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Sample records for biologically inspired modelling

  1. A model of engineering materials inspired by biological tissues

    Directory of Open Access Journals (Sweden)

    Holeček M.

    2009-12-01

    Full Text Available The perfect ability of living tissues to control and adapt their mechanical properties to varying external conditions may be an inspiration for designing engineering materials. An interesting example is the smooth muscle tissue since this "material" is able to change its global mechanical properties considerably by a subtle mechanism within individual muscle cells. Multi-scale continuum models may be useful in designing essentially simpler engineering materials having similar properties. As an illustration we present the model of an incompressible material whose microscopic structure is formed by flexible, soft but incompressible balls connected mutually by linear springs. This simple model, however, shows a nontrivial nonlinear behavior caused by the incompressibility of balls and is very sensitive on some microscopic parameters. It may elucidate the way by which "small" changes in biopolymer networks within individual muscular cells may control the stiffness of the biological tissue, which outlines a way of designing similar engineering materials. The 'balls and springs' material presents also prestress-induced stiffening and allows elucidating a contribution of extracellular fluids into the tissue’s viscous properties.

  2. Basic science through engineering? Synthetic modeling and the idea of biology-inspired engineering.

    Science.gov (United States)

    Knuuttila, Tarja; Loettgers, Andrea

    2013-06-01

    Synthetic biology is often understood in terms of the pursuit for well-characterized biological parts to create synthetic wholes. Accordingly, it has typically been conceived of as an engineering dominated and application oriented field. We argue that the relationship of synthetic biology to engineering is far more nuanced than that and involves a sophisticated epistemic dimension, as shown by the recent practice of synthetic modeling. Synthetic models are engineered genetic networks that are implanted in a natural cell environment. Their construction is typically combined with experiments on model organisms as well as mathematical modeling and simulation. What is especially interesting about this combinational modeling practice is that, apart from greater integration between these different epistemic activities, it has also led to the questioning of some central assumptions and notions on which synthetic biology is based. As a result synthetic biology is in the process of becoming more "biology inspired." Copyright © 2013 Elsevier Ltd. All rights reserved.

  3. Design, modeling and control of a pneumatically actuated manipulator inspired by biological continuum structures

    International Nuclear Information System (INIS)

    Kang, Rongjie; Zheng Tianjiang; Guglielmino, Emanuele; Caldwell, Darwin G; Branson, David T

    2013-01-01

    Biological tentacles, such as octopus arms, have entirely flexible structures and virtually infinite degrees of freedom (DOF) that allow for elongation, shortening and bending at any point along the arm length. The amazing dexterity of biological tentacles has driven the growing implementation of continuum manipulators in robotic systems. This paper presents a pneumatic manipulator inspired by biological continuum structures in some of their key features and functions, such as continuum morphology, intrinsic compliance and stereotyped motions with hyper redundant DOF. The kinematics and dynamics of the manipulator are formulated and identified, and a hierarchical controller taking inspiration from the structure of an octopus nervous system is used to relate desired stereotyped motions to individual actuator inputs. Simulations and experiments are carried out to validate the model and prototype where good agreement was found between the two. (paper)

  4. Paradigms for biologically inspired design

    DEFF Research Database (Denmark)

    Lenau, T. A.; Metzea, A.-L.; Hesselberg, T.

    2018-01-01

    engineering, medical engineering, nanotechnology, photonics,environmental protection and agriculture. However, a major obstacle for the wider use of biologically inspired design isthe knowledge barrier that exist between the application engineers that have insight into how to design suitable productsand......Biologically inspired design is attracting increasing interest since it offers access to a huge biological repository of wellproven design principles that can be used for developing new and innovative products. Biological phenomena can inspireproduct innovation in as diverse areas as mechanical...... the biologists with detailed knowledge and experience in understanding how biological organisms function in theirenvironment. The biologically inspired design process can therefore be approached using different design paradigmsdepending on the dominant opportunities, challenges and knowledge characteristics...

