schell, Michael; Sebti, Said; Kazi, Aslam; Chuang, Tian; Salup, Raoul; Helal, Mohamed; Zagaja, Gregory; Trabulsi, Edouard; McLarty, Jerry; Fazili, Tajammul; Williams, Christopher R; Schreiber, Fred; Anderson, Kyle

2012-01-21

In spite of the large number of nutrient-derived agents demonstrating promise as potential chemopreventive agents, most have failed to prove effectiveness in clinical trials. Critical requirements for moving nutrient-derived agents to recommendation for clinical use include adopting a systematic, molecular-mechanism based approach and utilizing the same ethical and rigorous methods such as are used to evaluate other pharmacological agents. Preliminary data on a mechanistic rationale for chemoprevention activity as observed from epidemiological, in vitro and preclinical studies, phase I data of safety in suitable cohorts, duration of intervention based on time to progression of preneoplastic disease to cancer and the use of a valid panel of biomarkers representing the hypothesized carcinogenesis pathway for measuring efficacy must inform the design of phase II clinical trials. The goal of this paper is to provide a model for evaluating a well characterized agent- Polyphenon E- in a phase II clinical trial of prostate cancer chemoprevention.

Prostate Cancer Chemoprevention Targeting Men with High-Grade Prostatic Intraepithelial Neoplasia (HGPIN) and Atypical Small Acinar Proliferation (ASAP): Model for Trial Design and Outcome Measures

PubMed Central

Kumar, Nagi; Crocker, Theresa; Smith, Tiffany; Connors, Shahnjayla; Pow-Sang, Julio; Spiess, Philippe E.; Egan, Kathleen; Quinn, Gwen; Schell, Michael; Sebti, Said; Kazi, Aslam; Chuang, Tian; Salup, Raoul; Helal, Mohamed; Zagaja, Gregory; Trabulsi, Edouard; McLarty, Jerry; Fazili, Tajammul; Williams, Christopher R.; Schreiber, Fred; Anderson, Kyle

2014-01-01

In spite of the large number of nutrient-derived agents demonstrating promise as potential chemopreventive agents, most have failed to prove effectiveness in clinical trials. Critical requirements for moving nutrient-derived agents to recommendation for clinical use include adopting a systematic, molecular-mechanism based approach and utilizing the same ethical and rigorous methods such as are used to evaluate other pharmacological agents. Preliminary data on a mechanistic rationale for chemoprevention activity as observed from epidemiological, in vitro and preclinical studies, phase I data of safety in suitable cohorts, duration of intervention based on time to progression of preneoplastic disease to cancer and the use of a valid panel of biomarkers representing the hypothesized carcinogenesis pathway for measuring efficacy must inform the design of phase II clinical trials. The goal of this paper is to provide a model for evaluating a well characterized agent- Polyphenon E- in a phase II clinical trial of prostate cancer chemoprevention. PMID:24533253

SpikingLab: modelling agents controlled by Spiking Neural Networks in Netlogo.

PubMed

Jimenez-Romero, Cristian; Johnson, Jeffrey

2017-01-01

The scientific interest attracted by Spiking Neural Networks (SNN) has lead to the development of tools for the simulation and study of neuronal dynamics ranging from phenomenological models to the more sophisticated and biologically accurate Hodgkin-and-Huxley-based and multi-compartmental models. However, despite the multiple features offered by neural modelling tools, their integration with environments for the simulation of robots and agents can be challenging and time consuming. The implementation of artificial neural circuits to control robots generally involves the following tasks: (1) understanding the simulation tools, (2) creating the neural circuit in the neural simulator, (3) linking the simulated neural circuit with the environment of the agent and (4) programming the appropriate interface in the robot or agent to use the neural controller. The accomplishment of the above-mentioned tasks can be challenging, especially for undergraduate students or novice researchers. This paper presents an alternative tool which facilitates the simulation of simple SNN circuits using the multi-agent simulation and the programming environment Netlogo (educational software that simplifies the study and experimentation of complex systems). The engine proposed and implemented in Netlogo for the simulation of a functional model of SNN is a simplification of integrate and fire (I&F) models. The characteristics of the engine (including neuronal dynamics, STDP learning and synaptic delay) are demonstrated through the implementation of an agent representing an artificial insect controlled by a simple neural circuit. The setup of the experiment and its outcomes are described in this work.

Proceedings of the Agent 2002 Conference on Social Agents : Ecology, Exchange, and Evolution

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

Macal, C., ed.; Sallach, D., ed.

2003-04-10

Welcome to the ''Proceedings'' of the third in a series of agent simulation conferences cosponsored by Argonne National Laboratory and The University of Chicago. The theme of this year's conference, ''Social Agents: Ecology, Exchange and Evolution'', was selected to foster the exchange of ideas on some of the most important social processes addressed by agent simulation models, namely: (1) The translation of ecology and ecological constraints into social dynamics; (2) The role of exchange processes, including the peer dependencies they create; and (3) The dynamics by which, and the attractor states toward which, social processes evolve. As stated in themore » ''Call for Papers'', throughout the social sciences, the simulation of social agents has emerged as an innovative and powerful research methodology. The promise of this approach, however, is accompanied by many challenges. First, modeling complexity in agents, environments, and interactions is non-trivial, and these representations must be explored and assessed systematically. Second, strategies used to represent complexities are differentially applicable to any particular problem space. Finally, to achieve sufficient generality, the design and experimentation inherent in agent simulation must be coupled with social and behavioral theory. Agent 2002 provides a forum for reviewing the current state of agent simulation scholarship, including research designed to address such outstanding issues. This year's conference introduces an extensive range of domains, models, and issues--from pre-literacy to future projections, from ecology to oligopolistic markets, and from design to validation. Four invited speakers highlighted major themes emerging from social agent simulation.« less

Excellent approach to modeling urban expansion by fuzzy cellular automata: agent base model

NASA Astrophysics Data System (ADS)

Khajavigodellou, Yousef; Alesheikh, Ali A.; Mohammed, Abdulrazak A. S.; Chapi, Kamran

2014-09-01

Recently, the interaction between humans and their environment is the one of important challenges in the world. Landuse/ cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. The complexity and dynamics of urban systems make the applicable practice of urban modeling very difficult. With the increased computational power and the greater availability of spatial data, micro-simulation such as the agent based and cellular automata simulation methods, has been developed by geographers, planners, and scholars, and it has shown great potential for representing and simulating the complexity of the dynamic processes involved in urban growth and land use change. This paper presents Fuzzy Cellular Automata in Geospatial Information System and remote Sensing to simulated and predicted urban expansion pattern. These FCA-based dynamic spatial urban models provide an improved ability to forecast and assess future urban growth and to create planning scenarios, allowing us to explore the potential impacts of simulations that correspond to urban planning and management policies. A fuzzy inference guided cellular automata approach. Semantic or linguistic knowledge on Land use change is expressed as fuzzy rules, based on which fuzzy inference is applied to determine the urban development potential for each pixel. The model integrates an ABM (agent-based model) and FCA (Fuzzy Cellular Automata) to investigate a complex decision-making process and future urban dynamic processes. Based on this model rapid development and green land protection under the influences of the behaviors and decision modes of regional authority agents, real estate developer agents, resident agents and non- resident agents and their interactions have been applied to predict the future development patterns of the Erbil metropolitan region.

Extending MAM5 Meta-Model and JaCalIV E Framework to Integrate Smart Devices from Real Environments.

PubMed

Rincon, J A; Poza-Lujan, Jose-Luis; Julian, V; Posadas-Yagüe, Juan-Luis; Carrascosa, C

2016-01-01

This paper presents the extension of a meta-model (MAM5) and a framework based on the model (JaCalIVE) for developing intelligent virtual environments. The goal of this extension is to develop augmented mirror worlds that represent a real and virtual world coupled, so that the virtual world not only reflects the real one, but also complements it. A new component called a smart resource artifact, that enables modelling and developing devices to access the real physical world, and a human in the loop agent to place a human in the system have been included in the meta-model and framework. The proposed extension of MAM5 has been tested by simulating a light control system where agents can access both virtual and real sensor/actuators through the smart resources developed. The results show that the use of real environment interactive elements (smart resource artifacts) in agent-based simulations allows to minimize the error between simulated and real system.

Extending MAM5 Meta-Model and JaCalIV E Framework to Integrate Smart Devices from Real Environments

PubMed Central

2016-01-01

This paper presents the extension of a meta-model (MAM5) and a framework based on the model (JaCalIVE) for developing intelligent virtual environments. The goal of this extension is to develop augmented mirror worlds that represent a real and virtual world coupled, so that the virtual world not only reflects the real one, but also complements it. A new component called a smart resource artifact, that enables modelling and developing devices to access the real physical world, and a human in the loop agent to place a human in the system have been included in the meta-model and framework. The proposed extension of MAM5 has been tested by simulating a light control system where agents can access both virtual and real sensor/actuators through the smart resources developed. The results show that the use of real environment interactive elements (smart resource artifacts) in agent-based simulations allows to minimize the error between simulated and real system. PMID:26926691

A decentralised multi-agent approach to enhance the stability of smart microgrids with renewable energy

NASA Astrophysics Data System (ADS)

Rahman, M. S.; Pota, H. R.; Mahmud, M. A.; Hossain, M. J.

2016-05-01

This paper presents the impact of large penetration of wind power on the transient stability through a dynamic evaluation of the critical clearing times (CCTs) by using intelligent agent-based approach. A decentralised multi-agent-based framework is developed, where agents represent a number of physical device models to form a complex infrastructure for computation and communication. They enable the dynamic flow of information and energy for the interaction between the physical processes and their activities. These agents dynamically adapt online measurements and use the CCT information for relay coordination to improve the transient stability of power systems. Simulations are carried out on a smart microgrid system for faults at increasing wind power penetration levels and the improvement in transient stability using the proposed agent-based framework is demonstrated.

Entropic determination of the phase transition in a coevolving opinion-formation model.

PubMed

Burgos, E; Hernández, Laura; Ceva, H; Perazzo, R P J

2015-03-01

We study an opinion formation model by the means of a coevolving complex network where the vertices represent the individuals, characterized by their evolving opinions, and the edges represent the interactions among them. The network adapts to the spreading of opinions in two ways: not only connected agents interact and eventually change their thinking but an agent may also rewire one of its links to a neighborhood holding the same opinion as his. The dynamics, based on a global majority rule, depends on an external parameter that controls the plasticity of the network. We show how the information entropy associated to the distribution of group sizes allows us to locate the phase transition between a phase of full consensus and another, where different opinions coexist. We also determine the minimum size of the most informative sampling. At the transition the distribution of the sizes of groups holding the same opinion is scale free.

Modeling the transmission of community-associated methicillin-resistant Staphylococcus aureus: a dynamic agent-based simulation.

PubMed

Macal, Charles M; North, Michael J; Collier, Nicholson; Dukic, Vanja M; Wegener, Duane T; David, Michael Z; Daum, Robert S; Schumm, Philip; Evans, James A; Wilder, Jocelyn R; Miller, Loren G; Eells, Samantha J; Lauderdale, Diane S

2014-05-12

Methicillin-resistant Staphylococcus aureus (MRSA) has been a deadly pathogen in healthcare settings since the 1960s, but MRSA epidemiology changed since 1990 with new genetically distinct strain types circulating among previously healthy people outside healthcare settings. Community-associated (CA) MRSA strains primarily cause skin and soft tissue infections, but may also cause life-threatening invasive infections. First seen in Australia and the U.S., it is a growing problem around the world. The U.S. has had the most widespread CA-MRSA epidemic, with strain type USA300 causing the great majority of infections. Individuals with either asymptomatic colonization or infection may transmit CA-MRSA to others, largely by skin-to-skin contact. Control measures have focused on hospital transmission. Limited public health education has focused on care for skin infections. We developed a fine-grained agent-based model for Chicago to identify where to target interventions to reduce CA-MRSA transmission. An agent-based model allows us to represent heterogeneity in population behavior, locations and contact patterns that are highly relevant for CA-MRSA transmission and control. Drawing on nationally representative survey data, the model represents variation in sociodemographics, locations, behaviors, and physical contact patterns. Transmission probabilities are based on a comprehensive literature review. Over multiple 10-year runs with one-hour ticks, our model generates temporal and geographic trends in CA-MRSA incidence similar to Chicago from 2001 to 2010. On average, a majority of transmission events occurred in households, and colonized rather than infected agents were the source of the great majority (over 95%) of transmission events. The key findings are that infected people are not the primary source of spread. Rather, the far greater number of colonized individuals must be targeted to reduce transmission. Our findings suggest that current paradigms in MRSA control in the United States cannot be very effective in reducing the incidence of CA-MRSA infections. Furthermore, the control measures that have focused on hospitals are unlikely to have much population-wide impact on CA-MRSA rates. New strategies need to be developed, as the incidence of CA-MRSA is likely to continue to grow around the world.

Coordination of heterogeneous nonlinear multi-agent systems with prescribed behaviours

NASA Astrophysics Data System (ADS)

Tang, Yutao

2017-10-01

In this paper, we consider a coordination problem for a class of heterogeneous nonlinear multi-agent systems with a prescribed input-output behaviour which was represented by another input-driven system. In contrast to most existing multi-agent coordination results with an autonomous (virtual) leader, this formulation takes possible control inputs of the leader into consideration. First, the coordination was achieved by utilising a group of distributed observers based on conventional assumptions of model matching problem. Then, a fully distributed adaptive extension was proposed without using the input of this input-output behaviour. An example was given to verify their effectiveness.

Including the Group Quarters Population in the US Synthesized Population Database

PubMed Central

Chasteen, Bernadette M.; Wheaton, William D.; Cooley, Philip C.; Ganapathi, Laxminarayana; Wagener, Diane K.

2011-01-01

In 2005, RTI International researchers developed methods to generate synthesized population data on US households for the US Synthesized Population Database. These data are used in agent-based modeling, which simulates large-scale social networks to test how changes in the behaviors of individuals affect the overall network. Group quarters are residences where individuals live in close proximity and interact frequently. Although the Synthesized Population Database represents the population living in households, data for the nation’s group quarters residents are not easily quantified because of US Census Bureau reporting methods designed to protect individuals’ privacy. Including group quarters population data can be an important factor in agent-based modeling because the number of residents and the frequency of their interactions are variables that directly affect modeling results. Particularly with infectious disease modeling, the increased frequency of agent interaction may increase the probability of infectious disease transmission between individuals and the probability of disease outbreaks. This report reviews our methods to synthesize data on group quarters residents to match US Census Bureau data. Our goal in developing the Group Quarters Population Database was to enable its use with RTI’s US Synthesized Population Database in the Modeling of Infectious Diseases Agent Study. PMID:21841972

Collaborative Model for Acceleration of Individualized Therapy of Colon Cancer

DTIC Science & Technology

2015-12-01

Approved for Public Release; Distribution Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT Colorectal cancer (CRC) represents a major health burden...15. SUBJECT TERMS Colorectal cancer, novel anti-cancer agents, bioinformatics, next-generation sequencing, predictive biomarkers, individualized...INTRODUCTION:   Colorectal   cancer   (CRC)   represents   a  major   health  burden,   and   is   the   third   leading

Statistical Agent Based Modelization of the Phenomenon of Drug Abuse

NASA Astrophysics Data System (ADS)

di Clemente, Riccardo; Pietronero, Luciano

2012-07-01

We introduce a statistical agent based model to describe the phenomenon of drug abuse and its dynamical evolution at the individual and global level. The agents are heterogeneous with respect to their intrinsic inclination to drugs, to their budget attitude and social environment. The various levels of drug use were inspired by the professional description of the phenomenon and this permits a direct comparison with all available data. We show that certain elements have a great importance to start the use of drugs, for example the rare events in the personal experiences which permit to overcame the barrier of drug use occasionally. The analysis of how the system reacts to perturbations is very important to understand its key elements and it provides strategies for effective policy making. The present model represents the first step of a realistic description of this phenomenon and can be easily generalized in various directions.

A task-based support architecture for developing point-of-care clinical decision support systems for the emergency department.

PubMed

Wilk, S; Michalowski, W; O'Sullivan, D; Farion, K; Sayyad-Shirabad, J; Kuziemsky, C; Kukawka, B

2013-01-01

The purpose of this study was to create a task-based support architecture for developing clinical decision support systems (CDSSs) that assist physicians in making decisions at the point-of-care in the emergency department (ED). The backbone of the proposed architecture was established by a task-based emergency workflow model for a patient-physician encounter. The architecture was designed according to an agent-oriented paradigm. Specifically, we used the O-MaSE (Organization-based Multi-agent System Engineering) method that allows for iterative translation of functional requirements into architectural components (e.g., agents). The agent-oriented paradigm was extended with ontology-driven design to implement ontological models representing knowledge required by specific agents to operate. The task-based architecture allows for the creation of a CDSS that is aligned with the task-based emergency workflow model. It facilitates decoupling of executable components (agents) from embedded domain knowledge (ontological models), thus supporting their interoperability, sharing, and reuse. The generic architecture was implemented as a pilot system, MET3-AE--a CDSS to help with the management of pediatric asthma exacerbation in the ED. The system was evaluated in a hospital ED. The architecture allows for the creation of a CDSS that integrates support for all tasks from the task-based emergency workflow model, and interacts with hospital information systems. Proposed architecture also allows for reusing and sharing system components and knowledge across disease-specific CDSSs.

Combining Bayesian Networks and Agent Based Modeling to develop a decision-support model in Vietnam

NASA Astrophysics Data System (ADS)

Nong, Bao Anh; Ertsen, Maurits; Schoups, Gerrit

2016-04-01

Complexity and uncertainty in natural resources management have been focus themes in recent years. Within these debates, with the aim to define an approach feasible for water management practice, we are developing an integrated conceptual modeling framework for simulating decision-making processes of citizens, in our case in the Day river area, Vietnam. The model combines Bayesian Networks (BNs) and Agent-Based Modeling (ABM). BNs are able to combine both qualitative data from consultants / experts / stakeholders, and quantitative data from observations on different phenomena or outcomes from other models. Further strengths of BNs are that the relationship between variables in the system is presented in a graphical interface, and that components of uncertainty are explicitly related to their probabilistic dependencies. A disadvantage is that BNs cannot easily identify the feedback of agents in the system once changes appear. Hence, ABM was adopted to represent the reaction among stakeholders under changes. The modeling framework is developed as an attempt to gain better understanding about citizen's behavior and factors influencing their decisions in order to reduce uncertainty in the implementation of water management policy.

29 CFR 453.21 - Interests held in agents, brokers, and surety companies.

Code of Federal Regulations, 2012 CFR

2012-07-01

... any surety company in which any labor organization or any officer, agent, shop steward, or other..., in which any labor organization or any officer, agent, shop steward, or other representative of a... a substantial number of officers, agents, shop stewards, or other representatives of a labor...

29 CFR 453.21 - Interests held in agents, brokers, and surety companies.

Code of Federal Regulations, 2014 CFR

2014-07-01

... any surety company in which any labor organization or any officer, agent, shop steward, or other..., in which any labor organization or any officer, agent, shop steward, or other representative of a... a substantial number of officers, agents, shop stewards, or other representatives of a labor...

29 CFR 453.21 - Interests held in agents, brokers, and surety companies.

Code of Federal Regulations, 2013 CFR

2013-07-01

... any surety company in which any labor organization or any officer, agent, shop steward, or other..., in which any labor organization or any officer, agent, shop steward, or other representative of a... a substantial number of officers, agents, shop stewards, or other representatives of a labor...

Evaluation of anticancer agents using patient-derived tumor organoids characteristically similar to source tissues.

PubMed

Tamura, Hirosumi; Higa, Arisa; Hoshi, Hirotaka; Hiyama, Gen; Takahashi, Nobuhiko; Ryufuku, Masae; Morisawa, Gaku; Yanagisawa, Yuka; Ito, Emi; Imai, Jun-Ichi; Dobashi, Yuu; Katahira, Kiyoaki; Soeda, Shu; Watanabe, Takafumi; Fujimori, Keiya; Watanabe, Shinya; Takagi, Motoki

2018-06-18

Patient-derived tumor xenograft models represent a promising preclinical cancer model that better replicates disease, compared with traditional cell culture; however, their use is low-throughput and costly. To overcome this limitation, patient-derived tumor organoids (PDOs) were established from human lung, ovarian and uterine tumor tissues, among others, to accurately and efficiently recapitulate the tissue architecture and function. PDOs were able to be cultured for >6 months, and formed cell clusters with similar morphologies to their source tumors. Comparative histological and comprehensive gene expression analyses proved that the characteristics of PDOs were similar to those of their source tumors, even following long-term expansion in culture. At present, 53 PDOs have been established by the Fukushima Translational Research Project, and were designated as Fukushima PDOs (F‑PDOs). In addition, the in vivo tumorigenesis of certain F‑PDOs was confirmed using a xenograft model. The present study represents a detailed analysis of three F‑PDOs (termed REME9, 11 and 16) established from endometrial cancer tissues. These were used for cell growth inhibition experiments using anticancer agents. A suitable high-throughput assay system, with 96- or 384‑well plates, was designed for each F‑PDO, and the efficacy of the anticancer agents was subsequently evaluated. REME9 and 11 exhibited distinct responses and increased resistance to the drugs, as compared with conventional cancer cell lines (AN3 CA and RL95-2). REME9 and 11, which were established from tumors that originated in patients who did not respond to paclitaxel and carboplatin (the standard chemotherapy for endometrial cancer), exhibited high resistance (half-maximal inhibitory concentration >10 µM) to the two agents. Therefore, assay systems using F‑PDOs may be utilized to evaluate anticancer agents using conditions that better reflect clinical conditions, compared with conventional methods using cancer cell lines, and to discover markers that identify the pharmacological effects of anticancer agents.

Multi-agent simulation of generation expansion in electricity markets.

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

Botterud, A; Mahalik, M. R.; Veselka, T. D.

2007-06-01

We present a new multi-agent model of generation expansion in electricity markets. The model simulates generation investment decisions of decentralized generating companies (GenCos) interacting in a complex, multidimensional environment. A probabilistic dispatch algorithm calculates prices and profits for new candidate units in different future states of the system. Uncertainties in future load, hydropower conditions, and competitors actions are represented in a scenario tree, and decision analysis is used to identify the optimal expansion decision for each individual GenCo. We test the model using real data for the Korea power system under different assumptions about market design, market concentration, and GenCo'smore » assumed expectations about their competitors investment decisions.« less

Method of predicting a change in an economy

DOEpatents

Pryor, Richard J [Albuquerque, NM; Basu, Nipa [Albany, NY

2006-01-10

An economy whose activity is to be predicted comprises a plurality of decision makers. Decision makers include, for example, households, government, industry, and banks. The decision makers are represented by agents, where an agent can represent one or more decision makers. Each agent has decision rules that determine the agent's actions. Each agent can affect the economy by affecting variable conditions characteristic of the economy or the internal state of other agents. Agents can communicate actions through messages. On a multiprocessor computer, the agents can be assigned to processing elements.

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.

Rural-urban migration including formal and informal workers in the urban sector: an agent-based numerical simulation study

NASA Astrophysics Data System (ADS)

Branco, Nilton; Oliveira, Tharnier; Silveira, Jaylson

2012-02-01

The goal of this work is to study rural-urban migration in the early stages of industrialization. We use an agent-based model and take into account the existence of informal and formal workers on the urban sector and possible migration movements, dependent on the agents' social and private utilities. Our agents are place on vertices of a square lattice, such that each vertex has only one agent. Rural, urban informal and urban formal workers are represented by different states of a three-state Ising model. At every step, a fraction a of the agents may change sectors or migrate. The total utility of a given agent is then calculated and compared to a random utility, in order to check if this agent turns into an actual migrant or changes sector. The dynamics is carried out until an equilibrium state is reached and equilibrium variables are then calculated and compared to available data. We find that a generalized Harris-Todaro condition is satisfied [1] on these equilibrium regimes, i.e, the ratio between expected wages between any pair of sectors reach a constant value. [4pt] [1] J. J. Silveira, A. L. Esp'indola and T. J. Penna, Physica A, 364, 445 (2006).

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.

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.

A framework for identifying water management typologies for agent based modeling of water resources and its application in the Boise River Basin, USA.

NASA Astrophysics Data System (ADS)

Kaiser, K. E.; Flores, A. N.; Hillis, V.; Moroney, J.; Schneider, J.

2017-12-01

Modeling the management of water resources necessitates incorporation of complex social and hydrologic dynamics. Simulation of these socio-ecological systems requires characterization of the decision-making process of relevant actors, the mechanisms through which they exert control on the biophysical system, their ability to react and adapt to regional environmental conditions, and the plausible behaviors in response to changes in those conditions. Agent based models (ABMs) are a useful tool in simulating these complex adaptive systems because they can dynamically couple hydrological models and the behavior of decision making actors. ABMs can provide a flexible, integrated framework that can represent multi-scale interactions, and the heterogeneity of information networks and sources. However, the variability in behavior of water management actors across systems makes characterizing agent behaviors and relationships challenging. Agent typologies, or agent functional types (AFTs), group together individuals and/or agencies with similar functional roles, management objectives, and decision-making strategies. AFTs have been used to represent archetypal land managers in the agricultural and forestry sectors in large-scale socio-economic system models. A similar typology of water actors could simplify the representation of water management across river basins, and increase transferability and scaling of resulting ABMs. Here, we present a framework for identifying and classifying major water actors and show how we will link an ABM of water management to a regional hydrologic model in a western river basin. The Boise River Basin in southwest Idaho is an interesting setting to apply our AFT framework because of the diverse stakeholders and associated management objectives which include managing urban growth pressures and water supply in the face of climate change. Precipitation in the upper basin supplies 90% of the surface water used in the basin, thus managers of the reservoir system (located in the upper basin) must balance flood control for the metropolitan area with water supply for downstream agricultural and hydropower use. Identifying dominant water management typologies that include state and federal agencies will increase the transferability of water management ABMs in the western US.

Incorporating GIS data into an agent-based model to support planning policy making for the development of creative industries

NASA Astrophysics Data System (ADS)

Liu, Helin; Silva, Elisabete A.; Wang, Qian

2016-07-01

This paper presents an extension to the agent-based model "Creative Industries Development-Urban Spatial Structure Transformation" by incorporating GIS data. Three agent classes, creative firms, creative workers and urban government, are considered in the model, and the spatial environment represents a set of GIS data layers (i.e. road network, key housing areas, land use). With the goal to facilitate urban policy makers to draw up policies locally and optimise the land use assignment in order to support the development of creative industries, the improved model exhibited its capacity to assist the policy makers conducting experiments and simulating different policy scenarios to see the corresponding dynamics of the spatial distributions of creative firms and creative workers across time within a city/district. The spatiotemporal graphs and maps record the simulation results and can be used as a reference by the policy makers to adjust land use plans adaptively at different stages of the creative industries' development process.

Exclusive queueing model including the choice of service windows

NASA Astrophysics Data System (ADS)

Tanaka, Masahiro; Yanagisawa, Daichi; Nishinari, Katsuhiro

2018-01-01

In a queueing system involving multiple service windows, choice behavior is a significant concern. This paper incorporates the choice of service windows into a queueing model with a floor represented by discrete cells. We contrived a logit-based choice algorithm for agents considering the numbers of agents and the distances to all service windows. Simulations were conducted with various parameters of agent choice preference for these two elements and for different floor configurations, including the floor length and the number of service windows. We investigated the model from the viewpoint of transit times and entrance block rates. The influences of the parameters on these factors were surveyed in detail and we determined that there are optimum floor lengths that minimize the transit times. In addition, we observed that the transit times were determined almost entirely by the entrance block rates. The results of the presented model are relevant to understanding queueing systems including the choice of service windows and can be employed to optimize facility design and floor management.

How do agents represent?

NASA Astrophysics Data System (ADS)

Ryan, Alex

Representation is inherent to the concept of an agent, but its importance in complex systems has not yet been widely recognised. In this paper I introduce Peirce's theory of signs, which facilitates a definition of representation in general. In summary, representation means that for some agent, a model is used to stand in for another entity in a way that shapes the behaviour of the agent with respect to that entity. Representation in general is then related to the theories of representation that have developed within different disciplines. I compare theories of representation from metaphysics, military theory and systems theory. Additional complications arise in explaining the special case of mental representations, which is the focus of cognitive science. I consider the dominant theory of cognition — that the brain is a representational device — as well as the sceptical anti-representational response. Finally, I argue that representation distinguishes agents from non-representational objects: agents are objects capable of representation.

Impact of Different Policies on Unhealthy Dietary Behaviors in an Urban Adult Population: An Agent-Based Simulation Model

PubMed Central

Giabbanelli, Philippe J.; Arah, Onyebuchi A.; Zimmerman, Frederick J.

2014-01-01

Objectives. Unhealthy eating is a complex-system problem. We used agent-based modeling to examine the effects of different policies on unhealthy eating behaviors. Methods. We developed an agent-based simulation model to represent a synthetic population of adults in Pasadena, CA, and how they make dietary decisions. Data from the 2007 Food Attitudes and Behaviors Survey and other empirical studies were used to calibrate the parameters of the model. Simulations were performed to contrast the potential effects of various policies on the evolution of dietary decisions. Results. Our model showed that a 20% increase in taxes on fast foods would lower the probability of fast-food consumption by 3 percentage points, whereas improving the visibility of positive social norms by 10%, either through community-based or mass-media campaigns, could improve the consumption of fruits and vegetables by 7 percentage points and lower fast-food consumption by 6 percentage points. Zoning policies had no significant impact. Conclusions. Interventions emphasizing healthy eating norms may be more effective than directly targeting food prices or regulating local food outlets. Agent-based modeling may be a useful tool for testing the population-level effects of various policies within complex systems. PMID:24832414

Competition of information channels in the spreading of innovations

NASA Astrophysics Data System (ADS)

Kocsis, Gergely; Kun, Ferenc

2011-08-01

We study the spreading of information on technological developments in socioeconomic systems where the social contacts of agents are represented by a network of connections. In the model, agents get informed about the existence and advantages of new innovations through advertising activities of producers, which are then followed by an interagent information transfer. Computer simulations revealed that varying the strength of external driving and of interagent coupling, furthermore, the topology of social contacts, the model presents a complex behavior with interesting novel features: On the macrolevel the system exhibits logistic behavior typical for the diffusion of innovations. The time evolution can be described analytically by an integral equation that captures the nucleation and growth of clusters of informed agents. On the microlevel, small clusters are found to be compact with a crossover to fractal structures with increasing size. The distribution of cluster sizes has a power-law behavior with a crossover to a higher exponent when long-range social contacts are present in the system. Based on computer simulations we construct an approximate phase diagram of the model on a regular square lattice of agents.

Agent Communication for Dynamic Belief Update

NASA Astrophysics Data System (ADS)

Kobayashi, Mikito; Tojo, Satoshi

Thus far, various formalizations of rational / logical agent model have been proposed. In this paper, we include the notion of communication channel and belief modality into update logic, and introduce Belief Update Logic (BUL). First, we discuss that how we can reformalize the inform action of FIPA-ACL into communication channel, which represents a connection between agents. Thus, our agents can send a message only when they believe, and also there actually is, a channel between him / her and a receiver. Then, we present a static belief logic (BL) and show its soundness and completeness. Next, we develop the logic to BUL, which can update Kripke model by the inform action; in which we show that in the updated model the belief operator also satisfies K45. Thereafter, we show that every sentence in BUL can be translated into BL; thus, we can contend that BUL is also sound and complete. Furthermore, we discuss the features of CUL, including the case of inconsistent information, as well as channel transmission. Finally, we summarize our contribution and discuss some future issues.

Competition of information channels in the spreading of innovations.

PubMed

Kocsis, Gergely; Kun, Ferenc

2011-08-01

We study the spreading of information on technological developments in socioeconomic systems where the social contacts of agents are represented by a network of connections. In the model, agents get informed about the existence and advantages of new innovations through advertising activities of producers, which are then followed by an interagent information transfer. Computer simulations revealed that varying the strength of external driving and of interagent coupling, furthermore, the topology of social contacts, the model presents a complex behavior with interesting novel features: On the macrolevel the system exhibits logistic behavior typical for the diffusion of innovations. The time evolution can be described analytically by an integral equation that captures the nucleation and growth of clusters of informed agents. On the microlevel, small clusters are found to be compact with a crossover to fractal structures with increasing size. The distribution of cluster sizes has a power-law behavior with a crossover to a higher exponent when long-range social contacts are present in the system. Based on computer simulations we construct an approximate phase diagram of the model on a regular square lattice of agents.

Prevention of chemotherapy-induced alopecia in rats by CDK inhibitors.

PubMed

Davis, S T; Benson, B G; Bramson, H N; Chapman, D E; Dickerson, S H; Dold, K M; Eberwein, D J; Edelstein, M; Frye, S V; Gampe, R T; Griffin, R J; Harris, P A; Hassell, A M; Holmes, W D; Hunter, R N; Knick, V B; Lackey, K; Lovejoy, B; Luzzio, M J; Murray, D; Parker, P; Rocque, W J; Shewchuk, L; Veal, J M; Walker, D H; Kuyper, L F

2001-01-05

Most traditional cytotoxic anticancer agents ablate the rapidly dividing epithelium of the hair follicle and induce alopecia (hair loss). Inhibition of cyclin-dependent kinase 2 (CDK2), a positive regulator of eukaryotic cell cycle progression, may represent a therapeutic strategy for prevention of chemotherapy-induced alopecia (CIA) by arresting the cell cycle and reducing the sensitivity of the epithelium to many cell cycle-active antitumor agents. Potent small-molecule inhibitors of CDK2 were developed using structure-based methods. Topical application of these compounds in a neonatal rat model of CIA reduced hair loss at the site of application in 33 to 50% of the animals. Thus, inhibition of CDK2 represents a potentially useful approach for the prevention of CIA in cancer patients.

Collective helping and bystander effects in coevolving helping networks.

PubMed

Jo, Hang-Hyun; Lee, Hyun Keun; Park, Hyunggyu

2010-06-01

We study collective helping behavior and bystander effects in a coevolving helping network model. A node and a link of the network represents an agent who renders or receives help and a friendly relation between agents, respectively. A helping trial of an agent depends on relations with other involved agents and its result (success or failure) updates the relation between the helper and the recipient. We study the network link dynamics and its steady states analytically and numerically. The full phase diagram is presented with various kinds of active and inactive phases and the nature of phase transitions are explored. We find various interesting bystander effects, consistent with the field study results, of which the underlying mechanism is proposed.

An application of queuing theory to waterfowl migration

USGS Publications Warehouse

Sojda, Richard S.; Cornely, John E.; Fredrickson, Leigh H.; Rizzoli, A.E.; Jakeman, A.J.

2002-01-01

There has always been great interest in the migration of waterfowl and other birds. We have applied queuing theory to modelling waterfowl migration, beginning with a prototype system for the Rocky Mountain Population of trumpeter swans (Cygnus buccinator) in Western North America. The queuing model can be classified as a D/BB/28 system, and we describe the input sources, service mechanism, and network configuration of queues and servers. The intrinsic nature of queuing theory is to represent the spatial and temporal characteristics of entities and how they move, are placed in queues, and are serviced. The service mechanism in our system is an algorithm representing how swans move through the flyway based on seasonal life cycle events. The system uses an observed number of swans at each of 27 areas for a breeding season as input and simulates their distribution through four seasonal steps. The result is a simulated distribution of birds for the subsequent year's breeding season. The model was built as a multiagent system with one agent handling movement algorithms, with one facilitating user interface, and with one to seven agents representing specific geographic areas for which swan management interventions can be implemented. The many parallels in queuing model servers and service mechanisms with waterfowl management areas and annual life cycle events made the transfer of the theory to practical application straightforward.

Consensus for linear multi-agent system with intermittent information transmissions using the time-scale theory

NASA Astrophysics Data System (ADS)

Taousser, Fatima; Defoort, Michael; Djemai, Mohamed

2016-01-01

This paper investigates the consensus problem for linear multi-agent system with fixed communication topology in the presence of intermittent communication using the time-scale theory. Since each agent can only obtain relative local information intermittently, the proposed consensus algorithm is based on a discontinuous local interaction rule. The interaction among agents happens at a disjoint set of continuous-time intervals. The closed-loop multi-agent system can be represented using mixed linear continuous-time and linear discrete-time models due to intermittent information transmissions. The time-scale theory provides a powerful tool to combine continuous-time and discrete-time cases and study the consensus protocol under a unified framework. Using this theory, some conditions are derived to achieve exponential consensus under intermittent information transmissions. Simulations are performed to validate the theoretical results.

A self-taught artificial agent for multi-physics computational model personalization.

PubMed

Neumann, Dominik; Mansi, Tommaso; Itu, Lucian; Georgescu, Bogdan; Kayvanpour, Elham; Sedaghat-Hamedani, Farbod; Amr, Ali; Haas, Jan; Katus, Hugo; Meder, Benjamin; Steidl, Stefan; Hornegger, Joachim; Comaniciu, Dorin

2016-12-01

Personalization is the process of fitting a model to patient data, a critical step towards application of multi-physics computational models in clinical practice. Designing robust personalization algorithms is often a tedious, time-consuming, model- and data-specific process. We propose to use artificial intelligence concepts to learn this task, inspired by how human experts manually perform it. The problem is reformulated in terms of reinforcement learning. In an off-line phase, Vito, our self-taught artificial agent, learns a representative decision process model through exploration of the computational model: it learns how the model behaves under change of parameters. The agent then automatically learns an optimal strategy for on-line personalization. The algorithm is model-independent; applying it to a new model requires only adjusting few hyper-parameters of the agent and defining the observations to match. The full knowledge of the model itself is not required. Vito was tested in a synthetic scenario, showing that it could learn how to optimize cost functions generically. Then Vito was applied to the inverse problem of cardiac electrophysiology and the personalization of a whole-body circulation model. The obtained results suggested that Vito could achieve equivalent, if not better goodness of fit than standard methods, while being more robust (up to 11% higher success rates) and with faster (up to seven times) convergence rate. Our artificial intelligence approach could thus make personalization algorithms generalizable and self-adaptable to any patient and any model. Copyright © 2016. Published by Elsevier B.V.

Anisotropic opinion dynamics

NASA Astrophysics Data System (ADS)

Neirotti, Juan

2016-07-01

We consider the process of opinion formation in a society of interacting agents, where there is a set B of socially accepted rules. In this scenario, we observed that agents, represented by simple feed-forward, adaptive neural networks, may have a conservative attitude (mostly in agreement with B ) or liberal attitude (mostly in agreement with neighboring agents) depending on how much their opinions are influenced by their peers. The topology of the network representing the interaction of the society's members is determined by a graph, where the agents' properties are defined over the vertexes and the interagent interactions are defined over the bonds. The adaptability of the agents allows us to model the formation of opinions as an online learning process, where agents learn continuously as new information becomes available to the whole society (online learning). Through the application of statistical mechanics techniques we deduced a set of differential equations describing the dynamics of the system. We observed that by slowly varying the average peer influence in such a way that the agents attitude changes from conservative to liberal and back, the average social opinion develops a hysteresis cycle. Such hysteretic behavior disappears when the variance of the social influence distribution is large enough. In all the cases studied, the change from conservative to liberal behavior is characterized by the emergence of conservative clusters, i.e., a closed knitted set of society members that follow a leader who agrees with the social status quo when the rule B is challenged.

A three-state kinetic agent-based model to analyze tax evasion dynamics

NASA Astrophysics Data System (ADS)

Crokidakis, Nuno

2014-11-01

In this work we study the problem of tax evasion on a fully-connected population. For this purpose, we consider that the agents may be in three different states, namely honest tax payers, tax evaders and undecided, that are individuals in an intermediate class among honests and evaders. Every individual can change his/her state following a kinetic exchange opinion dynamics, where the agents interact by pairs with competitive negative (with probability q) and positive (with probability 1-q) couplings, representing agreement/disagreement between pairs of agents. In addition, we consider the punishment rules of the Zaklan econophysics model, for which there is a probability pa of an audit each agent is subject to in every period and a length of time k detected tax evaders remain honest. Our results suggest that below the critical point qc=1/4 of the opinion dynamics the compliance is high, and the punishment rules have a small effect in the population. On the other hand, for q>qc the tax evasion can be considerably reduced by the enforcement mechanism. We also discuss the impact of the presence of the undecided agents in the evolution of the system.

Computational social network modeling of terrorist recruitment.

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

Berry, Nina M.; Turnley, Jessica Glicken; Smrcka, Julianne D.

2004-10-01

The Seldon terrorist model represents a multi-disciplinary approach to developing organization software for the study of terrorist recruitment and group formation. The need to incorporate aspects of social science added a significant contribution to the vision of the resulting Seldon toolkit. The unique addition of and abstract agent category provided a means for capturing social concepts like cliques, mosque, etc. in a manner that represents their social conceptualization and not simply as a physical or economical institution. This paper provides an overview of the Seldon terrorist model developed to study the formation of cliques, which are used as the majormore » recruitment entity for terrorist organizations.« less

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.

The effects of node exclusion on the centrality measures in graph models of interacting economic agents

NASA Astrophysics Data System (ADS)

Caetano, Marco Antonio Leonel; Yoneyama, Takashi

2015-07-01

This work concerns the study of the effects felt by a network as a whole when a specific node is perturbed. Many real world systems can be described by network models in which the interactions of the various agents can be represented as an edge of a graph. With a graph model in hand, it is possible to evaluate the effect of deleting some of its edges on the architecture and values of nodes of the network. Eventually a node may end up isolated from the rest of the network and an interesting problem is to have a quantitative measure of the impact of such an event. For instance, in the field of finance, the network models are very popular and the proposed methodology allows to carry out "what if" tests in terms of weakening the links between the economic agents, represented as nodes. The two main concepts employed in the proposed methodology are (i) the vibrational IC-Information Centrality, which can provide a measure of the relative importance of a particular node in a network and (ii) autocatalytic networks that can indicate the evolutionary trends of the network. Although these concepts were originally proposed in the context of other fields of knowledge, they were also found to be useful in analyzing financial networks. In order to illustrate the applicability of the proposed methodology, a case of study using the actual data comprising stock market indices of 12 countries is presented.

Evolutionary Agent-based Models to design distributed water management strategies

NASA Astrophysics Data System (ADS)

Giuliani, M.; Castelletti, A.; Reed, P. M.

2012-12-01

There is growing awareness in the scientific community that the traditional centralized approach to water resources management, as described in much of the water resources literature, provides an ideal optimal solution, which is certainly useful to quantify the best physically achievable performance, but is generally inapplicable. Most real world water resources management problems are indeed characterized by the presence of multiple, distributed and institutionally-independent decision-makers. Multi-Agent Systems provide a potentially more realistic alternative framework to model multiple and self-interested decision-makers in a credible context. Each decision-maker can be represented by an agent who, being self-interested, acts according to local objective functions and produces negative externalities on system level objectives. Different levels of coordination can potentially be included in the framework by designing coordination mechanisms to drive the current decision-making structure toward the global system efficiency. Yet, the identification of effective coordination strategies can be particularly complex in modern institutional contexts and current practice is dependent on largely ad-hoc coordination strategies. In this work we propose a novel Evolutionary Agent-based Modeling (EAM) framework that enables a mapping of fully uncoordinated and centrally coordinated solutions into their relative "many-objective" tradeoffs using multiobjective evolutionary algorithms. Then, by analysing the conflicts between local individual agent and global system level objectives it is possible to more fully understand the causes, consequences, and potential solution strategies for coordination failures. Game-theoretic criteria have value for identifying the most interesting alternatives from a policy making point of view as well as the coordination mechanisms that can be applied to obtain these interesting solutions. The proposed approach is numerically tested on a synthetic case study, representing a Y-shaped system composed by two regulated lakes, whose releases merge just upstream of a city. Each reservoir is operated by an agent in order to prevent floods along the lake shores (local objective). However, the optimal operation of the reservoirs with respect to the local objectives is conflicting with the minimization of floods in the city (global objective). The evolution of the Agent-based Model from individualistic management strategies of the reservoirs toward a global compromise that reduces the costs for the city is analysed.

Agent based simulations in disease modeling Comment on "Towards a unified approach in the modeling of fibrosis: A review with research perspectives" by Martine Ben Amar and Carlo Bianca

NASA Astrophysics Data System (ADS)

Pappalardo, Francesco; Pennisi, Marzio

2016-07-01

Fibrosis represents a process where an excessive tissue formation in an organ follows the failure of a physiological reparative or reactive process. Mathematical and computational techniques may be used to improve the understanding of the mechanisms that lead to the disease and to test potential new treatments that may directly or indirectly have positive effects against fibrosis [1]. In this scenario, Ben Amar and Bianca [2] give us a broad picture of the existing mathematical and computational tools that have been used to model fibrotic processes at the molecular, cellular, and tissue levels. Among such techniques, agent based models (ABM) can give a valuable contribution in the understanding and better management of fibrotic diseases.

A computational model for the flow of resin in self-healing composites

NASA Astrophysics Data System (ADS)

Hall, J.; Qamar, I. P. S.; Rendall, T. C. S.; Trask, R. S.

2015-03-01

To explore the flow characteristics of healing agent leaving a vascular network and infusing a damage site within a fibre reinforced polymer composite, a numerical model of healing agent flow from an orifice has been developed using smoothed particle hydrodynamics. As an initial validation the discharge coefficient for low Reynolds number flow from a cylindrical tank is calculated numerically, using two different viscosity formulations, and compared to existing experimental data. Results of this comparison are very favourable; the model is able to reproduce experimental results for the discharge coefficient in the high Reynolds number limit, together with the power-law behaviour for low Reynolds numbers. Results are also presented for a representative delamination geometry showing healing fluid behaviour and fraction filled inside the delamination for a variety of fluid viscosities. This work provides the foundations for the vascular self-healing community in calculating not only the flow rate through the network, but also, by simulating a representative damage site, the final location of the healing fluid within the damage site in order to assess the improvement in local and global mechanical properties and thus healing efficiency.

Basic emotions and adaptation. A computational and evolutionary model.

PubMed

Pacella, Daniela; Ponticorvo, Michela; Gigliotta, Onofrio; Miglino, Orazio

2017-01-01

The core principles of the evolutionary theories of emotions declare that affective states represent crucial drives for action selection in the environment and regulated the behavior and adaptation of natural agents in ancestrally recurrent situations. While many different studies used autonomous artificial agents to simulate emotional responses and the way these patterns can affect decision-making, few are the approaches that tried to analyze the evolutionary emergence of affective behaviors directly from the specific adaptive problems posed by the ancestral environment. A model of the evolution of affective behaviors is presented using simulated artificial agents equipped with neural networks and physically inspired on the architecture of the iCub humanoid robot. We use genetic algorithms to train populations of virtual robots across generations, and investigate the spontaneous emergence of basic emotional behaviors in different experimental conditions. In particular, we focus on studying the emotion of fear, therefore the environment explored by the artificial agents can contain stimuli that are safe or dangerous to pick. The simulated task is based on classical conditioning and the agents are asked to learn a strategy to recognize whether the environment is safe or represents a threat to their lives and select the correct action to perform in absence of any visual cues. The simulated agents have special input units in their neural structure whose activation keep track of their actual "sensations" based on the outcome of past behavior. We train five different neural network architectures and then test the best ranked individuals comparing their performances and analyzing the unit activations in each individual's life cycle. We show that the agents, regardless of the presence of recurrent connections, spontaneously evolved the ability to cope with potentially dangerous environment by collecting information about the environment and then switching their behavior to a genetically selected pattern in order to maximize the possible reward. We also prove the determinant presence of an internal time perception unit for the robots to achieve the highest performance and survivability across all conditions.

The dynamics of interaction of reflexive subjects operating with the two-valued versus many-valued logic.

PubMed

Sawa, Koji; Igamberdiev, Abir U

2017-12-01

In this paper we aim to approach a model of interacting subjects with the opposite types of reflexion that belong to the Western (W) and Eastern (E) reflexive modes according to Vladimir Lefebvre (1992). The model represents an expansion of the previously developed model of the Double Homunculus (Sawa and Igamberdiev, 2016) that describes reflexive agents as holding "the image of the self in the image of the self". A dialogue model between the two homunculus agents estimating their own reflexion in the opposite ways (generating the two-valued versus many-valued logic and loosely approximated as belonging to the W and E Lefebvre's types) is evolved. At the same time, the argument also unveils the relationship between a difference equation which is the key notion of the model and an emergence of logic. This can be a powerful tool for describing intercommunication of reflexive agents in the social environment as well as interactions between the entire social systems of different types. Copyright © 2017 Elsevier Ltd. All rights reserved.

Modeling the Ebolavirus Life Cycle with Transcription and Replication-Competent Viruslike Particle Assays.

PubMed

Biedenkopf, Nadine; Hoenen, Thomas

2017-01-01

Ebolaviruses are the causative agent of a severe hemorrhagic fever with high case fatality rates, for which no approved specific therapy is available. As biosafety level 4 (BSL4) agents, work with live ebolaviruses is restricted to maximum containment laboratories. Transcription and replication-competent viruslike particle (trVLP) systems are reverse genetics-based life cycle modeling systems that allow researchers to model virtually the entire ebolavirus life cycle outside of a maximum containment laboratory. These systems can be used to dissect the virus life cycle, and thus increase our understanding of virus biology, as well as for more applied uses such as the screening and development of novel antivirals, and thus represent powerful tools for work on ebolaviruses.

Discrete Element Framework for Modelling Extracellular Matrix, Deformable Cells and Subcellular Components.

