Evaluating Water Demand Using Agent-Based Modeling

Science.gov (United States)

Lowry, T. S.

2004-12-01

The supply and demand of water resources are functions of complex, inter-related systems including hydrology, climate, demographics, economics, and policy. To assess the safety and sustainability of water resources, planners often rely on complex numerical models that relate some or all of these systems using mathematical abstractions. The accuracy of these models relies on how well the abstractions capture the true nature of the systems interactions. Typically, these abstractions are based on analyses of observations and/or experiments that account only for the statistical mean behavior of each system. This limits the approach in two important ways: 1) It cannot capture cross-system disruptive events, such as major drought, significant policy change, or terrorist attack, and 2) it cannot resolve sub-system level responses. To overcome these limitations, we are developing an agent-based water resources model that includes the systems of hydrology, climate, demographics, economics, and policy, to examine water demand during normal and extraordinary conditions. Agent-based modeling (ABM) develops functional relationships between systems by modeling the interaction between individuals (agents), who behave according to a probabilistic set of rules. ABM is a "bottom-up" modeling approach in that it defines macro-system behavior by modeling the micro-behavior of individual agents. While each agent's behavior is often simple and predictable, the aggregate behavior of all agents in each system can be complex, unpredictable, and different than behaviors observed in mean-behavior models. Furthermore, the ABM approach creates a virtual laboratory where the effects of policy changes and/or extraordinary events can be simulated. Our model, which is based on the demographics and hydrology of the Middle Rio Grande Basin in the state of New Mexico, includes agent groups of residential, agricultural, and industrial users. Each agent within each group determines its water usage

A technology path to tactical agent-based modeling

Science.gov (United States)

James, Alex; Hanratty, Timothy P.

2017-05-01

Wargaming is a process of thinking through and visualizing events that could occur during a possible course of action. Over the past 200 years, wargaming has matured into a set of formalized processes. One area of growing interest is the application of agent-based modeling. Agent-based modeling and its additional supporting technologies has potential to introduce a third-generation wargaming capability to the Army, creating a positive overmatch decision-making capability. In its simplest form, agent-based modeling is a computational technique that helps the modeler understand and simulate how the "whole of a system" responds to change over time. It provides a decentralized method of looking at situations where individual agents are instantiated within an environment, interact with each other, and empowered to make their own decisions. However, this technology is not without its own risks and limitations. This paper explores a technology roadmap, identifying research topics that could realize agent-based modeling within a tactical wargaming context.

Evaluation of radiolabeled ruthenium compounds as tumor-localizing agents

International Nuclear Information System (INIS)

Srivastava, S.C.; Richards, P.; Meinken, G.E.; Som, P.; Atkins, H.L.; Larson, S.M.; Grunbaum, Z.; Rasey, J.S.; Clarke, M.H.; Dowling, M.

1979-01-01

This work introduces a new class of radiopharmaceuticals based on ruthenium-97. The excellent physical properties of Ru-97, the high chemical reactivity of Ru, the potential antitumor activity of several Ru coordination compounds, and BLIP production of Ru-97, provide a unique combination for the application of this isotope in nuclear oncology. A systematic study was undertaken on the synthesis, characterization, and evaluation of a number of ruthenium-labeled compounds. In a variety of animal tumor models, several compounds show considerable promise as tumor-localizing agents when compared to gallium-67 citrate. The compounds studied (with Ru in different oxidation states) include ionic Ru, a number of hydrophilic and lipophilic chelates, and various ammine derivatives

Agent-Based Models in Social Physics

Science.gov (United States)

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.

New approaches in agent-based modeling of complex financial systems

Science.gov (United States)

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.

Empirical agent-based modelling challenges and solutions

CERN Document Server

Barreteau, Olivier

2014-01-01

This instructional book showcases techniques to parameterise human agents in empirical agent-based models (ABM). In doing so, it provides a timely overview of key ABM methodologies and the most innovative approaches through a variety of empirical applications.  It features cutting-edge research from leading academics and practitioners, and will provide a guide for characterising and parameterising human agents in empirical ABM.  In order to facilitate learning, this text shares the valuable experiences of other modellers in particular modelling situations. Very little has been published in the area of empirical ABM, and this contributed volume will appeal to graduate-level students and researchers studying simulation modeling in economics, sociology, ecology, and trans-disciplinary studies, such as topics related to sustainability. In a similar vein to the instruction found in a cookbook, this text provides the empirical modeller with a set of 'recipes'  ready to be implemented. Agent-based modeling (AB...

Skull base tumor model.

Science.gov (United States)

Gragnaniello, Cristian; Nader, Remi; van Doormaal, Tristan; Kamel, Mahmoud; Voormolen, Eduard H J; Lasio, Giovanni; Aboud, Emad; Regli, Luca; Tulleken, Cornelius A F; Al-Mefty, Ossama

2010-11-01

Resident duty-hours restrictions have now been instituted in many countries worldwide. Shortened training times and increased public scrutiny of surgical competency have led to a move away from the traditional apprenticeship model of training. The development of educational models for brain anatomy is a fascinating innovation allowing neurosurgeons to train without the need to practice on real patients and it may be a solution to achieve competency within a shortened training period. The authors describe the use of Stratathane resin ST-504 polymer (SRSP), which is inserted at different intracranial locations to closely mimic meningiomas and other pathological entities of the skull base, in a cadaveric model, for use in neurosurgical training. Silicone-injected and pressurized cadaveric heads were used for studying the SRSP model. The SRSP presents unique intrinsic metamorphic characteristics: liquid at first, it expands and foams when injected into the desired area of the brain, forming a solid tumorlike structure. The authors injected SRSP via different passages that did not influence routes used for the surgical approach for resection of the simulated lesion. For example, SRSP injection routes included endonasal transsphenoidal or transoral approaches if lesions were to be removed through standard skull base approach, or, alternatively, SRSP was injected via a cranial approach if the removal was planned to be via the transsphenoidal or transoral route. The model was set in place in 3 countries (US, Italy, and The Netherlands), and a pool of 13 physicians from 4 different institutions (all surgeons and surgeons in training) participated in evaluating it and provided feedback. All 13 evaluating physicians had overall positive impressions of the model. The overall score on 9 components evaluated--including comparison between the tumor model and real tumor cases, perioperative requirements, general impression, and applicability--was 88% (100% being the best possible

Agent-based models in economics a toolkit

CERN Document Server

Fagiolo, Giorgio; Gallegati, Mauro; Richiardi, Matteo; Russo, Alberto

2018-01-01

In contrast to mainstream economics, complexity theory conceives the economy as a complex system of heterogeneous interacting agents characterised by limited information and bounded rationality. Agent Based Models (ABMs) are the analytical and computational tools developed by the proponents of this emerging methodology. Aimed at students and scholars of contemporary economics, this book includes a comprehensive toolkit for agent-based computational economics, now quickly becoming the new way to study evolving economic systems. Leading scholars in the field explain how ABMs can be applied fruitfully to many real-world economic examples and represent a great advancement over mainstream approaches. The essays discuss the methodological bases of agent-based approaches and demonstrate step-by-step how to build, simulate and analyse ABMs and how to validate their outputs empirically using the data. They also present a wide set of applications of these models to key economic topics, including the business cycle, lab...

Comparison of two brain tumor-localizing MRI agent. GD-BOPTA and GD-DTPA. MRI and ICP study of rat brain tumor model

International Nuclear Information System (INIS)

Zhang, T.; Matsumura, A.; Yamamoto, T.; Yoshida, F.; Nose, T.

2000-01-01

In this study, we compared the behavior of Gd-BOPTA as a brain tumor selective contrast agent with Gd-DTPA in a common dose of 0.1 mmol/kg. We performed a MRI study using those two agent as contrast material, and we measured tissue Gd-concentrations by ICP-AES. As a result, Gd-BOPTA showed a better MRI enhancement in brain tumor. ICP showed significantly greater uptake of Gd-BOPTA in tumor samples, at all time course peaked at 5 minutes after administration, Gd being retained for a longer time in brain tumor till 2 hours, without rapid elimination as Gd-DTPA. We conclude that Gd-BOPTA is a new useful contrast material for MR imaging in brain tumor and an effective absorption agent for neutron capture therapy for further research. (author)

Agent-based modeling and simulation Part 3 : desktop ABMS.

Energy Technology Data Exchange (ETDEWEB)

Macal, C. M.; North, M. J.; Decision and Information Sciences

2007-01-01

Agent-based modeling and simulation (ABMS) is a new approach to modeling systems comprised of autonomous, interacting agents. ABMS promises to have far-reaching effects on the way that businesses use computers to support decision-making and researchers use electronic laboratories to support their research. Some have gone so far as to contend that ABMS 'is a third way of doing science,' in addition to traditional deductive and inductive reasoning (Axelrod 1997b). Computational advances have made possible a growing number of agent-based models across a variety of application domains. Applications range from modeling agent behavior in the stock market, supply chains, and consumer markets, to predicting the spread of epidemics, the threat of bio-warfare, and the factors responsible for the fall of ancient civilizations. This tutorial describes the theoretical and practical foundations of ABMS, identifies toolkits and methods for developing agent models, and illustrates the development of a simple agent-based model of shopper behavior using spreadsheets.

Dissemination of Cultural Norms and Values: Agent-Based Modeling

Directory of Open Access Journals (Sweden)

Denis Andreevich Degterev

2016-12-01

Full Text Available This article shows how agent-based modeling allows us to explore the mechanisms of the dissemination of cultural norms and values both within one country and in the whole world. In recent years, this type of simulation is particularly prevalent in the analysis of international relations, becoming more popular than the system dynamics and discrete event simulation. The use of agent-based modeling in the analysis of international relations is connected with the agent-structure problem in international relations. Structure and agents act as interdependent and dynamically changing in the process of interaction between entities. Agent-structure interaction could be modeled by means of the theory of complex adaptive systems with the use of agent-based modeling techniques. One of the first examples of the use of agent-based modeling in political science is a model of racial segregation T. Shellinga. On the basis of this model, the author shows how the change in behavioral patterns at micro-level impacts on the macro-level. Patterns are changing due to the dynamics of cultural norms and values, formed by mass-media and other social institutes. The author shows the main areas of modern application of agent-based modeling in international studies including the analysis of ethnic conflicts, the formation of international coalitions. Particular attention is paid to Robert Axelrod approach based on the use of genetic algorithms to the spread of cultural norms and values. Agent-based modeling shows how to how to create such conditions that the norms that originally are not shared by a significant part of the population, eventually spread everywhere. Practical application of these algorithms is shown by the author of the article on the example of the situation in Ukraine in 2015-2016. The article also reveals the mechanisms of international spread of cultural norms and values. The main think-tanks using agent-based modeling in international studies are

An Active Learning Exercise for Introducing Agent-Based Modeling

Science.gov (United States)

Pinder, Jonathan P.

2013-01-01

Recent developments in agent-based modeling as a method of systems analysis and optimization indicate that students in business analytics need an introduction to the terminology, concepts, and framework of agent-based modeling. This article presents an active learning exercise for MBA students in business analytics that demonstrates agent-based…

A novel Tc-99m and fluorescence-labeled arginine-arginine-leucine-containing peptide as a multimodal tumor imaging agent in a murine tumor model.

Science.gov (United States)

Kim, Myoung Hyoun; Kim, Seul-Gi; Kim, Dae-Weung

2018-06-15

We developed a Tc-99m and TAMRA-labeled peptide, Tc-99m arginine-arginine-leucine (RRL) peptide (TAMRA-GHEG-ECG-RRL), to target tumor cells and evaluated the diagnostic performance of Tc-99m TAMRA-GHEG-ECG-RRL as a dual-modality imaging agent for tumor in a murine model. TAMRA-GHEG-ECG-RRL was synthesized using Fmoc solid-phase peptide synthesis. Binding affinity and in vitro cellular uptake studies were performed. Gamma camera imaging, biodistribution, and ex vivo imaging studies were performed in murine models with PC-3 tumors. Tumor tissue slides were prepared and analyzed with immunohistochemistry using confocal microscopy. After radiolabeling procedures with Tc-99m, Tc-99m TAMRA-GHEG-ECG-RRL complexes were prepared in high yield (>96%). The K d of Tc-99m TAMRA-GHEG-ECG-RRL determined by saturation binding was 41.7 ± 7.8 nM. Confocal microscopy images of PC-3 cells incubated with TAMRA-GHEG-ECG-RRL showed strong fluorescence in the cytoplasm. Gamma camera imaging revealed substantial uptake of Tc-99m TAMRA-GHEG-ECG-RRL in tumors. Tumor uptake was effectively blocked by the coinjection of an excess concentration of RRL. Specific uptake of Tc-99m TAMRA-GHEG-ECG-RRL was confirmed by biodistribution, ex vivo imaging, and immunohistochemistry stain studies. In conclusion, in vivo and in vitro studies revealed substantial uptake of Tc-99m TAMRA-GHEG-ECG-RRL in tumors. Tc-99m TAMRA-GHEG-ECG-RRL has potential as a dual-modality tumor imaging agent. Copyright © 2018 John Wiley & Sons, Ltd.

Modeling and simulation of complex systems a framework for efficient agent-based modeling and simulation

CERN Document Server

Siegfried, Robert

2014-01-01

Robert Siegfried presents a framework for efficient agent-based modeling and simulation of complex systems. He compares different approaches for describing structure and dynamics of agent-based models in detail. Based on this evaluation the author introduces the "General Reference Model for Agent-based Modeling and Simulation" (GRAMS). Furthermore he presents parallel and distributed simulation approaches for execution of agent-based models -from small scale to very large scale. The author shows how agent-based models may be executed by different simulation engines that utilize underlying hard

Markov chain aggregation for agent-based models

CERN Document Server

Banisch, Sven

2016-01-01

This self-contained text develops a Markov chain approach that makes the rigorous analysis of a class of microscopic models that specify the dynamics of complex systems at the individual level possible. It presents a general framework of aggregation in agent-based and related computational models, one which makes use of lumpability and information theory in order to link the micro and macro levels of observation. The starting point is a microscopic Markov chain description of the dynamical process in complete correspondence with the dynamical behavior of the agent-based model (ABM), which is obtained by considering the set of all possible agent configurations as the state space of a huge Markov chain. An explicit formal representation of a resulting “micro-chain” including microscopic transition rates is derived for a class of models by using the random mapping representation of a Markov process. The type of probability distribution used to implement the stochastic part of the model, which defines the upd...

Selected Alkylating Agents Can Overcome Drug Tolerance of G0-like Tumor Cells and Eradicate BRCA1-Deficient Mammary Tumors in Mice.

Science.gov (United States)

Pajic, Marina; Blatter, Sohvi; Guyader, Charlotte; Gonggrijp, Maaike; Kersbergen, Ariena; Küçükosmanoğlu, Aslι; Sol, Wendy; Drost, Rinske; Jonkers, Jos; Borst, Piet; Rottenberg, Sven

2017-11-15

Purpose: We aimed to characterize and target drug-tolerant BRCA1-deficient tumor cells that cause residual disease and subsequent tumor relapse. Experimental Design: We studied responses to various mono- and bifunctional alkylating agents in a genetically engineered mouse model for BRCA1/p53 -mutant breast cancer. Because of the large intragenic deletion of the Brca1 gene, no restoration of BRCA1 function is possible, and therefore, no BRCA1-dependent acquired resistance occurs. To characterize the cell-cycle stage from which Brca1 -/- ;p53 -/- mammary tumors arise after cisplatin treatment, we introduced the fluorescent ubiquitination-based cell-cycle indicator (FUCCI) construct into the tumor cells. Results: Despite repeated sensitivity to the MTD of platinum drugs, the Brca1 -mutated mammary tumors are not eradicated, not even by a frequent dosing schedule. We show that relapse comes from single-nucleated cells delaying entry into the S-phase. Such slowly cycling cells, which are present within the drug-naïve tumors, are enriched in tumor remnants. Using the FUCCI construct, we identified nonfluorescent G 0 -like cells as the population most tolerant to platinum drugs. Intriguingly, these cells are more sensitive to the DNA-crosslinking agent nimustine, resulting in an increased number of multinucleated cells that lack clonogenicity. This is consistent with our in vivo finding that the nimustine MTD, among several alkylating agents, is the most effective in eradicating Brca1 -mutated mouse mammary tumors. Conclusions: Our data show that targeting G 0 -like cells is crucial for the eradication of BRCA1/p53-deficient tumor cells. This can be achieved with selected alkylating agents such as nimustine. Clin Cancer Res; 23(22); 7020-33. ©2017 AACR . ©2017 American Association for Cancer Research.

The fractional volatility model: An agent-based interpretation

Science.gov (United States)

Vilela Mendes, R.

2008-06-01

Based on the criteria of mathematical simplicity and consistency with empirical market data, a model with volatility driven by fractional noise has been constructed which provides a fairly accurate mathematical parametrization of the data. Here, some features of the model are reviewed and extended to account for leverage effects. Using agent-based models, one tries to find which agent strategies and (or) properties of the financial institutions might be responsible for the features of the fractional volatility model.

A role based coordination model in agent systems

Institute of Scientific and Technical Information of China (English)

ZHANG Ya-ying; YOU Jin-yuan

2005-01-01

Coordination technology addresses the construction of open, flexible systems from active and independent software agents in concurrent and distributed systems. In most open distributed applications, multiple agents need interaction and communication to achieve their overall goal. Coordination technologies for the Internet typically are concerned with enabling interaction among agents and helping them cooperate with each other.At the same time, access control should also be considered to constrain interaction to make it harmless. Access control should be regarded as the security counterpart of coordination. At present, the combination of coordination and access control remains an open problem. Thus, we propose a role based coordination model with policy enforcement in agent application systems. In this model, coordination is combined with access control so as to fully characterize the interactions in agent systems. A set of agents interacting with each other for a common global system task constitutes a coordination group. Role based access control is applied in this model to prevent unauthorized accesses. Coordination policy is enforced in a distributed manner so that the model can be applied to the open distributed systems such as Intemet. An Internet online auction system is presented as a case study to illustrate the proposed coordination model and finally the performance analysis of the model is introduced.

Consentaneous agent-based and stochastic model of the financial markets.

Science.gov (United States)

Gontis, Vygintas; Kononovicius, Aleksejus

2014-01-01

We are looking for the agent-based treatment of the financial markets considering necessity to build bridges between microscopic, agent based, and macroscopic, phenomenological modeling. The acknowledgment that agent-based modeling framework, which may provide qualitative and quantitative understanding of the financial markets, is very ambiguous emphasizes the exceptional value of well defined analytically tractable agent systems. Herding as one of the behavior peculiarities considered in the behavioral finance is the main property of the agent interactions we deal with in this contribution. Looking for the consentaneous agent-based and macroscopic approach we combine two origins of the noise: exogenous one, related to the information flow, and endogenous one, arising form the complex stochastic dynamics of agents. As a result we propose a three state agent-based herding model of the financial markets. From this agent-based model we derive a set of stochastic differential equations, which describes underlying macroscopic dynamics of agent population and log price in the financial markets. The obtained solution is then subjected to the exogenous noise, which shapes instantaneous return fluctuations. We test both Gaussian and q-Gaussian noise as a source of the short term fluctuations. The resulting model of the return in the financial markets with the same set of parameters reproduces empirical probability and spectral densities of absolute return observed in New York, Warsaw and NASDAQ OMX Vilnius Stock Exchanges. Our result confirms the prevalent idea in behavioral finance that herding interactions may be dominant over agent rationality and contribute towards bubble formation.

Agent-based models for higher-order theory of mind

NARCIS (Netherlands)

de Weerd, Harmen; Verbrugge, Rineke; Verheij, Bart; Kamiński, Bogumił; Koloch, Grzegorz

2014-01-01

Agent-based models are a powerful tool for explaining the emergence of social phenomena in a society. In such models, individual agents typically have little cognitive ability. In this paper, we model agents with the cognitive ability to make use of theory of mind. People use this ability to reason

A Coupled Simulation Architecture for Agent-Based/Geohydrological Modelling

Science.gov (United States)

Jaxa-Rozen, M.

2016-12-01

The quantitative modelling of social-ecological systems can provide useful insights into the interplay between social and environmental processes, and their impact on emergent system dynamics. However, such models should acknowledge the complexity and uncertainty of both of the underlying subsystems. For instance, the agent-based models which are increasingly popular for groundwater management studies can be made more useful by directly accounting for the hydrological processes which drive environmental outcomes. Conversely, conventional environmental models can benefit from an agent-based depiction of the feedbacks and heuristics which influence the decisions of groundwater users. From this perspective, this work describes a Python-based software architecture which couples the popular NetLogo agent-based platform with the MODFLOW/SEAWAT geohydrological modelling environment. This approach enables users to implement agent-based models in NetLogo's user-friendly platform, while benefiting from the full capabilities of MODFLOW/SEAWAT packages or reusing existing geohydrological models. The software architecture is based on the pyNetLogo connector, which provides an interface between the NetLogo agent-based modelling software and the Python programming language. This functionality is then extended and combined with Python's object-oriented features, to design a simulation architecture which couples NetLogo with MODFLOW/SEAWAT through the FloPy library (Bakker et al., 2016). The Python programming language also provides access to a range of external packages which can be used for testing and analysing the coupled models, which is illustrated for an application of Aquifer Thermal Energy Storage (ATES).

Agent-based modelling of cholera diffusion

NARCIS (Netherlands)

Augustijn-Beckers, Petronella; Doldersum, Tom; Useya, Juliana; Augustijn, Dionysius C.M.

2016-01-01

This paper introduces a spatially explicit agent-based simulation model for micro-scale cholera diffusion. The model simulates both an environmental reservoir of naturally occurring V.cholerae bacteria and hyperinfectious V. cholerae. Objective of the research is to test if runoff from open refuse

Valine-based biphenylsulphonamide matrix metalloproteinase inhibitors as tumor imaging agents

Energy Technology Data Exchange (ETDEWEB)

Oltenfreiter, Ruth [Faculty of Pharmaceutical Sciences, Department of Radiopharmacy, Ghent University, Harelbekestraat 72, 9000 Ghent (Belgium)]. E-mail: ruth.oltenfreiter@ugent.be; Staelens, Ludovicus [Faculty of Pharmaceutical Sciences, Department of Radiopharmacy, Ghent University, Harelbekestraat 72, 9000 Ghent (Belgium); Kersemans, Veerle [Faculty of Pharmaceutical Sciences, Department of Radiopharmacy, Ghent University, Harelbekestraat 72, 9000 Ghent (Belgium); Cornelissen, Bart [Faculty of Pharmaceutical Sciences, Department of Radiopharmacy, Ghent University, Harelbekestraat 72, 9000 Ghent (Belgium); Frankenne, Francis [Laboratory of Tumor and Developmental Biology, University of Liege, Sart-Tilman, Liege (Belgium); Foidart, Jean-Michel [Laboratory of Tumor and Developmental Biology, University of Liege, Sart-Tilman, Liege (Belgium); Wiele, Christophe van de [Division of Nuclear Medicine, Gent University Hospital, De Pintelaan 185, 9000 Gent (Belgium); Slegers, Guido [Faculty of Pharmaceutical Sciences, Department of Radiopharmacy, Ghent University, Harelbekestraat 72, 9000 Ghent (Belgium)

2006-06-15

Among matrix metalloproteinases (MMPs), the subfamily of gelatinases (MMP-2, MMP-9) is of particular interest due to their ability to degrade type IV collagen and other non-fibrillar collagen domains and proteins such as fibronectin and laminin. Whilst malignant cells often over-express various MMPs, the gelatinases have been most consistently detected in malignant tissues and associated with tumor growth, metastatic potential and angiogenesis. Radiosynthesis of carboxylic (1') and hydroxamic (2') MMPIs resulted in radiochemical yields of 70+/-5% (n=6) and 60+/-5% (n=4), respectively. Evaluation in A549-inoculated athymic mice showed a tumor uptake of 2.0+/-0.7%ID/g (3h p.i.), a tumor/blood ratio of 0.5 and a tumor/muscle ratio of 4.6 at 48hp.i. for 1'. For compound 2' a tumor uptake of 0.7+/-0.2%ID/g (3hp.i.), a tumor/blood ratio of 1.2 and a tumor/muscle ratio of 1.8 at 24hp.i. were observed. HPLC analysis of the blood (plasma) showed no dehalogenation or other metabolites of 1' 2hp.i. For compound 2', 65.4% of intact compound was found in the blood (plasma) and one polar metabolite (31%) was detected whereas in the tumor 91.8% of the accumulated activity was caused by intact compound and only 8.1% by the metabolite. Planar imaging, using a Toshiba GCA-9300A/hg SPECT camera, showed that tumor tissue could be visualized and that image quality improved by decreasing specific activity resulting in lower liver uptake, indicating some degree of saturable binding in the liver. In vivo evaluation of these radioiodinated carboxylic and hydroxamic MMP inhibitor tracers revealed that MMP inhibitors could have potential as tumor imaging agents, but that further research is necessary.

Valine-based biphenylsulphonamide matrix metalloproteinase inhibitors as tumor imaging agents

International Nuclear Information System (INIS)

Oltenfreiter, Ruth; Staelens, Ludovicus; Kersemans, Veerle; Cornelissen, Bart; Frankenne, Francis; Foidart, Jean-Michel; Wiele, Christophe van de; Slegers, Guido

2006-01-01

Among matrix metalloproteinases (MMPs), the subfamily of gelatinases (MMP-2, MMP-9) is of particular interest due to their ability to degrade type IV collagen and other non-fibrillar collagen domains and proteins such as fibronectin and laminin. Whilst malignant cells often over-express various MMPs, the gelatinases have been most consistently detected in malignant tissues and associated with tumor growth, metastatic potential and angiogenesis. Radiosynthesis of carboxylic (1') and hydroxamic (2') MMPIs resulted in radiochemical yields of 70+/-5% (n=6) and 60+/-5% (n=4), respectively. Evaluation in A549-inoculated athymic mice showed a tumor uptake of 2.0+/-0.7%ID/g (3h p.i.), a tumor/blood ratio of 0.5 and a tumor/muscle ratio of 4.6 at 48hp.i. for 1'. For compound 2' a tumor uptake of 0.7+/-0.2%ID/g (3hp.i.), a tumor/blood ratio of 1.2 and a tumor/muscle ratio of 1.8 at 24hp.i. were observed. HPLC analysis of the blood (plasma) showed no dehalogenation or other metabolites of 1' 2hp.i. For compound 2', 65.4% of intact compound was found in the blood (plasma) and one polar metabolite (31%) was detected whereas in the tumor 91.8% of the accumulated activity was caused by intact compound and only 8.1% by the metabolite. Planar imaging, using a Toshiba GCA-9300A/hg SPECT camera, showed that tumor tissue could be visualized and that image quality improved by decreasing specific activity resulting in lower liver uptake, indicating some degree of saturable binding in the liver. In vivo evaluation of these radioiodinated carboxylic and hydroxamic MMP inhibitor tracers revealed that MMP inhibitors could have potential as tumor imaging agents, but that further research is necessary

Stability of subsystem solutions in agent-based models

Science.gov (United States)

Perc, Matjaž

2018-01-01

The fact that relatively simple entities, such as particles or neurons, or even ants or bees or humans, give rise to fascinatingly complex behaviour when interacting in large numbers is the hallmark of complex systems science. Agent-based models are frequently employed for modelling and obtaining a predictive understanding of complex systems. Since the sheer number of equations that describe the behaviour of an entire agent-based model often makes it impossible to solve such models exactly, Monte Carlo simulation methods must be used for the analysis. However, unlike pairwise interactions among particles that typically govern solid-state physics systems, interactions among agents that describe systems in biology, sociology or the humanities often involve group interactions, and they also involve a larger number of possible states even for the most simplified description of reality. This begets the question: when can we be certain that an observed simulation outcome of an agent-based model is actually stable and valid in the large system-size limit? The latter is key for the correct determination of phase transitions between different stable solutions, and for the understanding of the underlying microscopic processes that led to these phase transitions. We show that a satisfactory answer can only be obtained by means of a complete stability analysis of subsystem solutions. A subsystem solution can be formed by any subset of all possible agent states. The winner between two subsystem solutions can be determined by the average moving direction of the invasion front that separates them, yet it is crucial that the competing subsystem solutions are characterised by a proper composition and spatiotemporal structure before the competition starts. We use the spatial public goods game with diverse tolerance as an example, but the approach has relevance for a wide variety of agent-based models.

Synthesis and Biological Evaluation of Novel Furozan-Based Nitric Oxide-Releasing Derivatives of Oridonin as Potential Anti-Tumor Agents

Directory of Open Access Journals (Sweden)

Hao Cai

2012-06-01

Full Text Available To search for novel nitric oxide (NO releasing anti-tumor agents, a series of novel furoxan/oridonin hybrids were designed and synthesized. Firstly, the nitrate/nitrite levels in the cell lysates were tested by a Griess assay and the results showed that these furoxan-based NO-releasing derivatives could produce high levels of NO in vitro. Then the anti-proliferative activity of these hybrids against four human cancer cell lines was also determined, among which, 9h exhibited the most potential anti-tumor activity with IC₅₀ values of 1.82 µM against K562, 1.81 µM against MGC-803 and 0.86 µM against Bel-7402, respectively. Preliminary structure-activity relationship was concluded based on the experimental data obtained. These results suggested that NO-donor/natural product hybrids may provide a promising approach for the discovery of novel anti-tumor agents.

Tumor vascular-targeted co-delivery of anti-angiogenesis and chemotherapeutic agents by mesoporous silica nanoparticle-based drug delivery system for synergetic therapy of tumor

Directory of Open Access Journals (Sweden)

Li X

2015-12-01

Full Text Available Xiaoyu Li, Meiying Wu, Limin Pan, Jianlin Shi State Key Laboratory of High Performance Ceramics and Superfine Microstructure, Shanghai Institute of Ceramics, Chinese Academy of Sciences, Shanghai, People’s Republic of China Abstract: To overcome the drawback of drug non-selectivity in traditional chemotherapy, the construction of multifunctional targeting drug delivery systems is one of the most effective and prevailing approaches. The intratumoral anti-angiogenesis and the tumor cell-killing are two basic approaches in fighting tumors. Herein we report a novel tumor vascular-targeting multidrug delivery system using mesoporous silica nanoparticles as carrier to co-load an antiangiogenic agent (combretastatin A4 and a chemotherapeutic drug (doxorubicin and conjugate with targeting molecules (iRGD peptide for combined anti-angiogenesis and chemotherapy. Such a dual-loaded drug delivery system is capable of delivering the two agents at tumor vasculature and then within tumors through a differentiated drug release strategy, which consequently results in greatly improved antitumor efficacy at a very low doxorubicin dose of 1.5 mg/kg. The fast release of the antiangiogenic agent at tumor vasculatures led to the disruption of vascular structure and had a synergetic effect with the chemotherapeutic drug slowly released in the following delivery of chemotherapeutic drug into tumors. Keywords: mesoporous silica nanoparticles, drug delivery, tumor vasculatures targeting, antiangiogenic agent

The effect of interstitial pressure on therapeutic agent transport: coupling with the tumor blood and lymphatic vascular systems.

Science.gov (United States)

Wu, Min; Frieboes, Hermann B; Chaplain, Mark A J; McDougall, Steven R; Cristini, Vittorio; Lowengrub, John S

2014-08-21

Vascularized tumor growth is characterized by both abnormal interstitial fluid flow and the associated interstitial fluid pressure (IFP). Here, we study the effect that these conditions have on the transport of therapeutic agents during chemotherapy. We apply our recently developed vascular tumor growth model which couples a continuous growth component with a discrete angiogenesis model to show that hypertensive IFP is a physical barrier that may hinder vascular extravasation of agents through transvascular fluid flux convection, which drives the agents away from the tumor. This result is consistent with previous work using simpler models without blood flow or lymphatic drainage. We consider the vascular/interstitial/lymphatic fluid dynamics to show that tumors with larger lymphatic resistance increase the agent concentration more rapidly while also experiencing faster washout. In contrast, tumors with smaller lymphatic resistance accumulate less agents but are able to retain them for a longer time. The agent availability (area-under-the curve, or AUC) increases for less permeable agents as lymphatic resistance increases, and correspondingly decreases for more permeable agents. We also investigate the effect of vascular pathologies on agent transport. We show that elevated vascular hydraulic conductivity contributes to the highest AUC when the agent is less permeable, but to lower AUC when the agent is more permeable. We find that elevated interstitial hydraulic conductivity contributes to low AUC in general regardless of the transvascular agent transport capability. We also couple the agent transport with the tumor dynamics to simulate chemotherapy with the same vascularized tumor under different vascular pathologies. We show that tumors with an elevated interstitial hydraulic conductivity alone require the strongest dosage to shrink. We further show that tumors with elevated vascular hydraulic conductivity are more hypoxic during therapy and that the response

The use of innovative gadolinium-based contrast agent for MR-diagnosis of cancer in the experiment

International Nuclear Information System (INIS)

Chernov, V; Medvedeva, A; Sinilkin, I; Zelchan, R; Grigorev, E; Frolova, I; Nam, I

2016-01-01

The present study of the functional suitability and specific activity of the contrast agent gadolinium-based for magnetic resonance imaging demonstrated that the investigated contrast agent intensively accumulates in organs and anatomical structures of the experimental animals. In the model of tumor lesions in animals, study have shown that investigational contrast agent accumulates in the tumor tissue and retained there in for a long enough time. (paper)

Predicting the impact of combined therapies on myeloma cell growth using a hybrid multi-scale agent-based model.

Science.gov (United States)

Ji, Zhiwei; Su, Jing; Wu, Dan; Peng, Huiming; Zhao, Weiling; Nlong Zhao, Brian; Zhou, Xiaobo

2017-01-31

Multiple myeloma is a malignant still incurable plasma cell disorder. This is due to refractory disease relapse, immune impairment, and development of multi-drug resistance. The growth of malignant plasma cells is dependent on the bone marrow (BM) microenvironment and evasion of the host's anti-tumor immune response. Hence, we hypothesized that targeting tumor-stromal cell interaction and endogenous immune system in BM will potentially improve the response of multiple myeloma (MM). Therefore, we proposed a computational simulation of the myeloma development in the complicated microenvironment which includes immune cell components and bone marrow stromal cells and predicted the effects of combined treatment with multi-drugs on myeloma cell growth. We constructed a hybrid multi-scale agent-based model (HABM) that combines an ODE system and Agent-based model (ABM). The ODEs was used for modeling the dynamic changes of intracellular signal transductions and ABM for modeling the cell-cell interactions between stromal cells, tumor, and immune components in the BM. This model simulated myeloma growth in the bone marrow microenvironment and revealed the important role of immune system in this process. The predicted outcomes were consistent with the experimental observations from previous studies. Moreover, we applied this model to predict the treatment effects of three key therapeutic drugs used for MM, and found that the combination of these three drugs potentially suppress the growth of myeloma cells and reactivate the immune response. In summary, the proposed model may serve as a novel computational platform for simulating the formation of MM and evaluating the treatment response of MM to multiple drugs.

Mitigating Errors in External Respiratory Surrogate-Based Models of Tumor Position

Energy Technology Data Exchange (ETDEWEB)

Malinowski, Kathleen T. [Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD (United States); Fischell Department of Bioengineering, University of Maryland, College Park, MD (United States); McAvoy, Thomas J. [Fischell Department of Bioengineering, University of Maryland, College Park, MD (United States); Department of Chemical and Biomolecular Engineering and Institute of Systems Research, University of Maryland, College Park, MD (United States); George, Rohini [Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD (United States); Dieterich, Sonja [Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA (United States); D' Souza, Warren D., E-mail: wdsou001@umaryland.edu [Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD (United States); Fischell Department of Bioengineering, University of Maryland, College Park, MD (United States)

2012-04-01

Purpose: To investigate the effect of tumor site, measurement precision, tumor-surrogate correlation, training data selection, model design, and interpatient and interfraction variations on the accuracy of external marker-based models of tumor position. Methods and Materials: Cyberknife Synchrony system log files comprising synchronously acquired positions of external markers and the tumor from 167 treatment fractions were analyzed. The accuracy of Synchrony, ordinary-least-squares regression, and partial-least-squares regression models for predicting the tumor position from the external markers was evaluated. The quantity and timing of the data used to build the predictive model were varied. The effects of tumor-surrogate correlation and the precision in both the tumor and the external surrogate position measurements were explored by adding noise to the data. Results: The tumor position prediction errors increased during the duration of a fraction. Increasing the training data quantities did not always lead to more accurate models. Adding uncorrelated noise to the external marker-based inputs degraded the tumor-surrogate correlation models by 16% for partial-least-squares and 57% for ordinary-least-squares. External marker and tumor position measurement errors led to tumor position prediction changes 0.3-3.6 times the magnitude of the measurement errors, varying widely with model algorithm. The tumor position prediction errors were significantly associated with the patient index but not with the fraction index or tumor site. Partial-least-squares was as accurate as Synchrony and more accurate than ordinary-least-squares. Conclusions: The accuracy of surrogate-based inferential models of tumor position was affected by all the investigated factors, except for the tumor site and fraction index.

MRI contrast agent concentration and tumor interstitial fluid pressure.

Science.gov (United States)

Liu, L J; Schlesinger, M

2016-10-07

The present work describes the relationship between tumor interstitial fluid pressure (TIFP) and the concentration of contrast agent for dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). We predict the spatial distribution of TIFP based on that of contrast agent concentration. We also discuss the cases for estimating tumor interstitial volume fraction (void fraction or porosity of porous medium), ve, and contrast volume transfer constant, K(trans), by measuring the ratio of contrast agent concentration in tissue to that in plasma. A linear fluid velocity distribution may reflect a quadratic function of TIFP distribution and lead to a practical method for TIFP estimation. To calculate TIFP, the parameters or variables should preferably be measured along the direction of the linear fluid velocity (this is in the same direction as the gray value distribution of the image, which is also linear). This method may simplify the calculation for estimating TIFP. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

Basic study for development of new tumor specific agents for neutron capture therapy

International Nuclear Information System (INIS)

Matsumura, Akira; Nakagawa, Kunio; Yoshii, Yoshihiko; Nose, Tadao

1994-01-01

New tissue specific agents for neutron capture therapy was studied. Monoclonal labeled gadolinium-DTPA (Gd-MoAb) and porphyrin (ATN-10)-Gd-DTPA (Gd-ATN10) were studied as possible agents by using 9-L experimental brain tumor model. The tissue concentration were analyzed with magnetic resonance imaging (MRI) and inductively coupled plasma (ICP) analyzer. Gd-MoAb showed persistent retention in the tumor on MRI, but tissue gadolinium concentration was not detectable in the tumor by ICP analyzer, while there was high accumulation of Gd-MoAb in the liver. Gd-ATN10 showed prolonged and high accumulation in the tumor up to 48 hours on MRI. Gadolinium concentration reached up to 9 ppm in the tumor by 0.02 mmol/kg administration, but it disappeared within 6 hours after administration. This dissociation between MRI and ICP analysis was due to separation of ATN-10 and Gd-DTPA. As conclusions, the porphyrin compounds are potential agents for delivering gadolinium or boron specific to the tumor tissue, thus further improvement such as more stable conjugation between porphyrinfic to the tumor tissue, thus further improvement such as more stable conjugation between porphyrin and Gd-DTPA is needed. (author)

Agent-based Modeling with MATSim for Hazards Evacuation Planning

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Jones, J. M.; Ng, P.; Henry, K.; Peters, J.; Wood, N. J.

2015-12-01

Hazard evacuation planning requires robust modeling tools and techniques, such as least cost distance or agent-based modeling, to gain an understanding of a community's potential to reach safety before event (e.g. tsunami) arrival. Least cost distance modeling provides a static view of the evacuation landscape with an estimate of travel times to safety from each location in the hazard space. With this information, practitioners can assess a community's overall ability for timely evacuation. More information may be needed if evacuee congestion creates bottlenecks in the flow patterns. Dynamic movement patterns are best explored with agent-based models that simulate movement of and interaction between individual agents as evacuees through the hazard space, reacting to potential congestion areas along the evacuation route. The multi-agent transport simulation model MATSim is an agent-based modeling framework that can be applied to hazard evacuation planning. Developed jointly by universities in Switzerland and Germany, MATSim is open-source software written in Java and freely available for modification or enhancement. We successfully used MATSim to illustrate tsunami evacuation challenges in two island communities in California, USA, that are impacted by limited escape routes. However, working with MATSim's data preparation, simulation, and visualization modules in an integrated development environment requires a significant investment of time to develop the software expertise to link the modules and run a simulation. To facilitate our evacuation research, we packaged the MATSim modules into a single application tailored to the needs of the hazards community. By exposing the modeling parameters of interest to researchers in an intuitive user interface and hiding the software complexities, we bring agent-based modeling closer to practitioners and provide access to the powerful visual and analytic information that this modeling can provide.

Systemic use of tumor necrosis factor alpha as an anticancer agent

Science.gov (United States)

Roberts, Nicholas J.; Zhou, Shibin; Diaz, Luis A.; Holdhoff, Matthias

2011-01-01

Tumor necrosis factor-α (TNF-α) has been discussed as a potential anticancer agent for many years, however initial enthusiasm about its clinical use as a systemic agent was curbed due to significant toxicities and lack of efficacy. Combination of TNF-α with chemotherapy in the setting of hyperthermic isolated limb perfusion (ILP), has provided new insights into a potential therapeutic role of this agent. The therapeutic benefit from TNF-α in ILP is thought to be not only due to its direct anti-proliferative effect, but also due to its ability to increase penetration of the chemotherapeutic agents into the tumor tissue. New concepts for the use of TNF-α as a facilitator rather than as a direct actor are currently being explored with the goal to exploit the ability of this agent to increase drug delivery and to simultaneously reduce systemic toxicity. This review article provides a comprehensive overview on the published previous experience with systemic TNF-α. Data from 18 phase I and 10 phase II single agent as well as 18 combination therapy studies illustrate previously used treatment and dose schedules, response data as well as the most prominently observed adverse effects. Also discussed, based on recent preclinical data, is a potential future role of systemic TNF-α in combination with liposomal chemotherapy to facilitate increased drug uptake into tumors. PMID:22036896

Mitigating Errors in External Respiratory Surrogate-Based Models of Tumor Position

International Nuclear Information System (INIS)

Malinowski, Kathleen T.; McAvoy, Thomas J.; George, Rohini; Dieterich, Sonja; D'Souza, Warren D.

