A validation study of a stochastic model of human interaction

NASA Astrophysics Data System (ADS)

Burchfield, Mitchel Talmadge

The purpose of this dissertation is to validate a stochastic model of human interactions which is part of a developmentalism paradigm. Incorporating elements of ancient and contemporary philosophy and science, developmentalism defines human development as a progression of increasing competence and utilizes compatible theories of developmental psychology, cognitive psychology, educational psychology, social psychology, curriculum development, neurology, psychophysics, and physics. To validate a stochastic model of human interactions, the study addressed four research questions: (a) Does attitude vary over time? (b) What are the distributional assumptions underlying attitudes? (c) Does the stochastic model, {-}N{intlimitssbsp{-infty}{infty}}varphi(chi,tau)\\ Psi(tau)dtau, have utility for the study of attitudinal distributions and dynamics? (d) Are the Maxwell-Boltzmann, Fermi-Dirac, and Bose-Einstein theories applicable to human groups? Approximately 25,000 attitude observations were made using the Semantic Differential Scale. Positions of individuals varied over time and the logistic model predicted observed distributions with correlations between 0.98 and 1.0, with estimated standard errors significantly less than the magnitudes of the parameters. The results bring into question the applicability of Fisherian research designs (Fisher, 1922, 1928, 1938) for behavioral research based on the apparent failure of two fundamental assumptions-the noninteractive nature of the objects being studied and normal distribution of attributes. The findings indicate that individual belief structures are representable in terms of a psychological space which has the same or similar properties as physical space. The psychological space not only has dimension, but individuals interact by force equations similar to those described in theoretical physics models. Nonlinear regression techniques were used to estimate Fermi-Dirac parameters from the data. The model explained a high degree

Modelling of human-machine interaction in equipment design of manufacturing cells

NASA Astrophysics Data System (ADS)

Cochran, David S.; Arinez, Jorge F.; Collins, Micah T.; Bi, Zhuming

2017-08-01

This paper proposes a systematic approach to model human-machine interactions (HMIs) in supervisory control of machining operations; it characterises the coexistence of machines and humans for an enterprise to balance the goals of automation/productivity and flexibility/agility. In the proposed HMI model, an operator is associated with a set of behavioural roles as a supervisor for multiple, semi-automated manufacturing processes. The model is innovative in the sense that (1) it represents an HMI based on its functions for process control but provides the flexibility for ongoing improvements in the execution of manufacturing processes; (2) it provides a computational tool to define functional requirements for an operator in HMIs. The proposed model can be used to design production systems at different levels of an enterprise architecture, particularly at the machine level in a production system where operators interact with semi-automation to accomplish the goal of 'autonomation' - automation that augments the capabilities of human beings.

Exploring host–microbiota interactions in animal models and humans

PubMed Central

Kostic, Aleksandar D.; Howitt, Michael R.; Garrett, Wendy S.

2013-01-01

The animal and bacterial kingdoms have coevolved and coadapted in response to environmental selective pressures over hundreds of millions of years. The meta'omics revolution in both sequencing and its analytic pipelines is fostering an explosion of interest in how the gut microbiome impacts physiology and propensity to disease. Gut microbiome studies are inherently interdisciplinary, drawing on approaches and technical skill sets from the biomedical sciences, ecology, and computational biology. Central to unraveling the complex biology of environment, genetics, and microbiome interaction in human health and disease is a deeper understanding of the symbiosis between animals and bacteria. Experimental model systems, including mice, fish, insects, and the Hawaiian bobtail squid, continue to provide critical insight into how host–microbiota homeostasis is constructed and maintained. Here we consider how model systems are influencing current understanding of host–microbiota interactions and explore recent human microbiome studies. PMID:23592793

A Framework for Modeling Human-Machine Interactions

NASA Technical Reports Server (NTRS)

Shafto, Michael G.; Rosekind, Mark R. (Technical Monitor)

1996-01-01

Modern automated flight-control systems employ a variety of different behaviors, or modes, for managing the flight. While developments in cockpit automation have resulted in workload reduction and economical advantages, they have also given rise to an ill-defined class of human-machine problems, sometimes referred to as 'automation surprises'. Our interest in applying formal methods for describing human-computer interaction stems from our ongoing research on cockpit automation. In this area of aeronautical human factors, there is much concern about how flight crews interact with automated flight-control systems, so that the likelihood of making errors, in particular mode-errors, is minimized and the consequences of such errors are contained. The goal of the ongoing research on formal methods in this context is: (1) to develop a framework for describing human interaction with control systems; (2) to formally categorize such automation surprises; and (3) to develop tests for identification of these categories early in the specification phase of a new human-machine system.

Five Papers on Human-Machine Interaction.

ERIC Educational Resources Information Center

Norman, Donald A.

Different aspects of human-machine interaction are discussed in the five brief papers that comprise this report. The first paper, "Some Observations on Mental Models," discusses the role of a person's mental model in the interaction with systems. The second paper, "A Psychologist Views Human Processing: Human Errors and Other…

Head Motion Modeling for Human Behavior Analysis in Dyadic Interaction

PubMed Central

Xiao, Bo; Georgiou, Panayiotis; Baucom, Brian; Narayanan, Shrikanth S.

2015-01-01

This paper presents a computational study of head motion in human interaction, notably of its role in conveying interlocutors’ behavioral characteristics. Head motion is physically complex and carries rich information; current modeling approaches based on visual signals, however, are still limited in their ability to adequately capture these important properties. Guided by the methodology of kinesics, we propose a data driven approach to identify typical head motion patterns. The approach follows the steps of first segmenting motion events, then parametrically representing the motion by linear predictive features, and finally generalizing the motion types using Gaussian mixture models. The proposed approach is experimentally validated using video recordings of communication sessions from real couples involved in a couples therapy study. In particular we use the head motion model to classify binarized expert judgments of the interactants’ specific behavioral characteristics where entrainment in head motion is hypothesized to play a role: Acceptance, Blame, Positive, and Negative behavior. We achieve accuracies in the range of 60% to 70% for the various experimental settings and conditions. In addition, we describe a measure of motion similarity between the interaction partners based on the proposed model. We show that the relative change of head motion similarity during the interaction significantly correlates with the expert judgments of the interactants’ behavioral characteristics. These findings demonstrate the effectiveness of the proposed head motion model, and underscore the promise of analyzing human behavioral characteristics through signal processing methods. PMID:26557047

Carbon-climate-human interactions in an integrated human-Earth system model

NASA Astrophysics Data System (ADS)

Calvin, K. V.; Bond-Lamberty, B. P.; Jones, A. D.; Shi, X.

2016-12-01

The C4MIP and CMIP5 results highlighted large uncertainties in climate projections, driven to a large extent by limited understanding of the interactions between terrestrial carbon-cycle and climate feedbacks, and their associated uncertainties. These feedbacks are dominated by uncertainties in soil processes, disturbance dynamics, ecosystem response to climate change, and agricultural productivity, and land-use change. This research addresses three questions: (1) how do terrestrial feedbacks vary across different levels of climate change, (2) what is the relative contribution of CO2 fertilization and climate change, and (3) how robust are the results across different models and methods? We used a coupled modeling framework that integrates an Integrated Assessment Model (modeling economic and energy activity) with an Earth System Model (modeling the natural earth system) to examine how business-as-usual (RCP 8.5) climate change will affect ecosystem productivity, cropland extent, and other aspects of the human-Earth system. We find that higher levels of radiative forcing result in higher productivity growth, that increases in CO2 concentrations are the dominant contributors to that growth, and that our productivity increases fall in the middle of the range when compared to other CMIP5 models and the AgMIP models. These results emphasize the importance of examining both the anthropogenic and natural components of the earth system, and their long-term interactive feedbacks.

Understanding and Resolving Failures in Human-Robot Interaction: Literature Review and Model Development

PubMed Central

Honig, Shanee; Oron-Gilad, Tal

2018-01-01

While substantial effort has been invested in making robots more reliable, experience demonstrates that robots operating in unstructured environments are often challenged by frequent failures. Despite this, robots have not yet reached a level of design that allows effective management of faulty or unexpected behavior by untrained users. To understand why this may be the case, an in-depth literature review was done to explore when people perceive and resolve robot failures, how robots communicate failure, how failures influence people's perceptions and feelings toward robots, and how these effects can be mitigated. Fifty-two studies were identified relating to communicating failures and their causes, the influence of failures on human-robot interaction (HRI), and mitigating failures. Since little research has been done on these topics within the HRI community, insights from the fields of human computer interaction (HCI), human factors engineering, cognitive engineering and experimental psychology are presented and discussed. Based on the literature, we developed a model of information processing for robotic failures (Robot Failure Human Information Processing, RF-HIP), that guides the discussion of our findings. The model describes the way people perceive, process, and act on failures in human robot interaction. The model includes three main parts: (1) communicating failures, (2) perception and comprehension of failures, and (3) solving failures. Each part contains several stages, all influenced by contextual considerations and mitigation strategies. Several gaps in the literature have become evident as a result of this evaluation. More focus has been given to technical failures than interaction failures. Few studies focused on human errors, on communicating failures, or the cognitive, psychological, and social determinants that impact the design of mitigation strategies. By providing the stages of human information processing, RF-HIP can be used as a tool to

Learning models of Human-Robot Interaction from small data

PubMed Central

Zehfroosh, Ashkan; Kokkoni, Elena; Tanner, Herbert G.; Heinz, Jeffrey

2018-01-01

This paper offers a new approach to learning discrete models for human-robot interaction (HRI) from small data. In the motivating application, HRI is an integral part of a pediatric rehabilitation paradigm that involves a play-based, social environment aiming at improving mobility for infants with mobility impairments. Designing interfaces in this setting is challenging, because in order to harness, and eventually automate, the social interaction between children and robots, a behavioral model capturing the causality between robot actions and child reactions is needed. The paper adopts a Markov decision process (MDP) as such a model, and selects the transition probabilities through an empirical approximation procedure called smoothing. Smoothing has been successfully applied in natural language processing (NLP) and identification where, similarly to the current paradigm, learning from small data sets is crucial. The goal of this paper is two-fold: (i) to describe our application of HRI, and (ii) to provide evidence that supports the application of smoothing for small data sets. PMID:29492408

Learning models of Human-Robot Interaction from small data.

PubMed

Zehfroosh, Ashkan; Kokkoni, Elena; Tanner, Herbert G; Heinz, Jeffrey

2017-07-01

This paper offers a new approach to learning discrete models for human-robot interaction (HRI) from small data. In the motivating application, HRI is an integral part of a pediatric rehabilitation paradigm that involves a play-based, social environment aiming at improving mobility for infants with mobility impairments. Designing interfaces in this setting is challenging, because in order to harness, and eventually automate, the social interaction between children and robots, a behavioral model capturing the causality between robot actions and child reactions is needed. The paper adopts a Markov decision process (MDP) as such a model, and selects the transition probabilities through an empirical approximation procedure called smoothing. Smoothing has been successfully applied in natural language processing (NLP) and identification where, similarly to the current paradigm, learning from small data sets is crucial. The goal of this paper is two-fold: (i) to describe our application of HRI, and (ii) to provide evidence that supports the application of smoothing for small data sets.

A mathematical model of interaction among humans, vampires and werewolves populations

NASA Astrophysics Data System (ADS)

Sumarti, Novriana; Nurrizky, Insan; Nuraini, Nuning

2018-03-01

In every country there are many fictional creatures depicting evil. In the western world, fictional creatures who often appear in horror stories are vampires and werewolves. Many released movies expose the conflict between humans with one or both creatures. In this paper, the interaction among humans, vampires and werewolves is modeled using a system of differential equations. We consider the stability of equilibrium points of the system that represent four situations; only humans remain or a disease-free condition, either vampires or werewolves are going to extinction, and no population goes extinct. The derived model is implemented for depicting some scenarios in the movie series of Underworld. The model can describe the fluctuation of vampires and werewolves population from the beginning to their extinction at 1500 years since the story started.

Human-pet interaction and loneliness: a test of concepts from Roy's adaptation model.

PubMed

Calvert, M M

1989-01-01

This research used two key concepts from Roy's adaptation model of nursing to examine the relationship between human-pet interaction and loneliness in nursing home residents. These concepts included (a) environmental stimuli as factors influencing adaptation and (b) interdependence as a mode of response to the environment. The hypothesis of this study asserted that the residents of a nursing home who had greater levels of interaction with a pet program would experience less loneliness than those who had lower levels of interaction with a pet. The study used an ex post facto nonexperimental design with 65 subjects. The simplified version of the revised UCLA loneliness scale was used to measure loneliness. Reported level of human-pet interaction was measured according to a four-point scale (1 = no interaction, 4 = quite a lot of interaction). The hypothesis was supported at the p less than 0.03 level of significance. Implications for practice through organizing pet programs in situations where loneliness exists are discussed. Recommendations for future research include replicating the study using a larger sample and developing a comprehensive human-pet interaction tool.

Model-based safety analysis of human-robot interactions: the MIRAS walking assistance robot.

PubMed

Guiochet, Jérémie; Hoang, Quynh Anh Do; Kaaniche, Mohamed; Powell, David

2013-06-01

Robotic systems have to cope with various execution environments while guaranteeing safety, and in particular when they interact with humans during rehabilitation tasks. These systems are often critical since their failure can lead to human injury or even death. However, such systems are difficult to validate due to their high complexity and the fact that they operate within complex, variable and uncertain environments (including users), in which it is difficult to foresee all possible system behaviors. Because of the complexity of human-robot interactions, rigorous and systematic approaches are needed to assist the developers in the identification of significant threats and the implementation of efficient protection mechanisms, and in the elaboration of a sound argumentation to justify the level of safety that can be achieved by the system. For threat identification, we propose a method called HAZOP-UML based on a risk analysis technique adapted to system description models, focusing on human-robot interaction models. The output of this step is then injected in a structured safety argumentation using the GSN graphical notation. Those approaches have been successfully applied to the development of a walking assistant robot which is now in clinical validation.

Bayesian Safety Risk Modeling of Human-Flightdeck Automation Interaction

NASA Technical Reports Server (NTRS)

Ancel, Ersin; Shih, Ann T.

2015-01-01

Usage of automatic systems in airliners has increased fuel efficiency, added extra capabilities, enhanced safety and reliability, as well as provide improved passenger comfort since its introduction in the late 80's. However, original automation benefits, including reduced flight crew workload, human errors or training requirements, were not achieved as originally expected. Instead, automation introduced new failure modes, redistributed, and sometimes increased workload, brought in new cognitive and attention demands, and increased training requirements. Modern airliners have numerous flight modes, providing more flexibility (and inherently more complexity) to the flight crew. However, the price to pay for the increased flexibility is the need for increased mode awareness, as well as the need to supervise, understand, and predict automated system behavior. Also, over-reliance on automation is linked to manual flight skill degradation and complacency in commercial pilots. As a result, recent accidents involving human errors are often caused by the interactions between humans and the automated systems (e.g., the breakdown in man-machine coordination), deteriorated manual flying skills, and/or loss of situational awareness due to heavy dependence on automated systems. This paper describes the development of the increased complexity and reliance on automation baseline model, named FLAP for FLightdeck Automation Problems. The model development process starts with a comprehensive literature review followed by the construction of a framework comprised of high-level causal factors leading to an automation-related flight anomaly. The framework was then converted into a Bayesian Belief Network (BBN) using the Hugin Software v7.8. The effects of automation on flight crew are incorporated into the model, including flight skill degradation, increased cognitive demand and training requirements along with their interactions. Besides flight crew deficiencies, automation system

Multiscale Modeling of Human-Water Interactions: The Role of Time-Scales

NASA Astrophysics Data System (ADS)

Bloeschl, G.; Sivapalan, M.

2015-12-01

Much of the interest in hydrological modeling in the past decades revolved around resolving spatial variability. With the rapid changes brought about by human impacts on the hydrologic cycle, there is now an increasing need to refocus on time dependency. We present a co-evolutionary view of hydrologic systems, in which every part of the system including human systems, co-evolve, albeit at different rates. The resulting coupled human-nature system is framed as a dynamical system, characterized by interactions of fast and slow time scales and feedbacks between environmental and social processes. This gives rise to emergent phenomena such as the levee effect, adaptation to change and system collapse due to resource depletion. Changing human values play a key role in the emergence of these phenomena and should therefore be considered as internal to the system in a dynamic way. The co-evolutionary approach differs from the traditional view of water resource systems analysis as it allows for path dependence, multiple equilibria, lock-in situations and emergent phenomena. The approach may assist strategic water management for long time scales through facilitating stakeholder participation, exploring the possibility space of alternative futures, and helping to synthesise the observed dynamics of different case studies. Future research opportunities include the study of how changes in human values are connected to human-water interactions, historical analyses of trajectories of system co-evolution in individual places and comparative analyses of contrasting human-water systems in different climate and socio-economic settings. Reference Sivapalan, M. and G. Blöschl (2015) Time Scale Interactions and the Co-evolution of Humans and Water. Water Resour. Res., 51, in press.

Humans in Biogeophysical Models: Colonial Period Human-Environment Interactions in the Northeastern United States

NASA Astrophysics Data System (ADS)

Parolari, A.; Greco, F.; Green, M.; Lally, M.; Hermans, C.

2008-12-01

Earth system models increasingly require representation of human activities and the important role they play in the environment. At the most fundamental level, human decisions are driven by the need to acquire basic resources - nutrients, energy, water, and space - each derived from the biogeophysical setting. Modern theories in Ecological Economics place these basic resources at the base of a consumption hierarchy (from subsistence to luxury resources) on which societies and economies are built. Human decisions at all levels of this hierarchy are driven by dynamic environmental, social, and economic factors. Therefore, models merging socio-economic and biogeophysical dynamics are required to predict the evolving relationship between humans and the hydrologic cycle. To provide an example, our study focuses on changes to the hydrologic cycle during the United States colonial period (1600 to 1800). Both direct, intentional, human water use (e.g. water supply, irrigation, or hydropower) and indirect, unintentional effects resulting from the use of other resources (e.g. deforestation or beaver trapping) are considered. We argue that water was not the limiting resource to either the Native or Colonist population growth. However, food and tobacco production and harvesting of beaver pelts led to indirect interventions and consequent changes in the hydrologic cycle. The analysis presented here suggests the importance of incorporating human decision- making dynamics with existing geophysical models to fully understand trajectories of human-environment interactions. Predictive tools of this type are critical to characterizing the long-term signature of humans on the landscape and hydrologic cycle.

Toward a 3D model of human brain development for studying gene/environment interactions

PubMed Central

2013-01-01

This project aims to establish and characterize an in vitro model of the developing human brain for the purpose of testing drugs and chemicals. To accurately assess risk, a model needs to recapitulate the complex interactions between different types of glial cells and neurons in a three-dimensional platform. Moreover, human cells are preferred over cells from rodents to eliminate cross-species differences in sensitivity to chemicals. Previously, we established conditions to culture rat primary cells as three-dimensional aggregates, which will be humanized and evaluated here with induced pluripotent stem cells (iPSCs). The use of iPSCs allows us to address gene/environment interactions as well as the potential of chemicals to interfere with epigenetic mechanisms. Additionally, iPSCs afford us the opportunity to study the effect of chemicals during very early stages of brain development. It is well recognized that assays for testing toxicity in the developing brain must consider differences in sensitivity and susceptibility that arise depending on the time of exposure. This model will reflect critical developmental processes such as proliferation, differentiation, lineage specification, migration, axonal growth, dendritic arborization and synaptogenesis, which will probably display differences in sensitivity to different types of chemicals. Functional endpoints will evaluate the complex cell-to-cell interactions that are affected in neurodevelopment through chemical perturbation, and the efficacy of drug intervention to prevent or reverse phenotypes. The model described is designed to assess developmental neurotoxicity effects on unique processes occurring during human brain development by leveraging human iPSCs from diverse genetic backgrounds, which can be differentiated into different cell types of the central nervous system. Our goal is to demonstrate the feasibility of the personalized model using iPSCs derived from individuals with neurodevelopmental disorders

State Event Models for the Formal Analysis of Human-Machine Interactions

NASA Technical Reports Server (NTRS)

Combefis, Sebastien; Giannakopoulou, Dimitra; Pecheur, Charles

2014-01-01

The work described in this paper was motivated by our experience with applying a framework for formal analysis of human-machine interactions (HMI) to a realistic model of an autopilot. The framework is built around a formally defined conformance relation called "fullcontrol" between an actual system and the mental model according to which the system is operated. Systems are well-designed if they can be described by relatively simple, full-control, mental models for their human operators. For this reason, our framework supports automated generation of minimal full-control mental models for HMI systems, where both the system and the mental models are described as labelled transition systems (LTS). The autopilot that we analysed has been developed in the NASA Ames HMI prototyping tool ADEPT. In this paper, we describe how we extended the models that our HMI analysis framework handles to allow adequate representation of ADEPT models. We then provide a property-preserving reduction from these extended models to LTSs, to enable application of our LTS-based formal analysis algorithms. Finally, we briefly discuss the analyses we were able to perform on the autopilot model with our extended framework.

Interactive Model-Centric Systems Engineering (IMCSE) Phase 5

DTIC Science & Technology

2018-02-28

Conducting Program Team Launches ................................................................................................. 12 Informing Policy...research advances knowledge relevant to human interaction with models and model-generated information . Figure 1 highlights several questions the...stakeholders interact using models and model generated information ; facets of human interaction with visualizations and large data sets; and underlying

Aviation Safety: Modeling and Analyzing Complex Interactions between Humans and Automated Systems

NASA Technical Reports Server (NTRS)

Rungta, Neha; Brat, Guillaume; Clancey, William J.; Linde, Charlotte; Raimondi, Franco; Seah, Chin; Shafto, Michael

2013-01-01

The on-going transformation from the current US Air Traffic System (ATS) to the Next Generation Air Traffic System (NextGen) will force the introduction of new automated systems and most likely will cause automation to migrate from ground to air. This will yield new function allocations between humans and automation and therefore change the roles and responsibilities in the ATS. Yet, safety in NextGen is required to be at least as good as in the current system. We therefore need techniques to evaluate the safety of the interactions between humans and automation. We think that current human factor studies and simulation-based techniques will fall short in front of the ATS complexity, and that we need to add more automated techniques to simulations, such as model checking, which offers exhaustive coverage of the non-deterministic behaviors in nominal and off-nominal scenarios. In this work, we present a verification approach based both on simulations and on model checking for evaluating the roles and responsibilities of humans and automation. Models are created using Brahms (a multi-agent framework) and we show that the traditional Brahms simulations can be integrated with automated exploration techniques based on model checking, thus offering a complete exploration of the behavioral space of the scenario. Our formal analysis supports the notion of beliefs and probabilities to reason about human behavior. We demonstrate the technique with the Ueberligen accident since it exemplifies authority problems when receiving conflicting advices from human and automated systems.

Occupational stress in human computer interaction.

PubMed

Smith, M J; Conway, F T; Karsh, B T

1999-04-01

There have been a variety of research approaches that have examined the stress issues related to human computer interaction including laboratory studies, cross-sectional surveys, longitudinal case studies and intervention studies. A critical review of these studies indicates that there are important physiological, biochemical, somatic and psychological indicators of stress that are related to work activities where human computer interaction occurs. Many of the stressors of human computer interaction at work are similar to those stressors that have historically been observed in other automated jobs. These include high workload, high work pressure, diminished job control, inadequate employee training to use new technology, monotonous tasks, por supervisory relations, and fear for job security. New stressors have emerged that can be tied primarily to human computer interaction. These include technology breakdowns, technology slowdowns, and electronic performance monitoring. The effects of the stress of human computer interaction in the workplace are increased physiological arousal; somatic complaints, especially of the musculoskeletal system; mood disturbances, particularly anxiety, fear and anger; and diminished quality of working life, such as reduced job satisfaction. Interventions to reduce the stress of computer technology have included improved technology implementation approaches and increased employee participation in implementation. Recommendations for ways to reduce the stress of human computer interaction at work are presented. These include proper ergonomic conditions, increased organizational support, improved job content, proper workload to decrease work pressure, and enhanced opportunities for social support. A model approach to the design of human computer interaction at work that focuses on the system "balance" is proposed.

Metaphors for the Nature of Human-Computer Interaction in an Empowering Environment: Interaction Style Influences the Manner of Human Accomplishment.

ERIC Educational Resources Information Center

Weller, Herman G.; Hartson, H. Rex

1992-01-01

Describes human-computer interface needs for empowering environments in computer usage in which the machine handles the routine mechanics of problem solving while the user concentrates on its higher order meanings. A closed-loop model of interaction is described, interface as illusion is discussed, and metaphors for human-computer interaction are…

Agent Based Modeling of Human Gut Microbiome Interactions and Perturbations.

PubMed

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

2016-01-01

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

Shoe-Floor Interactions in Human Walking With Slips: Modeling and Experiments.

PubMed

Trkov, Mitja; Yi, Jingang; Liu, Tao; Li, Kang

2018-03-01

Shoe-floor interactions play a crucial role in determining the possibility of potential slip and fall during human walking. Biomechanical and tribological parameters influence the friction characteristics between the shoe sole and the floor and the existing work mainly focus on experimental studies. In this paper, we present modeling, analysis, and experiments to understand slip and force distributions between the shoe sole and floor surface during human walking. We present results for both soft and hard sole material. The computational approaches for slip and friction force distributions are presented using a spring-beam networks model. The model predictions match the experimentally observed sole deformations with large soft sole deformation at the beginning and the end stages of the stance, which indicates the increased risk for slip. The experiments confirm that both the previously reported required coefficient of friction (RCOF) and the deformation measurements in this study can be used to predict slip occurrence. Moreover, the deformation and force distribution results reported in this study provide further understanding and knowledge of slip initiation and termination under various biomechanical conditions.

Modeling human-climate interaction

NASA Astrophysics Data System (ADS)

Jacoby, Henry D.

If policymakers and the public are to be adequately informed about the climate change threat, climate modeling needs to include components far outside its conventional boundaries. An integration of climate chemistry and meteorology, oceanography, and terrestrial biology has been achieved over the past few decades. More recently the scope of these studies has been expanded to include the human systems that influence the planet, the social and ecological consequences of potential change, and the political processes that lead to attempts at mitigation and adaptation. For example, key issues—like the relative seriousness of climate change risk, the choice of long-term goals for policy, and the analysis of today's decisions when uncertainty may be reduced tomorrow—cannot be correctly understood without joint application of the natural science of the climate system and social and behavioral science aspects of human response. Though integration efforts have made significant contributions to understanding of the climate issue, daunting intellectual and institutional barriers stand in the way of needed progress. Deciding appropriate policies will be a continuing task over the long term, however, so efforts to extend the boundaries of climate modeling and assessment merit long-term attention as well. Components of the effort include development of a variety of approaches to analysis, the maintenance of a clear a division between close-in decision support and science/policy research, and the development of funding institutions that can sustain integrated research over the long haul.

The Semantic Environment: Heuristics for a Cross-Context Human-Information Interaction Model

NASA Astrophysics Data System (ADS)

Resmini, Andrea; Rosati, Luca

This chapter introduces a multidisciplinary holistic approach for the general design of successful bridge experiences as a cross-context human-information interaction model. Nowadays it is common to interact through a number of different domains in order to communicate successfully, complete a task, or elicit a desired response: Users visit a reseller’s web site to find a specific item, book it, then drive to the closest store to complete their purchase. As such, one of the crucial challenges user experience design will face in the near future is how to structure and provide bridge experiences seamlessly spanning multiple communication channels or media formats for a specific purpose.

Building a Formal Model of a Human-Interactive System: Insights into the Integration of Formal Methods and Human Factors Engineering

NASA Technical Reports Server (NTRS)

Bolton, Matthew L.; Bass, Ellen J.

2009-01-01

Both the human factors engineering (HFE) and formal methods communities are concerned with finding and eliminating problems with safety-critical systems. This work discusses a modeling effort that leveraged methods from both fields to use model checking with HFE practices to perform formal verification of a human-interactive system. Despite the use of a seemingly simple target system, a patient controlled analgesia pump, the initial model proved to be difficult for the model checker to verify in a reasonable amount of time. This resulted in a number of model revisions that affected the HFE architectural, representativeness, and understandability goals of the effort. If formal methods are to meet the needs of the HFE community, additional modeling tools and technological developments are necessary.

Development of an Anatomically Accurate Finite Element Human Ocular Globe Model for Blast-Related Fluid-Structure Interaction Studies

DTIC Science & Technology

2017-02-01

ARL-TR-7945 ● FEB 2017 US Army Research Laboratory Development of an Anatomically Accurate Finite Element Human Ocular Globe...ARL-TR-7945 ● FEB 2017 US Army Research Laboratory Development of an Anatomically Accurate Finite Element Human Ocular Globe Model... Finite Element Human Ocular Globe Model for Blast-Related Fluid-Structure Interaction Studies 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM

A neural network model of metaphor understanding with dynamic interaction based on a statistical language analysis: targeting a human-like model.

PubMed

Terai, Asuka; Nakagawa, Masanori

2007-08-01

The purpose of this paper is to construct a model that represents the human process of understanding metaphors, focusing specifically on similes of the form an "A like B". Generally speaking, human beings are able to generate and understand many sorts of metaphors. This study constructs the model based on a probabilistic knowledge structure for concepts which is computed from a statistical analysis of a large-scale corpus. Consequently, this model is able to cover the many kinds of metaphors that human beings can generate. Moreover, the model implements the dynamic process of metaphor understanding by using a neural network with dynamic interactions. Finally, the validity of the model is confirmed by comparing model simulations with the results from a psychological experiment.

Evaluation of a computerized aid for creating human behavioral representations of human-computer interaction.

PubMed

Williams, Kent E; Voigt, Jeffrey R

2004-01-01

The research reported herein presents the results of an empirical evaluation that focused on the accuracy and reliability of cognitive models created using a computerized tool: the cognitive analysis tool for human-computer interaction (CAT-HCI). A sample of participants, expert in interacting with a newly developed tactical display for the U.S. Army's Bradley Fighting Vehicle, individually modeled their knowledge of 4 specific tasks employing the CAT-HCI tool. Measures of the accuracy and consistency of task models created by these task domain experts using the tool were compared with task models created by a double expert. The findings indicated a high degree of consistency and accuracy between the different "single experts" in the task domain in terms of the resultant models generated using the tool. Actual or potential applications of this research include assessing human-computer interaction complexity, determining the productivity of human-computer interfaces, and analyzing an interface design to determine whether methods can be automated.

Interactively human: Sharing time, constructing materiality.

PubMed

Roepstorff, Andreas

2013-06-01

Predictive processing models of cognition are promising an elegant way to unite action, perception, and learning. However, in the current formulations, they are species-unspecific and have very little particularly human about them. I propose to examine how, in this framework, humans can be able to massively interact and to build shared worlds that are both material and symbolic.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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.

Human-scale interaction for virtual model displays: a clear case for real tools

NASA Astrophysics Data System (ADS)

Williams, George C.; McDowall, Ian E.; Bolas, Mark T.

1998-04-01

We describe a hand-held user interface for interacting with virtual environments displayed on a Virtual Model Display. The tool, constructed entirely of transparent materials, is see-through. We render a graphical counterpart of the tool on the display and map it one-to-one with the real tool. This feature, combined with a capability for touch- sensitive, discrete input, results in a useful spatial input device that is visually versatile. We discuss the tool's design and interaction techniques it supports. Briefly, we look at the human factors issues and engineering challenges presented by this tool and, in general, by the class of hand-held user interfaces that are see-through.

Human-computer interaction in multitask situations

NASA Technical Reports Server (NTRS)

Rouse, W. B.

1977-01-01

Human-computer interaction in multitask decisionmaking situations is considered, and it is proposed that humans and computers have overlapping responsibilities. Queueing theory is employed to model this dynamic approach to the allocation of responsibility between human and computer. Results of simulation experiments are used to illustrate the effects of several system variables including number of tasks, mean time between arrivals of action-evoking events, human-computer speed mismatch, probability of computer error, probability of human error, and the level of feedback between human and computer. Current experimental efforts are discussed and the practical issues involved in designing human-computer systems for multitask situations are considered.

Study on Human-structure Dynamic Interaction in Civil Engineering

NASA Astrophysics Data System (ADS)

Gao, Feng; Cao, Li Lin; Li, Xing Hua

2018-06-01

The research of human-structure dynamic interaction are reviewed. Firstly, the influence of the crowd load on structural dynamic characteristics is introduced and the advantages and disadvantages of different crowd load models are analyzed. Then, discussing the influence of structural vibration on the human-induced load, especially the influence of different stiffness structures on the crowd load. Finally, questions about human-structure interaction that require further study are presented.

Deciphering microbial interactions in synthetic human gut microbiome communities.

PubMed

Venturelli, Ophelia S; Carr, Alex C; Fisher, Garth; Hsu, Ryan H; Lau, Rebecca; Bowen, Benjamin P; Hromada, Susan; Northen, Trent; Arkin, Adam P

2018-06-21

The ecological forces that govern the assembly and stability of the human gut microbiota remain unresolved. We developed a generalizable model-guided framework to predict higher-dimensional consortia from time-resolved measurements of lower-order assemblages. This method was employed to decipher microbial interactions in a diverse human gut microbiome synthetic community. We show that pairwise interactions are major drivers of multi-species community dynamics, as opposed to higher-order interactions. The inferred ecological network exhibits a high proportion of negative and frequent positive interactions. Ecological drivers and responsive recipient species were discovered in the network. Our model demonstrated that a prevalent positive and negative interaction topology enables robust coexistence by implementing a negative feedback loop that balances disparities in monospecies fitness levels. We show that negative interactions could generate history-dependent responses of initial species proportions that frequently do not originate from bistability. Measurements of extracellular metabolites illuminated the metabolic capabilities of monospecies and potential molecular basis of microbial interactions. In sum, these methods defined the ecological roles of major human-associated intestinal species and illuminated design principles of microbial communities. © 2018 The Authors. Published under the terms of the CC BY 4.0 license.

The human dynamic clamp as a paradigm for social interaction

PubMed Central

Dumas, Guillaume; de Guzman, Gonzalo C.; Tognoli, Emmanuelle; Kelso, J. A. Scott

2014-01-01

Social neuroscience has called for new experimental paradigms aimed toward real-time interactions. A distinctive feature of interactions is mutual information exchange: One member of a pair changes in response to the other while simultaneously producing actions that alter the other. Combining mathematical and neurophysiological methods, we introduce a paradigm called the human dynamic clamp (HDC), to directly manipulate the interaction or coupling between a human and a surrogate constructed to behave like a human. Inspired by the dynamic clamp used so productively in cellular neuroscience, the HDC allows a person to interact in real time with a virtual partner itself driven by well-established models of coordination dynamics. People coordinate hand movements with the visually observed movements of a virtual hand, the parameters of which depend on input from the subject’s own movements. We demonstrate that HDC can be extended to cover a broad repertoire of human behavior, including rhythmic and discrete movements, adaptation to changes of pacing, and behavioral skill learning as specified by a virtual “teacher.” We propose HDC as a general paradigm, best implemented when empirically verified theoretical or mathematical models have been developed in a particular scientific field. The HDC paradigm is powerful because it provides an opportunity to explore parameter ranges and perturbations that are not easily accessible in ordinary human interactions. The HDC not only enables to test the veracity of theoretical models, it also illuminates features that are not always apparent in real-time human social interactions and the brain correlates thereof. PMID:25114256

The human dynamic clamp as a paradigm for social interaction.

PubMed

Dumas, Guillaume; de Guzman, Gonzalo C; Tognoli, Emmanuelle; Kelso, J A Scott

2014-09-02

Social neuroscience has called for new experimental paradigms aimed toward real-time interactions. A distinctive feature of interactions is mutual information exchange: One member of a pair changes in response to the other while simultaneously producing actions that alter the other. Combining mathematical and neurophysiological methods, we introduce a paradigm called the human dynamic clamp (HDC), to directly manipulate the interaction or coupling between a human and a surrogate constructed to behave like a human. Inspired by the dynamic clamp used so productively in cellular neuroscience, the HDC allows a person to interact in real time with a virtual partner itself driven by well-established models of coordination dynamics. People coordinate hand movements with the visually observed movements of a virtual hand, the parameters of which depend on input from the subject's own movements. We demonstrate that HDC can be extended to cover a broad repertoire of human behavior, including rhythmic and discrete movements, adaptation to changes of pacing, and behavioral skill learning as specified by a virtual "teacher." We propose HDC as a general paradigm, best implemented when empirically verified theoretical or mathematical models have been developed in a particular scientific field. The HDC paradigm is powerful because it provides an opportunity to explore parameter ranges and perturbations that are not easily accessible in ordinary human interactions. The HDC not only enables to test the veracity of theoretical models, it also illuminates features that are not always apparent in real-time human social interactions and the brain correlates thereof.

Insights from Modeling the Integrated Climate, Biogeochemical Cycles, Human Activities and Their Interactions in the ACME Earth System Model

NASA Astrophysics Data System (ADS)

Leung, L. R.; Thornton, P. E.; Riley, W. J.; Calvin, K. V.

2017-12-01

Towards the goal of understanding the contributions from natural and managed systems to current and future greenhouse gas fluxes and carbon-climate and carbon-CO2 feedbacks, efforts have been underway to improve representations of the terrestrial, river, and human components of the ACME earth system model. Broadly, our efforts include implementation and comparison of approaches to represent the nutrient cycles and nutrient limitations on ecosystem production, extending the river transport model to represent sediment and riverine biogeochemistry, and coupling of human systems such as irrigation, reservoir operations, and energy and land use with the ACME land and river components. Numerical experiments have been designed to understand how terrestrial carbon, nitrogen, and phosphorus cycles regulate climate system feedbacks and the sensitivity of the feedbacks to different model treatments, examine key processes governing sediment and biogeochemistry in the rivers and their role in the carbon cycle, and exploring the impacts of human systems in perturbing the hydrological and carbon cycles and their interactions. This presentation will briefly introduce the ACME modeling approaches and discuss preliminary results and insights from numerical experiments that lay the foundation for improving understanding of the integrated climate-biogeochemistry-human system.

Spectroscopic and molecular modeling studies of the interaction between cytidine and human serum albumin and its analytical application.

PubMed

Cui, Fengling; Wang, Junli; Yao, Xiaojun; Wang, Li; Zhang, Qiangzhai; Qu, Guirong

In this study, the interaction between cytidine and human serum albumin (HSA) was investigated for the first time by fluorescence spectroscopy in combination with UV absorption spectrum and molecular modeling under simulative physiological conditions. Experimental results indicated that cytidine had a strong ability to quench the intrinsic fluorescence of human serum albumin. The binding constants (K) at different temperatures, thermodynamic parameter enthalpy changes (DeltaH) and entropy changes (DeltaS) of HSA-cytidine had been calculated according to the relevant fluorescence data, which indicated that the hydrophobic and electrostatic interactions played a major role, which was in agreement with the results of molecular modeling study. In addition, the effects of other ions on the binding constants were also studied. Furthermore, synchronous fluorescence technology was successfully applied to the determination of human serum albumin added into the cytidine solution.

Ferromagnetic interaction model of activity level in workplace communication

NASA Astrophysics Data System (ADS)

Akitomi, Tomoaki; Ara, Koji; Watanabe, Jun-ichiro; Yano, Kazuo

2013-03-01

The nature of human-human interaction, specifically, how people synchronize with each other in multiple-participant conversations, is described by a ferromagnetic interaction model of people’s activity levels. We found two microscopic human interaction characteristics from a real-environment face-to-face conversation. The first characteristic is that people quite regularly synchronize their activity level with that of the other participants in a conversation. The second characteristic is that the degree of synchronization increases as the number of participants increases. Based on these microscopic ferromagnetic characteristics, a “conversation activity level” was modeled according to the Ising model. The results of a simulation of activity level based on this model well reproduce macroscopic experimental measurements of activity level. This model will give a new insight into how people interact with each other in a conversation.

Interactions between human osteoblasts and prostate cancer cells in a novel 3D in vitro model

PubMed Central

Sieh, Shirly; Lubik, Amy A; Clements, Judith A; Nelson, Colleen C

2010-01-01

Cell-cell and cell-matrix interactions play a major role in tumor morphogenesis and cancer metastasis. Therefore, it is crucial to create a model with a biomimetic microenvironment that allows such interactions to fully represent the pathophysiology of a disease for an in vitro study. This is achievable by using three-dimensional (3D) models instead of conventional two-dimensional (2D) cultures with the aid of tissue engineering technology. We are now able to better address the complex intercellular interactions underlying prostate cancer (CaP) bone metastasis through such models. In this study, we assessed the interaction of CaP cells and human osteoblasts (hOBs) within a tissue engineered bone (TEB) construct. Consistent with other in vivo studies, our findings show that intercellular and CaP cell-bone matrix interactions lead to elevated levels of matrix metalloproteinases, steroidogenic enzymes and the CaP biomarker, prostate specific antigen (PSA); all associated with CaP metastasis. Hence, it highlights the physiological relevance of this model. We believe that this model will provide new insights for understanding of the previously poorly understood molecular mechanisms of bone metastasis, which will foster further translational studies, and ultimately offer a potential tool for drug screening. PMID:21197221

Effects of molecular model, ionic strength, divalent ions, and hydrophobic interaction on human neurofilament conformation

NASA Astrophysics Data System (ADS)

Lee, Joonseong; Kim, Seonghoon; Chang, Rakwoo; Jayanthi, Lakshmi; Gebremichael, Yeshitila

2013-01-01

The present study examines the effects of the model dependence, ionic strength, divalent ions, and hydrophobic interaction on the structural organization of the human neurofilament (NF) brush, using canonical ensemble Monte Carlo (MC) simulations of a coarse-grained model with the amino-acid resolution. The model simplifies the interactions between the NF core and the sidearm or between the sidearms by the sum of excluded volume, electrostatic, and hydrophobic interactions, where both monovalent salt ions and solvents are implicitly incorporated into the electrostatic interaction potential. Several important observations are made from the MC simulations of the coarse-grained model NF systems. First, the mean-field type description of monovalent salt ions works reasonably well in the NF system. Second, the manner by which the NF sidearms are arranged on the surface of the NF backbone core has little influence on the lateral extension of NF sidearms. Third, the lateral extension of the NF sidearms is highly affected by the ionic strength of the system: at low ionic strength, NF-M is most extended but at high ionic strength, NF-H is more stretched out because of the effective screening of the electrostatic interaction. Fourth, the presence of Ca2 + ions induces the attraction between negatively charged residues, which leads to the contraction of the overall NF extension. Finally, the introduction of hydrophobic interaction does not change the general structural organization of the NF sidearms except that the overall extension is contracted.

Transient interaction model of electromagnetic field generated by lightning current pulses and human body

NASA Astrophysics Data System (ADS)

Iváncsy, T.; Kiss, I.; Szücs, L.; Tamus, Z. Á.

2015-10-01

The lightning current generates time-varying magnetic field near the down- conductor and the down-conductors are mounted on the wall of the buildings where residential places might be situated. It is well known that the rapidly changing magnetic fields can generate dangerous eddy currents in the human body.The higher duration and gradient of the magnetic field can cause potentially life threatening cardiac stimulation. The coupling mechanism between the electromagnetic field and the human body is based on a well-known physical phenomena (e.g. Faradays law of induction). However, the calculation of the induced current is very complicated because the shape of the organs is complex and the determination of the material properties of living tissues is difficult, as well. Our previous study revealed that the cardiac stimulation is independent of the rising time of the lightning current and only the peak of the current counts. In this study, the authors introduce an improved model of the interaction of electromagnetic fields of lighting current near down-conductor and human body. Our previous models are based on the quasi stationer field calculations, the new improved model is a transient model. This is because the magnetic field around the down-conductor and in the human body can be determined more precisely, therefore the dangerous currents in the body can be estimated.

