Voter models with contrarian agents

NASA Astrophysics Data System (ADS)

Masuda, Naoki

2013-11-01

In the voter and many other opinion formation models, agents are assumed to behave as congregators (also called the conformists); they are attracted to the opinions of others. In this study I investigate linear extensions of the voter model with contrarian agents. An agent is either congregator or contrarian and assumes a binary opinion. I investigate three models that differ in the behavior of the contrarian toward other agents. In model 1, contrarians mimic the opinions of other contrarians and oppose (i.e., try to select the opinion opposite to) those of congregators. In model 2, contrarians mimic the opinions of congregators and oppose those of other contrarians. In model 3, contrarians oppose anybody. In all models, congregators are assumed to like anybody. I show that even a small number of contrarians prohibits the consensus in the entire population to be reached in all three models. I also obtain the equilibrium distributions using the van Kampen small-fluctuation approximation and the Fokker-Planck equation for the case of many contrarians and a single contrarian, respectively. I show that the fluctuation around the symmetric coexistence equilibrium is much larger in model 2 than in models 1 and 3 when contrarians are rare.

A Micro-Level Data-Calibrated Agent-Based Model: The Synergy between Microsimulation and Agent-Based Modeling.

PubMed

Singh, Karandeep; Ahn, Chang-Won; Paik, Euihyun; Bae, Jang Won; Lee, Chun-Hee

2018-01-01

Artificial life (ALife) examines systems related to natural life, its processes, and its evolution, using simulations with computer models, robotics, and biochemistry. In this article, we focus on the computer modeling, or "soft," aspects of ALife and prepare a framework for scientists and modelers to be able to support such experiments. The framework is designed and built to be a parallel as well as distributed agent-based modeling environment, and does not require end users to have expertise in parallel or distributed computing. Furthermore, we use this framework to implement a hybrid model using microsimulation and agent-based modeling techniques to generate an artificial society. We leverage this artificial society to simulate and analyze population dynamics using Korean population census data. The agents in this model derive their decisional behaviors from real data (microsimulation feature) and interact among themselves (agent-based modeling feature) to proceed in the simulation. The behaviors, interactions, and social scenarios of the agents are varied to perform an analysis of population dynamics. We also estimate the future cost of pension policies based on the future population structure of the artificial society. The proposed framework and model demonstrates how ALife techniques can be used by researchers in relation to social issues and policies.

Development of a canine model to enable the preclinical assessment of pH-dependent absorption of test compounds.

PubMed

Fancher, R Marcus; Zhang, Hongjian; Sleczka, Bogdan; Derbin, George; Rockar, Richard; Marathe, Punit

2011-07-01

A preclinical canine model capable of predicting a compound's potential for pH-dependent absorption in humans was developed. This involved the surgical insertion of a gastrostomy feeding tube into the stomach of a beagle dog. The tube was sutured in position to allow frequent withdrawal of gastric fluid for pH measurement. Therefore, it was possible to measure pH in the stomach and assess the effect of gastric pH-modifying agents on the absorption of various test compounds. Fasted gastric pH in the dog showed considerable inter- and intra-animal variability. Pretreatment of pentagastrin (6 µg/kg intramuscularly) 20 min prior to test compound administration was determined to be adequate for simulating fasting stomach pH in humans. Pretreatment with famotidine [40 mg orally] 1 h prior to test compound administration was determined to be adequate for simulating human gastric pH when acid-reducing agents are coadministered. Pentagastrin and famotidine pretreatments were used to test two discovery compounds and distinct differences in their potential for pH-dependent absorption were observed. The model described herein can be used preclinically to screen out compounds, differentiate compounds, and support the assessment of various formulation- and prodrug-based strategies to mitigate the pH effect. Copyright © 2011 Wiley-Liss, Inc. and the American Pharmacists Association

Petri Nets as Modeling Tool for Emergent Agents

NASA Technical Reports Server (NTRS)

Bergman, Marto

2004-01-01

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

Scaffold Hopping Toward Agomelatine: Novel 3, 4-Dihydroisoquinoline Compounds as Potential Antidepressant Agents

NASA Astrophysics Data System (ADS)

Yang, Yang; Ang, Wei; Long, Haiyue; Chang, Ying; Li, Zicheng; Zhou, Liangxue; Yang, Tao; Deng, Yong; Luo, Youfu

2016-10-01

A scaffold-hopping strategy toward Agomelatine based on in silico screening and knowledge analysis was employed to design novel antidepressant agents. A series of 3, 4-dihydroisoquinoline compounds were selected for chemical synthesis and biological assessment. Three compounds (6a-1, 6a-2, 6a-9) demonstrated protective effects on corticosterone-induced lesion of PC12 cells. Compound 6a-1 also displayed low inhibitory effects on the growth of HEK293 and L02 normal cells and it was further evaluated for its potential antidepressant effects in vivo. The forced swim test (FST) results revealed that compound 6a-1 remarkably reduced the immobility time of rats and the open field test (OFT) results indicated a better general locomotor activity of the rats treated with compound 6a-1 than those with Agomelatine or Fluoxetine. Mechanism studies implied that compound 6a-1 can significantly reduce PC12 cell apoptosis by up-regulation of GSH and down-regulation of ROS in corticosterone-induced lesion of PC12 cells. Meanwhile, the down-regulation of calcium ion concentration and up-regulation of BDNF level in PC12 cells may account for the neuroprotective effects. Furthermore, compound 6a-1 can increase cell survival and cell proliferation, promote cell maturation in the rat hippocampus after chronic treatment. The acute toxicity data in vivo indicated compound 6a-1 exhibited less hepatotoxicity than Agomelatine.

Nerve agent analogues that produce authentic soman, sarin, tabun, and cyclohexyl methylphosphonate-modified human butyrylcholinesterase.

PubMed

Gilley, Cynthia; MacDonald, Mary; Nachon, Florian; Schopfer, Lawrence M; Zhang, Jun; Cashman, John R; Lockridge, Oksana

2009-10-01

The goal was to test 14 nerve agent model compounds of soman, sarin, tabun, and cyclohexyl methylphosphonofluoridate (GF) for their suitability as substitutes for true nerve agents. We wanted to know whether the model compounds would form the identical covalent adduct with human butyrylcholinesterase that is produced by reaction with true nerve agents. Nerve agent model compounds containing thiocholine or thiomethyl in place of fluorine or cyanide were synthesized as Sp and Rp stereoisomers. Purified human butyrylcholinesterase was treated with a 45-fold molar excess of nerve agent analogue at pH 7.4 for 17 h at 21 degrees C. The protein was denatured by boiling and was digested with trypsin. Aged and nonaged active site peptide adducts were quantified by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry of the tryptic digest mixture. The active site peptides were isolated by HPLC and analyzed by MALDI-TOF-TOF mass spectrometry. Serine 198 of butyrylcholinesterase was covalently modified by all 14 compounds. Thiocholine was the leaving group in all compounds that had thiocholine in place of fluorine or cyanide. Thiomethyl was the leaving group in the GF thiomethyl compounds. However, sarin thiomethyl compounds released either thiomethyl or isopropyl, while soman thiomethyl compounds released either thiomethyl or pinacolyl. Thiocholine compounds reacted more rapidly with butyrylcholinesterase than thiomethyl compounds. Labeling with the model compounds resulted in aged adducts that had lost the O-alkyl group (O-ethyl for tabun, O-cyclohexyl for GF, isopropyl for sarin, and pinacolyl for soman) in addition to the thiocholine or thiomethyl group. The nerve agent model compounds containing thiocholine and the GF thiomethyl analogue were found to be suitable substitutes for true soman, sarin, tabun, and GF in terms of the adduct that they produced with human butyrylcholinesterase. However, the soman and sarin thiomethyl compounds

The AMPK inhibitor Compound C is a potent AMPK-independent anti-glioma agent

PubMed Central

Liu, Xiaona; Chhipa, Rishi Raj; Nakano, Ichiro; Dasgupta, Biplab

2014-01-01

AMPK is an evolutionarily conserved energy sensor important for cell growth, proliferation, survival and metabolic regulation. Active AMPK inhibits biosynthetic enzymes like mTOR and acetyl CoA carboxylase (required for protein and lipid synthesis, respectively) to ensure that cells maintain essential nutrients and energy during metabolic crisis. Despite our knowledge about this incredibly important kinase, no specific chemical inhibitors are available to examine its function. However, one small molecule known as Compound C (also called dorsomorphin) has been widely used in cell-based, biochemical and in vivo assays as a selective AMPK inhibitor. In nearly all these reports including a recent study in glioma, the biochemical and cellular effects of Compound C has been attributed to its inhibitory action towards AMPK. While examining the status of AMPK activation in human gliomas, we observed that glioblastomas (GBMs) express copious amount of active AMPK. Compound C effectively reduced glioma viability in vitro both by inhibiting proliferation and inducing cell death. As expected, Compound C inhibited AMPK; however, all the antiproliferative effects of this compound were AMPK-independent. Instead, Compound C killed glioma cells by multiple mechanisms including activation of the Calpain/Cathepsin pathway, inhibition of AKT, mTORC1/C2, cell cycle block at G2M and induction of necroptosis and autophagy. Importantly, normal astrocytes were significantly less susceptible to Compound C. In summary, Compound C is an extremely potent anti-glioma agent but we suggest that caution should be taken in interpreting results when this compound is used as an AMPK inhibitor. PMID:24419061

Agent-Based Models in Social Physics

NASA Astrophysics Data System (ADS)

Quang, Le Anh; Jung, Nam; Cho, Eun Sung; Choi, Jae Han; Lee, Jae Woo

2018-06-01

We review the agent-based models (ABM) on social physics including econophysics. The ABM consists of agent, system space, and external environment. The agent is autonomous and decides his/her behavior by interacting with the neighbors or the external environment with the rules of behavior. Agents are irrational because they have only limited information when they make decisions. They adapt using learning from past memories. Agents have various attributes and are heterogeneous. ABM is a non-equilibrium complex system that exhibits various emergence phenomena. The social complexity ABM describes human behavioral characteristics. In ABMs of econophysics, we introduce the Sugarscape model and the artificial market models. We review minority games and majority games in ABMs of game theory. Social flow ABM introduces crowding, evacuation, traffic congestion, and pedestrian dynamics. We also review ABM for opinion dynamics and voter model. We discuss features and advantages and disadvantages of Netlogo, Repast, Swarm, and Mason, which are representative platforms for implementing ABM.

A CSP-Based Agent Modeling Framework for the Cougaar Agent-Based Architecture

NASA Technical Reports Server (NTRS)

Gracanin, Denis; Singh, H. Lally; Eltoweissy, Mohamed; Hinchey, Michael G.; Bohner, Shawn A.

2005-01-01

Cognitive Agent Architecture (Cougaar) is a Java-based architecture for large-scale distributed agent-based applications. A Cougaar agent is an autonomous software entity with behaviors that represent a real-world entity (e.g., a business process). A Cougaar-based Model Driven Architecture approach, currently under development, uses a description of system's functionality (requirements) to automatically implement the system in Cougaar. The Communicating Sequential Processes (CSP) formalism is used for the formal validation of the generated system. Two main agent components, a blackboard and a plugin, are modeled as CSP processes. A set of channels represents communications between the blackboard and individual plugins. The blackboard is represented as a CSP process that communicates with every agent in the collection. The developed CSP-based Cougaar modeling framework provides a starting point for a more complete formal verification of the automatically generated Cougaar code. Currently it is used to verify the behavior of an individual agent in terms of CSP properties and to analyze the corresponding Cougaar society.

Syntheses and evaluation of multicaulin and miltirone-like compounds as antituberculosis agents.

PubMed

Burmaoğlu, Serdar; Seçinti, Hatice; Mozioğlu, Erkan; Gören, Ahmet C; Altundaş, Ramazan; Seçen, Hasan

2017-12-01

Four multicaulin and miltirone-like phenanthrene derivatives were synthesised and evaluated as antituberculosis agents. The crucial step of the synthesis was Pschorr coupling of 4-(3-isopropyl-4-methoxyphenyl)-2-(2-aminophenyl)ethane (13) to give 2-isopropyl-3-methoxy-9,10-dihydrophenanthrene (9) and 4-isopropyl-3-methoxy-9,10-dihydrophenanthrene (9a). Compound 9 was converted to multicaulin and miltirone-like phenanthrene derivatives by further reactions. The best antituberculosis activity was exhibited by 2-isopropylphenanthrene-3-ol (11).

Ferulic acid-carbazole hybrid compounds: Combination of cholinesterase inhibition, antioxidant and neuroprotection as multifunctional anti-Alzheimer agents.

PubMed

Fang, Lei; Chen, Mohao; Liu, Zhikun; Fang, Xubin; Gou, Shaohua; Chen, Li

2016-02-15

In order to search for novel multifunctional anti-Alzheimer agents, a series of ferulic acid-carbazole hybrid compounds were designed and synthesized. Ellman's assay revealed that the hybrid compounds showed moderate to potent inhibitory activity against the cholinesterases. Particularly, the AChE inhibition potency of compound 5k (IC50 1.9μM) was even 5-fold higher than that of galantamine. In addition, the target compounds showed pronounced antioxidant ability and neuroprotective property, especially against the ROS-induced toxicity. Notably, the neuroprotective effect of 5k was obviously superior to that of the mixture of ferulic acid and carbazole, indicating the therapeutic effect of the hybrid compound is better than the combination administration of the corresponding mixture. Copyright © 2016 Elsevier Ltd. All rights reserved.

Chemical warfare agents.

PubMed

Kuca, Kamil; Pohanka, Miroslav

2010-01-01

Chemical warfare agents are compounds of different chemical structures. Simple molecules such as chlorine as well as complex structures such as ricin belong to this group. Nerve agents, vesicants, incapacitating agents, blood agents, lung-damaging agents, riot-control agents and several toxins are among chemical warfare agents. Although the use of these compounds is strictly prohibited, the possible misuse by terrorist groups is a reality nowadays. Owing to this fact, knowledge of the basic properties of these substances is of a high importance. This chapter briefly introduces the separate groups of chemical warfare agents together with their members and the potential therapy that should be applied in case someone is intoxicated by these agents.

AGENT-BASED MODELS IN EMPIRICAL SOCIAL RESEARCH*

PubMed Central

Bruch, Elizabeth; Atwell, Jon

2014-01-01

Agent-based modeling has become increasingly popular in recent years, but there is still no codified set of recommendations or practices for how to use these models within a program of empirical research. This article provides ideas and practical guidelines drawn from sociology, biology, computer science, epidemiology, and statistics. We first discuss the motivations for using agent-based models in both basic science and policy-oriented social research. Next, we provide an overview of methods and strategies for incorporating data on behavior and populations into agent-based models, and review techniques for validating and testing the sensitivity of agent-based models. We close with suggested directions for future research. PMID:25983351

Agent-based models of cellular systems.

PubMed

Cannata, Nicola; Corradini, Flavio; Merelli, Emanuela; Tesei, Luca

2013-01-01

Software agents are particularly suitable for engineering models and simulations of cellular systems. In a very natural and intuitive manner, individual software components are therein delegated to reproduce "in silico" the behavior of individual components of alive systems at a given level of resolution. Individuals' actions and interactions among individuals allow complex collective behavior to emerge. In this chapter we first introduce the readers to software agents and multi-agent systems, reviewing the evolution of agent-based modeling of biomolecular systems in the last decade. We then describe the main tools, platforms, and methodologies available for programming societies of agents, possibly profiting also of toolkits that do not require advanced programming skills.

Synthesis, biological evaluation, and molecular modeling of cinnamic acyl sulfonamide derivatives as novel antitubulin agents.

PubMed

Luo, Yin; Qiu, Ke-Ming; Lu, Xiang; Liu, Kai; Fu, Jie; Zhu, Hai-Liang

2011-08-15

A series of novel cinnamic acyl sulfonamide derivatives (9a-16e) have been designed and synthesized and their biological activities were also evaluated as potential tubulin polymerization inhibitors. Among all the compounds, 10c showed the most potent growth inhibitory activity against B16-F10 cancer cell line in vitro, with an IC(50) value of 0.8μg/mL. Docking simulation was performed to insert compound 10c into the crystal structure of tubulin at colchicine binding site to determine the probable binding model. Based on the preliminary results, compound 10c with potent inhibitory activity in tumor growth may be a potential anticancer agent. Copyright © 2011 Elsevier Ltd. All rights reserved.

Priming of plant resistance by natural compounds. Hexanoic acid as a model

PubMed Central

Aranega-Bou, Paz; de la O Leyva, Maria; Finiti, Ivan; García-Agustín, Pilar; González-Bosch, Carmen

2014-01-01

Some alternative control strategies of currently emerging plant diseases are based on the use of resistance inducers. This review highlights the recent advances made in the characterization of natural compounds that induce resistance by a priming mechanism. These include vitamins, chitosans, oligogalacturonides, volatile organic compounds, azelaic and pipecolic acid, among others. Overall, other than providing novel disease control strategies that meet environmental regulations, natural priming agents are valuable tools to help unravel the complex mechanisms underlying the induced resistance (IR) phenomenon. The data presented in this review reflect the novel contributions made from studying these natural plant inducers, with special emphasis placed on hexanoic acid (Hx), proposed herein as a model tool for this research field. Hx is a potent natural priming agent of proven efficiency in a wide range of host plants and pathogens. It can early activate broad-spectrum defenses by inducing callose deposition and the salicylic acid (SA) and jasmonic acid (JA) pathways. Later it can prime pathogen-specific responses according to the pathogen’s lifestyle. Interestingly, Hx primes redox-related genes to produce an anti-oxidant protective effect, which might be critical for limiting the infection of necrotrophs. Our Hx-IR findings also strongly suggest that it is an attractive tool for the molecular characterization of the plant alarmed state, with the added advantage of it being a natural compound. PMID:25324848

Organometallic compounds in the discovery of new agents against kinetoplastid-caused diseases.

PubMed

Ravera, Mauro; Moreno-Viguri, Elsa; Paucar, Rocio; Pérez-Silanes, Silvia; Gabano, Elisabetta

2018-06-01

The development of safe and affordable antiparasitic agents effective against neglected tropical diseases is a big challenge of the drug discovery. The drugs currently employed have limitations such as poor efficacy, drug resistance or side effects. Thus, the search for new promising drugs is more and more crucial. Metal complexes and, in particular, organometallic compounds may expand the list of the drug candidates due to the peculiar attributes that the presence of the metal core add to the organic fragment (e.g., redox and structural features, ability to interact with DNA or protein targets, etc.). To date, most organometallic compounds tested as anti-neglected tropical diseases are based on similarities or activity of the organic ligands against other diseases or parasites and/or consist in modification of existing drugs combining the features of the metal moiety and the organic ligands. This review focuses on recent studies (2012-2017) on organometallic compounds in treating kinetoplastid-caused diseases such as Human African trypanosomiasis, Chagas disease and leishmaniasis. This field of research, however, still lacks exhaustive studies to identify of parasitic targets and quantitative structure-activity relationships for a rational drug design. Copyright © 2018. Published by Elsevier Masson SAS.

Disaggregation and Refinement of System Dynamics Models via Agent-based Modeling

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

Nutaro, James J; Ozmen, Ozgur; Schryver, Jack C

System dynamics models are usually used to investigate aggregate level behavior, but these models can be decomposed into agents that have more realistic individual behaviors. Here we develop a simple model of the STEM workforce to illuminate the impacts that arise from the disaggregation and refinement of system dynamics models via agent-based modeling. Particularly, alteration of Poisson assumptions, adding heterogeneity to decision-making processes of agents, and discrete-time formulation are investigated and their impacts are illustrated. The goal is to demonstrate both the promise and danger of agent-based modeling in the context of a relatively simple model and to delineate themore » importance of modeling decisions that are often overlooked.« less

Synthesis and Performance of a Biomimetic Indicator for Alkylating Agents.

PubMed

Provencher, Philip A; Love, Jennifer A

2015-10-02

4-(4-Nitrobenzyl)pyridine (NBP) is a colorimetric indicator compound for many types of carcinogenic alkylating agents. Because of the similar reactivity of NBP and guanine in DNA, NBP serves as a DNA model. NBP assays are used in the toxicological screening of pharmaceutical compounds, detection of chemical warfare agents, environmental hygiene technology, preliminary toxicology tests, mutagenicity of medicinal compounds, and other chemical analyses. Nevertheless, the use of NBP as a DNA model suffers from the compound's low water solubility, its lack of reactive oxygen sites, and dissimilar steric encumbrance compared to DNA. We report herein the design and synthesis of NBP derivatives that address some of these issues. These derivatives have been tested in solution and found to be superior in the colorimetric assay of the alkylating anticancer drug cyclophosphamide. The derivatives have also been integrated into a polymeric silica material which changes color upon the exposure to dangerous alkylating agents, such as iodomethane vapor, without the need for an exogenous base. This material modernizes the NBP assay from a time-consuming laboratory analysis to a real-time solid state sensor, which requires neither solvent nor additional reagents and can detect both gas- and solution-phase alkylating agents.

User modeling for distributed virtual environment intelligent agents

NASA Astrophysics Data System (ADS)

Banks, Sheila B.; Stytz, Martin R.

1999-07-01

This paper emphasizes the requirement for user modeling by presenting the necessary information to motivate the need for and use of user modeling for intelligent agent development. The paper will present information on our current intelligent agent development program, the Symbiotic Information Reasoning and Decision Support (SIRDS) project. We then discuss the areas of intelligent agents and user modeling, which form the foundation of the SIRDS project. Included in the discussion of user modeling are its major components, which are cognitive modeling and behavioral modeling. We next motivate the need for and user of a methodology to develop user models to encompass work within cognitive task analysis. We close the paper by drawing conclusions from our current intelligent agent research project and discuss avenues of future research in the utilization of user modeling for the development of intelligent agents for virtual environments.

Agent Based Modeling Applications for Geosciences

NASA Astrophysics Data System (ADS)

Stein, J. S.

2004-12-01

Agent-based modeling techniques have successfully been applied to systems in which complex behaviors or outcomes arise from varied interactions between individuals in the system. Each individual interacts with its environment, as well as with other individuals, by following a set of relatively simple rules. Traditionally this "bottom-up" modeling approach has been applied to problems in the fields of economics and sociology, but more recently has been introduced to various disciplines in the geosciences. This technique can help explain the origin of complex processes from a relatively simple set of rules, incorporate large and detailed datasets when they exist, and simulate the effects of extreme events on system-wide behavior. Some of the challenges associated with this modeling method include: significant computational requirements in order to keep track of thousands to millions of agents, methods and strategies of model validation are lacking, as is a formal methodology for evaluating model uncertainty. Challenges specific to the geosciences, include how to define agents that control water, contaminant fluxes, climate forcing and other physical processes and how to link these "geo-agents" into larger agent-based simulations that include social systems such as demographics economics and regulations. Effective management of limited natural resources (such as water, hydrocarbons, or land) requires an understanding of what factors influence the demand for these resources on a regional and temporal scale. Agent-based models can be used to simulate this demand across a variety of sectors under a range of conditions and determine effective and robust management policies and monitoring strategies. The recent focus on the role of biological processes in the geosciences is another example of an area that could benefit from agent-based applications. A typical approach to modeling the effect of biological processes in geologic media has been to represent these processes in

Real-time point-of-care measurement of impaired renal function in a rat acute injury model employing exogenous fluorescent tracer agents

NASA Astrophysics Data System (ADS)

Dorshow, Richard B.; Fitch, Richard M.; Galen, Karen P.; Wojdyla, Jolette K.; Poreddy, Amruta R.; Freskos, John N.; Rajagopalan, Raghavan; Shieh, Jeng-Jong; Demirjian, Sevag G.

2013-02-01

Renal function assessment is needed for the detection of acute kidney injury and chronic kidney disease. Glomerular filtration rate (GFR) is now widely accepted as the best indicator of renal function, and current clinical guidelines advocate its use in the staging of kidney disease. The optimum measure of GFR is by the use of exogenous tracer agents. However current clinically employed agents lack sensitivity or are cumbersome to use. An exogenous GFR fluorescent tracer agent, whose elimination rate could be monitored noninvasively through skin would provide a substantial improvement over currently available methods. We developed a series of novel aminopyrazine analogs for use as exogenous fluorescent GFR tracer agents that emit light in the visible region for monitoring GFR noninvasively over skin. In rats, these compounds are eliminated by the kidney with urine recovery greater than 90% of injected dose, are not broken down or metabolized in vivo, are not secreted by the renal tubules, and have clearance values similar to a GFR reference compound, iothalamate. In addition, biological half-life of these compounds measured in rats by noninvasive optical methods correlated with plasma derived methods. In this study, we show that this noninvasive methodology with our novel fluorescent tracer agents can detect impaired renal function. A 5/6th nephrectomy rat model is employed.

Persistent agents in Axelrod's social dynamics model

NASA Astrophysics Data System (ADS)

Reia, Sandro M.; Neves, Ubiraci P. C.

2016-01-01

Axelrod's model of social dynamics has been studied under the effect of external media. Here we study the formation of cultural domains in the model by introducing persistent agents. These are agents whose cultural traits are not allowed to change but may be spread through local neighborhood. In the absence of persistent agents, the system is known to present a transition from a monocultural to a multicultural regime at some critical Q (number of traits). Our results reveal a dependence of critical Q on the occupation probability p of persistent agents and we obtain the phase diagram of the model in the (p,Q) -plane. The critical locus is explained by the competition of two opposite forces named here barrier and bonding effects. Such forces are verified to be caused by non-persistent agents which adhere (adherent agents) to the set of traits of persistent ones. The adherence (concentration of adherent agents) as a function of p is found to decay for constant Q. Furthermore, adherence as a function of Q is found to decay as a power law with constant p.

Graph theoretical analysis, insilico modeling, design, and synthesis of compounds containing benzimidazole skeleton as antidepressant agents.

PubMed

Theivendren, Panneerselvam; Subramanian, Arumugam; Murugan, Indhumathy; Joshi, Shrinivas D; More, Uttam A

2017-05-01

In this study, drug target was identified using KEGG database and network analysis through Cytoscape software. Designed series of novel benzimidazoles were taken along with reference standard Flibanserin for insilico modeling. The novel 4-(1H-benzo[d]imidazol-2-yl)-N-(substituted phenyl)-4-oxobutanamide (3a-j) analogs were synthesized and evaluated for their antidepressant activity. Reaction of 4-(1H-benzo[d]imidazol-2-yl)-4-oxobutanoic acid (1) with 4-(1H-benzo [d] imidazol-2-yl)-4-oxobutanoyl chloride (2) furnished novel 4-(1H-benzo [d] imidazol-2-yl)-N-(substituted phenyl)-4-oxobutanamide (3a-j). All the newly synthesized compounds were characterized by IR, 1 H-NMR, and mass spectral analysis. The antidepressant activities of synthesized derivatives were compared with standard drug clomipramine at a dose level of 20 mg/kg. Among the derivatives tested, most of the compounds were found to have potent activity against depression. The high level of activity was shown by the compounds 3d, 3e, 3i, and it significantly reduced the duration of immobility time at the dose level of 50 mg/kg. © 2016 John Wiley & Sons A/S.

Evaluating Water Demand Using Agent-Based Modeling

NASA Astrophysics Data System (ADS)

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 conceptual data model and modelling language for fields and agents

NASA Astrophysics Data System (ADS)

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

2016-04-01

Modelling is essential in order to understand environmental systems. Environmental systems are heterogeneous because they consist of fields and agents. Fields have a value defined everywhere at all times, for example surface elevation and temperature. Agents are bounded in space and time and have a value only within their bounds, for example biomass of a tree crown or the speed of a car. Many phenomena have properties of both fields and agents. Although many systems contain both fields and agents and integration of these concepts would be required for modelling, existing modelling frameworks concentrate on either agent-based or field-based modelling and are often low-level programming frameworks. A concept is lacking that integrates fields and agents in a way that is easy to use for modelers who are not software engineers. To address this issue, we develop a conceptual data model that represents fields and agents uniformly. We then show how the data model can be used in a high-level modelling language. The data model represents fields and agents in space-time. Also relations and networks can be represented using the same concepts. Using the conceptual data model we can represent static and mobile agents that may have spatial and temporal variation within their extent. The concepts we use are phenomenon, property set, item, property, domain and value. The phenomenon is the thing that is modelled, which can be any real world thing, for example trees. A phenomenon usually consists of several items, e.g. single trees. The domain is the spatiotemporal location and/or extent for which the items in the phenomenon are defined. Multiple different domains can coexist for a given phenomenon. For example a domain describing the extent of the trees and a domain describing the stem locations. The same goes for the property, which is an attribute of the thing that is being modeled. A property has a value, which is possibly discretized, for example the biomass over the tree crown

Rational drug design for anti-cancer chemotherapy: multi-target QSAR models for the in silico discovery of anti-colorectal cancer agents.

PubMed

Speck-Planche, Alejandro; Kleandrova, Valeria V; Luan, Feng; Cordeiro, M Natália D S

2012-08-01

The discovery of new and more potent anti-cancer agents constitutes one of the most active fields of research in chemotherapy. Colorectal cancer (CRC) is one of the most studied cancers because of its high prevalence and number of deaths. In the current pharmaceutical design of more efficient anti-CRC drugs, the use of methodologies based on Chemoinformatics has played a decisive role, including Quantitative-Structure-Activity Relationship (QSAR) techniques. However, until now, there is no methodology able to predict anti-CRC activity of compounds against more than one CRC cell line, which should constitute the principal goal. In an attempt to overcome this problem we develop here the first multi-target (mt) approach for the virtual screening and rational in silico discovery of anti-CRC agents against ten cell lines. Here, two mt-QSAR classification models were constructed using a large and heterogeneous database of compounds. The first model was based on linear discriminant analysis (mt-QSAR-LDA) employing fragment-based descriptors while the second model was obtained using artificial neural networks (mt-QSAR-ANN) with global 2D descriptors. Both models correctly classified more than 90% of active and inactive compounds in training and prediction sets. Some fragments were extracted from the molecules and their contributions to anti-CRC activity were calculated using mt-QSAR-LDA model. Several fragments were identified as potential substructural features responsible for the anti-CRC activity and new molecules designed from those fragments with positive contributions were suggested and correctly predicted by the two models as possible potent and versatile anti-CRC agents. Copyright © 2012 Elsevier Ltd. All rights reserved.

A hybrid agent-based approach for modeling microbiological systems.

PubMed

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

2008-11-21

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

The practice of agent-based model visualization.

PubMed

Dorin, Alan; Geard, Nicholas

2014-01-01

We discuss approaches to agent-based model visualization. Agent-based modeling has its own requirements for visualization, some shared with other forms of simulation software, and some unique to this approach. In particular, agent-based models are typified by complexity, dynamism, nonequilibrium and transient behavior, heterogeneity, and a researcher's interest in both individual- and aggregate-level behavior. These are all traits requiring careful consideration in the design, experimentation, and communication of results. In the case of all but final communication for dissemination, researchers may not make their visualizations public. Hence, the knowledge of how to visualize during these earlier stages is unavailable to the research community in a readily accessible form. Here we explore means by which all phases of agent-based modeling can benefit from visualization, and we provide examples from the available literature and online sources to illustrate key stages and techniques.

A technology path to tactical agent-based modeling

NASA Astrophysics Data System (ADS)

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.

The highly intelligent virtual agents for modeling financial markets

NASA Astrophysics Data System (ADS)

Yang, G.; Chen, Y.; Huang, J. P.

2016-02-01

Researchers have borrowed many theories from statistical physics, like ensemble, Ising model, etc., to study complex adaptive systems through agent-based modeling. However, one fundamental difference between entities (such as spins) in physics and micro-units in complex adaptive systems is that the latter are usually with high intelligence, such as investors in financial markets. Although highly intelligent virtual agents are essential for agent-based modeling to play a full role in the study of complex adaptive systems, how to create such agents is still an open question. Hence, we propose three principles for designing high artificial intelligence in financial markets and then build a specific class of agents called iAgents based on these three principles. Finally, we evaluate the intelligence of iAgents through virtual index trading in two different stock markets. For comparison, we also include three other types of agents in this contest, namely, random traders, agents from the wealth game (modified on the famous minority game), and agents from an upgraded wealth game. As a result, iAgents perform the best, which gives a well support for the three principles. This work offers a general framework for the further development of agent-based modeling for various kinds of complex adaptive systems.

Drosophila melanogaster as a model system for the evaluation of anti-aging compounds.

PubMed

Jafari, Mahtab

2010-01-01

Understanding the causes of aging is a complex problem due to the multiple factors that influence aging, which include genetics, environment, metabolism and reproduction, among others. These multiple factors create logistical difficulties in the evaluation of anti-aging agents. There is a need for good model systems to evaluate potential anti-aging compounds. The model systems used should represent the complexities of aging in humans, so that the findings may be extrapolated to human studies, but they should also present an opportunity to minimize the variables so that the experimental results can be accurately interpreted. In addition to positively affecting lifespan, the impact of the compound on the physiologic confounders of aging, including fecundity and the health span--the period of life where an organism is generally healthy and free from serious or chronic illness--of the model organism needs to be evaluated. Fecundity is considered a major confounder of aging in fruit flies. It is well established that female flies that are exposed to toxic substances typically reduce their dietary intake and their reproductive output and display an artifactual lifespan extension. As a result, drugs that achieve longevity benefits by reducing fecundity as a result of diminished food intake are probably not useful candidates for eventual treatment of aging in humans and should be eliminated during the screening process. Drosophila melanogaster provides a suitable model system for the screening of anti-aging compounds as D. melanogaster and humans have many conserved physiological and biological pathways. In this paper, I propose an algorithm to screen anti-aging compounds using Drosophila melanogaster as a model system.

21 CFR 700.13 - Use of mercury compounds in cosmetics including use as skinbleaching agents in cosmetic...

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 7 2011-04-01 2010-04-01 true Use of mercury compounds in cosmetics including use as skinbleaching agents in cosmetic preparations also regarded as drugs. 700.13 Section 700.13 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) COSMETICS...

Hydroxypyridonate and hydroxypyrimidinone chelating agents

DOEpatents

Raymond, Kenneth N.; Doble, Daniel M.; Sunderland, Christopher J.; Thompson, Marlon

2005-01-25

The present invention provides hydroxypyridinone and hydroxypyrimidone chelating agents. Also provides are Gd(III) complexes of these agents, which are useful as contrast enhancing agents for magnetic resonance imaging. The invention also provides methods of preparing the compounds of the invention, as well as methods of using the compounds in magnetic resonance imaging applications.

Modeling of a production system using the multi-agent approach

NASA Astrophysics Data System (ADS)

Gwiazda, A.; Sękala, A.; Banaś, W.