2012-01-01

Purpose: To investigate the effect of tumor site, measurement precision, tumor–surrogate correlation, training data selection, model design, and interpatient and interfraction variations on the accuracy of external marker-based models of tumor position. Methods and Materials: Cyberknife Synchrony system log files comprising synchronously acquired positions of external markers and the tumor from 167 treatment fractions were analyzed. The accuracy of Synchrony, ordinary-least-squares regression, and partial-least-squares regression models for predicting the tumor position from the external markers was evaluated. The quantity and timing of the data used to build the predictive model were varied. The effects of tumor–surrogate correlation and the precision in both the tumor and the external surrogate position measurements were explored by adding noise to the data. Results: The tumor position prediction errors increased during the duration of a fraction. Increasing the training data quantities did not always lead to more accurate models. Adding uncorrelated noise to the external marker-based inputs degraded the tumor–surrogate correlation models by 16% for partial-least-squares and 57% for ordinary-least-squares. External marker and tumor position measurement errors led to tumor position prediction changes 0.3–3.6 times the magnitude of the measurement errors, varying widely with model algorithm. The tumor position prediction errors were significantly associated with the patient index but not with the fraction index or tumor site. Partial-least-squares was as accurate as Synchrony and more accurate than ordinary-least-squares. Conclusions: The accuracy of surrogate-based inferential models of tumor position was affected by all the investigated factors, except for the tumor site and fraction index.

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

Science.gov (United States)

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.

Modelling of robotic work cells using agent based-approach

Science.gov (United States)

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.

Agent-Based Modeling in Systems Pharmacology.

Science.gov (United States)

Cosgrove, J; Butler, J; Alden, K; Read, M; Kumar, V; Cucurull-Sanchez, L; Timmis, J; Coles, M

2015-11-01

Modeling and simulation (M&S) techniques provide a platform for knowledge integration and hypothesis testing to gain insights into biological systems that would not be possible a priori. Agent-based modeling (ABM) is an M&S technique that focuses on describing individual components rather than homogenous populations. This tutorial introduces ABM to systems pharmacologists, using relevant case studies to highlight how ABM-specific strengths have yielded success in the area of preclinical mechanistic modeling.

Structuring Qualitative Data for Agent-Based Modelling

NARCIS (Netherlands)

Ghorbani, Amineh; Dijkema, Gerard P.J.; Schrauwen, Noortje

2015-01-01

Using ethnography to build agent-based models may result in more empirically grounded simulations. Our study on innovation practice and culture in the Westland horticulture sector served to explore what information and data from ethnographic analysis could be used in models and how. MAIA, a

Towards a standard model for research in agent-based modeling and simulation

Directory of Open Access Journals (Sweden)

Nuno Fachada

2015-11-01

Full Text Available Agent-based modeling (ABM is a bottom-up modeling approach, where each entity of the system being modeled is uniquely represented as an independent decision-making agent. ABMs are very sensitive to implementation details. Thus, it is very easy to inadvertently introduce changes which modify model dynamics. Such problems usually arise due to the lack of transparency in model descriptions, which constrains how models are assessed, implemented and replicated. In this paper, we present PPHPC, a model which aims to serve as a standard in agent based modeling research, namely, but not limited to, conceptual model specification, statistical analysis of simulation output, model comparison and parallelization studies. This paper focuses on the first two aspects (conceptual model specification and statistical analysis of simulation output, also providing a canonical implementation of PPHPC. The paper serves as a complete reference to the presented model, and can be used as a tutorial for simulation practitioners who wish to improve the way they communicate their ABMs.

Cyanine 5.5 conjugated nanobubbles as a tumor selective contrast agent for dual ultrasound-fluorescence imaging in a mouse model.

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Liyi Mai

Full Text Available Nanobubbles and microbubbles are non-invasive ultrasound imaging contrast agents that may potentially enhance diagnosis of tumors. However, to date, both nanobubbles and microbubbles display poor in vivo tumor-selectivity over non-targeted organs such as liver. We report here cyanine 5.5 conjugated nanobubbles (cy5.5-nanobubbles of a biocompatible chitosan-vitamin C lipid system as a dual ultrasound-fluorescence contrast agent that achieved tumor-selective imaging in a mouse tumor model. Cy5.5-nanobubble suspension contained single bubble spheres and clusters of bubble spheres with the size ranging between 400-800 nm. In the in vivo mouse study, enhancement of ultrasound signals at tumor site was found to persist over 2 h while tumor-selective fluorescence emission was persistently observed over 24 h with intravenous injection of cy5.5-nanobubbles. In vitro cell study indicated that cy5.5-flurescence dye was able to accumulate in cancer cells due to the unique conjugated nanobubble structure. Further in vivo fluorescence study suggested that cy5.5-nanobubbles were mainly located at tumor site and in the bladder of mice. Subsequent analysis confirmed that accumulation of high fluorescence was present at the intact subcutaneous tumor site and in isolated tumor tissue but not in liver tissue post intravenous injection of cy5.5-nanobubbles. All these results led to the conclusion that cy5.5-nanobubbles with unique crosslinked chitosan-vitamin C lipid system have achieved tumor-selective imaging in vivo.

A Multiscale Agent-Based in silico Model of Liver Fibrosis Progression

International Nuclear Information System (INIS)

Dutta-Moscato, Joyeeta; Solovyev, Alexey; Mi, Qi; Nishikawa, Taichiro; Soto-Gutierrez, Alejandro; Fox, Ira J.; Vodovotz, Yoram

2014-01-01

Chronic hepatic inflammation involves a complex interplay of inflammatory and mechanical influences, ultimately manifesting in a characteristic histopathology of liver fibrosis. We created an agent-based model (ABM) of liver tissue in order to computationally examine the consequence of liver inflammation. Our liver fibrosis ABM (LFABM) is comprised of literature-derived rules describing molecular and histopathological aspects of inflammation and fibrosis in a section of chemically injured liver. Hepatocytes are modeled as agents within hexagonal lobules. Injury triggers an inflammatory reaction, which leads to activation of local Kupffer cells and recruitment of monocytes from circulation. Portal fibroblasts and hepatic stellate cells are activated locally by the products of inflammation. The various agents in the simulation are regulated by above-threshold concentrations of pro- and anti-inflammatory cytokines and damage-associated molecular pattern molecules. The simulation progresses from chronic inflammation to collagen deposition, exhibiting periportal fibrosis followed by bridging fibrosis, and culminating in disruption of the regular lobular structure. The ABM exhibited key histopathological features observed in liver sections from rats treated with carbon tetrachloride (CCl 4 ). An in silico “tension test” for the hepatic lobules predicted an overall increase in tissue stiffness, in line with clinical elastography literature and published studies in CCl 4 -treated rats. Therapy simulations suggested differential anti-fibrotic effects of neutralizing tumor necrosis factor alpha vs. enhancing M2 Kupffer cells. We conclude that a computational model of liver inflammation on a structural skeleton of physical forces can recapitulate key histopathological and macroscopic properties of CCl 4 -injured liver. This multiscale approach linking molecular and chemomechanical stimuli enables a model that could be used to gain translationally relevant insights into

Agent-based modelling in synthetic biology.

Science.gov (United States)

Gorochowski, Thomas E

2016-11-30

Biological systems exhibit complex behaviours that emerge at many different levels of organization. These span the regulation of gene expression within single cells to the use of quorum sensing to co-ordinate the action of entire bacterial colonies. Synthetic biology aims to make the engineering of biology easier, offering an opportunity to control natural systems and develop new synthetic systems with useful prescribed behaviours. However, in many cases, it is not understood how individual cells should be programmed to ensure the emergence of a required collective behaviour. Agent-based modelling aims to tackle this problem, offering a framework in which to simulate such systems and explore cellular design rules. In this article, I review the use of agent-based models in synthetic biology, outline the available computational tools, and provide details on recently engineered biological systems that are amenable to this approach. I further highlight the challenges facing this methodology and some of the potential future directions. © 2016 The Author(s).

Agent Based Modelling for Social Simulation

NARCIS (Netherlands)

Smit, S.K.; Ubink, E.M.; Vecht, B. van der; Langley, D.J.

2013-01-01

This document is the result of an exploratory project looking into the status of, and opportunities for Agent Based Modelling (ABM) at TNO. The project focussed on ABM applications containing social interactions and human factors, which we termed ABM for social simulation (ABM4SS). During the course

Agent-based Modeling Methodology for Analyzing Weapons Systems

Science.gov (United States)

2015-03-26

technique involve model structure, system representation and the degree of validity, coupled with the simplicity, of the overall model. ABM is best suited... system representation of the air combat system . We feel that a simulation model that combines ABM with equation-based representation of weapons and...AGENT-BASED MODELING METHODOLOGY FOR ANALYZING WEAPONS SYSTEMS THESIS Casey D. Connors, Major, USA

Agent-based modeling in ecological economics.

Science.gov (United States)

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.

Improving Agent Based Modeling of Critical Incidents

Directory of Open Access Journals (Sweden)

Robert Till

2010-04-01

Full Text Available Agent Based Modeling (ABM is a powerful method that has been used to simulate potential critical incidents in the infrastructure and built environments. This paper will discuss the modeling of some critical incidents currently simulated using ABM and how they may be expanded and improved by using better physiological modeling, psychological modeling, modeling the actions of interveners, introducing Geographic Information Systems (GIS and open source models.

Agent-Based Model Approach to Complex Phenomena in Real Economy

Science.gov (United States)

Iyetomi, H.; Aoyama, H.; Fujiwara, Y.; Ikeda, Y.; Souma, W.

An agent-based model for firms' dynamics is developed. The model consists of firm agents with identical characteristic parameters and a bank agent. Dynamics of those agents are described by their balance sheets. Each firm tries to maximize its expected profit with possible risks in market. Infinite growth of a firm directed by the ``profit maximization" principle is suppressed by a concept of ``going concern". Possibility of bankruptcy of firms is also introduced by incorporating a retardation effect of information on firms' decision. The firms, mutually interacting through the monopolistic bank, become heterogeneous in the course of temporal evolution. Statistical properties of firms' dynamics obtained by simulations based on the model are discussed in light of observations in the real economy.

Advancing bioluminescence imaging technology for the evaluation of anticancer agents in the MDA-MB-435-HAL-Luc mammary fat pad and subrenal capsule tumor models.

Science.gov (United States)

Zhang, Cathy; Yan, Zhengming; Arango, Maria E; Painter, Cory L; Anderes, Kenna

2009-01-01

Tumors grafted s.c. or under the mammary fat pad (MFP) rarely develop efficient metastasis. By applying bioluminescence imaging (BLI) technology, the MDA-MB-435-HAL-Luc subrenal capsule (SRC) model was compared with the MFP model for disease progression, metastatic potential, and response to therapy. The luciferase-expressing MDA-MB-435-HAL-Luc cell line was used in both MFP and SRC models. BLI technology allowed longitudinal assessment of disease progression and the therapeutic response to PD-0332991, Avastin, and docetaxel. Immunohistochemical analysis of Ki67 and CD31 staining in the primary tumors was compared in these models. Caliper measurement was used in the MFP model to validate the BLI quantification of primary tumors. The primary tumors in MDA-MB-435-HAL-Luc MFP and SRC models displayed comparable growth rates and vascularity. However, tumor-bearing mice in the SRC model developed lung metastases much earlier (4 weeks) than in the MFP model (>7 weeks), and the metastatic progression contributed significantly to the survival time. In the MFP model, BLI and caliper measurements were comparable for quantifying palpable tumors, but BLI offered an advantage for detecting the primary tumors that fell below a palpable threshold and for visualizing metastases. In the SRC model, BLI allowed longitudinal assessment of the antitumor and antimetastatic effects of PD-0332991, Avastin, and docetaxel, and the results correlated with the survival benefits of these agents. The MDA-MB-435-HAL-Luc SRC model and the MFP model displayed differences in disease progression. BLI is an innovative approach for developing animal models and creates opportunities for improving preclinical evaluations of anticancer agents.

Enhancement of 67Ga tumor-to-blood ratios by chelating agent

International Nuclear Information System (INIS)

Saji, Hideo; Yokoyama, Akira; Hata, Naotaka; Misaki, Atsushi; Tanaka, Hisashi.

1980-01-01

Chelating agent, such as, CaEDTA, CaDTPA, D-penicillamine, DMSA, desferoxamine, NTA, cysteine ethyl ester, BAL, α-MPG, phthalein complexone, were tested as a possible contrast enhancing agent for tumor imaging with 67 Ga-citrate. The intravenous administration of a chelating agent to Ehrlich's tumor bearing mice, one hour after the injection of 67 Ga-citrate, accelerated the blood clearance with only a very slight change of activity in the target, increasing the tumor-to-blood ratio, and consequently achieving a better visualization. Among the tested chelating agents, D-penicillamine showed the highest target-to-nontarget ratio at a shorter time: a good tumor-to-blood ratio, performed after 24 hr with non-treated animals, was achieved in only 1-3 hr with post-treated animals. Thus, D-penicillamine hold a considerable promise as a contrast enhancing agent for future clinical use. (author)

Towards Agent-Based Model Specification in Smart Grid: A Cognitive Agent-based Computing Approach

OpenAIRE

Akram, Waseem; Niazi, Muaz A.; Iantovics, Laszlo Barna

2017-01-01

A smart grid can be considered as a complex network where each node represents a generation unit or a consumer. Whereas links can be used to represent transmission lines. One way to study complex systems is by using the agent-based modeling (ABM) paradigm. An ABM is a way of representing a complex system of autonomous agents interacting with each other. Previously, a number of studies have been presented in the smart grid domain making use of the ABM paradigm. However, to the best of our know...

Agent Based Fuzzy T-S Multi-Model System and Its Applications

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Xiaopeng Zhao

2015-11-01

Full Text Available Based on the basic concepts of agent and fuzzy T-S model, an agent based fuzzy T-S multi-model (ABFT-SMM system is proposed in this paper. Different from the traditional method, the parameters and the membership value of the agent can be adjusted along with the process. In this system, each agent can be described as a dynamic equation, which can be seen as the local part of the multi-model, and it can execute the task alone or collaborate with other agents to accomplish a fixed goal. It is proved in this paper that the agent based fuzzy T-S multi-model system can approximate any linear or nonlinear system at arbitrary accuracy. The applications to the benchmark problem of chaotic time series prediction, water heater system and waste heat utilizing process illustrate the viability and the efficiency of the mentioned approach. At the same time, the method can be easily used to a number of engineering fields, including identification, nonlinear control, fault diagnostics and performance analysis.

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

Science.gov (United States)

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.

An agent-based model of signal transduction in bacterial chemotaxis.

Directory of Open Access Journals (Sweden)

Jameson Miller

2010-05-01

Full Text Available We report the application of agent-based modeling to examine the signal transduction network and receptor arrays for chemotaxis in Escherichia coli, which are responsible for regulating swimming behavior in response to environmental stimuli. Agent-based modeling is a stochastic and bottom-up approach, where individual components of the modeled system are explicitly represented, and bulk properties emerge from their movement and interactions. We present the Chemoscape model: a collection of agents representing both fixed membrane-embedded and mobile cytoplasmic proteins, each governed by a set of rules representing knowledge or hypotheses about their function. When the agents were placed in a simulated cellular space and then allowed to move and interact stochastically, the model exhibited many properties similar to the biological system including adaptation, high signal gain, and wide dynamic range. We found the agent based modeling approach to be both powerful and intuitive for testing hypotheses about biological properties such as self-assembly, the non-linear dynamics that occur through cooperative protein interactions, and non-uniform distributions of proteins in the cell. We applied the model to explore the role of receptor type, geometry and cooperativity in the signal gain and dynamic range of the chemotactic response to environmental stimuli. The model provided substantial qualitative evidence that the dynamic range of chemotactic response can be traced to both the heterogeneity of receptor types present, and the modulation of their cooperativity by their methylation state.

An agent-based model of signal transduction in bacterial chemotaxis.

Science.gov (United States)

Miller, Jameson; Parker, Miles; Bourret, Robert B; Giddings, Morgan C

2010-05-13

We report the application of agent-based modeling to examine the signal transduction network and receptor arrays for chemotaxis in Escherichia coli, which are responsible for regulating swimming behavior in response to environmental stimuli. Agent-based modeling is a stochastic and bottom-up approach, where individual components of the modeled system are explicitly represented, and bulk properties emerge from their movement and interactions. We present the Chemoscape model: a collection of agents representing both fixed membrane-embedded and mobile cytoplasmic proteins, each governed by a set of rules representing knowledge or hypotheses about their function. When the agents were placed in a simulated cellular space and then allowed to move and interact stochastically, the model exhibited many properties similar to the biological system including adaptation, high signal gain, and wide dynamic range. We found the agent based modeling approach to be both powerful and intuitive for testing hypotheses about biological properties such as self-assembly, the non-linear dynamics that occur through cooperative protein interactions, and non-uniform distributions of proteins in the cell. We applied the model to explore the role of receptor type, geometry and cooperativity in the signal gain and dynamic range of the chemotactic response to environmental stimuli. The model provided substantial qualitative evidence that the dynamic range of chemotactic response can be traced to both the heterogeneity of receptor types present, and the modulation of their cooperativity by their methylation state.

Derivation of Continuum Models from An Agent-based Cancer Model: Optimization and Sensitivity Analysis.

Science.gov (United States)

Voulgarelis, Dimitrios; Velayudhan, Ajoy; Smith, Frank

2017-01-01

Agent-based models provide a formidable tool for exploring complex and emergent behaviour of biological systems as well as accurate results but with the drawback of needing a lot of computational power and time for subsequent analysis. On the other hand, equation-based models can more easily be used for complex analysis in a much shorter timescale. This paper formulates an ordinary differential equations and stochastic differential equations model to capture the behaviour of an existing agent-based model of tumour cell reprogramming and applies it to optimization of possible treatment as well as dosage sensitivity analysis. For certain values of the parameter space a close match between the equation-based and agent-based models is achieved. The need for division of labour between the two approaches is explored. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Spatial agent-based models for socio-ecological systems: challenges and prospects

NARCIS (Netherlands)

de Filatova, T.; Verburg, P.H.; Parker, D.C.; Stannard, S.R.

2013-01-01

Departing from the comprehensive reviews carried out in the field, we identify the key challenges that agent-based methodology faces when modeling coupled socio-ecological systems. Focusing primarily on the papers presented in this thematic issue, we review progress in spatial agent-based models

Tissue engineered tumor models.

Science.gov (United States)

Ingram, M; Techy, G B; Ward, B R; Imam, S A; Atkinson, R; Ho, H; Taylor, C R

2010-08-01

Many research programs use well-characterized tumor cell lines as tumor models for in vitro studies. Because tumor cells grown as three-dimensional (3-D) structures have been shown to behave more like tumors in vivo than do cells growing in monolayer culture, a growing number of investigators now use tumor cell spheroids as models. Single cell type spheroids, however, do not model the stromal-epithelial interactions that have an important role in controlling tumor growth and development in vivo. We describe here a method for generating, reproducibly, more realistic 3-D tumor models that contain both stromal and malignant epithelial cells with an architecture that closely resembles that of tumor microlesions in vivo. Because they are so tissue-like we refer to them as tumor histoids. They can be generated reproducibly in substantial quantities. The bioreactor developed to generate histoid constructs is described and illustrated. It accommodates disposable culture chambers that have filled volumes of either 10 or 64 ml, each culture yielding on the order of 100 or 600 histoid particles, respectively. Each particle is a few tenths of a millimeter in diameter. Examples of histological sections of tumor histoids representing cancers of breast, prostate, colon, pancreas and urinary bladder are presented. Potential applications of tumor histoids include, but are not limited to, use as surrogate tumors for pre-screening anti-solid tumor pharmaceutical agents, as reference specimens for immunostaining in the surgical pathology laboratory and use in studies of invasive properties of cells or other aspects of tumor development and progression. Histoids containing nonmalignant cells also may have potential as "seeds" in tissue engineering. For drug testing, histoids probably will have to meet certain criteria of size and tumor cell content. Using a COPAS Plus flow cytometer, histoids containing fluorescent tumor cells were analyzed successfully and sorted using such criteria.

A Multiscale Agent-Based in silico Model of Liver Fibrosis Progression

Energy Technology Data Exchange (ETDEWEB)

Dutta-Moscato, Joyeeta [Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA (United States); Department of Surgery, University of Pittsburgh, Pittsburgh, PA (United States); Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Solovyev, Alexey [Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Department of Mathematics, University of Pittsburgh, Pittsburgh, PA (United States); Mi, Qi [Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Department of Sports Medicine and Nutrition, University of Pittsburgh, Pittsburgh, PA (United States); Nishikawa, Taichiro [McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Department of Surgery, Children’s Hospital of Pittsburgh, Pittsburgh, PA (United States); Soto-Gutierrez, Alejandro [McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Department of Pathology, University of Pittsburgh, Pittsburgh, PA (United States); Thomas E. Starzl Transplantation Institute, University of Pittsburgh, Pittsburgh, PA (United States); Fox, Ira J. [McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Department of Surgery, Children’s Hospital of Pittsburgh, Pittsburgh, PA (United States); Thomas E. Starzl Transplantation Institute, University of Pittsburgh, Pittsburgh, PA (United States); Vodovotz, Yoram, E-mail: vodovotzy@upmc.edu [Department of Surgery, University of Pittsburgh, Pittsburgh, PA (United States); Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States)

2014-05-30

Chronic hepatic inflammation involves a complex interplay of inflammatory and mechanical influences, ultimately manifesting in a characteristic histopathology of liver fibrosis. We created an agent-based model (ABM) of liver tissue in order to computationally examine the consequence of liver inflammation. Our liver fibrosis ABM (LFABM) is comprised of literature-derived rules describing molecular and histopathological aspects of inflammation and fibrosis in a section of chemically injured liver. Hepatocytes are modeled as agents within hexagonal lobules. Injury triggers an inflammatory reaction, which leads to activation of local Kupffer cells and recruitment of monocytes from circulation. Portal fibroblasts and hepatic stellate cells are activated locally by the products of inflammation. The various agents in the simulation are regulated by above-threshold concentrations of pro- and anti-inflammatory cytokines and damage-associated molecular pattern molecules. The simulation progresses from chronic inflammation to collagen deposition, exhibiting periportal fibrosis followed by bridging fibrosis, and culminating in disruption of the regular lobular structure. The ABM exhibited key histopathological features observed in liver sections from rats treated with carbon tetrachloride (CCl{sub 4}). An in silico “tension test” for the hepatic lobules predicted an overall increase in tissue stiffness, in line with clinical elastography literature and published studies in CCl{sub 4}-treated rats. Therapy simulations suggested differential anti-fibrotic effects of neutralizing tumor necrosis factor alpha vs. enhancing M2 Kupffer cells. We conclude that a computational model of liver inflammation on a structural skeleton of physical forces can recapitulate key histopathological and macroscopic properties of CCl{sub 4}-injured liver. This multiscale approach linking molecular and chemomechanical stimuli enables a model that could be used to gain translationally relevant

Mobile Agent-Based Software Systems Modeling Approaches: A Comparative Study

Directory of Open Access Journals (Sweden)

Aissam Belghiat

2016-06-01

Full Text Available Mobile agent-based applications are special type of software systems which take the advantages of mobile agents in order to provide a new beneficial paradigm to solve multiple complex problems in several fields and areas such as network management, e-commerce, e-learning, etc. Likewise, we notice lack of real applications based on this paradigm and lack of serious evaluations of their modeling approaches. Hence, this paper provides a comparative study of modeling approaches of mobile agent-based software systems. The objective is to give the reader an overview and a thorough understanding of the work that has been done and where the gaps in the research are.

Modeling collective emotions: a stochastic approach based on Brownian agents

International Nuclear Information System (INIS)

Schweitzer, F.

2010-01-01

We develop a agent-based framework to model the emergence of collective emotions, which is applied to online communities. Agents individual emotions are described by their valence and arousal. Using the concept of Brownian agents, these variables change according to a stochastic dynamics, which also considers the feedback from online communication. Agents generate emotional information, which is stored and distributed in a field modeling the online medium. This field affects the emotional states of agents in a non-linear manner. We derive conditions for the emergence of collective emotions, observable in a bimodal valence distribution. Dependent on a saturated or a super linear feedback between the information field and the agent's arousal, we further identify scenarios where collective emotions only appear once or in a repeated manner. The analytical results are illustrated by agent-based computer simulations. Our framework provides testable hypotheses about the emergence of collective emotions, which can be verified by data from online communities. (author)

Quantitative Analysis of Intra Urban Growth Modeling using socio economic agents by combining cellular automata model with agent based model

Science.gov (United States)

Singh, V. K.; Jha, A. K.; Gupta, K.; Srivastav, S. K.

2017-12-01

Recent studies indicate that there is a significant improvement in the urban land use dynamics through modeling at finer spatial resolutions. Geo-computational models such as cellular automata and agent based model have given evident proof regarding the quantification of the urban growth pattern with urban boundary. In recent studies, socio- economic factors such as demography, education rate, household density, parcel price of the current year, distance to road, school, hospital, commercial centers and police station are considered to the major factors influencing the Land Use Land Cover (LULC) pattern of the city. These factors have unidirectional approach to land use pattern which makes it difficult to analyze the spatial aspects of model results both quantitatively and qualitatively. In this study, cellular automata model is combined with generic model known as Agent Based Model to evaluate the impact of socio economic factors on land use pattern. For this purpose, Dehradun an Indian city is selected as a case study. Socio economic factors were collected from field survey, Census of India, Directorate of economic census, Uttarakhand, India. A 3X3 simulating window is used to consider the impact on LULC. Cellular automata model results are examined for the identification of hot spot areas within the urban area and agent based model will be using logistic based regression approach where it will identify the correlation between each factor on LULC and classify the available area into low density, medium density, high density residential or commercial area. In the modeling phase, transition rule, neighborhood effect, cell change factors are used to improve the representation of built-up classes. Significant improvement is observed in the built-up classes from 84 % to 89 %. However after incorporating agent based model with cellular automata model the accuracy improved from 89 % to 94 % in 3 classes of urban i.e. low density, medium density and commercial classes

Agent Based Model of Livestock Movements

Science.gov (United States)

Miron, D. J.; Emelyanova, I. V.; Donald, G. E.; Garner, G. M.

The modelling of livestock movements within Australia is of national importance for the purposes of the management and control of exotic disease spread, infrastructure development and the economic forecasting of livestock markets. In this paper an agent based model for the forecasting of livestock movements is presented. This models livestock movements from farm to farm through a saleyard. The decision of farmers to sell or buy cattle is often complex and involves many factors such as climate forecast, commodity prices, the type of farm enterprise, the number of animals available and associated off-shore effects. In this model the farm agent's intelligence is implemented using a fuzzy decision tree that utilises two of these factors. These two factors are the livestock price fetched at the last sale and the number of stock on the farm. On each iteration of the model farms choose either to buy, sell or abstain from the market thus creating an artificial supply and demand. The buyers and sellers then congregate at the saleyard where livestock are auctioned using a second price sealed bid. The price time series output by the model exhibits properties similar to those found in real livestock markets.

Evaluation of 18F-labeled icotinib derivatives as potential PET agents for tumor imaging

International Nuclear Information System (INIS)

Hongyu Ren; Hongyu Ning; Jin Chang; Mingxia Zhao; Yong He; Yan Chong; Chuanmin Qi

2016-01-01

In this study, three 18 F-labeled crown ether fused anilinoquinazoline derivatives ([ 18 F]11a-c) were synthesized and evaluated as potential tumor imaging probes. The biodistribution results of [ 18 F]11b were good. Compared with [ 18 F]-fludeoxyglucose and l-[ 18 F]-fluoroethyltyrosine in the same animal model, [ 18 F]11b had better tumor/brain, tumor/muscle, and tumor/blood uptake ratios. Overall, these results suggest that [ 18 F]11b is promising as a tumor imaging agent for positron emission tomography. (author)

Identification of walking human model using agent-based modelling

Science.gov (United States)

Shahabpoor, Erfan; Pavic, Aleksandar; Racic, Vitomir

2018-03-01

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

Modeling Oil Exploration and Production: Resource-Constrained and Agent-Based Approaches

International Nuclear Information System (INIS)

Jakobsson, Kristofer

2010-05-01

Energy is essential to the functioning of society, and oil is the single largest commercial energy source. Some analysts have concluded that the peak in oil production is soon about to happen on the global scale, while others disagree. Such incompatible views can persist because the issue of 'peak oil' cuts through the established scientific disciplines. The question is: what characterizes the modeling approaches that are available today, and how can they be further developed to improve a trans-disciplinary understanding of oil depletion? The objective of this thesis is to present long-term scenarios of oil production (Paper I) using a resource-constrained model; and an agent-based model of the oil exploration process (Paper II). It is also an objective to assess the strengths, limitations, and future development potentials of resource-constrained modeling, analytical economic modeling, and agent-based modeling. Resource-constrained models are only suitable when the time frame is measured in decades, but they can give a rough indication of which production scenarios are reasonable given the size of the resource. However, the models are comprehensible, transparent and the only feasible long-term forecasting tools at present. It is certainly possible to distinguish between reasonable scenarios, based on historically observed parameter values, and unreasonable scenarios with parameter values obtained through flawed analogy. The economic subfield of optimal depletion theory is founded on the notion of rational economic agents, and there is a causal relation between decisions made at the micro-level and the macro-result. In terms of future improvements, however, the analytical form considerably restricts the versatility of the approach. Agent-based modeling makes it feasible to combine economically motivated agents with a physical environment. An example relating to oil exploration is given in Paper II, where it is shown that the exploratory activities of individual

A strategy learning model for autonomous agents based on classification

Directory of Open Access Journals (Sweden)

Śnieżyński Bartłomiej

2015-09-01

Full Text Available In this paper we propose a strategy learning model for autonomous agents based on classification. In the literature, the most commonly used learning method in agent-based systems is reinforcement learning. In our opinion, classification can be considered a good alternative. This type of supervised learning can be used to generate a classifier that allows the agent to choose an appropriate action for execution. Experimental results show that this model can be successfully applied for strategy generation even if rewards are delayed. We compare the efficiency of the proposed model and reinforcement learning using the farmer-pest domain and configurations of various complexity. In complex environments, supervised learning can improve the performance of agents much faster that reinforcement learning. If an appropriate knowledge representation is used, the learned knowledge may be analyzed by humans, which allows tracking the learning process

Understanding Group/Party Affiliation Using Social Networks and Agent-Based Modeling

Science.gov (United States)

Campbell, Kenyth

2012-01-01

The dynamics of group affiliation and group dispersion is a concept that is most often studied in order for political candidates to better understand the most efficient way to conduct their campaigns. While political campaigning in the United States is a very hot topic that most politicians analyze and study, the concept of group/party affiliation presents its own area of study that producers very interesting results. One tool for examining party affiliation on a large scale is agent-based modeling (ABM), a paradigm in the modeling and simulation (M&S) field perfectly suited for aggregating individual behaviors to observe large swaths of a population. For this study agent based modeling was used in order to look at a community of agents and determine what factors can affect the group/party affiliation patterns that are present. In the agent-based model that was used for this experiment many factors were present but two main factors were used to determine the results. The results of this study show that it is possible to use agent-based modeling to explore group/party affiliation and construct a model that can mimic real world events. More importantly, the model in the study allows for the results found in a smaller community to be translated into larger experiments to determine if the results will remain present on a much larger scale.

Combined-modality treatment of solid tumors using radiotherapy and molecular targeted agents.

Science.gov (United States)

Ma, Brigette B Y; Bristow, Robert G; Kim, John; Siu, Lillian L

2003-07-15

Molecular targeted agents have been combined with radiotherapy (RT) in recent clinical trials in an effort to optimize the therapeutic index of RT. The appeal of this strategy lies in their potential target specificity and clinically acceptable toxicity. This article integrates the salient, published research findings into the underlying molecular mechanisms, preclinical efficacy, and clinical applicability of combining RT with molecular targeted agents. These agents include inhibitors of intracellular signal transduction molecules, modulators of apoptosis, inhibitors of cell cycle checkpoints control, antiangiogenic agents, and cyclo-oxygenase-2 inhibitors. Molecular targeted agents can have direct effects on the cytoprotective and cytotoxic pathways implicated in the cellular response to ionizing radiation (IR). These pathways involve cellular proliferation, DNA repair, cell cycle progression, nuclear transcription, tumor angiogenesis, and prostanoid-associated inflammation. These pathways can also converge to alter RT-induced apoptosis, terminal growth arrest, and reproductive cell death. Pharmacologic modulation of these pathways may potentially enhance tumor response to RT though inhibition of tumor repopulation, improvement of tumor oxygenation, redistribution during the cell cycle, and alteration of intrinsic tumor radiosensitivity. Combining RT and molecular targeted agents is a rational approach in the treatment of solid tumors. Translation of this approach from promising preclinical data to clinical trials is actively underway.

Agent-based models of financial markets

Energy Technology Data Exchange (ETDEWEB)

Samanidou, E [Department of Economics, University of Kiel, Olshausenstrasse 40, D-24118 Kiel (Germany); Zschischang, E [HSH Nord Bank, Portfolio Mngmt. and Inv., Martensdamm 6, D-24103 Kiel (Germany); Stauffer, D [Institute for Theoretical Physics, Cologne University, D-50923 Koeln (Germany); Lux, T [Department of Economics, University of Kiel, Olshausenstrasse 40, D-24118 Kiel (Germany)

2007-03-15

This review deals with several microscopic ('agent-based') models of financial markets which have been studied by economists and physicists over the last decade: Kim-Markowitz, Levy-Levy-Solomon, Cont-Bouchaud, Solomon-Weisbuch, Lux-Marchesi, Donangelo-Sneppen and Solomon-Levy-Huang. After an overview of simulation approaches in financial economics, we first give a summary of the Donangelo-Sneppen model of monetary exchange and compare it with related models in economics literature. Our selective review then outlines the main ingredients of some influential early models of multi-agent dynamics in financial markets (Kim-Markowitz, Levy-Levy-Solomon). As will be seen, these contributions draw their inspiration from the complex appearance of investors' interactions in real-life markets. Their main aim is to reproduce (and, thereby, provide possible explanations) for the spectacular bubbles and crashes seen in certain historical episodes, but they lack (like almost all the work before 1998 or so) a perspective in terms of the universal statistical features of financial time series. In fact, awareness of a set of such regularities (power-law tails of the distribution of returns, temporal scaling of volatility) only gradually appeared over the nineties. With the more precise description of the formerly relatively vague characteristics (e.g. moving from the notion of fat tails to the more concrete one of a power law with index around three), it became clear that financial market dynamics give rise to some kind of universal scaling law. Showing similarities with scaling laws for other systems with many interacting sub-units, an exploration of financial markets as multi-agent systems appeared to be a natural consequence. This topic has been pursued by quite a number of contributions appearing in both the physics and economics literature since the late nineties. From the wealth of different flavours of multi-agent models that have appeared up to now, we

Agent-based models of financial markets

Science.gov (United States)

Samanidou, E.; Zschischang, E.; Stauffer, D.; Lux, T.

2007-03-01

This review deals with several microscopic ('agent-based') models of financial markets which have been studied by economists and physicists over the last decade: Kim-Markowitz, Levy-Levy-Solomon, Cont-Bouchaud, Solomon-Weisbuch, Lux-Marchesi, Donangelo-Sneppen and Solomon-Levy-Huang. After an overview of simulation approaches in financial economics, we first give a summary of the Donangelo-Sneppen model of monetary exchange and compare it with related models in economics literature. Our selective review then outlines the main ingredients of some influential early models of multi-agent dynamics in financial markets (Kim-Markowitz, Levy-Levy-Solomon). As will be seen, these contributions draw their inspiration from the complex appearance of investors' interactions in real-life markets. Their main aim is to reproduce (and, thereby, provide possible explanations) for the spectacular bubbles and crashes seen in certain historical episodes, but they lack (like almost all the work before 1998 or so) a perspective in terms of the universal statistical features of financial time series. In fact, awareness of a set of such regularities (power-law tails of the distribution of returns, temporal scaling of volatility) only gradually appeared over the nineties. With the more precise description of the formerly relatively vague characteristics (e.g. moving from the notion of fat tails to the more concrete one of a power law with index around three), it became clear that financial market dynamics give rise to some kind of universal scaling law. Showing similarities with scaling laws for other systems with many interacting sub-units, an exploration of financial markets as multi-agent systems appeared to be a natural consequence. This topic has been pursued by quite a number of contributions appearing in both the physics and economics literature since the late nineties. From the wealth of different flavours of multi-agent models that have appeared up to now, we discuss the Cont

Agent-based models of financial markets

International Nuclear Information System (INIS)

Samanidou, E; Zschischang, E; Stauffer, D; Lux, T

2007-01-01

This review deals with several microscopic ('agent-based') models of financial markets which have been studied by economists and physicists over the last decade: Kim-Markowitz, Levy-Levy-Solomon, Cont-Bouchaud, Solomon-Weisbuch, Lux-Marchesi, Donangelo-Sneppen and Solomon-Levy-Huang. After an overview of simulation approaches in financial economics, we first give a summary of the Donangelo-Sneppen model of monetary exchange and compare it with related models in economics literature. Our selective review then outlines the main ingredients of some influential early models of multi-agent dynamics in financial markets (Kim-Markowitz, Levy-Levy-Solomon). As will be seen, these contributions draw their inspiration from the complex appearance of investors' interactions in real-life markets. Their main aim is to reproduce (and, thereby, provide possible explanations) for the spectacular bubbles and crashes seen in certain historical episodes, but they lack (like almost all the work before 1998 or so) a perspective in terms of the universal statistical features of financial time series. In fact, awareness of a set of such regularities (power-law tails of the distribution of returns, temporal scaling of volatility) only gradually appeared over the nineties. With the more precise description of the formerly relatively vague characteristics (e.g. moving from the notion of fat tails to the more concrete one of a power law with index around three), it became clear that financial market dynamics give rise to some kind of universal scaling law. Showing similarities with scaling laws for other systems with many interacting sub-units, an exploration of financial markets as multi-agent systems appeared to be a natural consequence. This topic has been pursued by quite a number of contributions appearing in both the physics and economics literature since the late nineties. From the wealth of different flavours of multi-agent models that have appeared up to now, we discuss the Cont

Between Complexity and Parsimony: Can Agent-Based Modelling Resolve the Trade-off

DEFF Research Database (Denmark)

Nielsen, Helle Ørsted; Malawska, Anna Katarzyna

2013-01-01

to BR- based policy studies would be to couple research on bounded ra-tionality with agent-based modeling. Agent-based models (ABMs) are computational models for simulating the behavior and interactions of any number of decision makers in a dynamic system. Agent-based models are better suited than...... are general equilibrium models for capturing behavior patterns of complex systems. ABMs may have the potential to represent complex systems without oversimplifying them. At the same time, research in bounded rationality and behavioral economics has already yielded many insights that could inform the modeling......While Herbert Simon espoused development of general models of behavior, he also strongly advo-cated that these models be based on realistic assumptions about humans and therefore reflect the complexity of human cognition and social systems (Simon 1997). Hence, the model of bounded rationality...

Agent-based modeling as a tool for program design and evaluation.

Science.gov (United States)

Lawlor, Jennifer A; McGirr, Sara

2017-12-01

Recently, systems thinking and systems science approaches have gained popularity in the field of evaluation; however, there has been relatively little exploration of how evaluators could use quantitative tools to assist in the implementation of systems approaches therein. The purpose of this paper is to explore potential uses of one such quantitative tool, agent-based modeling, in evaluation practice. To this end, we define agent-based modeling and offer potential uses for it in typical evaluation activities, including: engaging stakeholders, selecting an intervention, modeling program theory, setting performance targets, and interpreting evaluation results. We provide demonstrative examples from published agent-based modeling efforts both inside and outside the field of evaluation for each of the evaluative activities discussed. We further describe potential pitfalls of this tool and offer cautions for evaluators who may chose to implement it in their practice. Finally, the article concludes with a discussion of the future of agent-based modeling in evaluation practice and a call for more formal exploration of this tool as well as other approaches to simulation modeling in the field. Copyright © 2017 Elsevier Ltd. All rights reserved.

Reverse engineering a social agent-based hidden markov model--visage.

Science.gov (United States)

Chen, Hung-Ching Justin; Goldberg, Mark; Magdon-Ismail, Malik; Wallace, William A

2008-12-01

We present a machine learning approach to discover the agent dynamics that drives the evolution of the social groups in a community. We set up the problem by introducing an agent-based hidden Markov model for the agent dynamics: an agent's actions are determined by micro-laws. Nonetheless, We learn the agent dynamics from the observed communications without knowing state transitions. Our approach is to identify the appropriate micro-laws corresponding to an identification of the appropriate parameters in the model. The model identification problem is then formulated as a mixed optimization problem. To solve the problem, we develop a multistage learning process for determining the group structure, the group evolution, and the micro-laws of a community based on the observed set of communications among actors, without knowing the semantic contents. Finally, to test the quality of our approximations and the feasibility of the approach, we present the results of extensive experiments on synthetic data as well as the results on real communities, such as Enron email and Movie newsgroups. Insight into agent dynamics helps us understand the driving forces behind social evolution.