  5. Introducing memory and association mechanism into a biologically inspired visual model.

    Science.gov (United States)

    Qiao, Hong; Li, Yinlin; Tang, Tang; Wang, Peng

    2014-09-01

    A famous biologically inspired hierarchical model (HMAX model), which was proposed recently and corresponds to V1 to V4 of the ventral pathway in primate visual cortex, has been successfully applied to multiple visual recognition tasks. The model is able to achieve a set of position- and scale-tolerant recognition, which is a central problem in pattern recognition. In this paper, based on some other biological experimental evidence, we introduce the memory and association mechanism into the HMAX model. The main contributions of the work are: 1) mimicking the active memory and association mechanism and adding the top down adjustment to the HMAX model, which is the first try to add the active adjustment to this famous model and 2) from the perspective of information, algorithms based on the new model can reduce the computation storage and have a good recognition performance. The new model is also applied to object recognition processes. The primary experimental results show that our method is efficient with a much lower memory requirement.

  6. Biologically inspired control and modeling of (biorobotic systems and some applications of fractional calculus in mechanics

    Directory of Open Access Journals (Sweden)

    Lazarević Mihailo P.

    2013-01-01

    Full Text Available In this paper, the applications of biologically inspired modeling and control of (biomechanical (nonredundant mechanisms are presented, as well as newly obtained results of author in mechanics which are based on using fractional calculus. First, it is proposed to use biological analog-synergy due to existence of invariant features in the execution of functional motion. Second, the model of (biomechanical system may be obtained using another biological concept called distributed positioning (DP, which is based on the inertial properties and actuation of joints of considered mechanical system. In addition, it is proposed to use other biological principles such as: principle of minimum interaction, which takes a main role in hierarchical structure of control and self-adjusting principle (introduce local positive/negative feedback on control with great amplifying, which allows efficiently realization of control based on iterative natural learning. Also, new, recently obtained results of the author in the fields of stability, electroviscoelasticity, and control theory are presented which are based on using fractional calculus (FC. [Projekat Ministarstva nauke Republike Srbije, br. 35006

  7. Biologically Inspired Technology Using Electroactive Polymers (EAP)

    Science.gov (United States)

    Bar-Cohen, Yoseph

    2006-01-01

    Evolution allowed nature to introduce highly effective biological mechanisms that are incredible inspiration for innovation. Humans have always made efforts to imitate nature's inventions and we are increasingly making advances that it becomes significantly easier to imitate, copy, and adapt biological methods, processes and systems. This brought us to the ability to create technology that is far beyond the simple mimicking of nature. Having better tools to understand and to implement nature's principles we are now equipped like never before to be inspired by nature and to employ our tools in far superior ways. Effectively, by bio-inspiration we can have a better view and value of nature capability while studying its models to learn what can be extracted, copied or adapted. Using electroactive polymers (EAP) as artificial muscles is adding an important element to the development of biologically inspired technologies.

  8. Modelling of a biologically inspired robotic fish driven by compliant parts

    International Nuclear Information System (INIS)

    Daou, Hadi El; Salumäe, Taavi; Kruusmaa, Maarja; Chambers, Lily D; Megill, William M

    2014-01-01

    Inspired by biological swimmers such as fish, a robot composed of a rigid head, a compliant body and a rigid caudal fin was built. It has the geometrical properties of a subcarangiform swimmer of the same size. The head houses a servo-motor which actuates the compliant body and the caudal fin. It achieves this by applying a concentrated moment on a point near the compliant body base. In this paper, the dynamics of the compliant body driving the robotic fish is modelled and experimentally validated. Lighthill’s elongated body theory is used to define the hydrodynamic forces on the compliant part and Rayleigh proportional damping is used to model damping. Based on the assumed modes method, an energetic approach is used to write the equations of motion of the compliant body and to compute the relationship between the applied moment and the resulting lateral deflections. Experiments on the compliant body were carried out to validate the model predictions. The results showed that a good match was achieved between the measured and predicted deformations. A discussion of the swimming motions between the real fish and the robot is presented. (paper)

  9. A biologically inspired neural network model to transformation invariant object recognition

    Science.gov (United States)

