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.

Generating Phenotypical Erroneous Human Behavior to Evaluate Human-automation Interaction Using Model Checking

PubMed Central

Bolton, Matthew L.; Bass, Ellen J.; Siminiceanu, Radu I.

2012-01-01

Breakdowns in complex systems often occur as a result of system elements interacting in unanticipated ways. In systems with human operators, human-automation interaction associated with both normative and erroneous human behavior can contribute to such failures. Model-driven design and analysis techniques provide engineers with formal methods tools and techniques capable of evaluating how human behavior can contribute to system failures. This paper presents a novel method for automatically generating task analytic models encompassing both normative and erroneous human behavior from normative task models. The generated erroneous behavior is capable of replicating Hollnagel’s zero-order phenotypes of erroneous action for omissions, jumps, repetitions, and intrusions. Multiple phenotypical acts can occur in sequence, thus allowing for the generation of higher order phenotypes. The task behavior model pattern capable of generating erroneous behavior can be integrated into a formal system model so that system safety properties can be formally verified with a model checker. This allows analysts to prove that a human-automation interactive system (as represented by the model) will or will not satisfy safety properties with both normative and generated erroneous human behavior. We present benchmarks related to the size of the statespace and verification time of models to show how the erroneous human behavior generation process scales. We demonstrate the method with a case study: the operation of a radiation therapy machine. A potential problem resulting from a generated erroneous human action is discovered. A design intervention is presented which prevents this problem from occurring. We discuss how our method could be used to evaluate larger applications and recommend future paths of development. PMID:23105914

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

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…

The BioGRID interaction database: 2017 update

PubMed Central

Chatr-aryamontri, Andrew; Oughtred, Rose; Boucher, Lorrie; Rust, Jennifer; Chang, Christie; Kolas, Nadine K.; O'Donnell, Lara; Oster, Sara; Theesfeld, Chandra; Sellam, Adnane; Stark, Chris; Breitkreutz, Bobby-Joe; Dolinski, Kara; Tyers, Mike

2017-01-01

The Biological General Repository for Interaction Datasets (BioGRID: https://thebiogrid.org) is an open access database dedicated to the annotation and archival of protein, genetic and chemical interactions for all major model organism species and humans. As of September 2016 (build 3.4.140), the BioGRID contains 1 072 173 genetic and protein interactions, and 38 559 post-translational modifications, as manually annotated from 48 114 publications. This dataset represents interaction records for 66 model organisms and represents a 30% increase compared to the previous 2015 BioGRID update. BioGRID curates the biomedical literature for major model organism species, including humans, with a recent emphasis on central biological processes and specific human diseases. To facilitate network-based approaches to drug discovery, BioGRID now incorporates 27 501 chemical–protein interactions for human drug targets, as drawn from the DrugBank database. A new dynamic interaction network viewer allows the easy navigation and filtering of all genetic and protein interaction data, as well as for bioactive compounds and their established targets. BioGRID data are directly downloadable without restriction in a variety of standardized formats and are freely distributed through partner model organism databases and meta-databases. PMID:27980099

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...

A definitional framework for the human/biometric sensor interaction model

NASA Astrophysics Data System (ADS)

Elliott, Stephen J.; Kukula, Eric P.

2010-04-01

Existing definitions for biometric testing and evaluation do not fully explain errors in a biometric system. This paper provides a definitional framework for the Human Biometric-Sensor Interaction (HBSI) model. This paper proposes six new definitions based around two classifications of presentations, erroneous and correct. The new terms are: defective interaction (DI), concealed interaction (CI), false interaction (FI), failure to detect (FTD), failure to extract (FTX), and successfully acquired samples (SAS). As with all definitions, the new terms require a modification to the general biometric model developed by Mansfield and Wayman [1].

Evolutionary Agent-Based Simulation of the Introduction of New Technologies in Air Traffic Management

NASA Technical Reports Server (NTRS)

Yliniemi, Logan; Agogino, Adrian K.; Tumer, Kagan

2014-01-01

Accurate simulation of the effects of integrating new technologies into a complex system is critical to the modernization of our antiquated air traffic system, where there exist many layers of interacting procedures, controls, and automation all designed to cooperate with human operators. Additions of even simple new technologies may result in unexpected emergent behavior due to complex human/ machine interactions. One approach is to create high-fidelity human models coming from the field of human factors that can simulate a rich set of behaviors. However, such models are difficult to produce, especially to show unexpected emergent behavior coming from many human operators interacting simultaneously within a complex system. Instead of engineering complex human models, we directly model the emergent behavior by evolving goal directed agents, representing human users. Using evolution we can predict how the agent representing the human user reacts given his/her goals. In this paradigm, each autonomous agent in a system pursues individual goals, and the behavior of the system emerges from the interactions, foreseen or unforeseen, between the agents/actors. We show that this method reflects the integration of new technologies in a historical case, and apply the same methodology for a possible future technology.

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.

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.

Formulation of human-structure interaction system models for vertical vibration

NASA Astrophysics Data System (ADS)

Caprani, Colin C.; Ahmadi, Ehsan

2016-09-01

In this paper, human-structure interaction system models for vibration in the vertical direction are considered. This work assembles various moving load models from the literature and proposes extension of the single pedestrian to a crowd of pedestrians for the FE formulation for crowd-structure interaction systems. The walking pedestrian vertical force is represented as a general time-dependent force, and the pedestrian is in turn modelled as moving force, moving mass, and moving spring-mass-damper. The arbitrary beam structure is modelled using either a formulation in modal coordinates or finite elements. In each case, the human-structure interaction (HSI) system is first formulated for a single walking pedestrian and then extended to consider a crowd of pedestrians. Finally, example applications for single pedestrian and crowd loading scenarios are examined. It is shown how the models can be used to quantify the interaction between the crowd and bridge structure. This work should find use for the evaluation of existing and new footbridges.

Human Factors Considerations in System Design

NASA Technical Reports Server (NTRS)

Mitchell, C. M. (Editor); Vanbalen, P. M. (Editor); Moe, K. L. (Editor)

1983-01-01

Human factors considerations in systems design was examined. Human factors in automated command and control, in the efficiency of the human computer interface and system effectiveness are outlined. The following topics are discussed: human factors aspects of control room design; design of interactive systems; human computer dialogue, interaction tasks and techniques; guidelines on ergonomic aspects of control rooms and highly automated environments; system engineering for control by humans; conceptual models of information processing; information display and interaction in real time environments.

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.

Intelligent Context-Aware and Adaptive Interface for Mobile LBS

PubMed Central

Liu, Yanhong

2015-01-01

Context-aware user interface plays an important role in many human-computer Interaction tasks of location based services. Although spatial models for context-aware systems have been studied extensively, how to locate specific spatial information for users is still not well resolved, which is important in the mobile environment where location based services users are impeded by device limitations. Better context-aware human-computer interaction models of mobile location based services are needed not just to predict performance outcomes, such as whether people will be able to find the information needed to complete a human-computer interaction task, but to understand human processes that interact in spatial query, which will in turn inform the detailed design of better user interfaces in mobile location based services. In this study, a context-aware adaptive model for mobile location based services interface is proposed, which contains three major sections: purpose, adjustment, and adaptation. Based on this model we try to describe the process of user operation and interface adaptation clearly through the dynamic interaction between users and the interface. Then we show how the model applies users' demands in a complicated environment and suggested the feasibility by the experimental results. PMID:26457077

Space station crew safety: Human factors interaction model

NASA Technical Reports Server (NTRS)

Cohen, M. M.; Junge, M. K.

1985-01-01

A model of the various human factors issues and interactions that might affect crew safety is developed. The first step addressed systematically the central question: How is this space station different from all other spacecraft? A wide range of possible issue was identified and researched. Five major topics of human factors issues that interacted with crew safety resulted: Protocols, Critical Habitability, Work Related Issues, Crew Incapacitation and Personal Choice. Second, an interaction model was developed that would show some degree of cause and effect between objective environmental or operational conditions and the creation of potential safety hazards. The intermediary steps between these two extremes of causality were the effects on human performance and the results of degraded performance. The model contains three milestones: stressor, human performance (degraded) and safety hazard threshold. Between these milestones are two countermeasure intervention points. The first opportunity for intervention is the countermeasure against stress. If this countermeasure fails, performance degrades. The second opportunity for intervention is the countermeasure against error. If this second countermeasure fails, the threshold of a potential safety hazard may be crossed.

Implicit prosody mining based on the human eye image capture technology

NASA Astrophysics Data System (ADS)

Gao, Pei-pei; Liu, Feng

2013-08-01

The technology of eye tracker has become the main methods of analyzing the recognition issues in human-computer interaction. Human eye image capture is the key problem of the eye tracking. Based on further research, a new human-computer interaction method introduced to enrich the form of speech synthetic. We propose a method of Implicit Prosody mining based on the human eye image capture technology to extract the parameters from the image of human eyes when reading, control and drive prosody generation in speech synthesis, and establish prosodic model with high simulation accuracy. Duration model is key issues for prosody generation. For the duration model, this paper put forward a new idea for obtaining gaze duration of eyes when reading based on the eye image capture technology, and synchronous controlling this duration and pronunciation duration in speech synthesis. The movement of human eyes during reading is a comprehensive multi-factor interactive process, such as gaze, twitching and backsight. Therefore, how to extract the appropriate information from the image of human eyes need to be considered and the gaze regularity of eyes need to be obtained as references of modeling. Based on the analysis of current three kinds of eye movement control model and the characteristics of the Implicit Prosody reading, relative independence between speech processing system of text and eye movement control system was discussed. It was proved that under the same text familiarity condition, gaze duration of eyes when reading and internal voice pronunciation duration are synchronous. The eye gaze duration model based on the Chinese language level prosodic structure was presented to change previous methods of machine learning and probability forecasting, obtain readers' real internal reading rhythm and to synthesize voice with personalized rhythm. This research will enrich human-computer interactive form, and will be practical significance and application prospect in terms of disabled assisted speech interaction. Experiments show that Implicit Prosody mining based on the human eye image capture technology makes the synthesized speech has more flexible expressions.

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.

Quantitative Modeling of Human-Environment Interactions in Preindustrial Time

NASA Astrophysics Data System (ADS)

Sommer, Philipp S.; Kaplan, Jed O.

2017-04-01

Quantifying human-environment interactions and anthropogenic influences on the environment prior to the Industrial revolution is essential for understanding the current state of the earth system. This is particularly true for the terrestrial biosphere, but marine ecosystems and even climate were likely modified by human activities centuries to millennia ago. Direct observations are however very sparse in space and time, especially as one considers prehistory. Numerical models are therefore essential to produce a continuous picture of human-environment interactions in the past. Agent-based approaches, while widely applied to quantifying human influence on the environment in localized studies, are unsuitable for global spatial domains and Holocene timescales because of computational demands and large parameter uncertainty. Here we outline a new paradigm for the quantitative modeling of human-environment interactions in preindustrial time that is adapted to the global Holocene. Rather than attempting to simulate agency directly, the model is informed by a suite of characteristics describing those things about society that cannot be predicted on the basis of environment, e.g., diet, presence of agriculture, or range of animals exploited. These categorical data are combined with the properties of the physical environment in coupled human-environment model. The model is, at its core, a dynamic global vegetation model with a module for simulating crop growth that is adapted for preindustrial agriculture. This allows us to simulate yield and calories for feeding both humans and their domesticated animals. We couple this basic caloric availability with a simple demographic model to calculate potential population, and, constrained by labor requirements and land limitations, we create scenarios of land use and land cover on a moderate-resolution grid. We further implement a feedback loop where anthropogenic activities lead to changes in the properties of the physical environment, e.g., through soil erosion.

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.

Interactive locomotion: Investigation and modeling of physically-paired humans while walking

PubMed Central

Le Goff, Camille G.; Ijspeert, Auke Jan

2017-01-01

In spite of extensive studies on human walking, less research has been conducted on human walking gait adaptation during interaction with another human. In this paper, we study a particular case of interactive locomotion where two humans carry a rigid object together. Experimental data from two persons walking together, one in front of the other, while carrying a stretcher-like object is presented, and the adaptation of their walking gaits and coordination of the foot-fall patterns are analyzed. It is observed that in more than 70% of the experiments the subjects synchronize their walking gaits; it is shown that these walking gaits can be associated to quadrupedal gaits. Moreover, in order to understand the extent by which the passive dynamics can explain this synchronization behaviour, a simple 2D model, made of two-coupled spring-loaded inverted pendulums, is developed, and a comparison between the experiments and simulations with this model is presented, showing that with this simple model we are able to reproduce some aspects of human walking behaviour when paired with another human. PMID:28877161

Revenue Prediction of a Local Event Using the Mathematical Model of Hit Phenomena

NASA Astrophysics Data System (ADS)

Ishii, A.; Matsumoto, T.; Miki, S.

We propose a theoretical approach to investigate human-humaninteraction in the society, which uses a many-body theory that incorporates human-human interaction. We treat advertisement as an external force, and include the word of mouth (WOM) effect as a two-body interaction between humans and the rumor effect as a three-body interaction among humans. The parameters to define the strength of human interactions are assumed to be constant values. The calculated result explained well the two local events ``Mizuki-Shigeru Road in Sakaiminato" and ``the sculpture festival at Tottori" in Japan.

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…

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.

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

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.

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

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.

Kernel Method Based Human Model for Enhancing Interactive Evolutionary Optimization

PubMed Central

Zhao, Qiangfu; Liu, Yong

2015-01-01

A fitness landscape presents the relationship between individual and its reproductive success in evolutionary computation (EC). However, discrete and approximate landscape in an original search space may not support enough and accurate information for EC search, especially in interactive EC (IEC). The fitness landscape of human subjective evaluation in IEC is very difficult and impossible to model, even with a hypothesis of what its definition might be. In this paper, we propose a method to establish a human model in projected high dimensional search space by kernel classification for enhancing IEC search. Because bivalent logic is a simplest perceptual paradigm, the human model is established by considering this paradigm principle. In feature space, we design a linear classifier as a human model to obtain user preference knowledge, which cannot be supported linearly in original discrete search space. The human model is established by this method for predicting potential perceptual knowledge of human. With the human model, we design an evolution control method to enhance IEC search. From experimental evaluation results with a pseudo-IEC user, our proposed model and method can enhance IEC search significantly. PMID:25879050

Multilevel depth and image fusion for human activity detection.

PubMed

Ni, Bingbing; Pei, Yong; Moulin, Pierre; Yan, Shuicheng

2013-10-01

Recognizing complex human activities usually requires the detection and modeling of individual visual features and the interactions between them. Current methods only rely on the visual features extracted from 2-D images, and therefore often lead to unreliable salient visual feature detection and inaccurate modeling of the interaction context between individual features. In this paper, we show that these problems can be addressed by combining data from a conventional camera and a depth sensor (e.g., Microsoft Kinect). We propose a novel complex activity recognition and localization framework that effectively fuses information from both grayscale and depth image channels at multiple levels of the video processing pipeline. In the individual visual feature detection level, depth-based filters are applied to the detected human/object rectangles to remove false detections. In the next level of interaction modeling, 3-D spatial and temporal contexts among human subjects or objects are extracted by integrating information from both grayscale and depth images. Depth information is also utilized to distinguish different types of indoor scenes. Finally, a latent structural model is developed to integrate the information from multiple levels of video processing for an activity detection. Extensive experiments on two activity recognition benchmarks (one with depth information) and a challenging grayscale + depth human activity database that contains complex interactions between human-human, human-object, and human-surroundings demonstrate the effectiveness of the proposed multilevel grayscale + depth fusion scheme. Higher recognition and localization accuracies are obtained relative to the previous methods.

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.

Traffic and Driving Simulator Based on Architecture of Interactive Motion.

PubMed

Paz, Alexander; Veeramisti, Naveen; Khaddar, Romesh; de la Fuente-Mella, Hanns; Modorcea, Luiza

2015-01-01

This study proposes an architecture for an interactive motion-based traffic simulation environment. In order to enhance modeling realism involving actual human beings, the proposed architecture integrates multiple types of simulation, including: (i) motion-based driving simulation, (ii) pedestrian simulation, (iii) motorcycling and bicycling simulation, and (iv) traffic flow simulation. The architecture has been designed to enable the simulation of the entire network; as a result, the actual driver, pedestrian, and bike rider can navigate anywhere in the system. In addition, the background traffic interacts with the actual human beings. This is accomplished by using a hybrid mesomicroscopic traffic flow simulation modeling approach. The mesoscopic traffic flow simulation model loads the results of a user equilibrium traffic assignment solution and propagates the corresponding traffic through the entire system. The microscopic traffic flow simulation model provides background traffic around the vicinities where actual human beings are navigating the system. The two traffic flow simulation models interact continuously to update system conditions based on the interactions between actual humans and the fully simulated entities. Implementation efforts are currently in progress and some preliminary tests of individual components have been conducted. The implementation of the proposed architecture faces significant challenges ranging from multiplatform and multilanguage integration to multievent communication and coordination.

Traffic and Driving Simulator Based on Architecture of Interactive Motion

PubMed Central

Paz, Alexander; Veeramisti, Naveen; Khaddar, Romesh; de la Fuente-Mella, Hanns; Modorcea, Luiza

2015-01-01

This study proposes an architecture for an interactive motion-based traffic simulation environment. In order to enhance modeling realism involving actual human beings, the proposed architecture integrates multiple types of simulation, including: (i) motion-based driving simulation, (ii) pedestrian simulation, (iii) motorcycling and bicycling simulation, and (iv) traffic flow simulation. The architecture has been designed to enable the simulation of the entire network; as a result, the actual driver, pedestrian, and bike rider can navigate anywhere in the system. In addition, the background traffic interacts with the actual human beings. This is accomplished by using a hybrid mesomicroscopic traffic flow simulation modeling approach. The mesoscopic traffic flow simulation model loads the results of a user equilibrium traffic assignment solution and propagates the corresponding traffic through the entire system. The microscopic traffic flow simulation model provides background traffic around the vicinities where actual human beings are navigating the system. The two traffic flow simulation models interact continuously to update system conditions based on the interactions between actual humans and the fully simulated entities. Implementation efforts are currently in progress and some preliminary tests of individual components have been conducted. The implementation of the proposed architecture faces significant challenges ranging from multiplatform and multilanguage integration to multievent communication and coordination. PMID:26491711

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.

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.

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.

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.

Unfolding large-scale online collaborative human dynamics

PubMed Central

Zha, Yilong; Zhou, Tao; Zhou, Changsong

2016-01-01

Large-scale interacting human activities underlie all social and economic phenomena, but quantitative understanding of regular patterns and mechanism is very challenging and still rare. Self-organized online collaborative activities with a precise record of event timing provide unprecedented opportunity. Our empirical analysis of the history of millions of updates in Wikipedia shows a universal double–power-law distribution of time intervals between consecutive updates of an article. We then propose a generic model to unfold collaborative human activities into three modules: (i) individual behavior characterized by Poissonian initiation of an action, (ii) human interaction captured by a cascading response to previous actions with a power-law waiting time, and (iii) population growth due to the increasing number of interacting individuals. This unfolding allows us to obtain an analytical formula that is fully supported by the universal patterns in empirical data. Our modeling approaches reveal “simplicity” beyond complex interacting human activities. PMID:27911766

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.

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

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. ...

A system dynamics model of human-water interaction in anthropogenic droughts

NASA Astrophysics Data System (ADS)

Blair, Peter; Buytaert, Wouter

2016-04-01

Modelling is set to be a key part of socio-hydrology's quest to understand the dynamics and long-term consequences of human-water interactions. As a subject in its infancy, still learning the questions to ask, conceptual models are of particular use in trying to understand the general nature of human-water systems. The conceptual model of Di Baldassarre et al. (2013), which investigates human-flood interactions, has been widely discussed, prompting great steps forward in understanding and coverage of socio-hydrology. The development of further conceptual models could generate further discussion and understanding. Flooding is one archetypal example of a system of human-water interaction; another is the case of water stress and drought. There has been a call to recognise and understand anthropogenic drought (Aghakouchak et al. 2015), and so this study investigates the nature of the socio-hydrological dynamics involved in these situations. Here we present a system dynamics model to simulate human-water interactions in the context of water-stressed areas, where drought is induced via a combination of lower than usual water availability and relatively high water use. It is designed based on an analysis of several case-studies where recent droughts have occurred, or where the prospect of drought looms. The locations investigated are Spain, Southeast Brazil, Northeast China and California. The numerical system dynamics model is based on causal loop, and stocks and flows diagrams, which are in turn developed from the qualitative analysis of the different cases studied. The study uses a comparative approach, which has the advantage of eliciting general system characteristics from the similarities between cases, while using the differences to determine the important factors which lead to different system behaviours. References: Aghakouchak, A., Feldman, D., Hoerling, M., Huxman, T., Lund, J., 2015. Recognize anthropogenic drought. Nature, 524, pp.409-411. Di Baldassarre, G., Viglione, A., Carr, G., Kuil, L., Salinas, J. L., Blöschl, G., 2013. Socio-hydrology: conceptualising human-flood interactions. Hydrology and Earth System Sciences, 17(8), pp.3295-3303. Available at: http://www.hydrol-earth-syst-sci.net/17/3295/2013/ [Accessed August 8, 2014].

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.

Least-cost transportation networks predict spatial interaction of invasion vectors.

PubMed

Drake, D Andrew R; Mandrak, Nicholas E

2010-12-01

Human-mediated dispersal among aquatic ecosystems often results in biotic transfer between drainage basins. Such activities may circumvent biogeographic factors, with considerable ecological, evolutionary, and economic implications. However, the efficacy of predictions concerning community changes following inter-basin movements are limited, often because the dispersal mechanism is poorly understood (e.g., quantified only partially). To date, spatial-interaction models that predict the movement of humans as vectors of biotic transfer have not incorporated patterns of human movement through transportation networks. As a necessary first step to determine the role of anglers as invasion vectors across a land-lake ecosystem, we investigate their movement potential within Ontario, Canada. To determine possible model improvements resulting from inclusion of network travel, spatial-interaction models were constructed using standard Euclidean (e.g., straight-line) distance measures and also with distances derived from least-cost routing of human transportation networks. Model comparisons determined that least-cost routing both provided the most parsimonious model and also excelled at forecasting spatial interactions, with a proportion of 0.477 total movement deviance explained. The distribution of movements was characterized by many relatively short to medium travel distances (median = 292.6 km) with fewer lengthier distances (75th percentile = 484.6 km, 95th percentile = 775.2 km); however, even the shortest movements were sufficient to overcome drainage-basin boundaries. Ranking of variables in order of their contribution within the most parsimonious model determined that distance traveled, origin outflow, lake attractiveness, and sportfish richness significantly influence movement patterns. Model improvements associated with least-cost routing of human transportation networks imply that patterns of human-mediated invasion are fundamentally linked to the spatial configuration and relative impedance of human transportation networks, placing increased importance on understanding their contribution to the invasion process.

Radiation doses and neutron irridation effects on human cells based on calculations

NASA Astrophysics Data System (ADS)

Radojevic, B. B.; Cukavac, M.; Jovanovic, D.

In general, main aim of our paper is to follow influence of neutron's radiation on materials, but one of possible applications of fast neutrons in therapeutical reasons i.e. their influence on carcinom cells of difficuilt geometries in human bodies too. Interactions between neutrons and human cells of tissue are analysed here. We know that the light nuclei of hydrogen, nitrogen, carbon, and oxygen are main constituents of human cells, and that different nuclear models are usually used to present interactions of nuclear particles with mentioned elements. Some of most widely used pre-equilibrium nuclear models are: intranuclear cascade model (ICN), Harp-Miller-Berne (HMB), geometry-dependent hybrid (GDH) and exciton models (EM). In this paper is studied and calculated the primary energetic spectra of the secundary particles (neutrons, protons, and gamas) emitted from this interactions, and followed by corresponding integral cross sections, based on exciton model (EM). The total emission cross-section is the sum of emissions in all stages of energies. Obtained spectra for interactions type of (n, n'), (n, p), and (n, ?), for various incident neutron energies in the interval from 3 MeV up to 30 MeV are analysed too. Some results of calculations are presented here.

Learning Analytics for Networked Learning Models

ERIC Educational Resources Information Center

Joksimovic, Srecko; Hatala, Marek; Gaševic, Dragan

2014-01-01

Teaching and learning in networked settings has attracted significant attention recently. The central topic of networked learning research is human-human and human-information interactions occurring within a networked learning environment. The nature of these interactions is highly complex and usually requires a multi-dimensional approach to…

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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.

The human factors of workstation telepresence

NASA Technical Reports Server (NTRS)

Smith, Thomas J.; Smith, Karl U.

1990-01-01

The term workstation telepresence has been introduced to describe human-telerobot compliance, which enables the human operator to effectively project his/her body image and behavioral skills to control of the telerobot itself. Major human-factors considerations for establishing high fidelity workstation telepresence during human-telerobot operation are discussed. Telerobot workstation telepresence is defined by the proficiency and skill with which the operator is able to control sensory feedback from direct interaction with the workstation itself, and from workstation-mediated interaction with the telerobot. Numerous conditions influencing such control have been identified. This raises the question as to what specific factors most critically influence the realization of high fidelity workstation telepresence. The thesis advanced here is that perturbations in sensory feedback represent a major source of variability in human performance during interactive telerobot operation. Perturbed sensory feedback research over the past three decades has established that spatial transformations or temporal delays in sensory feedback engender substantial decrements in interactive task performance, which training does not completely overcome. A recently developed social cybernetic model of human-computer interaction can be used to guide this approach, based on computer-mediated tracking and control of sensory feedback. How the social cybernetic model can be employed for evaluating the various modes, patterns, and integrations of interpersonal, team, and human-computer interactions which play a central role is workstation telepresence are discussed.

What, if anything, can monkeys tell us about human amnesia when they can’t say anything at all?

PubMed Central

Murray, Elisabeth A.; Wise, Steven P.

2010-01-01

Despite a half century of development, the orthodox monkey model of human amnesia needs improvement, in part because of two problems inherent in animal models of advanced human cognition. First, animal models are perforce comparative, but the principles of comparative and evolutionary biology have not featured prominently in developing the orthodox model. Second, no one understands the relationship between human consciousness and cognition in other animals, but the orthodox model implicitly assumes a close correspondence. If we treat these two difficulties with the deference they deserve, monkeys can tell us a lot about human amnesia and memory. Three future contributions seem most likely: (1) an improved monkey model, one refocused on the hippocampus rather than on the medial temporal lobe as a whole; (2) a better understanding of cortical areas unique to primates, especially the granular prefrontal cortex; and (3), taking the two together, insight into prefrontal-hippocampal interactions. We propose that interactions among the granular prefrontal areas create the kind of cross-domain, analogical and self-referential knowledge that underlies advanced cognition in modern humans. When these products of frontal-lobe function interact with the hippocampus, and its ancestral function in navigation, what emerges is the human ability to embed ourselves in scenarios — real and imagined, self-generated and received — thereby creating a coherent, conscious life experience. PMID:20097215

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

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.

Human performance interfaces in air traffic control.

PubMed

Chang, Yu-Hern; Yeh, Chung-Hsing

2010-01-01

This paper examines how human performance factors in air traffic control (ATC) affect each other through their mutual interactions. The paper extends the conceptual SHEL model of ergonomics to describe the ATC system as human performance interfaces in which the air traffic controllers interact with other human performance factors including other controllers, software, hardware, environment, and organisation. New research hypotheses about the relationships between human performance interfaces of the system are developed and tested on data collected from air traffic controllers, using structural equation modelling. The research result suggests that organisation influences play a more significant role than individual differences or peer influences on how the controllers interact with the software, hardware, and environment of the ATC system. There are mutual influences between the controller-software, controller-hardware, controller-environment, and controller-organisation interfaces of the ATC system, with the exception of the controller-controller interface. Research findings of this study provide practical insights in managing human performance interfaces of the ATC system in the face of internal or external change, particularly in understanding its possible consequences in relation to the interactions between human performance factors.

Evidence for a bimodal distribution in human communication.

PubMed

Wu, Ye; Zhou, Changsong; Xiao, Jinghua; Kurths, Jürgen; Schellnhuber, Hans Joachim

2010-11-02

Interacting human activities underlie the patterns of many social, technological, and economic phenomena. Here we present clear empirical evidence from Short Message correspondence that observed human actions are the result of the interplay of three basic ingredients: Poisson initiation of tasks and decision making for task execution in individual humans as well as interaction among individuals. This interplay leads to new types of interevent time distribution, neither completely Poisson nor power-law, but a bimodal combination of them. We show that the events can be separated into independent bursts which are generated by frequent mutual interactions in short times following random initiations of communications in longer times by the individuals. We introduce a minimal model of two interacting priority queues incorporating the three basic ingredients which fits well the distributions using the parameters extracted from the empirical data. The model can also embrace a range of realistic social interacting systems such as e-mail and letter communications when taking the time scale of processing into account. Our findings provide insight into various human activities both at the individual and network level. Our analysis and modeling of bimodal activity in human communication from the viewpoint of the interplay between processes of different time scales is likely to shed light on bimodal phenomena in other complex systems, such as interevent times in earthquakes, rainfall, forest fire, and economic systems, etc.

Evidence for a bimodal distribution in human communication

PubMed Central

Wu, Ye; Zhou, Changsong; Xiao, Jinghua; Kurths, Jürgen; Schellnhuber, Hans Joachim

2010-01-01

Interacting human activities underlie the patterns of many social, technological, and economic phenomena. Here we present clear empirical evidence from Short Message correspondence that observed human actions are the result of the interplay of three basic ingredients: Poisson initiation of tasks and decision making for task execution in individual humans as well as interaction among individuals. This interplay leads to new types of interevent time distribution, neither completely Poisson nor power-law, but a bimodal combination of them. We show that the events can be separated into independent bursts which are generated by frequent mutual interactions in short times following random initiations of communications in longer times by the individuals. We introduce a minimal model of two interacting priority queues incorporating the three basic ingredients which fits well the distributions using the parameters extracted from the empirical data. The model can also embrace a range of realistic social interacting systems such as e-mail and letter communications when taking the time scale of processing into account. Our findings provide insight into various human activities both at the individual and network level. Our analysis and modeling of bimodal activity in human communication from the viewpoint of the interplay between processes of different time scales is likely to shed light on bimodal phenomena in other complex systems, such as interevent times in earthquakes, rainfall, forest fire, and economic systems, etc. PMID:20959414

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.

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

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.

Engineering stromal-epithelial interactions in vitro for ...

EPA Pesticide Factsheets

Background: Crosstalk between epithelial and stromal cells drives the morphogenesis of ectodermal organs during development and promotes normal mature adult epithelial tissue function. Epithelial-mesenchymal interactions (EMIs) have been examined using mammalian models, ex vivo tissue recombination, and in vitro co-cultures. Although these approaches have elucidated signaling mechanisms underlying morphogenetic processes and adult mammalian epithelial tissue function, they are limited by the availability of human tissue, low throughput, and human developmental or physiological relevance. Objectives: Bioengineering strategies to promote EMIs using human epithelial and mesenchymal cells have enabled the development of human in vitro models of adult epidermal and glandular tissues. In this review, we describe recent bioengineered models of human epithelial tissue and organs that can instruct the design of organotypic models of human developmental processes.Methods: We reviewed current bioengineering literature and here describe how bioengineered EMIs have enabled the development of human in vitro epithelial tissue models.Discussion: Engineered models to promote EMIs have recapitulated the architecture, phenotype, and function of adult human epithelial tissue, and similar engineering principles could be used to develop models of developmental morphogenesis. We describe how bioengineering strategies including bioprinting and spheroid culture could be implemented to

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.

Biomechanical modeling and load-carrying simulation of lower limb exoskeleton.

PubMed

Zhu, Yanhe; Zhang, Guoan; Zhang, Chao; Liu, Gangfeng; Zhao, Jie

2015-01-01

This paper introduces novel modern equipment-a lower extremity exoskeleton, which can implement the mutual complement and the interaction between human intelligence and the robot's mechanical strength. In order to provide a reference for the exoskeleton structure and the drive unit, the human biomechanics were modeled and analyzed by LifeModeler and Adams software to derive each joint kinematic parameter. The control was designed to implement the zero-force interaction between human and exoskeleton. Furthermore, simulations were performed to verify the control and assist effect. In conclusion, the system scheme of lower extremity exoskeleton is demonstrated to be feasible.

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/ .

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.

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 caused by known mutations and chromosomal aberrations. Notably, such a human brain model will be a versatile tool for more complex testing platforms and strategies as well as research into central nervous system physiology and pathology. PMID:24564953

Recent technology products from Space Human Factors research

NASA Technical Reports Server (NTRS)

Jenkins, James P.

1991-01-01

The goals of the NASA Space Human Factors program and the research carried out concerning human factors are discussed with emphasis given to the development of human performance models, data, and tools. The major products from this program are described, which include the Laser Anthropometric Mapping System; a model of the human body for evaluating the kinematics and dynamics of human motion and strength in microgravity environment; an operational experience data base for verifying and validating the data repository of manned space flights; the Operational Experience Database Taxonomy; and a human-computer interaction laboratory whose products are the display softaware and requirements and the guideline documents and standards for applications on human-computer interaction. Special attention is given to the 'Convoltron', a prototype version of a signal processor for synthesizing the head-related transfer functions.

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…

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 promote the development of user-centered failure-handling strategies for HRIs.

Kinetic Analyses of Data from a Human Serum Albumin Assay Using the liSPR System.

PubMed

Henseleit, Anja; Pohl, Carolin; Kaltenbach, Hans-Michael; Hettwer, Karina; Simon, Kirsten; Uhlig, Steffen; Haustein, Natalie; Bley, Thomas; Boschke, Elke

2015-01-19

We used the interaction between human serum albumin (HSA) and a high-affinity antibody to evaluate binding affinity measurements by the bench-top liSPR system (capitalis technology GmbH). HSA was immobilized directly onto a carboxylated sensor layer, and the mechanism of interaction between the antibody and HSA was investigated. The bivalence and heterogeneity of the antibody caused a complex binding mechanism. Three different interaction models (1:1 binding, heterogeneous analyte, bivalent analyte) were compared, and the bivalent analyte model best fit the curves obtained from the assay. This model describes the interaction of a bivalent analyte with one or two ligands (A + L ↔ LA + L ↔ LLA). The apparent binding affinity for this model measured 37 pM for the first reaction step, and 20 pM for the second step.

Kinetic Analyses of Data from a Human Serum Albumin Assay Using the liSPR System

PubMed Central

Henseleit, Anja; Pohl, Carolin; Kaltenbach, Hans-Michael; Hettwer, Karina; Simon, Kirsten; Uhlig, Steffen; Haustein, Natalie; Bley, Thomas; Boschke, Elke

2015-01-01

We used the interaction between human serum albumin (HSA) and a high-affinity antibody to evaluate binding affinity measurements by the bench-top liSPR system (capitalis technology GmbH). HSA was immobilized directly onto a carboxylated sensor layer, and the mechanism of interaction between the antibody and HSA was investigated. The bivalence and heterogeneity of the antibody caused a complex binding mechanism. Three different interaction models (1:1 binding, heterogeneous analyte, bivalent analyte) were compared, and the bivalent analyte model best fit the curves obtained from the assay. This model describes the interaction of a bivalent analyte with one or two ligands (A + L ↔ LA + L ↔ LLA). The apparent binding affinity for this model measured 37 pM for the first reaction step, and 20 pM for the second step. PMID:25607476

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

Reflection of a Year Long Model-Driven Business and UI Modeling Development Project

NASA Astrophysics Data System (ADS)

Sukaviriya, Noi; Mani, Senthil; Sinha, Vibha

Model-driven software development enables users to specify an application at a high level - a level that better matches problem domain. It also promises the users with better analysis and automation. Our work embarks on two collaborating domains - business process and human interactions - to build an application. Business modeling expresses business operations and flows then creates business flow implementation. Human interaction modeling expresses a UI design, its relationship with business data, logic, and flow, and can generate working UI. This double modeling approach automates the production of a working system with UI and business logic connected. This paper discusses the human aspects of this modeling approach after a year long of building a procurement outsourcing contract application using the approach - the result of which was deployed in December 2008. The paper discusses in multiple areas the happy endings and some heartache. We end with insights on how a model-driven approach could do better for humans in the process.

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

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.

Shear Forces during Blast, Not Abrupt Changes in Pressure Alone, Generate Calcium Activity in Human Brain Cells

DTIC Science & Technology

2012-06-29

the tissue-force interaction(s) and the cellular damage properties remain unresolved. Studies on a mechanical head model demonstrated high transient...that pressure transient. In vitro models of primary blast injury [5,18,19] are likewise limited by an absence of real-time, high spatial and temporal... models , as well as with human injuries in which expression of bTBI symptoms among different individuals that are exposed to the same blast is

Brain-Computer Interfaces: A Neuroscience Paradigm of Social Interaction? A Matter of Perspective

PubMed Central

Mattout, Jérémie

2012-01-01

A number of recent studies have put human subjects in true social interactions, with the aim of better identifying the psychophysiological processes underlying social cognition. Interestingly, this emerging Neuroscience of Social Interactions (NSI) field brings up challenges which resemble important ones in the field of Brain-Computer Interfaces (BCI). Importantly, these challenges go beyond common objectives such as the eventual use of BCI and NSI protocols in the clinical domain or common interests pertaining to the use of online neurophysiological techniques and algorithms. Common fundamental challenges are now apparent and one can argue that a crucial one is to develop computational models of brain processes relevant to human interactions with an adaptive agent, whether human or artificial. Coupled with neuroimaging data, such models have proved promising in revealing the neural basis and mental processes behind social interactions. Similar models could help BCI to move from well-performing but offline static machines to reliable online adaptive agents. This emphasizes a social perspective to BCI, which is not limited to a computational challenge but extends to all questions that arise when studying the brain in interaction with its environment. PMID:22675291

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.

Standardised animal models of host microbial mutualism

PubMed Central

Macpherson, A J; McCoy, K D

2015-01-01

An appreciation of the importance of interactions between microbes and multicellular organisms is currently driving research in biology and biomedicine. Many human diseases involve interactions between the host and the microbiota, so investigating the mechanisms involved is important for human health. Although microbial ecology measurements capture considerable diversity of the communities between individuals, this diversity is highly problematic for reproducible experimental animal models that seek to establish the mechanistic basis for interactions within the overall host-microbial superorganism. Conflicting experimental results may be explained away through unknown differences in the microbiota composition between vivaria or between the microenvironment of different isolated cages. In this position paper, we propose standardised criteria for stabilised and defined experimental animal microbiotas to generate reproducible models of human disease that are suitable for systematic experimentation and are reproducible across different institutions. PMID:25492472

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.

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.

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:…

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

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 interactions (TIs) in yeast, and may be applied to infer TIs in other organisms. The predicted genetic interactions of a subnetwork of human T-cell apoptosis coincide with existing partial pathways, suggesting the potential of GASA on inferring biochemical pathways.

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).

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.

From Here to Autonomy.

PubMed

Endsley, Mica R

2017-02-01

As autonomous and semiautonomous systems are developed for automotive, aviation, cyber, robotics and other applications, the ability of human operators to effectively oversee and interact with them when needed poses a significant challenge. An automation conundrum exists in which as more autonomy is added to a system, and its reliability and robustness increase, the lower the situation awareness of human operators and the less likely that they will be able to take over manual control when needed. The human-autonomy systems oversight model integrates several decades of relevant autonomy research on operator situation awareness, out-of-the-loop performance problems, monitoring, and trust, which are all major challenges underlying the automation conundrum. Key design interventions for improving human performance in interacting with autonomous systems are integrated in the model, including human-automation interface features and central automation interaction paradigms comprising levels of automation, adaptive automation, and granularity of control approaches. Recommendations for the design of human-autonomy interfaces are presented and directions for future research discussed.

Variable responses of human and non-human primate gut microbiomes to a Western diet.

PubMed

Amato, Katherine R; Yeoman, Carl J; Cerda, Gabriela; Schmitt, Christopher A; Cramer, Jennifer Danzy; Miller, Margret E Berg; Gomez, Andres; Turner, Trudy R; Wilson, Brenda A; Stumpf, Rebecca M; Nelson, Karen E; White, Bryan A; Knight, Rob; Leigh, Steven R

2015-11-16

The human gut microbiota interacts closely with human diet and physiology. To better understand the mechanisms behind this relationship, gut microbiome research relies on complementing human studies with manipulations of animal models, including non-human primates. However, due to unique aspects of human diet and physiology, it is likely that host-gut microbe interactions operate differently in humans and non-human primates. Here, we show that the human microbiome reacts differently to a high-protein, high-fat Western diet than that of a model primate, the African green monkey, or vervet (Chlorocebus aethiops sabaeus). Specifically, humans exhibit increased relative abundance of Firmicutes and reduced relative abundance of Prevotella on a Western diet while vervets show the opposite pattern. Predictive metagenomics demonstrate an increased relative abundance of genes associated with carbohydrate metabolism in the microbiome of only humans consuming a Western diet. These results suggest that the human gut microbiota has unique properties that are a result of changes in human diet and physiology across evolution or that may have contributed to the evolution of human physiology. Therefore, the role of animal models for understanding the relationship between the human gut microbiota and host metabolism must be re-focused.

Human IgG subclass cross-species reactivity to mouse and cynomolgus monkey Fcγ receptors.

PubMed

Derebe, Mehabaw G; Nanjunda, Rupesh K; Gilliland, Gary L; Lacy, Eilyn R; Chiu, Mark L

2018-05-01

In therapeutic antibody discovery and early development, mice and cynomolgus monkey are used as animal models to assess toxicity, efficacy and other properties of candidate molecules. As more candidate antibodies are based on human immunoglobulin (IgG) subclasses, many strategies are pursued to simulate the human system in the test animal. However, translation rate from a successful preclinical trial to an approved drug is extremely low. This may partly be due to differences in interaction of human IgG based candidate molecules to endogenous Fcγ receptors of model animals in comparison to those of human Fcγ receptors. In this study, we compare binding characteristics of human IgG subclasses commonly used in drug development (IgG1, IgG2, IgG4) and their respective Fc silent versions (IgG1σ, IgG2σ, IgG4 PAA) to human, mouse, and cynomolgus monkey Fcγ receptors. To control interactions between Fab and Fc domains, the test IgGs all have the same variable region sequences. We found distinct variations of interaction of human IgG subclasses to model animal Fcγ receptors in comparison to their human counterparts. Particularly, cynomolgus monkey Fcγ receptors showed consistently tighter binding to human IgGs than human Fcγ receptors. Moreover, the presumably Fc silent human IgG4 PAA framework bound to cynomolgus monkey FcγRI with nanomolar affinity while only very weak binding was observed for the human FcγRI. Our results highlighted the need for a thorough in vitro affinity characterization of candidate IgGs against model animal Fcγ receptors and careful design of preclinical studies. Copyright © 2018. Published by Elsevier B.V.

Interactions of social, terrestrial, and marine sub-systems in the Galapagos Islands, Ecuador.