SIMULATING AN EVOLUTIONARY MULTI-AGENT BASED MODEL OF THE STOCK MARKET

Directory of Open Access Journals (Sweden)

Diana MARICA

2015-08-01

Full Text Available The paper focuses on artificial stock market simulations using a multi-agent model incorporating 2,000 heterogeneous agents interacting on the artificial market. The agents interaction is due to trading activity on the market through a call auction trading mechanism. The multi-agent model uses evolutionary techniques such as genetic programming in order to generate an adaptive and evolving population of agents. Each artificial agent is endowed with wealth and a genetic programming induced trading strategy. The trading strategy evolves and adapts to the new market conditions through a process called breeding, which implies that at each simulation step, new agents with better trading strategies are generated by the model, from recombining the best performing trading strategies and replacing the agents which have the worst performing trading strategies. The simulation model was build with the help of the simulation software Altreva Adaptive Modeler which offers a suitable platform for financial market simulations of evolutionary agent based models, the S&P500 composite index being used as a benchmark for the simulation results.

Vascular Targeting in Pancreatic Cancer: The Novel Tubulin-Binding Agent ZD6126 Reveals Antitumor Activity in Primary and Metastatic Tumor Models

Directory of Open Access Journals (Sweden)

Axel Kleespies

2005-10-01

Full Text Available ZD6126 is a novel vascular-targeting agent that acts by disrupting the tubulin cytoskeleton of an immature tumor endothelium, leading to an occlusion of tumor blood vessels and a subsequent tumor necrosis. We wanted to evaluate ZD6126 in primary and metastatic tumor models of human pancreatic cancer. Nude mice were injected orthotopically with L3.6pl pancreatic cancer cells. In single and multiple dosing experiments, mice received ZD6126, gemcitabine, a combination of both agents, or no treatment. For the induction of metastatic disease, additional groups of mice were injected with L3.6pl cells into the spleen. Twenty-four hours after a single-dose treatment, ZD6126 therapy led to an extensive central tumor necrosis, which was not seen after gemcitabine treatment. Multiple dosing of ZD6126 resulted in a significant growth inhibition of primary tumors and a marked reduction of spontaneous liver and lymph node metastases. Experimental metastatic disease could be significantly controlled by a combination of ZD6126 and gemcitabine, as shown by a reduction of the number and size of established liver metastases. As shown by additional in vitro and in vivo experiments, possible mechanisms involve antivascular activities and subsequent antiproliferative and proapoptotic effects of ZD6126 on tumor cells, whereas direct activities against tumor cells seem unlikely. These data highlight the antitumor and antimetastatic effects of ZD6126 in human pancreatic cancer and reveal benefits of adding ZD6126 to standard gemcitabine therapy.

EXCI-CEST: Exploiting pharmaceutical excipients as MRI-CEST contrast agents for tumor imaging.

Science.gov (United States)

Longo, Dario Livio; Moustaghfir, Fatima Zzahra; Zerbo, Alexandre; Consolino, Lorena; Anemone, Annasofia; Bracesco, Martina; Aime, Silvio

2017-06-15

Chemical Exchange Saturation Transfer (CEST) approach is a novel tool within magnetic resonance imaging (MRI) that allows visualization of molecules possessing exchangeable protons with water. Many molecules, employed as excipients for the formulation of finished drug products, are endowed with hydroxyl, amine or amide protons, thus can be exploitable as MRI-CEST contrast agents. Their high safety profiles allow them to be injected at very high doses. Here we investigated the MRI-CEST properties of several excipients (ascorbic acid, sucrose, N-acetyl-d-glucosamine, meglumine and 2-pyrrolidone) and tested them as tumor-detecting agents in two different murine tumor models (breast and melanoma cancers). All the investigated molecules showed remarkable CEST contrast upon i.v. administration in the range 1-3ppm according to the type of mobile proton groups. A marked increase of CEST contrast was observed in tumor regions up to 30min post injection. The combination of marked tumor contrast enhancement and lack of toxicity make these molecules potential candidates for the diagnosis of tumors within the MRI-CEST approach. Copyright © 2017 Elsevier B.V. All rights reserved.

Agent-Based Modeling: A Powerful Tool for Tourism Researchers

NARCIS (Netherlands)

Nicholls, Sarah; Amelung, B.; Student, Jillian

2017-01-01

Agent-based modeling (ABM) is a way of representing complex systems of autonomous agents or actors, and of simulating the multiple potential outcomes of these agents’ behaviors and interactions in the form of a range of alternatives or futures. Despite the complexity of the tourism system, and the

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

Science.gov (United States)

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

2018-03-20

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

Hypercompetitive Environments: An Agent-based model approach

Science.gov (United States)

Dias, Manuel; Araújo, Tanya

Information technology (IT) environments are characterized by complex changes and rapid evolution. Globalization and the spread of technological innovation have increased the need for new strategic information resources, both from individual firms and management environments. Improvements in multidisciplinary methods and, particularly, the availability of powerful computational tools, are giving researchers an increasing opportunity to investigate management environments in their true complex nature. The adoption of a complex systems approach allows for modeling business strategies from a bottom-up perspective — understood as resulting from repeated and local interaction of economic agents — without disregarding the consequences of the business strategies themselves to individual behavior of enterprises, emergence of interaction patterns between firms and management environments. Agent-based models are at the leading approach of this attempt.

A Multi-Agent Traffic Control Model Based on Distributed System

Directory of Open Access Journals (Sweden)

Qian WU

2014-06-01

Full Text Available With the development of urbanization construction, urban travel has become a quite thorny and imminent problem. Some previous researches on the large urban traffic systems easily change into NPC problems. We purpose a multi-agent inductive control model based on the distributed approach. To describe the real traffic scene, this model designs four different types of intelligent agents, i.e. we regard each lane, route, intersection and traffic region as different types of intelligent agents. Each agent can achieve the real-time traffic data from its neighbor agents, and decision-making agents establish real-time traffic signal plans through the communication between local agents and their neighbor agents. To evaluate the traffic system, this paper takes the average delay, the stopped time and the average speed as performance parameters. Finally, the distributed multi-agent is simulated on the VISSIM simulation platform, the simulation results show that the multi-agent system is more effective than the adaptive control system in solving the traffic congestion.

Linking agent-based models and stochastic models of financial markets.

Science.gov (United States)

Feng, Ling; Li, Baowen; Podobnik, Boris; Preis, Tobias; Stanley, H Eugene

2012-05-29

It is well-known that financial asset returns exhibit fat-tailed distributions and long-term memory. These empirical features are the main objectives of modeling efforts using (i) stochastic processes to quantitatively reproduce these features and (ii) agent-based simulations to understand the underlying microscopic interactions. After reviewing selected empirical and theoretical evidence documenting the behavior of traders, we construct an agent-based model to quantitatively demonstrate that "fat" tails in return distributions arise when traders share similar technical trading strategies and decisions. Extending our behavioral model to a stochastic model, we derive and explain a set of quantitative scaling relations of long-term memory from the empirical behavior of individual market participants. Our analysis provides a behavioral interpretation of the long-term memory of absolute and squared price returns: They are directly linked to the way investors evaluate their investments by applying technical strategies at different investment horizons, and this quantitative relationship is in agreement with empirical findings. Our approach provides a possible behavioral explanation for stochastic models for financial systems in general and provides a method to parameterize such models from market data rather than from statistical fitting.

A Computational Agent-Based Modeling Approach for Competitive Wireless Service Market

KAUST Repository

Douglas, C C; Hyoseop Lee,; Wonsuck Lee,

2011-01-01

Using an agent-based modeling method, we study market dynamism with regard to wireless cellular services that are in competition for a greater market share and profit. In the proposed model, service providers and consumers are described as agents

Preparation of 99mTc-Ancitabine as a Possible Tumor Imaging Agent

International Nuclear Information System (INIS)

Ibrahim, I.T.; Attallah, K.M.

2010-01-01

Ancitabine is one of the potent chemotherapeutic anticancer drugs. Tc-Ancitabine ( 99m Tc-ANC) was prepared using stannous chloride as reducing agent, which produced yield above 90% at ph 4 at room temperature within 1-5 min as reaction time. The labeled drug was stable for more than 8 h post labeling. Biodistribution study of 99m Tc-ANC in normal mice reflected that its uptake was increased in organ of high proliferation like stomach. In solid tumor bearing mice 99m Tc-ANC was incorporated rapidly in tumor site and declined slowly, while it was declined rapidly from other tissues. Biodistribution of 99m Tc-ANC in solid tumor presented a possible model for imaging of tumors.

A voxel-based multiscale model to simulate the radiation response of hypoxic tumors.

Science.gov (United States)

Espinoza, I; Peschke, P; Karger, C P

2015-01-01

In radiotherapy, it is important to predict the response of tumors to irradiation prior to the treatment. This is especially important for hypoxic tumors, which are known to be highly radioresistant. Mathematical modeling based on the dose distribution, biological parameters, and medical images may help to improve this prediction and to optimize the treatment plan. A voxel-based multiscale tumor response model for simulating the radiation response of hypoxic tumors was developed. It considers viable and dead tumor cells, capillary and normal cells, as well as the most relevant biological processes such as (i) proliferation of tumor cells, (ii) hypoxia-induced angiogenesis, (iii) spatial exchange of cells leading to tumor growth, (iv) oxygen-dependent cell survival after irradiation, (v) resorption of dead cells, and (vi) spatial exchange of cells leading to tumor shrinkage. Oxygenation is described on a microscopic scale using a previously published tumor oxygenation model, which calculates the oxygen distribution for each voxel using the vascular fraction as the most important input parameter. To demonstrate the capabilities of the model, the dependence of the oxygen distribution on tumor growth and radiation-induced shrinkage is investigated. In addition, the impact of three different reoxygenation processes is compared and tumor control probability (TCP) curves for a squamous cells carcinoma of the head and neck (HNSSC) are simulated under normoxic and hypoxic conditions. The model describes the spatiotemporal behavior of the tumor on three different scales: (i) on the macroscopic scale, it describes tumor growth and shrinkage during radiation treatment, (ii) on a mesoscopic scale, it provides the cell density and vascular fraction for each voxel, and (iii) on the microscopic scale, the oxygen distribution may be obtained in terms of oxygen histograms. With increasing tumor size, the simulated tumors develop a hypoxic core. Within the model, tumor shrinkage was

A voxel-based multiscale model to simulate the radiation response of hypoxic tumors

International Nuclear Information System (INIS)

Espinoza, I.; Peschke, P.; Karger, C. P.

2015-01-01

Purpose: In radiotherapy, it is important to predict the response of tumors to irradiation prior to the treatment. This is especially important for hypoxic tumors, which are known to be highly radioresistant. Mathematical modeling based on the dose distribution, biological parameters, and medical images may help to improve this prediction and to optimize the treatment plan. Methods: A voxel-based multiscale tumor response model for simulating the radiation response of hypoxic tumors was developed. It considers viable and dead tumor cells, capillary and normal cells, as well as the most relevant biological processes such as (i) proliferation of tumor cells, (ii) hypoxia-induced angiogenesis, (iii) spatial exchange of cells leading to tumor growth, (iv) oxygen-dependent cell survival after irradiation, (v) resorption of dead cells, and (vi) spatial exchange of cells leading to tumor shrinkage. Oxygenation is described on a microscopic scale using a previously published tumor oxygenation model, which calculates the oxygen distribution for each voxel using the vascular fraction as the most important input parameter. To demonstrate the capabilities of the model, the dependence of the oxygen distribution on tumor growth and radiation-induced shrinkage is investigated. In addition, the impact of three different reoxygenation processes is compared and tumor control probability (TCP) curves for a squamous cells carcinoma of the head and neck (HNSSC) are simulated under normoxic and hypoxic conditions. Results: The model describes the spatiotemporal behavior of the tumor on three different scales: (i) on the macroscopic scale, it describes tumor growth and shrinkage during radiation treatment, (ii) on a mesoscopic scale, it provides the cell density and vascular fraction for each voxel, and (iii) on the microscopic scale, the oxygen distribution may be obtained in terms of oxygen histograms. With increasing tumor size, the simulated tumors develop a hypoxic core. Within the

Agent-based Modeling Automated: Data-driven Generation of Innovation Diffusion Models

NARCIS (Netherlands)

Jensen, T.; Chappin, E.J.L.

2016-01-01

Simulation modeling is useful to gain insights into driving mechanisms of diffusion of innovations. This study aims to introduce automation to make identification of such mechanisms with agent-based simulation modeling less costly in time and labor. We present a novel automation procedure in which

PEGylated chitosan grafted with polyamidoaminedendron as tumor-targeted magnetic resonance imaging contrast agent

International Nuclear Information System (INIS)

Guangyue Zu; Xiaoyan Tong; Yi Cao; Ye Kuang; Yajie Zhang; Min Liu; Renjun Pei

2017-01-01

Macromolecular contrast agents labeled with targeting ligands are now receiving growing interest in tumor-targeted magnetic resonance imaging. In this study, a macromolecular contrast agent based on PEGylated chitosan was synthesized and characterized, and its application as an MRI contrast agent was then demonstrated both in vitro and in vivo. First, the chitosan backbone was partially grafted with poly(ethylene glycol), which was used to improve the in vivo stability, followed by modifying with azide groups. Second, alkynyl-terminated PAMAM dendron modified with gadolinium diethylenetriaminepentaacetic acid (Gd-DTPA) was synthesized and conjugated onto the chitosan backbone through click chemistry. Finally, the obtained mCA was further functionalized with folic acid to improve the target specificity. The obtained FA labeled mCA exhibited higher relaxivity (9.53 mM"-"1.s"-"1) relative to Gd-DTPA (4.25 mM"-"1.s"-"1) and showed negligible toxicity as determined by the WST assay. In vivo MRI results suggested that a relatively high signal enhancement was observed in the tumor region, which made it a promising candidate for tumor-targeted MRI CA. (authors)

Application of Benchtop-magnetic resonance imaging in a nude mouse tumor model

Directory of Open Access Journals (Sweden)

Mäder Karsten

2011-07-01

Full Text Available Abstract Background MRI plays a key role in the preclinical development of new drugs, diagnostics and their delivery systems. However, very high installation and running costs of existing superconducting MRI machines limit the spread of MRI. The new method of Benchtop-MRI (BT-MRI has the potential to overcome this limitation due to much lower installation and almost no running costs. However, due to the low field strength and decreased magnet homogeneity it is questionable, whether BT-MRI can achieve sufficient image quality to provide useful information for preclinical in vivo studies. It was the aim of the current study to explore the potential of BT-MRI on tumor models in mice. Methods We used a prototype of an in vivo BT-MRI apparatus to visualise organs and tumors and to analyse tumor progression in nude mouse xenograft models of human testicular germ cell tumor and colon carcinoma. Results Subcutaneous xenografts were easily identified as relative hypointense areas in transaxial slices of NMR images. Monitoring of tumor progression evaluated by pixel extension analyses based on NMR images correlated with increasing tumor volume calculated by calliper measurement. Gd-BOPTA contrast agent injection resulted in a better differentiation between parts of the urinary tissues and organs due to fast elimination of the agent via kidneys. In addition, interior structuring of tumors could be observed. A strong contrast enhancement within a tumor was associated with a central necrotic/fibrotic area. Conclusions BT-MRI provides satisfactory image quality to visualize organs and tumors and to monitor tumor progression and structure in mouse models.

Russian and Foreign Experience of Integration of Agent-Based Models and Geographic Information Systems

Directory of Open Access Journals (Sweden)

Konstantin Anatol’evich Gulin

2016-11-01

Full Text Available The article provides an overview of the mechanisms of integration of agent-based models and GIS technology developed by Russian and foreign researchers. The basic framework of the article is based on critical analysis of domestic and foreign literature (monographs, scientific articles. The study is based on the application of universal scientific research methods: system approach, analysis and synthesis, classification, systematization and grouping, generalization and comparison. The article presents theoretical and methodological bases of integration of agent-based models and geographic information systems. The concept and essence of agent-based models are explained; their main advantages (compared to other modeling methods are identified. The paper characterizes the operating environment of agents as a key concept in the theory of agent-based modeling. It is shown that geographic information systems have a wide range of information resources for calculations, searching, modeling of the real world in various aspects, acting as an effective tool for displaying the agents’ operating environment and allowing to bring the model as close as possible to the real conditions. The authors also focus on a wide range of possibilities for various researches in different spatial and temporal contexts. Comparative analysis of platforms supporting the integration of agent-based models and geographic information systems has been carried out. The authors give examples of complex socio-economic models: the model of a creative city, humanitarian assistance model. In the absence of standards for research results description, the authors focus on the models’ elements such as the characteristics of the agents and their operation environment, agents’ behavior, rules of interaction between the agents and the external environment. The paper describes the possibilities and prospects of implementing these models

Can agent based models effectively reduce fisheries management implementation uncertainty?

Science.gov (United States)

Drexler, M.

2016-02-01

Uncertainty is an inherent feature of fisheries management. Implementation uncertainty remains a challenge to quantify often due to unintended responses of users to management interventions. This problem will continue to plague both single species and ecosystem based fisheries management advice unless the mechanisms driving these behaviors are properly understood. Equilibrium models, where each actor in the system is treated as uniform and predictable, are not well suited to forecast the unintended behaviors of individual fishers. Alternatively, agent based models (AMBs) can simulate the behaviors of each individual actor driven by differing incentives and constraints. This study evaluated the feasibility of using AMBs to capture macro scale behaviors of the US West Coast Groundfish fleet. Agent behavior was specified at the vessel level. Agents made daily fishing decisions using knowledge of their own cost structure, catch history, and the histories of catch and quota markets. By adding only a relatively small number of incentives, the model was able to reproduce highly realistic macro patterns of expected outcomes in response to management policies (catch restrictions, MPAs, ITQs) while preserving vessel heterogeneity. These simulations indicate that agent based modeling approaches hold much promise for simulating fisher behaviors and reducing implementation uncertainty. Additional processes affecting behavior, informed by surveys, are continually being added to the fisher behavior model. Further coupling of the fisher behavior model to a spatial ecosystem model will provide a fully integrated social, ecological, and economic model capable of performing management strategy evaluations to properly consider implementation uncertainty in fisheries management.

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

Science.gov (United States)

Chen, Peng; Liu, Miaolong

2007-06-01

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

A murine model of targeted infusion for intracranial tumors.

Science.gov (United States)

Kim, Minhyung; Barone, Tara A; Fedtsova, Natalia; Gleiberman, Anatoli; Wilfong, Chandler D; Alosi, Julie A; Plunkett, Robert J; Gudkov, Andrei; Skitzki, Joseph J

2016-01-01

Historically, intra-arterial (IA) drug administration for malignant brain tumors including glioblastoma multiforme (GBM) was performed as an attempt to improve drug delivery. With the advent of percutaneous neuorovascular techniques and modern microcatheters, intracranial drug delivery is readily feasible; however, the question remains whether IA administration is safe and more effective compared to other delivery modalities such as intravenous (IV) or oral administrations. Preclinical large animal models allow for comparisons between treatment routes and to test novel agents, but can be expensive and difficult to generate large numbers and rapid results. Accordingly, we developed a murine model of IA drug delivery for GBM that is reproducible with clear readouts of tumor response and neurotoxicities. Herein, we describe a novel mouse model of IA drug delivery accessing the internal carotid artery to treat ipsilateral implanted GBM tumors that is consistent and reproducible with minimal experience. The intent of establishing this unique platform is to efficiently interrogate targeted anti-tumor agents that may be designed to take advantage of a directed, regional therapy approach for brain tumors.

Agent-Based Model of Price Competition and Product Differentiation on Congested Networks

OpenAIRE

Lei Zhang; David Levinson; Shanjiang Zhu

2007-01-01

Using consistent agent-based techniques, this research models the decision-making processes of users and infrastructure owner/operators to explore the welfare consequence of price competition, capacity choice, and product differentiation on congested transportation networks. Component models include: (1) An agent-based travel demand model wherein each traveler has learning capabilities and unique characteristics (e.g. value of time); (2) Econometric facility provision cost models; and (3) Rep...

Conceptual Framework for Agent-Based Modeling of Customer-Oriented Supply Networks

OpenAIRE

Solano-Vanegas , Clara ,; Carrillo-Ramos , Angela; Montoya-Torres , Jairo ,

2015-01-01

Part 3: Collaboration Frameworks; International audience; Supply Networks (SN) are complex systems involving the interaction of different actors, very often, with different objectives and goals. Among the different existing modeling approaches, agent-based systems can properly represent the autonomous behavior of SN links and, simultaneously, observe the general response of the system as a result of individual actions. Most of research using agent-based modeling in SN focuses on production is...

Agent-Based Approach for Modelling the Labour Migration from China to Russia

Directory of Open Access Journals (Sweden)

Valeriy Leonidovich Makarov

2017-06-01

Full Text Available The article describes the process of labour migration from China to Russia and shows its modelling using the agent-based approach. This approach allows us to simulate an artificial society in a computer program taking into account the diversity of individuals under consideration, as well as to model a set of laws and rules of conduct that make up the institutional environment in which the members of this society live. A brief review and analysis of agent-based migration models presented in the foreign literature are given. The agent-based model of labour migration from China to Russia developed by the Central Economic Mathematical Institute of the Russian Academy of Sciences simulates human behaviour close to reality, which is based on their internal purposes, determining the agents choice of territory as a place of residence. Therefore, at the development of the agents of the model and their behaviour algorithms, as well as the organization of the environment in which they exist and interact, the main characteristics of the population of two neighbouring countries and their demographic processes have been considered. Using the model, two experiments have been conducted. The purpose of the first of them was to assess the effect of depreciation of the rubble against the yuan on the overall indexes of labour migration, as well as its structure. In the second experiment, the procedure of the search of the information by agents for the migratory decision-making was changing. Namely, all generalizing information on the average salary by types of activity and skill level of employees, both in China and Russia, became available to all agents irrespective of their qualification level.

An Agent Based Collaborative Simplification of 3D Mesh Model

Science.gov (United States)

Wang, Li-Rong; Yu, Bo; Hagiwara, Ichiro

Large-volume mesh model faces the challenge in fast rendering and transmission by Internet. The current mesh models obtained by using three-dimensional (3D) scanning technology are usually very large in data volume. This paper develops a mobile agent based collaborative environment on the development platform of mobile-C. Communication among distributed agents includes grasping image of visualized mesh model, annotation to grasped image and instant message. Remote and collaborative simplification can be efficiently conducted by Internet.

Agent Based Modeling as an Educational Tool

Science.gov (United States)

Fuller, J. H.; Johnson, R.; Castillo, V.

2012-12-01

Motivation is a key element in high school education. One way to improve motivation and provide content, while helping address critical thinking and problem solving skills, is to have students build and study agent based models in the classroom. This activity visually connects concepts with their applied mathematical representation. "Engaging students in constructing models may provide a bridge between frequently disconnected conceptual and mathematical forms of knowledge." (Levy and Wilensky, 2011) We wanted to discover the feasibility of implementing a model based curriculum in the classroom given current and anticipated core and content standards.; Simulation using California GIS data ; Simulation of high school student lunch popularity using aerial photograph on top of terrain value map.

WE-H-BRA-03: Development of a Model to Include the Evolution of Resistant Tumor Subpopulations Into the Treatment Optimization Process for Schedules Involving Targeted Agents in Chemoradiation Therapy

International Nuclear Information System (INIS)

Grassberger, C; Paganetti, H

2016-01-01

Purpose: To develop a model that includes the process of resistance development into the treatment optimization process for schedules that include targeted therapies. Further, to validate the approach using clinical data and to apply the model to assess the optimal induction period with targeted agents before curative treatment with chemo-radiation in stage III lung cancer. Methods: Growth of the tumor and its subpopulations is modeled by Gompertzian growth dynamics, resistance induction as a stochastic process. Chemotherapy induced cell kill is modeled by log-cell kill dynamics, targeted agents similarly but restricted to the sensitive population. Radiation induced cell kill is assumed to follow the linear-quadratic model. The validation patient data consist of a cohort of lung cancer patients treated with tyrosine kinase inhibitors that had longitudinal imaging data available. Results: The resistance induction model was successfully validated using clinical trial data from 49 patients treated with targeted agents. The observed recurrence kinetics, with tumors progressing from 1.4–63 months, result in tumor growth equaling a median volume doubling time of 92 days [34–248] and a median fraction of pre-existing resistance of 0.035 [0–0.22], in agreement with previous clinical studies. The model revealed widely varying optimal time points for the use of curative therapy, reaching from ∼1m to >6m depending on the patient’s growth rate and amount of pre-existing resistance. This demonstrates the importance of patient-specific treatment schedules when targeted agents are incorporated into the treatment. Conclusion: We developed a model including evolutionary dynamics of resistant sub-populations with traditional chemotherapy and radiation cell kill models. Fitting to clinical data yielded patient specific growth rates and resistant fraction in agreement with previous studies. Further application of the model demonstrated how proper timing of chemo

WE-H-BRA-03: Development of a Model to Include the Evolution of Resistant Tumor Subpopulations Into the Treatment Optimization Process for Schedules Involving Targeted Agents in Chemoradiation Therapy

Energy Technology Data Exchange (ETDEWEB)

Grassberger, C; Paganetti, H [Massachusetts General Hospital, Boston, MA (United States)

2016-06-15

Purpose: To develop a model that includes the process of resistance development into the treatment optimization process for schedules that include targeted therapies. Further, to validate the approach using clinical data and to apply the model to assess the optimal induction period with targeted agents before curative treatment with chemo-radiation in stage III lung cancer. Methods: Growth of the tumor and its subpopulations is modeled by Gompertzian growth dynamics, resistance induction as a stochastic process. Chemotherapy induced cell kill is modeled by log-cell kill dynamics, targeted agents similarly but restricted to the sensitive population. Radiation induced cell kill is assumed to follow the linear-quadratic model. The validation patient data consist of a cohort of lung cancer patients treated with tyrosine kinase inhibitors that had longitudinal imaging data available. Results: The resistance induction model was successfully validated using clinical trial data from 49 patients treated with targeted agents. The observed recurrence kinetics, with tumors progressing from 1.4–63 months, result in tumor growth equaling a median volume doubling time of 92 days [34–248] and a median fraction of pre-existing resistance of 0.035 [0–0.22], in agreement with previous clinical studies. The model revealed widely varying optimal time points for the use of curative therapy, reaching from ∼1m to >6m depending on the patient’s growth rate and amount of pre-existing resistance. This demonstrates the importance of patient-specific treatment schedules when targeted agents are incorporated into the treatment. Conclusion: We developed a model including evolutionary dynamics of resistant sub-populations with traditional chemotherapy and radiation cell kill models. Fitting to clinical data yielded patient specific growth rates and resistant fraction in agreement with previous studies. Further application of the model demonstrated how proper timing of chemo

An Agent-Based Dynamic Model of Politics, Fertility and Economic Development

Directory of Open Access Journals (Sweden)

Zining Yang

2016-08-01

Full Text Available In the political economy of development, government policy choices at a single point in time can dramatically affect a country's development path by impacting fertility, economic and political decisions across generations. Combining system dynamics and agent-based modeling approaches in a complex adaptive system, a simulation framework of the Politics of Fertility and Economic Development (POFED is formalized to understand the relationship between politics, economic, and demography change at both macro and micro levels. First, a new political capacity measurement is used; and the system dynamics model is validated with the latest data. Second, the endogenous attributes are fused with non-cooperative game theory in an agent-based framework to simulate the interactive political economic dynamics of individual intra-societal transactions. Finally, macro and micro levels are connected with policy levers of political capacity and political instability by merging system dynamics and agent-based components. This paper also explores the agent-based model's behavioral dynamics via simulation methods to identify paths towards economic development and political stability. This model demonstrates micro level human agency can act, react and interact, thus driving macro level dynamics, while macro structures provide political, social and economic environments that constrain or incentivize micro level human behavior.

Calibrating emergent phenomena in stock markets with agent based models.

Science.gov (United States)

Fievet, Lucas; Sornette, Didier

2018-01-01

Since the 2008 financial crisis, agent-based models (ABMs), which account for out-of-equilibrium dynamics, heterogeneous preferences, time horizons and strategies, have often been envisioned as the new frontier that could revolutionise and displace the more standard models and tools in economics. However, their adoption and generalisation is drastically hindered by the absence of general reliable operational calibration methods. Here, we start with a different calibration angle that qualifies an ABM for its ability to achieve abnormal trading performance with respect to the buy-and-hold strategy when fed with real financial data. Starting from the common definition of standard minority and majority agents with binary strategies, we prove their equivalence to optimal decision trees. This efficient representation allows us to exhaustively test all meaningful single agent models for their potential anomalous investment performance, which we apply to the NASDAQ Composite index over the last 20 years. We uncover large significant predictive power, with anomalous Sharpe ratio and directional accuracy, in particular during the dotcom bubble and crash and the 2008 financial crisis. A principal component analysis reveals transient convergence between the anomalous minority and majority models. A novel combination of the optimal single-agent models of both classes into a two-agents model leads to remarkable superior investment performance, especially during the periods of bubbles and crashes. Our design opens the field of ABMs to construct novel types of advanced warning systems of market crises, based on the emergent collective intelligence of ABMs built on carefully designed optimal decision trees that can be reversed engineered from real financial data.

Calibrating emergent phenomena in stock markets with agent based models

Science.gov (United States)

Sornette, Didier

2018-01-01

Since the 2008 financial crisis, agent-based models (ABMs), which account for out-of-equilibrium dynamics, heterogeneous preferences, time horizons and strategies, have often been envisioned as the new frontier that could revolutionise and displace the more standard models and tools in economics. However, their adoption and generalisation is drastically hindered by the absence of general reliable operational calibration methods. Here, we start with a different calibration angle that qualifies an ABM for its ability to achieve abnormal trading performance with respect to the buy-and-hold strategy when fed with real financial data. Starting from the common definition of standard minority and majority agents with binary strategies, we prove their equivalence to optimal decision trees. This efficient representation allows us to exhaustively test all meaningful single agent models for their potential anomalous investment performance, which we apply to the NASDAQ Composite index over the last 20 years. We uncover large significant predictive power, with anomalous Sharpe ratio and directional accuracy, in particular during the dotcom bubble and crash and the 2008 financial crisis. A principal component analysis reveals transient convergence between the anomalous minority and majority models. A novel combination of the optimal single-agent models of both classes into a two-agents model leads to remarkable superior investment performance, especially during the periods of bubbles and crashes. Our design opens the field of ABMs to construct novel types of advanced warning systems of market crises, based on the emergent collective intelligence of ABMs built on carefully designed optimal decision trees that can be reversed engineered from real financial data. PMID:29499049

An agent-based information management model of the Chinese pig sector

NARCIS (Netherlands)

Osinga, S.A.; Kramer, M.R.; Hofstede, G.J.; Roozmand, O.; Beulens, A.J.M.

2010-01-01

This paper investigates the effect of a selected top-down measure (what-if scenario) on actual agent behaviour and total system behaviour by means of an agent-based simulation model, when agents’ behaviour cannot fully be managed because the agents are autonomous. The Chinese pork sector serves as

Experimental study of 99Tcm-tri-peptide as a novel tumor imaging agent

International Nuclear Information System (INIS)

Xie Wenhui; Cai Xiaojia; Liu Ciyi; Zeng Jun; Zhang Lihua; Lei Bei; Huang Gang

2011-01-01

Objective: To evaluate 99 Tc m -Arg-Glu-Ser ( 99 Tc m -RES) as a potential tumor imaging agent. Methods: RES was synthesized using solid phase peptide synthesis. The optimal labeling conditions of RES were determined under different reagents and reacting temperatures using SnC1 2 as reducing agent.The biodistribution of 99 Tc m -RES was studied in nude mice bearing human lung cancer A549. Results: The radiochemical purity of 99 Tc m -RES was up to 85% and the radiochemical purity was 75% ever after 6 h at room temperature. The tumor uptake of 99 Tc m -RES was obvious and the radioactivity ratios of tumor/blood, tumor/heart, tumor/liver, tumor/lung, tumor/spleen and tumor/muscle were 5.31, 1.88, 1.57, 3.58, 4.16 and 5.92, respectively at 6 h after 99 Tc m -RES injection. Gamma camera imaging showed that tumor uptake of 99 Tc m -RES was negative in rabbits with inflammatory mass but positive in those bearing tumor. The radioactivity ratio of tumor/inflammation was 3.12 at 6 h after injection. Conclusion: 99 Tc m -RES might possibly become a potential tumor imaging agent. (authors)

A standard protocol for describing individual-based and agent-based models

Science.gov (United States)

Grimm, Volker; Berger, Uta; Bastiansen, Finn; Eliassen, Sigrunn; Ginot, Vincent; Giske, Jarl; Goss-Custard, John; Grand, Tamara; Heinz, Simone K.; Huse, Geir; Huth, Andreas; Jepsen, Jane U.; Jorgensen, Christian; Mooij, Wolf M.; Muller, Birgit; Pe'er, Guy; Piou, Cyril; Railsback, Steven F.; Robbins, Andrew M.; Robbins, Martha M.; Rossmanith, Eva; Ruger, Nadja; Strand, Espen; Souissi, Sami; Stillman, Richard A.; Vabo, Rune; Visser, Ute; DeAngelis, Donald L.

2006-01-01

Simulation models that describe autonomous individual organisms (individual based models, IBM) or agents (agent-based models, ABM) have become a widely used tool, not only in ecology, but also in many other disciplines dealing with complex systems made up of autonomous entities. However, there is no standard protocol for describing such simulation models, which can make them difficult to understand and to duplicate. This paper presents a proposed standard protocol, ODD, for describing IBMs and ABMs, developed and tested by 28 modellers who cover a wide range of fields within ecology. This protocol consists of three blocks (Overview, Design concepts, and Details), which are subdivided into seven elements: Purpose, State variables and scales, Process overview and scheduling, Design concepts, Initialization, Input, and Submodels. We explain which aspects of a model should be described in each element, and we present an example to illustrate the protocol in use. In addition, 19 examples are available in an Online Appendix. We consider ODD as a first step for establishing a more detailed common format of the description of IBMs and ABMs. Once initiated, the protocol will hopefully evolve as it becomes used by a sufficiently large proportion of modellers.

Synthesis and evaluation of {sup 99m}Tc-labeled folate-tripeptide conjugate as a folate receptor-targeeted imaging agent in a tumor-bearing mouse model

Energy Technology Data Exchange (ETDEWEB)

Kim, Myoung Hyoun; Kim, Chang Guhn; Kim, Dae Weung [Dept. of Nuclear Medicine, Wonkwang University School of Medicine, Iksan (Korea, Republic of); Kim, Woo Hyoung [Dept. of Nuclear Medicine, Seoul National University Hospital, Seoul (Korea, Republic of)

2015-09-15

The folate receptor (FR) is an attractive molecular target since it is overexpressed in a variety of human tumors. The purpose of the present study was to synthesize and evaluate the feasibility of a novel {sup 99m}Tc-ECG-EDA (Glu-Cys-Gly-ethylenediamine)-folate as an FR-positive tumor imaging agent in a mouse tumor model. ECG-EDA-folate was synthesized using solid phase peptide synthesis (SPPS) and radiolabeled with {sup 99m}Tc using tripeptide ECG as a chelator. FR-positive KB cells were inoculated in athymic nude mice. Following injection of {sup 99m}Tc-ECG-EDA-folate, serial scintigraphy and micro-SPECT/CT imaging were performed at various time points with and without pre-administration of excess free folate. Mean count densities (MCD) for regions of interest drawn on KB tumors and major normal organs at each time point were measured, and uptake ratios of tumor to normal organs were calculated. ECG-EDA-folate was labeled with {sup 99m}Tc with high radiolabeling efficiency and stability (>96 %). FR-positive tumors were clearly visualized on both scintigraphy and micro-SPECT/CT images and the tumor uptake of {sup 99m}Tc-ECG-EDA-folate was markedly suppressed with faint visualization of tumors by pre-administration of excess free folate on serial planar scintigraphy, indicating FR-specific binding of the agent. Furthermore, semiquantitative analysis of MCD data showed again that both tumor MCD and tumor-to-normal organ ratios decreased considerably by pre-administration of excess free folate, supporting FR-specific tumor uptake. Tumor-to-normal organ ratios approximately increased with time after injection until 4 h. The present study demonstrated that 9{sup 99m}Tc-ECG-EDA-folate can bind specifically to FR with clear visualization of FR-positive tumors in a mouse tumor model.

An Agent Based Modelling Approach for Multi-Stakeholder Analysis of City Logistics Solutions

NARCIS (Netherlands)

Anand, N.

2015-01-01

This thesis presents a comprehensive framework for multi-stakeholder analysis of city logistics solutions using agent based modeling. The framework describes different stages for the systematic development of an agent based model for the city logistics domain. The framework includes a

Agent-based modelling of consumer energy choices

Science.gov (United States)

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.

Using Agent-Based Models in the Analysis and Forecast of Socio-Economic Development of Territories

Directory of Open Access Journals (Sweden)

Vitalii Nikolaevich Makoveev

2016-11-01

Full Text Available The purpose of the paper is to study the essence of agent-based modeling, defining its features and prospects of usage in the modeling of socio-economic development of territories and systematization of domestic and foreign approaches to the development of prototypes for agent-based models of territories. Information basis for the research comprised the works on agent-based modeling by Russian and foreign scholars, especially articles and monographs of scientists of the Central Economics and Mathematics Institute under the Russian Academy of Sciences, papers presented in an international journal The Journal of Artificial Societies and Social Simulation and other sources available on the Internet. The article presents theoretical and methodological foundations of agent-based models of territories. The author considers the concepts of “agent-based modeling” and “agent” and defines specifics of agent-based models in comparison with other types of simulation modeling. The paper also describes major stages of building agent-based models for territories and considers qualification requirements to a modeling subject. Furthermore, it reviews Russian and foreign approaches to the development of prototypes for agent-based models of territories. It has been determined that most of them deal with the modeling of spatial, territorial and socio-economic development of regions, cities and municipal entities. Agents in such models are presented by households, residents of regions and cities, enterprises and organizations operating in their territory, and public administration authorities (their inclusion in the model makes it possible to test different options of management impacts on territories by changing the model parameters, for instance, the introduction of certain prohibitions and quotas, issuance of permits, distribution of financial resources, etc.. At the end of the paper, the author formulates major conclusions. He shows the complexity faced

Agent Based Modelling for Social Simulation

OpenAIRE

Smit, S.K.; Ubink, E.M.; Vecht, B. van der; Langley, D.J.

2013-01-01

This document is the result of an exploratory project looking into the status of, and opportunities for Agent Based Modelling (ABM) at TNO. The project focussed on ABM applications containing social interactions and human factors, which we termed ABM for social simulation (ABM4SS). During the course of this project two workshops were organized. At these workshops, a wide range of experts, both ABM experts and domain experts, worked on several potential applications of ABM. The results and ins...

Nanodiamond-Manganese dual mode MRI contrast agents for enhanced liver tumor detection.

Science.gov (United States)

Hou, Weixin; Toh, Tan Boon; Abdullah, Lissa Nurrul; Yvonne, Tay Wei Zheng; Lee, Kuan J; Guenther, Ilonka; Chow, Edward Kai-Hua

2017-04-01

Contrast agent-enhanced magnetic resonance (MR) imaging is critical for the diagnosis and monitoring of a number of diseases, including cancer. Certain clinical applications, including the detection of liver tumors, rely on both T1 and T2-weighted images even though contrast agent-enhanced MR imaging is not always reliable. Thus, there is a need for improved dual mode contrast agents with enhanced sensitivity. We report the development of a nanodiamond-manganese dual mode contrast agent that enhanced both T1 and T2-weighted MR imaging. Conjugation of manganese to nanodiamonds resulted in improved longitudinal and transverse relaxivity efficacy over unmodified MnCl 2 as well as clinical contrast agents. Following intravenous administration, nanodiamond-manganese complexes outperformed current clinical contrast agents in an orthotopic liver cancer mouse model while also reducing blood serum concentration of toxic free Mn 2+ ions. Thus, nanodiamond-manganese complexes may serve as more effective dual mode MRI contrast agent, particularly in cancer. Copyright © 2016 Elsevier Inc. All rights reserved.

A critical survey of agent-based wholesale electricity market models

International Nuclear Information System (INIS)

Weidlich, Anke; Veit, Daniel

2008-01-01

The complexity of electricity markets calls for rich and flexible modeling techniques that help to understand market dynamics and to derive advice for the design of appropriate regulatory frameworks. Agent-Based Computational Economics (ACE) is a fairly young research paradigm that offers methods for realistic electricity market modeling. A growing number of researchers have developed agent-based models for simulating electricity markets. The diversity of approaches makes it difficult to overview the field of ACE electricity research; this literature survey should guide the way through and describe the state-of-the-art of this research area. In a conclusive summary, shortcomings of existing approaches and open issues that should be addressed by ACE electricity researchers are critically discussed. (author)

A Systematic Review of Agent-Based Modelling and Simulation Applications in the Higher Education Domain

Science.gov (United States)

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).…

Quantitative Molecular Imaging with a Single Gd-Based Contrast Agent Reveals Specific Tumor Binding and Retention in Vivo.