2017-08-01

The method that allows for the analysis of complex systems is a multi-agent simulation. The multi-agent simulation (Agent-based modeling and simulation - ABMS) is modeling of complex systems consisting of independent agents. In the case of the model of the production system agents may be manufactured pieces set apart from other types of agents like machine tools, conveyors or replacements stands. Agents are magazines and buffers. More generally speaking, the agents in the model can be single individuals, but you can also be defined as agents of collective entities. They are allowed hierarchical structures. It means that a single agent could belong to a certain class. Depending on the needs of the agent may also be a natural or physical resource. From a technical point of view, the agent is a bundle of data and rules describing its behavior in different situations. Agents can be autonomous or non-autonomous in making the decision about the types of classes of agents, class sizes and types of connections between elements of the system. Multi-agent modeling is a very flexible technique for modeling and model creating in the convention that could be adapted to any research problem analyzed from different points of views. One of the major problems associated with the organization of production is the spatial organization of the production process. Secondly, it is important to include the optimal scheduling. For this purpose use can approach multi-purposeful. In this regard, the model of the production process will refer to the design and scheduling of production space for four different elements. The program system was developed in the environment NetLogo. It was also used elements of artificial intelligence. The main agent represents the manufactured pieces that, according to previously assumed rules, generate the technological route and allow preprint the schedule of that line. Machine lines, reorientation stands, conveyors and transport devices also represent the

The LUE data model for representation of agents and fields

NASA Astrophysics Data System (ADS)

de Jong, Kor; Schmitz, Oliver; Karssenberg, Derek

2017-04-01

Traditionally, agents-based and field-based modelling environments use different data models to represent the state of information they manipulate. In agent-based modelling, involving the representation of phenomena as objects bounded in space and time, agents are often represented by classes, each of which represents a particular kind of agent and all its properties. Such classes can be used to represent entities like people, birds, cars and countries. In field-based modelling, involving the representation of the environment as continuous fields, fields are often represented by a discretization of space, using multidimensional arrays, each storing mostly a single attribute. Such arrays can be used to represent the elevation of the land-surface, the pH of the soil, or the population density in an area, for example. Representing a population of agents by class instances grouped in collections is an intuitive way of organizing information. A drawback, though, is that models in which class instances grouping properties are stored in collections are less efficient (execute slower) than models in which collections of properties are grouped. The field representation, on the other hand, is convenient for the efficient execution of models. Another drawback is that, because the data models used are so different, integrating agent-based and field-based models becomes difficult, since the model builder has to deal with multiple concepts, and often multiple modelling environments. With the development of the LUE data model [1] we aim at representing agents and fields within a single paradigm, by combining the advantages of the data models used in agent-based and field-based data modelling. This removes the barrier for writing integrated agent-based and field-based models. The resulting data model is intuitive to use and allows for efficient execution of models. LUE is both a high-level conceptual data model and a low-level physical data model. The LUE conceptual data model is

New approaches in agent-based modeling of complex financial systems

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Constructing Agent Model for Virtual Training Systems

NASA Astrophysics Data System (ADS)

Murakami, Yohei; Sugimoto, Yuki; Ishida, Toru

Constructing highly realistic agents is essential if agents are to be employed in virtual training systems. In training for collaboration based on face-to-face interaction, the generation of emotional expressions is one key. In training for guidance based on one-to-many interaction such as direction giving for evacuations, emotional expressions must be supplemented by diverse agent behaviors to make the training realistic. To reproduce diverse behavior, we characterize agents by using a various combinations of operation rules instantiated by the user operating the agent. To accomplish this goal, we introduce a user modeling method based on participatory simulations. These simulations enable us to acquire information observed by each user in the simulation and the operating history. Using these data and the domain knowledge including known operation rules, we can generate an explanation for each behavior. Moreover, the application of hypothetical reasoning, which offers consistent selection of hypotheses, to the generation of explanations allows us to use otherwise incompatible operation rules as domain knowledge. In order to validate the proposed modeling method, we apply it to the acquisition of an evacuee's model in a fire-drill experiment. We successfully acquire a subject's model corresponding to the results of an interview with the subject.

Multi-Agent Market Modeling of Foreign Exchange Rates

NASA Astrophysics Data System (ADS)

Zimmermann, Georg; Neuneier, Ralph; Grothmann, Ralph

A market mechanism is basically driven by a superposition of decisions of many agents optimizing their profit. The oeconomic price dynamic is a consequence of the cumulated excess demand/supply created on this micro level. The behavior analysis of a small number of agents is well understood through the game theory. In case of a large number of agents one may use the limiting case that an individual agent does not have an influence on the market, which allows the aggregation of agents by statistic methods. In contrast to this restriction, we can omit the assumption of an atomic market structure, if we model the market through a multi-agent approach. The contribution of the mathematical theory of neural networks to the market price formation is mostly seen on the econometric side: neural networks allow the fitting of high dimensional nonlinear dynamic models. Furthermore, in our opinion, there is a close relationship between economics and the modeling ability of neural networks because a neuron can be interpreted as a simple model of decision making. With this in mind, a neural network models the interaction of many decisions and, hence, can be interpreted as the price formation mechanism of a market.

Simulating cancer growth with multiscale agent-based modeling.

PubMed

Wang, Zhihui; Butner, Joseph D; Kerketta, Romica; Cristini, Vittorio; Deisboeck, Thomas S

2015-02-01

There have been many techniques developed in recent years to in silico model a variety of cancer behaviors. Agent-based modeling is a specific discrete-based hybrid modeling approach that allows simulating the role of diversity in cell populations as well as within each individual cell; it has therefore become a powerful modeling method widely used by computational cancer researchers. Many aspects of tumor morphology including phenotype-changing mutations, the adaptation to microenvironment, the process of angiogenesis, the influence of extracellular matrix, reactions to chemotherapy or surgical intervention, the effects of oxygen and nutrient availability, and metastasis and invasion of healthy tissues have been incorporated and investigated in agent-based models. In this review, we introduce some of the most recent agent-based models that have provided insight into the understanding of cancer growth and invasion, spanning multiple biological scales in time and space, and we further describe several experimentally testable hypotheses generated by those models. We also discuss some of the current challenges of multiscale agent-based cancer models. Copyright © 2014 Elsevier Ltd. All rights reserved.

Simulating Cancer Growth with Multiscale Agent-Based Modeling

PubMed Central

Wang, Zhihui; Butner, Joseph D.; Kerketta, Romica; Cristini, Vittorio; Deisboeck, Thomas S.

2014-01-01

There have been many techniques developed in recent years to in silico model a variety of cancer behaviors. Agent-based modeling is a specific discrete-based hybrid modeling approach that allows simulating the role of diversity in cell populations as well as within each individual cell; it has therefore become a powerful modeling method widely used by computational cancer researchers. Many aspects of tumor morphology including phenotype-changing mutations, the adaptation to microenvironment, the process of angiogenesis, the influence of extracellular matrix, reactions to chemotherapy or surgical intervention, the effects of oxygen and nutrient availability, and metastasis and invasion of healthy tissues have been incorporated and investigated in agent-based models. In this review, we introduce some of the most recent agent-based models that have provided insight into the understanding of cancer growth and invasion, spanning multiple biological scales in time and space, and we further describe several experimentally testable hypotheses generated by those models. We also discuss some of the current challenges of multiscale agent-based cancer models. PMID:24793698

Agent Model Development for Assessing Climate-Induced Geopolitical Instability.

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

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 modelsmore » 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« less

Verifying Multi-Agent Systems via Unbounded Model Checking

NASA Technical Reports Server (NTRS)

Kacprzak, M.; Lomuscio, A.; Lasica, T.; Penczek, W.; Szreter, M.

2004-01-01

We present an approach to the problem of verification of epistemic properties in multi-agent systems by means of symbolic model checking. In particular, it is shown how to extend the technique of unbounded model checking from a purely temporal setting to a temporal-epistemic one. In order to achieve this, we base our discussion on interpreted systems semantics, a popular semantics used in multi-agent systems literature. We give details of the technique and show how it can be applied to the well known train, gate and controller problem. Keywords: model checking, unbounded model checking, multi-agent systems

Biodegradation of coal-related model compounds

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

Campbell, J.A.; Stewart, D.L.; McCulloch, M.

1988-06-01

We have studied the reactions of model compounds having coal-related functionalities (ester linkages, ether linkages, PAH) with the intact organism, cell-free filtrate, and cell-free enzyme of C. versicolor to better understand the process of biosolubilization. Many of the degradation products have been identified by gas chromatography/mass spectroscopy (GC/MS). Results indicate that the two compounds tested with the intact fungal organism were completely degraded. Complete degradation refers to no recovery of model compound. We can probably assume that the other two would also be totally degraded, since we have not yet found a simple compound that will survive long-term exposure tomore » the intact fungus. The ease of degradation with the cell-free filtrate appears to be in the order: phenylbenzoate > benzylbenzoate > benzyl ether > methoxybenzophenone. Esters and ethers that are activated by aromatic rings appear to be susceptible to the fungal extract; however, aromatic ketones are not affected by the extract. From the limited results we have obtained from the isolated enzyme, it appears that the activity may parallel the cell-free filtrate. When the cell-free extract was tested with the model compounds indole, dibenzothiophene, and bibenzyl, no degradation with the enzyme was noted: however, exposure of these compounds to the intact organism resulted in complete degradation. Analysis of the controls indicated no degradation. 8 refs., 1 fig., 1 tab.« less

Stability of Two Antifungal Agents, Fluconazole and Miconazole, Compounded in HUMCO RECURA Topical Cream to Determine Beyond-Use Date.

PubMed

Gautam, Pradeep; Light, Bob; Purvis, Troy

2017-01-01

A novel compounding vehicle (RECURA) has previously been proven to penetrate the nail bed when compounded with the antifungal agent miconazole or fluconazole, providing for an effective treatment for onychomycosis. In this study, miconazole and fluconazole were compounded separately in RECURA compounding cream, and they were tested at different time points (0, 7, 14, 28, 45, 60, 90, and 180 days) to determine the beyond-use date of those formulations. The beyond-use date testing of both formulations (10% miconazole in RECURA and 10% fluconazole in RECURA) proved them to be physically, chemically, and microbiologically stable under International Conference of Harmonisation controlled room temperature (25°C ± 2°C/60% RH ±5%) for at least 180 days from the date of compounding. Stability-indicating analytical method validation was completed for the simultaneous determination of miconazole and fluconazole in RECURA base using high-performance liquid chromatography coupled with photodiode array detector prior to the study. Copyright© by International Journal of Pharmaceutical Compounding, Inc.

Agent Models for Self-Motivated Home-Assistant Bots

NASA Astrophysics Data System (ADS)

Merrick, Kathryn; Shafi, Kamran

2010-01-01

Modern society increasingly relies on technology to support everyday activities. In the past, this technology has focused on automation, using computer technology embedded in physical objects. More recently, there is an expectation that this technology will not just embed reactive automation, but also embed intelligent, proactive automation in the environment. That is, there is an emerging desire for novel technologies that can monitor, assist, inform or entertain when required, and not just when requested. This paper presents three self-motivated, home-assistant bot applications using different self-motivated agent models. Self-motivated agents use a computational model of motivation to generate goals proactively. Technologies based on self-motivated agents can thus respond autonomously and proactively to stimuli from their environment. Three prototypes of different self-motivated agent models, using different computational models of motivation, are described to demonstrate these concepts.

SYNTHESIS OF HIGHLY FLUORINATED CHLOROFORMATES AND THEIR USE AS DERIVATIZING AGENTS FOR HYDROPHILIC COMPOUNDS AND DRINKING WATER DISINFECTION BY-PRODUCTS

EPA Science Inventory

A rapid, safe and efficient procedure was developed to synthesize perfluorinated chloroformates in the small scale generally required to perform analytical derivatizations. This new family of derivatizing agents allows straightforward derivatization of highly polar compounds, co...

Water-assisted compounding of cellulose nanocrystals into polyamide 6 for use as a nucleating agent for microcellular foaming

Treesearch

Jun Peng; Philip J. Walsh; Ronald C. Sabo; Lih-Sheng Turng; Craig M. Clemons

2016-01-01

Cellulose nanocrystals (CNCs) are a biorenewable filler and can be an excellent nucleating agent for the development of microcellular foamed polymeric nanocomposites. However, their relatively low degradation temperature limits their use with engineering resins like polyamide 6 (PA6) in typical melt processing techniques such as injection molding, compounding, and...

Model of mobile agents for sexual interactions networks

NASA Astrophysics Data System (ADS)

González, M. C.; Lind, P. G.; Herrmann, H. J.

2006-02-01

We present a novel model to simulate real social networks of complex interactions, based in a system of colliding particles (agents). The network is build by keeping track of the collisions and evolves in time with correlations which emerge due to the mobility of the agents. Therefore, statistical features are a consequence only of local collisions among its individual agents. Agent dynamics is realized by an event-driven algorithm of collisions where energy is gained as opposed to physical systems which have dissipation. The model reproduces empirical data from networks of sexual interactions, not previously obtained with other approaches.

Multi-Agent Strategic Modeling in a Specific Environment

NASA Astrophysics Data System (ADS)

Gams, Matjaz; Bezek, Andraz

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

Economic modelling with low-cognition agents

NASA Astrophysics Data System (ADS)

Ormerod, Paul

2006-10-01

The standard socio-economic model (SSSM) postulates very considerable cognitive powers on the part of its agents. They are able to gather all relevant information in any given situation, and to take the optimal decision on the basis of it, given their tastes and preferences. This behavioural rule is postulated to be universal. The concept of bounded rationality relaxes this somewhat, by permitting agents to have access to only limited amounts of information. But agents still optimise subject to their information set and tastes. Empirical work in economics over the past 20 years or so has shown that in general these behavioural postulates lack empirical validity. Instead, agents appear to have limited ability to gather information, and use simple rules of thumb to process the information which they have in order to take decisions. Building theoretical models on these realistic foundations which give better accounts of empirical phenomena than does the SSSM is an important challenge to both economists and econophysicists. Considerable progress has already been made in a short space of time, and examples are given in this paper.

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

NASA Astrophysics Data System (ADS)

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

An Active Learning Exercise for Introducing Agent-Based Modeling

ERIC Educational Resources Information Center

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…

The potential of compounds isolated from Xylaria spp. as antifungal agents against anthracnose.

PubMed

Elias, Luciana M; Fortkamp, Diana; Sartori, Sérgio B; Ferreira, Marília C; Gomes, Luiz H; Azevedo, João L; Montoya, Quimi V; Rodrigues, André; Ferreira, Antonio G; Lira, Simone P

2018-03-31

Anthracnose is a crop disease usually caused by fungi in the genus Colletotrichum or Gloeosporium. These are considered one of the main pathogens, causing significant economic losses, such as in peppers and guarana. The current forms of control include the use of resistant cultivars, sanitary pruning and fungicides. However, even with the use of some methods of controlling these cultures, the crops are not free of anthracnose. Additionally, excessive application of fungicides increases the resistance of pathogens to agrochemicals and cause harm to human health and the environment. In order to find natural antifungal agents against guarana anthracnose, endophytic fungi were isolated from Amazon guarana. The compounds piliformic acid and cytochalasin D were isolated by chromatographic techniques from two Xylaria spp., guided by assays with Colletotrichum gloeosporioides. The isolated compounds were identified by spectrometric techniques, as NMR and mass spectrometry. This is the first report that piliformic acid and cytochalasin D have antifungal activity against C. gloeosporioides with MIC 2.92 and 2.46μmolmL -1 respectively. Captan and difenoconazole were included as positive controls (MIC 16.63 and 0.02μmolmL -1 , respectively). Thus, Xylaria species presented a biotechnological potential and production of different active compounds which might be promising against anthracnose disease. Copyright © 2018 Sociedade Brasileira de Microbiologia. Published by Elsevier Editora Ltda. All rights reserved.

A Cybernetic Approach to the Modeling of Agent Communities

NASA Technical Reports Server (NTRS)

Truszkowski, Walt; Karlin, Jay

2000-01-01

In an earlier paper [1] examples of agent technology in a NASA context were presented. Both groundbased and space-based applications were addressed. This paper continues the discussion of one aspect of the Goddard Space Flight Center's continuing efforts to develop a community of agents that can support both ground-based and space-based systems autonomy. The paper focuses on an approach to agent-community modeling based on the theory of viable systems developed by Stafford Beer. It gives the status of an initial attempt to capture some of the agent-community behaviors in a viable system context. This paper is expository in nature and focuses on a discussion of the modeling of some of the underlying concepts and infrastructure that will serve as the basis of more detailed investigative work into the behavior of agent communities. The paper is organized as follows. First, a general introduction to agent community requirements is presented. Secondly, a brief introduction to the cybernetic concept of a viable system is given. This concept forms the foundation of the modeling approach. Then the concept of an agent community is modeled in the cybernetic context.

Perspectives on zebrafish models of hallucinogenic drugs and related psychotropic compounds.

PubMed

Neelkantan, Nikhil; Mikhaylova, Alina; Stewart, Adam Michael; Arnold, Raymond; Gjeloshi, Visar; Kondaveeti, Divya; Poudel, Manoj K; Kalueff, Allan V

2013-08-21

Among different classes of psychotropic drugs, hallucinogenic agents exert one of the most prominent effects on human and animal behaviors, markedly altering sensory, motor, affective, and cognitive responses. The growing clinical and preclinical interest in psychedelic, dissociative, and deliriant hallucinogens necessitates novel translational, sensitive, and high-throughput in vivo models and screens. Primate and rodent models have been traditionally used to study cellular mechanisms and neural circuits of hallucinogenic drugs' action. The utility of zebrafish ( Danio rerio ) in neuroscience research is rapidly growing due to their high physiological and genetic homology to humans, ease of genetic manipulation, robust behaviors, and cost effectiveness. Possessing a fully characterized genome, both adult and larval zebrafish are currently widely used for in vivo screening of various psychotropic compounds, including hallucinogens and related drugs. Recognizing the growing importance of hallucinogens in biological psychiatry, here we discuss hallucinogenic-induced phenotypes in zebrafish and evaluate their potential as efficient preclinical models of drug-induced states in humans.

Perspectives on Zebrafish Models of Hallucinogenic Drugs and Related Psychotropic Compounds

PubMed Central

2013-01-01

Among different classes of psychotropic drugs, hallucinogenic agents exert one of the most prominent effects on human and animal behaviors, markedly altering sensory, motor, affective, and cognitive responses. The growing clinical and preclinical interest in psychedelic, dissociative, and deliriant hallucinogens necessitates novel translational, sensitive, and high-throughput in vivo models and screens. Primate and rodent models have been traditionally used to study cellular mechanisms and neural circuits of hallucinogenic drugs’ action. The utility of zebrafish (Danio rerio) in neuroscience research is rapidly growing due to their high physiological and genetic homology to humans, ease of genetic manipulation, robust behaviors, and cost effectiveness. Possessing a fully characterized genome, both adult and larval zebrafish are currently widely used for in vivo screening of various psychotropic compounds, including hallucinogens and related drugs. Recognizing the growing importance of hallucinogens in biological psychiatry, here we discuss hallucinogenic-induced phenotypes in zebrafish and evaluate their potential as efficient preclinical models of drug-induced states in humans. PMID:23883191

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

PubMed

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

2010-01-01

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

Biological agents for controlling excessive scarring.

PubMed

Berman, Brian

2010-01-01

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

A physical data model for fields and agents

NASA Astrophysics Data System (ADS)

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

Development and Sequential Analysis of a New Multi-Agent, Anti-Acne Formulation Based on Plant-Derived Antimicrobial and Anti-Inflammatory Compounds.

PubMed

Saviuc, Crina; Ciubucă, Bianca; Dincă, Gabriela; Bleotu, Coralia; Drumea, Veronica; Chifiriuc, Mariana-Carmen; Popa, Marcela; Gradisteanu Pircalabioru, Gratiela; Marutescu, Luminita; Lazăr, Veronica

2017-01-17

The antibacterial and anti-inflammatory potential of natural, plant-derived compounds has been reported in many studies. Emerging evidence indicates that plant-derived essential oils and/or their major compounds may represent a plausible alternative treatment for acne, a prevalent skin disorder in both adolescent and adult populations. Therefore, the purpose of this study was to develop and subsequently analyze the antimicrobial activity of a new multi-agent, synergic formulation based on plant-derived antimicrobial compounds (i.e., eugenol, β-pinene, eucalyptol, and limonene) and anti-inflammatory agents for potential use in the topical treatment of acne and other skin infections. The optimal antimicrobial combinations selected in this study were eugenol/β-pinene/salicylic acid and eugenol/β-pinene/2-phenoxyethanol/potassium sorbate. The possible mechanisms of action revealed by flow cytometry were cellular permeabilization and inhibition of efflux pumps activity induced by concentrations corresponding to sub-minimal inhibitory (sub-MIC) values. The most active antimicrobial combination represented by salycilic acid/eugenol/β-pinene/2-phenoxyethanol/potassium sorbate was included in a cream base, which demonstrated thermodynamic stability and optimum microbiological characteristics.

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

PubMed

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

2011-12-01

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

Efficient Agent-Based Models for Non-Genomic Evolution

NASA Technical Reports Server (NTRS)

Gupta, Nachi; Agogino, Adrian; Tumer, Kagan

2006-01-01

Modeling dynamical systems composed of aggregations of primitive proteins is critical to the field of astrobiological science involving early evolutionary structures and the origins of life. Unfortunately traditional non-multi-agent methods either require oversimplified models or are slow to converge to adequate solutions. This paper shows how to address these deficiencies by modeling the protein aggregations through a utility based multi-agent system. In this method each agent controls the properties of a set of proteins assigned to that agent. Some of these properties determine the dynamics of the system, such as the ability for some proteins to join or split other proteins, while additional properties determine the aggregation s fitness as a viable primitive cell. We show that over a wide range of starting conditions, there are mechanisins that allow protein aggregations to achieve high values of overall fitness. In addition through the use of agent-specific utilities that remain aligned with the overall global utility, we are able to reach these conclusions with 50 times fewer learning steps.

Consentaneous Agent-Based and Stochastic Model of the Financial Markets

PubMed Central

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. PMID:25029364

The fractional volatility model: An agent-based interpretation

NASA Astrophysics Data System (ADS)

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.

Single Agents with Designed Combination Chemotherapy Potential: Synthesis and Evaluation of Substituted Pyrimido[4,5-b]indoles as Receptor Tyrosine Kinase and Thymidylate Synthase Inhibitors and as Antitumor Agents

PubMed Central

Gangjee, Aleem; Zaware, Nilesh; Raghavan, Sudhir; Ihnat, Michael; Shenoy, Satyendra; Kisliuk, Roy L.

2010-01-01

Combinations of antiangiogenic agents (AAs) with cytotoxic agents have shown significant promise and several such clinical trials are currently underway. We have designed, synthesized and evaluated two compounds that each inhibit vascular endothelial growth factor receptor-2 (VEGFR-2) and platelet derived growth factor receptor-beta (PDGFR-β) for antiangiogenic effects and also inhibit human thymidylate synthase (hTS) for cytotoxic effects in single agents. The synthesis of these compounds involved the nucleophilic displacement of the common intermediate 5-chloro-9H-pyrimido[4,5-b]indole-2,4-diamine with appropriate benzenethiols. The inhibitory potency of both these single agents against VEGFR-2, PDGFR-β and hTS is better than or close to standards. In a COLO-205 xenograft mouse model one of the analogs significantly decreased tumor growth (TGI = 76% at 35 mg/kg), liver metastases and tumor blood vessels compared to a standard drug and to control and thus demonstrated potent tumor growth inhibition, inhibition of metastasis and antiangiogenic effects in vivo. These compounds afford combination chemotherapeutic potential in single agents. PMID:20092323

Safe motion planning for mobile agents: A model of reactive planning for multiple mobile agents

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

Fujimura, Kikuo.

1990-01-01

The problem of motion planning for multiple mobile agents is studied. Each planning agent independently plans its own action based on its map which contains a limited information about the environment. In an environment where more than one mobile agent interacts, the motions of the robots are uncertain and dynamic. A model for reactive agents is described and simulation results are presented to show their behavior patterns. 18 refs., 2 figs.

Discovery of multi-target receptor tyrosine kinase inhibitors as novel anti-angiogenesis agents

NASA Astrophysics Data System (ADS)

Wang, Jinfeng; Zhang, Lin; Pan, Xiaoyan; Dai, Bingling; Sun, Ying; Li, Chuansheng; Zhang, Jie

2017-03-01

Recently, we have identified a biphenyl-aryl urea incorporated with salicylaldoxime (BPS-7) as an anti-angiogenesis agent. Herein, we disclosed a series of novel anti-angiogenesis agents with BPS-7 as lead compound through combining diarylureas with N-pyridin-2-ylcyclopropane carboxamide. Several title compounds exhibited simultaneous inhibition effects against three pro-angiogenic RTKs (VEGFR-2, TIE-2 and EphB4). Some of them displayed potent anti-proliferative activity against human vascular endothelial cell (EA.hy926). In particular, two potent compounds (CDAU-1 and CDAU-2) could be considered as promising anti-angiogenesis agents with triplet inhibition profile. The biological evaluation and molecular docking results indicate that N-pyridin-2-ylcyclopropane carboxamide could serve as a hinge-binding group (HBG) for the discovery of multi-target anti-angiogenesis agents. CDAU-2 also exhibited promising anti-angiogenic potency in a tissue model for angiogenesis.

Discovery of multi-target receptor tyrosine kinase inhibitors as novel anti-angiogenesis agents

PubMed Central

Wang, Jinfeng; Zhang, Lin; Pan, Xiaoyan; Dai, Bingling; Sun, Ying; Li, Chuansheng; Zhang, Jie

2017-01-01

Recently, we have identified a biphenyl-aryl urea incorporated with salicylaldoxime (BPS-7) as an anti-angiogenesis agent. Herein, we disclosed a series of novel anti-angiogenesis agents with BPS-7 as lead compound through combining diarylureas with N-pyridin-2-ylcyclopropane carboxamide. Several title compounds exhibited simultaneous inhibition effects against three pro-angiogenic RTKs (VEGFR-2, TIE-2 and EphB4). Some of them displayed potent anti-proliferative activity against human vascular endothelial cell (EA.hy926). In particular, two potent compounds (CDAU-1 and CDAU-2) could be considered as promising anti-angiogenesis agents with triplet inhibition profile. The biological evaluation and molecular docking results indicate that N-pyridin-2-ylcyclopropane carboxamide could serve as a hinge-binding group (HBG) for the discovery of multi-target anti-angiogenesis agents. CDAU-2 also exhibited promising anti-angiogenic potency in a tissue model for angiogenesis. PMID:28332573

Stability of subsystem solutions in agent-based models

NASA Astrophysics Data System (ADS)

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 mechanisms of action of novel harmine derivatives as potential antitumor agents

PubMed Central

Zhang, Xiao-Fei; Sun, Rong-qin; Jia, Yi-fan; Chen, Qing; Tu, Rong-Fu; Li, Ke-ke; Zhang, Xiao-Dong; Du, Run-Lei; Cao, Ri-hui

2016-01-01

A series of novel harmine derivatives bearing a benzylindine substituent in position-1 of β-carboline ring were synthesized and evaluated as antitumor agents. The N2-benzylated β-carboline derivatives 3a–g represented the most interesting anticancer activities and compound 3c was found to be the most active agent to diverse cancer cell lines such as gastric carcinoma, melanoma and colorectal cancer. Notably, compound 3c showed low toxicity to normal cells. The treatment significantly induced cell apoptosis. Mechanistically, PI3K/AKT signaling pathway mediated compound 3c-induced apoptosis. Compound 3c inhibited phosphorylation of AKT and promoted the production of reactive oxygen species (ROS). The ROS scavenger, LNAC and GSH, could disturb the effect of compound 3c induced apoptosis and PI3K activity inhibitor LY294002 synergistically enhanced compound 3c efficacy. Moreover, the results from nude mice xenograft model showed that compound 3c treatment effectively inhibited tumor growth and decreased tumor weight. Collectively, our results demonstrated that compound 3c exerts apoptotic effect in cancer cells via suppression of phosphorylated AKT and evocation of ROS generation, which suggested that compound 3c might be served as a promising therapeutic agent for cancer treatment. PMID:27625151

Multi-agent Reinforcement Learning Model for Effective Action Selection

NASA Astrophysics Data System (ADS)

Youk, Sang Jo; Lee, Bong Keun

Reinforcement learning is a sub area of machine learning concerned with how an agent ought to take actions in an environment so as to maximize some notion of long-term reward. In the case of multi-agent, especially, which state space and action space gets very enormous in compared to single agent, so it needs to take most effective measure available select the action strategy for effective reinforcement learning. This paper proposes a multi-agent reinforcement learning model based on fuzzy inference system in order to improve learning collect speed and select an effective action in multi-agent. This paper verifies an effective action select strategy through evaluation tests based on Robocop Keep away which is one of useful test-beds for multi-agent. Our proposed model can apply to evaluate efficiency of the various intelligent multi-agents and also can apply to strategy and tactics of robot soccer system.

Agent-based models of financial markets

NASA Astrophysics Data System (ADS)

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

Complex dynamics of a nonlinear voter model with contrarian agents

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

Tanabe, Shoma; Masuda, Naoki, E-mail: masuda@mist.i.u-tokyo.ac.jp

2013-12-15

We investigate mean-field dynamics of a nonlinear opinion formation model with congregator and contrarian agents. Each agent assumes one of the two possible states. Congregators imitate the state of other agents with a rate that increases with the number of other agents in the opposite state, as in the linear voter model and nonlinear majority voting models. Contrarians flip the state with a rate that increases with the number of other agents in the same state. The nonlinearity controls the strength of the majority voting and is used as a main bifurcation parameter. We show that the model undergoes amore » rich bifurcation scenario comprising the egalitarian equilibrium, two symmetric lopsided equilibria, limit cycle, and coexistence of different types of stable equilibria with intertwining attractive basins.« less

Model-Drive Architecture for Agent-Based Systems

NASA Technical Reports Server (NTRS)

Gradanin, Denis; Singh, H. Lally; Bohner, Shawn A.; Hinchey, Michael G.

2004-01-01

The Model Driven Architecture (MDA) approach uses a platform-independent model to define system functionality, or requirements, using some specification language. The requirements are then translated to a platform-specific model for implementation. An agent architecture based on the human cognitive model of planning, the Cognitive Agent Architecture (Cougaar) is selected for the implementation platform. The resulting Cougaar MDA prescribes certain kinds of models to be used, how those models may be prepared and the relationships of the different kinds of models. Using the existing Cougaar architecture, the level of application composition is elevated from individual components to domain level model specifications in order to generate software artifacts. The software artifacts generation is based on a metamodel. Each component maps to a UML structured component which is then converted into multiple artifacts: Cougaar/Java code, documentation, and test cases.

Modeling and simulating human teamwork behaviors using intelligent agents

NASA Astrophysics Data System (ADS)

Fan, Xiaocong; Yen, John

2004-12-01

Among researchers in multi-agent systems there has been growing interest in using intelligent agents to model and simulate human teamwork behaviors. Teamwork modeling is important for training humans in gaining collaborative skills, for supporting humans in making critical decisions by proactively gathering, fusing, and sharing information, and for building coherent teams with both humans and agents working effectively on intelligence-intensive problems. Teamwork modeling is also challenging because the research has spanned diverse disciplines from business management to cognitive science, human discourse, and distributed artificial intelligence. This article presents an extensive, but not exhaustive, list of work in the field, where the taxonomy is organized along two main dimensions: team social structure and social behaviors. Along the dimension of social structure, we consider agent-only teams and mixed human-agent teams. Along the dimension of social behaviors, we consider collaborative behaviors, communicative behaviors, helping behaviors, and the underpinning of effective teamwork-shared mental models. The contribution of this article is that it presents an organizational framework for analyzing a variety of teamwork simulation systems and for further studying simulated teamwork behaviors.

Portable Sensor for Chemical Nerve Agents and Organophosphorus Compounds

DTIC Science & Technology

2015-08-18

as pesticides in crop, livestock, and poultry products and as chemical and biological warfare agents. As a result of the high toxicity and the...agents have been exploited for use as pesticides in crop, livestock, and poultry products and as chemical and biological warfare agents. As a result of

Metalloid compounds as drugs

PubMed Central

Sekhon, B. S.

2013-01-01

The six elements commonly known as metalloids are boron, silicon, germanium, arsenic, antimony, and tellurium. Metalloid containing compounds have been used as antiprotozoal drugs. Boron-based drugs, the benzoxaboroles have been exploited as potential treatments for neglected tropical diseases. Arsenic has been used as a medicinal agent and arsphenamine was the main drug used to treat syphilis. Arsenic trioxide has been approved for the treatment of acute promyelocytic leukemia. Pentavalent antimonials have been the recommended drug for visceral leishmaniasis and cutaneous leishmaniasis. Tellurium (IV) compounds may have important roles in thiol redox biological activity in the human body, and ammonium trichloro (dioxoethylene-O, O’-)tellurate (AS101) may be a promising agent for the treatment of Parkinson’s disease. Organosilicon compounds have been shown to be effective in vitro multidrug-resistance reverting agents. PMID:24019824

Training and the Change Agent Role Model

ERIC Educational Resources Information Center

Leach, Wesley B.; Owens, Vyrle W.

1973-01-01

The authors discuss the qualities possessed by a model change agent and roles played by him as resident technical participant: analyst, advisor, advocate, systems linker, innovator, and trainer. Besides presenting the teaching plan for change agents, the authors call upon their Peace Corps experiences to provide specific examples of what is…

Bivalent compound 17MN exerts neuroprotection through interaction at multiple sites in a cellular model of Alzheimer’s disease

PubMed Central

Liu, Kai; Chojnacki, Jeremy E.; Wade, Emily E.; Saathoff, John M.; Lesnefsky, Edward J.; Chen, Qun; Zhang, Shijun

2016-01-01

Multiple pathogenic factors have been suggested in playing a role in the development of Alzheimer’s disease (AD). The multifactorial nature of AD also suggests the potential use of compounds with polypharmacology as effective disease-modifying agents. Recently, we have developed a bivalent strategy to include cell membrane anchorage into the molecular design. Our results demonstrated that the bivalent compounds exhibited multifunctional properties and potent neuroprotection in a cellular AD model. Herein, we report the mechanistic exploration of one of the representative bivalent compounds, 17MN, in MC65 cells. Our results established that MC65 cells die through a necroptotic mechanism upon the removal of tetracycline (TC). Furthermore, we have shown that mitochondrial membrane potential (MMP) and cytosolic Ca2+ levels are increased upon removal of TC. Our bivalent compound 17MN can reverse such changes and protect MC65 cells from TC removal induced cytotoxicity. The results also suggest that 17MN may function between the Aβ species and RIPK1 in producing its neuroprotection. Colocalization studies employing a fluorescent analog of 17MN and confocal microscopy demonstrated the interactions of 17MN with both mitochondria and endoplasmic reticulum (ER), thus suggesting that 17MN exerts its neuroprotection via a multiple-site mechanism in MC65 cells. Collectively, these results strongly support our original design rationale of bivalent compounds and encourage further optimization of this bivalent strategy to develop more potent analogs as novel disease-modifying agents for AD. PMID:26401780

Agent-based Modeling with MATSim for Hazards Evacuation Planning

NASA Astrophysics Data System (ADS)

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.

Polyoxometalates as antitumor agents: Bioactivity of a new polyoxometalate with copper on a human osteosarcoma model.