    Iftekharuddin, Khan M.; Li, Yaqin; Siddiqui, Faraz

    2007-09-01

    Transformation invariant image recognition has been an active research area due to its widespread applications in a variety of fields such as military operations, robotics, medical practices, geographic scene analysis, and many others. The primary goal for this research is detection of objects in the presence of image transformations such as changes in resolution, rotation, translation, scale and occlusion. We investigate a biologically-inspired neural network (NN) model for such transformation-invariant object recognition. In a classical training-testing setup for NN, the performance is largely dependent on the range of transformation or orientation involved in training. However, an even more serious dilemma is that there may not be enough training data available for successful learning or even no training data at all. To alleviate this problem, a biologically inspired reinforcement learning (RL) approach is proposed. In this paper, the RL approach is explored for object recognition with different types of transformations such as changes in scale, size, resolution and rotation. The RL is implemented in an adaptive critic design (ACD) framework, which approximates the neuro-dynamic programming of an action network and a critic network, respectively. Two ACD algorithms such as Heuristic Dynamic Programming (HDP) and Dual Heuristic dynamic Programming (DHP) are investigated to obtain transformation invariant object recognition. The two learning algorithms are evaluated statistically using simulated transformations in images as well as with a large-scale UMIST face database with pose variations. In the face database authentication case, the 90° out-of-plane rotation of faces from 20 different subjects in the UMIST database is used. Our simulations show promising results for both designs for transformation-invariant object recognition and authentication of faces. Comparing the two algorithms, DHP outperforms HDP in learning capability, as DHP takes fewer steps to

  10. Honeybees as a model for the study of visually guided flight, navigation, and biologically inspired robotics.

    Science.gov (United States)

    Srinivasan, Mandyam V

    2011-04-01

    Research over the past century has revealed the impressive capacities of the honeybee, Apis mellifera, in relation to visual perception, flight guidance, navigation, and learning and memory. These observations, coupled with the relative ease with which these creatures can be trained, and the relative simplicity of their nervous systems, have made honeybees an attractive model in which to pursue general principles of sensorimotor function in a variety of contexts, many of which pertain not just to honeybees, but several other animal species, including humans. This review begins by describing the principles of visual guidance that underlie perception of the world in three dimensions, obstacle avoidance, control of flight speed, and orchestrating smooth landings. We then consider how navigation over long distances is accomplished, with particular reference to how bees use information from the celestial compass to determine their flight bearing, and information from the movement of the environment in their eyes to gauge how far they have flown. Finally, we illustrate how some of the principles gleaned from these studies are now being used to design novel, biologically inspired algorithms for the guidance of unmanned aerial vehicles.

  11. Biologically Inspired Micro-Flight Research

    Science.gov (United States)

    Raney, David L.; Waszak, Martin R.

    2003-01-01

    Natural fliers demonstrate a diverse array of flight capabilities, many of which are poorly understood. NASA has established a research project to explore and exploit flight technologies inspired by biological systems. One part of this project focuses on dynamic modeling and control of micro aerial vehicles that incorporate flexible wing structures inspired by natural fliers such as insects, hummingbirds and bats. With a vast number of potential civil and military applications, micro aerial vehicles represent an emerging sector of the aerospace market. This paper describes an ongoing research activity in which mechanization and control concepts for biologically inspired micro aerial vehicles are being explored. Research activities focusing on a flexible fixed- wing micro aerial vehicle design and a flapping-based micro aerial vehicle concept are presented.

  12. From biologically-inspired physics to physics-inspired biology From biologically-inspired physics to physics-inspired biology

    Science.gov (United States)

    Kornyshev, Alexei A.