PubMed

Walsh, Stephen J; Mena, Carlos F

2016-12-20

Galapagos is often cited as an example of the conflicts that are emerging between resource conservation and economic development in island ecosystems, as the pressures associated with tourism threaten nature, including the iconic and emblematic species, unique terrestrial landscapes, and special marine environments. In this paper, two projects are described that rely upon dynamic systems models and agent-based models to examine human-environment interactions. We use a theoretical context rooted in complexity theory to guide the development of our models that are linked to social-ecological dynamics. The goal of this paper is to describe key elements, relationships, and processes to inform and enhance our understanding of human-environment interactions in the Galapagos Islands of Ecuador. By formalizing our knowledge of how systems operate and the manner in which key elements are linked in coupled human-natural systems, we specify rules, relationships, and rates of exchange between social and ecological features derived through statistical functions and/or functions specified in theory or practice. The processes described in our models also have practical applications in that they emphasize how political policies generate different human responses and model outcomes, many detrimental to the social-ecological sustainability of the Galapagos Islands.

Analysis of Timing Control Mechanism of Utterance and Body Motion Using Dialogue between Human and Communication Robot

NASA Astrophysics Data System (ADS)

Takasugi, Shoji; Yamamoto, Tomohito; Muto, Yumiko; Abe, Hiroyuki; Miyake, Yoshihiro

The purpose of this study is to clarify the effects of timing control of utterance and body motion in human-robot interaction. Our previous study has already revealed the correlation of timing of utterance and body motion in human-human communication. Here we proposed a timing control model based on our previous research and estimated its influence to realize human-like communication using a questionnaire method. The results showed that the difference of effectiveness between the communication with the timing control model and that without it was observed. In addition, elderly people evaluated the communication with timing control much higher than younger people. These results show not only the importance of timing control of utterance and body motion in human communication but also its effectiveness for realizing human-like human-robot interaction.

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…

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.

Simulating forest landscape disturbances as coupled human and natural systems

USGS Publications Warehouse

Wimberly, Michael; Sohl, Terry L.; Liu, Zhihua; Lamsal, Aashis

2015-01-01

Anthropogenic disturbances resulting from human land use affect forest landscapes over a range of spatial and temporal scales, with diverse influences on vegetation patterns and dynamics. These processes fall within the scope of the coupled human and natural systems (CHANS) concept, which has emerged as an important framework for understanding the reciprocal interactions and feedbacks that connect human activities and ecosystem responses. Spatial simulation modeling of forest landscape change is an important technique for exploring the dynamics of CHANS over large areas and long time periods. Landscape models for simulating interactions between human activities and forest landscape dynamics can be grouped into two main categories. Forest landscape models (FLMs) focus on landscapes where forests are the dominant land cover and simulate succession and natural disturbances along with forest management activities. In contrast, land change models (LCMs) simulate mosaics of different land cover and land use classes that include forests in addition to other land uses such as developed areas and agricultural lands. There are also several examples of coupled models that combine elements of FLMs and LCMs. These integrated models are particularly useful for simulating human–natural interactions in landscapes where human settlement and agriculture are expanding into forested areas. Despite important differences in spatial scale and disciplinary scope, FLMs and LCMs have many commonalities in conceptual design and technical implementation that can facilitate continued integration. The ultimate goal will be to implement forest landscape disturbance modeling in a CHANS framework that recognizes the contextual effects of regional land use and other human activities on the forest ecosystem while capturing the reciprocal influences of forests and their disturbances on the broader land use mosaic.

A realistic host-vector transmission model for describing malaria prevalence pattern.

PubMed

Mandal, Sandip; Sinha, Somdatta; Sarkar, Ram Rup

2013-12-01

Malaria continues to be a major public health concern all over the world even after effective control policies have been employed, and considerable understanding of the disease biology have been attained, from both the experimental and modelling perspective. Interactions between different general and local processes, such as dependence on age and immunity of the human host, variations of temperature and rainfall in tropical and sub-tropical areas, and continued presence of asymptomatic infections, regulate the host-vector interactions, and are responsible for the continuing disease prevalence pattern.In this paper, a general mathematical model of malaria transmission is developed considering short and long-term age-dependent immunity of human host and its interaction with pathogen-infected mosquito vector. The model is studied analytically and numerically to understand the role of different parameters related to mosquitoes and humans. To validate the model with a disease prevalence pattern in a particular region, real epidemiological data from the north-eastern part of India was used, and the effect of seasonal variation in mosquito density was modelled based on local climactic data. The model developed based on general features of host-vector interactions, and modified simply incorporating local environmental factors with minimal changes, can successfully explain the disease transmission process in the region. This provides a general approach toward modelling malaria that can be adapted to control future outbreaks of malaria.

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.

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 of the variance in each probability distribution. The correlation between predicted and observed probabilities ranged from a low of 0.955 to a high value of 0.998, indicating that humans behave in psychological space as Fermions behave in momentum space.

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.

Operator dynamics for stability condition in haptic and teleoperation system: A survey.

PubMed

Li, Hongbing; Zhang, Lei; Kawashima, Kenji

2018-04-01

Currently, haptic systems ignore the varying impedance of the human hand with its countless configurations and thus cannot recreate the complex haptic interactions. The literature does not reveal a comprehensive survey on the methods proposed and this study is an attempt to bridge this gap. The paper includes an extensive review of human arm impedance modeling and control deployed to address inherent stability and transparency issues in haptic interaction and teleoperation systems. Detailed classification and comparative study of various contributions in human arm modeling are presented and summarized in tables and diagrams. The main challenges in modeling human arm impedance for haptic robotic applications are identified. The possible future research directions are outlined based on the gaps identified in the survey. Copyright © 2018 John Wiley & Sons, Ltd.

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

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.

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.

Selection of a Relevant In Vitro Blood-Brain Barrier Model to Investigate Pro-Metastatic Features of Human Breast Cancer Cell Lines.

PubMed

Drolez, Aurore; Vandenhaute, Elodie; Julien, Sylvain; Gosselet, Fabien; Burchell, Joy; Cecchelli, Roméo; Delannoy, Philippe; Dehouck, Marie-Pierre; Mysiorek, Caroline

2016-01-01

Around 7-17% of metastatic breast cancer patients will develop brain metastases, associated with a poor prognosis. To reach the brain parenchyma, cancer cells need to cross the highly restrictive endothelium of the Blood-Brain Barrier (BBB). As treatments for brain metastases are mostly inefficient, preventing cancer cells to reach the brain could provide a relevant and important strategy. For that purpose an in vitro approach is required to identify cellular and molecular interaction mechanisms between breast cancer cells and BBB endothelium, notably at the early steps of the interaction. However, while numerous studies are performed with in vitro models, the heterogeneity and the quality of BBB models used is a limitation to the extrapolation of the obtained results to in vivo context, showing that the choice of a model that fulfills the biological BBB characteristics is essential. Therefore, we compared pre-established and currently used in vitro models from different origins (bovine, mice, human) in order to define the most appropriate tool to study interactions between breast cancer cells and the BBB. On each model, the BBB properties and the adhesion capacities of breast cancer cell lines were evaluated. As endothelial cells represent the physical restriction site of the BBB, all the models consisted of endothelial cells from animal or human origins. Among these models, only the in vitro BBB model derived from human stem cells both displayed BBB properties and allowed measurement of meaningful different interaction capacities of the cancer cell lines. Importantly, the measured adhesion and transmigration were found to be in accordance with the cancer cell lines molecular subtypes. In addition, at a molecular level, the inhibition of ganglioside biosynthesis highlights the potential role of glycosylation in breast cancer cells adhesion capacities.

The high-affinity receptor for IgG, FcγRI, of humans and non-human primates.

PubMed

Chenoweth, Alicia M; Trist, Halina M; Tan, Peck-Szee; Wines, Bruce D; Hogarth, P Mark

2015-11-01

Non-human primate (NHP) models, especially involving macaques, are considered important models of human immunity and have been essential in preclinical testing for vaccines and therapeutics. Despite this, much less characterization of macaque Fc receptors has occurred compared to humans or mice. Much of the characterization of macaque Fc receptors so far has focused on the low-affinity Fc receptors, particularly FcγRIIIa. From these studies, it is clear that there are distinct differences between the human and macaque low-affinity receptors and their interaction with human IgG. Relatively little work has been performed on the high-affinity IgG receptor, FcγRI, especially in NHPs. This review will focus on what is currently known of how FcγRI interacts with IgG, from mutation studies and recent crystallographic studies of human FcγRI, and how amino acid sequence differences in the macaque FcγRI may affect this interaction. Additionally, this review will look at the functional consequences of differences in the amino acid sequences between humans and macaques. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Network-based analysis of genotype-phenotype correlations between different inheritance modes.

PubMed

Hao, Dapeng; Li, Chuanxing; Zhang, Shaojun; Lu, Jianping; Jiang, Yongshuai; Wang, Shiyuan; Zhou, Meng

2014-11-15

Recent studies on human disease have revealed that aberrant interaction between proteins probably underlies a substantial number of human genetic diseases. This suggests a need to investigate disease inheritance mode using interaction, and based on which to refresh our conceptual understanding of a series of properties regarding inheritance mode of human disease. We observed a strong correlation between the number of protein interactions and the likelihood of a gene causing any dominant diseases or multiple dominant diseases, whereas no correlation was observed between protein interaction and the likelihood of a gene causing recessive diseases. We found that dominant diseases are more likely to be associated with disruption of important interactions. These suggest inheritance mode should be understood using protein interaction. We therefore reviewed the previous studies and refined an interaction model of inheritance mode, and then confirmed that this model is largely reasonable using new evidences. With these findings, we found that the inheritance mode of human genetic diseases can be predicted using protein interaction. By integrating the systems biology perspectives with the classical disease genetics paradigm, our study provides some new insights into genotype-phenotype correlations. haodapeng@ems.hrbmu.edu.cn or biofomeng@hotmail.com Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A roadmap to computational social neuroscience.

PubMed

Tognoli, Emmanuelle; Dumas, Guillaume; Kelso, J A Scott

2018-02-01

To complement experimental efforts toward understanding human social interactions at both neural and behavioral levels, two computational approaches are presented: (1) a fully parameterizable mathematical model of a social partner, the Human Dynamic Clamp which, by virtue of experimentally controlled interactions between Virtual Partners and real people, allows for emergent behaviors to be studied; and (2) a multiscale neurocomputational model of social coordination that enables exploration of social self-organization at all levels-from neuronal patterns to people interacting with each other. These complementary frameworks and the cross product of their analysis aim at understanding the fundamental principles governing social behavior.

Photorealistic virtual anatomy based on Chinese Visible Human data.

PubMed

Heng, P A; Zhang, S X; Xie, Y M; Wong, T T; Chui, Y P; Cheng, C Y

2006-04-01

Virtual reality based learning of human anatomy is feasible when a database of 3D organ models is available for the learner to explore, visualize, and dissect in virtual space interactively. In this article, we present our latest work on photorealistic virtual anatomy applications based on the Chinese Visible Human (CVH) data. We have focused on the development of state-of-the-art virtual environments that feature interactive photo-realistic visualization and dissection of virtual anatomical models constructed from ultra-high resolution CVH datasets. We also outline our latest progress in applying these highly accurate virtual and functional organ models to generate realistic look and feel to advanced surgical simulators. (c) 2006 Wiley-Liss, Inc.

In silico study of the human rhodopsin and meta rhodopsin II/S-arrestin complexes: impact of single point mutations related to retina degenerative diseases.

PubMed

Mokarzel-Falcón, Leonardo; Padrón-García, Juan Alexander; Carrasco-Velar, Ramón; Berry, Colin; Montero-Cabrera, Luis A

2008-03-01

We propose two models of the human S-arrestin/rhodopsin complex in the inactive dark adapted rhodopsin and meta rhodopsin II form, obtained by homology modeling and knowledge based docking. First, a homology model for the human S-arrestin was built and validated by molecular dynamics, showing an average root mean square deviation difference from the pattern behavior of 0.76 A. Then, combining the human S-arrestin model and the modeled structure of the two human rhodopsin forms, we propose two models of interaction for the human S-arrestin/rhodopsin complex. The models involve two S-arrestin regions related to the N domain (residues 68-78; 170-182) and a third constituent of the C domain (248-253), with the rhodopsin C terminus (330-348). Of the 22 single point mutations related to retinitis pigmentosa and congenital night blindness located in the cytoplasmatic portion of rhodopsin or in S-arrestin, our models locate 16 in the interaction region and relate two others to possible dimer formation. Our calculations also predict that the light activated complex is more stable than the dark adapted rhodopsin and, therefore, of higher affinity to S-arrestin. 2008 Wiley-Liss, Inc.

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.

Adapting GOMS to Model Human-Robot Interaction

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

Drury, Jill; Scholtz, Jean; Kieras, David

2007-03-09

Human-robot interaction (HRI) has been maturing in tandem with robots’ commercial success. In the last few years HRI researchers have been adopting—and sometimes adapting—human-computer interaction (HCI) evaluation techniques to assess the efficiency and intuitiveness of HRI designs. For example, Adams (2005) used Goal Directed Task Analysis to determine the interaction needs of officers from the Nashville Metro Police Bomb Squad. Scholtz et al. (2004) used Endsley’s (1988) Situation Awareness Global Assessment Technique to determine robotic vehicle supervisors’ awareness of when vehicles were in trouble and thus required closer monitoring or intervention. Yanco and Drury (2004) employed usability testing to determinemore » (among other things) how well a search-andrescue interface supported use by first responders. One set of HCI tools that has so far seen little exploration in the HRI domain, however, is the class of modeling and evaluation techniques known as formal methods.« less

Interactions between airway epithelial cells and dendritic cells during viral infections using an in vitro co-culture model

EPA Science Inventory

Rationale: Historically, single cell culture models have been limited in pathological and physiological relevance. A co-culture model of dendritic cells (DCs) and differentiated human airway epithelial cells was developed to examine potential interactions between these two cell t...

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.

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

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 of tyrosinase in melanocytes. Western blot analysis of intracellular signaling factors revealed that withaferin A but not astaxanthin significantly abolished the endothelin-1-stimulated phosphorylation of Raf-1, MEK, ERK, MITF and CREB in human melanocytes. These results demonstrate that this co-culture system is an appropriate model to characterize melanogenic paracrine interactions and that astaxanthin and withaferin A serve as potent inhibitors of those interactions. Their effects are caused not only by down-regulating the increased secretion of an intrinsic melanogenic cytokine, endothelin-1, by UVB-exposed human keratinocytes, but also by interrupting the endothelin-1-triggered downstream intracellular signaling between protein kinase C and Raf-1 in human melanocytes (only for withaferin A). Copyright © 2015 Elsevier Ltd. All rights reserved.

The Cool and Belkin Faceted Classification of Information Interactions Revisited

ERIC Educational Resources Information Center

Huvila, Isto

2010-01-01

Introduction: The complexity of human information activity is a challenge for both practice and research in information sciences and information management. Literature presents a wealth of approaches to analytically structure and make sense of human information activity including a faceted classification model of information interactions published…

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);…

Statistical physics of human cooperation

NASA Astrophysics Data System (ADS)

Perc, Matjaž; Jordan, Jillian J.; Rand, David G.; Wang, Zhen; Boccaletti, Stefano; Szolnoki, Attila

2017-05-01

Extensive cooperation among unrelated individuals is unique to humans, who often sacrifice personal benefits for the common good and work together to achieve what they are unable to execute alone. The evolutionary success of our species is indeed due, to a large degree, to our unparalleled other-regarding abilities. Yet, a comprehensive understanding of human cooperation remains a formidable challenge. Recent research in the social sciences indicates that it is important to focus on the collective behavior that emerges as the result of the interactions among individuals, groups, and even societies. Non-equilibrium statistical physics, in particular Monte Carlo methods and the theory of collective behavior of interacting particles near phase transition points, has proven to be very valuable for understanding counterintuitive evolutionary outcomes. By treating models of human cooperation as classical spin models, a physicist can draw on familiar settings from statistical physics. However, unlike pairwise interactions among particles that typically govern solid-state physics systems, interactions among humans often involve group interactions, and they also involve a larger number of possible states even for the most simplified description of reality. The complexity of solutions therefore often surpasses that observed in physical systems. Here we review experimental and theoretical research that advances our understanding of human cooperation, focusing on spatial pattern formation, on the spatiotemporal dynamics of observed solutions, and on self-organization that may either promote or hinder socially favorable states.

Functional Coupling of Human Microphysiology Systems: Intestine, Liver, Kidney Proximal Tubule, Blood-Brain Barrier and Skeletal Muscle

PubMed Central

Vernetti, Lawrence; Gough, Albert; Baetz, Nicholas; Blutt, Sarah; Broughman, James R.; Brown, Jacquelyn A.; Foulke-Abel, Jennifer; Hasan, Nesrin; In, Julie; Kelly, Edward; Kovbasnjuk, Olga; Repper, Jonathan; Senutovitch, Nina; Stabb, Janet; Yeung, Catherine; Zachos, Nick C.; Donowitz, Mark; Estes, Mary; Himmelfarb, Jonathan; Truskey, George; Wikswo, John P.; Taylor, D. Lansing

2017-01-01

Organ interactions resulting from drug, metabolite or xenobiotic transport between organs are key components of human metabolism that impact therapeutic action and toxic side effects. Preclinical animal testing often fails to predict adverse outcomes arising from sequential, multi-organ metabolism of drugs and xenobiotics. Human microphysiological systems (MPS) can model these interactions and are predicted to dramatically improve the efficiency of the drug development process. In this study, five human MPS models were evaluated for functional coupling, defined as the determination of organ interactions via an in vivo-like sequential, organ-to-organ transfer of media. MPS models representing the major absorption, metabolism and clearance organs (the jejunum, liver and kidney) were evaluated, along with skeletal muscle and neurovascular models. Three compounds were evaluated for organ-specific processing: terfenadine for pharmacokinetics (PK) and toxicity; trimethylamine (TMA) as a potentially toxic microbiome metabolite; and vitamin D3. We show that the organ-specific processing of these compounds was consistent with clinical data, and discovered that trimethylamine-N-oxide (TMAO) crosses the blood-brain barrier. These studies demonstrate the potential of human MPS for multi-organ toxicity and absorption, distribution, metabolism and excretion (ADME), provide guidance for physically coupling MPS, and offer an approach to coupling MPS with distinct media and perfusion requirements. PMID:28176881

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.

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.

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

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.

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.

Finite element analysis of the biomechanical interaction between coronary sinus and proximal anchoring stent in coronary sinus annuloplasty

PubMed Central

Pham, Thuy; Deherrera, Milton; Sun, Wei

2013-01-01

Recent clinical studies of the percutaneous transvenous mitral annuloplasty (PTMA) devices have shown a short-term reduction of mitral regurgitation (MR) after implantation. However, adverse events associated with the devices such as compression and perforation of vessel branches, device migration and fracture were reported. In this study, a finite element analysis was performed to investigate the biomechanical interaction between the proximal anchor stent of a PTMA device and the coronary sinus (CS) vessel in three steps including i) the stent release and contact with the CS wall, ii) the axial pull at the stent connector and iii) the pressure inflation of the vessel wall. To investigate the impact of the material properties of tissues and stents on the interactive responses, the CS vessel was modeled with human and porcine material properties, and the proximal stent was modeled with two different Nitinol materials with one being stiffer than the other. The results indicated that the vessel wall stresses and contact forces imposed by the stents were much higher in human than porcine models. However, the mechanical differences induced by the two stent types were relatively small. The softer stent exhibited a better fatigue safety factor when deployed in the human model than in the porcine model. These results underscored the importance of the CS tissue mechanical properties. Higher vessel wall stress and stent radial force were obtained in human model than those in porcine model, which also brought up questions as to the validity of using porcine model to assess device mechanical function. The quantification of these biomechanical interactions can offer scientific insight into the development and optimization of PTMA device design. PMID:23405942

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.

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

Management Education: Reflective Learning on Human Interaction

ERIC Educational Resources Information Center

Clydesdale, Greg

2016-01-01

Purpose: This paper aims to describe an attempt to develop a more effective technique to teach self-awareness and relationship skills. Design/methodology/approach: A journal is used in combination with a model of human nature. The model lists human characteristics that the management trainee must identify in themselves and others they interact…

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

Physiologically relevant organs on chips

PubMed Central

Yum, Kyungsuk; Hong, Soon Gweon; Lee, Luke P.

2015-01-01

Recent advances in integrating microengineering and tissue engineering have generated promising microengineered physiological models for experimental medicine and pharmaceutical research. Here we review the recent development of microengineered physiological systems, or organs on chips, that reconstitute the physiologically critical features of specific human tissues and organs and their interactions. This technology uses microengineering approaches to construct organ-specific microenvironments, reconstituting tissue structures, tissue–tissue interactions and interfaces, and dynamic mechanical and biochemical stimuli found in specific organs, to direct cells to assemble into functional tissues. We first discuss microengineering approaches to reproduce the key elements of physiologically important, dynamic mechanical microenvironments, biochemical microenvironments, and microarchitectures of specific tissues and organs in microfluidic cell culture systems. This is followed by examples of microengineered individual organ models that incorporate the key elements of physiological microenvironments into single microfluidic cell culture systems to reproduce organ-level functions. Finally, microengineered multiple organ systems that simulate multiple organ interactions to better represent human physiology, including human responses to drugs, is covered in this review. This emerging organs-on-chips technology has the potential to become an alternative to 2D and 3D cell culture and animal models for experimental medicine, human disease modeling, drug development, and toxicology. PMID:24357624

Feedbacks in human-landscape systems

NASA Astrophysics Data System (ADS)

Chin, Anne

2015-04-01

As human interactions with Earth systems intensify in the "Anthropocene", understanding the complex relationships among human activity, landscape change, and societal responses to those changes is increasingly important. Interdisciplinary research centered on the theme of "feedbacks" in human-landscape systems serves as a promising focus for unraveling these interactions. Deciphering interacting human-landscape feedbacks extends our traditional approach of considering humans as unidirectional drivers of change. Enormous challenges exist, however, in quantifying impact-feedback loops in landscapes with significant human alterations. This paper illustrates an example of human-landscape interactions following a wildfire in Colorado (USA) that elicited feedback responses. After the 2012 Waldo Canyon Fire, concerns for heightened flood potential and debris flows associated with post-fire hydrologic changes prompted local landowners to construct tall fences at the base of a burned watershed. These actions changed the sediment transport regime and promoted further landscape change and human responses in a positive feedback cycle. The interactions ultimately increase flood and sediment hazards, rather than dampening the effects of fire. A simple agent-based model, capable of integrating social and hydro-geomorphological data, demonstrates how such interacting impacts and feedbacks could be simulated. Challenges for fully capturing human-landscape feedback interactions include the identification of diffuse and subtle feedbacks at a range of scales, the availability of data linking impact with response, the identification of multiple thresholds that trigger feedback mechanisms, and the varied metrics and data needed to represent both the physical and human systems. By collaborating with social scientists with expertise in the human causes of landscape change, as well as the human responses to those changes, geoscientists could more fully recognize and anticipate the coupled human-landscape interactions that will drive the evolution of Earth systems into the future.

Towards representing human behavior and decision making in Earth system models - an overview of techniques and approaches

NASA Astrophysics Data System (ADS)

Müller-Hansen, Finn; Schlüter, Maja; Mäs, Michael; Donges, Jonathan F.; Kolb, Jakob J.; Thonicke, Kirsten; Heitzig, Jobst

2017-11-01

Today, humans have a critical impact on the Earth system and vice versa, which can generate complex feedback processes between social and ecological dynamics. Integrating human behavior into formal Earth system models (ESMs), however, requires crucial modeling assumptions about actors and their goals, behavioral options, and decision rules, as well as modeling decisions regarding human social interactions and the aggregation of individuals' behavior. Here, we review existing modeling approaches and techniques from various disciplines and schools of thought dealing with human behavior at different levels of decision making. We demonstrate modelers' often vast degrees of freedom but also seek to make modelers aware of the often crucial consequences of seemingly innocent modeling assumptions. After discussing which socioeconomic units are potentially important for ESMs, we compare models of individual decision making that correspond to alternative behavioral theories and that make diverse modeling assumptions about individuals' preferences, beliefs, decision rules, and foresight. We review approaches to model social interaction, covering game theoretic frameworks, models of social influence, and network models. Finally, we discuss approaches to studying how the behavior of individuals, groups, and organizations can aggregate to complex collective phenomena, discussing agent-based, statistical, and representative-agent modeling and economic macro-dynamics. We illustrate the main ingredients of modeling techniques with examples from land-use dynamics as one of the main drivers of environmental change bridging local to global scales.

A video, text, and speech-driven realistic 3-d virtual head for human-machine interface.

PubMed

Yu, Jun; Wang, Zeng-Fu

2015-05-01

A multiple inputs-driven realistic facial animation system based on 3-D virtual head for human-machine interface is proposed. The system can be driven independently by video, text, and speech, thus can interact with humans through diverse interfaces. The combination of parameterized model and muscular model is used to obtain a tradeoff between computational efficiency and high realism of 3-D facial animation. The online appearance model is used to track 3-D facial motion from video in the framework of particle filtering, and multiple measurements, i.e., pixel color value of input image and Gabor wavelet coefficient of illumination ratio image, are infused to reduce the influence of lighting and person dependence for the construction of online appearance model. The tri-phone model is used to reduce the computational consumption of visual co-articulation in speech synchronized viseme synthesis without sacrificing any performance. The objective and subjective experiments show that the system is suitable for human-machine interaction.

On inclusion of water resource management in Earth system models - Part 1: Problem definition and representation of water demand

NASA Astrophysics Data System (ADS)

Nazemi, A.; Wheater, H. S.

2015-01-01

Human activities have caused various changes to the Earth system, and hence the interconnections between human activities and the Earth system should be recognized and reflected in models that simulate Earth system processes. One key anthropogenic activity is water resource management, which determines the dynamics of human-water interactions in time and space and controls human livelihoods and economy, including energy and food production. There are immediate needs to include water resource management in Earth system models. First, the extent of human water requirements is increasing rapidly at the global scale and it is crucial to analyze the possible imbalance between water demands and supply under various scenarios of climate change and across various temporal and spatial scales. Second, recent observations show that human-water interactions, manifested through water resource management, can substantially alter the terrestrial water cycle, affect land-atmospheric feedbacks and may further interact with climate and contribute to sea-level change. Due to the importance of water resource management in determining the future of the global water and climate cycles, the World Climate Research Program's Global Energy and Water Exchanges project (WRCP-GEWEX) has recently identified gaps in describing human-water interactions as one of the grand challenges in Earth system modeling (GEWEX, 2012). Here, we divide water resource management into two interdependent elements, related firstly to water demand and secondly to water supply and allocation. In this paper, we survey the current literature on how various components of water demand have been included in large-scale models, in particular land surface and global hydrological models. Issues of water supply and allocation are addressed in a companion paper. The available algorithms to represent the dominant demands are classified based on the demand type, mode of simulation and underlying modeling assumptions. We discuss the pros and cons of available algorithms, address various sources of uncertainty and highlight limitations in current applications. We conclude that current capability of large-scale models to represent human water demands is rather limited, particularly with respect to future projections and coupled land-atmospheric simulations. To fill these gaps, the available models, algorithms and data for representing various water demands should be systematically tested, intercompared and improved. In particular, human water demands should be considered in conjunction with water supply and allocation, particularly in the face of water scarcity and unknown future climate.

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 a hyper-resolution LSM this work allows for progress on hydrological monitoring and predictions, as well as drought preparedness and water impact assessments at relevant decision-making scales.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Modeling Leadership Styles in Human-Robot Team Dynamics

NASA Technical Reports Server (NTRS)

Cruz, Gerardo E.

2005-01-01

The recent proliferation of robotic systems in our society has placed questions regarding interaction between humans and intelligent machines at the forefront of robotics research. In response, our research attempts to understand the context in which particular types of interaction optimize efficiency in tasks undertaken by human-robot teams. It is our conjecture that applying previous research results regarding leadership paradigms in human organizations will lead us to a greater understanding of the human-robot interaction space. In doing so, we adapt four leadership styles prevalent in human organizations to human-robot teams. By noting which leadership style is more appropriately suited to what situation, as given by previous research, a mapping is created between the adapted leadership styles and human-robot interaction scenarios-a mapping which will presumably maximize efficiency in task completion for a human-robot team. In this research we test this mapping with two adapted leadership styles: directive and transactional. For testing, we have taken a virtual 3D interface and integrated it with a genetic algorithm for use in &le-operation of a physical robot. By developing team efficiency metrics, we can determine whether this mapping indeed prescribes interaction styles that will maximize efficiency in the teleoperation of a robot.

Emotion attribution to a non-humanoid robot in different social situations.

PubMed

Lakatos, Gabriella; Gácsi, Márta; Konok, Veronika; Brúder, Ildikó; Bereczky, Boróka; Korondi, Péter; Miklósi, Ádám

2014-01-01

In the last few years there was an increasing interest in building companion robots that interact in a socially acceptable way with humans. In order to interact in a meaningful way a robot has to convey intentionality and emotions of some sort in order to increase believability. We suggest that human-robot interaction should be considered as a specific form of inter-specific interaction and that human-animal interaction can provide a useful biological model for designing social robots. Dogs can provide a promising biological model since during the domestication process dogs were able to adapt to the human environment and to participate in complex social interactions. In this observational study we propose to design emotionally expressive behaviour of robots using the behaviour of dogs as inspiration and to test these dog-inspired robots with humans in inter-specific context. In two experiments (wizard-of-oz scenarios) we examined humans' ability to recognize two basic and a secondary emotion expressed by a robot. In Experiment 1 we provided our companion robot with two kinds of emotional behaviour ("happiness" and "fear"), and studied whether people attribute the appropriate emotion to the robot, and interact with it accordingly. In Experiment 2 we investigated whether participants tend to attribute guilty behaviour to a robot in a relevant context by examining whether relying on the robot's greeting behaviour human participants can detect if the robot transgressed a predetermined rule. Results of Experiment 1 showed that people readily attribute emotions to a social robot and interact with it in accordance with the expressed emotional behaviour. Results of Experiment 2 showed that people are able to recognize if the robot transgressed on the basis of its greeting behaviour. In summary, our findings showed that dog-inspired behaviour is a suitable medium for making people attribute emotional states to a non-humanoid robot.

Conversation as a Model of Instructional Interaction

ERIC Educational Resources Information Center

Van Bramer, Joan

2003-01-01

The role of social context and the nature of human interaction provide rich resources for the study of learning and human cognition. In order to understand these elements more fully, it is important to consider the language in use within these contexts. The early intervention Reading Recovery is grounded in the belief that the conversation between…

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.…

Antiferromagnetic character of workplace stress

NASA Astrophysics Data System (ADS)

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

2011-07-01

We study the nature of workplace stress from the aspect of human-human interactions. We investigated the distribution of Center for Epidemiological Studies Depression Scale scores, a measure of the degree of stress, in workplaces. We found that the degree of stress people experience when around other highly stressed people tends to be low, and vice versa. A simulation based on a model describing microlevel human-human interaction reproduced this observed phenomena and revealed that the energy state of a face-to-face communication network correlates with workplace stress macroscopically.

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.

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.

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.

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.

A hypothetical model of host-pathogen interaction of Streptococcus suis in the gastro-intestinal tract

PubMed Central

Ferrando, Maria Laura; Schultsz, Constance

2016-01-01

ABSTRACT Streptococcus suis (SS) is a zoonotic pathogen that can cause systemic infection in pigs and humans. The ingestion of contaminated pig meat is a well-established risk factor for zoonotic S. suis disease. In our studies, we provide experimental evidence that S. suis is capable to translocate across the host gastro-intestinal tract (GIT) using in vivo and in vitro models. Hence, S. suis should be considered an emerging foodborne pathogen. In this addendum, we give an overview of the complex interactions between S. suis and host-intestinal mucosa which depends on the host origin, the serotype and genotype of S. suis, as well as the presence and expression of virulence factors involved in host-pathogen interaction. Finally, we propose a hypothetical model of S. suis interaction with the host-GIT taking in account differences in conditions between the porcine and human host. PMID:26900998

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.

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.

Interactions within the MHC contribute to the genetic architecture of celiac disease.

PubMed

Goudey, Benjamin; Abraham, Gad; Kikianty, Eder; Wang, Qiao; Rawlinson, Dave; Shi, Fan; Haviv, Izhak; Stern, Linda; Kowalczyk, Adam; Inouye, Michael

2017-01-01

Interaction analysis of GWAS can detect signal that would be ignored by single variant analysis, yet few robust interactions in humans have been detected. Recent work has highlighted interactions in the MHC region between known HLA risk haplotypes for various autoimmune diseases. To better understand the genetic interactions underlying celiac disease (CD), we have conducted exhaustive genome-wide scans for pairwise interactions in five independent CD case-control studies, using a rapid model-free approach to examine over 500 billion SNP pairs in total. We found 14 independent interaction signals within the MHC region that achieved stringent replication criteria across multiple studies and were independent of known CD risk HLA haplotypes. The strongest independent CD interaction signal corresponded to genes in the HLA class III region, in particular PRRC2A and GPANK1/C6orf47, which are known to contain variants for non-Hodgkin's lymphoma and early menopause, co-morbidities of celiac disease. Replicable evidence for statistical interaction outside the MHC was not observed. Both within and between European populations, we observed striking consistency of two-locus models and model distribution. Within the UK population, models of CD based on both interactions and additive single-SNP effects increased explained CD variance by approximately 1% over those of single SNPs. The interactions signal detected across the five cohorts indicates the presence of novel associations in the MHC region that cannot be detected using additive models. Our findings have implications for the determination of genetic architecture and, by extension, the use of human genetics for validation of therapeutic targets.

The Virtual Teacher (VT) Paradigm: Learning New Patterns of Interpersonal Coordination Using the Human Dynamic Clamp

PubMed Central

2015-01-01

The Virtual Teacher paradigm, a version of the Human Dynamic Clamp (HDC), is introduced into studies of learning patterns of inter-personal coordination. Combining mathematical modeling and experimentation, we investigate how the HDC may be used as a Virtual Teacher (VT) to help humans co-produce and internalize new inter-personal coordination pattern(s). Human learners produced rhythmic finger movements whilst observing a computer-driven avatar, animated by dynamic equations stemming from the well-established Haken-Kelso-Bunz (1985) and Schöner-Kelso (1988) models of coordination. We demonstrate that the VT is successful in shifting the pattern co-produced by the VT-human system toward any value (Experiment 1) and that the VT can help humans learn unstable relative phasing patterns (Experiment 2). Using transfer entropy, we find that information flow from one partner to the other increases when VT-human coordination loses stability. This suggests that variable joint performance may actually facilitate interaction, and in the long run learning. VT appears to be a promising tool for exploring basic learning processes involved in social interaction, unraveling the dynamics of information flow between interacting partners, and providing possible rehabilitation opportunities. PMID:26569608

The Virtual Teacher (VT) Paradigm: Learning New Patterns of Interpersonal Coordination Using the Human Dynamic Clamp.

PubMed

Kostrubiec, Viviane; Dumas, Guillaume; Zanone, Pier-Giorgio; Kelso, J A Scott

2015-01-01

The Virtual Teacher paradigm, a version of the Human Dynamic Clamp (HDC), is introduced into studies of learning patterns of inter-personal coordination. Combining mathematical modeling and experimentation, we investigate how the HDC may be used as a Virtual Teacher (VT) to help humans co-produce and internalize new inter-personal coordination pattern(s). Human learners produced rhythmic finger movements whilst observing a computer-driven avatar, animated by dynamic equations stemming from the well-established Haken-Kelso-Bunz (1985) and Schöner-Kelso (1988) models of coordination. We demonstrate that the VT is successful in shifting the pattern co-produced by the VT-human system toward any value (Experiment 1) and that the VT can help humans learn unstable relative phasing patterns (Experiment 2). Using transfer entropy, we find that information flow from one partner to the other increases when VT-human coordination loses stability. This suggests that variable joint performance may actually facilitate interaction, and in the long run learning. VT appears to be a promising tool for exploring basic learning processes involved in social interaction, unraveling the dynamics of information flow between interacting partners, and providing possible rehabilitation opportunities.

Computer-assisted visual interactive recognition and its prospects of implementation over the Internet

NASA Astrophysics Data System (ADS)

Zou, Jie; Gattani, Abhishek

2005-01-01

When completely automated systems don't yield acceptable accuracy, many practical pattern recognition systems involve the human either at the beginning (pre-processing) or towards the end (handling rejects). We believe that it may be more useful to involve the human throughout the recognition process rather than just at the beginning or end. We describe a methodology of interactive visual recognition for human-centered low-throughput applications, Computer Assisted Visual InterActive Recognition (CAVIAR), and discuss the prospects of implementing CAVIAR over the Internet. The novelty of CAVIAR is image-based interaction through a domain-specific parameterized geometrical model, which reduces the semantic gap between humans and computers. The user may interact with the computer anytime that she considers its response unsatisfactory. The interaction improves the accuracy of the classification features by improving the fit of the computer-proposed model. The computer makes subsequent use of the parameters of the improved model to refine not only its own statistical model-fitting process, but also its internal classifier. The CAVIAR methodology was applied to implement a flower recognition system. The principal conclusions from the evaluation of the system include: 1) the average recognition time of the CAVIAR system is significantly shorter than that of the unaided human; 2) its accuracy is significantly higher than that of the unaided machine; 3) it can be initialized with as few as one training sample per class and still achieve high accuracy; and 4) it demonstrates a self-learning ability. We have also implemented a Mobile CAVIAR system, where a pocket PC, as a client, connects to a server through wireless communication. The motivation behind a mobile platform for CAVIAR is to apply the methodology in a human-centered pervasive environment, where the user can seamlessly interact with the system for classifying field-data. Deploying CAVIAR to a networked mobile platform poses the challenge of classifying field images and programming under constraints of display size, network bandwidth, processor speed, and memory size. Editing of the computer-proposed model is performed on the handheld while statistical model fitting and classification take place on the server. The possibility that the user can easily take several photos of the object poses an interesting information fusion problem. The advantage of the Internet is that the patterns identified by different users can be pooled together to benefit all peer users. When users identify patterns with CAVIAR in a networked setting, they also collect training samples and provide opportunities for machine learning from their intervention. CAVIAR implemented over the Internet provides a perfect test bed for, and extends, the concept of Open Mind Initiative proposed by David Stork. Our experimental evaluation focuses on human time, machine and human accuracy, and machine learning. We devoted much effort to evaluating the use of our image-based user interface and on developing principles for the evaluation of interactive pattern recognition system. The Internet architecture and Mobile CAVIAR methodology have many applications. We are exploring in the directions of teledermatology, face recognition, and education.

Observing Consistency in Online Communication Patterns for User Re-Identification.

PubMed

Adeyemi, Ikuesan Richard; Razak, Shukor Abd; Salleh, Mazleena; Venter, Hein S

2016-01-01

Comprehension of the statistical and structural mechanisms governing human dynamics in online interaction plays a pivotal role in online user identification, online profile development, and recommender systems. However, building a characteristic model of human dynamics on the Internet involves a complete analysis of the variations in human activity patterns, which is a complex process. This complexity is inherent in human dynamics and has not been extensively studied to reveal the structural composition of human behavior. A typical method of anatomizing such a complex system is viewing all independent interconnectivity that constitutes the complexity. An examination of the various dimensions of human communication pattern in online interactions is presented in this paper. The study employed reliable server-side web data from 31 known users to explore characteristics of human-driven communications. Various machine-learning techniques were explored. The results revealed that each individual exhibited a relatively consistent, unique behavioral signature and that the logistic regression model and model tree can be used to accurately distinguish online users. These results are applicable to one-to-one online user identification processes, insider misuse investigation processes, and online profiling in various areas.

Evaluating Mental Models in Mathematics: A Comparison of Methods

ERIC Educational Resources Information Center

Gogus, Aytac

2013-01-01

Cognitive scientists investigate mental models (how humans organize and structure knowledge in their minds) so as to understand human understanding of and interactions with the world. Cognitive and mental model research is concerned with internal conceptual systems that are not easily or directly observable. The goal of this research was to…

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.

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

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.

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

Inference on the Strength of Balancing Selection for Epistatically Interacting Loci

PubMed Central

Buzbas, Erkan Ozge; Joyce, Paul; Rosenberg, Noah A.

2011-01-01

Existing inference methods for estimating the strength of balancing selection in multi-locus genotypes rely on the assumption that there are no epistatic interactions between loci. Complex systems in which balancing selection is prevalent, such as sets of human immune system genes, are known to contain components that interact epistatically. Therefore, current methods may not produce reliable inference on the strength of selection at these loci. In this paper, we address this problem by presenting statistical methods that can account for epistatic interactions in making inference about balancing selection. A theoretical result due to Fearnhead (2006) is used to build a multi-locus Wright-Fisher model of balancing selection, allowing for epistatic interactions among loci. Antagonistic and synergistic types of interactions are examined. The joint posterior distribution of the selection and mutation parameters is sampled by Markov chain Monte Carlo methods, and the plausibility of models is assessed via Bayes factors. As a component of the inference process, an algorithm to generate multi-locus allele frequencies under balancing selection models with epistasis is also presented. Recent evidence on interactions among a set of human immune system genes is introduced as a motivating biological system for the epistatic model, and data on these genes are used to demonstrate the methods. PMID:21277883

Search for the standard model Higgs boson in $$l\

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

Li, Dikai

2013-01-01

Humans have always attempted to understand the mystery of Nature, and more recently physicists have established theories to describe the observed phenomena. The most recent theory is a gauge quantum field theory framework, called Standard Model (SM), which proposes a model comprised of elementary matter particles and interaction particles which are fundamental force carriers in the most unified way. The Standard Model contains the internal symmetries of the unitary product group SU(3) c ⓍSU(2) L Ⓧ U(1) Y , describes the electromagnetic, weak and strong interactions; the model also describes how quarks interact with each other through all of thesemore » three interactions, how leptons interact with each other through electromagnetic and weak forces, and how force carriers mediate the fundamental interactions.« less

Can Machines Think? Interaction and Perspective Taking with Robots Investigated via fMRI

PubMed Central

Krach, Sören; Hegel, Frank; Wrede, Britta; Sagerer, Gerhard; Binkofski, Ferdinand; Kircher, Tilo

2008-01-01

Background When our PC goes on strike again we tend to curse it as if it were a human being. Why and under which circumstances do we attribute human-like properties to machines? Although humans increasingly interact directly with machines it remains unclear whether humans implicitly attribute intentions to them and, if so, whether such interactions resemble human-human interactions on a neural level. In social cognitive neuroscience the ability to attribute intentions and desires to others is being referred to as having a Theory of Mind (ToM). With the present study we investigated whether an increase of human-likeness of interaction partners modulates the participants' ToM associated cortical activity. Methodology/Principal Findings By means of functional magnetic resonance imaging (subjects n = 20) we investigated cortical activity modulation during highly interactive human-robot game. Increasing degrees of human-likeness for the game partner were introduced by means of a computer partner, a functional robot, an anthropomorphic robot and a human partner. The classical iterated prisoner's dilemma game was applied as experimental task which allowed for an implicit detection of ToM associated cortical activity. During the experiment participants always played against a random sequence unknowingly to them. Irrespective of the surmised interaction partners' responses participants indicated having experienced more fun and competition in the interaction with increasing human-like features of their partners. Parametric modulation of the functional imaging data revealed a highly significant linear increase of cortical activity in the medial frontal cortex as well as in the right temporo-parietal junction in correspondence with the increase of human-likeness of the interaction partner (computer

Can machines think? Interaction and perspective taking with robots investigated via fMRI.