Science.gov (United States)

Johansen, Mette L; Gao, Ying; Hutnick, Melanie A; Craig, Sonya E L; Pokorski, Jonathan K; Flask, Chris A; Brady-Kalnay, Susann M

2017-06-06

Magnetic resonance imaging (MRI) has become an indispensable tool in the diagnosis and treatment of many diseases, especially cancer. However, the poor sensitivity of MRI relative to other imaging modalities, such as PET, has hindered the development and clinical use of molecular MRI contrast agents that could provide vital diagnostic information by specifically locating a molecular target altered in the disease process. This work describes the specific and sustained in vivo binding and retention of a protein tyrosine phosphatase mu (PTPμ)-targeted, molecular magnetic resonance (MR) contrast agent with a single gadolinium (Gd) chelate using a quantitative MRI T 1 mapping technique in glioma xenografts. Quantitative T 1 mapping is an imaging method used to measure the longitudinal relaxation time, the T 1 relaxation time, of protons in a magnetic field after excitation by a radiofrequency pulse. T 1 relaxation times can in turn be used to calculate the concentration of a gadolinium-containing contrast agent in a region of interest, thereby allowing the retention or clearance of an agent to be quantified. In this context, retention is a measure of molecular contrast agent binding. Using conventional peptide chemistry, a PTPμ-targeted peptide was linked to a chelator that had been conjugated to a lysine residue. Following complexation with Gd, this PTPμ-targeted molecular contrast agent containing a single Gd ion showed significant tumor enhancement and a sustained increase in Gd concentration in both heterotopic and orthotopic tumors using dynamic quantitative MRI. This single Gd-containing PTPμ agent was more effective than our previous version with three Gd ions. Differences between nonspecific and specific agents, due to specific tumor binding, can be determined within the first 30 min after agent administration by examining clearance rates. This more facile chemistry, when combined with quantitative MR techniques, allows for widespread adoption by academic

iCrowd: agent-based behavior modeling and crowd simulator

Science.gov (United States)

Kountouriotis, Vassilios I.; Paterakis, Manolis; Thomopoulos, Stelios C. A.

2016-05-01

Initially designed in the context of the TASS (Total Airport Security System) FP-7 project, the Crowd Simulation platform developed by the Integrated Systems Lab of the Institute of Informatics and Telecommunications at N.C.S.R. Demokritos, has evolved into a complete domain-independent agent-based behavior simulator with an emphasis on crowd behavior and building evacuation simulation. Under continuous development, it reflects an effort to implement a modern, multithreaded, data-oriented simulation engine employing latest state-of-the-art programming technologies and paradigms. It is based on an extensible architecture that separates core services from the individual layers of agent behavior, offering a concrete simulation kernel designed for high-performance and stability. Its primary goal is to deliver an abstract platform to facilitate implementation of several Agent-Based Simulation solutions with applicability in several domains of knowledge, such as: (i) Crowd behavior simulation during [in/out] door evacuation. (ii) Non-Player Character AI for Game-oriented applications and Gamification activities. (iii) Vessel traffic modeling and simulation for Maritime Security and Surveillance applications. (iv) Urban and Highway Traffic and Transportation Simulations. (v) Social Behavior Simulation and Modeling.

Comparative Evaluation of Using NOTA and DOTA Derivatives as Bifunctional Chelating Agents in the Preparation of 68Ga-Labeled Porphyrin: Impact on Pharmacokinetics and Tumor Uptake in a Mouse Model.

Science.gov (United States)

Guleria, Mohini; Das, Tapas; Amirdhanayagam, Jeyachitra; Sarma, Haladhar D; Dash, Ashutosh

2018-02-01

Both NOTA (1,4,7-triazacyclononane-1,4,7-triacetic acid) and DOTA (1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid) derivatives have been used as bifunctional chelating agents (BFCAs) for the preparation of 68 Ga-labeled target-specific agents having potential for positron emission tomography (PET) imaging of cancerous lesions. In the present work, the authors have attempted a comparative pharmacokinetic evaluation between 68 Ga-labeled porphyrins prepared using NOTA and DOTA derivatives as the BFCAs. A symmetrical porphyrin derivative, 5,10,15,20-tetrakis(p-carboxymethyleneoxyphenyl)porphyrin, was synthesized and coupled with two different BFCAs viz. p-NH 2 -benzyl-NOTA and p-NH 2 -benzyl-DOTA. Both the porphyrin-BFCA conjugates were radiolabeled with 68 Ga. A comparative bioevaluation involving pharmacokinetics and tumor affinity was performed in a tumor-bearing small animal model. Gallium-68-labeled porphyrin-amido-benzyl-NOTA and porphyrin-amido-benzyl-DOTA complexes were prepared with high radiochemical purity. Both radiolabeled complexes exhibited almost similar stability in human serum and near-identical tumor affinity and pharmacokinetic behavior in animal studies. The present study demonstrates that the pharmacokinetic behavior of 68 Ga-labeled porphyrin derivatives, prepared using either NOTA or DOTA derivatives as BFCAs, remains almost identical and hence both NOTA and DOTA derivatives could be considered equivalent for developing 68 Ga-based PET agents for imaging of tumorous lesions.

A Collective Case Study of Secondary Students' Model-Based Inquiry on Natural Selection through Programming in an Agent-Based Modeling Environment

Science.gov (United States)

Xiang, Lin

2011-01-01

This is a collective case study seeking to develop detailed descriptions of how programming an agent-based simulation influences a group of 8th grade students' model-based inquiry (MBI) by examining students' agent-based programmable modeling (ABPM) processes and the learning outcomes. The context of the present study was a biology unit on…

Efficacy of continuous treatment with radiation in a rat brain-tumor model

International Nuclear Information System (INIS)

Wheeler, K.T.; Kaufman, K.

1981-01-01

Rats bearing intracerebral 9L/Ro tumors were treated with 10 daily fractions of cesium-137 gamma-rays, BCNU, or combinations of these to agents beginning on either Day 10 or Day 12 after implantation. The treatments were administered either 5 days/week for 2 weeks, with the weekend off, or 10 consecutive days. The median day of death for untreated tumor-bearing rats was Day 15, so Day 12 tumors can be considered late tumors and Day 10 tumors can be considered moderately early. Although all single- and multiple-agent treatments significantly (p less than 0.05) increased the lifespan of tumor-bearing rats over that of the untreated controls, and all multiple-agent schedules significantly (p less than 0.05) increased the lifespan over that of the single-agent therapies, none of the 10 consecutive day schedules increased the lifespan of tumor-bearing rats significantly (p less than 0.2) over that obtained with the 5-day/week schedules. Thus, the evidence from this tumor model suggests that no significant improvement in lifespan would be expected if malignant brain tumors were treated with radiation 7 days a week, either alone or in combination with chemotherapeutic agents such as BCNU

A new ODE tumor growth modeling based on tumor population dynamics

Energy Technology Data Exchange (ETDEWEB)

Oroji, Amin; Omar, Mohd bin [Institute of Mathematical Sciences, Faculty of Science University of Malaya, 50603 Kuala Lumpur, Malaysia amin.oroji@siswa.um.edu.my, mohd@um.edu.my (Malaysia); Yarahmadian, Shantia [Mathematics Department Mississippi State University, USA Syarahmadian@math.msstate.edu (United States)

2015-10-22

In this paper a new mathematical model for the population of tumor growth treated by radiation is proposed. The cells dynamics population in each state and the dynamics of whole tumor population are studied. Furthermore, a new definition of tumor lifespan is presented. Finally, the effects of two main parameters, treatment parameter (q), and repair mechanism parameter (r) on tumor lifespan are probed, and it is showed that the change in treatment parameter (q) highly affects the tumor lifespan.

A new ODE tumor growth modeling based on tumor population dynamics

International Nuclear Information System (INIS)

Oroji, Amin; Omar, Mohd bin; Yarahmadian, Shantia

2015-01-01

In this paper a new mathematical model for the population of tumor growth treated by radiation is proposed. The cells dynamics population in each state and the dynamics of whole tumor population are studied. Furthermore, a new definition of tumor lifespan is presented. Finally, the effects of two main parameters, treatment parameter (q), and repair mechanism parameter (r) on tumor lifespan are probed, and it is showed that the change in treatment parameter (q) highly affects the tumor lifespan

Geometry of behavioral spaces: A computational approach to analysis and understanding of agent based models and agent behaviors

Science.gov (United States)

Cenek, Martin; Dahl, Spencer K.

2016-11-01

Systems with non-linear dynamics frequently exhibit emergent system behavior, which is important to find and specify rigorously to understand the nature of the modeled phenomena. Through this analysis, it is possible to characterize phenomena such as how systems assemble or dissipate and what behaviors lead to specific final system configurations. Agent Based Modeling (ABM) is one of the modeling techniques used to study the interaction dynamics between a system's agents and its environment. Although the methodology of ABM construction is well understood and practiced, there are no computational, statistically rigorous, comprehensive tools to evaluate an ABM's execution. Often, a human has to observe an ABM's execution in order to analyze how the ABM functions, identify the emergent processes in the agent's behavior, or study a parameter's effect on the system-wide behavior. This paper introduces a new statistically based framework to automatically analyze agents' behavior, identify common system-wide patterns, and record the probability of agents changing their behavior from one pattern of behavior to another. We use network based techniques to analyze the landscape of common behaviors in an ABM's execution. Finally, we test the proposed framework with a series of experiments featuring increasingly emergent behavior. The proposed framework will allow computational comparison of ABM executions, exploration of a model's parameter configuration space, and identification of the behavioral building blocks in a model's dynamics.

Agent based modeling of energy networks

International Nuclear Information System (INIS)

Gonzalez de Durana, José María; Barambones, Oscar; Kremers, Enrique; Varga, Liz

2014-01-01

Highlights: • A new approach for energy network modeling is designed and tested. • The agent-based approach is general and no technology dependent. • The models can be easily extended. • The range of applications encompasses from small to large energy infrastructures. - Abstract: Attempts to model any present or future power grid face a huge challenge because a power grid is a complex system, with feedback and multi-agent behaviors, integrated by generation, distribution, storage and consumption systems, using various control and automation computing systems to manage electricity flows. Our approach to modeling is to build upon an established model of the low voltage electricity network which is tested and proven, by extending it to a generalized energy model. But, in order to address the crucial issues of energy efficiency, additional processes like energy conversion and storage, and further energy carriers, such as gas, heat, etc., besides the traditional electrical one, must be considered. Therefore a more powerful model, provided with enhanced nodes or conversion points, able to deal with multidimensional flows, is being required. This article addresses the issue of modeling a local multi-carrier energy network. This problem can be considered as an extension of modeling a low voltage distribution network located at some urban or rural geographic area. But instead of using an external power flow analysis package to do the power flow calculations, as used in electric networks, in this work we integrate a multiagent algorithm to perform the task, in a concurrent way to the other simulation tasks, and not only for the electric fluid but also for a number of additional energy carriers. As the model is mainly focused in system operation, generation and load models are not developed

Image-based modeling of tumor shrinkage in head and neck radiation therapy

International Nuclear Information System (INIS)

Chao Ming; Xie Yaoqin; Moros, Eduardo G.; Le, Quynh-Thu; Xing Lei

2010-01-01

Purpose: Understanding the kinetics of tumor growth/shrinkage represents a critical step in quantitative assessment of therapeutics and realization of adaptive radiation therapy. This article presents a novel framework for image-based modeling of tumor change and demonstrates its performance with synthetic images and clinical cases. Methods: Due to significant tumor tissue content changes, similarity-based models are not suitable for describing the process of tumor volume changes. Under the hypothesis that tissue features in a tumor volume or at the boundary region are partially preserved, the kinetic change was modeled in two steps: (1) Autodetection of homologous tissue features shared by two input images using the scale invariance feature transformation (SIFT) method; and (2) establishment of a voxel-to-voxel correspondence between the images for the remaining spatial points by interpolation. The correctness of the tissue feature correspondence was assured by a bidirectional association procedure, where SIFT features were mapped from template to target images and reversely. A series of digital phantom experiments and five head and neck clinical cases were used to assess the performance of the proposed technique. Results: The proposed technique can faithfully identify the known changes introduced when constructing the digital phantoms. The subsequent feature-guided thin plate spline calculation reproduced the ''ground truth'' with accuracy better than 1.5 mm. For the clinical cases, the new algorithm worked reliably for a volume change as large as 30%. Conclusions: An image-based tumor kinetic algorithm was developed to model the tumor response to radiation therapy. The technique provides a practical framework for future application in adaptive radiation therapy.

Agent-based modeling of the energy network for hybrid cars

International Nuclear Information System (INIS)

Gonzalez de Durana, José María; Barambones, Oscar; Kremers, Enrique; Varga, Liz

2015-01-01

Highlights: • An approach to represent and calculate multicarrier energy networks has been developed. • It provides a modeling method based on agents, for multicarrier energy networks. • It allows the system representation on a single sheet. • Energy flows circulating in the system can be observed dynamically during simulation. • The method is technology independent. - Abstract: Studies in complex energy networks devoted to the modeling of electrical power grids, were extended in previous work, where a computational multi-layered ontology, implemented using agent-based methods, was adopted. This structure is compatible with recently introduced Multiplex Networks which using Multi-linear Algebra generalize some of classical results for single-layer networks, to multilayer networks in steady state. Static results do not assist overly in understanding dynamic networks in which the values of the variables in the nodes and edges can change suddenly, driven by events, and even where new nodes or edges may appear or disappear, also because of other events. To address this gap, a computational agent-based model is developed to extend the multi-layer and multiplex approaches. In order to demonstrate the benefits of a dynamical extension, a model of the energy network in a hybrid car is presented as a case study

Brief introductory guide to agent-based modeling and an illustration from urban health research

Directory of Open Access Journals (Sweden)

Amy H. Auchincloss

2015-11-01

Full Text Available Abstract There is growing interest among urban health researchers in addressing complex problems using conceptual and computation models from the field of complex systems. Agent-based modeling (ABM is one computational modeling tool that has received a lot of interest. However, many researchers remain unfamiliar with developing and carrying out an ABM, hindering the understanding and application of it. This paper first presents a brief introductory guide to carrying out a simple agent-based model. Then, the method is illustrated by discussing a previously developed agent-based model, which explored inequalities in diet in the context of urban residential segregation.

Brief introductory guide to agent-based modeling and an illustration from urban health research.

Science.gov (United States)

Auchincloss, Amy H; Garcia, Leandro Martin Totaro

2015-11-01

There is growing interest among urban health researchers in addressing complex problems using conceptual and computation models from the field of complex systems. Agent-based modeling (ABM) is one computational modeling tool that has received a lot of interest. However, many researchers remain unfamiliar with developing and carrying out an ABM, hindering the understanding and application of it. This paper first presents a brief introductory guide to carrying out a simple agent-based model. Then, the method is illustrated by discussing a previously developed agent-based model, which explored inequalities in diet in the context of urban residential segregation.

An MRI Method To Map Tumor Hypoxia Using Red Blood Cells Loaded with a pO2-Responsive Gd-Agent.

Science.gov (United States)

Di Gregorio, Enza; Ferrauto, Giuseppe; Gianolio, Eliana; Lanzardo, Stefania; Carrera, Carla; Fedeli, Franco; Aime, Silvio

2015-08-25

Hypoxia is a typical hallmark of many solid tumors and often leads to therapy resistance and the development of a more aggressive cancer phenotype. Oxygen content in tissues has been evaluated using numerous different methods for several imaging modalities, but none has yet reached the required standard of spatial and temporal resolution. Magnetic Resonance Imaging (MRI) appears to be the technique of choice and several pO2-responsive probes have been designed for it over the years. In vivo translation is often hampered in Gd-relaxation agents as it is not possible to separate effects that arise from changes in local concentration from those associated with responsive properties. A novel procedure for the MRI based assessment of hypoxia is reported herein. The method relies on the combined use of Gd-DOTP- and Gd-HPDO3A-labeled red blood cells (RBCs) where the first probe acts as a vascular oxygenation-responsive agent, while the second reports the local labeled RBC concentration in a transplanted breast tumor mouse model. The MRI assessment of oxygenation state has been validated by photoacoustic imaging and ex vivo immunofluorescence. The method refines tumor staging in preclinical models and makes possible an accurate monitoring of the relationship between oxygenation and tumor growth.

An Agent-Based Model for Studying Child Maltreatment and Child Maltreatment Prevention

Science.gov (United States)

Hu, Xiaolin; Puddy, Richard W.

This paper presents an agent-based model that simulates the dynamics of child maltreatment and child maltreatment prevention. The developed model follows the principles of complex systems science and explicitly models a community and its families with multi-level factors and interconnections across the social ecology. This makes it possible to experiment how different factors and prevention strategies can affect the rate of child maltreatment. We present the background of this work and give an overview of the agent-based model and show some simulation results.

Complexity and agent-based modelling in urban research

DEFF Research Database (Denmark)

Fertner, Christian

influence on the bigger system. Traditional scientific methods or theories often tried to simplify, not accounting complex relations of actors and decision-making. The introduction of computers in simulation made new approaches in modelling, as for example agent-based modelling (ABM), possible, dealing......Urbanisation processes are results of a broad variety of actors or actor groups and their behaviour and decisions based on different experiences, knowledge, resources, values etc. The decisions done are often on a micro/individual level but resulting in macro/collective behaviour. In urban research...

Practicality of Agent-Based Modeling of Civil Violence: an Assessment

OpenAIRE

Thron, Christopher; Jackson, Elizabeth

2015-01-01

Joshua Epstein (2002) proposed a simple agent-based model to describe the formation and evolution of spontaneous civil violence (such as riots or violent demonstrations). In this paper we study the practical applicability of Epstein's model.

Agent-Based Modeling of Taxi Behavior Simulation with Probe Vehicle Data

Directory of Open Access Journals (Sweden)

Saurav Ranjit

2018-05-01

Full Text Available Taxi behavior is a spatial–temporal dynamic process involving discrete time dependent events, such as customer pick-up, customer drop-off, cruising, and parking. Simulation models, which are a simplification of a real-world system, can help understand the effects of change of such dynamic behavior. In this paper, agent-based modeling and simulation is proposed, that describes the dynamic action of an agent, i.e., taxi, governed by behavior rules and properties, which emulate the taxi behavior. Taxi behavior simulations are fundamentally done for optimizing the service level for both taxi drivers as well as passengers. Moreover, simulation techniques, as such, could be applied to another field of application as well, where obtaining real raw data are somewhat difficult due to privacy issues, such as human mobility data or call detail record data. This paper describes the development of an agent-based simulation model which is based on multiple input parameters (taxi stay point cluster; trip information (origin and destination; taxi demand information; free taxi movement; and network travel time that were derived from taxi probe GPS data. As such, agent’s parameters were mapped into grid network, and the road network, for which the grid network was used as a base for query/search/retrieval of taxi agent’s parameters, while the actual movement of taxi agents was on the road network with routing and interpolation. The results obtained from the simulated taxi agent data and real taxi data showed a significant level of similarity of different taxi behavior, such as trip generation; trip time; trip distance as well as trip occupancy, based on its distribution. As for efficient data handling, a distributed computing platform for large-scale data was used for extracting taxi agent parameter from the probe data by utilizing both spatial and non-spatial indexing technique.

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

Science.gov (United States)

Shinde, Snehal B; Kurhekar, Manish P

2018-06-01

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

A review of Agent Based Modeling for agricultural policy evaluation

NARCIS (Netherlands)

Kremmydas, Dimitris; Athanasiadis, I.N.; Rozakis, Stelios

2018-01-01

Farm level scale policy analysis is receiving increased attention due to a changing agricultural policy orientation. Agent based models (ABM) are farm level models that have appeared in the end of 1990's, having several differences from traditional farm level models, like the consideration of

An agent-based simulation model to study accountable care organizations.

Science.gov (United States)

Liu, Pai; Wu, Shinyi

2016-03-01

Creating accountable care organizations (ACOs) has been widely discussed as a strategy to control rapidly rising healthcare costs and improve quality of care; however, building an effective ACO is a complex process involving multiple stakeholders (payers, providers, patients) with their own interests. Also, implementation of an ACO is costly in terms of time and money. Immature design could cause safety hazards. Therefore, there is a need for analytical model-based decision-support tools that can predict the outcomes of different strategies to facilitate ACO design and implementation. In this study, an agent-based simulation model was developed to study ACOs that considers payers, healthcare providers, and patients as agents under the shared saving payment model of care for congestive heart failure (CHF), one of the most expensive causes of sometimes preventable hospitalizations. The agent-based simulation model has identified the critical determinants for the payment model design that can motivate provider behavior changes to achieve maximum financial and quality outcomes of an ACO. The results show nonlinear provider behavior change patterns corresponding to changes in payment model designs. The outcomes vary by providers with different quality or financial priorities, and are most sensitive to the cost-effectiveness of CHF interventions that an ACO implements. This study demonstrates an increasingly important method to construct a healthcare system analytics model that can help inform health policy and healthcare management decisions. The study also points out that the likely success of an ACO is interdependent with payment model design, provider characteristics, and cost and effectiveness of healthcare interventions.

Sensitivity Analysis of an Agent-Based Model of Culture's Consequences for Trade

NARCIS (Netherlands)

Burgers, S.L.G.E.; Jonker, C.M.; Hofstede, G.J.; Verwaart, D.

2010-01-01

This paper describes the analysis of an agent-based model’s sensitivity to changes in parameters that describe the agents’ cultural background, relational parameters, and parameters of the decision functions. As agent-based models may be very sensitive to small changes in parameter values, it is of

Image-based modeling of tumor shrinkage in head and neck radiation therapy

Energy Technology Data Exchange (ETDEWEB)

Chao Ming; Xie Yaoqin; Moros, Eduardo G.; Le, Quynh-Thu; Xing Lei [Department of Radiation Oncology, Stanford University School of Medicine, 875 Blake Wilbur Drive, Stanford, California 94305-5847 and Department of Radiation Oncology, University of Arkansas for Medical Sciences, 4301 W. Markham Street, Little Rock, Arkansas 72205-1799 (United States); Department of Radiation Oncology, Stanford University School of Medicine, 875 Blake Wilbur Drive, Stanford, California 94305-5847 (United States); Department of Radiation Oncology, University of Arkansas for Medical Sciences, 4301 W. Markham Street, Little Rock, Arkansas 72205-1799 (United States); Department of Radiation Oncology, Stanford University School of Medicine, 875 Blake Wilbur Drive, Stanford, California 94305-5847 (United States)

2010-05-15

Purpose: Understanding the kinetics of tumor growth/shrinkage represents a critical step in quantitative assessment of therapeutics and realization of adaptive radiation therapy. This article presents a novel framework for image-based modeling of tumor change and demonstrates its performance with synthetic images and clinical cases. Methods: Due to significant tumor tissue content changes, similarity-based models are not suitable for describing the process of tumor volume changes. Under the hypothesis that tissue features in a tumor volume or at the boundary region are partially preserved, the kinetic change was modeled in two steps: (1) Autodetection of homologous tissue features shared by two input images using the scale invariance feature transformation (SIFT) method; and (2) establishment of a voxel-to-voxel correspondence between the images for the remaining spatial points by interpolation. The correctness of the tissue feature correspondence was assured by a bidirectional association procedure, where SIFT features were mapped from template to target images and reversely. A series of digital phantom experiments and five head and neck clinical cases were used to assess the performance of the proposed technique. Results: The proposed technique can faithfully identify the known changes introduced when constructing the digital phantoms. The subsequent feature-guided thin plate spline calculation reproduced the ''ground truth'' with accuracy better than 1.5 mm. For the clinical cases, the new algorithm worked reliably for a volume change as large as 30%. Conclusions: An image-based tumor kinetic algorithm was developed to model the tumor response to radiation therapy. The technique provides a practical framework for future application in adaptive radiation therapy.

Improving Agent Based Models and Validation through Data Fusion.

Science.gov (United States)

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

2011-01-01

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

An agent-based computational model for tuberculosis spreading on age-structured populations

Science.gov (United States)

Graciani Rodrigues, C. C.; Espíndola, Aquino L.; Penna, T. J. P.

2015-06-01

In this work we present an agent-based computational model to study the spreading of the tuberculosis (TB) disease on age-structured populations. The model proposed is a merge of two previous models: an agent-based computational model for the spreading of tuberculosis and a bit-string model for biological aging. The combination of TB with the population aging, reproduces the coexistence of health states, as seen in real populations. In addition, the universal exponential behavior of mortalities curves is still preserved. Finally, the population distribution as function of age shows the prevalence of TB mostly in elders, for high efficacy treatments.

Gadolinium-Loaded Solid Lipid Nanoparticles as a Tumor-Absorbable Contrast Agent for Early Diagnosis of Colorectal Tumors Using Magnetic Resonance Colonography.

Science.gov (United States)

Sun, Jihong; Zhang, Shizheng; Jiang, Shaojie; Bai, Weixian; Liu, Fei; Yuan, Hong; Ji, Jiansong; Luo, Jingfeng; Han, Guocan; Chen, Lumin; Jin, Yin; Hu, Peng; Yu, Lei; Yang, Xiaoming

2016-09-01

Magnetic resonance (MR) contrast agents focusing on special functions are required to improve cancer diagnosis, particularly in the early stages. Here, we designed multifunctional solid lipid nanoparticles (SLNs) with simultaneous loading of gadolinium (Gd) diethylenetriaminepentaacetic acid (Gd-DTPA) and octadecylamine fluorescein isothiocyanate (FITC) to obtain Gd-FITC-SLNs as a tumor-absorbable nanoparticle contrast agent for the histological confirmation of MR imaging (MRI) findings. Colorectal tumors were evaluated in vitro and in vivo via direct uptake of this contrast agent, which displayed reasonable T1 relaxivity and no significant cytotoxicity at the experimental concentrations in human colon carcinoma cells (HT29) and mouse colon carcinoma cells (CT26). In vitro cell uptake experiments demonstrated that contrast agent absorption by the two types of cancer cells was concentration-dependent in the safe concentration range. During in vivo MRI, transrectal infusion of Gd-FITC-SLNs showed more significant enhancement at the tumor site compared with the infusion of Gd-DTPA in female C57/BL mice with azoxymethane/dextran sulfate sodium-induced colorectal highgrade intraepithelial neoplasia. Subsequent confocal fluorescence microscopy demonstrated Gd-FITC-SLNs as highly concentrated green fluorescent spots distributed from the tumor capsule into the tumor. This study establishes the "proof-of-principle" of a new MRI technique wherein colorectal tumors are enhanced via direct absorption or uptake of the nanoparticle contrast agent.

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

Science.gov (United States)

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

Agent Based Reasoning in Multilevel Flow Modeling

DEFF Research Database (Denmark)

Lind, Morten; Zhang, Xinxin

2012-01-01

to launch the MFM Workbench into an agent based environment, which can complement disadvantages of the original software. The agent-based MFM Workbench is centered on a concept called “Blackboard System” and use an event based mechanism to arrange the reasoning tasks. This design will support the new...

The usefulness of US with contrast agent on breast tumors

International Nuclear Information System (INIS)

Jung, Hye An; Jung, Jung Im; Kim, Hak Hee; Son, Sang Bum; Byun, Jae Young; Lee, Jae Mun; Hahn, Sung Tae; Kim, Choon Yul

2000-01-01

To evaluate the usefulness of US with contrast agent breast tumors. Fifteen breast tumors in fourteen patients underwent color Doppler US before and after intravenous injection of a microbubble contrast agent (Levovist, Schering AG, Berlin, Germany). Benign lesions were 8 and malignant lesions were 7 among these. Real-time power Doppler ultrasonographic images were recorded on a videotape and representative images were color-printed. Tumor vascularity was analyzed on real-time images in regard to its presence or absence, and changes in diameter and number of vessels, presence or absence of blush around the vessels. Two observers reached a consensus. Results of malignant tumors were compared with those of benign tumors. Color Doppler signal intensity increased in 12 of 15 cases (80%). Number of vessel increased in 9 of 15 cases (60%) and diameter of vessel increased in 12 of 15 cases (80%). Vascular blush around the enhanced vessel was present in 5 of 15 patients (53%). Color Doppler signal increased in 5 of 8 benign lesions (63%) and 7 of 7 malignant lesions (100%). Number of vessel increased in 4 of 8 benign lesion (50%) and 5 of 7 malignant lesions (71%). Diameter of vessel increased in 5 of 8 benign lesions (63%) and 7 of 7 malignant lesions (100%). Blush around the enhanced vessel was present in one of 8 benign lesions (13%) and 4 of 7 malignant lesions (57%). The time to peak enhancement was shorter in malignant cases (mean=45 sec) than benign cases (mean=82 sec). US with contrast agent on breast tumors is effective to detect blood flow within the mass and may be helpful to differentiate malignant from benign lesions.

Agent-Based Modeling of Day-Ahead Real Time Pricing in a Pool-Based Electricity Market

Directory of Open Access Journals (Sweden)

Sh. Yousefi

2011-09-01

Full Text Available In this paper, an agent-based structure of the electricity retail market is presented based on which day-ahead (DA energy procurement for customers is modeled. Here, we focus on operation of only one Retail Energy Provider (REP agent who purchases energy from DA pool-based wholesale market and offers DA real time tariffs to a group of its customers. As a model of customer response to the offered real time prices, an hourly acceptance function is proposed in order to represent the hourly changes in the customer’s effective demand according to the prices. Here, Q-learning (QL approach is applied in day-ahead real time pricing for the customers enabling the REP agent to discover which price yields the most benefit through a trial-and-error search. Numerical studies are presented based on New England day-ahead market data which include comparing the results of RTP based on QL approach with that of genetic-based pricing.

Developing an agent-based model on how different individuals solve complex problems

Directory of Open Access Journals (Sweden)

Ipek Bozkurt

2015-01-01

Full Text Available Purpose: Research that focuses on the emotional, mental, behavioral and cognitive capabilities of individuals has been abundant within disciplines such as psychology, sociology, and anthropology, among others. However, when facing complex problems, a new perspective to understand individuals is necessary. The main purpose of this paper is to develop an agent-based model and simulation to gain understanding on the decision-making and problem-solving abilities of individuals. Design/Methodology/approach: The micro-level analysis modeling and simulation paradigm Agent-Based Modeling Through the use of Agent-Based Modeling, insight is gained on how different individuals with different profiles deal with complex problems. Using previous literature from different bodies of knowledge, established theories and certain assumptions as input parameters, a model is built and executed through a computer simulation. Findings: The results indicate that individuals with certain profiles have better capabilities to deal with complex problems. Moderate profiles could solve the entire complex problem, whereas profiles within extreme conditions could not. This indicates that having a strong predisposition is not the ideal way when approaching complex problems, and there should always be a component from the other perspective. The probability that an individual may use these capabilities provided by the opposite predisposition provides to be a useful option. Originality/value: The originality of the present research stems from how individuals are profiled, and the model and simulation that is built to understand how they solve complex problems. The development of the agent-based model adds value to the existing body of knowledge within both social sciences, and modeling and simulation.

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

Science.gov (United States)

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 Computational Modeling of Cell Culture ...

Science.gov (United States)

Quantitative characterization of cellular dose in vitro is needed for alignment of doses in vitro and in vivo. We used the agent-based software, CompuCell3D (CC3D), to provide a stochastic description of cell growth in culture. The model was configured so that isolated cells assumed a “fried egg shape” but became increasingly cuboidal with increasing confluency. The surface area presented by each cell to the overlying medium varies from cell-to-cell and is a determinant of diffusional flux of toxicant from the medium into the cell. Thus, dose varies among cells for a given concentration of toxicant in the medium. Computer code describing diffusion of H2O2 from medium into each cell and clearance of H2O2 was calibrated against H2O2 time-course data (25, 50, or 75 uM H2O2 for 60 min) obtained with the Amplex Red assay for the medium and the H2O2-sensitive fluorescent reporter, HyPer, for cytosol. Cellular H2O2 concentrations peaked at about 5 min and were near baseline by 10 min. The model predicted a skewed distribution of surface areas, with between cell variation usually 2 fold or less. Predicted variability in cellular dose was in rough agreement with the variation in the HyPer data. These results are preliminary, as the model was not calibrated to the morphology of a specific cell type. Future work will involve morphology model calibration against human bronchial epithelial (BEAS-2B) cells. Our results show, however, the potential of agent-based modeling

The Simulation of Financial Markets by Agent-Based Mix-Game Models

OpenAIRE

Chengling Gou

2006-01-01

This paper studies the simulation of financial markets using an agent-based mix-game model which is a variant of the minority game (MG). It specifies the spectra of parameters of mix-game models that fit financial markets by investigating the dynamic behaviors of mix-game models under a wide range of parameters. The main findings are (a) in order to approach efficiency, agents in a real financial market must be heterogeneous, boundedly rational and subject to asymmetric information; (b) an ac...

Cognitive Modeling for Agent-Based Simulation of Child Maltreatment

Science.gov (United States)

Hu, Xiaolin; Puddy, Richard

This paper extends previous work to develop cognitive modeling for agent-based simulation of child maltreatment (CM). The developed model is inspired from parental efficacy, parenting stress, and the theory of planned behavior. It provides an explanatory, process-oriented model of CM and incorporates causality relationship and feedback loops from different factors in the social ecology in order for simulating the dynamics of CM. We describe the model and present simulation results to demonstrate the features of this model.

Radiolabelling and evaluation of novel haloethylsulfoxides as PET imaging agents for tumor hypoxia

International Nuclear Information System (INIS)

Laurens, Evelyn; Yeoh, Shinn Dee; Rigopoulos, Angela; Cao, Diana; Cartwright, Glenn A.; O'Keefe, Graeme J.; Tochon-Danguy, Henri J.; White, Jonathan M.; Scott, Andrew M.; Ackermann, Uwe

2012-01-01

The significance of imaging hypoxia with the PET ligand [ 18 F]FMISO has been demonstrated in a variety of cancers. However, the slow kinetics of [ 18 F]FMISO require a 2-h delay between tracer administration and patient scanning. Labelled chloroethyl sulfoxides have shown faster kinetics and higher contrast than [ 18 F]FMISO in a rat model of ischemic stroke. However, these nitrogen mustard analogues are unsuitable for routine production and use in humans. Here we report on the synthesis and in vitro and in vivo evaluation of two novel sulfoxides which we synthesised from a single precursor molecule via either 2-[ 18 F]fluoroethyl azide click chemistry or conventional nucleophilic displacement of a chloride leaving group. The yields of the click chemistry approach were 90±5% of [ 18 F] based on 2-[ 18 F]fluoroethyl azide, and the yields for the S N reaction were 15±5% of [ 18 F] based on K[ 18 F]F. Both radiotracers underwent metabolism in an in vitro assay using S9 liver fractions with biological half-lives of 32.39 and 43.32 min, respectively. Imaging studies using an SK-RC-52 tumor model in BALB/c nude mice have revealed that only [ 18 F] is retained in hypoxic tumors, whereas [ 18 F] is cleared from those tumors at a rate similar to that of muscle tissue. [ 18 F] has emerged as a promising new lead structure for further development of sulfoxide-based hypoxia imaging agents. In particular, the mechanism of uptake needs to be elucidated and changes to the chemical structure need to be made in order to reduce metabolism and improve radiotracer kinetics.

Strategic directions for agent-based modeling: avoiding the YAAWN syndrome.

Science.gov (United States)

O'Sullivan, David; Evans, Tom; Manson, Steven; Metcalf, Sara; Ligmann-Zielinska, Arika; Bone, Chris

In this short communication, we examine how agent-based modeling has become common in land change science and is increasingly used to develop case studies for particular times and places. There is a danger that the research community is missing a prime opportunity to learn broader lessons from the use of agent-based modeling (ABM), or at the very least not sharing these lessons more widely. How do we find an appropriate balance between empirically rich, realistic models and simpler theoretically grounded models? What are appropriate and effective approaches to model evaluation in light of uncertainties not only in model parameters but also in model structure? How can we best explore hybrid model structures that enable us to better understand the dynamics of the systems under study, recognizing that no single approach is best suited to this task? Under what circumstances - in terms of model complexity, model evaluation, and model structure - can ABMs be used most effectively to lead to new insight for stakeholders? We explore these questions in the hope of helping the growing community of land change scientists using models in their research to move from 'yet another model' to doing better science with models.

An Agent-Based Model of Farmer Decision Making in Jordan

Science.gov (United States)

Selby, Philip; Medellin-Azuara, Josue; Harou, Julien; Klassert, Christian; Yoon, Jim

2016-04-01

We describe an agent based hydro-economic model of groundwater irrigated agriculture in the Jordan Highlands. The model employs a Multi-Agent-Simulation (MAS) framework and is designed to evaluate direct and indirect outcomes of climate change scenarios and policy interventions on farmer decision making, including annual land use, groundwater use for irrigation, and water sales to a water tanker market. Land use and water use decisions are simulated for groups of farms grouped by location and their behavioural and economic similarities. Decreasing groundwater levels, and the associated increase in pumping costs, are important drivers for change within Jordan'S agricultural sector. We describe how this is considered by coupling of agricultural and groundwater models. The agricultural production model employs Positive Mathematical Programming (PMP), a method for calibrating agricultural production functions to observed planted areas. PMP has successfully been used with disaggregate models for policy analysis. We adapt the PMP approach to allow explicit evaluation of the impact of pumping costs, groundwater purchase fees and a water tanker market. The work demonstrates the applicability of agent-based agricultural decision making assessment in the Jordan Highlands and its integration with agricultural model calibration methods. The proposed approach is designed and implemented with software such that it could be used to evaluate a variety of physical and human influences on decision making in agricultural water management.

Synthesis and evaluation of Tc-99m-labeled RRL-containing peptide as a non-invasive tumor imaging agent in a mouse fibrosarcoma model.

Science.gov (United States)

Kim, Dae-Weung; Kim, Woo Hyoung; Kim, Myoung Hyoun; Kim, Chang Guhn

2015-11-01

Arginine-arginine-leucine (RRL) is considered a tumor endothelial cell-specific binding sequence. RRL-containing peptide targeting tumor vessels is an excellent candidate for tumor imaging. In this study, we developed RRL-containing hexapeptides and evaluated their feasibility as a tumor imaging agent in a HT-1080 fibrosarcoma-bearing murine model. The hexapeptide, glutamic acid-cysteine-glycine (ECG)-RRL was synthesized using Fmoc solid-phase peptide synthesis. Radiolabeling efficiency was evaluated using instant thin-layer chromatography. Uptake of Tc-99m ECG-RRL within HT-1080 cells was evaluated in vitro by confocal microscopy and cellular binding affinity was calculated. Gamma images were acquired In HT-1080 fibrosarcoma tumor-bearing mice, and the tumor-to-muscle uptake ratio was calculated. The inflammatory-to-normal muscle uptake ratio was also calculated in an inflammation mouse model. A biodistribution study was performed to calculate %ID/g. A high yield of Tc-99m ECG-RRL complexes was prepared after Tc-99m radiolabeling. Binding of Tc-99m ECG-RRL to tumor cells had was confirmed by in vitro studies. Gamma camera imaging in the murine model showed that Tc-99m ECG-RRL accumulated substantially in the subcutaneously engrafted tumor and that tumoral uptake was blocked by co-injecting excess RRL. Moreover, Tc-99m ECG-RRL accumulated minimally in inflammatory lesions. We successfully developed Tc-99m ECG-RRL as a new tumor imaging candidate. Specific tumoral uptake of Tc-99m ECG-RRL was evaluated both in vitro and in vivo, and it was determined to be a good tumor imaging candidate. Additionally, Tc-99m ECG-RRL effectively distinguished between cancerous tissue and inflammatory lesions.

Targeting Potassium Channels for Increasing Delivery of Imaging Agents and Therapeutics to Brain Tumors

Directory of Open Access Journals (Sweden)

Nagendra Sanyasihally Ningaraj

2013-05-01

Full Text Available Every year in the US, 20,000 new primary and nearly 200,000 metastatic brain tumor cases are reported. The cerebral microvessels/ capillaries that form the blood–brain barrier (BBB not only protect the brain from toxic agents in the blood but also pose a significant hindrance to the delivery of small and large therapeutic molecules. Different strategies have been employed to circumvent the physiological barrier posed by blood-brain tumor barrier (BTB. Studies in our laboratory have identified significant differences in the expression levels of certain genes and proteins between normal and brain tumor capillary endothelial cells. In this study, we validated the non-invasive and clinically relevant Dynamic Contrast Enhancing-Magnetic Resonance Imaging (DCE-MRI method with invasive, clinically irrelevant but highly accurate Quantitative Autoradiography (QAR method using rat glioma model. We also showed that DCE-MRI metric of tissue vessel perfusion-permeability is sensitive to changes in blood vessel permeability following administration of calcium-activated potassium (BKCa channel activator NS-1619. Our results show that human gliomas and brain tumor endothelial cells that overexpress BKCa channels can be targeted for increased BTB permeability for MRI enhancing agents to brain tumors. We conclude that monitoring the outcome of increased MRI enhancing agents’ delivery to microsatellites and leading tumor edges in glioma patients would lead to beneficial clinical outcome.

Agent-based modeling of noncommunicable diseases: a systematic review.

Science.gov (United States)

Nianogo, Roch A; Arah, Onyebuchi A

2015-03-01

We reviewed the use of agent-based modeling (ABM), a systems science method, in understanding noncommunicable diseases (NCDs) and their public health risk factors. We systematically reviewed studies in PubMed, ScienceDirect, and Web of Sciences published from January 2003 to July 2014. We retrieved 22 relevant articles; each had an observational or interventional design. Physical activity and diet were the most-studied outcomes. Often, single agent types were modeled, and the environment was usually irrelevant to the studied outcome. Predictive validation and sensitivity analyses were most used to validate models. Although increasingly used to study NCDs, ABM remains underutilized and, where used, is suboptimally reported in public health studies. Its use in studying NCDs will benefit from clarified best practices and improved rigor to establish its usefulness and facilitate replication, interpretation, and application.

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

Science.gov (United States)

Alexandridis, Konstantinos T.

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

Persuasion Model and Its Evaluation Based on Positive Change Degree of Agent Emotion

Science.gov (United States)

Jinghua, Wu; Wenguang, Lu; Hailiang, Meng

For it can meet needs of negotiation among organizations take place in different time and place, and for it can make its course more rationality and result more ideal, persuasion based on agent can improve cooperation among organizations well. Integrated emotion change in agent persuasion can further bring agent advantage of artificial intelligence into play. Emotion of agent persuasion is classified, and the concept of positive change degree is given. Based on this, persuasion model based on positive change degree of agent emotion is constructed, which is explained clearly through an example. Finally, the method of relative evaluation is given, which is also verified through a calculation example.