    2010-10-01

    The conference 'From DNA-Inspired Physics to Physics-Inspired Biology' (1-5 June 2009, International Center for Theoretical Physics, Trieste, Italy) that myself and two former presidents of the American Biophysical Society—Wilma Olson (Rutgers University) and Adrian Parsegian (NIH), with the support of an ICTP team (Ralf Gebauer (Local Organizer) and Doreen Sauleek (Conference Secretary)), have organized was intended to establish stronger links between the biology and physics communities on the DNA front. The relationships between them were never easy. In 1997, Adrian published a paper in Physics Today ('Harness the Hubris') summarizing his thoughts about the main obstacles for a successful collaboration. The bottom line of that article was that physicists must seriously learn biology before exploring it and even having an interpreter, a friend or co-worker, who will be cooperating with you and translating the problems of biology into a physical language, may not be enough. He started his story with a joke about a physicist asking a biologist: 'I want to study the brain. Tell me something about it!' Biologist: 'First, the brain consists of two parts, and..' Physicist: 'Stop. You have told me too much.' Adrian listed a few direct avenues where physicists' contributions may be particularly welcome. This gentle and elegantly written paper caused, however, a stormy reaction from Bob Austin (Princeton), published together with Adrian's notes, accusing Adrian of forbidding physicists to attack big questions in biology straightaway. Twelve years have passed and many new developments have taken place in the biologist-physicist interaction. This was something I addressed in my opening conference speech, with my position lying somewhere inbetween Parsegian's and Austin's, which is briefly outlined here. I will first recall certain precepts or 'dogmas' that fly in the air like Valkyries, poisoning those relationships. Since the early seventies when I was a first year Ph

  13. Biologically inspired coupled antenna beampattern design

    Energy Technology Data Exchange (ETDEWEB)

    Akcakaya, Murat; Nehorai, Arye, E-mail: makcak2@ese.wustl.ed, E-mail: nehorai@ese.wustl.ed [Department of Electrical and Systems Engineering, Washington University in St Louis, St Louis, MO 63130 (United States)

    2010-12-15

    We propose to design a small-size transmission-coupled antenna array, and corresponding radiation pattern, having high performance inspired by the female Ormia ochracea's coupled ears. For reproduction purposes, the female Ormia is able to locate male crickets' call accurately despite the small distance between its ears compared with the incoming wavelength. This phenomenon has been explained by the mechanical coupling between the Ormia's ears, which has been modeled by a pair of differential equations. In this paper, we first solve these differential equations governing the Ormia ochracea's ear response, and convert the response to the pre-specified radio frequencies. We then apply the converted response of the biological coupling in the array factor of a uniform linear array composed of finite-length dipole antennas, and also include the undesired electromagnetic coupling due to the proximity of the elements. Moreover, we propose an algorithm to optimally choose the biologically inspired coupling for maximum array performance. In our numerical examples, we compute the radiation intensity of the designed system for binomial and uniform ordinary end-fire arrays, and demonstrate the improvement in the half-power beamwidth, sidelobe suppression and directivity of the radiation pattern due to the biologically inspired coupling.

  14. Biologically-inspired soft exosuit.

    Science.gov (United States)

    Asbeck, Alan T; Dyer, Robert J; Larusson, Arnar F; Walsh, Conor J

    2013-06-01

    In this paper, we present the design and evaluation of a novel soft cable-driven exosuit that can apply forces to the body to assist walking. Unlike traditional exoskeletons which contain rigid framing elements, the soft exosuit is worn like clothing, yet can generate moments at the ankle and hip with magnitudes of 18% and 30% of those naturally generated by the body during walking, respectively. Our design uses geared motors to pull on Bowden cables connected to the suit near the ankle. The suit has the advantages over a traditional exoskeleton in that the wearer's joints are unconstrained by external rigid structures, and the worn part of the suit is extremely light, which minimizes the suit's unintentional interference with the body's natural biomechanics. However, a soft suit presents challenges related to actuation force transfer and control, since the body is compliant and cannot support large pressures comfortably. We discuss the design of the suit and actuation system, including principles by which soft suits can transfer force to the body effectively and the biological inspiration for the design. For a soft exosuit, an important design parameter is the combined effective stiffness of the suit and its interface to the wearer. We characterize the exosuit's effective stiffness, and present preliminary results from it generating assistive torques to a subject during walking. We envision such an exosuit having broad applicability for assisting healthy individuals as well as those with muscle weakness.

  15. Biologically inspired toys using artificial muscles

    Science.gov (United States)

    Bar-Cohen, Y.