Cognitive engineering models: A prerequisite to the design of human-computer interaction in complex dynamic systems

NASA Technical Reports Server (NTRS)

Mitchell, Christine M.

1993-01-01

This chapter examines a class of human-computer interaction applications, specifically the design of human-computer interaction for the operators of complex systems. Such systems include space systems (e.g., manned systems such as the Shuttle or space station, and unmanned systems such as NASA scientific satellites), aviation systems (e.g., the flight deck of 'glass cockpit' airplanes or air traffic control) and industrial systems (e.g., power plants, telephone networks, and sophisticated, e.g., 'lights out,' manufacturing facilities). The main body of human-computer interaction (HCI) research complements but does not directly address the primary issues involved in human-computer interaction design for operators of complex systems. Interfaces to complex systems are somewhat special. The 'user' in such systems - i.e., the human operator responsible for safe and effective system operation - is highly skilled, someone who in human-machine systems engineering is sometimes characterized as 'well trained, well motivated'. The 'job' or task context is paramount and, thus, human-computer interaction is subordinate to human job interaction. The design of human interaction with complex systems, i.e., the design of human job interaction, is sometimes called cognitive engineering.

DigitalHuman (DH): An Integrative Mathematical Model ofHuman Physiology

NASA Technical Reports Server (NTRS)

Hester, Robert L.; Summers, Richard L.; lIescu, Radu; Esters, Joyee; Coleman, Thomas G.

2010-01-01

Mathematical models and simulation are important tools in discovering the key causal relationships governing physiological processes and improving medical intervention when physiological complexity is a central issue. We have developed a model of integrative human physiology called DigitalHuman (DH) consisting of -5000 variables modeling human physiology describing cardiovascular, renal, respiratory, endocrine, neural and metabolic physiology. Users can view time-dependent solutions and interactively introduce perturbations by altering numerical parameters to investigate new hypotheses. The variables, parameters and quantitative relationships as well as all other model details are described in XML text files. All aspects of the model, including the mathematical equations describing the physiological processes are written in XML open source, text-readable files. Model structure is based upon empirical data of physiological responses documented within the peer-reviewed literature. The model can be used to understand proposed physiological mechanisms and physiological interactions that may not be otherwise intUitively evident. Some of the current uses of this model include the analyses of renal control of blood pressure, the central role of the liver in creating and maintaining insulin resistance, and the mechanisms causing orthostatic hypotension in astronauts. Additionally the open source aspect of the modeling environment allows any investigator to add detailed descriptions of human physiology to test new concepts. The model accurately predicts both qualitative and more importantly quantitative changes in clinically and experimentally observed responses. DigitalHuman provides scientists a modeling environment to understand the complex interactions of integrative physiology. This research was supported by.NIH HL 51971, NSF EPSCoR, and NASA

A model of cerebrocerebello-spinomuscular interaction in the sagittal control of human walking.

PubMed

Jo, Sungho; Massaquoi, Steve G

2007-03-01

A computationally developed model of human upright balance control (Jo and Massaquoi on Biol cybern 91:188-202, 2004) has been enhanced to describe biped walking in the sagittal plane. The model incorporates (a) non-linear muscle mechanics having activation level -dependent impedance, (b) scheduled cerebrocerebellar interaction for control of center of mass position and trunk pitch angle, (c) rectangular pulse-like feedforward commands from a brainstem/ spinal pattern generator, and (d) segmental reflex modulation of muscular synergies to refine inter-joint coordination. The model can stand when muscles around the ankle are coactivated. When trigger signals activate, the model transitions from standing still to walking at 1.5 m/s. Simulated natural walking displays none of seven pathological gait features. The model can simulate different walking speeds by tuning the amplitude and frequency in spinal pattern generator. The walking is stable against forward and backward pushes of up to 70 and 75 N, respectively, and with sudden changes in trunk mass of up to 18%. The sensitivity of the model to changes in neural parameters and the predicted behavioral results of simulated neural system lesions are examined. The deficit gait simulations may be useful to support the functional and anatomical correspondences of the model. The model demonstrates that basic human-like walking can be achieved by a hierarchical structure of stabilized-long loop feedback and synergy-mediated feedforward controls. In particular, internal models of body dynamics are not required.

The Application of Humanized Mouse Models for the Study of Human Exclusive Viruses.

PubMed

Vahedi, Fatemeh; Giles, Elizabeth C; Ashkar, Ali A

2017-01-01

The symbiosis between humans and viruses has allowed human tropic pathogens to evolve intricate means of modulating the human immune response to ensure its survival among the human population. In doing so, these viruses have developed profound mechanisms that mesh closely with our human biology. The establishment of this intimate relationship has created a species-specific barrier to infection, restricting the virus-associated pathologies to humans. This specificity diminishes the utility of traditional animal models. Humanized mice offer a model unique to all other means of study, providing an in vivo platform for the careful examination of human tropic viruses and their interaction with human cells and tissues. These types of animal models have provided a reliable medium for the study of human-virus interactions, a relationship that could otherwise not be investigated without questionable relevance to humans.

A dynamical systems model of progesterone receptor interactions with inflammation in human parturition.

PubMed

Brubaker, Douglas; Barbaro, Alethea; R Chance, Mark; Mesiano, Sam

2016-08-19

Progesterone promotes uterine relaxation and is essential for the maintenance of pregnancy. Withdrawal of progesterone activity and increased inflammation within the uterine tissues are key triggers for parturition. Progesterone actions in myometrial cells are mediated by two progesterone receptor (PR) isoforms, PR-A and PR-B, that function as ligand-activated transcription factors. PR-B mediates relaxatory actions of progesterone, in part, by decreasing myometrial cell responsiveness to pro-inflammatory stimuli. These same pro-inflammatory stimuli promote the expression of PR-A which inhibits the anti-inflammatory activity of PR-B. Competitive interaction between the progesterone receptors then augments myometrial responsiveness to pro-inflammatory stimuli. The interaction between PR-B transcriptional activity and inflammation in the pregnancy myometrium is examined using a dynamical systems model in which quiescence and labor are represented as phase-space equilibrium points. Our model shows that PR-B transcriptional activity and the inflammatory load determine the stability of the quiescent and laboring phenotypes. The model is tested using published transcriptome datasets describing the mRNA abundances in the myometrium before and after the onset of labor at term. Surrogate transcripts were selected to reflect PR-B transcriptional activity and inflammation status. The model coupling PR-B activity and inflammation predicts contractile status (i.e., laboring or quiescent) with high precision and recall and outperforms uncoupled single and two-gene classifiers. Linear stability analysis shows that phase space bifurcations exist in our model that may reflect the phenotypic states of the pregnancy uterus. The model describes a possible tipping point for the transition of the quiescent to the contractile laboring phenotype. Our model describes the functional interaction between the PR-A:PR-B hypothesis and tissue level inflammation in the pregnancy uterus and is a

The ‘hit’ phenomenon: a mathematical model of human dynamics interactions as a stochastic process

NASA Astrophysics Data System (ADS)

Ishii, Akira; Arakaki, Hisashi; Matsuda, Naoya; Umemura, Sanae; Urushidani, Tamiko; Yamagata, Naoya; Yoshida, Narihiko

2012-06-01

A mathematical model for the ‘hit’ phenomenon in entertainment within a society is presented as a stochastic process of human dynamics interactions. The model uses only the advertisement budget time distribution as an input, and word-of-mouth (WOM), represented by posts on social network systems, is used as data to make a comparison with the calculated results. The unit of time is days. The WOM distribution in time is found to be very close to the revenue distribution in time. Calculations for the Japanese motion picture market based on the mathematical model agree well with the actual revenue distribution in time.

An object-oriented computational model to study cardiopulmonary hemodynamic interactions in humans.

PubMed

Ngo, Chuong; Dahlmanns, Stephan; Vollmer, Thomas; Misgeld, Berno; Leonhardt, Steffen

2018-06-01

This work introduces an object-oriented computational model to study cardiopulmonary interactions in humans. Modeling was performed in object-oriented programing language Matlab Simscape, where model components are connected with each other through physical connections. Constitutive and phenomenological equations of model elements are implemented based on their non-linear pressure-volume or pressure-flow relationship. The model includes more than 30 physiological compartments, which belong either to the cardiovascular or respiratory system. The model considers non-linear behaviors of veins, pulmonary capillaries, collapsible airways, alveoli, and the chest wall. Model parameters were derisved based on literature values. Model validation was performed by comparing simulation results with clinical and animal data reported in literature. The model is able to provide quantitative values of alveolar, pleural, interstitial, aortic and ventricular pressures, as well as heart and lung volumes during spontaneous breathing and mechanical ventilation. Results of baseline simulation demonstrate the consistency of the assigned parameters. Simulation results during mechanical ventilation with PEEP trials can be directly compared with animal and clinical data given in literature. Object-oriented programming languages can be used to model interconnected systems including model non-linearities. The model provides a useful tool to investigate cardiopulmonary activity during spontaneous breathing and mechanical ventilation. Copyright © 2018 Elsevier B.V. All rights reserved.

Analysis of human emotion in human-robot interaction

NASA Astrophysics Data System (ADS)

Blar, Noraidah; Jafar, Fairul Azni; Abdullah, Nurhidayu; Muhammad, Mohd Nazrin; Kassim, Anuar Muhamed

2015-05-01

There is vast application of robots in human's works such as in industry, hospital, etc. Therefore, it is believed that human and robot can have a good collaboration to achieve an optimum result of work. The objectives of this project is to analyze human-robot collaboration and to understand humans feeling (kansei factors) when dealing with robot that robot should adapt to understand the humans' feeling. Researches currently are exploring in the area of human-robot interaction with the intention to reduce problems that subsist in today's civilization. Study had found that to make a good interaction between human and robot, first it is need to understand the abilities of each. Kansei Engineering in robotic was used to undergo the project. The project experiments were held by distributing questionnaire to students and technician. After that, the questionnaire results were analyzed by using SPSS analysis. Results from the analysis shown that there are five feelings which significant to the human in the human-robot interaction; anxious, fatigue, relaxed, peaceful, and impressed.

Modeling Human-Computer Decision Making with Covariance Structure Analysis.

ERIC Educational Resources Information Center

Coovert, Michael D.; And Others

Arguing that sufficient theory exists about the interplay between human information processing, computer systems, and the demands of various tasks to construct useful theories of human-computer interaction, this study presents a structural model of human-computer interaction and reports the results of various statistical analyses of this model.…

A Viral-Human Interactome Based on Structural Motif-Domain Interactions Captures the Human Infectome

PubMed Central

Guo, Xianwu; Rodríguez-Pérez, Mario A.

2013-01-01

Protein interactions between a pathogen and its host are fundamental in the establishment of the pathogen and underline the infection mechanism. In the present work, we developed a single predictive model for building a host-viral interactome based on the identification of structural descriptors from motif-domain interactions of protein complexes deposited in the Protein Data Bank (PDB). The structural descriptors were used for searching, in a database of protein sequences of human and five clinically important viruses; therefore, viral and human proteins sharing a descriptor were predicted as interacting proteins. The analysis of the host-viral interactome allowed to identify a set of new interactions that further explain molecular mechanism associated with viral infections and showed that it was able to capture human proteins already associated to viral infections (human infectome) and non-infectious diseases (human diseasome). The analysis of human proteins targeted by viral proteins in the context of a human interactome showed that their neighbors are enriched in proteins reported with differential expression under infection and disease conditions. It is expected that the findings of this work will contribute to the development of systems biology for infectious diseases, and help guide the rational identification and prioritization of novel drug targets. PMID:23951184

Is Human-Computer Interaction Social or Parasocial?

ERIC Educational Resources Information Center

Sundar, S. Shyam

Conducted in the attribution-research paradigm of social psychology, a study examined whether human-computer interaction is fundamentally social (as in human-human interaction) or parasocial (as in human-television interaction). All 30 subjects (drawn from an undergraduate class on communication) were exposed to an identical interaction with…

On the application of motivation theory to human factors/ergonomics: motivational design principles for human-technology interaction.

PubMed

Szalma, James L

2014-12-01

Motivation is a driving force in human-technology interaction. This paper represents an effort to (a) describe a theoretical model of motivation in human technology interaction, (b) provide design principles and guidelines based on this theory, and (c) describe a sequence of steps for the. evaluation of motivational factors in human-technology interaction. Motivation theory has been relatively neglected in human factors/ergonomics (HF/E). In both research and practice, the (implicit) assumption has been that the operator is already motivated or that motivation is an organizational concern and beyond the purview of HF/E. However, technology can induce task-related boredom (e.g., automation) that can be stressful and also increase system vulnerability to performance failures. A theoretical model of motivation in human-technology interaction is proposed, based on extension of the self-determination theory of motivation to HF/E. This model provides the basis for both future research and for development of practical recommendations for design. General principles and guidelines for motivational design are described as well as a sequence of steps for the design process. Human motivation is an important concern for HF/E research and practice. Procedures in the design of both simple and complex technologies can, and should, include the evaluation of motivational characteristics of the task, interface, or system. In addition, researchers should investigate these factors in specific human-technology domains. The theory, principles, and guidelines described here can be incorporated into existing techniques for task analysis and for interface and system design.

Optimization of neural network architecture using genetic programming improves detection and modeling of gene-gene interactions in studies of human diseases

PubMed Central

Ritchie, Marylyn D; White, Bill C; Parker, Joel S; Hahn, Lance W; Moore, Jason H

2003-01-01

Background Appropriate definition of neural network architecture prior to data analysis is crucial for successful data mining. This can be challenging when the underlying model of the data is unknown. The goal of this study was to determine whether optimizing neural network architecture using genetic programming as a machine learning strategy would improve the ability of neural networks to model and detect nonlinear interactions among genes in studies of common human diseases. Results Using simulated data, we show that a genetic programming optimized neural network approach is able to model gene-gene interactions as well as a traditional back propagation neural network. Furthermore, the genetic programming optimized neural network is better than the traditional back propagation neural network approach in terms of predictive ability and power to detect gene-gene interactions when non-functional polymorphisms are present. Conclusion This study suggests that a machine learning strategy for optimizing neural network architecture may be preferable to traditional trial-and-error approaches for the identification and characterization of gene-gene interactions in common, complex human diseases. PMID:12846935

Semantic Likelihood Models for Bayesian Inference in Human-Robot Interaction

NASA Astrophysics Data System (ADS)

Sweet, Nicholas

Autonomous systems, particularly unmanned aerial systems (UAS), remain limited in au- tonomous capabilities largely due to a poor understanding of their environment. Current sensors simply do not match human perceptive capabilities, impeding progress towards full autonomy. Recent work has shown the value of humans as sources of information within a human-robot team; in target applications, communicating human-generated 'soft data' to autonomous systems enables higher levels of autonomy through large, efficient information gains. This requires development of a 'human sensor model' that allows soft data fusion through Bayesian inference to update the probabilistic belief representations maintained by autonomous systems. Current human sensor models that capture linguistic inputs as semantic information are limited in their ability to generalize likelihood functions for semantic statements: they may be learned from dense data; they do not exploit the contextual information embedded within groundings; and they often limit human input to restrictive and simplistic interfaces. This work provides mechanisms to synthesize human sensor models from constraints based on easily attainable a priori knowledge, develops compression techniques to capture information-dense semantics, and investigates the problem of capturing and fusing semantic information contained within unstructured natural language. A robotic experimental testbed is also developed to validate the above contributions.

Structural principles within the human-virus protein-protein interaction network

PubMed Central

Franzosa, Eric A.; Xia, Yu

2011-01-01

General properties of the antagonistic biomolecular interactions between viruses and their hosts (exogenous interactions) remain poorly understood, and may differ significantly from known principles governing the cooperative interactions within the host (endogenous interactions). Systems biology approaches have been applied to study the combined interaction networks of virus and human proteins, but such efforts have so far revealed only low-resolution patterns of host-virus interaction. Here, we layer curated and predicted 3D structural models of human-virus and human-human protein complexes on top of traditional interaction networks to reconstruct the human-virus structural interaction network. This approach reveals atomic resolution, mechanistic patterns of host-virus interaction, and facilitates systematic comparison with the host’s endogenous interactions. We find that exogenous interfaces tend to overlap with and mimic endogenous interfaces, thereby competing with endogenous binding partners. The endogenous interfaces mimicked by viral proteins tend to participate in multiple endogenous interactions which are transient and regulatory in nature. While interface overlap in the endogenous network results largely from gene duplication followed by divergent evolution, viral proteins frequently achieve interface mimicry without any sequence or structural similarity to an endogenous binding partner. Finally, while endogenous interfaces tend to evolve more slowly than the rest of the protein surface, exogenous interfaces—including many sites of endogenous-exogenous overlap—tend to evolve faster, consistent with an evolutionary “arms race” between host and pathogen. These significant biophysical, functional, and evolutionary differences between host-pathogen and within-host protein-protein interactions highlight the distinct consequences of antagonism versus cooperation in biological networks. PMID:21680884

The Use of Human Liver Cell Model and Cytochrome P450 Substrate-Inhibitor Panel for Studies of Dasatinib and Warfarin Interactions.

PubMed

Zakharyants, A A; Burmistrova, O A; Poloznikov, A A

2017-02-01

The possibility of interactions between warfarin and dasatinib and their interactions with other drugs metabolized by cytochrome P450 isoform CYP3A4 was demonstrated using a previously created cytochrome P450 substrate-inhibitor panel for preclinical in vitro studies of drug biotransformation on a 3D histotypical microfluidic cell model of human liver (liver-on-a-chip technology). Dasatinib and warfarin are inhibitors of CYP2C19 isoform and hence, can interfere the drugs metabolized by this isoform. Our findings are in line with the data obtained on primary culture of human hepatocytes and suggest that the model can be used in preclinical in vitro studies of drugs.

A study on the application of voice interaction in automotive human machine interface experience design

NASA Astrophysics Data System (ADS)

Huang, Zhaohui; Huang, Xiemin

2018-04-01

This paper, firstly, introduces the application trend of the integration of multi-channel interactions in automotive HMI ((Human Machine Interface) from complex information models faced by existing automotive HMI and describes various interaction modes. By comparing voice interaction and touch screen, gestures and other interaction modes, the potential and feasibility of voice interaction in automotive HMI experience design are concluded. Then, the related theories of voice interaction, identification technologies, human beings' cognitive models of voices and voice design methods are further explored. And the research priority of this paper is proposed, i.e. how to design voice interaction to create more humane task-oriented dialogue scenarios to enhance interactive experiences of automotive HMI. The specific scenarios in driving behaviors suitable for the use of voice interaction are studied and classified, and the usability principles and key elements for automotive HMI voice design are proposed according to the scenario features. Then, through the user participatory usability testing experiment, the dialogue processes of voice interaction in automotive HMI are defined. The logics and grammars in voice interaction are classified according to the experimental results, and the mental models in the interaction processes are analyzed. At last, the voice interaction design method to create the humane task-oriented dialogue scenarios in the driving environment is proposed.

Layout Design of Human-Machine Interaction Interface of Cabin Based on Cognitive Ergonomics and GA-ACA.

PubMed

Deng, Li; Wang, Guohua; Yu, Suihuai

2016-01-01

In order to consider the psychological cognitive characteristics affecting operating comfort and realize the automatic layout design, cognitive ergonomics and GA-ACA (genetic algorithm and ant colony algorithm) were introduced into the layout design of human-machine interaction interface. First, from the perspective of cognitive psychology, according to the information processing process, the cognitive model of human-machine interaction interface was established. Then, the human cognitive characteristics were analyzed, and the layout principles of human-machine interaction interface were summarized as the constraints in layout design. Again, the expression form of fitness function, pheromone, and heuristic information for the layout optimization of cabin was studied. The layout design model of human-machine interaction interface was established based on GA-ACA. At last, a layout design system was developed based on this model. For validation, the human-machine interaction interface layout design of drilling rig control room was taken as an example, and the optimization result showed the feasibility and effectiveness of the proposed method.

Layout Design of Human-Machine Interaction Interface of Cabin Based on Cognitive Ergonomics and GA-ACA

PubMed Central

Deng, Li; Wang, Guohua; Yu, Suihuai

2016-01-01

In order to consider the psychological cognitive characteristics affecting operating comfort and realize the automatic layout design, cognitive ergonomics and GA-ACA (genetic algorithm and ant colony algorithm) were introduced into the layout design of human-machine interaction interface. First, from the perspective of cognitive psychology, according to the information processing process, the cognitive model of human-machine interaction interface was established. Then, the human cognitive characteristics were analyzed, and the layout principles of human-machine interaction interface were summarized as the constraints in layout design. Again, the expression form of fitness function, pheromone, and heuristic information for the layout optimization of cabin was studied. The layout design model of human-machine interaction interface was established based on GA-ACA. At last, a layout design system was developed based on this model. For validation, the human-machine interaction interface layout design of drilling rig control room was taken as an example, and the optimization result showed the feasibility and effectiveness of the proposed method. PMID:26884745

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

PubMed

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

2017-01-01

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

Towards quantifying dynamic human-human physical interactions for robot assisted stroke therapy.

PubMed

Mohan, Mayumi; Mendonca, Rochelle; Johnson, Michelle J

2017-07-01

Human-Robot Interaction is a prominent field of robotics today. Knowledge of human-human physical interaction can prove vital in creating dynamic physical interactions between human and robots. Most of the current work in studying this interaction has been from a haptic perspective. Through this paper, we present metrics that can be used to identify if a physical interaction occurred between two people using kinematics. We present a simple Activity of Daily Living (ADL) task which involves a simple interaction. We show that we can use these metrics to successfully identify interactions.

Human intestinal transporter database: QSAR modeling and virtual profiling of drug uptake, efflux and interactions.

PubMed

Sedykh, Alexander; Fourches, Denis; Duan, Jianmin; Hucke, Oliver; Garneau, Michel; Zhu, Hao; Bonneau, Pierre; Tropsha, Alexander

2013-04-01

Membrane transporters mediate many biological effects of chemicals and play a major role in pharmacokinetics and drug resistance. The selection of viable drug candidates among biologically active compounds requires the assessment of their transporter interaction profiles. Using public sources, we have assembled and curated the largest, to our knowledge, human intestinal transporter database (>5,000 interaction entries for >3,700 molecules). This data was used to develop thoroughly validated classification Quantitative Structure-Activity Relationship (QSAR) models of transport and/or inhibition of several major transporters including MDR1, BCRP, MRP1-4, PEPT1, ASBT, OATP2B1, OCT1, and MCT1. QSAR models have been developed with advanced machine learning techniques such as Support Vector Machines, Random Forest, and k Nearest Neighbors using Dragon and MOE chemical descriptors. These models afforded high external prediction accuracies of 71-100% estimated by 5-fold external validation, and showed hit retrieval rates with up to 20-fold enrichment in the virtual screening of DrugBank compounds. The compendium of predictive QSAR models developed in this study can be used for virtual profiling of drug candidates and/or environmental agents with the optimal transporter profiles.

Predictive Mechanisms Are Not Involved the Same Way during Human-Human vs. Human-Machine Interactions: A Review

PubMed Central

Sahaï, Aïsha; Pacherie, Elisabeth; Grynszpan, Ouriel; Berberian, Bruno

2017-01-01

Nowadays, interactions with others do not only involve human peers but also automated systems. Many studies suggest that the motor predictive systems that are engaged during action execution are also involved during joint actions with peers and during other human generated action observation. Indeed, the comparator model hypothesis suggests that the comparison between a predicted state and an estimated real state enables motor control, and by a similar functioning, understanding and anticipating observed actions. Such a mechanism allows making predictions about an ongoing action, and is essential to action regulation, especially during joint actions with peers. Interestingly, the same comparison process has been shown to be involved in the construction of an individual's sense of agency, both for self-generated and observed other human generated actions. However, the implication of such predictive mechanisms during interactions with machines is not consensual, probably due to the high heterogeneousness of the automata used in the experimentations, from very simplistic devices to full humanoid robots. The discrepancies that are observed during human/machine interactions could arise from the absence of action/observation matching abilities when interacting with traditional low-level automata. Consistently, the difficulties to build a joint agency with this kind of machines could stem from the same problem. In this context, we aim to review the studies investigating predictive mechanisms during social interactions with humans and with automated artificial systems. We will start by presenting human data that show the involvement of predictions in action control and in the sense of agency during social interactions. Thereafter, we will confront this literature with data from the robotic field. Finally, we will address the upcoming issues in the field of robotics related to automated systems aimed at acting as collaborative agents. PMID:29081744

Prosthetic Leg Control in the Nullspace of Human Interaction.

PubMed

Gregg, Robert D; Martin, Anne E

2016-07-01

Recent work has extended the control method of virtual constraints, originally developed for autonomous walking robots, to powered prosthetic legs for lower-limb amputees. Virtual constraints define desired joint patterns as functions of a mechanical phasing variable, which are typically enforced by torque control laws that linearize the output dynamics associated with the virtual constraints. However, the output dynamics of a powered prosthetic leg generally depend on the human interaction forces, which must be measured and canceled by the feedback linearizing control law. This feedback requires expensive multi-axis load cells, and actively canceling the interaction forces may minimize the human's influence over the prosthesis. To address these limitations, this paper proposes a method for projecting virtual constraints into the nullspace of the human interaction terms in the output dynamics. The projected virtual constraints naturally render the output dynamics invariant with respect to the human interaction forces, which instead enter into the internal dynamics of the partially linearized prosthetic system. This method is illustrated with simulations of a transfemoral amputee model walking with a powered knee-ankle prosthesis that is controlled via virtual constraints with and without the proposed projection.

GABAergic modulation of human social interaction in a prisoner's dilemma model by acute administration of alprazolam.

PubMed

Lane, Scott D; Gowin, Joshua L

2009-10-01

Recent work in neuroeconomics has used game theory paradigms to examine neural systems that subserve human social interaction and decision making. Attempts to modify social interaction through pharmacological manipulation have been less common. Here we show dose-dependent modification of human social behavior in a prisoner's dilemma model after acute administration of the γ-aminobutyric acid (GABA)-A modulating benzodiazepine alprazolam. Nine healthy adults received doses of placebo, 0.5, 1.0, and 2.0 mg alprazolam in a counterbalanced within-subject design, while completing multiple test blocks per day on an iterated prisoner's dilemma game. During test blocks in which peak subjective effects of alprazolam were reported, cooperative choices were significantly decreased as a function of dose. Consistent with previous reports showing that high acute doses of GABA-modulating drugs are associated with violence and other antisocial behavior, our data suggest that at sufficiently high doses, alprazolam can decrease cooperation. These behavioral changes may be facilitated by changes in inhibitory control facilitated by GABA. Game theory paradigms may prove useful in behavioral pharmacology studies seeking to measure social interaction, and may help inform the emerging field of neuroeconomics.

Modeling and simulation studies of human β3 adrenergic receptor and its interactions with agonists.

PubMed

Sahi, Shakti; Tewatia, Parul; Malik, Balwant K

2012-12-01

β3 adrenergic receptor (β3AR) is known to mediate various pharmacological and physiological effects such as thermogenesis in brown adipocytes, lipolysis in white adipocytes, glucose homeostasis and intestinal smooth muscle relaxation. Several efforts have been made in this field to understand their function and regulation in different human tissues and they have emerged as potential attractive targets in drug discovery for the treatment of diabetes, depression, obesity etc. Although the crystal structures of Bovine Rhodopsin and β2 adrenergic receptor have been resolved, to date there is no three dimensional structural information on β3AR. Our aim in this study was to model 3D structure of β3AR by various molecular modeling and simulation techniques. In this paper, we describe a refined predicted model of β3AR using different algorithms for structure prediction. The structural refinement and minimization of the generated 3D model of β3AR were done by Schrodinger suite 9.1. Docking studies of β3AR model with the known agonists enabled us to identify specific residues, viz, Asp 117, Ser 208, Ser 209, Ser 212, Arg 315, Asn 332, within the β3AR binding pocket, which might play an important role in ligand binding. Receptor ligand interaction studies clearly indicated that these five residues showed strong hydrogen bonding interactions with the ligands. The results have been correlated with the experimental data available. The predicted ligand binding interactions and the simulation studies validate the methods used to predict the 3D-structure.

Modeling strategic behavior in human-automation interaction - Why an 'aid' can (and should) go unused

NASA Technical Reports Server (NTRS)

Kirlik, Alex

1993-01-01

Task-offload aids (e.g., an autopilot, an 'intelligent' assistant) can be selectively engaged by the human operator to dynamically delegate tasks to automation. Introducing such aids eliminates some task demands but creates new ones associated with programming, engaging, and disengaging the aiding device via an interface. The burdens associated with managing automation can sometimes outweigh the potential benefits of automation to improved system performance. Aid design parameters and features of the overall multitask context combine to determine whether or not a task-offload aid will effectively support the operator. A modeling and sensitivity analysis approach is presented that identifies effective strategies for human-automation interaction as a function of three task-context parameters and three aid design parameters. The analysis and modeling approaches provide resources for predicting how a well-adapted operator will use a given task-offload aid, and for specifying aid design features that ensure that automation will provide effective operator support in a multitask environment.

A concentrated parameter model for the human cardiovascular system including heart valve dynamics and atrioventricular interaction.

PubMed

Korakianitis, Theodosios; Shi, Yubing

2006-09-01

Numerical modeling of the human cardiovascular system has always been an active research direction since the 19th century. In the past, various simulation models of different complexities were proposed for different research purposes. In this paper, an improved numerical model to study the dynamic function of the human circulation system is proposed. In the development of the mathematical model, the heart chambers are described with a variable elastance model. The systemic and pulmonary loops are described based on the resistance-compliance-inertia concept by considering local effects of flow friction, elasticity of blood vessels and inertia of blood in different segments of the blood vessels. As an advancement from previous models, heart valve dynamics and atrioventricular interaction, including atrial contraction and motion of the annulus fibrosus, are specifically modeled. With these improvements the developed model can predict several important features that were missing in previous numerical models, including regurgitant flow on heart valve closure, the value of E/A velocity ratio in mitral flow, the motion of the annulus fibrosus (called the KG diaphragm pumping action), etc. These features have important clinical meaning and their changes are often related to cardiovascular diseases. Successful simulation of these features enhances the accuracy of simulations of cardiovascular dynamics, and helps in clinical studies of cardiac function.

Predicting human genetic interactions from cancer genome evolution.

PubMed

Lu, Xiaowen; Megchelenbrink, Wout; Notebaart, Richard A; Huynen, Martijn A

2015-01-01

Synthetic Lethal (SL) genetic interactions play a key role in various types of biological research, ranging from understanding genotype-phenotype relationships to identifying drug-targets against cancer. Despite recent advances in empirical measuring SL interactions in human cells, the human genetic interaction map is far from complete. Here, we present a novel approach to predict this map by exploiting patterns in cancer genome evolution. First, we show that empirically determined SL interactions are reflected in various gene presence, absence, and duplication patterns in hundreds of cancer genomes. The most evident pattern that we discovered is that when one member of an SL interaction gene pair is lost, the other gene tends not to be lost, i.e. the absence of co-loss. This observation is in line with expectation, because the loss of an SL interacting pair will be lethal to the cancer cell. SL interactions are also reflected in gene expression profiles, such as an under representation of cases where the genes in an SL pair are both under expressed, and an over representation of cases where one gene of an SL pair is under expressed, while the other one is over expressed. We integrated the various previously unknown cancer genome patterns and the gene expression patterns into a computational model to identify SL pairs. This simple, genome-wide model achieves a high prediction power (AUC = 0.75) for known genetic interactions. It allows us to present for the first time a comprehensive genome-wide list of SL interactions with a high estimated prediction precision, covering up to 591,000 gene pairs. This unique list can potentially be used in various application areas ranging from biotechnology to medical genetics.

CD4-gp120 interaction interface - a gateway for HIV-1 infection in human: molecular network, modeling and docking studies.

PubMed

Pandey, Deeksha; Podder, Avijit; Pandit, Mansi; Latha, Narayanan

2017-09-01

The major causative agent for Acquired Immune Deficiency Syndrome (AIDS) is Human Immunodeficiency Virus-1 (HIV-1). HIV-1 is a predominant subtype of HIV which counts on human cellular mechanism virtually in every aspect of its life cycle. Binding of viral envelope glycoprotein-gp120 with human cell surface CD4 receptor triggers the early infection stage of HIV-1. This study focuses on the interaction interface between these two proteins that play a crucial role for viral infectivity. The CD4-gp120 interaction interface has been studied through a comprehensive protein-protein interaction network (PPIN) analysis and highlighted as a useful step towards identifying potential therapeutic drug targets against HIV-1 infection. We prioritized gp41, Nef and Tat proteins of HIV-1 as valuable drug targets at early stage of viral infection. Lack of crystal structure has made it difficult to understand the biological implication of these proteins during disease progression. Here, computational protein modeling techniques and molecular dynamics simulations were performed to generate three-dimensional models of these targets. Besides, molecular docking was initiated to determine the desirability of these target proteins for already available HIV-1 specific drugs which indicates the usefulness of these protein structures to identify an effective drug combination therapy against AIDS.

Human systems dynamics: Toward a computational model

NASA Astrophysics Data System (ADS)

Eoyang, Glenda H.

2012-09-01

A robust and reliable computational model of complex human systems dynamics could support advancements in theory and practice for social systems at all levels, from intrapersonal experience to global politics and economics. Models of human interactions have evolved from traditional, Newtonian systems assumptions, which served a variety of practical and theoretical needs of the past. Another class of models has been inspired and informed by models and methods from nonlinear dynamics, chaos, and complexity science. None of the existing models, however, is able to represent the open, high dimension, and nonlinear self-organizing dynamics of social systems. An effective model will represent interactions at multiple levels to generate emergent patterns of social and political life of individuals and groups. Existing models and modeling methods are considered and assessed against characteristic pattern-forming processes in observed and experienced phenomena of human systems. A conceptual model, CDE Model, based on the conditions for self-organizing in human systems, is explored as an alternative to existing models and methods. While the new model overcomes the limitations of previous models, it also provides an explanatory base and foundation for prospective analysis to inform real-time meaning making and action taking in response to complex conditions in the real world. An invitation is extended to readers to engage in developing a computational model that incorporates the assumptions, meta-variables, and relationships of this open, high dimension, and nonlinear conceptual model of the complex dynamics of human systems.

Peer-to-Peer Human-Robot Interaction for Space Exploration

NASA Technical Reports Server (NTRS)

Fong, Terrence; Nourbakhsh, Illah

2004-01-01

NASA has embarked on a long-term program to develop human-robot systems for sustained, affordable space exploration. To support this mission, we are working to improve human-robot interaction and performance on planetary surfaces. Rather than building robots that function as glorified tools, our focus is to enable humans and robots to work as partners and peers. In this paper. we describe our approach, which includes contextual dialogue, cognitive modeling, and metrics-based field testing.

Modeling the within-host dynamics of cholera: bacterial-viral interaction.

PubMed

Wang, Xueying; Wang, Jin

2017-08-01

Novel deterministic and stochastic models are proposed in this paper for the within-host dynamics of cholera, with a focus on the bacterial-viral interaction. The deterministic model is a system of differential equations describing the interaction among the two types of vibrios and the viruses. The stochastic model is a system of Markov jump processes that is derived based on the dynamics of the deterministic model. The multitype branching process approximation is applied to estimate the extinction probability of bacteria and viruses within a human host during the early stage of the bacterial-viral infection. Accordingly, a closed-form expression is derived for the disease extinction probability, and analytic estimates are validated with numerical simulations. The local and global dynamics of the bacterial-viral interaction are analysed using the deterministic model, and the result indicates that there is a sharp disease threshold characterized by the basic reproduction number [Formula: see text]: if [Formula: see text], vibrios ingested from the environment into human body will not cause cholera infection; if [Formula: see text], vibrios will grow with increased toxicity and persist within the host, leading to human cholera. In contrast, the stochastic model indicates, more realistically, that there is always a positive probability of disease extinction within the human host.

Human Factors Model

NASA Technical Reports Server (NTRS)

1993-01-01

Jack is an advanced human factors software package that provides a three dimensional model for predicting how a human will interact with a given system or environment. It can be used for a broad range of computer-aided design applications. Jack was developed by the computer Graphics Research Laboratory of the University of Pennsylvania with assistance from NASA's Johnson Space Center, Ames Research Center and the Army. It is the University's first commercial product. Jack is still used for academic purposes at the University of Pennsylvania. Commercial rights were given to Transom Technologies, Inc.

Optimized Assistive Human-Robot Interaction Using Reinforcement Learning.

PubMed

Modares, Hamidreza; Ranatunga, Isura; Lewis, Frank L; Popa, Dan O

2016-03-01

An intelligent human-robot interaction (HRI) system with adjustable robot behavior is presented. The proposed HRI system assists the human operator to perform a given task with minimum workload demands and optimizes the overall human-robot system performance. Motivated by human factor studies, the presented control structure consists of two control loops. First, a robot-specific neuro-adaptive controller is designed in the inner loop to make the unknown nonlinear robot behave like a prescribed robot impedance model as perceived by a human operator. In contrast to existing neural network and adaptive impedance-based control methods, no information of the task performance or the prescribed robot impedance model parameters is required in the inner loop. Then, a task-specific outer-loop controller is designed to find the optimal parameters of the prescribed robot impedance model to adjust the robot's dynamics to the operator skills and minimize the tracking error. The outer loop includes the human operator, the robot, and the task performance details. The problem of finding the optimal parameters of the prescribed robot impedance model is transformed into a linear quadratic regulator (LQR) problem which minimizes the human effort and optimizes the closed-loop behavior of the HRI system for a given task. To obviate the requirement of the knowledge of the human model, integral reinforcement learning is used to solve the given LQR problem. Simulation results on an x - y table and a robot arm, and experimental implementation results on a PR2 robot confirm the suitability of the proposed method.

Loving Machines: Theorizing Human and Sociable-Technology Interaction

NASA Astrophysics Data System (ADS)

Shaw-Garlock, Glenda

Today, human and sociable-technology interaction is a contested site of inquiry. Some regard social robots as an innovative medium of communication that offer new avenues for expression, communication, and interaction. Other others question the moral veracity of human-robot relationships, suggesting that such associations risk psychological impoverishment. What seems clear is that the emergence of social robots in everyday life will alter the nature of social interaction, bringing with it a need for new theories to understand the shifting terrain between humans and machines. This work provides a historical context for human and sociable robot interaction. Current research related to human-sociable-technology interaction is considered in relation to arguments that confront a humanist view that confine 'technological things' to the nonhuman side of the human/nonhuman binary relation. Finally, it recommends a theoretical approach for the study of human and sociable-technology interaction that accommodates increasingly personal relations between human and nonhuman technologies.

Developing a model for effects of climate change on human health and health-environment interactions: Heat stress in Austin, Texas

EPA Science Inventory

Background/Question/Methods In December, 2010, a consortium of EPA, Centers for Disease Control, and state and local health officials convened in Austin, Texas for a “participatory modeling workshop” on climate change effects on human health and health-environment interactions. ...

The Human-Robot Interaction Operating System

NASA Technical Reports Server (NTRS)

Fong, Terrence; Kunz, Clayton; Hiatt, Laura M.; Bugajska, Magda

2006-01-01

In order for humans and robots to work effectively together, they need to be able to converse about abilities, goals and achievements. Thus, we are developing an interaction infrastructure called the "Human-Robot Interaction Operating System" (HRI/OS). The HRI/OS provides a structured software framework for building human-robot teams, supports a variety of user interfaces, enables humans and robots to engage in task-oriented dialogue, and facilitates integration of robots through an extensible API.

Modeling human-flood interactions: Collective action and community resilience.

NASA Astrophysics Data System (ADS)

Yu, D. J.; Sangwan, N.; Sung, K.

2016-12-01

Stylized models of socio-hydrology have mainly used social memory aspects such as community awareness or sensitivity to connect hydrologic change and social response. However, social memory alone does not satisfactorily capture the details of how human behavior is translated into collective action for water resources governance. Nor is it the only mechanism by which the two-way feedbacks of socio-hydrology can be operationalized. This study contributes towards bridging of this gap by developing a stylized model of a human-flood system that includes two additional drivers of change: (1) institutions for collective action, and (2) connections to an external economic system. Motivated by the case of community-managed flood protection systems (polders) in coastal Bangladesh, we use the model to understand critical general features that affect long-term resilience of human-flood systems. Our findings suggest that occasional adversity can enhance long-term resilience. Allowing some hydrological variability to enter into the polder can increase its adaptive capacity and resilience through the preservation of social memory and institutions for collective action. Further, there are potential tradeoffs associated with optimization of flood resilience through structural measures. By reducing sensitivity to flooding, the system may become more fragile under the double impact of flooding and economic change

Analyzing Human-Landscape Interactions: Tools That Integrate

NASA Astrophysics Data System (ADS)

Zvoleff, Alex; An, Li

2014-01-01

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

Design Science in Human-Computer Interaction: A Model and Three Examples

ERIC Educational Resources Information Center

Prestopnik, Nathan R.

2013-01-01

Humanity has entered an era where computing technology is virtually ubiquitous. From websites and mobile devices to computers embedded in appliances on our kitchen counters and automobiles parked in our driveways, information and communication technologies (ICTs) and IT artifacts are fundamentally changing the ways we interact with our world.…

Interactive Structure (EUCLID) For Static And Dynamic Representation Of Human Body

NASA Astrophysics Data System (ADS)

Renaud, Ch.; Steck, R.

1983-07-01

A specific software (EUCLID) for static and dynamic representation of human models is described. The data processing system is connected with ERGODATA and used in interactive mode by intrinsic or specific functions. More or less complex representations in 3-D view of models of the human body are developed. Biostereometric and conventional anthropometric raw data from the data bank are processed for different applications in ergonomy.

GABAergic modulation of human social interaction in a prisoner’s dilemma model via acute administration of alprazolam

PubMed Central

Lane, Scott D.; Gowin, Joshua L.

2010-01-01

Recent work in neuroeconomics has utilized game theory paradigms to examine neural systems that subserve human social interaction and decision making. Attempts to modify social interaction through pharmacological manipulation have been less common. Here we show dose-dependent modification of human social behavior in a prisoner’s dilemma (PD) model following acute administration of the GABA-A modulating benzodiazepine alprazolam. Nine healthy adults received doses of placebo, 0.5, 1.0, and 2.0 mg alprazolam in a counterbalanced within-subject design, while completing multiple test blocks per day on an iterated PD game. During test blocks in which peak subjective effects of alprazolam were reported, cooperative choices were significantly decreased as a function of dose. Consistent with previous reports showing that high acute doses of GABA-modulating drugs are associated with violence and other antisocial behavior, our data suggest that at sufficiently high doses, alprazolam can decrease cooperation. These behavioral changes may be facilitated by changes in inhibitory control facilitated by GABA. Game theory paradigms may prove useful in behavioral pharmacology studies seeking to measure social interaction, and may help inform the emerging field of neuroeconomics. PMID:19667972

A Nonlinear Model for Gene-Based Gene-Environment Interaction.