PubMed

Krach, Sören; Hegel, Frank; Wrede, Britta; Sagerer, Gerhard; Binkofski, Ferdinand; Kircher, Tilo

2008-07-09

When our PC goes on strike again we tend to curse it as if it were a human being. Why and under which circumstances do we attribute human-like properties to machines? Although humans increasingly interact directly with machines it remains unclear whether humans implicitly attribute intentions to them and, if so, whether such interactions resemble human-human interactions on a neural level. In social cognitive neuroscience the ability to attribute intentions and desires to others is being referred to as having a Theory of Mind (ToM). With the present study we investigated whether an increase of human-likeness of interaction partners modulates the participants' ToM associated cortical activity. By means of functional magnetic resonance imaging (subjects n = 20) we investigated cortical activity modulation during highly interactive human-robot game. Increasing degrees of human-likeness for the game partner were introduced by means of a computer partner, a functional robot, an anthropomorphic robot and a human partner. The classical iterated prisoner's dilemma game was applied as experimental task which allowed for an implicit detection of ToM associated cortical activity. During the experiment participants always played against a random sequence unknowingly to them. Irrespective of the surmised interaction partners' responses participants indicated having experienced more fun and competition in the interaction with increasing human-like features of their partners. Parametric modulation of the functional imaging data revealed a highly significant linear increase of cortical activity in the medial frontal cortex as well as in the right temporo-parietal junction in correspondence with the increase of human-likeness of the interaction partner (computer

Dynamics of deceptive interactions in social networks.

PubMed

Barrio, Rafael A; Govezensky, Tzipe; Dunbar, Robin; Iñiguez, Gerardo; Kaski, Kimmo

2015-11-06

In this paper, we examine the role of lies in human social relations by implementing some salient characteristics of deceptive interactions into an opinion formation model, so as to describe the dynamical behaviour of a social network more realistically. In this model, we take into account such basic properties of social networks as the dynamics of the intensity of interactions, the influence of public opinion and the fact that in every human interaction it might be convenient to deceive or withhold information depending on the instantaneous situation of each individual in the network. We find that lies shape the topology of social networks, especially the formation of tightly linked, small communities with loose connections between them. We also find that agents with a larger proportion of deceptive interactions are the ones that connect communities of different opinion, and, in this sense, they have substantial centrality in the network. We then discuss the consequences of these results for the social behaviour of humans and predict the changes that could arise due to a varying tolerance for lies in society. © 2015 The Author(s).

Emotion, Emotional Expression, and the Cognitive-Physiological Interaction: A Readout View.

ERIC Educational Resources Information Center

Buck, Ross

A basic tenet of this paper is that, from the time of the ancient Greeks, Western thought has distinguished between rational processes unique to humans and the processes governing animal behavior. A model of motivation, emotion, and the cognitive/physiological interaction that can be applied to both animals and humans is presented. The special…

Multimodal approaches for emotion recognition: a survey

NASA Astrophysics Data System (ADS)

Sebe, Nicu; Cohen, Ira; Gevers, Theo; Huang, Thomas S.

2004-12-01

Recent technological advances have enabled human users to interact with computers in ways previously unimaginable. Beyond the confines of the keyboard and mouse, new modalities for human-computer interaction such as voice, gesture, and force-feedback are emerging. Despite important advances, one necessary ingredient for natural interaction is still missing-emotions. Emotions play an important role in human-to-human communication and interaction, allowing people to express themselves beyond the verbal domain. The ability to understand human emotions is desirable for the computer in several applications. This paper explores new ways of human-computer interaction that enable the computer to be more aware of the user's emotional and attentional expressions. We present the basic research in the field and the recent advances into the emotion recognition from facial, voice, and physiological signals, where the different modalities are treated independently. We then describe the challenging problem of multimodal emotion recognition and we advocate the use of probabilistic graphical models when fusing the different modalities. We also discuss the difficult issues of obtaining reliable affective data, obtaining ground truth for emotion recognition, and the use of unlabeled data.

Multimodal approaches for emotion recognition: a survey

NASA Astrophysics Data System (ADS)

Sebe, Nicu; Cohen, Ira; Gevers, Theo; Huang, Thomas S.

2005-01-01

Recent technological advances have enabled human users to interact with computers in ways previously unimaginable. Beyond the confines of the keyboard and mouse, new modalities for human-computer interaction such as voice, gesture, and force-feedback are emerging. Despite important advances, one necessary ingredient for natural interaction is still missing-emotions. Emotions play an important role in human-to-human communication and interaction, allowing people to express themselves beyond the verbal domain. The ability to understand human emotions is desirable for the computer in several applications. This paper explores new ways of human-computer interaction that enable the computer to be more aware of the user's emotional and attentional expressions. We present the basic research in the field and the recent advances into the emotion recognition from facial, voice, and physiological signals, where the different modalities are treated independently. We then describe the challenging problem of multimodal emotion recognition and we advocate the use of probabilistic graphical models when fusing the different modalities. We also discuss the difficult issues of obtaining reliable affective data, obtaining ground truth for emotion recognition, and the use of unlabeled data.

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.

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

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.

Agent-based modeling of endotoxin-induced acute inflammatory response in human blood leukocytes.

PubMed

Dong, Xu; Foteinou, Panagiota T; Calvano, Steven E; Lowry, Stephen F; Androulakis, Ioannis P

2010-02-18

Inflammation is a highly complex biological response evoked by many stimuli. A persistent challenge in modeling this dynamic process has been the (nonlinear) nature of the response that precludes the single-variable assumption. Systems-based approaches offer a promising possibility for understanding inflammation in its homeostatic context. In order to study the underlying complexity of the acute inflammatory response, an agent-based framework is developed that models the emerging host response as the outcome of orchestrated interactions associated with intricate signaling cascades and intercellular immune system interactions. An agent-based modeling (ABM) framework is proposed to study the nonlinear dynamics of acute human inflammation. The model is implemented using NetLogo software. Interacting agents involve either inflammation-specific molecules or cells essential for the propagation of the inflammatory reaction across the system. Spatial orientation of molecule interactions involved in signaling cascades coupled with the cellular heterogeneity are further taken into account. The proposed in silico model is evaluated through its ability to successfully reproduce a self-limited inflammatory response as well as a series of scenarios indicative of the nonlinear dynamics of the response. Such scenarios involve either a persistent (non)infectious response or innate immune tolerance and potentiation effects followed by perturbations in intracellular signaling molecules and cascades. The ABM framework developed in this study provides insight on the stochastic interactions of the mediators involved in the propagation of endotoxin signaling at the cellular response level. The simulation results are in accordance with our prior research effort associated with the development of deterministic human inflammation models that include transcriptional dynamics, signaling, and physiological components. The hypothetical scenarios explored in this study would potentially improve our understanding of how manipulating the behavior of the molecular species could manifest into emergent behavior of the overall system.

How humans integrate the prospects of pain and reward during choice

PubMed Central

Talmi, Deborah; Dayan, Peter; Kiebel, Stefan J.; Frith, Chris D.; Dolan, Raymond J.

2010-01-01

The maxim “no pain, no gain” summarises scenarios where an action leading to reward also entails a cost. Although we know a substantial amount about how the brain represents pain and reward separately, we know little about how they are integrated during goal directed behaviour. Two theoretical models might account for the integration of reward and pain. An additive model specifies that the disutility of costs is summed linearly with the utility of benefits, while an interactive model suggests that cost and benefit utilities interact so that the sensitivity to benefits is attenuated as costs become increasingly aversive. Using a novel task that required integration of physical pain and monetary reward, we examined the mechanism underlying cost-benefit integration in humans. We provide evidence in support of an interactive model in behavioural choice. Using functional neuroimaging we identify a neural signature for this interaction such that when the consequences of actions embody a mixture of reward and pain, there is an attenuation of a predictive reward-signal in both ventral anterior cingulate cortex and ventral striatum. We conclude that these regions subserve integration of action costs and benefits in humans, a finding that suggests a cross-species similarity in neural substrates that implement this function and illuminates mechanisms that underlie altered decision making under aversive conditions. PMID:19923294

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

Bovine and human insulin adsorption at lipid monolayers: a comparison

NASA Astrophysics Data System (ADS)

Mauri, Sergio; Pandey, Ravindra; Rzeznicka, Izabela; Lu, Hao; Bonn, Mischa; Weidner, Tobias

2015-07-01

Insulin is a widely used peptide in protein research and it is utilised as a model peptide to understand the mechanics of fibril formation, which is believed to be the cause of diseases such as Alzheimer and Creutzfeld-Jakob syndrome. Insulin has been used as a model system due to its biomedical relevance, small size and relatively simple tertiary structure. The adsorption of insu lin on a variety of surfaces has become the focus of numerous studies lately. These works have helped in elucidating the consequence of surface/protein hydrophilic/hydrophobic interaction in terms of protein refolding and aggregation. Unfortunately, such model surfaces differ significantly from physiological surfaces. Here we spectroscopically investigate the adsorption of insulin at lipid monolayers, to further our understanding of the interaction of insulin with biological surfaces. In particular we study the effect of minor mutations of insulin’s primary amino acid sequence on its interaction with 1,2-Dipalmitoyl-sn-glycero-3-phosphoglycerol (DPPG) model lipid layers. We probe the structure of bovine and human insulin at the lipid/water interface using sum frequency generation spectroscopy (SFG). The SFG experiments are complemented with XPS analysis of Langmuir-Schaefer deposited lipid/insulin films. We find that bovine and human insulin, even though very similar in sequence, show a substantially different behavior when interacting with lipid films.

Micropatterned coculture of primary human hepatocytes and supportive cells for the study of hepatotropic pathogens.

PubMed

March, Sandra; Ramanan, Vyas; Trehan, Kartik; Ng, Shengyong; Galstian, Ani; Gural, Nil; Scull, Margaret A; Shlomai, Amir; Mota, Maria M; Fleming, Heather E; Khetani, Salman R; Rice, Charles M; Bhatia, Sangeeta N

2015-12-01

The development of therapies and vaccines for human hepatropic pathogens requires robust model systems that enable the study of host-pathogen interactions. However, in vitro liver models of infection typically use either hepatoma cell lines that exhibit aberrant physiology or primary human hepatocytes in culture conditions in which they rapidly lose their hepatic phenotype. To achieve stable and robust in vitro primary human hepatocyte models, we developed micropatterned cocultures (MPCCs), which consist of primary human hepatocytes organized into 2D islands that are surrounded by supportive fibroblast cells. By using this system, which can be established over a period of days, and maintained over multiple weeks, we demonstrate how to recapitulate in vitro hepatic life cycles for the hepatitis B and C viruses and the Plasmodium pathogens P. falciparum and P. vivax. The MPCC platform can be used to uncover aspects of host-pathogen interactions, and it has the potential to be used for drug and vaccine development.

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

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.

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 structure relates to biotic interactions on the community level. We further describe general categories of spatial distribution patterns and identify taxa conforming to these categories. To our knowledge, this is the first study combining spatial and temporal analyses of the human gut microbiome. This type of analysis can be used for identifying candidate probiotics and designing strategies for clinical intervention.

'Tagger' - a Mac OS X Interactive Graphical Application for Data Inference and Analysis of N-Dimensional Datasets in the Natural Physical Sciences.

NASA Astrophysics Data System (ADS)

Morse, P. E.; Reading, A. M.; Lueg, C.

2014-12-01

Pattern-recognition in scientific data is not only a computational problem but a human-observer problem as well. Human observation of - and interaction with - data visualization software can augment, select, interrupt and modify computational routines and facilitate processes of pattern and significant feature recognition for subsequent human analysis, machine learning, expert and artificial intelligence systems.'Tagger' is a Mac OS X interactive data visualisation tool that facilitates Human-Computer interaction for the recognition of patterns and significant structures. It is a graphical application developed using the Quartz Composer framework. 'Tagger' follows a Model-View-Controller (MVC) software architecture: the application problem domain (the model) is to facilitate novel ways of abstractly representing data to a human interlocutor, presenting these via different viewer modalities (e.g. chart representations, particle systems, parametric geometry) to the user (View) and enabling interaction with the data (Controller) via a variety of Human Interface Devices (HID). The software enables the user to create an arbitrary array of tags that may be appended to the visualised data, which are then saved into output files as forms of semantic metadata. Three fundamental problems that are not strongly supported by conventional scientific visualisation software are addressed:1] How to visually animate data over time, 2] How to rapidly deploy unconventional parametrically driven data visualisations, 3] How to construct and explore novel interaction models that capture the activity of the end-user as semantic metadata that can be used to computationally enhance subsequent interrogation. Saved tagged data files may be loaded into Tagger, so that tags may be tagged, if desired. Recursion opens up the possibility of refining or overlapping different types of tags, tagging a variety of different POIs or types of events, and of capturing different types of specialist observations of important or noticeable events. Other visualisations and modes of interaction will also be demonstrated, with the aim of discovering knowledge in large datasets in the natural, physical sciences. Fig.1 Wave height data from an oceanographic Wave Rider Buoy. Colors/radii are driven by wave height data.

The Human-Computer Interface and Information Literacy: Some Basics and Beyond.

ERIC Educational Resources Information Center

Church, Gary M.

1999-01-01

Discusses human/computer interaction research, human/computer interface, and their relationships to information literacy. Highlights include communication models; cognitive perspectives; task analysis; theory of action; problem solving; instructional design considerations; and a suggestion that human/information interface may be a more appropriate…

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.

Physiologically relevant organs on chips.

PubMed

Yum, Kyungsuk; Hong, Soon Gweon; Healy, Kevin E; Lee, Luke P

2014-01-01

Recent advances in integrating microengineering and tissue engineering have generated promising microengineered physiological models for experimental medicine and pharmaceutical research. Here we review the recent development of microengineered physiological systems, or also known as "ogans-on-chips", that reconstitute the physiologically critical features of specific human tissues and organs and their interactions. This technology uses microengineering approaches to construct organ-specific microenvironments, reconstituting tissue structures, tissue-tissue interactions and interfaces, and dynamic mechanical and biochemical stimuli found in specific organs, to direct cells to assemble into functional tissues. We first discuss microengineering approaches to reproduce the key elements of physiologically important, dynamic mechanical microenvironments, biochemical microenvironments, and microarchitectures of specific tissues and organs in microfluidic cell culture systems. This is followed by examples of microengineered individual organ models that incorporate the key elements of physiological microenvironments into single microfluidic cell culture systems to reproduce organ-level functions. Finally, microengineered multiple organ systems that simulate multiple organ interactions to better represent human physiology, including human responses to drugs, is covered in this review. This emerging organs-on-chips technology has the potential to become an alternative to 2D and 3D cell culture and animal models for experimental medicine, human disease modeling, drug development, and toxicology. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Canine REIC/Dkk-3 interacts with SGTA and restores androgen receptor signalling in androgen-independent prostate cancer cell lines.

PubMed

Kato, Yuiko; Ochiai, Kazuhiko; Kawakami, Shota; Nakao, Nobuhiro; Azakami, Daigo; Bonkobara, Makoto; Michishita, Masaki; Morimatsu, Masami; Watanabe, Masami; Omi, Toshinori

2017-06-09

The pathological condition of canine prostate cancer resembles that of human androgen-independent prostate cancer. Both canine and human androgen receptor (AR) signalling are inhibited by overexpression of the dimerized co-chaperone small glutamine-rich tetratricopeptide repeat-containing protein α (SGTA), which is considered to cause the development of androgen-independency. Reduced expression in immortalised cells (REIC/Dkk-3) interferes with SGTA dimerization and rescues AR signalling. This study aimed to assess the effects of REIC/Dkk-3 and SGTA interactions on AR signalling in the canine androgen-independent prostate cancer cell line CHP-1. Mammalian two-hybrid and Halo-tagged pull-down assays showed that canine REIC/Dkk-3 interacted with SGTA and interfered with SGTA dimerization. Additionally, reporter assays revealed that canine REIC/Dkk-3 restored AR signalling in both human and canine androgen-independent prostate cancer cells. Therefore, we confirmed the interaction between canine SGTA and REIC/Dkk-3, as well as their role in AR signalling. Our results suggest that this interaction might contribute to the development of a novel strategy for androgen-independent prostate cancer treatment. Moreover, we established the canine androgen-independent prostate cancer model as a suitable animal model for the study of this type of treatment-refractory human cancer.

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.

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.

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

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.

Engineering epithelial-stromal interactions in vitro for toxicology assessment.

PubMed

Belair, David G; Abbott, Barbara D

2017-05-01

Crosstalk between epithelial and stromal cells drives the morphogenesis of ectodermal organs during development and promotes normal mature adult epithelial tissue homeostasis. Epithelial-stromal interactions (ESIs) have historically been examined using mammalian models and ex vivo tissue recombination. Although these approaches have elucidated signaling mechanisms underlying embryonic morphogenesis processes and adult mammalian epithelial tissue function, they are limited by the availability of tissue, low throughput, and human developmental or physiological relevance. In this review, we describe how bioengineered ESIs, using either human stem cells or co-cultures of human primary epithelial and stromal cells, have enabled the development of human in vitro epithelial tissue models that recapitulate the architecture, phenotype, and function of adult human epithelial tissues. We discuss how the strategies used to engineer mature epithelial tissue models in vitro could be extrapolated to instruct the design of organotypic culture models that can recapitulate the structure of embryonic ectodermal tissues and enable the in vitro assessment of events critical to organ/tissue morphogenesis. Given the importance of ESIs towards normal epithelial tissue development and function, such models present a unique opportunity for toxicological screening assays to incorporate ESIs to assess the impact of chemicals on mature and developing epidermal tissues. Published by Elsevier B.V.

Engineering epithelial-stromal interactions in vitro for toxicology assessment

PubMed Central

Belair, David G.; Abbott, Barbara D.

2018-01-01

Crosstalk between epithelial and stromal cells drives the morphogenesis of ectodermal organs during development and promotes normal mature adult epithelial tissue homeostasis. Epithelial-stromal interactions (ESIs) have historically been examined using mammalian models and ex vivo tissue recombination. Although these approaches have elucidated signaling mechanisms underlying embryonic morphogenesis processes and adult mammalian epithelial tissue function, they are limited by the availability of tissue, low throughput, and human developmental or physiological relevance. In this review, we describe how bioengineered ESIs, using either human stem cells or co-cultures of human primary epithelial and stromal cells, have enabled the development of human in vitro epithelial tissue models that recapitulate the architecture, phenotype, and function of adult human epithelial tissues. We discuss how the strategies used to engineer mature epithelial tissue models in vitro could be extrapolated to instruct the design of organotypic culture models that can recapitulate the structure of embryonic ectodermal tissues and enable the in vitro assessment of events critical to organ/tissue morphogenesis. Given the importance of ESIs towards normal epithelial tissue development and function, such models present a unique opportunity for toxicological screening assays to incorporate ESIs to assess the impact of chemicals on mature and developing epidermal tissues. PMID:28285100

Metabolome of human gut microbiome is predictive of host dysbiosis.

PubMed

Larsen, Peter E; Dai, Yang

2015-01-01

Humans live in constant and vital symbiosis with a closely linked bacterial ecosystem called the microbiome, which influences many aspects of human health. When this microbial ecosystem becomes disrupted, the health of the human host can suffer; a condition called dysbiosis. However, the community compositions of human microbiomes also vary dramatically from individual to individual, and over time, making it difficult to uncover the underlying mechanisms linking the microbiome to human health. We propose that a microbiome's interaction with its human host is not necessarily dependent upon the presence or absence of particular bacterial species, but instead is dependent on its community metabolome; an emergent property of the microbiome. Using data from a previously published, longitudinal study of microbiome populations of the human gut, we extrapolated information about microbiome community enzyme profiles and metabolome models. Using machine learning techniques, we demonstrated that the aggregate predicted community enzyme function profiles and modeled metabolomes of a microbiome are more predictive of dysbiosis than either observed microbiome community composition or predicted enzyme function profiles. Specific enzyme functions and metabolites predictive of dysbiosis provide insights into the molecular mechanisms of microbiome-host interactions. The ability to use machine learning to predict dysbiosis from microbiome community interaction data provides a potentially powerful tool for understanding the links between the human microbiome and human health, pointing to potential microbiome-based diagnostics and therapeutic interventions.

Metabolome of human gut microbiome is predictive of host dysbiosis

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

Larsen, Peter E.; Dai, Yang

Background: Humans live in constant and vital symbiosis with a closely linked bacterial ecosystem called the microbiome, which influences many aspects of human health. When this microbial ecosystem becomes disrupted, the health of the human host can suffer; a condition called dysbiosis. The community compositions of human microbiomes also vary dramatically from individual to individual, and over time, making it difficult to uncover the underlying mechanisms linking the microbiome to human health. We propose that a microbiome’s interaction with its human host is not necessarily dependent upon the presence or absence of particular bacterial species, but instead is dependent onmore » its community metabolome; an emergent property of the microbiome. Results: Using data from a previously published, longitudinal study of microbiome populations of the human gut, we extrapolated information about microbiome community enzyme profiles and metabolome models. Using machine learning techniques, we demonstrated that the aggregate predicted community enzyme function profiles and modeled metabolomes of a microbiome are more predictive of dysbiosis than either observed microbiome community composition or predicted enzyme function profiles. Conclusions: Specific enzyme functions and metabolites predictive of dysbiosis provide insights into the molecular mechanisms of microbiome–host interactions. The ability to use machine learning to predict dysbiosis from microbiome community interaction data provides a potentially powerful tool for understanding the links between the human microbiome and human health, pointing to potential microbiome-based diagnostics and therapeutic interventions.« less

Metabolome of human gut microbiome is predictive of host dysbiosis

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

Larsen, Peter E.; Dai, Yang

Background: Humans live in constant and vital symbiosis with a closely linked bacterial ecosystem called the microbiome, which influences many aspects of human health. When this microbial ecosystem becomes disrupted, the health of the human host can suffer; a condition called dysbiosis. However, the community compositions of human microbiomes also vary dramatically from individual to individual, and over time, making it difficult to uncover the underlying mechanisms linking the microbiome to human health. We propose that a microbiome’s interaction with its human host is not necessarily dependent upon the presence or absence of particular bacterial species, but instead is dependentmore » on its community metabolome; an emergent property of the microbiome. Results: Using data from a previously published, longitudinal study of microbiome populations of the human gut, we extrapolated information about microbiome community enzyme profiles and metabolome models. Using machine learning techniques, we demonstrated that the aggregate predicted community enzyme function profiles and modeled metabolomes of a microbiome are more predictive of dysbiosis than either observed microbiome community composition or predicted enzyme function profiles. Conclusions: Specific enzyme functions and metabolites predictive of dysbiosis provide insights into the molecular mechanisms of microbiome–host interactions. The ability to use machine learning to predict dysbiosis from microbiome community interaction data provides a potentially powerful tool for understanding the links between the human microbiome and human health, pointing to potential microbiome-based diagnostics and therapeutic interventions.« less

Metabolome of human gut microbiome is predictive of host dysbiosis

DOE PAGES

Larsen, Peter E.; Dai, Yang

2015-09-14

Background: Humans live in constant and vital symbiosis with a closely linked bacterial ecosystem called the microbiome, which influences many aspects of human health. When this microbial ecosystem becomes disrupted, the health of the human host can suffer; a condition called dysbiosis. The community compositions of human microbiomes also vary dramatically from individual to individual, and over time, making it difficult to uncover the underlying mechanisms linking the microbiome to human health. We propose that a microbiome’s interaction with its human host is not necessarily dependent upon the presence or absence of particular bacterial species, but instead is dependent onmore » its community metabolome; an emergent property of the microbiome. Results: Using data from a previously published, longitudinal study of microbiome populations of the human gut, we extrapolated information about microbiome community enzyme profiles and metabolome models. Using machine learning techniques, we demonstrated that the aggregate predicted community enzyme function profiles and modeled metabolomes of a microbiome are more predictive of dysbiosis than either observed microbiome community composition or predicted enzyme function profiles. Conclusions: Specific enzyme functions and metabolites predictive of dysbiosis provide insights into the molecular mechanisms of microbiome–host interactions. The ability to use machine learning to predict dysbiosis from microbiome community interaction data provides a potentially powerful tool for understanding the links between the human microbiome and human health, pointing to potential microbiome-based diagnostics and therapeutic interventions.« less

Emotion Attribution to a Non-Humanoid Robot in Different Social Situations

PubMed Central

Lakatos, Gabriella; Gácsi, Márta; Konok, Veronika; Brúder, Ildikó; Bereczky, Boróka; Korondi, Péter; Miklósi, Ádám

2014-01-01

In the last few years there was an increasing interest in building companion robots that interact in a socially acceptable way with humans. In order to interact in a meaningful way a robot has to convey intentionality and emotions of some sort in order to increase believability. We suggest that human-robot interaction should be considered as a specific form of inter-specific interaction and that human–animal interaction can provide a useful biological model for designing social robots. Dogs can provide a promising biological model since during the domestication process dogs were able to adapt to the human environment and to participate in complex social interactions. In this observational study we propose to design emotionally expressive behaviour of robots using the behaviour of dogs as inspiration and to test these dog-inspired robots with humans in inter-specific context. In two experiments (wizard-of-oz scenarios) we examined humans' ability to recognize two basic and a secondary emotion expressed by a robot. In Experiment 1 we provided our companion robot with two kinds of emotional behaviour (“happiness” and “fear”), and studied whether people attribute the appropriate emotion to the robot, and interact with it accordingly. In Experiment 2 we investigated whether participants tend to attribute guilty behaviour to a robot in a relevant context by examining whether relying on the robot's greeting behaviour human participants can detect if the robot transgressed a predetermined rule. Results of Experiment 1 showed that people readily attribute emotions to a social robot and interact with it in accordance with the expressed emotional behaviour. Results of Experiment 2 showed that people are able to recognize if the robot transgressed on the basis of its greeting behaviour. In summary, our findings showed that dog-inspired behaviour is a suitable medium for making people attribute emotional states to a non-humanoid robot. PMID:25551218

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.

Computational Modeling and Simulation of Developmental ...

EPA Pesticide Factsheets

SYNOPSIS: The question of how tissues and organs are shaped during development is crucial for understanding human birth defects. Data from high-throughput screening assays on human stem cells may be utilized predict developmental toxicity with reasonable accuracy. Other types of models are necessary, however, for mechanism-specific analysis because embryogenesis requires precise timing and control. Agent-based modeling and simulation (ABMS) is an approach to virtually reconstruct these dynamics, cell-by-cell and interaction-by-interaction. Using ABMS, HTS lesions from ToxCast can be integrated with patterning systems heuristically to propagate key events This presentation to FDA-CFSAN will update progress on the applications of in silico modeling tools and approaches for assessing developmental toxicity.

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.

Perceptual precision of passive body tilt is consistent with statistically optimal cue integration

PubMed Central

Karmali, Faisal; Nicoucar, Keyvan; Merfeld, Daniel M.

2017-01-01

When making perceptual decisions, humans have been shown to optimally integrate independent noisy multisensory information, matching maximum-likelihood (ML) limits. Such ML estimators provide a theoretic limit to perceptual precision (i.e., minimal thresholds). However, how the brain combines two interacting (i.e., not independent) sensory cues remains an open question. To study the precision achieved when combining interacting sensory signals, we measured perceptual roll tilt and roll rotation thresholds between 0 and 5 Hz in six normal human subjects. Primary results show that roll tilt thresholds between 0.2 and 0.5 Hz were significantly lower than predicted by a ML estimator that includes only vestibular contributions that do not interact. In this paper, we show how other cues (e.g., somatosensation) and an internal representation of sensory and body dynamics might independently contribute to the observed performance enhancement. In short, a Kalman filter was combined with an ML estimator to match human performance, whereas the potential contribution of nonvestibular cues was assessed using published bilateral loss patient data. Our results show that a Kalman filter model including previously proven canal-otolith interactions alone (without nonvestibular cues) can explain the observed performance enhancements as can a model that includes nonvestibular contributions. NEW & NOTEWORTHY We found that human whole body self-motion direction-recognition thresholds measured during dynamic roll tilts were significantly lower than those predicted by a conventional maximum-likelihood weighting of the roll angular velocity and quasistatic roll tilt cues. Here, we show that two models can each match this “apparent” better-than-optimal performance: 1) inclusion of a somatosensory contribution and 2) inclusion of a dynamic sensory interaction between canal and otolith cues via a Kalman filter model. PMID:28179477

Model of rhythmic ball bouncing using a visually controlled neural oscillator.

PubMed

Avrin, Guillaume; Siegler, Isabelle A; Makarov, Maria; Rodriguez-Ayerbe, Pedro

2017-10-01

The present paper investigates the sensory-driven modulations of central pattern generator dynamics that can be expected to reproduce human behavior during rhythmic hybrid tasks. We propose a theoretical model of human sensorimotor behavior able to account for the observed data from the ball-bouncing task. The novel control architecture is composed of a Matsuoka neural oscillator coupled with the environment through visual sensory feedback. The architecture's ability to reproduce human-like performance during the ball-bouncing task in the presence of perturbations is quantified by comparison of simulated and recorded trials. The results suggest that human visual control of the task is achieved online. The adaptive behavior is made possible by a parametric and state control of the limit cycle emerging from the interaction of the rhythmic pattern generator, the musculoskeletal system, and the environment. NEW & NOTEWORTHY The study demonstrates that a behavioral model based on a neural oscillator controlled by visual information is able to accurately reproduce human modulations in a motor action with respect to sensory information during the rhythmic ball-bouncing task. The model attractor dynamics emerging from the interaction between the neuromusculoskeletal system and the environment met task requirements, environmental constraints, and human behavioral choices without relying on movement planning and explicit internal models of the environment. Copyright © 2017 the American Physiological Society.

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.

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.

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

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.

An expanded One Health model: integrating social science and One Health to inform study of the human-animal interface.

PubMed

Woldehanna, Sara; Zimicki, Susan

2015-03-01

Zoonotic disease emergence is not a purely biological process mediated only by ecologic factors; opportunities for transmission of zoonoses from animals to humans also depend on how people interact with animals. While exposure is conditioned by the type of animal and the location in which interactions occur, these in turn are influenced by human activity. The activities people engage in are determined by social as well as contextual factors including gender, age, socio-economic status, occupation, social norms, settlement patterns and livelihood systems, family and community dynamics, as well as national and global influences. This paper proposes an expanded "One Health" conceptual model for human-animal exposure that accounts for social as well as epidemiologic factors. The expanded model informed a new study approach to document the extent of human exposure to animals and explore the interplay of social and environmental factors that influence risk of transmission at the individual and community level. The approach includes a formative phase using qualitative and participatory methods, and a representative, random sample survey to quantify exposure to animals in a variety of settings. The paper discusses the different factors that were considered in developing the approach, including the range of animals asked about and the parameters of exposure that are included, as well as factors to be considered in local adaptation of the generic instruments. Illustrative results from research using this approach in Lao PDR are presented to demonstrate the effect of social factors on how people interact with animals. We believe that the expanded model can be similarly operationalized to explore the interactions of other social and policy-level determinants that may influence transmission of zoonoses. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

Microfluidics-Based in Vivo Mimetic Systems for the Study of Cellular Biology

PubMed Central

2015-01-01

Conspectus The human body is a complex network of molecules, organelles, cells, tissues, and organs: an uncountable number of interactions and transformations interconnect all the system’s components. In addition to these biochemical components, biophysical components, such as pressure, flow, and morphology, and the location of all of these interactions play an important role in the human body. Technical difficulties have frequently limited researchers from observing cellular biology as it occurs within the human body, but some state-of-the-art analytical techniques have revealed distinct cellular behaviors that occur only in the context of the interactions. These types of findings have inspired bioanalytical chemists to provide new tools to better understand these cellular behaviors and interactions. What blocks us from understanding critical biological interactions in the human body? Conventional approaches are often too naïve to provide realistic data and in vivo whole animal studies give complex results that may or may not be relevant for humans. Microfluidics offers an opportunity to bridge these two extremes: while these studies will not model the complexity of the in vivo human system, they can control the complexity so researchers can examine critical factors of interest carefully and quantitatively. In addition, the use of human cells, such as cells isolated from donated blood, captures human-relevant data and limits the use of animals in research. In addition, researchers can adapt these systems easily and cost-effectively to a variety of high-end signal transduction mechanisms, facilitating high-throughput studies that are also spatially, temporally, or chemically resolved. These strengths should allow microfluidic platforms to reveal critical parameters in the human body and provide insights that will help with the translation of pharmacological advances to clinical trials. In this Account, we describe selected microfluidic innovations within the last 5 years that focus on modeling both biophysical and biochemical interactions in cellular communication, such as flow and cell–cell networks. We also describe more advanced systems that mimic higher level biological networks, such as organ on-a-chip and animal on-a-chip models. Since the first papers in the early 1990s, interest in the bioanalytical use of microfluidics has grown significantly. Advances in micro-/nanofabrication technology have allowed researchers to produce miniaturized, biocompatible assay platforms suitable for microfluidic studies in biochemistry and chemical biology. Well-designed microfluidic platforms can achieve quick, in vitro analyses on pico- and femtoliter volume samples that are temporally, spatially, and chemically resolved. In addition, controlled cell culture techniques using a microfluidic platform have produced biomimetic systems that allow researchers to replicate and monitor physiological interactions. Pioneering work has successfully created cell–fluid, cell–cell, cell–tissue, tissue–tissue, even organ-like level interfaces. Researchers have monitored cellular behaviors in these biomimetic microfluidic environments, producing validated model systems to understand human pathophysiology and to support the development of new therapeutics. PMID:24555566

Microfluidics-based in vivo mimetic systems for the study of cellular biology.

PubMed

Kim, Donghyuk; Wu, Xiaojie; Young, Ashlyn T; Haynes, Christy L

2014-04-15

The human body is a complex network of molecules, organelles, cells, tissues, and organs: an uncountable number of interactions and transformations interconnect all the system's components. In addition to these biochemical components, biophysical components, such as pressure, flow, and morphology, and the location of all of these interactions play an important role in the human body. Technical difficulties have frequently limited researchers from observing cellular biology as it occurs within the human body, but some state-of-the-art analytical techniques have revealed distinct cellular behaviors that occur only in the context of the interactions. These types of findings have inspired bioanalytical chemists to provide new tools to better understand these cellular behaviors and interactions. What blocks us from understanding critical biological interactions in the human body? Conventional approaches are often too naïve to provide realistic data and in vivo whole animal studies give complex results that may or may not be relevant for humans. Microfluidics offers an opportunity to bridge these two extremes: while these studies will not model the complexity of the in vivo human system, they can control the complexity so researchers can examine critical factors of interest carefully and quantitatively. In addition, the use of human cells, such as cells isolated from donated blood, captures human-relevant data and limits the use of animals in research. In addition, researchers can adapt these systems easily and cost-effectively to a variety of high-end signal transduction mechanisms, facilitating high-throughput studies that are also spatially, temporally, or chemically resolved. These strengths should allow microfluidic platforms to reveal critical parameters in the human body and provide insights that will help with the translation of pharmacological advances to clinical trials. In this Account, we describe selected microfluidic innovations within the last 5 years that focus on modeling both biophysical and biochemical interactions in cellular communication, such as flow and cell-cell networks. We also describe more advanced systems that mimic higher level biological networks, such as organ on-a-chip and animal on-a-chip models. Since the first papers in the early 1990s, interest in the bioanalytical use of microfluidics has grown significantly. Advances in micro-/nanofabrication technology have allowed researchers to produce miniaturized, biocompatible assay platforms suitable for microfluidic studies in biochemistry and chemical biology. Well-designed microfluidic platforms can achieve quick, in vitro analyses on pico- and femtoliter volume samples that are temporally, spatially, and chemically resolved. In addition, controlled cell culture techniques using a microfluidic platform have produced biomimetic systems that allow researchers to replicate and monitor physiological interactions. Pioneering work has successfully created cell-fluid, cell-cell, cell-tissue, tissue-tissue, even organ-like level interfaces. Researchers have monitored cellular behaviors in these biomimetic microfluidic environments, producing validated model systems to understand human pathophysiology and to support the development of new therapeutics.

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.

Safety Analysis of FMS/CTAS Interactions During Aircraft Arrivals

NASA Technical Reports Server (NTRS)

Leveson, Nancy G.

1998-01-01

This grant funded research on human-computer interaction design and analysis techniques, using future ATC environments as a testbed. The basic approach was to model the nominal behavior of both the automated and human procedures and then to apply safety analysis techniques to these models. Our previous modeling language, RSML, had been used to specify the system requirements for TCAS II for the FAA. Using the lessons learned from this experience, we designed a new modeling language that (among other things) incorporates features to assist in designing less error-prone human-computer interactions and interfaces and in detecting potential HCI problems, such as mode confusion. The new language, SpecTRM-RL, uses "intent" abstractions, based on Rasmussen's abstraction hierarchy, and includes both informal (English and graphical) specifications and formal, executable models for specifying various aspects of the system. One of the goals for our language was to highlight the system modes and mode changes to assist in identifying the potential for mode confusion. Three published papers resulted from this research. The first builds on the work of Degani on mode confusion to identify aspects of the system design that could lead to potential hazards. We defined and modeled modes differently than Degani and also defined design criteria for SpecTRM-RL models. Our design criteria include the Degani criteria but extend them to include more potential problems. In a second paper, Leveson and Palmer showed how the criteria for indirect mode transitions could be applied to a mode confusion problem found in several ASRS reports for the MD-88. In addition, we defined a visual task modeling language that can be used by system designers to model human-computer interaction. The visual models can be translated into SpecTRM-RL models, and then the SpecTRM-RL suite of analysis tools can be used to perform formal and informal safety analyses on the task model in isolation or integrated with the rest of the modeled system. We had hoped to be able to apply these modeling languages and analysis tools to a TAP air/ground trajectory negotiation scenario, but the development of the tools took more time than we anticipated.

A Generic Model of Dyadic Social Relationships

PubMed Central

Favre, Maroussia; Sornette, Didier

2015-01-01

We introduce a model of dyadic social interactions and establish its correspondence with relational models theory (RMT), a theory of human social relationships. RMT posits four elementary models of relationships governing human interactions, singly or in combination: Communal Sharing, Authority Ranking, Equality Matching, and Market Pricing. To these are added the limiting cases of asocial and null interactions, whereby people do not coordinate with reference to any shared principle. Our model is rooted in the observation that each individual in a dyadic interaction can do either the same thing as the other individual, a different thing or nothing at all. To represent these three possibilities, we consider two individuals that can each act in one out of three ways toward the other: perform a social action X or Y, or alternatively do nothing. We demonstrate that the relationships generated by this model aggregate into six exhaustive and disjoint categories. We propose that four of these categories match the four relational models, while the remaining two correspond to the asocial and null interactions defined in RMT. We generalize our results to the presence of N social actions. We infer that the four relational models form an exhaustive set of all possible dyadic relationships based on social coordination. Hence, we contribute to RMT by offering an answer to the question of why there could exist just four relational models. In addition, we discuss how to use our representation to analyze data sets of dyadic social interactions, and how social actions may be valued and matched by the agents. PMID:25826403

Cognitive Network Modeling as a Basis for Characterizing Human Communication Dynamics and Belief Contagion in Technology Adoption

NASA Technical Reports Server (NTRS)

Hutto, Clayton; Briscoe, Erica; Trewhitt, Ethan

2012-01-01

Societal level macro models of social behavior do not sufficiently capture nuances needed to adequately represent the dynamics of person-to-person interactions. Likewise, individual agent level micro models have limited scalability - even minute parameter changes can drastically affect a model's response characteristics. This work presents an approach that uses agent-based modeling to represent detailed intra- and inter-personal interactions, as well as a system dynamics model to integrate societal-level influences via reciprocating functions. A Cognitive Network Model (CNM) is proposed as a method of quantitatively characterizing cognitive mechanisms at the intra-individual level. To capture the rich dynamics of interpersonal communication for the propagation of beliefs and attitudes, a Socio-Cognitive Network Model (SCNM) is presented. The SCNM uses socio-cognitive tie strength to regulate how agents influence--and are influenced by--one another's beliefs during social interactions. We then present experimental results which support the use of this network analytical approach, and we discuss its applicability towards characterizing and understanding human information processing.

Acetylsalicylic acid (aspirin) and salicylic acid interaction with the human erythrocyte membrane bilayer induce in vitro changes in the morphology of erythrocytes.

PubMed

Suwalsky, Mario; Belmar, Jessica; Villena, Fernando; Gallardo, María José; Jemiola-Rzeminska, Malgorzata; Strzalka, Kazimierz

2013-11-01

Despite the well-documented information, there are insufficient reports concerning the effects of salicylate compounds on the structure and functions of cell membranes, particularly those of human erythrocytes. With the aim to better understand the molecular mechanisms of the interaction of acetylsalicylic acid (ASA) and salicylic acid (SA) with cell membranes, human erythrocyte membranes and molecular models were utilized. These consisted of bilayers of dimyristoylphosphatidylcholine (DMPC) and dimyristoylphosphatidylethanolamine (DMPE), representative of phospholipid classes located in the outer and inner monolayers of the human erythrocyte membrane, respectively. The capacity of ASA and SA to perturb the multibilayer structures of DMPC and DMPE was evaluated by X-ray diffraction while DMPC unilamellar vesicles (LUV) were studied by fluorescence spectroscopy. Moreover, we took advantage of the capability of differential scanning calorimetry (DSC) to detect the changes in the thermotropic phase behavior of lipid bilayers resulting from ASA and SA interaction with PC and PE molecules. In an attempt to further elucidate their effects on cell membranes, the present work also examined their influence on the morphology of intact human erythrocytes by means of defocusing and scanning electron microscopy, while isolated unsealed human erythrocyte membranes (IUM) were studied by fluorescence spectroscopy. Results indicated that both salicylates interact with human erythrocytes and their molecular models in a concentration-dependent manner perturbing their bilayer structures. Copyright © 2013 Elsevier Inc. All rights reserved.

Computational Modeling of Laser-Cell Biochemical Interactions

DTIC Science & Technology

2010-12-31

San Antonio, TX 78228 Jeffrey W. Oliver. Ph.D. Human Effectiveness Directorate Directed Energy Bioeffects Division Optical Radiation Branch...Affairs Case No. 11-080 Air Force Research Laboratory 711 Human Performance Wing Human Effectiveness Directorate Directed Energy Bioeffects...Directed Energy Bioeffects Division Human Effectiveness Directorate 711 Human Performance Wing Air Force Research Laboratory This report is

Hands-On! Living in the Biosphere: Production, Pattern, Population, and Diversity. Developing Active Learning Module on the Human Dimensions of Global Change.

ERIC Educational Resources Information Center

Brown, Dwight

Biogeography examines questions of organism inventory and pattern, organisms' interactions with the environment, and the processes that create and change inventory, pattern, and interactions. This learning module uses time series maps and simple simulation models to illustrate how human actions alter biological productivity patterns at local and…

What can music tell us about social interaction?