    2001-01-01

    Recent developments in electroactive polymers, so-called artificial muscles, could one day be used to make bionics possible. Meanwhile, as this technology evolves novel mechanisms are expected to emerge that are biologically inspired.

  16. Biologically inspired information theory: Adaptation through construction of external reality models by living systems.

    Science.gov (United States)

    Nakajima, Toshiyuki

    2015-12-01

    Higher animals act in the world using their external reality models to cope with the uncertain environment. Organisms that have not developed such information-processing organs may also have external reality models built in the form of their biochemical, physiological, and behavioral structures, acquired by natural selection through successful models constructed internally. Organisms subject to illusions would fail to survive in the material universe. How can organisms, or living systems in general, determine the external reality from within? This paper starts with a phenomenological model, in which the self constitutes a reality model developed through the mental processing of phenomena. Then, the it-from-bit concept is formalized using a simple mathematical model. For this formalization, my previous work on an algorithmic process is employed to constitute symbols referring to the external reality, called the inverse causality, with additional improvements to the previous work. Finally, as an extension of this model, the cognizers system model is employed to describe the self as one of many material entities in a world, each of which acts as a subject by responding to the surrounding entities. This model is used to propose a conceptual framework of information theory that can deal with both the qualitative (semantic) and quantitative aspects of the information involved in biological processes. Copyright © 2015 Elsevier Ltd. All rights reserved.

  17. Biology-Inspired Autonomous Control

    Science.gov (United States)

    2011-08-31

    insect brain, allow these animals to fly with damaged wings, order of body mass payloads (e.g., foraging bees with a load of pollen , blood satiated...The research focus addressed two broad, complementary research areas : autonomous systems concepts inspired by the behavior and neurobiology...UL 46 19b. TELEPHONE NUMBER (include area code) 850 883-1887 Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std. Z39.18 iii Table of

  18. Biologically inspired emotion recognition from speech

    Directory of Open Access Journals (Sweden)

    Buscicchio Cosimo

    2011-01-01

    Full Text Available Abstract Emotion recognition has become a fundamental task in human-computer interaction systems. In this article, we propose an emotion recognition approach based on biologically inspired methods. Specifically, emotion classification is performed using a long short-term memory (LSTM recurrent neural network which is able to recognize long-range dependencies between successive temporal patterns. We propose to represent data using features derived from two different models: mel-frequency cepstral coefficients (MFCC and the Lyon cochlear model. In the experimental phase, results obtained from the LSTM network and the two different feature sets are compared, showing that features derived from the Lyon cochlear model give better recognition results in comparison with those obtained with the traditional MFCC representation.

  19. Biologically inspired technologies in NASA's morphing project

    Science.gov (United States)

    McGowan, Anna-Maria R.; Cox, David E.; Lazos, Barry S.; Waszak, Martin R.; Raney, David L.; Siochi, Emilie J.; Pao, S. Paul

    2003-07-01

    For centuries, biology has provided fertile ground for hypothesis, discovery, and inspiration. Time-tested methods used in nature are being used as a basis for several research studies conducted at the NASA Langley Research Center as a part of Morphing Project, which develops and assesses breakthrough vehicle technologies. These studies range from low drag airfoil design guided by marine and avian morphologies to soaring techniques inspired by birds and the study of small flexible wing vehicles. Biology often suggests unconventional yet effective approaches such as non-planar wings, dynamic soaring, exploiting aeroelastic effects, collaborative control, flapping, and fibrous active materials. These approaches and other novel technologies for future flight vehicles are being studied in NASA's Morphing Project. This paper will discuss recent findings in the aeronautics-based, biologically-inspired research in the project.