PubMed

Sa, Jian; Liu, Xu; He, Tao; Liu, Guifen; Cui, Yuehua

2016-06-04

A vast amount of literature has confirmed the role of gene-environment (G×E) interaction in the etiology of complex human diseases. Traditional methods are predominantly focused on the analysis of interaction between a single nucleotide polymorphism (SNP) and an environmental variable. Given that genes are the functional units, it is crucial to understand how gene effects (rather than single SNP effects) are influenced by an environmental variable to affect disease risk. Motivated by the increasing awareness of the power of gene-based association analysis over single variant based approach, in this work, we proposed a sparse principle component regression (sPCR) model to understand the gene-based G×E interaction effect on complex disease. We first extracted the sparse principal components for SNPs in a gene, then the effect of each principal component was modeled by a varying-coefficient (VC) model. The model can jointly model variants in a gene in which their effects are nonlinearly influenced by an environmental variable. In addition, the varying-coefficient sPCR (VC-sPCR) model has nice interpretation property since the sparsity on the principal component loadings can tell the relative importance of the corresponding SNPs in each component. We applied our method to a human birth weight dataset in Thai population. We analyzed 12,005 genes across 22 chromosomes and found one significant interaction effect using the Bonferroni correction method and one suggestive interaction. The model performance was further evaluated through simulation studies. Our model provides a system approach to evaluate gene-based G×E interaction.

Host-pathogen interactions between the human innate immune system and Candida albicans—understanding and modeling defense and evasion strategies

PubMed Central

Dühring, Sybille; Germerodt, Sebastian; Skerka, Christine; Zipfel, Peter F.; Dandekar, Thomas; Schuster, Stefan

2015-01-01

The diploid, polymorphic yeast Candida albicans is one of the most important human pathogenic fungi. C. albicans can grow, proliferate and coexist as a commensal on or within the human host for a long time. However, alterations in the host environment can render C. albicans virulent. In this review, we describe the immunological cross-talk between C. albicans and the human innate immune system. We give an overview in form of pairs of human defense strategies including immunological mechanisms as well as general stressors such as nutrient limitation, pH, fever etc. and the corresponding fungal response and evasion mechanisms. Furthermore, Computational Systems Biology approaches to model and investigate these complex interactions are highlighted with a special focus on game-theoretical methods and agent-based models. An outlook on interesting questions to be tackled by Systems Biology regarding entangled defense and evasion mechanisms is given. PMID:26175718

The role of gut microbiota in health and disease: In vitro modeling of host-microbe interactions at the aerobe-anaerobe interphase of the human gut.

PubMed

von Martels, Julius Z H; Sadaghian Sadabad, Mehdi; Bourgonje, Arno R; Blokzijl, Tjasso; Dijkstra, Gerard; Faber, Klaas Nico; Harmsen, Hermie J M

2017-04-01

The microbiota of the gut has many crucial functions in human health. Dysbiosis of the microbiota has been correlated to a large and still increasing number of diseases. Recent studies have mostly focused on analyzing the associations between disease and an aberrant microbiota composition. Functional studies using (in vitro) gut models are required to investigate the precise interactions that occur between specific bacteria (or bacterial mixtures) and gut epithelial cells. As most gut bacteria are obligate or facultative anaerobes, studying their effect on oxygen-requiring human gut epithelial cells is technically challenging. Still, several (anaerobic) bacterial-epithelial co-culture systems have recently been developed that mimic host-microbe interactions occurring in the human gut, including 1) the Transwell "apical anaerobic model of the intestinal epithelial barrier", 2) the Host-Microbiota Interaction (HMI) module, 3) the "Human oxygen-Bacteria anaerobic" (HoxBan) system, 4) the human gut-on-a-chip and 5) the HuMiX model. This review discusses the role of gut microbiota in health and disease and gives an overview of the characteristics and applications of these novel host-microbe co-culture systems. Copyright © 2017 Elsevier Ltd. All rights reserved.

Human mammary microenvironment better regulates the biology of human breast cancer in humanized mouse model.

PubMed

Zheng, Ming-Jie; Wang, Jue; Xu, Lu; Zha, Xiao-Ming; Zhao, Yi; Ling, Li-Jun; Wang, Shui

2015-02-01

During the past decades, many efforts have been made in mimicking the clinical progress of human cancer in mouse models. Previously, we developed a human breast tissue-derived (HB) mouse model. Theoretically, it may mimic the interactions between "species-specific" mammary microenvironment of human origin and human breast cancer cells. However, detailed evidences are absent. The present study (in vivo, cellular, and molecular experiments) was designed to explore the regulatory role of human mammary microenvironment in the progress of human breast cancer cells. Subcutaneous (SUB), mammary fat pad (MFP), and HB mouse models were developed for in vivo comparisons. Then, the orthotopic tumor masses from three different mouse models were collected for primary culture. Finally, the biology of primary cultured human breast cancer cells was compared by cellular and molecular experiments. Results of in vivo mouse models indicated that human breast cancer cells grew better in human mammary microenvironment. Cellular and molecular experiments confirmed that primary cultured human breast cancer cells from HB mouse model showed a better proliferative and anti-apoptotic biology than those from SUB to MFP mouse models. Meanwhile, primary cultured human breast cancer cells from HB mouse model also obtained the migratory and invasive biology for "species-specific" tissue metastasis to human tissues. Comprehensive analyses suggest that "species-specific" mammary microenvironment of human origin better regulates the biology of human breast cancer cells in our humanized mouse model of breast cancer, which is more consistent with the clinical progress of human breast cancer.

Enhancing Learning through Human Computer Interaction

ERIC Educational Resources Information Center

McKay, Elspeth, Ed.

2007-01-01

Enhancing Learning Through Human Computer Interaction is an excellent reference source for human computer interaction (HCI) applications and designs. This "Premier Reference Source" provides a complete analysis of online business training programs and e-learning in the higher education sector. It describes a range of positive outcomes for linking…

Modeling human diseases: an education in interactions and interdisciplinary approaches.

PubMed

Zon, Leonard

2016-06-01

Traditionally, most investigators in the biomedical arena exploit one model system in the course of their careers. Occasionally, an investigator will switch models. The selection of a suitable model system is a crucial step in research design. Factors to consider include the accuracy of the model as a reflection of the human disease under investigation, the numbers of animals needed and ease of husbandry, its physiology and developmental biology, and the ability to apply genetics and harness the model for drug discovery. In my lab, we have primarily used the zebrafish but combined it with other animal models and provided a framework for others to consider the application of developmental biology for therapeutic discovery. Our interdisciplinary approach has led to many insights into human diseases and to the advancement of candidate drugs to clinical trials. Here, I draw on my experiences to highlight the importance of combining multiple models, establishing infrastructure and genetic tools, forming collaborations, and interfacing with the medical community for successful translation of basic findings to the clinic. © 2016. Published by The Company of Biologists Ltd.

Cognitive Model of Trust Dynamics Predicts Human Behavior within and between Two Games of Strategic Interaction with Computerized Confederate Agents

PubMed Central

Collins, Michael G.; Juvina, Ion; Gluck, Kevin A.

2016-01-01

When playing games of strategic interaction, such as iterated Prisoner's Dilemma and iterated Chicken Game, people exhibit specific within-game learning (e.g., learning a game's optimal outcome) as well as transfer of learning between games (e.g., a game's optimal outcome occurring at a higher proportion when played after another game). The reciprocal trust players develop during the first game is thought to mediate transfer of learning effects. Recently, a computational cognitive model using a novel trust mechanism has been shown to account for human behavior in both games, including the transfer between games. We present the results of a study in which we evaluate the model's a priori predictions of human learning and transfer in 16 different conditions. The model's predictive validity is compared against five model variants that lacked a trust mechanism. The results suggest that a trust mechanism is necessary to explain human behavior across multiple conditions, even when a human plays against a non-human agent. The addition of a trust mechanism to the other learning mechanisms within the cognitive architecture, such as sequence learning, instance-based learning, and utility learning, leads to better prediction of the empirical data. It is argued that computational cognitive modeling is a useful tool for studying trust development, calibration, and repair. PMID:26903892

Multimodal interaction for human-robot teams

NASA Astrophysics Data System (ADS)

Burke, Dustin; Schurr, Nathan; Ayers, Jeanine; Rousseau, Jeff; Fertitta, John; Carlin, Alan; Dumond, Danielle

2013-05-01

Unmanned ground vehicles have the potential for supporting small dismounted teams in mapping facilities, maintaining security in cleared buildings, and extending the team's reconnaissance and persistent surveillance capability. In order for such autonomous systems to integrate with the team, we must move beyond current interaction methods using heads-down teleoperation which require intensive human attention and affect the human operator's ability to maintain local situational awareness and ensure their own safety. This paper focuses on the design, development and demonstration of a multimodal interaction system that incorporates naturalistic human gestures, voice commands, and a tablet interface. By providing multiple, partially redundant interaction modes, our system degrades gracefully in complex environments and enables the human operator to robustly select the most suitable interaction method given the situational demands. For instance, the human can silently use arm and hand gestures for commanding a team of robots when it is important to maintain stealth. The tablet interface provides an overhead situational map allowing waypoint-based navigation for multiple ground robots in beyond-line-of-sight conditions. Using lightweight, wearable motion sensing hardware either worn comfortably beneath the operator's clothing or integrated within their uniform, our non-vision-based approach enables an accurate, continuous gesture recognition capability without line-of-sight constraints. To reduce the training necessary to operate the system, we designed the interactions around familiar arm and hand gestures.

[Affective behavioural responses by dogs to tactile human-dog interactions].

PubMed

Kuhne, Franziska; Hössler, Johanna C; Struwe, Rainer

2012-01-01

The communication of dogs is based on complex, subtle body postures and facial expressions. Some social interaction between dogs includes physical contact. Humans generally use both verbal and tactile signals to communicate with dogs. Hence, interaction between humans and dogs might lead to conflicts because the behavioural responses of dogs to human-dog interaction may be misinterpreted and wrongly assessed. The behavioural responses of dogs to tactile human-dog interactions and human gestures are the focus of this study. The participating dogs (n = 47) were privately owned pets.They were of varying breed and gender.The test consisted of nine randomised test sequences (e. g. petting the dog's head or chest). A test sequence was performed for a period of 30 seconds. The inter-trial interval was set at 60 seconds and the test-retest interval was set at 10 minutes. The frequency and duration of the dogs'behavioural responses were recorded using INTERACT. To examine the behavioural responses of the dogs, a two-way analysis of variance within the linear mixed models procedure of IBM SPSS Statistics 19 was conducted. A significant influence of the test-sequenc order on the dogs' behaviour could be analysed for appeasement gestures (F8,137 = 2.42; p = 0.018), redirected behaviour (F8,161 = 6.31; p = 0.012) and socio-positive behaviour (F8,148 = 6.28; p = 0.012). The behavioural responses of the dogs, which were considered as displacement activities (F8,109 = 2.5; p = 0.014) differed significantly among the test sequences. The response of the dogs, measured as gestures of appeasement, redirected behaviours, and displacement activities, was most obvious during petting around the head and near the paws.The results of this study conspicuously indicate that dogs respond to tactile human-dog interactions with gestures of appeasement and displacement activities. Redirected behaviours, socio-positive behaviours as well displacement activities are behavioural responses which dogs

An integrated mathematical model of the human cardiopulmonary system: model development.

PubMed

Albanese, Antonio; Cheng, Limei; Ursino, Mauro; Chbat, Nicolas W

2016-04-01

Several cardiovascular and pulmonary models have been proposed in the last few decades. However, very few have addressed the interactions between these two systems. Our group has developed an integrated cardiopulmonary model (CP Model) that mathematically describes the interactions between the cardiovascular and respiratory systems, along with their main short-term control mechanisms. The model has been compared with human and animal data taken from published literature. Due to the volume of the work, the paper is divided in two parts. The present paper is on model development and normophysiology, whereas the second is on the model's validation on hypoxic and hypercapnic conditions. The CP Model incorporates cardiovascular circulation, respiratory mechanics, tissue and alveolar gas exchange, as well as short-term neural control mechanisms acting on both the cardiovascular and the respiratory functions. The model is able to simulate physiological variables typically observed in adult humans under normal and pathological conditions and to explain the underlying mechanisms and dynamics. Copyright © 2016 the American Physiological Society.

The Microphysiology Systems Database for Analyzing and Modeling Compound Interactions with Human and Animal Organ Models

PubMed Central

Vernetti, Lawrence; Bergenthal, Luke; Shun, Tong Ying; Taylor, D. Lansing

2016-01-01

Abstract Microfluidic human organ models, microphysiology systems (MPS), are currently being developed as predictive models of drug safety and efficacy in humans. To design and validate MPS as predictive of human safety liabilities requires safety data for a reference set of compounds, combined with in vitro data from the human organ models. To address this need, we have developed an internet database, the MPS database (MPS-Db), as a powerful platform for experimental design, data management, and analysis, and to combine experimental data with reference data, to enable computational modeling. The present study demonstrates the capability of the MPS-Db in early safety testing using a human liver MPS to relate the effects of tolcapone and entacapone in the in vitro model to human in vivo effects. These two compounds were chosen to be evaluated as a representative pair of marketed drugs because they are structurally similar, have the same target, and were found safe or had an acceptable risk in preclinical and clinical trials, yet tolcapone induced unacceptable levels of hepatotoxicity while entacapone was found to be safe. Results demonstrate the utility of the MPS-Db as an essential resource for relating in vitro organ model data to the multiple biochemical, preclinical, and clinical data sources on in vivo drug effects. PMID:28781990

Inferring genetic interactions via a nonlinear model and an optimization algorithm.

PubMed

Chen, Chung-Ming; Lee, Chih; Chuang, Cheng-Long; Wang, Chia-Chang; Shieh, Grace S

2010-02-26

Biochemical pathways are gradually becoming recognized as central to complex human diseases and recently genetic/transcriptional interactions have been shown to be able to predict partial pathways. With the abundant information made available by microarray gene expression data (MGED), nonlinear modeling of these interactions is now feasible. Two of the latest advances in nonlinear modeling used sigmoid models to depict transcriptional interaction of a transcription factor (TF) for a target gene, but do not model cooperative or competitive interactions of several TFs for a target. An S-shape model and an optimization algorithm (GASA) were developed to infer genetic interactions/transcriptional regulation of several genes simultaneously using MGED. GASA consists of a genetic algorithm (GA) and a simulated annealing (SA) algorithm, which is enhanced by a steepest gradient descent algorithm to avoid being trapped in local minimum. Using simulated data with various degrees of noise, we studied how GASA with two model selection criteria and two search spaces performed. Furthermore, GASA was shown to outperform network component analysis, the time series network inference algorithm (TSNI), GA with regular GA (GAGA) and GA with regular SA. Two applications are demonstrated. First, GASA is applied to infer a subnetwork of human T-cell apoptosis. Several of the predicted interactions are supported by the literature. Second, GASA was applied to infer the transcriptional factors of 34 cell cycle regulated targets in S. cerevisiae, and GASA performed better than one of the latest advances in nonlinear modeling, GAGA and TSNI. Moreover, GASA is able to predict multiple transcription factors for certain targets, and these results coincide with experiments confirmed data in YEASTRACT. GASA is shown to infer both genetic interactions and transcriptional regulatory interactions well. In particular, GASA seems able to characterize the nonlinear mechanism of transcriptional regulatory

Integrated modeling of land-use change: the role of coupling, interactions and feedbacks between the human and Earth systems

NASA Astrophysics Data System (ADS)

Monier, E.; Kicklighter, D. W.; Ejaz, Q.; Winchester, N.; Paltsev, S.; Reilly, J. M.

2016-12-01

Land-use change integrates a large number of components of the human and Earth systems, including climate, energy, water, and land. These complex coupling elements, interactions and feedbacks take place on a variety of space and time scales, thus increasing the complexity of land-use change modeling frameworks. In this study, we aim to identify which coupling elements, interactions and feedbacks are important for modeling land-use change, both at the global and regional level. First, we review the existing land-use change modeling framework used to develop land-use change projections for the Representative Concentration Pathways (RCP) scenarios. In such framework, land-use change is simulated by Integrated Assessment Models (IAMs) and mainly influenced by economic, energy, demographic and policy drivers. IAMs focus on representing the demand for agriculture and forestry goods (crops for food and bioenergy, forest products for construction and bioenergy), the interactions with other sectors of the economy and trade between various regions of the world. Then, we investigate how important various coupling elements and feedbacks with the Earth system are for projections of land-use change at the global and regional level. We focus on the following: i) the climate impacts on land productivity and greenhouse gas emissions, which requires climate change information and coupling to a terrestrial ecosystem model/crop model; ii) the climate and economic impacts on irrigation availability, which requires coupling the LUC modeling framework to a water resources management model and disaggregating rainfed and irrigated croplands; iii) the feedback of land-use change on the global and regional climate system through land-use change emissions and changes in the surface albedo and hydrology, which requires coupling to an Earth system model. Finally, we conclude our study by highlighting the current lack of clarity in how various components of the human and Earth systems are

Acetaminophen interacts with human hemoglobin: optical, physical and molecular modeling studies.

PubMed

Seal, Paromita; Sikdar, Jyotirmoy; Roy, Amartya; Haldar, Rajen

2017-05-01

Acetaminophen, a widely used analgesic and antipyretic drug has ample affinity to bind globular proteins. Here, we have illustrated a substantive study pertaining to the interaction of acetaminophen with human hemoglobin (HHb). Different spectroscopic (absorption, fluorescence, and circular dichroism (CD) spectroscopy), calorimetric, and molecular docking techniques have been employed in this study. Acetaminophen-induced graded alterations in absorbance and fluorescence of HHb confirm their interaction. Analysis of fluorescence quenching at different temperature and data obtained from isothermal titration calorimetry indicate that the interaction is static and the HHb has one binding site for the drug. The negative values of Gibbs energy change (ΔG 0 ) and enthalpy changes (ΔH 0 ) and positive value of entropy change (ΔS 0 ) strongly suggest that it is entropy-driven spontaneous and exothermic reaction. The reaction involves hydrophobic pocket of the protein which is further stabilized by hydrogen bonding as evidenced from ANS and sucrose binding studies. These findings were also supported by molecular docking simulation study using AutoDock 4.2. The interaction influences structural integrity as well as functional properties of HHb as evidenced by CD spectroscopy, increased rate of co-oxidation and decreased esterase activity of HHb. So, from these findings, we may conclude that acetaminophen interacts with HHb through hydrophobic and hydrogen bonding, and the interaction perturbs the structural and functional properties of HHb.

Dynamic inverse models in human-cyber-physical systems

NASA Astrophysics Data System (ADS)

Robinson, Ryan M.; Scobee, Dexter R. R.; Burden, Samuel A.; Sastry, S. Shankar

2016-05-01

Human interaction with the physical world is increasingly mediated by automation. This interaction is characterized by dynamic coupling between robotic (i.e. cyber) and neuromechanical (i.e. human) decision-making agents. Guaranteeing performance of such human-cyber-physical systems will require predictive mathematical models of this dynamic coupling. Toward this end, we propose a rapprochement between robotics and neuromechanics premised on the existence of internal forward and inverse models in the human agent. We hypothesize that, in tele-robotic applications of interest, a human operator learns to invert automation dynamics, directly translating from desired task to required control input. By formulating the model inversion problem in the context of a tracking task for a nonlinear control system in control-a_ne form, we derive criteria for exponential tracking and show that the resulting dynamic inverse model generally renders a portion of the physical system state (i.e., the internal dynamics) unobservable from the human operator's perspective. Under stability conditions, we show that the human can achieve exponential tracking without formulating an estimate of the system's state so long as they possess an accurate model of the system's dynamics. These theoretical results are illustrated using a planar quadrotor example. We then demonstrate that the automation can intervene to improve performance of the tracking task by solving an optimal control problem. Performance is guaranteed to improve under the assumption that the human learns and inverts the dynamic model of the altered system. We conclude with a discussion of practical limitations that may hinder exact dynamic model inversion.

Human-Robot Interaction

NASA Technical Reports Server (NTRS)

Sandor, Aniko; Cross, E. Vincent, II; Chang, Mai Lee

2015-01-01

Human-robot interaction (HRI) is a discipline investigating the factors affecting the interactions between humans and robots. It is important to evaluate how the design of interfaces affect the human's ability to perform tasks effectively and efficiently when working with a robot. By understanding the effects of interface design on human performance, workload, and situation awareness, interfaces can be developed to appropriately support the human in performing tasks with minimal errors and with appropriate interaction time and effort. Thus, the results of research on human-robot interfaces have direct implications for the design of robotic systems. For efficient and effective remote navigation of a rover, a human operator needs to be aware of the robot's environment. However, during teleoperation, operators may get information about the environment only through a robot's front-mounted camera causing a keyhole effect. The keyhole effect reduces situation awareness which may manifest in navigation issues such as higher number of collisions, missing critical aspects of the environment, or reduced speed. One way to compensate for the keyhole effect and the ambiguities operators experience when they teleoperate a robot is adding multiple cameras and including the robot chassis in the camera view. Augmented reality, such as overlays, can also enhance the way a person sees objects in the environment or in camera views by making them more visible. Scenes can be augmented with integrated telemetry, procedures, or map information. Furthermore, the addition of an exocentric (i.e., third-person) field of view from a camera placed in the robot's environment may provide operators with the additional information needed to gain spatial awareness of the robot. Two research studies investigated possible mitigation approaches to address the keyhole effect: 1) combining the inclusion of the robot chassis in the camera view with augmented reality overlays, and 2) modifying the camera

Modeling of protein-anion exchange resin interaction for the human growth hormone charge variants.

PubMed

Lapelosa, Mauro; Patapoff, Thomas W; Zarraga, Isidro E

2015-12-01

Modeling ion exchange chromatography (IEC) behavior has generated significant interest because of the wide use of IEC as an analytical technique as well as a preparative protein purification process; indeed there is a need for better understanding of what drives the unique behavior of protein charge variants. We hypothesize that a complex protein molecule, which contains both hydrophobic and charged moieties, would interact strongly with an in silico designed resin through charged electrostatic patches on the surface of the protein. In the present work, variants of recombinant human growth hormone that mimic naturally-occurring deamidation products were produced and characterized in silico. The study included these four variants: rhGH, N149D, N152D, and N149D/N152D. Poisson-Boltzmann calculations were used to determine surface electrostatic potential. Metropolis Monte Carlo simulations were carried out with the resulting variants to simulate IEC systems, examining the free energy of the interaction of the protein with an in silico anion exchange column represented by polylysine polypeptide. The results show that the charge variants have different average binding energies and the free energy of interaction can be used to predict the retention time for the different variants. Copyright © 2015 Elsevier B.V. All rights reserved.

Socially intelligent robots: dimensions of human-robot interaction.

PubMed

Dautenhahn, Kerstin

2007-04-29

Social intelligence in robots has a quite recent history in artificial intelligence and robotics. However, it has become increasingly apparent that social and interactive skills are necessary requirements in many application areas and contexts where robots need to interact and collaborate with other robots or humans. Research on human-robot interaction (HRI) poses many challenges regarding the nature of interactivity and 'social behaviour' in robot and humans. The first part of this paper addresses dimensions of HRI, discussing requirements on social skills for robots and introducing the conceptual space of HRI studies. In order to illustrate these concepts, two examples of HRI research are presented. First, research is surveyed which investigates the development of a cognitive robot companion. The aim of this work is to develop social rules for robot behaviour (a 'robotiquette') that is comfortable and acceptable to humans. Second, robots are discussed as possible educational or therapeutic toys for children with autism. The concept of interactive emergence in human-child interactions is highlighted. Different types of play among children are discussed in the light of their potential investigation in human-robot experiments. The paper concludes by examining different paradigms regarding 'social relationships' of robots and people interacting with them.

Numerical simulation of stress amplification induced by crack interaction in human femur bone

NASA Astrophysics Data System (ADS)

Alia, Noor; Daud, Ruslizam; Ramli, Mohammad Fadzli; Azman, Wan Zuki; Faizal, Ahmad; Aisyah, Siti

2015-05-01

This research is about numerical simulation using a computational method which study on stress amplification induced by crack interaction in human femur bone. Cracks in human femur bone usually occur because of large load or stress applied on it. Usually, the fracture takes longer time to heal itself. At present, the crack interaction is still not well understood due to bone complexity. Thus, brittle fracture behavior of bone may be underestimated and inaccurate. This study aims to investigate the geometrical effect of double co-planar edge cracks on stress intensity factor (K) in femur bone. This research focuses to analyze the amplification effect on the fracture behavior of double co-planar edge cracks, where numerical model is developed using computational method. The concept of fracture mechanics and finite element method (FEM) are used to solve the interacting cracks problems using linear elastic fracture mechanics (LEFM) theory. As a result, this study has shown the identification of the crack interaction limit (CIL) and crack unification limit (CUL) exist in the human femur bone model developed. In future research, several improvements will be made such as varying the load, applying thickness on the model and also use different theory or method in calculating the stress intensity factor (K).

Kinematic design to improve ergonomics in human machine interaction.

PubMed

Schiele, André; van der Helm, Frans C T

2006-12-01

This paper introduces a novel kinematic design paradigm for ergonomic human machine interaction. Goals for optimal design are formulated generically and applied to the mechanical design of an upper-arm exoskeleton. A nine degree-of-freedom (DOF) model of the human arm kinematics is presented and used to develop, test, and optimize the kinematic structure of an human arm interfacing exoskeleton. The resulting device can interact with an unprecedented portion of the natural limb workspace, including motions in the shoulder-girdle, shoulder, elbow, and the wrist. The exoskeleton does not require alignment to the human joint axes, yet is able to actuate each DOF of our redundant limb unambiguously and without reaching into singularities. The device is comfortable to wear and does not create residual forces if misalignments exist. Implemented in a rehabilitation robot, the design features of the exoskeleton could enable longer lasting training sessions, training of fully natural tasks such as activities of daily living and shorter dress-on and dress-off times. Results from inter-subject experiments with a prototype are presented, that verify usability over the entire workspace of the human arm, including shoulder and shoulder girdle.

User localization during human-robot interaction.

PubMed

Alonso-Martín, F; Gorostiza, Javi F; Malfaz, María; Salichs, Miguel A

2012-01-01

This paper presents a user localization system based on the fusion of visual information and sound source localization, implemented on a social robot called Maggie. One of the main requisites to obtain a natural interaction between human-human and human-robot is an adequate spatial situation between the interlocutors, that is, to be orientated and situated at the right distance during the conversation in order to have a satisfactory communicative process. Our social robot uses a complete multimodal dialog system which manages the user-robot interaction during the communicative process. One of its main components is the presented user localization system. To determine the most suitable allocation of the robot in relation to the user, a proxemic study of the human-robot interaction is required, which is described in this paper. The study has been made with two groups of users: children, aged between 8 and 17, and adults. Finally, at the end of the paper, experimental results with the proposed multimodal dialog system are presented.

The Interactive Minority Game: a Web-based investigation of human market interactions

NASA Astrophysics Data System (ADS)

Laureti, Paolo; Ruch, Peter; Wakeling, Joseph; Zhang, Yi-Cheng

2004-01-01

The unprecedented access offered by the World Wide Web brings with it the potential to gather huge amounts of data on human activities. Here we exploit this by using a toy model of financial markets, the Minority Game (MG), to investigate human speculative trading behaviour and information capacity. Hundreds of individuals have played a total of tens of thousands of game turns against computer-controlled agents in the Web-based Interactive Minority Game. The analytical understanding of the MG permits fine-tuning of the market situations encountered, allowing for investigation of human behaviour in a variety of controlled environments. In particular, our results indicate a transition in players’ decision-making, as the markets become more difficult, between deductive behaviour making use of short-term trends in the market, and highly repetitive behaviour that ignores entirely the market history, yet outperforms random decision-making.

TOPICAL REVIEW: Modelling the interaction of electromagnetic fields (10 MHz 10 GHz) with the human body: methods and applications

NASA Astrophysics Data System (ADS)

Hand, J. W.

2008-08-01

Numerical modelling of the interaction between electromagnetic fields (EMFs) and the dielectrically inhomogeneous human body provides a unique way of assessing the resulting spatial distributions of internal electric fields, currents and rate of energy deposition. Knowledge of these parameters is of importance in understanding such interactions and is a prerequisite when assessing EMF exposure or when assessing or optimizing therapeutic or diagnostic medical applications that employ EMFs. In this review, computational methods that provide this information through full time-dependent solutions of Maxwell's equations are summarized briefly. This is followed by an overview of safety- and medical-related applications where modelling has contributed significantly to development and understanding of the techniques involved. In particular, applications in the areas of mobile communications, magnetic resonance imaging, hyperthermal therapy and microwave radiometry are highlighted. Finally, examples of modelling the potentially new medical applications of recent technologies such as ultra-wideband microwaves are discussed.

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

PubMed

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

2014-01-01

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

Motor Contagion during Human-Human and Human-Robot Interaction

PubMed Central

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

2014-01-01

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

Functional metabolic interactions of human neuron-astrocyte 3D in vitro networks

PubMed Central

Simão, Daniel; Terrasso, Ana P.; Teixeira, Ana P.; Brito, Catarina; Sonnewald, Ursula; Alves, Paula M.

2016-01-01

The generation of human neural tissue-like 3D structures holds great promise for disease modeling, drug discovery and regenerative medicine strategies. Promoting the establishment of complex cell-cell interactions, 3D culture systems enable the development of human cell-based models with increased physiological relevance, over monolayer cultures. Here, we demonstrate the establishment of neuronal and astrocytic metabolic signatures and shuttles in a human 3D neural cell model, namely the glutamine-glutamate-GABA shuttle. This was indicated by labeling of neuronal GABA following incubation with the glia-specific substrate [2-13C]acetate, which decreased by methionine sulfoximine-induced inhibition of the glial enzyme glutamine synthetase. Cell metabolic specialization was further demonstrated by higher pyruvate carboxylase-derived labeling in glutamine than in glutamate, indicating its activity in astrocytes and not in neurons. Exposure to the neurotoxin acrylamide resulted in intracellular accumulation of glutamate and decreased GABA synthesis. These results suggest an acrylamide-induced impairment of neuronal synaptic vesicle trafficking and imbalanced glutamine-glutamate-GABA cycle, due to loss of cell-cell contacts at synaptic sites. This work demonstrates, for the first time to our knowledge, that neural differentiation of human cells in a 3D setting recapitulates neuronal-astrocytic metabolic interactions, highlighting the relevance of these models for toxicology and better understanding the crosstalk between human neural cells. PMID:27619889

Functional metabolic interactions of human neuron-astrocyte 3D in vitro networks.

PubMed

Simão, Daniel; Terrasso, Ana P; Teixeira, Ana P; Brito, Catarina; Sonnewald, Ursula; Alves, Paula M

2016-09-13

The generation of human neural tissue-like 3D structures holds great promise for disease modeling, drug discovery and regenerative medicine strategies. Promoting the establishment of complex cell-cell interactions, 3D culture systems enable the development of human cell-based models with increased physiological relevance, over monolayer cultures. Here, we demonstrate the establishment of neuronal and astrocytic metabolic signatures and shuttles in a human 3D neural cell model, namely the glutamine-glutamate-GABA shuttle. This was indicated by labeling of neuronal GABA following incubation with the glia-specific substrate [2-(13)C]acetate, which decreased by methionine sulfoximine-induced inhibition of the glial enzyme glutamine synthetase. Cell metabolic specialization was further demonstrated by higher pyruvate carboxylase-derived labeling in glutamine than in glutamate, indicating its activity in astrocytes and not in neurons. Exposure to the neurotoxin acrylamide resulted in intracellular accumulation of glutamate and decreased GABA synthesis. These results suggest an acrylamide-induced impairment of neuronal synaptic vesicle trafficking and imbalanced glutamine-glutamate-GABA cycle, due to loss of cell-cell contacts at synaptic sites. This work demonstrates, for the first time to our knowledge, that neural differentiation of human cells in a 3D setting recapitulates neuronal-astrocytic metabolic interactions, highlighting the relevance of these models for toxicology and better understanding the crosstalk between human neural cells.

Multi-View Interaction Modelling of human collaboration processes: a business process study of head and neck cancer care in a Dutch academic hospital.

PubMed

Stuit, Marco; Wortmann, Hans; Szirbik, Nick; Roodenburg, Jan

2011-12-01

In the healthcare domain, human collaboration processes (HCPs), which consist of interactions between healthcare workers from different (para)medical disciplines and departments, are of growing importance as healthcare delivery becomes increasingly integrated. Existing workflow-based process modelling tools for healthcare process management, which are the most commonly applied, are not suited for healthcare HCPs mainly due to their focus on the definition of task sequences instead of the graphical description of human interactions. This paper uses a case study of a healthcare HCP at a Dutch academic hospital to evaluate a novel interaction-centric process modelling method. The HCP under study is the care pathway performed by the head and neck oncology team. The evaluation results show that the method brings innovative, effective, and useful features. First, it collects and formalizes the tacit domain knowledge of the interviewed healthcare workers in individual interaction diagrams. Second, the method automatically integrates these local diagrams into a single global interaction diagram that reflects the consolidated domain knowledge. Third, the case study illustrates how the method utilizes a graphical modelling language for effective tree-based description of interactions, their composition and routing relations, and their roles. A process analysis of the global interaction diagram is shown to identify HCP improvement opportunities. The proposed interaction-centric method has wider applicability since interactions are the core of most multidisciplinary patient-care processes. A discussion argues that, although (multidisciplinary) collaboration is in many cases not optimal in the healthcare domain, it is increasingly considered a necessity to improve integration, continuity, and quality of care. The proposed method is helpful to describe, analyze, and improve the functioning of healthcare collaboration. Copyright © 2011 Elsevier Inc. All rights reserved.

Language evolution and human-computer interaction

NASA Technical Reports Server (NTRS)

Grudin, Jonathan; Norman, Donald A.

1991-01-01

Many of the issues that confront designers of interactive computer systems also appear in natural language evolution. Natural languages and human-computer interfaces share as their primary mission the support of extended 'dialogues' between responsive entities. Because in each case one participant is a human being, some of the pressures operating on natural languages, causing them to evolve in order to better support such dialogue, also operate on human-computer 'languages' or interfaces. This does not necessarily push interfaces in the direction of natural language - since one entity in this dialogue is not a human, this is not to be expected. Nonetheless, by discerning where the pressures that guide natural language evolution also appear in human-computer interaction, we can contribute to the design of computer systems and obtain a new perspective on natural languages.

Human-Computer Interaction and Virtual Environments

NASA Technical Reports Server (NTRS)

Noor, Ahmed K. (Compiler)

1995-01-01

The proceedings of the Workshop on Human-Computer Interaction and Virtual Environments are presented along with a list of attendees. The objectives of the workshop were to assess the state-of-technology and level of maturity of several areas in human-computer interaction and to provide guidelines for focused future research leading to effective use of these facilities in the design/fabrication and operation of future high-performance engineering systems.

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

PubMed

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

2018-03-26

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

Molecular Modeling of Structures and Interaction of Human Corticotropin-Releasing Factor (CRF) Binding Protein and CRF Type-2 Receptor

PubMed Central

Slater, Paula G.; Gutierrez-Maldonado, Sebastian E.; Gysling, Katia; Lagos, Carlos F.

2018-01-01

The corticotropin-releasing factor (CRF) system is a key mediator of the stress response and addictive behavior. The CRF system includes four peptides: The CRF system includes four peptides: CRF, urocortins I–III, CRF binding protein (CRF-BP) that binds CRF with high affinity, and two class B G-protein coupled receptors CRF1R and CRF2R. CRF-BP is a secreted protein without significant sequence homology to CRF receptors or to any other known class of protein. Recently, it has been described a potentiation role of CRF-BP over CRF signaling through CRF2R in addictive-related neuronal plasticity and behavior. In addition, it has been described that CRF-BP is capable to physically interact specifically with the α isoform of CRF2R and acts like an escort protein increasing the amount of the receptor in the plasma membrane. At present, there are no available structures for CRF-BP or for full-length CRFR. Knowing and studying the structure of these proteins could be beneficial in order to characterize the CRF-BP/CRF2αR interaction. In this work, we report the modeling of CRF-BP and of full-length CRF2αR and CRF2βR based on the recently solved crystal structures of the transmembrane domains of the human glucagon receptor and human CRF1R, in addition with the resolved N-terminal extracellular domain of CRFRs. These models were further studied using molecular dynamics simulations and protein–protein docking. The results predicted a higher possibility of interaction of CRF-BP with CRF2αR than CRF2βR and yielded the possible residues conforming the interacting interface. Thus, the present study provides a framework for further investigation of the CRF-BP/CRF2αR interaction. PMID:29515519

Prosodic alignment in human-computer interaction

NASA Astrophysics Data System (ADS)

Suzuki, N.; Katagiri, Y.

2007-06-01

Androids that replicate humans in form also need to replicate them in behaviour to achieve a high level of believability or lifelikeness. We explore the minimal social cues that can induce in people the human tendency for social acceptance, or ethopoeia, toward artifacts, including androids. It has been observed that people exhibit a strong tendency to adjust to each other, through a number of speech and language features in human-human conversational interactions, to obtain communication efficiency and emotional engagement. We investigate in this paper the phenomena related to prosodic alignment in human-computer interactions, with particular focus on human-computer alignment of speech characteristics. We found that people exhibit unidirectional and spontaneous short-term alignment of loudness and response latency in their speech in response to computer-generated speech. We believe this phenomenon of prosodic alignment provides one of the key components for building social acceptance of androids.

Eyeblink Synchrony in Multimodal Human-Android Interaction.

PubMed

Tatsukawa, Kyohei; Nakano, Tamami; Ishiguro, Hiroshi; Yoshikawa, Yuichiro

2016-12-23

As the result of recent progress in technology of communication robot, robots are becoming an important social partner for humans. Behavioral synchrony is understood as an important factor in establishing good human-robot relationships. In this study, we hypothesized that biasing a human's attitude toward a robot changes the degree of synchrony between human and robot. We first examined whether eyeblinks were synchronized between a human and an android in face-to-face interaction and found that human listeners' eyeblinks were entrained to android speakers' eyeblinks. This eyeblink synchrony disappeared when the android speaker spoke while looking away from the human listeners but was enhanced when the human participants listened to the speaking android while touching the android's hand. These results suggest that eyeblink synchrony reflects a qualitative state in human-robot interactions.

HLPI-Ensemble: Prediction of human lncRNA-protein interactions based on ensemble strategy.

PubMed

Hu, Huan; Zhang, Li; Ai, Haixin; Zhang, Hui; Fan, Yetian; Zhao, Qi; Liu, Hongsheng

2018-03-27

LncRNA plays an important role in many biological and disease progression by binding to related proteins. However, the experimental methods for studying lncRNA-protein interactions are time-consuming and expensive. Although there are a few models designed to predict the interactions of ncRNA-protein, they all have some common drawbacks that limit their predictive performance. In this study, we present a model called HLPI-Ensemble designed specifically for human lncRNA-protein interactions. HLPI-Ensemble adopts the ensemble strategy based on three mainstream machine learning algorithms of Support Vector Machines (SVM), Random Forests (RF) and Extreme Gradient Boosting (XGB) to generate HLPI-SVM Ensemble, HLPI-RF Ensemble and HLPI-XGB Ensemble, respectively. The results of 10-fold cross-validation show that HLPI-SVM Ensemble, HLPI-RF Ensemble and HLPI-XGB Ensemble achieved AUCs of 0.95, 0.96 and 0.96, respectively, in the test dataset. Furthermore, we compared the performance of the HLPI-Ensemble models with the previous models through external validation dataset. The results show that the false positives (FPs) of HLPI-Ensemble models are much lower than that of the previous models, and other evaluation indicators of HLPI-Ensemble models are also higher than those of the previous models. It is further showed that HLPI-Ensemble models are superior in predicting human lncRNA-protein interaction compared with previous models. The HLPI-Ensemble is publicly available at: http://ccsipb.lnu.edu.cn/hlpiensemble/ .

Metaphors to Drive By: Exploring New Ways to Guide Human-Robot Interaction

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

David J. Bruemmer; David I. Gertman; Curtis W. Nielsen

2007-08-01

Autonomous behaviors created by the research and development community are not being extensively utilized within energy, defense, security, or industrial contexts. This paper provides evidence that the interaction methods used alongside these behaviors may not provide a mental model that can be easily adopted or used by operators. Although autonomy has the potential to reduce overall workload, the use of robot behaviors often increased the complexity of the underlying interaction metaphor. This paper reports our development of new metaphors that support increased robot complexity without passing the complexity of the interaction onto the operator. Furthermore, we illustrate how recognition ofmore » problems in human-robot interactions can drive the creation of new metaphors for design and how human factors lessons in usability, human performance, and our social contract with technology have the potential for enormous payoff in terms of establishing effective, user-friendly robot systems when appropriate metaphors are used.« less

Quantifying human-environment interactions using videography in the context of infectious disease transmission.

PubMed

Julian, Timothy R; Bustos, Carla; Kwong, Laura H; Badilla, Alejandro D; Lee, Julia; Bischel, Heather N; Canales, Robert A

2018-05-08

Quantitative data on human-environment interactions are needed to fully understand infectious disease transmission processes and conduct accurate risk assessments. Interaction events occur during an individual's movement through, and contact with, the environment, and can be quantified using diverse methodologies. Methods that utilize videography, coupled with specialized software, can provide a permanent record of events, collect detailed interactions in high resolution, be reviewed for accuracy, capture events difficult to observe in real-time, and gather multiple concurrent phenomena. In the accompanying video, the use of specialized software to capture humanenvironment interactions for human exposure and disease transmission is highlighted. Use of videography, combined with specialized software, allows for the collection of accurate quantitative representations of human-environment interactions in high resolution. Two specialized programs include the Virtual Timing Device for the Personal Computer, which collects sequential microlevel activity time series of contact events and interactions, and LiveTrak, which is optimized to facilitate annotation of events in real-time. Opportunities to annotate behaviors at high resolution using these tools are promising, permitting detailed records that can be summarized to gain information on infectious disease transmission and incorporated into more complex models of human exposure and risk.

Temporal stability in human interaction networks

NASA Astrophysics Data System (ADS)

Fabbri, Renato; Fabbri, Ricardo; Antunes, Deborah Christina; Pisani, Marilia Mello; de Oliveira, Osvaldo Novais

2017-11-01

This paper reports on stable (or invariant) properties of human interaction networks, with benchmarks derived from public email lists. Activity, recognized through messages sent, along time and topology were observed in snapshots in a timeline, and at different scales. Our analysis shows that activity is practically the same for all networks across timescales ranging from seconds to months. The principal components of the participants in the topological metrics space remain practically unchanged as different sets of messages are considered. The activity of participants follows the expected scale-free trace, thus yielding the hub, intermediary and peripheral classes of vertices by comparison against the Erdös-Rényi model. The relative sizes of these three sectors are essentially the same for all email lists and the same along time. Typically, < 15% of the vertices are hubs, 15%-45% are intermediary and > 45% are peripheral vertices. Similar results for the distribution of participants in the three sectors and for the relative importance of the topological metrics were obtained for 12 additional networks from Facebook, Twitter and ParticipaBR. These properties are consistent with the literature and may be general for human interaction networks, which has important implications for establishing a typology of participants based on quantitative criteria.

User Localization During Human-Robot Interaction

PubMed Central

Alonso-Martín, F.; Gorostiza, Javi F.; Malfaz, María; Salichs, Miguel A.