PubMed

León, I E; Porro, V; Astrada, S; Egusquiza, M G; Cabello, C I; Bollati-Fogolin, M; Etcheverry, S B

2014-10-05

Polyoxometalates (POMs) are early transition metal oxygen anion clusters. They display interesting biological effects mainly related to their antiviral and antitumor properties. On the other hand, copper compounds also show different biological and pharmacological effects in cell culture and in animal models. We report herein for the first time, a detailed study of the mechanisms of action of a copper(II) compound of the group of HPOMs with the formula K7Na3[Cu4(H2O)2(PW9034)2]20H2O (PW9Cu), in a model of human osteosarcoma derived cell line, MG-63. The compound inhibited selectively the viability of the osteosarcoma cells in the range of 25-100μM (p<0.01). Besides, we have clearly shown a more deleterious action of PW9Cu on tumor osteoblasts than in normal cells. Cytotoxicity studies also showed deleterious effects for PW9Cu. The increment of reactive oxygen species (ROS) and the decrease of the GSH/GSSG ratio were involved in the antiproliferative effects of PW9Cu. Moreover, the compound caused cell cycle arrest in G2 phase, triggering apoptosis as determined by flow cytometry. As a whole, these results showed the main mechanisms of the deleterious effects of PW9Cu in the osteosarcoma cell line MG-63, demonstrating that this compound is a promissory agent for cancer treatments. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Agent-based modeling in ecological economics.

PubMed

Heckbert, Scott; Baynes, Tim; Reeson, Andrew

2010-01-01

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

Agent based modeling of the coevolution of hostility and pacifism

NASA Astrophysics Data System (ADS)

Dalmagro, Fermin; Jimenez, Juan

2015-01-01

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

Modeling marine oily wastewater treatment by a probabilistic agent-based approach.

PubMed

Jing, Liang; Chen, Bing; Zhang, Baiyu; Ye, Xudong

2018-02-01

This study developed a novel probabilistic agent-based approach for modeling of marine oily wastewater treatment processes. It begins first by constructing a probability-based agent simulation model, followed by a global sensitivity analysis and a genetic algorithm-based calibration. The proposed modeling approach was tested through a case study of the removal of naphthalene from marine oily wastewater using UV irradiation. The removal of naphthalene was described by an agent-based simulation model using 8 types of agents and 11 reactions. Each reaction was governed by a probability parameter to determine its occurrence. The modeling results showed that the root mean square errors between modeled and observed removal rates were 8.73 and 11.03% for calibration and validation runs, respectively. Reaction competition was analyzed by comparing agent-based reaction probabilities, while agents' heterogeneity was visualized by plotting their real-time spatial distribution, showing a strong potential for reactor design and process optimization. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Coupled Simulation Architecture for Agent-Based/Geohydrological Modelling

NASA Astrophysics Data System (ADS)

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 models in translational systems biology

PubMed Central

An, Gary; Mi, Qi; Dutta-Moscato, Joyeeta; Vodovotz, Yoram

2013-01-01

Effective translational methodologies for knowledge representation are needed in order to make strides against the constellation of diseases that affect the world today. These diseases are defined by their mechanistic complexity, redundancy, and nonlinearity. Translational systems biology aims to harness the power of computational simulation to streamline drug/device design, simulate clinical trials, and eventually to predict the effects of drugs on individuals. The ability of agent-based modeling to encompass multiple scales of biological process as well as spatial considerations, coupled with an intuitive modeling paradigm, suggests that this modeling framework is well suited for translational systems biology. This review describes agent-based modeling and gives examples of its translational applications in the context of acute inflammation and wound healing. PMID:20835989

Identification of compounds with anti-convulsant properties in a zebrafish model of epileptic seizures

PubMed Central

Baxendale, Sarah; Holdsworth, Celia J.; Meza Santoscoy, Paola L.; Harrison, Michael R. M.; Fox, James; Parkin, Caroline A.; Ingham, Philip W.; Cunliffe, Vincent T.

2012-01-01

SUMMARY The availability of animal models of epileptic seizures provides opportunities to identify novel anticonvulsants for the treatment of people with epilepsy. We found that exposure of 2-day-old zebrafish embryos to the convulsant agent pentylenetetrazole (PTZ) rapidly induces the expression of synaptic-activity-regulated genes in the CNS, and elicited vigorous episodes of calcium (Ca2+) flux in muscle cells as well as intense locomotor activity. We then screened a library of ∼2000 known bioactive small molecules and identified 46 compounds that suppressed PTZ-inducedtranscription of the synaptic-activity-regulated gene fos in 2-day-old (2 dpf) zebrafish embryos. Further analysis of a subset of these compounds, which included compounds with known and newly identified anticonvulsant properties, revealed that they exhibited concentration-dependent inhibition of both locomotor activity and PTZ-induced fos transcription, confirming their anticonvulsant characteristics. We conclude that this in situ hybridisation assay for fos transcription in the zebrafish embryonic CNS is a robust, high-throughput in vivo indicator of the neural response to convulsant treatment and lends itself well to chemical screening applications. Moreover, our results demonstrate that suppression of PTZ-induced fos expression provides a sensitive means of identifying compounds with anticonvulsant activities. PMID:22730455

Data-driven agent-based modeling, with application to rooftop solar adoption

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

Zhang, Haifeng; Vorobeychik, Yevgeniy; Letchford, Joshua

Agent-based modeling is commonly used for studying complex system properties emergent from interactions among many agents. We present a novel data-driven agent-based modeling framework applied to forecasting individual and aggregate residential rooftop solar adoption in San Diego county. Our first step is to learn a model of individual agent behavior from combined data of individual adoption characteristics and property assessment. We then construct an agent-based simulation with the learned model embedded in artificial agents, and proceed to validate it using a holdout sequence of collective adoption decisions. We demonstrate that the resulting agent-based model successfully forecasts solar adoption trends andmore » provides a meaningful quantification of uncertainty about its predictions. We utilize our model to optimize two classes of policies aimed at spurring solar adoption: one that subsidizes the cost of adoption, and another that gives away free systems to low-income house- holds. We find that the optimal policies derived for the latter class are significantly more efficacious, whereas the policies similar to the current California Solar Initiative incentive scheme appear to have a limited impact on overall adoption trends.« less

Data-driven agent-based modeling, with application to rooftop solar adoption

DOE PAGES

Zhang, Haifeng; Vorobeychik, Yevgeniy; Letchford, Joshua; ...

2016-01-25

Agent-based modeling is commonly used for studying complex system properties emergent from interactions among many agents. We present a novel data-driven agent-based modeling framework applied to forecasting individual and aggregate residential rooftop solar adoption in San Diego county. Our first step is to learn a model of individual agent behavior from combined data of individual adoption characteristics and property assessment. We then construct an agent-based simulation with the learned model embedded in artificial agents, and proceed to validate it using a holdout sequence of collective adoption decisions. We demonstrate that the resulting agent-based model successfully forecasts solar adoption trends andmore » provides a meaningful quantification of uncertainty about its predictions. We utilize our model to optimize two classes of policies aimed at spurring solar adoption: one that subsidizes the cost of adoption, and another that gives away free systems to low-income house- holds. We find that the optimal policies derived for the latter class are significantly more efficacious, whereas the policies similar to the current California Solar Initiative incentive scheme appear to have a limited impact on overall adoption trends.« less

A Culture-Sensitive Agent in Kirman's Ant Model

NASA Astrophysics Data System (ADS)

Chen, Shu-Heng; Liou, Wen-Ching; Chen, Ting-Yu

The global financial crisis brought a serious collapse involving a "systemic" meltdown. Internet technology and globalization have increased the chances for interaction between countries and people. The global economy has become more complex than ever before. Mark Buchanan [12] indicated that agent-based computer models will prevent another financial crisis and has been particularly influential in contributing insights. There are two reasons why culture-sensitive agent on the financial market has become so important. Therefore, the aim of this article is to establish a culture-sensitive agent and forecast the process of change regarding herding behavior in the financial market. We based our study on the Kirman's Ant Model[4,5] and Hofstede's Natational Culture[11] to establish our culture-sensitive agent based model. Kirman's Ant Model is quite famous and describes financial market herding behavior from the expectations of the future of financial investors. Hofstede's cultural consequence used the staff of IBM in 72 different countries to understand the cultural difference. As a result, this paper focuses on one of the five dimensions of culture from Hofstede: individualism versus collectivism and creates a culture-sensitive agent and predicts the process of change regarding herding behavior in the financial market. To conclude, this study will be of importance in explaining the herding behavior with cultural factors, as well as in providing researchers with a clearer understanding of how herding beliefs of people about different cultures relate to their finance market strategies.

Glutathione-Enhancing Agents Protect against Steatohepatitis in a Dietary Model

PubMed Central

Im, Hee-Jeong; Chen, Theresa S.; de Villiers, Willem J. S.; McClain, Craig J.

2010-01-01

Nonalcoholic fatty liver (NAFL) and steatohepatitis (NASH) may accompany obesity, diabetes, parenteral nutrition, jejeuno-ileal bypass, and chronic inflammatory bowel disease. Currently there is no FDA approved and effective therapy available. We investigated the potential efficacy of those agents that stimulate glutathione (GSH) biosynthesis on the development of experimental steatohepatitis. Rats fed (ad libitum) amino acid based methionine-choline deficient (MCD) diet were further gavaged with (1) vehicle (MCD), (2) S-adenosylmethionine (SAMe), or (3) 2(RS)-n-propylthiazolidine-4(R)-carboxylic acid (PTCA). Results: MCD diet significantly reduced hematocrit, and this abnormality improved in the treated groups (p < 0.01). Serum transaminases were considerably elevated (AST: 5.8-fold; ALT: 3.22-fold) in MCD rats. However, administration of GSH-enhancing agents significantly suppressed these abnormal enzyme activities. MCD rats developed severe liver pathology manifested by fatty degeneration, inflammation, and necrosis, which significantly improved with therapy. Blood levels of GSH were significantly depleted in MCD rats but normalized in the treated groups. Finally, RT-PCR measurements showed a significant upregulation of genes involved in tissue remodeling and fibrosis (matrix metalloproteinases, collagen-α1), suppressor of cytokines signaling1, and the inflammatory cytokines (IL-1β, IL-6, TNF-α, and TGF-β) in the livers of rats fed MCD. GSH-enhancing therapies significantly attenuated the expression of deleterious proinflammatory and fibrogenic genes in this dietary model. This is the first report that oral administration of SAMe and PTCA provide protection against liver injury in this model and suggests therapeutic applications of these compounds in NASH patients. PMID:16498637

Modelling of robotic work cells using agent based-approach

NASA Astrophysics Data System (ADS)

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

2016-08-01

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

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

NASA Astrophysics Data System (ADS)

Zhong, Wei; Kim, Yushim

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

Identification of TRAIL-inducing compounds highlights small molecule ONC201/TIC10 as a unique anti-cancer agent that activates the TRAIL pathway.

PubMed

Allen, Joshua E; Krigsfeld, Gabriel; Patel, Luv; Mayes, Patrick A; Dicker, David T; Wu, Gen Sheng; El-Deiry, Wafik S

2015-05-01

We previously reported the identification of ONC201/TIC10, a novel small molecule inducer of the human TRAIL gene that improves efficacy-limiting properties of recombinant TRAIL and is in clinical trials in advanced cancers based on its promising safety and antitumor efficacy in several preclinical models. We performed a high throughput luciferase reporter screen using the NCI Diversity Set II to identify TRAIL-inducing compounds. Small molecule-mediated induction of TRAIL reporter activity was relatively modest and the majority of the hit compounds induced low levels of TRAIL upregulation. Among the candidate TRAIL-inducing compounds, TIC9 and ONC201/TIC10 induced sustained TRAIL upregulation and apoptosis in tumor cells in vitro and in vivo. However, ONC201/TIC10 potentiated tumor cell death while sparing normal cells, unlike TIC9, and lacked genotoxicity in normal fibroblasts. Investigating the effects of TRAIL-inducing compounds on cell signaling pathways revealed that TIC9 and ONC201/TIC10, which are the most potent inducers of cell death, exclusively activate Foxo3a through inactivation of Akt/ERK to upregulate TRAIL and its pro-apoptotic death receptor DR5. These studies reveal the selective activity of ONC201/TIC10 that led to its selection as a lead compound for this novel class of antitumor agents and suggest that ONC201/TIC10 is a unique inducer of the TRAIL pathway through its concomitant regulation of the TRAIL ligand and its death receptor DR5.

Model reduction for agent-based social simulation: coarse-graining a civil violence model.

PubMed

Zou, Yu; Fonoberov, Vladimir A; Fonoberova, Maria; Mezic, Igor; Kevrekidis, Ioannis G

2012-06-01

Agent-based modeling (ABM) constitutes a powerful computational tool for the exploration of phenomena involving emergent dynamic behavior in the social sciences. This paper demonstrates a computer-assisted approach that bridges the significant gap between the single-agent microscopic level and the macroscopic (coarse-grained population) level, where fundamental questions must be rationally answered and policies guiding the emergent dynamics devised. Our approach will be illustrated through an agent-based model of civil violence. This spatiotemporally varying ABM incorporates interactions between a heterogeneous population of citizens [active (insurgent), inactive, or jailed] and a population of police officers. Detailed simulations exhibit an equilibrium punctuated by periods of social upheavals. We show how to effectively reduce the agent-based dynamics to a stochastic model with only two coarse-grained degrees of freedom: the number of jailed citizens and the number of active ones. The coarse-grained model captures the ABM dynamics while drastically reducing the computation time (by a factor of approximately 20).

Model reduction for agent-based social simulation: Coarse-graining a civil violence model

NASA Astrophysics Data System (ADS)

Zou, Yu; Fonoberov, Vladimir A.; Fonoberova, Maria; Mezic, Igor; Kevrekidis, Ioannis G.

2012-06-01

Agent-based modeling (ABM) constitutes a powerful computational tool for the exploration of phenomena involving emergent dynamic behavior in the social sciences. This paper demonstrates a computer-assisted approach that bridges the significant gap between the single-agent microscopic level and the macroscopic (coarse-grained population) level, where fundamental questions must be rationally answered and policies guiding the emergent dynamics devised. Our approach will be illustrated through an agent-based model of civil violence. This spatiotemporally varying ABM incorporates interactions between a heterogeneous population of citizens [active (insurgent), inactive, or jailed] and a population of police officers. Detailed simulations exhibit an equilibrium punctuated by periods of social upheavals. We show how to effectively reduce the agent-based dynamics to a stochastic model with only two coarse-grained degrees of freedom: the number of jailed citizens and the number of active ones. The coarse-grained model captures the ABM dynamics while drastically reducing the computation time (by a factor of approximately 20).

Pattern-oriented modeling of agent-based complex systems: Lessons from ecology

USGS Publications Warehouse

Grimm, Volker; Revilla, Eloy; Berger, Uta; Jeltsch, Florian; Mooij, Wolf M.; Railsback, Steven F.; Thulke, Hans-Hermann; Weiner, Jacob; Wiegand, Thorsten; DeAngelis, Donald L.

2005-01-01

Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.

Pattern-Oriented Modeling of Agent-Based Complex Systems: Lessons from Ecology

NASA Astrophysics Data System (ADS)

Grimm, Volker; Revilla, Eloy; Berger, Uta; Jeltsch, Florian; Mooij, Wolf M.; Railsback, Steven F.; Thulke, Hans-Hermann; Weiner, Jacob; Wiegand, Thorsten; DeAngelis, Donald L.

2005-11-01

Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.

Research on monocentric model of urbanization by agent-based simulation

NASA Astrophysics Data System (ADS)

Xue, Ling; Yang, Kaizhong

2008-10-01

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

Agent Based Model of Livestock Movements

NASA Astrophysics Data System (ADS)

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.

DAMS: A Model to Assess Domino Effects by Using Agent-Based Modeling and Simulation.

PubMed

Zhang, Laobing; Landucci, Gabriele; Reniers, Genserik; Khakzad, Nima; Zhou, Jianfeng

2017-12-19

Historical data analysis shows that escalation accidents, so-called domino effects, have an important role in disastrous accidents in the chemical and process industries. In this study, an agent-based modeling and simulation approach is proposed to study the propagation of domino effects in the chemical and process industries. Different from the analytical or Monte Carlo simulation approaches, which normally study the domino effect at probabilistic network levels, the agent-based modeling technique explains the domino effects from a bottom-up perspective. In this approach, the installations involved in a domino effect are modeled as agents whereas the interactions among the installations (e.g., by means of heat radiation) are modeled via the basic rules of the agents. Application of the developed model to several case studies demonstrates the ability of the model not only in modeling higher-level domino effects and synergistic effects but also in accounting for temporal dependencies. The model can readily be applied to large-scale complicated cases. © 2017 Society for Risk Analysis.

Investigations of chemical warfare agents and toxic industrial compounds with proton-transfer-reaction mass spectrometry for a real-time threat monitoring scenario.

PubMed

Kassebacher, Thomas; Sulzer, Philipp; Jürschik, Simone; Hartungen, Eugen; Jordan, Alfons; Edtbauer, Achim; Feil, Stefan; Hanel, Gernot; Jaksch, Stefan; Märk, Lukas; Mayhew, Chris A; Märk, Tilmann D

2013-01-30

Security and protection against terrorist attacks are major issues in modern society. One especially challenging task is the monitoring and protection of air conditioning and heating systems of buildings against terrorist attacks with toxic chemicals. As existing technologies have low selectivity, long response times or insufficient sensitivity, there is a need for a novel approach such as we present here. We have analyzed various chemical warfare agents (CWAs) and/or toxic industrial compounds (TICs) and related compounds, namely phosgene, diphosgene, chloroacetone, chloroacetophenone, diisopropylaminoethanol, and triethyl phosphate, utilizing a high-resolution proton-transfer-reaction time-of-flight mass spectrometry (PTR-TOFMS) instrument with the objective of finding key product ions and their intensities, which will allow a low-resolution quadrupole mass spectrometry based PTR-MS system to be used with high confidence in the assignment of threat agents in the atmosphere. We obtained high accuracy PTR-TOFMS mass spectra of the six compounds under study at two different values for the reduced electric field in the drift tube (E/N). From these data we have compiled a table containing product ions, and isotopic and E/N ratios for highly selective threat compound detection with a compact and cost-effective quadrupole-based PTR-MS instrument. Furthermore, using chloroacetophenone (tear gas), we demonstrated that this instrument's response is highly linear in the concentration range of typical Acute Exposure Guideline Levels (AEGLs). On the basis of the presented results it is possible to develop a compact and cost-effective PTR-QMS instrument that monitors air supply systems and triggers an alarm as soon as the presence of a threat agent is detected. We hope that this real-time surveillance device will help to seriously improve safety and security in environments vulnerable to terrorist attacks with toxic chemicals. Copyright © 2012 John Wiley & Sons, Ltd.

Zebrafish as a model for acetylcholinesterase-inhibiting organophosphorus agent exposure and oxime reactivation

PubMed Central

Koenig, Jeffrey A.; Dao, Thuy L.; Kan, Robert K.; Shih, Tsung-Ming

2016-01-01

The current research progression efforts for investigating novel treatments for exposure to organophosphorus (OP) compounds that inhibit acetylcholinesterase (AChE), including pesticides and chemical warfare nerve agents (CWNAs), rely solely on in vitro cell assays and in vivo rodent models. The zebrafish (Danio rerio) is a popular, well-established vertebrate model in biomedical research that offers high-throughput capabilities and genetic manipulation not readily available with rodents. A number of research studies have investigated the effects of subacute developmental exposure to OP pesticides in zebrafish, observing detrimental effects on gross morphology, neuronal development, and behavior. Few studies, however, have utilized this model to evaluate treatments, such as oxime reactivators, anticholinergics, or anticonvulsants, following acute exposure. Preliminary work has investigated the effects of CWNA exposure. The results clearly demonstrated relative toxicity and oxime efficacy similar to that reported for the rodent model. This review surveys the current literature utilizing zebrafish as a model for OP exposure and highlights its potential use as a high-throughput system for evaluating AChE reactivator antidotal treatments to acute pesticide and CWNA exposure. PMID:27123828

Compound toxicity screening and structure-activity relationship modeling in Escherichia coli.

PubMed

Planson, Anne-Gaëlle; Carbonell, Pablo; Paillard, Elodie; Pollet, Nicolas; Faulon, Jean-Loup

2012-03-01

Synthetic biology and metabolic engineering are used to develop new strategies for producing valuable compounds ranging from therapeutics to biofuels in engineered microorganisms. When developing methods for high-titer production cells, toxicity is an important element to consider. Indeed the production rate can be limited due to toxic intermediates or accumulation of byproducts of the heterologous biosynthetic pathway of interest. Conversely, highly toxic molecules are desired when designing antimicrobials. Compound toxicity in bacteria plays a major role in metabolic engineering as well as in the development of new antibacterial agents. Here, we screened a diversified chemical library of 166 compounds for toxicity in Escherichia coli. The dataset was built using a clustering algorithm maximizing the chemical diversity in the library. The resulting assay data was used to develop a toxicity predictor that we used to assess the toxicity of metabolites throughout the metabolome. This new tool for predicting toxicity can thus be used for fine-tuning heterologous expression and can be integrated in a computational-framework for metabolic pathway design. Many structure-activity relationship tools have been developed for toxicology studies in eukaryotes [Valerio (2009), Toxicol Appl Pharmacol, 241(3): 356-370], however, to the best of our knowledge we present here the first E. coli toxicity prediction web server based on QSAR models (EcoliTox server: http://www.issb.genopole.fr/∼faulon/EcoliTox.php). Copyright © 2011 Wiley Periodicals, Inc.

Demeter, persephone, and the search for emergence in agent-based models.

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

North, M. J.; Howe, T. R.; Collier, N. T.

2006-01-01

In Greek mythology, the earth goddess Demeter was unable to find her daughter Persephone after Persephone was abducted by Hades, the god of the underworld. Demeter is said to have embarked on a long and frustrating, but ultimately successful, search to find her daughter. Unfortunately, long and frustrating searches are not confined to Greek mythology. In modern times, agent-based modelers often face similar troubles when searching for agents that are to be to be connected to one another and when seeking appropriate target agents while defining agent behaviors. The result is a 'search for emergence' in that many emergent ormore » potentially emergent behaviors in agent-based models of complex adaptive systems either implicitly or explicitly require search functions. This paper considers a new nested querying approach to simplifying such agent-based modeling and multi-agent simulation search problems.« less

Indoor sorption of surrogates for sarin and related nerve agents.

PubMed

Singer, Brett C; Hodgson, Alfred T; Destaillats, Hugo; Hotchi, Toshifumi; Revzan, Kenneth L; Sextro, Richard G

2005-05-01

Sorption rate parameters were determined for three organophosphorus (OP) compounds [dimethyl methylphosphonate (DMMP), diethyl ethylphosphonate (DEEP), and triethyl phosphate (TEP)] as surrogates for the G-type nerve agents sarin (GB), soman (GD), and tabun (GA). OP surrogates were injected and vaporized with additional volatile organic compounds into a 50 m3 chamber finished with painted wallboard. Experiments were conducted at two furnishing levels: (i) chamber containing only hard surfaces including a desk, a bookcase, tables, and chairs and (ii) with the addition of plush materials including carpet with cushion, draperies, and upholstered furniture. Each furnishing level was studied with aged and new painted wallboard. Gas-phase concentrations were measured during sealed chamber adsorb and desorb phases and then fit to three mathematical variations of a previously proposed sorption model having a surface sink and allowing for an embedded sink. A four-parameter model allowing unequal transport rates between surface and embedded sinks provided excellent fits for all conditions. To evaluate the potential effect of sorption, this model was incorporated into an indoor air quality simulation model to predict indoor concentrations of a G-type agent and a nonsorbing agent for hypothetical outdoor releases with shelter-in-place (SIP) response. Sorption was simulated using a range of parameters obtained experimentally. Simulations considered outdoor Gaussian plumes of 1- and 5-h duration and infiltration rates of 0.1, 0.3, and 0.9 h(-1). Indoor toxic loads (TL) for a 10-h SIP were calculated as integral C2 dt for a G-type agent. For the 5-h plume, sheltering reduced TLs for the nonsorbing agent to approximately 10-65% of outdoor levels. Analogous TLs for a G-type agent were 2-31% or 0.3-12% of outdoor levels assuming slow or moderate sorption. The relative effect of sorption was more pronounced for the longer plume and higher infiltration rates.

Effective Team Support: From Modeling to Software Agents

NASA Technical Reports Server (NTRS)

Remington, Roger W. (Technical Monitor); John, Bonnie; Sycara, Katia

2003-01-01

The purpose of this research contract was to perform multidisciplinary research between CMU psychologists, computer scientists and engineers and NASA researchers to design a next generation collaborative system to support a team of human experts and intelligent agents. To achieve robust performance enhancement of such a system, we had proposed to perform task and cognitive modeling to thoroughly understand the impact technology makes on the organization and on key individual personnel. Guided by cognitively-inspired requirements, we would then develop software agents that support the human team in decision making, information filtering, information distribution and integration to enhance team situational awareness. During the period covered by this final report, we made substantial progress in modeling infrastructure and task infrastructure. Work is continuing under a different contract to complete empirical data collection, cognitive modeling, and the building of software agents to support the teams task.

Agent-Based Modeling of Growth Processes

ERIC Educational Resources Information Center

Abraham, Ralph

2014-01-01

Growth processes abound in nature, and are frequently the target of modeling exercises in the sciences. In this article we illustrate an agent-based approach to modeling, in the case of a single example from the social sciences: bullying.

Agent-Based Modeling in Public Health: Current Applications and Future Directions.

PubMed

Tracy, Melissa; Cerdá, Magdalena; Keyes, Katherine M

2018-04-01

Agent-based modeling is a computational approach in which agents with a specified set of characteristics interact with each other and with their environment according to predefined rules. We review key areas in public health where agent-based modeling has been adopted, including both communicable and noncommunicable disease, health behaviors, and social epidemiology. We also describe the main strengths and limitations of this approach for questions with public health relevance. Finally, we describe both methodologic and substantive future directions that we believe will enhance the value of agent-based modeling for public health. In particular, advances in model validation, comparisons with other causal modeling procedures, and the expansion of the models to consider comorbidity and joint influences more systematically will improve the utility of this approach to inform public health research, practice, and policy.

Agent-Based Model Approach to Complex Phenomena in Real Economy

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

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

2014-09-01

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

Development and verification of an agent-based model of opinion leadership.

PubMed

Anderson, Christine A; Titler, Marita G

2014-09-27

The use of opinion leaders is a strategy used to speed the process of translating research into practice. Much is still unknown about opinion leader attributes and activities and the context in which they are most effective. Agent-based modeling is a methodological tool that enables demonstration of the interactive and dynamic effects of individuals and their behaviors on other individuals in the environment. The purpose of this study was to develop and test an agent-based model of opinion leadership. The details of the design and verification of the model are presented. The agent-based model was developed by using a software development platform to translate an underlying conceptual model of opinion leadership into a computer model. Individual agent attributes (for example, motives and credibility) and behaviors (seeking or providing an opinion) were specified as variables in the model in the context of a fictitious patient care unit. The verification process was designed to test whether or not the agent-based model was capable of reproducing the conditions of the preliminary conceptual model. The verification methods included iterative programmatic testing ('debugging') and exploratory analysis of simulated data obtained from execution of the model. The simulation tests included a parameter sweep, in which the model input variables were adjusted systematically followed by an individual time series experiment. Statistical analysis of model output for the 288 possible simulation scenarios in the parameter sweep revealed that the agent-based model was performing, consistent with the posited relationships in the underlying model. Nurse opinion leaders act on the strength of their beliefs and as a result, become an opinion resource for their uncertain colleagues, depending on their perceived credibility. Over time, some nurses consistently act as this type of resource and have the potential to emerge as opinion leaders in a context where uncertainty exists. The

Carbonyl Compounds Produced by Vaporizing Cannabis Oil Thinning Agents.

PubMed

Troutt, William D; DiDonato, Matthew D

2017-11-01

Cannabis use has increased in the United States, particularly the use of vaporized cannabis oil, which is often mixed with thinning agents for use in vaporizing devices. E-cigarette research shows that heated thinning agents produce potentially harmful carbonyls; however, similar studies have not been conducted (1) with agents that are commonly used in the cannabis industry and (2) at temperatures that are appropriate for cannabis oil vaporization. The goal of this study was to determine whether thinning agents used in the cannabis industry produce potentially harmful carbonyls when heated to a temperature that is appropriate for cannabis oil vaporization. Four thinning agents (propylene glycol [PG], vegetable glycerin [VG], polyethylene glycol 400 [PEG 400], and medium chain triglycerides [MCT]) were heated to 230°C and the resulting vapors were tested for acetaldehyde, acrolein, and formaldehyde. Each agent was tested three times. Testing was conducted in a smoking laboratory. Carbonyl levels were measured in micrograms per puff block. Analyses showed that PEG 400 produced significantly higher levels of acetaldehyde and formaldehyde than PG, MCT, and VG. Formaldehyde production was also significantly greater in PG compared with MCT and VG. Acrolein production did not differ significantly across the agents. PG and PEG 400 produced high levels of acetaldehyde and formaldehyde when heated to 230°C. Formaldehyde production from PEG 400 isolate was particularly high, with one inhalation accounting for 1.12% of the daily exposure limit, nearly the same exposure as smoking one cigarette. Because PG and PEG 400 are often mixed with cannabis oil, individuals who vaporize cannabis oil products may risk exposure to harmful formaldehyde levels. Although more research is needed, consumers and policy makers should consider these potential health effects before use and when drafting cannabis-related legislation.

Modeling Natural Anti-Inflammatory Compounds by Molecular Topology

PubMed Central

Galvez-Llompart, María; Zanni, Riccardo; García-Domenech, Ramón

2011-01-01

One of the main pharmacological problems today in the treatment of chronic inflammation diseases consists of the fact that anti-inflammatory drugs usually exhibit side effects. The natural products offer a great hope in the identification of bioactive lead compounds and their development into drugs for treating inflammatory diseases. Computer-aided drug design has proved to be a very useful tool for discovering new drugs and, specifically, Molecular Topology has become a good technique for such a goal. A topological-mathematical model, obtained by linear discriminant analysis, has been developed for the search of new anti-inflammatory natural compounds. An external validation obtained with the remaining compounds (those not used in building up the model), has been carried out. Finally, a virtual screening on natural products was performed and 74 compounds showed actual anti-inflammatory activity. From them, 54 had been previously described as anti-inflammatory in the literature. This can be seen as a plus in the model validation and as a reinforcement of the role of Molecular Topology as an efficient tool for the discovery of new anti-inflammatory natural compounds. PMID:22272145

Precursors to radiopharmaceutical agents for tissue imaging

DOEpatents

Srivastava, Prem C.; Knapp, Jr., Furn F.

1988-01-01

A class of radiolabeled compounds to be used in tissue imaging that exhibits rapid brain uptake, good brain:blood radioactivity ratios, and long retention times. The imaging agents are more specifically radioiodinated aromatic amines attached to dihydropyridine carriers, that exhibit heart as well as brain specificity. In addition to the radiolabeled compounds, classes of compounds are also described that are used as precursors and intermediates in the preparation of the imaging agents.

Agent-Based vs. Equation-based Epidemiological Models:A Model Selection Case Study

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

Sukumar, Sreenivas R; Nutaro, James J

This paper is motivated by the need to design model validation strategies for epidemiological disease-spread models. We consider both agent-based and equation-based models of pandemic disease spread and study the nuances and complexities one has to consider from the perspective of model validation. For this purpose, we instantiate an equation based model and an agent based model of the 1918 Spanish flu and we leverage data published in the literature for our case- study. We present our observations from the perspective of each implementation and discuss the application of model-selection criteria to compare the risk in choosing one modeling paradigmmore » to another. We conclude with a discussion of our experience and document future ideas for a model validation framework.« less

Pain expressiveness and altruistic behavior: an exploration using agent-based modeling.

PubMed

de C Williams, Amanda C; Gallagher, Elizabeth; Fidalgo, Antonio R; Bentley, Peter J

2016-03-01

Predictions which invoke evolutionary mechanisms are hard to test. Agent-based modeling in artificial life offers a way to simulate behaviors and interactions in specific physical or social environments over many generations. The outcomes have implications for understanding adaptive value of behaviors in context. Pain-related behavior in animals is communicated to other animals that might protect or help, or might exploit or predate. An agent-based model simulated the effects of displaying or not displaying pain (expresser/nonexpresser strategies) when injured and of helping, ignoring, or exploiting another in pain (altruistic/nonaltruistic/selfish strategies). Agents modeled in MATLAB interacted at random while foraging (gaining energy); random injury interrupted foraging for a fixed time unless help from an altruistic agent, who paid an energy cost, speeded recovery. Environmental and social conditions also varied, and each model ran for 10,000 iterations. Findings were meaningful in that, in general, contingencies that evident from experimental work with a variety of mammals, over a few interactions, were replicated in the agent-based model after selection pressure over many generations. More energy-demanding expression of pain reduced its frequency in successive generations, and increasing injury frequency resulted in fewer expressers and altruists. Allowing exploitation of injured agents decreased expression of pain to near zero, but altruists remained. Decreasing costs or increasing benefits of helping hardly changed its frequency, whereas increasing interaction rate between injured agents and helpers diminished the benefits to both. Agent-based modeling allows simulation of complex behaviors and environmental pressures over evolutionary time.

Applications of agent-based modeling to nutrient movement Lake Michigan

EPA Science Inventory

As part of an ongoing project aiming to provide useful information for nearshore management (harmful algal blooms, nutrient loading), we explore the value of agent-based models in Lake Michigan. Agent-based models follow many individual “agents” moving through a simul...

Agent-Based Modeling in Systems Pharmacology.

PubMed

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.

A New Method of Comparing Forcing Agents in Climate Models

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

Kravitz, Benjamin S.; MacMartin, Douglas; Rasch, Philip J.

We describe a new method of comparing different climate forcing agents (e.g., CO2, CH4, and solar irradiance) that avoids many of the ambiguities introduced by temperature-related climate feedbacks. This is achieved by introducing an explicit feedback loop external to the climate model that adjusts one forcing agent to balance another while keeping global mean surface temperature constant. Compared to current approaches, this method has two main advantages: (i) the need to define radiative forcing is bypassed and (ii) by maintaining roughly constant global mean temperature, the effects of state dependence on internal feedback strengths are minimized. We demonstrate this approachmore » for several different forcing agents and derive the relationships between these forcing agents in two climate models; comparisons between forcing agents are highly linear in concordance with predicted functional forms. Transitivity of the relationships between the forcing agents appears to hold within a wide range of forcing. The relationships between the forcing agents obtained from this method are consistent across both models but differ from relationships that would be obtained from calculations of radiative forcing, highlighting the importance of controlling for surface temperature feedback effects when separating radiative forcing and climate response.« less

Comparing large-scale computational approaches to epidemic modeling: agent-based versus structured metapopulation models.