  20. Biology-inspired AMO physics

    Science.gov (United States)

    Mathur, Deepak

    2015-01-01

    This Topical Review presents an overview of increasingly robust interconnects that are being established between atomic, molecular and optical (AMO) physics and the life sciences. AMO physics, outgrowing its historical role as a facilitator—a provider of optical methodologies, for instance—now seeks to partner biology in its quest to link systems-level descriptions of biological entities to insights based on molecular processes. Of course, perspectives differ when AMO physicists and biologists consider various processes. For instance, while AMO physicists link molecular properties and dynamics to potential energy surfaces, these have to give way to energy landscapes in considerations of protein dynamics. But there are similarities also: tunnelling and non-adiabatic transitions occur both in protein dynamics and in molecular dynamics. We bring to the fore some such differences and similarities; we consider imaging techniques based on AMO concepts, like 4D fluorescence microscopy which allows access to the dynamics of cellular processes, multiphoton microscopy which offers a built-in confocality, and microscopy with femtosecond laser beams to saturate the suppression of fluorescence in spatially controlled fashion so as to circumvent the diffraction limit. Beyond imaging, AMO physics contributes with optical traps that probe the mechanical and dynamical properties of single ‘live’ cells, highlighting differences between healthy and diseased cells. Trap methodologies have also begun to probe the dynamics governing of neural stem cells adhering to each other to form neurospheres and, with squeezed light to probe sub-diffusive motion of yeast cells. Strong field science contributes not only by providing a source of energetic electrons and γ-rays via laser-plasma accelerations schemes, but also via filamentation and supercontinuum generation, enabling mainstream collision physics into play in diverse processes like DNA damage induced by low-energy collisions to

  1. Biology-inspired AMO physics

    International Nuclear Information System (INIS)

    Mathur, Deepak

    2015-01-01

    This Topical Review presents an overview of increasingly robust interconnects that are being established between atomic, molecular and optical (AMO) physics and the life sciences. AMO physics, outgrowing its historical role as a facilitator—a provider of optical methodologies, for instance—now seeks to partner biology in its quest to link systems-level descriptions of biological entities to insights based on molecular processes. Of course, perspectives differ when AMO physicists and biologists consider various processes. For instance, while AMO physicists link molecular properties and dynamics to potential energy surfaces, these have to give way to energy landscapes in considerations of protein dynamics. But there are similarities also: tunnelling and non-adiabatic transitions occur both in protein dynamics and in molecular dynamics. We bring to the fore some such differences and similarities; we consider imaging techniques based on AMO concepts, like 4D fluorescence microscopy which allows access to the dynamics of cellular processes, multiphoton microscopy which offers a built-in confocality, and microscopy with femtosecond laser beams to saturate the suppression of fluorescence in spatially controlled fashion so as to circumvent the diffraction limit. Beyond imaging, AMO physics contributes with optical traps that probe the mechanical and dynamical properties of single ‘live’ cells, highlighting differences between healthy and diseased cells. Trap methodologies have also begun to probe the dynamics governing of neural stem cells adhering to each other to form neurospheres and, with squeezed light to probe sub-diffusive motion of yeast cells. Strong field science contributes not only by providing a source of energetic electrons and γ-rays via laser-plasma accelerations schemes, but also via filamentation and supercontinuum generation, enabling mainstream collision physics into play in diverse processes like DNA damage induced by low-energy collisions to

  2. Biologically Inspired Intercellular Slot Synchronization

    Directory of Open Access Journals (Sweden)

    Alexander Tyrrell

    2009-01-01

    Full Text Available The present article develops a decentralized interbase station slot synchronization algorithm suitable for cellular mobile communication systems. The proposed cellular firefly synchronization (CelFSync algorithm is derived from the theory of pulse-coupled oscillators, common to describe synchronization phenomena in biological systems, such as the spontaneous synchronization of fireflies. In order to maintain synchronization among base stations (BSs, even when there is no direct link between adjacent BSs, some selected user terminals (UTs participate in the network synchronization process. Synchronization emerges by exchanging two distinct synchronization words, one transmitted by BSs and the other by active UTs, without any a priori assumption on the initial timing misalignments of BSs and UTs. In large-scale networks with inter-BS site distances up to a few kilometers, propagation delays severely affect the attainable timing accuracy of CelFSync. We show that by an appropriate combination of CelFSync with the timing advance procedure, which aligns uplink transmission of UTs to arrive simultaneously at the BS, a timing accuracy within a fraction of the inter-BS propagation delay is retained.