2012-01-01

This paper presents a user localization system based on the fusion of visual information and sound source localization, implemented on a social robot called Maggie. One of the main requisites to obtain a natural interaction between human-human and human-robot is an adequate spatial situation between the interlocutors, that is, to be orientated and situated at the right distance during the conversation in order to have a satisfactory communicative process. Our social robot uses a complete multimodal dialog system which manages the user-robot interaction during the communicative process. One of its main components is the presented user localization system. To determine the most suitable allocation of the robot in relation to the user, a proxemic study of the human-robot interaction is required, which is described in this paper. The study has been made with two groups of users: children, aged between 8 and 17, and adults. Finally, at the end of the paper, experimental results with the proposed multimodal dialog system are presented. PMID:23012577

On the Rhetorical Contract in Human-Computer Interaction.

ERIC Educational Resources Information Center

Wenger, Michael J.

1991-01-01

An exploration of the rhetorical contract--i.e., the expectations for appropriate interaction--as it develops in human-computer interaction revealed that direct manipulation interfaces were more likely to establish social expectations. Study results suggest that the social nature of human-computer interactions can be examined with reference to the…

Modelling human decision-making in coupled human and natural systems

NASA Astrophysics Data System (ADS)

Feola, G.

2012-12-01

A solid understanding of human decision-making is essential to analyze the complexity of coupled human and natural systems (CHANS) and inform policies to promote resilience in the face of environmental change. Human decisions drive and/or mediate the interactions and feedbacks, and contribute to the heterogeneity and non-linearity that characterize CHANS. However, human decision-making is usually over-simplistically modeled, whereby human agents are represented deterministically either as dumb or clairvoyant decision-makers. Decision-making models fall short in the integration of both environmental and human behavioral drivers, and concerning the latter, tend to focus on only one category, e.g. economic, cultural, or psychological. Furthermore, these models render a linear decision-making process and therefore fail to account for the recursive co-evolutionary dynamics in CHANS. As a result, these models constitute only a weak basis for policy-making. There is therefore scope and an urgent need for better approaches to human decision-making, to produce the knowledge that can inform vulnerability reduction policies in the face of environmental change. This presentation synthesizes the current state-of-the-art of modelling human decision-making in CHANS, with particular reference to agricultural systems, and delineates how the above mentioned shortcomings can be overcome. Through examples from research on pesticide use and adaptation to climate change, both based on the integrative agent-centered framework (Feola and Binder, 2010), the approach for an improved understanding of human agents in CHANS are illustrated. This entails: integrative approach, focus on behavioral dynamics more than states, feedbacks between individual and system levels, and openness to heterogeneity.

Simplifying the interaction between cognitive models and task environments with the JSON Network Interface.

PubMed

Hope, Ryan M; Schoelles, Michael J; Gray, Wayne D

2014-12-01

Process models of cognition, written in architectures such as ACT-R and EPIC, should be able to interact with the same software with which human subjects interact. By eliminating the need to simulate the experiment, this approach would simplify the modeler's effort, while ensuring that all steps required of the human are also required by the model. In practice, the difficulties of allowing one software system to interact with another present a significant barrier to any modeler who is not also skilled at this type of programming. The barrier increases if the programming language used by the modeling software differs from that used by the experimental software. The JSON Network Interface simplifies this problem for ACT-R modelers, and potentially, modelers using other systems.

Human-Robot Interaction: Status and Challenges.

PubMed

Sheridan, Thomas B

2016-06-01

The current status of human-robot interaction (HRI) is reviewed, and key current research challenges for the human factors community are described. Robots have evolved from continuous human-controlled master-slave servomechanisms for handling nuclear waste to a broad range of robots incorporating artificial intelligence for many applications and under human supervisory control. This mini-review describes HRI developments in four application areas and what are the challenges for human factors research. In addition to a plethora of research papers, evidence of success is manifest in live demonstrations of robot capability under various forms of human control. HRI is a rapidly evolving field. Specialized robots under human teleoperation have proven successful in hazardous environments and medical application, as have specialized telerobots under human supervisory control for space and repetitive industrial tasks. Research in areas of self-driving cars, intimate collaboration with humans in manipulation tasks, human control of humanoid robots for hazardous environments, and social interaction with robots is at initial stages. The efficacy of humanoid general-purpose robots has yet to be proven. HRI is now applied in almost all robot tasks, including manufacturing, space, aviation, undersea, surgery, rehabilitation, agriculture, education, package fetch and delivery, policing, and military operations. © 2016, Human Factors and Ergonomics Society.

Computational identification of gene–social environment interaction at the human IL6 locus

PubMed Central

Cole, Steven W.; Arevalo, Jesusa M. G.; Takahashi, Rie; Sloan, Erica K.; Lutgendorf, Susan K.; Sood, Anil K.; Sheridan, John F.; Seeman, Teresa E.

2010-01-01

To identify genetic factors that interact with social environments to impact human health, we used a bioinformatic strategy that couples expression array–based detection of environmentally responsive transcription factors with in silico discovery of regulatory polymorphisms to predict genetic loci that modulate transcriptional responses to stressful environments. Tests of one predicted interaction locus in the human IL6 promoter (SNP rs1800795) verified that it modulates transcriptional response to β-adrenergic activation of the GATA1 transcription factor in vitro. In vivo validation studies confirmed links between adverse social conditions and increased transcription of GATA1 target genes in primary neural, immune, and cancer cells. Epidemiologic analyses verified the health significance of those molecular interactions by documenting increased 10-year mortality risk associated with late-life depressive symptoms that occurred solely for homozygous carriers of the GATA1-sensitive G allele of rs1800795. Gating of depression-related mortality risk by IL6 genotype pertained only to inflammation-related causes of death and was associated with increased chronic inflammation as indexed by plasma C-reactive protein. Computational modeling of molecular interactions, in vitro biochemical analyses, in vivo animal modeling, and human molecular epidemiologic analyses thus converge in identifying β-adrenergic activation of GATA1 as a molecular pathway by which social adversity can alter human health risk selectively depending on individual genetic status at the IL6 locus. PMID:20176930

Cognitive Architectures and Human-Computer Interaction. Introduction to Special Issue.

ERIC Educational Resources Information Center

Gray, Wayne D.; Young, Richard M.; Kirschenbaum, Susan S.

1997-01-01

In this introduction to a special issue on cognitive architectures and human-computer interaction (HCI), editors and contributors provide a brief overview of cognitive architectures. The following four architectures represented by articles in this issue are: Soar; LICAI (linked model of comprehension-based action planning and instruction taking);…

The effect of model uncertainty on cooperation in sensorimotor interactions

PubMed Central

Grau-Moya, J.; Hez, E.; Pezzulo, G.; Braun, D. A.

2013-01-01

Decision-makers have been shown to rely on probabilistic models for perception and action. However, these models can be incorrect or partially wrong in which case the decision-maker has to cope with model uncertainty. Model uncertainty has recently also been shown to be an important determinant of sensorimotor behaviour in humans that can lead to risk-sensitive deviations from Bayes optimal behaviour towards worst-case or best-case outcomes. Here, we investigate the effect of model uncertainty on cooperation in sensorimotor interactions similar to the stag-hunt game, where players develop models about the other player and decide between a pay-off-dominant cooperative solution and a risk-dominant, non-cooperative solution. In simulations, we show that players who allow for optimistic deviations from their opponent model are much more likely to converge to cooperative outcomes. We also implemented this agent model in a virtual reality environment, and let human subjects play against a virtual player. In this game, subjects' pay-offs were experienced as forces opposing their movements. During the experiment, we manipulated the risk sensitivity of the computer player and observed human responses. We found not only that humans adaptively changed their level of cooperation depending on the risk sensitivity of the computer player but also that their initial play exhibited characteristic risk-sensitive biases. Our results suggest that model uncertainty is an important determinant of cooperation in two-player sensorimotor interactions. PMID:23945266

Interaction in Spoken Word Recognition Models: Feedback Helps.

PubMed

Magnuson, James S; Mirman, Daniel; Luthra, Sahil; Strauss, Ted; Harris, Harlan D

2018-01-01

Human perception, cognition, and action requires fast integration of bottom-up signals with top-down knowledge and context. A key theoretical perspective in cognitive science is the interactive activation hypothesis: forward and backward flow in bidirectionally connected neural networks allows humans and other biological systems to approximate optimal integration of bottom-up and top-down information under real-world constraints. An alternative view is that online feedback is neither necessary nor helpful; purely feed forward alternatives can be constructed for any feedback system, and online feedback could not improve processing and would preclude veridical perception. In the domain of spoken word recognition, the latter view was apparently supported by simulations using the interactive activation model, TRACE, with and without feedback: as many words were recognized more quickly without feedback as were recognized faster with feedback, However, these simulations used only a small set of words and did not address a primary motivation for interaction: making a model robust in noise. We conducted simulations using hundreds of words, and found that the majority were recognized more quickly with feedback than without. More importantly, as we added noise to inputs, accuracy and recognition times were better with feedback than without. We follow these simulations with a critical review of recent arguments that online feedback in interactive activation models like TRACE is distinct from other potentially helpful forms of feedback. We conclude that in addition to providing the benefits demonstrated in our simulations, online feedback provides a plausible means of implementing putatively distinct forms of feedback, supporting the interactive activation hypothesis.

Interaction in Spoken Word Recognition Models: Feedback Helps

PubMed Central

Magnuson, James S.; Mirman, Daniel; Luthra, Sahil; Strauss, Ted; Harris, Harlan D.

2018-01-01

Human perception, cognition, and action requires fast integration of bottom-up signals with top-down knowledge and context. A key theoretical perspective in cognitive science is the interactive activation hypothesis: forward and backward flow in bidirectionally connected neural networks allows humans and other biological systems to approximate optimal integration of bottom-up and top-down information under real-world constraints. An alternative view is that online feedback is neither necessary nor helpful; purely feed forward alternatives can be constructed for any feedback system, and online feedback could not improve processing and would preclude veridical perception. In the domain of spoken word recognition, the latter view was apparently supported by simulations using the interactive activation model, TRACE, with and without feedback: as many words were recognized more quickly without feedback as were recognized faster with feedback, However, these simulations used only a small set of words and did not address a primary motivation for interaction: making a model robust in noise. We conducted simulations using hundreds of words, and found that the majority were recognized more quickly with feedback than without. More importantly, as we added noise to inputs, accuracy and recognition times were better with feedback than without. We follow these simulations with a critical review of recent arguments that online feedback in interactive activation models like TRACE is distinct from other potentially helpful forms of feedback. We conclude that in addition to providing the benefits demonstrated in our simulations, online feedback provides a plausible means of implementing putatively distinct forms of feedback, supporting the interactive activation hypothesis. PMID:29666593

Self-Powered Human-Interactive Transparent Nanopaper Systems.

PubMed

Zhong, Junwen; Zhu, Hongli; Zhong, Qize; Dai, Jiaqi; Li, Wenbo; Jang, Soo-Hwan; Yao, Yonggang; Henderson, Doug; Hu, Qiyi; Hu, Liangbing; Zhou, Jun

2015-07-28

Self-powered human-interactive but invisible electronics have many applications in anti-theft and anti-fake systems for human society. In this work, for the first time, we demonstrate a transparent paper-based, self-powered, and human-interactive flexible system. The system is based on an electrostatic induction mechanism with no extra power system appended. The self-powered, transparent paper device can be used for a transparent paper-based art anti-theft system in museums or for a smart mapping anti-fake system in precious packaging and documents, by virtue of the advantages of adding/removing freely, having no impairment on the appearance of the protected objects, and being easily mass manufactured. This initial study bridges the transparent nanopaper with a self-powered and human-interactive electronic system, paving the way for the development of smart transparent paper electronics.

Eyeblink Synchrony in Multimodal Human-Android Interaction

PubMed Central

Tatsukawa, Kyohei; Nakano, Tamami; Ishiguro, Hiroshi; Yoshikawa, Yuichiro

2016-01-01

As the result of recent progress in technology of communication robot, robots are becoming an important social partner for humans. Behavioral synchrony is understood as an important factor in establishing good human-robot relationships. In this study, we hypothesized that biasing a human’s attitude toward a robot changes the degree of synchrony between human and robot. We first examined whether eyeblinks were synchronized between a human and an android in face-to-face interaction and found that human listeners’ eyeblinks were entrained to android speakers’ eyeblinks. This eyeblink synchrony disappeared when the android speaker spoke while looking away from the human listeners but was enhanced when the human participants listened to the speaking android while touching the android’s hand. These results suggest that eyeblink synchrony reflects a qualitative state in human-robot interactions. PMID:28009014

Quantitative systems pharmacology analysis of drug combination and scaling to humans: the interaction between noradrenaline and vasopressin on vasoconstriction.

PubMed

Yin, Anyue; Yamada, Akihiro; Stam, Wiro B; van Hasselt, Johan G C; van der Graaf, Piet H

2018-06-02

Development of combination therapies has received significant interest in recent years. Previously a two-receptor one-transducer (2R-1T) model was proposed to characterize drug interactions with two receptors that lead to the same phenotypic response through a common transducer pathway. We applied, for the first time, the 2R-1T model to characterize the interaction of noradrenaline and arginine-vasopressin on vasoconstriction, and performed inter-species scaling to humans using this mechanism-based model. Contractile data was obtained from in vitro rat small mesenteric arteries after exposure to single or combined challenges of noradrenaline and arginine-vasopressin with or without pre-treatment with the irreversible α-adrenoceptor antagonist, phenoxybenzamine. Data was analysed using the 2R-1T model to characterize the observed exposure-response relationships and drug-drug interaction. The model was then scaled to humans by accounting for differences in receptor density. With receptor affinities set to literature values, the 2R-1T model satisfactorily characterized the interaction between noradrenaline and arginine-vasopressin in rat small mesenteric arteries (relative standard error ≤ 20%), as well as the effect of phenoxybenzamine. Furthermore, after scaling the model to human vascular tissue, the model also adequately predicted the interaction between both agents on human renal arteries. The 2R-1T model can be of relevance to quantitatively characterize the interaction between two drugs that interact via different receptors and a common transducer pathway. Its mechanistic properties are valuable for scaling the model across species. This approach is therefore of significant value to rationally optimize novel combination treatments. This article is protected by copyright. All rights reserved.

Why E-Business Must Evolve beyond Market Orientation: Applying Human Interaction Models to Computer-Mediated Corporate Communications.

ERIC Educational Resources Information Center

Johnston, Kevin McCullough

2001-01-01

Considers the design of corporate communications for electronic business and discusses the increasing importance of corporate interaction as companies work in virtual environments. Compares sociological and psychological theories of human interaction and relationship formation with organizational interaction theories of corporate relationship…

A Budyko-type Model for Human Water Consumption

NASA Astrophysics Data System (ADS)

Lei, X.; Zhao, J.; Wang, D.; Sivapalan, M.

2017-12-01

With the expansion of human water footprint, water crisis is no longer only a conflict or competition for water between different economic sectors, but also increasingly between human and the environment. In order to describe the emergent dynamics and patterns of the interaction, a theoretical framework that encapsulates the physical and societal controls impacting human water consumption is needed. In traditional hydrology, Budyko-type models are simple but efficient descriptions of vegetation-mediated hydrologic cycle in catchments, i.e., the partitioning of mean annual precipitation into runoff and evapotranspiration. Plant water consumption plays a crucial role in the process. Hypothesized similarities between human-water and vegetation-water interactions, including water demand, constraints and system functioning, give the idea of corresponding Budyko-type framework for human water consumption at the catchment scale. Analogous to variables of Budyko-type models for hydrologic cycle, water demand, water consumption, environmental water use and available water are corresponding to potential evaporation, actual evaporation, runoff and precipitation respectively. Human water consumption data, economic and hydro-meteorological data for 51 human-impacted catchments and 10 major river basins in China are assembled to look for the existence of a Budyko-type relationship for human water consumption, and to seek explanations for the spread in the observed relationship. Guided by this, a Budyko-type analytical model is derived based on application of an optimality principle, that of maximum water benefit. The model derived has the same functional form and mathematical features as those that apply for the original Budyko model. Parameters of the new Budyko-type model for human consumption are linked to economic and social factors. The results of this paper suggest that the functioning of both social and hydrologic subsystems within catchment systems can be explored within

Implementing Lumberjacks and Black Swans Into Model-Based Tools to Support Human-Automation Interaction.

PubMed

Sebok, Angelia; Wickens, Christopher D

2017-03-01

The objectives were to (a) implement theoretical perspectives regarding human-automation interaction (HAI) into model-based tools to assist designers in developing systems that support effective performance and (b) conduct validations to assess the ability of the models to predict operator performance. Two key concepts in HAI, the lumberjack analogy and black swan events, have been studied extensively. The lumberjack analogy describes the effects of imperfect automation on operator performance. In routine operations, an increased degree of automation supports performance, but in failure conditions, increased automation results in more significantly impaired performance. Black swans are the rare and unexpected failures of imperfect automation. The lumberjack analogy and black swan concepts have been implemented into three model-based tools that predict operator performance in different systems. These tools include a flight management system, a remotely controlled robotic arm, and an environmental process control system. Each modeling effort included a corresponding validation. In one validation, the software tool was used to compare three flight management system designs, which were ranked in the same order as predicted by subject matter experts. The second validation compared model-predicted operator complacency with empirical performance in the same conditions. The third validation compared model-predicted and empirically determined time to detect and repair faults in four automation conditions. The three model-based tools offer useful ways to predict operator performance in complex systems. The three tools offer ways to predict the effects of different automation designs on operator performance.

Optimal design method to minimize users' thinking mapping load in human-machine interactions.

PubMed

Huang, Yanqun; Li, Xu; Zhang, Jie

2015-01-01

The discrepancy between human cognition and machine requirements/behaviors usually results in serious mental thinking mapping loads or even disasters in product operating. It is important to help people avoid human-machine interaction confusions and difficulties in today's mental work mastered society. Improving the usability of a product and minimizing user's thinking mapping and interpreting load in human-machine interactions. An optimal human-machine interface design method is introduced, which is based on the purpose of minimizing the mental load in thinking mapping process between users' intentions and affordance of product interface states. By analyzing the users' thinking mapping problem, an operating action model is constructed. According to human natural instincts and acquired knowledge, an expected ideal design with minimized thinking loads is uniquely determined at first. Then, creative alternatives, in terms of the way human obtains operational information, are provided as digital interface states datasets. In the last, using the cluster analysis method, an optimum solution is picked out from alternatives, by calculating the distances between two datasets. Considering multiple factors to minimize users' thinking mapping loads, a solution nearest to the ideal value is found in the human-car interaction design case. The clustering results show its effectiveness in finding an optimum solution to the mental load minimizing problems in human-machine interaction design.

Top-down systems biology integration of conditional prebiotic modulated transgenomic interactions in a humanized microbiome mouse model

PubMed Central

Martin, Francois-Pierre J; Wang, Yulan; Sprenger, Norbert; Yap, Ivan K S; Rezzi, Serge; Ramadan, Ziad; Peré-Trepat, Emma; Rochat, Florence; Cherbut, Christine; van Bladeren, Peter; Fay, Laurent B; Kochhar, Sunil; Lindon, John C; Holmes, Elaine; Nicholson, Jeremy K

2008-01-01

Gut microbiome–host metabolic interactions affect human health and can be modified by probiotic and prebiotic supplementation. Here, we have assessed the effects of consumption of a combination of probiotics (Lactobacillus paracasei or L. rhamnosus) and two galactosyl-oligosaccharide prebiotics on the symbiotic microbiome–mammalian supersystem using integrative metabolic profiling and modeling of multiple compartments in germ-free mice inoculated with a model of human baby microbiota. We have shown specific impacts of two prebiotics on the microbial populations of HBM mice when co-administered with two probiotics. We observed an increase in the populations of Bifidobacterium longum and B. breve, and a reduction in Clostridium perfringens, which were more marked when combining prebiotics with L. rhamnosus. In turn, these microbial effects were associated with modulation of a range of host metabolic pathways observed via changes in lipid profiles, gluconeogenesis, and amino-acid and methylamine metabolism associated to fermentation of carbohydrates by different bacterial strains. These results provide evidence for the potential use of prebiotics for beneficially modifying the gut microbial balance as well as host energy and lipid homeostasis. PMID:18628745

The Evolution of Integrated Assessment and Emerging Challenges in the Assessment of Human and Natural System Interactions

NASA Astrophysics Data System (ADS)

Clarke, L.

2017-12-01

Integrated assessment (IA) modeling and research has a long history, spanning over 30 years since its inception and addressing a wide range of contemporary issues along the way. Over the last decade, IA modeling and research has emerged as one of the primary analytical methods for understanding the complex interactions between human and natural systems, from the interactions between energy, water, and land/food systems to the interplay between health, climate, and air pollution. IA modeling and research is particularly well-suited for the analysis of these interactions because it is a discipline that strives to integrate representations of multiple systems into consistent computational platforms or frameworks. In doing so, it explicitly confronts the many tradeoffs that are frequently necessary to manage complexity and computational cost while still representing the most important interactions and overall, coupled system behavior. This talk explores the history of IA modeling and research as a means to better understand its role in the assessment of contemporary issues at the confluence of human and natural systems. It traces the evolution of IA modeling and research from initial exploration of long-term emissions pathways, to the role of technology in the global evolution of the energy system, to the key linkages between land and energy systems and, more recently, the linkages with water, air pollution, and other key systems and issues. It discusses the advances in modeling that have emerged over this evolution and the biggest challenges that still present themselves as we strive to better understand the most important interactions between human and natural systems and the implications of these interactions for human welfare and decision making.

Investigation of interactions of Comtan with human serum albumin by mathematically modeled voltammetric data: A study from bio-interaction to biosensing.

PubMed

Jalalvand, Ali R; Ghobadi, Sirous; Goicoechea, Hector C; Gu, Hui-Wen; Sanchooli, Esmael

2018-05-16

In this work, voltammetric data recorded at a glassy carbon electrode (GCE) were separately used to investigate the interactions of entacapone (Comtan, CAT) with human serum albumin (HSA). Then, an augmented data matrix was constructed by the combination of voltammetric and spectroscopic data and simultaneously analysed by multivariate curve resolution-alternating least squares (MCR-ALS) to obtain more information about CAT-HSA interactions. The absence of rotational ambiguities in results obtained by MCR-ALS was verified with the help of MCR-BANDS and we confirmed that the results were unambiguous and reliable. Binding of CAT to HSA was also modeled by molecular docking and the results were compatible with those of obtained by recording experimental data. Hard-modeling of combined voltammetric and spectroscopic data by EQUISPEC as an efficient chemometric algorithm helped us to compute binding constant of CAT-HSA complex specie which was in a good agreement with the binding constant value obtained by direct analysis of experimental data. For electrochemical sensing of serum albumin two amperometric measurements were performed to determine HSA in 2-27 nM and 27-70 nM with a limit of detection of 0.51 nM and a sensitivity of 1.84 μA nM -1 . Copyright © 2017 Elsevier B.V. All rights reserved.

New activity pattern in human interactive dynamics

NASA Astrophysics Data System (ADS)

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

2015-09-01

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

Control of a Robot Dancer for Enhancing Haptic Human-Robot Interaction in Waltz.

PubMed

Hongbo Wang; Kosuge, K

2012-01-01

Haptic interaction between a human leader and a robot follower in waltz is studied in this paper. An inverted pendulum model is used to approximate the human's body dynamics. With the feedbacks from the force sensor and laser range finders, the robot is able to estimate the human leader's state by using an extended Kalman filter (EKF). To reduce interaction force, two robot controllers, namely, admittance with virtual force controller, and inverted pendulum controller, are proposed and evaluated in experiments. The former controller failed the experiment; reasons for the failure are explained. At the same time, the use of the latter controller is validated by experiment results.

Interaction between synaptic inhibition and glial-potassium dynamics leads to diverse seizure transition modes in biophysical models of human focal seizures.

PubMed

Y Ho, E C; Truccolo, Wilson

2016-10-01

How focal seizures initiate and evolve in human neocortex remains a fundamental problem in neuroscience. Here, we use biophysical neuronal network models of neocortical patches to study how the interaction between inhibition and extracellular potassium ([K (+)] o ) dynamics may contribute to different types of focal seizures. Three main types of propagated focal seizures observed in recent intracortical microelectrode recordings in humans were modelled: seizures characterized by sustained (∼30-60 Hz) gamma local field potential (LFP) oscillations; seizures where the onset in the propagated site consisted of LFP spikes that later evolved into rhythmic (∼2-3 Hz) spike-wave complexes (SWCs); and seizures where a brief stage of low-amplitude fast-oscillation (∼10-20 Hz) LFPs preceded the SWC activity. Our findings are fourfold: (1) The interaction between elevated [K (+)] o (due to abnormal potassium buffering by glial cells) and the strength of synaptic inhibition plays a predominant role in shaping these three types of seizures. (2) Strengthening of inhibition leads to the onset of sustained narrowband gamma seizures. (3) Transition into SWC seizures is obtained either by the weakening of inhibitory synapses, or by a transient strengthening followed by an inhibitory breakdown (e.g. GABA depletion). This reduction or breakdown of inhibition among fast-spiking (FS) inhibitory interneurons increases their spiking activity and leads them eventually into depolarization block. Ictal spike-wave discharges in the model are then sustained solely by pyramidal neurons. (4) FS cell dynamics are also critical for seizures where the evolution into SWC activity is preceded by low-amplitude fast oscillations. Different levels of elevated [K (+)] o were important for transitions into and maintenance of sustained gamma oscillations and SWC discharges. Overall, our modelling study predicts that the interaction between inhibitory interneurons and [K (+)] o glial buffering under

A componential model of human interaction with graphs: 1. Linear regression modeling

NASA Technical Reports Server (NTRS)

Gillan, Douglas J.; Lewis, Robert

1994-01-01

Task analyses served as the basis for developing the Mixed Arithmetic-Perceptual (MA-P) model, which proposes (1) that people interacting with common graphs to answer common questions apply a set of component processes-searching for indicators, encoding the value of indicators, performing arithmetic operations on the values, making spatial comparisons among indicators, and repsonding; and (2) that the type of graph and user's task determine the combination and order of the components applied (i.e., the processing steps). Two experiments investigated the prediction that response time will be linearly related to the number of processing steps according to the MA-P model. Subjects used line graphs, scatter plots, and stacked bar graphs to answer comparison questions and questions requiring arithmetic calculations. A one-parameter version of the model (with equal weights for all components) and a two-parameter version (with different weights for arithmetic and nonarithmetic processes) accounted for 76%-85% of individual subjects' variance in response time and 61%-68% of the variance taken across all subjects. The discussion addresses possible modifications in the MA-P model, alternative models, and design implications from the MA-P model.

Interactive Exploration Robots: Human-Robotic Collaboration and Interactions

NASA Technical Reports Server (NTRS)

Fong, Terry

2017-01-01

For decades, NASA has employed different operational approaches for human and robotic missions. Human spaceflight missions to the Moon and in low Earth orbit have relied upon near-continuous communication with minimal time delays. During these missions, astronauts and mission control communicate interactively to perform tasks and resolve problems in real-time. In contrast, deep-space robotic missions are designed for operations in the presence of significant communication delay - from tens of minutes to hours. Consequently, robotic missions typically employ meticulously scripted and validated command sequences that are intermittently uplinked to the robot for independent execution over long periods. Over the next few years, however, we will see increasing use of robots that blend these two operational approaches. These interactive exploration robots will be remotely operated by humans on Earth or from a spacecraft. These robots will be used to support astronauts on the International Space Station (ISS), to conduct new missions to the Moon, and potentially to enable remote exploration of planetary surfaces in real-time. In this talk, I will discuss the technical challenges associated with building and operating robots in this manner, along with lessons learned from research conducted with the ISS and in the field.

Patient-Specific Computational Modeling of Human Phonation

NASA Astrophysics Data System (ADS)

Xue, Qian; Zheng, Xudong; University of Maine Team

2013-11-01

Phonation is a common biological process resulted from the complex nonlinear coupling between glottal aerodynamics and vocal fold vibrations. In the past, the simplified symmetric straight geometric models were commonly employed for experimental and computational studies. The shape of larynx lumen and vocal folds are highly three-dimensional indeed and the complex realistic geometry produces profound impacts on both glottal flow and vocal fold vibrations. To elucidate the effect of geometric complexity on voice production and improve the fundamental understanding of human phonation, a full flow-structure interaction simulation is carried out on a patient-specific larynx model. To the best of our knowledge, this is the first patient-specific flow-structure interaction study of human phonation. The simulation results are well compared to the established human data. The effects of realistic geometry on glottal flow and vocal fold dynamics are investigated. It is found that both glottal flow and vocal fold dynamics present a high level of difference from the previous simplified model. This study also paved the important step toward the development of computer model for voice disease diagnosis and surgical planning. The project described was supported by Grant Number ROlDC007125 from the National Institute on Deafness and Other Communication Disorders (NIDCD).

The relevance of non-human primate and rodent malaria models for humans

PubMed Central

2011-01-01

At the 2010 Keystone Symposium on "Malaria: new approaches to understanding Host-Parasite interactions", an extra scientific session to discuss animal models in malaria research was convened at the request of participants. This was prompted by the concern of investigators that skepticism in the malaria community about the use and relevance of animal models, particularly rodent models of severe malaria, has impacted on funding decisions and publication of research using animal models. Several speakers took the opportunity to demonstrate the similarities between findings in rodent models and human severe disease, as well as points of difference. The variety of malaria presentations in the different experimental models parallels the wide diversity of human malaria disease and, therefore, might be viewed as a strength. Many of the key features of human malaria can be replicated in a variety of nonhuman primate models, which are very under-utilized. The importance of animal models in the discovery of new anti-malarial drugs was emphasized. The major conclusions of the session were that experimental and human studies should be more closely linked so that they inform each other, and that there should be wider access to relevant clinical material. PMID:21288352

Modeling and simulating networks of interdependent protein interactions.

PubMed

Stöcker, Bianca K; Köster, Johannes; Zamir, Eli; Rahmann, Sven

2018-05-21

Protein interactions are fundamental building blocks of biochemical reaction systems underlying cellular functions. The complexity and functionality of these systems emerge not only from the protein interactions themselves but also from the dependencies between these interactions, as generated by allosteric effects or mutual exclusion due to steric hindrance. Therefore, formal models for integrating and utilizing information about interaction dependencies are of high interest. Here, we describe an approach for endowing protein networks with interaction dependencies using propositional logic, thereby obtaining constrained protein interaction networks ("constrained networks"). The construction of these networks is based on public interaction databases as well as text-mined information about interaction dependencies. We present an efficient data structure and algorithm to simulate protein complex formation in constrained networks. The efficiency of the model allows fast simulation and facilitates the analysis of many proteins in large networks. In addition, this approach enables the simulation of perturbation effects, such as knockout of single or multiple proteins and changes of protein concentrations. We illustrate how our model can be used to analyze a constrained human adhesome protein network, which is responsible for the formation of diverse and dynamic cell-matrix adhesion sites. By comparing protein complex formation under known interaction dependencies versus without dependencies, we investigate how these dependencies shape the resulting repertoire of protein complexes. Furthermore, our model enables investigating how the interplay of network topology with interaction dependencies influences the propagation of perturbation effects across a large biochemical system. Our simulation software CPINSim (for Constrained Protein Interaction Network Simulator) is available under the MIT license at http://github.com/BiancaStoecker/cpinsim and as a Bioconda package

Enhancing Human-Computer Interaction Design Education: Teaching Affordance Design for Emerging Mobile Devices

ERIC Educational Resources Information Center

Faiola, Anthony; Matei, Sorin Adam

2010-01-01

The evolution of human-computer interaction design (HCID) over the last 20 years suggests that there is a growing need for educational scholars to consider new and more applicable theoretical models of interactive product design. The authors suggest that such paradigms would call for an approach that would equip HCID students with a better…

Formal verification of human-automation interaction

NASA Technical Reports Server (NTRS)

Degani, Asaf; Heymann, Michael

2002-01-01

This paper discusses a formal and rigorous approach to the analysis of operator interaction with machines. It addresses the acute problem of detecting design errors in human-machine interaction and focuses on verifying the correctness of the interaction in complex and automated control systems. The paper describes a systematic methodology for evaluating whether the interface provides the necessary information about the machine to enable the operator to perform a specified task successfully and unambiguously. It also addresses the adequacy of information provided to the user via training material (e.g., user manual) about the machine's behavior. The essentials of the methodology, which can be automated and applied to the verification of large systems, are illustrated by several examples and through a case study of pilot interaction with an autopilot aboard a modern commercial aircraft. The expected application of this methodology is an augmentation and enhancement, by formal verification, of human-automation interfaces.

Human-Robot Interaction Directed Research Project

NASA Technical Reports Server (NTRS)

Rochlis, Jennifer; Ezer, Neta; Sandor, Aniko

2011-01-01

Human-robot interaction (HRI) is about understanding and shaping the interactions between humans and robots (Goodrich & Schultz, 2007). It is important to evaluate how the design of interfaces and command modalities affect the human s ability to perform tasks accurately, efficiently, and effectively (Crandall, Goodrich, Olsen Jr., & Nielsen, 2005) It is also critical to evaluate the effects of human-robot interfaces and command modalities on operator mental workload (Sheridan, 1992) and situation awareness (Endsley, Bolt , & Jones, 2003). By understanding the effects of interface design on human performance, workload, and situation awareness, interfaces can be developed that support the human in performing tasks with minimal errors and with appropriate interaction time and effort. Thus, the results of research on human-robot interfaces have direct implications for design. Because the factors associated with interfaces and command modalities in HRI are too numerous to address in 3 years of research, the proposed research concentrates on three manageable areas applicable to National Aeronautics and Space Administration (NASA) robot systems. These topic areas emerged from the Fiscal Year (FY) 2011 work that included extensive literature reviews and observations of NASA systems. The three topic areas are: 1) video overlays, 2) camera views, and 3) command modalities. Each area is described in detail below, along with relevance to existing NASA human-robot systems. In addition to studies in these three topic areas, a workshop is proposed for FY12. The workshop will bring together experts in human-robot interaction and robotics to discuss the state of the practice as applicable to research in space robotics. Studies proposed in the area of video overlays consider two factors in the implementation of augmented reality (AR) for operator displays during teleoperation. The first of these factors is the type of navigational guidance provided by AR symbology. In the proposed

Designers' models of the human-computer interface

NASA Technical Reports Server (NTRS)

Gillan, Douglas J.; Breedin, Sarah D.

1993-01-01

Understanding design models of the human-computer interface (HCI) may produce two types of benefits. First, interface development often requires input from two different types of experts: human factors specialists and software developers. Given the differences in their backgrounds and roles, human factors specialists and software developers may have different cognitive models of the HCI. Yet, they have to communicate about the interface as part of the design process. If they have different models, their interactions are likely to involve a certain amount of miscommunication. Second, the design process in general is likely to be guided by designers' cognitive models of the HCI, as well as by their knowledge of the user, tasks, and system. Designers do not start with a blank slate; rather they begin with a general model of the object they are designing. The author's approach to a design model of the HCI was to have three groups make judgments of categorical similarity about the components of an interface: human factors specialists with HCI design experience, software developers with HCI design experience, and a baseline group of computer users with no experience in HCI design. The components of the user interface included both display components such as windows, text, and graphics, and user interaction concepts, such as command language, editing, and help. The judgments of the three groups were analyzed using hierarchical cluster analysis and Pathfinder. These methods indicated, respectively, how the groups categorized the concepts, and network representations of the concepts for each group. The Pathfinder analysis provides greater information about local, pairwise relations among concepts, whereas the cluster analysis shows global, categorical relations to a greater extent.

Mechanical Impedance Modeling of Human Arm: A survey

NASA Astrophysics Data System (ADS)

Puzi, A. Ahmad; Sidek, S. N.; Sado, F.

2017-03-01

Human arm mechanical impedance plays a vital role in describing motion ability of the upper limb. One of the impedance parameters is stiffness which is defined as the ratio of an applied force to the measured deformation of the muscle. The arm mechanical impedance modeling is useful in order to develop a better controller for system that interacts with human as such an automated robot-assisted platform for automated rehabilitation training. The aim of the survey is to summarize the existing mechanical impedance models of human upper limb so to justify the need to have an improved version of the arm model in order to facilitate the development of better controller of such systems with ever increase in complexity. In particular, the paper will address the following issue: Human motor control and motor learning, constant and variable impedance models, methods for measuring mechanical impedance and mechanical impedance modeling techniques.

Facing the challenges of multiscale modelling of bacterial and fungal pathogen–host interactions

PubMed Central

Schleicher, Jana; Conrad, Theresia; Gustafsson, Mika; Cedersund, Gunnar; Guthke, Reinhard

2017-01-01

Abstract Recent and rapidly evolving progress on high-throughput measurement techniques and computational performance has led to the emergence of new disciplines, such as systems medicine and translational systems biology. At the core of these disciplines lies the desire to produce multiscale models: mathematical models that integrate multiple scales of biological organization, ranging from molecular, cellular and tissue models to organ, whole-organism and population scale models. Using such models, hypotheses can systematically be tested. In this review, we present state-of-the-art multiscale modelling of bacterial and fungal infections, considering both the pathogen and host as well as their interaction. Multiscale modelling of the interactions of bacteria, especially Mycobacterium tuberculosis, with the human host is quite advanced. In contrast, models for fungal infections are still in their infancy, in particular regarding infections with the most important human pathogenic fungi, Candida albicans and Aspergillus fumigatus. We reflect on the current availability of computational approaches for multiscale modelling of host–pathogen interactions and point out current challenges. Finally, we provide an outlook for future requirements of multiscale modelling. PMID:26857943

Immune Cell-Supplemented Human Skin Model for Studying Fungal Infections.

PubMed

Kühbacher, Andreas; Sohn, Kai; Burger-Kentischer, Anke; Rupp, Steffen

2017-01-01

Human skin is a niche for various fungal species which either colonize the surface of this tissue as commensals or, primarily under conditions of immunosuppression, invade the skin and cause infection. Here we present a method for generation of a human in vitro skin model supplemented with immune cells of choice. This model represents a complex yet amenable tool to study molecular mechanisms of host-fungi interactions at human skin.

Integrating social science into empirical models of coupled human and natural systems

Treesearch

Jeffrey D. Kline; Eric M. White; A Paige Fischer; Michelle M. Steen-Adams; Susan Charnley; Christine S. Olsen; Thomas A. Spies; John D. Bailey

2017-01-01

Coupled human and natural systems (CHANS) research highlights reciprocal interactions (or feedbacks) between biophysical and socioeconomic variables to explain system dynamics and resilience. Empirical models often are used to test hypotheses and apply theory that represent human behavior. Parameterizing reciprocal interactions presents two challenges for social...

Recognition of human activity characteristics based on state transitions modeling technique

NASA Astrophysics Data System (ADS)

Elangovan, Vinayak; Shirkhodaie, Amir

2012-06-01

Human Activity Discovery & Recognition (HADR) is a complex, diverse and challenging task but yet an active area of ongoing research in the Department of Defense. By detecting, tracking, and characterizing cohesive Human interactional activity patterns, potential threats can be identified which can significantly improve situation awareness, particularly, in Persistent Surveillance Systems (PSS). Understanding the nature of such dynamic activities, inevitably involves interpretation of a collection of spatiotemporally correlated activities with respect to a known context. In this paper, we present a State Transition model for recognizing the characteristics of human activities with a link to a prior contextbased ontology. Modeling the state transitions between successive evidential events determines the activities' temperament. The proposed state transition model poses six categories of state transitions including: Human state transitions of Object handling, Visibility, Entity-entity relation, Human Postures, Human Kinematics and Distance to Target. The proposed state transition model generates semantic annotations describing the human interactional activities via a technique called Casual Event State Inference (CESI). The proposed approach uses a low cost kinect depth camera for indoor and normal optical camera for outdoor monitoring activities. Experimental results are presented here to demonstrate the effectiveness and efficiency of the proposed technique.

Insights into the interaction of methotrexate and human serum albumin: A spectroscopic and molecular modeling approach.

PubMed

Cheng, Li-Yang; Fang, Min; Bai, Ai-Min; Ouyang, Yu; Hu, Yan-Jun

2017-08-01

In this study, fluorescence spectroscopy and molecular modeling approaches were employed to investigate the binding of methotrexate to human serum albumin (HSA) under physiological conditions. From the mechanism, it was demonstrated that fluorescence quenching of HSA by methotrexate results from the formation of a methotrexate/HSA complex. Binding parameters calculated using the Stern-Volmer method and the Scatchard method showed that methotrexate binds to HSA with binding affinities in the order 10 4  L·mol -1 . Thermodynamic parameter studies revealed that the binding reaction is spontaneous, and that hydrogen bonds and van der Waals interactions play a major role in the reaction. Site marker competitive displacement experiments and a molecular modeling approach demonstrated that methotrexate binds with appropriate affinity to site I (subdomain IIA) of HSA. Furthermore, we discuss some factors that influence methotrexate binding to HSA. Copyright © 2017 John Wiley & Sons, Ltd.

Neural correlate of human reciprocity in social interactions

PubMed Central

Sakaiya, Shiro; Shiraito, Yuki; Kato, Junko; Ide, Hiroko; Okada, Kensuke; Takano, Kouji; Kansaku, Kenji

2013-01-01

Reciprocity plays a key role maintaining cooperation in society. However, little is known about the neural process that underpins human reciprocity during social interactions. Our neuroimaging study manipulated partner identity (computer, human) and strategy (random, tit-for-tat) in repeated prisoner's dilemma games and investigated the neural correlate of reciprocal interaction with humans. Reciprocal cooperation with humans but exploitation of computers by defection was associated with activation in the left amygdala. Amygdala activation was also positively and negatively correlated with a preference change for human partners following tit-for-tat and random strategies, respectively. The correlated activation represented the intensity of positive feeling toward reciprocal and negative feeling toward non-reciprocal partners, and so reflected reciprocity in social interaction. Reciprocity in social interaction, however, might plausibly be misinterpreted and so we also examined the neural coding of insight into the reciprocity of partners. Those with and without insight revealed differential brain activation across the reward-related circuitry (i.e., the right middle dorsolateral prefrontal cortex and dorsal caudate) and theory of mind (ToM) regions [i.e., ventromedial prefrontal cortex (VMPFC) and precuneus]. Among differential activations, activation in the precuneus, which accompanied deactivation of the VMPFC, was specific to those without insight into human partners who were engaged in a tit-for-tat strategy. This asymmetric (de)activation might involve specific contributions of ToM regions to the human search for reciprocity. Consequently, the intensity of emotion attached to human reciprocity was represented in the amygdala, whereas insight into the reciprocity of others was reflected in activation across the reward-related and ToM regions. This suggests the critical role of mentalizing, which was not equated with reward expectation during social interactions

Neural correlate of human reciprocity in social interactions.