PubMed

Gardiner, Bruce S; Wong, Kelvin K L; Joldes, Grand R; Rich, Addison J; Tan, Chin Wee; Burgess, Antony W; Smith, David W

2015-10-01

This paper presents a framework for modelling biological tissues based on discrete particles. Cell components (e.g. cell membranes, cell cytoskeleton, cell nucleus) and extracellular matrix (e.g. collagen) are represented using collections of particles. Simple particle to particle interaction laws are used to simulate and control complex physical interaction types (e.g. cell-cell adhesion via cadherins, integrin basement membrane attachment, cytoskeletal mechanical properties). Particles may be given the capacity to change their properties and behaviours in response to changes in the cellular microenvironment (e.g., in response to cell-cell signalling or mechanical loadings). Each particle is in effect an 'agent', meaning that the agent can sense local environmental information and respond according to pre-determined or stochastic events. The behaviour of the proposed framework is exemplified through several biological problems of ongoing interest. These examples illustrate how the modelling framework allows enormous flexibility for representing the mechanical behaviour of different tissues, and we argue this is a more intuitive approach than perhaps offered by traditional continuum methods. Because of this flexibility, we believe the discrete modelling framework provides an avenue for biologists and bioengineers to explore the behaviour of tissue systems in a computational laboratory.

Model-Based Knowing: How Do Students Ground Their Understanding About Climate Systems in Agent-Based Computer Models?

NASA Astrophysics Data System (ADS)

Markauskaite, Lina; Kelly, Nick; Jacobson, Michael J.

2017-12-01

This paper gives a grounded cognition account of model-based learning of complex scientific knowledge related to socio-scientific issues, such as climate change. It draws on the results from a study of high school students learning about the carbon cycle through computational agent-based models and investigates two questions: First, how do students ground their understanding about the phenomenon when they learn and solve problems with computer models? Second, what are common sources of mistakes in students' reasoning with computer models? Results show that students ground their understanding in computer models in five ways: direct observation, straight abstraction, generalisation, conceptualisation, and extension. Students also incorporate into their reasoning their knowledge and experiences that extend beyond phenomena represented in the models, such as attitudes about unsustainable carbon emission rates, human agency, external events, and the nature of computational models. The most common difficulties of the students relate to seeing the modelled scientific phenomenon and connecting results from the observations with other experiences and understandings about the phenomenon in the outside world. An important contribution of this study is the constructed coding scheme for establishing different ways of grounding, which helps to understand some challenges that students encounter when they learn about complex phenomena with agent-based computer models.

Delicaflavone induces autophagic cell death in lung cancer via Akt/mTOR/p70S6K signaling pathway.

PubMed

Sui, Yuxia; Yao, Hong; Li, Shaoguang; Jin, Long; Shi, Peiying; Li, Zhijun; Wang, Gang; Lin, Shilan; Wu, Youjia; Li, Yuxiang; Huang, Liying; Liu, Qicai; Lin, Xinhua

2017-03-01

Searching for potential anticancer agents from natural sources is an effective strategy for developing novel chemotherapeutic agents. In this study, data supporting the in vitro and in vivo anticancer effects of delicaflavone, a rarely occurring biflavonoid from Selaginella doederleinii, were reported. Delicaflavone exhibited favorable anticancer properties, as shown by the MTT assay and xenograft model of human non-small cell lung cancer in male BALB/c nude mice without observable adverse effect. By transmission electron microscopy with acridine orange and Cyto-ID®Autophagy detection dyes, Western blot analysis, and RT-PCR assay, we confirmed that delicaflavone induces autophagic cell death by increasing the ratio of LC3-II to LC3-I, which are autophagy-related proteins, and promoting the generation of acidic vesicular organelles and autolysosomes in the cytoplasm of human lung cancer A549 and PC-9 cells in a time- and dose-dependent manner. Delicaflavone downregulated the expression of phospho-Akt, phospho-mTOR, and phospho-p70S6K in a time- and dose-dependent manner, suggesting that it induced autophagy by inhibiting the Akt/mTOR/p70S6K pathway in A549 and PC-9 cells. Delicaflavone is a potential anticancer agent that can induce autophagic cell death in human non-small cell lung cancer via the Akt/mTOR/p70S6K signaling pathway. Delicaflavone showed anti-lung cancer effects in vitro and in vivo. Delicaflavone induced autophagic cell death via Akt/mTOR/p70S6K signaling pathway. Delicaflavone did not show observable side effects in a xenograft mouse model. Delicaflavone may represent a potential therapeutic agent for lung cancer. Delicaflavone showed anti-lung cancer effects in vitro and in vivo. Delicaflavone induced autophagic cell death via Akt/mTOR/p70S6K signaling pathway. Delicaflavone did not show observable side effects in a xenograft mouse model. Delicaflavone may represent a potential therapeutic agent for lung cancer.

Integrating macro and micro scale approaches in the agent-based modeling of residential dynamics

NASA Astrophysics Data System (ADS)

Saeedi, Sara

2018-06-01

With the advancement of computational modeling and simulation (M&S) methods as well as data collection technologies, urban dynamics modeling substantially improved over the last several decades. The complex urban dynamics processes are most effectively modeled not at the macro-scale, but following a bottom-up approach, by simulating the decisions of individual entities, or residents. Agent-based modeling (ABM) provides the key to a dynamic M&S framework that is able to integrate socioeconomic with environmental models, and to operate at both micro and macro geographical scales. In this study, a multi-agent system is proposed to simulate residential dynamics by considering spatiotemporal land use changes. In the proposed ABM, macro-scale land use change prediction is modeled by Artificial Neural Network (ANN) and deployed as the agent environment and micro-scale residential dynamics behaviors autonomously implemented by household agents. These two levels of simulation interacted and jointly promoted urbanization process in an urban area of Tehran city in Iran. The model simulates the behavior of individual households in finding ideal locations to dwell. The household agents are divided into three main groups based on their income rank and they are further classified into different categories based on a number of attributes. These attributes determine the households' preferences for finding new dwellings and change with time. The ABM environment is represented by a land-use map in which the properties of the land parcels change dynamically over the simulation time. The outputs of this model are a set of maps showing the pattern of different groups of households in the city. These patterns can be used by city planners to find optimum locations for building new residential units or adding new services to the city. The simulation results show that combining macro- and micro-level simulation can give full play to the potential of the ABM to understand the driving mechanism of urbanization and provide decision-making support for urban management.

Integrated Agent-Based and Production Cost Modeling Framework for Renewable Energy Studies: Preprint

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

Gallo, Giulia

The agent-based framework for renewable energy studies (ARES) is an integrated approach that adds an agent-based model of industry actors to PLEXOS and combines the strengths of the two to overcome their individual shortcomings. It can examine existing and novel wholesale electricity markets under high penetrations of renewables. ARES is demonstrated by studying how increasing levels of wind will impact the operations and the exercise of market power of generation companies that exploit an economic withholding strategy. The analysis is carried out on a test system that represents the Electric Reliability Council of Texas energy-only market in the year 2020.more » The results more realistically reproduce the operations of an energy market under different and increasing penetrations of wind, and ARES can be extended to address pressing issues in current and future wholesale electricity markets.« less

Integrated Agent-Based and Production Cost Modeling Framework for Renewable Energy Studies

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

Gallo, Giulia

The agent-based framework for renewable energy studies (ARES) is an integrated approach that adds an agent-based model of industry actors to PLEXOS and combines the strengths of the two to overcome their individual shortcomings. It can examine existing and novel wholesale electricity markets under high penetrations of renewables. ARES is demonstrated by studying how increasing levels of wind will impact the operations and the exercise of market power of generation companies that exploit an economic withholding strategy. The analysis is carried out on a test system that represents the Electric Reliability Council of Texas energy-only market in the year 2020.more » The results more realistically reproduce the operations of an energy market under different and increasing penetrations of wind, and ARES can be extended to address pressing issues in current and future wholesale electricity markets.« less

Fault-tolerant Control of a Cyber-physical System

NASA Astrophysics Data System (ADS)

Roxana, Rusu-Both; Eva-Henrietta, Dulf

2017-10-01

Cyber-physical systems represent a new emerging field in automatic control. The fault system is a key component, because modern, large scale processes must meet high standards of performance, reliability and safety. Fault propagation in large scale chemical processes can lead to loss of production, energy, raw materials and even environmental hazard. The present paper develops a multi-agent fault-tolerant control architecture using robust fractional order controllers for a (13C) cryogenic separation column cascade. The JADE (Java Agent DEvelopment Framework) platform was used to implement the multi-agent fault tolerant control system while the operational model of the process was implemented in Matlab/SIMULINK environment. MACSimJX (Multiagent Control Using Simulink with Jade Extension) toolbox was used to link the control system and the process model. In order to verify the performance and to prove the feasibility of the proposed control architecture several fault simulation scenarios were performed.

Interplay between consensus and coherence in a model of interacting opinions

NASA Astrophysics Data System (ADS)

Battiston, Federico; Cairoli, Andrea; Nicosia, Vincenzo; Baule, Adrian; Latora, Vito

2016-06-01

The formation of agents' opinions in a social system is the result of an intricate equilibrium among several driving forces. On the one hand, the social pressure exerted by peers favors the emergence of local consensus. On the other hand, the concurrent participation of agents to discussions on different topics induces each agent to develop a coherent set of opinions across all the topics in which he/she is active. Moreover, the pervasive action of external stimuli, such as mass media, pulls the entire population towards a specific configuration of opinions on different topics. Here we propose a model in which agents with interrelated opinions, interacting on several layers representing different topics, tend to spread their own ideas to their neighborhood, strive to maintain internal coherence, due to the fact that each agent identifies meaningful relationships among its opinions on the different topics, and are at the same time subject to external fields, resembling the pressure of mass media. We show that the presence of heterogeneity in the internal coupling assigned by agents to their different opinions allows to obtain states with mixed levels of consensus, still ensuring that all the agents attain a coherent set of opinions. Furthermore, we show that all the observed features of the model are preserved in the presence of thermal noise up to a critical temperature, after which global consensus is no longer attainable. This suggests the relevance of our results for real social systems, where noise is inevitably present in the form of information uncertainty and misunderstandings. The model also demonstrates how mass media can be effectively used to favor the propagation of a chosen set of opinions, thus polarizing the consensus of an entire population.

Advancing complementary and alternative medicine through social network analysis and agent-based modeling.

PubMed

Frantz, Terrill L

2012-01-01

This paper introduces the contemporary perspectives and techniques of social network analysis (SNA) and agent-based modeling (ABM) and advocates applying them to advance various aspects of complementary and alternative medicine (CAM). SNA and ABM are invaluable methods for representing, analyzing and projecting complex, relational, social phenomena; they provide both an insightful vantage point and a set of analytic tools that can be useful in a wide range of contexts. Applying these methods in the CAM context can aid the ongoing advances in the CAM field, in both its scientific aspects and in developing broader acceptance in associated stakeholder communities. Copyright © 2012 S. Karger AG, Basel.

A hybrid fuzzy logic/constraint satisfaction problem approach to automatic decision making in simulation game models.

PubMed

Braathen, Sverre; Sendstad, Ole Jakob

2004-08-01

Possible techniques for representing automatic decision-making behavior approximating human experts in complex simulation model experiments are of interest. Here, fuzzy logic (FL) and constraint satisfaction problem (CSP) methods are applied in a hybrid design of automatic decision making in simulation game models. The decision processes of a military headquarters are used as a model for the FL/CSP decision agents choice of variables and rulebases. The hybrid decision agent design is applied in two different types of simulation games to test the general applicability of the design. The first application is a two-sided zero-sum sequential resource allocation game with imperfect information interpreted as an air campaign game. The second example is a network flow stochastic board game designed to capture important aspects of land manoeuvre operations. The proposed design is shown to perform well also in this complex game with a very large (billionsize) action set. Training of the automatic FL/CSP decision agents against selected performance measures is also shown and results are presented together with directions for future research.

Synthesis and Preclinical Characterization of a Cationic Iodinated Imaging Contrast Agent (CA4+) and Its Use for Quantitative Computed Tomography of Ex Vivo Human Hip Cartilage.

PubMed

Stewart, Rachel C; Patwa, Amit N; Lusic, Hrvoje; Freedman, Jonathan D; Wathier, Michel; Snyder, Brian D; Guermazi, Ali; Grinstaff, Mark W

2017-07-13

Contrast agents that go beyond qualitative visualization and enable quantitative assessments of functional tissue performance represent the next generation of clinically useful imaging tools. An optimized and efficient large-scale synthesis of a cationic iodinated contrast agent (CA4+) is described for imaging articular cartilage. Contrast-enhanced CT (CECT) using CA4+ reveals significantly greater agent uptake of CA4+ in articular cartilage compared to that of similar anionic or nonionic agents, and CA4+ uptake follows Donnan equilibrium theory. The CA4+ CECT attenuation obtained from imaging ex vivo human hip cartilage correlates with the glycosaminoglycan content, equilibrium modulus, and coefficient of friction, which are key indicators of cartilage functional performance and osteoarthritis stage. Finally, preliminary toxicity studies in a rat model show no adverse events, and a pharmacokinetics study documents a peak plasma concentration 30 min after dosing, with the agent no longer present in vivo at 96 h via excretion in the urine.

Role of conviction in nonequilibrium models of opinion formation

NASA Astrophysics Data System (ADS)

Crokidakis, Nuno; Anteneodo, Celia

2012-12-01

We analyze the critical behavior of a class of discrete opinion models in the presence of disorder. Within this class, each agent opinion takes a discrete value (±1 or 0) and its time evolution is ruled by two terms, one representing agent-agent interactions and the other the degree of conviction or persuasion (a self-interaction). The mean-field limit, where each agent can interact evenly with any other, is considered. Disorder is introduced in the strength of both interactions, with either quenched or annealed random variables. With probability p (1-p), a pairwise interaction reflects a negative (positive) coupling, while the degree of conviction also follows a binary probability distribution (two different discrete probability distributions are considered). Numerical simulations show that a nonequilibrium continuous phase transition, from a disordered state to a state with a prevailing opinion, occurs at a critical point pc that depends on the distribution of the convictions, with the transition being spoiled in some cases. We also show how the critical line, for each model, is affected by the update scheme (either parallel or sequential) as well as by the kind of disorder (either quenched or annealed).

Linking MODFLOW with an agent-based land-use model to support decision making

USGS Publications Warehouse

Reeves, H.W.; Zellner, M.L.

2010-01-01

The U.S. Geological Survey numerical groundwater flow model, MODFLOW, was integrated with an agent-based land-use model to yield a simulator for environmental planning studies. Ultimately, this integrated simulator will be used as a means to organize information, illustrate potential system responses, and facilitate communication within a participatory modeling framework. Initial results show the potential system response to different zoning policy scenarios in terms of the spatial patterns of development, which is referred to as urban form, and consequent impacts on groundwater levels. These results illustrate how the integrated simulator is capable of representing the complexity of the system. From a groundwater modeling perspective, the most important aspect of the integration is that the simulator generates stresses on the groundwater system within the simulation in contrast to the traditional approach that requires the user to specify the stresses through time. Copyright ?? 2010 The Author(s). Journal compilation ?? 2010 National Ground Water Association.

A comparison of multiple behavior models in a simulation of the aftermath of an improvised nuclear detonation.

PubMed

Parikh, Nidhi; Hayatnagarkar, Harshal G; Beckman, Richard J; Marathe, Madhav V; Swarup, Samarth

2016-11-01

We describe a large-scale simulation of the aftermath of a hypothetical 10kT improvised nuclear detonation at ground level, near the White House in Washington DC. We take a synthetic information approach, where multiple data sets are combined to construct a synthesized representation of the population of the region with accurate demographics, as well as four infrastructures: transportation, healthcare, communication, and power. In this article, we focus on the model of agents and their behavior, which is represented using the options framework. Six different behavioral options are modeled: household reconstitution, evacuation, healthcare-seeking, worry, shelter-seeking, and aiding & assisting others. Agent decision-making takes into account their health status, information about family members, information about the event, and their local environment. We combine these behavioral options into five different behavior models of increasing complexity and do a number of simulations to compare the models.

A comparison of multiple behavior models in a simulation of the aftermath of an improvised nuclear detonation

PubMed Central

Parikh, Nidhi; Hayatnagarkar, Harshal G.; Beckman, Richard J.; Marathe, Madhav V.; Swarup, Samarth

2016-01-01

We describe a large-scale simulation of the aftermath of a hypothetical 10kT improvised nuclear detonation at ground level, near the White House in Washington DC. We take a synthetic information approach, where multiple data sets are combined to construct a synthesized representation of the population of the region with accurate demographics, as well as four infrastructures: transportation, healthcare, communication, and power. In this article, we focus on the model of agents and their behavior, which is represented using the options framework. Six different behavioral options are modeled: household reconstitution, evacuation, healthcare-seeking, worry, shelter-seeking, and aiding & assisting others. Agent decision-making takes into account their health status, information about family members, information about the event, and their local environment. We combine these behavioral options into five different behavior models of increasing complexity and do a number of simulations to compare the models. PMID:27909393

Modelling multimodal expression of emotion in a virtual agent.

PubMed

Pelachaud, Catherine

2009-12-12

Over the past few years we have been developing an expressive embodied conversational agent system. In particular, we have developed a model of multimodal behaviours that includes dynamism and complex facial expressions. The first feature refers to the qualitative execution of behaviours. Our model is based on perceptual studies and encompasses several parameters that modulate multimodal behaviours. The second feature, the model of complex expressions, follows a componential approach where a new expression is obtained by combining facial areas of other expressions. Lately we have been working on adding temporal dynamism to expressions. So far they have been designed statically, typically at their apex. Only full-blown expressions could be modelled. To overcome this limitation, we have defined a representation scheme that describes the temporal evolution of the expression of an emotion. It is no longer represented by a static definition but by a temporally ordered sequence of multimodal signals.

Modelling Temporal Schedule of Urban Trains Using Agent-Based Simulation and NSGA2-BASED Multiobjective Optimization Approaches

NASA Astrophysics Data System (ADS)

Sahelgozin, M.; Alimohammadi, A.

2015-12-01

Increasing distances between locations of residence and services leads to a large number of daily commutes in urban areas. Developing subway systems has been taken into consideration of transportation managers as a response to this huge amount of travel demands. In developments of subway infrastructures, representing a temporal schedule for trains is an important task; because an appropriately designed timetable decreases Total passenger travel times, Total Operation Costs and Energy Consumption of trains. Since these variables are not positively correlated, subway scheduling is considered as a multi-criteria optimization problem. Therefore, proposing a proper solution for subway scheduling has been always a controversial issue. On the other hand, research on a phenomenon requires a summarized representation of the real world that is known as Model. In this study, it is attempted to model temporal schedule of urban trains that can be applied in Multi-Criteria Subway Schedule Optimization (MCSSO) problems. At first, a conceptual framework is represented for MCSSO. Then, an agent-based simulation environment is implemented to perform Sensitivity Analysis (SA) that is used to extract the interrelations between the framework components. These interrelations is then taken into account in order to construct the proposed model. In order to evaluate performance of the model in MCSSO problems, Tehran subway line no. 1 is considered as the case study. Results of the study show that the model was able to generate an acceptable distribution of Pareto-optimal solutions which are applicable in the real situations while solving a MCSSO is the goal. Also, the accuracy of the model in representing the operation of subway systems was significant.

OntoTrader: An Ontological Web Trading Agent Approach for Environmental Information Retrieval

PubMed Central

Iribarne, Luis; Padilla, Nicolás; Ayala, Rosa; Asensio, José A.; Criado, Javier

2014-01-01

Modern Web-based Information Systems (WIS) are becoming increasingly necessary to provide support for users who are in different places with different types of information, by facilitating their access to the information, decision making, workgroups, and so forth. Design of these systems requires the use of standardized methods and techniques that enable a common vocabulary to be defined to represent the underlying knowledge. Thus, mediation elements such as traders enrich the interoperability of web components in open distributed systems. These traders must operate with other third-party traders and/or agents in the system, which must also use a common vocabulary for communication between them. This paper presents the OntoTrader architecture, an Ontological Web Trading agent based on the OMG ODP trading standard. It also presents the ontology needed by some system agents to communicate with the trading agent and the behavioral framework for the SOLERES OntoTrader agent, an Environmental Management Information System (EMIS). This framework implements a “Query-Searching/Recovering-Response” information retrieval model using a trading service, SPARQL notation, and the JADE platform. The paper also presents reflection, delegation and, federation mediation models and describes formalization, an experimental testing environment in three scenarios, and a tool which allows our proposal to be evaluated and validated. PMID:24977211

OntoTrader: an ontological Web trading agent approach for environmental information retrieval.

PubMed

Iribarne, Luis; Padilla, Nicolás; Ayala, Rosa; Asensio, José A; Criado, Javier

2014-01-01

Modern Web-based Information Systems (WIS) are becoming increasingly necessary to provide support for users who are in different places with different types of information, by facilitating their access to the information, decision making, workgroups, and so forth. Design of these systems requires the use of standardized methods and techniques that enable a common vocabulary to be defined to represent the underlying knowledge. Thus, mediation elements such as traders enrich the interoperability of web components in open distributed systems. These traders must operate with other third-party traders and/or agents in the system, which must also use a common vocabulary for communication between them. This paper presents the OntoTrader architecture, an Ontological Web Trading agent based on the OMG ODP trading standard. It also presents the ontology needed by some system agents to communicate with the trading agent and the behavioral framework for the SOLERES OntoTrader agent, an Environmental Management Information System (EMIS). This framework implements a "Query-Searching/Recovering-Response" information retrieval model using a trading service, SPARQL notation, and the JADE platform. The paper also presents reflection, delegation and, federation mediation models and describes formalization, an experimental testing environment in three scenarios, and a tool which allows our proposal to be evaluated and validated.

Ribbon networks for modeling navigable paths of autonomous agents in virtual environments.

PubMed

Willemsen, Peter; Kearney, Joseph K; Wang, Hongling

2006-01-01

This paper presents the Environment Description Framework (EDF) for modeling complex networks of intersecting roads and pathways in virtual environments. EDF represents information about the layout of streets and sidewalks, the rules that govern behavior on roads and walkways, and the locations of agents with respect to navigable structures. The framework serves as the substrate on which behavior programs for autonomous vehicles and pedestrians are built. Pathways are modeled as ribbons in space. The ribbon structure provides a natural coordinate frame for defining the local geometry of navigable surfaces. EDF includes a powerful runtime interface supported by robust and efficient code for locating objects on the ribbon network, for mapping between Cartesian and ribbon coordinates, and for determining behavioral constraints imposed by the environment.

Dynamics of coupled human-landscape systems

NASA Astrophysics Data System (ADS)

Werner, B. T.; McNamara, D. E.

2007-11-01

A preliminary dynamical analysis of landscapes and humans as hierarchical complex systems suggests that strong coupling between the two that spreads to become regionally or globally pervasive should be focused at multi-year to decadal time scales. At these scales, landscape dynamics is dominated by water, sediment and biological routing mediated by fluvial, oceanic, atmospheric processes and human dynamics is dominated by simplifying, profit-maximizing market forces and political action based on projection of economic effect. Also at these scales, landscapes impact humans through patterns of natural disasters and trends such as sea level rise; humans impact landscapes by the effect of economic activity and changes meant to mitigate natural disasters and longer term trends. Based on this analysis, human-landscape coupled systems can be modeled using heterogeneous agents employing prediction models to determine actions to represent the nonlinear behavior of economic and political systems and rule-based routing algorithms to represent landscape processes. A cellular model for the development of New Orleans illustrates this approach, with routing algorithms for river and hurricane-storm surge determining flood extent, five markets (home, labor, hotel, tourism and port services) connecting seven types of economic agents (home buyers/laborers, home developers, hotel owners/ employers, hotel developers, tourists, port services developer and port services owners/employers), building of levees or a river spillway by political agents and damage to homes, hotels or port services within cells determined by the passage or depth of flood waters. The model reproduces historical aspects of New Orleans economic development and levee construction and the filtering of frequent small-scale floods at the expense of large disasters.

Multi-scale analysis of a household level agent-based model of landcover change.

PubMed

Evans, Tom P; Kelley, Hugh

2004-08-01

Scale issues have significant implications for the analysis of social and biophysical processes in complex systems. These same scale implications are likewise considerations for the design and application of models of landcover change. Scale issues have wide-ranging effects from the representativeness of data used to validate models to aggregation errors introduced in the model structure. This paper presents an analysis of how scale issues affect an agent-based model (ABM) of landcover change developed for a research area in the Midwest, USA. The research presented here explores how scale factors affect the design and application of agent-based landcover change models. The ABM is composed of a series of heterogeneous agents who make landuse decisions on a portfolio of cells in a raster-based programming environment. The model is calibrated using measures of fit derived from both spatial composition and spatial pattern metrics from multi-temporal landcover data interpreted from historical aerial photography. A model calibration process is used to find a best-fit set of parameter weights assigned to agents' preferences for different landuses (agriculture, pasture, timber production, and non-harvested forest). Previous research using this model has shown how a heterogeneous set of agents with differing preferences for a portfolio of landuses produces the best fit to landcover changes observed in the study area. The scale dependence of the model is explored by varying the resolution of the input data used to calibrate the model (observed landcover), ancillary datasets that affect land suitability (topography), and the resolution of the model landscape on which agents make decisions. To explore the impact of these scale relationships the model is run with input datasets constructed at the following spatial resolutions: 60, 90, 120, 150, 240, 300 and 480 m. The results show that the distribution of landuse-preference weights differs as a function of scale. In addition, with the gradient descent model fitting method used in this analysis the model was not able to converge to an acceptable fit at the 300 and 480 m spatial resolutions. This is a product of the ratio of the input cell resolution to the average parcel size in the landscape. This paper uses these findings to identify scale considerations in the design, development, validation and application of ABMs of landcover change.

Agent Based Modeling Applications for Geosciences

NASA Astrophysics Data System (ADS)

Stein, J. S.

2004-12-01

Agent-based modeling techniques have successfully been applied to systems in which complex behaviors or outcomes arise from varied interactions between individuals in the system. Each individual interacts with its environment, as well as with other individuals, by following a set of relatively simple rules. Traditionally this "bottom-up" modeling approach has been applied to problems in the fields of economics and sociology, but more recently has been introduced to various disciplines in the geosciences. This technique can help explain the origin of complex processes from a relatively simple set of rules, incorporate large and detailed datasets when they exist, and simulate the effects of extreme events on system-wide behavior. Some of the challenges associated with this modeling method include: significant computational requirements in order to keep track of thousands to millions of agents, methods and strategies of model validation are lacking, as is a formal methodology for evaluating model uncertainty. Challenges specific to the geosciences, include how to define agents that control water, contaminant fluxes, climate forcing and other physical processes and how to link these "geo-agents" into larger agent-based simulations that include social systems such as demographics economics and regulations. Effective management of limited natural resources (such as water, hydrocarbons, or land) requires an understanding of what factors influence the demand for these resources on a regional and temporal scale. Agent-based models can be used to simulate this demand across a variety of sectors under a range of conditions and determine effective and robust management policies and monitoring strategies. The recent focus on the role of biological processes in the geosciences is another example of an area that could benefit from agent-based applications. A typical approach to modeling the effect of biological processes in geologic media has been to represent these processes in a thermodynamic framework as a set of reactions that roll-up the integrated effect that diverse biological communities exert on a geological system. This approach may work well to predict the effect of certain biological communities in specific environments in which experimental data is available. However, it does not further our knowledge of how the geobiological system actually functions on a micro scale. Agent-based techniques may provide a framework to explore the fundamental interactions required to explain the system-wide behavior. This presentation will present a survey of several promising applications of agent-based modeling approaches to problems in the geosciences and describe specific contributions to some of the inherent challenges facing this approach.

Ontology of Earth's nonlinear dynamic complex systems

NASA Astrophysics Data System (ADS)

Babaie, Hassan; Davarpanah, Armita

2017-04-01

As a complex system, Earth and its major integrated and dynamically interacting subsystems (e.g., hydrosphere, atmosphere) display nonlinear behavior in response to internal and external influences. The Earth Nonlinear Dynamic Complex Systems (ENDCS) ontology formally represents the semantics of the knowledge about the nonlinear system element (agent) behavior, function, and structure, inter-agent and agent-environment feedback loops, and the emergent collective properties of the whole complex system as the result of interaction of the agents with other agents and their environment. It also models nonlinear concepts such as aperiodic, random chaotic behavior, sensitivity to initial conditions, bifurcation of dynamic processes, levels of organization, self-organization, aggregated and isolated functionality, and emergence of collective complex behavior at the system level. By incorporating several existing ontologies, the ENDCS ontology represents the dynamic system variables and the rules of transformation of their state, emergent state, and other features of complex systems such as the trajectories in state (phase) space (attractor and strange attractor), basins of attractions, basin divide (separatrix), fractal dimension, and system's interface to its environment. The ontology also defines different object properties that change the system behavior, function, and structure and trigger instability. ENDCS will help to integrate the data and knowledge related to the five complex subsystems of Earth by annotating common data types, unifying the semantics of shared terminology, and facilitating interoperability among different fields of Earth science.

Using Agent Based Distillation to Explore Issues Related to Asymmetric Warfare

DTIC Science & Technology

2009-10-01

hierarchical model of needs proposed by Abraham Maslow [12]. An interpretation of Maslow’s hierarchy of needs can be represented as a pyramid with the more...D. Kahnemann, E. Deiner, Dr. Phil Norbert Schwarz, « Foundations of Hedonic Psychology », Russell Sage Foundation, 1999 [12] Abraham.H. Maslow

20 CFR 429.103 - Who may file my claim?

Code of Federal Regulations, 2010 CFR

2010-04-01

... authorized agent, or your legal representative may file the claim. (c) Claims based on death. The executor or... behalf as agent, executor, administrator, parent, guardian or other representative. ...

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.

Nanoparticles as a Novel Delivery Vehicle for Therapeutics Targeting Erectile Dysfunction

PubMed Central

Han, George; Tar, Moses; Kuppam, Dwaraka S. R.; Friedman, Adam; Melman, Arnold; Friedman, Joel; Davies, Kelvin P.

2010-01-01

Introduction Nanoparticles represent a potential novel mechanism for transdermal delivery of erectogenic agents directly to the penis. Aim To determine if nanoparticles encapsulating known erectogenic agents (tadalafil, sialorphin, and nitric oxide [NO]) can improve erectile function in a rat model of erectile dysfunction (ED) as a result of aging (the Sprague-Dawley retired breeder rat). Methods Nanoparticles encapsulating the erectogenic agents were applied as a gel to the glans and penile shaft of anesthetized Sprague-Dawley rats and the intracorporal pressure/blood pressure (ICP/BP) monitored for up to 2 hours with or without stimulation of the cavernous nerve. Control nanoparticles were made without encapsulating erectogenic agents and applied in a similar manner in separate experiments. Results Nanoparticles encapsulating NO caused spontaneous visible erections in the rat, with an average time of onset of 4.5 minutes, duration of 1.42 minutes, and ICP/BP of 0.67 ± 0.14. The sialorphin nanoparticles also caused visible spontaneous erections after an average of 4.5 minutes, with a duration of 8 minutes and ICP/BP ratio of 0.72 ± 0.13. The difference in the erectile response between groups of animals treated with NO or sialorphin nanoparticles was significantly different from the control group treated with empty nanoparticles (P < 0.05) Tadalafil nanoparticles showed a significant increase in the mean ICP/BP (0.737 ± 0.029) following stimulation of the cavernous nerve (4 mA) 1 hour after application of the nanoparticles with a visibly improved erectile response. Conclusions Nanoparticles encapsulating three different erectogenic agents resulted in increased erectile function when applied to the penis of a rat model of ED. Nanoparticles represent a potential novel route for topical delivery of erectogenic agents which could improve the safety profile for existing orally administered drugs by avoiding effects of absorption and first-pass metabolism, and would be less hazardous than injection. PMID:19765204

Nanoparticles as a novel delivery vehicle for therapeutics targeting erectile dysfunction.

PubMed

Han, George; Tar, Moses; Kuppam, Dwaraka S R; Friedman, Adam; Melman, Arnold; Friedman, Joel; Davies, Kelvin P

2010-01-01

Nanoparticles represent a potential novel mechanism for transdermal delivery of erectogenic agents directly to the penis. To determine if nanoparticles encapsulating known erectogenic agents (tadalafil, sialorphin, and nitric oxide [NO]) can improve erectile function in a rat model of erectile dysfunction (ED) as a result of aging (the Sprague-Dawley retired breeder rat). Nanoparticles encapsulating the erectogenic agents were applied as a gel to the glans and penile shaft of anesthetized Sprague-Dawley rats and the intracorporal pressure/blood pressure (ICP/BP) monitored for up to 2 hours with or without stimulation of the cavernous nerve. Control nanoparticles were made without encapsulating erectogenic agents and applied in a similar manner in separate experiments. Nanoparticles encapsulating NO caused spontaneous visible erections in the rat, with an average time of onset of 4.5 minutes, duration of 1.42 minutes, and ICP/BP of 0.67 +/- 0.14. The sialorphin nanoparticles also caused visible spontaneous erections after an average of 4.5 minutes, with a duration of 8 minutes and ICP/BP ratio of 0.72 +/- 0.13. The difference in the erectile response between groups of animals treated with NO or sialorphin nanoparticles was significantly different from the control group treated with empty nanoparticles (P < 0.05) Tadalafil nanoparticles showed a significant increase in the mean ICP/BP (0.737 +/- 0.029) following stimulation of the cavernous nerve (4 mA) 1 hour after application of the nanoparticles with a visibly improved erectile response. Nanoparticles encapsulating three different erectogenic agents resulted in increased erectile function when applied to the penis of a rat model of ED. Nanoparticles represent a potential novel route for topical delivery of erectogenic agents which could improve the safety profile for existing orally administered drugs by avoiding effects of absorption and first-pass metabolism, and would be less hazardous than injection.

Directed Random Markets: Connectivity Determines Money

NASA Astrophysics Data System (ADS)

Martínez-Martínez, Ismael; López-Ruiz, Ricardo

2013-12-01

Boltzmann-Gibbs (BG) distribution arises as the statistical equilibrium probability distribution of money among the agents of a closed economic system where random and undirected exchanges are allowed. When considering a model with uniform savings in the exchanges, the final distribution is close to the gamma family. In this paper, we implement these exchange rules on networks and we find that these stationary probability distributions are robust and they are not affected by the topology of the underlying network. We introduce a new family of interactions: random but directed ones. In this case, it is found the topology to be determinant and the mean money per economic agent is related to the degree of the node representing the agent in the network. The relation between the mean money per economic agent and its degree is shown to be linear.

Learning Based Bidding Strategy for HVAC Systems in Double Auction Retail Energy Markets

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

Sun, Yannan; Somani, Abhishek; Carroll, Thomas E.

In this paper, a bidding strategy is proposed using reinforcement learning for HVAC systems in a double auction market. The bidding strategy does not require a specific model-based representation of behavior, i.e., a functional form to translate indoor house temperatures into bid prices. The results from reinforcement learning based approach are compared with the HVAC bidding approach used in the AEP gridSMART® smart grid demonstration project and it is shown that the model-free (learning based) approach tracks well the results from the model-based behavior. Successful use of model-free approaches to represent device-level economic behavior may help develop similar approaches tomore » represent behavior of more complex devices or groups of diverse devices, such as in a building. Distributed control requires an understanding of decision making processes of intelligent agents so that appropriate mechanisms may be developed to control and coordinate their responses, and model-free approaches to represent behavior will be extremely useful in that quest.« less

A network-patch methodology for adapting agent-based models for directly transmitted disease to mosquito-borne disease.

PubMed

Manore, Carrie A; Hickmann, Kyle S; Hyman, James M; Foppa, Ivo M; Davis, Justin K; Wesson, Dawn M; Mores, Christopher N

2015-01-01

Mosquito-borne diseases cause significant public health burden and are widely re-emerging or emerging. Understanding, predicting, and mitigating the spread of mosquito-borne disease in diverse populations and geographies are ongoing modelling challenges. We propose a hybrid network-patch model for the spread of mosquito-borne pathogens that accounts for individual movement through mosquito habitats, extending the capabilities of existing agent-based models (ABMs) to include vector-borne diseases. The ABM are coupled with differential equations representing 'clouds' of mosquitoes in patches accounting for mosquito ecology. We adapted an ABM for humans using this method and investigated the importance of heterogeneity in pathogen spread, motivating the utility of models of individual behaviour. We observed that the final epidemic size is greater in patch models with a high risk patch frequently visited than in a homogeneous model. Our hybrid model quantifies the importance of the heterogeneity in the spread of mosquito-borne pathogens, guiding mitigation strategies.

Enhanced Collaboration for Space Situational Awareness via Proxy Agents

NASA Astrophysics Data System (ADS)

Picciano, P.; Schurr, N.

2012-09-01

The call for dynamic partnerships demanded in the US. Space Policy confronts two formidable challenges. The first is evident in the lack of the adoption of technical innovations that could substantially enhance collaboration. The second category, and perhaps a greater impediment, involves organizational and social constraints that minimize information sharing. Compounding the technical challenges, the organizational barriers to collaboration present a different problem set. There is a culture in the space domain that predisposes most stakeholders to guard their information. Most owner/operators are reluctant to share asset data, whether experiencing an anomaly or just providing status updates. This is unfortunate, because the owner/operators generally have the most accurate and timely data pertaining to their satellite. Comprehensive Space Situational Awareness (SSA) requires the marshaling of disparate mission critical elements. The mission threads reliant on SSA are complex and often require analysis from a diverse team of experts with sophisticated systems and tools that may be dispersed across multiple entities including military, commercial, and public interests. Two significant trends are likely to further perpetuate this state of affairs: 1) the space environment continues to be more congested, contested, and competitive, and 2) further pressures to increase SSA Sharing with a greater number of stakeholders throughout the world. The challenge of delivering the right information to the right people, while protecting national security and privacy interests, is in need of an innovative solution. Our approach, entitled Space Collaboration via an Agent Network (SCAN), enables proxy software agents to represent stakeholders (as individuals and organizations) to enhance collaboration among various agency producers and consumers of space information The SCAN agent network will facilitate collaboration by identifying opportunities to collaborate, as well as optimize the processes given the mission context. The agent-based approach is uniquely capable of addressing the collaboration challenges from both the technical and organizational perspectives. To achieve these objectives, we are employing a modeling approach based on a Markov decision process (MDP). MDPs are very general models for optimizing decisions under uncertainty. The model was chosen because it is able to represent the uncertainty in outcomes (such as loss of satellite communication or inability for a colleague to finish a task on time) as well as the associated values of decisions made and their resulting outcomes. The key aspect of MDPs is that it is a sequential model, not only does it represent uncertainty for single decisions and outcomes, but estimates the state of the world in the future and optimizes decisions based on these future expectations. The SCAN prototype will be used to assess modeling parameters and assumptions as well as collect user feedback.

Boolean network representation of contagion dynamics during a financial crisis

NASA Astrophysics Data System (ADS)

Caetano, Marco Antonio Leonel; Yoneyama, Takashi

2015-01-01

This work presents a network model for representation of the evolution of certain patterns of economic behavior. More specifically, after representing the agents as points in a space in which each dimension associated to a relevant economic variable, their relative "motions" that can be either stationary or discordant, are coded into a boolean network. Patterns with stationary averages indicate the maintenance of status quo, whereas discordant patterns represent aggregation of new agent into the cluster or departure from the former policies. The changing patterns can be embedded into a network representation, particularly using the concept of autocatalytic boolean networks. As a case study, the economic tendencies of the BRIC countries + Argentina were studied. Although Argentina is not included in the cluster formed by BRIC countries, it tends to follow the BRIC members because of strong commercial ties.

Agent-based modeling of deforestation in southern Yucatán, Mexico, and reforestation in the Midwest United States

PubMed Central

Manson, Steven M.; Evans, Tom

2007-01-01

We combine mixed-methods research with integrated agent-based modeling to understand land change and economic decision making in the United States and Mexico. This work demonstrates how sustainability science benefits from combining integrated agent-based modeling (which blends methods from the social, ecological, and information sciences) and mixed-methods research (which interleaves multiple approaches ranging from qualitative field research to quantitative laboratory experiments and interpretation of remotely sensed imagery). We test assumptions of utility-maximizing behavior in household-level landscape management in south-central Indiana, linking parcel data, land cover derived from aerial photography, and findings from laboratory experiments. We examine the role of uncertainty and limited information, preferences, differential demographic attributes, and past experience and future time horizons. We also use evolutionary programming to represent bounded rationality in agriculturalist households in the southern Yucatán of Mexico. This approach captures realistic rule of thumb strategies while identifying social and environmental factors in a manner similar to econometric models. These case studies highlight the role of computational models of decision making in land-change contexts and advance our understanding of decision making in general. PMID:18093928

Experimental Evaluation of Suitability of Selected Multi-Criteria Decision-Making Methods for Large-Scale Agent-Based Simulations.

PubMed

Tučník, Petr; Bureš, Vladimír

2016-01-01

Multi-criteria decision-making (MCDM) can be formally implemented by various methods. This study compares suitability of four selected MCDM methods, namely WPM, TOPSIS, VIKOR, and PROMETHEE, for future applications in agent-based computational economic (ACE) models of larger scale (i.e., over 10 000 agents in one geographical region). These four MCDM methods were selected according to their appropriateness for computational processing in ACE applications. Tests of the selected methods were conducted on four hardware configurations. For each method, 100 tests were performed, which represented one testing iteration. With four testing iterations conducted on each hardware setting and separated testing of all configurations with the-server parameter de/activated, altogether, 12800 data points were collected and consequently analyzed. An illustrational decision-making scenario was used which allows the mutual comparison of all of the selected decision making methods. Our test results suggest that although all methods are convenient and can be used in practice, the VIKOR method accomplished the tests with the best results and thus can be recommended as the most suitable for simulations of large-scale agent-based models.

Massive Multi-Agent Systems Control

NASA Technical Reports Server (NTRS)

Campagne, Jean-Charles; Gardon, Alain; Collomb, Etienne; Nishida, Toyoaki

2004-01-01

In order to build massive multi-agent systems, considered as complex and dynamic systems, one needs a method to analyze and control the system. We suggest an approach using morphology to represent and control the state of large organizations composed of a great number of light software agents. Morphology is understood as representing the state of the multi-agent system as shapes in an abstract geometrical space, this notion is close to the notion of phase space in physics.

Prediction of the effect of formulation on the toxicity of chemicals.

PubMed

Mistry, Pritesh; Neagu, Daniel; Sanchez-Ruiz, Antonio; Trundle, Paul R; Vessey, Jonathan D; Gosling, John Paul

2017-01-01

Two approaches for the prediction of which of two vehicles will result in lower toxicity for anticancer agents are presented. Machine-learning models are developed using decision tree, random forest and partial least squares methodologies and statistical evidence is presented to demonstrate that they represent valid models. Separately, a clustering method is presented that allows the ordering of vehicles by the toxicity they show for chemically-related compounds.

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.

Network formation: neighborhood structures, establishment costs, and distributed learning.

PubMed

Chasparis, Georgios C; Shamma, Jeff S

2013-12-01

We consider the problem of network formation in a distributed fashion. Network formation is modeled as a strategic-form game, where agents represent nodes that form and sever unidirectional links with other nodes and derive utilities from these links. Furthermore, agents can form links only with a limited set of neighbors. Agents trade off the benefit from links, which is determined by a distance-dependent reward function, and the cost of maintaining links. When each agent acts independently, trying to maximize its own utility function, we can characterize “stable” networks through the notion of Nash equilibrium. In fact, the introduced reward and cost functions lead to Nash equilibria (networks), which exhibit several desirable properties such as connectivity, bounded-hop diameter, and efficiency (i.e., minimum number of links). Since Nash networks may not necessarily be efficient, we also explore the possibility of “shaping” the set of Nash networks through the introduction of state-based utility functions. Such utility functions may represent dynamic phenomena such as establishment costs (either positive or negative). Finally, we show how Nash networks can be the outcome of a distributed learning process. In particular, we extend previous learning processes to so-called “state-based” weakly acyclic games, and we show that the proposed network formation games belong to this class of games.

Toward an agent-based patient-physician model for the adoption of continuous glucose monitoring technology.

PubMed

Verella, J Tipan; Patek, Stephen D

2009-03-01

Health care is a major component of the U.S. economy, and tremendous research and development efforts are directed toward new technologies in this arena. Unfortunately few tools exist for predicting outcomes associated with new medical products, including whether new technologies will find widespread use within the target population. Questions of technology adoption are rife within the diabetes technology community, and we particularly consider the long-term prognosis for continuous glucose monitoring (CGM) technology. We present an approach to the design and analysis of an agent model that describes the process of CGM adoption among patients with type 1 diabetes mellitus (T1DM), their physicians, and related stakeholders. We particularly focus on patient-physician interactions, with patients discovering CGM technology through word-of-mouth communication and through advertising, applying pressure to their physicians in the context of CGM device adoption, and physicians, concerned about liability, looking to peers for a general level of acceptance of the technology before recommending CGM to their patients. Repeated simulation trials of the agent-based model show that the adoption process reflects the heterogeneity of the adopting community. We also find that the effect of the interaction between patients and physicians is agents. Each physician, say colored by the nature of the environment as defined by the model parameters. We find that, by being able to represent the diverse perspectives of different types of stakeholders, agent-based models can offer useful insights into the adoption process. Models of this sort may eventually prove to be useful in helping physicians, other health care providers, patient advocacy groups, third party payers, and device manufacturers understand the impact of their decisions about new technologies. (c) 2009 Diabetes Technology Society.

Basic emotions and adaptation. A computational and evolutionary model

PubMed Central

2017-01-01

The core principles of the evolutionary theories of emotions declare that affective states represent crucial drives for action selection in the environment and regulated the behavior and adaptation of natural agents in ancestrally recurrent situations. While many different studies used autonomous artificial agents to simulate emotional responses and the way these patterns can affect decision-making, few are the approaches that tried to analyze the evolutionary emergence of affective behaviors directly from the specific adaptive problems posed by the ancestral environment. A model of the evolution of affective behaviors is presented using simulated artificial agents equipped with neural networks and physically inspired on the architecture of the iCub humanoid robot. We use genetic algorithms to train populations of virtual robots across generations, and investigate the spontaneous emergence of basic emotional behaviors in different experimental conditions. In particular, we focus on studying the emotion of fear, therefore the environment explored by the artificial agents can contain stimuli that are safe or dangerous to pick. The simulated task is based on classical conditioning and the agents are asked to learn a strategy to recognize whether the environment is safe or represents a threat to their lives and select the correct action to perform in absence of any visual cues. The simulated agents have special input units in their neural structure whose activation keep track of their actual “sensations” based on the outcome of past behavior. We train five different neural network architectures and then test the best ranked individuals comparing their performances and analyzing the unit activations in each individual’s life cycle. We show that the agents, regardless of the presence of recurrent connections, spontaneously evolved the ability to cope with potentially dangerous environment by collecting information about the environment and then switching their behavior to a genetically selected pattern in order to maximize the possible reward. We also prove the determinant presence of an internal time perception unit for the robots to achieve the highest performance and survivability across all conditions. PMID:29107988

Cooling system operation efficiency of locomotive diesel engine

NASA Astrophysics Data System (ADS)

Ovcharenko, Sergey; Balagin, Oleg; Balagin, Dmitry

2017-10-01

A theoretical model for the calculation of the heat parameters of locomotive diesel engine cooling system in case of using heating agent bypass between the circuits is represented. The influence of the cooling fluid on the bypass from “hot” circuit to the “cold” circuit at different ambient air temperature is studied.

Multi-stage complex contagions.

PubMed

Melnik, Sergey; Ward, Jonathan A; Gleeson, James P; Porter, Mason A

2013-03-01

The spread of ideas across a social network can be studied using complex contagion models, in which agents are activated by contact with multiple activated neighbors. The investigation of complex contagions can provide crucial insights into social influence and behavior-adoption cascades on networks. In this paper, we introduce a model of a multi-stage complex contagion on networks. Agents at different stages-which could, for example, represent differing levels of support for a social movement or differing levels of commitment to a certain product or idea-exert different amounts of influence on their neighbors. We demonstrate that the presence of even one additional stage introduces novel dynamical behavior, including interplay between multiple cascades, which cannot occur in single-stage contagion models. We find that cascades-and hence collective action-can be driven not only by high-stage influencers but also by low-stage influencers.

Multi-stage complex contagions

NASA Astrophysics Data System (ADS)

Melnik, Sergey; Ward, Jonathan A.; Gleeson, James P.; Porter, Mason A.

2013-03-01

The spread of ideas across a social network can be studied using complex contagion models, in which agents are activated by contact with multiple activated neighbors. The investigation of complex contagions can provide crucial insights into social influence and behavior-adoption cascades on networks. In this paper, we introduce a model of a multi-stage complex contagion on networks. Agents at different stages—which could, for example, represent differing levels of support for a social movement or differing levels of commitment to a certain product or idea—exert different amounts of influence on their neighbors. We demonstrate that the presence of even one additional stage introduces novel dynamical behavior, including interplay between multiple cascades, which cannot occur in single-stage contagion models. We find that cascades—and hence collective action—can be driven not only by high-stage influencers but also by low-stage influencers.

Exits in order: How crowding affects particle lifetimes

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

Penington, Catherine J.; Simpson, Matthew J.; Baker, Ruth E.