  3. Biologically Inspired Visual Model With Preliminary Cognition and Active Attention Adjustment.

    Science.gov (United States)

    Qiao, Hong; Xi, Xuanyang; Li, Yinlin; Wu, Wei; Li, Fengfu

    2015-11-01

    Recently, many computational models have been proposed to simulate visual cognition process. For example, the hierarchical Max-Pooling (HMAX) model was proposed according to the hierarchical and bottom-up structure of V1 to V4 in the ventral pathway of primate visual cortex, which could achieve position- and scale-tolerant recognition. In our previous work, we have introduced memory and association into the HMAX model to simulate visual cognition process. In this paper, we improve our theoretical framework by mimicking a more elaborate structure and function of the primate visual cortex. We will mainly focus on the new formation of memory and association in visual processing under different circumstances as well as preliminary cognition and active adjustment in the inferior temporal cortex, which are absent in the HMAX model. The main contributions of this paper are: 1) in the memory and association part, we apply deep convolutional neural networks to extract various episodic features of the objects since people use different features for object recognition. Moreover, to achieve a fast and robust recognition in the retrieval and association process, different types of features are stored in separated clusters and the feature binding of the same object is stimulated in a loop discharge manner and 2) in the preliminary cognition and active adjustment part, we introduce preliminary cognition to classify different types of objects since distinct neural circuits in a human brain are used for identification of various types of objects. Furthermore, active cognition adjustment of occlusion and orientation is implemented to the model to mimic the top-down effect in human cognition process. Finally, our model is evaluated on two face databases CAS-PEAL-R1 and AR. The results demonstrate that our model exhibits its efficiency on visual recognition process with much lower memory storage requirement and a better performance compared with the traditional purely computational

  4. A Biologically Inspired Computational Model of Basal Ganglia in Action Selection.

    Science.gov (United States)

    Baston, Chiara; Ursino, Mauro

    2015-01-01

    The basal ganglia (BG) are a subcortical structure implicated in action selection. The aim of this work is to present a new cognitive neuroscience model of the BG, which aspires to represent a parsimonious balance between simplicity and completeness. The model includes the 3 main pathways operating in the BG circuitry, that is, the direct (Go), indirect (NoGo), and hyperdirect pathways. The main original aspects, compared with previous models, are the use of a two-term Hebb rule to train synapses in the striatum, based exclusively on neuronal activity changes caused by dopamine peaks or dips, and the role of the cholinergic interneurons (affected by dopamine themselves) during learning. Some examples are displayed, concerning a few paradigmatic cases: action selection in basal conditions, action selection in the presence of a strong conflict (where the role of the hyperdirect pathway emerges), synapse changes induced by phasic dopamine, and learning new actions based on a previous history of rewards and punishments. Finally, some simulations show model working in conditions of altered dopamine levels, to illustrate pathological cases (dopamine depletion in parkinsonian subjects or dopamine hypermedication). Due to its parsimonious approach, the model may represent a straightforward tool to analyze BG functionality in behavioral experiments.

  5. A Biologically Inspired Computational Model of Basal Ganglia in Action Selection

    Directory of Open Access Journals (Sweden)

    Chiara Baston

    2015-01-01

    Full Text Available The basal ganglia (BG are a subcortical structure implicated in action selection. The aim of this work is to present a new cognitive neuroscience model of the BG, which aspires to represent a parsimonious balance between simplicity and completeness. The model includes the 3 main pathways operating in the BG circuitry, that is, the direct (Go, indirect (NoGo, and hyperdirect pathways. The main original aspects, compared with previous models, are the use of a two-term Hebb rule to train synapses in the striatum, based exclusively on neuronal activity changes caused by dopamine peaks or dips, and the role of the cholinergic interneurons (affected by dopamine themselves during learning. Some examples are displayed, concerning a few paradigmatic cases: action selection in basal conditions, action selection in the presence of a strong conflict (where the role of the hyperdirect pathway emerges, synapse changes induced by phasic dopamine, and learning new actions based on a previous history of rewards and punishments. Finally, some simulations show model working in conditions of altered dopamine levels, to illustrate pathological cases (dopamine depletion in parkinsonian subjects or dopamine hypermedication. Due to its parsimonious approach, the model may represent a straightforward tool to analyze BG functionality in behavioral experiments.