PubMed

Sakaiya, Shiro; Shiraito, Yuki; Kato, Junko; Ide, Hiroko; Okada, Kensuke; Takano, Kouji; Kansaku, Kenji

2013-01-01

Reciprocity plays a key role maintaining cooperation in society. However, little is known about the neural process that underpins human reciprocity during social interactions. Our neuroimaging study manipulated partner identity (computer, human) and strategy (random, tit-for-tat) in repeated prisoner's dilemma games and investigated the neural correlate of reciprocal interaction with humans. Reciprocal cooperation with humans but exploitation of computers by defection was associated with activation in the left amygdala. Amygdala activation was also positively and negatively correlated with a preference change for human partners following tit-for-tat and random strategies, respectively. The correlated activation represented the intensity of positive feeling toward reciprocal and negative feeling toward non-reciprocal partners, and so reflected reciprocity in social interaction. Reciprocity in social interaction, however, might plausibly be misinterpreted and so we also examined the neural coding of insight into the reciprocity of partners. Those with and without insight revealed differential brain activation across the reward-related circuitry (i.e., the right middle dorsolateral prefrontal cortex and dorsal caudate) and theory of mind (ToM) regions [i.e., ventromedial prefrontal cortex (VMPFC) and precuneus]. Among differential activations, activation in the precuneus, which accompanied deactivation of the VMPFC, was specific to those without insight into human partners who were engaged in a tit-for-tat strategy. This asymmetric (de)activation might involve specific contributions of ToM regions to the human search for reciprocity. Consequently, the intensity of emotion attached to human reciprocity was represented in the amygdala, whereas insight into the reciprocity of others was reflected in activation across the reward-related and ToM regions. This suggests the critical role of mentalizing, which was not equated with reward expectation during social interactions.

A QCM-D study of the concentration- and time-dependent interactions of human LL37 with model mammalian lipid bilayers.

PubMed

Lozeau, Lindsay D; Rolle, Marsha W; Camesano, Terri A

2018-07-01

The human antimicrobial peptide LL37 is promising as an alternative to antibiotics due to its biophysical interactions with charged bacterial lipids. However, its clinical potential is limited due to its interactions with zwitterionic mammalian lipids leading to cytotoxicity. Mechanistic insight into the LL37 interactions with mammalian lipids may enable rational design of less toxic LL37-based therapeutics. To this end, we studied concentration- and time-dependent interactions of LL37 with zwitterionic model phosphatidylcholine (PC) bilayers with quartz crystal microbalance with dissipation (QCM-D). LL37 mass adsorption and PC bilayer viscoelasticity changes were monitored by measuring changes in frequency (Δf) and dissipation (ΔD), respectively. The Voigt-Kelvin viscoelastic model was applied to Δf and ΔD to study changes in bilayer thickness and density with LL37 concentration. At low concentrations (0.10-1.00 μM), LL37 adsorbed onto bilayers in a concentration-dependent manner. Further analyses of Δf, ΔD and thickness revealed that peptide saturation on the bilayers was a threshold for interactions observed above 2.00 μM, interactions that were rapid, multi-step, and reached equilibrium in a concentration- and time-dependent manner. Based on these data, we proposed a model of stable transmembrane pore formation at 2.00-10.0 μM, or transition from a primarily lipid to a primarily protein film with a transmembrane pore formation intermediate state at concentrations of LL37 > 10 μM. The concentration-dependent interactions between LL37 and PC bilayers correlated with the observed concentration-dependent biological activities of LL37 (antimicrobial, immunomodulatory and non-cytotoxic at 0.1-1.0 μM, hemolytic and some cytotoxicity at 2.0-13 μM and cytotoxic at >13 μM). Copyright © 2018 Elsevier B.V. All rights reserved.

A physical model of sensorimotor interactions during locomotion

NASA Astrophysics Data System (ADS)

Klein, Theresa J.; Lewis, M. Anthony

2012-08-01

In this paper, we describe the development of a bipedal robot that models the neuromuscular architecture of human walking. The body is based on principles derived from human muscular architecture, using muscles on straps to mimic agonist/antagonist muscle action as well as bifunctional muscles. Load sensors in the straps model Golgi tendon organs. The neural architecture is a central pattern generator (CPG) composed of a half-center oscillator combined with phase-modulated reflexes that is simulated using a spiking neural network. We show that the interaction between the reflex system, body dynamics and CPG results in a walking cycle that is entrained to the dynamics of the system. We also show that the CPG helped stabilize the gait against perturbations relative to a purely reflexive system, and compared the joint trajectories to human walking data. This robot represents a complete physical, or ‘neurorobotic’, model of the system, demonstrating the usefulness of this type of robotics research for investigating the neurophysiological processes underlying walking in humans and animals.

Human-Interaction Challenges in UAV-Based Autonomous Surveillance

NASA Technical Reports Server (NTRS)

Freed, Michael; Harris, Robert; Shafto, Michael G.

2004-01-01

Autonomous UAVs provide a platform for intelligent surveillance in application domains ranging from security and military operations to scientific information gathering and land management. Surveillance tasks are often long duration, requiring that any approach be adaptive to changes in the environment or user needs. We describe a decision- theoretic model of surveillance, appropriate for use on our autonomous helicopter, that provides a basis for optimizing the value of information returned by the UAV. From this approach arise a range of challenges in making this framework practical for use by human operators lacking specialized knowledge of autonomy and mathematics. This paper describes our platform and approach, then describes human-interaction challenges arising from this approach that we have identified and begun to address.

Computer modeling and simulation of human movement. Applications in sport and rehabilitation.

PubMed

Neptune, R R

2000-05-01

Computer modeling and simulation of human movement plays an increasingly important role in sport and rehabilitation, with applications ranging from sport equipment design to understanding pathologic gait. The complex dynamic interactions within the musculoskeletal and neuromuscular systems make analyzing human movement with existing experimental techniques difficult but computer modeling and simulation allows for the identification of these complex interactions and causal relationships between input and output variables. This article provides an overview of computer modeling and simulation and presents an example application in the field of rehabilitation.

Towards a Model of Human Resource Solutions for Achieving Intergenerational Interaction in Organisations

ERIC Educational Resources Information Center

McGuire, David; By, Rune Todnem; Hutchings, Kate

2007-01-01

Purpose: Achieving intergenerational interaction and avoiding conflict is becoming increasingly difficult in a workplace populated by three generations--Baby Boomers, Generation X-ers and Generation Y-ers. This paper presents a model and proposes HR solutions towards achieving co-operative generational interaction. Design/methodology/approach:…

A Physical Interaction Network of Dengue Virus and Human Proteins*

PubMed Central

Khadka, Sudip; Vangeloff, Abbey D.; Zhang, Chaoying; Siddavatam, Prasad; Heaton, Nicholas S.; Wang, Ling; Sengupta, Ranjan; Sahasrabudhe, Sudhir; Randall, Glenn; Gribskov, Michael; Kuhn, Richard J.; Perera, Rushika; LaCount, Douglas J.

2011-01-01

Dengue virus (DENV), an emerging mosquito-transmitted pathogen capable of causing severe disease in humans, interacts with host cell factors to create a more favorable environment for replication. However, few interactions between DENV and human proteins have been reported to date. To identify DENV-human protein interactions, we used high-throughput yeast two-hybrid assays to screen the 10 DENV proteins against a human liver activation domain library. From 45 DNA-binding domain clones containing either full-length viral genes or partially overlapping gene fragments, we identified 139 interactions between DENV and human proteins, the vast majority of which are novel. These interactions involved 105 human proteins, including six previously implicated in DENV infection and 45 linked to the replication of other viruses. Human proteins with functions related to the complement and coagulation cascade, the centrosome, and the cytoskeleton were enriched among the DENV interaction partners. To determine if the cellular proteins were required for DENV infection, we used small interfering RNAs to inhibit their expression. Six of 12 proteins targeted (CALR, DDX3X, ERC1, GOLGA2, TRIP11, and UBE2I) caused a significant decrease in the replication of a DENV replicon. We further showed that calreticulin colocalized with viral dsRNA and with the viral NS3 and NS5 proteins in DENV-infected cells, consistent with a direct role for calreticulin in DENV replication. Human proteins that interacted with DENV had significantly higher average degree and betweenness than expected by chance, which provides additional support for the hypothesis that viruses preferentially target cellular proteins that occupy central position in the human protein interaction network. This study provides a valuable starting point for additional investigations into the roles of human proteins in DENV infection. PMID:21911577

The interaction of 2-mercaptobenzimidazole with human serum albumin as determined by spectroscopy, atomic force microscopy and molecular modeling.

PubMed

Li, Yuqin; Jia, Baoxiu; Wang, Hao; Li, Nana; Chen, Gaopan; Lin, Yuejuan; Gao, Wenhua

2013-04-01

The interaction of 2-mercaptobenzimidazole (MBI) with human serum albumin (HSA) was studied in vitro by equilibrium dialysis under normal physiological conditions. This study used fluorescence, ultraviolet-visible spectroscopy (UV-vis), Fourier transform infrared (FT-IR), circular dichroism (CD) and Raman spectroscopy, atomic force microscopy (AFM) and molecular modeling techniques. Association constants, the number of binding sites and basic thermodynamic parameters were used to investigate the quenching mechanism. Based on the fluorescence resonance energy transfer, the distance between the HSA and MBI was 2.495 nm. The ΔG(0), ΔH(0), and ΔS(0) values across temperature indicated that the hydrophobic interaction was the predominant binding Force. The UV, FT-IR, CD and Raman spectra confirmed that the HSA secondary structure was altered in the presence of MBI. In addition, the molecular modeling showed that the MBI-HSA complex was stabilized by hydrophobic forces, which resulted from amino acid residues. The AFM results revealed that the individual HSA molecule dimensions were larger after interaction with MBI. Overall, this study suggested a method for characterizing the weak intermolecular interaction. In addition, this method is potentially useful for elucidating the toxigenicity of MBI when it is combined with the biomolecular function effect, transmembrane transport, toxicological testing and other experiments. Copyright © 2012 Elsevier B.V. All rights reserved.

A Perspective on Computational Human Performance Models as Design Tools

NASA Technical Reports Server (NTRS)

Jones, Patricia M.

2010-01-01

The design of interactive systems, including levels of automation, displays, and controls, is usually based on design guidelines and iterative empirical prototyping. A complementary approach is to use computational human performance models to evaluate designs. An integrated strategy of model-based and empirical test and evaluation activities is particularly attractive as a methodology for verification and validation of human-rated systems for commercial space. This talk will review several computational human performance modeling approaches and their applicability to design of display and control requirements.

Interactions Between Anandamide and Corticotropin-Releasing Factor Signaling Modulate Human Amygdala Function and Risk for Anxiety Disorders: An Imaging Genetics Strategy for Modeling Molecular Interactions.

PubMed

Demers, Catherine H; Drabant Conley, Emily; Bogdan, Ryan; Hariri, Ahmad R

2016-09-01

Preclinical models reveal that stress-induced amygdala activity and impairment in fear extinction reflect reductions in anandamide driven by corticotropin-releasing factor receptor type 1 (CRF1) potentiation of the anandamide catabolic enzyme fatty acid amide hydrolase. Here, we provide clinical translation for the importance of these molecular interactions using an imaging genetics strategy to examine whether interactions between genetic polymorphisms associated with differential anandamide (FAAH rs324420) and CRF1 (CRHR1 rs110402) signaling modulate amygdala function and anxiety disorder diagnosis. Analyses revealed that individuals with a genetic background predicting relatively high anandamide and CRF1 signaling exhibited blunted basolateral amygdala habituation, which further mediated increased risk for anxiety disorders among these same individuals. The convergence of preclinical and clinical data suggests that interactions between anandamide and CRF1 represent a fundamental molecular mechanism regulating amygdala function and anxiety. Our results further highlight the potential of imaging genetics to powerfully translate complex preclinical findings to clinically meaningful human phenotypes. Copyright © 2015 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

A Culture-Behavior-Brain Loop Model of Human Development.

PubMed

Han, Shihui; Ma, Yina

2015-11-01

Increasing evidence suggests that cultural influences on brain activity are associated with multiple cognitive and affective processes. These findings prompt an integrative framework to account for dynamic interactions between culture, behavior, and the brain. We put forward a culture-behavior-brain (CBB) loop model of human development that proposes that culture shapes the brain by contextualizing behavior, and the brain fits and modifies culture via behavioral influences. Genes provide a fundamental basis for, and interact with, the CBB loop at both individual and population levels. The CBB loop model advances our understanding of the dynamic relationships between culture, behavior, and the brain, which are crucial for human phylogeny and ontogeny. Future brain changes due to cultural influences are discussed based on the CBB loop model. Copyright © 2015 Elsevier Ltd. All rights reserved.

Role for protein–protein interaction databases in human genetics

PubMed Central

Pattin, Kristine A; Moore, Jason H

2010-01-01

Proteomics and the study of protein–protein interactions are becoming increasingly important in our effort to understand human diseases on a system-wide level. Thanks to the development and curation of protein-interaction databases, up-to-date information on these interaction networks is accessible and publicly available to the scientific community. As our knowledge of protein–protein interactions increases, it is important to give thought to the different ways that these resources can impact biomedical research. In this article, we highlight the importance of protein–protein interactions in human genetics and genetic epidemiology. Since protein–protein interactions demonstrate one of the strongest functional relationships between genes, combining genomic data with available proteomic data may provide us with a more in-depth understanding of common human diseases. In this review, we will discuss some of the fundamentals of protein interactions, the databases that are publicly available and how information from these databases can be used to facilitate genome-wide genetic studies. PMID:19929610

A Probabilistic Model of Social Working Memory for Information Retrieval in Social Interactions.

PubMed

Li, Liyuan; Xu, Qianli; Gan, Tian; Tan, Cheston; Lim, Joo-Hwee

2018-05-01

Social working memory (SWM) plays an important role in navigating social interactions. Inspired by studies in psychology, neuroscience, cognitive science, and machine learning, we propose a probabilistic model of SWM to mimic human social intelligence for personal information retrieval (IR) in social interactions. First, we establish a semantic hierarchy as social long-term memory to encode personal information. Next, we propose a semantic Bayesian network as the SWM, which integrates the cognitive functions of accessibility and self-regulation. One subgraphical model implements the accessibility function to learn the social consensus about IR-based on social information concept, clustering, social context, and similarity between persons. Beyond accessibility, one more layer is added to simulate the function of self-regulation to perform the personal adaptation to the consensus based on human personality. Two learning algorithms are proposed to train the probabilistic SWM model on a raw dataset of high uncertainty and incompleteness. One is an efficient learning algorithm of Newton's method, and the other is a genetic algorithm. Systematic evaluations show that the proposed SWM model is able to learn human social intelligence effectively and outperforms the baseline Bayesian cognitive model. Toward real-world applications, we implement our model on Google Glass as a wearable assistant for social interaction.

Formally verifying human–automation interaction as part of a system model: limitations and tradeoffs

PubMed Central

Bass, Ellen J.

2011-01-01

Both the human factors engineering (HFE) and formal methods communities are concerned with improving the design of safety-critical systems. This work discusses a modeling effort that leveraged methods from both fields to perform formal verification of human–automation interaction with a programmable device. This effort utilizes a system architecture composed of independent models of the human mission, human task behavior, human-device interface, device automation, and operational environment. The goals of this architecture were to allow HFE practitioners to perform formal verifications of realistic systems that depend on human–automation interaction in a reasonable amount of time using representative models, intuitive modeling constructs, and decoupled models of system components that could be easily changed to support multiple analyses. This framework was instantiated using a patient controlled analgesia pump in a two phased process where models in each phase were verified using a common set of specifications. The first phase focused on the mission, human-device interface, and device automation; and included a simple, unconstrained human task behavior model. The second phase replaced the unconstrained task model with one representing normative pump programming behavior. Because models produced in the first phase were too large for the model checker to verify, a number of model revisions were undertaken that affected the goals of the effort. While the use of human task behavior models in the second phase helped mitigate model complexity, verification time increased. Additional modeling tools and technological developments are necessary for model checking to become a more usable technique for HFE. PMID:21572930

Human-Computer Interaction in Smart Environments

PubMed Central

Paravati, Gianluca; Gatteschi, Valentina

2015-01-01

Here, we provide an overview of the content of the Special Issue on “Human-computer interaction in smart environments”. The aim of this Special Issue is to highlight technologies and solutions encompassing the use of mass-market sensors in current and emerging applications for interacting with Smart Environments. Selected papers address this topic by analyzing different interaction modalities, including hand/body gestures, face recognition, gaze/eye tracking, biosignal analysis, speech and activity recognition, and related issues.

A topological multilayer model of the human body.

PubMed

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

2015-11-04

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

Human interactions with sirenians (manatees and dugongs)

USGS Publications Warehouse

Bonde, Robert K.; Flint, Mark

2017-01-01

There are three extant sirenian species of the Trichechidae family and one living Dugongidae family member. Given their close ties to coastal and often urbanized habitats, sirenians are exposed to many types of anthropogenic activities that result in challenges to their well-being, poor health, and even death. In the wild, they are exposed to direct and indirect local pressures as well as subject to large-scale stressors such as global climate change acting on regions or entire genetic stocks. In captivity, they are subject to husbandry and management practices based on our collective knowledge, or in some cases lack thereof, of their needs and welfare. It is therefore reasonable to consider that their current imperiled status is very closely linked to our actions. In this chapter, we identify and define human interactions that may impact dugongs and manatees, including hunting, fisheries, boat interactions, negative interactions with man-made structures, disease and contaminants, and global climate change. We examine techniques used to investigate these impacts and the influence of sirenian biology and of changing human behaviors on potential outcomes. We examine how this differs for dugongs and manatees in the wild and for those held in captivity. Finally, we provide possible mitigation strategies and ways to assess the efforts we are making to improve the welfare of individuals and to conserve these species. This chapter identifies how the welfare of these species is intrinsically linked to the human interactions these animals experience, and how the nature of these interactions has changed with societal shifts. We proffer suggested ways to minimize negative impacts. Current knowledge should be used to minimize negative human interactions and impacts, to promote positive impacts, and to protect these animals for the future.

Acanthamoeba castellanii is not be an adequate model to study human adenovirus interactions with macrophagic cells

PubMed Central

Cateau, Estelle; Leveque, Nicolas; Kaaki, Sihem; Beby-Defaux, Agnès; Rodier, Marie-Hélène

2017-01-01

Free living amoebae (FLA) including Acanthamoeba castellanii, are protozoa that feed on different microorganisms including viruses. These microorganisms show remarkable similarities with macrophages in cellular structures, physiology or ability to phagocyte preys, and some authors have therefore wondered whether Acanthamoeba and macrophages are evolutionary related. It has been considered that this amoeba may be an in vitro model to investigate relationships between pathogens and macrophagic cells. So, we intended in this study to compare the interactions between a human adenovirus strain and A. castellanii or THP-1 macrophagic cells. The results of molecular and microscopy techniques following co-cultures experiments have shown that the presence of the adenovirus decreased the viability of macrophages, while it has no effect on amoebic viability. On another hand, the viral replication occurred only in macrophages. These results showed that this amoebal model is not relevant to explore the relationships between adenoviruses and macrophages in in vitro experiments. PMID:28591183

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

PubMed

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

2008-12-01

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

Visual exploration and analysis of human-robot interaction rules

NASA Astrophysics Data System (ADS)

Zhang, Hui; Boyles, Michael J.

2013-01-01

We present a novel interaction paradigm for the visual exploration, manipulation and analysis of human-robot interaction (HRI) rules; our development is implemented using a visual programming interface and exploits key techniques drawn from both information visualization and visual data mining to facilitate the interaction design and knowledge discovery process. HRI is often concerned with manipulations of multi-modal signals, events, and commands that form various kinds of interaction rules. Depicting, manipulating and sharing such design-level information is a compelling challenge. Furthermore, the closed loop between HRI programming and knowledge discovery from empirical data is a relatively long cycle. This, in turn, makes design-level verification nearly impossible to perform in an earlier phase. In our work, we exploit a drag-and-drop user interface and visual languages to support depicting responsive behaviors from social participants when they interact with their partners. For our principal test case of gaze-contingent HRI interfaces, this permits us to program and debug the robots' responsive behaviors through a graphical data-flow chart editor. We exploit additional program manipulation interfaces to provide still further improvement to our programming experience: by simulating the interaction dynamics between a human and a robot behavior model, we allow the researchers to generate, trace and study the perception-action dynamics with a social interaction simulation to verify and refine their designs. Finally, we extend our visual manipulation environment with a visual data-mining tool that allows the user to investigate interesting phenomena such as joint attention and sequential behavioral patterns from multiple multi-modal data streams. We have created instances of HRI interfaces to evaluate and refine our development paradigm. As far as we are aware, this paper reports the first program manipulation paradigm that integrates visual programming

Promoting Interactions Between Humans and Robots Using Robotic Emotional Behavior.

PubMed

Ficocelli, Maurizio; Terao, Junichi; Nejat, Goldie

2016-12-01

The objective of a socially assistive robot is to create a close and effective interaction with a human user for the purpose of giving assistance. In particular, the social interaction, guidance, and support that a socially assistive robot can provide a person can be very beneficial to patient-centered care. However, there are a number of research issues that need to be addressed in order to design such robots. This paper focuses on developing effective emotion-based assistive behavior for a socially assistive robot intended for natural human-robot interaction (HRI) scenarios with explicit social and assistive task functionalities. In particular, in this paper, a unique emotional behavior module is presented and implemented in a learning-based control architecture for assistive HRI. The module is utilized to determine the appropriate emotions of the robot to display, as motivated by the well-being of the person, during assistive task-driven interactions in order to elicit suitable actions from users to accomplish a given person-centered assistive task. A novel online updating technique is used in order to allow the emotional model to adapt to new people and scenarios. Experiments presented show the effectiveness of utilizing robotic emotional assistive behavior during HRI scenarios.

Towards Better Human Robot Interaction: Understand Human Computer Interaction in Social Gaming Using a Video-Enhanced Diary Method

NASA Astrophysics Data System (ADS)

See, Swee Lan; Tan, Mitchell; Looi, Qin En

This paper presents findings from a descriptive research on social gaming. A video-enhanced diary method was used to understand the user experience in social gaming. From this experiment, we found that natural human behavior and gamer’s decision making process can be elicited and speculated during human computer interaction. These are new information that we should consider as they can help us build better human computer interfaces and human robotic interfaces in future.

Enantiomeric metabolic interactions and stereoselective human methadone metabolism.

PubMed

Totah, Rheem A; Allen, Kyle E; Sheffels, Pamela; Whittington, Dale; Kharasch, Evan D

2007-04-01

Methadone is administered as a racemate, although opioid activity resides in the R-enantiomer. Methadone disposition is stereoselective, with considerable unexplained variability in clearance and plasma R/S ratios. N-Demethylation of methadone in vitro is predominantly mediated by cytochrome P450 CYP3A4 and CYP2B6 and somewhat by CYP2C19. This investigation evaluated stereoselectivity, models, and kinetic parameters for methadone N-demethylation by recombinant CYP2B6, CYP3A4, and CYP2C19, and the potential for interactions between enantiomers during racemate metabolism. CYP2B6 metabolism was stereoselective. CYP2C19 was less active, and stereoselectivity was opposite that for CYP2B6. CYP3A4 was not stereoselective. With all three isoforms, enantiomer N-dealkylation rates in the racemate were lower than those of (R)-(6-dimethyamino-4,4-diphenyl-heptan-3-one) hydrochloride (R-methadone) or (S)-(6-dimethyamino-4,4-diphenyl-heptan-3-one) hydrochloride (S-methadone) alone, suggesting an enantiomeric interaction and mutual metabolic inhibition. For CYP2B6, the interaction between enantiomers was stereoselective, with S-methadone as a more potent inhibitor of R-methadone N-demethylation than R-of S-methadone. In contrast, enantiomer interactions were not stereoselective with CYP2C19 or CYP3A4. For all three cytochromes P450, methadone N-demethylation was best described by two-site enzyme models with competitive inhibition. There were minor model differences between cytochromes P450 to account for stereoselectivity of metabolism and enantiomeric interactions. Changes in plasma R/S methadone ratios observed after rifampin or troleandomycin pretreatment in humans in vivo were successfully predicted by CYP2B6- but not CYP3A4-catalyzed methadone N-demethylation. CYP2B6 is a predominant catalyst of stereoselective methadone metabolism in vitro. In vivo, CYP2B6 may be a major determinant of methadone metabolism and disposition, and CYP2B6 activity and stereoselective metabolic

Human immune system mouse models of Ebola virus infection.

PubMed

Spengler, Jessica R; Prescott, Joseph; Feldmann, Heinz; Spiropoulou, Christina F

2017-08-01

Human immune system (HIS) mice, immunodeficient mice engrafted with human cells (with or without donor-matched tissue), offer a unique opportunity to study pathogens that cause disease predominantly or exclusively in humans. Several HIS mouse models have recently been used to study Ebola virus (EBOV) infection and disease. The results of these studies are encouraging and support further development and use of these models in Ebola research. HIS mice provide a small animal model to study EBOV isolates, investigate early viral interactions with human immune cells, screen vaccines and therapeutics that modulate the immune system, and investigate sequelae in survivors. Here we review existing models, discuss their use in pathogenesis studies and therapeutic screening, and highlight considerations for study design and analysis. Finally, we point out caveats to current models, and recommend future efforts for modeling EBOV infection in HIS mice. Published by Elsevier B.V.

Interaction of methotrexate with trypsin analyzed by spectroscopic and molecular modeling methods

NASA Astrophysics Data System (ADS)

Wang, Yanqing; Zhang, Hongmei; Cao, Jian; Zhou, Qiuhua

2013-11-01

Trypsin is one of important digestive enzymes that have intimate correlation with human health and illness. In this work, the interaction of trypsin with methotrexate was investigated by spectroscopic and molecular modeling methods. The results revealed that methotrexate could interact with trypsin with about one binding site. Methotrexate molecule could enter into the primary substrate-binding pocket, resulting in inhibition of trypsin activity. Furthermore, the thermodynamic analysis implied that electrostatic force, hydrogen bonding, van der Waals and hydrophobic interactions were the main interactions for stabilizing the trypsin-methotrexate system, which agreed well with the results from the molecular modeling study.

Trust and Trustworthiness in Human-Robot Interaction: A Formal Conceptualization

DTIC Science & Technology

2016-05-11

AFRL-AFOSR-VA-TR-2016-0198 Trust and Trustworthiness in Human- Robot Interaction: A formal conceptualization Alan Wagner GEORGIA TECH APPLIED RESEARCH...27/2013-03/31/2016 4. TITLE AND SUBTITLE Trust and Trustworthiness in Human- Robot Interaction: A formal conceptualization 5a. CONTRACT NUMBER 5b...evaluated algorithms for characterizing trust during interactions between a robot and a human and employed strategies for repairing trust during emergency

Interactions between human behaviour and ecological systems.

PubMed

Milner-Gulland, E J

2012-01-19

Research on the interactions between human behaviour and ecological systems tends to focus on the direct effects of human activities on ecosystems, such as biodiversity loss. There is also increasing research effort directed towards ecosystem services. However, interventions to control people's use of the environment alter the incentives that natural resource users face, and therefore their decisions about resource use. The indirect effects of conservation interventions on biodiversity, modulated through human decision-making, are poorly studied but are likely to be significant and potentially counterintuitive. This is particularly so where people are dependent on multiple natural resources for their livelihoods, when both poverty and biodiversity loss are acute. An inter-disciplinary approach is required to quantify these interactions, with an understanding of human decision-making at its core; otherwise, predictions about the impacts of conservation policies may be highly misleading.

Interactions between human behaviour and ecological systems

PubMed Central

Milner-Gulland, E. J.

2012-01-01

Research on the interactions between human behaviour and ecological systems tends to focus on the direct effects of human activities on ecosystems, such as biodiversity loss. There is also increasing research effort directed towards ecosystem services. However, interventions to control people's use of the environment alter the incentives that natural resource users face, and therefore their decisions about resource use. The indirect effects of conservation interventions on biodiversity, modulated through human decision-making, are poorly studied but are likely to be significant and potentially counterintuitive. This is particularly so where people are dependent on multiple natural resources for their livelihoods, when both poverty and biodiversity loss are acute. An inter-disciplinary approach is required to quantify these interactions, with an understanding of human decision-making at its core; otherwise, predictions about the impacts of conservation policies may be highly misleading. PMID:22144389

A Feature-Based Approach to Modeling Protein–DNA Interactions

PubMed Central

Segal, Eran

2008-01-01

Transcription factor (TF) binding to its DNA target site is a fundamental regulatory interaction. The most common model used to represent TF binding specificities is a position specific scoring matrix (PSSM), which assumes independence between binding positions. However, in many cases, this simplifying assumption does not hold. Here, we present feature motif models (FMMs), a novel probabilistic method for modeling TF–DNA interactions, based on log-linear models. Our approach uses sequence features to represent TF binding specificities, where each feature may span multiple positions. We develop the mathematical formulation of our model and devise an algorithm for learning its structural features from binding site data. We also developed a discriminative motif finder, which discovers de novo FMMs that are enriched in target sets of sequences compared to background sets. We evaluate our approach on synthetic data and on the widely used TF chromatin immunoprecipitation (ChIP) dataset of Harbison et al. We then apply our algorithm to high-throughput TF ChIP data from mouse and human, reveal sequence features that are present in the binding specificities of mouse and human TFs, and show that FMMs explain TF binding significantly better than PSSMs. Our FMM learning and motif finder software are available at http://genie.weizmann.ac.il/. PMID:18725950

Drivers' communicative interactions: on-road observations and modelling for integration in future automation systems.

PubMed

Portouli, Evangelia; Nathanael, Dimitris; Marmaras, Nicolas

2014-01-01

Social interactions with other road users are an essential component of the driving activity and may prove critical in view of future automation systems; still up to now they have received only limited attention in the scientific literature. In this paper, it is argued that drivers base their anticipations about the traffic scene to a large extent on observations of social behaviour of other 'animate human-vehicles'. It is further argued that in cases of uncertainty, drivers seek to establish a mutual situational awareness through deliberate communicative interactions. A linguistic model is proposed for modelling these communicative interactions. Empirical evidence from on-road observations and analysis of concurrent running commentary by 25 experienced drivers support the proposed model. It is suggested that the integration of a social interactions layer based on illocutionary acts in future driving support and automation systems will improve their performance towards matching human driver's expectations. Practitioner Summary: Interactions between drivers on the road may play a significant role in traffic coordination. On-road observations and running commentaries are presented as empirical evidence to support a model of such interactions; incorporation of drivers' interactions in future driving support and automation systems may improve their performance towards matching driver's expectations.

Probing Cocaine-Antibody Interactions in Buffer and Human Serum

PubMed Central

Ramakrishnan, Muthu; Alves De Melo, Fernando; Kinsey, Berma M.; Ladbury, John E.; Kosten, Thomas R.; Orson, Frank M.

2012-01-01

Background Despite progress in cocaine immunotherapy, the kinetic and thermodynamic properties of antibodies which bind to cocaine and its metabolites are not well understood. It is also not clear how the interactions between them differ in a complex matrix such as the serum present in the human body. In the present study, we have used microscale thermophoresis (MST), isothermal titration calorimetry (ITC), and surface plasmon resonance (SPR) we have evaluated the affinity properties of a representative mouse monoclonal (mAb08) as well as those of polyclonal antibodies purified from vaccinated mouse and human patient serum. Results MST analysis of fluorescently tagged mAb08 binding to cocaine reveals an approximately 15 fold decrease in its equilibrium dissociation constant in 20–50% human serum compared with that in saline buffer. A similar trend was also found using enriched polyclonal antibodies purified from vaccinated mice and patient serum, for which we have used fluorescently tagged bovine serum albumin conjugated to succinyl norcocaine (BSA-SNC). This conjugate closely mimics both cocaine and the hapten used to raise these antibodies. The ITC data also revealed that cocaine has a moderate affinity of about 2 µM to 20% human serum and very little interaction with human serum albumin or nonspecific human IgG at that concentration range. In a SPR inhibition experiment, the binding of mAb08 to immobilized BSA-SNC was inhibited by cocaine and benzoylecgonine in a highly competitive manner, whereas the purified polyclonal antibodies from vaccinated humans and mice, revealed preferential selectivity to pharmacologically active cocaine but not to the inactive metabolite benzoylecgonine. We have also developed a simple binding model to simulate the challenges associated with cocaine immunotherapy using the variable quantitative and kinetic properties of the antibodies. Conclusions High sensitivity calorimetric determination of antibody binding to cocaine and its

Dynamic interfacial properties of human tear-lipid films and their interactions with model-tear proteins in vitro.

PubMed

Svitova, Tatyana F; Lin, Meng C

2016-07-01

This review summarizes the current state of knowledge regarding interfacial properties of very complex biological colloids, specifically, human meibum and tear lipids, and their interactions with proteins similar to the proteins found in aqueous part of human tears. Tear lipids spread as thin films over the surface of tear-film aqueous and play crucial roles in tear-film stability and overall ocular-surface health. The vast majority of papers published to date report interfacial properties of meibum-lipid monolayers spread on various aqueous sub-phases, often containing model proteins, in Langmuir trough. However, it is well established that natural human ocular tear lipids exist as multilayered films with a thickness between 30 and 100nm, that is very much disparate from 1 to 2nm thick meibum monolayers. We employed sessile-bubble tensiometry to study the dynamic interfacial and rheological properties of reconstituted multilayered human tear-lipid films. Small amounts (0.5-1μg) of human tear lipids were deposited on an air-bubble surface to produce tear-lipid films in thickness range 30-100nm corresponding to ocular lipid films. Thus, we were able to overcome major Langmuir-trough method limitations because ocular tear lipids can be safely harvested only in minute, sub-milligram quantities, insufficient for Langmuir through studies. Sessile-bubble method is demonstrated to be a versatile tool for assessing conventional synthetic surfactants adsorption/desorption dynamics at an air-aqueous solution interface. (Svitova T., Weatherbee M., Radke C.J. Dynamics of surfactant sorption at the air/water interface: continuous-flow tensiometry. J. Colloid Interf. Sci. 2003;261:1170-179). The augmented flow-sessile-bubble setup, with step-strain relaxation module for dynamic interfacial rheological properties and high-precision syringe pump to generate larger and slow interfacial area expansions-contractions, was developed and employed in our studies. We established that

Kinetic Models for Topological Nearest-Neighbor Interactions

NASA Astrophysics Data System (ADS)

Blanchet, Adrien; Degond, Pierre

2017-12-01

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

A protein isolated from human oviductal tissue in vitro secretion, identified as human lactoferrin, interacts with spermatozoa and oocytes and modulates gamete interaction.

PubMed

Zumoffen, C M; Gil, R; Caille, A M; Morente, C; Munuce, M J; Ghersevich, S A

2013-05-01

reaction was assessed with Pisum sativum agglutinin conjugated with rhodamine. The effect of increasing concentrations of LF (0.1-100 µg/ml) on gamete interaction was evaluated by a sperm-ZP binding assay, using human oocytes donated by women undergoing IVF procedures. A protein isolated by the affinity column was identified as human LF. LF was immunolocalized in human oviductal tissue and detected in oviductal fluid and oviduct epithelial cell homogenates. In the latter case, LF expression was highest at the periovulatory phase of the menstrual cycle (P < 0.01). Different LF binding patterns were observed on spermatozoa depending upon capacitation stage and if the acrosome reaction had occurred. Unstained sperm were most prevalent before capacitation, but after incubation for 6 h under capacitating conditions and in acrosome-reacted sperm LF binding was observed, mainly localized in the equatorial segment and post-acrosomal region of the sperm head. LF binding studies on ZP showed homogenous staining. LF caused a dose-dependent significant inhibition of sperm-ZP interaction, and the effect was already significant (P < 0.01) with the lowest LF concentration used. This study has investigated the effect of LF only on human gamete interaction in vitro and thus has some limitations. Further investigations of the potential mechanisms involved in LF action both on gamete function in vitro and in vivo in animal models are needed to confirm the role of this protein in the reproductive process. The present data indicate that human oviductal LF expression is cycle dependent and inhibited gamete interaction in vitro. No previous data were available about potential direct effects of LF on gamete interaction. It could be thought that the protein is involved in the regulation of the reproductive process, perhaps contributing to prevent polyspermy. Thus, further research is needed to clarify the potential role of LF in the regulation of the fertilization process. This study was

Modeling RNA polymerase interaction in mitochondria of chordates

PubMed Central

2012-01-01

Background In previous work, we introduced a concept, a mathematical model and its computer realization that describe the interaction between bacterial and phage type RNA polymerases, protein factors, DNA and RNA secondary structures during transcription, including transcription initiation and termination. The model accurately reproduces changes of gene transcription level observed in polymerase sigma-subunit knockout and heat shock experiments in plant plastids. The corresponding computer program and a user guide are available at http://lab6.iitp.ru/en/rivals. Here we apply the model to the analysis of transcription and (partially) translation processes in the mitochondria of frog, rat and human. Notably, mitochondria possess only phage-type polymerases. We consider the entire mitochondrial genome so that our model allows RNA polymerases to complete more than one circle on the DNA strand. Results Our model of RNA polymerase interaction during transcription initiation and elongation accurately reproduces experimental data obtained for plastids. Moreover, it also reproduces evidence on bulk RNA concentrations and RNA half-lives in the mitochondria of frog, human with or without the MELAS mutation, and rat with normal (euthyroid) or hyposecretion of thyroid hormone (hypothyroid). The transcription characteristics predicted by the model include: (i) the fraction of polymerases terminating at a protein-dependent terminator in both directions (the terminator polarization), (ii) the binding intensities of the regulatory protein factor (mTERF) with the termination site and, (iii) the transcription initiation intensities (initiation frequencies) of all promoters in all five conditions (frog, healthy human, human with MELAS syndrome, healthy rat, and hypothyroid rat with aberrant mtDNA methylation). Using the model, absolute levels of all gene transcription can be inferred from an arbitrary array of the three transcription characteristics, whereas, for selected genes only

Metazoa Ludens: Mixed Reality Interaction and Play Between Humans and Animals

NASA Astrophysics Data System (ADS)

Cheok, Adrian David

Although animals and pets are so important for families and society, in modern urban lifestyles we can spend little time with our animal friends. Interactive media should be aimed to enhance not only human-to-human communication, but also human-to-animal communication. Thus, we promote a new type of inter-species media interaction which allows human users to interact and play with their small pet friends (in this case hamsters) remotely via the Internet through a mixed reality based game system “Metazoa Ludens”. We scientifically examined the effectiveness of this system in a two-pronged approach. Firstly and most importantly, the positive effects to the hamsters were ensured using Body Condition Score study. Secondly, the method of Duncan was used to assess the strength of preference of the hamsters towards Metazoa Ludens. Lastly, the effectiveness of this remote interaction with respect to the human users as a interactive gaming system with their pets/friends (hamsters) was examined based on Csikszentmihalyi's (Beyond boredom and anxiety, 1975) Flow theory. The results of both studies inform of positive remote interaction between human users and their pet friends using our research system. This research is not aimed just at providing specific experimental results on the implemented research system, but is aimed as a wider lesson for human-to-animal interactive media. Thus also the lessons learned are extrapolated and detailed in this chapter as a framework in general for human-to-animal interaction systems.

Mouse Models for Investigating the Developmental Bases of Human Birth Defects

PubMed Central

MOON, ANNE M.

2006-01-01

Clinicians and basic scientists share an interest in discovering how genetic or environmental factors interact to perturb normal development and cause birth defects and human disease. Given the complexity of such interactions, it is not surprising that 4% of human infants are born with a congenital malformation, and cardiovascular defects occur in nearly 1%. Our research is based on the fundamental hypothesis that an understanding of normal and abnormal development will permit us to generate effective strategies for both prevention and treatment of human birth defects. Animal models are invaluable in these efforts because they allow one to interrogate the genetic, molecular and cellular events that distinguish normal from abnormal development. Several features of the mouse make it a particularly powerful experimental model: it is a mammalian system with similar embryology, anatomy and physiology to humans; genes, proteins and regulatory programs are largely conserved between human and mouse; and finally, gene targeting in murine embryonic stem cells has made the mouse genome amenable to sophisticated genetic manipulation currently unavailable in any other model organism. PMID:16641221

Dynamic Human Body Modeling Using a Single RGB Camera.

PubMed

Zhu, Haiyu; Yu, Yao; Zhou, Yu; Du, Sidan

2016-03-18

In this paper, we present a novel automatic pipeline to build personalized parametric models of dynamic people using a single RGB camera. Compared to previous approaches that use monocular RGB images, our system can model a 3D human body automatically and incrementally, taking advantage of human motion. Based on coarse 2D and 3D poses estimated from image sequences, we first perform a kinematic classification of human body parts to refine the poses and obtain reconstructed body parts. Next, a personalized parametric human model is generated by driving a general template to fit the body parts and calculating the non-rigid deformation. Experimental results show that our shape estimation method achieves comparable accuracy with reconstructed models using depth cameras, yet requires neither user interaction nor any dedicated devices, leading to the feasibility of using this method on widely available smart phones.

From Network Analysis to Functional Metabolic Modeling of the Human Gut Microbiota.

PubMed

Bauer, Eugen; Thiele, Ines

2018-01-01

An important hallmark of the human gut microbiota is its species diversity and complexity. Various diseases have been associated with a decreased diversity leading to reduced metabolic functionalities. Common approaches to investigate the human microbiota include high-throughput sequencing with subsequent correlative analyses. However, to understand the ecology of the human gut microbiota and consequently design novel treatments for diseases, it is important to represent the different interactions between microbes with their associated metabolites. Computational systems biology approaches can give further mechanistic insights by constructing data- or knowledge-driven networks that represent microbe interactions. In this minireview, we will discuss current approaches in systems biology to analyze the human gut microbiota, with a particular focus on constraint-based modeling. We will discuss various community modeling techniques with their advantages and differences, as well as their application to predict the metabolic mechanisms of intestinal microbial communities. Finally, we will discuss future perspectives and current challenges of simulating realistic and comprehensive models of the human gut microbiota.

Neuro-immune interactions of neural stem cell transplants: From animal disease models to human trials

PubMed Central

Cossetti, Chiara; Pluchino, Stefano

2014-01-01

Stem cell technology is a promising branch of regenerative medicine that is aimed at developing new approaches for the treatment of severely debilitating human diseases, including those affecting the central nervous system (CNS). Despite the increasing understanding of the mechanisms governing their biology, the application of stem cell therapeutics remains challenging. The initial idea that stem cell transplants work in vivo via the replacement of endogenous cells lost or damaged owing to disease has been challenged by accumulating evidence of their therapeutic plasticity. This new concept covers the remarkable immune regulatory and tissue trophic effects that transplanted stem cells exert at the level of the neural microenvironment to promote tissue healing via combination of immune modulatory and tissue protective actions, while retaining predominantly undifferentiated features. Among a number of promising candidate stem cell sources, neural stem/precursor cells (NPCs) are under extensive investigation with regard to their therapeutic plasticity after transplantation. The significant impact in vivo of experimental NPC therapies in animal models of inflammatory CNS diseases has raised great expectations that these stem cells, or the manipulation of the mechanisms behind their therapeutic impact, could soon be translated to human studies. This review aims to provide an update on the most recent evidence of therapeutically-relevant neuroimmune interactions following NPC transplants in animal models of multiple sclerosis, cerebral stroke and traumas of the spinal cord, and consideration of the forthcoming challenges related to the early translation of some of these exciting experimental outcomes into clinical medicines. PMID:23507035

Neuro-immune interactions of neural stem cell transplants: from animal disease models to human trials.