2016-06-28

Diffusive processes are often represented using stochastic random walk frameworks. The amount of time taken for an individual in a random walk to intersect with an absorbing boundary is a fundamental property that is often referred to as the particle lifetime, or the first passage time. The mean lifetime of particles in a random walk model of diffusion is related to the amount of time required for the diffusive process to reach a steady state. Mathematical analysis describing the mean lifetime of particles in a standard model of diffusion without crowding is well known. However, the lifetime of agents inmore » a random walk with crowding has received much less attention. Since many applications of diffusion in biology and biophysics include crowding effects, here we study a discrete model of diffusion that incorporates crowding. Using simulations, we show that crowding has a dramatic effect on agent lifetimes, and we derive an approximate expression for the mean agent lifetime that includes crowding effects. Our expression matches simulation results very well, and highlights the importance of crowding effects that are sometimes overlooked.« less

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.).

Results and Lessons Learned from a Coupled Social and Physical Hydrology Model: Testing Alternative Water Management Policies and Institutional Structures Using Agent-Based Modeling and Regional Hydrology

NASA Astrophysics Data System (ADS)

Murphy, J.; Lammers, R. B.; Prousevitch, A.; Ozik, J.; Altaweel, M.; Collier, N. T.; Kliskey, A. D.; Alessa, L.

2015-12-01

Water Management in the U.S. Southwest is under increasing scrutiny as many areas endure persistent drought. The impact of these prolonged dry conditions is a product of regional climate and hydrological conditions, but also of a highly engineered water management infrastructure and a complex web of social arrangements whereby water is allocated, shared, exchanged, used, re-used, and finally consumed. We coupled an agent-based model with a regional hydrological model to understand the dynamics in one richly studied and highly populous area: southern Arizona, U.S.A., including metropolitan Phoenix and Tucson. There, multiple management entities representing an array of municipalities and other water providers and customers, including private companies and Native American tribes are enmeshed in a complex legal and economic context in which water is bought, leased, banked, and exchanged in a variety of ways and on multiple temporal and physical scales. A recurrent question in the literature of adaptive management is the impact of management structure on overall system performance. To explore this, we constructed an agent-based model to capture this social complexity, and coupled this with a physical hydrological model that we used to drive the system under a variety of water stress scenarios and to assess the regional impact of the social system's performance. We report the outcomes of ensembles of runs in which varieties of alternative policy constraints and management strategies are considered. We hope to contribute to policy discussions in this area and connected and legislatively similar areas (such as California) as current conditions change and existing legal and policy structures are revised. Additionally, we comment on the challenges of integrating models that ostensibly are in different domains (physical and social) but that independently represent a system in which physical processes and human actions are closely intertwined and difficult to disentangle.

Nursing opinion leadership: a preliminary model derived from philosophic theories of rational belief.

PubMed

Anderson, Christine A; Whall, Ann L

2013-10-01

Opinion leaders are informal leaders who have the ability to influence others' decisions about adopting new products, practices or ideas. In the healthcare setting, the importance of translating new research evidence into practice has led to interest in understanding how opinion leaders could be used to speed this process. Despite continued interest, gaps in understanding opinion leadership remain. Agent-based models are computer models that have proven to be useful for representing dynamic and contextual phenomena such as opinion leadership. The purpose of this paper is to describe the work conducted in preparation for the development of an agent-based model of nursing opinion leadership. The aim of this phase of the model development project was to clarify basic assumptions about opinions, the individual attributes of opinion leaders and characteristics of the context in which they are effective. The process used to clarify these assumptions was the construction of a preliminary nursing opinion leader model, derived from philosophical theories about belief formation. © 2013 John Wiley & Sons Ltd.

American Muslim Perceptions of Healing: Key Agents in Healing, and Their Roles

PubMed Central

Padela, Aasim I.; Killawi, Amal; Forman, Jane; DeMonner, Sonya; Heisler, Michele

2015-01-01

American Muslims represent a growing and diverse community. Efforts at promoting cultural competence, enhancing cross-cultural communication skills, and improving community health must account for the religio-cultural frame through which American Muslims view healing. Using a community-based participatory research model, we conducted 13 focus groups at area mosques in southeast Michigan to explore American Muslim views on healing and to identify the primary agents, and their roles, within the healing process. Participants shared a God-centric view of healing. Healing was accessed through direct means such as supplication and recitation of the Qur'an, or indirectly through human agents including imams, health care practitioners, family, friends, and community. Human agents served integral roles, influencing spiritual, psychological, and physical health. Additional research into how religiosity, health care systems, and community factors influence health-care-seeking behaviors is warranted. PMID:22393065

Individual Decision-Making in Uncertain and Large-Scale Multi-Agent Environments

DTIC Science & Technology

2009-02-18

first method, labeled as MC, limits and holds constant the number of models, 0 < KMC < M, where M is the possibly large number of candidate models of...equivalent and hence may be replaced by a subset of representative models without a significant loss in the optimality of the decision maker. KMC ...for different horizons. KMC and M are equal to 50 and 100 respectively for both approximate and exact approaches (Pentium 4, 3.0GHz, 1GB RAM, WinXP

Combining agent-based modeling and life cycle assessment for the evaluation of mobility policies.

PubMed

Florent, Querini; Enrico, Benetto

2015-02-03

This article presents agent-based modeling (ABM) as a novel approach for consequential life cycle assessment (C-LCA) of large scale policies, more specifically mobility-related policies. The approach is validated at the Luxembourgish level (as a first case study). The agent-based model simulates the car market (sales, use, and dismantling) of the population of users in the period 2013-2020, following the implementation of different mobility policies and available electric vehicles. The resulting changes in the car fleet composition as well as the hourly uses of the vehicles are then used to derive consistent LCA results, representing the consequences of the policies. Policies will have significant environmental consequences: when using ReCiPe2008, we observe a decrease of global warming, fossil depletion, acidification, ozone depletion, and photochemical ozone formation and an increase of metal depletion, ionizing radiations, marine eutrophication, and particulate matter formation. The study clearly shows that the extrapolation of LCA results for the circulating fleet at national scale following the introduction of the policies from the LCAs of single vehicles by simple up-scaling (using hypothetical deployment scenarios) would be flawed. The inventory has to be directly conducted at full scale and to this aim, ABM is indeed a promising approach, as it allows identifying and quantifying emerging effects while modeling the Life Cycle Inventory of vehicles at microscale through the concept of agents.

Stochastic opinion formation in scale-free networks

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

M. Bartolozzi; D. B. Leinweber; A. W. Thomas

2005-10-01

The dynamics of opinion formation in large groups of people is a complex nonlinear phenomenon whose investigation is just beginning. Both collective behavior and personal views play an important role in this mechanism. In the present work we mimic the dynamics of opinion formation of a group of agents, represented by two states 1, as a stochastic response of each agent to the opinion of his/her neighbors in the social network and to feedback from the average opinion of the whole. In the light of recent studies, a scale-free Barabsi-Albert network has been selected to simulate the topology of themore » interactions. A turbulent-like dynamics, characterized by an intermittent behavior, is observed for a certain range of the model parameters. The problem of uncertainty in decision taking is also addressed both from a topological point of view, using random and targeted removal of agents from the network, and by implementing a three-state model, where the third state, zero, is related to the information available to each agent. Finally, the results of the model are tested against the best known network of social interactions: the stock market. A time series of daily closures of the Dow-Jones index has been used as an indicator of the possible applicability of our model in the financial context. Good qualitative agreement is found.« less

Climate change effects on international stability : a white paper.

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

Murphy, Kathryn; Taylor, Mark A.; Fujii, Joy

2004-12-01

This white paper represents a summary of work intended to lay the foundation for development of a climatological/agent model of climate-induced conflict. The paper combines several loosely-coupled efforts and is the final report for a four-month late-start Laboratory Directed Research and Development (LDRD) project funded by the Advanced Concepts Group (ACG). The project involved contributions by many participants having diverse areas of expertise, with the common goal of learning how to tie together the physical and human causes and consequences of climate change. We performed a review of relevant literature on conflict arising from environmental scarcity. Rather than simply reviewingmore » the previous work, we actively collected data from the referenced sources, reproduced some of the work, and explored alternative models. We used the unfolding crisis in Darfur (western Sudan) as a case study of conflict related to or triggered by climate change, and as an exercise for developing a preliminary concept map. We also outlined a plan for implementing agents in a climate model and defined a logical progression toward the ultimate goal of running both types of models simultaneously in a two-way feedback mode, where the behavior of agents influences the climate and climate change affects the agents. Finally, we offer some ''lessons learned'' in attempting to keep a diverse and geographically dispersed group working together by using Web-based collaborative tools.« less

Agent 2003 Conference on Challenges in Social Simulation

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

Margaret Clemmons, ed.

Welcome to the Proceedings of the fourth in a series of agent simulation conferences cosponsored by Argonne National Laboratory and The University of Chicago. Agent 2003 is the second conference in which three Special Interest Groups from the North American Association for Computational Social and Organizational Science (NAACSOS) have been involved in planning the program--Computational Social Theory; Simulation Applications; and Methods, Toolkits and Techniques. The theme of Agent 2003, Challenges in Social Simulation, is especially relevant, as there seems to be no shortage of such challenges. Agent simulation has been applied with increasing frequency to social domains for several decades,more » and its promise is clear and increasingly visible. Like any nascent scientific methodology, however, it faces a number of problems or issues that must be addressed in order to progress. These challenges include: (1) Validating models relative to the social settings they are designed to represent; (2) Developing agents and interactions simple enough to understand but sufficiently complex to do justice to the social processes of interest; (3) Bridging the gap between empirically spare artificial societies and naturally occurring social phenomena; (4) Building multi-level models that span processes across domains; (5) Promoting a dialog among theoretical, qualitative, and empirical social scientists and area experts, on the one hand, and mathematical and computational modelers and engineers, on the other; (6) Using that dialog to facilitate substantive progress in the social sciences; and (7) Fulfilling the aspirations of users in business, government, and other application areas, while recognizing and addressing the preceding challenges. Although this list hardly exhausts the challenges the field faces, it does identify topics addressed throughout the presentations of Agent 2003. Agent 2003 is part of a much larger process in which new methods and techniques are applied to difficult social issues. Among the resources that give us the prospect of success is the innovative and transdisciplinary research community being built. We believe that Agent 2003 contributes to further progress in computational modeling of social processes, and we hope that you find these Proceedings to be stimulating and rewarding. As the horizons of this transdiscipline continue to emerge and converge, we hope to provide similar forums that will promote development of agent simulation modeling in the years to come.« less

Costs of Providing Infusion Therapy for Rheumatoid Arthritis in a Hospital-based Infusion Center Setting.

PubMed

Schmier, Jordana; Ogden, Kristine; Nickman, Nancy; Halpern, Michael T; Cifaldi, Mary; Ganguli, Arijit; Bao, Yanjun; Garg, Vishvas

2017-08-01

Many hospital-based infusion centers treat patients with rheumatoid arthritis (RA) with intravenous biologic agents, yet may have a limited understanding of the overall costs of infusion in this setting. The purposes of this study were to conduct a microcosting analysis from a hospital perspective and to develop a model using an activity-based costing approach for estimating costs associated with the provision of hospital-based infusion services (preparation, administration, and follow-up) in the United States for maintenance treatment of moderate to severe RA. A spreadsheet-based model was developed. Inputs included hourly wages, time spent providing care, supply/overhead costs, laboratory testing, infusion center size, and practice pattern information. Base-case values were derived from data from surveys, published studies, standard cost sources, and expert opinion. Costs are presented in year-2017 US dollars. The base case modeled a hospital infusion center serving patients with RA treated with abatacept, tocilizumab, infliximab, or rituximab. Estimated overall costs of infusions per patient per year were $36,663 (rituximab), $36,821 (tocilizumab), $44,973 (infliximab), and $46,532 (abatacept). Of all therapies, the biologic agents represented the greatest share of overall costs, ranging from 87% to $91% of overall costs per year. Excluding infusion drug costs, labor accounted for 53% to 57% of infusion costs. Biologic agents represented the highest single cost associated with RA infusion care; however, personnel, supplies, and overhead costs also contributed substantially to overall costs (8%-16%). This model may provide a helpful and adaptable framework for use by hospitals in informing decision making about services offered and their associated financial implications. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

CHAMPION: Intelligent Hierarchical Reasoning Agents for Enhanced Decision Support

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

Hohimer, Ryan E.; Greitzer, Frank L.; Noonan, Christine F.

2011-11-15

We describe the design and development of an advanced reasoning framework employing semantic technologies, organized within a hierarchy of computational reasoning agents that interpret domain specific information. Designed based on an inspirational metaphor of the pattern recognition functions performed by the human neocortex, the CHAMPION reasoning framework represents a new computational modeling approach that derives invariant knowledge representations through memory-prediction belief propagation processes that are driven by formal ontological language specification and semantic technologies. The CHAMPION framework shows promise for enhancing complex decision making in diverse problem domains including cyber security, nonproliferation and energy consumption analysis.

Modeling social learning of language and skills.

PubMed

Vogt, Paul; Haasdijk, Evert

2010-01-01

We present a model of social learning of both language and skills, while assuming—insofar as possible—strict autonomy, virtual embodiment, and situatedness. This model is built by integrating various previous models of language development and social learning, and it is this integration that, under the mentioned assumptions, provides novel challenges. The aim of the article is to investigate what sociocognitive mechanisms agents should have in order to be able to transmit language from one generation to the next so that it can be used as a medium to transmit internalized rules that represent skill knowledge. We have performed experiments where this knowledge solves the familiar poisonous-food problem. Simulations reveal under what conditions, regarding population structure, agents can successfully solve this problem. In addition to issues relating to perspective taking and mutual exclusivity, we show that agents need to coordinate interactions so that they can establish joint attention in order to form a scaffold for language learning, which in turn forms a scaffold for the learning of rule-based skills. Based on these findings, we conclude by hypothesizing that social learning at one level forms a scaffold for the social learning at another, higher level, thus contributing to the accumulation of cultural knowledge.

Introduction of a Framework for Dynamic Knowledge Representation of the Control Structure of Transplant Immunology: Employing the Power of Abstraction with a Solid Organ Transplant Agent-Based Model

PubMed Central

An, Gary

2015-01-01

Agent-based modeling has been used to characterize the nested control loops and non-linear dynamics associated with inflammatory and immune responses, particularly as a means of visualizing putative mechanistic hypotheses. This process is termed dynamic knowledge representation and serves a critical role in facilitating the ability to test and potentially falsify hypotheses in the current data- and hypothesis-rich biomedical research environment. Importantly, dynamic computational modeling aids in identifying useful abstractions, a fundamental scientific principle that pervades the physical sciences. Recognizing the critical scientific role of abstraction provides an intellectual and methodological counterweight to the tendency in biology to emphasize comprehensive description as the primary manifestation of biological knowledge. Transplant immunology represents yet another example of the challenge of identifying sufficient understanding of the inflammatory/immune response in order to develop and refine clinically effective interventions. Advances in immunosuppressive therapies have greatly improved solid organ transplant (SOT) outcomes, most notably by reducing and treating acute rejection. The end goal of these transplant immune strategies is to facilitate effective control of the balance between regulatory T cells and the effector/cytotoxic T-cell populations in order to generate, and ideally maintain, a tolerant phenotype. Characterizing the dynamics of immune cell populations and the interactive feedback loops that lead to graft rejection or tolerance is extremely challenging, but is necessary if rational modulation to induce transplant tolerance is to be accomplished. Herein is presented the solid organ agent-based model (SOTABM) as an initial example of an agent-based model (ABM) that abstractly reproduces the cellular and molecular components of the immune response to SOT. Despite its abstract nature, the SOTABM is able to qualitatively reproduce acute rejection and the suppression of acute rejection by immunosuppression to generate transplant tolerance. The SOTABM is intended as an initial example of how ABMs can be used to dynamically represent mechanistic knowledge concerning transplant immunology in a scalable and expandable form and can thus potentially serve as useful adjuncts to the investigation and development of control strategies to induce transplant tolerance. PMID:26594211

Introduction of a Framework for Dynamic Knowledge Representation of the Control Structure of Transplant Immunology: Employing the Power of Abstraction with a Solid Organ Transplant Agent-Based Model.

PubMed

An, Gary

2015-01-01

Agent-based modeling has been used to characterize the nested control loops and non-linear dynamics associated with inflammatory and immune responses, particularly as a means of visualizing putative mechanistic hypotheses. This process is termed dynamic knowledge representation and serves a critical role in facilitating the ability to test and potentially falsify hypotheses in the current data- and hypothesis-rich biomedical research environment. Importantly, dynamic computational modeling aids in identifying useful abstractions, a fundamental scientific principle that pervades the physical sciences. Recognizing the critical scientific role of abstraction provides an intellectual and methodological counterweight to the tendency in biology to emphasize comprehensive description as the primary manifestation of biological knowledge. Transplant immunology represents yet another example of the challenge of identifying sufficient understanding of the inflammatory/immune response in order to develop and refine clinically effective interventions. Advances in immunosuppressive therapies have greatly improved solid organ transplant (SOT) outcomes, most notably by reducing and treating acute rejection. The end goal of these transplant immune strategies is to facilitate effective control of the balance between regulatory T cells and the effector/cytotoxic T-cell populations in order to generate, and ideally maintain, a tolerant phenotype. Characterizing the dynamics of immune cell populations and the interactive feedback loops that lead to graft rejection or tolerance is extremely challenging, but is necessary if rational modulation to induce transplant tolerance is to be accomplished. Herein is presented the solid organ agent-based model (SOTABM) as an initial example of an agent-based model (ABM) that abstractly reproduces the cellular and molecular components of the immune response to SOT. Despite its abstract nature, the SOTABM is able to qualitatively reproduce acute rejection and the suppression of acute rejection by immunosuppression to generate transplant tolerance. The SOTABM is intended as an initial example of how ABMs can be used to dynamically represent mechanistic knowledge concerning transplant immunology in a scalable and expandable form and can thus potentially serve as useful adjuncts to the investigation and development of control strategies to induce transplant tolerance.

Researching a local heroin market as a complex adaptive system.

PubMed

Hoffer, Lee D; Bobashev, Georgiy; Morris, Robert J

2009-12-01

This project applies agent-based modeling (ABM) techniques to better understand the operation, organization, and structure of a local heroin market. The simulation detailed was developed using data from an 18-month ethnographic case study. The original research, collected in Denver, CO during the 1990s, represents the historic account of users and dealers who operated in the Larimer area heroin market. Working together, the authors studied the behaviors of customers, private dealers, street-sellers, brokers, and the police, reflecting the core elements pertaining to how the market operated. After evaluating the logical consistency between the data and agent behaviors, simulations scaled-up interactions to observe their aggregated outcomes. While the concept and findings from this study remain experimental, these methods represent a novel way in which to understand illicit drug markets and the dynamic adaptations and outcomes they generate. Extensions of this research perspective, as well as its strengths and limitations, are discussed.

Action understanding as inverse planning.

PubMed

Baker, Chris L; Saxe, Rebecca; Tenenbaum, Joshua B

2009-12-01

Humans are adept at inferring the mental states underlying other agents' actions, such as goals, beliefs, desires, emotions and other thoughts. We propose a computational framework based on Bayesian inverse planning for modeling human action understanding. The framework represents an intuitive theory of intentional agents' behavior based on the principle of rationality: the expectation that agents will plan approximately rationally to achieve their goals, given their beliefs about the world. The mental states that caused an agent's behavior are inferred by inverting this model of rational planning using Bayesian inference, integrating the likelihood of the observed actions with the prior over mental states. This approach formalizes in precise probabilistic terms the essence of previous qualitative approaches to action understanding based on an "intentional stance" [Dennett, D. C. (1987). The intentional stance. Cambridge, MA: MIT Press] or a "teleological stance" [Gergely, G., Nádasdy, Z., Csibra, G., & Biró, S. (1995). Taking the intentional stance at 12 months of age. Cognition, 56, 165-193]. In three psychophysical experiments using animated stimuli of agents moving in simple mazes, we assess how well different inverse planning models based on different goal priors can predict human goal inferences. The results provide quantitative evidence for an approximately rational inference mechanism in human goal inference within our simplified stimulus paradigm, and for the flexible nature of goal representations that human observers can adopt. We discuss the implications of our experimental results for human action understanding in real-world contexts, and suggest how our framework might be extended to capture other kinds of mental state inferences, such as inferences about beliefs, or inferring whether an entity is an intentional agent.

Using an agent-based model to evaluate the effect of producer specialization on the epidemiological resilience of livestock production networks.

PubMed

Wiltshire, Serge W

2018-01-01

An agent-based computer model that builds representative regional U.S. hog production networks was developed and employed to assess the potential impact of the ongoing trend towards increased producer specialization upon network-level resilience to catastrophic disease outbreaks. Empirical analyses suggest that the spatial distribution and connectivity patterns of contact networks often predict epidemic spreading dynamics. Our model heuristically generates realistic systems composed of hog producer, feed mill, and slaughter plant agents. Network edges are added during each run as agents exchange livestock and feed. The heuristics governing agents' contact patterns account for factors including their industry roles, physical proximities, and the age of their livestock. In each run, an infection is introduced, and may spread according to probabilities associated with the various modes of contact. For each of three treatments-defined by one-phase, two-phase, and three-phase production systems-a parameter variation experiment examines the impact of the spatial density of producer agents in the system upon the length and size of disease outbreaks. Resulting data show phase transitions whereby, above some density threshold, systemic outbreaks become possible, echoing findings from percolation theory. Data analysis reveals that multi-phase production systems are vulnerable to catastrophic outbreaks at lower spatial densities, have more abrupt percolation transitions, and are characterized by less-predictable outbreak scales and durations. Key differences in network-level metrics shed light on these results, suggesting that the absence of potentially-bridging producer-producer edges may be largely responsible for the superior disease resilience of single-phase "farrow to finish" production systems.

An Approach for Autonomy: A Collaborative Communication Framework for Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Dufrene, Warren Russell, Jr.

2005-01-01

Research done during the last three years has studied the emersion properties of Complex Adaptive Systems (CAS). The deployment of Artificial Intelligence (AI) techniques applied to remote Unmanned Aerial Vehicles has led the author to investigate applications of CAS within the field of Autonomous Multi-Agent Systems. The core objective of current research efforts is focused on the simplicity of Intelligent Agents (IA) and the modeling of these agents within complex systems. This research effort looks at the communication, interaction, and adaptability of multi-agents as applied to complex systems control. The embodiment concept applied to robotics has application possibilities within multi-agent frameworks. A new framework for agent awareness within a virtual 3D world concept is possible where the vehicle is composed of collaborative agents. This approach has many possibilities for applications to complex systems. This paper describes the development of an approach to apply this virtual framework to the NASA Goddard Space Flight Center (GSFC) tetrahedron structure developed under the Autonomous Nano Technology Swarm (ANTS) program and the Super Miniaturized Addressable Reconfigurable Technology (SMART) architecture program. These projects represent an innovative set of novel concepts deploying adaptable, self-organizing structures composed of many tetrahedrons. This technology is pushing current applied Agents Concepts to new levels of requirements and adaptability.

Does cost-effectiveness of influenza vaccine choice vary across the U.S.? An agent-based modeling study.

PubMed

DePasse, Jay V; Nowalk, Mary Patricia; Smith, Kenneth J; Raviotta, Jonathan M; Shim, Eunha; Zimmerman, Richard K; Brown, Shawn T

2017-07-13

In a prior agent-based modeling study, offering a choice of influenza vaccine type was shown to be cost-effective when the simulated population represented the large, Washington DC metropolitan area. This study calculated the public health impact and cost-effectiveness of the same four strategies: No Choice, Pediatric Choice, Adult Choice, or Choice for Both Age Groups in five United States (U.S.) counties selected to represent extremes in population age distribution. The choice offered was either inactivated influenza vaccine delivered intramuscularly with a needle (IIV-IM) or an age-appropriate needle-sparing vaccine, specifically, the nasal spray (LAIV) or intradermal (IIV-ID) delivery system. Using agent-based modeling, individuals were simulated as they interacted with others, and influenza was tracked as it spread through each population. Influenza vaccination coverage derived from Centers for Disease Control and Prevention (CDC) data, was increased by 6.5% (range 3.25%-11.25%) to reflect the effects of vaccine choice. Assuming moderate influenza infectivity, the number of averted cases was highest for the Choice for Both Age Groups in all five counties despite differing demographic profiles. In a cost-effectiveness analysis, Choice for Both Age Groups was the dominant strategy. Sensitivity analyses varying influenza infectivity, costs, and degrees of vaccine coverage increase due to choice, supported the base case findings. Offering a choice to receive a needle-sparing influenza vaccine has the potential to significantly reduce influenza disease burden and to be cost saving. Consistent findings across diverse populations confirmed these findings. Copyright © 2017 Elsevier Ltd. All rights reserved.

Collective decision dynamics in the presence of external drivers

NASA Astrophysics Data System (ADS)

Bassett, Danielle S.; Alderson, David L.; Carlson, Jean M.

2012-09-01

We develop a sequence of models describing information transmission and decision dynamics for a network of individual agents subject to multiple sources of influence. Our general framework is set in the context of an impending natural disaster, where individuals, represented by nodes on the network, must decide whether or not to evacuate. Sources of influence include a one-to-many externally driven global broadcast as well as pairwise interactions, across links in the network, in which agents transmit either continuous opinions or binary actions. We consider both uniform and variable threshold rules on the individual opinion as baseline models for decision making. Our results indicate that (1) social networks lead to clustering and cohesive action among individuals, (2) binary information introduces high temporal variability and stagnation, and (3) information transmission over the network can either facilitate or hinder action adoption, depending on the influence of the global broadcast relative to the social network. Our framework highlights the essential role of local interactions between agents in predicting collective behavior of the population as a whole.

State-level legal preparedness for nuclear and radiological emergencies in the U.S.: a network analysis of state laws and regulations.

PubMed

Guclu, Hasan; Ferrell Bjerke, Elizabeth; Galvan, Jared; Sweeney, Patricia; Potter, Margaret A

2014-01-01

This study explored if and to what extent the laws of U.S. states mirrored the U.S. federal laws for responding to nuclear-radiological emergencies (NREs). Emergency laws from a 12-state sample and the federal government were retrieved and translated into numeric codes representing acting agents, their partner agents, and the purposes of activity in terms of preparedness, response, and recovery. We used network analysis to explore the relationships among agents in terms of legally directed NRE activities. States' legal networks for NREs appear as not highly inclusive, involving an average of 28% of agents among those specified in the federal laws. Certain agents are highly central in NRE networks, so that their capacity and effectiveness might strongly influence an NRE response. State-level lawmakers and planners might consider whether or not greater inclusion of agents, modeled on the federal government laws, would enhance their NRE laws and if more agents should be engaged in planning and policy-making for NRE incidents. Further research should explore if and to what extent legislated NRE directives impose constraints on practical response activities including emergency planning.

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.

Evaluation of Radioresponse and Radiosensitizers in Glioblastoma Organotypic Cultures.

PubMed

Bayin, N Sumru; Ma, Lin; Placantonakis, Dimitris G; Barcellos-Hoff, Mary Helen

2018-01-01

Glioblastoma (GBM), a deadly primary brain malignancy, manifests pronounced radioresistance. Identifying agents that improve the sensitivity of tumor tissue to radiotherapy is critical for improving patient outcomes. The response to ionizing radiation is regulated by both cell-intrinsic and -extrinsic mechanisms. In particular, the tumor microenvironment is known to promote radioresistance in GBM. Therefore, model systems used to test radiosensitizing agents need to take into account the tumor microenvironment. We recently showed that GBM explant cultures represent an adaptable ex vivo platform for rapid and personalized testing of radiosensitizers. These explants preserve the cellular composition and tissue architecture of parental patient tumors and therefore capture the microenvironmental context that critically determines the response to radiotherapy. This chapter focuses on the detailed protocol for testing candidate radiosensitizing agents in GBM explants.

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

Simulation tools for developing policies for complex systems: modeling the health and safety of refugee communities.

PubMed

Anderson, James; Chaturvedi, Alok; Cibulskis, Mike

2007-12-01

The U.S. Committee for Refugees and Immigrants estimated that there were over 33 million refugees and internally displaced persons (IDPs) in the world at the beginning of 2005. IDP/Refugee communities behave in complex ways making it difficult to make policy decisions regarding the provision of humanitarian aid and health and safety. This paper reports the construction of an agent-based model that has been used to study humanitarian assistance policies executed by governments and NGOs that provide for the health and safety of refugee communities. Agent-based modeling (ABM) was chosen because the more widely used alternatives impose unrealistic restrictions and assumptions on the system being modeled and primarily apply to aggregate data. We created intelligent agents representing institutions, organizations, individuals, infrastructure, and governments and analyzed the resulting interactions and emergent behavior using a Central Composite Design of Experiments with five factors. The resulting model allows policy makers and analysts to create scenarios, to make rapid changes in parameters, and provides a test bed for concepts and strategies. Policies can be examined to see how refugee communities might respond to alternative courses of action and how these actions are likely to affect the health and well-being of the community.

Endogenous time-varying risk aversion and asset returns.

PubMed

Berardi, Michele

2016-01-01

Stylized facts about statistical properties for short horizon returns in financial markets have been identified in the literature, but a satisfactory understanding for their manifestation is yet to be achieved. In this work, we show that a simple asset pricing model with representative agent is able to generate time series of returns that replicate such stylized facts if the risk aversion coefficient is allowed to change endogenously over time in response to unexpected excess returns under evolutionary forces. The same model, under constant risk aversion, would instead generate returns that are essentially Gaussian. We conclude that an endogenous time-varying risk aversion represents a very parsimonious way to make the model match real data on key statistical properties, and therefore deserves careful consideration from economists and practitioners alike.

Linking Cognitive and Social Aspects of Sound Change Using Agent-Based Modeling.

PubMed

Harrington, Jonathan; Kleber, Felicitas; Reubold, Ulrich; Schiel, Florian; Stevens, Mary

2018-03-26

The paper defines the core components of an interactive-phonetic (IP) sound change model. The starting point for the IP-model is that a phonological category is often skewed phonetically in a certain direction by the production and perception of speech. A prediction of the model is that sound change is likely to come about as a result of perceiving phonetic variants in the direction of the skew and at the probabilistic edge of the listener's phonological category. The results of agent-based computational simulations applied to the sound change in progress, /u/-fronting in Standard Southern British, were consistent with this hypothesis. The model was extended to sound changes involving splits and mergers by using the interaction between the agents to drive the phonological reclassification of perceived speech signals. The simulations showed no evidence of any acoustic change when this extended model was applied to Australian English data in which /s/ has been shown to retract due to coarticulation in /str/ clusters. Some agents nevertheless varied in their phonological categorizations during interaction between /str/ and /ʃtr/: This vacillation may represent the potential for sound change to occur. The general conclusion is that many types of sound change are the outcome of how phonetic distributions are oriented with respect to each other, their association to phonological classes, and how these types of information vary between speakers that happen to interact with each other. Copyright © 2018 The Authors. Topics in Cognitive Science published by Wiley Periodicals, Inc. on behalf of Cognitive Science Society.

Social dynamics of science.

PubMed

Sun, Xiaoling; Kaur, Jasleen; Milojević, Staša; Flammini, Alessandro; Menczer, Filippo

2013-01-01

The birth and decline of disciplines are critical to science and society. How do scientific disciplines emerge? No quantitative model to date allows us to validate competing theories on the different roles of endogenous processes, such as social collaborations, and exogenous events, such as scientific discoveries. Here we propose an agent-based model in which the evolution of disciplines is guided mainly by social interactions among agents representing scientists. Disciplines emerge from splitting and merging of social communities in a collaboration network. We find that this social model can account for a number of stylized facts about the relationships between disciplines, scholars, and publications. These results provide strong quantitative support for the key role of social interactions in shaping the dynamics of science. While several "science of science" theories exist, this is the first account for the emergence of disciplines that is validated on the basis of empirical data.

Social Dynamics of Science

PubMed Central

Sun, Xiaoling; Kaur, Jasleen; Milojević, Staša; Flammini, Alessandro; Menczer, Filippo

2013-01-01

The birth and decline of disciplines are critical to science and society. How do scientific disciplines emerge? No quantitative model to date allows us to validate competing theories on the different roles of endogenous processes, such as social collaborations, and exogenous events, such as scientific discoveries. Here we propose an agent-based model in which the evolution of disciplines is guided mainly by social interactions among agents representing scientists. Disciplines emerge from splitting and merging of social communities in a collaboration network. We find that this social model can account for a number of stylized facts about the relationships between disciplines, scholars, and publications. These results provide strong quantitative support for the key role of social interactions in shaping the dynamics of science. While several “science of science” theories exist, this is the first account for the emergence of disciplines that is validated on the basis of empirical data. PMID:23323212

Social Dynamics of Science

NASA Astrophysics Data System (ADS)

Sun, Xiaoling; Kaur, Jasleen; Milojević, Staša; Flammini, Alessandro; Menczer, Filippo

2013-01-01

The birth and decline of disciplines are critical to science and society. How do scientific disciplines emerge? No quantitative model to date allows us to validate competing theories on the different roles of endogenous processes, such as social collaborations, and exogenous events, such as scientific discoveries. Here we propose an agent-based model in which the evolution of disciplines is guided mainly by social interactions among agents representing scientists. Disciplines emerge from splitting and merging of social communities in a collaboration network. We find that this social model can account for a number of stylized facts about the relationships between disciplines, scholars, and publications. These results provide strong quantitative support for the key role of social interactions in shaping the dynamics of science. While several ``science of science'' theories exist, this is the first account for the emergence of disciplines that is validated on the basis of empirical data.

Promiscuity and the evolution of sexual transmitted diseases

NASA Astrophysics Data System (ADS)

Gonçalves, Sebastián; Kuperman, Marcelo; Ferreira da Costa Gomes, Marcelo

2003-09-01

We study the relation between different social behaviors and the onset of epidemics in a model for the dynamics of sexual transmitted diseases. The model considers the society as a system of individual sexuated agents that can be organized in couples and interact with each other. The different social behaviors are incorporated assigning what we call a promiscuity value to each individual agent. The individual promiscuity is taken from a distribution and represents the daily probability of going out to look for a sexual partner, abandoning its eventual mate. In terms of this parameter we find a threshold for the epidemic which is much lower than the classical SIR model prediction, i.e., R0 (basic reproductive number)=1. Different forms for the distribution of the population promiscuity are considered showing that the threshold is weakly sensitive to them. We study the homosexual and the heterosexual case as well.

Interplay between social debate and propaganda in an opinion formation model

NASA Astrophysics Data System (ADS)

Gimenez, M. C.; Revelli, J. A.; Lama, M. S. de la; Lopez, J. M.; Wio, H. S.

2013-01-01

We introduce a simple model of opinion dynamics in which a two-state agent modified Sznajd model evolves due to the simultaneous action of stochastic driving and a periodic signal. The stochastic effect mimics a social temperature, so the agents may adopt decisions in support for or against some opinion or position, according to a modified Sznajd rule with a varying probability. The external force represents a simplified picture by which society feels the influence of the external effects of propaganda. By means of Monte Carlo simulations we have shown the dynamical interplay between the social condition or mood and the external influence, finding a stochastic resonance-like phenomenon when we depict the noise-to-signal ratio as a function of the social temperature. In addition, we have also studied the effects of the system size and the external signal strength on the opinion formation dynamics.

Multi-Agent simulation of generation capacity expansion decisions.

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

Botterud, A.; Mahalik, M.; Conzelmann, G.

2008-01-01

In this paper, we use a multi-agent simulation model, EMCAS, to analyze generation expansion in the Iberian electricity market. The expansion model simulates generation investment decisions of decentralized generating companies (GenCos) interacting in a complex, multidimensional environment. A probabilistic dispatch algorithm calculates prices and profits for new candidate units in different future states of the system. Uncertainties in future load, hydropower conditions, and competitorspsila actions are represented in a scenario tree, and decision analysis is used to identify the optimal expansion decision for each individual GenCo. We run the model using detailed data for the Iberian market. In a scenariomore » analysis, we look at the impact of market design variables, such as the energy price cap and carbon emission prices. We also analyze how market concentration and GenCospsila risk preferences influence the timing and choice of new generating capacity.« less

Experimental Evaluation of Suitability of Selected Multi-Criteria Decision-Making Methods for Large-Scale Agent-Based Simulations

PubMed Central

2016-01-01

Multi-criteria decision-making (MCDM) can be formally implemented by various methods. This study compares suitability of four selected MCDM methods, namely WPM, TOPSIS, VIKOR, and PROMETHEE, for future applications in agent-based computational economic (ACE) models of larger scale (i.e., over 10 000 agents in one geographical region). These four MCDM methods were selected according to their appropriateness for computational processing in ACE applications. Tests of the selected methods were conducted on four hardware configurations. For each method, 100 tests were performed, which represented one testing iteration. With four testing iterations conducted on each hardware setting and separated testing of all configurations with the–server parameter de/activated, altogether, 12800 data points were collected and consequently analyzed. An illustrational decision-making scenario was used which allows the mutual comparison of all of the selected decision making methods. Our test results suggest that although all methods are convenient and can be used in practice, the VIKOR method accomplished the tests with the best results and thus can be recommended as the most suitable for simulations of large-scale agent-based models. PMID:27806061

An integrative assessment of the commercial air transportation system via adaptive agents

NASA Astrophysics Data System (ADS)

Lim, Choon Giap

The overarching research objective is to address the tightly-coupled interactions between the demand-side and supply-side components of the United States Commercial Air Transportation System (CATS) in a time-variant environment. A system-of-system perspective is adopted, where the scope is extended beyond the National Airspace System (NAS) level to the National Transportation System (NTS) level to capture the intermodal and multimodal relationships between the NTS stakeholders. The Agent-Based Modeling and Simulation technique is employed where the NTS/NAS is treated as an integrated Multi-Agent System comprising of consumer and service provider agents, representing the demand-side and supply-side components respectively. Successful calibration and validation of both model components against the observable real world data resulted in a CATS simulation tool where the aviation demand is estimated from socioeconomic and demographic properties of the population instead of merely based on enplanement growth multipliers. This valuable achievement enabled a 20-year outlook simulation study to investigate the implications of a global fuel price hike on the airline industry and the U.S. CATS at large. Simulation outcomes revealed insights into the airline competitive behaviors and the subsequent responses from transportation consumers.

Model Error Budgets

NASA Technical Reports Server (NTRS)

Briggs, Hugh C.

2008-01-01

An error budget is a commonly used tool in design of complex aerospace systems. It represents system performance requirements in terms of allowable errors and flows these down through a hierarchical structure to lower assemblies and components. The requirements may simply be 'allocated' based upon heuristics or experience, or they may be designed through use of physics-based models. This paper presents a basis for developing an error budget for models of the system, as opposed to the system itself. The need for model error budgets arises when system models are a principle design agent as is increasingly more common for poorly testable high performance space systems.

Using the social structure of markets as a framework for analyzing vaccination debates: The case of emergency polio vaccination

PubMed Central

Connelly, Yaron; Ziv, Arnona; Goren, Uri; Tal, Orna; Kaplan, Giora; Velan, Baruch

2016-01-01

ABSTRACT The framework of the social structure of markets was used to analyze an online debate revolving around an emergency poliovirus vaccination campaign in Israel. Examination of a representative sample of 200 discussions revealed the activity of three parties: authoritative agents promoting vaccinations, alternative agents promoting anti-vaccination, both representing sellers, and the impartial agents, representing the customers—the general public deliberating whether to comply with vaccination or not. Both sellers interacted with consumers using mechanisms of luring and convincing. The authoritative agents conveyed their message by exhibiting professionalism, building trust and offering to share information. The alternative agents spread doubts and evoked negative emotions of distrust and fear. Among themselves, the alternative agents strived to discredit the authoritative agents, while the latter preferred to ignore the former. Content analysis of discussions conducted by the general public reveal reiteration of the messages conveyed by the sellers, implying that the transaction of pro and anti-vaccination ideas indeed took place. We suggest that the framework of the market as a social structure can be applied to the analysis of other vaccination debates, and thereby provide additional insights into vaccination polemics. PMID:27058586

Therapeutic Remyelination Strategies in a Novel Model of Multiple Sclerosis: Japanese Macaque Encephalomyelitis

DTIC Science & Technology

2012-05-01

determined and compared to simian and human herpesvirus genomes representing alpha-herpesvi- ruses, beta- herpesviruses and gamma-1 and gamma-2 her...report the isolation of a previously unknown herpesvirus , JMRV, isolated from acute JME TABLE 2: Clustal W Alignment of JMRV Genome with Select Simian and...to use this model in pre-clinical screens of novel agents with the potential to inhibit MS attacks and to promote remyelination and regeneration

Multiagent distributed watershed management

NASA Astrophysics Data System (ADS)

Giuliani, M.; Castelletti, A.; Amigoni, F.; Cai, X.

2012-04-01

Deregulation and democratization of water along with increasing environmental awareness are challenging integrated water resources planning and management worldwide. The traditional centralized approach to water management, as described in much of water resources literature, is often unfeasible in most of the modern social and institutional contexts. Thus it should be reconsidered from a more realistic and distributed perspective, in order to account for the presence of multiple and often independent Decision Makers (DMs) and many conflicting stakeholders. Game theory based approaches are often used to study these situations of conflict (Madani, 2010), but they are limited to a descriptive perspective. Multiagent systems (see Wooldridge, 2009), instead, seem to be a more suitable paradigm because they naturally allow to represent a set of self-interested agents (DMs and/or stakeholders) acting in a distributed decision process at the agent level, resulting in a promising compromise alternative between the ideal centralized solution and the actual uncoordinated practices. Casting a water management problem in a multiagent framework allows to exploit the techniques and methods that are already available in this field for solving distributed optimization problems. In particular, in Distributed Constraint Satisfaction Problems (DCSP, see Yokoo et al., 2000), each agent controls some variables according to his own utility function but has to satisfy inter-agent constraints; while in Distributed Constraint Optimization Problems (DCOP, see Modi et al., 2005), the problem is generalized by introducing a global objective function to be optimized that requires a coordination mechanism between the agents. In this work, we apply a DCSP-DCOP based approach to model a steady state hypothetical watershed management problem (Yang et al., 2009), involving several active human agents (i.e. agents who make decisions) and reactive ecological agents (i.e. agents representing environmental interests). Different scenarios of distributed management are simulated, i.e. a situation where all the agents act independently, a situation in which a global coordination takes place and in-between solutions. The solutions are compared with the ones presented in Yang et al. (2009), aiming to present more general multiagent approaches to solve distributed management problems.

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.

Evolution of wealth in a non-conservative economy driven by local Nash equilibria.

PubMed

Degond, Pierre; Liu, Jian-Guo; Ringhofer, Christian

2014-11-13

We develop a model for the evolution of wealth in a non-conservative economic environment, extending a theory developed in Degond et al. (2014 J. Stat. Phys. 154, 751-780 (doi:10.1007/s10955-013-0888-4)). The model considers a system of rational agents interacting in a game-theoretical framework. This evolution drives the dynamics of the agents in both wealth and economic configuration variables. The cost function is chosen to represent a risk-averse strategy of each agent. That is, the agent is more likely to interact with the market, the more predictable the market, and therefore the smaller its individual risk. This yields a kinetic equation for an effective single particle agent density with a Nash equilibrium serving as the local thermodynamic equilibrium. We consider a regime of scale separation where the large-scale dynamics is given by a hydrodynamic closure with this local equilibrium. A class of generalized collision invariants is developed to overcome the difficulty of the non-conservative property in the hydrodynamic closure derivation of the large-scale dynamics for the evolution of wealth distribution. The result is a system of gas dynamics-type equations for the density and average wealth of the agents on large scales. We recover the inverse Gamma distribution, which has been previously considered in the literature, as a local equilibrium for particular choices of the cost function. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

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.

Pathobiology and management of laboratory rodents administered CDC category A agents.

PubMed

He, Yongqun; Rush, Howard G; Liepman, Rachel S; Xiang, Zuoshuang; Colby, Lesley A

2007-02-01

The Centers for Disease Control and Prevention Category A infectious agents include Bacillus anthracis (anthrax), Clostridium botulinum toxin (botulism), Yersinia pestis (plague), variola major virus (smallpox), Francisella tularensis (tularemia), and the filoviruses and arenaviruses that induce viral hemorrhagic fevers. These agents are regarded as having the greatest potential for adverse impact on public health and therefore are a focus of renewed attention in infectious disease research. Frequently rodent models are used to study the pathobiology of these agents. Although much is known regarding naturally occurring infections in humans, less is documented on the sources of exposures and potential risks of infection to researchers and animal care personnel after the administration of these hazardous substances to laboratory animals. Failure to appropriately manage the animals can result both in the creation of workplace hazards if human exposures occur and in disruption of the research if unintended animal exposures occur. Here we review representative Category A agents, with a focus on comparing the biologic effects in naturally infected humans and rodent models and on considerations specific to the management of infected rodent subjects. The information reviewed for each agent has been curated manually and stored in a unique Internet-based database system called HazARD (Hazards in Animal Research Database, http://helab.bioinformatics.med.umich.edu/hazard/) that is designed to assist researchers, administrators, safety officials, Institutional Biosafety Committees, and veterinary personnel seeking information on the management of risks associated with animal studies involving hazardous substances.

A complex systems approach to evaluate HIV prevention in metropolitan areas: preliminary implications for combination intervention strategies.

PubMed

Marshall, Brandon D L; Paczkowski, Magdalena M; Seemann, Lars; Tempalski, Barbara; Pouget, Enrique R; Galea, Sandro; Friedman, Samuel R

2012-01-01

HIV transmission among injecting and non-injecting drug users (IDU, NIDU) is a significant public health problem. Continuing propagation in endemic settings and emerging regional outbreaks have indicated the need for comprehensive and coordinated HIV prevention. We describe the development of a conceptual framework and calibration of an agent-based model (ABM) to examine how combinations of interventions may reduce and potentially eliminate HIV transmission among drug-using populations. A multidisciplinary team of researchers from epidemiology, sociology, geography, and mathematics developed a conceptual framework based on prior ethnographic and epidemiologic research. An ABM was constructed and calibrated through an iterative design and verification process. In the model, "agents" represent IDU, NIDU, and non-drug users who interact with each other and within risk networks, engaging in sexual and, for IDUs, injection-related risk behavior over time. Agents also interact with simulated HIV prevention interventions (e.g., syringe exchange programs, substance abuse treatment, HIV testing) and initiate antiretroviral treatment (ART) in a stochastic manner. The model was constructed to represent the New York metropolitan statistical area (MSA) population, and calibrated by comparing output trajectories for various outcomes (e.g., IDU/NIDU prevalence, HIV prevalence and incidence) against previously validated MSA-level data. The model closely approximated HIV trajectories in IDU and NIDU observed in New York City between 1992 and 2002, including a linear decrease in HIV prevalence among IDUs. Exploratory results are consistent with empirical studies demonstrating that the effectiveness of a combination of interventions, including syringe exchange expansion and ART provision, dramatically reduced HIV prevalence among IDUs during this time period. Complex systems models of adaptive HIV transmission dynamics can be used to identify potential collective benefits of hypothetical combination prevention interventions. Future work will seek to inform novel strategies that may lead to more effective and equitable HIV prevention strategies for drug-using populations.

Case studies, cross-site comparisons, and the challenge of generalization: comparing agent-based models of land-use change in frontier regions

PubMed Central

Parker, Dawn C.; Entwisle, Barbara; Rindfuss, Ronald R.; Vanwey, Leah K.; Manson, Steven M.; Moran, Emilio; An, Li; Deadman, Peter; Evans, Tom P.; Linderman, Marc; Rizi, S. Mohammad Mussavi; Malanson, George

2009-01-01

Cross-site comparisons of case studies have been identified as an important priority by the land-use science community. From an empirical perspective, such comparisons potentially allow generalizations that may contribute to production of global-scale land-use and land-cover change projections. From a theoretical perspective, such comparisons can inform development of a theory of land-use science by identifying potential hypotheses and supporting or refuting evidence. This paper undertakes a structured comparison of four case studies of land-use change in frontier regions that follow an agent-based modeling approach. Our hypothesis is that each case study represents a particular manifestation of a common process. Given differences in initial conditions among sites and the time at which the process is observed, actual mechanisms and outcomes are anticipated to differ substantially between sites. Our goal is to reveal both commonalities and differences among research sites, model implementations, and ultimately, conclusions derived from the modeling process. PMID:19960107

Case studies, cross-site comparisons, and the challenge of generalization: comparing agent-based models of land-use change in frontier regions.

PubMed

Parker, Dawn C; Entwisle, Barbara; Rindfuss, Ronald R; Vanwey, Leah K; Manson, Steven M; Moran, Emilio; An, Li; Deadman, Peter; Evans, Tom P; Linderman, Marc; Rizi, S Mohammad Mussavi; Malanson, George

2008-01-01

Cross-site comparisons of case studies have been identified as an important priority by the land-use science community. From an empirical perspective, such comparisons potentially allow generalizations that may contribute to production of global-scale land-use and land-cover change projections. From a theoretical perspective, such comparisons can inform development of a theory of land-use science by identifying potential hypotheses and supporting or refuting evidence. This paper undertakes a structured comparison of four case studies of land-use change in frontier regions that follow an agent-based modeling approach. Our hypothesis is that each case study represents a particular manifestation of a common process. Given differences in initial conditions among sites and the time at which the process is observed, actual mechanisms and outcomes are anticipated to differ substantially between sites. Our goal is to reveal both commonalities and differences among research sites, model implementations, and ultimately, conclusions derived from the modeling process.

