Eric Tatara

• PhD Chemical Engineering
• Software Engineer at Argonne National Laboratory

There is much focus in the field of HIV prevention research on understanding the impact of social determinants of health (e.g., housing, employment, incarceration) on HIV transmission and developing interventions to address underlying structural drivers of HIV risk. However, such interventions are resource-intensive and logistically challenging, an...

Global elimination of chronic hepatitis C (CHC) remains difficult without an effective vaccine. Since injection drug use is the leading cause of hepatitis C virus (HCV) transmission in Western Europe and North America, people who inject drugs (PWID) are an important population for testing HCV vaccine effectiveness in randomized-clinical trials (RCT...

Importance Opioid-related overdose accounts for almost 80 000 deaths annually across the US. People who use drugs leaving jails are at particularly high risk for opioid-related overdose and may benefit from take-home naloxone (THN) distribution. Objective To estimate the population impact of THN distribution at jail release to reverse opioid-relat...

Access to treatment and medication for opioid use disorder (MOUD) is essential in reducing opioid use and associated behavioral risks, such as syringe sharing among persons who inject drugs (PWID). Syringe sharing among PWID carries high risk of transmission of serious infections such as hepatitis C and HIV. MOUD resources, such as methadone provid...

Despite the availability of direct-acting antivirals that cure individuals infected with the hepatitis C virus (HCV), developing a vaccine is critically needed in achieving HCV elimination. HCV vaccine trials have been performed in populations with high incidence of new HCV infection such as people who inject drugs (PWID). Developing strategies of...

Hepatitis C virus (HCV) infection is a leading cause of chronic liver disease and mortality worldwide. Direct-acting antiviral (DAA) therapy leads to high cure rates. However, persons who inject drugs (PWID) are at risk for reinfection after cure and may require multiple DAA treatments to reach the World Health Organization’s (WHO) goal of HCV elim...

Criminal justice involved (CJI) individuals with a history of opioid use disorder (OUD) are at high risk of overdose and death in the weeks following release from jail. We developed the Justice-Community Circulation Model (JCCM) to investigate OUD/CJI dynamics post-release and the effects of interventions on overdose deaths. The JCCM uses a synthet...

Several independent assessments have identified rare earth elements (REEs) as critical materials, notably neodymium (Nd), praseodymium (Pr), and dysprosium (Dy) used in permanent magnets. Factors affecting their criticality include expected growth in demand arising from their unique performance-enhancing properties in consumer, energy, and military...

Several independent assessments have identified rare earth elements (REEs) as critical materials, notably neodymium (Nd), praseodymium (Pr), and dysprosium (Dy) used in permanent magnets. Factors affecting their criticality include expected growth in demand arising from their unique performance-enhancing properties in consumer, energy, and military...

Hepatitis C (HCV) is a leading cause of chronic liver disease and mortality worldwide and persons who inject drugs (PWID) are at the highest risk for acquiring and transmitting HCV infection. We developed an agent-based model (ABM) to identify and optimize direct-acting antiviral (DAA) therapy scale-up and treatment strategies for achieving the Wor...

Hepatitis C (HCV) is a leading cause of chronic liver disease and mortality worldwide. Persons who inject drugs (PWID) are at the highest risk for acquiring and transmitting HCV infection. We developed an agent-based model (ABM) to identify and optimize direct-acting antiviral (DAA) therapy scale-up and treatment strategies for achieving the World...

Land exchange through rental transactions is a central process in agricultural systems. The land tenure regimes emerge from land transactions and structural and land use changes are tied to the dynamics of the land market. We introduce LARMA, a LAnd Rental MArket model embedded within the Pampas Model (PM), an agent-based model of Argentinean agric...

This paper presents a building infiltration detection and quantification technique using statistically optimized nearfield acoustic holography (SONAH) technique. A model building with known cracks on its wall was investigated in this study. The model building housed a synthetic acoustic source. A hologram measurement was performed outside the model...

A crack on a building wall and sound generated inside the building using an artificial sound source were simulated using Matlab. Various noise types affecting the pure sound signal, such as background noise in the room, were simulated. The forward problem of sound propagation from the crack surface to a virtual microphone array was simulated using...

Building infiltration is a significant portion of the heating and cooling load of buildings and accounts for nearly 4% of the total energy use in the United States. Current measurement methods for locating and quantifying infiltration in commercial buildings to apply remediation are very limited. In this talk, the development of a new measurement s...

Air infiltration, the uncontrolled leakage of air into buildings through the enclosure from pressure differences across it, accounts for a significant fraction of the heating energy in cold weather climates. Measurement and control of this infiltration is a necessary part of reducing the energy and carbon footprint of both current and newly constru...

Purpose This paper is to describe development of the features and functions of Repast Simphony, the widely used, free, and open source agent-based modeling environment that builds on the Repast 3 library. Repast Simphony was designed from the ground up with a focus on well-factored abstractions. The resulting code has a modular architecture that al...