PubMed

Ajelli, Marco; Gonçalves, Bruno; Balcan, Duygu; Colizza, Vittoria; Hu, Hao; Ramasco, José J; Merler, Stefano; Vespignani, Alessandro

2010-06-29

In recent years large-scale computational models for the realistic simulation of epidemic outbreaks have been used with increased frequency. Methodologies adapt to the scale of interest and range from very detailed agent-based models to spatially-structured metapopulation models. One major issue thus concerns to what extent the geotemporal spreading pattern found by different modeling approaches may differ and depend on the different approximations and assumptions used. We provide for the first time a side-by-side comparison of the results obtained with a stochastic agent-based model and a structured metapopulation stochastic model for the progression of a baseline pandemic event in Italy, a large and geographically heterogeneous European country. The agent-based model is based on the explicit representation of the Italian population through highly detailed data on the socio-demographic structure. The metapopulation simulations use the GLobal Epidemic and Mobility (GLEaM) model, based on high-resolution census data worldwide, and integrating airline travel flow data with short-range human mobility patterns at the global scale. The model also considers age structure data for Italy. GLEaM and the agent-based models are synchronized in their initial conditions by using the same disease parameterization, and by defining the same importation of infected cases from international travels. The results obtained show that both models provide epidemic patterns that are in very good agreement at the granularity levels accessible by both approaches, with differences in peak timing on the order of a few days. The relative difference of the epidemic size depends on the basic reproductive ratio, R0, and on the fact that the metapopulation model consistently yields a larger incidence than the agent-based model, as expected due to the differences in the structure in the intra-population contact pattern of the approaches. The age breakdown analysis shows that similar attack rates are

Efficacy of Several Therapeutic Agents in a Murine Model of Dry Eye Syndrome

PubMed Central

Kilic, Servet; Kulualp, Kadri

2016-01-01

In the current study, we used 56 female BALB/c mice with induced dry eye syndrome to evaluate the therapeutic effects of formal saline (FS), sodium hyaluronate (SH), diclofenac sodium (DS), olopatadine (OP), retinoic acid (RA), fluoromethanole (FML), cyclosporine A (CsA), and doxycycline hyclate (DH). All subjects were kept in an evaporative ‘dry eye cabinet’ for the assessment of blink rate, tear production, tear break-up time, and impression cytology prior to (baseline) and during weeks 2, 4, and 6 of the study. The right eyes of all subjects were treated topically with 5 µL of the test agent twice daily during weeks 2 through 6. Impression cytology and tear break-up time differed between time points in all groups and differed between groups at weeks 4 and 6. Blink rate differed by time point only in the FS, FML, and DH groups. Tear production according to the phenol red cotton thread test differed by time point for all groups except RA, CsA, and DH and differed between groups only at week 6. Among the compounds tested in the present study, DS and CsA were the most effective therapeutic agents in our mouse model of dry eye syndrome; these agents likely exert their therapeutic effect through their antiinflammatory activity. PMID:27053565

Developing a Conceptual Architecture for a Generalized Agent-based Modeling Environment (GAME)

DTIC Science & Technology

2008-03-01

4. REPAST (Java, Python , C#, Open Source) ........28 5. MASON: Multi-Agent Modeling Language (Swarm Extension... Python , C#, Open Source) Repast (Recursive Porous Agent Simulation Toolkit) was designed for building agent-based models and simulations in the...Repast makes it easy for inexperienced users to build models by including a built-in simple model and provide interfaces through which menus and Python

Modelling brain emergent behaviours through coevolution of neural agents.

PubMed

Maniadakis, Michail; Trahanias, Panos

2006-06-01

Recently, many research efforts focus on modelling partial brain areas with the long-term goal to support cognitive abilities of artificial organisms. Existing models usually suffer from heterogeneity, which constitutes their integration very difficult. The present work introduces a computational framework to address brain modelling tasks, emphasizing on the integrative performance of substructures. Moreover, implemented models are embedded in a robotic platform to support its behavioural capabilities. We follow an agent-based approach in the design of substructures to support the autonomy of partial brain structures. Agents are formulated to allow the emergence of a desired behaviour after a certain amount of interaction with the environment. An appropriate collaborative coevolutionary algorithm, able to emphasize both the speciality of brain areas and their cooperative performance, is employed to support design specification of agent structures. The effectiveness of the proposed approach is illustrated through the implementation of computational models for motor cortex and hippocampus, which are successfully tested on a simulated mobile robot.

Agent based models for wealth distribution with preference in interaction

NASA Astrophysics Data System (ADS)

Goswami, Sanchari; Sen, Parongama

2014-12-01

We propose a set of conservative models in which agents exchange wealth with a preference in the choice of interacting agents in different ways. The common feature in all the models is that the temporary values of financial status of agents is a deciding factor for interaction. Other factors which may play important role are past interactions and wealth possessed by individuals. Wealth distribution, network properties and activity are the main quantities which have been studied. Evidence of phase transitions and other interesting features are presented. The results show that certain observations of the real economic system can be reproduced by the models.

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

DOE PAGES

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

2015-10-30

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

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

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

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

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

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

PubMed

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.

Novel platinum compounds and nanoparticles as anticancer agents.

PubMed

Sarkar, Arindam

2018-01-01

Since the approval of cisplatin in 1979, platinum-based drugs have been regularly used in cancer chemotherapy as a first-line treatment or with the combination of other nonplatinum drugs. Subsequent approval of second- and third-generation drugs such as carboplatin and oxaliplatin respectively, has widened the therapeutic achievement of platinum compounds. There are few other platinum drugs approved recently and many other new drugs as well as the formulations of the old ones are going through clinical trials now. Considering the astonishing achievement of these drugs, analyses on the overall scenario of the patent applications on platinum compounds have become the priority to the scientific community. This review summarizes the published patent applications on the novel platinum anticancer compounds from 2012 to 2017 (August).

Agent-based model for rural-urban migration: A dynamic consideration

NASA Astrophysics Data System (ADS)

Cai, Ning; Ma, Hai-Ying; Khan, M. Junaid

2015-10-01

This paper develops a dynamic agent-based model for rural-urban migration, based on the previous relevant works. The model conforms to the typical dynamic linear multi-agent systems model concerned extensively in systems science, in which the communication network is formulated as a digraph. Simulations reveal that consensus of certain variable could be harmful to the overall stability and should be avoided.

Combinatorially-generated library of 6-fluoroquinolone analogs as potential novel antitubercular agents: a chemometric and molecular modeling assessment.

PubMed

Minovski, Nikola; Perdih, Andrej; Solmajer, Tom

2012-05-01

The virtual combinatorial chemistry approach as a methodology for generating chemical libraries of structurally-similar analogs in a virtual environment was employed for building a general mixed virtual combinatorial library with a total of 53.871 6-FQ structural analogs, introducing the real synthetic pathways of three well known 6-FQ inhibitors. The druggability properties of the generated combinatorial 6-FQs were assessed using an in-house developed drug-likeness filter integrating the Lipinski/Veber rule-sets. The compounds recognized as drug-like were used as an external set for prediction of the biological activity values using a neural-networks (NN) model based on an experimentally-determined set of active 6-FQs. Furthermore, a subset of compounds was extracted from the pool of drug-like 6-FQs, with predicted biological activity, and subsequently used in virtual screening (VS) campaign combining pharmacophore modeling and molecular docking studies. This complex scheme, a powerful combination of chemometric and molecular modeling approaches provided novel QSAR guidelines that could aid in the further lead development of 6-FQs agents.

Hybrid evolutionary computing model for mobile agents of wireless Internet multimedia

NASA Astrophysics Data System (ADS)

Hortos, William S.

2001-03-01

The ecosystem is used as an evolutionary paradigm of natural laws for the distributed information retrieval via mobile agents to allow the computational load to be added to server nodes of wireless networks, while reducing the traffic on communication links. Based on the Food Web model, a set of computational rules of natural balance form the outer stage to control the evolution of mobile agents providing multimedia services with a wireless Internet protocol WIP. The evolutionary model shows how mobile agents should behave with the WIP, in particular, how mobile agents can cooperate, compete and learn from each other, based on an underlying competition for radio network resources to establish the wireless connections to support the quality of service QoS of user requests. Mobile agents are also allowed to clone themselves, propagate and communicate with other agents. A two-layer model is proposed for agent evolution: the outer layer is based on the law of natural balancing, the inner layer is based on a discrete version of a Kohonen self-organizing feature map SOFM to distribute network resources to meet QoS requirements. The former is embedded in the higher OSI layers of the WIP, while the latter is used in the resource management procedures of Layer 2 and 3 of the protocol. Algorithms for the distributed computation of mobile agent evolutionary behavior are developed by adding a learning state to the agent evolution state diagram. When an agent is in an indeterminate state, it can communicate to other agents. Computing models can be replicated from other agents. Then the agents transitions to the mutating state to wait for a new information-retrieval goal. When a wireless terminal or station lacks a network resource, an agent in the suspending state can change its policy to submit to the environment before it transitions to the searching state. The agents learn the facts of agent state information entered into an external database. In the cloning process, two

Combined effect of zinc ions and cationic antibacterial agents on intraoral volatile sulphur compounds (VSC).

PubMed

Young, A; Jonski, G; Rölla, G

2003-08-01

Volatile sulphur compounds (VSC) are major components of oral malodour. As both zinc ions and cationic antibacterial agents inhibit the formation of oral VSC, this study aimed to determine whether these agents combined have synergistic anti-VSC actions. Baseline oral VSC measurements of mouth air from 10 volunteers following cysteine rinsing (6mM, pH 7.2) were obtained using gas chromatography (GC). Subjects rinsed for 1 min with 10ml of the test solutions, 0.3% zinc acetate (Zn), 0.025% chlorhexidine (CHX), 0.025% cetyl pyridinium (CPC), and the combinations Zn+CHX and Zn+CPC. Cysteine rinses were repeated at 1h, 2h and 3h and VSC measurements recorded. Three subjects rinsed with the Zn+CHX combination and fasted for 9h, undergoing cysteine rinses and VSC measurements at 3h intervals. 10 microl of the test solutions were also added to 1ml aliquots of human whole saliva (n=8). Following incubation at 37 degrees C for 24h VSC levels in the saliva headspace were measured by GC. Inhibition of VSC formation and the fractional inhibitory index indicating synergy were calculated. Zn+CHX mouthrinse had a synergistic anti-VSC effect, and was effective for at least 9h. Zn+CPC mouthrinse was less effective. Both combinations showed a synergistic inhibiting effect in-vitro. Synergy between Zn and the antibacterial agents confirms different mechanisms of operation.

APC10.1 cells as a model for assessing the efficacy of potential chemopreventive agents in the Apc(Min) mouse model in vivo.

PubMed

Sale, Stewart; Fong, Isabel L; de Giovanni, Carla; Landuzzi, Lorena; Brown, Karen; Steward, William P; Gescher, Andreas J

2009-11-01

Apc(Min) mice are widely used for mechanism and efficacy studies associated with the development of chemopreventive agents. APC10.1 cells have been derived from Apc(Min) mouse adenomas and retain the heterozygous Apc genotype. We tested the hypothesis that this cell type may provide an in vitro model to predict chemopreventive activity of agents in the Apc(Min) mouse in vivo. The growth inhibitory properties of 14 putative colorectal cancer chemopreventive agents, tricin, apigenin, 3',4',5',5,7-pentamethoxyflavone, resveratrol, curcumin, 3,4-methylenedioxy-3',4',5'-trimethoxychalcone (DMU135), 3,4,5,4'-tetramethoxystilbene (DMU212), celecoxib, aspirin, piroxicam, all-trans-retinoic acid, difluoromethylornithine (DFMO), quercetin and cyanidin-3-glucoside, were studied in this cell line, and the IC(50) values were calculated. The IC(50) values were plotted against previously published data of reduction of adenoma numbers caused by these agents in Apc(Min) mice. The correlation co-efficient was 0.678 (p<0.01), suggesting that there was a tentative correlation between the ability to inhibit the growth of APC10.1 cells and the ability to delay adenoma development in vivo. If this relationship is supported by using further agents, APC10.1 cells may serve in the future as an initial screen to prioritise compounds for assessing chemopreventive efficacy in Apc(Min) mice in vivo. Such a screen could reduce the number of animals required to find active agents, help reduce costs and increase throughput.

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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.

Multiscale agent-based cancer modeling.

PubMed

Zhang, Le; Wang, Zhihui; Sagotsky, Jonathan A; Deisboeck, Thomas S

2009-04-01

Agent-based modeling (ABM) is an in silico technique that is being used in a variety of research areas such as in social sciences, economics and increasingly in biomedicine as an interdisciplinary tool to study the dynamics of complex systems. Here, we describe its applicability to integrative tumor biology research by introducing a multi-scale tumor modeling platform that understands brain cancer as a complex dynamic biosystem. We summarize significant findings of this work, and discuss both challenges and future directions for ABM in the field of cancer research.

Chemometric modeling of 5-Phenylthiophenecarboxylic acid derivatives as anti-rheumatic agents.

PubMed

Adhikari, Nilanjan; Jana, Dhritiman; Halder, Amit K; Mondal, Chanchal; Maiti, Milan K; Jha, Tarun

2012-09-01

Arthritis involves joint inflammation, synovial proliferation and damage of cartilage. Interleukin-1 undergoes acute and chronic inflammatory mechanisms of arthritis. Non-steroidal anti-inflammatory drugs can produce symptomatic relief but cannot act through mechanisms of arthritis. Diseases modifying anti-rheumatoid drugs reduce the symptoms of arthritis like decrease in pain and disability score, reduction of swollen joints, articular index and serum concentration of acute phage proteins. Recently, some literature references are obtained on molecular modeling of antirheumatic agents. We have tried chemometric modeling through 2D-QSAR studies on a dataset of fifty-one compounds out of which forty-four 5-Phenylthiophenecarboxylic acid derivatives have IL-1 inhibitory activity and forty-six 5-Phenylthiophenecarboxylic acid derivatives have %AIA suppressive activity. The work was done to find out the structural requirements of these anti-rheumatic agents. 2D QSAR models were generated by 2D and 3D descriptors by using multiple linear regression and partial least square method where IL-1 antagonism was considered as the biological activity parameter. Statistically significant models were developed on the training set developed by k-means cluster analysis. Sterimol parameters, electronic interaction at atom number 9, 2D autocorrelation descriptors, information content descriptor, average connectivity index chi-3, radial distribution function, Balaban 3D index and 3D-MoRSE descriptors were found to play crucial roles to modulate IL-1 inhibitory activity. 2D autocorrelation descriptors like Broto-Moreau autocorrelation of topological structure-lag 3 weighted by atomic van der Waals volumes, Geary autocorrelation-lag 7 associated with weighted atomic Sanderson electronegativities and 3D-MoRSE descriptors like 3D-MoRSE-signal 22 related to atomic van der Waals volumes, 3D-MoRSE-signal 28 related to atomic van der Waals volumes and 3D-MoRSE-signal 9 which was unweighted

The Role of Compounds Derived from Natural Supplement as Anticancer Agents in Renal Cell Carcinoma: A Review.

PubMed

Haque, Inamul; Subramanian, Arvind; Huang, Chao H; Godwin, Andrew K; Van Veldhuizen, Peter J; Banerjee, Snigdha; Banerjee, Sushanta K

2017-12-31

Renal Cell Carcinoma (RCC) is the most prominent kidney cancer derived from renal tubules and accounts for roughly 85% of all malignant kidney cancer. Every year, over 60,000 new cases are registered, and about 14,000 people die from RCC. The incidence of this has been increasing significantly in the U.S. and other countries. An increased understanding of molecular biology and the genomics of RCC has uncovered several signaling pathways involved in the progression of this cancer. Significant advances in the treatment of RCC have been reported from agents approved by the Food and Drug Administration (FDA) that target these pathways. These agents have become drugs of choice because they demonstrate clinical benefit and increased survival in patients with metastatic disease. However, the patients eventually relapse and develop resistance to these drugs. To improve outcomes and seek approaches for producing long-term durable remission, the search for more effective therapies and preventative strategies are warranted. Treatment of RCC using natural products is one of these strategies to reduce the incidence. However, recent studies have focused on these chemoprevention agents as anti-cancer therapies given they can inhibit tumor cell grow and lack the severe side effects common to synthetic compounds. This review elaborates on the current understanding of natural products and their mechanisms of action as anti-cancer agents. The present review will provide information for possible use of these products alone or in combination with chemotherapy for the prevention and treatment of RCC.

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

PubMed

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.

Linking agent-based models and stochastic models of financial markets

PubMed Central

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

2012-01-01

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. PMID:22586086

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

PubMed

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.

Agent-based model to rural urban migration analysis

NASA Astrophysics Data System (ADS)

Silveira, Jaylson J.; Espíndola, Aquino L.; Penna, T. J. P.

2006-05-01

In this paper, we analyze the rural-urban migration phenomenon as it is usually observed in economies which are in the early stages of industrialization. The analysis is conducted by means of a statistical mechanics approach which builds a computational agent-based model. Agents are placed on a lattice and the connections among them are described via an Ising-like model. Simulations on this computational model show some emergent properties that are common in developing economies, such as a transitional dynamics characterized by continuous growth of urban population, followed by the equalization of expected wages between rural and urban sectors (Harris-Todaro equilibrium condition), urban concentration and increasing of per capita income.

X-ray attenuation coefficients of high-atomic-number, hexanuclear transition metal cluster compounds: a new paradigm for radiographic contrast agents.

PubMed

Mullan, B F; Madsen, M T; Messerle, L; Kolesnichenko, V; Kruger, J

2000-04-01

The purpose of this study was to examine the radiologic attenuation properties of the parent cluster compounds, particularly attenuation as a function of discrete photon energy, before investigating ligand substitutions, which are necessary to improve cluster biocompatibility and to impart desirable physicochemical properties. The linear attenuation coefficients for solutions of the cluster compounds Ta6Br14, K8Ta6O19, and (H3O)2W6Cl14 were determined at 60, 80, 103, 122, and 140 keV from gamma-ray transmission measurements with americium-241, xenon-133, gadolinium-153, cobalt-57, and technetium-99m radioactive sources. Transmission measurements were obtained for a fixed time interval that ensured a statistically accurate count distribution exceeding 20,000 counts through the sample for each trial. On a strictly mole per liter basis, a 0.075 mol/L aqueous solution of K8Ta6O19 showed 1.08 times the attenuation of 0.063 mol/L aqueous iohexol at 60 keV and 3.30 times the attenuation at 80 keV. Similarly, a 0.05 mol/L methanolic solution of (H3O)2W6Cl4 showed 0.96 times (96%) the attenuation of 0.063 mol/L aqueous iohexol at 60 keV but 3.09 times the attenuation of the iohexol solution at 80 keV. Attenuations of 0.063 mol/L aqueous iohexol and 0.0125 mol/L Ta6Br14 (ie, at approximately one-fifth the iohexol concentration) were comparable at greater than 60 keV. These results confirm the theoretic potential for use of early transition metal cluster compounds as radiographic contrast agents. At higher x-ray energies, cluster compounds demonstrate multiplied x-ray attenuation relative to iodinated contrast agents.

Kit for providing a technetium medical radioimaging agent

DOEpatents

Wildung, Raymond E.; Garland, Thomas R.; Li, Shu-Mei W.

2000-01-01

The present invention is directed toward a kit for microbial reduction of a technetium compound to form other compounds of value in medical imaging. The technetium compound is combined in a mixture with non-growing microbial cells which contain a technetium-reducing enzyme system, a stabilizing agent and an electron donor in a saline solution under anaerobic conditions. The mixture is substantially free of an inorganic technetium reducing agent and its reduction products. The resulting product is Tc of lower oxidation states, the form of which can be partially controlled by the stabilizing agent. It has been discovered that the microorganisms Shewanella alga, strain Bry and Shewanella putrifacians, strain CN-32 contain the necessary enzyme systems for technetium reduction and can form both mono nuclear and polynuclear reduced Tc species depending on the stabilizing agent.

Agent-Based Models in Empirical Social Research

ERIC Educational Resources Information Center

Bruch, Elizabeth; Atwell, Jon

2015-01-01

Agent-based modeling has become increasingly popular in recent years, but there is still no codified set of recommendations or practices for how to use these models within a program of empirical research. This article provides ideas and practical guidelines drawn from sociology, biology, computer science, epidemiology, and statistics. We first…

Identification of walking human model using agent-based modelling

NASA Astrophysics Data System (ADS)

Shahabpoor, Erfan; Pavic, Aleksandar; Racic, Vitomir

2018-03-01

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

Marine Natural Products as Prototype Agrochemical Agents

PubMed Central

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

2016-01-01

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

Hypercompetitive Environments: An Agent-based model approach

NASA Astrophysics Data System (ADS)

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.

Designing Multi-target Compound Libraries with Gaussian Process Models.

PubMed

Bieler, Michael; Reutlinger, Michael; Rodrigues, Tiago; Schneider, Petra; Kriegl, Jan M; Schneider, Gisbert

2016-05-01

We present the application of machine learning models to selecting G protein-coupled receptor (GPCR)-focused compound libraries. The library design process was realized by ant colony optimization. A proprietary Boehringer-Ingelheim reference set consisting of 3519 compounds tested in dose-response assays at 11 GPCR targets served as training data for machine learning and activity prediction. We compared the usability of the proprietary data with a public data set from ChEMBL. Gaussian process models were trained to prioritize compounds from a virtual combinatorial library. We obtained meaningful models for three of the targets (5-HT2c , MCH, A1), which were experimentally confirmed for 12 of 15 selected and synthesized or purchased compounds. Overall, the models trained on the public data predicted the observed assay results more accurately. The results of this study motivate the use of Gaussian process regression on public data for virtual screening and target-focused compound library design. © 2016 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA. This is an open access article under the terms of the Creative Commons Attribution Non-Commercial NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

THREE-DIMENSIONAL MODELING OF THE DYNAMICS OF THERAPEUTIC ULTRASOUND CONTRAST AGENTS

PubMed Central

Hsiao, Chao-Tsung; Lu, Xiaozhen; Chahine, Georges

2010-01-01

A 3-D thick-shell contrast agent dynamics model was developed by coupling a finite volume Navier-Stokes solver and a potential boundary element method flow solver to simulate the dynamics of thick-shelled contrast agents subjected to pressure waves. The 3-D model was validated using a spherical thick-shell model validated by experimental observations. We then used this model to study shell break-up during nonspherical deformations resulting from multiple contrast agent interaction or the presence of a nearby solid wall. Our simulations indicate that the thick viscous shell resists the contrast agent from forming a re-entrant jet, as normally observed for an air bubble oscillating near a solid wall. Instead, the shell thickness varies significantly from location to location during the dynamics, and this could lead to shell break-up caused by local shell thinning and stretching. PMID:20950929

Agent-based modeling: case study in cleavage furrow models

PubMed Central

Mogilner, Alex; Manhart, Angelika

2016-01-01

The number of studies in cell biology in which quantitative models accompany experiments has been growing steadily. Roughly, mathematical and computational techniques of these models can be classified as “differential equation based” (DE) or “agent based” (AB). Recently AB models have started to outnumber DE models, but understanding of AB philosophy and methodology is much less widespread than familiarity with DE techniques. Here we use the history of modeling a fundamental biological problem—positioning of the cleavage furrow in dividing cells—to explain how and why DE and AB models are used. We discuss differences, advantages, and shortcomings of these two approaches. PMID:27811328

Agent-based modelling in synthetic biology.

PubMed

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).

A Model of Human Teamwork for Agent-Assisted Search Operations

DTIC Science & Technology

2008-04-01

agent technology in providing effective team assistance , better understanding of robust human-agent teamwork is crucial. The goal of our research project...to various unexpected events. In order to fulfil the promise of agent technology in providing effective team assistance , better understanding of...distributed decision making. In Command and Control Research and Technology Symposium, 2004. A MODEL OF AGENT- ASSISTED SEARCH OPERATIONS 20 - 20 PUB REF NBR (e.g. RTO-MP-IST-999)

[Alkylating agents].

PubMed

Pourquier, Philippe

2011-11-01

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

A Generalized Quantum-Inspired Decision Making Model for Intelligent Agent

PubMed Central

Loo, Chu Kiong

2014-01-01

A novel decision making for intelligent agent using quantum-inspired approach is proposed. A formal, generalized solution to the problem is given. Mathematically, the proposed model is capable of modeling higher dimensional decision problems than previous researches. Four experiments are conducted, and both empirical experiments results and proposed model's experiment results are given for each experiment. Experiments showed that the results of proposed model agree with empirical results perfectly. The proposed model provides a new direction for researcher to resolve cognitive basis in designing intelligent agent. PMID:24778580

Agent-Based Modeling of Chronic Diseases: A Narrative Review and Future Research Directions.

PubMed

Li, Yan; Lawley, Mark A; Siscovick, David S; Zhang, Donglan; Pagán, José A

2016-05-26

The United States is experiencing an epidemic of chronic disease. As the US population ages, health care providers and policy makers urgently need decision models that provide systematic, credible prediction regarding the prevention and treatment of chronic diseases to improve population health management and medical decision-making. Agent-based modeling is a promising systems science approach that can model complex interactions and processes related to chronic health conditions, such as adaptive behaviors, feedback loops, and contextual effects. This article introduces agent-based modeling by providing a narrative review of agent-based models of chronic disease and identifying the characteristics of various chronic health conditions that must be taken into account to build effective clinical- and policy-relevant models. We also identify barriers to adopting agent-based models to study chronic diseases. Finally, we discuss future research directions of agent-based modeling applied to problems related to specific chronic health conditions.

[The vanadium compounds: chemistry, synthesis, insulinomimetic properties].

PubMed

Fedorova, E V; Buriakina, A V; Vorob'eva, N M; Baranova, N I

2014-01-01

The review considers the biological role of vanadium, its participation in various processes in humans and other mammals, and the anti-diabetic effect of its compounds. Vanadium salts have persistent hypoglycemic and antihyperlipidemic effects and reduce the probability of secondary complications in animals with experimental diabetes. The review contains a detailed description of all major synthesized vanadium complexes having antidiabetic activity. Currently, vanadium complexes with organic ligands are more effective and safer than the inorganic salts. Despite the proven efficacy of these compounds as the anti-diabetic agents in animal models, only one organic complex of vanadium is currently under the second phase of clinical trials. All of the considered data suggest that vanadium compound are a new promising class of drugs in modern pharmacotherapy of diabetes.

Calibrating emergent phenomena in stock markets with agent based models

PubMed Central

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

Calibrating emergent phenomena in stock markets with agent based models.

PubMed

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.

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

NASA Technical Reports Server (NTRS)

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.

4-haloethenylphenyl tropane:serotonin transporter imaging agents

DOEpatents

Goodman, Mark M.; Martarello, Laurent

2005-01-18

A series of compounds in the 4-fluoroalkyl-3-halophenyl nortropanes and 4-haloethenylphenyl tropane families are described as diagnostic and therapeutic agents for diseases associated with serotonin transporter dysfunction. These compounds bind to serotonin transporter protein with high affinity and selectivity. The invention provides methods of synthesis which incorporate radioisotopic halogens at a last step which permit high radiochemical yield and maximum usable product life. The radiolabeled compounds of the invention are useful as imaging agents for visualizing the location and density of serotonin transporter by PET and SPECT imaging.

A Distributed Platform for Global-Scale Agent-Based Models of Disease Transmission

PubMed Central

Parker, Jon; Epstein, Joshua M.

2013-01-01

The Global-Scale Agent Model (GSAM) is presented. The GSAM is a high-performance distributed platform for agent-based epidemic modeling capable of simulating a disease outbreak in a population of several billion agents. It is unprecedented in its scale, its speed, and its use of Java. Solutions to multiple challenges inherent in distributing massive agent-based models are presented. Communication, synchronization, and memory usage are among the topics covered in detail. The memory usage discussion is Java specific. However, the communication and synchronization discussions apply broadly. We provide benchmarks illustrating the GSAM’s speed and scalability. PMID:24465120

Improving Agent Based Models and Validation through Data Fusion.

PubMed

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

2011-01-01

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

Agent-based modelling of consumer energy choices

NASA Astrophysics Data System (ADS)

Rai, Varun; Henry, Adam Douglas

2016-06-01

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

Agent-Based Modeling of Chronic Diseases: A Narrative Review and Future Research Directions

PubMed Central

Lawley, Mark A.; Siscovick, David S.; Zhang, Donglan; Pagán, José A.

2016-01-01

The United States is experiencing an epidemic of chronic disease. As the US population ages, health care providers and policy makers urgently need decision models that provide systematic, credible prediction regarding the prevention and treatment of chronic diseases to improve population health management and medical decision-making. Agent-based modeling is a promising systems science approach that can model complex interactions and processes related to chronic health conditions, such as adaptive behaviors, feedback loops, and contextual effects. This article introduces agent-based modeling by providing a narrative review of agent-based models of chronic disease and identifying the characteristics of various chronic health conditions that must be taken into account to build effective clinical- and policy-relevant models. We also identify barriers to adopting agent-based models to study chronic diseases. Finally, we discuss future research directions of agent-based modeling applied to problems related to specific chronic health conditions. PMID:27236380

Model Checking the Remote Agent Planner

NASA Technical Reports Server (NTRS)

Khatib, Lina; Muscettola, Nicola; Havelund, Klaus; Norvig, Peter (Technical Monitor)

2001-01-01

This work tackles the problem of using Model Checking for the purpose of verifying the HSTS (Scheduling Testbed System) planning system. HSTS is the planner and scheduler of the remote agent autonomous control system deployed in Deep Space One (DS1). Model Checking allows for the verification of domain models as well as planning entries. We have chosen the real-time model checker UPPAAL for this work. We start by motivating our work in the introduction. Then we give a brief description of HSTS and UPPAAL. After that, we give a sketch for the mapping of HSTS models into UPPAAL and we present samples of plan model properties one may want to verify.

Novel Quorum-Quenching Agents Promote Methicillin-Resistant Staphylococcus aureus (MRSA) Wound Healing and Sensitize MRSA to β-Lactam Antibiotics

PubMed Central

Kuo, David; Yu, Guanping; Hoch, Wyatt; Gabay, Dean; Long, Lisa; Ghannoum, Mahmoud; Nagy, Nancy; Harding, Clifford V.; Viswanathan, Rajesh

2014-01-01

The dwindling repertoire of antibiotics to treat methicillin-resistant Staphylococcus aureus (MRSA) calls for novel treatment options. Quorum-quenching agents offer an alternative or an adjuvant to antibiotic therapy. Three biaryl hydroxyketone compounds discovered previously (F1, F12, and F19; G. Yu, D. Kuo, M. Shoham, and R. Viswanathan, ACS Comb Sci 16:85–91, 2014) were tested for efficacy in MRSA-infected animal models. Topical therapy of compounds F1 and F12 in a MRSA murine wound infection model promotes wound healing compared to the untreated control. Compounds F1, F12, and F19 afford significant survival benefits in a MRSA insect larva model. Combination therapy of these quorum-quenching agents with cephalothin or nafcillin, antibiotics to which MRSA is resistant in monotherapy, revealed additional survival benefits. The quorum-quenching agents sensitize MRSA to the antibiotic by a synergistic mode of action that also is observed in vitro. An adjuvant of 1 μg/ml F1, F12, or F19 reduces the MIC of nafcillin and cephalothin about 50-fold to values comparable to those for vancomycin, the antibiotic often prescribed for MRSA infections. These findings suggest that it is possible to resurrect obsolete antibiotic therapies in combination with these novel quorum-quenching agents. PMID:25534736

Construction of a microscopic agent-based model for firms' dynamics

NASA Astrophysics Data System (ADS)

Iyetomi, Hiroshi; Aoyama, Hideaki; Fujiwara, Yoshi; Ikeda, Yuichi; Kaizoji, Taisei; Soma, Wataru

2005-07-01

A workable microscopic model for firms' dynamics has been constructed. The model consists of firm agents and a bank agent dynamics of which are described by balance sheets. The size distribution of firms and the temporal evolution of the bank show critical dependence on whether or not firms use perfect information on their financial conditions to draw up next production plans.

Modeling Compound Flood Hazards in Coastal Embayments

NASA Astrophysics Data System (ADS)

Moftakhari, H.; Schubert, J. E.; AghaKouchak, A.; Luke, A.; Matthew, R.; Sanders, B. F.

2017-12-01

Coastal cities around the world are built on lowland topography adjacent to coastal embayments and river estuaries, where multiple factors threaten increasing flood hazards (e.g. sea level rise and river flooding). Quantitative risk assessment is required for administration of flood insurance programs and the design of cost-effective flood risk reduction measures. This demands a characterization of extreme water levels such as 100 and 500 year return period events. Furthermore, hydrodynamic flood models are routinely used to characterize localized flood level intensities (i.e., local depth and velocity) based on boundary forcing sampled from extreme value distributions. For example, extreme flood discharges in the U.S. are estimated from measured flood peaks using the Log-Pearson Type III distribution. However, configuring hydrodynamic models for coastal embayments is challenging because of compound extreme flood events: events caused by a combination of extreme sea levels, extreme river discharges, and possibly other factors such as extreme waves and precipitation causing pluvial flooding in urban developments. Here, we present an approach for flood risk assessment that coordinates multivariate extreme analysis with hydrodynamic modeling of coastal embayments. First, we evaluate the significance of correlation structure between terrestrial freshwater inflow and oceanic variables; second, this correlation structure is described using copula functions in unit joint probability domain; and third, we choose a series of compound design scenarios for hydrodynamic modeling based on their occurrence likelihood. The design scenarios include the most likely compound event (with the highest joint probability density), preferred marginal scenario and reproduced time series of ensembles based on Monte Carlo sampling of bivariate hazard domain. The comparison between resulting extreme water dynamics under the compound hazard scenarios explained above provides an insight to the

An Agent Based Collaborative Simplification of 3D Mesh Model

NASA Astrophysics Data System (ADS)

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.

A Novel Machine Learning Classifier Based on a Qualia Modeling Agent (QMA)

DTIC Science & Technology

Information Theory (IIT) of Consciousness , which proposes that the fundamental structural elements of consciousness are qualia. By modeling the...This research develops a computational agent, which overcomes this problem. The Qualia Modeling Agent (QMA) is modeled after two cognitive theories

Wild Roman chamomile extracts and phenolic compounds: enzymatic assays and molecular modelling studies with VEGFR-2 tyrosine kinase.

PubMed

Guimarães, Rafaela; Calhelha, Ricardo C; Froufe, Hugo J C; Abreu, Rui M V; Carvalho, Ana Maria; Queiroz, Maria João R P; Ferreira, Isabel C F R

2016-01-01

Angiogenesis is a process by which new blood vessels are formed from the pre-existing vasculature, and it is a key process that leads to tumour development. Some studies have recognized phenolic compounds as chemopreventive agents; flavonoids, in particular, seem to suppress the growth of tumor cells modifying the cell cycle. Herein, the antiangiogenic activity of Roman chamomile (Chamaemelum nobile L.) extracts (methanolic extract and infusion) and the main phenolic compounds present (apigenin, apigenin-7-O-glucoside, caffeic acid, chlorogenic acid, luteolin, and luteolin-7-O-glucoside) was evaluated through enzymatic assays using the tyrosine kinase intracellular domain of the Vascular Endothelium Growth Factor Receptor-2 (VEGFR-2), which is a transmembrane receptor expressed fundamentally in endothelial cells involved in angiogenesis, and molecular modelling studies. The methanolic extract showed a lower IC50 value (concentration that provided 50% of VEGFR-2 inhibition) than the infusion, 269 and 301 μg mL(-1), respectively. Regarding phenolic compounds, luteolin and apigenin showed the highest capacity to inhibit the phosphorylation of VEGFR-2, leading us to believe that these compounds are involved in the activity revealed by the methanolic extract.

Validating agent oriented methodology (AOM) for netlogo modelling and simulation

NASA Astrophysics Data System (ADS)

WaiShiang, Cheah; Nissom, Shane; YeeWai, Sim; Sharbini, Hamizan

2017-10-01

AOM (Agent Oriented Modeling) is a comprehensive and unified agent methodology for agent oriented software development. AOM methodology was proposed to aid developers with the introduction of technique, terminology, notation and guideline during agent systems development. Although AOM methodology is claimed to be capable of developing a complex real world system, its potential is yet to be realized and recognized by the mainstream software community and the adoption of AOM is still at its infancy. Among the reason is that there are not much case studies or success story of AOM. This paper presents two case studies on the adoption of AOM for individual based modelling and simulation. It demonstrate how the AOM is useful for epidemiology study and ecological study. Hence, it further validate the AOM in a qualitative manner.