Prioritizing therapeutic targets using patient-derived xenograft models

PubMed Central

Lodhia, K.A; Hadley, A; Haluska, P; Scott, C.L

2015-01-01

Effective systemic treatment of cancer relies on the delivery of agents with optimal therapeutic potential. The molecular age of medicine has provided genomic tools that can identify a large number of potential therapeutic targets in individual patients, heralding the promise of personalized treatment. However, determining which potential targets actually drive tumor growth and should be prioritized for therapy is challenging. Indeed, reliable molecular matches of target and therapeutic agent have been stringently validated in the clinic for only a small number of targets. Patient-derived xenografts (PDX) are tumor models developed in immunocompromised mice using tumor procured directly from the patient. As patient surrogates, PDX models represent a powerful tool for addressing individualized therapy. Challenges include humanizing the immune system of PDX models and ensuring high quality molecular annotation, in order to maximise insights for the clinic. Importantly, PDX can be sampled repeatedly and in parallel, to reveal clonal evolution, which may predict mechanisms of drug resistance and inform therapeutic strategy design. PMID:25783201

Simulating Alternative Approaches to Addressing Fiscal Resource Tensions and Quality in U.S. Public Higher Education

ERIC Educational Resources Information Center

Roebber, Paul J.; Meadows, G. Richard

2012-01-01

Severe fiscal tensions threaten U.S. public higher education. Many policy solutions have been suggested, but it is difficult to subject these qualitative ideas to rigorous empirical evaluation. In this work, we employ an agent-based model of a representative state-funded public university system (including a flagship campus, an urban campus, and…

A Biologically Inspired Cooperative Multi-Robot Control Architecture

NASA Technical Reports Server (NTRS)

Howsman, Tom; Craft, Mike; ONeil, Daniel; Howell, Joe T. (Technical Monitor)

2002-01-01

A prototype cooperative multi-robot control architecture suitable for the eventual construction of large space structures has been developed. In nature, there are numerous examples of complex architectures constructed by relatively simple insects, such as termites and wasps, which cooperatively assemble their nests. The prototype control architecture emulates this biological model. Actions of each of the autonomous robotic construction agents are only indirectly coordinated, thus mimicking the distributed construction processes of various social insects. The robotic construction agents perform their primary duties stigmergically i.e., without direct inter-agent communication and without a preprogrammed global blueprint of the final design. Communication and coordination between individual agents occurs indirectly through the sensed modifications that each agent makes to the structure. The global stigmergic building algorithm prototyped during the initial research assumes that the robotic builders only perceive the current state of the structure under construction. Simulation studies have established that an idealized form of the proposed architecture was indeed capable of producing representative large space structures with autonomous robots. This paper will explore the construction simulations in order to illustrate the multi-robot control architecture.

A Stigmergic Cooperative Multi-Robot Control Architecture

NASA Technical Reports Server (NTRS)

Howsman, Thomas G.; O'Neil, Daniel; Craft, Michael A.

2004-01-01

In nature, there are numerous examples of complex architectures constructed by relatively simple insects, such as termites and wasps, which cooperatively assemble their nests. A prototype cooperative multi-robot control architecture which may be suitable for the eventual construction of large space structures has been developed which emulates this biological model. Actions of each of the autonomous robotic construction agents are only indirectly coordinated, thus mimicking the distributed construction processes of various social insects. The robotic construction agents perform their primary duties stigmergically, i.e., without direct inter-agent communication and without a preprogrammed global blueprint of the final design. Communication and coordination between individual agents occurs indirectly through the sensed modifications that each agent makes to the structure. The global stigmergic building algorithm prototyped during the initial research assumes that the robotic builders only perceive the current state of the structure under construction. Simulation studies have established that an idealized form of the proposed architecture was indeed capable of producing representative large space structures with autonomous robots. This paper will explore the construction simulations in order to illustrate the multi-robot control architecture.

Multi-language naming game

NASA Astrophysics Data System (ADS)

Zhou, Jianfeng; Lou, Yang; Chen, Guanrong; Tang, Wallace K. S.

2018-04-01

Naming game is a simulation-based experiment used to study the evolution of languages. The conventional naming game focuses on a single language. In this paper, a novel naming game model named multi-language naming game (MLNG) is proposed, where the agents are different-language speakers who cannot communicate with each other without a translator (interpreter) in between. The MLNG model is general, capable of managing k different languages with k ≥ 2. For illustration, the paper only discusses the MLNG with two different languages, and studies five representative network topologies, namely random-graph, WS small-world, NW small-world, scale-free, and random-triangle topologies. Simulation and analysis results both show that: 1) using the network features and based on the proportion of translators the probability of establishing a conversation between two or three agents can be theoretically estimated; 2) the relationship between the convergence speed and the proportion of translators has a power-law-like relation; 3) different agents require different memory sizes, thus a local memory allocation rule is recommended for saving memory resources. The new model and new findings should be useful for further studies of naming games and for better understanding of languages evolution from a dynamical network perspective.

Establishment and characterization of a platinum- and paclitaxel-resistant high grade serous ovarian carcinoma cell line.

PubMed

Teng, Pang-Ning; Bateman, Nicholas W; Wang, Guisong; Litzi, Tracy; Blanton, Brian E; Hood, Brian L; Conrads, Kelly A; Ao, Wei; Oliver, Kate E; Darcy, Kathleen M; McGuire, William P; Paz, Keren; Sidransky, David; Hamilton, Chad A; Maxwell, G Larry; Conrads, Thomas P

2017-07-01

High grade serous ovarian cancer (HGSOC) patients have a high recurrence rate after surgery and adjuvant chemotherapy due to inherent or acquired drug resistance. Cell lines derived from HGSOC tumors that are resistant to chemotherapeutic agents represent useful pre-clinical models for drug discovery. Here, we describe establishment of a human ovarian carcinoma cell line, which we term WHIRC01, from a patient-derived mouse xenograft established from a chemorefractory HGSOC patient who did not respond to carboplatin and paclitaxel therapy. This newly derived cell line is platinum- and paclitaxel-resistant with cisplatin, carboplatin, and paclitaxel half-maximal lethal doses of 15, 130, and 20 µM, respectively. Molecular characterization of this cell line was performed using targeted DNA exome sequencing, transcriptomics (RNA-seq), and mass spectrometry-based proteomic analyses. Results from exomic sequencing revealed mutations in TP53 consistent with HGSOC. Transcriptomic and proteomic analyses of WHIRC01 showed high level of alpha-enolase and vimentin, which are associated with cell migration and epithelial-mesenchymal transition. WHIRC01 represents a chemorefractory human HGSOC cell line model with a comprehensive molecular profile to aid future investigations of drug resistance mechanisms and screening of chemotherapeutic agents.

[Alkylating agents].

PubMed

Pourquier, Philippe

2011-11-01

With the approval of mechlorethamine by the FDA in 1949 for the treatment of hematologic malignancies, alkylating agents are the oldest class of anticancer agents. Even though their clinical use is far beyond the use of new targeted therapies, they still occupy a major place in specific indications and sometimes represent the unique option for the treatment of refractory diseases. Here, we are reviewing the major classes of alkylating agents and their mechanism of action, with a particular emphasis for the new generations of alkylating agents. As for most of the chemotherapeutic agents used in the clinic, these compounds are derived from natural sources. With a complex but original mechanism of action, they represent new interesting alternatives for the clinicians, especially for tumors that are resistant to conventional DNA damaging agents. We also briefly describe the different strategies that have been or are currently developed to potentiate the use of classical alkylating agents, especially the inhibition of pathways that are involved in the repair of DNA lesions induced by these agents. In this line, the development of PARP inhibitors is a striking example of the recent regain of interest towards the "old" alkylating agents.

13 CFR 114.108 - What if my claim is approved?

Code of Federal Regulations, 2010 CFR

2010-01-01

... agent or legal representative the forms necessary to indicate satisfaction of your claim and your acceptance of the payment. Acceptance by you, your agent or your legal representative of any award, compromise or settlement releases all your claims against the United States under the Federal Tort Claims Act...

40 CFR 10.8 - Release.

Code of Federal Regulations, 2010 CFR

2010-07-01

... CLAIMS ACT Procedures § 10.8 Release. Acceptance by the claimant, his agent or legal representative of... 40 Protection of Environment 1 2010-07-01 2010-07-01 false Release. 10.8 Section 10.8 Protection... agent or legal representative and any other person on whose behalf or for whose benefit the claim has...

Using Semantic Components to Represent Dynamics of an Interdisciplinary Healthcare Team in a Multi-Agent Decision Support System.

PubMed

Wilk, Szymon; Kezadri-Hamiaz, Mounira; Rosu, Daniela; Kuziemsky, Craig; Michalowski, Wojtek; Amyot, Daniel; Carrier, Marc

2016-02-01

In healthcare organizations, clinical workflows are executed by interdisciplinary healthcare teams (IHTs) that operate in ways that are difficult to manage. Responding to a need to support such teams, we designed and developed the MET4 multi-agent system that allows IHTs to manage patients according to presentation-specific clinical workflows. In this paper, we describe a significant extension of the MET4 system that allows for supporting rich team dynamics (understood as team formation, management and task-practitioner allocation), including selection and maintenance of the most responsible physician and more complex rules of selecting practitioners for the workflow tasks. In order to develop this extension, we introduced three semantic components: (1) a revised ontology describing concepts and relations pertinent to IHTs, workflows, and managed patients, (2) a set of behavioral rules describing the team dynamics, and (3) an instance base that stores facts corresponding to instances of concepts from the ontology and to relations between these instances. The semantic components are represented in first-order logic and they can be automatically processed using theorem proving and model finding techniques. We employ these techniques to find models that correspond to specific decisions controlling the dynamics of IHT. In the paper, we present the design of extended MET4 with a special focus on the new semantic components. We then describe its proof-of-concept implementation using the WADE multi-agent platform and the Z3 solver (theorem prover/model finder). We illustrate the main ideas discussed in the paper with a clinical scenario of an IHT managing a patient with chronic kidney disease.

Dynamically analyzing cell interactions in biological environments using multiagent social learning framework.

PubMed

Zhang, Chengwei; Li, Xiaohong; Li, Shuxin; Feng, Zhiyong

2017-09-20

Biological environment is uncertain and its dynamic is similar to the multiagent environment, thus the research results of the multiagent system area can provide valuable insights to the understanding of biology and are of great significance for the study of biology. Learning in a multiagent environment is highly dynamic since the environment is not stationary anymore and each agent's behavior changes adaptively in response to other coexisting learners, and vice versa. The dynamics becomes more unpredictable when we move from fixed-agent interaction environments to multiagent social learning framework. Analytical understanding of the underlying dynamics is important and challenging. In this work, we present a social learning framework with homogeneous learners (e.g., Policy Hill Climbing (PHC) learners), and model the behavior of players in the social learning framework as a hybrid dynamical system. By analyzing the dynamical system, we obtain some conditions about convergence or non-convergence. We experimentally verify the predictive power of our model using a number of representative games. Experimental results confirm the theoretical analysis. Under multiagent social learning framework, we modeled the behavior of agent in biologic environment, and theoretically analyzed the dynamics of the model. We present some sufficient conditions about convergence or non-convergence and prove them theoretically. It can be used to predict the convergence of the system.

Development of Anti-Virulence Approaches for Candidiasis via a Novel Series of Small-Molecule Inhibitors of Candida albicans Filamentation

PubMed Central

Romo, Jesus A.; Pierce, Christopher G.; Chaturvedi, Ashok K.; Lazzell, Anna L.; McHardy, Stanton F.

2017-01-01

ABSTRACT Candida albicans remains the main etiologic agent of candidiasis, the most common fungal infection and now the third most frequent infection in U.S. hospitals. The scarcity of antifungal agents and their limited efficacy contribute to the unacceptably high morbidity and mortality rates associated with these infections. The yeast-to-hypha transition represents the main virulence factor associated with the pathogenesis of C. albicans infections. In addition, filamentation is pivotal for robust biofilm development, which represents another major virulence factor for candidiasis and further complicates treatment. Targeting pathogenic mechanisms rather than growth represents an attractive yet clinically unexploited approach in the development of novel antifungal agents. Here, we performed large-scale phenotypic screening assays with 30,000 drug-like small-molecule compounds within ChemBridge’s DIVERSet chemical library in order to identify small-molecule inhibitors of C. albicans filamentation, and our efforts led to the identification of a novel series of bioactive compounds with a common biaryl amide core structure. The leading compound of this series, N-[3-(allyloxy)-phenyl]-4-methoxybenzamide, was able to prevent filamentation under all liquid and solid medium conditions tested, suggesting that it impacts a common core component of the cellular machinery that mediates hypha formation under different environmental conditions. In addition to filamentation, this compound also inhibited C. albicans biofilm formation. This leading compound also demonstrated in vivo activity in clinically relevant murine models of invasive and oral candidiasis. Overall, our results indicate that compounds within this series represent promising candidates for the development of novel anti-virulence approaches to combat C. albicans infections. PMID:29208749

The influence of persuasion in opinion formation and polarization

NASA Astrophysics Data System (ADS)

La Rocca, C. E.; Braunstein, L. A.; Vazquez, F.

2014-05-01

We present a model that explores the influence of persuasion in a population of agents with positive and negative opinion orientations. The opinion of each agent is represented by an integer number k that expresses its level of agreement on a given issue, from totally against k=-M to totally in favor k = M. Same-orientation agents persuade each other with probability p, becoming more extreme, while opposite-orientation agents become more moderate as they reach a compromise with probability q. The population initially evolves to (a) a polarized state for r=p/q\\gt 1 , where opinions' distribution is peaked at the extreme values k=+/- M , or (b) a centralized state for r < 1, with most opinions around k=+/- 1 . When r \\gg 1 , polarization lasts for a time that diverges as r^M \\ln N , where N is the population's size. Finally, an extremist consensus (k = M or -M ) is reached in a time that scales as r^{-1} for r \\ll 1 .

4-aminoquinoline analogues and its platinum (II) complexes as antimalarial agents.

PubMed

de Souza, Nicolli Bellotti; Carmo, Arturene M L; Lagatta, Davi C; Alves, Márcio José Martins; Fontes, Ana Paula Soares; Coimbra, Elaine Soares; da Silva, Adilson David; Abramo, Clarice

2011-07-01

The high incidence of malaria and drug-resistant strains of Plasmodium have turned this disease into a problem of major health importance. One of the approaches used to control it is to search for new antimalarial agents, such as quinoline derivates. This class of compounds composes a broad group of antimalarial agents, which are largely employed, and inhibits the formation of β-haematin (malaria pigment), which is lethal to the parasite. More specifically, 4-aminoquinoline derivates represent potential sources of antimalarials, as the example of chloroquine, the most used antimalarial worldwide. In order to assess antimalarial activity, 12 4-aminoquinoline derived drugs were obtained and some of these derivatives were used to obtain platinum complexes platinum (II). These compounds were tested in vivo in a murine model and revealed remarkable inhibition of parasite multiplication values, whose majority ranged from 50 to 80%. In addition they were not cytotoxic. Thus, they may be object of further research for new antimalarial agents. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

Consensus in evolving networks of mobile agents

NASA Astrophysics Data System (ADS)

Baronchelli, Andrea; Díaz-Guilera, Albert

2012-02-01

Populations of mobile and communicating agents describe a vast array of technological and natural systems, ranging from sensor networks to animal groups. Here, we investigate how a group-level agreement may emerge in the continuously evolving networks defined by the local interactions of the moving individuals. We adopt a general scheme of motion in two dimensions and we let the individuals interact through the minimal naming game, a prototypical scheme to investigate social consensus. We distinguish different regimes of convergence determined by the emission range of the agents and by their mobility, and we identify the corresponding scaling behaviors of the consensus time. In the same way, we rationalize also the behavior of the maximum memory used during the convergence process, which determines the minimum cognitive/storage capacity needed by the individuals. Overall, we believe that the simple and general model presented in this talk can represent a helpful reference for a better understanding of the behavior of populations of mobile agents.

Consensus in networks of mobile communicating agents

NASA Astrophysics Data System (ADS)

Baronchelli, Andrea; Díaz-Guilera, Albert

2012-01-01

Populations of mobile and communicating agents describe a vast array of technological and natural systems, ranging from sensor networks to animal groups. Here, we investigate how a group-level agreement may emerge in the continuously evolving network defined by the local interactions of the moving individuals. We adopt a general scheme of motion in two dimensions and we let the individuals interact through the minimal naming game, a prototypical scheme to investigate social consensus. We distinguish different regimes of convergence determined by the emission range of the agents and by their mobility, and we identify the corresponding scaling behaviors of the consensus time. In the same way, we rationalize also the behavior of the maximum memory used during the convergence process, which determines the minimum cognitive/storage capacity needed by the individuals. Overall, we believe that the simple and general model presented in this paper can represent a helpful reference for a better understanding of the behavior of populations of mobile agents.

Mapping Disturbance Dynamics in Wet Sclerophyll Forests Using Time Series Landsat

NASA Astrophysics Data System (ADS)

Haywood, A.; Verbesselt, J.; Baker, P. J.

2016-06-01

In this study, we characterised the temporal-spectral patterns associated with identifying acute-severity disturbances and low-severity disturbances between 1985 and 2011 with the objective to test whether different disturbance agents within these categories can be identified with annual Landsat time series data. We analysed a representative State forest within the Central Highlands which has been exposed to a range of disturbances over the last 30 years, including timber harvesting (clearfell, selective and thinning) and fire (wildfire and prescribed burning). We fitted spectral time series models to annual normal burn ratio (NBR) and Tasseled Cap Indices (TCI), from which we extracted a range of disturbance and recovery metrics. With these metrics, three hierarchical random forest models were trained to 1) distinguish acute-severity disturbances from low-severity disturbances; 2a) attribute the disturbance agents most likely within the acute-severity class; 2b) and attribute the disturbance agents most likely within the low-severity class. Disturbance types (acute severity and low-severity) were successfully mapped with an overall accuracy of 72.9 %, and the individual disturbance types were successfully attributed with overall accuracies ranging from 53.2 % to 64.3 %. Low-severity disturbance agents were successfully mapped with an overall accuracy of 80.2 %, and individual agents were successfully attributed with overall accuracies ranging from 25.5 % to 95.1. Acute-severity disturbance agents were successfully mapped with an overall accuracy of 95.4 %, and individual agents were successfully attributed with overall accuracies ranging from 94.2 % to 95.2 %. Spectral metrics describing the disturbance magnitude were more important for distinguishing the disturbance agents than the post-disturbance response slope. Spectral changes associated with planned burning disturbances had generally lower magnitudes than selective harvesting. This study demonstrates the potential of landsat time series mapping for fire and timber harvesting disturbances at the agent level and highlights the need for distinguishing between agents to fully capture their impacts on ecosystem processes.

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).

In Silico Investigations of the Anti-Catabolic Effects of Pamidronate and Denosumab on Multiple Myeloma-Induced Bone Disease

PubMed Central

Wang, Yan; Lin, Bo

2012-01-01

It is unclear whether the new anti-catabolic agent denosumab represents a viable alternative to the widely used anti-catabolic agent pamidronate in the treatment of Multiple Myeloma (MM)-induced bone disease. This lack of clarity primarily stems from the lack of sufficient clinical investigations, which are costly and time consuming. However, in silico investigations require less time and expense, suggesting that they may be a useful complement to traditional clinical investigations. In this paper, we aim to (i) develop integrated computational models that are suitable for investigating the effects of pamidronate and denosumab on MM-induced bone disease and (ii) evaluate the responses to pamidronate and denosumab treatments using these integrated models. To achieve these goals, pharmacokinetic models of pamidronate and denosumab are first developed and then calibrated and validated using different clinical datasets. Next, the integrated computational models are developed by incorporating the simulated transient concentrations of pamidronate and denosumab and simulations of their actions on the MM-bone compartment into the previously proposed MM-bone model. These integrated models are further calibrated and validated by different clinical datasets so that they are suitable to be applied to investigate the responses to the pamidronate and denosumab treatments. Finally, these responses are evaluated by quantifying the bone volume, bone turnover, and MM-cell density. This evaluation identifies four denosumab regimes that potentially produce an overall improved bone-related response compared with the recommended pamidronate regime. This in silico investigation supports the idea that denosumab represents an appropriate alternative to pamidronate in the treatment of MM-induced bone disease. PMID:23028650

Curiosity driven reinforcement learning for motion planning on humanoids

PubMed Central

Frank, Mikhail; Leitner, Jürgen; Stollenga, Marijn; Förster, Alexander; Schmidhuber, Jürgen

2014-01-01

Most previous work on artificial curiosity (AC) and intrinsic motivation focuses on basic concepts and theory. Experimental results are generally limited to toy scenarios, such as navigation in a simulated maze, or control of a simple mechanical system with one or two degrees of freedom. To study AC in a more realistic setting, we embody a curious agent in the complex iCub humanoid robot. Our novel reinforcement learning (RL) framework consists of a state-of-the-art, low-level, reactive control layer, which controls the iCub while respecting constraints, and a high-level curious agent, which explores the iCub's state-action space through information gain maximization, learning a world model from experience, controlling the actual iCub hardware in real-time. To the best of our knowledge, this is the first ever embodied, curious agent for real-time motion planning on a humanoid. We demonstrate that it can learn compact Markov models to represent large regions of the iCub's configuration space, and that the iCub explores intelligently, showing interest in its physical constraints as well as in objects it finds in its environment. PMID:24432001

Development of animal models and sandwich-ELISA tests to detect the allergenicity and antigenicity of fining agent residues in wines.

PubMed

Lifrani, Awatif; Dos Santos, Jacinthe; Dubarry, Michel; Rautureau, Michelle; Blachier, Francois; Tome, Daniel

2009-01-28

Food allergy can cause food-related anaphylaxis. Food allergen labeling is the principal means of protecting sensitized individuals. This motivated European Directive 2003/89 on the labeling of ingredients or additives that could trigger adverse reactions, which has been in effect since 2005. During this study, we developed animal models with allergy to ovalbumin, caseinate, and isinglass in order to be able to detect fining agent residues that could induce anaphylactic reactions in sensitized mice. The second aim of the study was to design sandwich ELISA tests specific to each fining agent in order to detect their residue antigenicity, both during wine processing and in commercially available bottled wines. Sensitized mice and sandwich ELISA methods were established to test a vast panel of wines. The results showed that although they were positive to our highly sensitive sandwich-ELISA tests, some commercially available wines are not allergenic in sensitized mice. Commercially available bottled wines made using standardized processes, fining, maturation, and filtration, do not therefore represent any risk of anaphylactic reactions in sensitized mice.

An Agent-Based Dynamic Model for Analysis of Distributed Space Exploration Architectures

NASA Astrophysics Data System (ADS)

Sindiy, Oleg V.; DeLaurentis, Daniel A.; Stein, William B.

2009-07-01

A range of complex challenges, but also potentially unique rewards, underlie the development of exploration architectures that use a distributed, dynamic network of resources across the solar system. From a methodological perspective, the prime challenge is to systematically model the evolution (and quantify comparative performance) of such architectures, under uncertainty, to effectively direct further study of specialized trajectories, spacecraft technologies, concept of operations, and resource allocation. A process model for System-of-Systems Engineering is used to define time-varying performance measures for comparative architecture analysis and identification of distinguishing patterns among interoperating systems. Agent-based modeling serves as the means to create a discrete-time simulation that generates dynamics for the study of architecture evolution. A Solar System Mobility Network proof-of-concept problem is introduced representing a set of longer-term, distributed exploration architectures. Options within this set revolve around deployment of human and robotic exploration and infrastructure assets, their organization, interoperability, and evolution, i.e., a system-of-systems. Agent-based simulations quantify relative payoffs for a fully distributed architecture (which can be significant over the long term), the latency period before they are manifest, and the up-front investment (which can be substantial compared to alternatives). Verification and sensitivity results provide further insight on development paths and indicate that the framework and simulation modeling approach may be useful in architectural design of other space exploration mass, energy, and information exchange settings.

25 CFR 88.2 - Employment by tribes or individual claimants.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 25 Indians 1 2012-04-01 2011-04-01 true Employment by tribes or individual claimants. 88.2 Section... ATTORNEYS AND AGENTS TO REPRESENT CLAIMANTS § 88.2 Employment by tribes or individual claimants. All such attorneys or agents seeking approval of their employment by Indian tribes or desiring to represent...

25 CFR 88.2 - Employment by tribes or individual claimants.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 25 Indians 1 2011-04-01 2011-04-01 false Employment by tribes or individual claimants. 88.2... ATTORNEYS AND AGENTS TO REPRESENT CLAIMANTS § 88.2 Employment by tribes or individual claimants. All such attorneys or agents seeking approval of their employment by Indian tribes or desiring to represent...

25 CFR 88.2 - Employment by tribes or individual claimants.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 25 Indians 1 2014-04-01 2014-04-01 false Employment by tribes or individual claimants. 88.2... ATTORNEYS AND AGENTS TO REPRESENT CLAIMANTS § 88.2 Employment by tribes or individual claimants. All such attorneys or agents seeking approval of their employment by Indian tribes or desiring to represent...

25 CFR 88.2 - Employment by tribes or individual claimants.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 25 Indians 1 2010-04-01 2010-04-01 false Employment by tribes or individual claimants. 88.2... ATTORNEYS AND AGENTS TO REPRESENT CLAIMANTS § 88.2 Employment by tribes or individual claimants. All such attorneys or agents seeking approval of their employment by Indian tribes or desiring to represent...

25 CFR 88.2 - Employment by tribes or individual claimants.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 25 Indians 1 2013-04-01 2013-04-01 false Employment by tribes or individual claimants. 88.2... ATTORNEYS AND AGENTS TO REPRESENT CLAIMANTS § 88.2 Employment by tribes or individual claimants. All such attorneys or agents seeking approval of their employment by Indian tribes or desiring to represent...

Report of the Subcommittee for Travel/Tourism of the Hospitality/Tourism/Recreation Technical Committee.

ERIC Educational Resources Information Center

Oregon State Dept. of Education, Salem. Div. of Vocational Education.

Written by a technical committee's industry representatives, state officials, and educators in Oregon, this document lists the skills and knowledge required by employees in travel and tourism occupations. The following occupations are considered: rental representative; service agent; travel agent; bus/tour/driver/guide/sightseeing leader; manager…

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.

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.

Small Molecule Inhibitors in Acute Myeloid Leukemia: From the Bench to the Clinic

PubMed Central

Al-Hussaini, Muneera; DiPersio, John F.

2014-01-01

Many patients with acute myeloid leukemia (AML) will eventually develop refractory or relapsed disease. In the absence of standard therapy for this population, there is currently an urgent unmet need for novel therapeutic agents. Targeted therapy with small molecule inhibitors (SMIs) represents a new therapeutic intervention that has been successful for the treatment of multiple tumors (e.g., gastrointestinal stromal tumors, chronic myelogenous leukemia). Hence, there has been great interest in generating selective small molecule inhibitors targeting critical pathways of proliferation and survival in AML. This review highlights a selective group of intriguing therapeutic agents and their presumed targets in both preclinical models and in early human clinical trials. PMID:25025370

New 1-indanone thiosemicarbazone derivatives active against BVDV.

PubMed

Finkielsztein, Liliana M; Castro, Eliana F; Fabián, Lucas E; Moltrasio, Graciela Y; Campos, Rodolfo H; Cavallaro, Lucía V; Moglioni, Albertina G

2008-08-01

Identification of new therapeutic agents for the treatment of viral diseases represents an area of active investigation. In an effort to develop new antiviral compounds, a series of 1-indanone thiosemicarbazone derivatives were synthesized. These derivatives were structurally characterized using several spectroscopic techniques and evaluated against bovine viral diarrhoea virus as a surrogate model for hepatitis C virus. Thiosemicarbazone 2m showed potent anti-bovine viral diarrhoea virus activity with a higher selectivity index (SI=80.29) than that of ribavirin (SI=11.64). This result determines the potentiality of these thiosemicarbazones as antiviral agents for the treatment of infections caused by other highly related members of Flaviviridae family, as hepatitis C virus.

Design, Synthesis and Bio-evaluation of an EphA2-based Targeted Delivery System

PubMed Central

Barile, Elisa; Wang, Si; Das, Swadesh K.; Noberini, Roberta; Dahl, Russell; Stebbins, John L.; Pasquale, Elena B.; Fisher, Paul B.; Pellecchia, Maurizio

2014-01-01

We recently described a new targeted delivery system based on specific EphA2 receptor targeting peptides conjugated with the chemotherapeutic agent paclitaxel. In this manuscript we investigate the chemical determinants responsible for the stability and degradation of these agents in plasma. Introducing modifications in both the peptide and the linker between the peptide and paclitaxel, resulted in drug conjugates that are both long-lived in rat plasma and that markedly reduced tumor size in a prostate cancer xenograft model compared to paclitaxel alone treatment. These studies identify critical rate-limiting degradation sites on the peptide-drug conjugates, enabling the design of agents with increased stability and efficacy. These results provide support for our central hypothesis that peptide-drug conjugates targeting the EphA2 receptor represent an innovative and potentially effective strategy to selectively deliver cytotoxic drugs to cancer cells. PMID:24677792

Bromomethylthioindole Inspired Carbazole Hybrids as Promising Class of Anti-MRSA Agents.

PubMed

Cheng, Chia-Yi; Chang, Chun-Ping; Lauderdale, Tsai-Ling Yang; Yu, Guann-Yi; Lee, Jinq-Chyi; Jhang, Yi-Wun; Wu, Chien-Huang; Ke, Yi-Yu; Sadani, Amit A; Yeh, Ching-Fang; Huang, I-Wen; Kuo, Yi-Ping; Tsai, De-Jiun; Yeh, Teng-Kuang; Tseng, Chen-Tso; Song, Jen-Shin; Liu, Yu-Wei; Tsou, Lun K; Shia, Kak-Shan

2016-12-08

Series of N -substituted carbazole analogues bearing an indole ring were synthesized as anti-methicillin-resistant Staphylococcus aureus (MRSA) agents from a molecular hybridization approach. The representative compound 19 showed an MIC = 1 μg/mL against a panel of MRSA clinical isolates as it possessed comparable in vitro activities to that of vancomycin. Moreover, compound 19 also exhibited MIC = 1 μg/mL activities against a recent identified Z172 MRSA strain (vancomycin-intermediate and daptomycin-nonsusceptible phenotype) and the vancomycin-resistant Enterococcus faecalis (VRE) strain. In a mouse model with lethal infection of MRSA (4N216), a 75% survival rate was observed after a single dose of compound 19 was intravenously administered at 20 mg/kg. In light of their equipotent activities against different MRSA isolates and VRE strain, the data underscore the importance of designed hybrid series for the development of new N -substituted carbazoles as potential anti-MRSA agents.

Novel Multiscale Modeling Tool Applied to Pseudomonas aeruginosa Biofilm Formation

PubMed Central

Biggs, Matthew B.; Papin, Jason A.

2013-01-01

Multiscale modeling is used to represent biological systems with increasing frequency and success. Multiscale models are often hybrids of different modeling frameworks and programming languages. We present the MATLAB-NetLogo extension (MatNet) as a novel tool for multiscale modeling. We demonstrate the utility of the tool with a multiscale model of Pseudomonas aeruginosa biofilm formation that incorporates both an agent-based model (ABM) and constraint-based metabolic modeling. The hybrid model correctly recapitulates oxygen-limited biofilm metabolic activity and predicts increased growth rate via anaerobic respiration with the addition of nitrate to the growth media. In addition, a genome-wide survey of metabolic mutants and biofilm formation exemplifies the powerful analyses that are enabled by this computational modeling tool. PMID:24147108

Novel multiscale modeling tool applied to Pseudomonas aeruginosa biofilm formation.

PubMed

Biggs, Matthew B; Papin, Jason A

2013-01-01

Multiscale modeling is used to represent biological systems with increasing frequency and success. Multiscale models are often hybrids of different modeling frameworks and programming languages. We present the MATLAB-NetLogo extension (MatNet) as a novel tool for multiscale modeling. We demonstrate the utility of the tool with a multiscale model of Pseudomonas aeruginosa biofilm formation that incorporates both an agent-based model (ABM) and constraint-based metabolic modeling. The hybrid model correctly recapitulates oxygen-limited biofilm metabolic activity and predicts increased growth rate via anaerobic respiration with the addition of nitrate to the growth media. In addition, a genome-wide survey of metabolic mutants and biofilm formation exemplifies the powerful analyses that are enabled by this computational modeling tool.

In Vivo Assessment of Phage and Linezolid Based Implant Coatings for Treatment of Methicillin Resistant S. aureus (MRSA) Mediated Orthopaedic Device Related Infections

PubMed Central

Kaur, Sandeep; Harjai, Kusum; Chhibber, Sanjay

2016-01-01

Staphylococcus comprises up to two-thirds of all pathogens in orthopaedic implant infections with two species respectively Staphylococcus aureus and Staphylococcus epidermidis, being the predominate etiological agents isolated. Further, with the emergence of methicillin-resistant S. aureus (MRSA), treatment of S. aureus implant infections has become more difficult, thus representing a devastating complication. Use of local delivery system consisting of S.aureus specific phage along with linezolid (incorporated in biopolymer) allowing gradual release of the two agents at the implant site represents a new, still unexplored treatment option (against orthopaedic implant infections) that has been studied in an animal model of prosthetic joint infection. Naked wire, hydroxypropyl methylcellulose (HPMC) coated wire and phage and /or linezolid coated K-wire were surgically implanted into the intra-medullary canal of mouse femur bone of respective groups followed by inoculation of S.aureus ATCC 43300(MRSA). Mice implanted with K-wire coated with both the agents i.e phage as well as linezolid (dual coated wires) showed maximum reduction in bacterial adherence, associated inflammation of the joint as well as faster resumption of locomotion and motor function of the limb. Also, all the coating treatments showed no emergence of resistant mutants. Use of dual coated implants incorporating lytic phage (capable of self-multiplication) as well as linezolid presents an attractive and aggressive early approach in preventing as well as treating implant associated infections caused by methicillin resistant S. aureus strains as assessed in a murine model of experimental joint infection. PMID:27333300

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

Exploring Tradeoffs in Demand-side and Supply-side Management of Urban Water Resources using Agent-based Modeling and Evolutionary Computation

NASA Astrophysics Data System (ADS)

Kanta, L.; Berglund, E. Z.

2015-12-01

Urban water supply systems may be managed through supply-side and demand-side strategies, which focus on water source expansion and demand reductions, respectively. Supply-side strategies bear infrastructure and energy costs, while demand-side strategies bear costs of implementation and inconvenience to consumers. To evaluate the performance of demand-side strategies, the participation and water use adaptations of consumers should be simulated. In this study, a Complex Adaptive Systems (CAS) framework is developed to simulate consumer agents that change their consumption to affect the withdrawal from the water supply system, which, in turn influences operational policies and long-term resource planning. Agent-based models are encoded to represent consumers and a policy maker agent and are coupled with water resources system simulation models. The CAS framework is coupled with an evolutionary computation-based multi-objective methodology to explore tradeoffs in cost, inconvenience to consumers, and environmental impacts for both supply-side and demand-side strategies. Decisions are identified to specify storage levels in a reservoir that trigger (1) increases in the volume of water pumped through inter-basin transfers from an external reservoir and (2) drought stages, which restrict the volume of water that is allowed for residential outdoor uses. The proposed methodology is demonstrated for Arlington, Texas, water supply system to identify non-dominated strategies for an historic drought decade. Results demonstrate that pumping costs associated with maximizing environmental reliability exceed pumping costs associated with minimizing restrictions on consumer water use.

Development of an Agent-Based Model to Investigate the Impact of HIV Self-Testing Programs on Men Who Have Sex With Men in Atlanta and Seattle.

PubMed

Luo, Wei; Katz, David A; Hamilton, Deven T; McKenney, Jennie; Jenness, Samuel M; Goodreau, Steven M; Stekler, Joanne D; Rosenberg, Eli S; Sullivan, Patrick S; Cassels, Susan

2018-06-29

In the United States HIV epidemic, men who have sex with men (MSM) remain the most profoundly affected group. Prevention science is increasingly being organized around HIV testing as a launch point into an HIV prevention continuum for MSM who are not living with HIV and into an HIV care continuum for MSM who are living with HIV. An increasing HIV testing frequency among MSM might decrease future HIV infections by linking men who are living with HIV to antiretroviral care, resulting in viral suppression. Distributing HIV self-test (HIVST) kits is a strategy aimed at increasing HIV testing. Our previous modeling work suggests that the impact of HIV self-tests on transmission dynamics will depend not only on the frequency of tests and testers' behaviors but also on the epidemiological and testing characteristics of the population. The objective of our study was to develop an agent-based model to inform public health strategies for promoting safe and effective HIV self-tests to decrease the HIV incidence among MSM in Atlanta, GA, and Seattle, WA, cities representing profoundly different epidemiological settings. We adapted and extended a network- and agent-based stochastic simulation model of HIV transmission dynamics that was developed and parameterized to investigate racial disparities in HIV prevalence among MSM in Atlanta. The extension comprised several activities: adding a new set of model parameters for Seattle MSM; adding new parameters for tester types (ie, regular, risk-based, opportunistic-only, or never testers); adding parameters for simplified pre-exposure prophylaxis uptake following negative results for HIV tests; and developing a conceptual framework for the ways in which the provision of HIV self-tests might change testing behaviors. We derived city-specific parameters from previous cohort and cross-sectional studies on MSM in Atlanta and Seattle. Each simulated population comprised 10,000 MSM and targeted HIV prevalences are equivalent to 28% and 11% in Atlanta and Seattle, respectively. Previous studies provided sufficient data to estimate the model parameters representing nuanced HIV testing patterns and HIV self-test distribution. We calibrated the models to simulate the epidemics representing Atlanta and Seattle, including matching the expected stable HIV prevalence. The revised model facilitated the estimation of changes in 10-year HIV incidence based on counterfactual scenarios of HIV self-test distribution strategies and their impact on testing behaviors. We demonstrated that the extension of an existing agent-based HIV transmission model was sufficient to simulate the HIV epidemics among MSM in Atlanta and Seattle, to accommodate a more nuanced depiction of HIV testing behaviors than previous models, and to serve as a platform to investigate how HIV self-tests might impact testing and HIV transmission patterns among MSM in Atlanta and Seattle. In our future studies, we will use the model to test how different HIV self-test distribution strategies might affect HIV incidence among MSM. ©Wei Luo, David A Katz, Deven T Hamilton, Jennie McKenney, Samuel M Jenness, Steven M Goodreau, Joanne D Stekler, Eli S Rosenberg, Patrick S Sullivan, Susan Cassels. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 29.06.2018.

DualTrust: A Distributed Trust Model for Swarm-Based Autonomic Computing Systems

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

Maiden, Wendy M.; Dionysiou, Ioanna; Frincke, Deborah A.

2011-02-01

For autonomic computing systems that utilize mobile agents and ant colony algorithms for their sensor layer, trust management is important for the acceptance of the mobile agent sensors and to protect the system from malicious behavior by insiders and entities that have penetrated network defenses. This paper examines the trust relationships, evidence, and decisions in a representative system and finds that by monitoring the trustworthiness of the autonomic managers rather than the swarming sensors, the trust management problem becomes much more scalable and still serves to protect the swarm. We then propose the DualTrust conceptual trust model. By addressing themore » autonomic manager’s bi-directional primary relationships in the ACS architecture, DualTrust is able to monitor the trustworthiness of the autonomic managers, protect the sensor swarm in a scalable manner, and provide global trust awareness for the orchestrating autonomic manager.« less

Agent-Based Model with Asymmetric Trading and Herding for Complex Financial Systems

PubMed Central

Chen, Jun-Jie; Zheng, Bo; Tan, Lei

2013-01-01

Background For complex financial systems, the negative and positive return-volatility correlations, i.e., the so-called leverage and anti-leverage effects, are particularly important for the understanding of the price dynamics. However, the microscopic origination of the leverage and anti-leverage effects is still not understood, and how to produce these effects in agent-based modeling remains open. On the other hand, in constructing microscopic models, it is a promising conception to determine model parameters from empirical data rather than from statistical fitting of the results. Methods To study the microscopic origination of the return-volatility correlation in financial systems, we take into account the individual and collective behaviors of investors in real markets, and construct an agent-based model. The agents are linked with each other and trade in groups, and particularly, two novel microscopic mechanisms, i.e., investors’ asymmetric trading and herding in bull and bear markets, are introduced. Further, we propose effective methods to determine the key parameters in our model from historical market data. Results With the model parameters determined for six representative stock-market indices in the world, respectively, we obtain the corresponding leverage or anti-leverage effect from the simulation, and the effect is in agreement with the empirical one on amplitude and duration. At the same time, our model produces other features of the real markets, such as the fat-tail distribution of returns and the long-term correlation of volatilities. Conclusions We reveal that for the leverage and anti-leverage effects, both the investors’ asymmetric trading and herding are essential generation mechanisms. Among the six markets, however, the investors’ trading is approximately symmetric for the five markets which exhibit the leverage effect, thus contributing very little. These two microscopic mechanisms and the methods for the determination of the key parameters can be applied to other complex systems with similar asymmetries. PMID:24278146

Agent-based model with asymmetric trading and herding for complex financial systems.

PubMed

Chen, Jun-Jie; Zheng, Bo; Tan, Lei

2013-01-01

For complex financial systems, the negative and positive return-volatility correlations, i.e., the so-called leverage and anti-leverage effects, are particularly important for the understanding of the price dynamics. However, the microscopic origination of the leverage and anti-leverage effects is still not understood, and how to produce these effects in agent-based modeling remains open. On the other hand, in constructing microscopic models, it is a promising conception to determine model parameters from empirical data rather than from statistical fitting of the results. To study the microscopic origination of the return-volatility correlation in financial systems, we take into account the individual and collective behaviors of investors in real markets, and construct an agent-based model. The agents are linked with each other and trade in groups, and particularly, two novel microscopic mechanisms, i.e., investors' asymmetric trading and herding in bull and bear markets, are introduced. Further, we propose effective methods to determine the key parameters in our model from historical market data. With the model parameters determined for six representative stock-market indices in the world, respectively, we obtain the corresponding leverage or anti-leverage effect from the simulation, and the effect is in agreement with the empirical one on amplitude and duration. At the same time, our model produces other features of the real markets, such as the fat-tail distribution of returns and the long-term correlation of volatilities. We reveal that for the leverage and anti-leverage effects, both the investors' asymmetric trading and herding are essential generation mechanisms. Among the six markets, however, the investors' trading is approximately symmetric for the five markets which exhibit the leverage effect, thus contributing very little. These two microscopic mechanisms and the methods for the determination of the key parameters can be applied to other complex systems with similar asymmetries.

Using an agent-based model to evaluate the effect of producer specialization on the epidemiological resilience of livestock production networks

PubMed Central

2018-01-01

An agent-based computer model that builds representative regional U.S. hog production networks was developed and employed to assess the potential impact of the ongoing trend towards increased producer specialization upon network-level resilience to catastrophic disease outbreaks. Empirical analyses suggest that the spatial distribution and connectivity patterns of contact networks often predict epidemic spreading dynamics. Our model heuristically generates realistic systems composed of hog producer, feed mill, and slaughter plant agents. Network edges are added during each run as agents exchange livestock and feed. The heuristics governing agents’ contact patterns account for factors including their industry roles, physical proximities, and the age of their livestock. In each run, an infection is introduced, and may spread according to probabilities associated with the various modes of contact. For each of three treatments—defined by one-phase, two-phase, and three-phase production systems—a parameter variation experiment examines the impact of the spatial density of producer agents in the system upon the length and size of disease outbreaks. Resulting data show phase transitions whereby, above some density threshold, systemic outbreaks become possible, echoing findings from percolation theory. Data analysis reveals that multi-phase production systems are vulnerable to catastrophic outbreaks at lower spatial densities, have more abrupt percolation transitions, and are characterized by less-predictable outbreak scales and durations. Key differences in network-level metrics shed light on these results, suggesting that the absence of potentially-bridging producer–producer edges may be largely responsible for the superior disease resilience of single-phase “farrow to finish” production systems. PMID:29522574

Intelligent web agents for a 3D virtual community

NASA Astrophysics Data System (ADS)

Dave, T. M.; Zhang, Yanqing; Owen, G. S. S.; Sunderraman, Rajshekhar

2003-08-01

In this paper, we propose an Avatar-based intelligent agent technique for 3D Web based Virtual Communities based on distributed artificial intelligence, intelligent agent techniques, and databases and knowledge bases in a digital library. One of the goals of this joint NSF (IIS-9980130) and ACM SIGGRAPH Education Committee (ASEC) project is to create a virtual community of educators and students who have a common interest in comptuer graphics, visualization, and interactive techniqeus. In this virtual community (ASEC World) Avatars will represent the educators, students, and other visitors to the world. Intelligent agents represented as specially dressed Avatars will be available to assist the visitors to ASEC World. The basic Web client-server architecture of the intelligent knowledge-based avatars is given. Importantly, the intelligent Web agent software system for the 3D virtual community is implemented successfully.

From old alkylating agents to new minor groove binders.

PubMed

Puyo, Stéphane; Montaudon, Danièle; Pourquier, Philippe

2014-01-01

Alkylating agents represent the oldest class of anticancer agents with the approval of mechloretamine by the FDA in 1949. Even though their clinical use is far beyond the use of new targeted therapies, they still occupy a major place in the treatment of specific malignancies, sometimes representing the unique option for the treatment of refractory tumors. Here, we are reviewing the major classes of alkylating agents, with a particular focus on the latest generations of compounds that specifically target the minor groove of the DNA. These naturally occurring derivatives have a unique mechanism of action that explains the recent regain of interest in developing new classes of alkylating agents that could be used in combination with other anticancer drugs to enhance tumor response in the clinic. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

A model for cross-cultural reciprocal interactions through mass media.

PubMed

González-Avella, Juan Carlos; Cosenza, Mario G; San Miguel, Maxi

2012-01-01

We investigate the problem of cross-cultural interactions through mass media in a model where two populations of social agents, each with its own internal dynamics, get information about each other through reciprocal global interactions. As the agent dynamics, we employ Axelrod's model for social influence. The global interaction fields correspond to the statistical mode of the states of the agents and represent mass media messages on the cultural trend originating in each population. Several phases are found in the collective behavior of either population depending on parameter values: two homogeneous phases, one having the state of the global field acting on that population, and the other consisting of a state different from that reached by the applied global field; and a disordered phase. In addition, the system displays nontrivial effects: (i) the emergence of a largest minority group of appreciable size sharing a state different from that of the applied global field; (ii) the appearance of localized ordered states for some values of parameters when the entire system is observed, consisting of one population in a homogeneous state and the other in a disordered state. This last situation can be considered as a social analogue to a chimera state arising in globally coupled populations of oscillators.

Dynamics of Nearest-Neighbour Competitions on Graphs

NASA Astrophysics Data System (ADS)

Rador, Tonguç

2017-10-01

Considering a collection of agents representing the vertices of a graph endowed with integer points, we study the asymptotic dynamics of the rate of the increase of their points according to a very simple rule: we randomly pick an an edge from the graph which unambiguously defines two agents we give a point the the agent with larger point with probability p and to the lagger with probability q such that p+q=1. The model we present is the most general version of the nearest-neighbour competition model introduced by Ben-Naim, Vazquez and Redner. We show that the model combines aspects of hyperbolic partial differential equations—as that of a conservation law—graph colouring and hyperplane arrangements. We discuss the properties of the model for general graphs but we confine in depth study to d-dimensional tori. We present a detailed study for the ring graph, which includes a chemical potential approximation to calculate all its statistics that gives rather accurate results. The two-dimensional torus, not studied in depth as the ring, is shown to possess critical behaviour in that the asymptotic speeds arrange themselves in two-coloured islands separated by borders of three other colours and the size of the islands obey power law distribution. We also show that in the large d limit the d-dimensional torus shows inverse sine law for the distribution of asymptotic speeds.

Identification of novel PfDHODH inhibitors as antimalarial agents via pharmacophore-based virtual screening followed by molecular docking and in vivo antimalarial activity.

PubMed

Vyas, V K; Qureshi, G; Ghate, M; Patel, H; Dalai, S

2016-06-01

Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH) catalyses the fourth reaction of de novo pyrimidine biosynthesis in parasites, and represents an important target for the treatment of malaria. In this study, we describe pharmacophore-based virtual screening combined with docking study and biological evaluation as a rational strategy for identification of novel hits as antimalarial agents. Pharmacophore models were established from known PfDHODH inhibitors using the GALAHAD module with IC50 values ranging from 0.033 μM to 142 μM. The best pharmacophore model consisted of three hydrogen bond acceptor, one hydrogen bond donor and one hydrophobic features. The pharmacophore models were validated through receiver operating characteristic and Günere-Henry scoring methods. The best pharmacophore model as a 3D search query was searched against the IBS database. Several compounds with different structures (scaffolds) were retrieved as hit molecules. Among these compounds, those with a QFIT value of more than 81 were docked in the PfDHODH enzyme to further explore the binding modes of these compounds. In silico pharmacokinetic and toxicities were predicted for the best docked molecules. Finally, the identified hits were evaluated in vivo for their antimalarial activity in a parasite inhibition assay. The hits reported here showed good potential to become novel antimalarial agents.

Bouchaud-Mézard model on a random network

NASA Astrophysics Data System (ADS)

Ichinomiya, Takashi

2012-09-01

We studied the Bouchaud-Mézard (BM) model, which was introduced to explain Pareto's law in a real economy, on a random network. Using “adiabatic and independent” assumptions, we analytically obtained the stationary probability distribution function of wealth. The results show that wealth condensation, indicated by the divergence of the variance of wealth, occurs at a larger J than that obtained by the mean-field theory, where J represents the strength of interaction between agents. We compared our results with numerical simulation results and found that they were in good agreement.