PubMed

D'Ausilio, Alessandro; Novembre, Giacomo; Fadiga, Luciano; Keller, Peter E

2015-03-01

Humans are innately social creatures, but cognitive neuroscience, that has traditionally focused on individual brains, is only now beginning to investigate social cognition through realistic interpersonal interaction. Music provides an ideal domain for doing so because it offers a promising solution for balancing the trade-off between ecological validity and experimental control when testing cognitive and brain functions. Musical ensembles constitute a microcosm that provides a platform for parametrically modeling the complexity of human social interaction. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

In Silico Analyses of Substrate Interactions with Human Serum Paraoxonase 1

DTIC Science & Technology

2008-01-01

substrate interactions of HuPON1 remains elusive. In this study, we apply homology modeling, docking, and molecular dynamic (MD) simulations to probe the...mod- eling; docking; molecular dynamics simulations ; binding free energy decomposition. 486 PROTEINS Published 2008 WILEY-LISS, INC. yThis article is a...apply homology modeling, docking, and molecular dynamic (MD) simulations to probe the binding interactions of HuPON1 with representative substrates. The

The BioGRID Interaction Database: 2011 update

PubMed Central

Stark, Chris; Breitkreutz, Bobby-Joe; Chatr-aryamontri, Andrew; Boucher, Lorrie; Oughtred, Rose; Livstone, Michael S.; Nixon, Julie; Van Auken, Kimberly; Wang, Xiaodong; Shi, Xiaoqi; Reguly, Teresa; Rust, Jennifer M.; Winter, Andrew; Dolinski, Kara; Tyers, Mike

2011-01-01

The Biological General Repository for Interaction Datasets (BioGRID) is a public database that archives and disseminates genetic and protein interaction data from model organisms and humans (http://www.thebiogrid.org). BioGRID currently holds 347 966 interactions (170 162 genetic, 177 804 protein) curated from both high-throughput data sets and individual focused studies, as derived from over 23 000 publications in the primary literature. Complete coverage of the entire literature is maintained for budding yeast (Saccharomyces cerevisiae), fission yeast (Schizosaccharomyces pombe) and thale cress (Arabidopsis thaliana), and efforts to expand curation across multiple metazoan species are underway. The BioGRID houses 48 831 human protein interactions that have been curated from 10 247 publications. Current curation drives are focused on particular areas of biology to enable insights into conserved networks and pathways that are relevant to human health. The BioGRID 3.0 web interface contains new search and display features that enable rapid queries across multiple data types and sources. An automated Interaction Management System (IMS) is used to prioritize, coordinate and track curation across international sites and projects. BioGRID provides interaction data to several model organism databases, resources such as Entrez-Gene and other interaction meta-databases. The entire BioGRID 3.0 data collection may be downloaded in multiple file formats, including PSI MI XML. Source code for BioGRID 3.0 is freely available without any restrictions. PMID:21071413

Are Interactions between cis-Regulatory Variants Evidence for Biological Epistasis or Statistical Artifacts?

PubMed

Fish, Alexandra E; Capra, John A; Bush, William S

2016-10-06

The importance of epistasis-or statistical interactions between genetic variants-to the development of complex disease in humans has been controversial. Genome-wide association studies of statistical interactions influencing human traits have recently become computationally feasible and have identified many putative interactions. However, statistical models used to detect interactions can be confounded, which makes it difficult to be certain that observed statistical interactions are evidence for true molecular epistasis. In this study, we investigate whether there is evidence for epistatic interactions between genetic variants within the cis-regulatory region that influence gene expression after accounting for technical, statistical, and biological confounding factors. We identified 1,119 (FDR = 5%) interactions that appear to regulate gene expression in human lymphoblastoid cell lines, a tightly controlled, largely genetically determined phenotype. Many of these interactions replicated in an independent dataset (90 of 803 tested, Bonferroni threshold). We then performed an exhaustive analysis of both known and novel confounders, including ceiling/floor effects, missing genotype combinations, haplotype effects, single variants tagged through linkage disequilibrium, and population stratification. Every interaction could be explained by at least one of these confounders, and replication in independent datasets did not protect against some confounders. Assuming that the confounding factors provide a more parsimonious explanation for each interaction, we find it unlikely that cis-regulatory interactions contribute strongly to human gene expression, which calls into question the relevance of cis-regulatory interactions for other human phenotypes. We additionally propose several best practices for epistasis testing to protect future studies from confounding. Copyright © 2016 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Identifying Keystone Species in the Human Gut Microbiome from Metagenomic Timeseries Using Sparse Linear Regression

PubMed Central

Fisher, Charles K.; Mehta, Pankaj

2014-01-01

Human associated microbial communities exert tremendous influence over human health and disease. With modern metagenomic sequencing methods it is now possible to follow the relative abundance of microbes in a community over time. These microbial communities exhibit rich ecological dynamics and an important goal of microbial ecology is to infer the ecological interactions between species directly from sequence data. Any algorithm for inferring ecological interactions must overcome three major obstacles: 1) a correlation between the abundances of two species does not imply that those species are interacting, 2) the sum constraint on the relative abundances obtained from metagenomic studies makes it difficult to infer the parameters in timeseries models, and 3) errors due to experimental uncertainty, or mis-assignment of sequencing reads into operational taxonomic units, bias inferences of species interactions due to a statistical problem called “errors-in-variables”. Here we introduce an approach, Learning Interactions from MIcrobial Time Series (LIMITS), that overcomes these obstacles. LIMITS uses sparse linear regression with boostrap aggregation to infer a discrete-time Lotka-Volterra model for microbial dynamics. We tested LIMITS on synthetic data and showed that it could reliably infer the topology of the inter-species ecological interactions. We then used LIMITS to characterize the species interactions in the gut microbiomes of two individuals and found that the interaction networks varied significantly between individuals. Furthermore, we found that the interaction networks of the two individuals are dominated by distinct “keystone species”, Bacteroides fragilis and Bacteroided stercosis, that have a disproportionate influence on the structure of the gut microbiome even though they are only found in moderate abundance. Based on our results, we hypothesize that the abundances of certain keystone species may be responsible for individuality in the human gut microbiome. PMID:25054627

Integrating Household Risk Mitigation Behavior in Flood Risk Analysis: An Agent-Based Model Approach.

PubMed

Haer, Toon; Botzen, W J Wouter; de Moel, Hans; Aerts, Jeroen C J H

2017-10-01

Recent studies showed that climate change and socioeconomic trends are expected to increase flood risks in many regions. However, in these studies, human behavior is commonly assumed to be constant, which neglects interaction and feedback loops between human and environmental systems. This neglect of human adaptation leads to a misrepresentation of flood risk. This article presents an agent-based model that incorporates human decision making in flood risk analysis. In particular, household investments in loss-reducing measures are examined under three economic decision models: (1) expected utility theory, which is the traditional economic model of rational agents; (2) prospect theory, which takes account of bounded rationality; and (3) a prospect theory model, which accounts for changing risk perceptions and social interactions through a process of Bayesian updating. We show that neglecting human behavior in flood risk assessment studies can result in a considerable misestimation of future flood risk, which is in our case study an overestimation of a factor two. Furthermore, we show how behavior models can support flood risk analysis under different behavioral assumptions, illustrating the need to include the dynamic adaptive human behavior of, for instance, households, insurers, and governments. The method presented here provides a solid basis for exploring human behavior and the resulting flood risk with respect to low-probability/high-impact risks. © 2016 The Authors Risk Analysis published by Wiley Periodicals, Inc. on behalf of Society for Risk Analysis.

Observing Consistency in Online Communication Patterns for User Re-Identification

PubMed Central

Venter, Hein S.

2016-01-01

Comprehension of the statistical and structural mechanisms governing human dynamics in online interaction plays a pivotal role in online user identification, online profile development, and recommender systems. However, building a characteristic model of human dynamics on the Internet involves a complete analysis of the variations in human activity patterns, which is a complex process. This complexity is inherent in human dynamics and has not been extensively studied to reveal the structural composition of human behavior. A typical method of anatomizing such a complex system is viewing all independent interconnectivity that constitutes the complexity. An examination of the various dimensions of human communication pattern in online interactions is presented in this paper. The study employed reliable server-side web data from 31 known users to explore characteristics of human-driven communications. Various machine-learning techniques were explored. The results revealed that each individual exhibited a relatively consistent, unique behavioral signature and that the logistic regression model and model tree can be used to accurately distinguish online users. These results are applicable to one-to-one online user identification processes, insider misuse investigation processes, and online profiling in various areas. PMID:27918593

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.

Integrative Radiation Biology

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

Barcellos-Hoff, Mary Helen

We plan to study tissue-level mechanisms important to human breast radiation carcinogenesis. We propose that the cell biology of irradiated tissues reveals a coordinated multicellular damage response program in which individual cell contributions are primarily directed towards suppression of carcinogenesis and reestablishment of homeostasis. We identified transforming growth factor β1 (TGFβ) as a pivotal signal. Notably, we have discovered that TGFβ suppresses genomic instability by controlling the intrinsic DNA damage response and centrosome integrity. However, TGFβ also mediates disruption of microenvironment interactions, which drive epithelial to mesenchymal transition in irradiated human mammary epithelial cells. This apparent paradox of positive andmore » negative controls by TGFβ is the topic of the present proposal. First, we postulate that these phenotypes manifest differentially following fractionated or chronic exposures; second, that the interactions of multiple cell types in tissues modify the responses evident in this single cell type culture models. The goals are to: 1) study the effect of low dose rate and fractionated radiation exposure in combination with TGFβ on the irradiated phenotype and genomic instability of non-malignant human epithelial cells; and 2) determine whether stromal-epithelial interactions suppress the irradiated phenotype in cell culture and the humanized mammary mouse model. These data will be used to 3) develop a systems biology model that integrates radiation effects across multiple levels of tissue organization and time. Modeling multicellular radiation responses coordinated via extracellular signaling could have a significant impact on the extrapolation of human health risks from high dose to low dose/rate radiation exposure.« less

Improving homology modeling of G-protein coupled receptors through multiple-template derived conserved inter-residue interactions

NASA Astrophysics Data System (ADS)

Chaudhari, Rajan; Heim, Andrew J.; Li, Zhijun

2015-05-01

Evidenced by the three-rounds of G-protein coupled receptors (GPCR) Dock competitions, improving homology modeling methods of helical transmembrane proteins including the GPCRs, based on templates of low sequence identity, remains an eminent challenge. Current approaches addressing this challenge adopt the philosophy of "modeling first, refinement next". In the present work, we developed an alternative modeling approach through the novel application of available multiple templates. First, conserved inter-residue interactions are derived from each additional template through conservation analysis of each template-target pairwise alignment. Then, these interactions are converted into distance restraints and incorporated in the homology modeling process. This approach was applied to modeling of the human β2 adrenergic receptor using the bovin rhodopsin and the human protease-activated receptor 1 as templates and improved model quality was demonstrated compared to the homology model generated by standard single-template and multiple-template methods. This method of "refined restraints first, modeling next", provides a fast and complementary way to the current modeling approaches. It allows rational identification and implementation of additional conserved distance restraints extracted from multiple templates and/or experimental data, and has the potential to be applicable to modeling of all helical transmembrane proteins.

Theory of Planned Behavior in the Classroom: An Examination of the Instructor Confirmation-Interaction Model

ERIC Educational Resources Information Center

Burns, Michael E.; Houser, Marian L.; Farris, Kristen LeBlanc

2018-01-01

The current study utilizes the theory of planned behavior (Ajzen "Organizational Behavior and Human Decision Processes," 50, 179-211 Ajzen 1991) to examine an instructor confirmation-interaction model in the instructional communication context to discover a means by which instructors might cultivate positive student attitudes and…

Using landscape disturbance and succession models to support forest management

Treesearch

Eric J. Gustafson; Brian R. Sturtevant; Anatoly S. Shvidenko; Robert M. Scheller

2010-01-01

Managers of forested landscapes must account for multiple, interacting ecological processes operating at broad spatial and temporal scales. These interactions can be of such complexity that predictions of future forest ecosystem states are beyond the analytical capability of the human mind. Landscape disturbance and succession models (LDSM) are predictive and...

Hunter-Gatherer Inter-Band Interaction Rates: Implications for Cumulative Culture

PubMed Central

Hill, Kim R.; Wood, Brian M.; Baggio, Jacopo; Hurtado, A. Magdalena; Boyd, Robert T.

2014-01-01

Our species exhibits spectacular success due to cumulative culture. While cognitive evolution of social learning mechanisms may be partially responsible for adaptive human culture, features of early human social structure may also play a role by increasing the number potential models from which to learn innovations. We present interview data on interactions between same-sex adult dyads of Ache and Hadza hunter-gatherers living in multiple distinct residential bands (20 Ache bands; 42 Hadza bands; 1201 dyads) throughout a tribal home range. Results show high probabilities (5%–29% per year) of cultural and cooperative interactions between randomly chosen adults. Multiple regression suggests that ritual relationships increase interaction rates more than kinship, and that affinal kin interact more often than dyads with no relationship. These may be important features of human sociality. Finally, yearly interaction rates along with survival data allow us to estimate expected lifetime partners for a variety of social activities, and compare those to chimpanzees. Hadza and Ache men are estimated to observe over 300 men making tools in a lifetime, whereas male chimpanzees interact with only about 20 other males in a lifetime. High intergroup interaction rates in ancestral humans may have promoted the evolution of cumulative culture. PMID:25047714

Hunter-gatherer inter-band interaction rates: implications for cumulative culture.

PubMed

Hill, Kim R; Wood, Brian M; Baggio, Jacopo; Hurtado, A Magdalena; Boyd, Robert T

2014-01-01

Our species exhibits spectacular success due to cumulative culture. While cognitive evolution of social learning mechanisms may be partially responsible for adaptive human culture, features of early human social structure may also play a role by increasing the number potential models from which to learn innovations. We present interview data on interactions between same-sex adult dyads of Ache and Hadza hunter-gatherers living in multiple distinct residential bands (20 Ache bands; 42 Hadza bands; 1201 dyads) throughout a tribal home range. Results show high probabilities (5%-29% per year) of cultural and cooperative interactions between randomly chosen adults. Multiple regression suggests that ritual relationships increase interaction rates more than kinship, and that affinal kin interact more often than dyads with no relationship. These may be important features of human sociality. Finally, yearly interaction rates along with survival data allow us to estimate expected lifetime partners for a variety of social activities, and compare those to chimpanzees. Hadza and Ache men are estimated to observe over 300 men making tools in a lifetime, whereas male chimpanzees interact with only about 20 other males in a lifetime. High intergroup interaction rates in ancestral humans may have promoted the evolution of cumulative culture.

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.

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

Modeling of interactions of electromagnetic fields with human bodies

NASA Astrophysics Data System (ADS)

Caputa, Krzysztof

Interactions of electromagnetic fields with the human body have been a subject of scientific interest and public concern. In recent years, issues in power line field effects and those of wireless telephones have been in the forefront of research. Engineering research compliments biological investigations by quantifying the induced fields in biological bodies due to exposure to external fields. The research presented in this thesis aims at providing reliable tools, and addressing some of the unresolved issues related to interactions with the human body of power line fields and fields produced by handheld wireless telephones. The research comprises two areas, namely development of versatile models of the human body and their visualisation, and verification and application of numerical codes to solve selected problems of interest. The models of the human body, which are based on the magnetic resonance scans of the body, are unique and differ considerably from other models currently available. With the aid of computer software developed, the models can be arranged to different postures, and medical devices can be accurately placed inside them. A previously developed code for modeling interactions of power line fields with biological bodies has been verified by rigorous, quantitative inter-laboratory comparison for two human body models. This code has been employed to model electromagnetic interference (EMI) of the magnetic field with implanted cardiac pacemakers. In this case, the correct placement and representation of the pacemaker leads are critical, as simplified computations have been shown to result in significant errors. In modeling interactions of wireless communication devices, the finite difference time domain technique (FDTD) has become a de facto standard. The previously developed code has been verified by comparison with the analytical solution for a conductive sphere. While previously researchers limited their verifications to principal axes of the sphere, a global (volumetric) fields evaluation allowed for identification of locations of errors due to staircasing, and the singularities responsible for them. In evaluation of safety of cellular telephones and similar devices, the specific absorption rate (SAR) averaged over a 1 g (in North America) or 10 g (in Europe) cube is used. A new algorithm has been developed and tested, which allows for automatic and reliable identification of the maximum value with a user-selected inclusion of air (if required). This algorithm and the verified code have been used to model performance of a commercial telephone in the proximity of head, and to model EMI of this phone with a hearing aid placed in the ear canal. The modeling results, which relied on a proper representation of the antenna consisting of two helices and complex shape and structure of the telephone case, have been confirmed by measurements performed in another laboratory. Similarly, the EMI modeling has been in agreement with acoustic measurements (performed elsewhere). The latter comparison has allowed to confirm anticipated mechanism of the EMI.

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 a common conceptual framework, thus providing a unified socio-hydrologic basis for the study of coupled human-water systems. The exploration of the theoretical connections between the two subsystems pushes the water system modeling from a problem-solving orientation to puzzle-solving orientation.

Towards a Computational Model of Sketching

DTIC Science & Technology

2000-01-01

interaction that sketching provides in human-to- human communication , multimodal research will rely heavily upon, and even drive, AI research . This...can. Dimensions of sketching The power of sketching in human communication arises from the high bandwidth it provides [21] . There is high perceptual

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.

On the Utilization of Social Animals as a Model for Social Robotics

PubMed Central

Miklósi, Ádám; Gácsi, Márta

2012-01-01

Social robotics is a thriving field in building artificial agents. The possibility to construct agents that can engage in meaningful social interaction with humans presents new challenges for engineers. In general, social robotics has been inspired primarily by psychologists with the aim of building human-like robots. Only a small subcategory of “companion robots” (also referred to as robotic pets) was built to mimic animals. In this opinion essay we argue that all social robots should be seen as companions and more conceptual emphasis should be put on the inter-specific interaction between humans and social robots. This view is underlined by the means of an ethological analysis and critical evaluation of present day companion robots. We suggest that human–animal interaction provides a rich source of knowledge for designing social robots that are able to interact with humans under a wide range of conditions. PMID:22457658

The Use of the Humanized Mouse Model in Gene Therapy and Immunotherapy for HIV and Cancer

PubMed Central

Carrillo, Mayra A.; Zhen, Anjie; Kitchen, Scott G.

2018-01-01

HIV and cancer remain prevailing sources of morbidity and mortality worldwide. There are current efforts to discover novel therapeutic strategies for the treatment or cure of these diseases. Humanized mouse models provide the investigative tool to study the interaction between HIV or cancer and the human immune system in vivo. These humanized models consist of immunodeficient mice transplanted with human cells, tissues, or hematopoietic stem cells that result in reconstitution with a nearly full human immune system. In this review, we discuss preclinical studies evaluating therapeutic approaches in stem cell-based gene therapy and T cell-based immunotherapies for HIV and cancer using a humanized mouse model and some recent advances in using checkpoint inhibitors to improve antiviral or antitumor responses. PMID:29755454

Information Interaction: Providing a Framework for Information Architecture.

ERIC Educational Resources Information Center

Toms, Elaine G.

2002-01-01

Discussion of information architecture focuses on a model of information interaction that bridges the gap between human and computer and between information behavior and information retrieval. Illustrates how the process of information interaction is affected by the user, the system, and the content. (Contains 93 references.) (LRW)

From The Cover: Reconstruction of functionally normal and malignant human breast tissues in mice

NASA Astrophysics Data System (ADS)

Kuperwasser, Charlotte; Chavarria, Tony; Wu, Min; Magrane, Greg; Gray, Joe W.; Carey, Loucinda; Richardson, Andrea; Weinberg, Robert A.

2004-04-01

The study of normal breast epithelial morphogenesis and carcinogenesis in vivo has largely used rodent models. Efforts at studying mammary morphogenesis and cancer with xenotransplanted human epithelial cells have failed to recapitulate the full extent of development seen in the human breast. We have developed an orthotopic xenograft model in which both the stromal and epithelial components of the reconstructed mammary gland are of human origin. Genetic modification of human stromal cells before the implantation of ostensibly normal human mammary epithelial cells resulted in the outgrowth of benign and malignant lesions. This experimental model allows for studies of human epithelial morphogenesis and differentiation in vivo and underscores the critical role of heterotypic interactions in human breast development and carcinogenesis.

Comparison of a Conceptual Groundwater Model and Physically Based Groundwater Mode

NASA Astrophysics Data System (ADS)

Yang, J.; Zammit, C.; Griffiths, J.; Moore, C.; Woods, R. A.

2017-12-01

Groundwater is a vital resource for human activities including agricultural practice and urban water demand. Hydrologic modelling is an important way to study groundwater recharge, movement and discharge, and its response to both human activity and climate change. To understand the groundwater hydrologic processes nationally in New Zealand, we have developed a conceptually based groundwater flow model, which is fully integrated into a national surface-water model (TopNet), and able to simulate groundwater recharge, movement, and interaction with surface water. To demonstrate the capability of this groundwater model (TopNet-GW), we applied the model to an irrigated area with water shortage and pollution problems in the upper Ruamahanga catchment in Great Wellington Region, New Zealand, and compared its performance with a physically-based groundwater model (MODFLOW). The comparison includes river flow at flow gauging sites, and interaction between groundwater and river. Results showed that the TopNet-GW produced similar flow and groundwater interaction patterns as the MODFLOW model, but took less computation time. This shows the conceptually-based groundwater model has the potential to simulate national groundwater process, and could be used as a surrogate for the more physically based model.

Bio-Physicochemical Interactions of Engineered Nanomaterials in In Vitro Cell Culture Model

DTIC Science & Technology

2012-08-14

viz. human hepatocarcinoma cell line (Hep G2), human adinocarcinoma cell line (A549), human embryonic kidney cell line (HEK 293), human neuroblastoma...Glutamine, 1% Na-Pyruvate and 10 ml/L antibiotic solution at 37oC under a humidified atmosphere of 5% CO2/95% air.  Human hepatocarcinoma cell line

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.

Different binding mechanisms of neutral and anionic poly-/perfluorinated chemicals to human transthyretin revealed by In silico models.

PubMed

Yang, Xianhai; Lyakurwa, Felichesmi; Xie, Hongbin; Chen, Jingwen; Li, Xuehua; Qiao, Xianliang; Cai, Xiyun

2017-09-01

Chemical forms-dependent binding interactions between phenolic compounds and human transthyretin (hTTR) have been elaborated previously. However, it is not known whether the binding interactions between ionizable halogenated alphatic compounds and hTTR also have the same manner. In this study, poly-/perfluorinated chemicals (PFCs) were selected as model compounds and molecular dynamic simulation was performed to investigate the binding mechanisms between PFCs and hTTR. Results show the binding interactions between the halogenated aliphatic compounds and hTTR are related to the chemical forms. The ionized groups of PFCs can form electrostatic interactions with the -NH + 3 groups of Lys 15 residues in hTTR and form hydrogen bonds with the residues of hTTR. By analyzing the molecular orbital energies of PFCs, we also found that the anionic groups (nucleophile) in PFCs could form electron donor - acceptor interactions with the -NH + 3 groups (electrophile) in Lys 15. The aforementioned orientational interactions make the ionized groups of the PFCs point toward the entry port of the binding site. The roles of fluorine atoms in the binding interactions were also explored. The fluorine atoms can influence the binding interactions via inductive effects. Appropriate molecular descriptors were selected to characterize these interactions, and two quantitative structure-activity relationship models were developed. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

Machine Learning for Detecting Gene-Gene Interactions

PubMed Central

McKinney, Brett A.; Reif, David M.; Ritchie, Marylyn D.; Moore, Jason H.

2011-01-01

Complex interactions among genes and environmental factors are known to play a role in common human disease aetiology. There is a growing body of evidence to suggest that complex interactions are ‘the norm’ and, rather than amounting to a small perturbation to classical Mendelian genetics, interactions may be the predominant effect. Traditional statistical methods are not well suited for detecting such interactions, especially when the data are high dimensional (many attributes or independent variables) or when interactions occur between more than two polymorphisms. In this review, we discuss machine-learning models and algorithms for identifying and characterising susceptibility genes in common, complex, multifactorial human diseases. We focus on the following machine-learning methods that have been used to detect gene-gene interactions: neural networks, cellular automata, random forests, and multifactor dimensionality reduction. We conclude with some ideas about how these methods and others can be integrated into a comprehensive and flexible framework for data mining and knowledge discovery in human genetics. PMID:16722772

Interaction of fluorescently labeled pyrrole-imidazole polyamide probes with fixed and living murine and human cells.

PubMed

Nozeret, Karine; Loll, François; Cardoso, Gildas Mouta; Escudé, Christophe; Boutorine, Alexandre S

2018-06-01

Pericentromeric heterochromatin plays important roles in controlling gene expression and cellular differentiation. Fluorescent pyrrole-imidazole polyamides targeting murine pericentromeric DNA (major satellites) can be used for the visualization of pericentromeric heterochromatin foci in live mouse cells. New derivatives targeting human repeated DNA sequences (α-satellites) were synthesized and their interaction with target DNA was characterized. The possibility to use major satellite and α -satellite binding polyamides as tools for staining pericentromeric heterochromatin was further investigated in fixed and living mouse and human cells. The staining that was previously observed using the mouse model was further characterized and optimized, but remained limited regarding the fluorophores that can be used. The promising results regarding the staining in the mouse model could not be extended to the human model. Experiments performed in human cells showed chromosomal DNA staining without selectivity. Factors limiting the use of fluorescent polyamides, in particular probe aggregation in the cytoplasm, were investigated. Results are discussed with regards to structure and affinity of probes, density of target sites and chromatin accessibility in both models. Copyright © 2018 Elsevier B.V. and Société Française de Biochimie et Biologie Moléculaire (SFBBM). All rights reserved.

Evolving hard problems: Generating human genetics datasets with a complex etiology.

PubMed

Himmelstein, Daniel S; Greene, Casey S; Moore, Jason H

2011-07-07

A goal of human genetics is to discover genetic factors that influence individuals' susceptibility to common diseases. Most common diseases are thought to result from the joint failure of two or more interacting components instead of single component failures. This greatly complicates both the task of selecting informative genetic variants and the task of modeling interactions between them. We and others have previously developed algorithms to detect and model the relationships between these genetic factors and disease. Previously these methods have been evaluated with datasets simulated according to pre-defined genetic models. Here we develop and evaluate a model free evolution strategy to generate datasets which display a complex relationship between individual genotype and disease susceptibility. We show that this model free approach is capable of generating a diverse array of datasets with distinct gene-disease relationships for an arbitrary interaction order and sample size. We specifically generate eight-hundred Pareto fronts; one for each independent run of our algorithm. In each run the predictiveness of single genetic variation and pairs of genetic variants have been minimized, while the predictiveness of third, fourth, or fifth-order combinations is maximized. Two hundred runs of the algorithm are further dedicated to creating datasets with predictive four or five order interactions and minimized lower-level effects. This method and the resulting datasets will allow the capabilities of novel methods to be tested without pre-specified genetic models. This allows researchers to evaluate which methods will succeed on human genetics problems where the model is not known in advance. We further make freely available to the community the entire Pareto-optimal front of datasets from each run so that novel methods may be rigorously evaluated. These 76,600 datasets are available from http://discovery.dartmouth.edu/model_free_data/.

Toward experimental validation of a model for human sensorimotor learning and control in teleoperation

NASA Astrophysics Data System (ADS)

Roth, Eatai; Howell, Darrin; Beckwith, Cydney; Burden, Samuel A.

2017-05-01

Humans, interacting with cyber-physical systems (CPS), formulate beliefs about the system's dynamics. It is natural to expect that human operators, tasked with teleoperation, use these beliefs to control the remote robot. For tracking tasks in the resulting human-cyber-physical system (HCPS), theory suggests that human operators can achieve exponential tracking (in stable systems) without state estimation provided they possess an accurate model of the system's dynamics. This internalized inverse model, however, renders a portion of the system state unobservable to the human operator—the zero dynamics. Prior work shows humans can track through observable linear dynamics, thus we focus on nonlinear dynamics rendered unobservable through tracking control. We propose experiments to assess the human operator's ability to learn and invert such models, and distinguish this behavior from that achieved by pure feedback control.

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

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 int...

The Emerging and Employed Worker: Planning for the Strategic Imperative.

ERIC Educational Resources Information Center

Geroy, Gary D.

This paper describes a series of four models around which plans can be developed to determine human development needs. It presents needs assessment models describing the process and participant interaction by which information is gathered to be used in education, training, funding, and/or other human resource development interventions to increase…

A Goal-Oriented Model of Natural Language Interaction

DTIC Science & Technology

1977-01-01

AHSTKACT This report describes a research program in modeling human communication . The methodology involved selecting a single, naturally-occurring...knowledge is seldom used in the design process. Human communication skills have not bee’’ characferi?ed at a level of detail appropriate for guiding design...necessarily combine to give a complete picture of human communication . Experience over several more dialogues may suggest that one or all be replaced

Integrating Human Factors into Space Vehicle Processing for Risk Management

NASA Technical Reports Server (NTRS)

Woodbury, Sarah; Richards, Kimberly J.

2008-01-01

This presentation will discuss the multiple projects performed in United Space Alliance's Human Engineering Modeling and Performance (HEMAP) Lab, improvements that resulted from analysis, and the future applications of the HEMAP Lab for risk assessment by evaluating human/machine interaction and ergonomic designs.

The HUPO PSI's molecular interaction format--a community standard for the representation of protein interaction data.

PubMed

Hermjakob, Henning; Montecchi-Palazzi, Luisa; Bader, Gary; Wojcik, Jérôme; Salwinski, Lukasz; Ceol, Arnaud; Moore, Susan; Orchard, Sandra; Sarkans, Ugis; von Mering, Christian; Roechert, Bernd; Poux, Sylvain; Jung, Eva; Mersch, Henning; Kersey, Paul; Lappe, Michael; Li, Yixue; Zeng, Rong; Rana, Debashis; Nikolski, Macha; Husi, Holger; Brun, Christine; Shanker, K; Grant, Seth G N; Sander, Chris; Bork, Peer; Zhu, Weimin; Pandey, Akhilesh; Brazma, Alvis; Jacq, Bernard; Vidal, Marc; Sherman, David; Legrain, Pierre; Cesareni, Gianni; Xenarios, Ioannis; Eisenberg, David; Steipe, Boris; Hogue, Chris; Apweiler, Rolf

2004-02-01

A major goal of proteomics is the complete description of the protein interaction network underlying cell physiology. A large number of small scale and, more recently, large-scale experiments have contributed to expanding our understanding of the nature of the interaction network. However, the necessary data integration across experiments is currently hampered by the fragmentation of publicly available protein interaction data, which exists in different formats in databases, on authors' websites or sometimes only in print publications. Here, we propose a community standard data model for the representation and exchange of protein interaction data. This data model has been jointly developed by members of the Proteomics Standards Initiative (PSI), a work group of the Human Proteome Organization (HUPO), and is supported by major protein interaction data providers, in particular the Biomolecular Interaction Network Database (BIND), Cellzome (Heidelberg, Germany), the Database of Interacting Proteins (DIP), Dana Farber Cancer Institute (Boston, MA, USA), the Human Protein Reference Database (HPRD), Hybrigenics (Paris, France), the European Bioinformatics Institute's (EMBL-EBI, Hinxton, UK) IntAct, the Molecular Interactions (MINT, Rome, Italy) database, the Protein-Protein Interaction Database (PPID, Edinburgh, UK) and the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING, EMBL, Heidelberg, Germany).

Effects of human dynamics on epidemic spreading in Côte d'Ivoire

NASA Astrophysics Data System (ADS)

Li, Ruiqi; Wang, Wenxu; Di, Zengru

2017-02-01

Understanding and predicting outbreaks of contagious diseases are crucial to the development of society and public health, especially for underdeveloped countries. However, challenging problems are encountered because of complex epidemic spreading dynamics influenced by spatial structure and human dynamics (including both human mobility and human interaction intensity). We propose a systematical model to depict nationwide epidemic spreading in Côte d'Ivoire, which integrates multiple factors, such as human mobility, human interaction intensity, and demographic features. We provide insights to aid in modeling and predicting the epidemic spreading process by data-driven simulation and theoretical analysis, which is otherwise beyond the scope of local evaluation and geometrical views. We show that the requirement that the average local basic reproductive number to be greater than unity is not necessary for outbreaks of epidemics. The observed spreading phenomenon can be roughly explained as a heterogeneous diffusion-reaction process by redefining mobility distance according to the human mobility volume between nodes, which is beyond the geometrical viewpoint. However, the heterogeneity of human dynamics still poses challenges to precise prediction.

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.

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.

Positional cloning in mice and its use for molecular dissection of inflammatory arthritis.

PubMed

Abe, Koichiro; Yu, Philipp

2009-02-01

One of the upcoming next quests in the field of genetics might be molecular dissection of the genetic and environmental components of human complex diseases. In humans, however, there are certain experimental limitations for identification of a single component of the complex interactions by genetic analyses. Experimental animals offer simplified models for genetic and environmental interactions in human complex diseases. In particular, mice are the best mammalian models because of a long history and ample experience for genetic analyses. Forward genetics, which includes genetic screen and subsequent positional cloning of the causative genes, is a powerful strategy to dissect a complex phenomenon without preliminarily molecular knowledge of the process. In this review, first, we describe a general scheme of positional cloning in mice. Next, recent accomplishments on the patho-mechanisms of inflammatory arthritis by forward genetics approaches are introduced; Positional cloning effort for skg, Ali5, Ali18, cmo, and lupo mutants are provided as examples for the application to human complex diseases. As seen in the examples, the identification of genetic factors by positional cloning in the mouse have potential in solving molecular complexity of gene-environment interactions in human complex diseases.

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.

Narrative-Based Interactive Learning Environments from Modelling Reasoning

ERIC Educational Resources Information Center

Yearwood, John; Stranieri, Andrew

2007-01-01

Narrative and story telling has a long history of use in structuring, organising and communicating human experience. This paper describes a narrative based interactive intelligent learning environment which aims to elucidate practical reasoning using interactive emergent narratives that can be used in training novices in decision making. Its…

Simulating the decentralized processes of the human immune system in a virtual anatomy model.

PubMed

Sarpe, Vladimir; Jacob, Christian

2013-01-01

Many physiological processes within the human body can be perceived and modeled as large systems of interacting particles or swarming agents. The complex processes of the human immune system prove to be challenging to capture and illustrate without proper reference to the spatial distribution of immune-related organs and systems. Our work focuses on physical aspects of immune system processes, which we implement through swarms of agents. This is our first prototype for integrating different immune processes into one comprehensive virtual physiology simulation. Using agent-based methodology and a 3-dimensional modeling and visualization environment (LINDSAY Composer), we present an agent-based simulation of the decentralized processes in the human immune system. The agents in our model - such as immune cells, viruses and cytokines - interact through simulated physics in two different, compartmentalized and decentralized 3-dimensional environments namely, (1) within the tissue and (2) inside a lymph node. While the two environments are separated and perform their computations asynchronously, an abstract form of communication is allowed in order to replicate the exchange, transportation and interaction of immune system agents between these sites. The distribution of simulated processes, that can communicate across multiple, local CPUs or through a network of machines, provides a starting point to build decentralized systems that replicate larger-scale processes within the human body, thus creating integrated simulations with other physiological systems, such as the circulatory, endocrine, or nervous system. Ultimately, this system integration across scales is our goal for the LINDSAY Virtual Human project. Our current immune system simulations extend our previous work on agent-based simulations by introducing advanced visualizations within the context of a virtual human anatomy model. We also demonstrate how to distribute a collection of connected simulations over a network of computers. As a future endeavour, we plan to use parameter tuning techniques on our model to further enhance its biological credibility. We consider these in silico experiments and their associated modeling and optimization techniques as essential components in further enhancing our capabilities of simulating a whole-body, decentralized immune system, to be used both for medical education and research as well as for virtual studies in immunoinformatics.

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

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.

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).

Rana computatrix to human language: towards a computational neuroethology of language evolution.

PubMed

Arbib, Michael A

2003-10-15

Walter's Machina speculatrix inspired the name Rana computatrix for a family of models of visuomotor coordination in the frog, which contributed to the development of computational neuroethology. We offer here an 'evolutionary' perspective on models in the same tradition for rat, monkey and human. For rat, we show how the frog-like taxon affordance model provides a basis for the spatial navigation mechanisms that involve the hippocampus and other brain regions. For monkey, we recall two models of neural mechanisms for visuomotor coordination. The first, for saccades, shows how interactions between the parietal and frontal cortex augment superior colliculus seen as the homologue of frog tectum. The second, for grasping, continues the theme of parieto-frontal interactions, linking parietal affordances to motor schemas in premotor cortex. It further emphasizes the mirror system for grasping, in which neurons are active both when the monkey executes a specific grasp and when it observes a similar grasp executed by others. The model of human-brain mechanisms is based on the mirror-system hypothesis of the evolution of the language-ready brain, which sees the human Broca's area as an evolved extension of the mirror system for grasping.

Modeling Visual, Vestibular and Oculomotor Interactions in Self-Motion Estimation

NASA Technical Reports Server (NTRS)

Perrone, John

1997-01-01

A computational model of human self-motion perception has been developed in collaboration with Dr. Leland S. Stone at NASA Ames Research Center. The research included in the grant proposal sought to extend the utility of this model so that it could be used for explaining and predicting human performance in a greater variety of aerospace applications. This extension has been achieved along with physiological validation of the basic operation of the model.

A System Biology Perspective on Environment-Host-Microbe Interactions.

PubMed

Chen, Lianmin; Garmaeva, Sanzhima; Zherankova, Alexandra; Fu, Jingyuan; Wijmenga, Cisca

2018-04-16

A vast, complex and dynamic consortium of microorganisms known as the gut microbiome colonizes the human gut. Over the past few decades we have developed an increased awareness of its important role in human health. In this review we discuss the role of the gut microbiome in complex diseases and the possible causal scenarios behind its interactions with the host genome and environmental factors. We then propose a new analysis framework that combines a systems biology approach, cross-kingdom integration of multiple levels of omics data, and innovative in vitro models to yield an integrated picture of human host-microbe interactions. This new framework will lay the foundation for the development of the next phase in personalized medicine.

Sculpting the brain

PubMed Central

Garcia-Lopez, Pablo

2012-01-01

Neuroculture, conceived as the reciprocal interaction between neuroscience and different areas of human knowledge is influencing our lives under the prism of the latest neuroscientific discoveries. Simultaneously, neuroculture can create new models of thinking that can significantly impact neuroscientists' daily practice. Especially interesting is the interaction that takes place between neuroscience and the arts. This interaction takes place at different, infinite levels and contexts. I contextualize my work inside this neurocultural framework. Through my artwork, I try to give a more natural vision of the human brain, which could help to develop a more humanistic culture. PMID:22363275

Recent Progress in Hepatocyte Culture Models and Their Application to the Assessment of Drug Metabolism, Transport, and Toxicity in Drug Discovery: The Value of Tissue Engineering for the Successful Development of a Microphysiological System.

PubMed

Tetsuka, Kazuhiro; Ohbuchi, Masato; Tabata, Kenji

2017-09-01

Tissue engineering technology has provided many useful culture models. This article reviews the merits of this technology in a hepatocyte culture system and describes the applications of the sandwich-cultured hepatocyte model in drug discovery. In addition, we also review recent investigations of the utility of the 3-dimensional bioprinted human liver tissue model and spheroid model. Finally, we present the future direction and developmental challenges of a hepatocyte culture model for the successful establishment of a microphysiological system, represented as an organ-on-a-chip and even as a human-on-a-chip. A merit of advanced culture models is their potential use for detecting hepatotoxicity through repeated exposure to chemicals as they allow long-term culture while maintaining hepatocyte functionality. As a future direction, such advanced hepatocyte culture systems can be connected to other tissue models for evaluating tissue-to-tissue interaction beyond cell-to-cell interaction. This combination of culture models could represent parts of the human body in a microphysiological system. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

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.

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.

Molecular design of two sterol 14α-demethylase homology models and their interactions with the azole antifungals ketoconazole and bifonazole

NASA Astrophysics Data System (ADS)

Rupp, Bernd; Raub, Stephan; Marian, Christel; Höltje, Hans-Dieter

2005-03-01

Sterol 14α-demethylase (CYP51) is one of the known major targets for azole antifungals. Therapeutic side effects of these antifungals are based on interactions of the azoles with the human analogue enzyme. This study describes for the first time a comparison of a human CYP51 (HU-CYP51) homology model with a homology model of the fungal CYP51 of Candida albicans (CA-CYP51). Both models are constructed by using the crystal structure of Mycobacterium tuberculosis MT-CYP51 (PDB code: 1EA1). The binding mode of the azole ketoconazole is investigated in molecular dynamics simulations with the GROMACS force field. The usage of special parameters for the iron azole complex binding is necessary to obtain the correct complex geometry in the active site of the enzyme models. Based on the dynamics simulations it is possible to explain the enantioselectivity of the human enzyme and also to predict the binding mode of the isomers of ketoconazole in the active site of the fungal model.

Single-cell tracking of flavivirus RNA uncovers species-specific interactions with the immune system dictating disease outcome

PubMed Central

Douam, Florian; Hrebikova, Gabriela; Albrecht, Yentli E. Soto; Sellau, Julie; Sharon, Yael; Ding, Qiang; Ploss, Alexander

2017-01-01

Positive-sense RNA viruses pose increasing health and economic concerns worldwide. Our limited understanding of how these viruses interact with their host and how these processes lead to virulence and disease seriously hampers the development of anti-viral strategies. Here, we demonstrate the tracking of (+) and (−) sense viral RNA at single-cell resolution within complex subsets of the human and murine immune system in different mouse models. Our results provide insights into how a prototypic flavivirus, yellow fever virus (YFV-17D), differentially interacts with murine and human hematopoietic cells in these mouse models and how these dynamics influence distinct outcomes of infection. We detect (−) YFV-17D RNA in specific secondary lymphoid compartments and cell subsets not previously recognized as permissive for YFV replication, and we highlight potential virus–host interaction events that could be pivotal in regulating flavivirus virulence and attenuation. PMID:28290449

Variables, Decisions, and Scripting in Construct

DTIC Science & Technology

2009-09-01

grounded in sociology and cognitive science which seeks to model the processes and situations by which humans interact and share information...Construct is an embodiment of constructuralism (Carley 1986), a theory which posits that human social structures and cognitive structures co-evolve so that...human cognition reflects human social behavior, and that human social behavior simultaneously influences cognitive processes. Recent work with

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.

Environmental and anthropogenic factors affecting the increasing occurrence of shark-human interactions around a fast-developing Indian Ocean island.