The Role of Compounds Derived from Natural Supplement as Anticancer Agents in Renal Cell Carcinoma: A Review

PubMed Central

Haque, Inamul; Subramanian, Arvind; Huang, Chao H.; Godwin, Andrew K.; Van Veldhuizen, Peter J.; Banerjee, Snigdha; Banerjee, Sushanta K.

2017-01-01

Renal Cell Carcinoma (RCC) is the most prominent kidney cancer derived from renal tubules and accounts for roughly 85% of all malignant kidney cancer. Every year, over 60,000 new cases are registered, and about 14,000 people die from RCC. The incidence of this has been increasing significantly in the U.S. and other countries. An increased understanding of molecular biology and the genomics of RCC has uncovered several signaling pathways involved in the progression of this cancer. Significant advances in the treatment of RCC have been reported from agents approved by the Food and Drug Administration (FDA) that target these pathways. These agents have become drugs of choice because they demonstrate clinical benefit and increased survival in patients with metastatic disease. However, the patients eventually relapse and develop resistance to these drugs. To improve outcomes and seek approaches for producing long-term durable remission, the search for more effective therapies and preventative strategies are warranted. Treatment of RCC using natural products is one of these strategies to reduce the incidence. However, recent studies have focused on these chemoprevention agents as anti-cancer therapies given they can inhibit tumor cell grow and lack the severe side effects common to synthetic compounds. This review elaborates on the current understanding of natural products and their mechanisms of action as anti-cancer agents. The present review will provide information for possible use of these products alone or in combination with chemotherapy for the prevention and treatment of RCC. PMID:29301217

An in vitro model that can distinguish between effects on angiogenesis and on established vasculature: actions of TNP-470, marimastat and the tubulin-binding agent Ang-510.

PubMed

van Wijngaarden, Jens; Snoeks, Thomas J A; van Beek, Ermond; Bloys, Henny; Kaijzel, Eric L; van Hinsbergh, Victor W M; Löwik, Clemens W G M

2010-01-08

In anti-cancer therapy, current investigations explore the possibility of two different strategies to target tumor vasculature; one aims at interfering with angiogenesis, the process involving the outgrowth of new blood vessels from pre-existing vessels, while the other directs at affecting the already established tumor vasculature. However, the majority of in vitro model systems currently available examine the process of angiogenesis, while the current focus in anti-vascular therapies moves towards exploring the benefit of targeting established vasculature as well. This urges the need for in vitro systems that are able to differentiate between the effects of compounds on angiogenesis as well as on established vasculature. To achieve this, we developed an in vitro model in which effects of compounds on different vascular targets can be studied specifically. Using this model, we examined the actions of the fumagillin derivate TNP-470, the MMP-inhibitor marimastat and the recently developed tubulin-binding agent Ang-510. We show that TNP-470 and marimastat solely inhibited angiogenesis, whereas Ang-510 potently inhibited angiogenesis and caused massive disruption of newly established vasculature. We show that the use of this in vitro model allows for specific and efficient screening of the effects of compounds on different vascular targets, which may facilitate the identification of agents with potential clinical benefit. The indicated differences in the mode of action between marimastat, TNP-470 and Ang-510 to target vasculature are illustrative for this approach. Copyright 2009 Elsevier Inc. All rights reserved.

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

PubMed

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

2018-03-20

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

Modeling intelligent agent beliefs in a card game scenario

NASA Astrophysics Data System (ADS)

Gołuński, Marcel; Tomanek, Roman; WÄ siewicz, Piotr

In this paper we explore the problem of intelligent agent beliefs. We model agent beliefs using multimodal logics of belief, KD45(m) system implemented as a directed graph depicting Kripke semantics, precisely. We present a card game engine application which allows multiple agents to connect to a given game session and play the card game. As an example simplified version of popular Saboteur card game is used. Implementation was done in Java language using following libraries and applications: Apache Mina, LWJGL.

Design, synthesis and evaluation of 4-dimethylamine flavonoid derivatives as potential multifunctional anti-Alzheimer agents.

PubMed

Luo, Wen; Wang, Ting; Hong, Chen; Yang, Ya-Chen; Chen, Ying; Cen, Juan; Xie, Song-Qiang; Wang, Chao-Jie

2016-10-21

A new series of 4-dimethylamine flavonoid derivatives were designed and synthesized as potential multifunctional anti-Alzheimer agents. The inhibition of cholinesterase activity, self-induced β-amyloid (Aβ) aggregation, and antioxidant activity by these derivatives was investigated. Most of the compounds exhibited potent acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) inhibitory activity. A Lineweaver-Burk plot and molecular modeling study showed that these compounds targeted both the catalytic active site (CAS) and peripheral anionic site (PAS) of AChE. The derivatives showed potent self-induced Aβ aggregation inhibition and peroxyl radical absorbance activity. Moreover, compound 6d significantly protected PC12 neurons against H2O2-induced cell death at low concentrations. Thus, these compounds could become multifunctional agents for further development for the treatment of AD. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Statistical molecular design of balanced compound libraries for QSAR modeling.

PubMed

Linusson, A; Elofsson, M; Andersson, I E; Dahlgren, M K

2010-01-01

A fundamental step in preclinical drug development is the computation of quantitative structure-activity relationship (QSAR) models, i.e. models that link chemical features of compounds with activities towards a target macromolecule associated with the initiation or progression of a disease. QSAR models are computed by combining information on the physicochemical and structural features of a library of congeneric compounds, typically assembled from two or more building blocks, and biological data from one or more in vitro assays. Since the models provide information on features affecting the compounds' biological activity they can be used as guides for further optimization. However, in order for a QSAR model to be relevant to the targeted disease, and drug development in general, the compound library used must contain molecules with balanced variation of the features spanning the chemical space believed to be important for interaction with the biological target. In addition, the assays used must be robust and deliver high quality data that are directly related to the function of the biological target and the associated disease state. In this review, we discuss and exemplify the concept of statistical molecular design (SMD) in the selection of building blocks and final synthetic targets (i.e. compounds to synthesize) to generate information-rich, balanced libraries for biological testing and computation of QSAR models.

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

PubMed

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

2016-12-08

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

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

PubMed Central

2016-01-01

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

A framework for the use of agent based modeling to simulate ...

EPA Pesticide Factsheets

Simulation of human behavior in exposure modeling is a complex task. Traditionally, inter-individual variation in human activity has been modeled by drawing from a pool of single day time-activity diaries such as the US EPA Consolidated Human Activity Database (CHAD). Here, an agent-based model (ABM) is used to simulate population distributions of longitudinal patterns of four macro activities (sleeping, eating, working, and commuting) in populations of adults over a period of one year. In this ABM, an individual is modeled as an agent whose movement through time and space is determined by a set of decision rules. The rules are based on the agent having time-varying “needs” that are satisfied by performing actions. Needs are modeled as increasing over time, and taking an action reduces the need. Need-satisfying actions include sleeping (meeting the need for rest), eating (meeting the need for food), and commuting/working (meeting the need for income). Every time an action is completed, the model determines the next action the agent will take based on the magnitude of each of the agent’s needs at that point in time. Different activities advertise their ability to satisfy various needs of the agent (such as food to eat or sleeping in a bed or on a couch). The model then chooses the activity that satisfies the greatest of the agent’s needs. When multiple actions could address a need, the model will choose the most effective of the actions (bed over the couc

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

PubMed

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.

Improving Agent Based Models and Validation through Data Fusion

PubMed Central

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

2011-01-01

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

Boron compounds as anion binding agents for nonaqueous battery electrolytes

DOEpatents

Lee, Hung Sui; Yang, Xia-Oing; McBreen, James; Xiang, Caili

2000-02-08

Novel fluorinated boron-based compounds which act as anion receptors in non-aqueous battery electrolytes are provided. When added to non-aqueous battery electrolytes, the fluorinated boron-based compounds of the invention enhance ionic conductivity and cation transference number of non-aqueous electrolytes. The fluorinated boron-based anion receptors include borane and borate compounds bearing different fluorinated alkyl and aryl groups.

Modelling of Robotized Manufacturing Systems Using MultiAgent Formalism

NASA Astrophysics Data System (ADS)

Foit, K.; Gwiazda, A.; Banaś, W.

2016-08-01

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

Pyrolysis reaction networks for lignin model compounds: unraveling thermal deconstruction of β-O-4 and α-O-4 compounds

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

Choi, Yong S.; Singh, Rahul; Zhang, Jing

2016-01-01

Although lignin is one of the main components of biomass, its pyrolysis chemistry is not well understood due to complex heterogeneity. To gain insights into this chemistry, the pyrolysis of seven lignin model compounds (five ..beta..-O-4 and two ..alpha..-O-4 linked molecules) was investigated in a micropyrolyzer connected to GC-MS/FID. According to quantitative product mole balance for the reaction networks, concerted retro-ene fragmentation and homolytic dissociation were strongly suggested as the initial reaction step for ..beta..-O-4 compounds and ..alpha..-O-4 compounds, respectively. The difference in reaction pathway between compounds with different linkages was believed to result from thermodynamics of the radical initiation.more » The rate constants for the different reaction pathways were predicted from ab initio density functional theory calculations and pre-exponential literature values. The computational findings were consistent with the experiment results, further supporting the different pyrolysis mechanisms for the ..beta..-ether linked and ..alpha..-ether linked compounds. A combination of the two pathways from the dimeric model compounds was able to describe qualitatively the pyrolysis of a trimeric lignin model compound containing both ..beta..-O-4 and ..alpha..-O-4 linkages.« less

Heart testing compound

DOEpatents

Knapp, Jr., Furn F.; Goodman, Mark M.

1985-01-01

The compound 15-(p-[.sup.125 I]-iodophenyl)-6-tellurapentadecanoic acid is disclosed as a myocardial imaging agent having rapid and pronounced uptake, prolonged myocardial retention, and low in vivo deiodination.

Heart testing compound

DOEpatents

Knapp, F.F. Jr.; Goodman, M.M.

1983-06-29

The compound 15-(p-(/sup 125/I)-iodophenyl)-6-tellurapentadecanoic acid is disclosed as a myocardial imaging agent having rapid and pronounced uptake, prolonged myocardial retention, and low in vivo deiodination.

Can agent based models effectively reduce fisheries management implementation uncertainty?

NASA Astrophysics Data System (ADS)

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.

Diversity and Community: The Role of Agent-Based Modeling.

PubMed

Stivala, Alex

2017-06-01

Community psychology involves several dialectics between potentially opposing ideals, such as theory and practice, rights and needs, and respect for human diversity and sense of community. Some recent papers in the American Journal of Community Psychology have examined the diversity-community dialectic, some with the aid of agent-based modeling and concepts from network science. This paper further elucidates these concepts and suggests that research in community psychology can benefit from a useful dialectic between agent-based modeling and the real-world concerns of community psychology. © Society for Community Research and Action 2017.

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

NASA Astrophysics Data System (ADS)

Gouvea, Julia; Passmore, Cynthia

2017-03-01

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

The Agent-based Approach: A New Direction for Computational Models of Development.

ERIC Educational Resources Information Center

Schlesinger, Matthew; Parisi, Domenico

2001-01-01

Introduces the concepts of online and offline sampling and highlights the role of online sampling in agent-based models of learning and development. Compares the strengths of each approach for modeling particular developmental phenomena and research questions. Describes a recent agent-based model of infant causal perception. Discusses limitations…

Implementation of Multi-Agent Object Attention System Based on Biologically Inspired Attractor Selection

NASA Astrophysics Data System (ADS)

Hashimoto, Ryoji; Matsumura, Tomoya; Nozato, Yoshihiro; Watanabe, Kenji; Onoye, Takao

A multi-agent object attention system is proposed, which is based on biologically inspired attractor selection model. Object attention is facilitated by using a video sequence and a depth map obtained through a compound-eye image sensor TOMBO. Robustness of the multi-agent system over environmental changes is enhanced by utilizing the biological model of adaptive response by attractor selection. To implement the proposed system, an efficient VLSI architecture is employed with reducing enormous computational costs and memory accesses required for depth map processing and multi-agent attractor selection process. According to the FPGA implementation result of the proposed object attention system, which is accomplished by using 7,063 slices, 640×512 pixel input images can be processed in real-time with three agents at a rate of 9fps in 48MHz operation.

Screening and identification of novel compounds with potential anti-proliferative effects on gallium-resistant lung cancer through an AXL kinase pathway.

PubMed

Oyewumi, Moses O; Alazizi, Adnan; Liva, Sophia; Lin, Li; Geldenhuys, Werner J

2014-09-15

The clinical application of gallium compounds as anticancer agents is hampered by development of resistance. As a potential strategy to overcome the limitation, eight series of compounds were identified through virtual screening of AXL kinase homology model. Anti-proliferative studies were carried using gallium-sensitive (S) and gallium-resistant (R) human lung adenocarcinoma (A549) cells. Compounds 5476423 and 7919469 were identified as leads. The IC50 values from treating R-cells showed compounds 5476423 and 7919469 had 80 fold and 13 fold increased potency, respectively, compared to gallium acetylacetonate (GaAcAc). The efficacy of GaAcAc against R-cells was increased 2 fold and 1.2 fold when combined with compounds 5476423 and 7919469, respectively. Compared with S-cells, R-cells showed elevated expression of AXL protein, which was significantly suppressed through treatments with the lead compounds. It is anticipated that the lead compounds could be applied in virtual screening programs to identify novel scaffolds for new therapeutic agents as well as combinatorial therapy agents in gallium resistant lung cancer. Copyright © 2014 Elsevier Ltd. All rights reserved.

Method for halogenating or radiohalogenating a chemical compound

DOEpatents

Kabalka, George W.

2006-05-09

A method for obtaining a halogenated organic compound, whereby an organotrifluoroborate compound is reacted with a halide ion in the presence of an oxidizing agent to produce the corresponding halogenated organic compound. The method may be used for producing radiohalogenated organic compounds.

Study of Synthesis of N-Nitroborazine Compounds. I. Nitryl Chloride as Nitrating Agent.

DTIC Science & Technology

dinitrogen tetroxide (N2O4) as the solid complexes of boron trifluoride (BF3). Nearly water-white nitryl chloride was obtained in this manner. A tinge of...yellow was attributed to the presence of chlorine . The reaction of nitryl chloride with a model compound, lithium dimethylamide, was found to yield

Calibrating Building Energy Models Using Supercomputer Trained Machine Learning Agents

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

Sanyal, Jibonananda; New, Joshua Ryan; Edwards, Richard

2014-01-01

Building Energy Modeling (BEM) is an approach to model the energy usage in buildings for design and retrofit purposes. EnergyPlus is the flagship Department of Energy software that performs BEM for different types of buildings. The input to EnergyPlus can often extend in the order of a few thousand parameters which have to be calibrated manually by an expert for realistic energy modeling. This makes it challenging and expensive thereby making building energy modeling unfeasible for smaller projects. In this paper, we describe the Autotune research which employs machine learning algorithms to generate agents for the different kinds of standardmore » reference buildings in the U.S. building stock. The parametric space and the variety of building locations and types make this a challenging computational problem necessitating the use of supercomputers. Millions of EnergyPlus simulations are run on supercomputers which are subsequently used to train machine learning algorithms to generate agents. These agents, once created, can then run in a fraction of the time thereby allowing cost-effective calibration of building models.« less

Agent-based modeling: Methods and techniques for simulating human systems

PubMed Central

Bonabeau, Eric

2002-01-01

Agent-based modeling is a powerful simulation modeling technique that has seen a number of applications in the last few years, including applications to real-world business problems. After the basic principles of agent-based simulation are briefly introduced, its four areas of application are discussed by using real-world applications: flow simulation, organizational simulation, market simulation, and diffusion simulation. For each category, one or several business applications are described and analyzed. PMID:12011407

Fate of chemical warfare agents and toxic industrial chemicals in landfills.

PubMed

Bartelt-Hunt, Shannon L; Barlaz, Morton A; Knappe, Detlef R U; Kjeldsen, Peter

2006-07-01

One component of preparedness for a chemical attack is planning for the disposal of contaminated debris. To assess the feasibility of contaminated debris disposal in municipal solid waste (MSW) landfills, the fate of selected chemical warfare agents (CWAs) and toxic industrial chemicals (TICs) in MSW landfills was predicted with a mathematical model. Five blister agents [sulfur mustard (HD), nitrogen mustard (HN-2), lewisite (L), ethyldichloroarsine (ED), and phosgene oxime (CX)], eight nerve agents [tabun (GA), sarin (GB), soman (GD), GE, GF, VX, VG, and VM], one riot-control agent [CS], and two TICs [furan and carbon disulfide] were studied. The effects of both infiltration (climate) and contaminant biodegradability on fate predictions were assessed. Model results showed that hydrolysis and gas-phase advection were the principal fate pathways for CWAs and TICs, respectively. Apart from CX and the TICs, none of the investigated compounds was predicted to persist in a landfill for more than 5 years. Climate had little impact on CWA/TIC fate, and biodegradability was only important for compounds with long hydrolysis half-lives. Monte Carlo simulations were performed to assess the influence of uncertainty in model input parameters on CWA/TIC fate predictions. Correlation analyses showed that uncertainty in hydrolysis rate constants was the primary contributor to variance of CWA fate predictions, while uncertainty in the Henry's Law constant and landfill gas-production rate accounted for most of the variance of TIC fate predictions. CWA hydrolysates were more persistent than the parent CWAs, but limited information is available on abiotic or biotic transformation rates for these chemicals.

QSAR Classification Model for Antibacterial Compounds and Its Use in Virtual Screening

DTIC Science & Technology

2012-09-26

test set molecules that were not used to train the models . This allowed us to more accurately estimate the prediction power of the models . As...pathogens and deposited in PubChem Bioassays. Ultimately, the main purpose of this model is to make predictions , based on known antibacterial and non...the model built form the remaining compounds is used to predict the left out compound. Once all the compounds pass through this cycle of prediction , a

Multi-agent electricity market modeling with EMCAS.

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

North, M.; Macal, C.; Conzelmann, G.

2002-09-05

Electricity systems are a central component of modern economies. Many electricity markets are transitioning from centrally regulated systems to decentralized markets. Furthermore, several electricity markets that have recently undergone this transition have exhibited extremely unsatisfactory results, most notably in California. These high stakes transformations require the introduction of largely untested regulatory structures. Suitable tools that can be used to test these regulatory structures before they are applied to real systems are required. Multi-agent models can provide such tools. To better understand the requirements such as tool, a live electricity market simulation was created. This experience helped to shape the developmentmore » of the multi-agent Electricity Market Complex Adaptive Systems (EMCAS) model. To explore EMCAS' potential, several variations of the live simulation were created. These variations probed the possible effects of changing power plant outages and price setting rules on electricity market prices.« less

Investigational Antimicrobial Agents of 2013

PubMed Central

Pucci, Michael J.

2013-01-01

SUMMARY New antimicrobial agents are always needed to counteract the resistant pathogens that continue to be selected by current therapeutic regimens. This review provides a survey of known antimicrobial agents that were currently in clinical development in the fall of 2012 and spring of 2013. Data were collected from published literature primarily from 2010 to 2012, meeting abstracts (2011 to 2012), government websites, and company websites when appropriate. Compared to what was reported in previous surveys, a surprising number of new agents are currently in company pipelines, particularly in phase 3 clinical development. Familiar antibacterial classes of the quinolones, tetracyclines, oxazolidinones, glycopeptides, and cephalosporins are represented by entities with enhanced antimicrobial or pharmacological properties. More importantly, compounds of novel chemical structures targeting bacterial pathways not previously exploited are under development. Some of the most promising compounds include novel β-lactamase inhibitor combinations that target many multidrug-resistant Gram-negative bacteria, a critical medical need. Although new antimicrobial agents will continue to be needed to address increasing antibiotic resistance, there are novel agents in development to tackle at least some of the more worrisome pathogens in the current nosocomial setting. PMID:24092856

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

PubMed

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

2011-11-01

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

A generic biokinetic model for carbon-14 labelled compounds

NASA Astrophysics Data System (ADS)

Manger, Ryan Paul

Carbon-14, a radioactive nuclide, is used in many industrial applications. Due to its wide range of uses in industry, many workers are at risk of accidental internal exposure to 14C. Being a low energy beta emitter, 14C is not a significant external radiation hazard, but the internal consequences posed by 14C are important, especially because of its long half life of 5730 years [46]. The current biokinetic model recommended by the International Commission on Radiological Protection (ICRP) is a conservative estimate of how radiocarbon is treated by the human body. The ICRP generic radiocarbon model consists of a single compartment representing the entire human body. This compartment has a biological half life of 40 days yielding an effective dose coefficient of 5.8x10-10 Sv B q-1 [44, 45, 49, 53, 54]. This overestimates the dose of all radiocarbon compounds that have been studied [96]. An improved model has been developed that includes and alimentary tract, a urinary bladder, CO2 model, and an "Other" compartment used to model systemic tissues. The model can be adapted to replicate any excretion curve and excretion pattern. In addition, the effective dose coefficient produced by the updated model is near the mean effective dose coefficient of carbon compounds that have been considered in this research. The major areas of improvement are: more anatomically significant, a less conservative dose coefficient, and the ability to manipulate the model for known excretion data. Due to the wide variety of carbon compounds, it is suggested that specific biokinetic models be implemented for known radiocarbon substances. If the source of radiocarbon is dietary, then the physiologically based model proposed by Whillans [102] that splits all ingested radiocarbon compounds into carbohydrates, fats, and proteins should be used.

Novel quorum-quenching agents promote methicillin-resistant Staphylococcus aureus (MRSA) wound healing and sensitize MRSA to β-lactam antibiotics.

PubMed

Kuo, David; Yu, Guanping; Hoch, Wyatt; Gabay, Dean; Long, Lisa; Ghannoum, Mahmoud; Nagy, Nancy; Harding, Clifford V; Viswanathan, Rajesh; Shoham, Menachem

2015-03-01

The dwindling repertoire of antibiotics to treat methicillin-resistant Staphylococcus aureus (MRSA) calls for novel treatment options. Quorum-quenching agents offer an alternative or an adjuvant to antibiotic therapy. Three biaryl hydroxyketone compounds discovered previously (F1, F12, and F19; G. Yu, D. Kuo, M. Shoham, and R. Viswanathan, ACS Comb Sci 16:85-91, 2014) were tested for efficacy in MRSA-infected animal models. Topical therapy of compounds F1 and F12 in a MRSA murine wound infection model promotes wound healing compared to the untreated control. Compounds F1, F12, and F19 afford significant survival benefits in a MRSA insect larva model. Combination therapy of these quorum-quenching agents with cephalothin or nafcillin, antibiotics to which MRSA is resistant in monotherapy, revealed additional survival benefits. The quorum-quenching agents sensitize MRSA to the antibiotic by a synergistic mode of action that also is observed in vitro. An adjuvant of 1 μg/ml F1, F12, or F19 reduces the MIC of nafcillin and cephalothin about 50-fold to values comparable to those for vancomycin, the antibiotic often prescribed for MRSA infections. These findings suggest that it is possible to resurrect obsolete antibiotic therapies in combination with these novel quorum-quenching agents. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Protein targets for anticancer gold compounds: mechanistic inferences.

PubMed

Gabbiani, Chiara; Messori, Luigi

2011-12-01

Gold compounds form an interesting class of antiproliferative agents of potential pharmacological use in cancer treatment. Indeed, a number of gold compounds, either gold(III) or gold(I), were recently described and characterised that manifested remarkable cytotoxic properties in vitro against cultured cancer cells; for some of them encouraging in vivo results were also reported toward a few relevant animal models of cancer. The molecular mechanisms through which gold compounds exert their biological effects are still largely unknown and the subject of intense investigations. Recent studies point out that the modes of action of cytotoxic gold compounds are essentially DNA-independent and cisplatin-unrelated, relying -most likely- on gold interactions with a variety of protein targets. Notably, a few cellular proteins playing relevant functional roles were proposed to represent effective targets for cytotoxic gold compounds but these hypotheses need adequate validation. The state of the art of this research area and the perspectives for future studies are herein critically analysed and discussed.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Emergent Societal Effects of Crimino-Social Forces in an Animat Agent Model

NASA Astrophysics Data System (ADS)

Scogings, Chris J.; Hawick, Ken A.

Societal behaviour can be studied at a causal level by perturbing a stable multi-agent model with new microscopic behaviours and observing the statistical response over an ensemble of simulated model systems. We report on the effects of introducing criminal and law-enforcing behaviours into a large scale animat agent model and describe the complex spatial agent patterns and population changes that result. Our well-established predator-prey substrate model provides a background framework against which these new microscopic behaviours can be trialled and investigated. We describe some quantitative results and some surprising conclusions concerning the overall societal health when individually anti-social behaviour is introduced.

Driving-forces model on individual behavior in scenarios considering moving threat agents

NASA Astrophysics Data System (ADS)

Li, Shuying; Zhuang, Jun; Shen, Shifei; Wang, Jia

2017-09-01

The individual behavior model is a contributory factor to improve the accuracy of agent-based simulation in different scenarios. However, few studies have considered moving threat agents, which often occur in terrorist attacks caused by attackers with close-range weapons (e.g., sword, stick). At the same time, many existing behavior models lack validation from cases or experiments. This paper builds a new individual behavior model based on seven behavioral hypotheses. The driving-forces model is an extension of the classical social force model considering scenarios including moving threat agents. An experiment was conducted to validate the key components of the model. Then the model is compared with an advanced Elliptical Specification II social force model, by calculating the fitting errors between the simulated and experimental trajectories, and being applied to simulate a specific circumstance. Our results show that the driving-forces model reduced the fitting error by an average of 33.9% and the standard deviation by an average of 44.5%, which indicates the accuracy and stability of the model in the studied situation. The new driving-forces model could be used to simulate individual behavior when analyzing the risk of specific scenarios using agent-based simulation methods, such as risk analysis of close-range terrorist attacks in public places.

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

NASA Astrophysics Data System (ADS)

Yoon, J.; Gorelick, S.

2014-12-01

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

Majority-Vote Model with Heterogeneous Agents on Square Lattice

NASA Astrophysics Data System (ADS)

Lima, F. W. S.

2013-11-01

We study a nonequilibrium model with up-down symmetry and a noise parameter q known as majority-vote model (MVM) of [M. J. Oliveira, J. Stat. Phys.66, 273 (1992)] with heterogeneous agents on square lattice (SL). By Monte Carlo (MC) simulations and finite-size scaling relations, the critical exponents β/ν, γ/ν and 1/ν and points qc and U* are obtained. After extensive simulations, we obtain β/ν = 0.35(1), γ/ν = 1.23(8) and 1/ν = 1.05(5). The calculated values of the critical noise parameter and Binder cumulant are qc = 0.1589(4) and U* = 0.604(7). Within the error bars, the exponents obey the relation 2β/ν + γ/ν = 2 and the results presented here demonstrate that the MVM heterogeneous agents belongs to a different universality class than the nonequilibrium MVM with homogeneous agents on SL.

Modeling the transport of cryoprotective agents in articular cartilage for cryopreservation

NASA Astrophysics Data System (ADS)

Torqabeh, Alireza Abazari

Loading vitrifiable concentrations of cryoprotective agents is an important step for cryopreservation of biological tissues by vitrification for research and transplantation purposes. This may be done by immersing the tissue in a cryoprotective agent (CPA) solution, and increasing the concentration, continuously or in multiple steps, and simultaneously decreasing the temperature to decrease the toxicity effects of the cryoprotective agent on the tissue cellular system. During cryoprotective agent loading, osmotic water movement from the tissue to the surrounding solution, and the resultant tissue shrinkage and stress-strain in the tissue matrix as well as on the cellular system can significantly alter the outcome of the cryopreservation protocol. In this thesis, a biomechanical model for articular cartilage is developed to account for the transport of the cryoprotective agent, the nonideal-nondilute properties of the vitrifiable solutions, the osmotic water movement and the resultant tissue shrinkage and stress-strain in the tissue matrix, and the osmotic volume change of the chondrocytes, during cryoprotective agent loading in the cartilage matrix. Four essential transport parameters needed for the model were specified, the values of which were obtained uniquely by fitting the model to experimental data from porcine articular cartilage. Then, it was shown that using real nonuniform initial distributions of water and fixed charges in cartilage, measured separately in this thesis using MRI, in the model can significantly affect the model predictions. The model predictions for dimethyl sulfoxide diffusion in porcine articular cartilage were verified by comparing to spatially and temporally resolved measurements of dimethyl sulfoxide concentration in porcine articular cartilage using a spectral MRI technique, developed for this purpose and novel to the field of cryobiology. It was demonstrated in this thesis that the developed mathematical model provides a novel tool

B-tree search reinforcement learning for model based intelligent agent

NASA Astrophysics Data System (ADS)

Bhuvaneswari, S.; Vignashwaran, R.

2013-03-01

Agents trained by learning techniques provide a powerful approximation of active solutions for naive approaches. In this study using B - Trees implying reinforced learning the data search for information retrieval is moderated to achieve accuracy with minimum search time. The impact of variables and tactics applied in training are determined using reinforcement learning. Agents based on these techniques perform satisfactory baseline and act as finite agents based on the predetermined model against competitors from the course.

Agent-based Model for the Coupled Human-Climate System

NASA Astrophysics Data System (ADS)

Zvoleff, A.; Werner, B.

2006-12-01

Integrated assessment models have been used to predict the outcome of coupled economic growth, resource use, greenhouse gas emissions and climate change, both for scientific and policy purposes. These models generally have employed significant simplifications that suppress nonlinearities and the possibility of multiple equilibria in both their economic (DeCanio, 2005) and climate (Schneider and Kuntz-Duriseti, 2002) components. As one step toward exploring general features of the nonlinear dynamics of the coupled system, we have developed a series of variations on the well studied RICE and DICE models, which employ different forms of agent-based market dynamics and "climate surprises." Markets are introduced through the replacement of the production function of the DICE/RICE models with an agent-based market modeling the interactions of producers, policymakers, and consumer agents. Technological change and population growth are treated endogenously. Climate surprises are representations of positive (for example, ice sheet collapse) or negative (for example, increased aerosols from desertification) feedbacks that are turned on with probability depending on warming. Initial results point toward the possibility of large amplitude instabilities in the coupled human-climate system owing to the mismatch between short outlook market dynamics and long term climate responses. Implications for predictability of future climate will be discussed. Supported by the Andrew W Mellon Foundation and the UC Academic Senate.

Clean process to destroy arsenic-containing organic compounds with recovery of arsenic

DOEpatents

Upadhye, R.S.; Wang, F.T.

1996-08-13

A reduction method is provided for the treatment of arsenic-containing organic compounds with simultaneous recovery of pure arsenic. Arsenic-containing organic compounds include pesticides, herbicides, and chemical warfare agents such as Lewisite. The arsenic-containing compound is decomposed using a reducing agent. Arsine gas may be formed directly by using a hydrogen-rich reducing agent, or a metal arsenide may be formed using a pure metal reducing agent. In the latter case, the arsenide is reacted with an acid to form arsine gas. In either case, the arsine gas is then reduced to elemental arsenic. 1 fig.

Clean process to destroy arsenic-containing organic compounds with recovery of arsenic

DOEpatents

Upadhye, Ravindra S.; Wang, Francis T.

1996-01-01

A reduction method is provided for the treatment of arsenic-containing organic compounds with simultaneous recovery of pure arsenic. Arsenic-containing organic compounds include pesticides, herbicides, and chemical warfare agents such as Lewisite. The arsenic-containing compound is decomposed using a reducing agent. Arsine gas may be formed directly by using a hydrogen-rich reducing agent, or a metal arsenide may be formed using a pure metal reducing agent. In the latter case, the arsenide is reacted with an acid to form arsine gas. In either case, the arsine gas is then reduced to elemental arsenic.

Marine Mollusk‐Derived Agents with Antiproliferative Activity as Promising Anticancer Agents to Overcome Chemotherapy Resistance

PubMed Central

Lefranc, Florence; Carbone, Marianna; Mollo, Ernesto; Gavagnin, Margherita; Betancourt, Tania; Dasari, Ramesh

2016-01-01

Abstract The chemical investigation of marine mollusks has led to the isolation of a wide variety of bioactive metabolites, which evolved in marine organisms as favorable adaptations to survive in different environments. Most of them are derived from food sources, but they can be also biosynthesized de novo by the mollusks themselves, or produced by symbionts. Consequently, the isolated compounds cannot be strictly considered as “chemotaxonomic markers” for the different molluscan species. However, the chemical investigation of this phylum has provided many compounds of interest as potential anticancer drugs that assume particular importance in the light of the growing literature on cancer biology and chemotherapy. The current review highlights the diversity of chemical structures, mechanisms of action, and, most importantly, the potential of mollusk‐derived metabolites as anticancer agents, including those biosynthesized by mollusks and those of dietary origin. After the discussion of dolastatins and kahalalides, compounds previously studied in clinical trials, the review covers potentially promising anticancer agents, which are grouped based on their structural type and include terpenes, steroids, peptides, polyketides and nitrogen‐containing compounds. The “promise” of a mollusk‐derived natural product as an anticancer agent is evaluated on the basis of its ability to target biological characteristics of cancer cells responsible for poor treatment outcomes. These characteristics include high antiproliferative potency against cancer cells in vitro, preferential inhibition of the proliferation of cancer cells over normal ones, mechanism of action via nonapoptotic signaling pathways, circumvention of multidrug resistance phenotype, and high activity in vivo, among others. The review also includes sections on the targeted delivery of mollusk‐derived anticancer agents and solutions to their procurement in quantity. PMID:27925266

A multi agent model for the limit order book dynamics

NASA Astrophysics Data System (ADS)

Bartolozzi, M.

2010-11-01

In the present work we introduce a novel multi-agent model with the aim to reproduce the dynamics of a double auction market at microscopic time scale through a faithful simulation of the matching mechanics in the limit order book. The agents follow a noise decision making process where their actions are related to a stochastic variable, the market sentiment, which we define as a mixture of public and private information. The model, despite making just few basic assumptions over the trading strategies of the agents, is able to reproduce several empirical features of the high-frequency dynamics of the market microstructure not only related to the price movements but also to the deposition of the orders in the book.

Statistical mechanics of competitive resource allocation using agent-based models

NASA Astrophysics Data System (ADS)

Chakraborti, Anirban; Challet, Damien; Chatterjee, Arnab; Marsili, Matteo; Zhang, Yi-Cheng; Chakrabarti, Bikas K.

2015-01-01

Demand outstrips available resources in most situations, which gives rise to competition, interaction and learning. In this article, we review a broad spectrum of multi-agent models of competition (El Farol Bar problem, Minority Game, Kolkata Paise Restaurant problem, Stable marriage problem, Parking space problem and others) and the methods used to understand them analytically. We emphasize the power of concepts and tools from statistical mechanics to understand and explain fully collective phenomena such as phase transitions and long memory, and the mapping between agent heterogeneity and physical disorder. As these methods can be applied to any large-scale model of competitive resource allocation made up of heterogeneous adaptive agent with non-linear interaction, they provide a prospective unifying paradigm for many scientific disciplines.