Continuing Professional Education of Insurance and Risk Management Practitioners: A Comparative Case Study of Customer Service Representatives, Insurance Agents and Risk Managers

ERIC Educational Resources Information Center

Krauss, George E.

2009-01-01

The purpose of this study is to understand how selected insurance practitioners learn and developed in their practices setting. The selected insurance practitioners (collectively customer service representatives, insurance agents, and risk managers) are responsible for the counseling and placement of insurance products and the implementation of…

The Impact of Cell Density and Mutations in a Model of Multidrug Resistance in Solid Tumors

PubMed Central

Greene, James; Lavi, Orit; Gottesman, Michael M.; Levy, Doron

2016-01-01

In this paper we develop a mathematical framework for describing multidrug resistance in cancer. To reflect the complexity of the underlying interplay between cancer cells and the therapeutic agent, we assume that the resistance level is a continuous parameter. Our model is written as a system of integro-differential equations that are parametrized by the resistance level. This model incorporates the cell-density and mutation dependence. Analysis and simulations of the model demonstrate how the dynamics evolves to a selection of one or more traits corresponding to different levels of resistance. The emerging limit distribution with nonzero variance is the desirable modeling outcome as it represents tumor heterogeneity. PMID:24553772

An Empirical Agent-Based Model to Simulate the Adoption of Water Reuse Using the Social Amplification of Risk Framework.

PubMed

Kandiah, Venu; Binder, Andrew R; Berglund, Emily Z

2017-10-01

Water reuse can serve as a sustainable alternative water source for urban areas. However, the successful implementation of large-scale water reuse projects depends on community acceptance. Because of the negative perceptions that are traditionally associated with reclaimed water, water reuse is often not considered in the development of urban water management plans. This study develops a simulation model for understanding community opinion dynamics surrounding the issue of water reuse, and how individual perceptions evolve within that context, which can help in the planning and decision-making process. Based on the social amplification of risk framework, our agent-based model simulates consumer perceptions, discussion patterns, and their adoption or rejection of water reuse. The model is based on the "risk publics" model, an empirical approach that uses the concept of belief clusters to explain the adoption of new technology. Each household is represented as an agent, and parameters that define their behavior and attributes are defined from survey data. Community-level parameters-including social groups, relationships, and communication variables, also from survey data-are encoded to simulate the social processes that influence community opinion. The model demonstrates its capabilities to simulate opinion dynamics and consumer adoption of water reuse. In addition, based on empirical data, the model is applied to investigate water reuse behavior in different regions of the United States. Importantly, our results reveal that public opinion dynamics emerge differently based on membership in opinion clusters, frequency of discussion, and the structure of social networks. © 2017 Society for Risk Analysis.

Using stylized agent-based models for population-environment research: A case study from the Galápagos Islands

PubMed Central

Miller, Brian W.; Breckheimer, Ian; McCleary, Amy L.; Guzmán-Ramirez, Liza; Caplow, Susan C.; Jones-Smith, Jessica C.; Walsh, Stephen J.

2010-01-01

Agent Based Models (ABMs) are powerful tools for population-environment research but are subject to trade-offs between model complexity and abstraction. This study strikes a compromise between abstract and highly specified ABMs by designing a spatially explicit, stylized ABM and using it to explore policy scenarios in a setting that is facing substantial conservation and development challenges. Specifically, we present an ABM that reflects key Land Use / Land Cover (LULC) dynamics and livelihood decisions on Isabela Island in the Galápagos Archipelago of Ecuador. We implement the model using the NetLogo software platform, a free program that requires relatively little programming experience. The landscape is composed of a satellite-derived distribution of a problematic invasive species (common guava) and a stylized representation of the Galápagos National Park, the community of Puerto Villamil, the agricultural zone, and the marine area. The agent module is based on publicly available data and household interviews, and represents the primary livelihoods of the population in the Galápagos Islands – tourism, fisheries, and agriculture. We use the model to enact hypothetical agricultural subsidy scenarios aimed at controlling invasive guava and assess the resulting population and land cover dynamics. Findings suggest that spatially explicit, stylized ABMs have considerable utility, particularly during preliminary stages of research, as platforms for (1) sharpening conceptualizations of population-environment systems, (2) testing alternative scenarios, and (3) uncovering critical data gaps. PMID:20539752

Identifying and Modeling Dynamic Preference Evolution in Multipurpose Water Resources Systems

NASA Astrophysics Data System (ADS)

Mason, E.; Giuliani, M.; Castelletti, A.; Amigoni, F.

2018-04-01

Multipurpose water systems are usually operated on a tradeoff of conflicting operating objectives. Under steady state climatic and socioeconomic conditions, such tradeoff is supposed to represent a fair and/or efficient preference. Extreme variability in external forcing might affect water operators' risk aversion and force a change in her/his preference. Properly accounting for these shifts is key to any rigorous retrospective assessment of the operator's behaviors, and to build descriptive models for projecting the future system evolution. In this study, we explore how the selection of different preferences is linked to variations in the external forcing. We argue that preference selection evolves according to recent, extreme variations in system performance: underperforming in one of the objectives pushes the preference toward the harmed objective. To test this assumption, we developed a rational procedure to simulate the operator's preference selection. We map this selection onto a multilateral negotiation, where multiple virtual agents independently optimize different objectives. The agents periodically negotiate a compromise policy for the operation of the system. Agents' attitudes in each negotiation step are determined by the recent system performance measured by the specific objective they maximize. We then propose a numerical model of preference dynamics that implements a concept from cognitive psychology, the availability bias. We test our modeling framework on a synthetic lake operated for flood control and water supply. Results show that our model successfully captures the operator's preference selection and dynamic evolution driven by extreme wet and dry situations.

Using stylized agent-based models for population-environment research: A case study from the Galápagos Islands.

PubMed

Miller, Brian W; Breckheimer, Ian; McCleary, Amy L; Guzmán-Ramirez, Liza; Caplow, Susan C; Jones-Smith, Jessica C; Walsh, Stephen J

2010-05-01

Agent Based Models (ABMs) are powerful tools for population-environment research but are subject to trade-offs between model complexity and abstraction. This study strikes a compromise between abstract and highly specified ABMs by designing a spatially explicit, stylized ABM and using it to explore policy scenarios in a setting that is facing substantial conservation and development challenges. Specifically, we present an ABM that reflects key Land Use / Land Cover (LULC) dynamics and livelihood decisions on Isabela Island in the Galápagos Archipelago of Ecuador. We implement the model using the NetLogo software platform, a free program that requires relatively little programming experience. The landscape is composed of a satellite-derived distribution of a problematic invasive species (common guava) and a stylized representation of the Galápagos National Park, the community of Puerto Villamil, the agricultural zone, and the marine area. The agent module is based on publicly available data and household interviews, and represents the primary livelihoods of the population in the Galápagos Islands - tourism, fisheries, and agriculture. We use the model to enact hypothetical agricultural subsidy scenarios aimed at controlling invasive guava and assess the resulting population and land cover dynamics. Findings suggest that spatially explicit, stylized ABMs have considerable utility, particularly during preliminary stages of research, as platforms for (1) sharpening conceptualizations of population-environment systems, (2) testing alternative scenarios, and (3) uncovering critical data gaps.

A simulation framework for mapping risks in clinical processes: the case of in-patient transfers.

PubMed

Dunn, Adam G; Ong, Mei-Sing; Westbrook, Johanna I; Magrabi, Farah; Coiera, Enrico; Wobcke, Wayne

2011-05-01

To model how individual violations in routine clinical processes cumulatively contribute to the risk of adverse events in hospital using an agent-based simulation framework. An agent-based simulation was designed to model the cascade of common violations that contribute to the risk of adverse events in routine clinical processes. Clinicians and the information systems that support them were represented as a group of interacting agents using data from direct observations. The model was calibrated using data from 101 patient transfers observed in a hospital and results were validated for one of two scenarios (a misidentification scenario and an infection control scenario). Repeated simulations using the calibrated model were undertaken to create a distribution of possible process outcomes. The likelihood of end-of-chain risk is the main outcome measure, reported for each of the two scenarios. The simulations demonstrate end-of-chain risks of 8% and 24% for the misidentification and infection control scenarios, respectively. Over 95% of the simulations in both scenarios are unique, indicating that the in-patient transfer process diverges from prescribed work practices in a variety of ways. The simulation allowed us to model the risk of adverse events in a clinical process, by generating the variety of possible work subject to violations, a novel prospective risk analysis method. The in-patient transfer process has a high proportion of unique trajectories, implying that risk mitigation may benefit from focusing on reducing complexity rather than augmenting the process with further rule-based protocols.

Effects of Clove Oil as a Euthanasia Agent on Blood Collection Efficiency and Serum Cortisol Levels in Danio rerio

PubMed Central

Davis, Daniel J; Klug, Jenna; Hankins, Miriam; Doerr, Holly M; Monticelli, Stephanie R; Song, Ava; Gillespie, Catherine H; Bryda, Elizabeth C

2015-01-01

Zebrafish are an important laboratory animal model for biomedical research and are increasingly being used for behavioral neuroscience. Tricaine methanesulfonate (MS222) is the standard agent used for euthanasia of zebrafish. However, recent studies of zebrafish behavior suggest that MS222 may be aversive, and clove oil might be a possible alternative. In this study, we compared the effects of MS222 or clove oil as a euthanasia agent in zebrafish on the volume of blood collected and on serum levels of cortisol. Greater amounts of serum could be collected and lower serum levels of cortisol were present in fish euthanized with clove oil compared with equipotent dose of MS222. Euthanasia with clove oil did not blunt the expected elevation of serum cortisol levels elicited by an acute premortem stress. According to our findings, clove oil is a fast-acting agent that minimizes the cortisol response to euthanasia in zebrafish and allows the collection of large volumes of blood postmortem. These results represent a significant refinement in euthanasia methods for zebrafish. PMID:26424256

Effects of Clove Oil as a Euthanasia Agent on Blood Collection Efficiency and Serum Cortisol Levels in Danio rerio.

PubMed

Davis, Daniel J; Klug, Jenna; Hankins, Miriam; Doerr, Holly M; Monticelli, Stephanie R; Song, Ava; Gillespie, Catherine H; Bryda, Elizabeth C

2015-09-01

Zebrafish are an important laboratory animal model for biomedical research and are increasingly being used for behavioral neuroscience. Tricaine methanesulfonate (MS222) is the standard agent used for euthanasia of zebrafish. However, recent studies of zebrafish behavior suggest that MS222 may be aversive, and clove oil might be a possible alternative. In this study, we compared the effects of MS222 or clove oil as a euthanasia agent in zebrafish on the volume of blood collected and on serum levels of cortisol. Greater amounts of serum could be collected and lower serum levels of cortisol were present in fish euthanized with clove oil compared with equipotent dose of MS222. Euthanasia with clove oil did not blunt the expected elevation of serum cortisol levels elicited by an acute premortem stress. According to our findings, clove oil is a fast-acting agent that minimizes the cortisol response to euthanasia in zebrafish and allows the collection of large volumes of blood postmortem. These results represent a significant refinement in euthanasia methods for zebrafish.

Relative susceptibilities of male germ cells to genetic defects induced by cancer chemotherapies

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

Wyrobek, A J; Schmid, T E; Marchetti, F

Some chemotherapy regimens include agents that are mutagenic or clastogenic in model systems. This raises concerns that cancer survivors, who were treated before or during their reproductive years, may be at increased risks for abnormal reproductive outcomes. However, the available data from offspring of cancer survivors are limited, representing diverse cancers, therapies, time-to-pregnancies, and reproductive outcomes. Rodent breeding data after paternal exposures to individual chemotherapeutic agents illustrate the complexity of factors that influence the risk for transmitted genetic damage including agent, dose, endpoint, and the germ-cell susceptibility profiles that vary across agents. Direct measurements of chromosomal abnormalities in sperm ofmore » mice and humans by sperm FISH have corroborated the differences in germ-cell susceptibilities. The available evidence suggests that the risk of producing chromosomally defective sperm is highest during the first few weeks after the end of chemotherapy, and decays with time. Thus, sperm samples provided immediately after the initiation of cancer therapies may contain treatment-induced genetic defects that will jeopardize the genetic health of offspring.« less

Agent-based modeling of autophagy reveals emergent regulatory behavior of spatio-temporal autophagy dynamics.

PubMed

Börlin, Christoph S; Lang, Verena; Hamacher-Brady, Anne; Brady, Nathan R

2014-09-10

Autophagy is a vesicle-mediated pathway for lysosomal degradation, essential under basal and stressed conditions. Various cellular components, including specific proteins, protein aggregates, organelles and intracellular pathogens, are targets for autophagic degradation. Thereby, autophagy controls numerous vital physiological and pathophysiological functions, including cell signaling, differentiation, turnover of cellular components and pathogen defense. Moreover, autophagy enables the cell to recycle cellular components to metabolic substrates, thereby permitting prolonged survival under low nutrient conditions. Due to the multi-faceted roles for autophagy in maintaining cellular and organismal homeostasis and responding to diverse stresses, malfunction of autophagy contributes to both chronic and acute pathologies. We applied a systems biology approach to improve the understanding of this complex cellular process of autophagy. All autophagy pathway vesicle activities, i.e. creation, movement, fusion and degradation, are highly dynamic, temporally and spatially, and under various forms of regulation. We therefore developed an agent-based model (ABM) to represent individual components of the autophagy pathway, subcellular vesicle dynamics and metabolic feedback with the cellular environment, thereby providing a framework to investigate spatio-temporal aspects of autophagy regulation and dynamic behavior. The rules defining our ABM were derived from literature and from high-resolution images of autophagy markers under basal and activated conditions. Key model parameters were fit with an iterative method using a genetic algorithm and a predefined fitness function. From this approach, we found that accurate prediction of spatio-temporal behavior required increasing model complexity by implementing functional integration of autophagy with the cellular nutrient state. The resulting model is able to reproduce short-term autophagic flux measurements (up to 3 hours) under basal and activated autophagy conditions, and to measure the degree of cell-to-cell variability. Moreover, we experimentally confirmed two model predictions, namely (i) peri-nuclear concentration of autophagosomes and (ii) inhibitory lysosomal feedback on mTOR signaling. Agent-based modeling represents a novel approach to investigate autophagy dynamics, function and dysfunction with high biological realism. Our model accurately recapitulates short-term behavior and cell-to-cell variability under basal and activated conditions of autophagy. Further, this approach also allows investigation of long-term behaviors emerging from biologically-relevant alterations to vesicle trafficking and metabolic state.

Impacts of Farmers' Knowledge Increase on Farm Profit and Watershed Water Quality

NASA Astrophysics Data System (ADS)

Ding, D.; Bennett, D. A.

2013-12-01

This study explores the impact that an increase in real-time data might have on farmers' nitrogen management, on-farm profit, and watershed water quality in the Midwestern US. In this study, an agent-based model (ABM) is used to simulate farmers' decisions about nitrogen application rate and timing in corn fields. SWAT (soil-water assessment tool) is used to generate a database that characterizes the response of corn yields to nitrogen fertilizer application and the dynamics of nitrogen loss under different scenarios of rainfall events. The database simulates a scenario where farmers would receive real-time feedback about the fate and impact of nitrogen applied to their fields from in-situ sensors. The ability to transform these data into optimal actions is simulated at multiple levels for farmer agents. In a baseline scenario, the farmer agent is only aware of the yield potential of the land field and single values of N rates for achieving the yield potential and is not aware of N loss from farm fields. Knowledge increase is represented by greater accuracy in predicting rainfall events, and the increase of the number of discrete points in a field-specific quadratic curve that captures crop yield response to various levels of nitrogen perceived by farmer agents. In addition, agents perceive N loss from farm fields at increased temporal resolutions. Correspondingly, agents make adjustments to the rate of N application for crops and the timing of fertilizer application given the rainfall events predictions. Farmers' decisions simulated by the ABM are input into SWAT to model nitrogen concentration in impacted streams. Farm profit statistics and watershed-level nitrogen loads are compared among different scenarios of knowledge increase. The hypothesis that the increase of farmers' knowledge benefits both farm profits and watershed water quality is tested through the comparison.

Probing voltage sensing domain of KCNQ2 channel as a potential target to combat epilepsy: a comparative study.

PubMed

Mehta, Pakhuri; Srivastava, Shubham; Choudhary, Bhanwar Singh; Sharma, Manish; Malik, Ruchi

2017-12-01

Multidrug resistance along with side-effects of available anti-epileptic drugs and unavailability of potent and effective agents in submicromolar quantities presents the biggest therapeutic challenges in anti-epileptic drug discovery. The molecular modeling techniques allow us to identify agents with novel structures to match the continuous urge for its discovery. KCNQ2 channel represents one of the validated targets for its therapy. The present study involves identification of newer anti-epileptic agents by means of a computer-aided drug design adaptive protocol involving both structure-based virtual screening of Asinex library using homology model of KCNQ2 and 3D-QSAR based virtual screening with docking analysis, followed by dG bind and ligand efficiency calculations with ADMET studies, of which 20 hits qualified all the criterions. The best ligands of both screenings with least potential for toxicity predicted computationally were then taken for molecular dynamic simulations. All the crucial amino acid interactions were observed in hits of both screenings such as Glu130, Arg207, Arg210 and Phe137. Robustness of docking protocol was analyzed through Receiver operating characteristic (ROC) curve values 0.88 (Area under curve AUC = 0.87) in Standard Precision and 0.84 (AUC = 0.82) in Extra Precision modes. Novelty analysis indicates that these compounds have not been reported previously as anti-epileptic agents.

Glucose dysregulation and response to common anti-diabetic agents in the FATZO/Pco mouse.

PubMed

Peterson, Richard G; Jackson, Charles Van; Zimmerman, Karen M; Alsina-Fernandez, Jorge; Michael, M Dodson; Emmerson, Paul J; Coskun, Tamer

2017-01-01

The FATZO/Pco mouse is the result of a cross of the C57BL/6J and AKR/J strains. The crossing of these two strains and the selective inbreeding for obesity, insulin resistance and hyperglycemia has resulted in an inbred strain exhibiting obesity in the presumed presence of an intact leptin pathway. Routinely used rodent models for obesity and diabetes research have a monogenic defect in leptin signaling that initiates obesity. Given that obesity and its sequelae in humans are polygenic in nature and not associated with leptin signaling defects, the FATZO mouse may represent a more translatable rodent model for study of obesity and its associated metabolic disturbances. The FATZO mouse develops obesity spontaneously when fed a normal chow diet. Glucose intolerance with increased insulin levels are apparent in FATZO mice as young as 6 weeks of age. These progress to hyperglycemia/pre-diabetes and frank diabetes with decreasing insulin levels as they age. The disease in these mice is multi-faceted, similar to the metabolic syndrome apparent in obese individuals, and thus provides a long pre-diabetic state for determining the preventive value of new interventions. We have assessed the utility of this new model for the pre-clinical screening of agents to stop or slow progression of the metabolic syndrome to severe diabetes. Our assessment included: 1) characterization of the spontaneous development of disease, 2) comparison of metabolic disturbances of FATZO mice to control mice and 3) validation of the model with regard to the effectiveness of current and emerging anti-diabetic agents; rosiglitazone, metformin and semaglutide. Male FATZO mice spontaneously develop significant metabolic disease when compared to normal controls while maintaining hyperglycemia in the presence of high leptin levels and hyperinsulinemia. The disease condition responds to commonly used antidiabetic agents.

Achieving "organic compositionality" through self-organization: reviews on brain-inspired robotics experiments.

PubMed

Tani, Jun; Nishimoto, Ryunosuke; Paine, Rainer W

2008-05-01

The current paper examines how compositional structures can self-organize in given neuro-dynamical systems when robot agents are forced to learn multiple goal-directed behaviors simultaneously. Firstly, we propose a basic model accounting for the roles of parietal-premotor interactions for representing skills for goal-directed behaviors. The basic model had been implemented in a set of robotics experiments employing different neural network architectures. The comparative reviews among those experimental results address the issues of local vs distributed representations in representing behavior and the effectiveness of level structures associated with different sensory-motor articulation mechanisms. It is concluded that the compositional structures can be acquired "organically" by achieving generalization in learning and by capturing the contextual nature of skilled behaviors under specific conditions. Furthermore, the paper discusses possible feedback for empirical neuroscience studies in the future.

Setting the agenda: Different strategies of a Mass Media in a model of cultural dissemination

NASA Astrophysics Data System (ADS)

Pinto, Sebastián; Balenzuela, Pablo; Dorso, Claudio O.

2016-09-01

Day by day, people exchange opinions about news with relatives, friends, and coworkers. In most cases, they get informed about a given issue by reading newspapers, listening to the radio, or watching TV, i.e., through a Mass Media (MM). However, the importance of a given new can be stimulated by the Media by assigning newspaper's pages or time in TV programs. In this sense, we say that the Media has the power to "set the agenda", i.e., it decides which new is important and which is not. On the other hand, the Media can know people's concerns through, for instance, websites or blogs where they express their opinions, and then it can use this information in order to be more appealing to an increasing number of people. In this work, we study different scenarios in an agent-based model of cultural dissemination, in which a given Mass Media has a specific purpose: To set a particular topic of discussion and impose its point of view to as many social agents as it can. We model this by making the Media has a fixed feature, representing its point of view in the topic of discussion, while it tries to attract new consumers, by taking advantage of feedback mechanisms, represented by adaptive features. We explore different strategies that the Media can adopt in order to increase the affinity with potential consumers and then the probability to be successful in imposing this particular topic.

Analysis and application of opinion model with multiple topic interactions.

PubMed

Xiong, Fei; Liu, Yun; Wang, Liang; Wang, Ximeng

2017-08-01

To reveal heterogeneous behaviors of opinion evolution in different scenarios, we propose an opinion model with topic interactions. Individual opinions and topic features are represented by a multidimensional vector. We measure an agent's action towards a specific topic by the product of opinion and topic feature. When pairs of agents interact for a topic, their actions are introduced to opinion updates with bounded confidence. Simulation results show that a transition from a disordered state to a consensus state occurs at a critical point of the tolerance threshold, which depends on the opinion dimension. The critical point increases as the dimension of opinions increases. Multiple topics promote opinion interactions and lead to the formation of macroscopic opinion clusters. In addition, more topics accelerate the evolutionary process and weaken the effect of network topology. We use two sets of large-scale real data to evaluate the model, and the results prove its effectiveness in characterizing a real evolutionary process. Our model achieves high performance in individual action prediction and even outperforms state-of-the-art methods. Meanwhile, our model has much smaller computational complexity. This paper provides a demonstration for possible practical applications of theoretical opinion dynamics.

Integrating Agent Models of Subsistence Farming With Dynamic Models of Water Distribution

NASA Astrophysics Data System (ADS)

Bithell, M.; Brasington, J.

2004-12-01

Subsistence farming communities are dependent on the landscape to provide the resource base upon which their societies can be built. A key component of this is the role of climate, and the feedback between rainfall, crop growth and land clearance, and their coupling to the hydrological cycle. Temporal fluctuations in rainfall on timescales from annual through to decadal and longer, and the associated changes in in the spatial distribution of water availability mediated by the soil-type, slope and landcover determine the locations within the landscape that can support agriculture, and control sustainability of farming practices. We seek to make an integrated modelling system to represent land use change by coupling an agent based model of subsistence farming, and the associated exploitation of natural resources, to a realistic representation of the hydrology at the catchment scale, using TOPMODEL to map the spatial distribution of crop water stress for given time-series of rainfall. In this way we can, for example, investigate how demographic changes and associated removal of forest cover influence the possibilities for field locations within the catchment, through changes in ground water availability. The framework for this modelling exercise will be presented and preliminary results from this system will be discussed.

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

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.

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

Decentralization and the Composition of Public Expenditures

DTIC Science & Technology

2012-01-01

decentralized governance and expenditure composition by means of a distance-sensitive representative agent model. Then we estimate the impact of fiscal...countries with regards to population age structure. We are not certain of what effects that may have in our estimates , but previous studies have found find...variables to estimate a scalar value for g(xβ), which then is multiplied to each variables coefficient. For this, we choose the mean values of the

Hidden multidimensional social structure modeling applied to biased social perception

NASA Astrophysics Data System (ADS)

Maletić, Slobodan; Zhao, Yi

2018-02-01

Intricacies of the structure of social relations are realized by representing a collection of overlapping opinions as a simplicial complex, thus building latent multidimensional structures, through which agents are, virtually, moving as they exchange opinions. The influence of opinion space structure on the distribution of opinions is demonstrated by modeling consensus phenomena when the opinion exchange between individuals may be affected by the false consensus effect. The results indicate that in the cases with and without bias, the road toward consensus is influenced by the structure of multidimensional space of opinions, and in the biased case, complete consensus is achieved. The applications of proposed modeling framework can easily be generalized, as they transcend opinion formation modeling.

"Campus" - An Agent-Based Platform for Distance Education.

ERIC Educational Resources Information Center

Westhoff, Dirk; Unger, Claus

This paper presents "Campus," an environment that allows University of Hagen (Germany) students to connect briefly to the Internet but remain represented by personalized, autonomous agents that can fulfill a variety of information, communication, planning, and cooperation tasks. A brief survey is presented of existing mobile agent system…

A predictive pharmacokinetic-pharmacodynamic model of tumor growth kinetics in xenograft mice after administration of anticancer agents given in combination.

PubMed

Terranova, Nadia; Germani, Massimiliano; Del Bene, Francesca; Magni, Paolo

2013-08-01

In clinical oncology, combination treatments are widely used and increasingly preferred over single drug administrations. A better characterization of the interaction between drug effects and the selection of synergistic combinations represent an open challenge in drug development process. To this aim, preclinical studies are routinely performed, even if they are only qualitatively analyzed due to the lack of generally applicable mathematical models. This paper presents a new pharmacokinetic-pharmacodynamic model that, starting from the well-known single agent Simeoni TGI model, is able to describe tumor growth in xenograft mice after the co-administration of two anticancer agents. Due to the drug action, tumor cells are divided in two groups: damaged and not damaged ones. The damaging rate has two terms proportional to drug concentrations (as in the single drug administration model) and one interaction term proportional to their product. Six of the eight pharmacodynamic parameters assume the same value as in the corresponding single drug models. Only one parameter summarizes the interaction, and it can be used to compute two important indexes that are a clear way to score the synergistic/antagonistic interaction among drug effects. The model was successfully applied to four new compounds co-administered with four drugs already available on the market for the treatment of three different tumor cell lines. It also provided reliable predictions of different combination regimens in which the same drugs were administered at different doses/schedules. A good and quantitative measurement of the intensity and nature of interaction between drug effects, as well as the capability to correctly predict new combination arms, suggest the use of this generally applicable model for supporting the experiment optimal design and the prioritization of different therapies.

[Cutaneous Malassezia infections and Malassezia associated dermatoses: An update].

PubMed

Nenoff, P; Krüger, C; Mayser, P

2015-06-01

The lipophilic yeast fungus Malassezia (M.) spp. is the only fungal genus or species which is part of the physiological human microbiome. Today, at least 14 different Malassezia species are known; most of them can only be identified using molecular biological techniques. As a facultative pathogenic microorganism, Malassezia represents the causative agent both of superficial cutaneous infections and of blood stream infections. Pityriasis versicolor is the probably most frequent infection caused by Malassezia. Less common, Malassezia folliculitis occurs. There is only an episodic report on Malassezia-induced onychomycosis. Seborrhoeic dermatitis represents a Malassezia-associated inflammatory dermatosis. In addition, Malassezia allergenes should be considered as the trigger of "Head-Neck"-type atopic dermatitis. Ketoconazole possesses the strongest in vitro activity against Malassezia, and represents the treatment of choice for topical therapy of pityriasis versicolor. Alternatives include other azole antifungals but also the allylamine terbinafine and the hydroxypyridone antifungal agent ciclopirox olamine. "Antiseborrhoeic" agents, e.g. zinc pyrithione, selenium disulfide, and salicylic acid, are also effective in pityriasis versicolor. The drug of choice for oral treatment of pityriasis versicolor is itraconazole; an effective alternative represents fluconazole. Seborrhoeic dermatitis is best treated with topical medication, including topical corticosteroids and antifungal agents like ketoconazole or sertaconazole. Calcineurin inhibitors, e.g. pimecrolimus and tacrolimus, are reliable in seborrhoeic dermatitis, however are used off-label.

Conversational Agents in E-Learning

NASA Astrophysics Data System (ADS)

Kerry, Alice; Ellis, Richard; Bull, Susan

This paper discusses the use of natural language or 'conversational' agents in e-learning environments. We describe and contrast the various applications of conversational agent technology represented in the e-learning literature, including tutors, learning companions, language practice and systems to encourage reflection. We offer two more detailed examples of conversational agents, one which provides learning support, and the other support for self-assessment. Issues and challenges for developers of conversational agent systems for e-learning are identified and discussed.

Furan-based benzene mono- and dicarboxylic acid derivatives as multiple inhibitors of the bacterial Mur ligases (MurC-MurF): experimental and computational characterization.

PubMed

Perdih, Andrej; Hrast, Martina; Pureber, Kaja; Barreteau, Hélène; Grdadolnik, Simona Golič; Kocjan, Darko; Gobec, Stanislav; Solmajer, Tom; Wolber, Gerhard

2015-06-01

Bacterial resistance to the available antibiotic agents underlines an urgent need for the discovery of novel antibacterial agents. Members of the bacterial Mur ligase family MurC-MurF involved in the intracellular stages of the bacterial peptidoglycan biosynthesis have recently emerged as a collection of attractive targets for novel antibacterial drug design. In this study, we have first extended the knowledge of the class of furan-based benzene-1,3-dicarboxylic acid derivatives by first showing a multiple MurC-MurF ligase inhibition for representatives of the extended series of this class. Steady-state kinetics studies on the MurD enzyme were performed for compound 1, suggesting a competitive inhibition with respect to ATP. To the best of our knowledge, compound 1 represents the first ATP-competitive MurD inhibitor reported to date with concurrent multiple inhibition of all four Mur ligases (MurC-MurF). Subsequent molecular dynamic (MD) simulations coupled with interaction energy calculations were performed for two alternative in silico models of compound 1 in the UMA/D-Glu- and ATP-binding sites of MurD, identifying binding in the ATP-binding site as energetically more favorable in comparison to the UMA/D-Glu-binding site, which was in agreement with steady-state kinetic data. In the final stage, based on the obtained MD data novel furan-based benzene monocarboxylic acid derivatives 8-11, exhibiting multiple Mur ligase (MurC-MurF) inhibition with predominantly superior ligase inhibition over the original series, were discovered and for compound 10 it was shown to possess promising antibacterial activity against S. aureus. These compounds represent novel leads that could by further optimization pave the way to novel antibacterial agents.

Furan-based benzene mono- and dicarboxylic acid derivatives as multiple inhibitors of the bacterial Mur ligases (MurC-MurF): experimental and computational characterization

NASA Astrophysics Data System (ADS)

Perdih, Andrej; Hrast, Martina; Pureber, Kaja; Barreteau, Hélène; Grdadolnik, Simona Golič; Kocjan, Darko; Gobec, Stanislav; Solmajer, Tom; Wolber, Gerhard

2015-06-01

Bacterial resistance to the available antibiotic agents underlines an urgent need for the discovery of novel antibacterial agents. Members of the bacterial Mur ligase family MurC-MurF involved in the intracellular stages of the bacterial peptidoglycan biosynthesis have recently emerged as a collection of attractive targets for novel antibacterial drug design. In this study, we have first extended the knowledge of the class of furan-based benzene-1,3-dicarboxylic acid derivatives by first showing a multiple MurC-MurF ligase inhibition for representatives of the extended series of this class. Steady-state kinetics studies on the MurD enzyme were performed for compound 1, suggesting a competitive inhibition with respect to ATP. To the best of our knowledge, compound 1 represents the first ATP-competitive MurD inhibitor reported to date with concurrent multiple inhibition of all four Mur ligases (MurC-MurF). Subsequent molecular dynamic (MD) simulations coupled with interaction energy calculations were performed for two alternative in silico models of compound 1 in the UMA/ d-Glu- and ATP-binding sites of MurD, identifying binding in the ATP-binding site as energetically more favorable in comparison to the UMA/ d-Glu-binding site, which was in agreement with steady-state kinetic data. In the final stage, based on the obtained MD data novel furan-based benzene monocarboxylic acid derivatives 8- 11, exhibiting multiple Mur ligase (MurC-MurF) inhibition with predominantly superior ligase inhibition over the original series, were discovered and for compound 10 it was shown to possess promising antibacterial activity against S. aureus. These compounds represent novel leads that could by further optimization pave the way to novel antibacterial agents.

Functional Information: Towards Synthesis of Biosemiotics and Cybernetics

PubMed Central

Sharov, Alexei A.

2012-01-01

Biosemiotics and cybernetics are closely related, yet they are separated by the boundary between life and non-life: biosemiotics is focused on living organisms, whereas cybernetics is applied mostly to non-living artificial devices. However, both classes of systems are agents that perform functions necessary for reaching their goals. I propose to shift the focus of biosemiotics from living organisms to agents in general, which all belong to a pragmasphere or functional universe. Agents should be considered in the context of their hierarchy and origin because their semiosis can be inherited or induced by higher-level agents. To preserve and disseminate their functions, agents use functional information - a set of signs that encode and control their functions. It includes stable memory signs, transient messengers, and natural signs. The origin and evolution of functional information is discussed in terms of transitions between vegetative, animal, and social levels of semiosis, defined by Kull. Vegetative semiosis differs substantially from higher levels of semiosis, because signs are recognized and interpreted via direct code-based matching and are not associated with ideal representations of objects. Thus, I consider a separate classification of signs at the vegetative level that includes proto-icons, proto-indexes, and proto-symbols. Animal and social semiosis are based on classification, and modeling of objects, which represent the knowledge of agents about their body (Innenwelt) and environment (Umwelt). PMID:22368439

Prostate cancer chemoprevention agent development: the National Cancer Institute, Division of Cancer Prevention portfolio.

PubMed

Parnes, Howard L; House, Margaret G; Kagan, Jacob; Kausal, David J; Lieberman, Ronald

2004-02-01

We describe the current National Cancer Institute chemoprevention agent development program and provide a summary of the intermediate end points used. The National Cancer Institute is currently sponsoring a wide range of studies of promising chemoprevention agents in a variety of informative cohorts, eg high grade prostatic intraepithelial neoplasia, positive family history of cancer, increased prostate specific antigen with negative biopsies, prostate cancer followed expectantly, prostate cancer awaiting definitive therapy and the general population. The rationale for each agent under investigation is derived from epidemiological observations, prostate cancer treatment trials, secondary analyses of large cancer prevention studies, an understanding of cancer biology and prostate carcinogenesis, and/or experimental animal models. Carcinogenesis is a multistep process occurring over decades which is characterized by disruption of the normal regulatory pathways controlling cellular proliferation, programmed cell death and differentiation. Administration of agents to reverse, inhibit or slow this process of malignant transformation is known as chemoprevention. Chemoprevention represents a promising approach to reducing the morbidity and mortality of prostate cancer. A variety of agents are currently being studied in phase 2 clinical trials, some of which may warrant subsequent evaluation in phase 3 trials with definitive cancer end points. Two large phase 3 trials, the Prostate Cancer Prevention Trial and the Selenium and Vitamin E Cancer Prevention Trial, which are ongoing, are also sponsored by the National Cancer Institute.

Functional Information: Towards Synthesis of Biosemiotics and Cybernetics.

PubMed

Sharov, Alexei A

2010-04-27

Biosemiotics and cybernetics are closely related, yet they are separated by the boundary between life and non-life: biosemiotics is focused on living organisms, whereas cybernetics is applied mostly to non-living artificial devices. However, both classes of systems are agents that perform functions necessary for reaching their goals. I propose to shift the focus of biosemiotics from living organisms to agents in general, which all belong to a pragmasphere or functional universe. Agents should be considered in the context of their hierarchy and origin because their semiosis can be inherited or induced by higher-level agents. To preserve and disseminate their functions, agents use functional information - a set of signs that encode and control their functions. It includes stable memory signs, transient messengers, and natural signs. The origin and evolution of functional information is discussed in terms of transitions between vegetative, animal, and social levels of semiosis, defined by Kull. Vegetative semiosis differs substantially from higher levels of semiosis, because signs are recognized and interpreted via direct code-based matching and are not associated with ideal representations of objects. Thus, I consider a separate classification of signs at the vegetative level that includes proto-icons, proto-indexes, and proto-symbols. Animal and social semiosis are based on classification, and modeling of objects, which represent the knowledge of agents about their body (Innenwelt) and environment (Umwelt).

Analysis of a decision model in the context of equilibrium pricing and order book pricing

NASA Astrophysics Data System (ADS)

Wagner, D. C.; Schmitt, T. A.; Schäfer, R.; Guhr, T.; Wolf, D. E.

2014-12-01

An agent-based model for financial markets has to incorporate two aspects: decision making and price formation. We introduce a simple decision model and consider its implications in two different pricing schemes. First, we study its parameter dependence within a supply-demand balance setting. We find realistic behavior in a wide parameter range. Second, we embed our decision model in an order book setting. Here, we observe interesting features which are not present in the equilibrium pricing scheme. In particular, we find a nontrivial behavior of the order book volumes which reminds of a trend switching phenomenon. Thus, the decision making model alone does not realistically represent the trading and the stylized facts. The order book mechanism is crucial.

Petri Nets as Modeling Tool for Emergent Agents

NASA Technical Reports Server (NTRS)

Bergman, Marto

2004-01-01

Emergent agents, those agents whose local interactions can cause unexpected global results, require a method of modeling that is both dynamic and structured Petri Nets, a modeling tool developed for dynamic discrete event system of mainly functional agents, provide this, and have the benefit of being an established tool. We present here the details of the modeling method here and discuss how to implement its use for modeling agent-based systems. Petri Nets have been used extensively in the modeling of functional agents, those agents who have defined purposes and whose actions should result in a know outcome. However, emergent agents, those agents who have a defined structure but whose interaction causes outcomes that are unpredictable, have not yet found a modeling style that suits them. A problem with formally modeling emergent agents that any formal modeling style usually expects to show the results of a problem and the results of problems studied using emergent agents are not apparent from the initial construction. However, the study of emergent agents still requires a method to analyze the agents themselves, and have sensible conversation about the differences and similarities between types of emergent agents. We attempt to correct this problem by applying Petri Nets to the characterization of emergent agents. In doing so, the emergent properties of these agents can be highlighted, and conversation about the nature and compatibility of the differing methods of agent creation can begin.

Integrating the simulation of domestic water demand behaviour to an urban water model using agent based modelling

NASA Astrophysics Data System (ADS)

Koutiva, Ifigeneia; Makropoulos, Christos

2015-04-01

The urban water system's sustainable evolution requires tools that can analyse and simulate the complete cycle including both physical and cultural environments. One of the main challenges, in this regard, is the design and development of tools that are able to simulate the society's water demand behaviour and the way policy measures affect it. The effects of these policy measures are a function of personal opinions that subsequently lead to the formation of people's attitudes. These attitudes will eventually form behaviours. This work presents the design of an ABM tool for addressing the social dimension of the urban water system. The created tool, called Urban Water Agents' Behaviour (UWAB) model, was implemented, using the NetLogo agent programming language. The main aim of the UWAB model is to capture the effects of policies and environmental pressures to water conservation behaviour of urban households. The model consists of agents representing urban households that are linked to each other creating a social network that influences the water conservation behaviour of its members. Household agents are influenced as well by policies and environmental pressures, such as drought. The UWAB model simulates behaviour resulting in the evolution of water conservation within an urban population. The final outcome of the model is the evolution of the distribution of different conservation levels (no, low, high) to the selected urban population. In addition, UWAB is implemented in combination with an existing urban water management simulation tool, the Urban Water Optioneering Tool (UWOT) in order to create a modelling platform aiming to facilitate an adaptive approach of water resources management. For the purposes of this proposed modelling platform, UWOT is used in a twofold manner: (1) to simulate domestic water demand evolution and (2) to simulate the response of the water system to the domestic water demand evolution. The main advantage of the UWAB - UWOT model integration is that it allows the investigation of the effects of different water demand management strategies to an urban population's water demand behaviour and ultimately the effects of these policies to the volume of domestic water demand and the water resources system. The proposed modelling platform is optimised to simulate the effects of water policies during the Athens drought period of 1988-1994. The calibrated modelling platform is then applied to evaluate scenarios of water supply, water demand and water demand management strategies.

An agent-based model for an air emissions cap and trade program: A case study in Taiwan.

PubMed

Huang, Hsing-Fu; Ma, Hwong-Wen

2016-12-01

To determine the actual status of individuals in a system and the trading interaction between polluters, this study uses an agent-based model to set up a virtual world that represents the Kaohsiung and Pingtung regions in Taiwan, which are under the country's air emissions cap and trade program. The model can simulate each controlled industry's dynamic behavioral condition with the bottom-up method and can investigate the impact of the program and determine the industry's emissions reduction and trading condition. This model can be used elastically to predict the impact of the trading market through adjusting different settings of the program rules or combining the settings with other measures. The simulation results show that the emissions trading market has an oversupply, but we find that the market trading amounts are low. Additionally, we find that increasing the air pollution fee and offset rate restrains the agents' trading decision, according to the simulation results of each scenario. In particular, NO x and SO x trading amounts are easily impacted by the pollution fee, reduction rate, and offset rate. Also, the more transparent the market, the more it can help polluters trade. Therefore, if authorities want to intervene in the emissions trading market, they must be careful in adjusting the air pollution fee and program rules; otherwise, the trading market system cannot work effectively. We also suggest setting up a trading platform to help the dealers negotiate successfully. Copyright © 2016 Elsevier Ltd. All rights reserved.

Zebrafish (Danio rerio): A Potential Model for Toxinological Studies.

PubMed

Vargas, Rafael Antonio; Sarmiento, Karen; Vásquez, Isabel Cristina

2015-10-01

Zebrafish are an emerging basic biomedical research model that has multiple advantages compared with other research models. Given that biotoxins, such as toxins, poisons, and venoms, represent health hazards to animals and humans, a low-cost biological model that is highly sensitive to biotoxins is useful to understand the damage caused by such agents and to develop biological tests to prevent and reduce the risk of poisoning in potential cases of bioterrorism or food contamination. In this article, a narrative review of the general aspects of zebrafish as a model in basic biomedical research and various studies in the field of toxinology that have used zebrafish as a biological model are presented. This information will provide useful material to beginner students and researchers who are interested in developing toxinological studies with the zebrafish model.

Micro-foundations for macroeconomics: New set-up based on statistical physics

NASA Astrophysics Data System (ADS)

Yoshikawa, Hiroshi

2016-12-01

Modern macroeconomics is built on "micro foundations." Namely, optimization of micro agent such as consumer and firm is explicitly analyzed in model. Toward this goal, standard model presumes "the representative" consumer/firm, and analyzes its behavior in detail. However, the macroeconomy consists of 107 consumers and 106 firms. For the purpose of analyzing such macro system, it is meaningless to pursue the micro behavior in detail. In this respect, there is no essential difference between economics and physics. The method of statistical physics can be usefully applied to the macroeconomy, and provides Keynesian economics with correct micro-foundations.

Molecular Targeted Therapies Using Botanicals for Prostate Cancer Chemoprevention.

PubMed

Kumar, Nagi; Chornokur, Ganna

2012-12-31

In spite of the large number of botanicals demonstrating promise as potential cancer chemopreventive agents, most have failed to prove effectiveness in clinical trials. Critical requirements for moving botanical agents to recommendation for clinical use include adopting a systematic, molecular-target based approach and utilizing the same ethical and rigorous methods that are used to evaluate other pharmacological agents. Preliminary data on a mechanistic rationale for chemoprevention activity as observed from epidemiological, in vitro and preclinical studies, phase I data of safety in suitable cohorts, duration of intervention based on time to progression of pre-neoplastic disease to cancer and using a valid panel of biomarkers representing the hypothesized carcinogenesis pathway for measuring efficacy must inform the design of clinical trials. Botanicals have been shown to influence multiple biochemical and molecular cascades that inhibit mutagenesis, proliferation, induce apoptosis, suppress the formation and growth of human cancers, thus modulating several hallmarks of carcinogenesis. These agents appear promising in their potential to make a dramatic impact in cancer prevention and treatment, with a significantly superior safety profile than most agents evaluated to date. The goal of this paper is to provide models of translational research based on the current evidence of promising botanicals with a specific focus on targeted therapies for PCa chemoprevention.

Molecular Targeted Therapies Using Botanicals for Prostate Cancer Chemoprevention

PubMed Central

Kumar, Nagi; Chornokur, Ganna

2014-01-01

In spite of the large number of botanicals demonstrating promise as potential cancer chemopreventive agents, most have failed to prove effectiveness in clinical trials. Critical requirements for moving botanical agents to recommendation for clinical use include adopting a systematic, molecular-target based approach and utilizing the same ethical and rigorous methods that are used to evaluate other pharmacological agents. Preliminary data on a mechanistic rationale for chemoprevention activity as observed from epidemiological, in vitro and preclinical studies, phase I data of safety in suitable cohorts, duration of intervention based on time to progression of pre-neoplastic disease to cancer and using a valid panel of biomarkers representing the hypothesized carcinogenesis pathway for measuring efficacy must inform the design of clinical trials. Botanicals have been shown to influence multiple biochemical and molecular cascades that inhibit mutagenesis, proliferation, induce apoptosis, suppress the formation and growth of human cancers, thus modulating several hallmarks of carcinogenesis. These agents appear promising in their potential to make a dramatic impact in cancer prevention and treatment, with a significantly superior safety profile than most agents evaluated to date. The goal of this paper is to provide models of translational research based on the current evidence of promising botanicals with a specific focus on targeted therapies for PCa chemoprevention. PMID:24527269

Bromomethylthioindole Inspired Carbazole Hybrids as Promising Class of Anti-MRSA Agents

PubMed Central

2016-01-01

Series of N-substituted carbazole analogues bearing an indole ring were synthesized as anti-methicillin-resistant Staphylococcus aureus (MRSA) agents from a molecular hybridization approach. The representative compound 19 showed an MIC = 1 μg/mL against a panel of MRSA clinical isolates as it possessed comparable in vitro activities to that of vancomycin. Moreover, compound 19 also exhibited MIC = 1 μg/mL activities against a recent identified Z172 MRSA strain (vancomycin-intermediate and daptomycin-nonsusceptible phenotype) and the vancomycin-resistant Enterococcus faecalis (VRE) strain. In a mouse model with lethal infection of MRSA (4N216), a 75% survival rate was observed after a single dose of compound 19 was intravenously administered at 20 mg/kg. In light of their equipotent activities against different MRSA isolates and VRE strain, the data underscore the importance of designed hybrid series for the development of new N-substituted carbazoles as potential anti-MRSA agents. PMID:27994762

Formal Darwinism, the individual-as-maximizing-agent analogy and bet-hedging

PubMed Central

Grafen, A.

1999-01-01

The central argument of The origin of species was that mechanical processes (inheritance of features and the differential reproduction they cause) can give rise to the appearance of design. The 'mechanical processes' are now mathematically represented by the dynamic systems of population genetics, and the appearance of design by optimization and game theory in which the individual plays the part of the maximizing agent. Establishing a precise individual-as-maximizing-agent (IMA) analogy for a population-genetics system justifies optimization approaches, and so provides a modern formal representation of the core of Darwinism. It is a hitherto unnoticed implication of recent population-genetics models that, contrary to a decades-long consensus, an IMA analogy can be found in models with stochastic environments (subject to a convexity assumption), in which individuals maximize expected reproductive value. The key is that the total reproductive value of a species must be considered as constant, so therefore reproductive value should always be calculated in relative terms. This result removes a major obstacle from the theoretical challenge to find a unifying framework which establishes the IMA analogy for all of Darwinian biology, including as special cases inclusive fitness, evolutionarily stable strategies, evolutionary life-history theory, age-structured models and sex ratio theory. This would provide a formal, mathematical justification of fruitful and widespread but 'intentional' terms in evolutionary biology, such as 'selfish', 'altruism' and 'conflict'.

Agent-based mathematical modeling as a tool for estimating Trypanosoma cruzi vector-host contact rates.

PubMed

Yong, Kamuela E; Mubayi, Anuj; Kribs, Christopher M

2015-11-01

The parasite Trypanosoma cruzi, spread by triatomine vectors, affects over 100 mammalian species throughout the Americas, including humans, in whom it causes Chagas' disease. In the U.S., only a few autochthonous cases have been documented in humans, but prevalence is high in sylvatic hosts (primarily raccoons in the southeast and woodrats in Texas). The sylvatic transmission of T. cruzi is spread by the vector species Triatoma sanguisuga and Triatoma gerstaeckeri biting their preferred hosts and thus creating multiple interacting vector-host cycles. The goal of this study is to quantify the rate of contacts between different host and vector species native to Texas using an agent-based model framework. The contact rates, which represent bites, are required to estimate transmission coefficients, which can be applied to models of infection dynamics. In addition to quantitative estimates, results confirm host irritability (in conjunction with host density) and vector starvation thresholds and dispersal as determining factors for vector density as well as host-vector contact rates. Copyright © 2015 Elsevier B.V. All rights reserved.