PubMed

Giusto, Elena; Donegà, Matteo; Cossetti, Chiara; Pluchino, Stefano

2014-10-01

Stem cell technology is a promising branch of regenerative medicine that is aimed at developing new approaches for the treatment of severely debilitating human diseases, including those affecting the central nervous system (CNS). Despite the increasing understanding of the mechanisms governing their biology, the application of stem cell therapeutics remains challenging. The initial idea that stem cell transplants work in vivo via the replacement of endogenous cells lost or damaged owing to disease has been challenged by accumulating evidence of their therapeutic plasticity. This new concept covers the remarkable immune regulatory and tissue trophic effects that transplanted stem cells exert at the level of the neural microenvironment to promote tissue healing via combination of immune modulatory and tissue protective actions, while retaining predominantly undifferentiated features. Among a number of promising candidate stem cell sources, neural stem/precursor cells (NPCs) are under extensive investigation with regard to their therapeutic plasticity after transplantation. The significant impact in vivo of experimental NPC therapies in animal models of inflammatory CNS diseases has raised great expectations that these stem cells, or the manipulation of the mechanisms behind their therapeutic impact, could soon be translated to human studies. This review aims to provide an update on the most recent evidence of therapeutically-relevant neuro-immune interactions following NPC transplants in animal models of multiple sclerosis, cerebral stroke and traumas of the spinal cord, and consideration of the forthcoming challenges related to the early translation of some of these exciting experimental outcomes into clinical medicines. Copyright © 2013 Elsevier Inc. All rights reserved.

Eye Tracking Based Control System for Natural Human-Computer Interaction

PubMed Central

Lin, Shu-Fan

2017-01-01

Eye movement can be regarded as a pivotal real-time input medium for human-computer communication, which is especially important for people with physical disability. In order to improve the reliability, mobility, and usability of eye tracking technique in user-computer dialogue, a novel eye control system with integrating both mouse and keyboard functions is proposed in this paper. The proposed system focuses on providing a simple and convenient interactive mode by only using user's eye. The usage flow of the proposed system is designed to perfectly follow human natural habits. Additionally, a magnifier module is proposed to allow the accurate operation. In the experiment, two interactive tasks with different difficulty (searching article and browsing multimedia web) were done to compare the proposed eye control tool with an existing system. The Technology Acceptance Model (TAM) measures are used to evaluate the perceived effectiveness of our system. It is demonstrated that the proposed system is very effective with regard to usability and interface design. PMID:29403528

Eye Tracking Based Control System for Natural Human-Computer Interaction.

PubMed

Zhang, Xuebai; Liu, Xiaolong; Yuan, Shyan-Ming; Lin, Shu-Fan

2017-01-01

Eye movement can be regarded as a pivotal real-time input medium for human-computer communication, which is especially important for people with physical disability. In order to improve the reliability, mobility, and usability of eye tracking technique in user-computer dialogue, a novel eye control system with integrating both mouse and keyboard functions is proposed in this paper. The proposed system focuses on providing a simple and convenient interactive mode by only using user's eye. The usage flow of the proposed system is designed to perfectly follow human natural habits. Additionally, a magnifier module is proposed to allow the accurate operation. In the experiment, two interactive tasks with different difficulty (searching article and browsing multimedia web) were done to compare the proposed eye control tool with an existing system. The Technology Acceptance Model (TAM) measures are used to evaluate the perceived effectiveness of our system. It is demonstrated that the proposed system is very effective with regard to usability and interface design.

Advancing coupled human-earth system models: The integrated Earth System Model Project

NASA Astrophysics Data System (ADS)

Thomson, A. M.; Edmonds, J. A.; Collins, W.; Thornton, P. E.; Hurtt, G. C.; Janetos, A. C.; Jones, A.; Mao, J.; Chini, L. P.; Calvin, K. V.; Bond-Lamberty, B. P.; Shi, X.

2012-12-01

As human and biogeophysical models develop, opportunities for connections between them evolve and can be used to advance our understanding of human-earth systems interaction in the context of a changing climate. One such integration is taking place with the Community Earth System Model (CESM) and the Global Change Assessment Model (GCAM). A multi-disciplinary, multi-institution team has succeeded in integrating the GCAM integrated assessment model of human activity into CESM to dynamically represent the feedbacks between changing climate and human decision making, in the context of greenhouse gas mitigation policies. The first applications of this capability have focused on the feedbacks between climate change impacts on terrestrial ecosystem productivity and human decisions affecting future land use change, which are in turn connected to human decisions about energy systems and bioenergy production. These experiments have been conducted in the context of the RCP4.5 scenario, one of four pathways of future radiative forcing being used in CMIP5, which constrains future human-induced greenhouse gas emissions from energy and land activities to stabilize radiative forcing at 4.5 W/m2 (~650 ppm CO2 -eq) by 2100. When this pathway is run in GCAM with the climate feedback on terrestrial productivity from CESM, there are implications for both the land use and energy system changes required for stabilization. Early findings indicate that traditional definitions of radiative forcing used in scenario development are missing a critical component of the biogeophysical consequences of land use change and their contribution to effective radiative forcing. Initial full coupling of the two global models has important implications for how climate impacts on terrestrial ecosystems changes the dynamics of future land use change for agriculture and forestry, particularly in the context of a climate mitigation policy designed to reduce emissions from land use as well as energy systems

Using hydraulic modeling to simulate human interactions with water resources in an Omani irrigation system

NASA Astrophysics Data System (ADS)

Xanthopoulou, Themis; Ertsen, Maurits; Düring, Bleda; Kolen, Jan

2017-04-01

In the dry Southern Oman, more than a thousand years ago, a large water system that connected the mountain mass with the coastal region was constructed. Its length (up to 30 km) and the fact that the coastal region has a rich groundwater aquifer create confusion as to why the system was initially built. Nonetheless, it was abandoned a couple of centuries later only to be partially revived by small farming communities in the 17th to 18th century. The focus of our research is one of the irrigation systems that used the water conveyed from the large water system. Not much is known about these small irrigation systems functioning in the Wadi Al Jizzi of the greater Sohar region. There are no written records and we can only make guesses about the way the systems were managed based on ethnographical studies and the traditional Omani techniques. On the other hand, the good preservation state of the canals offers a great opportunity for hydraulic reconstruction of irrigation events. More than that, the material remains suggest and at the same time limit the ways in which humans interacted with the system and the water resources of the region. All irrigation activities and some daily activities had to be realized through the canal system and only if the canal system permits it these actions would have been feasible. We created a conceptual model of irrigation that includes the human agent and feedback mechanisms through hydraulics and then we simulated irrigation events using the Sobek software. Scenarios and sensibility analysis were used to address the unknown aspects of the system. Our research yielded insights about the way the farming community interacted with the larger water system, the levels of co-ordination and co-operation required for successful irrigation and the predisposition of conflict and power relations.

Characterizing the interaction among bullet, body armor, and human and surrogate targets.

PubMed

Shen, Weixin; Niu, Yuqing; Bykanova, Lucy; Laurence, Peter; Link, Norman

2010-12-01

This study used a combined experimental and modeling approach to characterize and quantify the interaction among bullet, body armor, and human surrogate targets during the 10-1000 μs range that is crucial to evaluating the protective effectiveness of body armor against blunt injuries. Ballistic tests incorporating high-speed flash X-ray measurements were performed to acquire the deformations of bullets and body armor samples placed against ballistic clay and gelatin targets with images taken between 10 μs and 1 ms of the initial impact. Finite element models (FEMs) of bullet, armor, and gelatin and clay targets were developed with material parameters selected to best fit model calculations to the test measurements. FEMs of bullet and armor interactions were then assembled with a FEM of a human torso and FEMs of clay and gelatin blocks in the shape of a human torso to examine the effects of target material and geometry on the interaction. Test and simulation results revealed three distinct loading phases during the interaction. In the first phase, the bullet was significantly slowed in about 60 μs as it transferred a major portion of its energy into the body armor. In the second phase, fibers inside the armor were pulled toward the point of impact and kept on absorbing energy until about 100 μs after the initial impact when energy absorption reached its peak. In the third phase, the deformation on the armor's back face continued to grow and energies inside both armor and targets redistributed through wave propagation. The results indicated that armor deformation and energy absorption in the second and third phases were significantly affected by the material properties (density and stiffness) and geometrical characteristics (curvature and gap at the armor-target interface) of the targets. Valid surrogate targets for testing the ballistic resistance of the armor need to account for these factors and produce the same armor deformation and energy absorption as on a

Advances and perspectives in in vitro human gut fermentation modeling.

PubMed

Payne, Amanda N; Zihler, Annina; Chassard, Christophe; Lacroix, Christophe

2012-01-01

The gut microbiota is a highly specialized organ containing host-specific assemblages of microbes whereby metabolic activity directly impacts human health and disease. In vitro gut fermentation models present an unmatched opportunity of performing studies frequently challenged in humans and animals owing to ethical concerns. Multidisciplinary systems biology analyses supported by '-omics' platforms remain widely neglected in the field of in vitro gut fermentation modeling but are key to advancing the significance of these models. Model-driven experimentation using a combination of in vitro gut fermentation and in vitro human cell models represent an advanced approach in identifying complex host-microbe interactions and niches central to gut fermentation processes. The aim of this review is to highlight the advances and challenges exhibited by in vitro human gut fermentation modeling. Copyright © 2011 Elsevier Ltd. All rights reserved.

From 'automation' to 'autonomy': the importance of trust repair in human-machine interaction.

PubMed

de Visser, Ewart J; Pak, Richard; Shaw, Tyler H

2018-04-09

Modern interactions with technology are increasingly moving away from simple human use of computers as tools to the establishment of human relationships with autonomous entities that carry out actions on our behalf. In a recent commentary, Peter Hancock issued a stark warning to the field of human factors that attention must be focused on the appropriate design of a new class of technology: highly autonomous systems. In this article, we heed the warning and propose a human-centred approach directly aimed at ensuring that future human-autonomy interactions remain focused on the user's needs and preferences. By adapting literature from industrial psychology, we propose a framework to infuse a unique human-like ability, building and actively repairing trust, into autonomous systems. We conclude by proposing a model to guide the design of future autonomy and a research agenda to explore current challenges in repairing trust between humans and autonomous systems. Practitioner Summary: This paper is a call to practitioners to re-cast our connection to technology as akin to a relationship between two humans rather than between a human and their tools. To that end, designing autonomy with trust repair abilities will ensure future technology maintains and repairs relationships with their human partners.

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

PubMed Central

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

2015-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Yeast Phenomics: An Experimental Approach for Modeling Gene Interaction Networks that Buffer Disease

PubMed Central

Hartman, John L.; Stisher, Chandler; Outlaw, Darryl A.; Guo, Jingyu; Shah, Najaf A.; Tian, Dehua; Santos, Sean M.; Rodgers, John W.; White, Richard A.

2015-01-01

The genome project increased appreciation of genetic complexity underlying disease phenotypes: many genes contribute each phenotype and each gene contributes multiple phenotypes. The aspiration of predicting common disease in individuals has evolved from seeking primary loci to marginal risk assignments based on many genes. Genetic interaction, defined as contributions to a phenotype that are dependent upon particular digenic allele combinations, could improve prediction of phenotype from complex genotype, but it is difficult to study in human populations. High throughput, systematic analysis of S. cerevisiae gene knockouts or knockdowns in the context of disease-relevant phenotypic perturbations provides a tractable experimental approach to derive gene interaction networks, in order to deduce by cross-species gene homology how phenotype is buffered against disease-risk genotypes. Yeast gene interaction network analysis to date has revealed biology more complex than previously imagined. This has motivated the development of more powerful yeast cell array phenotyping methods to globally model the role of gene interaction networks in modulating phenotypes (which we call yeast phenomic analysis). The article illustrates yeast phenomic technology, which is applied here to quantify gene X media interaction at higher resolution and supports use of a human-like media for future applications of yeast phenomics for modeling human disease. PMID:25668739

Compliance control based on PSO algorithm to improve the feeling during physical human-robot interaction.

PubMed

Jiang, Zhongliang; Sun, Yu; Gao, Peng; Hu, Ying; Zhang, Jianwei

2016-01-01

Robots play more important roles in daily life and bring us a lot of convenience. But when people work with robots, there remain some significant differences in human-human interactions and human-robot interaction. It is our goal to make robots look even more human-like. We design a controller which can sense the force acting on any point of a robot and ensure the robot can move according to the force. First, a spring-mass-dashpot system was used to describe the physical model, and the second-order system is the kernel of the controller. Then, we can establish the state space equations of the system. In addition, the particle swarm optimization algorithm had been used to obtain the system parameters. In order to test the stability of system, the root-locus diagram had been shown in the paper. Ultimately, some experiments had been carried out on the robotic spinal surgery system, which is developed by our team, and the result shows that the new controller performs better during human-robot interaction.

Physical Forces between Humans and How Humans Attract and Repel Each Other Based on Their Social Interactions in an Online World

PubMed Central

Thurner, Stefan; Fuchs, Benedikt

2015-01-01

Physical interactions between particles are the result of the exchange of gauge bosons. Human interactions are mediated by the exchange of messages, goods, money, promises, hostilities, etc. While in the physical world interactions and their associated forces have immediate dynamical consequences (Newton’s laws) the situation is not clear for human interactions. Here we quantify the relative acceleration between humans who interact through the exchange of messages, goods and hostilities in a massive multiplayer online game. For this game we have complete information about all interactions (exchange events) between about 430,000 players, and about their trajectories (movements) in the metric space of the game universe at any point in time. We use this information to derive “interaction potentials" for communication, trade and attacks and show that they are harmonic in nature. Individuals who exchange messages and trade goods generally attract each other and start to separate immediately after exchange events end. The form of the interaction potential for attacks mirrors the usual “hit-and-run" tactics of aggressive players. By measuring interaction intensities as a function of distance, velocity and acceleration, we show that “forces" between players are directly related to the number of exchange events. We find an approximate power-law decay of the likelihood for interactions as a function of distance, which is in accordance with previous real world empirical work. We show that the obtained potentials can be understood with a simple model assuming an exchange-driven force in combination with a distance-dependent exchange rate. PMID:26196505

Physical Forces between Humans and How Humans Attract and Repel Each Other Based on Their Social Interactions in an Online World.

PubMed

Thurner, Stefan; Fuchs, Benedikt

2015-01-01

Physical interactions between particles are the result of the exchange of gauge bosons. Human interactions are mediated by the exchange of messages, goods, money, promises, hostilities, etc. While in the physical world interactions and their associated forces have immediate dynamical consequences (Newton's laws) the situation is not clear for human interactions. Here we quantify the relative acceleration between humans who interact through the exchange of messages, goods and hostilities in a massive multiplayer online game. For this game we have complete information about all interactions (exchange events) between about 430,000 players, and about their trajectories (movements) in the metric space of the game universe at any point in time. We use this information to derive "interaction potentials" for communication, trade and attacks and show that they are harmonic in nature. Individuals who exchange messages and trade goods generally attract each other and start to separate immediately after exchange events end. The form of the interaction potential for attacks mirrors the usual "hit-and-run" tactics of aggressive players. By measuring interaction intensities as a function of distance, velocity and acceleration, we show that "forces" between players are directly related to the number of exchange events. We find an approximate power-law decay of the likelihood for interactions as a function of distance, which is in accordance with previous real world empirical work. We show that the obtained potentials can be understood with a simple model assuming an exchange-driven force in combination with a distance-dependent exchange rate.

Dynamic Human Body Modeling Using a Single RGB Camera

PubMed Central

Zhu, Haiyu; Yu, Yao; Zhou, Yu; Du, Sidan

2016-01-01

In this paper, we present a novel automatic pipeline to build personalized parametric models of dynamic people using a single RGB camera. Compared to previous approaches that use monocular RGB images, our system can model a 3D human body automatically and incrementally, taking advantage of human motion. Based on coarse 2D and 3D poses estimated from image sequences, we first perform a kinematic classification of human body parts to refine the poses and obtain reconstructed body parts. Next, a personalized parametric human model is generated by driving a general template to fit the body parts and calculating the non-rigid deformation. Experimental results show that our shape estimation method achieves comparable accuracy with reconstructed models using depth cameras, yet requires neither user interaction nor any dedicated devices, leading to the feasibility of using this method on widely available smart phones. PMID:26999159

Holistic Modeling for Human-Autonomous System Interaction

DTIC Science & Technology

2015-01-01

piloting ...2012).  18X   Pilots  Learn  RPAs  First.      Retrieved  April  7,  2013,  from   http://www.holloman.af.mil/news/story.asp...human  processor  (QN-­‐ MHP):  a  computational  architecture  for   multitask  performance  in  human-­‐machine  

Modeling human behaviors and reactions under dangerous environment.

PubMed

Kang, J; Wright, D K; Qin, S F; Zhao, Y

2005-01-01

This paper describes the framework of a real-time simulation system to model human behavior and reactions in dangerous environments. The system utilizes the latest 3D computer animation techniques, combined with artificial intelligence, robotics and psychology, to model human behavior, reactions and decision making under expected/unexpected dangers in real-time in virtual environments. The development of the system includes: classification on the conscious/subconscious behaviors and reactions of different people; capturing different motion postures by the Eagle Digital System; establishing 3D character animation models; establishing 3D models for the scene; planning the scenario and the contents; and programming within Virtools Dev. Programming within Virtools Dev is subdivided into modeling dangerous events, modeling character's perceptions, modeling character's decision making, modeling character's movements, modeling character's interaction with environment and setting up the virtual cameras. The real-time simulation of human reactions in hazardous environments is invaluable in military defense, fire escape, rescue operation planning, traffic safety studies, and safety planning in chemical factories, the design of buildings, airplanes, ships and trains. Currently, human motion modeling can be realized through established technology, whereas to integrate perception and intelligence into virtual human's motion is still a huge undertaking. The challenges here are the synchronization of motion and intelligence, the accurate modeling of human's vision, smell, touch and hearing, the diversity and effects of emotion and personality in decision making. There are three types of software platforms which could be employed to realize the motion and intelligence within one system, and their advantages and disadvantages are discussed.

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

PubMed

Endert, A; Fiaux, P; North, C

2012-12-01

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

Human agency beliefs influence behaviour during virtual social interactions.

PubMed

Caruana, Nathan; Spirou, Dean; Brock, Jon

2017-01-01

In recent years, with the emergence of relatively inexpensive and accessible virtual reality technologies, it is now possible to deliver compelling and realistic simulations of human-to-human interaction. Neuroimaging studies have shown that, when participants believe they are interacting via a virtual interface with another human agent, they show different patterns of brain activity compared to when they know that their virtual partner is computer-controlled. The suggestion is that users adopt an "intentional stance" by attributing mental states to their virtual partner. However, it remains unclear how beliefs in the agency of a virtual partner influence participants' behaviour and subjective experience of the interaction. We investigated this issue in the context of a cooperative "joint attention" game in which participants interacted via an eye tracker with a virtual onscreen partner, directing each other's eye gaze to different screen locations. Half of the participants were correctly informed that their partner was controlled by a computer algorithm ("Computer" condition). The other half were misled into believing that the virtual character was controlled by a second participant in another room ("Human" condition). Those in the "Human" condition were slower to make eye contact with their partner and more likely to try and guide their partner before they had established mutual eye contact than participants in the "Computer" condition. They also responded more rapidly when their partner was guiding them, although the same effect was also found for a control condition in which they responded to an arrow cue. Results confirm the influence of human agency beliefs on behaviour in this virtual social interaction context. They further suggest that researchers and developers attempting to simulate social interactions should consider the impact of agency beliefs on user experience in other social contexts, and their effect on the achievement of the application's goals.

Fused cerebral organoids model interactions between brain regions.

PubMed

Bagley, Joshua A; Reumann, Daniel; Bian, Shan; Lévi-Strauss, Julie; Knoblich, Juergen A

2017-07-01

Human brain development involves complex interactions between different regions, including long-distance neuronal migration or formation of major axonal tracts. Different brain regions can be cultured in vitro within 3D cerebral organoids, but the random arrangement of regional identities limits the reliable analysis of complex phenotypes. Here, we describe a coculture method combining brain regions of choice within one organoid tissue. By fusing organoids of dorsal and ventral forebrain identities, we generate a dorsal-ventral axis. Using fluorescent reporters, we demonstrate CXCR4-dependent GABAergic interneuron migration from ventral to dorsal forebrain and describe methodology for time-lapse imaging of human interneuron migration. Our results demonstrate that cerebral organoid fusion cultures can model complex interactions between different brain regions. Combined with reprogramming technology, fusions should offer researchers the possibility to analyze complex neurodevelopmental defects using cells from neurological disease patients and to test potential therapeutic compounds.

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

PubMed

Abubshait, Abdulaziz; Wiese, Eva

2017-01-01

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

Human-Computer Interaction with Medical Decisions Support Systems

NASA Technical Reports Server (NTRS)

Adolf, Jurine A.; Holden, Kritina L.

1994-01-01

Decision Support Systems (DSSs) have been available to medical diagnosticians for some time, yet their acceptance and use have not increased with advances in technology and availability of DSS tools. Medical DSSs will be necessary on future long duration space missions, because access to medical resources and personnel will be limited. Human-Computer Interaction (HCI) experts at NASA's Human Factors and Ergonomics Laboratory (HFEL) have been working toward understanding how humans use DSSs, with the goal of being able to identify and solve the problems associated with these systems. Work to date consists of identification of HCI research areas, development of a decision making model, and completion of two experiments dealing with 'anchoring'. Anchoring is a phenomenon in which the decision maker latches on to a starting point and does not make sufficient adjustments when new data are presented. HFEL personnel have replicated a well-known anchoring experiment and have investigated the effects of user level of knowledge. Future work includes further experimentation on level of knowledge, confidence in the source of information and sequential decision making.

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

ERIC Educational Resources Information Center

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

2012-01-01

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

Acquisition and production of skilled behavior in dynamic decision-making tasks: Modeling strategic behavior in human-automation interaction: Why and aid can (and should) go unused

NASA Technical Reports Server (NTRS)

Kirlik, Alex

1991-01-01

Advances in computer and control technology offer the opportunity for task-offload aiding in human-machine systems. A task-offload aid (e.g., an autopilot, an intelligent assistant) can be selectively engaged by the human operator to dynamically delegate tasks to an automated system. Successful design and performance prediction in such systems requires knowledge of the factors influencing the strategy the operator develops and uses for managing interaction with the task-offload aid. A model is presented that shows how such strategies can be predicted as a function of three task context properties (frequency and duration of secondary tasks and costs of delaying secondary tasks) and three aid design properties (aid engagement and disengagement times, aid performance relative to human performance). Sensitivity analysis indicates how each of these contextual and design factors affect the optimal aid aid usage strategy and attainable system performance. The model is applied to understanding human-automation interaction in laboratory experiments on human supervisory control behavior. The laboratory task allowed subjects freedom to determine strategies for using an autopilot in a dynamic, multi-task environment. Modeling results suggested that many subjects may indeed have been acting appropriately by not using the autopilot in the way its designers intended. Although autopilot function was technically sound, this aid was not designed with due regard to the overall task context in which it was placed. These results demonstrate the need for additional research on how people may strategically manage their own resources, as well as those provided by automation, in an effort to keep workload and performance at acceptable levels.

Ghost-in-the-Machine reveals human social signals for human-robot interaction.

PubMed

Loth, Sebastian; Jettka, Katharina; Giuliani, Manuel; de Ruiter, Jan P

2015-01-01

We used a new method called "Ghost-in-the-Machine" (GiM) to investigate social interactions with a robotic bartender taking orders for drinks and serving them. Using the GiM paradigm allowed us to identify how human participants recognize the intentions of customers on the basis of the output of the robotic recognizers. Specifically, we measured which recognizer modalities (e.g., speech, the distance to the bar) were relevant at different stages of the interaction. This provided insights into human social behavior necessary for the development of socially competent robots. When initiating the drink-order interaction, the most important recognizers were those based on computer vision. When drink orders were being placed, however, the most important information source was the speech recognition. Interestingly, the participants used only a subset of the available information, focussing only on a few relevant recognizers while ignoring others. This reduced the risk of acting on erroneous sensor data and enabled them to complete service interactions more swiftly than a robot using all available sensor data. We also investigated socially appropriate response strategies. In their responses, the participants preferred to use the same modality as the customer's requests, e.g., they tended to respond verbally to verbal requests. Also, they added redundancy to their responses, for instance by using echo questions. We argue that incorporating the social strategies discovered with the GiM paradigm in multimodal grammars of human-robot interactions improves the robustness and the ease-of-use of these interactions, and therefore provides a smoother user experience.

Human Development Theories: A Comparison of Classic Human Development Theorists and the Implications for a Model of Developmental Social Interaction.

ERIC Educational Resources Information Center

Ollhoff, Jim

This paper explores several theories of human development, with particular attention to the development of social interaction. Part 1 compares and contrasts major developmental theories, including those of Freud, Erikson, Piaget, Kohlberg, Kegan, Fowler, and Selman. From birth to 1 year, infants are laying the foundation that will guide their…

Interaction Models for Functional Regression.

PubMed

Usset, Joseph; Staicu, Ana-Maria; Maity, Arnab

2016-02-01

A functional regression model with a scalar response and multiple functional predictors is proposed that accommodates two-way interactions in addition to their main effects. The proposed estimation procedure models the main effects using penalized regression splines, and the interaction effect by a tensor product basis. Extensions to generalized linear models and data observed on sparse grids or with measurement error are presented. A hypothesis testing procedure for the functional interaction effect is described. The proposed method can be easily implemented through existing software. Numerical studies show that fitting an additive model in the presence of interaction leads to both poor estimation performance and lost prediction power, while fitting an interaction model where there is in fact no interaction leads to negligible losses. The methodology is illustrated on the AneuRisk65 study data.

Synchronization in human musical rhythms and mutually interacting complex systems

PubMed Central

Hennig, Holger

2014-01-01

Though the music produced by an ensemble is influenced by multiple factors, including musical genre, musician skill, and individual interpretation, rhythmic synchronization is at the foundation of musical interaction. Here, we study the statistical nature of the mutual interaction between two humans synchronizing rhythms. We find that the interbeat intervals of both laypeople and professional musicians exhibit scale-free (power law) cross-correlations. Surprisingly, the next beat to be played by one person is dependent on the entire history of the other person’s interbeat intervals on timescales up to several minutes. To understand this finding, we propose a general stochastic model for mutually interacting complex systems, which suggests a physiologically motivated explanation for the occurrence of scale-free cross-correlations. We show that the observed long-term memory phenomenon in rhythmic synchronization can be imitated by fractal coupling of separately recorded or synthesized audio tracks and thus applied in electronic music. Though this study provides an understanding of fundamental characteristics of timing and synchronization at the interbrain level, the mutually interacting complex systems model may also be applied to study the dynamics of other complex systems where scale-free cross-correlations have been observed, including econophysics, physiological time series, and collective behavior of animal flocks. PMID:25114228

A Mobile, Map-Based Tasking Interface for Human-Robot Interaction

DTIC Science & Technology

2010-12-01

A MOBILE, MAP-BASED TASKING INTERFACE FOR HUMAN-ROBOT INTERACTION By Eli R. Hooten Thesis Submitted to the Faculty of the Graduate School of...SUBTITLE A Mobile, Map-Based Tasking Interface for Human-Robot Interaction 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6...3 II.1 Interactive Modalities and Multi-Touch . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 II.2

Human-technology interaction for standoff IED detection

NASA Astrophysics Data System (ADS)

Zhang, Evan; Zou, Yiyang; Zachrich, Liping; Fulton, Jack

2011-03-01

IEDs kill our soldiers and innocent people every day. Lessons learned from Iraq and Afghanistan clearly indicated that IEDs cannot be detected/defeated by technology alone; human-technology interaction must be engaged. In most cases, eye is the best detector, brain is the best computer, and technologies are tools, they must be used by human being properly then can achieve full functionality. In this paper, a UV Raman/fluorescence, CCD and LWIR 3 sensor fusion system for standoff IED detection and a handheld fusion system for close range IED detection are developed and demonstrated. We must train solders using their eyes or CCD/LWIR cameras to do wide area search while on the move to find small suspected area first then use the spectrometer because the laser spot is too small, to scan a one-mile long and 2-meter wide road needs 185 days although our fusion system can detect the IED in 30m with 1s interrogating time. Even if the small suspected area (e.g., 0.5mx0.5m) is found, human eyes still cannot detect the IED, soldiers must use or interact with the technology - laser based spectrometer to scan the area then they are able to detect and identify the IED in 10 minutes not 185 days. Therefore, the human-technology interaction approach will be the best solution for IED detection.

Computational modeling of blast wave interaction with a human body and assessment of traumatic brain injury

NASA Astrophysics Data System (ADS)

Tan, X. G.; Przekwas, A. J.; Gupta, R. K.

2017-11-01

The modeling of human body biomechanics resulting from blast exposure poses great challenges because of the complex geometry and the substantial material heterogeneity. We developed a detailed human body finite element model representing both the geometry and the materials realistically. The model includes the detailed head (face, skull, brain and spinal cord), the neck, the skeleton, air cavities (lungs) and the tissues. Hence, it can be used to properly model the stress wave propagation in the human body subjected to blast loading. The blast loading on the human was generated from a simulated C4 explosion. We used the highly scalable solvers in the multi-physics code CoBi for both the blast simulation and the human body biomechanics. The meshes generated for these simulations are of good quality so that relatively large time-step sizes can be used without resorting to artificial time scaling treatments. The coupled gas dynamics and biomechanics solutions were validated against the shock tube test data. The human body models were used to conduct parametric simulations to find the biomechanical response and the brain injury mechanism due to blasts impacting the human body. Under the same blast loading condition, we showed the importance of inclusion of the whole body.

A new method measuring the interaction of radiotracers with the human P-glycoprotein (P-gp) transporter.

PubMed

Vraka, Chrysoula; Dumanic, Monika; Racz, Teresa; Pichler, Florian; Philippe, Cecile; Balber, Theresa; Klebermass, Eva-Maria; Wagner, Karl-Heinz; Hacker, Marcus; Wadsak, Wolfgang; Mitterhauser, Markus

2018-05-01

In drug development, biomarkers for cerebral applications have a lower success rate compared to cardiovascular drugs or tumor therapeutics. One reason is the missing blood brain barrier penetration, caused by the tracer's interaction with efflux transporters such as the P-gp (MDR1 or ABCB1). Aim of this study was the development of a reliable model to measure the interaction of radiotracers with the human efflux transporter P-gp in parallel to the radiolabeling process. LigandTracer® Technology was used with the wildtype cell line MDCKII and the equivalent cell line overexpressing human P-gp (MDCKII-hMDR1). The method was evaluated based on established PET tracers with known interaction with the human P-gp transporter and in nanomolar concentration (15 nM). [ 11 C]SNAP-7941 and [ 18 F]FE@SNAP were used as P-gp substrates by comparing the real-time model with an uptake assay and μPET images. [ 11 C]DASB [ 11 C]Harmine, [ 18 F]FMeNER,[ 18 F]FE@SUPPY and [ 11 C]Me@HAPTHI were used as tracers without interactions with P-gp in vitro. However, [ 11 C]Me@HAPTHI shows a significant increase in SUV levels after blocking with Tariquidar. The developed real-time kinetic model uses directly PET tracers in a compound concentration, which is reflecting the in vivo situation. This method may be used at an early stage of radiopharmaceutical development to measure interactions to P-gp before conducting animal experiments. Copyright © 2018 Elsevier Inc. All rights reserved.

Comparison of dogs and humans in visual scanning of social interaction.

PubMed

Törnqvist, Heini; Somppi, Sanni; Koskela, Aija; Krause, Christina M; Vainio, Outi; Kujala, Miiamaaria V

2015-09-01

Previous studies have demonstrated similarities in gazing behaviour of dogs and humans, but comparisons under similar conditions are rare, and little is known about dogs' visual attention to social scenes. Here, we recorded the eye gaze of dogs while they viewed images containing two humans or dogs either interacting socially or facing away: the results were compared with equivalent data measured from humans. Furthermore, we compared the gazing behaviour of two dog and two human populations with different social experiences: family and kennel dogs; dog experts and non-experts. Dogs' gazing behaviour was similar to humans: both species gazed longer at the actors in social interaction than in non-social images. However, humans gazed longer at the actors in dog than human social interaction images, whereas dogs gazed longer at the actors in human than dog social interaction images. Both species also made more saccades between actors in images representing non-conspecifics, which could indicate that processing social interaction of non-conspecifics may be more demanding. Dog experts and non-experts viewed the images very similarly. Kennel dogs viewed images less than family dogs, but otherwise their gazing behaviour did not differ, indicating that the basic processing of social stimuli remains similar regardless of social experiences.

Human-Computer Interaction, Tourism and Cultural Heritage

NASA Astrophysics Data System (ADS)

Cipolla Ficarra, Francisco V.

We present a state of the art of the human-computer interaction aimed at tourism and cultural heritage in some cities of the European Mediterranean. In the work an analysis is made of the main problems deriving from training understood as business and which can derail the continuous growth of the HCI, the new technologies and tourism industry. Through a semiotic and epistemological study the current mistakes in the context of the interrelations of the formal and factual sciences will be detected and also the human factors that have an influence on the professionals devoted to the development of interactive systems in order to safeguard and boost cultural heritage.

Ridge Regression for Interactive Models.

ERIC Educational Resources Information Center

Tate, Richard L.

1988-01-01

An exploratory study of the value of ridge regression for interactive models is reported. Assuming that the linear terms in a simple interactive model are centered to eliminate non-essential multicollinearity, a variety of common models, representing both ordinal and disordinal interactions, are shown to have "orientations" that are…

Designing automation for human use: empirical studies and quantitative models.

PubMed

Parasuraman, R

2000-07-01

An emerging knowledge base of human performance research can provide guidelines for designing automation that can be used effectively by human operators of complex systems. Which functions should be automated and to what extent in a given system? A model for types and levels of automation that provides a framework and an objective basis for making such choices is described. The human performance consequences of particular types and levels of automation constitute primary evaluative criteria for automation design when using the model. Four human performance areas are considered--mental workload, situation awareness, complacency and skill degradation. Secondary evaluative criteria include such factors as automation reliability, the risks of decision/action consequences and the ease of systems integration. In addition to this qualitative approach, quantitative models can inform design. Several computational and formal models of human interaction with automation that have been proposed by various researchers are reviewed. An important future research need is the integration of qualitative and quantitative approaches. Application of these models provides an objective basis for designing automation for effective human use.

Quantitative modeling of human-environment interactions in the preindustrial world

NASA Astrophysics Data System (ADS)

Kaplan, J. O.; Sommer, P.; Kay, A. U.; Phelps, L. N.

2016-12-01

Over the past 10,000 years, a series of agricultural and technological developments revolutionized land use by societies on most continents. The spread of crop plants, the use of fire for land management, the adoption of animal traction, the invention of the plow and the wheel, of metal agricultural implements, and the application of organic fertilizers all led to the intensification agricultural land use. This intensification allowed both growing human populations to be supported by a stable land base, and opened up new frontiers for agriculture that were previously undesirable for cultivation. In some cases, growing populations further developed macro-levels of social organization that facilitated collective undertakings that influenced land use, such as irrigation and terracing. All of these phenomena occurred heterogeneously in space and time, and their importance for anthropogenic land cover change over the Holocene is strongly debated. Here we quantify human influence on global landscapes using a numerical model describing preindustrial agriculture. The model is driven by archaeological information describing agriculture, technology, and social organization, and with environmental constraints from climate and soils. We simulate the environmental impact of changing land use systems over the early agricultural era. At least since the 3000 BP, agricultural land use is substantial enough to have had a significant impact on the distribution of forests and wetlands across large parts of Eurasia, Africa, and the Americas.

A pairwise maximum entropy model accurately describes resting-state human brain networks

PubMed Central

Watanabe, Takamitsu; Hirose, Satoshi; Wada, Hiroyuki; Imai, Yoshio; Machida, Toru; Shirouzu, Ichiro; Konishi, Seiki; Miyashita, Yasushi; Masuda, Naoki

2013-01-01

The resting-state human brain networks underlie fundamental cognitive functions and consist of complex interactions among brain regions. However, the level of complexity of the resting-state networks has not been quantified, which has prevented comprehensive descriptions of the brain activity as an integrative system. Here, we address this issue by demonstrating that a pairwise maximum entropy model, which takes into account region-specific activity rates and pairwise interactions, can be robustly and accurately fitted to resting-state human brain activities obtained by functional magnetic resonance imaging. Furthermore, to validate the approximation of the resting-state networks by the pairwise maximum entropy model, we show that the functional interactions estimated by the pairwise maximum entropy model reflect anatomical connexions more accurately than the conventional functional connectivity method. These findings indicate that a relatively simple statistical model not only captures the structure of the resting-state networks but also provides a possible method to derive physiological information about various large-scale brain networks. PMID:23340410

Partonomies for interactive explorable 3D-models of anatomy.

PubMed

Schubert, R; Höhne, K H

1998-01-01

We introduce a concept to model subtle part-whole-semantics for the use with interactive 3d-models of human anatomy. Similar to experiences with modeling partonomies for physical artifacts like machines or buildings we found one unique part-whole-relation to be insufficient to represent anatomical reality. This claim will be illustrated with anatomical examples. According to the requirements these examples demand, a semantic classification of part-whole-relations is introduced. Initial results in modeling anatomical partonomies for a 3d-visualization environment proved this approach to be an promising way to represent anatomy and to enable powerful complex inferences.

The Science of Human Interaction and Teaching

ERIC Educational Resources Information Center

Yano, Kazuo

2013-01-01

There is a missing link between our understanding of teaching as high-level social phenomenon and teaching as a physiological phenomenon of brain activity. We suggest that the science of human interaction is the missing link. Using over one-million days of human-behavior data, we have discovered that "collective activenes" (CA), which indicates…

Functionalized anatomical models for EM-neuron Interaction modeling

NASA Astrophysics Data System (ADS)

Neufeld, Esra; Cassará, Antonino Mario; Montanaro, Hazael; Kuster, Niels; Kainz, Wolfgang

2016-06-01

The understanding of interactions between electromagnetic (EM) fields and nerves are crucial in contexts ranging from therapeutic neurostimulation to low frequency EM exposure safety. To properly consider the impact of in vivo induced field inhomogeneity on non-linear neuronal dynamics, coupled EM-neuronal dynamics modeling is required. For that purpose, novel functionalized computable human phantoms have been developed. Their implementation and the systematic verification of the integrated anisotropic quasi-static EM solver and neuronal dynamics modeling functionality, based on the method of manufactured solutions and numerical reference data, is described. Electric and magnetic stimulation of the ulnar and sciatic nerve were modeled to help understanding a range of controversial issues related to the magnitude and optimal determination of strength-duration (SD) time constants. The results indicate the importance of considering the stimulation-specific inhomogeneous field distributions (especially at tissue interfaces), realistic models of non-linear neuronal dynamics, very short pulses, and suitable SD extrapolation models. These results and the functionalized computable phantom will influence and support the development of safe and effective neuroprosthetic devices and novel electroceuticals. Furthermore they will assist the evaluation of existing low frequency exposure standards for the entire population under all exposure conditions.

Computational Determination of the Effects of Bacteriophage Bacteriophage Interactions in Human body.

PubMed

Mostafa, Marwa Mostafa; Nassef, Mohammad; Badr, Amr

2017-10-19

Chronic diseases are becoming more serious and widely spreading and this carries a heavy burden on doctors to deal with such patients. Although many of these diseases can be treated by bacteriophages, the situation is significantly dangerous in patients having concomitant more than one chronic disease, where conflicts between phages used in treating these diseases are very closer to happen. This research paper presents a method to detecting the Bacteriophage-Bacteriophage Interaction. This method is implemented based on Domain-Domain Interactions model and it was used to infer Domain-Domain Interactions between the bacteriophages injected in the human body at the same time. By testing the method over bacteriophages that are used to treat tuberculosis, salmonella and virulent E.coli, many interactions have been inferred and detected between these bacteriophages. Several effects were detected for the resulted interactions such as: playing a role in DNA repair such as non-homologous end joining, playing a role in DNA replication, playing a role in the interaction between the immune system and the tumor cells and playing a role in the stiff man syndrome. We revised all patents relating to bacteriophage bacteriophage interactions and phage therapy. The proposed method is developed to help doctors to realize the effect of simultaneously injecting different bacteriophages into the human body to treat different diseases. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Structural Model for the Interaction of a Designed Ankyrin Repeat Protein with the Human Epidermal Growth Factor Receptor 2

PubMed Central

Epa, V. Chandana; Dolezal, Olan; Doughty, Larissa; Xiao, Xiaowen; Jost, Christian; Plückthun, Andreas; Adams, Timothy E.

2013-01-01

Designed Ankyrin Repeat Proteins are a class of novel binding proteins that can be selected and evolved to bind to targets with high affinity and specificity. We are interested in the DARPin H10-2-G3, which has been evolved to bind with very high affinity to the human epidermal growth factor receptor 2 (HER2). HER2 is found to be over-expressed in 30% of breast cancers, and is the target for the FDA-approved therapeutic monoclonal antibodies trastuzumab and pertuzumab and small molecule tyrosine kinase inhibitors. Here, we use computational macromolecular docking, coupled with several interface metrics such as shape complementarity, interaction energy, and electrostatic complementarity, to model the structure of the complex between the DARPin H10-2-G3 and HER2. We analyzed the interface between the two proteins and then validated the structural model by showing that selected HER2 point mutations at the putative interface with H10-2-G3 reduce the affinity of binding up to 100-fold without affecting the binding of trastuzumab. Comparisons made with a subsequently solved X-ray crystal structure of the complex yielded a backbone atom root mean square deviation of 0.84–1.14 Ångstroms. The study presented here demonstrates the capability of the computational techniques of structural bioinformatics in generating useful structural models of protein-protein interactions. PMID:23527120

Modeling Child–Nature Interaction in a Nature Preschool: A Proof of Concept

PubMed Central

Kahn, Peter H.; Weiss, Thea; Harrington, Kit

2018-01-01

This article provides a proof of concept for an approach to modeling child–nature interaction based on the idea of interaction patterns: characterizations of essential features of interaction between humans and nature, specified abstractly enough such that countless different instantiations of each one can occur – in more domestic or wild forms – given different types of nature, people, and purposes. The model draws from constructivist psychology, ecological psychology, and evolutionary psychology, and is grounded in observational data collected through a time-sampling methodology at a nature preschool. Through using a nature language that emphasizes ontogenetic and phylogenetic significance, seven keystone interaction patterns are described for this nature preschool: using one’s body vigorously in nature, striking wood on wood, constructing shelter, being in solitude in nature, lying on earth, cohabiting with a wild animal, and being outside in weather. These 7 interactions patterns are then brought together with 13 other patterns published elsewhere to provide a total of 20 keystone interaction patterns that begin to fill out the model, and to show its promise. Discussion focuses on what the model aims to be in terms of both product and process, on what work the model can currently do, and how to further develop the model. PMID:29896143

Modeling Child-Nature Interaction in a Nature Preschool: A Proof of Concept.

PubMed

Kahn, Peter H; Weiss, Thea; Harrington, Kit

2018-01-01

This article provides a proof of concept for an approach to modeling child-nature interaction based on the idea of interaction patterns : characterizations of essential features of interaction between humans and nature, specified abstractly enough such that countless different instantiations of each one can occur - in more domestic or wild forms - given different types of nature, people, and purposes. The model draws from constructivist psychology, ecological psychology, and evolutionary psychology, and is grounded in observational data collected through a time-sampling methodology at a nature preschool. Through using a nature language that emphasizes ontogenetic and phylogenetic significance, seven keystone interaction patterns are described for this nature preschool: using one's body vigorously in nature, striking wood on wood, constructing shelter, being in solitude in nature, lying on earth, cohabiting with a wild animal , and being outside in weather . These 7 interactions patterns are then brought together with 13 other patterns published elsewhere to provide a total of 20 keystone interaction patterns that begin to fill out the model, and to show its promise. Discussion focuses on what the model aims to be in terms of both product and process, on what work the model can currently do, and how to further develop the model.