Embodied Agents, E-SQ and Stickiness: Improving Existing Cognitive and Affective Models

NASA Astrophysics Data System (ADS)

de Diesbach, Pablo Brice

This paper synthesizes results from two previous studies of embodied virtual agents on commercial websites. We analyze and criticize the proposed models and discuss the limits of the experimental findings. Results from other important research in the literature are integrated. We also integrate concepts from profound, more business-related, analysis that deepens on the mechanisms of rhetoric in marketing and communication, and the possible role of E-SQ in man-agent interaction. We finally suggest a refined model for the impacts of these agents on web site users, and limits of the improved model are commented.

Synthesis and evaluation of new 3-phenylcoumarin derivatives as potential antidepressant agents.

PubMed

Sashidhara, Koneni V; Rao, K Bhaskara; Singh, Seema; Modukuri, Ram K; Aruna Teja, G; Chandasana, Hardik; Shukla, Shubha; Bhatta, Rabi S

2014-10-15

A series of amine substituted 3-phenyl coumarin derivatives were designed and synthesized as potential antidepressant agents. In preliminary screening, all compounds were evaluated in forced swimming test (FST), a model to screen antidepressant activity in rodents. Among the series, compounds 5c and 6a potentially decreased the immobility time by 73.4% and 79.7% at a low dose of 0.5 mg/kg as compared to standard drug fluoxetine (FXT) which reduced the immobility time by 74% at a dose of 20 mg/kg, ip. Additionally, these active compounds also exhibited significant efficacy in tail suspension test (TST) (another model to screen antidepressant compounds). Interestingly, rotarod and locomotor activity tests confirmed that these two compounds do not have any motor impairment effect and neurotoxicity in mice. Our studies demonstrate that the new 3-phenylcoumarin derivatives may serve as a promising antidepressant lead and hence pave the way for further investigation around this chemical space. Copyright © 2014 Elsevier Ltd. All rights reserved.

IMS software developments for the detection of chemical warfare agent

NASA Technical Reports Server (NTRS)

Klepel, ST.; Graefenhain, U.; Lippe, R.; Stach, J.; Starrock, V.

1995-01-01

Interference compounds like gasoline, diesel, burning wood or fuel, etc. are presented in common battlefield situations. These compounds can cause detectors to respond as a false positive or interfere with the detector's ability to respond to target compounds such as chemical warfare agents. To ensure proper response of the ion mobility spectrometer to chemical warfare agents, two special software packages were developed and incorporated into the Bruker RAID-1. The programs suppress interferring signals caused by car exhaust or smoke gases resulting from burning materials and correct the influence of variable sample gas humidity which is important for detection and quantification of blister agents like mustard gas or lewisite.

Modeling the gas-phase thermochemistry of organosulfur compounds.

PubMed

Vandeputte, Aäron G; Sabbe, Maarten K; Reyniers, Marie-Françoise; Marin, Guy B

2011-06-27

Key to understanding the involvement of organosulfur compounds in a variety of radical chemistries, such as atmospheric chemistry, polymerization, pyrolysis, and so forth, is knowledge of their thermochemical properties. For organosulfur compounds and radicals, thermochemical data are, however, much less well documented than for hydrocarbons. The traditional recourse to the Benson group additivity method offers no solace since only a very limited number of group additivity values (GAVs) is available. In this work, CBS-QB3 calculations augmented with 1D hindered rotor corrections for 122 organosulfur compounds and 45 organosulfur radicals were used to derive 93 Benson group additivity values, 18 ring-strain corrections, 2 non-nearest-neighbor interactions, and 3 resonance corrections for standard enthalpies of formation, standard molar entropies, and heat capacities for organosulfur compounds and organosulfur radicals. The reported GAVs are consistent with previously reported GAVs for hydrocarbons and hydrocarbon radicals and include 77 contributions, among which 26 radical contributions, which, to the best of our knowledge, have not been reported before. The GAVs allow one to estimate the standard enthalpies of formation at 298 K, the standard entropies at 298 K, and standard heat capacities in the temperature range 300-1500 K for a large set of organosulfur compounds, that is, thiols, thioketons, polysulfides, alkylsulfides, thials, dithioates, and cyclic sulfur compounds. For a validation set of 26 organosulfur compounds, the mean absolute deviation between experimental and group additively modeled enthalpies of formation amounts to 1.9  kJ  mol(-1). For an additional set of 14 organosulfur compounds, it was shown that the mean absolute deviations between calculated and group additively modeled standard entropies and heat capacities are restricted to 4 and 2 J  mol(-1)  K(-1), respectively. As an alternative to Benson GAVs, 26 new hydrogen

Sunscreening Agents

PubMed Central

Martis, Jacintha; Shobha, V; Sham Shinde, Rutuja; Bangera, Sudhakar; Krishnankutty, Binny; Bellary, Shantala; Varughese, Sunoj; Rao, Prabhakar; Naveen Kumar, B.R.

2013-01-01

The increasing incidence of skin cancers and photodamaging effects caused by ultraviolet radiation has increased the use of sunscreening agents, which have shown beneficial effects in reducing the symptoms and reoccurrence of these problems. Many sunscreen compounds are in use, but their safety and efficacy are still in question. Efficacy is measured through indices, such as sun protection factor, persistent pigment darkening protection factor, and COLIPA guidelines. The United States Food and Drug Administration and European Union have incorporated changes in their guidelines to help consumers select products based on their sun protection factor and protection against ultraviolet radiation, whereas the Indian regulatory agency has not yet issued any special guidance on sunscreening agents, as they are classified under cosmetics. In this article, the authors discuss the pharmacological actions of sunscreening agents as well as the available formulations, their benefits, possible health hazards, safety, challenges, and proper application technique. New technologies and scope for the development of sunscreening agents are also discussed as well as the role of the physician in patient education about the use of these agents. PMID:23320122

Comparison of tumor related signaling pathways with known compounds to determine potential agents for lung adenocarcinoma.

PubMed

Xu, Song; Liu, Renwang; Da, Yurong

2018-06-05

This study compared tumor-related signaling pathways with known compounds to determine potential agents for lung adenocarcinoma (LUAD) treatment. Kyoto Encyclopedia of Genes and Genomes signaling pathway analyses were performed based on LUAD differentially expressed genes from The Cancer Genome Atlas (TCGA) project and genotype-tissue expression controls. These results were compared to various known compounds using the Connectivity Mapping dataset. The clinical significance of the hub genes identified by overlapping pathway enrichment analysis was further investigated using data mining from multiple sources. A drug-pathway network for LUAD was constructed, and molecular docking was carried out. After the integration of 57 LUAD-related pathways and 35 pathways affected by small molecules, five overlapping pathways were revealed. Among these five pathways, the p53 signaling pathway was the most significant, with CCNB1, CCNB2, CDK1, CDKN2A, and CHEK1 being identified as hub genes. The p53 signaling pathway is implicated as a risk factor for LUAD tumorigenesis and survival. A total of 88 molecules significantly inhibiting the five LUAD-related oncogenic pathways were involved in the LUAD drug-pathway network. Daunorubicin, mycophenolic acid, and pyrvinium could potentially target the hub gene CHEK1 directly. Our study highlights the critical pathways that should be targeted in the search for potential LUAD treatments, most importantly, the p53 signaling pathway. Some compounds, such as ciclopirox and AG-028671, may have potential roles for LUAD treatment but require further experimental verification. © 2018 The Authors. Thoracic Cancer published by China Lung Oncology Group and John Wiley & Sons Australia, Ltd.

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

ERIC Educational Resources Information Center

Gu, X.; Blackmore, K. L.

2015-01-01

This paper presents the results of a systematic review of agent-based modelling and simulation (ABMS) applications in the higher education (HE) domain. Agent-based modelling is a "bottom-up" modelling paradigm in which system-level behaviour (macro) is modelled through the behaviour of individual local-level agent interactions (micro).…

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

PubMed Central

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

2011-01-01

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

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

PubMed

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

2011-03-09

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

Design of cinnamaldehyde amino acid Schiff base compounds based on the quantitative structure-activity relationship.

PubMed

Wang, Hui; Jiang, Mingyue; Li, Shujun; Hse, Chung-Yun; Jin, Chunde; Sun, Fangli; Li, Zhuo

2017-09-01

Cinnamaldehyde amino acid Schiff base (CAAS) is a new class of safe, bioactive compounds which could be developed as potential antifungal agents for fungal infections. To design new cinnamaldehyde amino acid Schiff base compounds with high bioactivity, the quantitative structure-activity relationships (QSARs) for CAAS compounds against Aspergillus niger ( A. niger ) and Penicillium citrinum (P. citrinum) were analysed. The QSAR models ( R 2  = 0.9346 for A. niger , R 2  = 0.9590 for P. citrinum, ) were constructed and validated. The models indicated that the molecular polarity and the Max atomic orbital electronic population had a significant effect on antifungal activity. Based on the best QSAR models, two new compounds were designed and synthesized. Antifungal activity tests proved that both of them have great bioactivity against the selected fungi.

Design of cinnamaldehyde amino acid Schiff base compounds based on the quantitative structure–activity relationship

PubMed Central

Wang, Hui; Jiang, Mingyue; Hse, Chung-Yun; Jin, Chunde; Sun, Fangli; Li, Zhuo

2017-01-01

Cinnamaldehyde amino acid Schiff base (CAAS) is a new class of safe, bioactive compounds which could be developed as potential antifungal agents for fungal infections. To design new cinnamaldehyde amino acid Schiff base compounds with high bioactivity, the quantitative structure–activity relationships (QSARs) for CAAS compounds against Aspergillus niger (A. niger) and Penicillium citrinum (P. citrinum) were analysed. The QSAR models (R2 = 0.9346 for A. niger, R2 = 0.9590 for P. citrinum,) were constructed and validated. The models indicated that the molecular polarity and the Max atomic orbital electronic population had a significant effect on antifungal activity. Based on the best QSAR models, two new compounds were designed and synthesized. Antifungal activity tests proved that both of them have great bioactivity against the selected fungi. PMID:28989758

Unsilencing Critical Conversations in Social-Studies Teacher Education Using Agent-Based Modeling

ERIC Educational Resources Information Center

Hostetler, Andrew; Sengupta, Pratim; Hollett, Ty

2018-01-01

In this article, we argue that when complex sociopolitical issues such as ethnocentrism and racial segregation are represented as complex, emergent systems using agent-based computational models (in short agent-based models or ABMs), discourse about these representations can disrupt social studies teacher candidates' dispositions of teaching…

A multi-agent safety response model in the construction industry.

PubMed

Meliá, José L

2015-01-01

The construction industry is one of the sectors with the highest accident rates and the most serious accidents. A multi-agent safety response approach allows a useful diagnostic tool in order to understand factors affecting risk and accidents. The special features of the construction sector can influence the relationships among safety responses along the model of safety influences. The purpose of this paper is to test a model explaining risk and work-related accidents in the construction industry as a result of the safety responses of the organization, the supervisors, the co-workers and the worker. 374 construction employees belonging to 64 small Spanish construction companies working for two main companies participated in the study. Safety responses were measured using a 45-item Likert-type questionnaire. The structure of the measure was analyzed using factor analysis and the model of effects was tested using a structural equation model. Factor analysis clearly identifies the multi-agent safety dimensions hypothesized. The proposed safety response model of work-related accidents, involving construction specific results, showed a good fit. The multi-agent safety response approach to safety climate is a useful framework for the assessment of organizational and behavioral risks in construction.

Modeling the transport of chemical warfare agents and simulants in polymeric substrates for reactive decontamination

NASA Astrophysics Data System (ADS)

Pearl, Thomas; Mantooth, Brent; Varady, Mark; Willis, Matthew

2014-03-01

Chemical warfare agent simulants are often used for environmental testing in place of highly toxic agents. This work sets the foundation for modeling decontamination of absorbing polymeric materials with the focus on determining relationships between agents and simulants. The correlations of agents to simulants must consider the three way interactions in the chemical-material-decontaminant system where transport and reaction occur in polymer materials. To this end, diffusion modeling of the subsurface transport of simulants and live chemical warfare agents was conducted for various polymer systems (e.g., paint coatings) with and without reaction pathways with applied decontamination. The models utilized 1D and 2D finite difference diffusion and reaction models to simulate absorption and reaction in the polymers, and subsequent flux of the chemicals out of the polymers. Experimental data including vapor flux measurements and dynamic contact angle measurements were used to determine model input parameters. Through modeling, an understanding of the relationship of simulant to live chemical warfare agent was established, focusing on vapor emission of agents and simulants from materials.

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

PubMed

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

2011-07-01

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

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

NASA Astrophysics Data System (ADS)

Chen, Peng; Liu, Miaolong

2007-06-01

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

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

PubMed

Jimenez-Romero, Cristian; Johnson, Jeffrey

2017-01-01

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

The self-aware diabetic patient software agent model.

PubMed

Wang, Zhanle; Paranjape, Raman

2013-11-01

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

A simplified building airflow model for agent concentration prediction.

PubMed

Jacques, David R; Smith, David A

2010-11-01

A simplified building airflow model is presented that can be used to predict the spread of a contaminant agent from a chemical or biological attack. If the dominant means of agent transport throughout the building is an air-handling system operating at steady-state, a linear time-invariant (LTI) model can be constructed to predict the concentration in any room of the building as a result of either an internal or external release. While the model does not capture weather-driven and other temperature-driven effects, it is suitable for concentration predictions under average daily conditions. The model is easily constructed using information that should be accessible to a building manager, supplemented with assumptions based on building codes and standard air-handling system design practices. The results of the model are compared with a popular multi-zone model for a simple building and are demonstrated for building examples containing one or more air-handling systems. The model can be used for rapid concentration prediction to support low-cost placement strategies for chemical and biological detection sensors.

Phenomenological modelling of self-healing polymers based on integrated healing agents

NASA Astrophysics Data System (ADS)

Mergheim, Julia; Steinmann, Paul

2013-09-01

The present contribution introduces a phenomenological model for self-healing polymers. Self-healing polymers are a promising class of materials which mimic nature by their capability to autonomously heal micro-cracks. This self-healing is accomplished by the integration of microcapsules containing a healing agent and a dispersed catalyst into the matrix material. Propagating microcracks may then break the capsules which releases the healing agent into the microcracks where it polymerizes with the catalyst, closes the crack and 'heals' the material. The present modelling approach treats these processes at the macroscopic scale, the microscopic details of crack propagation and healing are thus described by means of continuous damage and healing variables. The formulation of the healing model accounts for the fact that healing is directly associated with the curing process of healing agent and catalyst. The model is implemented and its capabilities are studied by means of numerical examples.

Modeling the Biodegradability of Chemical Compounds Using the Online CHEmical Modeling Environment (OCHEM).

PubMed

Vorberg, Susann; Tetko, Igor V

2014-01-01

Biodegradability describes the capacity of substances to be mineralized by free-living bacteria. It is a crucial property in estimating a compound's long-term impact on the environment. The ability to reliably predict biodegradability would reduce the need for laborious experimental testing. However, this endpoint is difficult to model due to unavailability or inconsistency of experimental data. Our approach makes use of the Online Chemical Modeling Environment (OCHEM) and its rich supply of machine learning methods and descriptor sets to build classification models for ready biodegradability. These models were analyzed to determine the relationship between characteristic structural properties and biodegradation activity. The distinguishing feature of the developed models is their ability to estimate the accuracy of prediction for each individual compound. The models developed using seven individual descriptor sets were combined in a consensus model, which provided the highest accuracy. The identified overrepresented structural fragments can be used by chemists to improve the biodegradability of new chemical compounds. The consensus model, the datasets used, and the calculated structural fragments are publicly available at http://ochem.eu/article/31660. © 2014 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Molecular targets of organophosphorus compounds and antidotal agents on nicotinic, glutamatergic and gabaergic synapses. Appendix 1. Final report

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

Albuquerque, E.X.

1994-03-16

There are several major motivators behind this work. We need to understand OP intoxication sufficiently to provide insight and direction for development of improved antidotal therapy. The persistent environmental use of chemical insecticides, which some feel is necessary for optimal agricultural production but others challenge vehemently, requires that we understand the toxicological consequences of such use. Also, OPs have such a powerful effect or, vital functions, it could be immensely beneficial to understand in great detail the physiological mechanisms that are targeted by OPs. Such information could benefit medical treatments of diseases and pathologies other than those directly caused bymore » OPs. Finally, we hope to present the material in a manner that will be instructive to a broad spectrum of professionals in pharmacology and toxicology. Where it is appropriate, we may draw heavily from other topical reviews. In all cases, we will provide citations to original work and/or well-referenced RA I, Lab Animals, Rats, Frogs, Compounds, Nerve Agents, Organophosphorous, BD, CD Agents, XCSM, Neurotransmitters, Receptors, Ion Channel, Oximes.« less

Neurotoxic disorders of organophosphorus compounds and their managements.

PubMed

Balali-Mood, Mahdi; Balali-Mood, Kia

2008-01-01

Organophosphorus compounds have been used as pesticides and as chemical warfare nerve agents. The mechanism of toxicity of organophosphorus compounds is the inhibition of acetylcholinesterase, which results in accumulation of acetylcholine and the continued stimulation of acetylcholine receptors. Therefore, they are also called anticholinesterase agents. Organophosphorus pesticides have largely been used worldwide, and poisoning by these agents, particularly in developing countries, is a serious health problem. Organophosphorus nerve agents were used by Iraqi army against Iranian combatants and even civilian population in 1983 - 1988. They were also used for chemical terrorism in Japan in 1994 - 1995. Their use is still a constant threat to the population. Therefore, medical and health professionals should be aware and learn more about the toxicology and proper management of organophosphorus poisoning. Determination of acetylcholinesterase and butyrylcholinesterase activity in blood remains a mainstay for the fast initial screening of organophosphorus compounds but lacks sensitivity and specificity. Quantitative analysis of organophosphorus compounds and their degradation products in plasma and urine by mass spectrometric methods may prove exposure but is expensive and is limited to specialized laboratories. However, history of exposure to organophosphorous compounds and clinical manifestations of a cholinergic syndrome are sufficient for management of the affected patients. The standard management of poisoning with organophosphorous compounds consists of decontamination, and injection of atropine sulfate with an oxime. Recent advances on treatment of organophosphorus pesticides poisoning revealed that blood alkalinization with sodium bicarbonate and also magnesium sulfate as adjunctive therapies are promising. Patients who receive prompt proper treatment usually recover from acute toxicity but may suffer from neurologic complications.

Reverse Osmosis Processing of Organic Model Compounds and Fermentation Broths

DTIC Science & Technology

2006-04-01

AFRL-ML-TY-TP-2007-4545 POSTPRINT REVERSE OSMOSIS PROCESSING OF ORGANIC MODEL COMPOUNDS AND FERMENTATION BROTHS Robert Diltz...TELEPHONE NUMBER (Include area code) Bioresource Technology 98 (2007) 686–695Reverse osmosis processing of organic model compounds and fermentation broths...December 2005; accepted 31 January 2006 Available online 4 April 2006Abstract Post-treatment of an anaerobic fermentation broth was evaluated using a 150

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

PubMed

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.

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

PubMed

Pooyandeh, Majeed; Marceau, Danielle J

2013-11-15

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

Agent-Based Modeling of Cancer Stem Cell Driven Solid Tumor Growth.

PubMed

Poleszczuk, Jan; Macklin, Paul; Enderling, Heiko

2016-01-01

Computational modeling of tumor growth has become an invaluable tool to simulate complex cell-cell interactions and emerging population-level dynamics. Agent-based models are commonly used to describe the behavior and interaction of individual cells in different environments. Behavioral rules can be informed and calibrated by in vitro assays, and emerging population-level dynamics may be validated with both in vitro and in vivo experiments. Here, we describe the design and implementation of a lattice-based agent-based model of cancer stem cell driven tumor growth.

Influence of hydrogenated oil as cocoa butter replacers in the development of sugar-free compound chocolates: Use of inulin as stabilizing agent.

PubMed

Rodriguez Furlán, Laura T; Baracco, Yanina; Lecot, Javier; Zaritzky, Noemi; Campderrós, Mercedes E

2017-02-15

The effect of the addition of inulin as a surfactant or stability agent on white compound chocolate sweetened with sucralose and Stevia was studied. Samples were stored at 7, 15 and 30°C during 100days and the influence of inulin on rheological properties, sensorial attributes, shelf-life, physical properties such as melting, crystallization and blooming were analyzed. The shelf-life of the compound chocolate with the incorporation of inulin was higher than the control sample without replacement. Compound chocolate with inulin at 10%w/w showed a dense matrix structure, reducing the size and number of fat crystals formed during storage; furthermore they presented higher values of brightness and WI. This chocolate also showed less fracturability and improved thermal properties. DSC studies revealed increased values of onset and peak temperatures and enthalpy of melting of the polymorphic form V, at higher storage temperatures, achieving greater stability against degradation processes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Synthesis and Utilization of Trialkylammonium-Substituted Cyclodextrins as Water-Soluble Chiral NMR Solvating Agents for Anionic Compounds.

PubMed

Dowey, Alison E; Puentes, Cira Mollings; Carey-Hatch, Mira; Sandridge, Keyana L; Krishna, Nikhil B; Wenzel, Thomas J

2016-04-01

Cationic trialkylammonium-substituted α-, β-, and γ-cyclodextrins containing trimethyl-, triethyl-, and tri-n-propylammonium substituent groups were synthesized and analyzed for utility as water-soluble chiral nuclear magnetic resonance (NMR) solvating agents. Racemic and enantiomerically pure (3-chloro-2-hydroxypropyl)trimethyl-, triethyl-, and tri-n-propyl ammonium chloride were synthesized from the corresponding trialkyl amine hydrochloride and either racemic or enantiomerically pure epichlorohydrin. The ammonium salts were then reacted with α-, β-, and γ-cyclodextrins at basic pH to provide the corresponding randomly substituted cationic cyclodextrins. The (1) H NMR spectra of a range of anionic, aromatic compounds was recorded with the cationic cyclodextrins. Cyclodextrins with a single stereochemistry at the hydroxy group on the (2-hydroxypropyl)trialkylammonium chloride substituent were often but not always more effective than the corresponding cyclodextrin in which the C-2 position was racemic. In several cases, the larger triethyl or tri-n-propyl derivatives were more effective than the corresponding trimethyl derivative at causing enantiomeric differentiation. None of the cyclodextrin derivatives were consistently the most effective for all of the anionic compounds studied. © 2016 Wiley Periodicals, Inc.

New rodent models for studies of chemopreventive agents.

PubMed

Lipkin, M

1997-01-01

Some recent studies of the effects of chemopreventive agents have begun to use new rodent models to improve the analysis of stages of colonic preneoplasia, and how chemopreventive agents modify progressive abnormal cell development. In one of the models of inherited predisposition to colon cancer, mice carrying a truncated Apc allele with a nonsense mutation in exon 15 have been generated by gene targeting and embryonic stem cell technology (Apc1638 mice). These mice develop multiple gastrointestinal lesions, including adenomas and carcinomas, focal areas of high-grade dysplasia (FAD), and polypoid hyperplasias with FADS. The incidence of inherited colonic neoplasms has now been modulated by a chemopreventive regimen. Colonic lesions significantly increased in Apc1638 mice on a Western-style diet, which has higher fat content and lower calcium and vitamin D compared to the same mice on AIN-76A diet. In another rodent model, Min mice were treated with sulindac, which markedly reduced the incidence of intestinal tumors. A third new rodent model containing a targeted mutation in the gene Mcc (mutated in colorectal cancer) recently became available for chemoprevention studies. These mice develop multiple types of neoplasms including adenocarcinomas, focal areas of gastrointestinal dysplasia, papillomas of the forestomach, and tumors in other organs including lung, liver, and lymphoid tissue. Feeding a Western-style diet to the Mcc mutant mice also resulted in significantly increased gastrointestinal lesions. These nutrient modifications also have been given to normal mice, demonstrating without any chemical carcinogen that a Western-style diet induced colonic tumorigenesis. Western-style diets also have now induced modulation of cell proliferation in other organs including mammary gland, pancreas, and prostate. These findings help develop new preclinical rodent models to aid the analysis of genetic and environmental factors leading to neoplasia, as well as new methods

Peptides: β-cyclodextrin inclusion compounds as highly effective antimicrobial and anti-epithelial proliferation agents.

PubMed

Consuegra, Jessika; de Lima, Maria Elena; Santos, Daniel; Sinisterra, Rubén Dario; Cortés, Maria Esperanza

2013-12-01

The use of antimicrobial peptides (AMPs) as therapeutic agents for periodontal infections has great advantages, such as broad spectrum of action, low toxicity, and limited bacterial resistance. However, their practical use is limited because of the large amount of peptide required to exercise the microbicidal function. LyeTxI, LL37f, and KR12 cationic peptides were prepared with β-cyclodextrin (βCD) at 1:1 molar ratios. The susceptibility of Porphyromonas gingivalis, Aggregatibacter actinomycetemcomitans, and Fusobacterium nucleatum were assessed in anaerobic conditions. Cytotoxicity assays were performed using osteoblast and Caco-2 epithelial cells, and hemolytic activity was assessed on rabbit erythrocytes at an absorbance of 414 nm. Parameters of surface roughness and electrical charge were established by atomic force microscopy and zeta (ζ) potential, respectively. AMP/βCDs drastically decreased the peptide concentration required for activity against the bacteria tested. Moreover, AMPs associated with βCD were able to modify cell-surface parameters, such as roughness and ζ potential. On the other hand, AMP/βCD did not alter the degree of hemolysis induced by the pure AMPs. The effective concentration at half-maximum values of the peptides and compounds on osteoblasts were greater than the concentrations required to achieve inhibition of bacterial growth in all the species tested. AMP/βCDs inhibited the proliferation of Caco-2 epithelial cells in a more efficient manner than AMPs alone. AMP/βCD compounds more effectively inhibit periodontopathogenic bacteria than AMPs alone, with the additional ability of inhibiting the proliferation of epithelial cells at concentrations that are non-cytotoxic for osteoblasts and erythrocytes.

Compound prioritization methods increase rates of chemical probe discovery in model organisms

PubMed Central

Wallace, Iain M; Urbanus, Malene L; Luciani, Genna M; Burns, Andrew R; Han, Mitchell KL; Wang, Hao; Arora, Kriti; Heisler, Lawrence E; Proctor, Michael; St. Onge, Robert P; Roemer, Terry; Roy, Peter J; Cummins, Carolyn L; Bader, Gary D; Nislow, Corey; Giaever, Guri

2011-01-01

SUMMARY Pre-selection of compounds that are more likely to induce a phenotype can increase the efficiency and reduce the costs for model organism screening. To identify such molecules, we screened ~81,000 compounds in S. cerevisiae and identified ~7,500 that inhibit cell growth. Screening these growth-inhibitory molecules across a diverse panel of model organisms resulted in an increased phenotypic hit-rate. This data was used to build a model to predict compounds that inhibit yeast growth. Empirical and in silico application of the model enriched the discovery of bioactive compounds in diverse model organisms. To demonstrate the potential of these molecules as lead chemical probes we used chemogenomic profiling in yeast and identified specific inhibitors of lanosterol synthase and of stearoyl-CoA 9-desaturase. As community resources, the ~7,500 growth-inhibitory molecules has been made commercially available and the computational model and filter used are provided. PMID:22035796

Theory of agent-based market models with controlled levels of greed and anxiety

NASA Astrophysics Data System (ADS)

Papadopoulos, P.; Coolen, A. C. C.

2010-01-01

We use generating functional analysis to study minority-game-type market models with generalized strategy valuation updates that control the psychology of agents' actions. The agents' choice between trend-following and contrarian trading, and their vigor in each, depends on the overall state of the market. Even in 'fake history' models, the theory now involves an effective overall bid process (coupled to the effective agent process) which can exhibit profound remanence effects and new phase transitions. For some models the bid process can be solved directly, others require Maxwell-construction-type approximations.

Evolvable social agents for bacterial systems modeling.

PubMed

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

2004-09-01

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

Building occupancy simulation and data assimilation using a graph-based agent-oriented model

NASA Astrophysics Data System (ADS)

Rai, Sanish; Hu, Xiaolin

2018-07-01

Building occupancy simulation and estimation simulates the dynamics of occupants and estimates their real-time spatial distribution in a building. It requires a simulation model and an algorithm for data assimilation that assimilates real-time sensor data into the simulation model. Existing building occupancy simulation models include agent-based models and graph-based models. The agent-based models suffer high computation cost for simulating large numbers of occupants, and graph-based models overlook the heterogeneity and detailed behaviors of individuals. Recognizing the limitations of existing models, this paper presents a new graph-based agent-oriented model which can efficiently simulate large numbers of occupants in various kinds of building structures. To support real-time occupancy dynamics estimation, a data assimilation framework based on Sequential Monte Carlo Methods is also developed and applied to the graph-based agent-oriented model to assimilate real-time sensor data. Experimental results show the effectiveness of the developed model and the data assimilation framework. The major contributions of this work are to provide an efficient model for building occupancy simulation that can accommodate large numbers of occupants and an effective data assimilation framework that can provide real-time estimations of building occupancy from sensor data.

Mathematical modeling of atmospheric fine particle-associated primary organic compound concentrations

NASA Astrophysics Data System (ADS)

Rogge, Wolfgang F.; Hildemann, Lynn M.; Mazurek, Monica A.; Cass, Glen R.; Simoneit, Bernd R. T.

1996-08-01

An atmospheric transport model has been used to explore the relationship between source emissions and ambient air quality for individual particle phase organic compounds present in primary aerosol source emissions. An inventory of fine particulate organic compound emissions was assembled for the Los Angeles area in the year 1982. Sources characterized included noncatalyst- and catalyst-equipped autos, diesel trucks, paved road dust, tire wear, brake lining dust, meat cooking operations, industrial oil-fired boilers, roofing tar pots, natural gas combustion in residential homes, cigarette smoke, fireplaces burning oak and pine wood, and plant leaf abrasion products. These primary fine particle source emissions were supplied to a computer-based model that simulates atmospheric transport, dispersion, and dry deposition based on the time series of hourly wind observations and mixing depths. Monthly average fine particle organic compound concentrations that would prevail if the primary organic aerosol were transported without chemical reaction were computed for more than 100 organic compounds within an 80 km × 80 km modeling area centered over Los Angeles. The monthly average compound concentrations predicted by the transport model were compared to atmospheric measurements made at monitoring sites within the study area during 1982. The predicted seasonal variation and absolute values of the concentrations of the more stable compounds are found to be in reasonable agreement with the ambient observations. While model predictions for the higher molecular weight polycyclic aromatic hydrocarbons (PAH) are in agreement with ambient observations, lower molecular weight PAH show much higher predicted than measured atmospheric concentrations in the particle phase, indicating atmospheric decay by chemical reactions or evaporation from the particle phase. The atmospheric concentrations of dicarboxylic acids and aromatic polycarboxylic acids greatly exceed the contributions that

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

PubMed Central

Marshall, Brandon D. L.; Galea, Sandro

2015-01-01

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

An experimental study of hafting adhesives and the implications for compound tool technology.

PubMed

Zipkin, Andrew M; Wagner, Mark; McGrath, Kate; Brooks, Alison S; Lucas, Peter W

2014-01-01

Experimental studies of hafting adhesives and modifications to compound tool components can demonstrate the extent to which human ancestors understood and exploited material properties only formally defined by science within the last century. Discoveries of Stone Age hafting adhesives at archaeological sites in Europe, the Middle East, and Africa have spurred experiments that sought to replicate or create models of such adhesives. Most of these studies, however, have been actualistic in design, focusing on replicating ancient applications of adhesive technology. In contrast, this study tested several glues based on Acacia resin within a materials science framework to better understand the effect of each adhesive ingredient on compound tool durability. Using an overlap joint as a model for a compound tool, adhesives formulated with loading agents from a range of particle sizes and mineral compositions were tested for toughness on smooth and rough substrates. Our results indicated that overlap joint toughness is significantly increased by using a roughened joint surface. Contrary to some previous studies, there was no evidence that particle size diversity in a loading agent improved adhesive effectiveness. Generally, glues containing quartz or ochre loading agents in the silt and clay-sized particle class yielded the toughest overlap joints, with the effect of particle size found to be more significant for rough rather than smooth substrate joints. Additionally, no particular ochre mineral or mineral mixture was found to be a clearly superior loading agent. These two points taken together suggest that Paleolithic use of ochre-loaded adhesives and the criteria used to select ochres for this purpose may have been mediated by visual and symbolic considerations rather than purely functional concerns.

An Experimental Study of Hafting Adhesives and the Implications for Compound Tool Technology

PubMed Central

Zipkin, Andrew M.; Wagner, Mark; McGrath, Kate; Brooks, Alison S.; Lucas, Peter W.

2014-01-01

Experimental studies of hafting adhesives and modifications to compound tool components can demonstrate the extent to which human ancestors understood and exploited material properties only formally defined by science within the last century. Discoveries of Stone Age hafting adhesives at archaeological sites in Europe, the Middle East, and Africa have spurred experiments that sought to replicate or create models of such adhesives. Most of these studies, however, have been actualistic in design, focusing on replicating ancient applications of adhesive technology. In contrast, this study tested several glues based on Acacia resin within a materials science framework to better understand the effect of each adhesive ingredient on compound tool durability. Using an overlap joint as a model for a compound tool, adhesives formulated with loading agents from a range of particle sizes and mineral compositions were tested for toughness on smooth and rough substrates. Our results indicated that overlap joint toughness is significantly increased by using a roughened joint surface. Contrary to some previous studies, there was no evidence that particle size diversity in a loading agent improved adhesive effectiveness. Generally, glues containing quartz or ochre loading agents in the silt and clay-sized particle class yielded the toughest overlap joints, with the effect of particle size found to be more significant for rough rather than smooth substrate joints. Additionally, no particular ochre mineral or mineral mixture was found to be a clearly superior loading agent. These two points taken together suggest that Paleolithic use of ochre-loaded adhesives and the criteria used to select ochres for this purpose may have been mediated by visual and symbolic considerations rather than purely functional concerns. PMID:25383871

An Agent-Based Model of Farmer Decision Making in Jordan

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

Alexandridis, Konstantinos T.

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

Agent-Based Modeling of Noncommunicable Diseases: A Systematic Review

PubMed Central

Arah, Onyebuchi A.

2015-01-01

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. PMID:25602871

From actors to agents in socio-ecological systems models

PubMed Central

Rounsevell, M. D. A.; Robinson, D. T.; Murray-Rust, D.

2012-01-01

The ecosystem service concept has emphasized the role of people within socio-ecological systems (SESs). In this paper, we review and discuss alternative ways of representing people, their behaviour and decision-making processes in SES models using an agent-based modelling (ABM) approach. We also explore how ABM can be empirically grounded using information from social survey. The capacity for ABM to be generalized beyond case studies represents a crucial next step in modelling SESs, although this comes with considerable intellectual challenges. We propose the notion of human functional types, as an analogy of plant functional types, to support the expansion (scaling) of ABM to larger areas. The expansion of scope also implies the need to represent institutional agents in SES models in order to account for alternative governance structures and policy feedbacks. Further development in the coupling of human-environment systems would contribute considerably to better application and use of the ecosystem service concept. PMID:22144388

From actors to agents in socio-ecological systems models.