Development and validation of a risk-prediction nomogram for in-hospital mortality in adults poisoned with drugs and nonpharmaceutical agents

PubMed Central

Lionte, Catalina; Sorodoc, Victorita; Jaba, Elisabeta; Botezat, Alina

2017-01-01

Abstract Acute poisoning with drugs and nonpharmaceutical agents represents an important challenge in the emergency department (ED). The objective is to create and validate a risk-prediction nomogram for use in the ED to predict the risk of in-hospital mortality in adults from acute poisoning with drugs and nonpharmaceutical agents. This was a prospective cohort study involving adults with acute poisoning from drugs and nonpharmaceutical agents admitted to a tertiary referral center for toxicology between January and December 2015 (derivation cohort) and between January and June 2016 (validation cohort). We used a program to generate nomograms based on binary logistic regression predictive models. We included variables that had significant associations with death. Using regression coefficients, we calculated scores for each variable, and estimated the event probability. Model validation was performed using bootstrap to quantify our modeling strategy and using receiver operator characteristic (ROC) analysis. The nomogram was tested on a separate validation cohort using ROC analysis and goodness-of-fit tests. Data from 315 patients aged 18 to 91 years were analyzed (n = 180 in the derivation cohort; n = 135 in the validation cohort). In the final model, the following variables were significantly associated with mortality: age, laboratory test results (lactate, potassium, MB isoenzyme of creatine kinase), electrocardiogram parameters (QTc interval), and echocardiography findings (E wave velocity deceleration time). Sex was also included to use the same model for men and women. The resulting nomogram showed excellent survival/mortality discrimination (area under the curve [AUC] 0.976, 95% confidence interval [CI] 0.954–0.998, P < 0.0001 for the derivation cohort; AUC 0.957, 95% CI 0.892–1, P < 0.0001 for the validation cohort). This nomogram provides more precise, rapid, and simple risk-analysis information for individual patients acutely exposed to drugs and nonpharmaceutical agents, and accurately estimates the probability of in-hospital death, exclusively using the results of objective tests available in the ED. PMID:28328838

Functional insights from proteome-wide structural modeling of Treponema pallidum subspecies pallidum, the causative agent of syphilis.

PubMed

Houston, Simon; Lithgow, Karen Vivien; Osbak, Kara Krista; Kenyon, Chris Richard; Cameron, Caroline E

2018-05-16

Syphilis continues to be a major global health threat with 11 million new infections each year, and a global burden of 36 million cases. The causative agent of syphilis, Treponema pallidum subspecies pallidum, is a highly virulent bacterium, however the molecular mechanisms underlying T. pallidum pathogenesis remain to be definitively identified. This is due to the fact that T. pallidum is currently uncultivatable, inherently fragile and thus difficult to work with, and phylogenetically distinct with no conventional virulence factor homologs found in other pathogens. In fact, approximately 30% of its predicted protein-coding genes have no known orthologs or assigned functions. Here we employed a structural bioinformatics approach using Phyre2-based tertiary structure modeling to improve our understanding of T. pallidum protein function on a proteome-wide scale. Phyre2-based tertiary structure modeling generated high-confidence predictions for 80% of the T. pallidum proteome (780/978 predicted proteins). Tertiary structure modeling also inferred the same function as primary structure-based annotations from genome sequencing pipelines for 525/605 proteins (87%), which represents 54% (525/978) of all T. pallidum proteins. Of the 175 T. pallidum proteins modeled with high confidence that were not assigned functions in the previously annotated published proteome, 167 (95%) were able to be assigned predicted functions. Twenty-one of the 175 hypothetical proteins modeled with high confidence were also predicted to exhibit significant structural similarity with proteins experimentally confirmed to be required for virulence in other pathogens. Phyre2-based structural modeling is a powerful bioinformatics tool that has provided insight into the potential structure and function of the majority of T. pallidum proteins and helped validate the primary structure-based annotation of more than 50% of all T. pallidum proteins with high confidence. This work represents the first T. pallidum proteome-wide structural modeling study and is one of few studies to apply this approach for the functional annotation of a whole proteome.

A Multi-Level Model of Information Seeking in the Clinical Domain

PubMed Central

Hung, Peter W.; Johnson, Stephen B.; Kaufman, David R.; Mendonça, Eneida A.

2008-01-01

Objective: Clinicians often have difficulty translating information needs into effective search strategies to find appropriate answers. Information retrieval systems employing an intelligent search agent that generates adaptive search strategies based on human search expertise could be helpful in meeting clinician information needs. A prerequisite for creating such systems is an information seeking model that facilitates the representation of human search expertise. The purpose of developing such a model is to provide guidance to information seeking system development and to shape an empirical research program. Design: The information seeking process was modeled as a complex problem-solving activity. After considering how similarly complex activities had been modeled in other domains, we determined that modeling context-initiated information seeking across multiple problem spaces allows the abstraction of search knowledge into functionally consistent layers. The knowledge layers were identified in the information science literature and validated through our observations of searches performed by health science librarians. Results: A hierarchical multi-level model of context-initiated information seeking is proposed. Each level represents (1) a problem space that is traversed during the online search process, and (2) a distinct layer of knowledge that is required to execute a successful search. Grand strategy determines what information resources will be searched, for what purpose, and in what order. The strategy level represents an overall approach for searching a single resource. Tactics are individual moves made to further a strategy. Operations are mappings of abstract intentions to information resource-specific concrete input. Assessment is the basis of interaction within the strategic hierarchy, influencing the direction of the search. Conclusion: The described multi-level model provides a framework for future research and the foundation for development of an automated information retrieval system that uses an intelligent search agent to bridge clinician information needs and human search expertise. PMID:18006383

Simulating farmer behaviour under water markets

NASA Astrophysics Data System (ADS)

Padula, SIlvia; Erfani, Tohid; Henriques, Catarina; Maziotis, Alexandros; Garbe, Jennifer; Swinscoe, Thomas; Harou, Julien; Weatherhead, Keith; Beevers, Lindsay; Fleskens, Luuk

2015-04-01

Increasing water scarcity may lead water managers to consider alternative approaches to water allocation including water markets. One concern with markets is how will specific sectors interact with a potential water market, when will they gain or loose water and will they benefit economically - why, when and how? The behaviours of different individual abstractors or institutional actors under water markets is of interest to regulators who seek to design effective market policies which satisfy multiple stakeholder groups. In this study we consider two dozen agricultural water users in eastern England (Nar basin). Using partially synthetic but regionally representative cropping and irrigation data we simulate the buying and selling behaviour of farmers on a weekly basis over multiple years. The impact of on-farm water storage is assessed for farmers who own a reservoir. A river-basin-scale hydro-economic multi-agent model is used that represents individual abstractors and can simulate a spot market under various licensing regimes. Weekly varying economic demand curves for water are calibrated based on historical climate and water use data. The model represents the trade-off between current use value and expected gains from trade to reach weekly decisions. Early results are discussed and model limitations and possible extensions are presented.

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.

The Internet Knowledge Manager, Dynamic Digital Libraries, and Agents You Can Understand.

ERIC Educational Resources Information Center

Walker, Adrian

1998-01-01

Discusses the Internet Knowledge Manager (IKM) which provides an understandable way of representing knowledge, as readable software agents. Gives an example of writing and running an IKM agent for transfer pricing in corporations. Describes how the technology works. Concludes that the IKM could trigger new ways of performing knowledge management,…

Avatars, Pedagogical Agents, and Virtual Environments: Social Learning Systems Online

ERIC Educational Resources Information Center

Ausburn, Lynna J.; Martens, Jon; Dotterer, Gary; Calhoun, Pat

2009-01-01

This paper presents a review of literature that introduces major concepts and issues in using avatars and pedagogical agents in first- and second-person virtual environments (VEs) for learning online. In these VEs, avatars and pedagogical agents represent self and other learners/participants or serve as personal learning "guides". The…

Collective Machine Learning: Team Learning and Classification in Multi-Agent Systems

ERIC Educational Resources Information Center

Gifford, Christopher M.

2009-01-01

This dissertation focuses on the collaboration of multiple heterogeneous, intelligent agents (hardware or software) which collaborate to learn a task and are capable of sharing knowledge. The concept of collaborative learning in multi-agent and multi-robot systems is largely under studied, and represents an area where further research is needed to…

Organic molecule-based photothermal agents: an expanding photothermal therapy universe.

PubMed

Jung, Hyo Sung; Verwilst, Peter; Sharma, Amit; Shin, Jinwoo; Sessler, Jonathan L; Kim, Jong Seung

2018-04-03

Over the last decade, organic photothermal therapy (PTT) agents have attracted increasing attention as a potential complement for, or alternative to, classical drugs and sensitizers involving inorganic nanomaterials. In this tutorial review, we provide a structured description of the main classes of organic photothermal agents and their characteristics. Representative agents that have been studied in the context of photothermal therapy since 2000 are summarized and recent advances in using PTT agents to address various cancers indications are highlighted.

Patient-specific orthotopic glioblastoma xenograft models recapitulate the histopathology and biology of human glioblastomas in situ.

PubMed

Joo, Kyeung Min; Kim, Jinkuk; Jin, Juyoun; Kim, Misuk; Seol, Ho Jun; Muradov, Johongir; Yang, Heekyoung; Choi, Yoon-La; Park, Woong-Yang; Kong, Doo-Sik; Lee, Jung-Il; Ko, Young-Hyeh; Woo, Hyun Goo; Lee, Jeongwu; Kim, Sunghoon; Nam, Do-Hyun

2013-01-31

Frequent discrepancies between preclinical and clinical results of anticancer agents demand a reliable translational platform that can precisely recapitulate the biology of human cancers. Another critical unmet need is the ability to predict therapeutic responses for individual patients. Toward this goal, we have established a library of orthotopic glioblastoma (GBM) xenograft models using surgical samples of GBM patients. These patient-specific GBM xenograft tumors recapitulate histopathological properties and maintain genomic characteristics of parental GBMs in situ. Furthermore, in vivo irradiation, chemotherapy, and targeted therapy of these xenograft tumors mimic the treatment response of parental GBMs. We also found that establishment of orthotopic xenograft models portends poor prognosis of GBM patients and identified the gene signatures and pathways signatures associated with the clinical aggressiveness of GBMs. Together, the patient-specific orthotopic GBM xenograft library represent the preclinically and clinically valuable "patient tumor's phenocopy" that represents molecular and functional heterogeneity of GBMs. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

Ventral tegmental area/substantia nigra and prefrontal cortex rodent organotypic brain slices as an integrated model to study the cellular changes induced by oxygen/glucose deprivation and reperfusion: effect of neuroprotective agents.

PubMed

Colombo, Laura; Parravicini, Chiara; Lecca, Davide; Dossi, Elena; Heine, Claudia; Cimino, Mauro; Wanke, Enzo; Illes, Peter; Franke, Heike; Abbracchio, Maria P

2014-01-01

Unveiling the roles of distinct cell types in brain response to insults is a partially unsolved challenge and a key issue for new neuroreparative approaches. In vivo models are not able to dissect the contribution of residential microglia and infiltrating blood-borne monocytes/macrophages, which are fundamentally undistinguishable; conversely, cultured cells lack original tissue anatomical and functional complexity, which profoundly alters reactivity. Here, we tested whether rodent organotypic co-cultures from mesencephalic ventral tegmental area/substantia nigra and prefrontal cortex (VTA/SN-PFC) represent a suitable model to study changes induced by oxygen/glucose deprivation and reperfusion (OGD/R). OGD/R induced cytotoxicity to both VTA/SN and PFC slices, with higher VTA/SN susceptibility. Neurons were highly affected, with astrocytes and oligodendrocytes undergoing very mild damage. Marked reactive astrogliosis was also evident. Notably, OGD/R triggered the activation of CD68-expressing microglia and increased expression of Ym1 and Arg1, two markers of "alternatively" activated beneficial microglia. Treatment with two well-known neuroprotective drugs, the anticonvulsant agent valproic acid and the purinergic P2-antagonist PPADS, prevented neuronal damage. Thus, VTA/SN-PFC cultures are an integrated model to investigate OGD/R-induced effects on distinct cells and easily screen neuroprotective agents. The model is particularly adequate to dissect the microglia phenotypic shift in the lack of a functional vascular compartment. Copyright © 2014 Elsevier Ltd. All rights reserved.

Combination of the MEK inhibitor pimasertib with BTK or PI3K-delta inhibitors is active in preclinical models of aggressive lymphomas.

PubMed

Gaudio, E; Tarantelli, C; Kwee, I; Barassi, C; Bernasconi, E; Rinaldi, A; Ponzoni, M; Cascione, L; Targa, A; Stathis, A; Goodstal, S; Zucca, E; Bertoni, F

2016-06-01

Lymphomas are among the most common human cancers and represent the cause of death for still too many patients. The B-cell receptor with its downstream signaling pathways represents an important therapeutic target for B-cell lymphomas. Here, we evaluated the activity of the MEK1/2 inhibitor pimasertib as single agent and in combination with other targeted drugs in lymphoma preclinical models. Cell lines derived mature B-cell lymphomas were exposed to increasing doses of pimasertib alone. Immunoblotting and gene expression profiling were performed. Combination of pimasertib with idelalisib or ibrutinib was assessed. Pimasertib as single agent exerted a dose-dependent antitumor activity across a panel of 23 lymphoma cell lines, although at concentrations higher than reported for solid tumors. Strong synergism was observed with pimasertib combined with the PI3K inhibitor idelalisib and the BTK inhibitor ibrutinib in cell lines derived from diffuse large B-cell lymphoma (DLBCL) and mantle cell lymphoma. The data were confirmed in an in vivo experiment treating DLBCL xenografts with pimasertib and ibrutinib. The data presented here provide the basis for further investigation of regimens including pimasertib in relapsed and refractory lymphomas. © The Author 2016. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Artificial intelligence based decision support for trumpeter swan management

USGS Publications Warehouse

Sojda, Richard S.

2002-01-01

The number of trumpeter swans (Cygnus buccinator) breeding in the Tri-State area where Montana, Idaho, and Wyoming come together has declined to just a few hundred pairs. However, these birds are part of the Rocky Mountain Population which additionally has over 3,500 birds breeding in Alberta, British Columbia, Northwest Territories, and Yukon Territory. To a large degree, these birds seem to have abandoned traditional migratory pathways in the flyway. Waterfowl managers have been interested in decision support tools that would help them explore simulated management scenarios in their quest towards reaching population recovery and the reestablishment of traditional migratory pathways. I have developed a decision support system to assist biologists with such management, especially related to wetland ecology. Decision support systems use a combination of models, analytical techniques, and information retrieval to help develop and evaluate appropriate alternatives. Swan management is a domain that is ecologically complex, and this complexity is compounded by spatial and temporal issues. As such, swan management is an inherently distributed problem. Therefore, the ecological context for modeling swan movements in response to management actions was built as a multiagent system of interacting intelligent agents that implements a queuing model representing swan migration. These agents accessed ecological knowledge about swans, their habitats, and flyway management principles from three independent expert systems. The agents were autonomous, had some sensory capability, and could respond to changing conditions. A key problem when developing ecological decision support systems is empirically determining that the recommendations provided are valid. Because Rocky Mountain trumpeter swans have been surveyed for a long period of time, I was able to compare simulated distributions provided by the system with actual field observations across 20 areas for the period 1988-2000. Applying the Matched Pairs Multivariate Permutation Test as a statistical tool was a new approach for comparing flyway distributions of waterfowl over time that seemed to work well. Based on this approach, the empirical evidence that I gathered led me to conclude that the base queuing model does accurately simulate swan distributions in the flyway. The system was insensitive to almost all model parameters tested. That remains perplexing, but might result from the base queuing model, itself, being particularly effective at representing the actual ecological diversity in the world of Rocky Mountain trumpeter swans, both spatial and temporally.

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.

Marine guanidine alkaloids crambescidins inhibit tumor growth and activate intrinsic apoptotic signaling inducing tumor regression in a colorectal carcinoma zebrafish xenograft model.

PubMed

Roel, María; Rubiolo, Juan A; Guerra-Varela, Jorge; Silva, Siguara B L; Thomas, Olivier P; Cabezas-Sainz, Pablo; Sánchez, Laura; López, Rafael; Botana, Luis M

2016-12-13

The marine environment constitutes an extraordinary resource for the discovery of new therapeutic agents. In the present manuscript we studied the effect of 3 different sponge derived guanidine alkaloids, crambescidine-816, -830, and -800. We show that these compounds strongly inhibit tumor cell proliferation by down-regulating cyclin-dependent kinases 2/6 and cyclins D/A expression while up-regulating the cell cyclin-dependent kinase inhibitors -2A, -2D and -1A. We also show that these guanidine compounds disrupt tumor cell adhesion and cytoskeletal integrity promoting the activation of the intrinsic apoptotic signaling, resulting in loss of mitochondrial membrane potential and concomitant caspase-3 cleavage and activation. The crambescidin 816 anti-tumor effect was fnally assayed in a zebrafish xenotransplantation model confirming its potent antitumor activity against colorectal carcinoma in vivo.Considering these results crambescidins could represent promising natural anticancer agents and therapeutic tools.

Marine guanidine alkaloids crambescidins inhibit tumor growth and activate intrinsic apoptotic signaling inducing tumor regression in a colorectal carcinoma zebrafish xenograft model

PubMed Central

Roel, María; Rubiolo, Juan A.; Guerra-Varela, Jorge; Silva, Siguara B. L.; Thomas, Olivier P.; Cabezas-Sainz, Pablo; Sánchez, Laura; López, Rafael; Botana, Luis M.

2016-01-01

The marine environment constitutes an extraordinary resource for the discovery of new therapeutic agents. In the present manuscript we studied the effect of 3 different sponge derived guanidine alkaloids, crambescidine-816, -830, and -800. We show that these compounds strongly inhibit tumor cell proliferation by down-regulating cyclin-dependent kinases 2/6 and cyclins D/A expression while up-regulating the cell cyclin-dependent kinase inhibitors -2A, -2D and -1A. We also show that these guanidine compounds disrupt tumor cell adhesion and cytoskeletal integrity promoting the activation of the intrinsic apoptotic signaling, resulting in loss of mitochondrial membrane potential and concomitant caspase-3 cleavage and activation. The crambescidin 816 anti-tumor effect was fnally assayed in a zebrafish xenotransplantation model confirming its potent antitumor activity against colorectal carcinoma in vivo. Considering these results crambescidins could represent promising natural anticancer agents and therapeutic tools. PMID:27825113

Adapting biomodulatory strategies for treatment in new contexts: pancreatic and oral cancers (Conference Presentation)

NASA Astrophysics Data System (ADS)

Anbil, Sriram R.; Rizvi, Imran; Khan, Amjad P.; Celli, Jonathan P.; Maytin, Edward V.; Hasan, Tayyaba

2016-03-01

Biomodulation of cancer cell metabolism represents a promising approach to overcome tumor heterogeneity and poor selectivity, which contribute significantly to treatment resistance. To date, several studies have demonstrated that modulation of cell metabolism including the heme synthesis pathway serves as an elegant approach to improve the efficacy of aminolevulinic acid (ALA) based photodynamic therapy (PDT). However, the ability of biomodulation-enhanced PDT to improve outcomes in low resource settings and to address challenges in treating lethal tumors with exogenous photosensitizers remains underexplored. The ability of vitamin D or methotrexate to enhance PDT efficacy in a carcinogen-induced hamster cheek pouch model of oral squamous cell carcinoma and in 3D cell-based models for pancreatic ductal adenocarcinoma is evaluated. Challenges associated with adapting PDT regimens to low resource settings, understanding the effects of biomodulatory agents on the metabolism of cancer cells, and the differential effects of biomodulatory agents on tumor and stromal cells will be discussed.

Opinion competition dynamics on multiplex networks

NASA Astrophysics Data System (ADS)

Amato, R.; Kouvaris, N. E.; San Miguel, M.; Díaz-Guilera, A.

2017-12-01

Multilayer and multiplex networks represent a good proxy for the description of social phenomena where social structure is important and can have different origins. Here, we propose a model of opinion competition where individuals are organized according to two different structures in two layers. Agents exchange opinions according to the Abrams-Strogatz model in each layer separately and opinions can be copied across layers by the same individual. In each layer a different opinion is dominant, so each layer has a different absorbing state. Consensus in one opinion is not the only possible stable solution because of the interaction between the two layers. A new mean field solution has been found where both opinions coexist. In a finite system there is a long transient time for the dynamical coexistence of both opinions. However, the system ends in a consensus state due to finite size effects. We analyze sparse topologies in the two layers and the existence of positive correlations between them, which enables the coexistence of inter-layer groups of agents sharing the same opinion.

Cell-cycle dependent expression of a translocation-mediated fusion oncogene mediates checkpoint adaptation in rhabdomyosarcoma.

PubMed

Kikuchi, Ken; Hettmer, Simone; Aslam, M Imran; Michalek, Joel E; Laub, Wolfram; Wilky, Breelyn A; Loeb, David M; Rubin, Brian P; Wagers, Amy J; Keller, Charles

2014-01-01

Rhabdomyosarcoma is the most commonly occurring soft-tissue sarcoma in childhood. Most rhabdomyosarcoma falls into one of two biologically distinct subgroups represented by alveolar or embryonal histology. The alveolar subtype harbors a translocation-mediated PAX3:FOXO1A fusion gene and has an extremely poor prognosis. However, tumor cells have heterogeneous expression for the fusion gene. Using a conditional genetic mouse model as well as human tumor cell lines, we show that that Pax3:Foxo1a expression is enriched in G2 and triggers a transcriptional program conducive to checkpoint adaptation under stress conditions such as irradiation in vitro and in vivo. Pax3:Foxo1a also tolerizes tumor cells to clinically-established chemotherapy agents and emerging molecularly-targeted agents. Thus, the surprisingly dynamic regulation of the Pax3:Foxo1a locus is a paradigm that has important implications for the way in which oncogenes are modeled in cancer cells.

Novel substituted (pyridin-3-yl)phenyloxazolidinones: antibacterial agents with reduced activity against monoamine oxidase A and increased solubility.

PubMed

Reck, Folkert; Zhou, Fei; Eyermann, Charles J; Kern, Gunther; Carcanague, Dan; Ioannidis, Georgine; Illingworth, Ruth; Poon, Grace; Gravestock, Michael B

2007-10-04

Oxazolidinones represent a new and promising class of antibacterial agents. Current research in this area is mainly concentrated on improving the safety profile and the antibacterial spectrum. Oxazolidinones bearing a (pyridin-3-yl)phenyl moiety (e.g., 3) generally show improved antibacterial activity compared to linezolid but suffer from potent monoamine oxidase A (MAO-A) inhibition and low solubility. We now disclose the finding that new analogues of 3 with acyclic substituents on the pyridyl moiety exhibit excellent activity against Gram-positive pathogens, including linezolid-resistant Streptococcus pneumoniae. Generally, more bulky substituents yielded significantly reduced MAO-A inhibition relative to the unsubstituted compound 3. The MAO-A SAR can be rationalized on the basis of docking studies using a MAO-A/MAO-B homology model. Solubility was enhanced with incorporation of polar groups. One optimized analogue, compound 13, showed low clearance in the rat and efficacy against S. pneumoniae in a mouse pneumonia model.

Activity Diagrams for DEVS Models: A Case Study Modeling Health Care Behavior

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

Ozmen, Ozgur; Nutaro, James J

Discrete Event Systems Specification (DEVS) is a widely used formalism for modeling and simulation of discrete and continuous systems. While DEVS provides a sound mathematical representation of discrete systems, its practical use can suffer when models become complex. Five main functions, which construct the core of atomic modules in DEVS, can realize the behaviors that modelers want to represent. The integration of these functions is handled by the simulation routine, however modelers can implement each function in various ways. Therefore, there is a need for graphical representations of complex models to simplify their implementation and facilitate their reproduction. In thismore » work, we illustrate the use of activity diagrams for this purpose in the context of a health care behavior model, which is developed with an agent-based modeling paradigm.« less

22 CFR 204.12 - Guaranty eligibility.

Code of Federal Regulations, 2010 CFR

2010-04-01

... representative of A.I.D. together with a certificate of authentication manually executed by a Paying Agent whose... signature shall be binding on A.I.D. The certificate of authentication of the Paying Agent issued pursuant...

Cognitive, cultural, and linguistic sources of a handshape distinction expressing agentivity.

PubMed

Brentari, Diane; Di Renzo, Alessio; Keane, Jonathan; Volterra, Virginia

2015-01-01

In this paper the cognitive, cultural, and linguistic bases for a pattern of conventionalization of two types of iconic handshapes are described. Work on sign languages has shown that handling handshapes (H-HSs: those that represent how objects are handled or manipulated) and object handshapes (O-HSs: those that represent the class, size, or shape of objects) express an agentive/non-agentive semantic distinction in many sign languages. H-HSs are used in agentive event descriptions and O-HSs are used in non-agentive event descriptions. In this work, American Sign Language (ASL) and Italian Sign Language (LIS) productions are compared (adults and children) as well as the corresponding groups of gesturers in each country using "silent gesture." While the gesture groups, in general, did not employ an H-HS/O-HS distinction, all participants (signers and gesturers) used iconic handshapes (H-HSs and O-HSs together) more often in agentive than in no-agent event descriptions; moreover, none of the subjects produced an opposite pattern than the expected one (i.e., H-HSs associated with no-agent descriptions and O-HSs associated with agentive ones). These effects are argued to be grounded in cognition. In addition, some individual gesturers were observed to produce the H-HS/O-HS opposition for agentive and non-agentive event descriptions-that is, more Italian than American adult gesturers. This effect is argued to be grounded in culture. Finally, the agentive/non-agentive handshape opposition is confirmed for signers of ASL and LIS, but previously unreported cross-linguistic differences were also found across both adult and child sign groups. It is, therefore, concluded that cognitive, cultural, and linguistic factors contribute to the conventionalization of this distinction of handshape type. Copyright © 2014 Cognitive Science Society, Inc.

A general equilibrium model of a production economy with asset markets

NASA Astrophysics Data System (ADS)

Raberto, Marco; Teglio, Andrea; Cincotti, Silvano

2006-10-01

In this paper, a general equilibrium model of a monetary production economy is presented. The model is characterized by three classes of agents: a representative firm, heterogeneous households, and the government. Two markets (i.e., a labour market and a goods market, are considered) and two assets are traded in exchange of money, namely, government bonds and equities. Households provide the labour force and decide on consumption and savings, whereas the firm provides consumption goods and demands labour. The government receives taxes from households and pays interests on debt. The Walrasian equilibrium is derived analytically. The dynamics through quantity constrained equilibria out from the Walrasian equilibrium is also studied by means of computer simulations.

Games network and application to PAs system.

PubMed

Chettaoui, C; Delaplace, F; Manceny, M; Malo, M

2007-02-01

In this article, we present a game theory based framework, named games network, for modeling biological interactions. After introducing the theory, we more precisely describe the methodology to model biological interactions. Then we apply it to the plasminogen activator system (PAs) which is a signal transduction pathway involved in cancer cell migration. The games network theory extends game theory by including the locality of interactions. Each game in a games network represents local interactions between biological agents. The PAs system is implicated in cytoskeleton modifications via regulation of actin and microtubules, which in turn favors cell migration. The games network model has enabled us a better understanding of the regulation involved in the PAs system.

Anti-inflammatory natural product goniothalamin reduces colitis-associated and sporadic colorectal tumorigenesis

PubMed Central

Vendramini-Costa, Débora Barbosa; Francescone, Ralph; Posocco, David; Hou, Vivianty; Dmitrieva, Oxana; Hensley, Harvey; de Carvalho, João Ernesto; Pilli, Ronaldo Aloise; Grivennikov, Sergei I.

2017-01-01

The tumor microenvironment offers multiple targets for cancer therapy, including pro-tumorigenic inflammation. Natural compounds represent an enormous source of new anti-inflammatory and anticancer agents. We previously showed that the styryl lactone goniothalamin (GTN) has promising antiproliferative and anti-inflammatory activities. Because inflammation is a major driver of colorectal cancer (CRC), we therefore evaluated the therapeutic and preventive potentials of GTN in colitis, colitis-associated cancer (CAC) and spontaneous CRC. First, in a simplistic model of inflammation in vitro, GTN was able to inhibit cytokine production in bone marrow-derived macrophages induced by lipopolysaccharide. Next, in dextran sulfate sodium (DSS) induced-colitis model, mice treated with GTN displayed restored tissue architecture, increased cell proliferation in the colonic crypts and reduced epithelial damage. Moreover, colon tissue from GTN-treated mice had significantly less expression of the inflammatory genes interleukin 1β (IL-1β), tumor necrosis factor α (TNF-α), interleukin 6 (IL-6), S100A9, interleukin 23A (IL-23A), IL-22 and IL-17A. In the azoxymethane/DSS model of CAC, GTN reduced tumor multiplicity, load and size. Additionally, GTN suppressed production of IL-6, IL-17 and TNF-α in tumor tissue, as well as abrogated stromal immune cell activation and nuclear translocation of NF-κB. Finally, in a tamoxifen inducible model of sporadic CRC, GTN-treated mice had significantly fewer tumors and decreased levels of IL-17A, IL-6, S100A9 and TNF-α protein within the tumors. These results suggest that GTN possesses anti-inflammatory and antitumor activities and represents a preventive and therapeutic agent modulating the inflammatory environment in the colon during colitis as well as CAC and CRC development. PMID:27797827

Health behavior change in advance care planning: an agent-based model.

PubMed

Ernecoff, Natalie C; Keane, Christopher R; Albert, Steven M

2016-02-29

A practical and ethical challenge in advance care planning research is controlling and intervening on human behavior. Additionally, observing dynamic changes in advance care planning (ACP) behavior proves difficult, though tracking changes over time is important for intervention development. Agent-based modeling (ABM) allows researchers to integrate complex behavioral data about advance care planning behaviors and thought processes into a controlled environment that is more easily alterable and observable. Literature to date has not addressed how best to motivate individuals, increase facilitators and reduce barriers associated with ACP. We aimed to build an ABM that applies the Transtheoretical Model of behavior change to ACP as a health behavior and accurately reflects: 1) the rates at which individuals complete the process, 2) how individuals respond to barriers, facilitators, and behavioral variables, and 3) the interactions between these variables. We developed a dynamic ABM of the ACP decision making process based on the stages of change posited by the Transtheoretical Model. We integrated barriers, facilitators, and other behavioral variables that agents encounter as they move through the process. We successfully incorporated ACP barriers, facilitators, and other behavioral variables into our ABM, forming a plausible representation of ACP behavior and decision-making. The resulting distributions across the stages of change replicated those found in the literature, with approximately half of participants in the action-maintenance stage in both the model and the literature. Our ABM is a useful method for representing dynamic social and experiential influences on the ACP decision making process. This model suggests structural interventions, e.g. increasing access to ACP materials in primary care clinics, in addition to improved methods of data collection for behavioral studies, e.g. incorporating longitudinal data to capture behavioral dynamics.

Intraperitoneal (188)Re-Liposome delivery switches ovarian cancer metabolism from glycolysis to oxidative phosphorylation and effectively controls ovarian tumour growth in mice.

PubMed

Shen, Yao An; Lan, Keng Li; Chang, Chih Hsien; Lin, Liang Ting; He, Chun Lin; Chen, Po Hung; Lee, Te Wei; Lee, Yi Jang; Chuang, Chi Mu

2016-05-01

Cancer stem cells exhibit distinctive cellular metabolism compared with the more differentiated counterparts or normal cells. We aimed to investigate the impact of a novel radionuclide anti-cancer agent (188)Re-Liposome on stemness markers' expression and cellular metabolism in an ovarian cancer model. A 2×2 factorial experiment was designed in which factor 1 represented the drug treatment comparing (188)Re-BMEDA, a free form of (188)Re, with (188)Re-Liposome, a nanoparticle-encapsulated form of (188)Re. Factor 2 represented the delivery route, comparing intravenous with intraperitoneal delivery. Intraperitoneal delivery of (188)Re-Liposome predominantly killed the CSCs-like cells in tumours and switched metabolism from glycolysis to oxidative phosphorylation. Further, intraperitoneal delivery of (188)Re-Liposome treatment was able to block epithelial-to-mesenchymal transition (EMT) and reactivate p53 function. Collectively, these molecular changes led to a striking tumour-killing effect. Radionuclides encapsulated in liposomes may represent a novel treatment for ovarian cancer when delivered intraperitoneally (a type of loco-regional delivery). In the future, this concept may be further extended for the treatment of several relevant cancers that have been proved to be suitable for loco-regional delivery of therapeutic agents, such as colon cancer, gastric cancer, and pancreatic cancer. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Open Software Tools Applied to Jordan's National Multi-Agent Water Management Model

NASA Astrophysics Data System (ADS)

Knox, Stephen; Meier, Philipp; Harou, Julien; Yoon, Jim; Selby, Philip; Lachaut, Thibaut; Klassert, Christian; Avisse, Nicolas; Khadem, Majed; Tilmant, Amaury; Gorelick, Steven

2016-04-01

Jordan is the fourth most water scarce country in the world, where demand exceeds supply in a politically and demographically unstable context. The Jordan Water Project (JWP) aims to perform policy evaluation by modelling the hydrology, economics, and governance of Jordan's water resource system. The multidisciplinary nature of the project requires a modelling software system capable of integrating submodels from multiple disciplines into a single decision making process and communicating results to stakeholders. This requires a tool for building an integrated model and a system where diverse data sets can be managed and visualised. The integrated Jordan model is built using Pynsim, an open-source multi-agent simulation framework implemented in Python. Pynsim operates on network structures of nodes and links and supports institutional hierarchies, where an institution represents a grouping of nodes, links or other institutions. At each time step, code within each node, link and institution can executed independently, allowing for their fully autonomous behaviour. Additionally, engines (sub-models) perform actions over the entire network or on a subset of the network, such as taking a decision on a set of nodes. Pynsim is modular in design, allowing distinct modules to be modified easily without affecting others. Data management and visualisation is performed using Hydra (www.hydraplatform.org), an open software platform allowing users to manage network structure and data. The Hydra data manager connects to Pynsim, providing necessary input parameters for the integrated model. By providing a high-level portal to the model, Hydra removes a barrier between the users of the model (researchers, stakeholders, planners etc) and the model itself, allowing them to manage data, run the model and visualise results all through a single user interface. Pynsim's ability to represent institutional hierarchies, inter-network communication and the separation of node, link and institutional logic from higher level processes (engine) suit JWP's requirements. The use of Hydra Platform and Pynsim helps make complex customised models such as the JWP model easier to run and manage with international groups of researchers.

Early spatiotemporal-specific changes in intermediate signals are predictive of cytotoxic sensitivity to TNFα and co-treatments

NASA Astrophysics Data System (ADS)

Loo, Lit-Hsin; Bougen-Zhukov, Nicola Michelle; Tan, Wei-Ling Cecilia

2017-03-01

Signaling pathways can generate different cellular responses to the same cytotoxic agents. Current quantitative models for predicting these differential responses are usually based on large numbers of intracellular gene products or signals at different levels of signaling cascades. Here, we report a study to predict cellular sensitivity to tumor necrosis factor alpha (TNFα) using high-throughput cellular imaging and machine-learning methods. We measured and compared 1170 protein phosphorylation events in a panel of human lung cancer cell lines based on different signals, subcellular regions, and time points within one hour of TNFα treatment. We found that two spatiotemporal-specific changes in an intermediate signaling protein, p90 ribosomal S6 kinase (RSK), are sufficient to predict the TNFα sensitivity of these cell lines. Our models could also predict the combined effects of TNFα and other kinase inhibitors, many of which are not known to target RSK directly. Therefore, early spatiotemporal-specific changes in intermediate signals are sufficient to represent the complex cellular responses to these perturbations. Our study provides a general framework for the development of rapid, signaling-based cytotoxicity screens that may be used to predict cellular sensitivity to a cytotoxic agent, or identify co-treatments that may sensitize or desensitize cells to the agent.

Early spatiotemporal-specific changes in intermediate signals are predictive of cytotoxic sensitivity to TNFα and co-treatments

PubMed Central

Loo, Lit-Hsin; Bougen-Zhukov, Nicola Michelle; Tan, Wei-Ling Cecilia

2017-01-01

Signaling pathways can generate different cellular responses to the same cytotoxic agents. Current quantitative models for predicting these differential responses are usually based on large numbers of intracellular gene products or signals at different levels of signaling cascades. Here, we report a study to predict cellular sensitivity to tumor necrosis factor alpha (TNFα) using high-throughput cellular imaging and machine-learning methods. We measured and compared 1170 protein phosphorylation events in a panel of human lung cancer cell lines based on different signals, subcellular regions, and time points within one hour of TNFα treatment. We found that two spatiotemporal-specific changes in an intermediate signaling protein, p90 ribosomal S6 kinase (RSK), are sufficient to predict the TNFα sensitivity of these cell lines. Our models could also predict the combined effects of TNFα and other kinase inhibitors, many of which are not known to target RSK directly. Therefore, early spatiotemporal-specific changes in intermediate signals are sufficient to represent the complex cellular responses to these perturbations. Our study provides a general framework for the development of rapid, signaling-based cytotoxicity screens that may be used to predict cellular sensitivity to a cytotoxic agent, or identify co-treatments that may sensitize or desensitize cells to the agent. PMID:28272488

Purple spot damage dynamics investigated by an integrated approach on a 1244 A.D. parchment roll from the Secret Vatican Archive.

PubMed

Migliore, Luciana; Thaller, Maria Cristina; Vendittozzi, Giulia; Mejia, Astrid Yazmine; Mercuri, Fulvio; Orlanducci, Silvia; Rubechini, Alessandro

2017-09-07

Ancient parchments are commonly attacked by microbes, producing purple spots and detachment of the superficial layer. Neither standard cultivation nor molecular methods (DGGE) solved the issue: causative agents and colonization model are still unknown. To identify the putative causal agents, we describe the 16 S rRNA gene analysis (454-pyrosequencing) of the microbial communities colonizing a damaged parchment roll dated 1244 A.D. (A.A. Arm. I-XVIII 3328, Vatican Secret Archives). The taxa in damaged or undamaged areas of the same document were different. In the purple spots, marine halotolerant Gammaproteobacteria, mainly Vibrio, were found; these microorganisms are rare or absent in the undamaged areas. Ubiquitous and environmental microorganisms were observed in samples from both damaged and undamaged areas. Pseudonocardiales were the most common, representing the main colonizers of undamaged areas. We hypothesize a successional model of biodeterioration, based on metagenomic data and spectroscopic analysis of pigments, which help to relate the damage to a microbial agent. Furthermore, a new method (Light Transmitted Analysis) was utilized to evaluate the kind and entity of the damage to native collagen. These data give a significant advance to the knowledge in the field and open new perspectives to remediation activity on a huge amount of ancient document.

Autonomous Agent-Based Systems and Their Applications in Fluid Dynamics, Particle Separation, and Co-evolving Networks

NASA Astrophysics Data System (ADS)

Graeser, Oliver

This thesis comprises three parts, reporting research results in Fluid Dynamics (Part I), Particle Separation (Part II) and Co-evolving Networks (Part III). Part I deals with the simulation of fluid dynamics using the lattice-Boltzmann method. Microfluidic devices often feature two-dimensional, repetitive arrays. Flows through such devices are pressure-driven and confined by solid walls. We have defined new adaptive generalised periodic boundary conditions to represent the effects of outer solid walls, and are thus able to exploit the periodicity of the array by simulating the flow through one unit cell in lieu of the entire device. The so-calculated fully developed flow describes the flow through the entire array accurately, but with computational requirements that are reduced according to the dimensions of the array. Part II discusses the problem of separating macromolecules like proteins or DNA coils. The reliable separation of such molecules is a crucial task in molecular biology. The use of Brownian ratchets as mechanisms for the separation of such particles has been proposed and discussed during the last decade. Pressure-driven flows have so far been dismissed as possible driving forces for Brownian ratchets, as they do not generate ratchet asymmetry. We propose a microfluidic design that uses pressure-driven flows to create asymmetry and hence allows particle separation. The dependence of the asymmetry on various factors of the microfluidic geometry is discussed. We further exemplify the feasibility of our approach using Brownian dynamics simulations of particles of different sizes in such a device. The results show that ratchet-based particle separation using flows as the driving force is possible. Simulation results and ratchet theory predictions are in excellent agreement. Part III deals with the co-evolution of networks and dynamic models. A group of agents occupies the nodes of a network, which defines the relationship between these agents. The evolution of the agents is defined by the rules of the dynamic model and depends on the relationship between agents, i.e., the state of the network. In return, the evolution of the network depends on the state of the dynamic model. The concept is introduced through the adaptive SIS model. We show that the previously used criterion determining the critical infected fraction, i.e., the number of infected agents required to sustain the epidemic, is inappropriate for this model. We introduce a different criterion and show that the critical infected fraction so determined is in good agreement with results obtained by numerical simulations. We further discuss the concept of co-evolving dynamics using the Snowdrift Game as a model paradigm. Co-evolution occurs through agents cutting dissatisfied links and rewiring to other agents at random. The effect of co-evolution on the emergence of cooperation is discussed using a mean-field theory and numerical simulations. A transition between a connected and a disconnected, highly cooperative state of the system is observed, and explained using the mean-field model. Quantitative deviations regarding the level of cooperation in the disconnected regime can be fully resolved through an improved mean-field theory that includes the effect of random fluctuations into its model.

Towards a 3d Spatial Urban Energy Modelling Approach

NASA Astrophysics Data System (ADS)

Bahu, J.-M.; Koch, A.; Kremers, E.; Murshed, S. M.

2013-09-01

Today's needs to reduce the environmental impact of energy use impose dramatic changes for energy infrastructure and existing demand patterns (e.g. buildings) corresponding to their specific context. In addition, future energy systems are expected to integrate a considerable share of fluctuating power sources and equally a high share of distributed generation of electricity. Energy system models capable of describing such future systems and allowing the simulation of the impact of these developments thus require a spatial representation in order to reflect the local context and the boundary conditions. This paper describes two recent research approaches developed at EIFER in the fields of (a) geo-localised simulation of heat energy demand in cities based on 3D morphological data and (b) spatially explicit Agent-Based Models (ABM) for the simulation of smart grids. 3D city models were used to assess solar potential and heat energy demand of residential buildings which enable cities to target the building refurbishment potentials. Distributed energy systems require innovative modelling techniques where individual components are represented and can interact. With this approach, several smart grid demonstrators were simulated, where heterogeneous models are spatially represented. Coupling 3D geodata with energy system ABMs holds different advantages for both approaches. On one hand, energy system models can be enhanced with high resolution data from 3D city models and their semantic relations. Furthermore, they allow for spatial analysis and visualisation of the results, with emphasis on spatially and structurally correlations among the different layers (e.g. infrastructure, buildings, administrative zones) to provide an integrated approach. On the other hand, 3D models can benefit from more detailed system description of energy infrastructure, representing dynamic phenomena and high resolution models for energy use at component level. The proposed modelling strategies conceptually and practically integrate urban spatial and energy planning approaches. The combined modelling approach that will be developed based on the described sectorial models holds the potential to represent hybrid energy systems coupling distributed generation of electricity with thermal conversion systems.

Three-strategy N-person snowdrift game incorporating loners

NASA Astrophysics Data System (ADS)

Xu, Meng; Zheng, Da-Fang; Xu, C.; Hui, P. M.

2017-02-01

The N-person snowdrift game is generalized to incorporate a third strategy. In addition to the cooperative C and non-cooperative D strategies, a strategy L representing a loner behavior is introduced. Agents taking on the L strategy (L-agents) do not contribute to the game as the C-agents do but they do not take advantage of the C-agents. Instead, they would rather settle with a fixed payoff L. Dynamical equations governing the time evolution of the frequencies of the strategies in a well-mixed population are derived. The dynamics and the frequencies of the steady state reveal the rich behavior resulting from the interplay between the payoff r, which promotes the non-cooperative behavior, and L. Detailed studies on how a system evolves indicated that the steady state could be an AllL, AllC, or C+D state, depending on the parameters r, L, and group size N. In contrast, only a C+D state results for r > 0 and an AllC state is possible only at r = 0 without the strategy L. With the strategy L, the AllC phase occupies a finite, though tiny, region of the r- L parameter space. The L-agents play an important role in the dynamics leading to the AllC phase. They help eliminate the D strategy in the transient and later only to be replaced by the C strategy. Phase diagrams in the r- L space are presented for different values of N. The strategy L plays two roles. It leads to an AllL phase and helps give an AllC phase. An algorithm for simulating the model numerically is described and validated. The algorithm will be useful in studying our model in various structured populations.

Learning Natural Selection in 4th Grade with Multi-Agent-Based Computational Models

NASA Astrophysics Data System (ADS)

Dickes, Amanda Catherine; Sengupta, Pratim

2013-06-01

In this paper, we investigate how elementary school students develop multi-level explanations of population dynamics in a simple predator-prey ecosystem, through scaffolded interactions with a multi-agent-based computational model (MABM). The term "agent" in an MABM indicates individual computational objects or actors (e.g., cars), and these agents obey simple rules assigned or manipulated by the user (e.g., speeding up, slowing down, etc.). It is the interactions between these agents, based on the rules assigned by the user, that give rise to emergent, aggregate-level behavior (e.g., formation and movement of the traffic jam). Natural selection is such an emergent phenomenon, which has been shown to be challenging for novices (K16 students) to understand. Whereas prior research on learning evolutionary phenomena with MABMs has typically focused on high school students and beyond, we investigate how elementary students (4th graders) develop multi-level explanations of some introductory aspects of natural selection—species differentiation and population change—through scaffolded interactions with an MABM that simulates predator-prey dynamics in a simple birds-butterflies ecosystem. We conducted a semi-clinical interview based study with ten participants, in which we focused on the following: a) identifying the nature of learners' initial interpretations of salient events or elements of the represented phenomena, b) identifying the roles these interpretations play in the development of their multi-level explanations, and c) how attending to different levels of the relevant phenomena can make explicit different mechanisms to the learners. In addition, our analysis also shows that although there were differences between high- and low-performing students (in terms of being able to explain population-level behaviors) in the pre-test, these differences disappeared in the post-test.

Fate of Prions in Soil: A Review

PubMed Central

Smith, Christen B.; Booth, Clarissa J.; Pedersen, Joel A.

2011-01-01

Prions are the etiological agents of transmissible spongiform encephalopathies (TSEs), a class of fatal neurodegenerative diseases affecting humans and other mammals. The pathogenic prion protein is a misfolded form of the host-encoded prion protein and represents the predominant, if not sole, component of the infectious agent. Environmental routes of TSE transmission are implicated in epizootics of sheep scrapie and chronic wasting disease (CWD) of deer, elk, and moose. Soil represents a plausible environmental reservoir of scrapie and CWD agents, which can persist in the environment for years. Attachment to soil particles likely influences the persistence and infectivity of prions in the environment. Effective methods to inactivate TSE agents in soil are currently lacking, and the effects of natural degradation mechanisms on TSE infectivity are largely unknown. An improved understanding of the processes affecting the mobility, persistence, and bioavailability of prions in soil is needed for the management of TSE-contaminated environments. PMID:21520752

In the Opponent's Shoes: Increasing the Behavioral Validity of Attackers' Judgments in Counterterrorism Models.

PubMed

Sri Bhashyam, Sumitra; Montibeller, Gilberto

2016-04-01

A key objective for policymakers and analysts dealing with terrorist threats is trying to predict the actions that malicious agents may take. A recent trend in counterterrorism risk analysis is to model the terrorists' judgments, as these will guide their choices of such actions. The standard assumptions in most of these models are that terrorists are fully rational, following all the normative desiderata required for rational choices, such as having a set of constant and ordered preferences, being able to perform a cost-benefit analysis of their alternatives, among many others. However, are such assumptions reasonable from a behavioral perspective? In this article, we analyze the types of assumptions made across various counterterrorism analytical models that represent malicious agents' judgments and discuss their suitability from a descriptive point of view. We then suggest how some of these assumptions could be modified to describe terrorists' preferences more accurately, by drawing knowledge from the fields of behavioral decision research, politics, philosophy of choice, public choice, and conflict management in terrorism. Such insight, we hope, might help make the assumptions of these models more behaviorally valid for counterterrorism risk analysis. © 2016 The Authors Wound Repair and Regeneration published by Wiley Periodicals, Inc. on behalf of The Wound Healing Society.

Towards a Hybrid Agent-based Model for Mosquito Borne Disease.

PubMed

Mniszewski, S M; Manore, C A; Bryan, C; Del Valle, S Y; Roberts, D

2014-07-01

Agent-based models (ABM) are used to simulate the spread of infectious disease through a population. Detailed human movement, demography, realistic business location networks, and in-host disease progression are available in existing ABMs, such as the Epidemic Simulation System (EpiSimS). These capabilities make possible the exploration of pharmaceutical and non-pharmaceutical mitigation strategies used to inform the public health community. There is a similar need for the spread of mosquito borne pathogens due to the re-emergence of diseases such as chikungunya and dengue fever. A network-patch model for mosquito dynamics has been coupled with EpiSimS. Mosquitoes are represented as a "patch" or "cloud" associated with a location. Each patch has an ordinary differential equation (ODE) mosquito dynamics model and mosquito related parameters relevant to the location characteristics. Activities at each location can have different levels of potential exposure to mosquitoes based on whether they are inside, outside, or somewhere in-between. As a proof of concept, the hybrid network-patch model is used to simulate the spread of chikungunya through Washington, DC. Results are shown for a base case, followed by varying the probability of transmission, mosquito count, and activity exposure. We use visualization to understand the pattern of disease spread.

An architecture and protocol for communications satellite constellations regarded as multi-agent systems

NASA Technical Reports Server (NTRS)

Lindley, Craig A.