Gene Expression Profiles of Human Dendritic Cells Interacting with Aspergillus fumigatus in a Bilayer Model of the Alveolar Epithelium/Endothelium Interface

PubMed Central

Morton, Charles Oliver; Fliesser, Mirjam; Dittrich, Marcus; Mueller, Tobias; Bauer, Ruth; Kneitz, Susanne; Hope, William; Rogers, Thomas Richard; Einsele, Hermann; Loeffler, Juergen

2014-01-01

The initial stages of the interaction between the host and Aspergillus fumigatus at the alveolar surface of the human lung are critical in the establishment of aspergillosis. Using an in vitro bilayer model of the alveolus, including both the epithelium (human lung adenocarcinoma epithelial cell line, A549) and endothelium (human pulmonary artery epithelial cells, HPAEC) on transwell membranes, it was possible to closely replicate the in vivo conditions. Two distinct sub-groups of dendritic cells (DC), monocyte-derived DC (moDC) and myeloid DC (mDC), were included in the model to examine immune responses to fungal infection at the alveolar surface. RNA in high quantity and quality was extracted from the cell layers on the transwell membrane to allow gene expression analysis using tailored custom-made microarrays, containing probes for 117 immune-relevant genes. This microarray data indicated minimal induction of immune gene expression in A549 alveolar epithelial cells in response to germ tubes of A. fumigatus. In contrast, the addition of DC to the system greatly increased the number of differentially expressed immune genes. moDC exhibited increased expression of genes including CLEC7A, CD209 and CCL18 in the absence of A. fumigatus compared to mDC. In the presence of A. fumigatus, both DC subgroups exhibited up-regulation of genes identified in previous studies as being associated with the exposure of DC to A. fumigatus and exhibiting chemotactic properties for neutrophils, including CXCL2, CXCL5, CCL20, and IL1B. This model closely approximated the human alveolus allowing for an analysis of the host pathogen interface that complements existing animal models of IA. PMID:24870357

Modeling In Vivo Interactions of Engineered Nanoparticles in the Pulmonary Alveolar Lining Fluid

PubMed Central

Mukherjee, Dwaipayan; Porter, Alexandra; Ryan, Mary; Schwander, Stephan; Chung, Kian Fan; Tetley, Teresa; Zhang, Junfeng; Georgopoulos, Panos

2015-01-01

Increasing use of engineered nanomaterials (ENMs) in consumer products may result in widespread human inhalation exposures. Due to their high surface area per unit mass, inhaled ENMs interact with multiple components of the pulmonary system, and these interactions affect their ultimate fate in the body. Modeling of ENM transport and clearance in vivo has traditionally treated tissues as well-mixed compartments, without consideration of nanoscale interaction and transformation mechanisms. ENM agglomeration, dissolution and transport, along with adsorption of biomolecules, such as surfactant lipids and proteins, cause irreversible changes to ENM morphology and surface properties. The model presented in this article quantifies ENM transformation and transport in the alveolar air to liquid interface and estimates eventual alveolar cell dosimetry. This formulation brings together established concepts from colloidal and surface science, physics, and biochemistry to provide a stochastic framework capable of capturing essential in vivo processes in the pulmonary alveolar lining layer. The model has been implemented for in vitro solutions with parameters estimated from relevant published in vitro measurements and has been extended here to in vivo systems simulating human inhalation exposures. Applications are presented for four different ENMs, and relevant kinetic rates are estimated, demonstrating an approach for improving human in vivo pulmonary dosimetry. PMID:26240755

Application of postured human model for SAR measurements

NASA Astrophysics Data System (ADS)

Vuchkovikj, M.; Munteanu, I.; Weiland, T.

2013-07-01

In the last two decades, the increasing number of electronic devices used in day-to-day life led to a growing interest in the study of the electromagnetic field interaction with biological tissues. The design of medical devices and wireless communication devices such as mobile phones benefits a lot from the bio-electromagnetic simulations in which digital human models are used. The digital human models currently available have an upright position which limits the research activities in realistic scenarios, where postured human bodies must be considered. For this reason, a software application called "BodyFlex for CST STUDIO SUITE" was developed. In its current version, this application can deform the voxel-based human model named HUGO (Dipp GmbH, 2010) to allow the generation of common postures that people use in normal life, ensuring the continuity of tissues and conserving the mass to an acceptable level. This paper describes the enhancement of the "BodyFlex" application, which is related to the movements of the forearm and the wrist of a digital human model. One of the electromagnetic applications in which the forearm and the wrist movement of a voxel based human model has a significant meaning is the measurement of the specific absorption rate (SAR) when a model is exposed to a radio frequency electromagnetic field produced by a mobile phone. Current SAR measurements of the exposure from mobile phones are performed with the SAM (Specific Anthropomorphic Mannequin) phantom which is filled with a dispersive but homogeneous material. We are interested what happens with the SAR values if a realistic inhomogeneous human model is used. To this aim, two human models, a homogeneous and an inhomogeneous one, in two simulation scenarios are used, in order to examine and observe the differences in the results for the SAR values.

Three-dimensional cell culture models for investigating human viruses.

PubMed

He, Bing; Chen, Guomin; Zeng, Yi

2016-10-01

Three-dimensional (3D) culture models are physiologically relevant, as they provide reproducible results, experimental flexibility and can be adapted for high-throughput experiments. Moreover, these models bridge the gap between traditional two-dimensional (2D) monolayer cultures and animal models. 3D culture systems have significantly advanced basic cell science and tissue engineering, especially in the fields of cell biology and physiology, stem cell research, regenerative medicine, cancer research, drug discovery, and gene and protein expression studies. In addition, 3D models can provide unique insight into bacteriology, virology, parasitology and host-pathogen interactions. This review summarizes and analyzes recent progress in human virological research with 3D cell culture models. We discuss viral growth, replication, proliferation, infection, virus-host interactions and antiviral drugs in 3D culture models.

A Simple Model for Human and Nature Interaction

NASA Astrophysics Data System (ADS)

Motesharrei, S.; Rivas, J.; Kalnay, E.

2012-12-01

There are widespread concerns that current trends in population and resource-use are unsustainable, but the possibilities of an overshoot and collapse remain unclear and controversial. Collapses of civilizations have occurred many times in the past 5000 years, often followed by centuries of economic, intellectual, and population decline. Many different natural and social phenomena have been invoked to explain specific collapses, but a general explanation remains elusive. Two important features seem to appear across societies that have collapsed: Ecological Strain and Economic Stratification. Our new model (Human And Nature DYnamics, HANDY) has just four equations that describe the evolution of Elites, Commoners, Nature, and Wealth. Mechanisms leading to collapse are discussed and the measure "Carrying Capacity" is developed and defined. The model shows that societal collapse can happen due to either one of two independent factors: (1) over-consumption of natural resources, and/or (2) deep inequity between Elites and Commoners. The model also portrays two distinct types of collapse: (i) collapse followed by recovery of nature, and (ii) full collapse. The model suggests that the estimation of Carrying Capacity is a practical means for early detection of a collapse. Collapse can be avoided, and population can reach a sustainable equilibrium, if the rate of depletion of nature is reduced to a sustainable level, and if resources are distributed in a reasonably equitable fashion.; A type-ii (full) collapse is shown in this figure. With high inequality and high depletion, societies are doomed to collapse. Wealth starts to decrease when population rises above the carrying capacity. The large gap between carrying capacity and its maximum is a result of depletion factor being much larger than the sustainable limit. ; It is possible to overshoot, oscillate, and eventually converge to an equilibrium, even in an inequitable society. However, it requires policies that control

A systems model for immune cell interactions unravels the mechanism of inflammation in human skin.

PubMed

Valeyev, Najl V; Hundhausen, Christian; Umezawa, Yoshinori; Kotov, Nikolay V; Williams, Gareth; Clop, Alex; Ainali, Crysanthi; Ouzounis, Christos; Tsoka, Sophia; Nestle, Frank O

2010-12-02

Inflammation is characterized by altered cytokine levels produced by cell populations in a highly interdependent manner. To elucidate the mechanism of an inflammatory reaction, we have developed a mathematical model for immune cell interactions via the specific, dose-dependent cytokine production rates of cell populations. The model describes the criteria required for normal and pathological immune system responses and suggests that alterations in the cytokine production rates can lead to various stable levels which manifest themselves in different disease phenotypes. The model predicts that pairs of interacting immune cell populations can maintain homeostatic and elevated extracellular cytokine concentration levels, enabling them to operate as an immune system switch. The concept described here is developed in the context of psoriasis, an immune-mediated disease, but it can also offer mechanistic insights into other inflammatory pathologies as it explains how interactions between immune cell populations can lead to disease phenotypes.

Modeling and prediction of human word search behavior in interactive machine translation

NASA Astrophysics Data System (ADS)

Ji, Duo; Yu, Bai; Ma, Bin; Ye, Na

2017-12-01

As a kind of computer aided translation method, Interactive Machine Translation technology reduced manual translation repetitive and mechanical operation through a variety of methods, so as to get the translation efficiency, and played an important role in the practical application of the translation work. In this paper, we regarded the behavior of users' frequently searching for words in the translation process as the research object, and transformed the behavior to the translation selection problem under the current translation. The paper presented a prediction model, which is a comprehensive utilization of alignment model, translation model and language model of the searching words behavior. It achieved a highly accurate prediction of searching words behavior, and reduced the switching of mouse and keyboard operations in the users' translation process.

Human-Automation Interaction Design for Adaptive Cruise Control Systems of Ground Vehicles.

PubMed

Eom, Hwisoo; Lee, Sang Hun

2015-06-12

A majority of recently developed advanced vehicles have been equipped with various automated driver assistance systems, such as adaptive cruise control (ACC) and lane keeping assistance systems. ACC systems have several operational modes, and drivers can be unaware of the mode in which they are operating. Because mode confusion is a significant human error factor that contributes to traffic accidents, it is necessary to develop user interfaces for ACC systems that can reduce mode confusion. To meet this requirement, this paper presents a new human-automation interaction design methodology in which the compatibility of the machine and interface models is determined using the proposed criteria, and if the models are incompatible, one or both of the models is/are modified to make them compatible. To investigate the effectiveness of our methodology, we designed two new interfaces by separately modifying the machine model and the interface model and then performed driver-in-the-loop experiments. The results showed that modifying the machine model provides a more compact, acceptable, effective, and safe interface than modifying the interface model.

Human-Automation Interaction Design for Adaptive Cruise Control Systems of Ground Vehicles

PubMed Central

Eom, Hwisoo; Lee, Sang Hun

2015-01-01

A majority of recently developed advanced vehicles have been equipped with various automated driver assistance systems, such as adaptive cruise control (ACC) and lane keeping assistance systems. ACC systems have several operational modes, and drivers can be unaware of the mode in which they are operating. Because mode confusion is a significant human error factor that contributes to traffic accidents, it is necessary to develop user interfaces for ACC systems that can reduce mode confusion. To meet this requirement, this paper presents a new human-automation interaction design methodology in which the compatibility of the machine and interface models is determined using the proposed criteria, and if the models are incompatible, one or both of the models is/are modified to make them compatible. To investigate the effectiveness of our methodology, we designed two new interfaces by separately modifying the machine model and the interface model and then performed driver-in-the-loop experiments. The results showed that modifying the machine model provides a more compact, acceptable, effective, and safe interface than modifying the interface model. PMID:26076406

Human-robot interaction modeling and simulation of supervisory control and situational awareness during field experimentation with military manned and unmanned ground vehicles

NASA Astrophysics Data System (ADS)

Johnson, Tony; Metcalfe, Jason; Brewster, Benjamin; Manteuffel, Christopher; Jaswa, Matthew; Tierney, Terrance

2010-04-01

The proliferation of intelligent systems in today's military demands increased focus on the optimization of human-robot interactions. Traditional studies in this domain involve large-scale field tests that require humans to operate semiautomated systems under varying conditions within military-relevant scenarios. However, provided that adequate constraints are employed, modeling and simulation can be a cost-effective alternative and supplement. The current presentation discusses a simulation effort that was executed in parallel with a field test with Soldiers operating military vehicles in an environment that represented key elements of the true operational context. In this study, "constructive" human operators were designed to represent average Soldiers executing supervisory control over an intelligent ground system. The constructive Soldiers were simulated performing the same tasks as those performed by real Soldiers during a directly analogous field test. Exercising the models in a high-fidelity virtual environment provided predictive results that represented actual performance in certain aspects, such as situational awareness, but diverged in others. These findings largely reflected the quality of modeling assumptions used to design behaviors and the quality of information available on which to articulate principles of operation. Ultimately, predictive analyses partially supported expectations, with deficiencies explicable via Soldier surveys, experimenter observations, and previously-identified knowledge gaps.

Mathematical Analysis for Non-reciprocal-interaction-based Model of Collective Behavior

NASA Astrophysics Data System (ADS)

Kano, Takeshi; Osuka, Koichi; Kawakatsu, Toshihiro; Ishiguro, Akio

2017-12-01

In many natural and social systems, collective behaviors emerge as a consequence of non-reciprocal interaction between their constituents. As a first step towards understanding the core principle that underlies these phenomena, we previously proposed a minimal model of collective behavior based on non-reciprocal interactions by drawing inspiration from friendship formation in human society, and demonstrated via simulations that various non-trivial patterns emerge by changing parameters. In this study, a mathematical analysis of the proposed model wherein the system size is small is performed. Through the analysis, the mechanism of the transition between several patterns is elucidated.

The study of early human embryos using interactive 3-dimensional computer reconstructions.

PubMed

Scarborough, J; Aiton, J F; McLachlan, J C; Smart, S D; Whiten, S C

1997-07-01

Tracings of serial histological sections from 4 human embryos at different Carnegie stages were used to create 3-dimensional (3D) computer models of the developing heart. The models were constructed using commercially available software developed for graphic design and the production of computer generated virtual reality environments. They are available as interactive objects which can be downloaded via the World Wide Web. This simple method of 3D reconstruction offers significant advantages for understanding important events in morphological sciences.

The impact of human-environment interactions on the stability of forest-grassland mosaic ecosystems

PubMed Central

Innes, Clinton; Anand, Madhur; Bauch, Chris T.

2013-01-01

Forest-grassland mosaic ecosystems can exhibit alternative stables states, whereby under the same environmental conditions, the ecosystem could equally well reside either in one state or another, depending on the initial conditions. We develop a mathematical model that couples a simplified forest-grassland mosaic model to a dynamic model of opinions about conservation priorities in a population, based on perceptions of ecosystem rarity. Weak human influence increases the region of parameter space where alternative stable states are possible. However, strong human influence precludes bistability, such that forest and grassland either co-exist at a single, stable equilibrium, or their relative abundance oscillates. Moreover, a perturbation can shift the system from a stable state to an oscillatory state. We conclude that human-environment interactions can qualitatively alter the composition of forest-grassland mosaic ecosystems. The human role in such systems should be viewed as dynamic, responsive element rather than as a fixed, unchanging entity. PMID:24048359

Cross-orientation interactions in human vision.

PubMed

Roeber, Urte; Wong, Elaine M Y; Freeman, Alan W

2008-03-18

Humans can discriminate one visual contour from another on the basis of small differences in orientation. This capability depends on cortical detectors that are selective for a small range of orientations. We have measured this orientation bandwidth and the suppression that helps to shape it, with a reverse correlation technique. Human subjects were presented with a stream of randomly oriented gratings at a rate of 30 per second. Their task was to press a key whenever they saw an orientation nominated as the target. We analyzed the data by finding the probability density of two orientations: One preceded the key-press by the reaction time, and the second preceded the first by up to 100 ms. The results were as follows: (1) One grating facilitated the following one in producing a key-press when the gratings differed little in orientation. The estimate of orientation bandwidth resulting from this facilitation was 38 degrees . (2) A large angle between the two orientations reduced the probability of a key-press. This finding was best modelled as a suppression that did not vary with orientation, consistent with the idea that cross-orientation suppression is non-oriented. (3) Analysis of non-consecutive grating pairs showed that cross-orientation interactions lasted no longer than 67 ms.

Study of the interaction of deoxynivalenol with human serum albumin by spectroscopic technique and molecular modelling.

PubMed

Li, Yuqin; Wang, Hao; Jia, Baoxiu; Liu, Caihong; Liu, Ke; Qi, Yongxiu; Hu, Zhide

2013-01-01

The mechanism of interaction between deoxynivalenol (DON) and human serum albumin (HSA) was studied using spectroscopic methods including fluorescence spectra, UV-VIS, Fourier transform infrared (FT-IR) and circular dichroism (CD). The quenching mechanism was investigated in terms of the association constants, number of binding sites and basic thermodynamic parameters. The distance between the HSA donor and the acceptor DON was 2.80 nm as derived from fluorescence resonance energy transfer. The secondary structure compositions of free HSA and its DON complexes were estimated by the FT-IR spectra. Alteration of the secondary protein structure in the presence of DON was confirmed by UV-VIS and CD spectroscopy. Molecular modelling revealed that a DON-protein complex was stabilised by hydrophobic forces and hydrogen bonding. It was potentially useful for elucidating the toxigenicity of DON when combined with biomolecular function effect, transmembrane transport, toxicological testing and the other experiments.

Astaxanthin and withaferin A block paracrine cytokine interactions between UVB-exposed human keratinocytes and human melanocytes via the attenuation of endothelin-1 secretion and its downstream intracellular signaling.

PubMed

Niwano, Takao; Terazawa, Shuko; Nakajima, Hiroaki; Wakabayashi, Yuki; Imokawa, Genji

2015-06-01

Paracrine interactions between keratinocytes and melanocytes via cytokines play an essential role in regulating pigmentation in epidermal hyperpigmentary disorders. There is an urgent need for a human epidermal model in which melanogenic paracrine interactions between UVB-exposed keratinocytes and melanocytes can be precisely evaluated because human epidermal equivalents consisting of multilayered keratinocytes and melanocytes have significant limitations in this respect. To resolve this challenge, we established a co-culture system with cell inserts using human keratinocytes and human melanocytes that serves as an appropriate new model for UVB-induced hyperpigmentation. Using that new model, we examined the blocking effects of two natural chemicals, astaxanthin and withaferin A, on paracrine cytokine interactions between UVB-exposed keratinocytes and melanocytes and characterized their mechanisms of action. RT-PCR analysis showed that co-culture of human keratinocytes that had been exposed to UVB significantly stimulated human melanocytes to increase their expression of genes encoding microphthalmia-associated transcription factor, tyrosinase and tyrosinase-related protein 1. The catalytic activity of tyrosinase was also increased. ELISA assays revealed that UVB significantly increased the secretion of interleukin-1α, interleukin-6/8, granulocyte macrophage stimulatory factor and endothelin-1 but not α-melanocyte stimulating hormone. The addition of an endothelin-1 neutralizing antibody significantly abrogated the increase of tyrosinase activity. Post-irradiation treatment with astaxanthin or withaferin A significantly abolished the up-regulation of tyrosinase activity induced by UVB. Treatment with astaxanthin or withaferin A significantly reduced the increased levels of interleukin-1α, interleukin-6/8, granulocyte macrophage stimulatory factor and endothelin-1. Withaferin A but not astaxanthin also significantly abrogated the endothelin-1-stimulated activity

Evaluation of an eye-pointer interaction device for human-computer interaction.

PubMed

Cáceres, Enrique; Carrasco, Miguel; Ríos, Sebastián

2018-03-01

Advances in eye-tracking technology have led to better human-computer interaction, and involve controlling a computer without any kind of physical contact. This research describes the transformation of a commercial eye-tracker for use as an alternative peripheral device in human-computer interactions, implementing a pointer that only needs the eye movements of a user facing a computer screen, thus replacing the need to control the software by hand movements. The experiment was performed with 30 test individuals who used the prototype with a set of educational videogames. The results show that, although most of the test subjects would prefer a mouse to control the pointer, the prototype tested has an empirical precision similar to that of the mouse, either when trying to control its movements or when attempting to click on a point of the screen.

Singularity now: using the ventricular assist device as a model for future human-robotic physiology.

PubMed

Martin, Archer K

2016-04-01

In our 21 st century world, human-robotic interactions are far more complicated than Asimov predicted in 1942. The future of human-robotic interactions includes human-robotic machine hybrids with an integrated physiology, working together to achieve an enhanced level of baseline human physiological performance. This achievement can be described as a biological Singularity. I argue that this time of Singularity cannot be met by current biological technologies, and that human-robotic physiology must be integrated for the Singularity to occur. In order to conquer the challenges we face regarding human-robotic physiology, we first need to identify a working model in today's world. Once identified, this model can form the basis for the study, creation, expansion, and optimization of human-robotic hybrid physiology. In this paper, I present and defend the line of argument that currently this kind of model (proposed to be named "IshBot") can best be studied in ventricular assist devices - VAD.

Singularity now: using the ventricular assist device as a model for future human-robotic physiology

PubMed Central

Martin, Archer K.

2016-01-01

In our 21st century world, human-robotic interactions are far more complicated than Asimov predicted in 1942. The future of human-robotic interactions includes human-robotic machine hybrids with an integrated physiology, working together to achieve an enhanced level of baseline human physiological performance. This achievement can be described as a biological Singularity. I argue that this time of Singularity cannot be met by current biological technologies, and that human-robotic physiology must be integrated for the Singularity to occur. In order to conquer the challenges we face regarding human-robotic physiology, we first need to identify a working model in today’s world. Once identified, this model can form the basis for the study, creation, expansion, and optimization of human-robotic hybrid physiology. In this paper, I present and defend the line of argument that currently this kind of model (proposed to be named “IshBot”) can best be studied in ventricular assist devices – VAD. PMID:28913480

Computational Modeling of Blast Wave Transmission Through Human Ear.

PubMed

Leckness, Kegan; Nakmali, Don; Gan, Rong Z

2018-03-01

Hearing loss has become the most common disability among veterans. Understanding how blast waves propagate through the human ear is a necessary step in the development of effective hearing protection devices (HPDs). This article presents the first 3D finite element (FE) model of the human ear to simulate blast wave transmission through the ear. The 3D FE model of the human ear consisting of the ear canal, tympanic membrane, ossicular chain, and middle ear cavity was imported into ANSYS Workbench for coupled fluid-structure interaction analysis in the time domain. Blast pressure waveforms recorded external to the ear in human cadaver temporal bone tests were applied at the entrance of the ear canal in the model. The pressure waveforms near the tympanic membrane (TM) in the canal (P1) and behind the TM in the middle ear cavity (P2) were calculated. The model-predicted results were then compared with measured P1 and P2 waveforms recorded in human cadaver ears during blast tests. Results show that the model-derived P1 waveforms were in an agreement with the experimentally recorded waveforms with statistic Kurtosis analysis. The FE model will be used for the evaluation of HPDs in future studies.

More-Realistic Digital Modeling of a Human Body

NASA Technical Reports Server (NTRS)

Rogge, Renee

2010-01-01

A MATLAB computer program has been written to enable improved (relative to an older program) modeling of a human body for purposes of designing space suits and other hardware with which an astronaut must interact. The older program implements a kinematic model based on traditional anthropometric measurements that do provide important volume and surface information. The present program generates a three-dimensional (3D) whole-body model from 3D body-scan data. The program utilizes thin-plate spline theory to reposition the model without need for additional scans.

Quantifying Engagement: Measuring Player Involvement in Human-Avatar Interactions

PubMed Central

Norris, Anne E.; Weger, Harry; Bullinger, Cory; Bowers, Alyssa

2014-01-01

This research investigated the merits of using an established system for rating behavioral cues of involvement in human dyadic interactions (i.e., face-to-face conversation) to measure involvement in human-avatar interactions. Gameplay audio-video and self-report data from a Feasibility Trial and Free Choice study of an effective peer resistance skill building simulation game (DRAMA-RAMA™) were used to evaluate reliability and validity of the rating system when applied to human-avatar interactions. The Free Choice study used a revised game prototype that was altered to be more engaging. Both studies involved girls enrolled in a public middle school in Central Florida that served a predominately Hispanic (greater than 80%), low-income student population. Audio-video data were coded by two raters, trained in the rating system. Self-report data were generated using measures of perceived realism, predictability and flow administered immediately after game play. Hypotheses for reliability and validity were supported: Reliability values mirrored those found in the human dyadic interaction literature. Validity was supported by factor analysis, significantly higher levels of involvement in Free Choice as compared to Feasibility Trial players, and correlations between involvement dimension sub scores and self-report measures. Results have implications for the science of both skill-training intervention research and game design. PMID:24748718

The Dimensionality and Correlates of Flow in Human-Computer Interactions.

ERIC Educational Resources Information Center

Webster, Jane; And Others

1993-01-01

Defines playfulness in human-computer interactions in terms of flow theory and explores the dimensionality of the flow concept. Two studies are reported that investigated the factor structure and correlates of flow in human-computer interactions: one examined MBA students using Lotus 1-2-3 spreadsheet software, and one examined employees using…

Interaction of an antiepileptic drug, lamotrigine with human serum albumin (HSA): Application of spectroscopic techniques and molecular modeling methods.

PubMed

Poureshghi, Fatemeh; Ghandforoushan, Parisa; Safarnejad, Azam; Soltani, Somaieh

2017-01-01

Lamotrigine (an epileptic drug) interaction with human serum albumin (HSA) was investigated by fluorescence, UV-Vis, FTIR, CD spectroscopic techniques, and molecular modeling methods. Binding constant (K b ) of 5.74×10 3 and number of binding site of 0.97 showed that there is a slight interaction between lamotrigine and HSA. Thermodynamic studies was constructed using the flourimetric titrations in three different temperatures and the resulted data used to calculate the parameters using Vant Hoff equation. Decreased Stern Volmer quenching constant by enhanced temperature revealed the static quenching mechanism. Negative standard enthalpy (ΔH) and standard entropy (ΔS) changes indicated that van der Waals interactions and hydrogen bonds were dominant forces which facilitate the binding of Lamotrigine to HSA, the results were confirmed by molecular docking studies which showed no hydrogen binding. The FRET studies showed that there is a possibility of energy transfer between Trp214 and lamotrigine. Also the binding of lamotrigine to HSA in the studied concentrations was not as much as many other drugs, but the secondary structure of the HSA was significantly changed following the interaction in a way that α-helix percentage was reduced from 67% to 57% after the addition of lamotrigine in the molar ratio of 4:1 to HSA. According to the docking studies, lamotrigine binds to IB site preferably. Copyright © 2016. Published by Elsevier B.V.

Computational Modeling of Human Metabolism and Its Application to Systems Biomedicine.

PubMed

Aurich, Maike K; Thiele, Ines

2016-01-01

Modern high-throughput techniques offer immense opportunities to investigate whole-systems behavior, such as those underlying human diseases. However, the complexity of the data presents challenges in interpretation, and new avenues are needed to address the complexity of both diseases and data. Constraint-based modeling is one formalism applied in systems biology. It relies on a genome-scale reconstruction that captures extensive biochemical knowledge regarding an organism. The human genome-scale metabolic reconstruction is increasingly used to understand normal cellular and disease states because metabolism is an important factor in many human diseases. The application of human genome-scale reconstruction ranges from mere querying of the model as a knowledge base to studies that take advantage of the model's topology and, most notably, to functional predictions based on cell- and condition-specific metabolic models built based on omics data.An increasing number and diversity of biomedical questions are being addressed using constraint-based modeling and metabolic models. One of the most successful biomedical applications to date is cancer metabolism, but constraint-based modeling also holds great potential for inborn errors of metabolism or obesity. In addition, it offers great prospects for individualized approaches to diagnostics and the design of disease prevention and intervention strategies. Metabolic models support this endeavor by providing easy access to complex high-throughput datasets. Personalized metabolic models have been introduced. Finally, constraint-based modeling can be used to model whole-body metabolism, which will enable the elucidation of metabolic interactions between organs and disturbances of these interactions as either causes or consequence of metabolic diseases. This chapter introduces constraint-based modeling and describes some of its contributions to systems biomedicine.

Velocity-curvature patterns limit human-robot physical interaction

PubMed Central

Maurice, Pauline; Huber, Meghan E.; Hogan, Neville; Sternad, Dagmar

2018-01-01

Physical human-robot collaboration is becoming more common, both in industrial and service robotics. Cooperative execution of a task requires intuitive and efficient interaction between both actors. For humans, this means being able to predict and adapt to robot movements. Given that natural human movement exhibits several robust features, we examined whether human-robot physical interaction is facilitated when these features are considered in robot control. The present study investigated how humans adapt to biological and non-biological velocity patterns in robot movements. Participants held the end-effector of a robot that traced an elliptic path with either biological (two-thirds power law) or non-biological velocity profiles. Participants were instructed to minimize the force applied on the robot end-effector. Results showed that the applied force was significantly lower when the robot moved with a biological velocity pattern. With extensive practice and enhanced feedback, participants were able to decrease their force when following a non-biological velocity pattern, but never reached forces below those obtained with the 2/3 power law profile. These results suggest that some robust features observed in natural human movements are also a strong preference in guided movements. Therefore, such features should be considered in human-robot physical collaboration. PMID:29744380

Velocity-curvature patterns limit human-robot physical interaction.

PubMed

Maurice, Pauline; Huber, Meghan E; Hogan, Neville; Sternad, Dagmar

2018-01-01

Physical human-robot collaboration is becoming more common, both in industrial and service robotics. Cooperative execution of a task requires intuitive and efficient interaction between both actors. For humans, this means being able to predict and adapt to robot movements. Given that natural human movement exhibits several robust features, we examined whether human-robot physical interaction is facilitated when these features are considered in robot control. The present study investigated how humans adapt to biological and non-biological velocity patterns in robot movements. Participants held the end-effector of a robot that traced an elliptic path with either biological (two-thirds power law) or non-biological velocity profiles. Participants were instructed to minimize the force applied on the robot end-effector. Results showed that the applied force was significantly lower when the robot moved with a biological velocity pattern. With extensive practice and enhanced feedback, participants were able to decrease their force when following a non-biological velocity pattern, but never reached forces below those obtained with the 2/3 power law profile. These results suggest that some robust features observed in natural human movements are also a strong preference in guided movements. Therefore, such features should be considered in human-robot physical collaboration.

Leveraging Human Insights by Combining Multi-Objective Optimization with Interactive Evolution

DTIC Science & Technology

2015-03-26

application, a program that used human selections to guide the evolution of insect -like images. He was able to demonstrate that humans provide key insights...LEVERAGING HUMAN INSIGHTS BY COMBINING MULTI-OBJECTIVE OPTIMIZATION WITH INTERACTIVE EVOLUTION THESIS Joshua R. Christman, Second Lieutenant, USAF...COMBINING MULTI-OBJECTIVE OPTIMIZATION WITH INTERACTIVE EVOLUTION THESIS Presented to the Faculty Department of Electrical and Computer Engineering

Review on modeling heat transfer and thermoregulatory responses in human body.

PubMed

Fu, Ming; Weng, Wenguo; Chen, Weiwang; Luo, Na

2016-12-01

Several mathematical models of human thermoregulation have been developed, contributing to a deep understanding of thermal responses in different thermal conditions and applications. In these models, the human body is represented by two interacting systems of thermoregulation: the controlling active system and the controlled passive system. This paper reviews the recent research of human thermoregulation models. The accuracy and scope of the thermal models are improved, for the consideration of individual differences, integration to clothing models, exposure to cold and hot conditions, and the changes of physiological responses for the elders. The experimental validated methods for human subjects and manikin are compared. The coupled method is provided for the manikin, controlled by the thermal model as an active system. Computational Fluid Dynamics (CFD) is also used along with the manikin or/and the thermal model, to evaluate the thermal responses of human body in various applications, such as evaluation of thermal comfort to increase the energy efficiency, prediction of tolerance limits and thermal acceptability exposed to hostile environments, indoor air quality assessment in the car and aerospace industry, and design protective equipment to improve function of the human activities. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Preliminary Study of Peer-to-Peer Human-Robot Interaction

NASA Technical Reports Server (NTRS)

Fong, Terrence; Flueckiger, Lorenzo; Kunz, Clayton; Lees, David; Schreiner, John; Siegel, Michael; Hiatt, Laura M.; Nourbakhsh, Illah; Simmons, Reid; Ambrose, Robert

2006-01-01

The Peer-to-Peer Human-Robot Interaction (P2P-HRI) project is developing techniques to improve task coordination and collaboration between human and robot partners. Our work is motivated by the need to develop effective human-robot teams for space mission operations. A central element of our approach is creating dialogue and interaction tools that enable humans and robots to flexibly support one another. In order to understand how this approach can influence task performance, we recently conducted a series of tests simulating a lunar construction task with a human-robot team. In this paper, we describe the tests performed, discuss our initial results, and analyze the effect of intervention on task performance.

Interactive Modelling of Salinity Intrusion in the Rhine-Meuse Delta

NASA Astrophysics Data System (ADS)

Baart, F.; Kranenburg, W.; Luijendijk, A.

2015-12-01

In many delta's of the world salinity intrusion imposes limits to fresh water availability. With increasing population and industry, the need for fresh water increases. But also salinity intrusion is expected to increase due to changes in river discharge, sea level and storm characteristics. In the Rhine-Meuse delta salt intrusion is impacted by human activities as well, like deepening of waterways and opening of delta-branches closed earlier. All these developments call for increasing the understanding of the system, but also for means for policy makers, coastal planners and engineers to assess effects of changes and to explore and design measures. In our presentation we present the developments in interactive modelling of salinity intrusion in the Rhine-Meuse delta. In traditional process-based numerical modelling, impacts are investigated by researchers and engineers by following the steps of pre-defining scenario's, running the model and post-processing the results. Interactive modelling lets users adjust simulations while running. Users can for instance change river discharges or bed levels, and can add measures like changes to geometry. The model will take the adjustments into account immediately, and will directly compute the effect. In this way, a tool becomes available with which coastal planners, policy makers and engineers together can develop and evaluate ideas and designs by interacting with the numerical model. When developing interactive numerical engines, one of the challenges is to optimize the exchange of variables as e.g. salt concentration. In our case we exchange variables on a 3D grid every time step. For this, the numerical model adheres to the Basic Model Interface (http://csdms.colorado.edu/wiki), which allows external control and the exchange of variables through pointers while the model is running. In our presentation we further explain our method and show examples of interactive design of salinity intrusion measures in the Rhine

Computing the stresses and deformations of the human eye components due to a high explosive detonation using fluid-structure interaction model.

PubMed

Karimi, Alireza; Razaghi, Reza; Navidbakhsh, Mahdi; Sera, Toshihiro; Kudo, Susumu

2016-05-01

In spite the fact that a very small human body surface area is comprised by the eye, its wounds due to detonation have recently been dramatically amplified. Although many efforts have been devoted to measure injury of the globe, there is still a lack of knowledge on the injury mechanism due to Primary Blast Wave (PBW). The goal of this study was to determine the stresses and deformations of the human eye components, including the cornea, aqueous, iris, ciliary body, lens, vitreous, retina, sclera, optic nerve, and muscles, attributed to PBW induced by trinitrotoluene (TNT) explosion via a Lagrangian-Eulerian computational coupling model. Magnetic Resonance Imaging (MRI) was employed to establish a Finite Element (FE) model of the human eye according to a normal human eye. The solid components of the eye were modelled as Lagrangian mesh, while an explosive TNT, air domain, and aqueous were modelled using Arbitrary Lagrangian-Eulerian (ALE) mesh. Nonlinear dynamic FE simulations were accomplished using the explicit FE code, namely LS-DYNA. In order to simulate the blast wave generation, propagation, and interaction with the eye, the ALE formulation with Jones-Wilkins-Lee (JWL) equation defining the explosive material were employed. The results revealed a peak stress of 135.70kPa brought about by detonation upsurge on the cornea at the distance of 25cm. The highest von Mises stresses were observed on the sclera (267.3kPa), whereas the lowest one was seen on the vitreous body (0.002kPa). The results also showed a relatively high resultant displacement for the macula as well as a high variation for the radius of curvature for the cornea and lens, which can result in both macular holes, optic nerve damage and, consequently, vision loss. These results may have implications not only for understanding the value of stresses and strains in the human eye components but also giving an outlook about the process of PBW triggers damage to the eye. Copyright © 2016 Elsevier Ltd

Human-Robot Interaction Directed Research Project

NASA Technical Reports Server (NTRS)

Sandor, Aniko; Cross, Ernest V., II; Chang, Mai Lee

2014-01-01

Human-robot interaction (HRI) is a discipline investigating the factors affecting the interactions between humans and robots. It is important to evaluate how the design of interfaces and command modalities affect the human's ability to perform tasks accurately, efficiently, and effectively when working with a robot. By understanding the effects of interface design on human performance, workload, and situation awareness, interfaces can be developed to appropriately support the human in performing tasks with minimal errors and with appropriate interaction time and effort. Thus, the results of research on human-robot interfaces have direct implications for the design of robotic systems. This DRP concentrates on three areas associated with interfaces and command modalities in HRI which are applicable to NASA robot systems: 1) Video Overlays, 2) Camera Views, and 3) Command Modalities. The first study focused on video overlays that investigated how Augmented Reality (AR) symbology can be added to the human-robot interface to improve teleoperation performance. Three types of AR symbology were explored in this study, command guidance (CG), situation guidance (SG), and both (SCG). CG symbology gives operators explicit instructions on what commands to input, whereas SG symbology gives operators implicit cues so that operators can infer the input commands. The combination of CG and SG provided operators with explicit and implicit cues allowing the operator to choose which symbology to utilize. The objective of the study was to understand how AR symbology affects the human operator's ability to align a robot arm to a target using a flight stick and the ability to allocate attention between the symbology and external views of the world. The study evaluated the effects type of symbology (CG and SG) has on operator tasks performance and attention allocation during teleoperation of a robot arm. The second study expanded on the first study by evaluating the effects of the type of

Characterization of human-dog social interaction using owner report.

PubMed

Lit, Lisa; Schweitzer, Julie B; Oberbauer, Anita M

2010-07-01

Dog owners were surveyed for observations of social behaviors in their dogs, using questions adapted from the human Autism Diagnostic Observation Schedule (ADOS) pre-verbal module. Using 939 responses for purebred and mixed-breed dogs, three factors were identified: initiation of reciprocal social behaviors (INIT), response to social interactions (RSPNS), and communication (COMM). There were small or no effects of sex, age, breed group or training. For six breeds with more than 35 responses (Border Collie, Rough Collie, German Shepherd, Golden Retriever, Labrador Retriever, Standard Poodle), the behaviors eye contact with humans, enjoyment in interactions with human interaction, and name recognition demonstrated little variability across breeds, while asking for objects, giving/showing objects to humans, and attempts to direct humans' attention showed higher variability across these breeds. Breeds with genetically similar backgrounds had similar response distributions for owner reports of dog response to pointing. When considering these breeds according to the broad categories of "herders" and "retrievers," owners reported that the "herders" used more eye contact and vocalization, while the "retrievers" used more body contact. Information regarding social cognitive abilities in dogs provided by owner report suggest that there is variability across many social cognitive abilities in dogs and offers direction for further experimental investigations. Copyright (c) 2010 Elsevier B.V. All rights reserved.

DenHunt - A Comprehensive Database of the Intricate Network of Dengue-Human Interactions

PubMed Central

Arjunan, Selvam; Sastri, Narayan P.; Chandra, Nagasuma

2016-01-01

Dengue virus (DENV) is a human pathogen and its etiology has been widely established. There are many interactions between DENV and human proteins that have been reported in literature. However, no publicly accessible resource for efficiently retrieving the information is yet available. In this study, we mined all publicly available dengue–human interactions that have been reported in the literature into a database called DenHunt. We retrieved 682 direct interactions of human proteins with dengue viral components, 382 indirect interactions and 4120 differentially expressed human genes in dengue infected cell lines and patients. We have illustrated the importance of DenHunt by mapping the dengue–human interactions on to the host interactome and observed that the virus targets multiple host functional complexes of important cellular processes such as metabolism, immune system and signaling pathways suggesting a potential role of these interactions in viral pathogenesis. We also observed that 7 percent of the dengue virus interacting human proteins are also associated with other infectious and non-infectious diseases. Finally, the understanding that comes from such analyses could be used to design better strategies to counteract the diseases caused by dengue virus. The whole dataset has been catalogued in a searchable database, called DenHunt (http://proline.biochem.iisc.ernet.in/DenHunt/). PMID:27618709

DenHunt - A Comprehensive Database of the Intricate Network of Dengue-Human Interactions.

PubMed

Karyala, Prashanthi; Metri, Rahul; Bathula, Christopher; Yelamanchi, Syam K; Sahoo, Lipika; Arjunan, Selvam; Sastri, Narayan P; Chandra, Nagasuma

2016-09-01

Dengue virus (DENV) is a human pathogen and its etiology has been widely established. There are many interactions between DENV and human proteins that have been reported in literature. However, no publicly accessible resource for efficiently retrieving the information is yet available. In this study, we mined all publicly available dengue-human interactions that have been reported in the literature into a database called DenHunt. We retrieved 682 direct interactions of human proteins with dengue viral components, 382 indirect interactions and 4120 differentially expressed human genes in dengue infected cell lines and patients. We have illustrated the importance of DenHunt by mapping the dengue-human interactions on to the host interactome and observed that the virus targets multiple host functional complexes of important cellular processes such as metabolism, immune system and signaling pathways suggesting a potential role of these interactions in viral pathogenesis. We also observed that 7 percent of the dengue virus interacting human proteins are also associated with other infectious and non-infectious diseases. Finally, the understanding that comes from such analyses could be used to design better strategies to counteract the diseases caused by dengue virus. The whole dataset has been catalogued in a searchable database, called DenHunt (http://proline.biochem.iisc.ernet.in/DenHunt/).

Social interaction enhances motor resonance for observed human actions.

PubMed

Hogeveen, Jeremy; Obhi, Sukhvinder S

2012-04-25

Understanding the neural basis of social behavior has become an important goal for cognitive neuroscience and a key aim is to link neural processes observed in the laboratory to more naturalistic social behaviors in real-world contexts. Although it is accepted that mirror mechanisms contribute to the occurrence of motor resonance (MR) and are common to action execution, observation, and imitation, questions remain about mirror (and MR) involvement in real social behavior and in processing nonhuman actions. To determine whether social interaction primes the MR system, groups of participants engaged or did not engage in a social interaction before observing human or robotic actions. During observation, MR was assessed via motor-evoked potentials elicited with transcranial magnetic stimulation. Compared with participants who did not engage in a prior social interaction, participants who engaged in the social interaction showed a significant increase in MR for human actions. In contrast, social interaction did not increase MR for robot actions. Thus, naturalistic social interaction and laboratory action observation tasks appear to involve common MR mechanisms, and recent experience tunes the system to particular agent types.

Designing for flexible interaction between humans and automation: delegation interfaces for supervisory control.