Dynamic contrast-enhanced MRI using a macromolecular MR contrast agent (P792): Evaluation of antivascular drug effect in a rabbit VX2 liver tumor model

Energy Technology Data Exchange (ETDEWEB)

Park, Hee Sun [Dept. of Radiology, Konkuk University School of Medicine, Seoul (Korea, Republic of); Han, Joon Koo; Lee, Jeong Min; Woo, Sung Min; Choi, Byung Ihn [Seoul National University Hospital, Seoul (Korea, Republic of); Kim, Young Il [Dept. of Radiology, Sheikh Khalifa Specialty Hospital, Ras Al Khaimah (United Arab Emirates); Choi, Jin Young [Dept. of Radiology, Yonsei University College of Medicine, Seoul (Korea, Republic of)

2015-10-15

To evaluate the utility of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) using macromolecular contrast agent (P792) for assessment of vascular disrupting drug effect in rabbit VX2 liver tumor models. This study was approved by our Institutional Animal Care and Use Committee. DCE-MRI was performed with 3-T scanner in 13 VX2 liver tumor-bearing rabbits, before, 4 hours after, and 24 hours after administration of vascular disrupting agent (VDA), using gadomelitol (P792, n = 7) or low molecular weight contrast agent (gadoterate meglumine [Gd-DOTA], n = 6). P792 was injected at a of dose 0.05 mmol/kg, while that of Gd-DOTA was 0.2 mmol/kg. DCE-MRI parameters including volume transfer coefficient (Ktrans) and initial area under the gadolinium concentration-time curve until 60 seconds (iAUC) of tumors were compared between the 2 groups at each time point. DCE-MRI parameters were correlated with tumor histopathology. Reproducibility in measurement of DCE-MRI parameters and image quality of source MR were compared between groups. P792 group showed a more prominent decrease in Ktrans and iAUC at 4 hours and 24 hours, as compared to the Gd-DOTA group. Changes in DCE-MRI parameters showed a weak correlation with histologic parameters (necrotic fraction and microvessel density) in both groups. Reproducibility of DCE-MRI parameters and overall image quality was not significantly better in the P792 group, as compared to the Gd-DOTA group. Dynamic contrast-enhanced magnetic resonance imaging using a macromolecular contrast agent shows changes of hepatic perfusion more clearly after administration of the VDA. Gadolinium was required at smaller doses than a low molecular contrast agent.

Dynamic contrast-enhanced MRI using a macromolecular MR contrast agent (P792): Evaluation of antivascular drug effect in a rabbit VX2 liver tumor model

International Nuclear Information System (INIS)

Park, Hee Sun; Han, Joon Koo; Lee, Jeong Min; Woo, Sung Min; Choi, Byung Ihn; Kim, Young Il; Choi, Jin Young

2015-01-01

To evaluate the utility of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) using macromolecular contrast agent (P792) for assessment of vascular disrupting drug effect in rabbit VX2 liver tumor models. This study was approved by our Institutional Animal Care and Use Committee. DCE-MRI was performed with 3-T scanner in 13 VX2 liver tumor-bearing rabbits, before, 4 hours after, and 24 hours after administration of vascular disrupting agent (VDA), using gadomelitol (P792, n = 7) or low molecular weight contrast agent (gadoterate meglumine [Gd-DOTA], n = 6). P792 was injected at a of dose 0.05 mmol/kg, while that of Gd-DOTA was 0.2 mmol/kg. DCE-MRI parameters including volume transfer coefficient (Ktrans) and initial area under the gadolinium concentration-time curve until 60 seconds (iAUC) of tumors were compared between the 2 groups at each time point. DCE-MRI parameters were correlated with tumor histopathology. Reproducibility in measurement of DCE-MRI parameters and image quality of source MR were compared between groups. P792 group showed a more prominent decrease in Ktrans and iAUC at 4 hours and 24 hours, as compared to the Gd-DOTA group. Changes in DCE-MRI parameters showed a weak correlation with histologic parameters (necrotic fraction and microvessel density) in both groups. Reproducibility of DCE-MRI parameters and overall image quality was not significantly better in the P792 group, as compared to the Gd-DOTA group. Dynamic contrast-enhanced magnetic resonance imaging using a macromolecular contrast agent shows changes of hepatic perfusion more clearly after administration of the VDA. Gadolinium was required at smaller doses than a low molecular contrast agent

Magnetic resonance characterization of tumor microvessels in experimental breast tumors using a slow clearance blood pool contrast agent (carboxymethyldextran-A2-Gd-DOTA) with histopathological correlation

International Nuclear Information System (INIS)

Preda, Anda; Novikov, Viktor; Moeglich, Martina; Turetschek, Karl; Shames, David M.; Roberts, Timothy P.L.; Brasch, Robert C.; Floyd, Eugenia; Carter, Wayne O.; Corot, Claire

2005-01-01

Carboxymethyldextran (CMD)-A2-Gd-DOTA, a slow clearance blood pool contrast agent with a molecular weight of 52.1 kDa, designed to have intravascular residence for more than 1 h, was evaluated for its potential to characterize and differentiate the microvessels of malignant and benign breast tumors. Precontrast single-slice inversion-recovery snapshot FLASH and dynamic contrast-enhanced MRI using an axial T1-weighted three-dimensional spoiled gradient recalled sequence was performed in 30 Sprague-Dawley rats with chemically induced breast tumors. Endothelial transfer coefficient and fractional plasma volume of the breast tumors were estimated from MRI data acquired with CMD-A2-Gd-DOTA enhancement injected at a dose of 0.1 mmol Gd/kg body weight using a two-compartment bidirectional model of the tumor tissue. The correlation between MRI microvessel characteristics and histopathological tumor grade was determined using the Scarff-Bloom-Richardson method. Using CMD-A2-Gd-DOTA, no significant correlations were found between the MR-estimated endothelial transfer coefficient or plasma volumes with histological tumor grade. Analysis of CMD-A2-Gd-DOTA-enhanced MR kinetic data failed to demonstrate feasibility for the differentiation of benign from malignant tumors or for image-based tumor grading. (orig.)

Down-regulation of DNA mismatch repair proteins in human and murine tumor spheroids: implications for multicellular resistance to alkylating agents.

Science.gov (United States)

Francia, Giulio; Green, Shane K; Bocci, Guido; Man, Shan; Emmenegger, Urban; Ebos, John M L; Weinerman, Adina; Shaked, Yuval; Kerbel, Robert S

2005-10-01

Similar to other anticancer agents, intrinsic or acquired resistance to DNA-damaging chemotherapeutics is a major obstacle for cancer therapy. Current strategies aimed at overcoming this problem are mostly based on the premise that tumor cells acquire heritable genetic mutations that contribute to drug resistance. Here, we present evidence for an epigenetic, tumor cell adhesion-mediated, and reversible form of drug resistance that is associated with a reduction of DNA mismatch repair proteins PMS2 and/or MLH1 as well as other members of this DNA repair process. Growth of human breast cancer, human melanoma, and murine EMT-6 breast cancer cell lines as multicellular spheroids in vitro, which is associated with increased resistance to many chemotherapeutic drugs, including alkylating agents, is shown to lead to a reproducible down-regulation of PMS2, MLH1, or, in some cases, both as well as MHS6, MSH3, and MSH2. The observed down-regulation is in part reversible by treatment of tumor spheroids with the DNA-demethylating agent, 5-azacytidine. Thus, treatment of EMT-6 mouse mammary carcinoma spheroids with 5-azacytidine resulted in reduced and/or disrupted cell-cell adhesion, which in turn sensitized tumor spheroids to cisplatin-mediated killing in vitro. Our results suggest that antiadhesive agents might sensitize tumor spheroids to alkylating agents in part by reversing or preventing reduced DNA mismatch repair activity and that the chemosensitization properties of 5-azacytidine may conceivably reflect its role as a potential antiadhesive agent as well as reversal agent for MLH1 gene silencing in human tumors.

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

Science.gov (United States)

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.

Cyclophosphamide Enhances Human Tumor Growth in Nude Rat Xenografted Tumor Models

Directory of Open Access Journals (Sweden)

Yingjen Jeffrey Wu

2009-02-01

Full Text Available The effect of the immunomodulatory chemotherapeutic agent cyclophosphamide (CTX on tumor growth was investigated in primary and metastatic intracerebral and subcutaneous rat xenograft models. Nude rats were treated with CTX (100 mg/kg, intraperitoneally 24 hours before human ovarian carcinoma (SKOV3, small cell lung carcinoma (LX-1 SCLC, and glioma (UW28, U87MG, and U251 tumor cells were inoculated subcutaneously, intraperitoneally, or in the right cerebral hemisphere or were infused into the right internal carotid artery. Tumor development was monitored and recorded. Potential mechanisms were further investigated. Only animals that received both CTX and Matrigel showed consistent growth of subcutaneous tumors. Cyclophosphamide pretreatment increased the percentage (83.3% vs 0% of animals showing intraperitoneal tumors. In intracerebral implantation tumor models, CTX pretreatment increased the tumor volume and the percentage of animals showing tumors. Cyclophosphamide increased lung carcinoma bone and facial metastases after intra-arterial injection, and 20% of animals showed brain metastases. Cyclophosphamide transiently decreased nude rat white blood cell counts and glutathione concentration, whereas serum vascular endothelial growth factor was significantly elevated. Cyclophosphamide also increased CD31 reactivity, a marker of vascular endothelium, and macrophage (CD68-positive infiltration into glioma cell-inoculated rat brains. Cyclophosphamide may enhance primary and metastatic tumor growth through multiple mechanisms, including immune modulation, decreased response to oxidative stress, increased tumor vascularization, and increased macrophage infiltration. These findings may be clinically relevant because chemotherapy may predispose human cancer subjects to tumor growth in the brain or other tissues.

An agent-based model for diffusion of electric vehicles

NARCIS (Netherlands)

Kangur, Ayla; Jager, Wander; Verbrugge, Rineke; Bockarjova, Marija

2017-01-01

The transition from fuel cars to electric cars is a large-scale process involving many interactions between consumers and other stakeholders over decades. To explore how policies may interact with consumer behavior over such a long time period, we developed an agent-based social simulation model. In

Graceful Failure and Societal Resilience Analysis Via Agent-Based Modeling and Simulation

Science.gov (United States)

Schopf, P. S.; Cioffi-Revilla, C.; Rogers, J. D.; Bassett, J.; Hailegiorgis, A. B.

2014-12-01

Agent-based social modeling is opening up new methodologies for the study of societal response to weather and climate hazards, and providing measures of resiliency that can be studied in many contexts, particularly in coupled human and natural-technological systems (CHANTS). Since CHANTS are complex adaptive systems, societal resiliency may or may not occur, depending on dynamics that lack closed form solutions. Agent-based modeling has been shown to provide a viable theoretical and methodological approach for analyzing and understanding disasters and societal resiliency in CHANTS. Our approach advances the science of societal resilience through computational modeling and simulation methods that complement earlier statistical and mathematical approaches. We present three case studies of social dynamics modeling that demonstrate the use of these agent based models. In Central Asia, we exmaine mutltiple ensemble simulations with varying climate statistics to see how droughts and zuds affect populations, transmission of wealth across generations, and the overall structure of the social system. In Eastern Africa, we explore how successive episodes of drought events affect the adaptive capacity of rural households. Human displacement, mainly, rural to urban migration, and livelihood transition particularly from pastoral to farming are observed as rural households interacting dynamically with the biophysical environment and continually adjust their behavior to accommodate changes in climate. In the far north case we demonstrate one of the first successful attempts to model the complete climate-permafrost-infrastructure-societal interaction network as a complex adaptive system/CHANTS implemented as a ``federated'' agent-based model using evolutionary computation. Analysis of population changes resulting from extreme weather across these and other cases provides evidence for the emergence of new steady states and shifting patterns of resilience.

Data Provenance for Agent-Based Models in a Distributed Memory

Directory of Open Access Journals (Sweden)

Delmar B. Davis

2018-04-01

Full Text Available Agent-Based Models (ABMs assist with studying emergent collective behavior of individual entities in social, biological, economic, network, and physical systems. Data provenance can support ABM by explaining individual agent behavior. However, there is no provenance support for ABMs in a distributed setting. The Multi-Agent Spatial Simulation (MASS library provides a framework for simulating ABMs at fine granularity, where agents and spatial data are shared application resources in a distributed memory. We introduce a novel approach to capture ABM provenance in a distributed memory, called ProvMASS. We evaluate our technique with traditional data provenance queries and performance measures. Our results indicate that a configurable approach can capture provenance that explains coordination of distributed shared resources, simulation logic, and agent behavior while limiting performance overhead. We also show the ability to support practical analyses (e.g., agent tracking and storage requirements for different capture configurations.

An agent-based model for integrated emotion regulation and contagion in socially affected decision making

OpenAIRE

Manzoor, A.; Treur, J.

2015-01-01

This paper addresses an agent-based computational social agent model for the integration of emotion regulation, emotion contagion and decision making in a social context. The model integrates emotion-related valuing, in order to analyse the role of emotions in socially affected decision making. The agent-based model is illustrated for the interaction between two persons. Simulation experiments for different kinds of scenarios help to understand how decisions can be affected by regulating the ...

The fabrication of novel nanobubble ultrasound contrast agent for potential tumor imaging

Energy Technology Data Exchange (ETDEWEB)

Xing Zhanwen; Ke Hengte; Yue Xiuli; Dai Zhifei [Nanobiotechnology Division, State Key Laboratory of Urban Water Resources and Environment, School of Sciences, Harbin Institute of Technology, Harbin 150080 (China); Wang Jinrui; Zhao Bo [Department of Ultrasonography, Peking University Third Hospital, Beijing 100083 (China); Liu Jibin, E-mail: zhifei.dai@hit.edu.cn, E-mail: ji-bin.liu@jefferson.edu [Ultrasound Research and Education Institute, Thomas Jefferson University, Philadelphia, PA 19107 (United States)

2010-04-09

Novel biocompatible nanobubbles were fabricated by ultrasonication of a mixture of Span 60 and polyoxyethylene 40 stearate (PEG40S) followed by differential centrifugation to isolate the relevant subpopulation from the parent suspensions. Particle sizing analysis and optical microscopy inspection indicated that the freshly generated micro/nanobubble suspension was polydisperse and the size distribution was bimodal with large amounts of nanobubbles. To develop a nano-sized contrast agent that is small enough to leak through tumor pores, a fractionation to extract smaller bubbles by variation in the time of centrifugation at 20g (relative centrifuge field, RCF) was suggested. The results showed that the population of nanobubbles with a precisely controlled mean diameter could be sorted from the initial polydisperse suspensions to meet the specified requirements. The isolated bubbles were stable over two weeks under the protection of perfluoropropane gas. The acoustic behavior of the nano-sized contrast agent was evaluated using power Doppler imaging in a normal rabbit model. An excellent power Doppler enhancement was found in vivo renal imaging after intravenous injection of the obtained nanobubbles. Given the broad spectrum of potential clinical applications, the nano-sized contrast agent may provide a versatile adjunct for ultrasonic imaging enhancement and/or treatment of tumors.

The fabrication of novel nanobubble ultrasound contrast agent for potential tumor imaging

International Nuclear Information System (INIS)

Xing Zhanwen; Ke Hengte; Yue Xiuli; Dai Zhifei; Wang Jinrui; Zhao Bo; Liu Jibin

2010-01-01

Novel biocompatible nanobubbles were fabricated by ultrasonication of a mixture of Span 60 and polyoxyethylene 40 stearate (PEG40S) followed by differential centrifugation to isolate the relevant subpopulation from the parent suspensions. Particle sizing analysis and optical microscopy inspection indicated that the freshly generated micro/nanobubble suspension was polydisperse and the size distribution was bimodal with large amounts of nanobubbles. To develop a nano-sized contrast agent that is small enough to leak through tumor pores, a fractionation to extract smaller bubbles by variation in the time of centrifugation at 20g (relative centrifuge field, RCF) was suggested. The results showed that the population of nanobubbles with a precisely controlled mean diameter could be sorted from the initial polydisperse suspensions to meet the specified requirements. The isolated bubbles were stable over two weeks under the protection of perfluoropropane gas. The acoustic behavior of the nano-sized contrast agent was evaluated using power Doppler imaging in a normal rabbit model. An excellent power Doppler enhancement was found in vivo renal imaging after intravenous injection of the obtained nanobubbles. Given the broad spectrum of potential clinical applications, the nano-sized contrast agent may provide a versatile adjunct for ultrasonic imaging enhancement and/or treatment of tumors.

The fabrication of novel nanobubble ultrasound contrast agent for potential tumor imaging

Science.gov (United States)

Xing, Zhanwen; Wang, Jinrui; Ke, Hengte; Zhao, Bo; Yue, Xiuli; Dai, Zhifei; Liu, Jibin

2010-04-01

Novel biocompatible nanobubbles were fabricated by ultrasonication of a mixture of Span 60 and polyoxyethylene 40 stearate (PEG40S) followed by differential centrifugation to isolate the relevant subpopulation from the parent suspensions. Particle sizing analysis and optical microscopy inspection indicated that the freshly generated micro/nanobubble suspension was polydisperse and the size distribution was bimodal with large amounts of nanobubbles. To develop a nano-sized contrast agent that is small enough to leak through tumor pores, a fractionation to extract smaller bubbles by variation in the time of centrifugation at 20g (relative centrifuge field, RCF) was suggested. The results showed that the population of nanobubbles with a precisely controlled mean diameter could be sorted from the initial polydisperse suspensions to meet the specified requirements. The isolated bubbles were stable over two weeks under the protection of perfluoropropane gas. The acoustic behavior of the nano-sized contrast agent was evaluated using power Doppler imaging in a normal rabbit model. An excellent power Doppler enhancement was found in vivo renal imaging after intravenous injection of the obtained nanobubbles. Given the broad spectrum of potential clinical applications, the nano-sized contrast agent may provide a versatile adjunct for ultrasonic imaging enhancement and/or treatment of tumors.

Synthesis and evaluation of novel Tc-99m labeled NGR-containing hexapeptides as tumor imaging agents.

Science.gov (United States)

Kim, Dae-Weung; Kim, Woo Hyoung; Kim, Myoung Hyoun; Kim, Chang Guhn

2015-02-01

Asparagine-glycine-arginine (NGR)-containing peptides targeting aminopeptidase N (APN)/CD13 can be an excellent candidate for targeting ligands in molecular tumor imaging. In this study, we developed two NGR-containing hexapeptides, and evaluated the diagnostic performance of Tc-99m labeled hexapeptides as molecular imaging agents in an HT-1080 fibrosarcoma-bearing murine model. Peptides were synthesized using Fmoc solid-phase peptide synthesis. Radiochemical purity of Tc-99m was evaluated using instant thin-layer chromatography. The uptake of two NGR-containing hexapeptides within HT-1080 cells was evaluated in vitro. In HT-1080 fibrosarcoma tumor-bearing mice, gamma images were acquired. A biodistribution study was performed to calculate percentage of the injected dose per gram of tissue (%ID/g). Two hexapeptides, glutamic acid-cysteine-glycine (ECG)-NGR and NGR-ECG were successfully synthesized. After radiolabeling procedures with Tc-99m, the complexes Tc-99m hexapeptides were prepared in high yield. The uptake of Tc-99m ECG-NGR within the tumor cells had been assured by in vitro studies. The gamma camera imaging in the murine model showed that Tc-99m ECG-NGR was accumulated substantially in the subcutaneously engrafted tumor. However, Tc-99m NGR-ECG was accumulated minimally in the tumor. Two NGR-containing hexapeptides, ECG-NGR and NGR-ECG were developed as molecular imaging agents to target APN/CD13 in HT-1080 fibrosarcoma. Tc-99m ECG-NGR showed a significant uptake in the tumor, and it is a good candidate for tumor imaging. Copyright © 2015 John Wiley & Sons, Ltd.

Contrast agents for tumor diagnosis in magnetic resonance imaging

Energy Technology Data Exchange (ETDEWEB)

Goto, Rensuke; Doi, Hisayoshi; Okada, Shoji [University of Shizuoka (Japan). School of Pharmaceutical Science; Yano, Masayuki; Katano, Susumu; Nakajima, Nobuaki

1992-01-01

In order to develop contrast agents for tumor diagnosis in magnetic resonance imaging (MRI), we investigated the effects of several gadolinium complexes on T{sub 1} relaxation time of proton in some tissues of Ehrlich solid tumor-bearing mice. L-Aspartic acid, L-glutamic acid, DL-homocysteine, L-glutamyl-glutamic acid, glutathione, sperimidine and ethylenediaminetetrakis (methylenephosphate) (EDTMP) were used as ligands for Gd{sup 3+}. Since each Gd-complex could not be purified except Gd-EDTMP, the mixture of GdCl{sub 3} and a ligand was administered intravenously. Among the compounds tested, the mixture of aspartic acid, glutathione or spermidine with GdCl{sub 3} showed almost the same or above reduction of T{sub 1} relaxation times in the tumor tissue compared with Gd-diethylenetriamine pentaacetic acid (Gd-DTPA) which is used clinically. Furthermore, the contrast-enhancing effect of the three mixtures in the tumor was observed by in vivo T{sub 1}-weighted magnetic resonance imaging. The in vivo tissue distribution using radioactive {sup 153}Gd{sup 3+} showed that these mixtures mentioned above were also taken up more highly in the tumor than {sup 153}GdCl{sub 3} itself and {sup 153}Gd-DTPA, suggesting the formation of Gd-complexes. However, the overall tissue distribution of the mixtures was similar to that of {sup 153}GdCl{sub 3} because the Gd-complexes were not purified. Gd-EDTMP exhibited the almost same effects with Gd-DTPA as a contrast agent. (author).

Hybrid liposomes showing enhanced accumulation in tumors as theranostic agents in the orthotopic graft model mouse of colorectal cancer.

Science.gov (United States)

Okumura, Masaki; Ichihara, Hideaki; Matsumoto, Yoko

2018-11-01

Hybrid liposomes (HLs) can be prepared by simply sonicating a mixture of vesicular and micellar molecules in a buffer solution. This study aimed to elucidate the therapeutic effects and ability of HLs to detect (diagnosis) cancer in an orthotopic graft mouse model of colorectal cancer with HCT116 cells for the use of HLs as theranostic agents. In the absence of a chemotherapeutic drug, HLs exhibited therapeutic effects by inhibiting the growth of HCT116 colorectal cancer cells in vitro, possibly through an increase in apoptosis. Intravenously administered HLs also caused a remarkable reduction in the relative cecum weight in an orthotopic graft mouse model of colorectal cancer. A decrease in tumor size in the cecal sections was confirmed by histological analysis using HE staining. TUNEL staining indicated an induction of apoptosis in HCT116 cells in the orthotopic graft mouse model of colorectal cancer. For the detection (diagnosis) of colorectal cancer by HLs, the accumulation of HLs encapsulating a fluorescent probe (ICG) was observed in HCT116 cells in the in vivo colorectal cancer model following intravenous administration. These data indicate that HLs can accumulate in tumor cells in the cecum of the orthotopic graft mouse model of colorectal cancer for a prolonged period of time, and inhibit the growth of HCT116 cells.

Image-based modeling of tumor shrinkage in head and neck radiation therapy1

Science.gov (United States)

Chao, Ming; Xie, Yaoqin; Moros, Eduardo G.; Le, Quynh-Thu; Xing, Lei

2010-01-01

Purpose: Understanding the kinetics of tumor growth∕shrinkage represents a critical step in quantitative assessment of therapeutics and realization of adaptive radiation therapy. This article presents a novel framework for image-based modeling of tumor change and demonstrates its performance with synthetic images and clinical cases. Methods: Due to significant tumor tissue content changes, similarity-based models are not suitable for describing the process of tumor volume changes. Under the hypothesis that tissue features in a tumor volume or at the boundary region are partially preserved, the kinetic change was modeled in two steps: (1) Autodetection of homologous tissue features shared by two input images using the scale invariance feature transformation (SIFT) method; and (2) establishment of a voxel-to-voxel correspondence between the images for the remaining spatial points by interpolation. The correctness of the tissue feature correspondence was assured by a bidirectional association procedure, where SIFT features were mapped from template to target images and reversely. A series of digital phantom experiments and five head and neck clinical cases were used to assess the performance of the proposed technique. Results: The proposed technique can faithfully identify the known changes introduced when constructing the digital phantoms. The subsequent feature-guided thin plate spline calculation reproduced the “ground truth” with accuracy better than 1.5 mm. For the clinical cases, the new algorithm worked reliably for a volume change as large as 30%. Conclusions: An image-based tumor kinetic algorithm was developed to model the tumor response to radiation therapy. The technique provides a practical framework for future application in adaptive radiation therapy. PMID:20527569

Land-use change arising from rural land exchange : an agent-based simulation model

NARCIS (Netherlands)

Bakker, Martha M.; Alam, Shah Jamal; van Dijk, Jerry|info:eu-repo/dai/nl/29612642X; Rounsevell, Mark D. A.

Land exchange can be a major factor driving land-use change in regions with high pressure on land, but is generally not incorporated in land-use change models. Here we present an agent-based model to simulate land-use change arising from land exchange between multiple agent types representing

A state-based probabilistic model for tumor respiratory motion prediction

International Nuclear Information System (INIS)

Kalet, Alan; Sandison, George; Schmitz, Ruth; Wu Huanmei

2010-01-01

This work proposes a new probabilistic mathematical model for predicting tumor motion and position based on a finite state representation using the natural breathing states of exhale, inhale and end of exhale. Tumor motion was broken down into linear breathing states and sequences of states. Breathing state sequences and the observables representing those sequences were analyzed using a hidden Markov model (HMM) to predict the future sequences and new observables. Velocities and other parameters were clustered using a k-means clustering algorithm to associate each state with a set of observables such that a prediction of state also enables a prediction of tumor velocity. A time average model with predictions based on average past state lengths was also computed. State sequences which are known a priori to fit the data were fed into the HMM algorithm to set a theoretical limit of the predictive power of the model. The effectiveness of the presented probabilistic model has been evaluated for gated radiation therapy based on previously tracked tumor motion in four lung cancer patients. Positional prediction accuracy is compared with actual position in terms of the overall RMS errors. Various system delays, ranging from 33 to 1000 ms, were tested. Previous studies have shown duty cycles for latencies of 33 and 200 ms at around 90% and 80%, respectively, for linear, no prediction, Kalman filter and ANN methods as averaged over multiple patients. At 1000 ms, the previously reported duty cycles range from approximately 62% (ANN) down to 34% (no prediction). Average duty cycle for the HMM method was found to be 100% and 91 ± 3% for 33 and 200 ms latency and around 40% for 1000 ms latency in three out of four breathing motion traces. RMS errors were found to be lower than linear and no prediction methods at latencies of 1000 ms. The results show that for system latencies longer than 400 ms, the time average HMM prediction outperforms linear, no prediction, and the more

An Adaptive Agent-Based Model of Homing Pigeons: A Genetic Algorithm Approach

Directory of Open Access Journals (Sweden)

Francis Oloo

2017-01-01

Full Text Available Conventionally, agent-based modelling approaches start from a conceptual model capturing the theoretical understanding of the systems of interest. Simulation outcomes are then used “at the end” to validate the conceptual understanding. In today’s data rich era, there are suggestions that models should be data-driven. Data-driven workflows are common in mathematical models. However, their application to agent-based models is still in its infancy. Integration of real-time sensor data into modelling workflows opens up the possibility of comparing simulations against real data during the model run. Calibration and validation procedures thus become automated processes that are iteratively executed during the simulation. We hypothesize that incorporation of real-time sensor data into agent-based models improves the predictive ability of such models. In particular, that such integration results in increasingly well calibrated model parameters and rule sets. In this contribution, we explore this question by implementing a flocking model that evolves in real-time. Specifically, we use genetic algorithms approach to simulate representative parameters to describe flight routes of homing pigeons. The navigation parameters of pigeons are simulated and dynamically evaluated against emulated GPS sensor data streams and optimised based on the fitness of candidate parameters. As a result, the model was able to accurately simulate the relative-turn angles and step-distance of homing pigeons. Further, the optimised parameters could replicate loops, which are common patterns in flight tracks of homing pigeons. Finally, the use of genetic algorithms in this study allowed for a simultaneous data-driven optimization and sensitivity analysis.

A Computational Agent-Based Modeling Approach for Competitive Wireless Service Market

KAUST Repository

Douglas, C C

2011-04-01

Using an agent-based modeling method, we study market dynamism with regard to wireless cellular services that are in competition for a greater market share and profit. In the proposed model, service providers and consumers are described as agents who interact with each other and actively participate in an economically well-defined marketplace. Parameters of the model are optimized using the Levenberg-Marquardt method. The quantitative prediction capabilities of the proposed model are examined through data reproducibility using past data from the U.S. and Korean wireless service markets. Finally, we investigate a disruptive market event, namely the introduction of the iPhone into the U.S. in 2007 and the resulting changes in the modeling parameters. We predict and analyze the impacts of the introduction of the iPhone into the Korean wireless service market assuming a release date of 2Q09 based on earlier data. © 2011 IEEE.

Agent-based game theory modeling for driverless vehicles at intersections.

Science.gov (United States)

2013-02-01

This report presents three research efforts that were published in various journals. The first research effort presents a reactive-driving agent based algorithm for modeling driver left turn gap acceptance behavior at signalized intersections. This m...

Modeling and simulation of tumor-influenced high resolution real-time physics-based breast models for model-guided robotic interventions

Science.gov (United States)

Neylon, John; Hasse, Katelyn; Sheng, Ke; Santhanam, Anand P.

2016-03-01

Breast radiation therapy is typically delivered to the patient in either supine or prone position. Each of these positioning systems has its limitations in terms of tumor localization, dose to the surrounding normal structures, and patient comfort. We envision developing a pneumatically controlled breast immobilization device that will enable the benefits of both supine and prone positioning. In this paper, we present a physics-based breast deformable model that aids in both the design of the breast immobilization device as well as a control module for the device during every day positioning. The model geometry is generated from a subject's CT scan acquired during the treatment planning stage. A GPU based deformable model is then generated for the breast. A mass-spring-damper approach is then employed for the deformable model, with the spring modeled to represent a hyperelastic tissue behavior. Each voxel of the CT scan is then associated with a mass element, which gives the model its high resolution nature. The subject specific elasticity is then estimated from a CT scan in prone position. Our results show that the model can deform at >60 deformations per second, which satisfies the real-time requirement for robotic positioning. The model interacts with a computer designed immobilization device to position the breast and tumor anatomy in a reproducible location. The design of the immobilization device was also systematically varied based on the breast geometry, tumor location, elasticity distribution and the reproducibility of the desired tumor location.

Methods for Model-Based Reasoning within Agent-Based Ambient Intelligence Applications

NARCIS (Netherlands)

Bosse, T.; Both, F.; Gerritsen, C.; Hoogendoorn, M.; Treur, J.

2012-01-01

Within agent-based Ambient Intelligence applications agents react to humans based on information obtained by sensoring and their knowledge about human functioning. Appropriate types of reactions depend on the extent to which an agent understands the human and is able to interpret the available

Agent-Based Modeling of Consumer Decision making Process Based on Power Distance and Personality

NARCIS (Netherlands)

Roozmand, O.; Ghasem-Aghaee, N.; Hofstede, G.J.; Nematbakhsh, M.A.; Baraani, A.; Verwaart, T.

2011-01-01

Simulating consumer decision making processes involves different disciplines such as: sociology, social psychology, marketing, and computer science. In this paper, we propose an agent-based conceptual and computational model of consumer decision-making based on culture, personality and human needs.

Computed Tomography Imaging of Solid Tumors Using a Liposomal-Iodine Contrast Agent in Companion Dogs with Naturally Occurring Cancer.

Science.gov (United States)

Ghaghada, Ketan B; Sato, Amy F; Starosolski, Zbigniew A; Berg, John; Vail, David M

2016-01-01

Companion dogs with naturally occurring cancer serve as an important large animal model in translational research because they share strong similarities with human cancers. In this study, we investigated a long circulating liposomal-iodine contrast agent (Liposomal-I) for computed tomography (CT) imaging of solid tumors in companion dogs with naturally occurring cancer. The institutional animal ethics committees approved the study and written informed consent was obtained from all owners. Thirteen dogs (mean age 10.1 years) with a variety of masses including primary and metastatic liver tumors, sarcomas, mammary carcinoma and lung tumors, were enrolled in the study. CT imaging was performed pre-contrast and at 15 minutes and 24 hours after intravenous administration of Liposomal-I (275 mg/kg iodine dose). Conventional contrast-enhanced CT imaging was performed in a subset of dogs, 90 minutes prior to administration of Liposomal-I. Histologic or cytologic diagnosis was obtained for each dog prior to admission into the study. Liposomal-I resulted in significant (p contrast agent was demonstrated. Liposomal-I enabled visualization of primary and metastatic liver tumors. Sub-cm sized liver lesions grossly appeared as hypo-enhanced compared to the surrounding normal parenchyma with improved lesion conspicuity in the post-24 hour scan. Large liver tumors (> 1 cm) demonstrated a heterogeneous pattern of intra-tumoral signal with visibly higher signal enhancement at the post-24 hour time point. Extra-hepatic, extra-splenic tumors, including histiocytic sarcoma, anaplastic sarcoma, mammary carcinoma and lung tumors, were visualized with a heterogeneous enhancement pattern in the post-24 hour scan. The long circulating liposomal-iodine contrast agent enabled prolonged visualization of small and large tumors in companion dogs with naturally occurring cancer. The study warrants future work to assess the sensitivity and specificity of the Liposomal-I agent in various types of

Genetic Algorithms for Agent-Based Infrastructure Interdependency Modeling and Analysis

Energy Technology Data Exchange (ETDEWEB)

May Permann

2007-03-01

Today’s society relies greatly upon an array of complex national and international infrastructure networks such as transportation, electric power, telecommunication, and financial networks. This paper describes initial research combining agent-based infrastructure modeling software and genetic algorithms (GAs) to help optimize infrastructure protection and restoration decisions. This research proposes to apply GAs to the problem of infrastructure modeling and analysis in order to determine the optimum assets to restore or protect from attack or other disaster. This research is just commencing and therefore the focus of this paper is the integration of a GA optimization method with a simulation through the simulation’s agents.

Multi-Agent Based Microscopic Simulation Modeling for Urban Traffic Flow

Directory of Open Access Journals (Sweden)

Xianyan Kuang

2014-10-01

Full Text Available Traffic simulation plays an important role in the evaluation of traffic decisions. The movement of vehicles essentially is the operating process of drivers, in order to reproduce the urban traffic flow from the micro-aspect on computer, this paper establishes an urban traffic flow microscopic simulation system (UTFSim based on multi-agent. The system is seen as an intelligent virtual environment system (IVES, and the four-layer structure of it is built. The road agent, vehicle agent and signal agent are modeled. The concept of driving trajectory which is divided into LDT (Lane Driving Trajectory and VDDT (Vehicle Dynamic Driving Trajectory is introduced. The “Link-Node” road network model is improved. The driving behaviors including free driving, following driving, lane changing, slowing down, vehicle stop, etc. are analyzed. The results of the signal control experiments utilizing the UTFSim developed in the platform of Visual Studio. NET indicates that it plays a good performance and can be used in the evaluation of traffic management and control.

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

Directory of Open Access Journals (Sweden)

Theodore Eugene Day

Full Text Available 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.

Biodistribution of ultra small gadolinium-based nanoparticles as theranostic agent: application to brain tumors.

Science.gov (United States)

Miladi, Imen; Duc, Géraldine Le; Kryza, David; Berniard, Aurélie; Mowat, Pierre; Roux, Stéphane; Taleb, Jacqueline; Bonazza, Pauline; Perriat, Pascal; Lux, François; Tillement, Olivier; Billotey, Claire; Janier, Marc

2013-09-01

Gadolinium-based nanoparticles are novel objects with interesting physical properties, allowing their use for diagnostic and therapeutic applications. Gadolinium-based nanoparticles were imaged following intravenous injection in healthy rats and rats grafted with 9L gliosarcoma tumors using magnetic resonance imaging and scintigraphic imaging. Quantitative biodistribution using gamma-counting of each sampled organ confirmed that these nanoparticles were rapidly cleared essentially by renal excretion. Accumulation of these nanoparticles in 9L gliosarcoma tumors implanted in the rat brain was quantitated. This passive and long-duration accumulation of gadolinium-based nanoparticles in tumor, which is related to disruption of the blood-brain barrier, is in good agreement with the use of these nanoparticles as radiosensitizers for brain tumors.

The Simulation of Financial Markets by an Agent-Based Mix-Game Model

OpenAIRE

Chengling Gou

2006-01-01

This paper studies the simulation of financial markets using an agent-based mix-game model which is a variant of the minority game (MG). It specifies the spectra of parameters of mix-game models that fit financial markets by investigating the dynamic behaviors of mix-game models under a wide range of parameters. The main findings are (a) in order to approach efficiency, agents in a real financial market must be heterogeneous, boundedly rational and subject to asymmetric information; (b) an ac...

Agent-Based and Macroscopic Modeling of the Complex Socio-Economic Systems

Directory of Open Access Journals (Sweden)

Aleksejus Kononovičius

2013-08-01

Full Text Available Purpose – The focus of this contribution is the correspondence between collective behavior and inter-individual interactions in the complex socio-economic systems. Currently there is a wide selection of papers proposing various models for the both collective behavior and inter-individual interactions in the complex socio-economic systems. Yet the papers directly relating these two concepts are still quite rare. By studying this correspondence we discuss a cutting edge approach to the modeling of complex socio-economic systems. Design/methodology/approach – The collective behavior is often modeled using stochastic and ordinary calculus, while the inter-individual interactions are modeled using agent-based models. In order to obtain the ideal model, one should start from these frameworks and build a bridge to reach another. This is a formidable task, if we consider the top-down approach, namely starting from the collective behavior and moving towards inter-individual interactions. The bottom-up approach also fails, if complex inter-individual interaction models are considered, yet in this case we can start with simple models and increase the complexity as needed. Findings – The bottom-up approach, considering simple agent-based herding model as a model for the inter-individual interactions, allows us to derive certain macroscopic models of the complex socio-economic systems from the agent-based perspective. This provides interesting insights into the collective behavior patterns observed in the complex socio-economic systems. Research limitations/implications –The simplicity of the agent-based herding model might be considered to be somewhat limiting. Yet this simplicity implies that the model is highly universal. It reproduces universal features of social behavior and also can be further extended to fit different socio-economic scenarios. Practical implications – Insights provided in this contribution might be used to modify existing

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

Science.gov (United States)

Yoon, J.; Gorelick, S.

2014-12-01

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

A mathematical framework for agent based models of complex biological networks.

Science.gov (United States)

Hinkelmann, Franziska; Murrugarra, David; Jarrah, Abdul Salam; Laubenbacher, Reinhard

2011-07-01

Agent-based modeling and simulation is a useful method to study biological phenomena in a wide range of fields, from molecular biology to ecology. Since there is currently no agreed-upon standard way to specify such models, it is not always easy to use published models. Also, since model descriptions are not usually given in mathematical terms, it is difficult to bring mathematical analysis tools to bear, so that models are typically studied through simulation. In order to address this issue, Grimm et al. proposed a protocol for model specification, the so-called ODD protocol, which provides a standard way to describe models. This paper proposes an addition to the ODD protocol which allows the description of an agent-based model as a dynamical system, which provides access to computational and theoretical tools for its analysis. The mathematical framework is that of algebraic models, that is, time-discrete dynamical systems with algebraic structure. It is shown by way of several examples how this mathematical specification can help with model analysis. This mathematical framework can also accommodate other model types such as Boolean networks and the more general logical models, as well as Petri nets.

Simulating the Reproductive Behavior of a Region’s Population with an Agent-Based Model

Directory of Open Access Journals (Sweden)

Valeriy Leonidovich Makarov

2015-09-01

Full Text Available The research analyses the impact of the inequality of demographic transition on socio-demographic characteristics of the regional population and on the dynamics of these characteristics. The study was conducted with the help of computer-based experiments (simulations, which was run on the original agent-based model. The model is an artificial society, and personal characteristics of its members are set so that they could represent age-demographic structure of a simulate region. The agents are divided into two subgroups, which differ in their reproductive strategy. The first group has traditional strategy with high birth rate. The second group has considerably lower birth rate, observed in the modern developed societies. The model uses stochastic approaches to imitate the principle processes of population growth: mortality and morbidity. Mortality is set according to age-sex specific mortality coefficients, which do not differ across the population as a whole. New agents (child births appear as a choice of agents – women of reproductive age, and the choice depends on the subgroup. The overall age and social structure of the region is aggregated across individual agents. A number of experiments has been carried out with the model utilization. This allowed forecasting the size and structure of the population of a given region. The results of the experiments have revealed that despite its simplicity, the developed agent-based model well predicts the initial conditions in the region (e.g. age-demographic and social structure. The model shows good fit in terms of estimating the dynamics of major characteristics of the population.

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

Science.gov (United States)

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

2011-03-09

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

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

Directory of Open Access Journals (Sweden)

David J Poza

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

An Agent-Based Model of New Venture Creation: Conceptual Design for Simulating Entrepreneurship

Science.gov (United States)

Provance, Mike; Collins, Andrew; Carayannis, Elias

2012-01-01

There is a growing debate over the means by which regions can foster the growth of entrepreneurial activity in order to stimulate recovery and growth of their economies. On one side, agglomeration theory suggests the regions grow because of strong clusters that foster knowledge spillover locally; on the other side, the entrepreneurial action camp argues that innovative business models are generated by entrepreneurs with unique market perspectives who draw on knowledge from more distant domains. We will show you the design for a novel agent-based model of new venture creation that will demonstrate the relationship between agglomeration and action. The primary focus of this model is information exchange as the medium for these agent interactions. Our modeling and simulation study proposes to reveal interesting relationships in these perspectives, offer a foundation on which these disparate theories from economics and sociology can find common ground, and expand the use of agent-based modeling into entrepreneurship research.