1995-01-01

This paper presents an architecture for satellites regarded as intercommunicating agents. The architecture is based upon a postmodern paradigm of artificial intelligence in which represented knowledge is regarded as text, inference procedures are regarded as social discourse and decision making conventions and the semantics of representations are grounded in the situated behaviour and activity of agents. A particular protocol is described for agent participation in distributed search and retrieval operations conducted as joint activities.

Anti-CD22 and anti-CD79B antibody drug conjugates are active in different molecular diffuse large B-cell lymphoma subtypes.

PubMed

Pfeifer, M; Zheng, B; Erdmann, T; Koeppen, H; McCord, R; Grau, M; Staiger, A; Chai, A; Sandmann, T; Madle, H; Dörken, B; Chu, Y-W; Chen, A I; Lebovic, D; Salles, G A; Czuczman, M S; Palanca-Wessels, M C; Press, O W; Advani, R; Morschhauser, F; Cheson, B D; Lenz, P; Ott, G; Polson, A G; Mundt, K E; Lenz, G

2015-07-01

Antibody drug conjugates (ADCs), in which cytotoxic drugs are linked to antibodies targeting antigens on tumor cells, represent promising novel agents for the treatment of malignant lymphomas. Pinatuzumab vedotin is an anti-CD22 ADC and polatuzumab vedotin an anti-CD79B ADC that are both linked to the microtubule-disrupting agent monomethyl auristatin E (MMAE). In the present study, we analyzed the activity of these agents in different molecular subtypes of diffuse large B-cell lymphoma (DLBCL) both in vitro and in early clinical trials. Both anti-CD22-MMAE and anti-CD79B-MMAE were highly active and induced cell death in the vast majority of activated B-cell-like (ABC) and germinal center B-cell-like (GCB) DLBCL cell lines. Similarly, both agents induced cytotoxicity in models with and without mutations in the signaling molecule CD79B. In line with these observations, relapsed and refractory DLBCL patients of both subtypes responded to these agents. Importantly, a strong correlation between CD22 and CD79B expression in vitro and in vivo was not detectable, indicating that patients should not be excluded from anti-CD22-MMAE or anti-CD79B-MMAE treatment because of low target expression. In summary, these studies suggest that pinatuzumab vedotin and polatuzumab vedotin are active agents for the treatment of patients with different subtypes of DLBCL.

Use of caries-preventive agents in children: findings from the dental practice-based research network.

PubMed

Riley, J L; Richman, Joshua S; Rindal, D Brad; Fellows, Jeffrey L; Qvist, Vibeke; Gilbert, Gregg H; Gordan, Valeria V

2010-01-01

Scientific evidence supports the application of caries-preventive agents in children and adolescents, and this knowledge must be applied to the practice of dentistry. There are few multi-region data that allow for comparisons of practice patterns between types of dental practices and geographical regions. The objective of the present study was to characterise the use of specific caries-preventive agents for paediatric patients in a large multi-region sample of practising clinicians. The present study surveyed clinicians from the Dental Practice-based Research Network who perform restorative dentistry in their practices. The survey consisted of a questionnaire that presented a range of questions about caries risk assessment and the use of preventive techniques in children aged 6 to 18 years. Dental sealants (69%) or in-office fluoride (82%) were the most commonly used caries-preventive agents of the caries preventive regimens. The recommendation of at-home caries-preventive agents ranged from 36% to 7%,with the most commonly used agent being non-prescription fluoride rinse. Clinicians who practised in a large group practice model and clinicians who come from the Scandinavian region use caries risk assessment more frequently compared to clinicians who come from regions that had, predominantly, clinicians in private practice. Whether or not clinicians used caries risk assessment with their paediatric patients was poorly correlated with the likelihood of actually using caries-preventive treatments on patients. Although clinicians reported the use of some form of in-office caries-preventive agent, there was considerable variability across practices. These differences could represent a lack of consensus across practising clinicians about the benefits of caries-preventive agents, or a function of differing financial incentives, or patient pools with differing levels of overall caries risk.

Marine Natural Products as Prototype Agrochemical Agents

PubMed Central

Peng, Jiangnan; Shen, Xiaoyu; El Sayed, Khalid A.; Dunbar, D. C Harles; Perry, Tony L.; Wilkins, Scott P.; Hamann, Mark T.; Bobzin, Steve; Huesing, Joseph; Camp, Robin; Prinsen, Mike; Krupa, Dan; Wideman, Margaret A.

2016-01-01

In the interest of identifying new leads that could serve as prototype agrochemical agents, 18 structurally diverse marine-derived compounds were examined for insecticidal, herbicidal, and fungicidal activities. Several new classes of compounds have been shown to be insecticidal, herbicidal, and fungicidal, which suggests that marine natural products represent an intriguing source for the discovery of new agrochemical agents. PMID:12670165

Agent autonomy approach to probabilistic physics-of-failure modeling of complex dynamic systems with interacting failure mechanisms

NASA Astrophysics Data System (ADS)

Gromek, Katherine Emily

A novel computational and inference framework of the physics-of-failure (PoF) reliability modeling for complex dynamic systems has been established in this research. The PoF-based reliability models are used to perform a real time simulation of system failure processes, so that the system level reliability modeling would constitute inferences from checking the status of component level reliability at any given time. The "agent autonomy" concept is applied as a solution method for the system-level probabilistic PoF-based (i.e. PPoF-based) modeling. This concept originated from artificial intelligence (AI) as a leading intelligent computational inference in modeling of multi agents systems (MAS). The concept of agent autonomy in the context of reliability modeling was first proposed by M. Azarkhail [1], where a fundamentally new idea of system representation by autonomous intelligent agents for the purpose of reliability modeling was introduced. Contribution of the current work lies in the further development of the agent anatomy concept, particularly the refined agent classification within the scope of the PoF-based system reliability modeling, new approaches to the learning and the autonomy properties of the intelligent agents, and modeling interacting failure mechanisms within the dynamic engineering system. The autonomous property of intelligent agents is defined as agent's ability to self-activate, deactivate or completely redefine their role in the analysis. This property of agents and the ability to model interacting failure mechanisms of the system elements makes the agent autonomy fundamentally different from all existing methods of probabilistic PoF-based reliability modeling. 1. Azarkhail, M., "Agent Autonomy Approach to Physics-Based Reliability Modeling of Structures and Mechanical Systems", PhD thesis, University of Maryland, College Park, 2007.

12 CFR 793.3 - Administrative claim; who may file.

Code of Federal Regulations, 2010 CFR

2010-01-01

... authorized agent, or his legal representative. (c) A claim based on death may be presented by the executor or... accompanied by evidence of his authority to present a claim on behalf of the claimant as agent, executor...

An Agent-Based Optimization Framework for Engineered Complex Adaptive Systems with Application to Demand Response in Electricity Markets

NASA Astrophysics Data System (ADS)

Haghnevis, Moeed

The main objective of this research is to develop an integrated method to study emergent behavior and consequences of evolution and adaptation in engineered complex adaptive systems (ECASs). A multi-layer conceptual framework and modeling approach including behavioral and structural aspects is provided to describe the structure of a class of engineered complex systems and predict their future adaptive patterns. The approach allows the examination of complexity in the structure and the behavior of components as a result of their connections and in relation to their environment. This research describes and uses the major differences of natural complex adaptive systems (CASs) with artificial/engineered CASs to build a framework and platform for ECAS. While this framework focuses on the critical factors of an engineered system, it also enables one to synthetically employ engineering and mathematical models to analyze and measure complexity in such systems. In this way concepts of complex systems science are adapted to management science and system of systems engineering. In particular an integrated consumer-based optimization and agent-based modeling (ABM) platform is presented that enables managers to predict and partially control patterns of behaviors in ECASs. Demonstrated on the U.S. electricity markets, ABM is integrated with normative and subjective decision behavior recommended by the U.S. Department of Energy (DOE) and Federal Energy Regulatory Commission (FERC). The approach integrates social networks, social science, complexity theory, and diffusion theory. Furthermore, it has unique and significant contribution in exploring and representing concrete managerial insights for ECASs and offering new optimized actions and modeling paradigms in agent-based simulation.

Investigations of the Binding of [Pt2(DTBPA)Cl2](II) and [Pt2(TPXA)Cl2](II) to DNA via Various Cross-Linking Modes

PubMed Central

Yue, Hongwei; Yang, Bo; Wang, Yan; Chen, Guangju

2013-01-01

We have constructed models for a series of platinum-DNA adducts that represent the binding of two agents, [Pt2(DTBPA)Cl2](II) and [Pt2(TPXA)Cl2](II), to DNA via inter- and intra-strand cross-linking, and carried out molecular dynamics simulations and DNA conformational dynamics calculations. The effects of trans- and cis-configurations of the centers of these di-nuclear platinum agents, and of different bridging linkers, have been investigated on the conformational distortions of platinum-DNA adducts formed via inter- and intra-strand cross-links. The results demonstrate that the DNA conformational distortions for the various platinum-DNA adducts with differing cross-linking modes are greatly influenced by the difference between the platinum-platinum distance for the platinum agent and the platinum-bound N7–N7 distance for the DNA molecule, and by the flexibility of the bridging linkers in the platinum agent. However, the effects of trans/cis-configurations of the platinum-centers on the DNA conformational distortions in the platinum-DNA adducts depend on the inter- and intra-strand cross-linking modes. In addition, we discuss the relevance of DNA base motions, including opening, shift and roll, to the changes in the parameters of the DNA major and minor grooves caused by binding of the platinum agent. PMID:24077126

Functional, thermodynamics, structural and biological studies of in silico-identified inhibitors of Mycobacterium tuberculosis enoyl-ACP(CoA) reductase enzyme

NASA Astrophysics Data System (ADS)

Martinelli, Leonardo K. B.; Rotta, Mariane; Villela, Anne D.; Rodrigues-Junior, Valnês S.; Abbadi, Bruno L.; Trindade, Rogério V.; Petersen, Guilherme O.; Danesi, Giuliano M.; Nery, Laura R.; Pauli, Ivani; Campos, Maria M.; Bonan, Carla D.; de Souza, Osmar Norberto; Basso, Luiz A.; Santos, Diogenes S.

2017-04-01

Novel chemotherapeutics agents are needed to kill Mycobacterium tuberculosis, the main causative agent of tuberculosis (TB). The M. tuberculosis 2-trans-enoyl-ACP(CoA) reductase enzyme (MtInhA) is the druggable bona fide target of isoniazid. New chemotypes were previously identified by two in silico approaches as potential ligands to MtInhA. The inhibition mode was determined by steady-state kinetics for seven compounds that inhibited MtInhA activity. Dissociation constant values at different temperatures were determined by protein fluorescence spectroscopy. van’t Hoff analyses of ligand binding to MtInhA:NADH provided the thermodynamic signatures of non-covalent interactions (ΔH°, ΔS°, ΔG°). Phenotypic screening showed that five compounds inhibited in vitro growth of M. tuberculosis H37Rv strain. Labio_16 and Labio_17 compounds also inhibited the in vitro growth of PE-003 multidrug-resistant strain. Cytotoxic effects on Hacat, Vero and RAW 264.7 cell lines were assessed for the latter two compounds. The Labio_16 was bacteriostatic and Labio_17 bactericidal in an M. tuberculosis-infected macrophage model. In Zebrafish model, Labio_16 showed no cardiotoxicity whereas Labio_17 showed dose-dependent cardiotoxicity. Accordingly, a model was built for the MtInhA:NADH:Labio_16 ternary complex. The results show that the Labio_16 compound is a direct inhibitor of MtInhA, and it may represent a hit for the development of chemotherapeutic agents to treat TB.

Nanoparticle-mediated drug delivery to treat infections in the female reproductive tract: evaluation of experimental systems and the potential for mathematical modeling.

PubMed

Sims, Lee B; Frieboes, Hermann B; Steinbach-Rankins, Jill M

2018-01-01

A variety of drug-delivery platforms have been employed to deliver therapeutic agents across cervicovaginal mucus (CVM) and the vaginal mucosa, offering the capability to increase the longevity and retention of active agents to treat infections of the female reproductive tract (FRT). Nanoparticles (NPs) have been shown to improve retention, diffusion, and cell-specific targeting via specific surface modifications, relative to other delivery platforms. In particular, polymeric NPs represent a promising option that has shown improved distribution through the CVM. These NPs are typically fabricated from nontoxic, non-inflammatory, US Food and Drug Administration-approved polymers that improve biocompatibility. This review summarizes recent experimental studies that have evaluated NP transport in the FRT, and highlights research areas that more thoroughly and efficiently inform polymeric NP design, including mathematical modeling. An overview of the in vitro, ex vivo, and in vivo NP studies conducted to date - whereby transport parameters are determined, extrapolated, and validated - is presented first. The impact of different NP design features on transport through the FRT is summarized, and gaps that exist due to the limitations of iterative experimentation alone are identified. The potential of mathematical modeling to complement the characterization and evaluation of diffusion and transport of delivery vehicles and active agents through the CVM and mucosa is discussed. Lastly, potential advancements combining experimental and mathematical knowledge are suggested to inform next-generation NP designs, such that infections in the FRT may be more effectively treated.

Universal size effects for populations in group-outcome decision-making problems

NASA Astrophysics Data System (ADS)

Borghesi, Christian; Hernández, Laura; Louf, Rémi; Caparros, Fabrice

2013-12-01

Elections constitute a paradigm of decision-making problems that have puzzled experts of different disciplines for decades. We study two decision-making problems, where groups make decisions that impact only themselves as a group. In both studied cases, participation in local elections and the number of democratic representatives at different scales (from local to national), we observe a universal scaling with the constituency size. These results may be interpreted as constituencies having a hierarchical structure, where each group of N agents, at each level of the hierarchy, is divided in about Nδ subgroups with δ≈1/3. Following this interpretation, we propose a phenomenological model of vote participation where abstention is related to the perceived link of an agent to the rest of the constituency and which reproduces quantitatively the observed data.

Path scanning for the detection of anomalous subgraphs and use of DNS requests and host agents for anomaly/change detection and network situational awareness

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

Neil, Joshua Charles; Fisk, Michael Edward; Brugh, Alexander William

A system, apparatus, computer-readable medium, and computer-implemented method are provided for detecting anomalous behavior in a network. Historical parameters of the network are determined in order to determine normal activity levels. A plurality of paths in the network are enumerated as part of a graph representing the network, where each computing system in the network may be a node in the graph and the sequence of connections between two computing systems may be a directed edge in the graph. A statistical model is applied to the plurality of paths in the graph on a sliding window basis to detect anomalousmore » behavior. Data collected by a Unified Host Collection Agent ("UHCA") may also be used to detect anomalous behavior.« less

A technology platform to assess multiple cancer agents simultaneously within a patient's tumor

PubMed Central

Klinghoffer, Richard A.; Frazier, Jason P.; Moreno-Gonzalez, Alicia; Strand, Andrew D.; Kerwin, William S.; Casalini, Joseph R.; Thirstrup, Derek J.; You, Sheng; Morris, Shelli M.; Watts, Korashon L.; Veiseh, Mandana; Grenley, Marc O.; Tretyak, Ilona; Dey, Joyoti; Carleton, Michael; Beirne, Emily; Pedro, Kyle D.; Ditzler, Sally H.; Girard, Emily J.; Deckwerth, Thomas L.; Bertout, Jessica A.; Meleo, Karri A.; Filvaroff, Ellen H.; Chopra, Rajesh; Press, Oliver W.; Olson, James M.

2016-01-01

A fundamental problem in cancer drug development is that antitumor efficacy in preclinical cancer models does not translate faithfully to patient outcomes. Much of early cancer drug discovery is performed under in vitro conditions in cell-based models that poorly represent actual malignancies. To address this inconsistency, we have developed a technology platform called CIVO, which enables simultaneous assessment of up to eight drugs or drug combinations within a single solid tumor in vivo. The platform is currently designed for use in animal models of cancer and patients with superficial tumors but can be modified for investigation of deeper-seated malignancies. In xenograft lymphoma models, CIVO microinjection of well-characterized anticancer agents (vincristine, doxorubicin, mafosfamide, and prednisolone) induced spatially defined cellular changes around sites of drug exposure, specific to the known mechanisms of action of each drug. The observed localized responses predicted responses to systemically delivered drugs in animals. In pair-matched lymphoma models, CIVO correctly demonstrated tumor resistance to doxorubicin and vincristine and an unexpected enhanced sensitivity to mafosfamide in multidrug-resistant lymphomas compared with chemotherapy-naïve lymphomas. A CIVO-enabled in vivo screen of 97 approved oncology agents revealed a novel mTOR (mammalian target of rapamycin) pathway inhibitor that exhibits significantly increased tumor-killing activity in the drug-resistant setting compared with chemotherapy-naïve tumors. Finally, feasibility studies to assess the use of CIVO in human and canine patients demonstrated that microinjection of drugs is toxicity-sparing while inducing robust, easily tracked, drug-specific responses in autochthonous tumors, setting the stage for further application of this technology in clinical trials. PMID:25904742

Simulated Models Suggest That Price per Calorie Is the Dominant Price Metric That Low-Income Individuals Use for Food Decision Making123

PubMed Central

2016-01-01

Background: The price of food has long been considered one of the major factors that affects food choices. However, the price metric (e.g., the price of food per calorie or the price of food per gram) that individuals predominantly use when making food choices is unclear. Understanding which price metric is used is especially important for studying individuals with severe budget constraints because food price then becomes even more important in food choice. Objective: We assessed which price metric is used by low-income individuals in deciding what to eat. Methods: With the use of data from NHANES and the USDA Food and Nutrient Database for Dietary Studies, we created an agent-based model that simulated an environment representing the US population, wherein individuals were modeled as agents with a specific weight, age, and income. In our model, agents made dietary food choices while meeting their budget limits with the use of 1 of 3 different metrics for decision making: energy cost (price per calorie), unit price (price per gram), and serving price (price per serving). The food consumption patterns generated by our model were compared to 3 independent data sets. Results: The food choice behaviors observed in 2 of the data sets were found to be closest to the simulated dietary patterns generated by the price per calorie metric. The behaviors observed in the third data set were equidistant from the patterns generated by price per calorie and price per serving metrics, whereas results generated by the price per gram metric were further away. Conclusions: Our simulations suggest that dietary food choice based on price per calorie best matches actual consumption patterns and may therefore be the most salient price metric for low-income populations. PMID:27655757

Simulated Models Suggest That Price per Calorie Is the Dominant Price Metric That Low-Income Individuals Use for Food Decision Making.

PubMed

Beheshti, Rahmatollah; Igusa, Takeru; Jones-Smith, Jessica

2016-11-01

The price of food has long been considered one of the major factors that affects food choices. However, the price metric (e.g., the price of food per calorie or the price of food per gram) that individuals predominantly use when making food choices is unclear. Understanding which price metric is used is especially important for studying individuals with severe budget constraints because food price then becomes even more important in food choice. We assessed which price metric is used by low-income individuals in deciding what to eat. With the use of data from NHANES and the USDA Food and Nutrient Database for Dietary Studies, we created an agent-based model that simulated an environment representing the US population, wherein individuals were modeled as agents with a specific weight, age, and income. In our model, agents made dietary food choices while meeting their budget limits with the use of 1 of 3 different metrics for decision making: energy cost (price per calorie), unit price (price per gram), and serving price (price per serving). The food consumption patterns generated by our model were compared to 3 independent data sets. The food choice behaviors observed in 2 of the data sets were found to be closest to the simulated dietary patterns generated by the price per calorie metric. The behaviors observed in the third data set were equidistant from the patterns generated by price per calorie and price per serving metrics, whereas results generated by the price per gram metric were further away. Our simulations suggest that dietary food choice based on price per calorie best matches actual consumption patterns and may therefore be the most salient price metric for low-income populations. © 2016 American Society for Nutrition.

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.

Glucose dysregulation and response to common anti-diabetic agents in the FATZO/Pco mouse

PubMed Central

Jackson, Charles Van; Zimmerman, Karen M.; Alsina-Fernandez, Jorge; Michael, M. Dodson; Emmerson, Paul J.; Coskun, Tamer

2017-01-01

The FATZO/Pco mouse is the result of a cross of the C57BL/6J and AKR/J strains. The crossing of these two strains and the selective inbreeding for obesity, insulin resistance and hyperglycemia has resulted in an inbred strain exhibiting obesity in the presumed presence of an intact leptin pathway. Routinely used rodent models for obesity and diabetes research have a monogenic defect in leptin signaling that initiates obesity. Given that obesity and its sequelae in humans are polygenic in nature and not associated with leptin signaling defects, the FATZO mouse may represent a more translatable rodent model for study of obesity and its associated metabolic disturbances. The FATZO mouse develops obesity spontaneously when fed a normal chow diet. Glucose intolerance with increased insulin levels are apparent in FATZO mice as young as 6 weeks of age. These progress to hyperglycemia/pre-diabetes and frank diabetes with decreasing insulin levels as they age. The disease in these mice is multi-faceted, similar to the metabolic syndrome apparent in obese individuals, and thus provides a long pre-diabetic state for determining the preventive value of new interventions. We have assessed the utility of this new model for the pre-clinical screening of agents to stop or slow progression of the metabolic syndrome to severe diabetes. Our assessment included: 1) characterization of the spontaneous development of disease, 2) comparison of metabolic disturbances of FATZO mice to control mice and 3) validation of the model with regard to the effectiveness of current and emerging anti-diabetic agents; rosiglitazone, metformin and semaglutide. Conclusion: Male FATZO mice spontaneously develop significant metabolic disease when compared to normal controls while maintaining hyperglycemia in the presence of high leptin levels and hyperinsulinemia. The disease condition responds to commonly used antidiabetic agents. PMID:28640857

A Platform for Simulating Language Evolution

NASA Astrophysics Data System (ADS)

Vogel, Carl; Woods, Justin

A platform for conducting experiments in the simulation of natural language evolution is presented. The system is paramaterized for independent specification of important features like: number of agents, communication attempt frequency, agent short term memory capacity, communicative urgency, etc. Representative experiments are demonstrated.

Adaptive Sampling of Time Series During Remote Exploration

NASA Technical Reports Server (NTRS)

Thompson, David R.

2012-01-01

This work deals with the challenge of online adaptive data collection in a time series. A remote sensor or explorer agent adapts its rate of data collection in order to track anomalous events while obeying constraints on time and power. This problem is challenging because the agent has limited visibility (all its datapoints lie in the past) and limited control (it can only decide when to collect its next datapoint). This problem is treated from an information-theoretic perspective, fitting a probabilistic model to collected data and optimizing the future sampling strategy to maximize information gain. The performance characteristics of stationary and nonstationary Gaussian process models are compared. Self-throttling sensors could benefit environmental sensor networks and monitoring as well as robotic exploration. Explorer agents can improve performance by adjusting their data collection rate, preserving scarce power or bandwidth resources during uninteresting times while fully covering anomalous events of interest. For example, a remote earthquake sensor could conserve power by limiting its measurements during normal conditions and increasing its cadence during rare earthquake events. A similar capability could improve sensor platforms traversing a fixed trajectory, such as an exploration rover transect or a deep space flyby. These agents can adapt observation times to improve sample coverage during moments of rapid change. An adaptive sampling approach couples sensor autonomy, instrument interpretation, and sampling. The challenge is addressed as an active learning problem, which already has extensive theoretical treatment in the statistics and machine learning literature. A statistical Gaussian process (GP) model is employed to guide sample decisions that maximize information gain. Nonsta tion - ary (e.g., time-varying) covariance relationships permit the system to represent and track local anomalies, in contrast with current GP approaches. Most common GP models are stationary, e.g., the covariance relationships are time-invariant. In such cases, information gain is independent of previously collected data, and the optimal solution can always be computed in advance. Information-optimal sampling of a stationary GP time series thus reduces to even spacing, and such models are not appropriate for tracking localized anomalies. Additionally, GP model inference can be computationally expensive.

The BTBR mouse model of idiopathic autism – current view on mechanisms

PubMed Central

Meyza, K. Z.; Blanchard, D. C.

2017-01-01

Autism spectrum disorder (ASD) is the most commonly diagnosed neurodevelopmental disorder, with current estimates of more than 1% of affected children across nations. The patients form a highly heterogeneous group with only the behavioral phenotype in common. The genetic heterogeneity is reflected in a plethora of animal models representing multiple mutations found in families of affected children. Despite many years of scientific effort, for the majority of cases the genetic cause remains elusive. It is therefore crucial to include well-validated models of idiopathic autism in studies searching for potential therapeutic agents. One of these models is the BTBR T+Itpr3tf/J mouse. The current review summarizes data gathered in recent research on potential molecular mechanisms responsible for the autism-like behavioral phenotype of this strain. PMID:28167097

Value of the distant future: Model-independent results

NASA Astrophysics Data System (ADS)

Katz, Yuri A.

2017-01-01

This paper shows that the model-independent account of correlations in an interest rate process or a log-consumption growth process leads to declining long-term tails of discount curves. Under the assumption of an exponentially decaying memory in fluctuations of risk-free real interest rates, I derive the analytical expression for an apt value of the long run discount factor and provide a detailed comparison of the obtained result with the outcome of the benchmark risk-free interest rate models. Utilizing the standard consumption-based model with an isoelastic power utility of the representative economic agent, I derive the non-Markovian generalization of the Ramsey discounting formula. Obtained analytical results allowing simple calibration, may augment the rigorous cost-benefit and regulatory impact analysis of long-term environmental and infrastructure projects.

An agent-based model driven by tropical rainfall to understand the spatio-temporal heterogeneity of a chikungunya outbreak.

PubMed

Dommar, Carlos J; Lowe, Rachel; Robinson, Marguerite; Rodó, Xavier

2014-01-01

Vector-borne diseases, such as dengue, malaria and chikungunya, are increasing across their traditional ranges and continuing to infiltrate new, previously unaffected, regions. The spatio-temporal evolution of these diseases is determined by the interaction of the host and vector, which is strongly dependent on social structures and mobility patterns. We develop an agent-based model (ABM), in which each individual is explicitly represented and vector populations are linked to precipitation estimates in a tropical setting. The model is implemented on both scale-free and regular networks. The spatio-temporal transmission of chikungunya is analysed and the presence of asymptomatic silent spreaders within the population is investigated in the context of implementing travel restrictions during an outbreak. Preventing the movement of symptomatic individuals is found to be an insufficient mechanism to halt the spread of the disease, which can be readily carried to neighbouring nodes via sub-clinical individuals. Furthermore, the impact of topology structure vs. precipitation levels is assessed and precipitation is found to be the dominant factor driving spatio-temporal transmission. Copyright © 2013 Elsevier B.V. All rights reserved.

A model of adaptive decision-making from representation of information environment by quantum fields.

PubMed

Bagarello, F; Haven, E; Khrennikov, A

2017-11-13

We present the mathematical model of decision-making (DM) of agents acting in a complex and uncertain environment (combining huge variety of economical, financial, behavioural and geopolitical factors). To describe interaction of agents with it, we apply the formalism of quantum field theory (QTF). Quantum fields are a purely informational nature. The QFT model can be treated as a far relative of the expected utility theory, where the role of utility is played by adaptivity to an environment (bath). However, this sort of utility-adaptivity cannot be represented simply as a numerical function. The operator representation in Hilbert space is used and adaptivity is described as in quantum dynamics. We are especially interested in stabilization of solutions for sufficiently large time. The outputs of this stabilization process, probabilities for possible choices, are treated in the framework of classical DM. To connect classical and quantum DM, we appeal to Quantum Bayesianism. We demonstrate the quantum-like interference effect in DM, which is exhibited as a violation of the formula of total probability, and hence the classical Bayesian inference scheme.This article is part of the themed issue 'Second quantum revolution: foundational questions'. © 2017 The Author(s).

A model of adaptive decision-making from representation of information environment by quantum fields

NASA Astrophysics Data System (ADS)

Bagarello, F.; Haven, E.; Khrennikov, A.

2017-10-01

We present the mathematical model of decision-making (DM) of agents acting in a complex and uncertain environment (combining huge variety of economical, financial, behavioural and geopolitical factors). To describe interaction of agents with it, we apply the formalism of quantum field theory (QTF). Quantum fields are a purely informational nature. The QFT model can be treated as a far relative of the expected utility theory, where the role of utility is played by adaptivity to an environment (bath). However, this sort of utility-adaptivity cannot be represented simply as a numerical function. The operator representation in Hilbert space is used and adaptivity is described as in quantum dynamics. We are especially interested in stabilization of solutions for sufficiently large time. The outputs of this stabilization process, probabilities for possible choices, are treated in the framework of classical DM. To connect classical and quantum DM, we appeal to Quantum Bayesianism. We demonstrate the quantum-like interference effect in DM, which is exhibited as a violation of the formula of total probability, and hence the classical Bayesian inference scheme. This article is part of the themed issue `Second quantum revolution: foundational questions'.

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.

Remodeling of the fibroblast cytoskeletal architecture during the replication cycle of Ectromelia virus: A morphological in vitro study in a murine cell line.

PubMed

Szulc-Dabrowska, Lidia; Gregorczyk, Karolina P; Struzik, Justyna; Boratynska-Jasinska, Anna; Szczepanowska, Joanna; Wyzewski, Zbigniew; Toka, Felix N; Gierynska, Malgorzata; Ostrowska, Agnieszka; Niemialtowski, Marek G

2016-08-01

Ectromelia virus (ECTV, the causative agent of mousepox), which represents the same genus as variola virus (VARV, the agent responsible for smallpox in humans), has served for years as a model virus for studying mechanisms of poxvirus-induced disease. Despite increasing knowledge on the interaction between ECTV and its natural host-the mouse-surprisingly, still little is known about the cell biology of ECTV infection. Because pathogen interaction with the cytoskeleton is still a growing area of research in the virus-host cell interplay, the aim of the present study was to evaluate the consequences of ECTV infection on the cytoskeleton in a murine fibroblast cell line. The viral effect on the cytoskeleton was reflected by changes in migration of the cells and rearrangement of the architecture of tubulin, vimentin, and actin filaments. The virus-induced cytoskeletal rearrangements observed in these studies contributed to the efficient cell-to-cell spread of infection, which is an important feature of ECTV virulence. Additionally, during later stages of infection L929 cells produced two main types of actin-based cellular protrusions: short (actin tails and "dendrites") and long (cytoplasmic corridors). Due to diversity of filopodial extensions induced by the virus, we suggest that ECTV represents a valuable new model for studying processes and pathways that regulate the formation of cytoskeleton-based cellular structures. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

A surgical confocal microlaparoscope for real-time optical biopsies

NASA Astrophysics Data System (ADS)

Tanbakuchi, Anthony Amir

The first real-time fluorescence confocal microlaparoscope has been developed that provides instant in vivo cellular images, comparable to those provided by histology, through a nondestructive procedure. The device includes an integrated contrast agent delivery mechanism and a computerized depth scan system. The instrument uses a fiber bundle to relay the image plane of a slit-scan confocal microlaparoscope into tissue. The confocal laparoscope was used to image the ovaries of twenty-one patients in vivo using fluorescein sodium and acridine orange as the fluorescent contrast agents. The results indicate that the device is safe and functions as designed. A Monte Carlo model was developed to characterize the system performance in a scattering media representative of human tissues. The results indicate that a slit aperture has limited ability to image below the surface of tissue. In contrast, the results show that multi-pinhole apertures such as a Nipkow disk or a linear pinhole array can achieve nearly the same depth performance as a single pinhole aperture. The model was used to determine the optimal aperture spacing for the multi-pinhole apertures. The confocal microlaparoscope represents a new type of in vivo imaging device. With its ability to image cellular details in real time, it has the potential to aid in the early diagnosis of cancer. Initially, the device may be used to locate unusual regions for guided biopsies. In the long term, the device may be able to supplant traditional biopsies and allow the surgeon to identify early stage cancer in vivo.

COMBAT: Initial experience with a randomized clinical trial of plasma-based resuscitation in the field for traumatic hemorrhagic shock

PubMed Central

Chapman, Michael P.; Moore, Ernest E.; Chin, Theresa L; Ghasabyan, Arsen; Chandler, James; Stringham, John; Gonzalez, Eduardo; Moore, Hunter B.; Banerjee, Anirban; Silliman, Christopher C; Sauaia, Angela

2015-01-01

The existing evidence shows great promise for plasma as the first resuscitation fluid in both civilian and military trauma. We embarked on the Control of Major Bleeding After Trauma (COMBAT) trial with the support of the Department of Defense, in order to determine if plasma-first resuscitation yields hemostatic and survival benefits. The methodology of the COMBAT study represents not only three years of development work, but the integration of nearly two-decades of technical experience with the design and implementation of other clinical trials and studies. Herein, we describe the key features of the study design, critical personnel and infrastructural elements, and key innovations. We will also briefly outline the systems engineering challenges entailed by this study. COMBAT is a randomized, placebo controlled, semi-blinded prospective Phase IIB clinical trial, conducted in a ground ambulance fleet based at a Level I trauma center, and part of a multicenter collaboration. The primary objective of COMBAT is to determine the efficacy of field resuscitation with plasma first, compared to standard of care (normal saline). To date we have enrolled 30 subjects in the COMBAT study. The ability to achieve intervention with a hemostatic resuscitation agent in the closest possible temporal proximity to injury is critical and represents an opportunity to forestall the evolution of the “bloody vicious cycle”. Thus, the COMBAT model for deploying plasma in first response units should serve as a model for RCTs of other hemostatic resuscitative agents. PMID:25784527

Performance evaluation of an agent-based occupancy simulation model

DOE PAGES

Luo, Xuan; Lam, Khee Poh; Chen, Yixing; ...

2017-01-17

Occupancy is an important factor driving building performance. Static and homogeneous occupant schedules, commonly used in building performance simulation, contribute to issues such as performance gaps between simulated and measured energy use in buildings. Stochastic occupancy models have been recently developed and applied to better represent spatial and temporal diversity of occupants in buildings. However, there is very limited evaluation of the usability and accuracy of these models. This study used measured occupancy data from a real office building to evaluate the performance of an agent-based occupancy simulation model: the Occupancy Simulator. The occupancy patterns of various occupant types weremore » first derived from the measured occupant schedule data using statistical analysis. Then the performance of the simulation model was evaluated and verified based on (1) whether the distribution of observed occupancy behavior patterns follows the theoretical ones included in the Occupancy Simulator, and (2) whether the simulator can reproduce a variety of occupancy patterns accurately. Results demonstrated the feasibility of applying the Occupancy Simulator to simulate a range of occupancy presence and movement behaviors for regular types of occupants in office buildings, and to generate stochastic occupant schedules at the room and individual occupant levels for building performance simulation. For future work, model validation is recommended, which includes collecting and using detailed interval occupancy data of all spaces in an office building to validate the simulated occupant schedules from the Occupancy Simulator.« less

Performance evaluation of an agent-based occupancy simulation model

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

Luo, Xuan; Lam, Khee Poh; Chen, Yixing

Occupancy is an important factor driving building performance. Static and homogeneous occupant schedules, commonly used in building performance simulation, contribute to issues such as performance gaps between simulated and measured energy use in buildings. Stochastic occupancy models have been recently developed and applied to better represent spatial and temporal diversity of occupants in buildings. However, there is very limited evaluation of the usability and accuracy of these models. This study used measured occupancy data from a real office building to evaluate the performance of an agent-based occupancy simulation model: the Occupancy Simulator. The occupancy patterns of various occupant types weremore » first derived from the measured occupant schedule data using statistical analysis. Then the performance of the simulation model was evaluated and verified based on (1) whether the distribution of observed occupancy behavior patterns follows the theoretical ones included in the Occupancy Simulator, and (2) whether the simulator can reproduce a variety of occupancy patterns accurately. Results demonstrated the feasibility of applying the Occupancy Simulator to simulate a range of occupancy presence and movement behaviors for regular types of occupants in office buildings, and to generate stochastic occupant schedules at the room and individual occupant levels for building performance simulation. For future work, model validation is recommended, which includes collecting and using detailed interval occupancy data of all spaces in an office building to validate the simulated occupant schedules from the Occupancy Simulator.« less

Development of analysis technique to predict the material behavior of blowing agent

NASA Astrophysics Data System (ADS)

Hwang, Ji Hoon; Lee, Seonggi; Hwang, So Young; Kim, Naksoo

2014-11-01

In order to numerically simulate the foaming behavior of mastic sealer containing the blowing agent, a foaming and driving force model are needed which incorporate the foaming characteristics. Also, the elastic stress model is required to represent the material behavior of co-existing phase of liquid state and the cured polymer. It is important to determine the thermal properties such as thermal conductivity and specific heat because foaming behavior is heavily influenced by temperature change. In this study, three models are proposed to explain the foaming process and material behavior during and after the process. To obtain the material parameters in each model, following experiments and the numerical simulations are performed: thermal test, simple shear test and foaming test. The error functions are defined as differences between the experimental measurements and the numerical simulation results, and then the parameters are determined by minimizing the error functions. To ensure the validity of the obtained parameters, the confirmation simulation for each model is conducted by applying the determined parameters. The cross-verification is performed by measuring the foaming/shrinkage force. The results of cross-verification tended to follow the experimental results. Interestingly, it was possible to estimate the micro-deformation occurring in automobile roof surface by applying the proposed model to oven process analysis. The application of developed analysis technique will contribute to the design with minimized micro-deformation.

Menaquinone analogs inhibit growth of bacterial pathogens.

PubMed

Schlievert, Patrick M; Merriman, Joseph A; Salgado-Pabón, Wilmara; Mueller, Elizabeth A; Spaulding, Adam R; Vu, Bao G; Chuang-Smith, Olivia N; Kohler, Petra L; Kirby, John R

2013-11-01

Gram-positive bacteria cause serious human illnesses through combinations of cell surface and secreted virulence factors. We initiated studies with four of these organisms to develop novel topical antibacterial agents that interfere with growth and exotoxin production, focusing on menaquinone analogs. Menadione, 1,4-naphthoquinone, and coenzymes Q1 to Q3 but not menaquinone, phylloquinone, or coenzyme Q10 inhibited the growth and to a greater extent exotoxin production of Staphylococcus aureus, Bacillus anthracis, Streptococcus pyogenes, and Streptococcus agalactiae at concentrations of 10 to 200 μg/ml. Coenzyme Q1 reduced the ability of S. aureus to cause toxic shock syndrome in a rabbit model, inhibited the growth of four Gram-negative bacteria, and synergized with another antimicrobial agent, glycerol monolaurate, to inhibit S. aureus growth. The staphylococcal two-component system SrrA/B was shown to be an antibacterial target of coenzyme Q1. We hypothesize that menaquinone analogs both induce toxic reactive oxygen species and affect bacterial plasma membranes and biosynthetic machinery to interfere with two-component systems, respiration, and macromolecular synthesis. These compounds represent a novel class of potential topical therapeutic agents.

Spatial patterns and scale freedom in Prisoner's Dilemma cellular automata with Pavlovian strategies

NASA Astrophysics Data System (ADS)

Fort, H.; Viola, S.

2005-01-01

A cellular automaton in which cells represent agents playing the Prisoner's Dilemma (PD) game following the simple 'win—stay, lose—shift' strategy is studied. Individuals with binary behaviour, such that they can either cooperate (C) or defect (D), play repeatedly with their neighbours (Von Neumann's and Moore's neighbourhoods). Their utilities in each round of the game are given by a rescaled pay-off matrix described by a single parameter τ, which measures the ratio of temptation to defect to reward for cooperation. Depending on the region of the parameter space τ, the system self-organizes—after a transient—into dynamical equilibrium states characterized by different definite fractions of C agents \\bar {c}_\\infty (two states for the von Neumann neighbourhood and four for the Moore neighbourhood). For some ranges of τ the cluster size distributions, the power spectra P(f) and the perimeter-area curves follow power law scalings. Percolation below threshold is also found for D agent clusters. We also analyse the asynchronous dynamics version of this model and compare results.

Microbiological control of soil-borne phytopathogenic fungi with special emphasis on wilt-inducing Fusarium oxysporum.

PubMed

Alabouvette, Claude; Olivain, Chantal; Migheli, Quirico; Steinberg, Christian

2009-11-01

Plant diseases induced by soil-borne plant pathogens are among the most difficult to control. In the absence of effective chemical control methods, there is renewed interest in biological control based on application of populations of antagonistic micro-organisms. In addition to Pseudomonas spp. and Trichoderma spp., which are the two most widely studied groups of biological control agents, the protective strains of Fusarium oxysporum represent an original model. These protective strains of F. oxysporum can be used to control wilt induced by pathogenic strains of the same species. Exploring the mechanisms involved in the protective capability of these strains is not only necessary for their development as commercial biocontrol agents but raises many basic questions related to the determinism of pathogenicity versus biocontrol capacity in the F. oxysporum species complex. In this paper, current knowledge regarding the interaction between the plant and the protective strains is reviewed in comparison with interactions between the plant and pathogenic strains. The success of biological control depends not only on plant-microbial interactions but also on the ecological fitness of the biological control agents.

Threshold model of cascades in empirical temporal networks

NASA Astrophysics Data System (ADS)

Karimi, Fariba; Holme, Petter

2013-08-01

Threshold models try to explain the consequences of social influence like the spread of fads and opinions. Along with models of epidemics, they constitute a major theoretical framework of social spreading processes. In threshold models on static networks, an individual changes her state if a certain fraction of her neighbors has done the same. When there are strong correlations in the temporal aspects of contact patterns, it is useful to represent the system as a temporal network. In such a system, not only contacts but also the time of the contacts are represented explicitly. In many cases, bursty temporal patterns slow down disease spreading. However, as we will see, this is not a universal truth for threshold models. In this work we propose an extension of Watts’s classic threshold model to temporal networks. We do this by assuming that an agent is influenced by contacts which lie a certain time into the past. I.e., the individuals are affected by contacts within a time window. In addition to thresholds in the fraction of contacts, we also investigate the number of contacts within the time window as a basis for influence. To elucidate the model’s behavior, we run the model on real and randomized empirical contact datasets.

Homeopathy: clarifying its relationship to hormesis.

PubMed

Calabrese, Edward J; Jonas, Wayne B

2010-07-01

This paper presents the case that certain types of homeopathic medicine may represent a form of hormesis, that is, either pre- or post-conditioning hormesis. An example of a post-conditioning model by van Wijk and colleagues demonstrated successful enhancement of adaptive responses using below-toxic threshold doses (i.e. hormetic doses) of inducing agents when administered subsequent to a highly toxic chemical exposure, thus satisfying a basic experimental biomedical standard. Of note is that this model uses exposures within a measurable predicted hormetic range, unlike most forms of homeopathy. This experimental framework (along with a pre-conditioning model developed by Bellavite) provides a possible vehicle by which certain aspect(s) of homeopathy may be integrated into mainstream biomedical assessment and clinical practice.

29 CFR 548.400 - Procedures.

Code of Federal Regulations, 2010 CFR

2010-07-01

... represented by a collective bargaining agent, a joint application of the employer and the bargaining agent... ESTABLISHED BASIC RATES FOR COMPUTING OVERTIME PAY Interpretations Rates Authorized on Application § 548.400... immediately preceding 4-week period, he should apply to the Administrator for authorization. The application...

TACtic- A Multi Behavioral Agent for Trading Agent Competition

NASA Astrophysics Data System (ADS)

Khosravi, Hassan; Shiri, Mohammad E.; Khosravi, Hamid; Iranmanesh, Ehsan; Davoodi, Alireza

Software agents are increasingly being used to represent humans in online auctions. Such agents have the advantages of being able to systematically monitor a wide variety of auctions and then make rapid decisions about what bids to place in what auctions. They can do this continuously and repetitively without losing concentration. To provide a means of evaluating and comparing (benchmarking) research methods in this area the trading agent competition (TAC) was established. This paper describes the design, of TACtic. Our agent uses multi behavioral techniques at the heart of its decision making to make bidding decisions in the face of uncertainty, to make predictions about the likely outcomes of auctions, and to alter the agent's bidding strategy in response to the prevailing market conditions.

GIS model for identifying urban areas vulnerable to noise pollution: case study

NASA Astrophysics Data System (ADS)

Bilaşco, Ştefan; Govor, Corina; Roşca, Sanda; Vescan, Iuliu; Filip, Sorin; Fodorean, Ioan

2017-04-01

The unprecedented expansion of the national car ownership over the last few years has been determined by economic growth and the need for the population and economic agents to reduce travel time in progressively expanding large urban centres. This has led to an increase in the level of road noise and a stronger impact on the quality of the environment. Noise pollution generated by means of transport represents one of the most important types of pollution with negative effects on a population's health in large urban areas. As a consequence, tolerable limits of sound intensity for the comfort of inhabitants have been determined worldwide and the generation of sound maps has been made compulsory in order to identify the vulnerable zones and to make recommendations how to decrease the negative impact on humans. In this context, the present study aims at presenting a GIS spatial analysis model-based methodology for identifying and mapping zones vulnerable to noise pollution. The developed GIS model is based on the analysis of all the components influencing sound propagation, represented as vector databases (points of sound intensity measurements, buildings, lands use, transport infrastructure), raster databases (DEM), and numerical databases (wind direction and speed, sound intensity). Secondly, the hourly changes (for representative hours) were analysed to identify the hotspots characterised by major traffic flows specific to rush hours. The validated results of the model are represented by GIS databases and useful maps for the local public administration to use as a source of information and in the process of making decisions.

STAT3 Oligonucleotide Inhibits Tumor Angiogenesis in Preclinical Models of Squamous Cell Carcinoma

PubMed Central

Klein, Jonah D.; Sano, Daisuke; Sen, Malabika; Myers, Jeffrey N.; Grandis, Jennifer R.; Kim, Seungwon

2014-01-01

Purpose Signal transducer and activator of transcription 3 (STAT3) has shown to play a critical role in head and neck squamous cell carcinoma (HNSCC) and we have recently completed clinical trials of STAT3 decoy oligonucleotide in patients with recurrent or metastatic HNSCC. However, there is limited understanding of the role of STAT3 in modulating other aspects of tumorigenesis such as angiogenesis. In this study, we aimed to examine the effects of STAT3 decoy oligonucleotide on tumor angiogenesis. Experimental Design A STAT3 decoy oligonucleotide and small interfering RNA (siRNA) were used to inhibit STAT3 in endothelial cells in vitro and in vivo. The biochemical effects of STAT3 inhibition were examined in conjunction with the consequences on proliferation, migration, apoptotic staining, and tubule formation. Additionally, we assessed the effects of STAT3 inhibition on tumor angiogenesis using murine xenograft models. Results STAT3 decoy oligonucleotide decreased proliferation, induces apoptosis, decreased migration, and decreased tubule formation of endothelial cells in vitro. The STAT3 decoy oligonucleotide also inhibited tumor angiogenesis in murine tumor xenografts. Lastly, our data suggest that the antiangiogenic effects of STAT3 decoy oligonucleotide were mediatedthrough the inhibition of both STAT3 and STAT1. Conclusions The STAT3 decoy oligonucleotidewas found to be an effective antiangiogenic agent, which is likely to contribute to the overall antitumor effects of this agent in solid tumors.Taken together with the previously demonstrated antitumor activity of this agent, STAT3 decoy oligonucleotide represents a promising single agent approach to targeting both the tumor and vascular compartments in various malignancies. PMID:24404126

QSAR modeling of GPCR ligands: methodologies and examples of applications.

PubMed

Tropsha, A; Wang, S X

2006-01-01

GPCR ligands represent not only one of the major classes of current drugs but the major continuing source of novel potent pharmaceutical agents. Because 3D structures of GPCRs as determined by experimental techniques are still unavailable, ligand-based drug discovery methods remain the major computational molecular modeling approaches to the analysis of growing data sets of tested GPCR ligands. This paper presents an overview of modern Quantitative Structure Activity Relationship (QSAR) modeling. We discuss the critical issue of model validation and the strategy for applying the successfully validated QSAR models to virtual screening of available chemical databases. We present several examples of applications of validated QSAR modeling approaches to GPCR ligands. We conclude with the comments on exciting developments in the QSAR modeling of GPCR ligands that focus on the study of emerging data sets of compounds with dual or even multiple activities against two or more of GPCRs.

Perspectives on why digital ecologies matter: combining population genetics and ecologically informed agent-based models with GIS for managing dipteran livestock pests.

PubMed

Peck, Steven L

2014-10-01

It is becoming clear that handling the inherent complexity found in ecological systems is an essential task for finding ways to control insect pests of tropical livestock such as tsetse flies, and old and new world screwworms. In particular, challenging multivalent management programs, such as Area Wide Integrated Pest Management (AW-IPM), face daunting problems of complexity at multiple spatial scales, ranging from landscape level processes to those of smaller scales such as the parasite loads of individual animals. Daunting temporal challenges also await resolution, such as matching management time frames to those found on ecological and even evolutionary temporal scales. How does one deal with representing processes with models that involve multiple spatial and temporal scales? Agent-based models (ABM), combined with geographic information systems (GIS), may allow for understanding, predicting and managing pest control efforts in livestock pests. This paper argues that by incorporating digital ecologies in our management efforts clearer and more informed decisions can be made. I also point out the power of these models in making better predictions in order to anticipate the range of outcomes possible or likely. Copyright © 2014 International Atomic Energy Agency 2014. Published by Elsevier B.V. All rights reserved.

Prevention of acetic acid-induced colitis by desferrithiocin analogs in a rat model.