PubMed

Miller, Christopher A; Parasuraman, Raja

2007-02-01

To develop a method enabling human-like, flexible supervisory control via delegation to automation. Real-time supervisory relationships with automation are rarely as flexible as human task delegation to other humans. Flexibility in human-adaptable automation can provide important benefits, including improved situation awareness, more accurate automation usage, more balanced mental workload, increased user acceptance, and improved overall performance. We review problems with static and adaptive (as opposed to "adaptable") automation; contrast these approaches with human-human task delegation, which can mitigate many of the problems; and revise the concept of a "level of automation" as a pattern of task-based roles and authorizations. We argue that delegation requires a shared hierarchical task model between supervisor and subordinates, used to delegate tasks at various levels, and offer instruction on performing them. A prototype implementation called Playbook is described. On the basis of these analyses, we propose methods for supporting human-machine delegation interactions that parallel human-human delegation in important respects. We develop an architecture for machine-based delegation systems based on the metaphor of a sports team's "playbook." Finally, we describe a prototype implementation of this architecture, with an accompanying user interface and usage scenario, for mission planning for uninhabited air vehicles. Delegation offers a viable method for flexible, multilevel human-automation interaction to enhance system performance while maintaining user workload at a manageable level. Most applications of adaptive automation (aviation, air traffic control, robotics, process control, etc.) are potential avenues for the adaptable, delegation approach we advocate. We present an extended example for uninhabited air vehicle mission planning.

Human agency beliefs influence behaviour during virtual social interactions

PubMed Central

Brock, Jon

2017-01-01

In recent years, with the emergence of relatively inexpensive and accessible virtual reality technologies, it is now possible to deliver compelling and realistic simulations of human-to-human interaction. Neuroimaging studies have shown that, when participants believe they are interacting via a virtual interface with another human agent, they show different patterns of brain activity compared to when they know that their virtual partner is computer-controlled. The suggestion is that users adopt an “intentional stance” by attributing mental states to their virtual partner. However, it remains unclear how beliefs in the agency of a virtual partner influence participants’ behaviour and subjective experience of the interaction. We investigated this issue in the context of a cooperative “joint attention” game in which participants interacted via an eye tracker with a virtual onscreen partner, directing each other’s eye gaze to different screen locations. Half of the participants were correctly informed that their partner was controlled by a computer algorithm (“Computer” condition). The other half were misled into believing that the virtual character was controlled by a second participant in another room (“Human” condition). Those in the “Human” condition were slower to make eye contact with their partner and more likely to try and guide their partner before they had established mutual eye contact than participants in the “Computer” condition. They also responded more rapidly when their partner was guiding them, although the same effect was also found for a control condition in which they responded to an arrow cue. Results confirm the influence of human agency beliefs on behaviour in this virtual social interaction context. They further suggest that researchers and developers attempting to simulate social interactions should consider the impact of agency beliefs on user experience in other social contexts, and their effect on the achievement

The scaling of human interactions with city size

PubMed Central

Schläpfer, Markus; Bettencourt, Luís M. A.; Grauwin, Sébastian; Raschke, Mathias; Claxton, Rob; Smoreda, Zbigniew; West, Geoffrey B.; Ratti, Carlo

2014-01-01

The size of cities is known to play a fundamental role in social and economic life. Yet, its relation to the structure of the underlying network of human interactions has not been investigated empirically in detail. In this paper, we map society-wide communication networks to the urban areas of two European countries. We show that both the total number of contacts and the total communication activity grow superlinearly with city population size, according to well-defined scaling relations and resulting from a multiplicative increase that affects most citizens. Perhaps surprisingly, however, the probability that an individual's contacts are also connected with each other remains largely unaffected. These empirical results predict a systematic and scale-invariant acceleration of interaction-based spreading phenomena as cities get bigger, which is numerically confirmed by applying epidemiological models to the studied networks. Our findings should provide a microscopic basis towards understanding the superlinear increase of different socioeconomic quantities with city size, that applies to almost all urban systems and includes, for instance, the creation of new inventions or the prevalence of certain contagious diseases. PMID:24990287

A Functional Analysis on the Interspecies Interaction between Mouse LFA-1 and Human Intercellular Adhesion Molecule-1 at the Cell Level

PubMed Central

Núñez, David; Comas, Laura; Lanuza, Pilar M.; Sánchez-Martinez, Diego; Pérez-Hernández, Marta; Catalán, Elena; Domingo, María Pilar; Velázquez-Campoy, Adrián; Pardo, Julián; Gálvez, Eva M.

2017-01-01

The interaction between intercellular adhesion molecules (ICAM) and the integrin leukocyte function-associated antigen-1 (LFA-1) is crucial for the regulation of several physiological and pathophysiological processes like cell-mediated elimination of tumor or virus infected cells, cancer metastasis, or inflammatory and autoimmune processes. Using purified proteins it was reported a species restriction for the interaction of ICAM-1 and LFA-1, being mouse ICAM-1 able to interact with human LFA-1 but not human ICAM-1 with mouse LFA-1. However, in vivo results employing tumor cells transfected with human ICAM-1 suggest that functionally mouse LFA-1 can recognize human ICAM-1. In order to clarify the interspecies cross-reactivity of the ICAM-1/LFA-1 interaction, we have performed functional studies analyzing the ability of human soluble ICAM-1 and human/mouse LFA-1 derived peptides to inhibit cell aggregation and adhesion as well as cell-mediated cytotoxicity in both mouse and human systems. In parallel, the affinity of the interaction between mouse LFA-1-derived peptides and human ICAM-1 was determined by calorimetry assays. According to the results obtained, it seems that human ICAM-1 is able to interact with mouse LFA-1 on intact cells, which should be taking into account when using humanized mice and xenograft models for the study of immune-related processes. PMID:29312326

A Functional Analysis on the Interspecies Interaction between Mouse LFA-1 and Human Intercellular Adhesion Molecule-1 at the Cell Level.

PubMed

Núñez, David; Comas, Laura; Lanuza, Pilar M; Sánchez-Martinez, Diego; Pérez-Hernández, Marta; Catalán, Elena; Domingo, María Pilar; Velázquez-Campoy, Adrián; Pardo, Julián; Gálvez, Eva M

2017-01-01

The interaction between intercellular adhesion molecules (ICAM) and the integrin leukocyte function-associated antigen-1 (LFA-1) is crucial for the regulation of several physiological and pathophysiological processes like cell-mediated elimination of tumor or virus infected cells, cancer metastasis, or inflammatory and autoimmune processes. Using purified proteins it was reported a species restriction for the interaction of ICAM-1 and LFA-1, being mouse ICAM-1 able to interact with human LFA-1 but not human ICAM-1 with mouse LFA-1. However, in vivo results employing tumor cells transfected with human ICAM-1 suggest that functionally mouse LFA-1 can recognize human ICAM-1. In order to clarify the interspecies cross-reactivity of the ICAM-1/LFA-1 interaction, we have performed functional studies analyzing the ability of human soluble ICAM-1 and human/mouse LFA-1 derived peptides to inhibit cell aggregation and adhesion as well as cell-mediated cytotoxicity in both mouse and human systems. In parallel, the affinity of the interaction between mouse LFA-1-derived peptides and human ICAM-1 was determined by calorimetry assays. According to the results obtained, it seems that human ICAM-1 is able to interact with mouse LFA-1 on intact cells, which should be taking into account when using humanized mice and xenograft models for the study of immune-related processes.

Real-time human-robot interaction underlying neurorobotic trust and intent recognition.

PubMed

Bray, Laurence C Jayet; Anumandla, Sridhar R; Thibeault, Corey M; Hoang, Roger V; Goodman, Philip H; Dascalu, Sergiu M; Bryant, Bobby D; Harris, Frederick C

2012-08-01

In the past three decades, the interest in trust has grown significantly due to its important role in our modern society. Everyday social experience involves "confidence" among people, which can be interpreted at the neurological level of a human brain. Recent studies suggest that oxytocin is a centrally-acting neurotransmitter important in the development and alteration of trust. Its administration in humans seems to increase trust and reduce fear, in part by directly inhibiting the amygdala. However, the cerebral microcircuitry underlying this mechanism is still unknown. We propose the first biologically realistic model for trust, simulating spiking neurons in the cortex in a real-time human-robot interaction simulation. At the physiological level, oxytocin cells were modeled with triple apical dendrites characteristic of their structure in the paraventricular nucleus of the hypothalamus. As trust was established in the simulation, this architecture had a direct inhibitory effect on the amygdala tonic firing, which resulted in a willingness to exchange an object from the trustor (virtual neurorobot) to the trustee (human actor). Our software and hardware enhancements allowed the simulation of almost 100,000 neurons in real time and the incorporation of a sophisticated Gabor mechanism as a visual filter. Our brain was functional and our robotic system was robust in that it trusted or distrusted a human actor based on movement imitation. Copyright © 2012 Elsevier Ltd. All rights reserved.

modPDZpep: a web resource for structure based analysis of human PDZ-mediated interaction networks.

PubMed

Sain, Neetu; Mohanty, Debasisa

2016-09-21

PDZ domains recognize short sequence stretches usually present in C-terminal of their interaction partners. Because of the involvement of PDZ domains in many important biological processes, several attempts have been made for developing bioinformatics tools for genome-wide identification of PDZ interaction networks. Currently available tools for prediction of interaction partners of PDZ domains utilize machine learning approach. Since, they have been trained using experimental substrate specificity data for specific PDZ families, their applicability is limited to PDZ families closely related to the training set. These tools also do not allow analysis of PDZ-peptide interaction interfaces. We have used a structure based approach to develop modPDZpep, a program to predict the interaction partners of human PDZ domains and analyze structural details of PDZ interaction interfaces. modPDZpep predicts interaction partners by using structural models of PDZ-peptide complexes and evaluating binding energy scores using residue based statistical pair potentials. Since, it does not require training using experimental data on peptide binding affinity, it can predict substrates for diverse PDZ families. Because of the use of simple scoring function for binding energy, it is also fast enough for genome scale structure based analysis of PDZ interaction networks. Benchmarking using artificial as well as real negative datasets indicates good predictive power with ROC-AUC values in the range of 0.7 to 0.9 for a large number of human PDZ domains. Another novel feature of modPDZpep is its ability to map novel PDZ mediated interactions in human protein-protein interaction networks, either by utilizing available experimental phage display data or by structure based predictions. In summary, we have developed modPDZpep, a web-server for structure based analysis of human PDZ domains. It is freely available at http://www.nii.ac.in/modPDZpep.html or http://202.54.226.235/modPDZpep.html . This

Interaction of Human Hemoglobin with Methotrexate

NASA Astrophysics Data System (ADS)

Zaharia, M.; Gradinaru, R.

2015-05-01

This study focuses on the interaction between methotrexate and human hemoglobin using steady-state ultraviolet-visible and fluorescence quenching methods. Fluorescence quenching was found to be valuable in assessing drug binding to hemoglobin. The quenching of methotrexate is slightly smaller than the quenching observed with related analogs (dihydrofolate and tetrahydrofolate). The quenching studies were performed at four different temperatures and various pH values. The number of binding sites for tryptophan is ~1. Parameter-dependent assays revealed that electrostatic forces play an essential role in the methotrexate-hemoglobin interaction. Furthermore, the complex was easily eluted using gel filtration chromatography.

ISS Plasma Interaction: Measurements and Modeling

NASA Technical Reports Server (NTRS)

Barsamian, H.; Mikatarian, R.; Alred, J.; Minow, J.; Koontz, S.

2004-01-01

Ionospheric plasma interaction effects on the International Space Station are discussed in the following paper. The large structure and high voltage arrays of the ISS represent a complex system interacting with LEO plasma. Discharge current measurements made by the Plasma Contactor Units and potential measurements made by the Floating Potential Probe delineate charging and magnetic induction effects on the ISS. Based on theoretical and physical understanding of the interaction phenomena, a model of ISS plasma interaction has been developed. The model includes magnetic induction effects, interaction of the high voltage solar arrays with ionospheric plasma, and accounts for other conductive areas on the ISS. Based on these phenomena, the Plasma Interaction Model has been developed. Limited verification of the model has been performed by comparison of Floating Potential Probe measurement data to simulations. The ISS plasma interaction model will be further tested and verified as measurements from the Floating Potential Measurement Unit become available, and construction of the ISS continues.

Are Children with Autism More Responsive to Animated Characters? A Study of Interactions with Humans and Human-Controlled Avatars

ERIC Educational Resources Information Center

Carter, Elizabeth J.; Williams, Diane L.; Hodgins, Jessica K.; Lehman, Jill F.

2014-01-01

Few direct comparisons have been made between the responsiveness of children with autism to computer-generated or animated characters and their responsiveness to humans. Twelve 4-to 8-year-old children with autism interacted with a human therapist; a human-controlled, interactive avatar in a theme park; a human actor speaking like the avatar; and…

A Multiscale Survival Process for Modeling Human Activity Patterns.

PubMed

Zhang, Tianyang; Cui, Peng; Song, Chaoming; Zhu, Wenwu; Yang, Shiqiang

2016-01-01

Human activity plays a central role in understanding large-scale social dynamics. It is well documented that individual activity pattern follows bursty dynamics characterized by heavy-tailed interevent time distributions. Here we study a large-scale online chatting dataset consisting of 5,549,570 users, finding that individual activity pattern varies with timescales whereas existing models only approximate empirical observations within a limited timescale. We propose a novel approach that models the intensity rate of an individual triggering an activity. We demonstrate that the model precisely captures corresponding human dynamics across multiple timescales over five orders of magnitudes. Our model also allows extracting the population heterogeneity of activity patterns, characterized by a set of individual-specific ingredients. Integrating our approach with social interactions leads to a wide range of implications.

Promoter-enhancer interactions identified from Hi-C data using probabilistic models and hierarchical topological domains.

PubMed

Ron, Gil; Globerson, Yuval; Moran, Dror; Kaplan, Tommy

2017-12-21

Proximity-ligation methods such as Hi-C allow us to map physical DNA-DNA interactions along the genome, and reveal its organization into topologically associating domains (TADs). As the Hi-C data accumulate, computational methods were developed for identifying domain borders in multiple cell types and organisms. Here, we present PSYCHIC, a computational approach for analyzing Hi-C data and identifying promoter-enhancer interactions. We use a unified probabilistic model to segment the genome into domains, which we then merge hierarchically and fit using a local background model, allowing us to identify over-represented DNA-DNA interactions across the genome. By analyzing the published Hi-C data sets in human and mouse, we identify hundreds of thousands of putative enhancers and their target genes, and compile an extensive genome-wide catalog of gene regulation in human and mouse. As we show, our predictions are highly enriched for ChIP-seq and DNA accessibility data, evolutionary conservation, eQTLs and other DNA-DNA interaction data.

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

PubMed

Lee, Seungcheol Austin; Liang, Yuhua Jake

2015-04-01

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

Multi-tasking arbitration and behaviour design for human-interactive robots

NASA Astrophysics Data System (ADS)

Kobayashi, Yuichi; Onishi, Masaki; Hosoe, Shigeyuki; Luo, Zhiwei

2013-05-01

Robots that interact with humans in household environments are required to handle multiple real-time tasks simultaneously, such as carrying objects, collision avoidance and conversation with human. This article presents a design framework for the control and recognition processes to meet these requirements taking into account stochastic human behaviour. The proposed design method first introduces a Petri net for synchronisation of multiple tasks. The Petri net formulation is converted to Markov decision processes and processed in an optimal control framework. Three tasks (safety confirmation, object conveyance and conversation) interact and are expressed by the Petri net. Using the proposed framework, tasks that normally tend to be designed by integrating many if-then rules can be designed in a systematic manner in a state estimation and optimisation framework from the viewpoint of the shortest time optimal control. The proposed arbitration method was verified by simulations and experiments using RI-MAN, which was developed for interactive tasks with humans.

Cytoscape: a software environment for integrated models of biomolecular interaction networks.

PubMed

Shannon, Paul; Markiel, Andrew; Ozier, Owen; Baliga, Nitin S; Wang, Jonathan T; Ramage, Daniel; Amin, Nada; Schwikowski, Benno; Ideker, Trey

2003-11-01

Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.

Endocrine-immune interactions in human endometrium.

PubMed

Kayisli, U A; Guzeloglu-Kayisli, O; Arici, A

2004-12-01

The immune system is a complex entity designed to eliminate foreign intruding antigens and is influenced by and, in turn, influences the function of the reproductive system. Despite the widespread associations between immunology and reproductive medicine, the study of system interactions remains in its infancy. Many diverse facts are accumulating, and pieces of the puzzle are becoming available to provide a clearer picture. In this review article, we focus on the interactions between endocrine and immune systems in the human endometrium. Understanding the molecular pathways in endocrine-immune interactions in the human endometrium is crucial to understand events such as menstrual bleeding, tissue repair and regeneration, inflammation, angiogenesis, blastocyst implantation, and progression of pregnancy. These events require a balanced regulation of endometrial differentiation, proliferation, cell survival, leukocyte recruitment, apoptosis, and angiogenesis by sex steroids. In this review, we first outline the role of survival factors such as phosphoinositol 3-kinase/protein kinase B, PTEN, NFkappaB, and apoptotic molecules (Fas-FasL, Bcl-2). We then discuss their regulation by estrogen and progesterone in the endometrium. We present evidence for direct and/or indirect roles of steroid hormones on the expression of chemotactic cytokines (interleukin-8 and monocyte chemotactic protein-1) and on the survival versus apoptosis of resident endometrial cells (stromal, epithelial, and endothelial cells) and nonresident cells (leukocytes).

FE Modelling of the Fluid-Structure-Acoustic Interaction for the Vocal Folds Self-Oscillation

NASA Astrophysics Data System (ADS)

Švancara, Pavel; Horáček, J.; Hrůza, V.

The flow induced self-oscillation of the human vocal folds in interaction with acoustic processes in the simplified vocal tract model was explored by three-dimensional (3D) finite element (FE) model. Developed FE model includes vocal folds pretension before phonation, large deformations of the vocal fold tissue, vocal folds contact, fluid-structure interaction, morphing the fluid mesh according the vocal folds motion (Arbitrary Lagrangian-Eulerian approach), unsteady viscous compressible airflow described by the Navier-Stokes equations and airflow separation during the glottis closure. Iterative partitioned approach is used for modelling the fluid-structure interaction. Computed results prove that the developed model can be used for simulation of the vocal folds self-oscillation and resulting acoustic waves. The developed model enables to numerically simulate an influence of some pathological changes in the vocal fold tissue on the voice production.

Development of an interactive anatomical three-dimensional eye model.

PubMed

Allen, Lauren K; Bhattacharyya, Siddhartha; Wilson, Timothy D

2015-01-01

The discrete anatomy of the eye's intricate oculomotor system is conceptually difficult for novice students to grasp. This is problematic given that this group of muscles represents one of the most common sites of clinical intervention in the treatment of ocular motility disorders and other eye disorders. This project was designed to develop a digital, interactive, three-dimensional (3D) model of the muscles and cranial nerves of the oculomotor system. Development of the 3D model utilized data from the Visible Human Project (VHP) dataset that was refined using multiple forms of 3D software. The model was then paired with a virtual user interface in order to create a novel 3D learning tool for the human oculomotor system. Development of the virtual eye model was done while attempting to adhere to the principles of cognitive load theory (CLT) and the reduction of extraneous load in particular. The detailed approach, digital tools employed, and the CLT guidelines are described herein. © 2014 American Association of Anatomists.

Modeling human-machine interactions for operations room layouts

NASA Astrophysics Data System (ADS)

Hendy, Keith C.; Edwards, Jack L.; Beevis, David

2000-11-01

The LOCATE layout analysis tool was used to analyze three preliminary configurations for the Integrated Command Environment (ICE) of a future USN platform. LOCATE develops a cost function reflecting the quality of all human-human and human-machine communications within a workspace. This proof- of-concept study showed little difference between the efficacy of the preliminary designs selected for comparison. This was thought to be due to the limitations of the study, which included the assumption of similar size for each layout and a lack of accurate measurement data for various objects in the designs, due largely to their notional nature. Based on these results, the USN offered an opportunity to conduct a LOCATE analysis using more appropriate assumptions. A standard crew was assumed, and subject matter experts agreed on the communications patterns for the analysis. Eight layouts were evaluated with the concepts of coordination and command factored into the analysis. Clear differences between the layouts emerged. The most promising design was refined further by the USN, and a working mock-up built for human-in-the-loop evaluation. LOCATE was applied to this configuration for comparison with the earlier analyses.

Centrality of Social Interaction in Human Brain Function.

PubMed

Hari, Riitta; Henriksson, Linda; Malinen, Sanna; Parkkonen, Lauri

2015-10-07

People are embedded in social interaction that shapes their brains throughout lifetime. Instead of emerging from lower-level cognitive functions, social interaction could be the default mode via which humans communicate with their environment. Should this hypothesis be true, it would have profound implications on how we think about brain functions and how we dissect and simulate them. We suggest that the research on the brain basis of social cognition and interaction should move from passive spectator science to studies including engaged participants and simultaneous recordings from the brains of the interacting persons. Copyright © 2015 Elsevier Inc. All rights reserved.

Linguistic steganography on Twitter: hierarchical language modeling with manual interaction

NASA Astrophysics Data System (ADS)

Wilson, Alex; Blunsom, Phil; Ker, Andrew D.

2014-02-01

This work proposes a natural language stegosystem for Twitter, modifying tweets as they are written to hide 4 bits of payload per tweet, which is a greater payload than previous systems have achieved. The system, CoverTweet, includes novel components, as well as some already developed in the literature. We believe that the task of transforming covers during embedding is equivalent to unilingual machine translation (paraphrasing), and we use this equivalence to de ne a distortion measure based on statistical machine translation methods. The system incorporates this measure of distortion to rank possible tweet paraphrases, using a hierarchical language model; we use human interaction as a second distortion measure to pick the best. The hierarchical language model is designed to model the speci c language of the covers, which in this setting is the language of the Twitter user who is embedding. This is a change from previous work, where general-purpose language models have been used. We evaluate our system by testing the output against human judges, and show that humans are unable to distinguish stego tweets from cover tweets any better than random guessing.

Association with humans and seasonality interact to reverse predictions for animal space use.

PubMed

Laver, Peter N; Alexander, Kathleen A

2018-01-01

Variation in animal space use reflects fitness trade-offs associated with ecological constraints. Associated theories such as the metabolic theory of ecology and the resource dispersion hypothesis generate predictions about what drives variation in animal space use. But, metabolic theory is usually tested in macro-ecological studies and is seldom invoked explicitly in within-species studies. Full evaluation of the resource dispersion hypothesis requires testing in more species. Neither have been evaluated in the context of anthropogenic landscape change. In this study, we used data for banded mongooses ( Mungos mungo ) in northeastern Botswana, along a gradient of association with humans, to test for effects of space use drivers predicted by these theories. We used Bayesian parameter estimation and inference from linear models to test for seasonal differences in space use metrics and to model seasonal effects of space use drivers. Results suggest that space use is strongly associated with variation in the level of overlap that mongoose groups have with humans. Seasonality influences this association, reversing seasonal space use predictions historically-accepted by ecologists. We found support for predictions of the metabolic theory when moderated by seasonality, by association with humans and by their interaction. Space use of mongooses living in association with humans was more concentrated in the dry season than the wet season, when historically-accepted ecological theory predicted more dispersed space use. Resource richness factors such as building density were associated with space use only during the dry season. We found negligible support for predictions of the resource dispersion hypothesis in general or for metabolic theory where seasonality and association with humans were not included. For mongooses living in association with humans, space use was not associated with patch dispersion or group size over both seasons. In our study, living in association

Modeling Humans as Reinforcement Learners: How to Predict Human Behavior in Multi-Stage Games

NASA Technical Reports Server (NTRS)

Lee, Ritchie; Wolpert, David H.; Backhaus, Scott; Bent, Russell; Bono, James; Tracey, Brendan

2011-01-01

This paper introduces a novel framework for modeling interacting humans in a multi-stage game environment by combining concepts from game theory and reinforcement learning. The proposed model has the following desirable characteristics: (1) Bounded rational players, (2) strategic (i.e., players account for one anothers reward functions), and (3) is computationally feasible even on moderately large real-world systems. To do this we extend level-K reasoning to policy space to, for the first time, be able to handle multiple time steps. This allows us to decompose the problem into a series of smaller ones where we can apply standard reinforcement learning algorithms. We investigate these ideas in a cyber-battle scenario over a smart power grid and discuss the relationship between the behavior predicted by our model and what one might expect of real human defenders and attackers.

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

PubMed Central

Mörtl, Alexander; Lorenz, Tamara; Hirche, Sandra

2014-01-01

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

Numerical models as interactive art

NASA Astrophysics Data System (ADS)

Donchyts, G.; Baart, F.; van de Pas, B.; Joling, A.

2017-12-01

We capture our understanding of the environment in advanced computer models. We use these numerical models to simulate the growth of deltas, meandering rivers, dune erosion, river floodings, effects of interventions. If presented with care, models can help understand the complexity of our environment and show the beautiful patterns of nature. While the topics are relevant and appealing to the general public the use of numerical models has been limited to technical users. Not many people have appreciations for the pluriform of options, esoteric user interfaces, manual editing of configuration files and extensive jargon. The models are static, you can start them, but then you have to wait, usually hours or more, for the results to become available, not something that you could imagine resulting in an immersive, interactive experience for the general public. How can we go beyond just using results? How can we adapt existing numerical models so they can be used in an interactive environment? How can we touch them and feel them? Here we show how we adapted existing models (Delft3D, Lisflood, XBeach) and reused them in as the basis for interactive exhibitions in museums with an educative goal. We present our structured approach which consists of combining a story, inspiration, a canvas, colors, shapes and interactive elements. We show how the progression from simple presentation forms to interactive art installations.

Insight into the interaction mechanism of human SGLT2 with its inhibitors: 3D-QSAR studies, homology modeling, and molecular docking and molecular dynamics simulations.

PubMed

Dong, Lili; Feng, Ruirui; Bi, Jiawei; Shen, Shengqiang; Lu, Huizhe; Zhang, Jianjun

2018-03-06

Human sodium-dependent glucose co-transporter 2 (hSGLT2) is a crucial therapeutic target in the treatment of type 2 diabetes. In this study, both comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were applied to generate three-dimensional quantitative structure-activity relationship (3D-QSAR) models. In the most accurate CoMFA-based and CoMSIA-based QSAR models, the cross-validated coefficients (r 2 cv ) were 0.646 and 0.577, respectively, while the non-cross-validated coefficients (r 2 ) were 0.997 and 0.991, respectively, indicating that both models were reliable. In addition, we constructed a homology model of hSGLT2 in the absence of a crystal structure. Molecular docking was performed to explore the bonding mode of inhibitors to the active site of hSGLT2. Molecular dynamics (MD) simulations and binding free energy calculations using MM-PBSA and MM-GBSA were carried out to further elucidate the interaction mechanism. With regards to binding affinity, we found that hydrogen-bond interactions of Asn51 and Glu75, located in the active site of hSGLT2, with compound 40 were critical. Hydrophobic and electrostatic interactions were shown to enhance activity, in agreement with the results obtained from docking and 3D-QSAR analysis. Our study results shed light on the interaction mode between inhibitors and hSGLT2 and may aid in the development of C-aryl glucoside SGLT2 inhibitors.

An interactive framework for acquiring vision models of 3-D objects from 2-D images.

PubMed

Motai, Yuichi; Kak, Avinash

2004-02-01

This paper presents a human-computer interaction (HCI) framework for building vision models of three-dimensional (3-D) objects from their two-dimensional (2-D) images. Our framework is based on two guiding principles of HCI: 1) provide the human with as much visual assistance as possible to help the human make a correct input; and 2) verify each input provided by the human for its consistency with the inputs previously provided. For example, when stereo correspondence information is elicited from a human, his/her job is facilitated by superimposing epipolar lines on the images. Although that reduces the possibility of error in the human marked correspondences, such errors are not entirely eliminated because there can be multiple candidate points close together for complex objects. For another example, when pose-to-pose correspondence is sought from a human, his/her job is made easier by allowing the human to rotate the partial model constructed in the previous pose in relation to the partial model for the current pose. While this facility reduces the incidence of human-supplied pose-to-pose correspondence errors, such errors cannot be eliminated entirely because of confusion created when multiple candidate features exist close together. Each input provided by the human is therefore checked against the previous inputs by invoking situation-specific constraints. Different types of constraints (and different human-computer interaction protocols) are needed for the extraction of polygonal features and for the extraction of curved features. We will show results on both polygonal objects and object containing curved features.

Molecular modeling of interactions in electronic nose sensors for environmental monitoring

NASA Technical Reports Server (NTRS)

Shevade, A. V.; Ryan, M. A.; Homer, M. L.; Manfreda, A. M.; Yen, S. -P. S.; Zhou, H.; Manatt, K.

2002-01-01

We report a study aimed at understanding analyte interactions with sensors made from polymer-carbon black composite films. The sensors are used in an Electronic Nose (ENose) which is used for monitoring the breathing air quality in human habitats. The model mimics the experimental conditions of the composite film deposition and formation and was developed using molecular modeling and simulation tools. The Dreiding 2.21 Force Field was used for the polymer and analyte molecules while graphite parameters were assigned to the carbon black atoms. The polymer considered for this work is methyl vinyl ether / maleic acid copolymer. The target analytes include both inorganic (NH3) and organic (methanol) types of compound. Results indicate different composite-analyte interaction behavior.

Intrinsic interactive reinforcement learning - Using error-related potentials for real world human-robot interaction.

PubMed

Kim, Su Kyoung; Kirchner, Elsa Andrea; Stefes, Arne; Kirchner, Frank

2017-12-14

Reinforcement learning (RL) enables robots to learn its optimal behavioral strategy in dynamic environments based on feedback. Explicit human feedback during robot RL is advantageous, since an explicit reward function can be easily adapted. However, it is very demanding and tiresome for a human to continuously and explicitly generate feedback. Therefore, the development of implicit approaches is of high relevance. In this paper, we used an error-related potential (ErrP), an event-related activity in the human electroencephalogram (EEG), as an intrinsically generated implicit feedback (rewards) for RL. Initially we validated our approach with seven subjects in a simulated robot learning scenario. ErrPs were detected online in single trial with a balanced accuracy (bACC) of 91%, which was sufficient to learn to recognize gestures and the correct mapping between human gestures and robot actions in parallel. Finally, we validated our approach in a real robot scenario, in which seven subjects freely chose gestures and the real robot correctly learned the mapping between gestures and actions (ErrP detection (90% bACC)). In this paper, we demonstrated that intrinsically generated EEG-based human feedback in RL can successfully be used to implicitly improve gesture-based robot control during human-robot interaction. We call our approach intrinsic interactive RL.

Human-Robot Interaction Directed Research Project

NASA Technical Reports Server (NTRS)

Sandor, Aniko; Cross, Ernest V., II; Chang, M. L.

2014-01-01

Human-robot interaction (HRI) is a discipline investigating the factors affecting the interactions between humans and robots. It is important to evaluate how the design of interfaces and command modalities affect the human's ability to perform tasks accurately, efficiently, and effectively when working with a robot. By understanding the effects of interface design on human performance, workload, and situation awareness, interfaces can be developed to appropriately support the human in performing tasks with minimal errors and with appropriate interaction time and effort. Thus, the results of research on human-robot interfaces have direct implications for the design of robotic systems. This DRP concentrates on three areas associated with interfaces and command modalities in HRI which are applicable to NASA robot systems: 1) Video Overlays, 2) Camera Views, and 3) Command Modalities. The first study focused on video overlays that investigated how Augmented Reality (AR) symbology can be added to the human-robot interface to improve teleoperation performance. Three types of AR symbology were explored in this study, command guidance (CG), situation guidance (SG), and both (SCG). CG symbology gives operators explicit instructions on what commands to input, whereas SG symbology gives operators implicit cues so that operators can infer the input commands. The combination of CG and SG provided operators with explicit and implicit cues allowing the operator to choose which symbology to utilize. The objective of the study was to understand how AR symbology affects the human operator's ability to align a robot arm to a target using a flight stick and the ability to allocate attention between the symbology and external views of the world. The study evaluated the effects type of symbology (CG and SG) has on operator tasks performance and attention allocation during teleoperation of a robot arm. The second study expanded on the first study by evaluating the effects of the type of

Haptic communication between humans is tuned by the hard or soft mechanics of interaction

PubMed Central

Usai, Francesco; Ganesh, Gowrishankar; Sanguineti, Vittorio; Burdet, Etienne

2018-01-01

To move a hard table together, humans may coordinate by following the dominant partner’s motion [1–4], but this strategy is unsuitable for a soft mattress where the perceived forces are small. How do partners readily coordinate in such differing interaction dynamics? To address this, we investigated how pairs tracked a target using flexion-extension of their wrists, which were coupled by a hard, medium or soft virtual elastic band. Tracking performance monotonically increased with a stiffer band for the worse partner, who had higher tracking error, at the cost of the skilled partner’s muscular effort. This suggests that the worse partner followed the skilled one’s lead, but simulations show that the results are better explained by a model where partners share movement goals through the forces, whilst the coupling dynamics determine the capacity of communicable information. This model elucidates the versatile mechanism by which humans can coordinate during both hard and soft physical interactions to ensure maximum performance with minimal effort. PMID:29565966

BaffleText: a Human Interactive Proof

NASA Astrophysics Data System (ADS)

Chew, Monica; Baird, Henry S.

2003-01-01

Internet services designed for human use are being abused by programs. We present a defense against such attacks in the form of a CAPTCHA (Completely Automatic Public Turing test to tell Computers and Humans Apart) that exploits the difference in ability between humans and machines in reading images of text. CAPTCHAs are a special case of 'human interactive proofs,' a broad class of security protocols that allow people to identify themselves over networks as members of given groups. We point out vulnerabilities of reading-based CAPTCHAs to dictionary and computer-vision attacks. We also draw on the literature on the psychophysics of human reading, which suggests fresh defenses available to CAPTCHAs. Motivated by these considerations, we propose BaffleText, a CAPTCHA which uses non-English pronounceable words to defend against dictionary attacks, and Gestalt-motivated image-masking degradations to defend against image restoration attacks. Experiments on human subjects confirm the human legibility and user acceptance of BaffleText images. We have found an image-complexity measure that correlates well with user acceptance and assists in engineering the generation of challenges to fit the ability gap. Recent computer-vision attacks, run independently by Mori and Jitendra, suggest that BaffleText is stronger than two existing CAPTCHAs.

See You See Me: the Role of Eye Contact in Multimodal Human-Robot Interaction.

PubMed

Xu, Tian Linger; Zhang, Hui; Yu, Chen

2016-05-01

We focus on a fundamental looking behavior in human-robot interactions - gazing at each other's face. Eye contact and mutual gaze between two social partners are critical in smooth human-human interactions. Therefore, investigating at what moments and in what ways a robot should look at a human user's face as a response to the human's gaze behavior is an important topic. Toward this goal, we developed a gaze-contingent human-robot interaction system, which relied on momentary gaze behaviors from a human user to control an interacting robot in real time. Using this system, we conducted an experiment in which human participants interacted with the robot in a joint attention task. In the experiment, we systematically manipulated the robot's gaze toward the human partner's face in real time and then analyzed the human's gaze behavior as a response to the robot's gaze behavior. We found that more face looks from the robot led to more look-backs (to the robot's face) from human participants and consequently created more mutual gaze and eye contact between the two. Moreover, participants demonstrated more coordinated and synchronized multimodal behaviors between speech and gaze when more eye contact was successfully established and maintained.

Interaction studies reveal specific recognition of an anti-inflammatory polyphosphorhydrazone dendrimer by human monocytes

NASA Astrophysics Data System (ADS)

Ledall, Jérémy; Fruchon, Séverine; Garzoni, Matteo; Pavan, Giovanni M.; Caminade, Anne-Marie; Turrin, Cédric-Olivier; Blanzat, Muriel; Poupot, Rémy

2015-10-01

Dendrimers are nano-materials with perfectly defined structure and size, and multivalency properties that confer substantial advantages for biomedical applications. Previous work has shown that phosphorus-based polyphosphorhydrazone (PPH) dendrimers capped with azabisphosphonate (ABP) end groups have immuno-modulatory and anti-inflammatory properties leading to efficient therapeutic control of inflammatory diseases in animal models. These properties are mainly prompted through activation of monocytes. Here, we disclose new insights into the molecular mechanisms underlying the anti-inflammatory activation of human monocytes by ABP-capped PPH dendrimers. Following an interdisciplinary approach, we have characterized the physicochemical and biological behavior of the lead ABP dendrimer with model and cell membranes, and compared this experimental set of data to predictive computational modelling studies. The behavior of the ABP dendrimer was compared to the one of an isosteric analog dendrimer capped with twelve azabiscarboxylate (ABC) end groups instead of twelve ABP end groups. The ABC dendrimer displayed no biological activity on human monocytes, therefore it was considered as a negative control. In detail, we show that the ABP dendrimer can bind both non-specifically and specifically to the membrane of human monocytes. The specific binding leads to the internalization of the ABP dendrimer by human monocytes. On the contrary, the ABC dendrimer only interacts non-specifically with human monocytes and is not internalized. These data indicate that the bioactive ABP dendrimer is recognized by specific receptor(s) at the surface of human monocytes.Dendrimers are nano-materials with perfectly defined structure and size, and multivalency properties that confer substantial advantages for biomedical applications. Previous work has shown that phosphorus-based polyphosphorhydrazone (PPH) dendrimers capped with azabisphosphonate (ABP) end groups have immuno-modulatory and anti

An ecocultural model predicts Neanderthal extinction through competition with modern humans.

PubMed

Gilpin, William; Feldman, Marcus W; Aoki, Kenichi

2016-02-23

Archaeologists argue that the replacement of Neanderthals by modern humans was driven by interspecific competition due to a difference in culture level. To assess the cogency of this argument, we construct and analyze an interspecific cultural competition model based on the Lotka-Volterra model, which is widely used in ecology, but which incorporates the culture level of a species as a variable interacting with population size. We investigate the conditions under which a difference in culture level between cognitively equivalent species, or alternatively a difference in underlying learning ability, may produce competitive exclusion of a comparatively (although not absolutely) large local Neanderthal population by an initially smaller modern human population. We find, in particular, that this competitive exclusion is more likely to occur when population growth occurs on a shorter timescale than cultural change, or when the competition coefficients of the Lotka-Volterra model depend on the difference in the culture levels of the interacting species.

Tactile interactions activate mirror system regions in the human brain.

PubMed

McKyton, Ayelet

2011-12-07

Communicating with others is essential for the development of a society. Although types of communications, such as language and visual gestures, were thoroughly investigated in the past, little research has been done to investigate interactions through touch. To study this we used functional magnetic resonance imaging. Twelve participants were scanned with their eyes covered while stroking four kinds of items, representing different somatosensory stimuli: a human hand, a realistic rubber hand, an object, and a simple texture. Although the human and the rubber hands had the same overall shape, in three regions there was significantly more blood oxygen level dependent activation when touching the real hand: the anterior medial prefrontal cortex, the ventral premotor cortex, and the posterior superior temporal cortex. The last two regions are part of the mirror network and are known to be activated through visual interactions such as gestures. Interestingly, in this study, these areas were activated through a somatosensory interaction. A control experiment was performed to eliminate confounds of temperature, texture, and imagery, suggesting that the activation in these areas was correlated with the touch of a human hand. These results reveal the neuronal network working behind human tactile interactions, and highlight the participation of the mirror system in such functions.

[An interactive three-dimensional model of the human body].

PubMed

Liem, S L

2009-01-01

Driven by advanced computer technology, it is now possible to show the human anatomy on a computer. On the internet, the Visible Body programme makes it possible to navigate in all directions through the anatomical structures of the human body, using mouse and keyboard. Visible Body is a wonderful tool to give insight in the human structures, body functions and organs.

Human interaction as environmental enrichment for pair-housed wolves and wolf-dog crosses.

PubMed

Mehrkam, Lindsay R; Verdi, Nicolle T; Wynne, Clive D L

2014-01-01

Private nonhuman animal sanctuaries are often financially limited in their ability to implement traditional environmental enrichment strategies. One possible solution may be to provide socialized animals with human interaction sessions. However, the merit of human interaction as enrichment has received little empirical attention to date. The present study aimed to evaluate whether human interaction could be enriching for socialized, pair-housed wolves and wolf-dog crosses at a private sanctuary. Observations of each subject were conducted in a reversal design to measure species-typical affiliation, activity levels, and aberrant behaviors when caretakers were both present and absent. The results demonstrate significantly higher levels of conspecific-directed affiliation and activity levels and reduced aberrant behavior when human interaction was available. Social play also increased when caregivers were present, supporting the hypothesis that play among conspecifics may be maintained by positive changes in an animal's environment. The potential for human interaction to be established as a scientifically validated, cost-effective enrichment strategy is supported by these findings.

Study on intelligent processing system of man-machine interactive garment frame model

NASA Astrophysics Data System (ADS)

Chen, Shuwang; Yin, Xiaowei; Chang, Ruijiang; Pan, Peiyun; Wang, Xuedi; Shi, Shuze; Wei, Zhongqian

2018-05-01

A man-machine interactive garment frame model intelligent processing system is studied in this paper. The system consists of several sensor device, voice processing module, mechanical parts and data centralized acquisition devices. The sensor device is used to collect information on the environment changes brought by the body near the clothes frame model, the data collection device is used to collect the information of the environment change induced by the sensor device, voice processing module is used for speech recognition of nonspecific person to achieve human-machine interaction, mechanical moving parts are used to make corresponding mechanical responses to the information processed by data collection device.it is connected with data acquisition device by a means of one-way connection. There is a one-way connection between sensor device and data collection device, two-way connection between data acquisition device and voice processing module. The data collection device is one-way connection with mechanical movement parts. The intelligent processing system can judge whether it needs to interact with the customer, realize the man-machine interaction instead of the current rigid frame model.

Interactive vs. Non-Interactive Multi-Model Ensembles

NASA Astrophysics Data System (ADS)

Duane, G. S.

2013-12-01

If the members of an ensemble of different models are allowed to interact with one another in run time, predictive skill can be improved as compared to that of any individual model or any average of indvidual model outputs. Inter-model connections in such an interactive ensemble can be trained, using historical data, so that the resulting ``supermodel' synchronizes with reality when used in weather-prediction mode, where the individual models perform data assimilation from each other (with trainable inter-model 'observation error') as well as from real observations. In climate-projection mode, parameters of the individual models are changed, as might occur from an increase in GHG levels, and one obtains relevant statistical properties of the new supermodel attractor. In simple cases, it has been shown that training of the inter-model connections with the old parameter values gives a supermodel that is still predictive when the parameter values are changed. Here we inquire as to the circumstances under which supermodel performance can be expected to exceed that of the customary weighted average of model outputs. We consider a supermodel formed from quasigeostrophic (QG) channel models with different forcing coefficients, and introduce an effective training scheme for the inter-model connections. We show that the blocked-zonal index cycle is reproduced better by the supermodel than by any non-interactive ensemble in the extreme case where the forcing coefficients of the different models are very large or very small. With realistic differences in forcing coefficients, as would be representative of actual differences among IPCC-class models, the usual linearity assumption is justified and a weighted average of model outputs is adequate. It is therefore hypothesized that supermodeling is likely to be useful in situations where there are qualitative model differences, as arising from sub-gridscale parameterizations, that affect overall model behavior. Otherwise the usual

Engineering a humanized bone organ model in mice to study bone metastases.

PubMed