PubMed

Rounsevell, M D A; Robinson, D T; Murray-Rust, D

2012-01-19

The ecosystem service concept has emphasized the role of people within socio-ecological systems (SESs). In this paper, we review and discuss alternative ways of representing people, their behaviour and decision-making processes in SES models using an agent-based modelling (ABM) approach. We also explore how ABM can be empirically grounded using information from social survey. The capacity for ABM to be generalized beyond case studies represents a crucial next step in modelling SESs, although this comes with considerable intellectual challenges. We propose the notion of human functional types, as an analogy of plant functional types, to support the expansion (scaling) of ABM to larger areas. The expansion of scope also implies the need to represent institutional agents in SES models in order to account for alternative governance structures and policy feedbacks. Further development in the coupling of human-environment systems would contribute considerably to better application and use of the ecosystem service concept.

Going beyond the unitary curve: incorporating richer cognition into agent-based water resources models

NASA Astrophysics Data System (ADS)

Kock, B. E.

2008-12-01

The increased availability and understanding of agent-based modeling technology and techniques provides a unique opportunity for water resources modelers, allowing them to go beyond traditional behavioral approaches from neoclassical economics, and add rich cognition to social-hydrological models. Agent-based models provide for an individual focus, and the easier and more realistic incorporation of learning, memory and other mechanisms for increased cognitive sophistication. We are in an age of global change impacting complex water resources systems, and social responses are increasingly recognized as fundamentally adaptive and emergent. In consideration of this, water resources models and modelers need to better address social dynamics in a manner beyond the capabilities of neoclassical economics theory and practice. However, going beyond the unitary curve requires unique levels of engagement with stakeholders, both to elicit the richer knowledge necessary for structuring and parameterizing agent-based models, but also to make sure such models are appropriately used. With the aim of encouraging epistemological and methodological convergence in the agent-based modeling of water resources, we have developed a water resources-specific cognitive model and an associated collaborative modeling process. Our cognitive model emphasizes efficiency in architecture and operation, and capacity to adapt to different application contexts. We describe a current application of this cognitive model and modeling process in the Arkansas Basin of Colorado. In particular, we highlight the potential benefits of, and challenges to, using more sophisticated cognitive models in agent-based water resources models.

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

NASA Astrophysics Data System (ADS)

Haer, Toon; Aerts, Jeroen

2015-04-01

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

Development of a whole-organism model to screen new compounds for sun protection.

PubMed

Wang, Yun-Hsin; Wen, Chi-Chung; Yang, Zhi-Shiang; Cheng, Chien-Chung; Tsai, Jen-Ning; Ku, Chia-Chen; Wu, Hsin-Ju; Chen, Yau-Hung

2009-01-01

We used zebrafish as a whole-organism model to screen new compounds for sun protection activity. First of all, we designed a series of UVB exposure experiments and recorded the phenotypic changes of zebrafish embryos. Results showed that 100 mJ/cm(2) of UVB given six times separated by 30 min intervals is the best condition. Fin malformation (reduced and/or absent fin) phenotypes are the most evident consequences after exposure to UVB. Each fin was affected by UVB, including pelvic, ventral, caudal, and dorsal fin, but pelvic fin seemed to be the most sensitive target after UVB exposure. We furthermore carried out "prevention" and "treatment" experiments using green tea extract and/or (-)-epigallocatechin (EGCG) to test this whole-organism model by observing the morphological changes of all fins (especially pelvic fin) after UVB exposure. Effects of UVB, green tea extract and EGCG on fin development were assessed using the Kaplan-Meier analysis, log-rank test and Cox proportional hazards regression. Results showed that a zebrafish pelvic fin in the UVB + green tea (treatment) group is 5.51 (range from 2.39 to 14.90) times, one in the UVB + green tea (prevention) group is 7.04 (range from 3.11 to 18.92) times, and one in the 25 ppm of EGCG (prevention) group is 22.19 (range from 9.40 to 61.50) times more likely to return to normal fin than one in the UVB only group. On the basis of these observations, we believe this model is effective for screening the higher stability and lower toxicity of new compounds, such as small chemicals which are derivative from EGCG or other dietary agents for sun protection.

Agent-based modeling: case study in cleavage furrow models.

PubMed

Mogilner, Alex; Manhart, Angelika

2016-11-07

The number of studies in cell biology in which quantitative models accompany experiments has been growing steadily. Roughly, mathematical and computational techniques of these models can be classified as "differential equation based" (DE) or "agent based" (AB). Recently AB models have started to outnumber DE models, but understanding of AB philosophy and methodology is much less widespread than familiarity with DE techniques. Here we use the history of modeling a fundamental biological problem-positioning of the cleavage furrow in dividing cells-to explain how and why DE and AB models are used. We discuss differences, advantages, and shortcomings of these two approaches. © 2016 Mogilner and Manhart. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Antitumor activity of (2E,5Z)-5-(2-hydroxybenzylidene)-2-((4-phenoxyphenyl)imino) thiazolidin-4-one, a novel microtubule-depolymerizing agent, in U87MG human glioblastoma cells and corresponding mouse xenograft model.

PubMed

Zhang, Qiu; Liu, Xiaojun; Li, Xiue; Li, Changlong; Zhou, Hongyu; Yan, Bing

2013-01-01

Glioblastoma is the most lethal brain cancer. In spite of intensive therapy, the prognosis of patients with glioblastoma is very poor. To discover novel therapeutic agents, we screened a combinatorial compound library containing 372 thiazolidinone compounds using U87MG human glioblastoma cells. (2E,5Z)-5-(2-hydroxybenzylidene)-2-((4-phenoxyphenyl)imino) thiazolidin-4-one (HBPT) was identified as the most potent anti-glioblastoma compound. HBPT inhibits U87MG human glioblastoma cell proliferation with an IC50 of 20 μM, which is almost 5-fold more potent than temozolomide (a widely used drug for treating malignant glioma in the clinic). Mechanistic investigation demonstrated that HBPT is a novel microtubule-depolymerizing agent, which arrests cancer cells at the G2/M phase of the cell cycle and induces cell apoptosis. In the mouse U87MG xenograft model, HBPT elicits a robust tumor inhibitory effect. More importantly, no obvious toxicity was observed for HBPT therapy in animal experiments. These findings indicate that HBPT has the potential to be developed as a novel agent for the treatment of glioblastoma. [Supplementary Tables: available only at http://dx.doi.org/10.1254/jphs.13064FP].

Agent-Based Deterministic Modeling of the Bone Marrow Homeostasis.

PubMed

Kurhekar, Manish; Deshpande, Umesh

2016-01-01

Modeling of stem cells not only describes but also predicts how a stem cell's environment can control its fate. The first stem cell populations discovered were hematopoietic stem cells (HSCs). In this paper, we present a deterministic model of bone marrow (that hosts HSCs) that is consistent with several of the qualitative biological observations. This model incorporates stem cell death (apoptosis) after a certain number of cell divisions and also demonstrates that a single HSC can potentially populate the entire bone marrow. It also demonstrates that there is a production of sufficient number of differentiated cells (RBCs, WBCs, etc.). We prove that our model of bone marrow is biologically consistent and it overcomes the biological feasibility limitations of previously reported models. The major contribution of our model is the flexibility it allows in choosing model parameters which permits several different simulations to be carried out in silico without affecting the homeostatic properties of the model. We have also performed agent-based simulation of the model of bone marrow system proposed in this paper. We have also included parameter details and the results obtained from the simulation. The program of the agent-based simulation of the proposed model is made available on a publicly accessible website.

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

NASA Astrophysics Data System (ADS)

Gromek, Katherine Emily

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

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

PubMed

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.

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

PubMed Central

Auchincloss, Amy H.; Garcia, Leandro Martin Totaro

2017-01-01

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. PMID:26648364

Agent based reasoning for the non-linear stochastic models of long-range memory

NASA Astrophysics Data System (ADS)

Kononovicius, A.; Gontis, V.

2012-02-01

We extend Kirman's model by introducing variable event time scale. The proposed flexible time scale is equivalent to the variable trading activity observed in financial markets. Stochastic version of the extended Kirman's agent based model is compared to the non-linear stochastic models of long-range memory in financial markets. The agent based model providing matching macroscopic description serves as a microscopic reasoning of the earlier proposed stochastic model exhibiting power law statistics.

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

NASA Astrophysics Data System (ADS)

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.

Stable adducts of nerve agents sarin, soman and cyclosarin with TRIS, TES and related buffer compounds--characterization by LC-ESI-MS/MS and NMR and implications for analytical chemistry.

PubMed

Gäb, Jürgen; John, Harald; Melzer, Marco; Blum, Marc-Michael

2010-05-15

Buffering compounds like TRIS are frequently used in chemical, biochemical and biomedical applications to control pH in solution. One of the prerequisites of a buffer compound, in addition to sufficient buffering capacity and pH stability over time, is its non-reactivity with other constituents of the solution. This is especially important in the field of analytical chemistry where analytes are to be determined quantitatively. Investigating the enzymatic hydrolysis of G-type nerve agents sarin, soman and cyclosarin in buffered solution we have identified stable buffer adducts of TRIS, TES and other buffer compounds with the nerve agents. We identified the molecular structure of these adducts as phosphonic diesters using 1D (1)H-(31)P HSQC NMR and LC-ESI-MS/MS techniques. Reaction rates with TRIS and TES are fast enough to compete with spontaneous hydrolysis in aqueous solution and to yield substantial amounts (up to 20-40%) of buffer adduct over the course of several hours. A reaction mechanism is proposed in which the amino function of the buffer serves as an intramolecular proton acceptor rendering the buffer hydroxyl groups nucleophilic enough for attack on the phosphorus atom of the agents. Results show that similar buffer adducts are formed with a range of hydroxyl and amino function containing buffers including TES, BES, TRIS, BIS-TRIS, BIS-TRIS propane, Tricine, Bicine, HEPES and triethanol amine. It is recommended to use alternative buffers like MOPS, MES and CHES when working with G-type nerve agents especially at higher concentrations and over prolonged times. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Nocardiopsis species: a potential source of bioactive compounds.

PubMed

Bennur, T; Ravi Kumar, A; Zinjarde, S S; Javdekar, V

2016-01-01

Members of the genus Nocardiopsis are an ecologically versatile and biotechnologically important group of Actinomycetes. Most of the isolates are halotolerant or halophilic and they prevail in soils, marine environments or hypersaline locations. To aid their survival under these conditions, they mainly produce extremozymes, compatible solutes, surfactants and bioactive compounds. The current review details the bioactive compounds obtained for this genus. Important antimicrobial agents obtained from this genus include polyketides, phenzines, quinoline alkaloids, terphenyls, proteins, thiopeptides and amines. Polyketides and peptides displaying potent anticancer activities are also significant. Tumour promoting agents, P-glycoprotein (P-gp) inhibitors, immunomodulators and protein kinase inhibitors are other relevant products obtained from Nocardiopsis species. Structurally, polyketides (synthesized by polyketide synthases) and peptides (made by nonribosomal peptide synthetases or cyclodipeptide synthases) are important compounds. Considered here are also toxins, anti photoaging and adipogenic agents produced by this genus. The gene clusters mediating the synthesis of bioactive compounds have been described. Commercially available products (Apoptolidins and K-252a) derived from this genus have also been described. This review highlights the significance of a single genus in producing an assortment of compounds with varied biological activities. On account of these features, the members of this genus have established a place for themselves and are of considerable value in producing compounds with profound bio-medical applications. © 2015 The Society for Applied Microbiology.

Crowd Simulation Incorporating Agent Psychological Models, Roles and Communication

DTIC Science & Technology

2005-01-01

system (PMFserv) that implements human behavior models from a range of ability, stress, emotion , decision theoretic and motivation sources. An...autonomous agents, human behavior models, culture and emotions 1. Introduction There are many applications of computer animation and simulation where...We describe a new architecture to integrate a psychological model into a crowd simulation system in order to obtain believable emergent behaviors

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

PubMed

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.

Agent-based modeling of malaria vectors: the importance of spatial simulation.

PubMed

Bomblies, Arne

2014-07-03

The modeling of malaria vector mosquito populations yields great insight into drivers of malaria transmission at the village scale. Simulation of individual mosquitoes as "agents" in a distributed, dynamic model domain may be greatly beneficial for simulation of spatial relationships of vectors and hosts. In this study, an agent-based model is used to simulate the life cycle and movement of individual malaria vector mosquitoes in a Niger Sahel village, with individual simulated mosquitoes interacting with their physical environment as well as humans. Various processes that are known to be epidemiologically important, such as the dependence of parity on flight distance between developmental habitat and blood meal hosts and therefore spatial relationships of pools and houses, are readily simulated using this modeling paradigm. Impacts of perturbations can be evaluated on the basis of vectorial capacity, because the interactions between individuals that make up the population- scale metric vectorial capacity can be easily tracked for simulated mosquitoes and human blood meal hosts, without the need to estimate vectorial capacity parameters. As expected, model results show pronounced impacts of pool source reduction from larvicide application and draining, but with varying degrees of impact depending on the spatial relationship between pools and human habitation. Results highlight the importance of spatially-explicit simulation that can model individuals such as in an agent-based model. The impacts of perturbations on village scale malaria transmission depend on spatial locations of individual mosquitoes, as well as the tracking of relevant life cycle events and characteristics of individual mosquitoes. This study demonstrates advantages of using an agent-based approach for village-scale mosquito simulation to address questions in which spatial relationships are known to be important.

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

PubMed

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.

Methylene-Cycloalkylacetate (MCA) Scaffold-Based Compounds as Novel Neurotropic Agents.

PubMed

Lankri, David; Haham, Dikla; Lahiani, Adi; Lazarovici, Philip; Tsvelikhovsky, Dmitry

2018-04-18

One of the main symptoms in degenerative diseases is death of neuronal cell followed by the loss of neuronal pathways. In neuronal cultures, neurite outgrowths are cell sprouts capable of transforming into either axons or dendrites, to further form functional neuronal synaptic connections. Such connections have an important role in brain cognition, neuronal plasticity, neuronal survival, and regeneration. Therefore, drugs that stimulate neurite outgrowth may be found beneficial in ameliorating neural degeneration. Here, we establish the existence of a unique family of methylene-cycloalkylacetate-based molecules (MCAs) that interface with neuronal cell properties and operate as acceptable pharmacophores for a novel neurotropic (neurite outgrowth inducing) lead compounds. Using an established PC12 cell bioassay, we investigated the neurotropic effect of methylene-cycloalkylacetate compounds by comparison to NGF, a known neurotropic factor. Micrographs of the cells were collected by using a light microscope camera, and digitized photographs were analyzed for compound-induced neurotropic activity using an NIH image protocol. The results indicate that the alkene element, integrated within the cycloalkylacetate core, is indispensable for neurotropic activity. The discovered lead compounds need further mechanistic investigation and may be improved toward development of a neurotropic drug.

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

NASA Astrophysics Data System (ADS)

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.

Cognitive Modeling for Agent-Based Simulation of Child Maltreatment

NASA Astrophysics Data System (ADS)

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.

Complex groundwater flow systems as traveling agent models

PubMed Central

Padilla, Pablo; Escolero, Oscar; González, Tomas; Morales-Casique, Eric; Osorio-Olvera, Luis

2014-01-01

Analyzing field data from pumping tests, we show that as with many other natural phenomena, groundwater flow exhibits complex dynamics described by 1/f power spectrum. This result is theoretically studied within an agent perspective. Using a traveling agent model, we prove that this statistical behavior emerges when the medium is complex. Some heuristic reasoning is provided to justify both spatial and dynamic complexity, as the result of the superposition of an infinite number of stochastic processes. Even more, we show that this implies that non-Kolmogorovian probability is needed for its study, and provide a set of new partial differential equations for groundwater flow. PMID:25337455

Method and reaction pathway for selectively oxidizing organic compounds

DOEpatents

Camaioni, Donald M.; Lilga, Michael A.

1998-01-01

A method of selectively oxidizing an organic compound in a single vessel comprises: a) combining an organic compound, an acid solution in which the organic compound is soluble, a compound containing two oxygen atoms bonded to one another, and a metal ion reducing agent capable of reducing one of such oxygen atoms, and thereby forming a mixture; b) reducing the compound containing the two oxygen atoms by reducing one of such oxygen atoms with the metal ion reducing agent to, 1) oxidize the metal ion reducing agent to a higher valence state, and 2) produce an oxygen containing intermediate capable of oxidizing the organic compound; c) reacting the oxygen containing intermediate with the organic compound to oxidize the organic compound into an oxidized organic intermediate, the oxidized organic intermediate having an oxidized carbon atom; d) reacting the oxidized organic intermediate with the acid counter ion and higher valence state metal ion to bond the acid counter ion to the oxidized carbon atom and thereby produce a quantity of an ester incorporating the organic intermediate and acid counter ion; and e) reacting the oxidized organic intermediate with the higher valence state metal ion and water to produce a quantity of alcohol which is less than the quantity of ester, the acid counter ion incorporated in the ester rendering the carbon atom bonded to the counter ion less reactive with the oxygen containing intermediate in the mixture than is the alcohol with the oxygen containing intermediate.

Synthetic iron complexes as models for natural iron-humic compounds: Synthesis, characterization and algal growth experiments.

PubMed

Orlowska, Ewelina; Roller, Alexander; Pignitter, Marc; Jirsa, Franz; Krachler, Regina; Kandioller, Wolfgang; Keppler, Bernhard K

2017-01-15

A series of monomeric and dimeric Fe III complexes with O,O-; O,N-; O,S-coordination motifs has been prepared and characterized by standard analytical methods in order to elucidate their potential to act as model compounds for aquatic humic acids. Due to the postulated reduction of iron in humic acids and following uptake by microorganisms, the redox behavior of the models was investigated with cyclic voltammetry. Most of the investigated compounds showed iron reduction potentials accessible to biological reducing agents. Additionally, observed reduction processes were predominantly irreversible, suggesting that subsequent reactions can take place after reduction of the iron center. Also the stability of the synthesized complexes in pure water and artificial seawater was monitored from 24h up to 21days by means of UV-Vis spectrometry. Several complexes remained stable even after 21days, showing only partially precipitation but some of them showed changes in UV-Vis spectra already after 24h which were connected to protonation/deprotonation processes as well as redox processes and degradation of the complexes. The ability to act as an iron source for primary producers was tested in algal growth experiments with two marine algae species Chlorella salina and Prymnesium parvum. Some of the compounds showed effects on the algal cultures, which are comparable with natural humic acids and better as for the samples kept under ideal conditions. Those findings help to understand which functional groups of humic acids could be responsible for the reversible iron binding and transport in aquatic humic substances. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Agent based modeling in tactical wargaming

NASA Astrophysics Data System (ADS)

James, Alex; Hanratty, Timothy P.; Tuttle, Daniel C.; Coles, John B.

2016-05-01

Army staffs at division, brigade, and battalion levels often plan for contingency operations. As such, analysts consider the impact and potential consequences of actions taken. The Army Military Decision-Making Process (MDMP) dictates identification and evaluation of possible enemy courses of action; however, non-state actors often do not exhibit the same level and consistency of planned actions that the MDMP was originally designed to anticipate. The fourth MDMP step is a particular challenge, wargaming courses of action within the context of complex social-cultural behaviors. Agent-based Modeling (ABM) and its resulting emergent behavior is a potential solution to model terrain in terms of the human domain and improve the results and rigor of the traditional wargaming process.

Identification of cancer specific ligands from one-bead one compound combinatorial libraries to develop theranostics agents against oral squamous cell carcinoma

NASA Astrophysics Data System (ADS)

Yang, Frances Fan

Background: Oral squamous cell carcinoma (OSCC) is one of the most prevalent disease worldwide. One-bead one-compound (OBOC) combinatorial technology is a powerful method to identify peptidomimetic ligands against a variety of receptors on cell surfaces. We therefore hypothesized that cancer specific ligands against OSCC might be identified and can be conjugated to optical dyes or nanocarriers to develop theranostic agents against OSCC. Material and methods: Different OSCC cell lines were incubated with OBOC libraries and beads with cell binding were sorted and then screened with normal human cells to identify peptide-beads binding to different OSCC cell lines but not binding to normal human cells. The molecular probes of OSCC were developed by biotinylating the carboxyl end of the ligands. OSCC theranostic agents were developed by decorating LLY13 with NPs and evaluated by using orthotopic bioluminescent oral cancer model. Results: Six OSCC specific ligands were discovered. Initial peptide-histochemistry study indicated that LLY12 and LLY13 were able to specifically detect OSCC cells grown on chamber slides at the concentration of 1 muM. In addition, LLY13 was found to penetrate into the OSCC cells and accumulate in the cytoplasm, and nucleus. After screened with a panel of integrin antibodies, only anti-alpha3 antibody was able to block most of OSCC cells binding to the LLY13 beads. OSCC theranostic agents developed using targeting LLY13 micelles (25+/- 4nm in diameter) were more efficient in binding to HSC-3 cancer cells compared to non-targeting micelles. Ex vivo images demonstrated that xenografts from the mice with targeting micelles appeared to have higher signals than the non-targeting groups. Conclusion: LLY13 has promising in vitro and in vivo targeting activity against OSCC. In addition, LLY13 is also able to penetrate into cancer cells via endocytosis. Initial study indicated that alpha3 integrin might partially be the corresponding receptor involved

An elemental model of retrospective revaluation without within-compound associations.

PubMed

Connor, Patrick C; Lolordo, Vincent M; Trappenberg, Thomas P

2014-03-01

When retrospective revaluation phenomena (e.g., unovershadowing: AB+, then A-, then test B) were discovered, simple elemental models were at a disadvantage because they could not explain such phenomena. Extensions of these models and novel models appealed to within-compound associations to accommodate these new data. Here, we present an elemental, neural network model of conditioning that explains retrospective revaluation apart from within-compound associations. In the model, previously paired stimuli (say, A and B, after AB+) come to activate similar ensembles of neurons, so that revaluation of one stimulus (A-) has the opposite effect on the other stimulus (B) through changes (decreases) in the strength of the inhibitory connections between neurons activated by B. The ventral striatum is discussed as a possible home for the structure and function of the present model.

Modeling the Biodegradability of Chemical Compounds Using the Online CHEmical Modeling Environment (OCHEM)

PubMed Central

Vorberg, Susann

2013-01-01

Abstract Biodegradability describes the capacity of substances to be mineralized by free‐living bacteria. It is a crucial property in estimating a compound’s long‐term impact on the environment. The ability to reliably predict biodegradability would reduce the need for laborious experimental testing. However, this endpoint is difficult to model due to unavailability or inconsistency of experimental data. Our approach makes use of the Online Chemical Modeling Environment (OCHEM) and its rich supply of machine learning methods and descriptor sets to build classification models for ready biodegradability. These models were analyzed to determine the relationship between characteristic structural properties and biodegradation activity. The distinguishing feature of the developed models is their ability to estimate the accuracy of prediction for each individual compound. The models developed using seven individual descriptor sets were combined in a consensus model, which provided the highest accuracy. The identified overrepresented structural fragments can be used by chemists to improve the biodegradability of new chemical compounds. The consensus model, the datasets used, and the calculated structural fragments are publicly available at http://ochem.eu/article/31660. PMID:27485201

Agent Based Modeling of Collaboration and Work Practices Onboard the International Space Station

NASA Technical Reports Server (NTRS)

Acquisti, Alessandro; Sierhuis, Maarten; Clancey, William J.; Bradshaw, Jeffrey M.; Shaffo, Mike (Technical Monitor)

2002-01-01

The International Space Station is one the most complex projects ever, with numerous interdependent constraints affecting productivity and crew safety. This requires planning years before crew expeditions, and the use of sophisticated scheduling tools. Human work practices, however, are difficult to study and represent within traditional planning tools. We present an agent-based model and simulation of the activities and work practices of astronauts onboard the ISS based on an agent-oriented approach. The model represents 'a day in the life' of the ISS crew and is developed in Brahms, an agent-oriented, activity-based language used to model knowledge in situated action and learning in human activities.

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

PubMed

Shinde, Snehal B; Kurhekar, Manish P

2018-06-01

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

iCrowd: agent-based behavior modeling and crowd simulator

NASA Astrophysics Data System (ADS)

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.

Benzofuran-pyran hybrids: A new class of potential bone anabolic agents.

PubMed

Gupta, Sampa; Adhikary, Sulekha; Modukuri, Ram K; Choudhary, Dharmendra; Trivedi, Ritu; Sashidhara, Koneni V

2018-06-01

Benzofuran moiety is an important pharmacophore showing positive effects on bone health. In the present study, sixteen benzofuran-pyran hybrids were synthesized and were evaluated for their osteogenic effects on primary osteoblast cells isolated from calvaria. Compounds 22 and 24 were found potent in stimulating osteoblast differentiation as assessed by the alkaline phosphatase activity. These compounds were also found to be nontoxic to osteoblast cells as compared to the control cells in MTT assay. Further, Alizarin Red-S staining for visualization of calcium nodules demonstrated compounds 22 and 34 as active in enhancing mineralization in osteoblast cells. Additionally, transcriptional analysis of these compounds on osteoblast cells revealed that compound 22 up-regulated the expression of osteogenic genes RUNX2, BMP-2, COL-1, thus substantiating that compound 22 having two geminal methyl groups in its R 3 position is a potent osteogenic agent. Additionally, compound 22 enhanced the ability of bone marrow stromal cells to differentiate towards osteoblast lineage and therefore can be further studied in vivo in bone loss model. Copyright © 2018 Elsevier Ltd. All rights reserved.

Biodegradation of coal-related model compounds. [C. versicolor

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

Campbell, J.A.; Stewart, D.L.; McCulloch, M.

1988-01-01

The details of the specific reactions of lignin biodegradation, and the biochemistry involved, have been primarily based on the use of low molecular weight compounds representing specific substructures rather than the complex, polymeric lignin material. The authors have studied the reactions of model compounds having coal-related functionalities (ester linkages, ether linkages, PAH) with the intact organisms, cell-free filtrate, and cell-free enzyme of C. versicolor to better understand the process of biosolubilization. Many of the degradation products have been identified by gas chromatography/mass spectrometry (GC/MS). Results are discussed.

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

NASA Astrophysics Data System (ADS)

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

2010-12-01

Agricultural watersheds are coupled human-natural systems where the land use decisions of human agents (farmers) affect surface water quality, and in turn, are affected by the weather and yields. The reliable modeling of such systems requires an approach that considers both the human and natural aspects. Agent-based modeling (ABM), representing the human aspect, coupled with hydrologic modeling, representing the natural aspect, is one such approach. ABM is a relatively new modeling paradigm that formulates the system from the perspectives of the individual agents, i.e., each agent is modeled as a discrete autonomous entity with distinct goals and actions. The primary objective of this study is to demonstrate the applicability of this approach to agricultural watershed management. This is done using a semi-hypothetical case study of farmers in the Salt Creek watershed in East-Central Illinois under the influence markets for carbon and second-generation bioenergy crop (specifically, miscanthus). An agent-based model of the system is developed and linked to a hydrologic model of the watershed. The former is based on fundamental economic and mathematical programming principles, while the latter is based on the Soil and Water Assessment Tool (SWAT). Carbon and second-generation bioenergy crop markets are of interest here due to climate change and energy independence concerns. The agent-based model is applied to fifty hypothetical heterogeneous farmers. The farmers' decisions depend on their perceptions of future conditions. Those perceptions are updated, according to a pre-defined algorithm, as the farmers make new observations of prices, costs, yields and the weather with time. The perceptions are also updated as the farmers interact with each other as they share new information on initially unfamiliar activities (e.g., carbon trading, miscanthus cultivation). The updating algorithm is set differently for different farmers such that each is unique in his processing of

An extensible simulation environment and movement metrics for testing walking behavior in agent-based models

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

Paul M. Torrens; Atsushi Nara; Xun Li

2012-01-01

Human movement is a significant ingredient of many social, environmental, and technical systems, yet the importance of movement is often discounted in considering systems complexity. Movement is commonly abstracted in agent-based modeling (which is perhaps the methodological vehicle for modeling complex systems), despite the influence of movement upon information exchange and adaptation in a system. In particular, agent-based models of urban pedestrians often treat movement in proxy form at the expense of faithfully treating movement behavior with realistic agency. There exists little consensus about which method is appropriate for representing movement in agent-based schemes. In this paper, we examine popularly-usedmore » methods to drive movement in agent-based models, first by introducing a methodology that can flexibly handle many representations of movement at many different scales and second, introducing a suite of tools to benchmark agent movement between models and against real-world trajectory data. We find that most popular movement schemes do a relatively poor job of representing movement, but that some schemes may well be 'good enough' for some applications. We also discuss potential avenues for improving the representation of movement in agent-based frameworks.« less

Agent-Based Computational Modeling of Cell Culture ...

EPA Pesticide Factsheets

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

[Gadolinium-based contrast agents for magnetic resonance imaging].

PubMed

Carrasco Muñoz, S; Calles Blanco, C; Marcin, Javier; Fernández Álvarez, C; Lafuente Martínez, J

2014-06-01

Gadolinium-based contrast agents are increasingly being used in magnetic resonance imaging. These agents can improve the contrast in images and provide information about function and metabolism, increasing both sensitivity and specificity. We describe the gadolinium-based contrast agents that have been approved for clinical use, detailing their main characteristics based on their chemical structure, stability, and safety. In general terms, these compounds are safe. Nevertheless, adverse reactions, the possibility of nephrotoxicity from these compounds, and the possibility of developing nephrogenic systemic fibrosis will be covered in this article. Lastly, the article will discuss the current guidelines, recommendations, and contraindications for their clinical use, including the management of pregnant and breast-feeding patients. Copyright © 2014 SERAM. Published by Elsevier Espana. All rights reserved.

Effect of mechanical damage on emission of volatile organic compounds from plant leaves and implications for evaluation of host plant specificity of prospective biological control agents of weeds

USDA-ARS?s Scientific Manuscript database

Assessment of host plant specificity is a critical step in the evaluation of classical biological control agents of weeds, which is necessary for avoiding possible damage to nontarget plants. Volatile organic compounds (VOC) emitted by plants likely play an important role in determining which plant...

[Supramolecular Agents for Theranostics].

PubMed

Deyev, S M; Lebedenko, E N

2015-01-01

This mini-review summarizes recent data obtained in the process of creation of a versatile module platform suitable for construction of supramolecular theranostic agents. As an example, we consider multifunctional hybrid agents for imaging and elimination of cancer cells. The use of an adapter protein system barnase:barstar for producing targeted multifunctional hybrid structures on the basis of highly specific peptides and mini-antibodies as addressing modules and recombinant proteins and/or nanoparticles of different nature (quantum dots, nanogold, magnetic nanoparticles, nanodiamonds, upconverting nanophosphores, polymer nanoparticles) as agents visualizing and damaging cancer cells is described. New perspectives for creation of selective and highly effective compounds for theranostics and personified medicine are contemplated.

Reducing the Complexity of an Agent-Based Local Heroin Market Model

PubMed Central

Heard, Daniel; Bobashev, Georgiy V.; Morris, Robert J.

2014-01-01

This project explores techniques for reducing the complexity of an agent-based model (ABM). The analysis involved a model developed from the ethnographic research of Dr. Lee Hoffer in the Larimer area heroin market, which involved drug users, drug sellers, homeless individuals and police. The authors used statistical techniques to create a reduced version of the original model which maintained simulation fidelity while reducing computational complexity. This involved identifying key summary quantities of individual customer behavior as well as overall market activity and replacing some agents with probability distributions and regressions. The model was then extended to allow external market interventions in the form of police busts. Extensions of this research perspective, as well as its strengths and limitations, are discussed. PMID:25025132

An In Ovo Model for Testing Insulin-mimetic Compounds.

PubMed

Haselgrübler, Renate; Stübl, Flora; Stadlbauer, Verena; Lanzerstorfer, Peter; Weghuber, Julian

2018-04-23

Elevated blood glucose levels in type 2 diabetes mellitus (T2DM), a complex and multifactorial metabolic disease, are caused by insulin resistance and β-cell failure. Various strategies, including the injection of insulin or the usage of insulin-sensitizing drugs, were pursued to treat T2DM or at least reduce the symptoms. In addition, the application of herbal compounds has attracted increasing attention. Thus, it is necessary to find efficient test systems to identify and characterize insulin-mimetic compounds. Here we developed a modified chick embryo model, which enables testing of synthetic compounds and herbal extracts with insulin-mimetic properties. Using a fluorescence microscopy-based primary screen, which quantifies the translocation of Glucose transporter 4 (Glut4) to the plasma membrane, we were able to identify compounds, mainly herbal extracts, which lead to an increase of intracellular glucose concentrations in adipocytes. However, the efficacy of these substances requires further verification in a living organism. Thus, we used an in-ovo approach to identify their blood glucose-reducing properties. The approval by an ethics committee is not needed since the use of chicken embryos during the first two-thirds of embryonic development is not considered an animal experiment. Here, the application of this model is described in detail.

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

PubMed

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

2016-12-01

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

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

PubMed

Marshall, Brandon D L; Galea, Sandro

2015-01-15

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

New p-methylsulfonamido phenylethylamine analogues as class III antiarrhythmic agents: design, synthesis, biological assay, and 3D-QSAR analysis.

PubMed

Liu, Hong; Ji, Ming; Luo, Xiaomin; Shen, Jianhua; Huang, Xiaoqin; Hua, Weiyi; Jiang, Hualiang; Chen, Kaixian

2002-07-04

Class III antiarrhythmic agents selectively delay the effective refractory period (ERP) and increase the transmembrane action potential duration (APD). Using dofetilide (2) as a template of class III antiarrhythmic agents, we designed and synthesized 16 methylsulfonamido phenylethylamine analogues (4a-d and 5a-l). Pharmacological assay indicated that all of these compounds showed activity for increasing the ERP in isolated animal atrium; among them, the effective concentration of compound 4a is 1.6 x 10(-8) mol/L in increasing ERP by 10 ms, slightly less potent than that of 2, 1.1 x 10(-8) mol/L. Compound 4a also produced a slightly lower change in ERP at 10(-5) M, DeltaERP% = 17.5% (DeltaERP% = 24.0% for dofetilide). On the basis of this bioassay result, these 16 compounds together with dofetilide were investigated by the three-dimensional quantitative structure-activity relationship (3D-QSAR) techniques of comparative molecular field analysis (CoMFA), comparative molecular similarity index analysis (CoMSIA), and the hologram QSAR (HQSAR). The 3D-QSAR models were tested with another 11 compounds (4e-h and 5m-s) that we synthesized later. Results revealed that the CoMFA, CoMSIA, and HQSAR predicted activities for the 11 newly synthesized compounds that have a good correlation with their experimental value, r(2) = 0.943, 0.891, and 0.809 for the three QSAR models, respectively. This indicates that the 3D-QSAR models proved a good predictive ability and could describe the steric, electrostatic, and hydrophobic requirements for recognition forces of the receptor site. On the basis of these results, we designed and synthesized another eight new analogues of methanesulfonamido phenylethyamine (6a-h) according to the clues provided by the 3D-QSAR analyses. Pharmacological assay indicated that the effective concentrations of delaying the ERP by 10 ms of these newly designed compounds correlated well with the 3D-QSAR predicted values. It is remarkable that the percent

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

PubMed Central

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

2015-01-01

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. PMID:27158257

Deduction of initial strategy distributions of agents in mix-game models

NASA Astrophysics Data System (ADS)

Gou, Chengling

2006-11-01

This paper reports the effort of deducing the initial strategy distributions (ISDs) of agents in mix-game models that is used to predict a real financial time series generated from a target financial market. Using mix-games to predict Shanghai Index, we find that the time series of prediction accurate rates is sensitive to the ISDs of agents in group 2 who play a minority game, but less sensitive to the ISDs of agents in group 1 who play a majority game. And agents in group 2 tend to cluster in full strategy space (FSS) if the real financial time series has obvious tendency (upward or downward), otherwise they tend to scatter in FSS. We also find that the ISDs and the number of agents in group 1 influence the level of prediction accurate rates. Finally, this paper gives suggestion about further research.