PubMed

Bergeron, Raymond J; Wiegand, Jan; Weimar, William R; Nguyen, John Nhut; Sninsky, Charles A

2003-02-01

Iron contributes significantly to the formation of reactive oxygen species via the Fenton reaction. Therefore, we assessed whether a series of desferrithiocin analogs, both carboxylic acids and hydroxamates, could (1) either promote or diminish the iron-mediated oxidation of ascorbate, (2) quench a model radical species, 2,2'-azinobis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS+), and (3) when applied topically, prevent acetic acid-induced colitis in rats. Surprisingly, most of the desferrithiocin analogs inhibited the Fenton reaction to an approximately equivalent degree; however, substantial differences were observed in the capacity of the analogs to scavenge the model radical cation. Four carboxylic acid desferrithiocin analogs and their respective N-methylhydroxamates were tested along with desferrioxamine and Rowasa, a currently accepted topical therapeutic agent for inflammatory bowel disease (IBD), in a rodent model of acetic acid-induced colitis. The colonic damage was quantitated by two independent measurements. Although neither radical scavenging nor prevention of Fenton chemistry was a definitive predictor of in vivo efficacy, the overall trend is that desferrithiocin analogs substituted with an N-methylhydroxamate in the place of the carboxylic acid are both better free radical scavengers and more active against acetic acid-induced colitis. These results represent an intriguing alternative avenue to the development of improved IBD therapeutic agents.

Medical Treatments for Endometriosis-Associated Pelvic Pain

PubMed Central

Luppi, Stefania; Ricci, Giuseppe

2014-01-01

The main sequelae of endometriosis are represented by infertility and chronic pelvic pain. Chronic pelvic pain causes disability and distress with a very high economic impact. In the last decades, an impressive amount of pharmacological agents have been tested for the treatment of endometriosis-associated pelvic pain. However, only a few of these have been introduced into clinical practice. Following the results of the controlled studies available, to date, the first-line treatment for endometriosis associated pain is still represented by oral contraceptives used continuously. Progestins represent an acceptable alternative. In women with rectovaginal lesions or colorectal endometriosis, norethisterone acetate at low dosage should be preferred. GnRH analogues may be used as second-line treatment, but significant side effects should be taken into account. Nonsteroidal anti-inflammatory drugs are widely used, but there is inconclusive evidence for their efficacy in relieving endometriosis-associated pelvic pain. Other agents such as GnRH antagonist, aromatase inhibitors, immunomodulators, selective progesterone receptor modulators, and histone deacetylase inhibitors seem to be very promising, but there is not enough evidence to support their introduction into routine clinical practice. Some other agents, such as peroxisome proliferator activated receptors-γ ligands, antiangiogenic agents, and melatonin have been proven to be efficacious in animal studies, but they have not yet been tested in clinical studies. PMID:25165691

Formal analysis of temporal dynamics in anxiety states and traits for virtual patients

NASA Astrophysics Data System (ADS)

Aziz, Azizi Ab; Ahmad, Faudziah; Yusof, Nooraini; Ahmad, Farzana Kabir; Yusof, Shahrul Azmi Mohd

2016-08-01

This paper presents a temporal dynamic model of anxiety states and traits for an individual. Anxiety is a natural part of life, and most of us experience it from time to time. But for some people, anxiety can be extreme. Based on several personal characteristics, traits, and a representation of events (i.e. psychological and physiological stressors), the formal model can represent whether a human that experience certain scenarios will fall into an anxiety states condition. A number of well-known relations between events and the course of anxiety are summarized from the literature and it is shown that the model exhibits those patterns. In addition, the formal model has been mathematically analyzed to find out which stable situations exist. Finally, it is pointed out how this model can be used in therapy, supported by a software agent.

Potentiation of chemotherapeutics by bromelain and N-acetylcysteine: sequential and combination therapy of gastrointestinal cancer cells

PubMed Central

Amini, Afshin; Masoumi-Moghaddam, Samar; Ehteda, Anahid; Liauw, Winston; Morris, David Lawson

2016-01-01

Intraperitoneal chemotherapy together with cytoreductive surgery is the standard of care for a number of peritoneal surface malignancies. However, this approach fails to maintain the complete response and disease recurs due to microscopic residual disease. Although safer than systemic chemotherapy regimens, locoregional treatment with chemotherapeutics can induce toxicity which is a major concern affecting the patient’s treatment protocol and outcome. For an enhanced treatment efficacy, efforts should be made to maximize cytotoxic effects of chemotherapeutic agents on tumor cells while minimizing their toxic effects on host cells. Bromelain and N-acetylcysteine are two natural agents with good safety profiles shown to have anti-cancer effects. However, their interaction with chemotherapeutics is unknown. In this study, we investigated if these agents have the potential to sensitize in vitro gastrointestinal cancer models to cisplatin, paclitaxel, 5-fluorouracil, and vincristine. The drug-drug interaction was also analyzed. Our findings suggest that combination of bromelain and N-acetylcysteine with chemotherapeutic agents could give rise to an improved chemotherapeutic index in therapeutic approaches to peritoneal surface malignancies of gastrointestinal origin so that maximum benefits could result from less toxic and more patient-friendly doses. This represents a potentially efficacious strategy for the enhancement of microscopic cytoreduction and is a promising area for future research. PMID:27186409

Synthesis and mechanisms of action of novel harmine derivatives as potential antitumor agents

PubMed Central

Zhang, Xiao-Fei; Sun, Rong-qin; Jia, Yi-fan; Chen, Qing; Tu, Rong-Fu; Li, Ke-ke; Zhang, Xiao-Dong; Du, Run-Lei; Cao, Ri-hui

2016-01-01

A series of novel harmine derivatives bearing a benzylindine substituent in position-1 of β-carboline ring were synthesized and evaluated as antitumor agents. The N2-benzylated β-carboline derivatives 3a–g represented the most interesting anticancer activities and compound 3c was found to be the most active agent to diverse cancer cell lines such as gastric carcinoma, melanoma and colorectal cancer. Notably, compound 3c showed low toxicity to normal cells. The treatment significantly induced cell apoptosis. Mechanistically, PI3K/AKT signaling pathway mediated compound 3c-induced apoptosis. Compound 3c inhibited phosphorylation of AKT and promoted the production of reactive oxygen species (ROS). The ROS scavenger, LNAC and GSH, could disturb the effect of compound 3c induced apoptosis and PI3K activity inhibitor LY294002 synergistically enhanced compound 3c efficacy. Moreover, the results from nude mice xenograft model showed that compound 3c treatment effectively inhibited tumor growth and decreased tumor weight. Collectively, our results demonstrated that compound 3c exerts apoptotic effect in cancer cells via suppression of phosphorylated AKT and evocation of ROS generation, which suggested that compound 3c might be served as a promising therapeutic agent for cancer treatment. PMID:27625151

The highly intelligent virtual agents for modeling financial markets

NASA Astrophysics Data System (ADS)

Yang, G.; Chen, Y.; Huang, J. P.

2016-02-01

Researchers have borrowed many theories from statistical physics, like ensemble, Ising model, etc., to study complex adaptive systems through agent-based modeling. However, one fundamental difference between entities (such as spins) in physics and micro-units in complex adaptive systems is that the latter are usually with high intelligence, such as investors in financial markets. Although highly intelligent virtual agents are essential for agent-based modeling to play a full role in the study of complex adaptive systems, how to create such agents is still an open question. Hence, we propose three principles for designing high artificial intelligence in financial markets and then build a specific class of agents called iAgents based on these three principles. Finally, we evaluate the intelligence of iAgents through virtual index trading in two different stock markets. For comparison, we also include three other types of agents in this contest, namely, random traders, agents from the wealth game (modified on the famous minority game), and agents from an upgraded wealth game. As a result, iAgents perform the best, which gives a well support for the three principles. This work offers a general framework for the further development of agent-based modeling for various kinds of complex adaptive systems.

A Systematic Review of Agent-Based Modelling and Simulation Applications in the Higher Education Domain

ERIC Educational Resources Information Center

Gu, X.; Blackmore, K. L.

2015-01-01

This paper presents the results of a systematic review of agent-based modelling and simulation (ABMS) applications in the higher education (HE) domain. Agent-based modelling is a "bottom-up" modelling paradigm in which system-level behaviour (macro) is modelled through the behaviour of individual local-level agent interactions (micro).…

A Quantum Approach to Multi-Agent Systems (MAS), Organizations, and Control

DTIC Science & Technology

2003-06-01

interdependent interactions between individuals represented approximately as vocal harmonic I resonators. Then the growth rate of an organization fits ...A quantum approach to multi-agent systems (MAS), organizations , and control W.F. Lawless Paine College 1235 15th Street Augusta, GA 30901...AND SUBTITLE A quantum approach to multi-agent systems (MAS), organizations , and control 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT

7 CFR 905.120 - Nomination procedure.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Agreements and Orders; Fruits, Vegetables, Nuts), DEPARTMENT OF AGRICULTURE ORANGES, GRAPEFRUIT, TANGERINES... be delivered by the chairman or the secretary of the meeting to the agent of the Secretary. If ballots are not used, the committee's representative shall deliver to the Secretary's agent a listing of...

42 CFR 71.1 - Scope and definitions.

Code of Federal Regulations, 2010 CFR

2010-10-01

... disease from foreign countries into the States or possessions of the United States. Regulations pertaining... representative. Disinfection means the killing of infectious agents or inactivation of their toxic products outside the body by direct exposure to chemical or physical agents. Disinfestation means any chemical or...

42 CFR 71.1 - Scope and definitions.

Code of Federal Regulations, 2012 CFR

2012-10-01

... disease from foreign countries into the States or possessions of the United States. Regulations pertaining... representative. Disinfection means the killing of infectious agents or inactivation of their toxic products outside the body by direct exposure to chemical or physical agents. Disinfestation means any chemical or...

42 CFR 71.1 - Scope and definitions.

Code of Federal Regulations, 2011 CFR

2011-10-01

... disease from foreign countries into the States or possessions of the United States. Regulations pertaining... representative. Disinfection means the killing of infectious agents or inactivation of their toxic products outside the body by direct exposure to chemical or physical agents. Disinfestation means any chemical or...

Buoyancy-generating agents for stomach-specific drug delivery: an overview with special emphasis on floating behavior.

PubMed

Ishak, Rania A H

2015-01-01

Gastric retentive drug delivery provides a promising technology exhibiting an extended gastric residence and a drug release independent of patient related variables. It is usually useful in improving local gastric treatment as well as overcoming drug-related problems .i.e. drugs having narrow absorption window, short half-life or low intestinal solubility. Buoyancy is considered one of the most promising approaches for gastro-retention of dosage forms. Floating drug delivery systems have a bulk density lower than gastric fluids and thus remain buoyant in the stomach causing an increase in gastric residence time. The buoyancy of these systems is attained by the aid of substances responsible to generate the low density. Various agents with different mechanisms were adopted either gas-generating agents, air entrapping swellable polymers, inherent low density substances, porous excipients, hollow/porous particles inducing preparation techniques or sublimating agents. Therefore, this review gives an exclusive descriptive classification of the different categories of these buoyancy-generating agents while representing the related research works. An overview is also conducted to describe relevant techniques assessing the floating behavior of such dosage forms either in vitro or in vivo. Finally, a collection representing FDA-approved floating pharmaceutical products is adopted with emphasis on the buoyancy-generating agent type used in each product.

Nitrosoureas: a review of experimental antitumor activity.

PubMed

Schabel, F M

1976-06-01

The chemical class of drugs known as the nitrosoureas are a recently developed group of very active alkylating-agent anticancer drugs which are best represented by BCNU, CCNU, and methyl-CCNU (meCCNU). The nitrosoureas are among the most active, if not the most active, anticancer drugs both quantitatively (log kill of sensitive tumor cells in vivo) and qualitatively (spectrum of mouse, rat, and hamster tumors responding to treatment). Therapeutic anticancer activity of the nitrosoureas has been consistently observed with oral as well as parenteral administration. The nitrosoureas are clearly the most active group of anticancer drugs observed against experimental meningeal leukemias and intracerebrally implanted transplantable primary tumors of central nervous system origin (eg, gliomas, ependymoblastomas, and astrocytomas in mice and hamsters). The nitrosoureas have been observed to be less than additive in lethal toxicity for vital normal cells in the mouse in combination with representatives of the other major classes of anticancer agents, eg, purine antagonists, pyrimidine antagonists, inhibitors of DNA polymerase(s) or ribonucleotide reductase(s), mitotic inhibitors, drugs that bind to or intercalate with DNA, and other alkylating agents. Therapeutic synergism against one or more transplantable or spontaneous tumors of mice, rats, or hamsters with one of several nitrosoureas in two-drug combinations with representatives of most of the major classes of anticancer agents listed above has been reported. With a number of advanced-stages mouse tumors, generally considered to be refractory to treatment with most anticancer agents, long-term cures have been obtained with combination-drug or combined-modality (surgery plus chemotherapy) treatment. The demonstrated lack of cross-resistance of several leukemias and solid tumors of mice selected for resistance to BCNU, meCCNU, or other alkylating agents suggests that the widely held opinion that all alkylating agents are very similar in biologic mechanism of action, and therefore resistance to one alkylating agent probably predicts cross-resistance to all alkylating agents, may no longer be tenable. If not, then alkylating-agent drug combinations, either used alone or combined with other treatment modalities (eg, surgery) which have been reported to result in therapeutic improvement in a number of experimental murine tumor systems, may be indicated for serious consideration as surgical adjuvant chemotherapy by surgeons or as primary therapy by medical oncologists.

Revisiting the differentiation paradigm in acute promyelocytic leukemia.

PubMed

Ablain, Julien; de The, Hugues

2011-06-02

As the result of intense clinical and basic research, acute promyelocytic leukemia (APL) has progressively evolved from a deadly to a curable disease. Historically, efforts aimed at understanding the molecular bases for therapy response have repeatedly illuminated APL pathogenesis. The classic model attributes this therapeutic success to the transcriptional reactivation elicited by retinoic acid and the resulting overcoming of the differentiation block characteristic of APL blasts. However, in clinical practice, retinoic acid by itself only rarely yields prolonged remissions, even though it induces massive differentiation. In contrast, as a single agent, arsenic trioxide neither directly activates transcription nor triggers terminal differentiation ex vivo, but cures many patients. Here we review the evidence from recent ex vivo and in vivo studies that allow a reassessment of the role of differentiation in APL cure. We discuss alternative models in which PML-RARA degradation and the subsequent loss of APL cell self-renewal play central roles. Rather than therapy aimed at inducing differentiation, targeting cancer cell self-renewal may represent a more effective goal, achievable by a broader range of therapeutic agents.

The co-evolutionary dynamics of directed network of spin market agents

NASA Astrophysics Data System (ADS)

Horváth, Denis; Kuscsik, Zoltán; Gmitra, Martin

2006-09-01

The spin market model [S. Bornholdt, Int. J. Mod. Phys. C 12 (2001) 667] is generalized by employing co-evolutionary principles, where strategies of the interacting and competitive traders are represented by local and global couplings between the nodes of dynamic directed stochastic network. The co-evolutionary principles are applied in the frame of Bak-Sneppen self-organized dynamics [P. Bak, K. Sneppen, Phys. Rev. Lett. 71 (1993) 4083] that includes the processes of selection and extinction actuated by the local (node) fitness. The local fitness is related to orientation of spin agent with respect to the instant magnetization. The stationary regime is formed due to the interplay of self-organization and adaptivity effects. The fat tailed distributions of log-price returns are identified numerically. The non-trivial model consequence is the evidence of the long time market memory indicated by the power-law range of the autocorrelation function of volatility with exponent smaller than one. The simulations yield network topology with broad-scale node degree distribution characterized by the range of exponents 1.3<γin<3 coinciding with social networks.

Inhibitors of type II NADH:menaquinone oxidoreductase represent a class of antitubercular drugs

PubMed Central

Weinstein, Edward A.; Yano, Takahiro; Li, Lin-Sheng; Avarbock, David; Avarbock, Andrew; Helm, Douglas; McColm, Andrew A.; Duncan, Ken; Lonsdale, John T.; Rubin, Harvey

2005-01-01

Mycobacterium tuberculosis (Mtb) is an obligate aerobe that is capable of long-term persistence under conditions of low oxygen tension. Analysis of the Mtb genome predicts the existence of a branched aerobic respiratory chain terminating in a cytochrome bd system and a cytochrome aa3 system. Both chains can be initiated with type II NADH:menaquinone oxidoreductase. We present a detailed biochemical characterization of the aerobic respiratory chains from Mtb and show that phenothiazine analogs specifically inhibit NADH:menaquinone oxidoreductase activity. The emergence of drug-resistant strains of Mtb has prompted a search for antimycobacterial agents. Several phenothiazines analogs are highly tuberculocidal in vitro, suppress Mtb growth in a mouse model of acute infection, and represent lead compounds that may give rise to a class of selective antibiotics. PMID:15767566

Multistage Fuzzy Decision Making in Bilateral Negotiation with Finite Termination Times

NASA Astrophysics Data System (ADS)

Richter, Jan; Kowalczyk, Ryszard; Klusch, Matthias

In this paper we model the negotiation process as a multistage fuzzy decision problem where the agents preferences are represented by a fuzzy goal and fuzzy constraints. The opponent is represented by a fuzzy Markov decision process in the form of offer-response patterns which enables utilization of limited and uncertain information, e.g. the characteristics of the concession behaviour. We show that we can obtain adaptive negotiation strategies by only using the negotiation threads of two past cases to create and update the fuzzy transition matrix. The experimental evaluation demonstrates that our approach is adaptive towards different negotiation behaviours and that the fuzzy representation of the preferences and the transition matrix allows for application in many scenarios where the available information, preferences and constraints are soft or imprecise.

Ultrasound detection and identification of cosmetic fillers in the skin.

PubMed

Wortsman, X; Wortsman, J; Orlandi, C; Cardenas, G; Sazunic, I; Jemec, G B E

2012-03-01

While the incidence of cosmetic filler injections is rising world-wide, neither exact details of the procedure nor the agent used are always reported or remembered by the patients. Thus, although complications are reportedly rare, availability of a precise diagnostic tool to detect cutaneous filler deposits could help clarify the association between the procedure and the underlying pathology. The aim of this study was to evaluate cutaneous sonography in the detection and identification of cosmetic fillers deposits and, describe dermatological abnormalities found associated with the presence of those agents. We used ultrasound in a porcine skin model to determine the sonographic characteristics of commonly available filler agents, and subsequently applied the analysis to detect and identify cosmetic fillers among patients referred for skin disorders. Fillers are recognizable on ultrasound and generate different patterns of echogenicity and posterior acoustic artefacts. Cosmetic fillers were identified in 118 dermatological patients; most commonly hyaluronic acid among degradable agents and silicone oil among non-degradable. Fillers deposits were loosely scattered throughout the subcutaneous tissue, with occasional infiltration of local muscles and loco-regional lymph nodes. Accompanying dermatopathies were represented by highly localized inflammatory processes unresponsive to conventional treatment, morphea-like reactions, necrosis of fatty tissue and epidermal cysts; in the case of non-degradable agents, the associated dermatopathies were transient, resolving upon disappearance of the filler. Cosmetic filler agents may be detected and identified during routine ultrasound of dermatological lesions; the latter appear to be pathologically related to the cosmetic procedure. © 2011 The Authors. Journal of the European Academy of Dermatology and Venereology © 2011 European Academy of Dermatology and Venereology.

Second generation benzofuranone ring substituted noscapine analogs: Synthesis and biological evaluation

PubMed Central

Mishra, Ram Chandra; Karna, Prasanthi; Gundala, Sushma Reddy; Pannu, Vaishali; Stanton, Richard A.; Gupta, Kamlesh Kumar; Robinson, Mary; Lopus, Manu; Wilson, Leslie; Henary, Maged; Aneja, Ritu

2011-01-01

Microtubules, composed of α/β tubulin heterodimers, represent a validated target for cancer chemotherapy. Thus, tubulin- and microtubule-binding antimitotic drugs such as taxanes and vincas are widely employed for the chemotherapeutic management of various malignancies. Although quite successful in the clinic, these drugs are associated with severe toxicity and drug resistance problems. Noscapinoids represent an emerging class of microtubule-modulating anticancer agents based upon the parent molecule noscapine, a naturally-occurring non-toxic cough-suppressant opium alkaloid. Here we report in silico molecular modeling, chemical synthesis and biological evaluation of novel analogs derived by modification at position-7 of the benzofuranone ring system of noscapine. The synthesized analogs were evaluated for their tubulin polymerization activity and their biological activity was examined by their antiproliferative potential using representative cancer cell lines from varying tissue-origin [A549 (lung), CEM (lymphoma), MIA PaCa-2 (pancreatic), MCF-7 (breast) and PC-3 (prostate)]. Cell-cycle studies were performed to explore their ability to halt the cell-cycle and induce subsequent apoptosis. The varying biological activity of these analogs that differ in the nature and bulk of substituent at position-7 was rationalized utilizing predictive in silico molecular modeling. PMID:21501599

The Underlying Social Dynamics of Paradigm Shifts.

PubMed

Rodriguez-Sickert, Carlos; Cosmelli, Diego; Claro, Francisco; Fuentes, Miguel Angel

2015-01-01

We develop here a multi-agent model of the creation of knowledge (scientific progress or technological evolution) within a community of researchers devoted to such endeavors. In the proposed model, agents learn in a physical-technological landscape, and weight is attached to both individual search and social influence. We find that the combination of these two forces together with random experimentation can account for both i) marginal change, that is, periods of normal science or refinements on the performance of a given technology (and in which the community stays in the neighborhood of the current paradigm); and ii) radical change, which takes the form of scientific paradigm shifts (or discontinuities in the structure of performance of a technology) that is observed as a swift migration of the knowledge community towards the new and superior paradigm. The efficiency of the search process is heavily dependent on the weight that agents posit on social influence. The occurrence of a paradigm shift becomes more likely when each member of the community attaches a small but positive weight to the experience of his/her peers. For this parameter region, nevertheless, a conservative force is exerted by the representatives of the current paradigm. However, social influence is not strong enough to seriously hamper individual discovery, and can act so as to empower successful individual pioneers who have conquered the new and superior paradigm.

The Underlying Social Dynamics of Paradigm Shifts

PubMed Central

Claro, Francisco; Fuentes, Miguel Angel

2015-01-01

We develop here a multi-agent model of the creation of knowledge (scientific progress or technological evolution) within a community of researchers devoted to such endeavors. In the proposed model, agents learn in a physical-technological landscape, and weight is attached to both individual search and social influence. We find that the combination of these two forces together with random experimentation can account for both i) marginal change, that is, periods of normal science or refinements on the performance of a given technology (and in which the community stays in the neighborhood of the current paradigm); and ii) radical change, which takes the form of scientific paradigm shifts (or discontinuities in the structure of performance of a technology) that is observed as a swift migration of the knowledge community towards the new and superior paradigm. The efficiency of the search process is heavily dependent on the weight that agents posit on social influence. The occurrence of a paradigm shift becomes more likely when each member of the community attaches a small but positive weight to the experience of his/her peers. For this parameter region, nevertheless, a conservative force is exerted by the representatives of the current paradigm. However, social influence is not strong enough to seriously hamper individual discovery, and can act so as to empower successful individual pioneers who have conquered the new and superior paradigm. PMID:26418255

Discrete Element Framework for Modelling Extracellular Matrix, Deformable Cells and Subcellular Components

PubMed Central

Gardiner, Bruce S.; Wong, Kelvin K. L.; Joldes, Grand R.; Rich, Addison J.; Tan, Chin Wee; Burgess, Antony W.; Smith, David W.

2015-01-01

This paper presents a framework for modelling biological tissues based on discrete particles. Cell components (e.g. cell membranes, cell cytoskeleton, cell nucleus) and extracellular matrix (e.g. collagen) are represented using collections of particles. Simple particle to particle interaction laws are used to simulate and control complex physical interaction types (e.g. cell-cell adhesion via cadherins, integrin basement membrane attachment, cytoskeletal mechanical properties). Particles may be given the capacity to change their properties and behaviours in response to changes in the cellular microenvironment (e.g., in response to cell-cell signalling or mechanical loadings). Each particle is in effect an ‘agent’, meaning that the agent can sense local environmental information and respond according to pre-determined or stochastic events. The behaviour of the proposed framework is exemplified through several biological problems of ongoing interest. These examples illustrate how the modelling framework allows enormous flexibility for representing the mechanical behaviour of different tissues, and we argue this is a more intuitive approach than perhaps offered by traditional continuum methods. Because of this flexibility, we believe the discrete modelling framework provides an avenue for biologists and bioengineers to explore the behaviour of tissue systems in a computational laboratory. PMID:26452000

User modeling for distributed virtual environment intelligent agents

NASA Astrophysics Data System (ADS)

Banks, Sheila B.; Stytz, Martin R.

1999-07-01

This paper emphasizes the requirement for user modeling by presenting the necessary information to motivate the need for and use of user modeling for intelligent agent development. The paper will present information on our current intelligent agent development program, the Symbiotic Information Reasoning and Decision Support (SIRDS) project. We then discuss the areas of intelligent agents and user modeling, which form the foundation of the SIRDS project. Included in the discussion of user modeling are its major components, which are cognitive modeling and behavioral modeling. We next motivate the need for and user of a methodology to develop user models to encompass work within cognitive task analysis. We close the paper by drawing conclusions from our current intelligent agent research project and discuss avenues of future research in the utilization of user modeling for the development of intelligent agents for virtual environments.

Discovery of potent NEK2 inhibitors as potential anticancer agents using structure-based exploration of NEK2 pharmacophoric space coupled with QSAR analyses.

PubMed

Khanfar, Mohammad A; Banat, Fahmy; Alabed, Shada; Alqtaishat, Saja

2017-02-01

High expression of Nek2 has been detected in several types of cancer and it represents a novel target for human cancer. In the current study, structure-based pharmacophore modeling combined with multiple linear regression (MLR)-based QSAR analyses was applied to disclose the structural requirements for NEK2 inhibition. Generated pharmacophoric models were initially validated with receiver operating characteristic (ROC) curve, and optimum models were subsequently implemented in QSAR modeling with other physiochemical descriptors. QSAR-selected models were implied as 3D search filters to mine the National Cancer Institute (NCI) database for novel NEK2 inhibitors, whereas the associated QSAR model prioritized the bioactivities of captured hits for in vitro evaluation. Experimental validation identified several potent NEK2 inhibitors of novel structural scaffolds. The most potent captured hit exhibited an [Formula: see text] value of 237 nM.

Economic dynamics with financial fragility and mean-field interaction: A model

NASA Astrophysics Data System (ADS)

Di Guilmi, C.; Gallegati, M.; Landini, S.

2008-06-01

Following Aoki’s statistical mechanics methodology [Masanao Aoki, New Approaches to Macroeconomic Modeling, Cambridge University Press, 1996; Masanao Aoki, Modeling Aggregate Behaviour and Fluctuations in Economics, Cambridge University Press, 2002; Masanao Aoki, and Hiroshi Yoshikawa, Reconstructing Macroeconomics, Cambridge University Press, 2006], we provide some insights into the well-known works of [Bruce Greenwald, Joseph Stiglitz, Macroeconomic models with equity and credit rationing, in: R. Hubbard (Ed.), Information, Capital Markets and Investment, Chicago University Press, Chicago, 1990; Bruce Greenwald, Joseph Stiglitz, Financial markets imperfections and business cycles, Quarterly journal of Economics (1993)]. Specifically, we reach analytically a closed form solution of their models overcoming the aggregation problem. The key idea is to represent the economy as an evolving complex system, composed by heterogeneous interacting agents, that can be partitioned into a space of macroscopic states. This meso level of aggregation permits to adopt mean-field interaction modeling and master equation techniques.

A proposed-standard format to represent and distribute tomographic models and other earth spatial data

NASA Astrophysics Data System (ADS)

Postpischl, L.; Morelli, A.; Danecek, P.

2009-04-01

Formats used to represent (and distribute) tomographic earth models differ considerably and are rarely self-consistent. In fact, each earth scientist, or research group, uses specific conventions to encode the various parameterizations used to describe, e.g., seismic wave speed or density in three dimensions, and complete information is often found in related documents or publications (if available at all) only. As a consequence, use of various tomographic models from different authors requires considerable effort, is more cumbersome than it should be and prevents widespread exchange and circulation within the community. We propose a format, based on modern web standards, able to represent different (grid-based) model parameterizations within the same simple text-based environment, easy to write, to parse, and to visualise. The aim is the creation of self-describing data-structures, both human and machine readable, that are automatically recognised by general-purpose software agents, and easily imported in the scientific programming environment. We think that the adoption of such a representation as a standard for the exchange and distribution of earth models can greatly ease their usage and enhance their circulation, both among fellow seismologists and among a broader non-specialist community. The proposed solution uses semantic web technologies, fully fitting the current trends in data accessibility. It is based on Json (JavaScript Object Notation), a plain-text, human-readable lightweight computer data interchange format, which adopts a hierarchical name-value model for representing simple data structures and associative arrays (called objects). Our implementation allows integration of large datasets with metadata (authors, affiliations, bibliographic references, units of measure etc.) into a single resource. It is equally suited to represent other geo-referenced volumetric quantities — beyond tomographic models — as well as (structured and unstructured) computational meshes. This approach can exploit the capabilities of the web browser as a computing platform: a series of in-page quick tools for comparative analysis between models will be presented, as well as visualisation techniques for tomographic layers in Google Maps and Google Earth. We are working on tools for conversion into common scientific format like netCDF, to allow easy visualisation in GEON-IDV or gmt.

Multiplexed evaluation of capture agent binding kinetics using arrays of silicon photonic microring resonators.

PubMed

Byeon, Ji-Yeon; Bailey, Ryan C

2011-09-07

High affinity capture agents recognizing biomolecular targets are essential in the performance of many proteomic detection methods. Herein, we report the application of a label-free silicon photonic biomolecular analysis platform for simultaneously determining kinetic association and dissociation constants for two representative protein capture agents: a thrombin-binding DNA aptamer and an anti-thrombin monoclonal antibody. The scalability and inherent multiplexing capability of the technology make it an attractive platform for simultaneously evaluating the binding characteristics of multiple capture agents recognizing the same target antigen, and thus a tool complementary to emerging high-throughput capture agent generation strategies.

Social Network Analysis and Nutritional Behavior: An Integrated Modeling Approach

PubMed Central

Senior, Alistair M.; Lihoreau, Mathieu; Buhl, Jerome; Raubenheimer, David; Simpson, Stephen J.

2016-01-01

Animals have evolved complex foraging strategies to obtain a nutritionally balanced diet and associated fitness benefits. Recent research combining state-space models of nutritional geometry with agent-based models (ABMs), show how nutrient targeted foraging behavior can also influence animal social interactions, ultimately affecting collective dynamics and group structures. Here we demonstrate how social network analyses can be integrated into such a modeling framework and provide a practical analytical tool to compare experimental results with theory. We illustrate our approach by examining the case of nutritionally mediated dominance hierarchies. First we show how nutritionally explicit ABMs that simulate the emergence of dominance hierarchies can be used to generate social networks. Importantly the structural properties of our simulated networks bear similarities to dominance networks of real animals (where conflicts are not always directly related to nutrition). Finally, we demonstrate how metrics from social network analyses can be used to predict the fitness of agents in these simulated competitive environments. Our results highlight the potential importance of nutritional mechanisms in shaping dominance interactions in a wide range of social and ecological contexts. Nutrition likely influences social interactions in many species, and yet a theoretical framework for exploring these effects is currently lacking. Combining social network analyses with computational models from nutritional ecology may bridge this divide, representing a pragmatic approach for generating theoretical predictions for nutritional experiments. PMID:26858671

Modelling large scale human activity in San Francisco

NASA Astrophysics Data System (ADS)

Gonzalez, Marta

2010-03-01

Diverse group of people with a wide variety of schedules, activities and travel needs compose our cities nowadays. This represents a big challenge for modeling travel behaviors in urban environments; those models are of crucial interest for a wide variety of applications such as traffic forecasting, spreading of viruses, or measuring human exposure to air pollutants. The traditional means to obtain knowledge about travel behavior is limited to surveys on travel journeys. The obtained information is based in questionnaires that are usually costly to implement and with intrinsic limitations to cover large number of individuals and some problems of reliability. Using mobile phone data, we explore the basic characteristics of a model of human travel: The distribution of agents is proportional to the population density of a given region, and each agent has a characteristic trajectory size contain information on frequency of visits to different locations. Additionally we use a complementary data set given by smart subway fare cards offering us information about the exact time of each passenger getting in or getting out of the subway station and the coordinates of it. This allows us to uncover the temporal aspects of the mobility. Since we have the actual time and place of individual's origin and destination we can understand the temporal patterns in each visited location with further details. Integrating two described data set we provide a dynamical model of human travels that incorporates different aspects observed empirically.

On the Morphology of a Growing City: A Heuristic Experiment Merging Static Economics with Dynamic Geography.

PubMed

Delloye, Justin; Peeters, Dominique; Thomas, Isabelle

2015-01-01

In this paper, we aim at exploring how individual location decisions affect the shape of a growing city and, more precisely, how they may add up to a configuration that diverges from equilibrium configurations formulated ex-ante. To do so, we provide a two-sector city model merging a static equilibrium analysis with agent-based simulations. Results show that under strong agglomeration effects, urban development is monotonic and ends up with circular, monocentric long-term configurations. For low agglomeration effects however, elongated and multicentric urban configurations may emerge. The occurrence and underlying dynamics of these configurations are also discussed regarding commuting costs and the distance-decay of agglomeration economies between firms. To sum up, our paper warns urban planning policy makers against the difference that may stand between appropriate long-term perspectives, represented here by analytic equilibrium configurations, and short-term urban configurations, simulated here by a multi-agent system.

Nucleic acid-binding polymers as anti-inflammatory agents

PubMed Central

Lee, Jaewoo; Sohn, Jang Wook; Zhang, Ying; Leong, Kam W.; Pisetsky, David; Sullenger, Bruce A.

2011-01-01

Dead and dying cells release nucleic acids. These extracellular RNAs and DNAs can be taken up by inflammatory cells and activate multiple nucleic acid-sensing toll-like receptors (TLR3, 7, 8, and 9). The inappropriate activation of these TLRs can engender a variety of inflammatory and autoimmune diseases. The redundancy of the TLR family encouraged us to seek materials that can neutralize the proinflammatory effects of any nucleic acid regardless of its sequence, structure or chemistry. Herein we demonstrate that certain nucleic acid-binding polymers can inhibit activation of all nucleic acid-sensing TLRs irrespective of whether they recognize ssRNA, dsRNA or hypomethylated DNA. Furthermore, systemic administration of such polymers can prevent fatal liver injury engendered by proinflammatory nucleic acids in an acute toxic shock model in mice. Therefore these polymers represent a novel class of anti-inflammatory agent that can act as molecular scavengers to neutralize the proinflammatory effects of various nucleic acids. PMID:21844380

Transaction based approach

NASA Astrophysics Data System (ADS)

Hunka, Frantisek; Matula, Jiri

2017-07-01

Transaction based approach is utilized in some methodologies in business process modeling. Essential parts of these transactions are human beings. The notion of agent or actor role is usually used for them. The paper on a particular example describes possibilities of Design Engineering Methodology for Organizations (DEMO) and Resource-Event-Agent (REA) methodology. Whereas the DEMO methodology can be regarded as a generic methodology having its foundation in the theory of Enterprise Ontology the REA methodology is regarded as the domain specific methodology and has its origin in accountancy systems. The results of these approaches is that the DEMO methodology captures everything that happens in the reality with a good empirical evidence whereas the REA methodology captures only changes connected with economic events. Economic events represent either change of the property rights to economic resource or consumption or production of economic resources. This results from the essence of economic events and their connection to economic resources.

Biphasic dose responses in biology, toxicology and medicine: accounting for their generalizability and quantitative features.

PubMed

Calabrese, Edward J

2013-11-01

The most common quantitative feature of the hormetic-biphasic dose response is its modest stimulatory response which at maximum is only 30-60% greater than control values, an observation that is consistently independent of biological model, level of organization (i.e., cell, organ or individual), endpoint measured, chemical/physical agent studied, or mechanism. This quantitative feature suggests an underlying "upstream" mechanism common across biological systems, therefore basic and general. Hormetic dose response relationships represent an estimate of the peak performance of integrative biological processes that are allometrically based. Hormetic responses reflect both direct stimulatory or overcompensation responses to damage induced by relatively low doses of chemical or physical agents. The integration of the hormetic dose response within an allometric framework provides, for the first time, an explanation for both the generality and the quantitative features of the hormetic dose response. Copyright © 2013 Elsevier Ltd. All rights reserved.

Inbound Call Centers and Emotional Dissonance in the Job Demands – Resources Model

PubMed Central

Molino, Monica; Emanuel, Federica; Zito, Margherita; Ghislieri, Chiara; Colombo, Lara; Cortese, Claudio G.

2016-01-01

Background: Emotional labor, defined as the process of regulating feelings and expressions as part of the work role, is a major characteristic in call centers. In particular, interacting with customers, agents are required to show certain emotions that are considered acceptable by the organization, even though these emotions may be different from their true feelings. This kind of experience is defined as emotional dissonance and represents a feature of the job especially for call center inbound activities. Aim: The present study was aimed at investigating whether emotional dissonance mediates the relationship between job demands (workload and customer verbal aggression) and job resources (supervisor support, colleague support, and job autonomy) on the one hand, and, on the other, affective discomfort, using the job demands-resources model as a framework. The study also observed differences between two different types of inbound activities: customer assistance service (CA) and information service. Method: The study involved agents of an Italian Telecommunication Company, 352 of whom worked in the CA and 179 in the information service. The hypothesized model was tested across the two groups through multi-group structural equation modeling. Results: Analyses showed that CA agents experience greater customer verbal aggression and emotional dissonance than information service agents. Results also showed, only for the CA group, a full mediation of emotional dissonance between workload and affective discomfort, and a partial mediation of customer verbal aggression and job autonomy, and affective discomfort. Conclusion: This study’s findings contributed both to the emotional labor literature, investigating the mediational role of emotional dissonance in the job demands-resources model, and to call center literature, considering differences between two specific kinds of inbound activities. Suggestions for organizations and practitioners emerged in order to identify practical implications useful both to support employees in coping with emotional labor and to promote well-being in inbound call centers. In detail, results showed the need to improve training programs in order to enhance employees’ emotion regulation skills, and to introduce human resource practices aimed at clarifying emotional requirements of the job. PMID:27516752

Inbound Call Centers and Emotional Dissonance in the Job Demands - Resources Model.

PubMed

Molino, Monica; Emanuel, Federica; Zito, Margherita; Ghislieri, Chiara; Colombo, Lara; Cortese, Claudio G

2016-01-01

Emotional labor, defined as the process of regulating feelings and expressions as part of the work role, is a major characteristic in call centers. In particular, interacting with customers, agents are required to show certain emotions that are considered acceptable by the organization, even though these emotions may be different from their true feelings. This kind of experience is defined as emotional dissonance and represents a feature of the job especially for call center inbound activities. The present study was aimed at investigating whether emotional dissonance mediates the relationship between job demands (workload and customer verbal aggression) and job resources (supervisor support, colleague support, and job autonomy) on the one hand, and, on the other, affective discomfort, using the job demands-resources model as a framework. The study also observed differences between two different types of inbound activities: customer assistance service (CA) and information service. The study involved agents of an Italian Telecommunication Company, 352 of whom worked in the CA and 179 in the information service. The hypothesized model was tested across the two groups through multi-group structural equation modeling. Analyses showed that CA agents experience greater customer verbal aggression and emotional dissonance than information service agents. RESULTS also showed, only for the CA group, a full mediation of emotional dissonance between workload and affective discomfort, and a partial mediation of customer verbal aggression and job autonomy, and affective discomfort. This study's findings contributed both to the emotional labor literature, investigating the mediational role of emotional dissonance in the job demands-resources model, and to call center literature, considering differences between two specific kinds of inbound activities. Suggestions for organizations and practitioners emerged in order to identify practical implications useful both to support employees in coping with emotional labor and to promote well-being in inbound call centers. In detail, results showed the need to improve training programs in order to enhance employees' emotion regulation skills, and to introduce human resource practices aimed at clarifying emotional requirements of the job.

Convection-enhanced delivery of SN-38-loaded polymeric micelles (NK012) enables consistent distribution of SN-38 and is effective against rodent intracranial brain tumor models.

PubMed

Zhang, Rong; Saito, Ryuta; Mano, Yui; Sumiyoshi, Akira; Kanamori, Masayuki; Sonoda, Yukihiko; Kawashima, Ryuta; Tominaga, Teiji

2016-10-01

Convection-enhanced delivery (CED) of therapeutic agents is a promising local delivery technique that has been extensively studied as a treatment for CNS diseases over the last two decades. One continuing challenge of CED is accurate and consistent delivery of the agents to the target. The present study focused on a new type of therapeutic agent, NK012, a novel SN-38-loaded polymeric micelle. Local delivery profiles of NK012 and SN-38 were studied using rodent brain and intracranial rodent brain tumor models. First, the cytotoxicity of NK012 against glioma cell lines was determined in vitro. Proliferations of glioma cells were significantly reduced after exposure to NK012. Then, the distribution and local toxicity after CED delivery of NK012 and SN-38 were evaluated in vivo. Volume of distribution of NK012 after CED was much larger than that of SN-38. Histological examination revealed minimum brain tissue damage in rat brains after delivery of 40 µg NK012 but severe damage with SN-38 at the same dose. Subsequently, the efficacy of NK012 delivered via CED was tested in 9L and U87MG rodent orthotopic brain tumor models. CED of NK012 displayed excellent efficacy in the 9L and U87MG orthotopic brain tumor models. Furthermore, NK012 and gadolinium diamide were co-delivered via CED to monitor the NK012 distribution using MRI. Volume of NK012 distribution evaluated by histology and MRI showed excellent agreement. CED of NK012 represents an effective treatment option for malignant gliomas. MRI-guided CED of NK012 has potential for clinical application.

Serotonergic involvement in levodopa-induced dyskinesias in Parkinson's disease.

PubMed

Cheshire, Perdita A; Williams, David R

2012-03-01

Levodopa-induced dyskinesias (LID) represent a substantial barrier to effective symptomatic management of Parkinson's disease, but current treatment options for this debilitating side effect are limited, despite an increasing understanding of their pathophysiology from animal models. Increasing evidence suggests that serotonin neurons have a pivotal role in the induction and maintenance of dyskinesias, and provide a promising target for anti-dyskinetic therapies. Here, we review the evidence for serotonergic involvement in dyskinesias from animal and human data, and highlight some of the translational gaps which may explain why the success of serotonin autoreceptor agonists as anti-dyskinetic agents in experimental models has failed to be replicated in clinical trials. Copyright © 2011 Elsevier Ltd. All rights reserved.

Assessment of the impact of climate shifts on malaria transmission in the Sahel.

PubMed

Bomblies, Arne; Eltahir, Elfatih A B

2009-09-01

Climate affects malaria transmission through a complex network of causative pathways. We seek to evaluate the impact of hypothetical climate change scenarios on malaria transmission in the Sahel by using a novel mechanistic, high spatial- and temporal-resolution coupled hydrology and agent-based entomology model. The hydrology model component resolves individual precipitation events and individual breeding pools. The impact of future potential climate shifts on the representative Sahel village of Banizoumbou, Niger, is estimated by forcing the model of Banizoumbou environment with meteorological data from two locations along the north-south climatological gradient observed in the Sahel--both for warmer, drier scenarios from the north and cooler, wetter scenarios from the south. These shifts in climate represent hypothetical but historically realistic climate change scenarios. For Banizoumbou climatic conditions (latitude 13.54 N), a shift toward cooler, wetter conditions may dramatically increase mosquito abundance; however, our modeling results indicate that the increased malaria transmissibility is not simply proportional to the precipitation increase. The cooler, wetter conditions increase the length of the sporogonic cycle, dampening a large vectorial capacity increase otherwise brought about by increased mosquito survival and greater overall abundance. Furthermore, simulations varying rainfall event frequency demonstrate the importance of precipitation patterns, rather than simply average or time-integrated precipitation, as a controlling factor of these dynamics. Modeling results suggest that in addition to changes in temperature and total precipitation, changes in rainfall patterns are very important to predict changes in disease susceptibility resulting from climate shifts. The combined effect of these climate-shift-induced perturbations can be represented with the aid of a detailed mechanistic model.

Developing a Conceptual Architecture for a Generalized Agent-based Modeling Environment (GAME)

DTIC Science & Technology

2008-03-01

4. REPAST (Java, Python , C#, Open Source) ........28 5. MASON: Multi-Agent Modeling Language (Swarm Extension... Python , C#, Open Source) Repast (Recursive Porous Agent Simulation Toolkit) was designed for building agent-based models and simulations in the...Repast makes it easy for inexperienced users to build models by including a built-in simple model and provide interfaces through which menus and Python

Disaggregation and Refinement of System Dynamics Models via Agent-based Modeling

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

Nutaro, James J; Ozmen, Ozgur; Schryver, Jack C

System dynamics models are usually used to investigate aggregate level behavior, but these models can be decomposed into agents that have more realistic individual behaviors. Here we develop a simple model of the STEM workforce to illuminate the impacts that arise from the disaggregation and refinement of system dynamics models via agent-based modeling. Particularly, alteration of Poisson assumptions, adding heterogeneity to decision-making processes of agents, and discrete-time formulation are investigated and their impacts are illustrated. The goal is to demonstrate both the promise and danger of agent-based modeling in the context of a relatively simple model and to delineate themore » importance of modeling decisions that are often overlooked.« less

Agent-Based Modeling of Chronic Diseases: A Narrative Review and Future Research Directions

PubMed Central

Lawley, Mark A.; Siscovick, David S.; Zhang, Donglan; Pagán, José A.

2016-01-01

The United States is experiencing an epidemic of chronic disease. As the US population ages, health care providers and policy makers urgently need decision models that provide systematic, credible prediction regarding the prevention and treatment of chronic diseases to improve population health management and medical decision-making. Agent-based modeling is a promising systems science approach that can model complex interactions and processes related to chronic health conditions, such as adaptive behaviors, feedback loops, and contextual effects. This article introduces agent-based modeling by providing a narrative review of agent-based models of chronic disease and identifying the characteristics of various chronic health conditions that must be taken into account to build effective clinical- and policy-relevant models. We also identify barriers to adopting agent-based models to study chronic diseases. Finally, we discuss future research directions of agent-based modeling applied to problems related to specific chronic health conditions. PMID:27236380

Agent-Based Modeling of Chronic Diseases: A Narrative Review and Future Research Directions.

PubMed

Li, Yan; Lawley, Mark A; Siscovick, David S; Zhang, Donglan; Pagán, José A

2016-05-26

The United States is experiencing an epidemic of chronic disease. As the US population ages, health care providers and policy makers urgently need decision models that provide systematic, credible prediction regarding the prevention and treatment of chronic diseases to improve population health management and medical decision-making. Agent-based modeling is a promising systems science approach that can model complex interactions and processes related to chronic health conditions, such as adaptive behaviors, feedback loops, and contextual effects. This article introduces agent-based modeling by providing a narrative review of agent-based models of chronic disease and identifying the characteristics of various chronic health conditions that must be taken into account to build effective clinical- and policy-relevant models. We also identify barriers to adopting agent-based models to study chronic diseases. Finally, we discuss future research directions of agent-based modeling applied to problems related to specific chronic health conditions.

7 CFR 97.155 - Signatures.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 3 2010-01-01 2010-01-01 false Signatures. 97.155 Section 97.155 Agriculture... PLANT VARIETY AND PROTECTION Attorneys and Agents § 97.155 Signatures. Every document filed by an attorney or agent representing an applicant or party to a proceeding in the Office shall bear the signature...

45 CFR 35.8 - Release.

Code of Federal Regulations, 2010 CFR

2010-10-01

... § 35.8 Release. Acceptance by the claimant, his agent or legal representative, of any award, compromise or settlement made hereunder, shall be final and conclusive on the claimant, his agent or legal... 45 Public Welfare 1 2010-10-01 2010-10-01 false Release. 35.8 Section 35.8 Public Welfare...

Unification of the macro- and microbiome in trophic ecology

USDA-ARS?s Scientific Manuscript database

Biological control is a key part of virtually any IPM program, and microbial bio-control agents represent particularly effective agents because of their capacity to be applied via conventional spray application methods. We are showing that fungi function just as arthropods do in the food web—the fun...

26 CFR 301.9000-6 - Examples.

Code of Federal Regulations, 2012 CFR

2012-04-01

... suit for refund requests testimony from an IRS revenue agent. This is an IRS matter. A testimony... of Justice attorney representing the IRS in a suit for refund asks that the IRS revenue agent be made... refund suit involving Taxpayer A. The testimony may include tax convention information, as defined in...

26 CFR 301.9000-6 - Examples.

Code of Federal Regulations, 2013 CFR

2013-04-01

... suit for refund requests testimony from an IRS revenue agent. This is an IRS matter. A testimony... of Justice attorney representing the IRS in a suit for refund asks that the IRS revenue agent be made... refund suit involving Taxpayer A. The testimony may include tax convention information, as defined in...

26 CFR 301.9000-6 - Examples.

Code of Federal Regulations, 2014 CFR

2014-04-01

... suit for refund requests testimony from an IRS revenue agent. This is an IRS matter. A testimony... of Justice attorney representing the IRS in a suit for refund asks that the IRS revenue agent be made... refund suit involving Taxpayer A. The testimony may include tax convention information, as defined in...

26 CFR 301.9000-6 - Examples.

Code of Federal Regulations, 2011 CFR

2011-04-01

... suit for refund requests testimony from an IRS revenue agent. This is an IRS matter. A testimony... of Justice attorney representing the IRS in a suit for refund asks that the IRS revenue agent be made... refund suit involving Taxpayer A. The testimony may include tax convention information, as defined in...