Financial Regulation in an Agent Based Macroeconomic Model

OpenAIRE

Riccetti, Luca; Russo, Alberto; Mauro, Gallegati

2013-01-01

Starting from the agent-based decentralized matching macroeconomic model proposed in Riccetti et al. (2012), we explore the effects of banking regulation on macroeconomic dynamics. In particular, we study the overall credit exposure and the lending concentration towards a single counterparty, finding that the portfolio composition seems to be more relevant than the overall exposure for banking stability, even if both features are very important. We show that a too tight regulation is dangerou...

Moral Guilt : An Agent-Based Model Analysis

OpenAIRE

Gaudou , Benoit; Lorini , Emiliano; Mayor , Eunate

2013-01-01

International audience; In this article we analyze the influence of a concrete moral emotion (i.e. moral guilt) on strategic decision making. We present a normal form Prisoner’s Dilemma with a moral component. We assume that agents evaluate the game’s outcomes with respect to their ideality degree (i.e. how much a given outcome conforms to the player’s moral values), based on two proposed notions on ethical preferences: Harsanyi’s and Rawls’. Based on such game, we construct and agent-based m...

Agent-Based Model of Information Security System: Architecture and Formal Framework for Coordinated Intelligent Agents Behavior Specification

National Research Council Canada - National Science Library

Gorodetski, Vladimir

2001-01-01

The contractor will research and further develop the technology supporting an agent-based architecture for an information security system and a formal framework to specify a model of distributed knowledge...

Multi-agent based modeling for electric vehicle integration in a distribution network operation

DEFF Research Database (Denmark)

Hu, Junjie; Morais, Hugo; Lind, Morten

2016-01-01

The purpose of this paper is to present a multi-agent based modeling technology for simulating and operating a hierarchical energy management of a power distribution system with focus on EVs integration. The proposed multi-agent system consists of four types of agents: i) Distribution system...... operator (DSO) technical agent and ii) DSO market agents that both belong to the top layer of the hierarchy and their roles are to manage the distribution network by avoiding grid congestions and using congestion prices to coordinate the energy scheduled; iii) Electric vehicle virtual power plant agents...

Using Agent Base Models to Optimize Large Scale Network for Large System Inventories

Science.gov (United States)

Shameldin, Ramez Ahmed; Bowling, Shannon R.

2010-01-01

The aim of this paper is to use Agent Base Models (ABM) to optimize large scale network handling capabilities for large system inventories and to implement strategies for the purpose of reducing capital expenses. The models used in this paper either use computational algorithms or procedure implementations developed by Matlab to simulate agent based models in a principal programming language and mathematical theory using clusters, these clusters work as a high performance computational performance to run the program in parallel computational. In both cases, a model is defined as compilation of a set of structures and processes assumed to underlie the behavior of a network system.

Scopolamine provocation-based pharmacological MRI model for testing procognitive agents.

Science.gov (United States)

Hegedűs, Nikolett; Laszy, Judit; Gyertyán, István; Kocsis, Pál; Gajári, Dávid; Dávid, Szabolcs; Deli, Levente; Pozsgay, Zsófia; Tihanyi, Károly

2015-04-01

There is a huge unmet need to understand and treat pathological cognitive impairment. The development of disease modifying cognitive enhancers is hindered by the lack of correct pathomechanism and suitable animal models. Most animal models to study cognition and pathology do not fulfil either the predictive validity, face validity or construct validity criteria, and also outcome measures greatly differ from those of human trials. Fortunately, some pharmacological agents such as scopolamine evoke similar effects on cognition and cerebral circulation in rodents and humans and functional MRI enables us to compare cognitive agents directly in different species. In this paper we report the validation of a scopolamine based rodent pharmacological MRI provocation model. The effects of deemed procognitive agents (donepezil, vinpocetine, piracetam, alpha 7 selective cholinergic compounds EVP-6124, PNU-120596) were compared on the blood-oxygen-level dependent responses and also linked to rodent cognitive models. These drugs revealed significant effect on scopolamine induced blood-oxygen-level dependent change except for piracetam. In the water labyrinth test only PNU-120596 did not show a significant effect. This provocational model is suitable for testing procognitive compounds. These functional MR imaging experiments can be paralleled with human studies, which may help reduce the number of false cognitive clinical trials. © The Author(s) 2015.

Anti-SEMA3A Antibody: A Novel Therapeutic Agent to Suppress GBM Tumor Growth.

Science.gov (United States)

Lee, Jaehyun; Shin, Yong Jae; Lee, Kyoungmin; Cho, Hee Jin; Sa, Jason K; Lee, Sang-Yun; Kim, Seok-Hyung; Lee, Jeongwu; Yoon, Yeup; Nam, Do-Hyun

2017-11-10

Glioblastoma (GBM) is classified as one of the most aggressive and lethal brain tumor. Great strides have been made in understanding the genomic and molecular underpinnings of GBM, which translated into development of new therapeutic approaches to combat such deadly disease. However, there are only few therapeutic agents that can effectively inhibit GBM invasion in a clinical framework. In an effort to address such challenges, we have generated anti-SEMA3A monoclonal antibody as a potential therapeutic antibody against GBM progression. We employed public glioma datasets, Repository of Molecular Brain Neoplasia Data and The Cancer Genome Atlas, to analyze SEMA3A mRNA expression in human GBM specimens. We also evaluated for protein expression level of SEMA3A via tissue microarray (TMA) analysis. Cell migration and proliferation kinetics were assessed in various GBM patient-derived cells (PDCs) and U87-MG cell-line for SEMA3A antibody efficacy. GBM patient-derived xenograft (PDX) models were generated to evaluate tumor inhibitory effect of anti-SEMA3A antibody in vivo. By combining bioinformatics and TMA analysis, we discovered that SEMA3A is highly expressed in human GBM specimens compared to non-neoplastic tissues. We developed three different anti-SEMA3A antibodies, in fully human IgG form, through screening phage-displayed synthetic antibody library using a classical panning method. Neutralization of SEMA3A significantly reduced migration and proliferation capabilities of PDCs and U87-MG cell-line in vitro. In PDX models, treatment with anti-SEMA3A antibody exhibited notable tumor inhibitory effect through down-regulation of cellular proliferative kinetics and tumor-associated macrophages recruitment. In present study, we demonstrated tumor inhibitory effect of SEMA3A antibody in GBM progression and present its potential relevance as a therapeutic agent in a clinical framework.

Availability of perfluoroctylbromide (PFOB) emulsion used as agent in the liver tumor imaging of computed tomography (CT)

International Nuclear Information System (INIS)

Ozawa, Takachika

1986-01-01

We carried out a fundamental study on the availability of perfluoroctylbromide (PFOB) emulsion used as an agent in the liver tumor imaging of computed tomography (CT). For this study, we used emulsified yolk phospolipid as a surfactant for PFOB emulsion because it is generally considered to have higher safety relative to the administration to the humans. In the rabbits' liver tumor model in which VX 2 tumor cell was implanted into their livers, we observed increases in the CT values of the livers when 5 to 10 ml/kg of PFOB emulsion (20 % w/v) was administered into the vein, and also ringlike enhancement and increases in the CT values on the tumor rim when 20 ml/kg of PFOB emulsion was administered. In addition, in the chemical analysis of a gas chromatography, we also observed significant increases in the PFOB concentration on the tumor rim, compared with those of normal liver parenchyma, when 20 ml/kg of PFOB emulsion was given. In the finding of CT values in the human liver tumor by means of organ perfusion system, we recognized increases in the CT values (induced by the accumulation of PFOB emulsion) on the rim of the metastatic tumor of colon cancer. These results suggest that PFOB emulsion has certain availability as an agent for the liver tumor imaging of computed tomography (CT). (author)

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

Science.gov (United States)

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.

Lapse of time effects on tax evasion in an agent-based econophysics model

Science.gov (United States)

Seibold, Götz; Pickhardt, Michael

2013-05-01

We investigate an inhomogeneous Ising model in the context of tax evasion dynamics where different types of agents are parameterized via local temperatures and magnetic fields. In particular, we analyze the impact of lapse of time effects (i.e. backauditing) and endogenously determined penalty rates on tax compliance. Both features contribute to a microfoundation of agent-based econophysics models of tax evasion.

WE-E-17A-01: Characterization of An Imaging-Based Model of Tumor Angiogenesis

International Nuclear Information System (INIS)

Adhikarla, V; Jeraj, R

2014-01-01

Purpose: Understanding the transient dynamics of tumor oxygenation is important when evaluating tumor-vasculature response to anti-angiogenic therapies. An imaging-based tumor-vasculature model was used to elucidate factors that affect these dynamics. Methods: Tumor growth depends on its doubling time (Td). Hypoxia increases pro-angiogenic factor (VEGF) concentration which is modeled to reduce vessel perfusion, attributing to its effect of increasing vascular permeability. Perfused vessel recruitment depends on the existing perfused vasculature, VEGF concentration and maximum VEGF concentration (VEGFmax) for vessel dysfunction. A convolution-based algorithm couples the tumor to the normal tissue vessel density (VD-nt). The parameters are benchmarked to published pre-clinical data and a sensitivity study evaluating the changes in the peak and time to peak tumor oxygenation characterizes them. The model is used to simulate changes in hypoxia and proliferation PET imaging data obtained using [Cu- 61]Cu-ATSM and [F-18]FLT respectively. Results: Td and VD-nt were found to be the most influential on peak tumor pO2 while VEGFmax was marginally influential. A +20 % change in Td, VD-nt and VEGFmax resulted in +50%, +25% and +5% increase in peak pO2. In contrast, Td was the most influential on the time to peak oxygenation with VD-nt and VEGFmax playing marginal roles. A +20% change in Td, VD-nt and VEGFmax increased the time to peak pO2 by +50%, +5% and +0%. A −20% change in the above parameters resulted in comparable decreases in the peak and time to peak pO2. Model application to the PET data was able to demonstrate the voxel-specific changes in hypoxia of the imaged tumor. Conclusion: Tumor-specific doubling time and vessel density are important parameters to be considered when evaluating hypoxia transients. While the current model simulates the oxygen dynamics of an untreated tumor, incorporation of therapeutic effects can make the model a potent tool for analyzing

MRI monitoring of tumor response following angiogenesis inhibition in an experimental human breast cancer model

International Nuclear Information System (INIS)

Turetschek, Karl; Preda, Anda; Shames, David M.; Novikov, Viktor; Roberts, Timothy P.L.; Fu, Yanjun; Brasch, Robert C.; Floyd, Eugenia; Carter, Wayne O.; Wood, Jeanette M.

2003-01-01

The aim of this study was to evaluate the potential of dynamic magnetic resonance imaging (MRI) enhanced by macromolecular contrast agents to monitor noninvasively the therapeutic effect of an anti-angiogenesis VEGF receptor kinase inhibitor in an experimental cancer model. MDA-MB-435, a poorly differentiated human breast cancer cell line, was implanted into the mammary fat pad in 20 female homozygous athymic rats. Animals were assigned randomly to a control (n=10) or drug treatment group (n=10). Baseline dynamic MRI was performed on sequential days using albumin-(GdDTPA) 30 (6.0 nm diameter) and ultrasmall superparamagnetic iron oxide (USPIO) particles (30 nm diameter). Subjects were treated either with PTK787/ZK 222584, a VEGF receptor tyrosine kinase inhibitor, or saline given orally twice daily for 1 week followed by repeat MRI examinations serially using each contrast agent. Employing a unidirectional kinetic model comprising the plasma and interstitial water compartments, tumor microvessel characteristics including fractional plasma volume and transendothelial permeability (K PS ) were estimated for each contrast medium. Tumor growth and the microvascular density, a histologic surrogate of angiogenesis, were also measured. Control tumors significantly increased (P PS ) based on MRI assays using both macromolecular contrast media. In contrast, tumor growth was significantly reduced (P PS values declined slightly. Estimated values for the fractional plasma volume did not differ significantly between treatment groups or contrast agents. Microvascular density counts correlated fairly with the tumor growth rate (r=0.64) and were statistically significant higher (P PS ), using either of two macromolecular contrast media, were able to detect effects of treatment with a VEGF receptor tyrosine kinase inhibitor on tumor vascular permeability. In a clinical setting such quantitative MRI measurements could be used to monitor tumor anti-angiogenesis therapy. (orig.)

The effect of anti-tumor necrosis factor alpha agents on postoperative anastomotic complications in Crohn's disease

DEFF Research Database (Denmark)

El-Hussuna, Alaa Abdul-Hussein H; Krag, Aleksander; Olaison, Gunnar

2013-01-01

Patients with Crohn's disease treated with anti-tumor necrosis factor alpha agents may have an increased risk of surgical complications.......Patients with Crohn's disease treated with anti-tumor necrosis factor alpha agents may have an increased risk of surgical complications....

A Functional Iron Oxide Nanoparticles Modified with PLA-PEG-DG as Tumor-Targeted MRI Contrast Agent.

Science.gov (United States)

Xiong, Fei; Hu, Ke; Yu, Haoli; Zhou, Lijun; Song, Lina; Zhang, Yu; Shan, Xiuhong; Liu, Jianping; Gu, Ning

2017-08-01

Tumor targeting could greatly promote the performance of magnetic nanomaterials as MRI (Magnetic Resonance Imaging) agent for tumor diagnosis. Herein, we reported a novel magnetic nanoparticle modified with PLA (poly lactic acid)-PEG (polyethylene glycol)-DG (D-glucosamine) as Tumor-targeted MRI Contrast Agent. In this work, we took use of the D-glucose passive targeting on tumor cells, combining it on PLA-PEG through amide reaction, and then wrapped the PLA-PEG-DG up to the Fe 3 O 4 @OA NPs. The stability and anti phagocytosis of Fe 3 O 4 @OA@PLA-PEG-DG was tested in vitro; the MRI efficiency and toxicity was also detected in vivo. These functional magnetic nanoparticles demonstrated good biocompatibility and stability both in vitro and in vivo. Cell experiments showed that Fe 3 O 4 @OA@PLA-PEG-DG nanoparticles exist good anti phagocytosis and high targetability. In vivo MRI images showed that the contrast effect of Fe 3 O 4 @OA@PLA-PEG-DG nanoparticles prevailed over the commercial non tumor-targeting magnetic nanomaterials MRI agent at a relatively low dose. The DG can validly enhance the tumor-targetting effect of Fe 3 O 4 @OA@PLA-PEG nanoparticle. Maybe MRI agents with DG can hold promise as tumor-targetting development in the future.

X-ray Scatter Imaging of Hepatocellular Carcinoma in a Mouse Model Using Nanoparticle Contrast Agents

Science.gov (United States)

Rand, Danielle; Derdak, Zoltan; Carlson, Rolf; Wands, Jack R.; Rose-Petruck, Christoph

2015-10-01

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide and is almost uniformly fatal. Current methods of detection include ultrasound examination and imaging by CT scan or MRI; however, these techniques are problematic in terms of sensitivity and specificity, and the detection of early tumors (<1 cm diameter) has proven elusive. Better, more specific, and more sensitive detection methods are therefore urgently needed. Here we discuss the application of a newly developed x-ray imaging technique called Spatial Frequency Heterodyne Imaging (SFHI) for the early detection of HCC. SFHI uses x-rays scattered by an object to form an image and is more sensitive than conventional absorption-based x-radiography. We show that tissues labeled in vivo with gold nanoparticle contrast agents can be detected using SFHI. We also demonstrate that directed targeting and SFHI of HCC tumors in a mouse model is possible through the use of HCC-specific antibodies. The enhanced sensitivity of SFHI relative to currently available techniques enables the x-ray imaging of tumors that are just a few millimeters in diameter and substantially reduces the amount of nanoparticle contrast agent required for intravenous injection relative to absorption-based x-ray imaging.

Oleuropein, a non-toxic olive iridoid, is an anti-tumor agent and cytoskeleton disruptor

International Nuclear Information System (INIS)

Hamdi, Hamdi K.; Castellon, Raquel

2005-01-01

Oleuropein, a non-toxic secoiridoid derived from the olive tree, is a powerful antioxidant and anti-angiogenic agent. Here, we show it to be a potent anti-cancer compound, directly disrupting actin filaments in cells and in a cell-free assay. Oleuropein inhibited the proliferation and migration of advanced-grade tumor cell lines in a dose-responsive manner. In a novel tube-disruption assay, Oleuropein irreversibly rounded cancer cells, preventing their replication, motility, and invasiveness; these effects were reversible in normal cells. When administered orally to mice that developed spontaneous tumors, Oleuropein completely regressed tumors in 9-12 days. When tumors were resected prior to complete regression, they lacked cohesiveness and had a crumbly consistency. No viable cells could be recovered from these tumors. These observations elevate Oleuropein from a non-toxic antioxidant into a potent anti-tumor agent with direct effects against tumor cells. Our data may also explain the cancer-protective effects of the olive-rich Mediterranean diet

Using data-driven agent-based models for forecasting emerging infectious diseases

Directory of Open Access Journals (Sweden)

Srinivasan Venkatramanan

2018-03-01

Full Text Available Producing timely, well-informed and reliable forecasts for an ongoing epidemic of an emerging infectious disease is a huge challenge. Epidemiologists and policy makers have to deal with poor data quality, limited understanding of the disease dynamics, rapidly changing social environment and the uncertainty on effects of various interventions in place. Under this setting, detailed computational models provide a comprehensive framework for integrating diverse data sources into a well-defined model of disease dynamics and social behavior, potentially leading to better understanding and actions. In this paper, we describe one such agent-based model framework developed for forecasting the 2014–2015 Ebola epidemic in Liberia, and subsequently used during the Ebola forecasting challenge. We describe the various components of the model, the calibration process and summarize the forecast performance across scenarios of the challenge. We conclude by highlighting how such a data-driven approach can be refined and adapted for future epidemics, and share the lessons learned over the course of the challenge. Keywords: Emerging infectious diseases, Agent-based models, Simulation optimization, Bayesian calibration, Ebola

The vascular disrupting agent ZD6126 shows increased antitumor efficacy and enhanced radiation response in large, advanced tumors

International Nuclear Information System (INIS)

Siemann, Dietmar W.; Rojiani, Amyn M.

2005-01-01

Purpose: ZD6126 is a vascular-targeting agent that induces selective effects on the morphology of proliferating and immature endothelial cells by disrupting the tubulin cytoskeleton. The efficacy of ZD6126 was investigated in large vs. small tumors in a variety of animal models. Methods and Materials: Three rodent tumor models (KHT, SCCVII, RIF-1) and three human tumor xenografts (Caki-1, KSY-1, SKBR3) were used. Mice bearing leg tumors ranging in size from 0.1-2.0 g were injected intraperitoneally with a single 150 mg/kg dose of ZD6126. The response was assessed by morphologic and morphometric means as well as an in vivo to in vitro clonogenic cell survival assay. To examine the impact of tumor size on the extent of enhancement of radiation efficacy by ZD6126, KHT sarcomas of three different sizes were irradiated locally with a range of radiation doses, and cell survival was determined. Results: All rodent tumors and human tumor xenografts evaluated showed a strong correlation between increasing tumor size and treatment effect as determined by clonogenic cell survival. Detailed evaluation of KHT sarcomas treated with ZD6126 showed a reduction in patent tumor blood vessels that was ∼20% in small ( 90% in large (>1.0 g) tumors. Histologic assessment revealed that the extent of tumor necrosis after ZD6126 treatment, although minimal in small KHT sarcomas, became more extensive with increasing tumor size. Clonogenic cell survival after ZD6126 exposure showed a decrease in tumor surviving fraction from approximately 3 x 10 -1 to 1 x 10 -4 with increasing tumor size. When combined with radiotherapy, ZD6126 treatment resulted in little enhancement of the antitumor effect of radiation in small (<0.3 g) tumors but marked increases in cell kill in tumors larger than 1.0 g. Conclusions: Because bulky neoplastic disease is typically the most difficult to manage, the present findings provide further support for the continued development of vascular disrupting agents such as

CASCADE: An Agent Based Framework For Modeling The Dynamics Of Smart Electricity Systems

OpenAIRE

Rylatt, R. M.; Gammon, Rupert; Boait, Peter John; Varga, L.; Allen, P.; Savill, M.; Snape, J. Richard; Lemon, Mark; Ardestani, B. M.; Pakka, V. H.; Fletcher, G.; Smith, S.; Fan, D.; Strathern, M.

2013-01-01

Collaborative project with Cranfield University The Complex Adaptive Systems, Cognitive Agents and Distributed Energy (CASCADE) project is developing a framework based on Agent Based Modelling (ABM). The CASCADE Framework can be used both to gain policy and industry relevant insights into the smart grid concept itself and as a platform to design and test distributed ICT solutions for smart grid based business entities. ABM is used to capture the behaviors of diff erent socia...

Evolutionary Agent-based Models to design distributed water management strategies

Science.gov (United States)

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

Story telling engine based on agent interaction

OpenAIRE

Porcel, Juan Carlos

2008-01-01

Comics have been used as a programming tool for agents, giving them instructions on how to act. In this thesis I do this in reverse, I use comics to describe the actions of agents already interacting with each other to create a storytelling engine that dynamically generate stories, based on the interaction of said agents. The model for the agent behaviours is based on the improvisational puppets model of Barbara Hayes-Roth. This model is chosen due to the nature of comics themselves. Comics ...

A review of agent-based models for forecasting the deployment of distributed generation in energy systems

NARCIS (Netherlands)

Veneman, J.F.; Oey, M.A.; Kortmann, L.J.; Brazier, F.M.; De Vries, L.J.

2011-01-01

Agent-based models are seeing increasing use in the study of distributed generation (DG) deployment. Researchers and decision makers involved in the implementation of DG have been lacking a concise overview of why they should consider using agent-based modeling (ABM) for forecasting purposes. Since

Effect of Au-dextran NPs as anti-tumor agent against EAC and solid tumor in mice by biochemical evaluations and histopathological investigations.

Science.gov (United States)

Medhat, Dalia; Hussein, Jihan; El-Naggar, Mehrez E; Attia, Mohamed F; Anwar, Mona; Latif, Yasmine Abdel; Booles, Hoda F; Morsy, Safaa; Farrag, Abdel Razik; Khalil, Wagdy K B; El-Khayat, Zakaria

2017-07-01

Dextran-capped gold nanoparticles (Au-dextran NPs) were prepared exploiting the natural polysaccharide polymer as both reducing and stabilizing agent in the synthesis process, aiming at studying their antitumor effect on solid carcinoma and EAC-bearing mice. To this end, Au-dextran NPs were designed via simple eco-friendly chemical reaction and they were characterized revealing the monodispersed particles with narrow distributed size of around 49nm with high negative charge. In vivo experiments were performed on mice. Biochemical analysis of liver and kidney functions and oxidation stress ratio in addition to histopathological investigations of such tumor tissues were done demonstrating the potentiality of Au-dextran NPs as antitumor agent. The obtained results revealed that EAC and solid tumors caused significant increase in liver and kidney functions, liver oxidant parameters, alpha feto protein levels and diminished liver antioxidant accompanied by positive expression of tumor protein p53 of liver while the treatment with Au-dextran NPs for both types caused improvement in liver and kidney functions, increased liver antioxidant, increased the expression level of B-cell lymphoma 2 gene and subsequently suppressed the apoptotic pathway. As a result, the obtained data provides significant antitumor effects of the Au-dextran NPs in both Ehrlich ascites and solid tumor in mice models. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Strengthening Theoretical Testing in Criminology Using Agent-based Modeling.

Science.gov (United States)

Johnson, Shane D; Groff, Elizabeth R

2014-07-01

The Journal of Research in Crime and Delinquency ( JRCD ) has published important contributions to both criminological theory and associated empirical tests. In this article, we consider some of the challenges associated with traditional approaches to social science research, and discuss a complementary approach that is gaining popularity-agent-based computational modeling-that may offer new opportunities to strengthen theories of crime and develop insights into phenomena of interest. Two literature reviews are completed. The aim of the first is to identify those articles published in JRCD that have been the most influential and to classify the theoretical perspectives taken. The second is intended to identify those studies that have used an agent-based model (ABM) to examine criminological theories and to identify which theories have been explored. Ecological theories of crime pattern formation have received the most attention from researchers using ABMs, but many other criminological theories are amenable to testing using such methods. Traditional methods of theory development and testing suffer from a number of potential issues that a more systematic use of ABMs-not without its own issues-may help to overcome. ABMs should become another method in the criminologists toolbox to aid theory testing and falsification.

Diffusion and Aggregation in an Agent Based Model of Stock Market Fluctuations

Science.gov (United States)

Castiglione, Filippo

We describe a new model to simulate the dynamic interactions between market price and the decisions of two different kind of traders. They possess spatial mobility allowing to group together to form coalitions. Each coalition follows a strategy chosen from a proportional voting ``dominated'' by a leader's decision. The interplay of both kind of agents gives rise to complex price dynamics that is consistent with the main stylized facts of financial time series. The present model incorporates many features of other known models and is meant to be the first step toward the construction of an agent-based model that uses more realistic markets rules, strategies, and information structures.

An Agent Model Integrating an Adaptive Model for Environmental Dynamics

NARCIS (Netherlands)

Treur, J.; Umair, M.

2011-01-01

The environments in which agents are used often may be described by dynamical models, e.g., in the form of a set of differential equations. In this paper, an agent model is proposed that can perform model-based reasoning about the environment, based on a numerical (dynamical system) model of the

An agent-based model for energy service companies

International Nuclear Information System (INIS)

Robinson, Marguerite; Varga, Liz; Allen, Peter

2015-01-01

Highlights: • An agent-based model for household energy efficiency upgrades is considered. • Energy service companies provide an alternative to traditional utility providers. • Household self-financing is a limiting factor to widespread efficiency upgrading. • Longer term service contracts can lead to reduced household energy costs. • Future energy price increases enable service providers to retain their customer base. - Abstract: The residential housing sector is a major consumer of energy accounting for approximately one third of carbon emissions in the United Kingdom. Achieving a sustainable, low-carbon infrastructure necessitates a reduced and more efficient use of domestic energy supplies. Energy service companies offer an alternative to traditional providers, which supply a single utility product to satisfy the unconstrained demand of end users, and have been identified as a potentially important actor in sustainable future economies. An agent-based model is developed to examine the potential of energy service companies to contribute to the large scale upgrading of household energy efficiency, which would ultimately lead to a more sustainable and secure energy infrastructure. The migration of households towards energy service companies is described by an attractiveness array, through which potential customers can evaluate the future benefits, in terms of household energy costs, of changing provider. It is shown that self-financing is a limiting factor to the widespread upgrading of residential energy efficiency. Greater reductions in household energy costs could be achieved by committing to longer term contracts, allowing upgrade costs to be distributed over greater time intervals. A steadily increasing cost of future energy usage lends an element of stability to the market, with energy service companies displaying the ability to retain customers on contract expiration. The model highlights how a greater focus on the provision of energy services, as

Using the Agent-Based Modeling in Economic Field

Directory of Open Access Journals (Sweden)

Nora Mihail

2006-12-01

Full Text Available The last ten years of the XX century has been the witnesses of the apparition of a new scientific field, which is usually defined as the study of “Complex adaptive systems”. This field, generic named Complexity Sciences, shares its subject, the general proprieties of complex systems across traditional disciplinary boundaries, with cybernetics and general systems theory. But the development of Complexity Sciences approaches is determined by the extensive use of Agent-Based-Models (ABM as a research tool and an emphasis on systems, such as markets, populations or ecologies, which are less integrated or “organized” than the ones, such as companies and economies, intensively studied by the traditional disciplines. For ABM, a complex system is a system of individual agents who have the freedom to act in ways that are not always totally predictable, and whose actions are interconnected such that one agent’s actions changes the context (environment for other agents. These are many examples of such complex systems: the stock market, the human body immune system, a business organization, an institution, a work-team, a family etc.

Agent-based model of angiogenesis simulates capillary sprout initiation in multicellular networks.

Science.gov (United States)

Walpole, J; Chappell, J C; Cluceru, J G; Mac Gabhann, F; Bautch, V L; Peirce, S M

2015-09-01

Many biological processes are controlled by both deterministic and stochastic influences. However, efforts to model these systems often rely on either purely stochastic or purely rule-based methods. To better understand the balance between stochasticity and determinism in biological processes a computational approach that incorporates both influences may afford additional insight into underlying biological mechanisms that give rise to emergent system properties. We apply a combined approach to the simulation and study of angiogenesis, the growth of new blood vessels from existing networks. This complex multicellular process begins with selection of an initiating endothelial cell, or tip cell, which sprouts from the parent vessels in response to stimulation by exogenous cues. We have constructed an agent-based model of sprouting angiogenesis to evaluate endothelial cell sprout initiation frequency and location, and we have experimentally validated it using high-resolution time-lapse confocal microscopy. ABM simulations were then compared to a Monte Carlo model, revealing that purely stochastic simulations could not generate sprout locations as accurately as the rule-informed agent-based model. These findings support the use of rule-based approaches for modeling the complex mechanisms underlying sprouting angiogenesis over purely stochastic methods.

Emergence of heterogeneity in an agent-based model

OpenAIRE

Abdullah, Wan Ahmad Tajuddin Wan

2002-01-01

We study an interacting agent model of a game-theoretical economy. The agents play a minority-subsequently-majority game and they learn, using backpropagation networks, to obtain higher payoffs. We study the relevance of heterogeneity to performance, and how heterogeneity emerges.

Multi-issue Agent Negotiation Based on Fairness

Science.gov (United States)

Zuo, Baohe; Zheng, Sue; Wu, Hong

Agent-based e-commerce service has become a hotspot now. How to make the agent negotiation process quickly and high-efficiently is the main research direction of this area. In the multi-issue model, MAUT(Multi-attribute Utility Theory) or its derived theory usually consider little about the fairness of both negotiators. This work presents a general model of agent negotiation which considered the satisfaction of both negotiators via autonomous learning. The model can evaluate offers from the opponent agent based on the satisfaction degree, learn online to get the opponent's knowledge from interactive instances of history and negotiation of this time, make concessions dynamically based on fair object. Through building the optimal negotiation model, the bilateral negotiation achieved a higher efficiency and fairer deal.

Modeling Multi-Mobile Agents System Based on Coalition Signature Mechanism Using UML

Institute of Scientific and Technical Information of China (English)

SUNZhixin; HUANGHaiping; WANGRuchuan

2004-01-01

With the development of electronic commerce and agent techniques, multi-mobile agents cooperation can not only improve the efficiency of electronic business trade, but more importantly, it has a comprehensive applicative value in solving the security issues of mobile agent system. This paper firstly describes the mechanism of multi-mobile agents coalition signature aiming at the system security. Subsequently it brings forward a basic architecture of Multi-mobile agents system (MMAS) based on the design pattern of multi-mobile agents. The paper uses the diagrs_rn of UML, such as use case diagram, class diagram and sequence diagram to build the detailed model of the coalition signature and multi-mobile agents cooperation results. Through security analysis, we find that multimobile agents cooperation and interaction can solve some security problems of mobile agents in transfer, and also it can improve the efficiency of business trade. These results indicate that MMAS has a high security performance and can be widely used in E-commerce trade.

Agent Based Modeling on Organizational Dynamics of Terrorist Network

Directory of Open Access Journals (Sweden)

Bo Li

2015-01-01

Full Text Available Modeling organizational dynamics of terrorist network is a critical issue in computational analysis of terrorism research. The first step for effective counterterrorism and strategic intervention is to investigate how the terrorists operate with the relational network and what affects the performance. In this paper, we investigate the organizational dynamics by employing a computational experimentation methodology. The hierarchical cellular network model and the organizational dynamics model are developed for modeling the hybrid relational structure and complex operational processes, respectively. To intuitively elucidate this method, the agent based modeling is used to simulate the terrorist network and test the performance in diverse scenarios. Based on the experimental results, we show how the changes of operational environments affect the development of terrorist organization in terms of its recovery and capacity to perform future tasks. The potential strategies are also discussed, which can be used to restrain the activities of terrorists.

Modeling and simulation of virtual human's coordination based on multi-agent systems

Science.gov (United States)

Zhang, Mei; Wen, Jing-Hua; Zhang, Zu-Xuan; Zhang, Jian-Qing

2006-10-01

The difficulties and hotspots researched in current virtual geographic environment (VGE) are sharing space and multiusers operation, distributed coordination and group decision-making. The theories and technologies of MAS provide a brand-new environment for analysis, design and realization of distributed opening system. This paper takes cooperation among virtual human in VGE which multi-user participate in as main researched object. First we describe theory foundation truss of VGE, and present the formalization description of Multi-Agent System (MAS). Then we detailed analyze and research arithmetic of collectivity operating behavior learning of virtual human based on best held Genetic Algorithm(GA), and establish dynamics action model which Multi-Agents and object interact dynamically and colony movement strategy. Finally we design a example which shows how 3 evolutional Agents cooperate to complete the task of colony pushing column box, and design a virtual world prototype of virtual human pushing box collectively based on V-Realm Builder 2.0, moreover we make modeling and dynamic simulation with Simulink 6.

Agent-based modeling and simulation of clean heating system adoption in Norway

Energy Technology Data Exchange (ETDEWEB)

Sopha, Bertha Maya

2011-03-15

A sound climate policy encouraging clean energy investment is important to mitigate global warming. Previous research has demonstrated that consumer choice indeed plays an important role in adoption of sustainable technologies. This thesis strives to gain a better understanding of consumers' decision-making on heating systems and to explore the potential application of agent-based modeling (ABM) in exploring mechanism underlying adoption in which heating system adoption by Norwegian households is taken up as a case study. An interdisciplinary approach, applying various established theories including those of psychology, is applied to create a model for consumer behavior and implement this behavior in an Agent-Based Model (ABM) to simulate heating technology diffusion. A mail-survey, carried out in autumn 2008, is a means to collect information for parameterizing the agent-based model, for gaining empirical facts, and for validating the developed model at micro-level. Survey sample consisted of 1500 Norwegian households drawn from population register and 1500 wood pellet users in Norway. The response rates were 10.3% and 34.6% for population sample and wood pellet sample respectively. This study is divided into two parts; empirical analysis and agent-based simulation. The empirical analysis aims at fully understanding the important aspects of adoption decision and their implications, in order to assist simulation. The analysis particularly contributes to the identification of differences/similarities between adopters and non adopters of wood pellet heating with respects to some key points of adoption derived from different theories, psychological factors underlying the adoption-decision of wood pellet heating, and the rationales underlying Norwegian households' decisions regarding their future heating system. The simulation study aims at exploring the mechanism of heterogeneous household decision-making giving rise to the diffusion of heating systems, and

Investigating immune system aging: system dynamics and agent-based modeling

OpenAIRE

Figueredo, Grazziela; Aickelin, Uwe

2010-01-01

System dynamics and agent based simulation models can\\ud both be used to model and understand interactions of entities within a population. Our modeling work presented here is concerned with understanding the suitability of the different types of simulation for the immune system aging problems and comparing their results. We are trying to answer questions such as: How fit is the immune system given a certain age? Would an immune boost be of therapeutic value, e.g. to improve the effectiveness...

A framework to specify agent-based models in geographic sciences

OpenAIRE

Grueau, Cédric; Araújo, João

2015-01-01

Agent-Based Modeling (ABM) and simulation have gained popularity in the Geographic Information Systems (GIS) domain. Despite the increasing number of models built by experts and users, it remains challenging for users to specify their models in a manner in which one can understand it. This constraint represents an inhibition to the development and acceptance of the ABM approach. In this paper, we raise the questions that need to be answered in order to cope with ABM specification issues. We r...

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

Science.gov (United States)

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

Is the person-situation debate important for agent-based modeling and vice-versa?

Directory of Open Access Journals (Sweden)

Katarzyna Sznajd-Weron

Full Text Available Agent-based models (ABM are believed to be a very powerful tool in the social sciences, sometimes even treated as a substitute for social experiments. When building an ABM we have to define the agents and the rules governing the artificial society. Given the complexity and our limited understanding of the human nature, we face the problem of assuming that either personal traits, the situation or both have impact on the social behavior of agents. However, as the long-standing person-situation debate in psychology shows, there is no consensus as to the underlying psychological mechanism and the important question that arises is whether the modeling assumptions we make will have a substantial influence on the simulated behavior of the system as a whole or not.Studying two variants of the same agent-based model of opinion formation, we show that the decision to choose either personal traits or the situation as the primary factor driving social interactions is of critical importance. Using Monte Carlo simulations (for Barabasi-Albert networks and analytic calculations (for a complete graph we provide evidence that assuming a person-specific response to social influence at the microscopic level generally leads to a completely different and less realistic aggregate or macroscopic behavior than an assumption of a situation-specific response; a result that has been reported by social psychologists for a range of experimental setups, but has been downplayed or ignored in the opinion dynamics literature.This sensitivity to modeling assumptions has far reaching consequences also beyond opinion dynamics, since agent-based models are becoming a popular tool among economists and policy makers and are often used as substitutes of real social experiments.

An agent-based model for integrated emotion regulation and contagion in socially affected decision making

NARCIS (Netherlands)

Manzoor, A.; Treur, J.

2015-01-01

This paper addresses an agent-based computational social agent model for the integration of emotion regulation, emotion contagion and decision making in a social context. The model integrates emotion-related valuing, in order to analyse the role of emotions in socially affected decision making. The

Radiotherapy planning for glioblastoma based on a tumor growth model: improving target volume delineation

Science.gov (United States)

Unkelbach, Jan; Menze, Bjoern H.; Konukoglu, Ender; Dittmann, Florian; Le, Matthieu; Ayache, Nicholas; Shih, Helen A.

2014-02-01

Glioblastoma differ from many other tumors in the sense that they grow infiltratively into the brain tissue instead of forming a solid tumor mass with a defined boundary. Only the part of the tumor with high tumor cell density can be localized through imaging directly. In contrast, brain tissue infiltrated by tumor cells at low density appears normal on current imaging modalities. In current clinical practice, a uniform margin, typically two centimeters, is applied to account for microscopic spread of disease that is not directly assessable through imaging. The current treatment planning procedure can potentially be improved by accounting for the anisotropy of tumor growth, which arises from different factors: anatomical barriers such as the falx cerebri represent boundaries for migrating tumor cells. In addition, tumor cells primarily spread in white matter and infiltrate gray matter at lower rate. We investigate the use of a phenomenological tumor growth model for treatment planning. The model is based on the Fisher-Kolmogorov equation, which formalizes these growth characteristics and estimates the spatial distribution of tumor cells in normal appearing regions of the brain. The target volume for radiotherapy planning can be defined as an isoline of the simulated tumor cell density. This paper analyzes the model with respect to implications for target volume definition and identifies its most critical components. A retrospective study involving ten glioblastoma patients treated at our institution has been performed. To illustrate the main findings of the study, a detailed case study is presented for a glioblastoma located close to the falx. In this situation, the falx represents a boundary for migrating tumor cells, whereas the corpus callosum provides a route for the tumor to spread to the contralateral hemisphere. We further discuss the sensitivity of the model with respect to the input parameters. Correct segmentation of the brain appears to be the most

Radiotherapy planning for glioblastoma based on a tumor growth model: improving target volume delineation

International Nuclear Information System (INIS)

Unkelbach, Jan; Dittmann, Florian; Le, Matthieu; Shih, Helen A; Menze, Bjoern H; Ayache, Nicholas; Konukoglu, Ender

2014-01-01

Glioblastoma differ from many other tumors in the sense that they grow infiltratively into the brain tissue instead of forming a solid tumor mass with a defined boundary. Only the part of the tumor with high tumor cell density can be localized through imaging directly. In contrast, brain tissue infiltrated by tumor cells at low density appears normal on current imaging modalities. In current clinical practice, a uniform margin, typically two centimeters, is applied to account for microscopic spread of disease that is not directly assessable through imaging. The current treatment planning procedure can potentially be improved by accounting for the anisotropy of tumor growth, which arises from different factors: anatomical barriers such as the falx cerebri represent boundaries for migrating tumor cells. In addition, tumor cells primarily spread in white matter and infiltrate gray matter at lower rate. We investigate the use of a phenomenological tumor growth model for treatment planning. The model is based on the Fisher–Kolmogorov equation, which formalizes these growth characteristics and estimates the spatial distribution of tumor cells in normal appearing regions of the brain. The target volume for radiotherapy planning can be defined as an isoline of the simulated tumor cell density. This paper analyzes the model with respect to implications for target volume definition and identifies its most critical components. A retrospective study involving ten glioblastoma patients treated at our institution has been performed. To illustrate the main findings of the study, a detailed case study is presented for a glioblastoma located close to the falx. In this situation, the falx represents a boundary for migrating tumor cells, whereas the corpus callosum provides a route for the tumor to spread to the contralateral hemisphere. We further discuss the sensitivity of the model with respect to the input parameters. Correct segmentation of the brain appears to be the most

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

Science.gov (United States)

Dickes, Amanda Catherine; Sengupta, Pratim

2013-01-01

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…

Gastric stromal tumor: two-phase dynamic CT findings with water as oral contrast agents

International Nuclear Information System (INIS)

Lee, Se Hyo; Cho, June Sik; Shin, Kyung Sook; Jeong, Ki Ho; Park, Jin Yong; Yu, Ho Jun; Kim, Young Min; Jeon, Kwang Jin

2000-01-01

To evaluate two-phase dynamic CT with water as oral contrast agents in the CT diagnosis of gastric stromal tumors. We retrospectively reviewed the CT findings in 21 patients with pathologically proven gastric stromal tumors. Six were found to be benign, twelve were malignant, and there were three cases of STUMP (stromal tumor uncertain malignant potential). Two-phase dynamic CT scans with water as oral contrast agents were obtained 60-70 secs (portal phase) and 3 mins (equilibrium phase) after the start of IV contrast administration. We determined the size, growth pattern, and enhancement pattern of the tumors and overlying mucosa, the presence or absence of ulceration and necrosis, tumor extent, and lymph nod and distant metastasis. The CT and pathologic findings were correlated. All six benign tumors and three STUMP were less than 5.5 cm in size, and during the portal phase showed round endogastric masses with highly enhanced, intact overlying mucosa. Twelve malignant tumors were 4.5-15.5 cm in size (mean, 11.5 cm); an endogastric mass was seen in three cases, an exogastric mass in one, and a mixed pattern in eight. On portal phase images the tumors were not significantly enhanced, but highly enhanced feeding vessels were noted in five larger tumors (greater than 10 cm). All 12 malignant tumors showed ulceration and necrosis, and interruption of overlying mucosa was clearly seen during the portal phase. We were readily able to evaluate tumor extent during this phase, and in ten malignant tumors there was no invasion of adjacent organs. Seven malignant tumors showed air density within their necrotic portion (p less than 0.05). On equilibrium phase images, all malignant tumors showed heterogeneous enhancement due to necrosis, and poorly enhanced overlying mucosa. Dynamic CT during the portal phase with water as oral contrast agents was useful for depicting the submucosal origin of gastric stromal tumors and for evaluating the extent of malignant stromal tumors. Our

A Multi Agent Based Model for Airport Service Planning

Directory of Open Access Journals (Sweden)

W.H. Ip

2010-09-01

Full Text Available Aviation industry is highly dynamic and demanding in nature that time and safety are the two most important factors while one of the major sources of delay is aircraft on ground because of it complexity, a lot of machinery like vehicles are involved and lots of communication are involved. As one of the aircraft ground services providers in Hong Kong International Airport, China Aircraft Services Limited (CASL aims to increase competitiveness by better its service provided while minimizing cost is also needed. One of the ways is to optimize the number of maintenance vehicles allocated in order to minimize chance of delay and also operating costs. In the paper, an agent-based model is proposed for support decision making in vehicle allocation. The overview of the aircrafts ground services procedures is firstly mentioned with different optimization methods suggested by researchers. Then, the agent-based approach is introduced and in the latter part of report and a multi-agent system is built and proposed which is decision supportive for CASL in optimizing the maintenance vehicles' allocation. The application provides flexibility for inputting number of different kinds of vehicles, simulation duration and aircraft arrival rate in order to simulation different scenarios which occurs in HKIA.