PubMed

Lagabrielle, Erwann; Allibert, Agathe; Kiszka, Jeremy J; Loiseau, Nicolas; Kilfoil, James P; Lemahieu, Anne

2018-02-27

Understanding the environmental drivers of interactions between predators and humans is critical for public safety and management purposes. In the marine environment, this issue is exemplified by shark-human interactions. The annual shark bite incidence rate (SBIR) in La Réunion (Indian Ocean) is among the highest in the world (up to 1 event per 24,000 hours of surfing) and has experienced a 23-fold increase over the 2005-2016 period. Since 1988, 86% of shark bite events on ocean-users involved surfers off the leeward coast, where 96% of surfing activities took place. We modeled the SBIR as a function of environmental variables, including benthic substrate, sea temperature and period of day. The SBIR peaked in winter, during the afternoon and dramatically increased on coral substrate since the mid-2000s. Seasonal patterns of increasing SBIR followed similar fluctuations of large coastal shark occurrences (particularly the bull shark Carcharhinus leucas), consistent with the hypothesis that higher shark presence may result in an increasing likelihood of shark bite events. Potential contributing factors and adaptation of ocean-users to the increasing shark bite hazard are discussed. This interdisciplinary research contributes to a better understanding of shark-human interactions. The modeling method is relevant for wildlife hazard management in general.

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.

Targeted Proteomics and Absolute Protein Quantification for the Construction of a Stoichiometric Host-Pathogen Surface Density Model*

PubMed Central

Sjöholm, Kristoffer; Kilsgård, Ola; Teleman, Johan; Happonen, Lotta; Malmström, Lars; Malmström, Johan

2017-01-01

Sepsis is a systemic immune response responsible for considerable morbidity and mortality. Molecular modeling of host-pathogen interactions in the disease state represents a promising strategy to define molecular events of importance for the transition from superficial to invasive infectious diseases. Here we used the Gram-positive bacterium Streptococcus pyogenes as a model system to establish a mass spectrometry based workflow for the construction of a stoichiometric surface density model between the S. pyogenes surface, the surface virulence factor M-protein, and adhered human blood plasma proteins. The workflow relies on stable isotope labeled reference peptides and selected reaction monitoring mass spectrometry analysis of a wild-type strain and an M-protein deficient mutant strain, to generate absolutely quantified protein stoichiometry ratios between S. pyogenes and interacting plasma proteins. The stoichiometry ratios in combination with a novel targeted mass spectrometry method to measure cell numbers enabled the construction of a stoichiometric surface density model using protein structures available from the protein data bank. The model outlines the topology and density of the host-pathogen protein interaction network on the S. pyogenes bacterial surface, revealing a dense and highly organized protein interaction network. Removal of the M-protein from S. pyogenes introduces a drastic change in the network topology, validated by electron microscopy. We propose that the stoichiometric surface density model of S. pyogenes in human blood plasma represents a scalable framework that can continuously be refined with the emergence of new results. Future integration of new results will improve the understanding of protein-protein interactions and their importance for bacterial virulence. Furthermore, we anticipate that the general properties of the developed workflow will facilitate the production of stoichiometric surface density models for other types of host-pathogen interactions. PMID:28183813

Can Inhibitors of Snake Venom Phospholipases A₂ Lead to New Insights into Anti-Inflammatory Therapy in Humans? A Theoretical Study.

PubMed

Sales, Thaís A; Marcussi, Silvana; da Cunha, Elaine F F; Kuca, Kamil; Ramalho, Teodorico C

2017-10-25

Human phospholipase A₂ ( h PLA₂) of the IIA group (HGIIA) catalyzes the hydrolysis of membrane phospholipids, producing arachidonic acid and originating potent inflammatory mediators. Therefore, molecules that can inhibit this enzyme are a source of potential anti-inflammatory drugs, with different action mechanisms of known anti-inflammatory agents. For the study and development of new anti-inflammatory drugs with this action mechanism, snake venom PLA₂ ( sv PLA₂) can be employed, since the sv PLA₂ has high similarity with the human PLA₂ HGIIA. Despite the high similarity between these secretory PLA₂s , it is still not clear if these toxins can really be employed as an experimental model to predict the interactions that occur with the human PLA₂ HGIIA and its inhibitors. Thus, the present study aims to compare and evaluate, by means of theoretical calculations, docking and molecular dynamics simulations, as well as experimental studies, the interactions of human PLA₂ HGIIA and two sv PLA₂s , Bothrops toxin II and Crotoxin B (BthTX-II and CB, respectively). Our theoretical findings corroborate experimental data and point out that the human PLA₂ HGIIA and sv PLA₂ BthTX-II lead to similar interactions with the studied compounds. From our results, the sv PLA₂ BthTX-II can be used as an experimental model for the development of anti-inflammatory drugs for therapy in humans.

An integrated modeling framework for exploring flow regime and water quality changes with increasing biofuel crop production in the U.S. Corn Belt

NASA Astrophysics Data System (ADS)

Yaeger, Mary A.; Housh, Mashor; Cai, Ximing; Sivapalan, Murugesu

2014-12-01

To better address the dynamic interactions between human and hydrologic systems, we develop an integrated modeling framework that employs a System of Systems optimization model to emulate human development decisions which are then incorporated into a watershed model to estimate the resulting hydrologic impacts. The two models are run interactively to simulate the coevolution of coupled human-nature systems, such that reciprocal feedbacks between hydrologic processes and human decisions (i.e., human impacts on critical low flows and hydrologic impacts on human decisions on land and water use) can be assessed. The framework is applied to a Midwestern U.S. agricultural watershed, in the context of proposed biofuels development. This operation is illustrated by projecting three possible future coevolution trajectories, two of which use dedicated biofuel crops to reduce annual watershed nitrate export while meeting ethanol production targets. Imposition of a primary external driver (biofuel mandate) combined with different secondary drivers (water quality targets) results in highly nonlinear and multiscale responses of both the human and hydrologic systems, including multiple tradeoffs, impacting the future coevolution of the system in complex, heterogeneous ways. The strength of the hydrologic response is sensitive to the magnitude of the secondary driver; 45% nitrate reduction target leads to noticeable impacts at the outlet, while a 30% reduction leads to noticeable impacts that are mainly local. The local responses are conditioned by previous human-hydrologic modifications and their spatial relationship to the new biofuel development, highlighting the importance of past coevolutionary history in predicting future trajectories of change.

Anatomical education and surgical simulation based on the Chinese Visible Human: a three-dimensional virtual model of the larynx region.

PubMed

Liu, Kaijun; Fang, Binji; Wu, Yi; Li, Ying; Jin, Jun; Tan, Liwen; Zhang, Shaoxiang

2013-09-01

Anatomical knowledge of the larynx region is critical for understanding laryngeal disease and performing required interventions. Virtual reality is a useful method for surgical education and simulation. Here, we assembled segmented cross-section slices of the larynx region from the Chinese Visible Human dataset. The laryngeal structures were precisely segmented manually as 2D images, then reconstructed and displayed as 3D images in the virtual reality Dextrobeam system. Using visualization and interaction with the virtual reality modeling language model, a digital laryngeal anatomy instruction was constructed using HTML and JavaScript languages. The volume larynx models can thus display an arbitrary section of the model and provide a virtual dissection function. This networked teaching system of the digital laryngeal anatomy can be read remotely, displayed locally, and manipulated interactively.

Modeling and Docking Studies on Novel Mutants (K71L and T204V) of the ATPase Domain of Human Heat Shock 70 kDa Protein 1

PubMed Central

Elengoe, Asita; Naser, Mohammed Abu; Hamdan, Salehhuddin

2014-01-01

The purpose of exploring protein interactions between human adenovirus and heat shock protein 70 is to exploit a potentially synergistic interaction to enhance anti-tumoral efficacy and decrease toxicity in cancer treatment. However, the protein interaction of Hsp70 with E1A32 kDa of human adenovirus serotype 5 remains to be elucidated. In this study, two residues of ATPase domain of human heat shock 70 kDa protein 1 (PDB: 1 HJO) were mutated. 3D mutant models (K71L and T204V) using PyMol software were then constructed. The structures were evaluated by PROCHECK, ProQ, ERRAT, Verify 3D and ProSA modules. All evidence suggests that all protein models are acceptable and of good quality. The E1A32 kDa motif was retrieved from UniProt (P03255), as well as subjected to docking interaction with NBD, K71L and T204V, using the Autodock 4.2 program. The best lowest binding energy value of −9.09 kcal/mol was selected for novel T204V. Moreover, the protein-ligand complex structures were validated by RMSD, RMSF, hydrogen bonds and salt bridge analysis. This revealed that the T204V-E1A32 kDa motif complex was the most stable among all three complex structures. This study provides information about the interaction between Hsp70 and the E1A32 kDa motif, which emphasizes future perspectives to design rational drugs and vaccines in cancer therapy. PMID:24758925

Virtual Reality Anatomy: Is It Comparable with Traditional Methods in the Teaching of Human Forearm Musculoskeletal Anatomy?

ERIC Educational Resources Information Center

Codd, Anthony M.; Choudhury, Bipasha

2011-01-01

The use of cadavers to teach anatomy is well established, but limitations with this approach have led to the introduction of alternative teaching methods. One such method is the use of three-dimensional virtual reality computer models. An interactive, three-dimensional computer model of human forearm anterior compartment musculoskeletal anatomy…

Inquiry-Based Investigation on the Internet: Sound and the Human Ear

ERIC Educational Resources Information Center

Quinlan, Kevin; Sterling, Donna R.

2006-01-01

In this online exploration of sound energy and the human ear, students carry out an inquiry-based activity, which leads them to websites featuring a diagram of a human ear, an interactive demonstration of the Doppler effect, a model of longitudinal waves, and an animation of human hearing. In the activity, students formulate, justify, and evaluate…

A superellipsoid-plane model for simulating foot-ground contact during human gait.

PubMed

Lopes, D S; Neptune, R R; Ambrósio, J A; Silva, M T

2016-01-01

Musculoskeletal models and forward dynamics simulations of human movement often include foot-ground interactions, with the foot-ground contact forces often determined using a constitutive model that depends on material properties and contact kinematics. When using soft constraints to model the foot-ground interactions, the kinematics of the minimum distance between the foot and planar ground needs to be computed. Due to their geometric simplicity, a considerable number of studies have used point-plane elements to represent these interacting bodies, but few studies have provided comparisons between point contact elements and other geometrically based analytical solutions. The objective of this work was to develop a more general-purpose superellipsoid-plane contact model that can be used to determine the three-dimensional foot-ground contact forces. As an example application, the model was used in a forward dynamics simulation of human walking. Simulation results and execution times were compared with a point-like viscoelastic contact model. Both models produced realistic ground reaction forces and kinematics with similar computational efficiency. However, solving the equations of motion with the surface contact model was found to be more efficient (~18% faster), and on average numerically ~37% less stiff. The superellipsoid-plane elements are also more versatile than point-like elements in that they allow for volumetric contact during three-dimensional motions (e.g. rotating, rolling, and sliding). In addition, the superellipsoid-plane element is geometrically accurate and easily integrated within multibody simulation code. These advantages make the use of superellipsoid-plane contact models in musculoskeletal simulations an appealing alternative to point-like elements.

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.

Interactive Model-Centric Systems Engineering (IMCSE) Phase Two

DTIC Science & Technology

2015-02-28

109 Backend Implementation...42 Figure 10. Interactive Epoch-Era Analysis leverages humans-in-the-loop analysis and supporting infrastructure ...preliminary supporting 10 infrastructure . This will inform the transition strategies, additional case application and prototype user testing. • The

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.

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

Brain-derived neurotrophic factor as a model system for examining gene by environment interactions across development.

PubMed

Casey, B J; Glatt, C E; Tottenham, N; Soliman, F; Bath, K; Amso, D; Altemus, M; Pattwell, S; Jones, R; Levita, L; McEwen, B; Magariños, A M; Gunnar, M; Thomas, K M; Mezey, J; Clark, A G; Hempstead, B L; Lee, F S

2009-11-24

There has been a dramatic rise in gene x environment studies of human behavior over the past decade that have moved the field beyond simple nature versus nurture debates. These studies offer promise in accounting for more variability in behavioral and biological phenotypes than studies that focus on genetic or experiential factors alone. They also provide clues into mechanisms of modifying genetic risk or resilience in neurodevelopmental disorders. Yet, it is rare that these studies consider how these interactions change over the course of development. In this paper, we describe research that focuses on the impact of a polymorphism in a brain-derived neurotrophic factor (BDNF) gene, known to be involved in learning and development. Specifically we present findings that assess the effects of genotypic and environmental loadings on neuroanatomic and behavioral phenotypes across development. The findings illustrate the use of a genetic mouse model that mimics the human polymorphism, to constrain the interpretation of gene-environment interactions across development in humans.

Avionics Collaborative Engineering Technology Delivery Order 0035: Secure Knowledge Management (SKM) Technology Research Roadmap - Technology Trends for Collaborative Information and Knowledge Management Research

DTIC Science & Technology

2004-06-01

such as that represented in the know-how of the master craftsman), and cognitive (know why, perceptions, values, beliefs, and mental models).4... cognitive engineering, educational technology, industrial/organizational psychology, sociology, cultural anthropology, and computational...such as human-human interaction, interface design and evaluation methodology, cognitive models and user models, health and ergonomic studies, empirical

Some Technical Implications of Distributed Cognition on the Design on Interactive Learning Environments.

ERIC Educational Resources Information Center

Dillenbourg, Pierre

1996-01-01

Maintains that diagnosis, explanation, and tutoring, the functions of an interactive learning environment, are collaborative processes. Examines how human-computer interaction can be improved using a distributed cognition framework. Discusses situational and distributed knowledge theories and provides a model on how they can be used to redesign…

The ethics of donor human milk banking.

PubMed

Arnold, Lois D W

2006-01-01

This case study of donor human milk banking and the ethics that govern interested parties is the first time the ethics of donor milk banking has been explored. Two different models of ethics and their direct impact on donor milk banking are examined: biomedical ethics and public health ethics. How these models and principles affect different aspects of donor human milk banking and the parties involved in the delivery of this service are elucidated. Interactions of parties with each other and how the quality and type of interaction affects the ethical delivery of donor milk banking services are described. Crystallization is at the heart of the qualitative methodology used. Writing as a method of inquiry, an integrative research review, and personal experience are the three methods involved in the crystallization process. Suggestions are made for improving access and knowledge of banked donor human milk, a valuable public health resource.

The Design of Hand Gestures for Human-Computer Interaction: Lessons from Sign Language Interpreters.

PubMed

Rempel, David; Camilleri, Matt J; Lee, David L

2015-10-01

The design and selection of 3D modeled hand gestures for human-computer interaction should follow principles of natural language combined with the need to optimize gesture contrast and recognition. The selection should also consider the discomfort and fatigue associated with distinct hand postures and motions, especially for common commands. Sign language interpreters have extensive and unique experience forming hand gestures and many suffer from hand pain while gesturing. Professional sign language interpreters (N=24) rated discomfort for hand gestures associated with 47 characters and words and 33 hand postures. Clear associations of discomfort with hand postures were identified. In a nominal logistic regression model, high discomfort was associated with gestures requiring a flexed wrist, discordant adjacent fingers, or extended fingers. These and other findings should be considered in the design of hand gestures to optimize the relationship between human cognitive and physical processes and computer gesture recognition systems for human-computer input.

A review on the removal of antibiotics by carbon nanotubes.

PubMed

Cong, Qiao; Yuan, Xing; Qu, Jiao

2013-01-01

Increasing concerns have been raised regarding the potential risks of antibiotics to human and ecological health due to their extensive use. Carbon nanotubes (CNTs) have drawn special research attention because of their unique properties and potential applications as a kind of adsorbents. This review summarizes the currently available research on the adsorption of antibiotics on CNTs, and will provide useful information for CNT application and risk assessment. Four different models, the Freundlich model (FM), Langmuir model (LM), Polanyi-Mane model (PMM), and Dubinin-Ashtakhov model (DAM), are often used to fit the adsorption isotherms. Because different mechanisms may act simultaneously, including electrostatic interactions, hydrophobic interactions, π-π bonds, and hydrogen bonds, the prediction of organic chemical adsorption on CNTs is not straightforward. Properties of CNTs, such as specific surface area, adsorption sites, and oxygen content, may influence the adsorption of antibiotics on CNTs. Adsorption heterogeneity and hysteresis are two features of antibiotic-CNT interactions. In addition, CNTs with adsorbed antibiotics may have potential risks for human health. So, further research examining how to reduce such risks is needed.

Systems view on spatial planning and perception based on invariants in agent-environment dynamics

PubMed Central

Mettler, Bérénice; Kong, Zhaodan; Li, Bin; Andersh, Jonathan

2015-01-01

Modeling agile and versatile spatial behavior remains a challenging task, due to the intricate coupling of planning, control, and perceptual processes. Previous results have shown that humans plan and organize their guidance behavior by exploiting patterns in the interactions between agent or organism and the environment. These patterns, described under the concept of Interaction Patterns (IPs), capture invariants arising from equivalences and symmetries in the interaction with the environment, as well as effects arising from intrinsic properties of human control and guidance processes, such as perceptual guidance mechanisms. The paper takes a systems' perspective, considering the IP as a unit of organization, and builds on its properties to present a hierarchical model that delineates the planning, control, and perceptual processes and their integration. The model's planning process is further elaborated by showing that the IP can be abstracted, using spatial time-to-go functions. The perceptual processes are elaborated from the hierarchical model. The paper provides experimental support for the model's ability to predict the spatial organization of behavior and the perceptual processes. PMID:25628524

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.

A Parametric Model of Shoulder Articulation for Virtual Assessment of Space Suit Fit

NASA Technical Reports Server (NTRS)

Young, Karen; Kim, Han; Bernal, Yaritza; Vu, Linh; Boppana, Adhi; Benson, Elizabeth; Jarvis, Sarah; Rajulu, Sudhakar

2016-01-01

Goal of space human factors analyses: Place the highly variable human body within these restrictive physical environments to ensure that the entire anticipated population can live, work, and interact. Space suits are a very restrictive space and if not properly sized can result in pain or injury. The highly dynamic motions performed while wearing a space suit often make it difficult to model. Limited human body models do not have much allowance for customization of anthropometry and representation of the population that may wear a space suit.

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.

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

NASA Astrophysics Data System (ADS)

Yoon, J.; Gorelick, S.

2014-12-01

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

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 coupled in IAMs , and the need for a lexicon that is agreed upon by the IAM community.

Micropatterned coculture of primary human hepatocytes and supportive cells for the study of hepatotropic pathogens

PubMed Central

March, Sandra; Ramanan, Vyas; Trehan, Kartik; Ng, Shengyong; Galstian, Ani; Gural, Nil; Scull, Margaret A.; Shlomai, Amir; Mota, Maria; Fleming, Heather E.; Khetani, Salman R.; Rice, Charles M.; Bhatia, Sangeeta N.

2018-01-01

Studying human hepatotropic pathogens such as hepatitis B and C viruses and malaria will be necessary for understanding host-pathogen interactions, and developing therapy and prophylaxis. Unfortunately, existing in vitro liver models typically employ either cell lines that exhibit aberrant physiology, or primary human hepatocytes in culture configurations wherein they rapidly lose their hepatic functional phenotype. Stable, robust, and reliable in vitro primary human hepatocyte models are needed as platforms for infectious disease applications. For this purpose, we describe the application of micropatterned co-cultures (MPCCs), which consist of primary human hepatocytes organized into 2D islands that are surrounded by supportive cells. Using this system, we demonstrate how to recapitulate in vitro liver infection by the hepatitis B and C viruses and Plasmodium pathogens. In turn, the MPCC platform can be used to uncover aspects of host-pathogen interactions, and has the potential to be used for medium-throughput drug screening and vaccine development. PMID:26584444

Molecular modeling and analysis of human and plant endo-β-N-acetyl- glucosaminidases for mutations effects on function

PubMed Central

Choragudi, Shechinah Felice; Veeramachaneni, Ganesh Kumar; Raman, BV; JS, Bondili

2014-01-01

Endo- β-N-acetylgucosaminidases (ENGases) are the enzymes that catalyze both hydrolysis and transglycosylation reactions. It is of interest to study ENGases because of their ability to synthesize glycopeptides. Homology models of Human, Arabidopsis thaliana and Sorghum ENGases were developed and their active sites marked based on information available from Arthrobacter protophormiae (PDB ID: 3FHQ) ENGase. Further, these models were docked with the natural substrate GlcNAc-Asn and the inhibitor Man3GlcNAc-thiazoline. The catalytic triad of Asn, Glu and Tyr (N171, E173 and Y205 of bacteria) were found to be conserved across the phyla. The crucial Y299F mutation showing 3 times higher transglycosylation activity than in wild type Endo-A is known. The hydrolytic activity remained unchanged in bacteria, while the transglycosylation activity increased. This Y to F change is found to be naturally evolved and should be attributing higher transglycosylation rates in human and Arabidopsis thaliana ENGases. Ligand interactions Ligplots revealed the interaction of amino acids with hydrophobic side chains and polar uncharged side chain amino acids. Thus, structure based molecular model-ligand interactions provide insights into the catalytic mechanism of ENGases and assist in the rational engineering of ENGases. PMID:25258486

Molecular modeling and analysis of human and plant endo-β-N-acetyl- glucosaminidases for mutations effects on function.

PubMed

Choragudi, Shechinah Felice; Veeramachaneni, Ganesh Kumar; Raman, Bv; Js, Bondili

2014-01-01

Endo- β-N-acetylgucosaminidases (ENGases) are the enzymes that catalyze both hydrolysis and transglycosylation reactions. It is of interest to study ENGases because of their ability to synthesize glycopeptides. Homology models of Human, Arabidopsis thaliana and Sorghum ENGases were developed and their active sites marked based on information available from Arthrobacter protophormiae (PDB ID: 3FHQ) ENGase. Further, these models were docked with the natural substrate GlcNAc-Asn and the inhibitor Man3GlcNAc-thiazoline. The catalytic triad of Asn, Glu and Tyr (N171, E173 and Y205 of bacteria) were found to be conserved across the phyla. The crucial Y299F mutation showing 3 times higher transglycosylation activity than in wild type Endo-A is known. The hydrolytic activity remained unchanged in bacteria, while the transglycosylation activity increased. This Y to F change is found to be naturally evolved and should be attributing higher transglycosylation rates in human and Arabidopsis thaliana ENGases. Ligand interactions Ligplots revealed the interaction of amino acids with hydrophobic side chains and polar uncharged side chain amino acids. Thus, structure based molecular model-ligand interactions provide insights into the catalytic mechanism of ENGases and assist in the rational engineering of ENGases.

Domain learning naming game for color categorization.

PubMed

Li, Doujie; Fan, Zhongyan; Tang, Wallace K S

2017-01-01

Naming game simulates the evolution of vocabulary in a population of agents. Through pairwise interactions in the games, agents acquire a set of vocabulary in their memory for object naming. The existing model confines to a one-to-one mapping between a name and an object. Focus is usually put onto name consensus in the population rather than knowledge learning in agents, and hence simple learning model is usually adopted. However, the cognition system of human being is much more complex and knowledge is usually presented in a complicated form. Therefore, in this work, we extend the agent learning model and design a new game to incorporate domain learning, which is essential for more complicated form of knowledge. In particular, we demonstrate the evolution of color categorization and naming in a population of agents. We incorporate the human perceptive model into the agents and introduce two new concepts, namely subjective perception and subliminal stimulation, in domain learning. Simulation results show that, even without any supervision or pre-requisition, a consensus of a color naming system can be reached in a population solely via the interactions. Our work confirms the importance of society interactions in color categorization, which is a long debate topic in human cognition. Moreover, our work also demonstrates the possibility of cognitive system development in autonomous intelligent agents.

Domain learning naming game for color categorization

PubMed Central

2017-01-01

Naming game simulates the evolution of vocabulary in a population of agents. Through pairwise interactions in the games, agents acquire a set of vocabulary in their memory for object naming. The existing model confines to a one-to-one mapping between a name and an object. Focus is usually put onto name consensus in the population rather than knowledge learning in agents, and hence simple learning model is usually adopted. However, the cognition system of human being is much more complex and knowledge is usually presented in a complicated form. Therefore, in this work, we extend the agent learning model and design a new game to incorporate domain learning, which is essential for more complicated form of knowledge. In particular, we demonstrate the evolution of color categorization and naming in a population of agents. We incorporate the human perceptive model into the agents and introduce two new concepts, namely subjective perception and subliminal stimulation, in domain learning. Simulation results show that, even without any supervision or pre-requisition, a consensus of a color naming system can be reached in a population solely via the interactions. Our work confirms the importance of society interactions in color categorization, which is a long debate topic in human cognition. Moreover, our work also demonstrates the possibility of cognitive system development in autonomous intelligent agents. PMID:29136661

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.

Spectroscopic and molecular modeling studies on the binding of the flavonoid luteolin and human serum albumin.

PubMed

Jurasekova, Zuzana; Marconi, Giancarlo; Sanchez-Cortes, Santiago; Torreggiani, Armida

2009-11-01

Luteolin (LUT) is a polyphenolic compound, found in a variety of fruits, vegetables, and seeds, which has a variety of pharmacological properties. In the present contribution, binding of LUT to human serum albumin (HSA), the most abundant carrier protein in the blood, was investigated with the aim of describing the binding mode and parameters of the interaction. The application of circular dichroism, UV-Vis absorption, fluorescence, Raman and surface-enhanced Raman scattering spectroscopy combined with molecular modeling afforded a clear picture of the association mode of LUT to HSA. Specific interactions with protein amino acids were evidenced. LUT was found to be associated in subdomain IIA where an interaction with Trp-214 is established. Hydrophobic and electrostatic interactions are the major acting forces in the binding of LUT to HSA. The HSA conformations were slightly altered by the drug complexation with reduction of alpha-helix and increase of beta-turns structures, suggesting a partial protein unfolding. Also the configuration of at least two disulfide bridges were altered. Furthermore, the study of molecular modeling afforded the binding geometry. 2009 Wiley Periodicals, Inc.

Culturicon model: A new model for cultural-based emoticon

NASA Astrophysics Data System (ADS)

Zukhi, Mohd Zhafri Bin Mohd; Hussain, Azham

2017-10-01

Emoticons are popular among distributed collective interaction user in expressing their emotion, gestures and actions. Emoticons have been proved to be able to avoid misunderstanding of the message, attention saving and improved the communications among different native speakers. However, beside the benefits that emoticons can provide, the study regarding emoticons in cultural perspective is still lacking. As emoticons are crucial in global communication, culture should be one of the extensively research aspect in distributed collective interaction. Therefore, this study attempt to explore and develop model for cultural-based emoticon. Three cultural models that have been used in Human-Computer Interaction were studied which are the Hall Culture Model, Trompenaars and Hampden Culture Model and Hofstede Culture Model. The dimensions from these three models will be used in developing the proposed cultural-based emoticon model.

Multiple scales modelling approaches to social interaction in crowd dynamics and crisis management. Comment on "Human behaviours in evacuation crowd dynamics: From modelling to "big data" toward crisis management" by Nicola Bellomo et al.

NASA Astrophysics Data System (ADS)

Trucu, Dumitru

2016-09-01

In this comprehensive review concerning the modelling of human behaviours in crowd dynamics [3], the authors explore a wide range of mathematical approaches spanning over multiple scales that are suitable to describe emerging crowd behaviours in extreme situations. Focused on deciphering the key aspects leading to emerging crowd patterns evolutions in challenging times such as those requiring an evacuation on a complex venue, the authors address this complex dynamics at both microscale (individual level), mesoscale (probability distributions of interacting individuals), and macroscale (population level), ultimately aiming to gain valuable understanding and knowledge that would inform decision making in managing crisis situations.

A Coupled Modeling Framework of the Co-evolution of Humans and Water: Case Study of Tarim River Basin, Western China

NASA Astrophysics Data System (ADS)

Liu, D.; Tian, F.; Lin, M.; Sivapalan, M.

2014-12-01

The complex interactions and feedbacks between humans and water are very essential issues but are poorly understood in the newly proposed discipline of socio-hydrology (Sivapalan et al., 2012). An exploratory model with the appropriate level of simplification can be valuable to improve our understanding of the co-evolution and self-organization of socio-hydrological systems driven by interactions and feedbacks operating at different scales. In this study, a simple coupled modeling framework for socio-hydrology co-evolution is developed for the Tarim River Basin in Western China, and is used to illustrate the explanatory power of such a model. The study area is the mainstream of the Tarim River, which is divided into two modeling units. The socio-hydrological system is composed of four parts, i.e., social sub-system, economic sub-system, ecological sub-system, and hydrological sub-system. In each modeling unit, four coupled ordinary differential equations are used to simulate the dynamics of the social sub-system represented by human population, the economic sub-system represented by irrigated crop area, the ecological sub-system represented by natural vegetation cover and the hydrological sub-system represented by stream discharge. The coupling and feedback processes of the four dominant sub-systems (and correspondingly four state variables) are integrated into several internal system characteristics interactively and jointly determined by themselves and by other coupled systems. For example, the stream discharge is coupled to the irrigated crop area by the colonization rate and mortality rate of the irrigated crop area in the upper reach and the irrigated area is coupled to stream discharge through irrigation water consumption. The co-evolution of the Tarim socio-hydrological system is then analyzed within this modeling framework to gain insights into the overall system dynamics and its sensitivity to the external drivers and internal system variables. In the modeling framework, the state of each subsystem is holistically described by one state variable and the framework is flexible enough to comprise more processes and constitutive relationships if they are needed to illustrate the interaction and feedback mechanisms of the human-water system.

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.

Toward the Language-Ready Brain: Biological Evolution and Primate Comparisons.

PubMed

Arbib, Michael A

2017-02-01

The approach to language evolution suggested here focuses on three questions: How did the human brain evolve so that humans can develop, use, and acquire languages? How can the evolutionary quest be informed by studying brain, behavior, and social interaction in monkeys, apes, and humans? How can computational modeling advance these studies? I hypothesize that the brain is language ready in that the earliest humans had protolanguages but not languages (i.e., communication systems endowed with rich and open-ended lexicons and grammars supporting a compositional semantics), and that it took cultural evolution to yield societies (a cultural constructed niche) in which language-ready brains could become language-using brains. The mirror system hypothesis is a well-developed example of this approach, but I offer it here not as a closed theory but as an evolving framework for the development and analysis of conflicting subhypotheses in the hope of their eventual integration. I also stress that computational modeling helps us understand the evolving role of mirror neurons, not in and of themselves, but only in their interaction with systems "beyond the mirror." Because a theory of evolution needs a clear characterization of what it is that evolved, I also outline ideas for research in neurolinguistics to complement studies of the evolution of the language-ready brain. A clear challenge is to go beyond models of speech comprehension to include sign language and models of production, and to link language to visuomotor interaction with the physical and social world.

Designing visual displays and system models for safe reactor operations based on the user`s perspective of the system

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

Brown-VanHoozer, S.A.

Most designers are not schooled in the area of human-interaction psychology and therefore tend to rely on the traditional ergonomic aspects of human factors when designing complex human-interactive workstations related to reactor operations. They do not take into account the differences in user information processing behavior and how these behaviors may affect individual and team performance when accessing visual displays or utilizing system models in process and control room areas. Unfortunately, by ignoring the importance of the integration of the user interface at the information process level, the result can be sub-optimization and inherently error- and failure-prone systems. Therefore, tomore » minimize or eliminate failures in human-interactive systems, it is essential that the designers understand how each user`s processing characteristics affects how the user gathers information, and how the user communicates the information to the designer and other users. A different type of approach in achieving this understanding is Neuro Linguistic Programming (NLP). The material presented in this paper is based on two studies involving the design of visual displays, NLP, and the user`s perspective model of a reactor system. The studies involve the methodology known as NLP, and its use in expanding design choices from the user`s ``model of the world,`` in the areas of virtual reality, workstation design, team structure, decision and learning style patterns, safety operations, pattern recognition, and much, much more.« less

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.

Streptococcus dysgalactiae subsp. dysgalactiae isolated from milk of the bovine udder as emerging pathogens: In vitro and in vivo infection of human cells and zebrafish as biological models.

PubMed

Alves-Barroco, Cinthia; Roma-Rodrigues, Catarina; Raposo, Luís R; Brás, Catarina; Diniz, Mário; Caço, João; Costa, Pedro M; Santos-Sanches, Ilda; Fernandes, Alexandra R

2018-03-25

Streptococcus dysgalactiae subsp. dysgalactiae (SDSD) is a major cause of bovine mastitis and has been regarded as an animal-restricted pathogen, although rare infections have been described in humans. Previous studies revealed the presence of virulence genes encoded by phages of the human pathogen Group A Streptococcus pyogenes (GAS) in SDSD isolated from the milk of bovine udder with mastitis. The isolates SDSD VSD5 and VSD13 could adhere and internalize human primary keratinocyte cells, suggesting a possible human infection potential of bovine isolates. In this work, the in vitro and in vivo potential of SDSD to internalize/adhere human cells of the respiratory track and zebrafish as biological models was evaluated. Our results showed that, in vitro, bovine SDSD strains could interact and internalize human respiratory cell lines and that this internalization was dependent on an active transport mechanism and that, in vivo, SDSD are able to cause invasive infections producing zebrafish morbidity and mortality. The infectious potential of these isolates showed to be isolate-specific and appeared to be independent of the presence or absence of GAS phage-encoded virulence genes. Although the infection ability of the bovine SDSD strains was not as strong as the human pathogenic S. pyogenes in the zebrafish model, results suggested that these SDSD isolates are able to interact with human cells and infect zebrafish, a vertebrate infectious model, emerging as pathogens with zoonotic capability. © 2018 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.

Modeling the Western Diet for Preclinical Investigations.

PubMed

Hintze, Korry J; Benninghoff, Abby D; Cho, Clara E; Ward, Robert E

2018-05-01

Rodent models have been invaluable for biomedical research. Preclinical investigations with rodents allow researchers to investigate diseases by using study designs that are not suitable for human subjects. The primary criticism of preclinical animal models is that results are not always translatable to humans. Some of this lack of translation is due to inherent differences between species. However, rodent models have been refined over time, and translatability to humans has improved. Transgenic animals have greatly aided our understanding of interactions between genes and disease and have narrowed the translation gap between humans and model animals. Despite the technological innovations of animal models through advances in genetics, relatively little attention has been given to animal diets. Namely, developing diets that replicate what humans eat will help make animal models more relevant to human populations. This review focuses on commonly used rodent diets that are used to emulate the Western dietary pattern in preclinical studies of obesity and type 2 diabetes, nonalcoholic liver disease, maternal nutrition, and colorectal cancer.

LAPSUS: soil erosion - landscape evolution model

NASA Astrophysics Data System (ADS)

van Gorp, Wouter; Temme, Arnaud; Schoorl, Jeroen

2015-04-01

LAPSUS is a soil erosion - landscape evolution model which is capable of simulating landscape evolution of a gridded DEM by using multiple water, mass movement and human driven processes on multiple temporal and spatial scales. It is able to deal with a variety of human landscape interventions such as landuse management and tillage and it can model their interactions with natural processes. The complex spatially explicit feedbacks the model simulates demonstrate the importance of spatial interaction of human activity and erosion deposition patterns. In addition LAPSUS can model shallow landsliding, slope collapse, creep, solifluction, biological and frost weathering, fluvial behaviour. Furthermore, an algorithm to deal with natural depressions has been added and event-based modelling with an improved infiltration description and dust deposition has been pursued. LAPSUS has been used for case studies in many parts of the world and is continuously developing and expanding. it is now available for third-party and educational use. It has a comprehensive user interface and it is accompanied by a manual and exercises. The LAPSUS model is highly suitable to quantify and understand catchment-scale erosion processes. More information and a download link is available on www.lapsusmodel.nl.

A Proteome-wide Fission Yeast Interactome Reveals Network Evolution Principles from Yeasts to Human.

PubMed

Vo, Tommy V; Das, Jishnu; Meyer, Michael J; Cordero, Nicolas A; Akturk, Nurten; Wei, Xiaomu; Fair, Benjamin J; Degatano, Andrew G; Fragoza, Robert; Liu, Lisa G; Matsuyama, Akihisa; Trickey, Michelle; Horibata, Sachi; Grimson, Andrew; Yamano, Hiroyuki; Yoshida, Minoru; Roth, Frederick P; Pleiss, Jeffrey A; Xia, Yu; Yu, Haiyuan

2016-01-14

Here, we present FissionNet, a proteome-wide binary protein interactome for S. pombe, comprising 2,278 high-quality interactions, of which ∼ 50% were previously not reported in any species. FissionNet unravels previously unreported interactions implicated in processes such as gene silencing and pre-mRNA splicing. We developed a rigorous network comparison framework that accounts for assay sensitivity and specificity, revealing extensive species-specific network rewiring between fission yeast, budding yeast, and human. Surprisingly, although genes are better conserved between the yeasts, S. pombe interactions are significantly better conserved in human than in S. cerevisiae. Our framework also reveals that different modes of gene duplication influence the extent to which paralogous proteins are functionally repurposed. Finally, cross-species interactome mapping demonstrates that coevolution of interacting proteins is remarkably prevalent, a result with important implications for studying human disease in model organisms. Overall, FissionNet is a valuable resource for understanding protein functions and their evolution. Copyright © 2016 Elsevier Inc. All rights reserved.

HUMAN--A Comprehensive Physiological Model.

ERIC Educational Resources Information Center

Coleman, Thomas G.; Randall, James E.

1983-01-01

Describes computer program (HUMAN) used to simulate physiological experiments on patient pathology. Program (available from authors, including versions for microcomputers) consists of dynamic interactions of over 150 physiological variables and integrating approximations of cardiovascular, renal, lung, temperature regulation, and some hormone…

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.

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.

The Dynamics of a SEIR-SIRC Antigenic Drift Influenza Model.

PubMed

Adi-Kusumo, Fajar

2017-06-01

We consider the dynamics of an influenza model with antigenic drift mechanism. Antigenic drift is an antigen mutation on the skin surface of the influenza virus that do not produce a new virus strain. The mutation produces the same virus but with slightly different antigens that cannot be recognized by the immune receptors formed by the previous infection. There are some type of influenza that involve the interaction between two populations such as human and animal. In this paper, we construct an influenza model with antigenic drift mechanism on the human population that has interaction with the animal population. The animal population is assumed to follow the SEIR epidemic model. Our model is motivated by the fact that some of the influenza cases in human come from the animal such as the swine and the avian. The transmission parameter that shows number of contact between the susceptible human and the infectious animals are important to study. The parameter plays an important role to detect the cycle of infection of the disease. The other important parameters are the seasonality degree, which shows the pathogen appearance and disappearance via annual migration, and the infection rate on the human population. We employ the bifurcation theory to analyze the behavior of the system and to detect the cycle of infection types when the parameters values are varied.

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.

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.

Modeling of three dimensional structure of human alpha-fetoprotein complexed with diethylstilbestrol: docking and molecular dynamics simulation study.

PubMed

Terentiev, Alexander A; Moldogazieva, Nurbubu T; Levtsova, Olga V; Maximenko, Dmitry M; Borozdenko, Denis A; Shaitan, Konstantin V

2012-04-01

It has been long experimentally demonstrated that human alpha-fetoprotein (HAFP) has an ability to bind immobilized estrogens with the most efficiency for synthetic estrogen analog - diethylstilbestrol (DES). However, the question remains why the human AFP (HAFP), unlike rodent AFP, cannot bind free estrogens. Moreover, despite the fact that AFP was first discovered more than 50 years ago and is presently recognized as a "golden standard" among onco-biomarkers, its three-dimensional (3D) structure has not been experimentally solved yet. In this work using MODELLER program, we generated 3D model of HAFP on the basis of homology with human serum albumin (HSA) and Vitamin D-binding protein (VTDB) with subsequent molecular docking of DES to the model structure and molecular dynamics (MD) simulation study of the complex obtained. The model constructed has U-shaped structure in which a cavity may be distinguished. In this cavity the putative estrogen-binding site is localized. Validation by RMSD calculation and with the use of PROCHECK program showed good quality of the model and stability of extended region of four alpha-helical structures that contains putative hormone-binding residues. Data extracted from MD simulation trajectory allow proposing two types of interactions between amino acid residues of HAFP and DES molecule: (1) hydrogen bonding with involvement of residues S445, R452, and E551; (2) hydrophobic interactions with participation of L138, M448, and M548 residues. A suggestion is made that immobilization of the hormone using a long spacer provides delivery of the estrogen molecule to the binding site and, thereby, facilitates interaction between HAFP and the hormone.

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.

Evolutionary model selection and parameter estimation for protein-protein interaction network based on differential evolution algorithm

PubMed Central

Huang, Lei; Liao, Li; Wu, Cathy H.

2016-01-01

Revealing the underlying evolutionary mechanism plays an important role in understanding protein interaction networks in the cell. While many evolutionary models have been proposed, the problem about applying these models to real network data, especially for differentiating which model can better describe evolutionary process for the observed network urgently remains as a challenge. The traditional way is to use a model with presumed parameters to generate a network, and then evaluate the fitness by summary statistics, which however cannot capture the complete network structures information and estimate parameter distribution. In this work we developed a novel method based on Approximate Bayesian Computation and modified Differential Evolution (ABC-DEP) that is capable of conducting model selection and parameter estimation simultaneously and detecting the underlying evolutionary mechanisms more accurately. We tested our method for its power in differentiating models and estimating parameters on the simulated data and found significant improvement in performance benchmark, as compared with a previous method. We further applied our method to real data of protein interaction networks in human and yeast. Our results show Duplication Attachment model as the predominant evolutionary mechanism for human PPI networks and Scale-Free model as the predominant mechanism for yeast PPI networks. PMID:26357273

[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.

In vivo imaging in NHP models of malaria: challenges, progress and outlooks.

PubMed

Beignon, Anne-Sophie; Le Grand, Roger; Chapon, Catherine

2014-02-01

Animal models of malaria, mainly mice, have made a large contribution to our knowledge of host-pathogen interactions and immune responses, and to drug and vaccine design. Non-human primate (NHP) models for malaria are admittedly under-used, although they are probably closer models than mice for human malaria; in particular, NHP models allow the use of human pathogens (Plasmodium falciparum, Plasmodium vivax, Plasmodium malariae and Plasmodium knowlesi). NHPs, whether natural hosts or experimentally challenged with a simian Plasmodium, can also serve as robust pre-clinical models. Some simian parasites are closely related to a human counterpart, with which they may share a common ancestor, and display similar major features with the human infection and pathology. NHP models allow longitudinal studies, from the early events following sporozoite inoculation to the later events, including analysis of organs and tissues, particularly liver, spleen, brain and bone marrow. NHP models have one other significant advantage over mouse models: NHPs are our closest relatives and thus their biology is very similar to ours. Recently developed in vivo imaging tools have provided insight into malaria parasite infection and disease in mouse models. One advantage of these tools is that they limit the need for invasive procedures, such as tissue biopsies. Many such technologies are now available for NHP studies and provide new opportunities for elucidating host/parasite interactions. The aim of this review is to bring the malaria community up to date on what is currently possible and what soon will be, in terms of in vivo imaging in NHP models of malaria, to consider the pros and the cons of the various techniques, and to identify challenges. © 2013.

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.