Abstract We have developed a multi-scale, 3D agent-based model (ABM) of mammalian arterial blood vessels specifically focusing on the pathobiology of pulmonary arterial hypertension (PAH), a disease that may involve pathologies in any of the various signaling pathways, cell types, layers, or connective structures in blood vessel walls. Model and Me...

RATIONALE Computational models of disease that rely on animal studies often do not present rigorous approaches to model validation. Statistical analyses may only include univariate approaches that lack random variable distributions. Although often accepted, qualitative comparisons between model outputs and available experimental data do not suffici...

Much remains unknown about how dynamic properties of vessels across multiple spatial scales contribute to increased vascular impedance and RV afterload. Some investigators have developed computational models of pulmonary vascular impedance to analyze changes in pulmonary hemodynamics in response to disease, however these models are generally either...

The Argentine Pampas, one of the main agricultural areas in the world, recently has undergone significant changes in land use and structural characteristics of agricultural production systems. Concerns about the environmental and societal impacts of the changes motivated development of an agent-based model (ABM) to gain insight on processes underly...

The dominant strategy among game theorists is to pose a problem narrowly, formalize that structure, and then pursue analytical solutions. This strategy has achieved a number of stylized insights, but has not produced nuanced game-theoretic solutions to larger and more complex issues such as extended international historical conflicts, or the detail...

The complex and interconnected world in which organizations operate presents many challenges to the traditional neo-classical view of research and management and associated research techniques. Fundamental to the operation of financial capital markets, investor confidence relies on accurate investment analyst earnings forecasts. We propose agent-ba...

The dominant strategy among game theorists is to pose a problem narrowly, formalize that structure, and then pursue analytical solutions. This strategy has achieved a number of stylized insights, but has not produced nuanced game-theoretic solutions to larger and more complex issues such as extended international historical conflicts, or the detail...

Multiagent systems provide a powerful framework for developing real-time process supervision and control systems for distributed and networked processes by automating adaptation and situation-dependent rearrangement of confidence to specific monitoring and diagnosis techniques. An agent-based framework for monitoring, analysis, diagnosis, and contr...

Multiagent systems provide a powerful framework for developing real-time process supervision and control systems for distributed and networked processes by automating adaptability and situation-dependent rearrangement of confidence to specific monitoring and diagnosis techniques. An agent-based framework for monitoring, analysis, diagnosis, and con...

Search has been recognized as an important technology for a wide range of software applications. Agentbased modelers often face search challenges both when looking for agents that need to be connected to one another and when seeking appropriate target agents while defining agent behaviors. This chapter presents an approach to simplifying such searc...

Repast is a widely used, free, and open-source agent-based modeling and simulation toolkit. Three Repast platforms are currently available, each of which has the same core features but a different environment for these features. Repast Simphony (Repast S) extends the Repast portfolio by offering a new approach to simulation development and executio...

Control of spatially distributed systems is a challenging problem because of their complex nature, nonlinearity, and generally high order. The lack of accurate and computationally efficient model-based techniques for large, spatially distributed systems leads to challenges in controlling the system. Agent-based control structures provide a powerful...

This paper presents an introductory tutorial and illustration of the modeling capabilities of the Repast Simphony simulation framework using an agent-based model of regional natural gas and electric power system interdependencies. The natural gas transmission and distribution and electrical power companies are modeled as social agent organizations....

Large-scale spatially distributed systems provide control challenges because of their nonlinearity, spatial distribution and generally high order. The control structure for these systems tend to be both discrete and distributed. A layered control structure interfaced with complex arrays of sensors and actuators provides a flexible supervision and c...

Repast is a widely used, free, and open-source, agent-based modeling and simulation toolkit. Three Repast platforms are currently available, each of which has the same core features but a different environment for these features. Repast Simphony (Repast S) extends the Repast portfolio by offering a new approach to simulation development and executi...

Sociologist Georg Simmel has said that “every relationship between persons causes a picture of each to take form in the mind of the other, and this picture evidently is in reciprocal relationship with that personal relationship.” As a pioneer of the scientific study of social structure, Simmel recognized the sophistication of both social systems an...

Control of spatially distributed systems is a challenging problem because of their complex nature, nonlinearity, and generally high order. Agent-based control structures provide a powerful tool for managing distributed systems by utilizing local and global information obtained from the system. A hierarchical, agent-based system with local and globa...

Large-scale spatially distributed systems provide a unique and difficult control challenge because of their nonlinearity, spatialdistribution and generally high order. The control structure for these systems tend to be both discrete and distributed as well and contain discrete and continuous elements. A layered control structure interfaced with com...

From a control system perspective, spatially distributed systems offer challenges because of their distributed nature, nonlinearity, and high order. In addition, the control structure for these spatially distributed networks combine discrete and distributed components, in the form of complex arrays of sensors and actuators. Manipulation of the netw...