Creating Agent-Based Energy Transition Management Models That Can Uncover Profitable Pathways to Climate Change Mitigation

Directory of Open Access Journals (Sweden)

Auke Hoekstra

2017-01-01

Full Text Available The energy domain is still dominated by equilibrium models that underestimate both the dangers and opportunities related to climate change. In reality, climate and energy systems contain tipping points, feedback loops, and exponential developments. This paper describes how to create realistic energy transition management models: quantitative models that can discover profitable pathways from fossil fuels to renewable energy. We review the literature regarding agent-based economics, disruptive innovation, and transition management and determine the following requirements. Actors must be detailed, heterogeneous, interacting, learning, and strategizing. Technology should be represented as a detailed and heterogeneous portfolio that can develop in a bottom-up manner, using endogenous feedback loops. Assumptions about discount rates and the social cost of carbon should be configurable. The model should contain interactions between the global, national, local, and individual level. A review of modelling techniques shows that equilibrium models are unsuitable and that system dynamics and discrete event simulation are too limited. The agent-based approach is found to be uniquely suited for the complex adaptive sociotechnical systems that must be modelled. But the choice for agent-based models does not mean a rejection of other approaches because they can be accommodated within the agent-based framework. We conclude with practical guidelines.

Radioiodinated VEGF to image tumor angiogenesis in a LS180 tumor xenograft model

International Nuclear Information System (INIS)

Yoshimoto, Mitsuyoshi; Kinuya, Seigo; Kawashima, Atsuhiro; Nishii, Ryuichi; Yokoyama, Kunihiko; Kawai, Keiichi

2006-01-01

Introduction: Angiogenesis is essential for tumor growth or metastasis. A method involving noninvasive detection of angiogenic activity in vivo would provide diagnostic information regarding antiangiogenic therapy targeting vascular endothelial cells as well as important insight into the role of vascular endothelial growth factor (VEGF) and its receptor (flt-1 and KDR) system in tumor biology. We evaluated radioiodinated VEGF 121 , which displays high binding affinity for KDR, and VEGF 165 , which possesses high binding affinity for flt-1 and low affinity for KDR, as angiogenesis imaging agents using the LS180 tumor xenograft model. Methods: VEGF 121 and VEGF 165 were labeled with 125 I by the chloramine-T method. Biodistribution was observed in an LS180 human colon cancer xenograft model. Additionally, autoradiographic imaging and immunohistochemical staining of tumors were performed with 125 I-VEGF 121 . Results: 125 I-VEGF 121 and 125 I-VEGF 165 exhibited strong, continuous uptake by tumors and the uterus, an organ characterized by angiogenesis. 125 I-VEGF 121 uptake in tumors was twofold higher than that of 125 I-VEGF 165 (9.12±98 and 4.79±1.08 %ID/g at 2 h, respectively). 125 I-VEGF 121 displayed higher tumor to nontumor (T/N) ratios in most normal organs in comparison with 125 I-VEGF 165 . 125 I-VEGF 121 accumulation in tumors decreased with increasing tumor volume. Autoradiographic and immunohistochemical analyses confirmed that the difference in 125 I-VEGF 121 tumor accumulation correlated with degree of tumor vascularity. Conclusion: Radioiodinated VEGF 121 is a promising tracer for noninvasive delineation of angiogenesis in vivo

AlgiMatrix™ based 3D cell culture system as an in-vitro tumor model for anticancer studies.

Directory of Open Access Journals (Sweden)

Chandraiah Godugu

Full Text Available Three-dimensional (3D in-vitro cultures are recognized for recapitulating the physiological microenvironment and exhibiting high concordance with in-vivo conditions. Taking the advantages of 3D culture, we have developed the in-vitro tumor model for anticancer drug screening.Cancer cells grown in 6 and 96 well AlgiMatrix™ scaffolds resulted in the formation of multicellular spheroids in the size range of 100-300 µm. Spheroids were grown in two weeks in cultures without compromising the growth characteristics. Different marketed anticancer drugs were screened by incubating them for 24 h at 7, 9 and 11 days in 3D cultures and cytotoxicity was measured by AlamarBlue® assay. Effectiveness of anticancer drug treatments were measured based on spheroid number and size distribution. Evaluation of apoptotic and anti-apoptotic markers was done by immunohistochemistry and RT-PCR. The 3D results were compared with the conventional 2D monolayer cultures. Cellular uptake studies for drug (Doxorubicin and nanoparticle (NLC were done using spheroids.IC(50 values for anticancer drugs were significantly higher in AlgiMatrix™ systems compared to 2D culture models. The cleaved caspase-3 expression was significantly decreased (2.09 and 2.47 folds respectively for 5-Fluorouracil and Camptothecin in H460 spheroid cultures compared to 2D culture system. The cytotoxicity, spheroid size distribution, immunohistochemistry, RT-PCR and nanoparticle penetration data suggested that in vitro tumor models show higher resistance to anticancer drugs and supporting the fact that 3D culture is a better model for the cytotoxic evaluation of anticancer drugs in vitro.The results from our studies are useful to develop a high throughput in vitro tumor model to study the effect of various anticancer agents and various molecular pathways affected by the anticancer drugs and formulations.

Strategies to Enhance Online Learning Teams. Team Assessment and Diagnostics Instrument and Agent-based Modeling

Science.gov (United States)

2010-08-12

Strategies to Enhance Online Learning Teams Team Assessment and Diagnostics Instrument and Agent-based Modeling Tristan E. Johnson, Ph.D. Learning ...REPORT DATE AUG 2010 2. REPORT TYPE 3. DATES COVERED 00-00-2010 to 00-00-2010 4. TITLE AND SUBTITLE Strategies to Enhance Online Learning ...TeamsTeam Strategies to Enhance Online Learning Teams: Team Assessment and Diagnostics Instrument and Agent-based Modeling 5a. CONTRACT NUMBER 5b. GRANT

Linking Bayesian and agent-based models to simulate complex social-ecological systems in semi-arid regions

Directory of Open Access Journals (Sweden)

Aloah J Pope

2015-08-01

Full Text Available Interdependencies of ecologic, hydrologic, and social systems challenge traditional approaches to natural resource management in semi-arid regions. As a complex social-ecological system, water demands in the Sonoran Desert from agricultural and urban users often conflicts with water needs for its ecologically-significant riparian corridors. To explore this system, we developed an agent-based model to simulate complex feedbacks between human decisions and environmental conditions in the Rio Sonora Watershed. Cognitive mapping in conjunction with stakeholder participation produced a Bayesian model of conditional probabilities of local human decision-making processes resulting to changes in water demand. Probabilities created in the Bayesian model were incorporated into the agent-based model, so that each agent had a unique probability to make a positive decision based on its perceived environment at each point in time and space. By using a Bayesian approach, uncertainty in the human decision-making process could be incorporated. The spatially-explicit agent-based model simulated changes in depth-to-groundwater by well pumping based on an agent’s water demand. Changes in depth-to-groundwater feedback to influence agent behavior, as well as determine unique vegetation classes within the riparian corridor. Each vegetation class then provides varying stakeholder-defined quality values of ecosystem services. Using this modeling approach allowed us to examine effects on both the ecological and social system of semi-arid riparian corridors under various scenarios. The insight provided by the model contributes to understanding how specific interventions may alter the complex social-ecological system in the future.

Biodegradable Drug-Loaded Hydroxyapatite Nanotherapeutic Agent for Targeted Drug Release in Tumors.

Science.gov (United States)

Sun, Wen; Fan, Jiangli; Wang, Suzhen; Kang, Yao; Du, Jianjun; Peng, Xiaojun

2018-03-07

Tumor-targeted drug delivery systems have been increasingly used to improve the therapeutic efficiency of anticancer drugs and reduce their toxic side effects in vivo. Focused on this point, doxorubicin (DOX)-loaded hydroxyapatite (HAP) nanorods consisting of folic acid (FA) modification (DOX@HAP-FA) were developed for efficient antitumor treatment. The DOX-loaded nanorods were synthesized through in situ coprecipitation and hydrothermal method with a DOX template, demonstrating a new procedure for drug loading in HAP materials. DOX could be efficiently released from DOX@HAP-FA within 24 h in weakly acidic buffer solution (pH = 6.0) because of the degradation of HAP nanorods. With endocytosis under the mediation of folate receptors, the nanorods exhibited enhanced cellular uptake and further degraded, and consequently, the proliferation of targeted cells was inhibited. More importantly, in a tumor-bearing mouse model, DOX@HAP-FA treatment demonstrated excellent tumor growth inhibition. In addition, no apparent side effects were observed during the treatment. These results suggested that DOX@HAP-FA may be a promising nanotherapeutic agent for effective cancer treatment in vivo.

Easing the adoption of agent-based modelling (ABM) in tourism research

NARCIS (Netherlands)

Johnson, Peter; Nicholls, Sarah; Student, Jillian; Amelung, Bas; Baggio, Rodolfo; Balbi, Stefano; Boavida-Portugal, Ines; Jong, de Eline; Hofstede, G.J.; Lamers, M.A.J.; Pons, Marc; Steiger, Robert

2017-01-01

Agent-based modelling (ABM) is an emerging approach in tourism research. Despite the natural fit between theories of tourism as a complex, interconnected system, and the generative approach supported in ABM, there has been only limited integration within mainstream tourism research. This research

Agent-Based Modeling for Testing and Designing Novel Decentralized Command and Control System Paradigms

National Research Council Canada - National Science Library

Bonabeau, Eric; Hunt, Carl W; Gaudiano, Paolo

2003-01-01

Agent-based modeling (ABM) is a recent simulation modeling technique that consists of modeling a system from the bottom up, capturing the interactions taking place between the system's constituent units...

A 3-D model of tumor progression based on complex automata driven by particle dynamics.

Science.gov (United States)

Wcisło, Rafał; Dzwinel, Witold; Yuen, David A; Dudek, Arkadiusz Z

2009-12-01

The dynamics of a growing tumor involving mechanical remodeling of healthy tissue and vasculature is neglected in most of the existing tumor models. This is due to the lack of efficient computational framework allowing for simulation of mechanical interactions. Meanwhile, just these interactions trigger critical changes in tumor growth dynamics and are responsible for its volumetric and directional progression. We describe here a novel 3-D model of tumor growth, which combines particle dynamics with cellular automata concept. The particles represent both tissue cells and fragments of the vascular network. They interact with their closest neighbors via semi-harmonic central forces simulating mechanical resistance of the cell walls. The particle dynamics is governed by both the Newtonian laws of motion and the cellular automata rules. These rules can represent cell life-cycle and other biological interactions involving smaller spatio-temporal scales. We show that our complex automata, particle based model can reproduce realistic 3-D dynamics of the entire system consisting of the tumor, normal tissue cells, blood vessels and blood flow. It can explain phenomena such as the inward cell motion in avascular tumor, stabilization of tumor growth by the external pressure, tumor vascularization due to the process of angiogenesis, trapping of healthy cells by invading tumor, and influence of external (boundary) conditions on the direction of tumor progression. We conclude that the particle model can serve as a general framework for designing advanced multiscale models of tumor dynamics and it is very competitive to the modeling approaches presented before.

Agent-based modeling: a new approach for theory building in social psychology.

Science.gov (United States)

Smith, Eliot R; Conrey, Frederica R

2007-02-01

Most social and psychological phenomena occur not as the result of isolated decisions by individuals but rather as the result of repeated interactions between multiple individuals over time. Yet the theory-building and modeling techniques most commonly used in social psychology are less than ideal for understanding such dynamic and interactive processes. This article describes an alternative approach to theory building, agent-based modeling (ABM), which involves simulation of large numbers of autonomous agents that interact with each other and with a simulated environment and the observation of emergent patterns from their interactions. The authors believe that the ABM approach is better able than prevailing approaches in the field, variable-based modeling (VBM) techniques such as causal modeling, to capture types of complex, dynamic, interactive processes so important in the social world. The article elaborates several important contrasts between ABM and VBM and offers specific recommendations for learning more and applying the ABM approach.

MULTI AGENT-BASED ENVIRONMENTAL LANDSCAPE (MABEL) - AN ARTIFICIAL INTELLIGENCE SIMULATION MODEL: SOME EARLY ASSESSMENTS

OpenAIRE

Alexandridis, Konstantinos T.; Pijanowski, Bryan C.

2002-01-01

The Multi Agent-Based Environmental Landscape model (MABEL) introduces a Distributed Artificial Intelligence (DAI) systemic methodology, to simulate land use and transformation changes over time and space. Computational agents represent abstract relations among geographic, environmental, human and socio-economic variables, with respect to land transformation pattern changes. A multi-agent environment is developed providing task-nonspecific problem-solving abilities, flexibility on achieving g...

Study of the attractor structure of an agent-based sociological model

Energy Technology Data Exchange (ETDEWEB)

Timpanaro, Andre M; Prado, Carmen P C, E-mail: timpa@if.usp.br, E-mail: prado@if.usp.br [Instituto de Fisica da Universidade de Sao Paulo, Sao Paulo (Brazil)

2011-03-01

The Sznajd model is a sociophysics model that is based in the Potts model, and used for describing opinion propagation in a society. It employs an agent-based approach and interaction rules favouring pairs of agreeing agents. It has been successfully employed in modeling some properties and scale features of both proportional and majority elections (see for instance the works of A. T. Bernardes and R. N. Costa Filho), but its stationary states are always consensus states. In order to explain more complicated behaviours, we have modified the bounded confidence idea (introduced before in other opinion models, like the Deffuant model), with the introduction of prejudices and biases (we called this modification confidence rules), and have adapted it to the discrete Sznajd model. This generalized Sznajd model is able to reproduce almost all of the previous versions of the Sznajd model, by using appropriate choices of parameters. We solved the attractor structure of the resulting model in a mean-field approach and made Monte Carlo simulations in a Barabasi-Albert network. These simulations show great similarities with the mean-field, for the tested cases of 3 and 4 opinions. The dynamical systems approach that we devised allows for a deeper understanding of the potential of the Sznajd model as an opinion propagation model and can be easily extended to other models, like the voter model. Our modification of the bounded confidence rule can also be readily applied to other opinion propagation models.

Agent-Based Optimization

CERN Document Server

Jędrzejowicz, Piotr; Kacprzyk, Janusz

2013-01-01

This volume presents a collection of original research works by leading specialists focusing on novel and promising approaches in which the multi-agent system paradigm is used to support, enhance or replace traditional approaches to solving difficult optimization problems. The editors have invited several well-known specialists to present their solutions, tools, and models falling under the common denominator of the agent-based optimization. The book consists of eight chapters covering examples of application of the multi-agent paradigm and respective customized tools to solve  difficult optimization problems arising in different areas such as machine learning, scheduling, transportation and, more generally, distributed and cooperative problem solving.

Carbon emissions trading scheme exploration in China: A multi-agent-based model

International Nuclear Information System (INIS)

Tang, Ling; Wu, Jiaqian; Yu, Lean; Bao, Qin

2015-01-01

To develop a low-carbon economy, China launched seven pilot programs for carbon emissions trading (CET) in 2011 and plans to establish a nationwide CET mechanism in 2015. This paper formulated a multi-agent-based model to investigate the impacts of different CET designs in order to find the most appropriate one for China. The proposed bottom-up model includes all main economic agents in a general equilibrium framework. The simulation results indicate that (1) CET would effectively reduce carbon emissions, with a certain negative impact on the economy, (2) as for allowance allocation, the grandfathering rule is relatively moderate, while the benchmarking rule is more aggressive, (3) as for the carbon price, when the price level in the secondary CET market is regulated to be around RMB 40 per metric ton, a satisfactory emission mitigation effect can be obtained, (4) the penalty rate is suggested to be carefully designed to balance the economy development and mitigation effect, and (5) subsidy policy for energy technology improvement can effectively reduce carbon emissions without an additional negative impact on the economy. The results also indicate that the proposed novel model is a promising tool for CET policy making and analyses. -- Highlights: •A multi-agent-based model is proposed for carbon emissions trading (CET) in China. •Three agents are included: government, firms in different sectors and households. •The impacts of CET on the economy and environment in China are analyzed. •Different CET designs are simulated to find an appropriate policy for China. •Results confirm the effectiveness of the model and give helpful insights into CET design

An Evolutionary, Agent-Based Model to Aid in Computer Intrusion Detection and Prevention

National Research Council Canada - National Science Library

Shargel, Ben; Bonabeau, Eric; Budynek, Julien; Gaudiano, Paolo

2005-01-01

We have developed a realistic agent-based simulation model of hacker behavior. In the model, hacker scripts are generated using a simple but powerful hacker grammar that has the potential to cover all possible hacker scripts...

Evaluating urban parking policies with agent-based model of driver parking behavior

NARCIS (Netherlands)

Martens, C.J.C.M.; Benenson, I.

2008-01-01

This paper presents an explicit agent-based model of parking search in a city. In the model, “drivers” drive toward their destination, search for parking, park, remain at the parking place, and leave. The city’s infrastructure is represented by a high-resolution geographic information system (GIS)

Investment in the future electricity system - An agent-based modelling approach

NARCIS (Netherlands)

Kraan, O.; Kramer, G. J.; Nikolic, I.

2018-01-01

Now that renewable technologies are both technically and commercially mature, the imperfect rational behaviour of investors becomes a critical factor in the future success of the energy transition. Here, we take an agent-based approach to model investor decision making in the electricity sector

Comparison of lung tumor motion measured using a model-based 4DCT technique and a commercial protocol.

Science.gov (United States)

O'Connell, Dylan; Shaverdian, Narek; Kishan, Amar U; Thomas, David H; Dou, Tai H; Lewis, John H; Lamb, James M; Cao, Minsong; Tenn, Stephen; Percy, Lee P; Low, Daniel A

2017-11-11

To compare lung tumor motion measured with a model-based technique to commercial 4-dimensional computed tomography (4DCT) scans and describe a workflow for using model-based 4DCT as a clinical simulation protocol. Twenty patients were imaged using a model-based technique and commercial 4DCT. Tumor motion was measured on each commercial 4DCT dataset and was calculated on model-based datasets for 3 breathing amplitude percentile intervals: 5th to 85th, 5th to 95th, and 0th to 100th. Internal target volumes (ITVs) were defined on the 4DCT and 5th to 85th interval datasets and compared using Dice similarity. Images were evaluated for noise and rated by 2 radiation oncologists for artifacts. Mean differences in tumor motion magnitude between commercial and model-based images were 0.47 ± 3.0, 1.63 ± 3.17, and 5.16 ± 4.90 mm for the 5th to 85th, 5th to 95th, and 0th to 100th amplitude intervals, respectively. Dice coefficients between ITVs defined on commercial and 5th to 85th model-based images had a mean value of 0.77 ± 0.09. Single standard deviation image noise was 11.6 ± 9.6 HU in the liver and 6.8 ± 4.7 HU in the aorta for the model-based images compared with 57.7 ± 30 and 33.7 ± 15.4 for commercial 4DCT. Mean model error within the ITV regions was 1.71 ± 0.81 mm. Model-based images exhibited reduced presence of artifacts at the tumor compared with commercial images. Tumor motion measured with the model-based technique using the 5th to 85th percentile breathing amplitude interval corresponded more closely to commercial 4DCT than the 5th to 95th or 0th to 100th intervals, which showed greater motion on average. The model-based technique tended to display increased tumor motion when breathing amplitude intervals wider than 5th to 85th were used because of the influence of unusually deep inhalations. These results suggest that care must be taken in selecting the appropriate interval during image generation when using model-based 4DCT methods. Copyright © 2017

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

David Gurarie

Full Text Available BACKGROUND: 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. METHODOLOGY/PRINCIPAL FINDINGS: 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. CONCLUSIONS/SIGNIFICANCE: Our approach represents a novel, convenient and versatile method to model Plasmodium falciparum infection.

Exploration of agent of change’s role in biodiesel energy transition process using agent-based model

Science.gov (United States)

Hidayatno, A.; Vicky, L. R.; Destyanto, A. R.

2017-11-01

As the world’s largest Crude Palm Oil (CPO) producer, Indonesia uses CPO as raw material for biodiesel. A number of policies have been designed by the Indonesian government to support adoption of biodiesel. However, the role of energy alternatives faced complex problems. Agent-based modeling can be applied to predict the impact of policies on the actors in the business process to acquire a rich discernment of the behavior and decision making by the biodiesel industries. This study evaluates government policy by attending at the adoption of the biodiesel industry in the tender run by a government with the intervention of two policy options biodiesel energy utilization by developing an agent-based model. The simulation result show that the policy of adding the biodiesel plant installed capacity has a good impact in increasing the production capacity and vendor adoption in the tender. Even so, the government should consider the cost to be incurred and the profits for vendors, so the biodiesel production targets can be successfully fulfilled.

Toward Agent-Based Models of the Development And Evolution of Business Relations and Networks

Science.gov (United States)

Wilkinson, Ian F.; Marks, Robert E.; Young, Louise

Firms achieve competitive advantage in part through the development of cooperative relations with other firms and organisations. We describe a program of research designed to map and model the development of cooperative inter-firm relations, including the processes and paths by which firms may evolve from adversarial to more cooperative relations. Narrative-event-history methods will be used to develop stylised histories of the emergence of business relations in various contexts and to identify relevant causal mechanisms to be included in the agent-based models of relationship and network evolution. The relationship histories will provide the means of assuring the agent-based models developed.

Dynamics of bloggers’ communities: Bipartite networks from empirical data and agent-based modeling

Science.gov (United States)

Mitrović, Marija; Tadić, Bosiljka

2012-11-01

We present an analysis of the empirical data and the agent-based modeling of the emotional behavior of users on the Web portals where the user interaction is mediated by posted comments, like Blogs and Diggs. We consider the dataset of discussion-driven popular Diggs, in which all comments are screened by machine-learning emotion detection in the text, to determine positive and negative valence (attractiveness and aversiveness) of each comment. By mapping the data onto a suitable bipartite network, we perform an analysis of the network topology and the related time-series of the emotional comments. The agent-based model is then introduced to simulate the dynamics and to capture the emergence of the emotional behaviors and communities. The agents are linked to posts on a bipartite network, whose structure evolves through their actions on the posts. The emotional states (arousal and valence) of each agent fluctuate in time, subject to the current contents of the posts to which the agent is exposed. By an agent’s action on a post its current emotions are transferred to the post. The model rules and the key parameters are inferred from the considered empirical data to ensure their realistic values and mutual consistency. The model assumes that the emotional arousal over posts drives the agent’s action. The simulations are preformed for the case of constant flux of agents and the results are analyzed in full analogy with the empirical data. The main conclusions are that the emotion-driven dynamics leads to long-range temporal correlations and emergent networks with community structure, that are comparable with the ones in the empirical system of popular posts. In view of pure emotion-driven agents actions, this type of comparisons provide a quantitative measure for the role of emotions in the dynamics on real blogs. Furthermore, the model reveals the underlying mechanisms which relate the post popularity with the emotion dynamics and the prevalence of negative

Building a high-resolution T2-weighted MR-based probabilistic model of tumor occurrence in the prostate.

Science.gov (United States)

Nagarajan, Mahesh B; Raman, Steven S; Lo, Pechin; Lin, Wei-Chan; Khoshnoodi, Pooria; Sayre, James W; Ramakrishna, Bharath; Ahuja, Preeti; Huang, Jiaoti; Margolis, Daniel J A; Lu, David S K; Reiter, Robert E; Goldin, Jonathan G; Brown, Matthew S; Enzmann, Dieter R

2018-02-19

We present a method for generating a T2 MR-based probabilistic model of tumor occurrence in the prostate to guide the selection of anatomical sites for targeted biopsies and serve as a diagnostic tool to aid radiological evaluation of prostate cancer. In our study, the prostate and any radiological findings within were segmented retrospectively on 3D T2-weighted MR images of 266 subjects who underwent radical prostatectomy. Subsequent histopathological analysis determined both the ground truth and the Gleason grade of the tumors. A randomly chosen subset of 19 subjects was used to generate a multi-subject-derived prostate template. Subsequently, a cascading registration algorithm involving both affine and non-rigid B-spline transforms was used to register the prostate of every subject to the template. Corresponding transformation of radiological findings yielded a population-based probabilistic model of tumor occurrence. The quality of our probabilistic model building approach was statistically evaluated by measuring the proportion of correct placements of tumors in the prostate template, i.e., the number of tumors that maintained their anatomical location within the prostate after their transformation into the prostate template space. Probabilistic model built with tumors deemed clinically significant demonstrated a heterogeneous distribution of tumors, with higher likelihood of tumor occurrence at the mid-gland anterior transition zone and the base-to-mid-gland posterior peripheral zones. Of 250 MR lesions analyzed, 248 maintained their original anatomical location with respect to the prostate zones after transformation to the prostate. We present a robust method for generating a probabilistic model of tumor occurrence in the prostate that could aid clinical decision making, such as selection of anatomical sites for MR-guided prostate biopsies.

Fluorine-Containing Taxoid Anticancer Agents and Their Tumor-Targeted Drug Delivery

OpenAIRE

Seitz, Joshua; Vineberg, Jacob G.; Zuniga, Edison S.; Ojima, Iwao

2013-01-01

A long-standing problem of conventional chemotherapy is the lack of tumor-specific treatments. Traditional chemotherapy relies on the premise that rapidly proliferating cancer cells are more likely to be killed by a cytotoxic agent. In reality, however, cytotoxic agents have very little or no specificity, which leads to systemic toxicity, causing undesirable severe side effects. Consequently, various “molecularly targeted cancer therapies” have been developed for use in specific cancers, incl...

An Agent-Based Modeling Framework and Application for the Generic Nuclear Fuel Cycle

Science.gov (United States)

Gidden, Matthew J.

Key components of a novel methodology and implementation of an agent-based, dynamic nuclear fuel cycle simulator, Cyclus , are presented. The nuclear fuel cycle is a complex, physics-dependent supply chain. To date, existing dynamic simulators have not treated constrained fuel supply, time-dependent, isotopic-quality based demand, or fuel fungibility particularly well. Utilizing an agent-based methodology that incorporates sophisticated graph theory and operations research techniques can overcome these deficiencies. This work describes a simulation kernel and agents that interact with it, highlighting the Dynamic Resource Exchange (DRE), the supply-demand framework at the heart of the kernel. The key agent-DRE interaction mechanisms are described, which enable complex entity interaction through the use of physics and socio-economic models. The translation of an exchange instance to a variant of the Multicommodity Transportation Problem, which can be solved feasibly or optimally, follows. An extensive investigation of solution performance and fidelity is then presented. Finally, recommendations for future users of Cyclus and the DRE are provided.

Evaluation of Tumor Angiogenesis with a Second-Generation US Contrast Medium in a Rat Breast Tumor Model

International Nuclear Information System (INIS)

Ko, Eun Young; Lee, Sang Hoon; Kim, Hak Hee; Kim, Sung Moon; Shin, Myung Jin; Kim, Nam Kug; Gong, Gyung Yub

2008-01-01

Tumor angiogenesis is an important factor for tumor growth, treatment response and prognosis. Noninvasive imaging methods for the evaluation of tumor angiogenesis have been studied, but a method for the quantification of tumor angiogenesis has not been established. This study was designed to evaluate tumor angiogenesis in a rat breast tumor model by the use of a contrast enhanced ultrasound (US) examination with a second-generation US contrast agent. The alkylating agent 19N-ethyl-N-nitrosourea (ENU) was injected into the intraperitoneal cavity of 30-day-old female Sprague-Dawley rats. Three to four months later, breast tumors were detected along the mammary lines of the rats. A total of 17 breast tumors larger than 1 cm in nine rats were evaluated by gray-scale US, color Doppler US and contrast-enhanced US using SonoVue. The results were recorded as digital video images; time-intensity curves and hemodynamic parameters were analyzed. Pathological breast tumor specimens were obtained just after the US examinations. The tumor specimens were stained with hematoxylin and eosin (H and E) and the expression of CD31, an endothelial cell marker, was determined by immunohistochemical staining. We also evaluated the pathological diagnosis of the tumors and the microvessel density (MVD). Spearman's correlation and the Kruskal-Wallis test were used for the analysis. The pathological diagnoses were 11 invasive ductal carcinomas and six benign intraductal epithelial proliferations. The MVD did not correlate with the pathological diagnosis. However, blood volume (BV) showed a statistically significant correlation with MVD (Spearman's correlation, p < 0.05). Contrast-enhanced US using a second-generation US contrast material was useful for the evaluation of tumor angiogenesis of breast tumors in the rat

Mechanisms of chemoresistance to alkylating agents in malignant glioma.

Science.gov (United States)

Sarkaria, Jann N; Kitange, Gaspar J; James, C David; Plummer, Ruth; Calvert, Hilary; Weller, Michael; Wick, Wolfgang

2008-05-15

Intrinsic or acquired chemoresistance to alkylating agents is a major cause of treatment failure in patients with malignant brain tumors. Alkylating agents, the mainstay of treatment for brain tumors, damage the DNA and induce apoptosis, but the cytotoxic activity of these agents is dependent on DNA repair pathways. For example, O6-methylguanine DNA adducts can cause double-strand breaks, but this is dependent on a functional mismatch repair pathway. Thus, tumor cell lines deficient in mismatch repair are resistant to alkylating agents. Perhaps the most important mechanism of resistance to alkylating agents is the DNA repair enzyme O6-methylguanine methyltransferase, which can eliminate the cytotoxic O6-methylguanine DNA adduct before it causes harm. Another mechanism of resistance to alkylating agents is the base excision repair (BER) pathway. Consequently, efforts are ongoing to develop effective inhibitors of BER. Poly(ADP-ribose)polymerase plays a pivotal role in BER and is an important therapeutic target. Developing effective strategies to overcome chemoresistance requires the identification of reliable preclinical models that recapitulate human disease and which can be used to facilitate drug development. This article describes the diverse mechanisms of chemoresistance operating in malignant glioma and efforts to develop reliable preclinical models and novel pharmacologic approaches to overcome resistance to alkylating agents.

Statistical Agent Based Modelization of the Phenomenon of Drug Abuse

Science.gov (United States)

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.

Buying on margin, selling short in an agent-based market model

Science.gov (United States)

Zhang, Ting; Li, Honggang

2013-09-01

Credit trading, or leverage trading, which includes buying on margin and selling short, plays an important role in financial markets, where agents tend to increase their leverages for increased profits. This paper presents an agent-based asset market model to study the effect of the permissive leverage level on traders’ wealth and overall market indicators. In this model, heterogeneous agents can assume fundamental value-converging expectations or trend-persistence expectations, and their effective demands of assets depend both on demand willingness and wealth constraints, where leverage can relieve the wealth constraints to some extent. The asset market price is determined by a market maker, who watches the market excess demand, and is influenced by noise factors. By simulations, we examine market results for different leverage ratios. At the individual level, we focus on how the leverage ratio influences agents’ wealth accumulation. At the market level, we focus on how the leverage ratio influences changes in the asset price, volatility, and trading volume. Qualitatively, our model provides some meaningful results supported by empirical facts. More importantly, we find a continuous phase transition as we increase the leverage threshold, which may provide a further prospective of credit trading.

Multispace Behavioral Model for Face-Based Affective Social Agents

Directory of Open Access Journals (Sweden)

DiPaola Steve

2007-01-01

Full Text Available This paper describes a behavioral model for affective social agents based on three independent but interacting parameter spaces: knowledge, personality, and mood. These spaces control a lower-level geometry space that provides parameters at the facial feature level. Personality and mood use findings in behavioral psychology to relate the perception of personality types and emotional states to the facial actions and expressions through two-dimensional models for personality and emotion. Knowledge encapsulates the tasks to be performed and the decision-making process using a specially designed XML-based language. While the geometry space provides an MPEG-4 compatible set of parameters for low-level control, the behavioral extensions available through the triple spaces provide flexible means of designing complicated personality types, facial expression, and dynamic interactive scenarios.

Multispace Behavioral Model for Face-Based Affective Social Agents

Directory of Open Access Journals (Sweden)

Ali Arya

2007-03-01

Full Text Available This paper describes a behavioral model for affective social agents based on three independent but interacting parameter spaces: knowledge, personality, and mood. These spaces control a lower-level geometry space that provides parameters at the facial feature level. Personality and mood use findings in behavioral psychology to relate the perception of personality types and emotional states to the facial actions and expressions through two-dimensional models for personality and emotion. Knowledge encapsulates the tasks to be performed and the decision-making process using a specially designed XML-based language. While the geometry space provides an MPEG-4 compatible set of parameters for low-level control, the behavioral extensions available through the triple spaces provide flexible means of designing complicated personality types, facial expression, and dynamic interactive scenarios.

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

Science.gov (United States)

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

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.

Science.gov (United States)

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

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

Science.gov (United States)

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

Modeling investor sentiment and overconfidence in an agent-based stock market

NARCIS (Netherlands)

Lovric, M.; Kaymak, U.; Spronk, J.

2010-01-01

Agent-based stock markets as bottom-up models of financial markets allow us to study the link between individual investor behavior and aggregate market phenomena, and as such are a useful tool for investigating the implications of behavioral finance and investor psychology. In this paper we want to

Fluorescence Imaging/Agents in Tumor Resection.

Science.gov (United States)

Stummer, Walter; Suero Molina, Eric

2017-10-01

Intraoperative fluorescence imaging allows real-time identification of diseased tissue during surgery without being influenced by brain shift and surgery interruption. 5-Aminolevulinic acid, useful for malignant gliomas and other tumors, is the most broadly explored compound approved for fluorescence-guided resection. Intravenous fluorescein sodium has recently received attention, highlighting tumor tissue based on extravasation at the blood-brain barrier (defective in many brain tumors). Fluorescein in perfused brain, unselective extravasation in brain perturbed by surgery, and propagation with edema are concerns. Fluorescein is not approved but targeted fluorochromes with affinity to brain tumor cells, in development, may offer future advantages. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Quantitative Evaluation of Tumor Early Response to a Vascular-Disrupting Agent with Dynamic PET.

Science.gov (United States)

Guo, Ning; Zhang, Fan; Zhang, Xiaomeng; Guo, Jinxia; Lang, Lixin; Kiesewetter, Dale O; Niu, Gang; Li, Quanzheng; Chen, Xiaoyuan

2015-12-01

The purpose of this study is to evaluate the early response of tumors to a vascular-disrupting agent (VDA) VEGF121/recombinant toxin gelonin (rGel) using dynamic [(18)F]FPPRGD2 positron emission tomography (PET) and kinetic parameter estimation. Two tumor xenograft models: U87MG (highly vascularized) and A549 (moderately vascularized), were selected, and both were randomized into treatment and control groups. Sixty-minute dynamic PET scans with [(18)F]FPPRGD2 that targets to integrin αvβ3 were performed at days 0 (baseline), 1, and 3 since VEGF121/rGel treatment started. Dynamic PET-derived binding potential (BPND) and parametric maps were compared with tumor uptake (%ID/g) and the static PET image at 1 h after the tracer administration. The growth of U87MG tumor was obviously delayed upon VEGF121/rGel treatment. A549 tumor was not responsive to the same treatment. BPND of treated U87MG tumors decreased significantly at day 1 (p dynamic PET with [(18)F]FPPRGD2 shows advantages in distinguishing effective from ineffective treatment during the course of VEGF121/rGel therapy at early stage and is therefore more sensitive in assessing therapy response than static PET.

Imaging tumor hypoxia: Blood-borne delivery of imaging agents is fundamentally different in hypoxia subtypes

Directory of Open Access Journals (Sweden)

Peter Vaupel

2014-03-01

Full Text Available Hypoxic tissue subvolumes are a hallmark feature of solid malignant tumors, relevant for cancer therapy and patient outcome because they increase both the intrinsic aggressiveness of tumor cells and their resistance to several commonly used anticancer strategies. Pathogenetic mechanisms leading to hypoxia are diverse, may coexist within the same tumor and are commonly grouped according to the duration of their effects. Chronic hypoxia is mainly caused by diffusion limitations resulting from enlarged intercapillary distances and adverse diffusion geometries and — to a lesser extent — by hypoxemia, compromised perfusion or long-lasting microregional flow stops. Conversely, acute hypoxia preferentially results from transient disruptions in perfusion. While each of these features of the tumor microenvironment can contribute to a critical reduction of oxygen availability, the delivery of imaging agents (as well as nutrients and anticancer agents may be compromised or remain unaffected. Thus, a critical appraisal of the effects of the various mechanisms leading to hypoxia with regard to the blood-borne delivery of imaging agents is necessary to judge their ability to correctly represent the hypoxic phenotype of solid malignancies.

The highly intelligent virtual agents for modeling financial markets

Science.gov (United States)

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.

Embolization biomaterial reinforced with nanotechnology for an in-situ release of anti-angiogenic agent in the treatment of hyper-vascularized tumors and arteriovenous malformations.

Science.gov (United States)

Jubeli, E; Yagoubi, N; Pascale, F; Bédouet, L; Slimani, K; Labarre, D; Saint-Maurice, J P; Laurent, A; Moine, L

2015-10-01

A polymer based material was developed to act as an embolic agent and drug reservoir for the treatment of arteriovenous malformations (AVM) and hyper vascularized solid tumors. The aim was to combine the blocking of blood supply to the target region and the inhibition of the embolization-stimulated angiogenesis. The material is composed of an ethanolic solution of a linear acrylate based copolymer and acrylate calibrated microparticles containing nanospheres loaded with sunitinib, an anti-angiogenic agent. The precipitation of the linear copolymer in aqueous environment after injection through microcatheter results in the formation of an in-situ embolization gel whereas the microparticles serve to increase the cohesive properties of the embolization agent and to form a reservoir from which the sunitinib-loaded nanospheres are released post-embolization. The swollen state of the microparticles in contact with aqueous medium results in the release of the nanospheres out of microparticles macromolecular structure. After the synthesis, the formulation and the characterization of the different components of the material, anti-angiogenic activity was evaluated in vitro using endothelial cells and in vivo using corneal neovascularization model in rabbit. The efficiency of the arterial embolization was tested in vivo in a sheep model. Results proved the feasibility of this new system for vascular embolization in association with an in situ delivery of anti-angiogenic drug. This combination is a promising strategy for the management of arteriovenous malformations and solid tumors. Copyright © 2015 Elsevier B.V. All rights reserved.

Technological progress and effects of (supra) regional innovation and production collaboration. An agent-based model simulation study.

NARCIS (Netherlands)

Vermeulen, B.; Pyka, A.; Serguieva, A.; Maringer, D.; Palade, V.; Almeida, R.J.

2014-01-01

We provide a novel technology development model in which economic agents search for transformations to build artifacts. Using this technology development model, we conduct an agent-based model simulation study on the effect of (supra-)regional collaboration in production and innovation on

Dendrimer-based Macromolecular MRI Contrast Agents: Characteristics and Application

Directory of Open Access Journals (Sweden)

Hisataka Kobayashi

2003-01-01

Full Text Available Numerous macromolecular MRI contrast agents prepared employing relatively simple chemistry may be readily available that can provide sufficient enhancement for multiple applications. These agents operate using a ~100-fold lower concentration of gadolinium ions in comparison to the necessary concentration of iodine employed in CT imaging. Herein, we describe some of the general potential directions of macromolecular MRI contrast agents using our recently reported families of dendrimer-based agents as examples. Changes in molecular size altered the route of excretion. Smaller-sized contrast agents less than 60 kDa molecular weight were excreted through the kidney resulting in these agents being potentially suitable as functional renal contrast agents. Hydrophilic and larger-sized contrast agents were found better suited for use as blood pool contrast agents. Hydrophobic variants formed with polypropylenimine diaminobutane dendrimer cores created liver contrast agents. Larger hydrophilic agents are useful for lymphatic imaging. Finally, contrast agents conjugated with either monoclonal antibodies or with avidin are able to function as tumor-specific contrast agents, which also might be employed as therapeutic drugs for either gadolinium neutron capture therapy or in conjunction with radioimmunotherapy.