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

Human-System Technology: Human-Robot Interaction to Address Critical Navy Needs of the Present and Future

DTIC Science & Technology

2006-10-31

Articles: Danks , D. "Psychological Theories of Categorization as Probabilistic Graphical Models," Journal of Mathematical Psychology, submitted. Kyburg...and when there is no set of competent and authorized humans available to make the decisions themselves. Ultimately, it is a matter of expected utility

Inhibition of Ovarian Cancer Chemoresistance and Metastasis with Antagonists of Hyaluronan-CD44-CD147 Interactions

DTIC Science & Technology

2013-07-01

oligosaccharides , which have previously been shown to antagonize hyaluronan-receptor interactions, sensitize cisplatin-resistant human ovarian...carcinoma cells to cisplatin treatment in a mouse xenograft model, as well as in cell culture. Hyaluronan oligosaccharide -decorated nanoparticles... oligosaccharides antagonize hyaluronan-receptor signaling by disrupting constitutive hyaluronan polymer- receptor interaction, thus leading to

Automatic Sound Generation for Spherical Objects Hitting Straight Beams Based on Physical Models.

ERIC Educational Resources Information Center

Rauterberg, M.; And Others

Sounds are the result of one or several interactions between one or several objects at a certain place and in a certain environment; the attributes of every interaction influence the generated sound. The following factors influence users in human/computer interaction: the organization of the learning environment, the content of the learning tasks,…

Interactions of landscape disturbances and climate change dictate ecological pattern and process: spatial modeling of wildfire, insect, and disease dynamics under future climates

Treesearch

Rachel A. Loehman; Robert E. Keane; Lisa M. Holsinger; Zhiwei Wu

2017-01-01

Context: Interactions among disturbances, climate, and vegetation influence landscape patterns and ecosystem processes. Climate changes, exotic invasions, beetle outbreaks, altered fire regimes, and human activities may interact to produce landscapes that appear and function beyond historical analogs. Objectives We used the mechanistic...

Closed-loop dialog model of face-to-face communication with a photo-real virtual human

NASA Astrophysics Data System (ADS)

Kiss, Bernadette; Benedek, Balázs; Szijárto, Gábor; Takács, Barnabás

2004-01-01

We describe an advanced Human Computer Interaction (HCI) model that employs photo-realistic virtual humans to provide digital media users with information, learning services and entertainment in a highly personalized and adaptive manner. The system can be used as a computer interface or as a tool to deliver content to end-users. We model the interaction process between the user and the system as part of a closed loop dialog taking place between the participants. This dialog, exploits the most important characteristics of a face-to-face communication process, including the use of non-verbal gestures and meta communication signals to control the flow of information. Our solution is based on a Virtual Human Interface (VHI) technology that was specifically designed to be able to create emotional engagement between the virtual agent and the user, thus increasing the efficiency of learning and/or absorbing any information broadcasted through this device. The paper reviews the basic building blocks and technologies needed to create such a system and discusses its advantages over other existing methods.

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 abnormal conditions may explain different types of ictal transitions and dynamics during propagated seizures in human focal epilepsy.

Relative contributions of the major human CYP450 to the metabolism of icotinib and its implication in prediction of drug-drug interaction between icotinib and CYP3A4 inhibitors/inducers using physiologically based pharmacokinetic modeling.

PubMed

Chen, Jia; Liu, Dongyang; Zheng, Xin; Zhao, Qian; Jiang, Ji; Hu, Pei

2015-06-01

Icotinib is an anticancer drug, but relative contributions of CYP450 have not been identified. This study was carried out to identify the contribution percentage of CYP450 to icotinib and use the results to develop a physiologically based pharmacokinetic (PBPK) model, which can help to predict drug-drug interaction (DDI). Human liver microsome (HLM) and supersome using relative activity factor (RAF) were employed to determine the relative contributions of the major human P450 to the net hepatic metabolism of icotinib. These values were introduced to develop a PBPK model using SimCYP. The model was validated by the observed data in a Phase I clinical trial in Chinese healthy subjects. Finally, the model was used to simulate the DDI with ketoconazole or rifampin. Final contribution of CYP450 isoforms determined by HLM showed that CYP3A4 provided major contributions to the metabolism of icotinib. The percentage contributions of the P450 to the net hepatic metabolism of icotinib were determined by HLM inhibition assay and RAF. The AUC ratio under concomitant use of ketoconazole and rifampin was 3.22 and 0.55, respectively. Percentage of contribution of CYP450 to icotinib metabolism was calculated by RAF. The model has been proven to fit the observed data and is used in predicting icotinib-ketoconazole/rifampin interaction.

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.

Three-Dimensional Rotating Wall Vessel-Derived Cell Culture Models for Studying Virus-Host Interactions

PubMed Central

Gardner, Jameson K.; Herbst-Kralovetz, Melissa M.

2016-01-01

The key to better understanding complex virus-host interactions is the utilization of robust three-dimensional (3D) human cell cultures that effectively recapitulate native tissue architecture and model the microenvironment. A lack of physiologically-relevant animal models for many viruses has limited the elucidation of factors that influence viral pathogenesis and of complex host immune mechanisms. Conventional monolayer cell cultures may support viral infection, but are unable to form the tissue structures and complex microenvironments that mimic host physiology and, therefore, limiting their translational utility. The rotating wall vessel (RWV) bioreactor was designed by the National Aeronautics and Space Administration (NASA) to model microgravity and was later found to more accurately reproduce features of human tissue in vivo. Cells grown in RWV bioreactors develop in a low fluid-shear environment, which enables cells to form complex 3D tissue-like aggregates. A wide variety of human tissues (from neuronal to vaginal tissue) have been grown in RWV bioreactors and have been shown to support productive viral infection and physiological meaningful host responses. The in vivo-like characteristics and cellular features of the human 3D RWV-derived aggregates make them ideal model systems to effectively recapitulate pathophysiology and host responses necessary to conduct rigorous basic science, preclinical and translational studies. PMID:27834891

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 pose an important challenge for future work in integrating human and landscape components.

DEPOSITION OF SULFATE ACID AEROSOLS IN THE DEVELOPING HUMAN LUNG

EPA Science Inventory

Computations of aerosol deposition as affected by (i) aerosol hygroscopicity, (ii) human age, and (iii) respiratory intensity are accomplished using a validated mathematical model. he interactive effects are very complicated but systematic. ew general observations can be made; ra...

HUMAN-ECOSYSTEM INTERACTIONS: THE CASE OF MERCURY

EPA Science Inventory

Human and ecosystem exposure studies evaluate exposure of sensitive and vulnerable populations. We will discuss how ecosystem exposure modeling studies completed for input into the US Clean Air Mercury Rule (CAMR) to evaluate the response of aquatic ecosystems to changes in mercu...

Human - Ecosystem Interactions: The Case of Mercury

EPA Science Inventory

Human and ecosystem exposure studies evaluate exposure of sensitive and vulnerable populations. We will discuss how ecosystem exposure modeling studies completed for input into the US Clean Air Mercury Rule (CAMR) to evaluate the response of aquatic ecosystems to changes in mercu...

Mice with Reconstituted Human Immune System Components as a Tool to Study Immune Cell Interactions in EBV Infection.

PubMed

Heuts, Frank; Nagy, Noemi

2017-01-01

Recent developments in mouse models that harbor part of a human immune system have proved extremely valuable to study the in vivo immune response to human specific pathogens such as Epstein-Barr virus. Over the last decades, advances in immunodeficient mouse strains that can be used as recipients for human immune cells have greatly enhanced the use of these models. Here, we describe the generation of mice with reconstituted human immune system (HIS mice) using immunocompromised mice transplanted with human CD34 + hematopoietic stem cells. We will also describe how such mice, in which human immune cells are generated de novo, can be used to study EBV infection.

Probabilistic simulation of the human factor in structural reliability

NASA Technical Reports Server (NTRS)

Shah, Ashwin R.; Chamis, Christos C.

1991-01-01

Many structural failures have occasionally been attributed to human factors in engineering design, analyses maintenance, and fabrication processes. Every facet of the engineering process is heavily governed by human factors and the degree of uncertainty associated with them. Factors such as societal, physical, professional, psychological, and many others introduce uncertainties that significantly influence the reliability of human performance. Quantifying human factors and associated uncertainties in structural reliability require: (1) identification of the fundamental factors that influence human performance, and (2) models to describe the interaction of these factors. An approach is being developed to quantify the uncertainties associated with the human performance. This approach consists of a multi factor model in conjunction with direct Monte-Carlo simulation.

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.

Zebrafish and Streptococcal Infections.

PubMed

Saralahti, A; Rämet, M

2015-09-01

Streptococcal bacteria are a versatile group of gram-positive bacteria capable of infecting several host organisms, including humans and fish. Streptococcal species are common colonizers of the human respiratory and gastrointestinal tract, but they also cause some of the most common life-threatening, invasive infections in humans and aquaculture. With its unique characteristics and efficient tools for genetic and imaging applications, the zebrafish (Danio rerio) has emerged as a powerful vertebrate model for infectious diseases. Several zebrafish models introduced so far have shown that zebrafish are suitable models for both zoonotic and human-specific infections. Recently, several zebrafish models mimicking human streptococcal infections have also been developed. These models show great potential in providing novel information about the pathogenic mechanisms and host responses associated with human streptococcal infections. Here, we review the zebrafish infection models for the most relevant streptococcal species: the human-specific Streptococcus pneumoniae and Streptococcus pyogenes, and the zoonotic Streptococcus iniae and Streptococcus agalactiae. The recent success and the future potential of these models for the study of host-pathogen interactions in streptococcal infections are also discussed. © 2015 The Foundation for the Scandinavian Journal of Immunology.

Dynamical simulation priors for human motion tracking.

PubMed

Vondrak, Marek; Sigal, Leonid; Jenkins, Odest Chadwicke

2013-01-01

We propose a simulation-based dynamical motion prior for tracking human motion from video in presence of physical ground-person interactions. Most tracking approaches to date have focused on efficient inference algorithms and/or learning of prior kinematic motion models; however, few can explicitly account for the physical plausibility of recovered motion. Here, we aim to recover physically plausible motion of a single articulated human subject. Toward this end, we propose a full-body 3D physical simulation-based prior that explicitly incorporates a model of human dynamics into the Bayesian filtering framework. We consider the motion of the subject to be generated by a feedback “control loop” in which Newtonian physics approximates the rigid-body motion dynamics of the human and the environment through the application and integration of interaction forces, motor forces, and gravity. Interaction forces prevent physically impossible hypotheses, enable more appropriate reactions to the environment (e.g., ground contacts), and are produced from detected human-environment collisions. Motor forces actuate the body, ensure that proposed pose transitions are physically feasible, and are generated using a motion controller. For efficient inference in the resulting high-dimensional state space, we utilize an exemplar-based control strategy that reduces the effective search space of motor forces. As a result, we are able to recover physically plausible motion of human subjects from monocular and multiview video. We show, both quantitatively and qualitatively, that our approach performs favorably with respect to Bayesian filtering methods with standard motion priors.

[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 mainly show after a human-dog interaction.

Modeling Viral Infectious Diseases and Development of Antiviral Therapies Using Human Induced Pluripotent Stem Cell-Derived Systems.

PubMed

Trevisan, Marta; Sinigaglia, Alessandro; Desole, Giovanna; Berto, Alessandro; Pacenti, Monia; Palù, Giorgio; Barzon, Luisa

2015-07-13

The recent biotechnology breakthrough of cell reprogramming and generation of induced pluripotent stem cells (iPSCs), which has revolutionized the approaches to study the mechanisms of human diseases and to test new drugs, can be exploited to generate patient-specific models for the investigation of host-pathogen interactions and to develop new antimicrobial and antiviral therapies. Applications of iPSC technology to the study of viral infections in humans have included in vitro modeling of viral infections of neural, liver, and cardiac cells; modeling of human genetic susceptibility to severe viral infectious diseases, such as encephalitis and severe influenza; genetic engineering and genome editing of patient-specific iPSC-derived cells to confer antiviral resistance.

Social coordination in animal vocal interactions. Is there any evidence of turn-taking? The starling as an animal model

PubMed Central

Henry, Laurence; Craig, Adrian J. F. K.; Lemasson, Alban; Hausberger, Martine

2015-01-01

Turn-taking in conversation appears to be a common feature in various human cultures and this universality raises questions about its biological basis and evolutionary trajectory. Functional convergence is a widespread phenomenon in evolution, revealing sometimes striking functional similarities between very distant species even though the mechanisms involved may be different. Studies on mammals (including non-human primates) and bird species with different levels of social coordination reveal that temporal and structural regularities in vocal interactions may depend on the species' social structure. Here we test the hypothesis that turn-taking and associated rules of conversations may be an adaptive response to the requirements of social life, by testing the applicability of turn-taking rules to an animal model, the European starling. Birdsong has for many decades been considered as one of the best models of human language and starling songs have been well described in terms of vocal production and perception. Starlings do have vocal interactions where alternating patterns predominate. Observational and experimental data on vocal interactions reveal that (1) there are indeed clear temporal and structural regularities, (2) the temporal and structural patterning is influenced by the immediate social context, the general social situation, the individual history, and the internal state of the emitter. Comparison of phylogenetically close species of Sturnids reveals that the alternating pattern of vocal interactions varies greatly according to the species' social structure, suggesting that interactional regularities may have evolved together with social systems. These findings lead to solid bases of discussion on the evolution of communication rules in relation to social evolution. They will be discussed also in terms of processes, at the light of recent neurobiological findings. PMID:26441787

Connecting the dots between genes, biochemistry, and disease susceptibility: systems biology modeling in human genetics.

PubMed

Moore, Jason H; Boczko, Erik M; Summar, Marshall L

2005-02-01

Understanding how DNA sequence variations impact human health through a hierarchy of biochemical and physiological systems is expected to improve the diagnosis, prevention, and treatment of common, complex human diseases. We have previously developed a hierarchical dynamic systems approach based on Petri nets for generating biochemical network models that are consistent with genetic models of disease susceptibility. This modeling approach uses an evolutionary computation approach called grammatical evolution as a search strategy for optimal Petri net models. We have previously demonstrated that this approach routinely identifies biochemical network models that are consistent with a variety of genetic models in which disease susceptibility is determined by nonlinear interactions between two or more DNA sequence variations. We review here this approach and then discuss how it can be used to model biochemical and metabolic data in the context of genetic studies of human disease susceptibility.

Embodied cognition for autonomous interactive robots.

PubMed

Hoffman, Guy

2012-10-01

In the past, notions of embodiment have been applied to robotics mainly in the realm of very simple robots, and supporting low-level mechanisms such as dynamics and navigation. In contrast, most human-like, interactive, and socially adept robotic systems turn away from embodiment and use amodal, symbolic, and modular approaches to cognition and interaction. At the same time, recent research in Embodied Cognition (EC) is spanning an increasing number of complex cognitive processes, including language, nonverbal communication, learning, and social behavior. This article suggests adopting a modern EC approach for autonomous robots interacting with humans. In particular, we present three core principles from EC that may be applicable to such robots: (a) modal perceptual representation, (b) action/perception and action/cognition integration, and (c) a simulation-based model of top-down perceptual biasing. We describe a computational framework based on these principles, and its implementation on two physical robots. This could provide a new paradigm for embodied human-robot interaction based on recent psychological and neurological findings. Copyright © 2012 Cognitive Science Society, Inc.

Comparison of experimental models for predicting laser-tissue interaction from 3.8-micron lasers

NASA Astrophysics Data System (ADS)

Williams, Piper C. M.; Winston, Golda C. H.; Randolph, Don Q.; Neal, Thomas A.; Eurell, Thomas E.; Johnson, Thomas E.

2004-07-01

The purpose of this study was to evaluate the laser-tissue interactions of engineered human skin and in-vivo pig skin following exposure to a single 3.8 micron laser light pulse. The goal of the study was to determine if these tissues shared common histologic features following laser exposure that might prove useful in developing in-vitro and in-vivo experimental models to predict the bioeffects of human laser exposure. The minimum exposure required to produce gross morphologic changes following a four microsecond, pulsed skin exposure for both models was determined. Histology was used to compare the cellular responses of the experimental models following laser exposure. Eighteen engineered skin equivalents (in-vitro model), were exposed to 3.8 micron laser light and the tissue responses compared to equivalent exposures made on five Yorkshire pigs (in-vivo model). Representative biopsies of pig skin were taken for histologic evaluation from various body locations immediately, one hour, and 24 hours following exposure. The pattern of epithelial changes seen following in-vitro laser exposure of the engineered human skin and in-vivo exposure of pig skin indicated a common histologic response for this particular combination of laser parameters.

Socio-hydrologic modeling to understand and mediate the competition for water between agriculture development and environmental health: Murrumbidgee River Basin, Australia

NASA Astrophysics Data System (ADS)

van Emmerik, T. H. M.; Li, Z.; Sivapalan, M.; Pande, S.; Kandasamy, J.; Savenije, H. H. G.; Chanan, A.; Vigneswaran, S.

2014-03-01

Competition for water between humans and ecosystems is set to become a flash point in the coming decades in many parts of the world. An entirely new and comprehensive quantitative framework is needed to establish a holistic understanding of that competition, thereby enabling the development of effective mediation strategies. This paper presents a modeling study centered on the Murrumbidgee River Basin (MRB). The MRB has witnessed a unique system dynamics over the last 100 years as a result of interactions between patterns of water management and climate driven hydrological variability. Data analysis has revealed a pendulum swing between agricultural development and restoration of environmental health and ecosystem services over different stages of basin scale water resource development. A parsimonious, stylized, quasi-distributed coupled socio-hydrologic system model that simulates the two-way coupling between human and hydrological systems of the MRB is used to mimic dominant features of the pendulum swing. The model consists of coupled nonlinear ordinary differential equations that describe the interaction between five state variables that govern the co-evolution: reservoir storage, irrigated area, human population, ecosystem health, and a measure of environmental awareness. The model simulations track the propagation of the external climatic and socio-economic drivers through this coupled, complex system to the emergence of the pendulum swing. The model results point to a competition between human "productive" and environmental "restorative" forces that underpin the pendulum swing. Both the forces are endogenous, i.e., generated by the system dynamics in response to external drivers and mediated by humans through technology change and environmental awareness, respectively. We propose this as a generalizable modeling framework for coupled human hydrological systems that is potentially transferable to systems in different climatic and socio-economic settings.

Predictability, Force and (Anti-)Resonance in Complex Object Control.

PubMed

Maurice, Pauline; Hogan, Neville; Sternad, Dagmar

2018-04-18

Manipulation of complex objects as in tool use is ubiquitous and has given humans an evolutionary advantage. This study examined the strategies humans choose when manipulating an object with underactuated internal dynamics, such as a cup of coffee. The object's dynamics renders the temporal evolution complex, possibly even chaotic, and difficult to predict. A cart-and-pendulum model, loosely mimicking coffee sloshing in a cup, was implemented in a virtual environment with a haptic interface. Participants rhythmically manipulated the virtual cup containing a rolling ball; they could choose the oscillation frequency, while the amplitude was prescribed. Three hypotheses were tested: 1) humans decrease interaction forces between hand and object; 2) humans increase the predictability of the object dynamics; 3) humans exploit the resonances of the coupled object-hand system. Analysis revealed that humans chose either a high-frequency strategy with anti-phase cup-and-ball movements or a low-frequency strategy with in-phase cup-and-ball movements. Counter Hypothesis 1, they did not decrease interaction force; instead, they increased the predictability of the interaction dynamics, quantified by mutual information, supporting Hypothesis 2. To address Hypothesis 3, frequency analysis of the coupled hand-object system revealed two resonance frequencies separated by an anti-resonance frequency. The low-frequency strategy exploited one resonance, while the high-frequency strategy afforded more choice, consistent with the frequency response of the coupled system; both strategies avoided the anti-resonance. Hence, humans did not prioritize interaction force, but rather strategies that rendered interactions predictable. These findings highlight that physical interactions with complex objects pose control challenges not present in unconstrained movements.

Mouse models for pathogenic African trypanosomes: unravelling the immunology of host-parasite-vector interactions.

PubMed

Magez, S; Caljon, G

2011-08-01

African trypanosomiasis is a parasitic disease that affects a variety of mammals, including humans, on the sub-Saharan African continent. To understand the diverse parameters that govern the host-parasite-vector interactions, mouse models for the disease have proven to be a cornerstone. Despite the fact that most trypanosomes cannot be considered natural pathogens for rodents, experimental infections in mice have shed a tremendous amount of light on the general biology of these parasites and their interaction with and evasion of the mammalian immune system. Different aspects including inflammation, vaccine failure, antigenic variation, resistance/sensitivity to normal human serum and the influence of tsetse compounds on parasite transmission have all been addressed using mouse models. In more recent years, the introduction of various 'knock-out' mouse strains has allowed to analyse the implication of various cytokines, particularly TNF, IFNγ and IL-10, in the regulation of parasitaemia and induction of pathological conditions during infection. © 2011 Blackwell Publishing Ltd.

Cooperative binding of drugs on human serum albumin

NASA Astrophysics Data System (ADS)

Varela, L. M.; Pérez-Rodríguez, M.; García, M.

In order to explain the adsorption isotherms of the amphiphilic penicillins nafcillin and cloxacillin onto human serum albumin (HSA), a cooperative multilayer adsorption model is introduced, combining the Brunauer-Emmet-Teller (BET) adsorption isotherm with an amphiphilic ionic adsorbate, whose chemical potential is derived from Guggenheim's theory. The non-cooperative model has been previously proved to qualitatively predict the measured adsorption maxima of these drugs [Varela, L. M., García, M., Pérez-Rodríguez, M., Taboada, P., Ruso, J. M., and Mosquera, V., 2001, J. chem. Phys., 114, 7682]. The surface interactions among adsorbed drug molecules are modelled in a mean-field fashion, so the chemical potential of the adsorbate is assumed to include a term proportional to the surface coverage, the constant of proportionality being the lateral interaction energy between bound molecules. The interaction energies obtained from the empirical binding isotherms are of the order of tenths of the thermal energy, therefore suggesting the principal role of van der Waals forces in the binding process.

Reading Aloud: Discrete Stage(s) Redux

PubMed Central

Robidoux, Serje; Besner, Derek

2017-01-01

Interactive activation accounts of processing have had a broad and deep influence on cognitive psychology, particularly so in the context of computational accounts of reading aloud at the single word level. Here we address the issue of whether such a framework can simulate the joint effects of stimulus quality and word frequency (which have been shown to produce both additive and interactive effects depending on the context). We extend previous work on this question by considering an alternative implementation of a stimulus quality manipulation, and the role of interactive activation. Simulations with a version of the Dual Route Cascaded model (a model with interactive activation dynamics along the lexical route) demonstrate that the model is unable to simulate the entire pattern seen in human performance. We discuss how a hybrid interactive activation model that includes some context dependent staged processing could accommodate these data. PMID:28289395

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.

Three-factor models versus time series models: quantifying time-dependencies of interactions between stimuli in cell biology and psychobiology for short longitudinal data.

PubMed

Frank, Till D; Kiyatkin, Anatoly; Cheong, Alex; Kholodenko, Boris N

2017-06-01

Signal integration determines cell fate on the cellular level, affects cognitive processes and affective responses on the behavioural level, and is likely to be involved in psychoneurobiological processes underlying mood disorders. Interactions between stimuli may subjected to time effects. Time-dependencies of interactions between stimuli typically lead to complex cell responses and complex responses on the behavioural level. We show that both three-factor models and time series models can be used to uncover such time-dependencies. However, we argue that for short longitudinal data the three factor modelling approach is more suitable. In order to illustrate both approaches, we re-analysed previously published short longitudinal data sets. We found that in human embryonic kidney 293 cells cells the interaction effect in the regulation of extracellular signal-regulated kinase (ERK) 1 signalling activation by insulin and epidermal growth factor is subjected to a time effect and dramatically decays at peak values of ERK activation. In contrast, we found that the interaction effect induced by hypoxia and tumour necrosis factor-alpha for the transcriptional activity of the human cyclo-oxygenase-2 promoter in HEK293 cells is time invariant at least in the first 12-h time window after stimulation. Furthermore, we applied the three-factor model to previously reported animal studies. In these studies, memory storage was found to be subjected to an interaction effect of the beta-adrenoceptor agonist clenbuterol and certain antagonists acting on the alpha-1-adrenoceptor / glucocorticoid-receptor system. Our model-based analysis suggests that only if the antagonist drug is administer in a critical time window, then the interaction effect is relevant. © The authors 2016. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.

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.

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.

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

HYDRAULIC ANALYSIS ON STREAM-AQUIFER INTERACTION BY STORAGE FUNCTION MODELS

EPA Science Inventory

In the natural hydrologic cycle, surface and subsurface water in a watershed are closely related and interact with each other. However, their relatrionships are affected by human activities. For instance, as the impervious area of a basin spreads due to urbanization, rainfall r...

Risk, individual differences, and environment: an Agent-Based Modeling approach to sexual risk-taking.

PubMed

Nagoski, Emily; Janssen, Erick; Lohrmann, David; Nichols, Eric

2012-08-01

Risky sexual behaviors, including the decision to have unprotected sex, result from interactions between individuals and their environment. The current study explored the use of Agent-Based Modeling (ABM)-a methodological approach in which computer-generated artificial societies simulate human sexual networks-to assess the influence of heterogeneity of sexual motivation on the risk of contracting HIV. The models successfully simulated some characteristics of human sexual systems, such as the relationship between individual differences in sexual motivation (sexual excitation and inhibition) and sexual risk, but failed to reproduce the scale-free distribution of number of partners observed in the real world. ABM has the potential to inform intervention strategies that target the interaction between an individual and his or her social environment.

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.

A composites-based hyperelastic constitutive model for soft tissue with application to the human annulus fibrosus

NASA Astrophysics Data System (ADS)

Guo, Z. Y.; Peng, X. Q.; Moran, B.

2006-09-01

This paper presents a composites-based hyperelastic constitutive model for soft tissue. Well organized soft tissue is treated as a composite in which the matrix material is embedded with a single family of aligned fibers. The fiber is modeled as a generalized neo-Hookean material in which the stiffness depends on fiber stretch. The deformation gradient is decomposed multiplicatively into two parts: a uniaxial deformation along the fiber direction and a subsequent shear deformation. This permits the fiber-matrix interaction caused by inhomogeneous deformation to be estimated by using effective properties from conventional composites theory based on small strain linear elasticity and suitably generalized to the present large deformation case. A transversely isotropic hyperelastic model is proposed to describe the mechanical behavior of fiber-reinforced soft tissue. This model is then applied to the human annulus fibrosus. Because of the layered anatomical structure of the annulus fibrosus, an orthotropic hyperelastic model of the annulus fibrosus is developed. Simulations show that the model reproduces the stress-strain response of the human annulus fibrosus accurately. We also show that the expression for the fiber-matrix shear interaction energy used in a previous phenomenological model is compatible with that derived in the present paper.

Zebrafish Axenic Larvae Colonization with Human Intestinal Microbiota.

PubMed

Arias-Jayo, Nerea; Alonso-Saez, Laura; Ramirez-Garcia, Andoni; Pardo, Miguel A

2018-04-01

The human intestine hosts a vast and complex microbial community that is vital for maintaining several functions related with host health. The processes that determine the gut microbiome composition are poorly understood, being the interaction between species, the external environment, and the relationship with the host the most feasible. Animal models offer the opportunity to understand the interactions between the host and the microbiota. There are different gnotobiotic mice or rat models colonized with the human microbiota, however, to our knowledge, there are no reports on the colonization of germ-free zebrafish with a complex human intestinal microbiota. In the present study, we have successfully colonized 5 days postfertilization germ-free zebrafish larvae with the human intestinal microbiota previously extracted from a donor and analyzed by high-throughput sequencing the composition of the transferred microbial communities that established inside the zebrafish gut. Thus, we describe for first time which human bacteria phylotypes are able to colonize the zebrafish digestive tract. Species with relevant interest because of their linkage to dysbiosis in different human diseases, such as Akkermansia muciniphila, Eubacterium rectale, Faecalibacterium prausnitzii, Prevotella spp., or Roseburia spp. have been successfully transferred inside the zebrafish digestive tract.

Memory and Learning--Using Mouse to Model Neurobiological and Behavioural Aspects of Down Syndrome and Assess Pharmacotherapeutics

ERIC Educational Resources Information Center

Gardiner, Katheleen

2009-01-01

Mouse models are a standard tool in the study of many human diseases, providing insights into the normal functions of a gene, how these are altered in disease and how they contribute to a disease process, as well as information on drug action, efficacy and side effects. Our knowledge of human genes, their genetics, functions, interactions and…

Commensal bacteria produce GPCR ligands that mimic human signaling molecules

PubMed Central

Cohen, Louis J.; Esterhazy, Daria; Kim, Seong-Hwan; Lemetre, Christophe; Aguilar, Rhiannon R.; Gordon, Emma A.; Pickard, Amanda J.; Cross, Justin R.; Emiliano, Ana B.; Han, Sun M.; Chu, John; Vila-Farres, Xavier; Kaplitt, Jeremy; Rogoz, Aneta; Calle, Paula Y.; Hunter, Craig; Bitok, J. Kipchirchir; Brady, Sean F.

2017-01-01

Summary Statement Commensal bacteria are believed to play important roles in human health. The mechanisms by which they affect mammalian physiology are poorly understood; however, bacterial metabolites are likely to be key components of host interactions. Here, we use bioinformatics and synthetic biology to mine the human microbiota for N-acyl amides that interact with G-protein-coupled receptors (GPCRs). We found that N-acyl amide synthase genes are enriched in gastrointestinal bacteria and the lipids they encode interact with GPCRs that regulate gastrointestinal tract physiology. Mouse and cell-based models demonstrate that commensal GPR119 agonists regulate metabolic hormones and glucose homeostasis as efficiently as human ligands although future studies are needed to define their potential physiologic role in humans. This work suggests that chemical mimicry of eukaryotic signaling molecules may be common among commensal bacteria and that manipulation of microbiota genes encoding metabolites that elicit host cellular responses represents a new small molecule therapeutic modality (microbiome-biosynthetic-gene-therapy). PMID:28854168

Calcium-dependent interaction of monomeric S100P protein with serum albumin.

PubMed

Kazakov, Alexei S; Shevelyova, Marina P; Ismailov, Ramis G; Permyakova, Maria E; Litus, Ekaterina A; Permyakov, Eugene A; Permyakov, Sergei E

2018-03-01

S100 proteins are multifunctional (intra/extra)cellular mostly dimeric calcium-binding proteins engaged into numerous diseases. We have found that monomeric recombinant human S100P protein interacts with intact human serum albumin (HSA) in excess of calcium ions with equilibrium dissociation constant of 25-50nM, as evidenced by surface plasmon resonance spectroscopy and fluorescent titration by HSA of S100P labelled by fluorescein isothiocyanate. Calcium removal or S100P dimerization abolish the S100P-HSA interaction. The interaction is selective, since S100P does not bind bovine serum albumin and monomeric human S100B lacks interaction with HSA. In vitro glycation of HSA disables its binding to S100P. The revealed selective and highly specific conformation-dependent interaction between S100P and HSA shows that functional properties of monomeric and dimeric forms of S100 proteins are different, and raises concerns on validity of cell-based assays and animal models used for studies of (patho)physiological roles of extracellular S100 proteins. Copyright © 2017 Elsevier B.V. All rights reserved.

Intrinsic Sensing and Evolving Internal Model Control of Compact Elastic Module for a Lower Extremity Exoskeleton.

PubMed

Wang, Likun; Du, Zhijiang; Dong, Wei; Shen, Yi; Zhao, Guangyu

2018-03-19

To achieve strength augmentation, endurance enhancement, and human assistance in a functional autonomous exoskeleton, control precision, back drivability, low output impedance, and mechanical compactness are desired. In our previous work, two elastic modules were designed for human-robot interaction sensing and compliant control, respectively. According to the intrinsic sensing properties of the elastic module, in this paper, only one compact elastic module is applied to realize both purposes. Thus, the corresponding control strategy is required and evolving internal model control is proposed to address this issue. Moreover, the input signal to the controller is derived from the deflection of the compact elastic module. The human-robot interaction is considered as the disturbance which is approximated by the output error between the exoskeleton control plant and evolving forward learning model. Finally, to verify our proposed control scheme, several experiments are conducted with our robotic exoskeleton system. The experiment shows a satisfying result and promising application feasibility.

Combining Multiple Forms Of Visual Information To Specify Contact Relations In Spatial Layout

NASA Astrophysics Data System (ADS)

Sedgwick, Hal A.

1990-03-01

An expert system, called Layout2, has been described, which models a subset of available visual information for spatial layout. The system is used to examine detailed interactions between multiple, partially redundant forms of information in an environment-centered geometrical model of an environment obeying certain rather general constraints. This paper discusses the extension of Layout2 to include generalized contact relations between surfaces. In an environment-centered model, the representation of viewer-centered distance is replaced by the representation of environmental location. This location information is propagated through the representation of the environment by a network of contact relations between contiguous surfaces. Perspective information interacts with other forms of information to specify these contact relations. The experimental study of human perception of contact relations in extended spatial layouts is also discussed. Differences between human results and Layout2 results reveal limitations in the human ability to register available information; they also point to the existence of certain forms of information not yet formalized in Layout2.

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.

What Machines Need to Learn to Support Human Problem-Solving

NASA Technical Reports Server (NTRS)

Vera, Alonso

2017-01-01

In the development of intelligent systems that interact with humans, there is often confusion between how the system functions with respect to the humans it interacts with and how it interfaces with those humans. The former is a much deeper challenge than the latter it requires a system-level understanding of evolving human roles as well as an understanding of what humans need to know (and when) in order to perform their tasks. This talk will focus on some of the challenges in getting this right as well as on the type of research and development that results in successful human-autonomy teaming. Brief Bio: Dr. Alonso Vera is Chief of the Human Systems Integration Division at NASA Ames Research Center. His expertise is in human-computer interaction, information systems, artificial intelligence, and computational human performance modeling. He has led the design, development and deployment of mission software systems across NASA robotic and human space flight missions, including Mars Exploration Rovers, Phoenix Mars Lander, ISS, Constellation, and Exploration Systems. Dr. Vera received a Bachelor of Science with First Class Honors from McGill University in 1985 and a Ph.D. from Cornell University in 1991. He went on to a Post-Doctoral Fellowship in the School of Computer Science at Carnegie Mellon University from 1990-93.

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.

Wildlife as valuable natural resources vs. intolerable pests: A suburban wildlife management model

USGS Publications Warehouse

DeStefano, S.; Deblinger, R.D.

2005-01-01

Management of wildlife in suburban environments involves a complex set of interactions between both human and wildlife populations. Managers need additional tools, such as models, that can help them assess the status of wildlife populations, devise and apply management programs, and convey this information to other professionals and the public. We present a model that conceptualizes how some wildlife populations can fluctuate between extremely low (rare, threatened, or endangered status) and extremely high (overabundant) numbers over time. Changes in wildlife abundance can induce changes in human perceptions, which continually redefine species as a valuable resource to be protected versus a pest to be controlled. Management programs thatincorporate a number of approaches and promote more stable populations of wildlife avoid the problems of the resource versus pest transformation, are less costly to society, and encourage more positive and less negative interactions between humans and wildlife. We presenta case example of the beaver Castor canadensis in Massachusetts to illustrate how this model functions and can be applied. ?? 2005 Springer Science + Business Media, Inc.

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.

Army-NASA aircrew/aircraft integration program (A3I) software detailed design document, phase 3

NASA Technical Reports Server (NTRS)

Banda, Carolyn; Chiu, Alex; Helms, Gretchen; Hsieh, Tehming; Lui, Andrew; Murray, Jerry; Shankar, Renuka

1990-01-01

The capabilities and design approach of the MIDAS (Man-machine Integration Design and Analysis System) computer-aided engineering (CAE) workstation under development by the Army-NASA Aircrew/Aircraft Integration Program is detailed. This workstation uses graphic, symbolic, and numeric prototyping tools and human performance models as part of an integrated design/analysis environment for crewstation human engineering. Developed incrementally, the requirements and design for Phase 3 (Dec. 1987 to Jun. 1989) are described. Software tools/models developed or significantly modified during this phase included: an interactive 3-D graphic cockpit design editor; multiple-perspective graphic views to observe simulation scenarios; symbolic methods to model the mission decomposition, equipment functions, pilot tasking and loading, as well as control the simulation; a 3-D dynamic anthropometric model; an intermachine communications package; and a training assessment component. These components were successfully used during Phase 3 to demonstrate the complex interactions and human engineering findings involved with a proposed cockpit communications design change in a simulated AH-64A Apache helicopter/mission that maps to empirical data from a similar study and AH-1 Cobra flight test.

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

EPA Science Inventory

Human health and well-being are and will be affected by climate change, both directly through changes in extreme weather events and indirectly through weather-induced changes in human and natural systems. Populations are vulnerable to these changes in varying degrees, depending ...

Human Birth Weight and Reproductive Immunology: Testing for Interactions between Maternal and Offspring KIR and HLA-C Genes.

PubMed

Clark, Michelle M; Chazara, Olympe; Sobel, Eric M; Gjessing, Håkon K; Magnus, Per; Moffett, Ashley; Sinsheimer, Janet S

2016-01-01

Maternal and offspring cell contact at the site of placentation presents a plausible setting for maternal-fetal genotype (MFG) interactions affecting fetal growth. We test hypotheses regarding killer cell immunoglobulin-like receptor (KIR) and HLA-C MFG effects on human birth weight by extending the quantitative MFG (QMFG) test. Until recently, association testing for MFG interactions had limited applications. To improve the ability to test for these interactions, we developed the extended QMFG test, a linear mixed-effect model that can use multi-locus genotype data from families. We demonstrate the extended QMFG test's statistical properties. We also show that if an offspring-only model is fit when MFG effects exist, associations can be missed or misattributed. Furthermore, imprecisely modeling the effects of both KIR and HLA-C could result in a failure to replicate if these loci's allele frequencies differ among populations. To further illustrate the extended QMFG test's advantages, we apply the extended QMFG test to a UK cohort study and the Norwegian Mother and Child Cohort (MoBa) study. We find a significant KIR-HLA-C interaction effect on birth weight. More generally, the QMFG test can detect genetic associations that may be missed by standard genome-wide association studies for quantitative traits. © 2017 S. Karger AG, Basel.

The Neural Representations Underlying Human Episodic Memory.

PubMed

Xue, Gui

2018-06-01

A fundamental question of human episodic memory concerns the cognitive and neural representations and processes that give rise to the neural signals of memory. By integrating behavioral tests, formal computational models, and neural measures of brain activity patterns, recent studies suggest that memory signals not only depend on the neural processes and representations during encoding and retrieval, but also on the interaction between encoding and retrieval (e.g., transfer-appropriate processing), as well as on the interaction between the tested events and all other events in the episodic memory space (e.g., global matching). In addition, memory signals are also influenced by the compatibility of the event with the existing long-term knowledge (e.g., schema matching). These studies highlight the interactive nature of human episodic memory. Copyright © 2018 Elsevier Ltd. All rights reserved.

Exploiting Motion Capture to Enhance Avoidance Behaviour in Games

NASA Astrophysics Data System (ADS)

van Basten, Ben J. H.; Jansen, Sander E. M.; Karamouzas, Ioannis

Realistic simulation of interacting virtual characters is essential in computer games, training and simulation applications. The problem is very challenging since people are accustomed to real-world situations and thus, they can easily detect inconsistencies and artifacts in the simulations. Over the past twenty years several models have been proposed for simulating individuals, groups and crowds of characters. However, little effort has been made to actually understand how humans solve interactions and avoid inter-collisions in real-life. In this paper, we exploit motion capture data to gain more insights into human-human interactions. We propose four measures to describe the collision-avoidance behavior. Based on these measures, we extract simple rules that can be applied on top of existing agent and force based approaches, increasing the realism of the resulting simulations.

Residents' Interaction with Their College Living-Learning Peer Mentor: A Grounded Theory

ERIC Educational Resources Information Center

Wylie, Jonathan Patrick

2012-01-01

This study used Strauss and Corbin's (1998) grounded theory model to describe and explain the stories of residents' interactions with their peer mentor, in a health, education, and human development living-learning community (LLC). The question answered in this study was: What is the impact of the interaction between a peer mentor and…

Effects of septum and pericardium on heart-lung interactions in a cardiopulmonary simulation model.

PubMed

Karamolegkos, Nikolaos; Albanese, Antonio; Chbat, Nicolas W

2017-07-01

Mechanical heart-lung interactions are often overlooked in clinical settings. However, their impact on cardiac function can be quite significant. Mechanistic physiology-based models can provide invaluable insights into such cardiorespiratory interactions, which occur not only under external mechanical ventilatory support but in normal physiology as well. In this work, we focus on the cardiac component of a previously developed mathematical model of the human cardiopulmonary system, aiming to improve the model's response to the intrathoracic pressure variations that are associated with the respiratory cycle. Interventricular septum and pericardial membrane are integrated into the existing model. Their effect on the overall cardiac response is explained by means of comparison against simulation results from the original model as well as experimental data from literature.

Interactive Genetic Algorithm - An Adaptive and Interactive Decision Support Framework for Design of Optimal Groundwater Monitoring Plans

NASA Astrophysics Data System (ADS)

Babbar-Sebens, M.; Minsker, B. S.

2006-12-01

In the water resources management field, decision making encompasses many kinds of engineering, social, and economic constraints and objectives. Representing all of these problem dependant criteria through models (analytical or numerical) and various formulations (e.g., objectives, constraints, etc.) within an optimization- simulation system can be a very non-trivial issue. Most models and formulations utilized for discerning desirable traits in a solution can only approximate the decision maker's (DM) true preference criteria, and they often fail to consider important qualitative and incomputable phenomena related to the management problem. In our research, we have proposed novel decision support frameworks that allow DMs to actively participate in the optimization process. The DMs explicitly indicate their true preferences based on their subjective criteria and the results of various simulation models and formulations. The feedback from the DMs is then used to guide the search process towards solutions that are "all-rounders" from the perspective of the DM. The two main research questions explored in this work are: a) Does interaction between the optimization algorithm and a DM assist the system in searching for groundwater monitoring designs that are robust from the DM's perspective?, and b) How can an interactive search process be made more effective when human factors, such as human fatigue and cognitive learning processes, affect the performance of the algorithm? The application of these frameworks on a real-world groundwater long-term monitoring (LTM) case study in Michigan highlighted the following salient advantages: a) in contrast to the non-interactive optimization methodology, the proposed interactive frameworks were able to identify low cost monitoring designs whose interpolation maps respected the expected spatial distribution of the contaminants, b) for many same-cost designs, the interactive methodologies were able to propose multiple alternatives that met the DM's preference criteria, therefore allowing the expert to select among several strong candidate designs depending on her/his LTM budget, c) two of the methodologies - Case-Based Micro Interactive Genetic Algorithm (CBMIGA) and Interactive Genetic Algorithm with Mixed Initiative Interaction (IGAMII) - were also able to assist in controlling human fatigue and adapt to the DM's learning process.