Spatially distributed systems such as reactor networks hosting multiple autocatalytic species demonstrate a rich spectrum of complex behavior. From a control systems perspective, spatially distributed systems offer a difficult control challenge because of their distributed nature, nonlinearity, and high order. Furthermore, manipulation of the netwo...

Systems with high steady-state multiplicity and rich dynamic behavior are difficult to investigate using conventional reductionist methods. A network of more than five reactors hosting cubic autocatalytic reactions may potentially have more than 102 steady states and many distinct dynamic regimes, all for the same parameter set. This paper discusse...

From a control system perspective, spatially distributed systems offer challenges because of their distributed nature, nonlinearity, and high order. in addition, the control structure for these spatially distributed networks combine discrete and distributed components, in the form of complex arrays of sensors and actuators. Manipulation of the netw...

Several recent studies on autocatalytic reactions in single and coupled continuous stirred-tank reactor (CSTR) networks have demonstrated a rich spec-trum of complex behavior. From a control systems perspective, the operating regime of a CSTR network can be manipulated by changing the flow rates between the reactors. Systems of more than one CSTR r...

The static and dynamic behavior of the autocatalytic reaction R + 2P → 3P with decay P → D is studied in networks of coupled continuous stirred tank reactors (CSTRs). Numerical bifurcation studies of the system are performed, resulting in rich steady-state bifurcation structures with multiple steady states and isolas. The heterogeneity of the netwo...

Supervision of batch bioprocess operations in real-time during the progress of a batch run offers many advantages over end-of-batch quality control. Multivariate statistical techniques such as multiway partial least squares (MPLS) provide an efficient modeling and supervision framework. A new type of MPLS modeling technique that is especially suita...

Slight changes in raw material properties or operating conditions during critical periods of operation of batch and semi-batch polymerization reactors may have a strong influence on reaction mechanism and impact final product quality. Online process monitoring, fault detection, fault diagnosis, and product quality prediction in real-time ensure saf...

Real-time supervision of batch operations during the progress of a batch run offers many advantages over end-of-batch quality control. Process monitoring, quality estimation, and fault diagnosis activities are automated and supervised by embedding them into a real-time knowledge-based system (RTKBS). Interpretation of multivariate charts is also au...

A model of competition between cubic autocatalators is applied to model the population dynamics of multiple species living in a certain ecology. The two species scheme is studied by many researchers, and is shown to have steady state multiplicity in the form of mushrooms and isolas. When two or more species compete pure and simply (in the sense tha...

A knowledge-based system (KBS) was designed for automated system identification, process monitoring, and diagnosis of sensor faults. The real-time KBS consists of a supervisory system using G2 KBS development software linked with external statistical modules for system identification and sensor fault diagnosis. The various statistical techniques we...

The use of an automated system integrating data conditioning, statistical methods, and artificial intelligence tools to summarize and interpret high-frequency physiological data such as the electrocardiogram is investigated. The development of a methodology and its associated tools for real-time patient monitoring and diagnosis is accomplished by u...

On-line real-time monitoring of fermentation processes is a crucial task. Conventional on-line process monitoring techniques and an adaptive hierarchical Principal Component Analysis technique were applied. A hybrid supervisory knowledge-based system with a heuristic rule-base was also developed and integrated with on-line monitoring techniques for...

Batch and fed-batch bioprocesses generally exhibit batch-to-batch variation. Multivariate statistical monitoring of these processes based on the use of empirical models developed from the multiway principal component analysis was performed by using contribution, T² and square prediction error plots. To cope with uncertainties in the ferm...

Automated data collection from patients has created new challenges for health care professionals in their efforts to extract useful information from raw data. Online monitoring devices may generate large amounts of data that must be interpreted quickly and accurately. The use of statistical methods and artificial intelligence (AI) tools to summariz...

Patient monitoring by automated data collection has created new challenges for health care professionals in their efforts to extract useful information from raw data. New online monitoring devices may generate large amounts of data that must be interpreted quickly and accurately. The use of statistical methods and artificial intelligence tools to s...

An intelligent process monitoring and fault diagnosis environment is developed by interfacing multivariate statistical process monitoring (MSPM) techniques and knowledge-based systems (KBS) for monitoring continuous multivariable process operation. The software is tested by monitoring the performance of a continuous stirred tank reactor for polymer...

An intelligent sensor monitoring and auditing environment has been developed by interfacing multivariate statistical process monitoring (MSPM) techniques and knowledge-based systems (KBS) for monitoring sensor status in multivariable processes. The real-time KBS development environment G2 is integrated with an MSPM method that can monitor multivari...

Large-scale spatially distributed systems provide control challenges because of their nonlinearity, spatial distribution, and generally high order. The control structure for these systems tends to be both discrete and distributed. A layered control structure interfaced with complex arrays of sensors and actuators provides a flexible supervision and...