Uses of Agent-Based Modeling for Health Communication: the TELL ME Case Study.

Science.gov (United States)

Barbrook-Johnson, Peter; Badham, Jennifer; Gilbert, Nigel

2017-08-01

Government communication is an important management tool during a public health crisis, but understanding its impact is difficult. Strategies may be adjusted in reaction to developments on the ground and it is challenging to evaluate the impact of communication separately from other crisis management activities. Agent-based modeling is a well-established research tool in social science to respond to similar challenges. However, there have been few such models in public health. We use the example of the TELL ME agent-based model to consider ways in which a non-predictive policy model can assist policy makers. This model concerns individuals' protective behaviors in response to an epidemic, and the communication that influences such behavior. Drawing on findings from stakeholder workshops and the results of the model itself, we suggest such a model can be useful: (i) as a teaching tool, (ii) to test theory, and (iii) to inform data collection. We also plot a path for development of similar models that could assist with communication planning for epidemics.

In-vivo luminescence model for the study of tumor regression and regrowth following combination regimens with differentiation-promoting agents and photodynamic therapy

Science.gov (United States)

Rollakanti, K.; Anand, S.; Maytin, E. V.

2013-03-01

Photodynamic therapy with aminolevulinic acid can be modified by pretreatment regimens with drugs such as 5- Fluorouracil (5-FU) or Vitamin D (calcitriol) that enhance accumulation of protoporphyrin IX (PpIX) within tumor tissue which presumably will enhance the therapeutic response to light. However, histological approaches for monitoring therapeutic responses are poorly suited for studying long term survival because large numbers of mice need to be sacrificed. To address this limitation, a non-invasive model to monitor tumor regression and regrowth has been established. Breast cancer cells, stably transfected with firefly luciferase (MDA-Luc cell line), are implanted orthotopically in nude mice (0.25 - 1 x 106 cells/site), and monitored 0-60 min after s.c. injection of luciferin, with Xenogen in-vivo imaging system. Luminescence is detectable at day 1 post-implantation. Tumors are suitable for experimentation on day 6, when daily injections of pretreatment agents (5-FU, 300 mg/kg; calcitriol, 1 μg/kg) begin. On day 9, ALA (75 mg/kg i.p.) is given for 4 hr, followed by illumination (633 nm, 100 J/cm2). Tumor luminescence post- PDT is monitored daily and compared with caliper measurements. Pretreatments (5-FU, calcitriol) by themselves do not inhibit luciferase expression, and all tumors grow at a similar rate during the pretreatment period. Results from in vivo survival experiments can be correlated to survival responses of MDA-Luc cells grown in monolayer cultures +/- PDT and +/- pretreatments, and additional mechanistic information (e.g. Ki67 and E-cadherin expression) obtained. In summary, this noninvasive model will permit testing of the therapeutic survival advantages of various pretreatments during cPDT.

Agent-based modelling of heating system adoption in Norway

Energy Technology Data Exchange (ETDEWEB)

Sopha, Bertha Maya; Kloeckner, Christian A.; Hertwich, Edgar G.

2010-07-01

Full text: This paper introduces agent-based modelling as a methodological approach to understand the effect of decision making mechanism on the adoption of heating systems in Norway. The model is used as an experimental/learning tool to design possible interventions, not for prediction. The intended users of the model are therefore policy designers. Primary heating system adoptions of electric heating, heat pump and wood pellet heating were selected. Random topology was chosen to represent social network among households. Agents were households with certain location, number of peers, current adopted heating system, employed decision strategy, and degree of social influence in decision making. The overall framework of decision-making integrated theories from different disciplines; customer behavior theory, behavioral economics, theory of planned behavior, and diffusion of innovation, in order to capture possible decision making processes in households. A mail survey of 270 Norwegian households conducted in 2008 was designed specifically for acquiring data for the simulation. The model represents real geographic area of households and simulates the overall fraction of adopted heating system under study. The model was calibrated with historical data from Statistics Norway (SSB). Interventions with respects to total cost, norms, indoor air quality, reliability, supply security, required work, could be explored using the model. For instance, the model demonstrates that a considerable total cost (investment and operating cost) increase of electric heating and heat pump, rather than a reduction of wood pellet heating's total cost, are required to initiate and speed up wood pellet adoption. (Author)

Integrating evolutionary game theory into an agent-based model of ductal carcinoma in situ: Role of gap junctions in cancer progression.

Science.gov (United States)

Malekian, Negin; Habibi, Jafar; Zangooei, Mohammad Hossein; Aghakhani, Hojjat

2016-11-01

There are many cells with various phenotypic behaviors in cancer interacting with each other. For example, an apoptotic cell may induce apoptosis in adjacent cells. A living cell can also protect cells from undergoing apoptosis and necrosis. These survival and death signals are propagated through interaction pathways between adjacent cells called gap junctions. The function of these signals depends on the cellular context of the cell receiving them. For instance, a receiver cell experiencing a low level of oxygen may interpret a received survival signal as an apoptosis signal. In this study, we examine the effect of these signals on tumor growth. We make an evolutionary game theory component in order to model the signal propagation through gap junctions. The game payoffs are defined as a function of cellular context. Then, the game theory component is integrated into an agent-based model of tumor growth. After that, the integrated model is applied to ductal carcinoma in situ, a type of early stage breast cancer. Different scenarios are explored to observe the impact of the gap junction communication and parameters of the game theory component on cancer progression. We compare these scenarios by using the Wilcoxon signed-rank test. The Wilcoxon signed-rank test succeeds in proving a significant difference between the tumor growth of the model before and after considering the gap junction communication. The Wilcoxon signed-rank test also proves that the tumor growth significantly depends on the oxygen threshold of turning survival signals into apoptosis. In this study, the gap junction communication is modeled by using evolutionary game theory to illustrate its role at early stage cancers such as ductal carcinoma in situ. This work indicates that the gap junction communication and the oxygen threshold of turning survival signals into apoptosis can notably affect cancer progression. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

How Transparent About its Inflation Target Should a Central Bank be? An Agent-Based Model Assessment

NARCIS (Netherlands)

Salle, I.; Sénégas, M.A.; Yıldızoğlu, M.

2013-01-01

This paper revisits the benefits of explicitly announcing an inflation target for the con- duct of monetary policy in the framework of an agent-based model (ABM). This framework offers a flexible tool for modeling heterogeneity among individual agents and their bounded rationality, and to emphasize,

Money-Scape: A Generic Agent-Based Model of Corruption

OpenAIRE

Hokky Situngkir

2004-01-01

There has been a lot of works on corruption cases. We must think that corruption is a cultural aspect in a social life. We cannot separate the corruption with the cultural system where the corruption raised. Indonesia has been recorded to be one of the countries of the worst economic and political system on corruption case. The paper is introducing the usage of agent based simulation for analyzing the corruption specifically in Indonesia as the biggest corruption level. The model showed is na...

Validating agent based models through virtual worlds.

Energy Technology Data Exchange (ETDEWEB)

Lakkaraju, Kiran; Whetzel, Jonathan H.; Lee, Jina; Bier, Asmeret Brooke; Cardona-Rivera, Rogelio E.; Bernstein, Jeremy Ray Rhythm

2014-01-01

As the US continues its vigilance against distributed, embedded threats, understanding the political and social structure of these groups becomes paramount for predicting and dis- rupting their attacks. Agent-based models (ABMs) serve as a powerful tool to study these groups. While the popularity of social network tools (e.g., Facebook, Twitter) has provided extensive communication data, there is a lack of ne-grained behavioral data with which to inform and validate existing ABMs. Virtual worlds, in particular massively multiplayer online games (MMOG), where large numbers of people interact within a complex environ- ment for long periods of time provide an alternative source of data. These environments provide a rich social environment where players engage in a variety of activities observed between real-world groups: collaborating and/or competing with other groups, conducting battles for scarce resources, and trading in a market economy. Strategies employed by player groups surprisingly re ect those seen in present-day con icts, where players use diplomacy or espionage as their means for accomplishing their goals. In this project, we propose to address the need for ne-grained behavioral data by acquiring and analyzing game data a commercial MMOG, referred to within this report as Game X. The goals of this research were: (1) devising toolsets for analyzing virtual world data to better inform the rules that govern a social ABM and (2) exploring how virtual worlds could serve as a source of data to validate ABMs established for analogous real-world phenomena. During this research, we studied certain patterns of group behavior to compliment social modeling e orts where a signi cant lack of detailed examples of observed phenomena exists. This report outlines our work examining group behaviors that underly what we have termed the Expression-To-Action (E2A) problem: determining the changes in social contact that lead individuals/groups to engage in a particular behavior

Walk This Way: Improving Pedestrian Agent-Based Models through Scene Activity Analysis

Directory of Open Access Journals (Sweden)

Andrew Crooks

2015-09-01

Full Text Available Pedestrian movement is woven into the fabric of urban regions. With more people living in cities than ever before, there is an increased need to understand and model how pedestrians utilize and move through space for a variety of applications, ranging from urban planning and architecture to security. Pedestrian modeling has been traditionally faced with the challenge of collecting data to calibrate and validate such models of pedestrian movement. With the increased availability of mobility datasets from video surveillance and enhanced geolocation capabilities in consumer mobile devices we are now presented with the opportunity to change the way we build pedestrian models. Within this paper we explore the potential that such information offers for the improvement of agent-based pedestrian models. We introduce a Scene- and Activity-Aware Agent-Based Model (SA2-ABM, a method for harvesting scene activity information in the form of spatiotemporal trajectories, and incorporate this information into our models. In order to assess and evaluate the improvement offered by such information, we carry out a range of experiments using real-world datasets. We demonstrate that the use of real scene information allows us to better inform our model and enhance its predictive capabilities.

Simulating GenCo bidding strategies in electricity markets with an agent-based model

International Nuclear Information System (INIS)

Botterud, Audun; Thimmapuram, Prakash R.; Yamakado, Malo

2005-01-01

In this paper we use an agent-based simulation model, EMCAS, to analyze market power in electricity markets. We focus on the effect of congestion management on the ability of generating companies (GenCos) to raise prices beyond competitive levels. An 11-node test power system is used to compare a market design based on locational marginal pricing with a market design that uses system marginal pricing and congestion management by counter trading. Bidding strategies based on both physical and economic withholding are compared to a base case with production cost bidding. The results show that unilateral market power is exercised under both pricing mechanisms. However, the largest changes in consumer costs and GenCo profits due to strategic bidding occur under the locational marginal pricing scheme. The analysis also illustrates that agent-based modeling can contribute important insights into the complex interactions between the participants in transmission-constrained electricity markets. (Author)

Controlling for false negatives in agent-based models

DEFF Research Database (Denmark)

Secchi, Davide; Seri, Raffaello

2017-01-01

This article is concerned with the study of statistical power in agent-based modeling (ABM). After an overview of classic statistics theory on how to interpret Type-II error (whose occurrence is also referred to as a false negative) and power, the manuscript presents a study on ABM simulation art...... of simulation runs to reach an appropriate level of power. The study concludes with the importance for organizational behavior scholars to perform their models in an attempt to reach a power of 0.95 or higher at the 0.01 significance level....

Agent Model Development for Assessing Climate-Induced Geopolitical Instability.

Energy Technology Data Exchange (ETDEWEB)

Boslough, Mark B.; Backus, George A.

2005-12-01

We present the initial stages of development of new agent-based computational methods to generate and test hypotheses about linkages between environmental change and international instability. This report summarizes the first year's effort of an originally proposed three-year Laboratory Directed Research and Development (LDRD) project. The preliminary work focused on a set of simple agent-based models and benefited from lessons learned in previous related projects and case studies of human response to climate change and environmental scarcity. Our approach was to define a qualitative model using extremely simple cellular agent models akin to Lovelock's Daisyworld and Schelling's segregation model. Such models do not require significant computing resources, and users can modify behavior rules to gain insights. One of the difficulties in agent-based modeling is finding the right balance between model simplicity and real-world representation. Our approach was to keep agent behaviors as simple as possible during the development stage (described herein) and to ground them with a realistic geospatial Earth system model in subsequent years. This work is directed toward incorporating projected climate data--including various C02 scenarios from the Intergovernmental Panel on Climate Change (IPCC) Third Assessment Report--and ultimately toward coupling a useful agent-based model to a general circulation model.3

Turning green: Agent-based modeling of the adoption of dynamic electricity tariffs

International Nuclear Information System (INIS)

Kowalska-Pyzalska, Anna; Maciejowska, Katarzyna; Suszczyński, Karol; Sznajd-Weron, Katarzyna; Weron, Rafał

2014-01-01

Using an agent-based modeling approach we study the temporal dynamics of consumer opinions regarding switching to dynamic electricity tariffs and the actual decisions to switch. We assume that the decision to switch is based on the unanimity of τ past opinions. The resulting model offers a hypothetical, yet plausible explanation of why there is such a big discrepancy between consumer opinions, as measured by market surveys, and the actual participation in pilot programs and the adoption of dynamic tariffs. We argue that due to the high indifference level in today's retail electricity markets, customer opinions are very unstable and change frequently. The conducted simulation study shows that reducing the indifference level can result in narrowing the intention–behavior gap. A similar effect can be achieved by decreasing the decision time that a consumer takes to make a decision. - Highlights: • We propose an agent-based model to study the adoption of dynamic electricity tariffs. • The decision to change the tariff is based on the unanimity of τ past opinions. • The model explains why the empirically observed intention–behavior gap exists. • The adoption of dynamic tariffs is impossible due to the high level of indifference in today's societies. • Reducing the indifference level or decreasing the decision time can result in narrowing the gap

Numerical Problems and Agent-Based Models for a Mass Transfer Course

Science.gov (United States)

Murthi, Manohar; Shea, Lonnie D.; Snurr, Randall Q.

2009-01-01

Problems requiring numerical solutions of differential equations or the use of agent-based modeling are presented for use in a course on mass transfer. These problems were solved using the popular technical computing language MATLABTM. Students were introduced to MATLAB via a problem with an analytical solution. A more complex problem to which no…

Personalised learning object based on multi-agent model and learners’ learning styles

Directory of Open Access Journals (Sweden)

Noppamas Pukkhem

2011-09-01

Full Text Available A multi-agent model is proposed in which learning styles and a word analysis technique to create a learning object recommendation system are used. On the basis of a learning style-based design, a concept map combination model is proposed to filter out unsuitable learning concepts from a given course. Our learner model classifies learners into eight styles and implements compatible computational methods consisting of three recommendations: i non-personalised, ii preferred feature-based, and iii neighbour-based collaborative filtering. The analysis of preference error (PE was performed by comparing the actual preferred learning object with the predicted one. In our experiments, the feature-based recommendation algorithm has the fewest PE.

A physical data model for fields and agents

Science.gov (United States)

de Jong, Kor; de Bakker, Merijn; Karssenberg, Derek

2016-04-01

Two approaches exist in simulation modeling: agent-based and field-based modeling. In agent-based (or individual-based) simulation modeling, the entities representing the system's state are represented by objects, which are bounded in space and time. Individual objects, like an animal, a house, or a more abstract entity like a country's economy, have properties representing their state. In an agent-based model this state is manipulated. In field-based modeling, the entities representing the system's state are represented by fields. Fields capture the state of a continuous property within a spatial extent, examples of which are elevation, atmospheric pressure, and water flow velocity. With respect to the technology used to create these models, the domains of agent-based and field-based modeling have often been separate worlds. In environmental modeling, widely used logical data models include feature data models for point, line and polygon objects, and the raster data model for fields. Simulation models are often either agent-based or field-based, even though the modeled system might contain both entities that are better represented by individuals and entities that are better represented by fields. We think that the reason for this dichotomy in kinds of models might be that the traditional object and field data models underlying those models are relatively low level. We have developed a higher level conceptual data model for representing both non-spatial and spatial objects, and spatial fields (De Bakker et al. 2016). Based on this conceptual data model we designed a logical and physical data model for representing many kinds of data, including the kinds used in earth system modeling (e.g. hydrological and ecological models). The goal of this work is to be able to create high level code and tools for the creation of models in which entities are representable by both objects and fields. Our conceptual data model is capable of representing the traditional feature data

Modeling the Internet of Things, Self-Organizing and Other Complex Adaptive Communication Networks: A Cognitive Agent-Based Computing Approach.

Directory of Open Access Journals (Sweden)

Samreen Laghari

Full Text Available Computer Networks have a tendency to grow at an unprecedented scale. Modern networks involve not only computers but also a wide variety of other interconnected devices ranging from mobile phones to other household items fitted with sensors. This vision of the "Internet of Things" (IoT implies an inherent difficulty in modeling problems.It is practically impossible to implement and test all scenarios for large-scale and complex adaptive communication networks as part of Complex Adaptive Communication Networks and Environments (CACOONS. The goal of this study is to explore the use of Agent-based Modeling as part of the Cognitive Agent-based Computing (CABC framework to model a Complex communication network problem.We use Exploratory Agent-based Modeling (EABM, as part of the CABC framework, to develop an autonomous multi-agent architecture for managing carbon footprint in a corporate network. To evaluate the application of complexity in practical scenarios, we have also introduced a company-defined computer usage policy.The conducted experiments demonstrated two important results: Primarily CABC-based modeling approach such as using Agent-based Modeling can be an effective approach to modeling complex problems in the domain of IoT. Secondly, the specific problem of managing the Carbon footprint can be solved using a multiagent system approach.

Modeling the Internet of Things, Self-Organizing and Other Complex Adaptive Communication Networks: A Cognitive Agent-Based Computing Approach.

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Laghari, Samreen; Niazi, Muaz A

2016-01-01

Computer Networks have a tendency to grow at an unprecedented scale. Modern networks involve not only computers but also a wide variety of other interconnected devices ranging from mobile phones to other household items fitted with sensors. This vision of the "Internet of Things" (IoT) implies an inherent difficulty in modeling problems. It is practically impossible to implement and test all scenarios for large-scale and complex adaptive communication networks as part of Complex Adaptive Communication Networks and Environments (CACOONS). The goal of this study is to explore the use of Agent-based Modeling as part of the Cognitive Agent-based Computing (CABC) framework to model a Complex communication network problem. We use Exploratory Agent-based Modeling (EABM), as part of the CABC framework, to develop an autonomous multi-agent architecture for managing carbon footprint in a corporate network. To evaluate the application of complexity in practical scenarios, we have also introduced a company-defined computer usage policy. The conducted experiments demonstrated two important results: Primarily CABC-based modeling approach such as using Agent-based Modeling can be an effective approach to modeling complex problems in the domain of IoT. Secondly, the specific problem of managing the Carbon footprint can be solved using a multiagent system approach.

Agent-based financial dynamics model from stochastic interacting epidemic system and complexity analysis

International Nuclear Information System (INIS)

Lu, Yunfan; Wang, Jun; Niu, Hongli

2015-01-01

An agent-based financial stock price model is developed and investigated by a stochastic interacting epidemic system, which is one of the statistical physics systems and has been used to model the spread of an epidemic or a forest fire. Numerical and statistical analysis are performed on the simulated returns of the proposed financial model. Complexity properties of the financial time series are explored by calculating the correlation dimension and using the modified multiscale entropy method. In order to verify the rationality of the financial model, the real stock market indexes, Shanghai Composite Index and Shenzhen Component Index, are studied in comparison with the simulation data of the proposed model for the different infectiousness parameters. The empirical research reveals that this financial model can reproduce some important features of the real stock markets. - Highlights: • A new agent-based financial price model is developed by stochastic interacting epidemic system. • The structure of the proposed model allows to simulate the financial dynamics. • Correlation dimension and MMSE are applied to complexity analysis of financial time series. • Empirical results show the rationality of the proposed financial model

Agent-based financial dynamics model from stochastic interacting epidemic system and complexity analysis

Energy Technology Data Exchange (ETDEWEB)

Lu, Yunfan, E-mail: yunfanlu@yeah.net; Wang, Jun; Niu, Hongli

2015-06-12

An agent-based financial stock price model is developed and investigated by a stochastic interacting epidemic system, which is one of the statistical physics systems and has been used to model the spread of an epidemic or a forest fire. Numerical and statistical analysis are performed on the simulated returns of the proposed financial model. Complexity properties of the financial time series are explored by calculating the correlation dimension and using the modified multiscale entropy method. In order to verify the rationality of the financial model, the real stock market indexes, Shanghai Composite Index and Shenzhen Component Index, are studied in comparison with the simulation data of the proposed model for the different infectiousness parameters. The empirical research reveals that this financial model can reproduce some important features of the real stock markets. - Highlights: • A new agent-based financial price model is developed by stochastic interacting epidemic system. • The structure of the proposed model allows to simulate the financial dynamics. • Correlation dimension and MMSE are applied to complexity analysis of financial time series. • Empirical results show the rationality of the proposed financial model.

Spatial Planning and Policy Evaluation in an Urban Conurbation: a Regional Agent-Based Economic Model

Directory of Open Access Journals (Sweden)

Luzius Stricker

2017-03-01

Full Text Available This paper studies different functions and relations between 45 agglomerated municipalities in southern Switzerland (Ticino, using a territorial agent-based model. Our research adopts a bottom-up approach to urban systems, considering the agglomeration mechanism and effects of different regional and urban policies, and simulates the individual actions of diverse agents on a real city using an Agent-based model (ABM. Simulating the individual actions of diverse agents on a real city and measuring the resulting system behaviour and outcomes over time, they effectively provide a good test bed for evaluating the impact of different policies. The database is created merging the Swiss official secondary data for one reference year (2011 with Eurostat and OECD-Regpat. The results highlight that the understanding of municipalities’ functions on the territory appears to be essential for designing a solid institutional agglomeration (or city. From a methodological point of view, we contribute to improve the application of territorial ABM. Finally, our results provide a robust base to evaluate in a dynamic way various political interventions, in order to ensure a sustainable development of the agglomeration and the surrounding territories. Applying the analyses and the model on a larger scale, including further regions and conurbations, and including more indicators and variables, to obtain a more detailed and characteristic model, will constitute a further step of the research.

Agent-based land markets: Heterogeneous agents, land proces and urban land use change

NARCIS (Netherlands)

Filatova, Tatiana; Parker, Dawn C.; van der Veen, A.; Amblard, F.

2007-01-01

We construct a spatially explicit agent-based model of a bilateral land market. Heterogeneous agents form their bid and ask prices for land based on the utility that they obtain from a certain location (houte/land) and base on the state of the market (an excess of demand or supply). We underline the

An Agent-based Modeling of Water-Food Nexus towards Sustainable Management of Urban Water Resources

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Esmaeili, N.; Kanta, L.

2017-12-01

Growing population, urbanization, and climate change have put tremendous stress on water systems in many regions. A shortage in water system not only affects water users of a municipality but also that of food system. About 70% of global water is withdrawn for agriculture; livestock and dairy productions are also dependent on water availability. Although researchers and policy makers have identified and emphasized the water-food (WF) nexus in recent decade, most existing WF models offer strategies to reduce trade-offs and to generate benefits without considering feedback loops and adaptations between those systems. Feedback loops between water and food system can help understand long-term behavioral trends between water users of the integrated WF system which, in turn, can help manage water resources sustainably. An Agent-based modeling approach is applied here to develop a conceptual framework of WF systems. All water users in this system are modeled as agents, who are capable of making decisions and can adapt new behavior based on inputs from other agents in a shared environment through a set of logical and mathematical rules. Residential and commercial/industrial consumers are represented as municipal agents; crop, livestock, and dairy farmers are represented as food agents; and water management officials are represented as policy agent. During the period of water shortage, policy agent will propose/impose various water conservation measures, such as adapting water-efficient technologies, banning outdoor irrigation, implementing supplemental irrigation, using recycled water for livestock/dairy production, among others. Municipal and food agents may adapt conservation strategies and will update their demand accordingly. Emergent properties of the WF nexus will arise through dynamic interactions between various actors of water and food system. This model will be implemented to a case study for resource allocation and future policy development.

The sensitivity testing of Wilms' tumors to cytostatic agents with an autoradiographic in vitro short-term test

International Nuclear Information System (INIS)

Willnow, U.

1984-01-01

Sensitivity of 15 Wilms' tumors in children was tested towards cytostatic agents in vitro by means of an autoradiographic short-term test. Sensitivity was measured as the magnitude of the inhibition of 3 H-thymidine or 3 H-uridine incorporation. The test was performed with Adriamycin, Actinomycin D, Daunomycin, Bleomycin, Cyclophosphamide, Ifosfamide, Trenimon, and Arabinosylcytosine. None of the tumors is resistant to all substances, they are responsive against 2 or more drugs. The most effective drugs tested are Adriamycin, Actinomycin D and Cyclophosphamide. The tumors show a marked individual sensitivity pattern. This behavior is explained mainly by the usually high proliferative activity of Wilms' tumors. The possibilities and limits of long-term and short-term methods for sensitivity testing are discussed critically. For the evaluation of the results of in vitro testing and in vivo effectiveness the close correlation should be considered between the type of cytostatic agent and proliferation kinetics of the tumor, cytostatic agent and effect on tumor metabolism as well as the effect of the cytostatics and the nucleic acid precursors used for the short-term test. Despite the methodological limitations preclinical testing should be preferred to unselected chemotherapy. (author)

Comparison of Communication Models for Mobile Agents

Directory of Open Access Journals (Sweden)

Xining Li

2003-04-01

Full Text Available An agent is a self-contained process being acting on behalf of a user. A Mobile Agent is an agent roaming the internet to access data and services, and carry out its assigned task remotely. This paper will focus on the communication models for Mobile Agents. Generally speaking, communication models concern with problems of how to name Mobile Agents, how to establish communication relationships, how to trace moving agents, and how to guarantee reliable communication. Some existing MA systems are purely based on RPC-style communication, whereas some adopts asynchronous message passing, or event registration/handling. Different communication concepts suitable for Mobile Agents are well discussed in [1]. However, we will investigate these concepts and existing models from a different point view: how to track down agents and deliver messages in a dynamic, changing world.

Validation techniques of agent based modelling for geospatial simulations

Directory of Open Access Journals (Sweden)

M. Darvishi

2014-10-01

Full Text Available One of the most interesting aspects of modelling and simulation study is to describe the real world phenomena that have specific properties; especially those that are in large scales and have dynamic and complex behaviours. Studying these phenomena in the laboratory is costly and in most cases it is impossible. Therefore, Miniaturization of world phenomena in the framework of a model in order to simulate the real phenomena is a reasonable and scientific approach to understand the world. Agent-based modelling and simulation (ABMS is a new modelling method comprising of multiple interacting agent. They have been used in the different areas; for instance, geographic information system (GIS, biology, economics, social science and computer science. The emergence of ABM toolkits in GIS software libraries (e.g. ESRI’s ArcGIS, OpenMap, GeoTools, etc for geospatial modelling is an indication of the growing interest of users to use of special capabilities of ABMS. Since ABMS is inherently similar to human cognition, therefore it could be built easily and applicable to wide range applications than a traditional simulation. But a key challenge about ABMS is difficulty in their validation and verification. Because of frequent emergence patterns, strong dynamics in the system and the complex nature of ABMS, it is hard to validate and verify ABMS by conventional validation methods. Therefore, attempt to find appropriate validation techniques for ABM seems to be necessary. In this paper, after reviewing on Principles and Concepts of ABM for and its applications, the validation techniques and challenges of ABM validation are discussed.

Validation techniques of agent based modelling for geospatial simulations

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Darvishi, M.; Ahmadi, G.

2014-10-01

One of the most interesting aspects of modelling and simulation study is to describe the real world phenomena that have specific properties; especially those that are in large scales and have dynamic and complex behaviours. Studying these phenomena in the laboratory is costly and in most cases it is impossible. Therefore, Miniaturization of world phenomena in the framework of a model in order to simulate the real phenomena is a reasonable and scientific approach to understand the world. Agent-based modelling and simulation (ABMS) is a new modelling method comprising of multiple interacting agent. They have been used in the different areas; for instance, geographic information system (GIS), biology, economics, social science and computer science. The emergence of ABM toolkits in GIS software libraries (e.g. ESRI's ArcGIS, OpenMap, GeoTools, etc) for geospatial modelling is an indication of the growing interest of users to use of special capabilities of ABMS. Since ABMS is inherently similar to human cognition, therefore it could be built easily and applicable to wide range applications than a traditional simulation. But a key challenge about ABMS is difficulty in their validation and verification. Because of frequent emergence patterns, strong dynamics in the system and the complex nature of ABMS, it is hard to validate and verify ABMS by conventional validation methods. Therefore, attempt to find appropriate validation techniques for ABM seems to be necessary. In this paper, after reviewing on Principles and Concepts of ABM for and its applications, the validation techniques and challenges of ABM validation are discussed.

Recent progress in econophysics: Chaos, leverage, and business cycles as revealed by agent-based modeling and human experiments

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Xin, Chen; Huang, Ji-Ping

2017-12-01

Agent-based modeling and controlled human experiments serve as two fundamental research methods in the field of econophysics. Agent-based modeling has been in development for over 20 years, but how to design virtual agents with high levels of human-like "intelligence" remains a challenge. On the other hand, experimental econophysics is an emerging field; however, there is a lack of experience and paradigms related to the field. Here, we review some of the most recent research results obtained through the use of these two methods concerning financial problems such as chaos, leverage, and business cycles. We also review the principles behind assessments of agents' intelligence levels, and some relevant designs for human experiments. The main theme of this review is to show that by combining theory, agent-based modeling, and controlled human experiments, one can garner more reliable and credible results on account of a better verification of theory; accordingly, this way, a wider range of economic and financial problems and phenomena can be studied.

Recent progress in econophysics: Chaos, leverage,and business cycles as revealed by agent-based modeling and human experiments

Institute of Scientific and Technical Information of China (English)

Chen Xin; Ji-Ping Huang

2017-01-01

Agent-based modeling and controlled human experiments serve as two fundamental research methods in the field of econophysics.Agent-based modeling has been in development for over 20 years,but how to design virtual agents with high levels of human-like "intelligence" remains a challenge.On the other hand,experimental econophysics is an emerging field;however,there is a lack of experience and paradigms related to the field.Here,we review some of the most recent research results obtained through the use of these two methods concerning financial problems such as chaos,leverage,and business cycles.We also review the principles behind assessments of agents' intelligence levels,and some relevant designs for human experiments.The main theme of this review is to show that by combining theory,agent-based modeling,and controlled human experiments,one can garner more reliable and credible results on account of a better verification of theory;accordingly,this way,a wider range of economic and financial problems and phenomena can be studied.

Brain Tumor Segmentation Using a Generative Model with an RBM Prior on Tumor Shape

DEFF Research Database (Denmark)

Agn, Mikael; Puonti, Oula; Rosenschöld, Per Munck af

2016-01-01

In this paper, we present a fully automated generative method for brain tumor segmentation in multi-modal magnetic resonance images. The method is based on the type of generative model often used for segmenting healthy brain tissues, where tissues are modeled by Gaussian mixture models combined...... the use of the intensity information in the training images. Experiments on public benchmark data of patients suffering from low- and high-grade gliomas show that the method performs well compared to current state-of-the-art methods, while not being tied to any specific imaging protocol....... with a spatial atlas-based tissue prior. We extend this basic model with a tumor prior, which uses convolutional restricted Boltzmann machines (cRBMs) to model the shape of both tumor core and complete tumor, which includes edema and core. The cRBMs are trained on expert segmentations of training images, without...

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

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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

An agent-based dialogical model with fuzzy attitudes

NARCIS (Netherlands)

Dykstra, Piter; Jager, Wander; Elsenbroich, Corinna; Verbrugge, Rineke; De Lavalette, Gerard Renardel

2015-01-01

We present DIAL, a model of group dynamics and opinion dynamics. It features dialogues, in which agents gamble about reputation points. Intra-group radicalisation of opinions appears to be an emergent phenomenon. We position this model within the theoretical literature on opinion dynamics and social

The elaboration of a manufacturing flow connectivity model, based on Multi Agent System

Directory of Open Access Journals (Sweden)

Fahhama Lamyae

2017-01-01

The aim of this paper was to establish a model of the industrial flow connectivity; Afterward, we’ve detailed a network configuration model based on the multi-agents systems, to study the interactions between all the actors and give a more realistic vision onto manufacturing coordination in the supply chain.

Model-based prediction of progression-free survival in patients with first-line renal cell carcinoma using week 8 tumor size change from baseline.

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Claret, Laurent; Zheng, Jenny; Mercier, Francois; Chanu, Pascal; Chen, Ying; Rosbrook, Brad; Yazdi, Pithavala; Milligan, Peter A; Bruno, Rene

2016-09-01

To assess the link between early tumor shrinkage (ETS) and progression-free survival (PFS) based on historical first-line metastatic renal cell carcinoma (mRCC) data. Tumor size data from 921 patients with first-line mRCC who received interferon-alpha, sunitinib, sorafenib or axitinib in two Phase III studies were modeled. The relationship between model-based estimates of ETS at week 8 as well as the baseline prognostic factors and PFS was tested in multivariate log-logistic models. Model performance was evaluated using simulations of PFS distributions and hazard ratio (HR) across treatments for the two studies. In addition, an external validation was conducted using data from an independent Phase II RCC study. The relationship between expected HR of an investigational treatment vs. sunitinib and the differences in ETS was simulated. A model with a nonlinear ETS-PFS link was qualified to predict PFS distribution by ETS quartiles as well as to predict HRs of sunitinib vs. interferon-alpha and axitinib vs. sorafenib. The model also performed well in simulations of an independent study of axitinib (external validation). The simulations suggested that if a new investigational treatment could further reduce the week 8 ETS by 30 % compared with sunitinib, an expected HR [95 % predictive interval] of the new treatment vs. sunitinib would be 0.59 [0.46, 0.79]. A model has been developed that uses early changes in tumor size to predict the HR for PFS differences between treatment arms for first-line mRCC. Such a model may have utility in predicting the outcome of ongoing studies (e.g., as part of interim futility analyses), supporting early decision making and future study design for investigational agents in development for this indication.

Hyaluronic acid-functionalized single-walled carbon nanotubes as tumor-targeting MRI contrast agent

Directory of Open Access Journals (Sweden)

Hou L

2015-07-01

Full Text Available Lin Hou,* Huijuan Zhang,* Yating Wang, Lili Wang, Xiaomin Yang, Zhenzhong ZhangSchool of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, People’s Republic of China*These authors contributed equally to this workAbstract: A tumor-targeting carrier, hyaluronic acid (HA-functionalized single-walled carbon nanotubes (SWCNTs, was explored to deliver magnetic resonance imaging (MRI contrast agents (CAs targeting to the tumor cells specifically. In this system, HA surface modification for SWCNTs was simply accomplished by amidation process and could make this nanomaterial highly hydrophilic. Cellular uptake was performed to evaluate the intracellular transport capabilities of HA-SWCNTs for tumor cells and the uptake rank was HA-SWCNTs> SWCNTs owing to the presence of HA, which was also evidenced by flow cytometry. The safety evaluation of this MRI CAs was investigated in vitro and in vivo. It revealed that HA-SWCNTs could stand as a biocompatible nanocarrier and gadolinium (Gd/HA-SWCNTs demonstrated almost no toxicity compared with free GdCl3. Moreover, GdCl3 bearing HA-SWCNTs could significantly increase the circulation time for MRI. Finally, to investigate the MRI contrast enhancing capabilities of Gd/HA-SWCNTs, T1-weighted MR images of tumor-bearing mice were acquired. The results suggested Gd/HA-SWCNTs had the highest tumor-targeting efficiency and T1-relaxivity enhancement, indicating HA-SWCNTs could be developed as a tumor-targeting carrier to deliver the CAs, GdCl3, for the identifiable diagnosis of tumor.Keywords: gadolinium, magnetic resonance, SWCNTs, hyaluronic acid, contrast agent

Introducing spatial information into predictive NF-kappaB modelling--an agent-based approach.

Directory of Open Access Journals (Sweden)

Mark Pogson

2008-06-01

Full Text Available Nature is governed by local interactions among lower-level sub-units, whether at the cell, organ, organism, or colony level. Adaptive system behaviour emerges via these interactions, which integrate the activity of the sub-units. To understand the system level it is necessary to understand the underlying local interactions. Successful models of local interactions at different levels of biological organisation, including epithelial tissue and ant colonies, have demonstrated the benefits of such 'agent-based' modelling. Here we present an agent-based approach to modelling a crucial biological system--the intracellular NF-kappaB signalling pathway. The pathway is vital to immune response regulation, and is fundamental to basic survival in a range of species. Alterations in pathway regulation underlie a variety of diseases, including atherosclerosis and arthritis. Our modelling of individual molecules, receptors and genes provides a more comprehensive outline of regulatory network mechanisms than previously possible with equation-based approaches. The method also permits consideration of structural parameters in pathway regulation; here we predict that inhibition of NF-kappaB is directly affected by actin filaments of the cytoskeleton sequestering excess inhibitors, therefore regulating steady-state and feedback behaviour.

Climate Shocks and Migration: An Agent-Based Modeling Approach

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Entwisle, Barbara; Williams, Nathalie E.; Verdery, Ashton M.; Rindfuss, Ronald R.; Walsh, Stephen J.; Malanson, George P.; Mucha, Peter J.; Frizzelle, Brian G.; McDaniel, Philip M.; Yao, Xiaozheng; Heumann, Benjamin W.; Prasartkul, Pramote; Sawangdee, Yothin; Jampaklay, Aree

2016-01-01

This is a study of migration responses to climate shocks. We construct an agent-based model that incorporates dynamic linkages between demographic behaviors, such as migration, marriage, and births, and agriculture and land use, which depend on rainfall patterns. The rules and parameterization of our model are empirically derived from qualitative and quantitative analyses of a well-studied demographic field site, Nang Rong district, Northeast Thailand. With this model, we simulate patterns of migration under four weather regimes in a rice economy: 1) a reference, ‘normal’ scenario; 2) seven years of unusually wet weather; 3) seven years of unusually dry weather; and 4) seven years of extremely variable weather. Results show relatively small impacts on migration. Experiments with the model show that existing high migration rates and strong selection factors, which are unaffected by climate change, are likely responsible for the weak migration response. PMID:27594725

Application of Mesenchymal Stem Cells for Therapeutic Agent Delivery in Anti-tumor Treatment

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Daria S. Chulpanova

2018-03-01

Full Text Available Mesenchymal stem cells (MSCs are non-hematopoietic progenitor cells, which can be isolated from different types of tissues including bone marrow, adipose tissue, tooth pulp, and placenta/umbilical cord blood. There isolation from adult tissues circumvents the ethical concerns of working with embryonic or fetal stem cells, whilst still providing cells capable of differentiating into various cell lineages, such as adipocytes, osteocytes and chondrocytes. An important feature of MSCs is the low immunogenicity due to the lack of co-stimulatory molecules expression, meaning there is no need for immunosuppression during allogenic transplantation. The tropism of MSCs to damaged tissues and tumor sites makes them a promising vector for therapeutic agent delivery to tumors and metastatic niches. MSCs can be genetically modified by virus vectors to encode tumor suppressor genes, immunomodulating cytokines and their combinations, other therapeutic approaches include MSCs priming/loading with chemotherapeutic drugs or nanoparticles. MSCs derived membrane microvesicles (MVs, which play an important role in intercellular communication, are also considered as a new therapeutic agent and drug delivery vector. Recruited by the tumor, MSCs can exhibit both pro- and anti-oncogenic properties. In this regard, for the development of new methods for cancer therapy using MSCs, a deeper understanding of the molecular and cellular interactions between MSCs and the tumor microenvironment is necessary. In this review, we discuss MSC and tumor interaction mechanisms and review the new therapeutic strategies using MSCs and MSCs derived MVs for cancer treatment.

Agent-Based Modeling in Molecular Systems Biology.

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Soheilypour, Mohammad; Mofrad, Mohammad R K

2018-06-08

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

"Economic microscope": The agent-based model set as an instrument in an economic system research

Science.gov (United States)

Berg, D. B.; Zvereva, O. M.; Akenov, Serik

2017-07-01

To create a valid model of a social or economic system one must consider a lot of parameters, conditions and restrictions. Systems and, consequently, the corresponding models are proved to be very complicated. The problem of such system model engineering can't be solved only with mathematical methods usage. The decision could be found in computer simulation. Simulation does not reject mathematical methods, mathematical expressions could become the foundation for a computer model. In these materials the set of agent-based computer models is under discussion. All the set models simulate productive agents communications, but every model is geared towards the specific goal, and, thus, has its own algorithm and its own peculiarities. It is shown that computer simulation can discover new features of the agents' behavior that can not be obtained by analytical solvation of mathematical equations and thus plays the role of some kind of economic microscope.

Agent-based simulation of electricity markets : a literature review

International Nuclear Information System (INIS)

Sensfuss, F.; Genoese, M.; Genoese, M.; Most, D.

2007-01-01

The electricity sector in Europe and North America is undergoing considerable changes as a result of deregulation, issues related to climate change, and the integration of renewable resources within the electricity grid. This article reviewed agent-based simulation methods of analyzing electricity markets. The paper provided an analysis of research currently being conducted on electricity market designs and examined methods of modelling agent decisions. Methods of coupling long term and short term decisions were also reviewed. Issues related to single and multiple market analysis methods were discussed, as well as different approaches to integrating agent-based models with models of other commodities. The integration of transmission constraints within agent-based models was also discussed, and methods of measuring market efficiency were evaluated. Other topics examined in the paper included approaches to integrating investment decisions, carbon dioxide (CO 2 ) trading, and renewable support schemes. It was concluded that agent-based models serve as a test bed for the electricity sector, and will help to provide insights for future policy decisions. 74 refs., 6 figs

Agent-based Modelling, a new kind of research