Multiple tipping points and optimal repairing in interacting networks

PubMed Central

Majdandzic, Antonio; Braunstein, Lidia A.; Curme, Chester; Vodenska, Irena; Levy-Carciente, Sary; Eugene Stanley, H.; Havlin, Shlomo

2016-01-01

Systems composed of many interacting dynamical networks—such as the human body with its biological networks or the global economic network consisting of regional clusters—often exhibit complicated collective dynamics. Three fundamental processes that are typically present are failure, damage spread and recovery. Here we develop a model for such systems and find a very rich phase diagram that becomes increasingly more complex as the number of interacting networks increases. In the simplest example of two interacting networks we find two critical points, four triple points, ten allowed transitions and two ‘forbidden' transitions, as well as complex hysteresis loops. Remarkably, we find that triple points play the dominant role in constructing the optimal repairing strategy in damaged interacting systems. To test our model, we analyse an example of real interacting financial networks and find evidence of rapid dynamical transitions between well-defined states, in agreement with the predictions of our model. PMID:26926803

Modeling pilot interaction with automated digital avionics systems: Guidance and control algorithms for contour and nap-of-the-Earth flight

NASA Technical Reports Server (NTRS)

Hess, Ronald A.

1990-01-01

A collection of technical papers are presented that cover modeling pilot interaction with automated digital avionics systems and guidance and control algorithms for contour and nap-of-the-earth flight. The titles of the papers presented are as follows: (1) Automation effects in a multiloop manual control system; (2) A qualitative model of human interaction with complex dynamic systems; (3) Generalized predictive control of dynamic systems; (4) An application of generalized predictive control to rotorcraft terrain-following flight; (5) Self-tuning generalized predictive control applied to terrain-following flight; and (6) Precise flight path control using a predictive algorithm.

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.

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.

Attentional control of associative learning--a possible role of the central cholinergic system.

PubMed

Pauli, Wolfgang M; O'Reilly, Randall C

2008-04-02

How does attention interact with learning? Kruschke [Kruschke, J.K. (2001). Toward a unified Model of Attention in Associative Learning. J. Math. Psychol. 45, 812-863.] proposed a model (EXIT) that captures Mackintosh's [Mackintosh, N.J. (1975). A theory of attention: Variations in the associability of stimuli with reinforcement. Psychological Review, 82(4), 276-298.] framework for attentional modulation of associative learning. We developed a computational model that showed analogous interactions between selective attention and associative learning, but is significantly simplified and, in contrast to EXIT, is motivated by neurophysiological findings. Competition among input representations in the internal representation layer, which increases the contrast between stimuli, is critical for simulating these interactions in human behavior. Furthermore, this competition is modulated in a way that might be consistent with the phasic activation of the central cholinergic system, which modulates activity in sensory cortices. Specifically, phasic increases in acetylcholine can cause increased excitability of both pyramidal excitatory neurons in cortical layers II/III and cortical GABAergic inhibitory interneurons targeting the same pyramidal neurons. These effects result in increased attentional contrast in our model. This model thus represents an initial attempt to link human attentional learning data with underlying neural substrates.

Attentional control of associative learning—A possible role of the central cholinergic system

PubMed Central

Pauli, Wolfgang M.; O'Reilly, Randall C.

2010-01-01

How does attention interact with learning? Kruschke [Kruschke, J.K. (2001). Toward a unified Model of Attention in Associative Learning. J. Math. Psychol. 45, 812–863.] proposed a model (EXIT) that captures Mackintosh's [Mackintosh, N.J. (1975). A theory of attention: Variations in the associability of stimuli with reinforcement. Psychological Review, 82(4), 276–298.] framework for attentional modulation of associative learning. We developed a computational model that showed analogous interactions between selective attention and associative learning, but is significantly simplified and, in contrast to EXIT, is motivated by neurophysiological findings. Competition among input representations in the internal representation layer, which increases the contrast between stimuli, is critical for simulating these interactions in human behavior. Furthermore, this competition is modulated in a way that might be consistent with the phasic activation of the central cholinergic system, which modulates activity in sensory cortices. Specifically, phasic increases in acetylcholine can cause increased excitability of both pyramidal excitatory neurons in cortical layers II/III and cortical GABAergic inhibitory interneurons targeting the same pyramidal neurons. These effects result in increased attentional contrast in our model. This model thus represents an initial attempt to link human attentional learning data with underlying neural substrates. PMID:17870060

What are the Outstanding Questions in Biosphere-Atmosphere Exchange?

NASA Astrophysics Data System (ADS)

Katul, G.; Finnigan, J.

2002-12-01

Our answer to this question has three parts. At the highest level human population is now so large (and will grow to 10-12 million by 2050 before stabilizing and reversing) and our capacity to influence the biosphere is so profound that we must now treat human, biophysical and geophysical processes as a single interacting system: the Anthroposphere. The Anthroposphere is a complex adaptive system (CAS) in the sense that action of humans individually or in groups (as large as nations) are a response to an environment that includes not just the geosphere and biosphere but the sum of human interactions as well. These actions, in turn, will change this system that provides critical ecosystem services that we are just now realizing are finite and threatened. At present we lack the tools and understanding even to frame key questions about the Anthroposphere although the emerging discipline of Complex System Science is hinting at ways this might be done. At the next level we address the problems posed by cross-scale interactions central to the state and function of the geosphere and biosphere, where processes at the cellular level, (e.g. photosynthesis and respiration), have consequences on the global level and vice-versa through a sequence of non-linear upscale and downscale interactions. Currently there are large gaps in our understanding of this scale cascade that inhibit our ability to parameterize, model and predict phenomena such as the rapid shifts in climate that recent studies of the paleo record have revealed. In short, we need to quantify the risk that our current actions may cause abrupt climate changes that may then feed upon the Anthrosphere. Unless we can reduce the uncertainty with which we describe quantitatively the non-human parts of the Anthroposphere, the injection of models of human interaction, initially tentative, may reduce our predictive ability to unusable levels. Finally we can detail a set of key processes that are themselves critical to geosphere-biosphere functioning but which are poorly understood as yet.

Neisseria gonorrhoeae co-infection exacerbates vaginal HIV shedding without affecting systemic viral loads in human CD34+ engrafted mice.

PubMed

Xu, Stacey X; Leontyev, Danila; Kaul, Rupert; Gray-Owen, Scott D

2018-01-01

HIV synergy with sexually transmitted co-infections is well-documented in the clinic. Co-infection with Neisseria gonorrhoeae in particular, increases genital HIV shedding and mucosal transmission. However, no animal model of co-infection currently exists to directly explore this relationship or to bridge the gap in understanding between clinical and in vitro studies of this interaction. This study aims to test the feasibility of using a humanized mouse model to overcome this barrier. Combining recent in vivo modelling advancements in both HIV and gonococcal research, we developed a co-infection model by engrafting immunodeficient NSG mice with human CD34+ hematopoietic stem cells to generate humanized mice that permit both systemic HIV infection and genital N. gonorrhoeae infection. Systemic plasma and vaginal lavage titres of HIV were measured in order to assess the impact of gonococcal challenge on viral plasma titres and genital shedding. Engrafted mice showed human CD45+ leukocyte repopulation in blood and mucosal tissues. Systemic HIV challenge resulted in 104-105 copies/mL of viral RNA in blood by week 4 post-infection, as well as vaginal shedding of virus. Subsequent gonococcal challenge resulted in unchanged plasma HIV levels but higher viral shedding in the genital tract, which reflects published clinical observations. Thus, human CD34+ stem cell-transplanted NSG mice represent an experimentally tractable animal model in which to study HIV shedding during gonococcal co-infection, allowing dissection of molecular and immunological interactions between these pathogens, and providing a platform to assess future therapeutics aimed at reducing HIV transmission.

Data-driven analysis of functional brain interactions during free listening to music and speech.

PubMed

Fang, Jun; Hu, Xintao; Han, Junwei; Jiang, Xi; Zhu, Dajiang; Guo, Lei; Liu, Tianming

2015-06-01

Natural stimulus functional magnetic resonance imaging (N-fMRI) such as fMRI acquired when participants were watching video streams or listening to audio streams has been increasingly used to investigate functional mechanisms of the human brain in recent years. One of the fundamental challenges in functional brain mapping based on N-fMRI is to model the brain's functional responses to continuous, naturalistic and dynamic natural stimuli. To address this challenge, in this paper we present a data-driven approach to exploring functional interactions in the human brain during free listening to music and speech streams. Specifically, we model the brain responses using N-fMRI by measuring the functional interactions on large-scale brain networks with intrinsically established structural correspondence, and perform music and speech classification tasks to guide the systematic identification of consistent and discriminative functional interactions when multiple subjects were listening music and speech in multiple categories. The underlying premise is that the functional interactions derived from N-fMRI data of multiple subjects should exhibit both consistency and discriminability. Our experimental results show that a variety of brain systems including attention, memory, auditory/language, emotion, and action networks are among the most relevant brain systems involved in classic music, pop music and speech differentiation. Our study provides an alternative approach to investigating the human brain's mechanism in comprehension of complex natural music and speech.

Transcriptomic Studies of Malaria: a Paradigm for Investigation of Systemic Host-Pathogen Interactions

PubMed Central

2018-01-01

SUMMARY Transcriptomics, the analysis of genome-wide RNA expression, is a common approach to investigate host and pathogen processes in infectious diseases. Technical and bioinformatic advances have permitted increasingly thorough analyses of the association of RNA expression with fundamental biology, immunity, pathogenesis, diagnosis, and prognosis. Transcriptomic approaches can now be used to realize a previously unattainable goal, the simultaneous study of RNA expression in host and pathogen, in order to better understand their interactions. This exciting prospect is not without challenges, especially as focus moves from interactions in vitro under tightly controlled conditions to tissue- and systems-level interactions in animal models and natural and experimental infections in humans. Here we review the contribution of transcriptomic studies to the understanding of malaria, a parasitic disease which has exerted a major influence on human evolution and continues to cause a huge global burden of disease. We consider malaria a paradigm for the transcriptomic assessment of systemic host-pathogen interactions in humans, because much of the direct host-pathogen interaction occurs within the blood, a readily sampled compartment of the body. We illustrate lessons learned from transcriptomic studies of malaria and how these lessons may guide studies of host-pathogen interactions in other infectious diseases. We propose that the potential of transcriptomic studies to improve the understanding of malaria as a disease remains partly untapped because of limitations in study design rather than as a consequence of technological constraints. Further advances will require the integration of transcriptomic data with analytical approaches from other scientific disciplines, including epidemiology and mathematical modeling. PMID:29695497

Transcriptomic Studies of Malaria: a Paradigm for Investigation of Systemic Host-Pathogen Interactions.

PubMed

Lee, Hyun Jae; Georgiadou, Athina; Otto, Thomas D; Levin, Michael; Coin, Lachlan J; Conway, David J; Cunnington, Aubrey J

2018-06-01

Transcriptomics, the analysis of genome-wide RNA expression, is a common approach to investigate host and pathogen processes in infectious diseases. Technical and bioinformatic advances have permitted increasingly thorough analyses of the association of RNA expression with fundamental biology, immunity, pathogenesis, diagnosis, and prognosis. Transcriptomic approaches can now be used to realize a previously unattainable goal, the simultaneous study of RNA expression in host and pathogen, in order to better understand their interactions. This exciting prospect is not without challenges, especially as focus moves from interactions in vitro under tightly controlled conditions to tissue- and systems-level interactions in animal models and natural and experimental infections in humans. Here we review the contribution of transcriptomic studies to the understanding of malaria, a parasitic disease which has exerted a major influence on human evolution and continues to cause a huge global burden of disease. We consider malaria a paradigm for the transcriptomic assessment of systemic host-pathogen interactions in humans, because much of the direct host-pathogen interaction occurs within the blood, a readily sampled compartment of the body. We illustrate lessons learned from transcriptomic studies of malaria and how these lessons may guide studies of host-pathogen interactions in other infectious diseases. We propose that the potential of transcriptomic studies to improve the understanding of malaria as a disease remains partly untapped because of limitations in study design rather than as a consequence of technological constraints. Further advances will require the integration of transcriptomic data with analytical approaches from other scientific disciplines, including epidemiology and mathematical modeling. Copyright © 2018 Lee et al.

Phase transitions in models of human cooperation

NASA Astrophysics Data System (ADS)

Perc, Matjaž

2016-08-01

If only the fittest survive, why should one cooperate? Why should one sacrifice personal benefits for the common good? Recent research indicates that a comprehensive answer to such questions requires that we look beyond the individual and focus on the collective behavior that emerges as a result of the interactions among individuals, groups, and societies. Although undoubtedly driven also by culture and cognition, human cooperation is just as well an emergent, collective phenomenon in a complex system. Nonequilibrium statistical physics, in particular the collective behavior of interacting particles near phase transitions, has already been recognized as very valuable for understanding counterintuitive evolutionary outcomes. However, unlike pairwise interactions among particles that typically govern solid-state physics systems, interactions among humans often involve group interactions, and they also involve a larger number of possible states even for the most simplified description of reality. Here we briefly review research done in the realm of the public goods game, and we outline future research directions with an emphasis on merging the most recent advances in the social sciences with methods of nonequilibrium statistical physics. By having a firm theoretical grip on human cooperation, we can hope to engineer better social systems and develop more efficient policies for a sustainable and better future.

Identification of methyllysine peptides binding to chromobox protein homolog 6 chromodomain in the human proteome.

PubMed

Li, Nan; Stein, Richard S L; He, Wei; Komives, Elizabeth; Wang, Wei

2013-10-01

Methylation is one of the important post-translational modifications that play critical roles in regulating protein functions. Proteomic identification of this post-translational modification and understanding how it affects protein activity remain great challenges. We tackled this problem from the aspect of methylation mediating protein-protein interaction. Using the chromodomain of human chromobox protein homolog 6 as a model system, we developed a systematic approach that integrates structure modeling, bioinformatics analysis, and peptide microarray experiments to identify lysine residues that are methylated and recognized by the chromodomain in the human proteome. Given the important role of chromobox protein homolog 6 as a reader of histone modifications, it was interesting to find that the majority of its interacting partners identified via this approach function in chromatin remodeling and transcriptional regulation. Our study not only illustrates a novel angle for identifying methyllysines on a proteome-wide scale and elucidating their potential roles in regulating protein function, but also suggests possible strategies for engineering the chromodomain-peptide interface to enhance the recognition of and manipulate the signal transduction mediated by such interactions.

Anatomical connectivity influences both intra- and inter-brain synchronizations.

PubMed

Dumas, Guillaume; Chavez, Mario; Nadel, Jacqueline; Martinerie, Jacques

2012-01-01

Recent development in diffusion spectrum brain imaging combined to functional simulation has the potential to further our understanding of how structure and dynamics are intertwined in the human brain. At the intra-individual scale, neurocomputational models have already started to uncover how the human connectome constrains the coordination of brain activity across distributed brain regions. In parallel, at the inter-individual scale, nascent social neuroscience provides a new dynamical vista of the coupling between two embodied cognitive agents. Using EEG hyperscanning to record simultaneously the brain activities of subjects during their ongoing interaction, we have previously demonstrated that behavioral synchrony correlates with the emergence of inter-brain synchronization. However, the functional meaning of such synchronization remains to be specified. Here, we use a biophysical model to quantify to what extent inter-brain synchronizations are related to the anatomical and functional similarity of the two brains in interaction. Pairs of interacting brains were numerically simulated and compared to real data. Results show a potential dynamical property of the human connectome to facilitate inter-individual synchronizations and thus may partly account for our propensity to generate dynamical couplings with others.

Quantifying the influences of various ecological factors on land surface temperature of urban forests.

PubMed

Ren, Yin; Deng, Lu-Ying; Zuo, Shu-Di; Song, Xiao-Dong; Liao, Yi-Lan; Xu, Cheng-Dong; Chen, Qi; Hua, Li-Zhong; Li, Zheng-Wei

2016-09-01

Identifying factors that influence the land surface temperature (LST) of urban forests can help improve simulations and predictions of spatial patterns of urban cool islands. This requires a quantitative analytical method that combines spatial statistical analysis with multi-source observational data. The purpose of this study was to reveal how human activities and ecological factors jointly influence LST in clustering regions (hot or cool spots) of urban forests. Using Xiamen City, China from 1996 to 2006 as a case study, we explored the interactions between human activities and ecological factors, as well as their influences on urban forest LST. Population density was selected as a proxy for human activity. We integrated multi-source data (forest inventory, digital elevation models (DEM), population, and remote sensing imagery) to develop a database on a unified urban scale. The driving mechanism of urban forest LST was revealed through a combination of multi-source spatial data and spatial statistical analysis of clustering regions. The results showed that the main factors contributing to urban forest LST were dominant tree species and elevation. The interactions between human activity and specific ecological factors linearly or nonlinearly increased LST in urban forests. Strong interactions between elevation and dominant species were generally observed and were prevalent in either hot or cold spots areas in different years. In conclusion, quantitative studies based on spatial statistics and GeogDetector models should be conducted in urban areas to reveal interactions between human activities, ecological factors, and LST. Copyright © 2016 Elsevier Ltd. All rights reserved.

Bayesian networks and information theory for audio-visual perception modeling.

PubMed

Besson, Patricia; Richiardi, Jonas; Bourdin, Christophe; Bringoux, Lionel; Mestre, Daniel R; Vercher, Jean-Louis

2010-09-01

Thanks to their different senses, human observers acquire multiple information coming from their environment. Complex cross-modal interactions occur during this perceptual process. This article proposes a framework to analyze and model these interactions through a rigorous and systematic data-driven process. This requires considering the general relationships between the physical events or factors involved in the process, not only in quantitative terms, but also in term of the influence of one factor on another. We use tools from information theory and probabilistic reasoning to derive relationships between the random variables of interest, where the central notion is that of conditional independence. Using mutual information analysis to guide the model elicitation process, a probabilistic causal model encoded as a Bayesian network is obtained. We exemplify the method by using data collected in an audio-visual localization task for human subjects, and we show that it yields a well-motivated model with good predictive ability. The model elicitation process offers new prospects for the investigation of the cognitive mechanisms of multisensory perception.

Targeted Proteomics and Absolute Protein Quantification for the Construction of a Stoichiometric Host-Pathogen Surface Density Model.

PubMed

Sjöholm, Kristoffer; Kilsgård, Ola; Teleman, Johan; Happonen, Lotta; Malmström, Lars; Malmström, Johan

2017-04-01

Sepsis is a systemic immune response responsible for considerable morbidity and mortality. Molecular modeling of host-pathogen interactions in the disease state represents a promising strategy to define molecular events of importance for the transition from superficial to invasive infectious diseases. Here we used the Gram-positive bacterium Streptococcus pyogenes as a model system to establish a mass spectrometry based workflow for the construction of a stoichiometric surface density model between the S. pyogenes surface, the surface virulence factor M-protein, and adhered human blood plasma proteins. The workflow relies on stable isotope labeled reference peptides and selected reaction monitoring mass spectrometry analysis of a wild-type strain and an M-protein deficient mutant strain, to generate absolutely quantified protein stoichiometry ratios between S. pyogenes and interacting plasma proteins. The stoichiometry ratios in combination with a novel targeted mass spectrometry method to measure cell numbers enabled the construction of a stoichiometric surface density model using protein structures available from the protein data bank. The model outlines the topology and density of the host-pathogen protein interaction network on the S. pyogenes bacterial surface, revealing a dense and highly organized protein interaction network. Removal of the M-protein from S. pyogenes introduces a drastic change in the network topology, validated by electron microscopy. We propose that the stoichiometric surface density model of S. pyogenes in human blood plasma represents a scalable framework that can continuously be refined with the emergence of new results. Future integration of new results will improve the understanding of protein-protein interactions and their importance for bacterial virulence. Furthermore, we anticipate that the general properties of the developed workflow will facilitate the production of stoichiometric surface density models for other types of host-pathogen interactions. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

An evaluative model of system performance in manned teleoperational systems

NASA Technical Reports Server (NTRS)

Haines, Richard F.

1989-01-01

Manned teleoperational systems are used in aerospace operations in which humans must interact with machines remotely. Manual guidance of remotely piloted vehicles, controling a wind tunnel, carrying out a scientific procedure remotely are examples of teleoperations. A four input parameter throughput (Tp) model is presented which can be used to evaluate complex, manned, teleoperations-based systems and make critical comparisons among candidate control systems. The first two parameters of this model deal with nominal (A) and off-nominal (B) predicted events while the last two focus on measured events of two types, human performance (C) and system performance (D). Digital simulations showed that the expression A(1-B)/C+D) produced the greatest homogeneity of variance and distribution symmetry. Results from a recently completed manned life science telescience experiment will be used to further validate the model. Complex, interacting teleoperational systems may be systematically evaluated using this expression much like a computer benchmark is used.

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.

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.

Solution structure of the first RNA recognition motif domain of human spliceosomal protein SF3b49 and its mode of interaction with a SF3b145 fragment

PubMed Central

Nameki, Nobukazu; Tsuda, Kengo; Takahashi, Mari; Sato, Atsuko; Tochio, Naoya; Inoue, Makoto; Terada, Takaho; Kigawa, Takanori; Kobayashi, Naohiro; Shirouzu, Mikako; Ito, Takuhiro; Sakamoto, Taiichi; Wakamatsu, Kaori; Güntert, Peter; Takahashi, Seizo; Yokoyama, Shigeyuki

2016-01-01

Abstract The spliceosomal protein SF3b49, a component of the splicing factor 3b (SF3b) protein complex in the U2 small nuclear ribonucleoprotein, contains two RNA recognition motif (RRM) domains. In yeast, the first RRM domain (RRM1) of Hsh49 protein (yeast orthologue of human SF3b49) reportedly interacts with another component, Cus1 protein (orthologue of human SF3b145). Here, we solved the solution structure of the RRM1 of human SF3b49 and examined its mode of interaction with a fragment of human SF3b145 using NMR methods. Chemical shift mapping showed that the SF3b145 fragment spanning residues 598–631 interacts with SF3b49 RRM1, which adopts a canonical RRM fold with a topology of β1‐α1‐β2‐β3‐α2‐β4. Furthermore, a docking model based on NOESY measurements suggests that residues 607–616 of the SF3b145 fragment adopt a helical structure that binds to RRM1 predominantly via α1, consequently exhibiting a helix–helix interaction in almost antiparallel. This mode of interaction was confirmed by a mutational analysis using GST pull‐down assays. Comparison with structures of all RRM domains when complexed with a peptide found that this helix–helix interaction is unique to SF3b49 RRM1. Additionally, all amino acid residues involved in the interaction are well conserved among eukaryotes, suggesting evolutionary conservation of this interaction mode between SF3b49 RRM1 and SF3b145. PMID:27862552

Metagenomic systems biology and metabolic modeling of the human microbiome: from species composition to community assembly rules.

PubMed

Levy, Roie; Borenstein, Elhanan

2014-01-01

The human microbiome is a key contributor to health and development. Yet little is known about the ecological forces that are at play in defining the composition of such host-associated communities. Metagenomics-based studies have uncovered clear patterns of community structure but are often incapable of distinguishing alternative structuring paradigms. In a recent study, we integrated metagenomic analysis with a systems biology approach, using a reverse ecology framework to model numerous human microbiota species and to infer metabolic interactions between species. Comparing predicted interactions with species composition data revealed that the assembly of the human microbiome is dominated at the community level by habitat filtering. Furthermore, we demonstrated that this habitat filtering cannot be accounted for by known host phenotypes or by the metabolic versatility of the various species. Here we provide a summary of our findings and offer a brief perspective on related studies and on future approaches utilizing this metagenomic systems biology framework.

Human bone marrow-derived MSCs can home to orthotopic breast cancer tumors and promote bone metastasis

PubMed Central

Goldstein, Robert H; Reagan, Michaela R; Anderson, Kristen; Kaplan, David L; Rosenblatt, Michael

2010-01-01

American women have a nearly 25% lifetime risk of developing breast cancer, with 20–40% of these patients developing life-threatening metastases. Over 70% of patients presenting with metastases have skeletal involvement, which signals progression to an incurable stage. Tumor-stroma cell interactions are only superficially understood, specifically regarding the ability of stromal cells to affect metastasis. In vivo models show that exogenously supplied hBMSCs (human bone-marrow derived stem cells) migrate to breast cancer tumors, but no reports have shown endogenous hBMSC migration from the bone to primary tumors. Here we present a model of in vivo hBMSC migration from a physiologic human bone environment to human breast tumors. Further, hBMSCs alter tumor growth and bone metastasis frequency. hBMSCs may home to certain breast tumors based on tumor-derived TGF-β1. Moreover, at the primary tumor IL-17B/IL-17BR signaling may mediate interactions between hBMSCs and breast cancer cells (BCCs). PMID:21159629

The Design of Hand Gestures for Human-Computer Interaction: Lessons from Sign Language Interpreters

PubMed Central

Rempel, David; Camilleri, Matt J.; Lee, David L.

2015-01-01

The design and selection of 3D modeled hand gestures for human-computer interaction should follow principles of natural language combined with the need to optimize gesture contrast and recognition. The selection should also consider the discomfort and fatigue associated with distinct hand postures and motions, especially for common commands. Sign language interpreters have extensive and unique experience forming hand gestures and many suffer from hand pain while gesturing. Professional sign language interpreters (N=24) rated discomfort for hand gestures associated with 47 characters and words and 33 hand postures. Clear associations of discomfort with hand postures were identified. In a nominal logistic regression model, high discomfort was associated with gestures requiring a flexed wrist, discordant adjacent fingers, or extended fingers. These and other findings should be considered in the design of hand gestures to optimize the relationship between human cognitive and physical processes and computer gesture recognition systems for human-computer input. PMID:26028955

A rapid method for selecting suitable animal species for studying pathogen interactions with plasma protein ligands in vivo.

PubMed

Naudin, Clément; Schumski, Ariane; Salo-Ahen, Outi M H; Herwald, Heiko; Smeds, Emanuel

2017-05-01

Species tropism constitutes a serious problem for developing relevant animal models of infection. Human pathogens can express virulence factors that show specific selectivity to human proteins, while their affinity for orthologs from other species can vary significantly. Suitable animal species must be used to analyse whether virulence factors are potential targets for drug development. We developed an assay that rapidly predicts applicable animal species for studying virulence factors binding plasma proteins. We used two well-characterized Staphylococcus aureus proteins, SSL7 and Efb, to develop an ELISA-based inhibition assay using plasma from different animal species. The interaction between SSL7 and human C5 and the binding of Efb to human fibrinogen and human C3 was studied. Affinity experiments and Western blot analyses were used to validate the assay. Human, monkey and cat plasma interfered with binding of SSL7 to human C5. Binding of Efb to human fibrinogen was blocked in human, monkey, gerbil and pig plasma, while human, monkey, gerbil, rabbit, cat and guinea pig plasma inhibited the binding of Efb to human C3. These results emphasize the importance of choosing correct animal models, and thus, our approach is a rapid and cost-effective method that can be used to prevent unnecessary animal experiments. © 2017 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.

Predicting interactions among fishing, ocean warming, and ocean acidification in a marine system with whole-ecosystem models.

PubMed

Griffith, Gary P; Fulton, Elizabeth A; Gorton, Rebecca; Richardson, Anthony J

2012-12-01

An important challenge for conservation is a quantitative understanding of how multiple human stressors will interact to mitigate or exacerbate global environmental change at a community or ecosystem level. We explored the interaction effects of fishing, ocean warming, and ocean acidification over time on 60 functional groups of species in the southeastern Australian marine ecosystem. We tracked changes in relative biomass within a coupled dynamic whole-ecosystem modeling framework that included the biophysical system, human effects, socioeconomics, and management evaluation. We estimated the individual, additive, and interactive effects on the ecosystem and for five community groups (top predators, fishes, benthic invertebrates, plankton, and primary producers). We calculated the size and direction of interaction effects with an additive null model and interpreted results as synergistic (amplified stress), additive (no additional stress), or antagonistic (reduced stress). Individually, only ocean acidification had a negative effect on total biomass. Fishing and ocean warming and ocean warming with ocean acidification had an additive effect on biomass. Adding fishing to ocean warming and ocean acidification significantly changed the direction and magnitude of the interaction effect to a synergistic response on biomass. The interaction effect depended on the response level examined (ecosystem vs. community). For communities, the size, direction, and type of interaction effect varied depending on the combination of stressors. Top predator and fish biomass had a synergistic response to the interaction of all three stressors, whereas biomass of benthic invertebrates responded antagonistically. With our approach, we were able to identify the regional effects of fishing on the size and direction of the interacting effects of ocean warming and ocean acidification. ©2012 Society for Conservation Biology.

Learning to make collective decisions: the impact of confidence escalation.

PubMed

Mahmoodi, Ali; Bang, Dan; Ahmadabadi, Majid Nili; Bahrami, Bahador

2013-01-01

Little is known about how people learn to take into account others' opinions in joint decisions. To address this question, we combined computational and empirical approaches. Human dyads made individual and joint visual perceptual decision and rated their confidence in those decisions (data previously published). We trained a reinforcement (temporal difference) learning agent to get the participants' confidence level and learn to arrive at a dyadic decision by finding the policy that either maximized the accuracy of the model decisions or maximally conformed to the empirical dyadic decisions. When confidences were shared visually without verbal interaction, RL agents successfully captured social learning. When participants exchanged confidences visually and interacted verbally, no collective benefit was achieved and the model failed to predict the dyadic behaviour. Behaviourally, dyad members' confidence increased progressively and verbal interaction accelerated this escalation. The success of the model in drawing collective benefit from dyad members was inversely related to confidence escalation rate. The findings show an automated learning agent can, in principle, combine individual opinions and achieve collective benefit but the same agent cannot discount the escalation suggesting that one cognitive component of collective decision making in human may involve discounting of overconfidence arising from interactions.

Requirements for psychological models to support design: Towards ecological task analysis

NASA Technical Reports Server (NTRS)

Kirlik, Alex

1991-01-01

Cognitive engineering is largely concerned with creating environmental designs to support skillful and effective human activity. A set of necessary conditions are proposed for psychological models capable of supporting this enterprise. An analysis of the psychological nature of the design product is used to identify a set of constraints that models must meet if they can usefully guide design. It is concluded that cognitive engineering requires models with resources for describing the integrated human-environment system, and that these models must be capable of describing the activities underlying fluent and effective interaction. These features are required in order to be able to predict the cognitive activity that will be required given various design concepts, and to design systems that promote the acquisition of fluent, skilled behavior. These necessary conditions suggest that an ecological approach can provide valuable resources for psychological modeling to support design. Relying heavily on concepts from Brunswik's and Gibson's ecological theories, ecological task analysis is proposed as a framework in which to predict the types of cognitive activity required to achieve productive behavior, and to suggest how interfaces can be manipulated to alleviate certain types of cognitive demands. The framework is described in terms, and illustrated with an example from the previous research on modeling skilled human-environment interaction.

Development of an Intelligent Digital Watershed to understand water-human interaction for a sustainable Agroeconomy in Midwest USA

NASA Astrophysics Data System (ADS)

Mishra, S. K.; Rapolu, U.; Ding, D.; Muste, M.; Bennett, D.; Schnoor, J. L.

2011-12-01

Human activity is intricately linked to the quality and quantity of water resources. Although many studies have examined water-human interaction, the complexity of such coupled systems is not well understood largely because of gaps in our knowledge of water-cycle processes which are heavily influenced by socio-economic drivers. Considerable research has been performed to develop an understanding of the impact of local land use decisions on field and catchment processes at an annual basis. Still less is known about the impact of economic and environmental outcomes on decision-making processes at the local and national level. Traditional geographic information management systems lack the ability to support the modeling and analysis of complex spatial processes. New frameworks are needed to track, query, and analyze the massive amounts of data generated by ensembles of simulations produced by multiple models that couple socioeconomic and natural system processes. On this context, we propose to develop an Intelligent Digital Watershed (IDW) which fuses emerging concepts of Digital Watershed (DW). DW is a comprehensive characterization of the eco hydrologic systems based on the best available digital data generated by measurements and simulations models. Prototype IDW in the form of a cyber infrastructure based engineered system will facilitate novel insights into human/environment interactions through multi-disciplinary research focused on watershed-related processes at multiple spatio-temporal scales. In ongoing effort, the prototype IDW is applied to Clear Creek watershed, an agricultural dominating catchment in Iowa, to understand water-human processes relevant to management decisions by farmers regarding agro ecosystems. This paper would also lay out the database design that stores metadata about simulation scenarios, scenario inputs and outputs, and connections among these elements- essentially the database. The paper describes the cyber infrastructure and workflows developed for connecting the IDW modeling tools: ABM, Data-Driven Modeling, and SWAT.

The EBM-DPSER Conceptual Model: Integrating Ecosystem Services into the DPSIR Framework

PubMed Central

Kelble, Christopher R.; Loomis, Dave K.; Lovelace, Susan; Nuttle, William K.; Ortner, Peter B.; Fletcher, Pamela; Cook, Geoffrey S.; Lorenz, Jerry J.; Boyer, Joseph N.

2013-01-01

There is a pressing need to integrate biophysical and human dimensions science to better inform holistic ecosystem management supporting the transition from single species or single-sector management to multi-sector ecosystem-based management. Ecosystem-based management should focus upon ecosystem services, since they reflect societal goals, values, desires, and benefits. The inclusion of ecosystem services into holistic management strategies improves management by better capturing the diversity of positive and negative human-natural interactions and making explicit the benefits to society. To facilitate this inclusion, we propose a conceptual model that merges the broadly applied Driver, Pressure, State, Impact, and Response (DPSIR) conceptual model with ecosystem services yielding a Driver, Pressure, State, Ecosystem service, and Response (EBM-DPSER) conceptual model. The impact module in traditional DPSIR models focuses attention upon negative anthropomorphic impacts on the ecosystem; by replacing impacts with ecosystem services the EBM-DPSER model incorporates not only negative, but also positive changes in the ecosystem. Responses occur as a result of changes in ecosystem services and include inter alia management actions directed at proactively altering human population or individual behavior and infrastructure to meet societal goals. The EBM-DPSER conceptual model was applied to the Florida Keys and Dry Tortugas marine ecosystem as a case study to illustrate how it can inform management decisions. This case study captures our system-level understanding and results in a more holistic representation of ecosystem and human society interactions, thus improving our ability to identify trade-offs. The EBM-DPSER model should be a useful operational tool for implementing EBM, in that it fully integrates our knowledge of all ecosystem components while focusing management attention upon those aspects of the ecosystem most important to human society and does so within a framework already familiar to resource managers. PMID:23951002

The EBM-DPSER conceptual model: integrating ecosystem services into the DPSIR framework.

PubMed

Kelble, Christopher R; Loomis, Dave K; Lovelace, Susan; Nuttle, William K; Ortner, Peter B; Fletcher, Pamela; Cook, Geoffrey S; Lorenz, Jerry J; Boyer, Joseph N

2013-01-01

There is a pressing need to integrate biophysical and human dimensions science to better inform holistic ecosystem management supporting the transition from single species or single-sector management to multi-sector ecosystem-based management. Ecosystem-based management should focus upon ecosystem services, since they reflect societal goals, values, desires, and benefits. The inclusion of ecosystem services into holistic management strategies improves management by better capturing the diversity of positive and negative human-natural interactions and making explicit the benefits to society. To facilitate this inclusion, we propose a conceptual model that merges the broadly applied Driver, Pressure, State, Impact, and Response (DPSIR) conceptual model with ecosystem services yielding a Driver, Pressure, State, Ecosystem service, and Response (EBM-DPSER) conceptual model. The impact module in traditional DPSIR models focuses attention upon negative anthropomorphic impacts on the ecosystem; by replacing impacts with ecosystem services the EBM-DPSER model incorporates not only negative, but also positive changes in the ecosystem. Responses occur as a result of changes in ecosystem services and include inter alia management actions directed at proactively altering human population or individual behavior and infrastructure to meet societal goals. The EBM-DPSER conceptual model was applied to the Florida Keys and Dry Tortugas marine ecosystem as a case study to illustrate how it can inform management decisions. This case study captures our system-level understanding and results in a more holistic representation of ecosystem and human society interactions, thus improving our ability to identify trade-offs. The EBM-DPSER model should be a useful operational tool for implementing EBM, in that it fully integrates our knowledge of all ecosystem components while focusing management attention upon those aspects of the ecosystem most important to human society and does so within a framework already familiar to resource managers.

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

PubMed

Martine, Laure C; Holzapfel, Boris M; McGovern, Jacqui A; Wagner, Ferdinand; Quent, Verena M; Hesami, Parisa; Wunner, Felix M; Vaquette, Cedryck; De-Juan-Pardo, Elena M; Brown, Toby D; Nowlan, Bianca; Wu, Dan Jing; Hutmacher, Cosmo Orlando; Moi, Davide; Oussenko, Tatiana; Piccinini, Elia; Zandstra, Peter W; Mazzieri, Roberta; Lévesque, Jean-Pierre; Dalton, Paul D; Taubenberger, Anna V; Hutmacher, Dietmar W

2017-04-01

Current in vivo models for investigating human primary bone tumors and cancer metastasis to the bone rely on the injection of human cancer cells into the mouse skeleton. This approach does not mimic species-specific mechanisms occurring in human diseases and may preclude successful clinical translation. We have developed a protocol to engineer humanized bone within immunodeficient hosts, which can be adapted to study the interactions between human cancer cells and a humanized bone microenvironment in vivo. A researcher trained in the principles of tissue engineering will be able to execute the protocol and yield study results within 4-6 months. Additive biomanufactured scaffolds seeded and cultured with human bone-forming cells are implanted ectopically in combination with osteogenic factors into mice to generate a physiological bone 'organ', which is partially humanized. The model comprises human bone cells and secreted extracellular matrix (ECM); however, other components of the engineered tissue, such as the vasculature, are of murine origin. The model can be further humanized through the engraftment of human hematopoietic stem cells (HSCs) that can lead to human hematopoiesis within the murine host. The humanized organ bone model has been well characterized and validated and allows dissection of some of the mechanisms of the bone metastatic processes in prostate and breast cancer.

PyramidalExplorer: A New Interactive Tool to Explore Morpho-Functional Relations of Human Pyramidal Neurons.

PubMed

Toharia, Pablo; Robles, Oscar D; Fernaud-Espinosa, Isabel; Makarova, Julia; Galindo, Sergio E; Rodriguez, Angel; Pastor, Luis; Herreras, Oscar; DeFelipe, Javier; Benavides-Piccione, Ruth

2015-01-01

This work presents PyramidalExplorer, a new tool to interactively explore and reveal the detailed organization of the microanatomy of pyramidal neurons with functionally related models. It consists of a set of functionalities that allow possible regional differences in the pyramidal cell architecture to be interactively discovered by combining quantitative morphological information about the structure of the cell with implemented functional models. The key contribution of this tool is the morpho-functional oriented design that allows the user to navigate within the 3D dataset, filter and perform Content-Based Retrieval operations. As a case study, we present a human pyramidal neuron with over 9000 dendritic spines in its apical and basal dendritic trees. Using PyramidalExplorer, we were able to find unexpected differential morphological attributes of dendritic spines in particular compartments of the neuron, revealing new aspects of the morpho-functional organization of the pyramidal neuron.

PyramidalExplorer: A New Interactive Tool to Explore Morpho-Functional Relations of Human Pyramidal Neurons

PubMed Central

Toharia, Pablo; Robles, Oscar D.; Fernaud-Espinosa, Isabel; Makarova, Julia; Galindo, Sergio E.; Rodriguez, Angel; Pastor, Luis; Herreras, Oscar; DeFelipe, Javier; Benavides-Piccione, Ruth

2016-01-01

This work presents PyramidalExplorer, a new tool to interactively explore and reveal the detailed organization of the microanatomy of pyramidal neurons with functionally related models. It consists of a set of functionalities that allow possible regional differences in the pyramidal cell architecture to be interactively discovered by combining quantitative morphological information about the structure of the cell with implemented functional models. The key contribution of this tool is the morpho-functional oriented design that allows the user to navigate within the 3D dataset, filter and perform Content-Based Retrieval operations. As a case study, we present a human pyramidal neuron with over 9000 dendritic spines in its apical and basal dendritic trees. Using PyramidalExplorer, we were able to find unexpected differential morphological attributes of dendritic spines in particular compartments of the neuron, revealing new aspects of the morpho-functional organization of the pyramidal neuron. PMID:26778972

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.

OFMspert: An architecture for an operator's associate that evolves to an intelligent tutor

NASA Technical Reports Server (NTRS)

Mitchell, Christine M.

1991-01-01

With the emergence of new technology for both human-computer interaction and knowledge-based systems, a range of opportunities exist which enhance the effectiveness and efficiency of controllers of high-risk engineering systems. The design of an architecture for an operator's associate is described. This associate is a stand-alone model-based system designed to interact with operators of complex dynamic systems, such as airplanes, manned space systems, and satellite ground control systems in ways comparable to that of a human assistant. The operator function model expert system (OFMspert) architecture and the design and empirical validation of OFMspert's understanding component are described. The design and validation of OFMspert's interactive and control components are also described. A description of current work in which OFMspert provides the foundation in the development of an intelligent tutor that evolves to an assistant, as operator expertise evolves from novice to expert, is provided.

Petri net modeling of high-order genetic systems using grammatical evolution.

PubMed

Moore, Jason H; Hahn, Lance W

2003-11-01

Understanding how DNA sequence variations impact human health through a hierarchy of biochemical and physiological systems is expected to improve the diagnosis, prevention, and treatment of common, complex human diseases. We have previously developed a hierarchical dynamic systems approach based on Petri nets for generating biochemical network models that are consistent with genetic models of disease susceptibility. This modeling approach uses an evolutionary computation approach called grammatical evolution as a search strategy for optimal Petri net models. We have previously demonstrated that this approach routinely identifies biochemical network models that are consistent with a variety of genetic models in which disease susceptibility is determined by nonlinear interactions between two DNA sequence variations. In the present study, we evaluate whether the Petri net approach is capable of identifying biochemical networks that are consistent with disease susceptibility due to higher order nonlinear interactions between three DNA sequence variations. The results indicate that our model-building approach is capable of routinely identifying good, but not perfect, Petri net models. Ideas for improving the algorithm for this high-dimensional problem are presented.

Interaction with Machine Improvisation

NASA Astrophysics Data System (ADS)

Assayag, Gerard; Bloch, George; Cont, Arshia; Dubnov, Shlomo

We describe two multi-agent architectures for an improvisation oriented musician-machine interaction systems that learn in real time from human performers. The improvisation kernel is based on sequence modeling and statistical learning. We present two frameworks of interaction with this kernel. In the first, the stylistic interaction is guided by a human operator in front of an interactive computer environment. In the second framework, the stylistic interaction is delegated to machine intelligence and therefore, knowledge propagation and decision are taken care of by the computer alone. The first framework involves a hybrid architecture using two popular composition/performance environments, Max and OpenMusic, that are put to work and communicate together, each one handling the process at a different time/memory scale. The second framework shares the same representational schemes with the first but uses an Active Learning architecture based on collaborative, competitive and memory-based learning to handle stylistic interactions. Both systems are capable of processing real-time audio/video as well as MIDI. After discussing the general cognitive background of improvisation practices, the statistical modelling tools and the concurrent agent architecture are presented. Then, an Active Learning scheme is described and considered in terms of using different improvisation regimes for improvisation planning. Finally, we provide more details about the different system implementations and describe several performances with the system.