Cyanobacteria as a Source for Novel Anti-Leukemic Compounds.

PubMed

Humisto, Anu; Herfindal, Lars; Jokela, Jouni; Karkman, Antti; Bjørnstad, Ronja; Choudhury, Romi R; Sivonen, Kaarina

2016-01-01

Cyanobacteria are an inspiring source of bioactive secondary metabolites. These bioactive agents are a diverse group of compounds which are varying in their bioactive targets, the mechanisms of action, and chemical structures. Cyanobacteria from various environments, especially marine benthic cyanobacteria, are found to be rich sources for the search for novel bioactive compounds. Several compounds with anticancer activities have been discovered from cyanobacteria and some of these have succeeded to enter the clinical trials. Varying anticancer agents are needed to overcome increasing challenges in cancer treatments. Different search methods are used to reveal anticancer compounds from natural products, but cell based methods are the most common. Cyanobacterial bioactive compounds as agents against acute myeloid leukemia are not well studied. Here we examined our new results combined with previous studies of anti-leukemic compounds from cyanobacteria with emphasis to reveal common features in strains producing such activity. We report that cyanobacteria harbor specific anti-leukemic compounds since several studied strains induced apoptosis against AML cells but were inactive against non-malignant cells like hepatocytes. We noted that particularly benthic strains from the Baltic Sea, such as Anabaena sp., were especially potential AML apoptosis inducers. Taken together, this review and re-analysis of data demonstrates the power of maintaining large culture collections for the search for novel bioactivities, and also how anti-AML activity in cyanobacteria can be revealed by relatively simple and low-cost assays.

Structural estimation of a principal-agent model: moral hazard in medical insurance.

PubMed

Vera-Hernández, Marcos

2003-01-01

Despite the importance of principal-agent models in the development of modern economic theory, there are few estimations of these models. I recover the estimates of a principal-agent model and obtain an approximation to the optimal contract. The results show that out-of-pocket payments follow a concave profile with respect to costs of treatment. I estimate the welfare loss due to moral hazard, taking into account income effects. I also propose a new measure of moral hazard based on the conditional correlation between contractible and noncontractible variables.

An ambient agent model for analyzing managers' performance during stress

NASA Astrophysics Data System (ADS)

ChePa, Noraziah; Aziz, Azizi Ab; Gratim, Haned

2016-08-01

Stress at work have been reported everywhere. Work related performance during stress is a pattern of reactions that occurs when managers are presented with work demands that are not matched with their knowledge, skills, or abilities, and which challenge their ability to cope. Although there are many prior findings pertaining to explain the development of manager performance during stress, less attention has been given to explain the same concept through computational models. In such, a descriptive nature in psychological theories about managers' performance during stress can be transformed into a causal-mechanistic stage that explains the relationship between a series of observed phenomena. This paper proposed an ambient agent model for analyzing managers' performance during stress. Set of properties and variables are identified through past literatures to construct the model. Differential equations have been used in formalizing the model. Set of equations reflecting relations involved in the proposed model are presented. The proposed model is essential and can be encapsulated within an intelligent agent or robots that can be used to support managers during stress.

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

PubMed

Evans, Tom P; Kelley, Hugh

2004-08-01

Scale issues have significant implications for the analysis of social and biophysical processes in complex systems. These same scale implications are likewise considerations for the design and application of models of landcover change. Scale issues have wide-ranging effects from the representativeness of data used to validate models to aggregation errors introduced in the model structure. This paper presents an analysis of how scale issues affect an agent-based model (ABM) of landcover change developed for a research area in the Midwest, USA. The research presented here explores how scale factors affect the design and application of agent-based landcover change models. The ABM is composed of a series of heterogeneous agents who make landuse decisions on a portfolio of cells in a raster-based programming environment. The model is calibrated using measures of fit derived from both spatial composition and spatial pattern metrics from multi-temporal landcover data interpreted from historical aerial photography. A model calibration process is used to find a best-fit set of parameter weights assigned to agents' preferences for different landuses (agriculture, pasture, timber production, and non-harvested forest). Previous research using this model has shown how a heterogeneous set of agents with differing preferences for a portfolio of landuses produces the best fit to landcover changes observed in the study area. The scale dependence of the model is explored by varying the resolution of the input data used to calibrate the model (observed landcover), ancillary datasets that affect land suitability (topography), and the resolution of the model landscape on which agents make decisions. To explore the impact of these scale relationships the model is run with input datasets constructed at the following spatial resolutions: 60, 90, 120, 150, 240, 300 and 480 m. The results show that the distribution of landuse-preference weights differs as a function of scale. In addition

Highly sweet compounds of plant origin.

PubMed

Kim, Nam-Cheol; Kinghorn, A Douglas

2002-12-01

The demand for new alternative "low calorie" sweeteners for dietetic and diabetic purposes has increased worldwide. Although the currently developed and commercially used highly sweet sucrose substitutes are mostly synthetic compounds, the search for such compounds from natural sources is continuing. As of mid-2002, over 100 plant-derived sweet compounds of 20 major structural types had been reported, and were isolated from more than 25 different families of green plants. Several of these highly sweet natural products are marketed as sweeteners or flavoring agents in some countries as pure compounds, compound mixtures, or refined extracts. These highly sweet natural substances are reviewed herein.

Devices for collecting chemical compounds

DOEpatents

Scott, Jill R; Groenewold, Gary S

2013-12-24

A device for sampling chemical compounds from fixed surfaces and related methods are disclosed. The device may include a vacuum source, a chamber and a sorbent material. The device may utilize vacuum extraction to volatilize the chemical compounds from a fixed surface so that they may be sorbed by the sorbent material. The sorbent material may then be analyzed using conventional thermal desorption/gas chromatography/mass spectrometry (TD/GC/MS) instrumentation to determine presence of the chemical compounds. The methods may include detecting release and presence of one or more chemical compounds and determining the efficacy of decontamination. The device may be useful in collection and analysis of a variety of chemical compounds, such as residual chemical warfare agents, chemical attribution signatures and toxic industrial chemicals.

Agents, Bayes, and Climatic Risks - a modular modelling approach

NASA Astrophysics Data System (ADS)

Haas, A.; Jaeger, C.

2005-08-01

When insurance firms, energy companies, governments, NGOs, and other agents strive to manage climatic risks, it is by no way clear what the aggregate outcome should and will be. As a framework for investigating this subject, we present the LAGOM model family. It is based on modules depicting learning social agents. For managing climate risks, our agents use second order probabilities and update them by means of a Bayesian mechanism while differing in priors and risk aversion. The interactions between these modules and the aggregate outcomes of their actions are implemented using further modules. The software system is implemented as a series of parallel processes using the CIAMn approach. It is possible to couple modules irrespective of the language they are written in, the operating system under which they are run, and the physical location of the machine.

Survey of Chemical Compounds Tested In Vitro against Rumen Protozoa for Possible Control of Bloat

PubMed Central

Willard, F. L.; Kodras, Rudolph

1967-01-01

Over 170 chemical agents were screened for antiprotozoal action in bovine ruminal fluid. Compounds were tested at 0.1 and 0.05% concentrations. Tested compounds included inorganic compounds, antibiotics, biocides, neuromuscular agents, arsenicals, plant and animal hormones, antimalarials, surface-active agents, anthelmintics, and many others. The most active compounds were cupric sulfate, nickel sulfate, nitrofurazone, hydrogen peroxide, dodecyl sodium sulfate, pelargonic acid, iodoacetic acid, 1-diethylaminoethylamino-4-methylthiaxanthrone, sodium arsanilate, sodium arsenate, bismuth glycolyl arsanilate, 1-β-hydroxyethyl-2-methyl-5-nitroimidazole, and p-nitroaniline. Copper ion was not particularly effective against entodinia; nickel ion had no effect on holotrichs. Hydrogen peroxide and iodoacetic acid were effective at a concentration of 0.005%. Anionic surface-active agents were very effective, especially long-chain sulfates and phosphates. These antiprotozoal agents warrant further in vivo studies for possible use in treating or curing bloat in ruminants. PMID:6077407

Survey of chemical compounds tested in vitro against rumen protozoa for possible control of bloat.

PubMed

Willard, F L; Kodras, R

1967-09-01

Over 170 chemical agents were screened for antiprotozoal action in bovine ruminal fluid. Compounds were tested at 0.1 and 0.05% concentrations. Tested compounds included inorganic compounds, antibiotics, biocides, neuromuscular agents, arsenicals, plant and animal hormones, antimalarials, surface-active agents, anthelmintics, and many others. The most active compounds were cupric sulfate, nickel sulfate, nitrofurazone, hydrogen peroxide, dodecyl sodium sulfate, pelargonic acid, iodoacetic acid, 1-diethylaminoethylamino-4-methylthiaxanthrone, sodium arsanilate, sodium arsenate, bismuth glycolyl arsanilate, 1-beta-hydroxyethyl-2-methyl-5-nitroimidazole, and p-nitroaniline. Copper ion was not particularly effective against entodinia; nickel ion had no effect on holotrichs. Hydrogen peroxide and iodoacetic acid were effective at a concentration of 0.005%. Anionic surface-active agents were very effective, especially long-chain sulfates and phosphates. These antiprotozoal agents warrant further in vivo studies for possible use in treating or curing bloat in ruminants.

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

NASA Technical Reports Server (NTRS)

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

2010-01-01

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

Multi-agent simulation of the von Thunen model formation mechanism

NASA Astrophysics Data System (ADS)

Tao, Haiyan; Li, Xia; Chen, Xiaoxiang; Deng, Chengbin

2008-10-01

This research tries to explain the internal driving forces of circular structure formation in urban geography via the simulation of interaction between individual behavior and market. On the premise of single city center, unchanged scale merit and complete competition, enterprise migration theory as well, an R-D algorithm, that has agents searched the best behavior rules in some given locations, is introduced with agent-based modeling technique. The experiment conducts a simulation on Swarm platform, whose result reflects and replays the formation process of Von Thünen circular structure. Introducing and considering some heterogeneous factors, such as traffic roads, the research verifies several landuse models and discusses the self-adjustment function of price mechanism.

Evolutionary Agent-based Models to design distributed water management strategies

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

QSAR modeling and chemical space analysis of antimalarial compounds

NASA Astrophysics Data System (ADS)

Sidorov, Pavel; Viira, Birgit; Davioud-Charvet, Elisabeth; Maran, Uko; Marcou, Gilles; Horvath, Dragos; Varnek, Alexandre

2017-05-01

Generative topographic mapping (GTM) has been used to visualize and analyze the chemical space of antimalarial compounds as well as to build predictive models linking structure of molecules with their antimalarial activity. For this, a database, including 3000 molecules tested in one or several of 17 anti- Plasmodium activity assessment protocols, has been compiled by assembling experimental data from in-house and ChEMBL databases. GTM classification models built on subsets corresponding to individual bioassays perform similarly to the earlier reported SVM models. Zones preferentially populated by active and inactive molecules, respectively, clearly emerge in the class landscapes supported by the GTM model. Their analysis resulted in identification of privileged structural motifs of potential antimalarial compounds. Projection of marketed antimalarial drugs on this map allowed us to delineate several areas in the chemical space corresponding to different mechanisms of antimalarial activity. This helped us to make a suggestion about the mode of action of the molecules populating these zones.

QSAR modeling and chemical space analysis of antimalarial compounds.

PubMed

Sidorov, Pavel; Viira, Birgit; Davioud-Charvet, Elisabeth; Maran, Uko; Marcou, Gilles; Horvath, Dragos; Varnek, Alexandre

2017-05-01

Generative topographic mapping (GTM) has been used to visualize and analyze the chemical space of antimalarial compounds as well as to build predictive models linking structure of molecules with their antimalarial activity. For this, a database, including ~3000 molecules tested in one or several of 17 anti-Plasmodium activity assessment protocols, has been compiled by assembling experimental data from in-house and ChEMBL databases. GTM classification models built on subsets corresponding to individual bioassays perform similarly to the earlier reported SVM models. Zones preferentially populated by active and inactive molecules, respectively, clearly emerge in the class landscapes supported by the GTM model. Their analysis resulted in identification of privileged structural motifs of potential antimalarial compounds. Projection of marketed antimalarial drugs on this map allowed us to delineate several areas in the chemical space corresponding to different mechanisms of antimalarial activity. This helped us to make a suggestion about the mode of action of the molecules populating these zones.

SEPARATION PROCESS FOR TRANSURANIC ELEMENT AND COMPOUNDS THEREOF

DOEpatents

Magnusson, L.B.

1958-04-01

A process is described for the separation of neptunium, from aqueous solutions of neptunium, plutonium, uraniunn, and fission prcducts. This separation from an acidic aqueous solution of a tetravalent neptuniunn can be made by contacting the solution with a certain type of chelating,; agent, preferably dissolved in an organic solvent, to form a neptunium chelate compound. When the organic solvent is present, the neptunium chelate compound is extracted; otherwise, it precipitates from the aqueous solution and is separated by any suitable means. The chelating agent is a fluorinated BETA -diketone. such as trifluoroacetyl acetone.

Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds

PubMed Central

Alves, Vinicius M.; Muratov, Eugene; Fourches, Denis; Strickland, Judy; Kleinstreuer, Nicole; Andrade, Carolina H.; Tropsha, Alexander

2015-01-01

Repetitive exposure to a chemical agent can induce an immune reaction in inherently susceptible individuals that leads to skin sensitization. Although many chemicals have been reported as skin sensitizers, there have been very few rigorously validated QSAR models with defined applicability domains (AD) that were developed using a large group of chemically diverse compounds. In this study, we have aimed to compile, curate, and integrate the largest publicly available dataset related to chemically-induced skin sensitization, use this data to generate rigorously validated and QSAR models for skin sensitization, and employ these models as a virtual screening tool for identifying putative sensitizers among environmental chemicals. We followed best practices for model building and validation implemented with our predictive QSAR workflow using random forest modeling technique in combination with SiRMS and Dragon descriptors. The Correct Classification Rate (CCR) for QSAR models discriminating sensitizers from non-sensitizers were 71–88% when evaluated on several external validation sets, within a broad AD, with positive (for sensitizers) and negative (for non-sensitizers) predicted rates of 85% and 79% respectively. When compared to the skin sensitization module included in the OECD QSAR toolbox as well as to the skin sensitization model in publicly available VEGA software, our models showed a significantly higher prediction accuracy for the same sets of external compounds as evaluated by Positive Predicted Rate, Negative Predicted Rate, and CCR. These models were applied to identify putative chemical hazards in the ScoreCard database of possible skin or sense organ toxicants as primary candidates for experimental validation. PMID:25560674

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

PubMed

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

2014-01-01

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

Information of Complex Systems and Applications in Agent Based Modeling.

PubMed

Bao, Lei; Fritchman, Joseph C

2018-04-18

Information about a system's internal interactions is important to modeling the system's dynamics. This study examines the finer categories of the information definition and explores the features of a type of local information that describes the internal interactions of a system. Based on the results, a dual-space agent and information modeling framework (AIM) is developed by explicitly distinguishing an information space from the material space. The two spaces can evolve both independently and interactively. The dual-space framework can provide new analytic methods for agent based models (ABMs). Three examples are presented including money distribution, individual's economic evolution, and artificial stock market. The results are analyzed in the dual-space, which more clearly shows the interactions and evolutions within and between the information and material spaces. The outcomes demonstrate the wide-ranging applicability of using the dual-space AIMs to model and analyze a broad range of interactive and intelligent systems.

Marine compounds with therapeutic potential in gram-negative sepsis.

PubMed

Solov'eva, Tamara; Davydova, Viktoria; Krasikova, Inna; Yermak, Irina

2013-06-19

This paper concerns the potential use of compounds, including lipid A, chitosan, and carrageenan, from marine sources as agents for treating endotoxemic complications from Gram-negative infections, such as sepsis and endotoxic shock. Lipid A, which can be isolated from various species of marine bacteria, is a potential antagonist of bacterial endotoxins (lipopolysaccharide (LPSs)). Chitosan is a widespread marine polysaccharide that is derived from chitin, the major component of crustacean shells. The potential of chitosan as an LPS-binding and endotoxin-neutralizing agent is also examined in this paper, including a discussion on the generation of hydrophobic chitosan derivatives to increase the binding affinity of chitosan to LPS. In addition, the ability of carrageenan, which is the polysaccharide of red alga, to decrease the toxicity of LPS is discussed. We also review data obtained using animal models that demonstrate the potency of carrageenan and chitosan as antiendotoxin agents.

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

NASA Astrophysics Data System (ADS)

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.

Computational Models of the Representation of Bangla Compound Words in the Mental Lexicon.

PubMed

Dasgupta, Tirthankar; Sinha, Manjira; Basu, Anupam

2016-08-01

In this paper we aim to model the organization and processing of Bangla compound words in the mental lexicon. Our objective is to determine whether the mental lexicon access a Bangla compound word as a whole or decomposes the whole word into its constituent morphemes and then recognize them accordingly. To address this issue, we adopted two different strategies. First, we conduct a cross-modal priming experiment over a number of native speakers. Analysis of reaction time (RT) and error rates indicates that in general, Bangla compound words are accessed via partial decomposition process. That is some word follows full-listing mode of representation and some words follow the decomposition route of representation. Next, based on the collected RT data we have developed a computational model that can explain the processing phenomena of the access and representation of Bangla compound words. In order to achieve this, we first explored the individual roles of head word position, morphological complexity, orthographic transparency and semantic compositionality between the constituents and the whole compound word. Accordingly, we have developed a complexity based model by combining these features together. To a large extent we have successfully explained the possible processing phenomena of most of the Bangla compound words. Our proposed model shows an accuracy of around 83 %.

Selective Oxidation of Lignin Model Compounds.

PubMed

Gao, Ruili; Li, Yanding; Kim, Hoon; Mobley, Justin K; Ralph, John

2018-05-02

Lignin, the planet's most abundant renewable source of aromatic compounds, is difficult to degrade efficiently to welldefined aromatics. We developed a microwave-assisted catalytic Swern oxidation system using an easily prepared catalyst, MoO 2 Cl 2 (DMSO) 2 , and DMSO as the solvent and oxidant. It demonstrated high efficiency in transforming lignin model compounds containing the units and functional groups found in native lignins. The aromatic ring substituents strongly influenced the selectivity of β-ether phenolic dimer cleavage to generate sinapaldehyde and coniferaldehyde, monomers not usually produced by oxidative methods. Time-course studies on two key intermediates provided insight into the reaction pathway. Owing to the broad scope of this oxidation system and the insight gleaned with regard to its mechanism, this strategy could be adapted and applied in a general sense to the production of useful aromatic chemicals from phenolics and lignin. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

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

NASA Technical Reports Server (NTRS)

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.

IPA (v1): a framework for agent-based modelling of soil water movement

NASA Astrophysics Data System (ADS)

Mewes, Benjamin; Schumann, Andreas H.

2018-06-01

In the last decade, agent-based modelling (ABM) became a popular modelling technique in social sciences, medicine, biology, and ecology. ABM was designed to simulate systems that are highly dynamic and sensitive to small variations in their composition and their state. As hydrological systems, and natural systems in general, often show dynamic and non-linear behaviour, ABM can be an appropriate way to model these systems. Nevertheless, only a few studies have utilized the ABM method for process-based modelling in hydrology. The percolation of water through the unsaturated soil is highly responsive to the current state of the soil system; small variations in composition lead to major changes in the transport system. Hence, we present a new approach for modelling the movement of water through a soil column: autonomous water agents that transport water through the soil while interacting with their environment as well as with other agents under physical laws.

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

NASA Astrophysics Data System (ADS)

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

New Therapeutic Agent against Arterial Thrombosis: An Iridium(III)-Derived Organometallic Compound.

PubMed

Hsia, Chih-Wei; Velusamy, Marappan; Tsao, Jeng-Ting; Hsia, Chih-Hsuan; Chou, Duen-Suey; Jayakumar, Thanasekaran; Lee, Lin-Wen; Li, Jiun-Yi; Sheu, Joen-Rong

2017-12-05

Platelet activation plays a major role in cardio and cerebrovascular diseases, and cancer progression. Disruption of platelet activation represents an attractive therapeutic target for reducing the bidirectional cross talk between platelets and tumor cells. Platinum (Pt) compounds have been used for treating cancer. Hence, replacing Pt with iridium (Ir) is considered a potential alternative. We recently developed an Ir(III)-derived complex, [Ir(Cp*)1-(2-pyridyl)-3-(2-hydroxyphenyl)imidazo[1,5-a]pyridine Cl]BF₄ (Ir-11), which exhibited strong antiplatelet activity; hence, we assessed the therapeutic potential of Ir-11 against arterial thrombosis. In collagen-activated platelets, Ir-11 inhibited platelet aggregation, adenosine triphosphate (ATP) release, intracellular Ca 2+ mobilization, P-selectin expression, and OH · formation, as well as the phosphorylation of phospholipase Cγ2 (PLCγ2), protein kinase C (PKC), mitogen-activated protein kinases (MAPKs), and Akt. Neither the adenylate cyclase inhibitor nor the guanylate cyclase inhibitor reversed the Ir-11-mediated antiplatelet effects. In experimental mice, Ir-11 prolonged the bleeding time and reduced mortality associated with acute pulmonary thromboembolism. Ir-11 plays a crucial role by inhibiting platelet activation through the inhibition of the PLCγ2-PKC cascade, and the subsequent suppression of Akt and MAPK activation, ultimately inhibiting platelet aggregation. Therefore, Ir-11 can be considered a new therapeutic agent against either arterial thrombosis or the bidirectional cross talk between platelets and tumor cells.

Soft antimicrobial agents: synthesis and activity of labile environmentally friendly long chain quaternary ammonium compounds.

PubMed

Thorsteinsson, Thorsteinn; Másson, Már; Kristinsson, Karl G; Hjálmarsdóttir, Martha A; Hilmarsson, Hilmar; Loftsson, Thorsteinn

2003-09-11

A series of soft quaternary ammonium antimicrobial agents, which are analogues to currently used quaternary ammonium preservatives such as cetyl pyridinium chloride and benzalkonium chloride, were synthesized. These soft analogues consist of long alkyl chain connected to a polar headgroup via chemically labile spacer group. They are characterized by facile nonenzymatic and enzymatic degradation to form their original nontoxic building blocks. However, their chemical stability has to be adequate in order for them to have antimicrobial effects. Stability studies and antibacterial and antiviral activity measurements revealed relationship between activity, lipophilicity, and stability. Their minimum inhibitory concentration (MIC) was as low as 1 microg/mL, and their viral reduction was in some cases greater than 6.7 log. The structure-activity studies demonstrate that the bioactive compounds (i.e., MIC for Gram-positive bacteria of <10 microg/mL) have an alkyl chain length between 12 and 18 carbon atoms, with a polar headgroup preferably of a small quaternary ammonium group, and their acquired inactivation half-life must be greater than 3 h at 60 degrees C.

Assessing Uncertainty of Interspecies Correlation Estimation Models for Aromatic Compounds

EPA Science Inventory

We developed Interspecies Correlation Estimation (ICE) models for aromatic compounds containing 1 to 4 benzene rings to assess uncertainty in toxicity extrapolation in two data compilation approaches. ICE models are mathematical relationships between surrogate and predicted test ...

Hydrolysis of Nerve Agents by Model Nucleophiles: A Computational Study

PubMed Central

Beck, Jeremy M.

2008-01-01

Density functional theory calculations were employed to study the reaction of five nerve agents with model nucleophiles, including EtX− and EtXH (X = O, S, Se) for serine, cysteine and selenocysteine, respectively. Calculations at the B3LYP/6-311++G(2d,p) level of theory predict an exothermic reaction between ethoxide and all of the nerve agents studied. As compared to EtO− as a nucleophile, these reactions become ~30 kcal/mol more endothermic for EtS−, and by ~40 kcal/mol for EtSe−. The equivalent reactions with the neutral nucleophiles (EtXH) were more endothermic. The effect of solvation on the reaction thermochemistry was determined using a polarizable continuum model simulating the dielectric constant of chloroform. While there was a large exothermic shift for reactions involving charged nucleophiles with solvation modeling, the corresponding shift was minimal for the reaction with neutral nucleophiles. PMID:18538754

Facile synthesis and biological evaluation of novel symmetrical biphenyls as antitumor agents.

PubMed

Zhang, Jie; Zhang, Yanmin; Pan, Xiaoyan; Wang, Chen; Hu, Zhigang; Wang, Sicen; He, Langchong

2012-03-01

As a continuation to our previous work in developing anticancer agents, eighteen symmetrical biphenyl derivatives structurally related to taspine were synthesized and evaluated in vitro and in vivo. All the compounds were prepared with varied substitutions in the phenyl ring of aniline moiety. The cytotoxicity and anticancer activity of biphenyls was evaluated against various human tumor and normal cell line. Antiproliferative assays indicated that some of them exhibited potent anticancer activity. The potent antiproliferative activity of these compounds against ECV304 suggested that these biphenyls could be served as antiangiogenic agents. The highly active compound (2) also exhibited potent growth inhibition against cancer cell lines in vivo. Our findings demonstrated that these symmetrical biphenyl derivatives would be a promising candidate as novel anticancer agents.

Laccase-mediator catalyzed conversion of model lignin compounds

USDA-ARS?s Scientific Manuscript database

Laccases play an important role in the biological breakdown of lignin and have great potential in the deconstruction of lignocellulosic feedstocks. We examined a variety of laccases, both commercially prepared and crude extracts, for their ability to oxidize three model lignol compounds (p-coumaryl...

Modeling Multi-Agent Self-Organization through the Lens of Higher Order Attractor Dynamics.

PubMed

Butner, Jonathan E; Wiltshire, Travis J; Munion, A K

2017-01-01

Social interaction occurs across many time scales and varying numbers of agents; from one-on-one to large-scale coordination in organizations, crowds, cities, and colonies. These contexts, are characterized by emergent self-organization that implies higher order coordinated patterns occurring over time that are not due to the actions of any particular agents, but rather due to the collective ordering that occurs from the interactions of the agents. Extant research to understand these social coordination dynamics (SCD) has primarily examined dyadic contexts performing rhythmic tasks. To advance this area of study, we elaborate on attractor dynamics, our ability to depict them visually, and quantitatively model them. Primarily, we combine difference/differential equation modeling with mixture modeling as a way to infer the underlying topological features of the data, which can be described in terms of attractor dynamic patterns. The advantage of this approach is that we are able to quantify the self-organized dynamics that agents exhibit, link these dynamics back to activity from individual agents, and relate it to other variables central to understanding the coordinative functionality of a system's behavior. We present four examples that differ in the number of variables used to depict the attractor dynamics (1, 2, and 6) and range from simulated to non-simulated data sources. We demonstrate that this is a flexible method that advances scientific study of SCD in a variety of multi-agent systems.

Examining the Impact of the Walking School Bus With an Agent-Based Model

PubMed Central

Diez-Roux, Ana; Evenson, Kelly R.; Colabianchi, Natalie

2014-01-01

We used an agent-based model to examine the impact of the walking school bus (WSB) on children’s active travel to school. We identified a synergistic effect of the WSB with other intervention components such as an educational campaign designed to improve attitudes toward active travel to school. Results suggest that to maximize active travel to school, children should arrive on time at “bus stops” to allow faster WSB walking speeds. We also illustrate how an agent-based model can be used to identify the location of routes maximizing the effects of the WSB on active travel. Agent-based models can be used to examine plausible effects of the WSB on active travel to school under various conditions and to identify ways of implementing the WSB that maximize its effectiveness. PMID:24832410

Dynamical systems approach to the study of a sociophysics agent-based model

NASA Astrophysics Data System (ADS)

Timpanaro, André M.; Prado, Carmen P. C.

2011-03-01

The Sznajd model is a Potts-like model that has been studied in the context of sociophysics [1,2] (where spins are interpreted as opinions). In a recent work [3], we generalized the Sznajd model to include assymetric interactions between the spins (interpreted as biases towards opinions) and used dynamical systems techniques to tackle its mean-field version, given by the flow: ησ = ∑ σ' = 1Mησησ'(ησρσ'→σ-σ'ρσ→σ'). Where hs is the proportion of agents with opinion (spin) σ', M is the number of opinions and σ'→σ' is the probability weight for an agent with opinion σ being convinced by another agent with opinion σ'. We made Monte Carlo simulations of the model in a complex network (using Barabási-Albert networks [4]) and they displayed the same attractors than the mean-field. Using linear stability analysis, we were able to determine the mean-field attractor structure analytically and to show that it has connections with well known graph theory problems (maximal independent sets and positive fluxes in directed graphs). Our dynamical systems approach is quite simple and can be used also in other models, like the voter model.

Adding ecosystem function to agent-based land use models

USDA-ARS?s Scientific Manuscript database

The objective of this paper is to examine issues in the inclusion of simulations of ecosystem functions in agent-based models of land use decision-making. The reasons for incorporating these simulations include local interests in land fertility and global interests in carbon sequestration. Biogeoche...

Using an agent-based model to analyze the dynamic communication network of the immune response

PubMed Central

2011-01-01

Background The immune system behaves like a complex, dynamic network with interacting elements including leukocytes, cytokines, and chemokines. While the immune system is broadly distributed, leukocytes must communicate effectively to respond to a pathological challenge. The Basic Immune Simulator 2010 contains agents representing leukocytes and tissue cells, signals representing cytokines, chemokines, and pathogens, and virtual spaces representing organ tissue, lymphoid tissue, and blood. Agents interact dynamically in the compartments in response to infection of the virtual tissue. Agent behavior is imposed by logical rules derived from the scientific literature. The model captured the agent-to-agent contact history, and from this the network topology and the interactions resulting in successful versus failed viral clearance were identified. This model served to integrate existing knowledge and allowed us to examine the immune response from a novel perspective directed at exploiting complex dynamics, ultimately for the design of therapeutic interventions. Results Analyzing the evolution of agent-agent interactions at incremental time points from identical initial conditions revealed novel features of immune communication associated with successful and failed outcomes. There were fewer contacts between agents for simulations ending in viral elimination (win) versus persistent infection (loss), due to the removal of infected agents. However, early cellular interactions preceded successful clearance of infection. Specifically, more Dendritic Agent interactions with TCell and BCell Agents, and more BCell Agent interactions with TCell Agents early in the simulation were associated with the immune win outcome. The Dendritic Agents greatly influenced the outcome, confirming them as hub agents of the immune network. In addition, unexpectedly high frequencies of Dendritic Agent-self interactions occurred in the lymphoid compartment late in the loss outcomes. Conclusions

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

NASA Astrophysics Data System (ADS)

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.

Determination of the n-octanol/water partition coefficients of weakly ionizable basic compounds by reversed-phase high-performance liquid chromatography with neutral model compounds.

PubMed

Liang, Chao; Han, Shu-ying; Qiao, Jun-qin; Lian, Hong-zhen; Ge, Xin

2014-11-01

A strategy to utilize neutral model compounds for lipophilicity measurement of ionizable basic compounds by reversed-phase high-performance liquid chromatography is proposed in this paper. The applicability of the novel protocol was justified by theoretical derivation. Meanwhile, the linear relationships between logarithm of apparent n-octanol/water partition coefficients (logKow '') and logarithm of retention factors corresponding to the 100% aqueous fraction of mobile phase (logkw ) were established for a basic training set, a neutral training set and a mixed training set of these two. As proved in theory, the good linearity and external validation results indicated that the logKow ''-logkw relationships obtained from a neutral model training set were always reliable regardless of mobile phase pH. Afterwards, the above relationships were adopted to determine the logKow of harmaline, a weakly dissociable alkaloid. As far as we know, this is the first report on experimental logKow data for harmaline (logKow = 2.28 ± 0.08). Introducing neutral compounds into a basic model training set or using neutral model compounds alone is recommended to measure the lipophilicity of weakly ionizable basic compounds especially those with high hydrophobicity for the advantages of more suitable model compound choices and convenient mobile phase pH control. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

NASA Astrophysics Data System (ADS)

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.

Natural chelating agents for radionuclide decorporation

DOEpatents

Premuzic, E.T.

1985-06-11

This invention relates to the production of metal-binding compounds useful for the therapy of heavy metal poisoning, for biological mining and for decorporation of radionuclides. The present invention deals with an orderly and effective method of producing new therapeutically effective chelating agents. This method uses challenge biosynthesis for the production of chelating agents that are specific for a particular metal. In this approach, the desired chelating agents are prepared from microorganisms challenged by the metal that the chelating agent is designed to detoxify. This challenge induces the formation of specific or highly selective chelating agents. The present invention involves the use of the challenge biosynthetic method to produce new complexing/chelating agents that are therapeutically useful to detoxify uranium, plutonium, thorium and other toxic metals. The Pseudomonas aeruginosa family of organisms is the referred family of microorganisms to be used in the present invention to produce the new chelating agent because this family is known to elaborate strains resistant to toxic metals.

Study on Heat Transfer Agent Models of Transmission Line and Transformer

NASA Astrophysics Data System (ADS)

Wang, B.; Zhang, P. P.

2018-04-01

When using heat transfer simulation to study the dynamic overload of transmission line and transformer, it needs to establish the mathematical expression of heat transfer. However, the formula is a nonlinear differential equation or equation set and it is not easy to get general solutions. Aiming at this problem, some different temperature change processes caused by different initial conditions are calculated by differential equation and equation set. New agent models are developed according to the characteristics of different temperature change processes. The results show that the agent models have high precision and can solve the problem that the original equation cannot be directly applied in some practical engineers.

Comparison of epidermal morphologic response to commercial antiwrinkle agents in the hairless mouse.

PubMed

Bhattacharyya, Tapan K; Higgins, Natalie P; Sebastian, J Scott; Thomas, J Regan

2009-07-01

A large number of commercial antiwrinkle and antiaging compounds are available to consumers for rejuvenation of facial skin ravaged by age or solar radiation. Experimental data on the histological effects of these commercial products in laboratory models are sparse. To compare the efficacy of topical application of five commercially available antiaging compounds (retinoic acid, glycolic acid, vitamin C, estrogen, and soy) on the dorsal skin. The effects were examined using light microscopic analysis of the epidermis in the normal nonirradiated hairless mouse. The agents were applied daily to dorsal tattooed areas for 2 weeks before histological assessment; neighboring untreated surface areas were used as control. Morphometric measurements of total epidermal width, nuclear volume of keratinocytes in three layers, and index of proliferating cell nuclear antigen according to immunohistochemistry were obtained and statistically analyzed. Significant histomorphometric effects were noticed with all five agents, but more pronounced changes were obtained with glycolic acid, estrogen, and retinoic acid product. These baseline data will be useful for future studies on the effect of ultraviolet radiation to cause photoaging and reparative effects of similar agents in this animal. The information contained in the report may provide guidelines to consumers and clinicians.

To what extent have functional studies of ischaemia in animals been useful in the assessment of potential neuroprotective agents?