Evolution of direct reciprocity under uncertainty can explain human generosity in one-shot encounters

PubMed Central

Delton, Andrew W.; Krasnow, Max M.; Cosmides, Leda; Tooby, John

2011-01-01

Are humans too generous? The discovery that subjects choose to incur costs to allocate benefits to others in anonymous, one-shot economic games has posed an unsolved challenge to models of economic and evolutionary rationality. Using agent-based simulations, we show that such generosity is the necessary byproduct of selection on decision systems for regulating dyadic reciprocity under conditions of uncertainty. In deciding whether to engage in dyadic reciprocity, these systems must balance (i) the costs of mistaking a one-shot interaction for a repeated interaction (hence, risking a single chance of being exploited) with (ii) the far greater costs of mistaking a repeated interaction for a one-shot interaction (thereby precluding benefits from multiple future cooperative interactions). This asymmetry builds organisms naturally selected to cooperate even when exposed to cues that they are in one-shot interactions. PMID:21788489

Evolution of direct reciprocity under uncertainty can explain human generosity in one-shot encounters.

PubMed

Delton, Andrew W; Krasnow, Max M; Cosmides, Leda; Tooby, John

2011-08-09

Are humans too generous? The discovery that subjects choose to incur costs to allocate benefits to others in anonymous, one-shot economic games has posed an unsolved challenge to models of economic and evolutionary rationality. Using agent-based simulations, we show that such generosity is the necessary byproduct of selection on decision systems for regulating dyadic reciprocity under conditions of uncertainty. In deciding whether to engage in dyadic reciprocity, these systems must balance (i) the costs of mistaking a one-shot interaction for a repeated interaction (hence, risking a single chance of being exploited) with (ii) the far greater costs of mistaking a repeated interaction for a one-shot interaction (thereby precluding benefits from multiple future cooperative interactions). This asymmetry builds organisms naturally selected to cooperate even when exposed to cues that they are in one-shot interactions.

Traversing the conceptual divide between biological and statistical epistasis: systems biology and a more modern synthesis.

PubMed

Moore, Jason H; Williams, Scott M

2005-06-01

Epistasis plays an important role in the genetic architecture of common human diseases and can be viewed from two perspectives, biological and statistical, each derived from and leading to different assumptions and research strategies. Biological epistasis is the result of physical interactions among biomolecules within gene regulatory networks and biochemical pathways in an individual such that the effect of a gene on a phenotype is dependent on one or more other genes. In contrast, statistical epistasis is defined as deviation from additivity in a mathematical model summarizing the relationship between multilocus genotypes and phenotypic variation in a population. The goal of this essay is to review definitions and examples of biological and statistical epistasis and to explore the relationship between the two. Specifically, we present and discuss the following two questions in the context of human health and disease. First, when does statistical evidence of epistasis in human populations imply underlying biomolecular interactions in the etiology of disease? Second, when do biomolecular interactions produce patterns of statistical epistasis in human populations? Answers to these two reciprocal questions will provide an important framework for using genetic information to improve our ability to diagnose, prevent and treat common human diseases. We propose that systems biology will provide the necessary information for addressing these questions and that model systems such as bacteria, yeast and digital organisms will be a useful place to start.

Homo sapiens exhibit a distinct pattern of CNV genes regulation: an important role of miRNAs and SNPs in expression plasticity.

PubMed

Dweep, Harsh; Kubikova, Nada; Gretz, Norbert; Voskarides, Konstantinos; Felekkis, Kyriacos

2015-07-16

Gene expression regulation is a complex and highly organized process involving a variety of genomic factors. It is widely accepted that differences in gene expression can contribute to the phenotypic variability between species, and that their interpretation can aid in the understanding of the physiologic variability. CNVs and miRNAs are two major players in the regulation of expression plasticity and may be responsible for the unique phenotypic characteristics observed in different lineages. We have previously demonstrated that a close interaction between these two genomic elements may have contributed to the regulation of gene expression during evolution. This work presents the molecular interactions between CNV and non CNV genes with miRNAs and other genomic elements in eight different species. A comprehensive analysis of these interactions indicates a unique nature of human CNV genes regulation as compared to other species. By using genes with short 3' UTR that abolish the "canonical" miRNA-dependent regulation, as a model, we demonstrate a distinct and tight regulation of human genes that might explain some of the unique features of human physiology. In addition, comparison of gene expression regulation between species indicated that there is a significant difference between humans and mice possibly questioning the effectiveness of the latest as experimental models of human diseases.

Homo sapiens exhibit a distinct pattern of CNV genes regulation: an important role of miRNAs and SNPs in expression plasticity

PubMed Central

Dweep, Harsh; Kubikova, Nada; Gretz, Norbert; Voskarides, Konstantinos; Felekkis, Kyriacos

2015-01-01

Gene expression regulation is a complex and highly organized process involving a variety of genomic factors. It is widely accepted that differences in gene expression can contribute to the phenotypic variability between species, and that their interpretation can aid in the understanding of the physiologic variability. CNVs and miRNAs are two major players in the regulation of expression plasticity and may be responsible for the unique phenotypic characteristics observed in different lineages. We have previously demonstrated that a close interaction between these two genomic elements may have contributed to the regulation of gene expression during evolution. This work presents the molecular interactions between CNV and non CNV genes with miRNAs and other genomic elements in eight different species. A comprehensive analysis of these interactions indicates a unique nature of human CNV genes regulation as compared to other species. By using genes with short 3′ UTR that abolish the “canonical” miRNA-dependent regulation, as a model, we demonstrate a distinct and tight regulation of human genes that might explain some of the unique features of human physiology. In addition, comparison of gene expression regulation between species indicated that there is a significant difference between humans and mice possibly questioning the effectiveness of the latest as experimental models of human diseases. PMID:26178010

Matters of simulation of the semicircular canal system

NASA Technical Reports Server (NTRS)

Gurfinkel, V. S.; Petukhov, S. V.

1977-01-01

A scale model of the human semicircular canal system was developed based on the theory of dynamic similitude. This enlarged model makes it convenient to conduct tests on the vestibular processes and dynamics in the semicircular canals. Tests revealed hydromechanical interaction between canals, with asymmetry of the conditions of movement of the endolymph in the canals in opposite directions. A type of vestibular reactions, occurring with angular oscillations of the head, was predicted and demonstrated using this model and human test subjects.

Representing natural and manmade drainage systems in an earth system modeling framework

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

Li, Hongyi; Wu, Huan; Huang, Maoyi

Drainage systems can be categorized into natural or geomorphological drainage systems, agricultural drainage systems and urban drainage systems. They interact closely among themselves and with climate and human society, particularly under extreme climate and hydrological events such as floods. This editorial articulates the need to holistically understand and model drainage systems in the context of climate change and human influence, and discusses the requirements and examples of feasible approaches to representing natural and manmade drainage systems in an earth system modeling framework.

Mapping substrate interactions of the human membrane-associated neuraminidase, NEU3, using STD NMR.

PubMed

Albohy, Amgad; Richards, Michele R; Cairo, Christopher W

2015-03-01

Saturation transfer difference (STD) nuclear magnetic resonance (NMR) is a powerful technique which can be used to investigate interactions between proteins and their substrates. The method identifies specific sites of interaction found on a small molecule ligand when in complex with a protein. The ability of STD NMR to provide specific insight into binding interactions in the absence of other structural data is an attractive feature for its use with membrane proteins. We chose to employ STD NMR in our ongoing investigations of the human membrane-associated neuraminidase NEU3 and its interaction with glycolipid substrates (e.g., GM3). In order to identify critical substrate-enzyme interactions, we performed STD NMR with a catalytically inactive form of the enzyme, NEU3(Y370F), containing an N-terminal maltose-binding protein (MBP)-affinity tag. In the absence of crystallographic data on the enzyme, these data represent a critical experimental test of proposed homology models, as well as valuable new structural data. To aid interpretation of the STD NMR data, we compared the results with molecular dynamics (MD) simulations of the enzyme-substrate complexes. We find that the homology model is able to predict essential features of the experimental data, including close contact of the hydrophobic aglycone and the Neu5Ac residue with the enzyme. Additionally, the model and STD NMR data agree on the facial recognition of the galactose and glucose residues of the GM3-analog studied. We conclude that the homology model of NEU3 can be used to predict substrate recognition, but our data indicate that unstructured portions of the NEU3 model may require further refinement. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Spinal circuits can accommodate interaction torques during multijoint limb movements.

PubMed

Buhrmann, Thomas; Di Paolo, Ezequiel A

2014-01-01

The dynamic interaction of limb segments during movements that involve multiple joints creates torques in one joint due to motion about another. Evidence shows that such interaction torques are taken into account during the planning or control of movement in humans. Two alternative hypotheses could explain the compensation of these dynamic torques. One involves the use of internal models to centrally compute predicted interaction torques and their explicit compensation through anticipatory adjustment of descending motor commands. The alternative, based on the equilibrium-point hypothesis, claims that descending signals can be simple and related to the desired movement kinematics only, while spinal feedback mechanisms are responsible for the appropriate creation and coordination of dynamic muscle forces. Partial supporting evidence exists in each case. However, until now no model has explicitly shown, in the case of the second hypothesis, whether peripheral feedback is really sufficient on its own for coordinating the motion of several joints while at the same time accommodating intersegmental interaction torques. Here we propose a minimal computational model to examine this question. Using a biomechanics simulation of a two-joint arm controlled by spinal neural circuitry, we show for the first time that it is indeed possible for the neuromusculoskeletal system to transform simple descending control signals into muscle activation patterns that accommodate interaction forces depending on their direction and magnitude. This is achieved without the aid of any central predictive signal. Even though the model makes various simplifications and abstractions compared to the complexities involved in the control of human arm movements, the finding lends plausibility to the hypothesis that some multijoint movements can in principle be controlled even in the absence of internal models of intersegmental dynamics or learned compensatory motor signals.

Fibroblasts Influence Survival and Therapeutic Response in a 3D Co-Culture Model

PubMed Central

Majety, Meher; Pradel, Leon P.; Gies, Manuela; Ries, Carola H.

2015-01-01

In recent years, evidence has indicated that the tumor microenvironment (TME) plays a significant role in tumor progression. Fibroblasts represent an abundant cell population in the TME and produce several growth factors and cytokines. Fibroblasts generate a suitable niche for tumor cell survival and metastasis under the influence of interactions between fibroblasts and tumor cells. Investigating these interactions requires suitable experimental systems to understand the cross-talk involved. Most in vitro experimental systems use 2D cell culture and trans-well assays to study these interactions even though these paradigms poorly represent the tumor, in which direct cell-cell contacts in 3D spaces naturally occur. Investigating these interactions in vivo is of limited value due to problems regarding the challenges caused by the species-specificity of many molecules. Thus, it is essential to use in vitro models in which human fibroblasts are co-cultured with tumor cells to understand their interactions. Here, we developed a 3D co-culture model that enables direct cell-cell contacts between pancreatic, breast and or lung tumor cells and human fibroblasts/ or tumor-associated fibroblasts (TAFs). We found that co-culturing with fibroblasts/TAFs increases the proliferation in of several types of cancer cells. We also observed that co-culture induces differential expression of soluble factors in a cancer type-specific manner. Treatment with blocking antibodies against selected factors or their receptors resulted in the inhibition of cancer cell proliferation in the co-cultures. Using our co-culture model, we further revealed that TAFs can influence the response to therapeutic agents in vitro. We suggest that this model can be reliably used as a tool to investigate the interactions between a tumor and the TME. PMID:26053043

Numerical Models of Human Circulatory System under Altered Gravity: Brain Circulation

NASA Technical Reports Server (NTRS)

Kim, Chang Sung; Kiris, Cetin; Kwak, Dochan; David, Tim

2003-01-01

A computational fluid dynamics (CFD) approach is presented to model the blood flow through the human circulatory system under altered gravity conditions. Models required for CFD simulation relevant to major hemodynamic issues are introduced such as non-Newtonian flow models governed by red blood cells, a model for arterial wall motion due to fluid-wall interactions, a vascular bed model for outflow boundary conditions, and a model for auto-regulation mechanism. The three-dimensional unsteady incompressible Navier-Stokes equations coupled with these models are solved iteratively using the pseudocompressibility method and dual time stepping. Moving wall boundary conditions from the first-order fluid-wall interaction model are used to study the influence of arterial wall distensibility on flow patterns and wall shear stresses during the heart pulse. A vascular bed modeling utilizing the analogy with electric circuits is coupled with an auto-regulation algorithm for multiple outflow boundaries. For the treatment of complex geometry, a chimera overset grid technique is adopted to obtain connectivity between arterial branches. For code validation, computed results are compared with experimental data for steady and unsteady non-Newtonian flows. Good agreement is obtained for both cases. In sin-type Gravity Benchmark Problems, gravity source terms are added to the Navier-Stokes equations to study the effect of gravitational variation on the human circulatory system. This computational approach is then applied to localized blood flows through a realistic carotid bifurcation and two Circle of Willis models, one using an idealized geometry and the other model using an anatomical data set. A three- dimensional anatomical Circle of Willis configuration is reconstructed from human-specific magnetic resonance images using an image segmentation method. The blood flow through these Circle of Willis models is simulated to provide means for studying gravitational effects on the brain circulation under auto-regulation.

The Importance of HRA in Human Space Flight: Understanding the Risks

NASA Technical Reports Server (NTRS)

Hamlin, Teri

2010-01-01

Human performance is critical to crew safety during space missions. Humans interact with hardware and software during ground processing, normal flight, and in response to events. Human interactions with hardware and software can cause Loss of Crew and/or Vehicle (LOCV) through improper actions, or may prevent LOCV through recovery and control actions. Humans have the ability to deal with complex situations and system interactions beyond the capability of machines. Human Reliability Analysis (HRA) is a method used to qualitatively and quantitatively assess the occurrence of human failures that affect availability and reliability of complex systems. Modeling human actions with their corresponding failure probabilities in a Probabilistic Risk Assessment (PRA) provides a more complete picture of system risks and risk contributions. A high-quality HRA can provide valuable information on potential areas for improvement, including training, procedures, human interfaces design, and the need for automation. Modeling human error has always been a challenge in part because performance data is not always readily available. For spaceflight, the challenge is amplified not only because of the small number of participants and limited amount of performance data available, but also due to the lack of definition of the unique factors influencing human performance in space. These factors, called performance shaping factors in HRA terminology, are used in HRA techniques to modify basic human error probabilities in order to capture the context of an analyzed task. Many of the human error modeling techniques were developed within the context of nuclear power plants and therefore the methodologies do not address spaceflight factors such as the effects of microgravity and longer duration missions. This presentation will describe the types of human error risks which have shown up as risk drivers in the Shuttle PRA which may be applicable to commercial space flight. As with other large PRAs of complex machines, human error in the Shuttle PRA proved to be an important contributor (12 percent) to LOCV. An existing HRA technique was adapted for use in the Shuttle PRA, but additional guidance and improvements are needed to make the HRA task in space-related PRAs easier and more accurate. Therefore, this presentation will also outline plans for expanding current HRA methodology to more explicitly cover spaceflight performance shaping factors.

Impact of Human like Cues on Human Trust in Machines: Brain Imaging and Modeling Studies for Human-Machine Interactions

DTIC Science & Technology

2018-01-05

research team recorded fMRI or event-related potentials while subjects were playing two cognitive games . At the first experiment, human subjects played a...theory-of-mind bilateral game with two types of computerized agents: with or without humanlike cues. At the second experiment, human subjects played...a unilateral game in which the human subjects played the role of the Coach (or supervisor) while a computer agent played as the Player

In vitro effects of the anti-Alzheimer drug memantine on the human erythrocyte membrane and molecular models

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

Zambrano, Pablo; Suwalsky, Mario; Villena, Fernando

Memantine is a NMDA antagonist receptor clinically used for treating Alzheimer's disease. NMDA receptors are present in the human neurons and erythrocyte membranes. The aim of the present study was to investigate the effects of memantine on human erythrocytes. With this purpose, the drug was developed to in vitro interact with human red cells and bilayers built-up of dimyristoylphosphatidylcholine (DMPC) and dimyristoylphosphatidylethanolamine (DMPE). The latter represent lipids respectively present in both outer and inner monolayers of the red cell membrane. Results obtained by scanning electron microscopy (SEM) showed that memantine changed the normal biconcave shape of red cells to cup-shaped stomatocytes.more » According to the bilayer-couple hypothesis the drug intercalated into the inner monolayer of the erythrocyte membrane. Experimental results obtained by X-ray diffraction on multibilayers of DMPC and DMPE, and by differential scanning calorimetry on multilamellar vesicles indicated that memantine preferentially interacted with DMPC in a concentration-dependent manner. Thus, it can be concluded that in the low therapeutic plasma concentration of circa 1 μM memantine is located in NMDA receptor channel without affecting the erythrocyte shape. However, at higher concentrations, once the receptors became saturated excess of memantine molecules (20 μM) would interact with phosphoinositide lipids present in the inner monolayer of the erythrocyte membrane inducing the formation of stomatocytes. However, 40–50 μM memantine was required to interact with isolated phosphatidylcholine bilayers. - Highlights: • The interaction of memantine with human erythrocytes and lipid bilayers were assessed. • Memantine induced morphological changes to human erythrocytes. • Memantine interacted with classes of phospholipids present in the erythrocyte membrane. • Results support the hypothesis that memantine interacts with NMDA receptors.« less

Operator function modeling: Cognitive task analysis, modeling and intelligent aiding in supervisory control systems

NASA Technical Reports Server (NTRS)

Mitchell, Christine M.

1990-01-01

The design, implementation, and empirical evaluation of task-analytic models and intelligent aids for operators in the control of complex dynamic systems, specifically aerospace systems, are studied. Three related activities are included: (1) the models of operator decision making in complex and predominantly automated space systems were used and developed; (2) the Operator Function Model (OFM) was used to represent operator activities; and (3) Operator Function Model Expert System (OFMspert), a stand-alone knowledge-based system was developed, that interacts with a human operator in a manner similar to a human assistant in the control of aerospace systems. OFMspert is an architecture for an operator's assistant that uses the OFM as its system and operator knowledge base and a blackboard paradigm of problem solving to dynamically generate expectations about upcoming operator activities and interpreting actual operator actions. An experiment validated the OFMspert's intent inferencing capability and showed that it inferred the intentions of operators in ways comparable to both a human expert and operators themselves. OFMspert was also augmented with control capabilities. An interface allowed the operator to interact with OFMspert, delegating as much or as little control responsibility as the operator chose. With its design based on the OFM, OFMspert's control capabilities were available at multiple levels of abstraction and allowed the operator a great deal of discretion over the amount and level of delegated control. An experiment showed that overall system performance was comparable for teams consisting of two human operators versus a human operator and OFMspert team.

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.

Determinants of FIV and HIV Vif sensitivity of feline APOBEC3 restriction factors.

PubMed

Zhang, Zeli; Gu, Qinyong; Jaguva Vasudevan, Ananda Ayyappan; Hain, Anika; Kloke, Björn-Philipp; Hasheminasab, Sascha; Mulnaes, Daniel; Sato, Kei; Cichutek, Klaus; Häussinger, Dieter; Bravo, Ignacio G; Smits, Sander H J; Gohlke, Holger; Münk, Carsten

2016-07-01

Feline immunodeficiency virus (FIV) is a global pathogen of Felidae species and a model system for Human immunodeficiency virus (HIV)-induced AIDS. In felids such as the domestic cat (Felis catus), APOBEC3 (A3) genes encode for single-domain A3Z2s, A3Z3 and double-domain A3Z2Z3 anti-viral cytidine deaminases. The feline A3Z2Z3 is expressed following read-through transcription and alternative splicing, introducing a previously untranslated exon in frame, encoding a domain insertion called linker. Only A3Z3 and A3Z2Z3 inhibit Vif-deficient FIV. Feline A3s also are restriction factors for HIV and Simian immunodeficiency viruses (SIV). Surprisingly, HIV-2/SIV Vifs can counteract feline A3Z2Z3. To identify residues in feline A3s that Vifs need for interaction and degradation, chimeric human-feline A3s were tested. Here we describe the molecular direct interaction of feline A3s with Vif proteins from cat FIV and present the first structural A3 model locating these interaction regions. In the Z3 domain we have identified residues involved in binding of FIV Vif, and their mutation blocked Vif-induced A3Z3 degradation. We further identified additional essential residues for FIV Vif interaction in the A3Z2 domain, allowing the generation of FIV Vif resistant A3Z2Z3. Mutated feline A3s also showed resistance to the Vif of a lion-specific FIV, indicating an evolutionary conserved Vif-A3 binding. Comparative modelling of feline A3Z2Z3 suggests that the residues interacting with FIV Vif have, unlike Vif-interacting residues in human A3s, a unique location at the domain interface of Z2 and Z3 and that the linker forms a homeobox-like domain protruding of the Z2Z3 core. HIV-2/SIV Vifs efficiently degrade feline A3Z2Z3 by possible targeting the linker stretch connecting both Z-domains. Here we identified in feline A3s residues important for binding of FIV Vif and a unique protein domain insertion (linker). To understand Vif evolution, a structural model of the feline A3 was developed. Our results show that HIV Vif binds human A3s differently than FIV Vif feline A3s. The linker insertion is suggested to form a homeo-box domain, which is unique to A3s of cats and related species, and not found in human and mouse A3s. Together, these findings indicate a specific and different A3 evolution in cats and human.

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 human torso until at least about 100 μs (maximum armor energy absorption) or more preferably 300 μs (maximum armor deformation).

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

TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models.

PubMed

Yao, Zhi-Jiang; Dong, Jie; Che, Yu-Jing; Zhu, Min-Feng; Wen, Ming; Wang, Ning-Ning; Wang, Shan; Lu, Ai-Ping; Cao, Dong-Sheng

2016-05-01

Drug-target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug-drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user's molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75-100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com .

TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models

NASA Astrophysics Data System (ADS)

Yao, Zhi-Jiang; Dong, Jie; Che, Yu-Jing; Zhu, Min-Feng; Wen, Ming; Wang, Ning-Ning; Wang, Shan; Lu, Ai-Ping; Cao, Dong-Sheng

2016-05-01

Drug-target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug-drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user's molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75-100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com.

Toxicodynamic analysis of the combined cholinesterase inhibition by paraoxon and methamidophos in human whole blood

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

Bosgra, Sieto; Eijkeren, Jan C.H. van; Schans, Marcel J. van der

2009-04-01

Theoretical work has shown that the isobole method is not generally valid as a method for testing the absence or presence of interaction (in the biochemical sense) between chemicals. The present study illustrates how interaction can be tested by fitting a toxicodynamic model to the results of a mixture experiment. The inhibition of cholinesterases (ChE) in human whole blood by various dose combinations of paraoxon and methamidophos was measured in vitro. A toxicodynamic model describing the processes related to both OPs in inhibiting AChE activity was developed, and fit to the observed activities. This model, not containing any interaction betweenmore » the two OPs, described the results from the mixture experiment well, and it was concluded that the OPs did not interact in the whole blood samples. While this approach of toxicodynamic modeling is the most appropriate method for predicting combined effects, it is not rapidly applicable. Therefore, we illustrate how toxicodynamic modeling can be used to explore under which conditions dose addition would give an acceptable approximation of the combined effects from various chemicals. In the specific case of paraoxon and methamidophos in whole blood samples, it was found that dose addition gave a reasonably accurate prediction of the combined effects, despite considerable difference in some of their rate constants, and mildly non-parallel dose-response curves. Other possibilities of validating dose-addition using toxicodynamic modeling are briefly discussed.« less

What should I do next? Using shared representations to solve interaction problems.

PubMed

Pezzulo, Giovanni; Dindo, Haris

2011-06-01

Studies on how "the social mind" works reveal that cognitive agents engaged in joint actions actively estimate and influence another's cognitive variables and form shared representations with them. (How) do shared representations enhance coordination? In this paper, we provide a probabilistic model of joint action that emphasizes how shared representations help solving interaction problems. We focus on two aspects of the model. First, we discuss how shared representations permit to coordinate at the level of cognitive variables (beliefs, intentions, and actions) and determine a coherent unfolding of action execution and predictive processes in the brains of two agents. Second, we discuss the importance of signaling actions as part of a strategy for sharing representations and the active guidance of another's actions toward the achievement of a joint goal. Furthermore, we present data from a human-computer experiment (the Tower Game) in which two agents (human and computer) have to build together a tower made of colored blocks, but only the human knows the constellation of the tower to be built (e.g., red-blue-red-blue-…). We report evidence that humans use signaling strategies that take another's uncertainty into consideration, and that in turn our model is able to use humans' actions as cues to "align" its representations and to select complementary actions.

Stromal-Epithelial Interactions and Tamoxifen-Sensitivity: A Bench-to-Bedside Model of Chemoprevention

DTIC Science & Technology

2008-05-01

effects of tamoxifen can be directly attributed to competitive interactions with ER. Tamox- ifen induces apoptosis in cholangiocarcinoma cells and...Pickens A, et al. Apoptosis and tumorigenesis in human cholangiocarcinoma cells. Involvement of Fas/APO-1 (CD95) and calmodulin. Am J Pathol 1999;155:193

Reusable, Lifelike Virtual Humans for Mentoring and Role-Playing

ERIC Educational Resources Information Center

Sims, Edward M.

2007-01-01

Lifelike, interactive digital characters, serving as mentors and role-playing actors, have been shown to significantly improve learner motivation and retention. However, the cost of modeling such characters, authoring and editing their interactions, and delivering them over limited-bandwidth connections can be prohibitive. This paper describes a…

An individual-based modeling approach to simulating recreation use in wilderness settings

Treesearch

Randy Gimblett; Terry Daniel; Michael J. Meitner

2000-01-01

Landscapes protect biological diversity and provide unique opportunities for human-nature interactions. Too often, these desirable settings suffer from extremely high visitation. Given the complexity of social, environmental and economic interactions, resource managers need tools that provide insights into the cause and effect relationships between management actions...

Feedback in Information Retrieval.

ERIC Educational Resources Information Center

Spink, Amanda; Losee, Robert M.

1996-01-01

As Information Retrieval (IR) has evolved, it has become a highly interactive process, rooted in cognitive and situational contexts. Consequently the traditional cybernetic-based IR model does not suffice for interactive IR or the human approach to IR. Reviews different views of feedback in IR and their relationship to cybernetic and social…

A Digital Ecosystems Model of Assessment Feedback on Student Learning

ERIC Educational Resources Information Center

Gomez, Stephen; Andersson, Holger; Park, Julian; Maw, Stephen; Crook, Anne; Orsmond, Paul

2013-01-01

The term ecosystem has been used to describe complex interactions between living organisms and the physical world. The principles underlying ecosystems can also be applied to complex human interactions in the digital world. As internet technologies make an increasing contribution to teaching and learning practice in higher education, the…

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

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

Environmental controls, oceanography and population dynamics of pathogens and harmful algal blooms: connecting sources to human exposure.

PubMed

Dyble, Julianne; Bienfang, Paul; Dusek, Eva; Hitchcock, Gary; Holland, Fred; Laws, Ed; Lerczak, James; McGillicuddy, Dennis J; Minnett, Peter; Moore, Stephanie K; O'Kelly, Charles; Solo-Gabriele, Helena; Wang, John D

2008-11-07

Coupled physical-biological models are capable of linking the complex interactions between environmental factors and physical hydrodynamics to simulate the growth, toxicity and transport of infectious pathogens and harmful algal blooms (HABs). Such simulations can be used to assess and predict the impact of pathogens and HABs on human health. Given the widespread and increasing reliance of coastal communities on aquatic systems for drinking water, seafood and recreation, such predictions are critical for making informed resource management decisions. Here we identify three challenges to making this connection between pathogens/HABs and human health: predicting concentrations and toxicity; identifying the spatial and temporal scales of population and ecosystem interactions; and applying the understanding of population dynamics of pathogens/HABs to management strategies. We elaborate on the need to meet each of these challenges, describe how modeling approaches can be used and discuss strategies for moving forward in addressing these challenges.

CHISSL: A Human-Machine Collaboration Space for Unsupervised Learning

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

Arendt, Dustin L.; Komurlu, Caner; Blaha, Leslie M.

We developed CHISSL, a human-machine interface that utilizes supervised machine learning in an unsupervised context to help the user group unlabeled instances by her own mental model. The user primarily interacts via correction (moving a misplaced instance into its correct group) or confirmation (accepting that an instance is placed in its correct group). Concurrent with the user's interactions, CHISSL trains a classification model guided by the user's grouping of the data. It then predicts the group of unlabeled instances and arranges some of these alongside the instances manually organized by the user. We hypothesize that this mode of human andmore » machine collaboration is more effective than Active Learning, wherein the machine decides for itself which instances should be labeled by the user. We found supporting evidence for this hypothesis in a pilot study where we applied CHISSL to organize a collection of handwritten digits.« less

Pilot interaction with automated airborne decision making systems

NASA Technical Reports Server (NTRS)

Rouse, W. B.; Chu, Y. Y.; Greenstein, J. S.; Walden, R. S.

1976-01-01

An investigation was made of interaction between a human pilot and automated on-board decision making systems. Research was initiated on the topic of pilot problem solving in automated and semi-automated flight management systems and attempts were made to develop a model of human decision making in a multi-task situation. A study was made of allocation of responsibility between human and computer, and discussed were various pilot performance parameters with varying degrees of automation. Optimal allocation of responsibility between human and computer was considered and some theoretical results found in the literature were presented. The pilot as a problem solver was discussed. Finally the design of displays, controls, procedures, and computer aids for problem solving tasks in automated and semi-automated systems was considered.

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  

Final Report: PAGE: Policy Analytics Generation Engine

DTIC Science & Technology

2016-08-12

develop a parallel framework for it. We also developed policies and methods by which a group of defensive resources (e.g. checkpoints) could be...Sarit Kraus. Learning to Reveal Information in Repeated Human -Computer Negotiation, Human -Agent Interaction Design and Models Workshop 2012. 04-JUN...Joseph Keshet, Sarit Kraus. Predicting Human Strategic Decisions Using Facial Expressions, International Joint Conference on Artificial

A Computational Model of Active Vision for Visual Search in Human-Computer Interaction

DTIC Science & Technology

2010-08-01

processors that interact with the production rules to produce behavior, and (c) parameters that constrain the behavior of the model (e.g., the...velocity of a saccadic eye movement). While the parameters can be task-specific, the majority of the parameters are usually fixed across a wide variety...previously estimated durations. Hooge and Erkelens (1996) review these four explanations of fixation duration control. A variety of research

Applications of artificial intelligence in safe human-robot interactions.

PubMed

Najmaei, Nima; Kermani, Mehrdad R

2011-04-01

The integration of industrial robots into the human workspace presents a set of unique challenges. This paper introduces a new sensory system for modeling, tracking, and predicting human motions within a robot workspace. A reactive control scheme to modify a robot's operations for accommodating the presence of the human within the robot workspace is also presented. To this end, a special class of artificial neural networks, namely, self-organizing maps (SOMs), is employed for obtaining a superquadric-based model of the human. The SOM network receives information of the human's footprints from the sensory system and infers necessary data for rendering the human model. The model is then used in order to assess the danger of the robot operations based on the measured as well as predicted human motions. This is followed by the introduction of a new reactive control scheme that results in the least interferences between the human and robot operations. The approach enables the robot to foresee an upcoming danger and take preventive actions before the danger becomes imminent. Simulation and experimental results are presented in order to validate the effectiveness of the proposed method.

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

Automation effects in a multiloop manual control system

NASA Technical Reports Server (NTRS)

Hess, R. A.; Mcnally, B. D.

1986-01-01

An experimental and analytical study was undertaken to investigate human interaction with a simple multiloop manual control system in which the human's activity was systematically varied by changing the level of automation. The system simulated was the longitudinal dynamics of a hovering helicopter. The automation-systems-stabilized vehicle responses from attitude to velocity to position and also provided for display automation in the form of a flight director. The control-loop structure resulting from the task definition can be considered a simple stereotype of a hierarchical control system. The experimental study was complemented by an analytical modeling effort which utilized simple crossover models of the human operator. It was shown that such models can be extended to the description of multiloop tasks involving preview and precognitive human operator behavior. The existence of time optimal manual control behavior was established for these tasks and the role which internal models may play in establishing human-machine performance was discussed.

APPLYING THE PATUXENT LANDSCAPE UNIT MODEL TO HUMAN DOMINATED ECOSYSTEMS: THE CASE OF AGRICULTURE. (R827169)

EPA Science Inventory

Non-spatial dynamics are core to landscape simulations. Unit models simulate system interactions aggregated within one space unit of resolution used within a spatial model. For unit models to be applicable to spatial simulations they have to be formulated in a general enough w...

Proteomic interactions in the mouse vitreous-retina complex.

PubMed

Skeie, Jessica M; Mahajan, Vinit B

2013-01-01

Human vitreoretinal diseases are due to presumed abnormal mechanical interactions between the vitreous and retina, and translational models are limited. This study determined whether nonstructural proteins and potential retinal biomarkers were expressed by the normal mouse vitreous and retina. Vitreous and retina samples from mice were collected by evisceration and analyzed by liquid chromatography-tandem mass spectrometry. Identified proteins were further analyzed for differential expression and functional interactions using bioinformatic software. We identified 1,680 unique proteins in the retina and 675 unique proteins in the vitreous. Unbiased clustering identified protein pathways that distinguish retina from vitreous including oxidative phosphorylation and neurofilament cytoskeletal remodeling, whereas the vitreous expressed oxidative stress and innate immunology pathways. Some intracellular protein pathways were found in both retina and vitreous, such as glycolysis and gluconeogenesis and neuronal signaling, suggesting proteins might be shuttled between the retina and vitreous. We also identified human disease biomarkers represented in the mouse vitreous and retina, including carbonic anhydrase-2 and 3, crystallins, macrophage inhibitory factor, glutathione peroxidase, peroxiredoxins, S100 precursors, and von Willebrand factor. Our analysis suggests the vitreous expresses nonstructural proteins that functionally interact with the retina to manage oxidative stress, immune reactions, and intracellular proteins may be exchanged between the retina and vitreous. This novel proteomic dataset can be used for investigating human vitreoretinopathies in mouse models. Validation of vitreoretinal biomarkers for human ocular diseases will provide a critical tool for diagnostics and an avenue for therapeutics.

Exploring Human Diseases and Biological Mechanisms by Protein Structure Prediction and Modeling.

PubMed

Wang, Juexin; Luttrell, Joseph; Zhang, Ning; Khan, Saad; Shi, NianQing; Wang, Michael X; Kang, Jing-Qiong; Wang, Zheng; Xu, Dong

2016-01-01

Protein structure prediction and modeling provide a tool for understanding protein functions by computationally constructing protein structures from amino acid sequences and analyzing them. With help from protein prediction tools and web servers, users can obtain the three-dimensional protein structure models and gain knowledge of functions from the proteins. In this chapter, we will provide several examples of such studies. As an example, structure modeling methods were used to investigate the relation between mutation-caused misfolding of protein and human diseases including epilepsy and leukemia. Protein structure prediction and modeling were also applied in nucleotide-gated channels and their interaction interfaces to investigate their roles in brain and heart cells. In molecular mechanism studies of plants, rice salinity tolerance mechanism was studied via structure modeling on crucial proteins identified by systems biology analysis; trait-associated protein-protein interactions were modeled, which sheds some light on the roles of mutations in soybean oil/protein content. In the age of precision medicine, we believe protein structure prediction and modeling will play more and more important roles in investigating biomedical mechanism of diseases and drug design.

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.

Dynamic Task Performance, Cohesion, and Communications in Human Groups.

PubMed

Giraldo, Luis Felipe; Passino, Kevin M

2016-10-01

In the study of the behavior of human groups, it has been observed that there is a strong interaction between the cohesiveness of the group, its performance when the group has to solve a task, and the patterns of communication between the members of the group. Developing mathematical and computational tools for the analysis and design of task-solving groups that are not only cohesive but also perform well is of importance in social sciences, organizational management, and engineering. In this paper, we model a human group as a dynamical system whose behavior is driven by a task optimization process and the interaction between subsystems that represent the members of the group interconnected according to a given communication network. These interactions are described as attractions and repulsions among members. We show that the dynamics characterized by the proposed mathematical model are qualitatively consistent with those observed in real-human groups, where the key aspect is that the attraction patterns in the group and the commitment to solve the task are not static but change over time. Through a theoretical analysis of the system we provide conditions on the parameters that allow the group to have cohesive behaviors, and Monte Carlo simulations are used to study group dynamics for different sets of parameters, communication topologies, and tasks to solve.

NATO Human View Architecture and Human Networks

NASA Technical Reports Server (NTRS)

Handley, Holly A. H.; Houston, Nancy P.

2010-01-01

The NATO Human View is a system architectural viewpoint that focuses on the human as part of a system. Its purpose is to capture the human requirements and to inform on how the human impacts the system design. The viewpoint contains seven static models that include different aspects of the human element, such as roles, tasks, constraints, training and metrics. It also includes a Human Dynamics component to perform simulations of the human system under design. One of the static models, termed Human Networks, focuses on the human-to-human communication patterns that occur as a result of ad hoc or deliberate team formation, especially teams distributed across space and time. Parameters of human teams that effect system performance can be captured in this model. Human centered aspects of networks, such as differences in operational tempo (sense of urgency), priorities (common goal), and team history (knowledge of the other team members), can be incorporated. The information captured in the Human Network static model can then be included in the Human Dynamics component so that the impact of distributed teams is represented in the simulation. As the NATO militaries transform to a more networked force, the Human View architecture is an important tool that can be used to make recommendations on the proper mix of technological innovations and human interactions.

Aesthetic emotions to art - What they are and what makes them special. Comment on "The quartet theory of human emotions: An integrative and neurofunctional model" by S. Koelsch et al.

NASA Astrophysics Data System (ADS)

Leder, Helmut; Markey, Patrick S.; Pelowski, Matthew

2015-06-01

Establishing a functional understanding of emotional processes is crucial for profound insight into human cognition and behavior [6]. The study of human interactions with art provides an excellent window into the complex emotional reactions that can be had with the environment. Recent advances in the empirical study of art reception have given rise to new models [8,9], and a growing interest in aesthetic affect and emotion.

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.

(−) Arctigenin and (+) Pinoresinol Are Antagonists of the Human Thyroid Hormone Receptor β

PubMed Central

2015-01-01

Lignans are important biologically active dietary polyphenolic compounds. Consumption of foods that are rich in lignans is associated with positive health effects. Using modeling tools to probe the ligand-binding pockets of molecular receptors, we found that lignans have high docking affinity for the human thyroid hormone receptor β. Follow-up experimental results show that lignans (−) arctigenin and (+) pinoresinol are antagonists of the human thyroid hormone receptor β. The modeled complexes show key plausible interactions between the two ligands and important amino acid residues of the receptor. PMID:25383984

Probabilistic modeling of discourse-aware sentence processing.

PubMed

Dubey, Amit; Keller, Frank; Sturt, Patrick

2013-07-01

Probabilistic models of sentence comprehension are increasingly relevant to questions concerning human language processing. However, such models are often limited to syntactic factors. This restriction is unrealistic in light of experimental results suggesting interactions between syntax and other forms of linguistic information in human sentence processing. To address this limitation, this article introduces two sentence processing models that augment a syntactic component with information about discourse co-reference. The novel combination of probabilistic syntactic components with co-reference classifiers permits them to more closely mimic human behavior than existing models. The first model uses a deep model of linguistics, based in part on probabilistic logic, allowing it to make qualitative predictions on experimental data; the second model uses shallow processing to make quantitative predictions on a broad-coverage reading-time corpus. Copyright © 2013 Cognitive Science Society, Inc.

Interactions of donor sources and media influence the histo-morphological quality of full-thickness skin models.

PubMed

Lange, Julia; Weil, Frederik; Riegler, Christoph; Groeber, Florian; Rebhan, Silke; Kurdyn, Szymon; Alb, Miriam; Kneitz, Hermann; Gelbrich, Götz; Walles, Heike; Mielke, Stephan

2016-10-01

Human artificial skin models are increasingly employed as non-animal test platforms for research and medical purposes. However, the overall histopathological quality of such models may vary significantly. Therefore, the effects of manufacturing protocols and donor sources on the quality of skin models built-up from fibroblasts and keratinocytes derived from juvenile foreskins is studied. Histo-morphological parameters such as epidermal thickness, number of epidermal cell layers, dermal thickness, dermo-epidermal adhesion and absence of cellular nuclei in the corneal layer are obtained and scored accordingly. In total, 144 full-thickness skin models derived from 16 different donors, built-up in triplicates using three different culture conditions were successfully generated. In univariate analysis both media and donor age affected the quality of skin models significantly. Both parameters remained statistically significant in multivariate analyses. Performing general linear model analyses we could show that individual medium-donor-interactions influence the quality. These observations suggest that the optimal choice of media may differ from donor to donor and coincides with findings where significant inter-individual variations of growth rates in keratinocytes and fibroblasts have been described. Thus, the consideration of individual medium-donor-interactions may improve the overall quality of human organ models thereby forming a reproducible test platform for sophisticated clinical research. Copyright © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A comparison of the biological properties of small molecular weight agonists and antagonists of CD200:CD200R interactions.

PubMed

Gorczynski, Reg; Boudakov, Ivo; Khatri, Ismat

2008-11-01

Our laboratory and others have documented in some detail the immunological consequences which follow from interaction of the ubiquitously expressed molecule CD200 with its receptor(s) CD200R (expressed predominantly on cells of myeloid and lymphoid origin). In particular, there is evidence that these interactions lead to immunosuppressive signals which modulate graft rejection responses; decrease the manifestations of arthritis in rodent models; diminish mast cell mediator release in models of allergic disease; and favour the growth of tumors in both mice and humans. The development of small molecular weight agonists (and/or antagonists) of these interactions would thus likely have significant clinical importance. The data reported herein characterizes several such molecules in a number of rodent models.

A Sequence in the loop domain of hepatitis C virus E2 protein identified in silico as crucial for the selective binding to human CD81

PubMed Central

Chang, Chun-Chun; Hsu, Hao-Jen; Yen, Jui-Hung; Lo, Shih-Yen

2017-01-01

Hepatitis C virus (HCV) is a species-specific pathogenic virus that infects only humans and chimpanzees. Previous studies have indicated that interactions between the HCV E2 protein and CD81 on host cells are required for HCV infection. To determine the crucial factors for species-specific interactions at the molecular level, this study employed in silico molecular docking involving molecular dynamic simulations of the binding of HCV E2 onto human and rat CD81s. In vitro experiments including surface plasmon resonance measurements and cellular binding assays were applied for simple validations of the in silico results. The in silico studies identified two binding regions on the HCV E2 loop domain, namely E2-site1 and E2-site2, as being crucial for the interactions with CD81s, with the E2-site2 as the determinant factor for human-specific binding. Free energy calculations indicated that the E2/CD81 binding process might follow a two-step model involving (i) the electrostatic interaction-driven initial binding of human-specific E2-site2, followed by (ii) changes in the E2 orientation to facilitate the hydrophobic and van der Waals interaction-driven binding of E2-site1. The sequence of the human-specific, stronger-binding E2-site2 could serve as a candidate template for the future development of HCV-inhibiting peptide drugs. PMID:28481946