  6. A biologically inspired neural model for visual and proprioceptive integration including sensory training.

    Science.gov (United States)

    Saidi, Maryam; Towhidkhah, Farzad; Gharibzadeh, Shahriar; Lari, Abdolaziz Azizi

    2013-12-01

    Humans perceive the surrounding world by integration of information through different sensory modalities. Earlier models of multisensory integration rely mainly on traditional Bayesian and causal Bayesian inferences for single causal (source) and two causal (for two senses such as visual and auditory systems), respectively. In this paper a new recurrent neural model is presented for integration of visual and proprioceptive information. This model is based on population coding which is able to mimic multisensory integration of neural centers in the human brain. The simulation results agree with those achieved by casual Bayesian inference. The model can also simulate the sensory training process of visual and proprioceptive information in human. Training process in multisensory integration is a point with less attention in the literature before. The effect of proprioceptive training on multisensory perception was investigated through a set of experiments in our previous study. The current study, evaluates the effect of both modalities, i.e., visual and proprioceptive training and compares them with each other through a set of new experiments. In these experiments, the subject was asked to move his/her hand in a circle and estimate its position. The experiments were performed on eight subjects with proprioception training and eight subjects with visual training. Results of the experiments show three important points: (1) visual learning rate is significantly more than that of proprioception; (2) means of visual and proprioceptive errors are decreased by training but statistical analysis shows that this decrement is significant for proprioceptive error and non-significant for visual error, and (3) visual errors in training phase even in the beginning of it, is much less than errors of the main test stage because in the main test, the subject has to focus on two senses. The results of the experiments in this paper is in agreement with the results of the neural model

  7. Biological Inspiration for Agile Autonomous Air Vehicles

    Science.gov (United States)

    2007-11-01

    half of one wing, bees with legs packed with pollen , butterflies or moths with torn and frayed wings likewise are capable of apparently normal flight...technologies. To appreciate this, consider a not unreasonable extension of a wide area autonomous search (WAAS) munition operational scenario. Here...detect and destroy missile launchers that are operating in the back alleys of an urban areas or search Evers, J.H. (2007) Biological Inspiration for Agile

  8. Biologically inspired water purification through selective transport

    International Nuclear Information System (INIS)

    Freeman, E C; Soncini, R M; Weiland, L M

    2013-01-01

    Biologically inspired systems based on cellular mechanics demonstrate the ability to selectively transport ions across a bilayer membrane. These systems may be observed in nature in plant roots, which remove select nutrients from the surrounding soil against significant concentration gradients. Using biomimetic principles in the design of tailored active materials allows for the development of selective membranes for capturing and filtering targeted ions. Combining this biomimetic transport system with a method for reclaiming the captured ions will allow for increased removal potential. To illustrate this concept, a device for removing nutrients from waterways to aid in reducing eutrophication is outlined and discussed. Presented is a feasibility study of various cellular configurations designed for this purpose, focusing on maximizing nutrient uptake. The results enable a better understanding of the benefits and obstacles when developing these cellularly inspired systems. (paper)

  9. Drawing inspiration from biological optical systems

    Science.gov (United States)

    Wolpert, H. D.

    2009-08-01

    Bio-Mimicking/Bio-Inspiration: How can we not be inspired by Nature? Life has evolved on earth over the last 3.5 to 4 billion years. Materials formed during this time were not toxic; they were created at low temperatures and low pressures unlike many of the materials developed today. The natural materials formed are self-assembled, multifunctional, nonlinear, complex, adaptive, self-repairing and biodegradable. The designs that failed are fossils. Those that survived are the success stories. Natural materials are mostly formed from organics, inorganic crystals and amorphous phases. The materials make economic sense by optimizing the design of the structures or systems to meet multiple needs. We constantly "see" many similar strategies in approaches, between man and nature, but we seldom look at the details of natures approaches. The power of image processing, in many of natures creatures, is a detail that is often overlooked. Seldon does the engineer interact with the biologist and learn what nature has to teach us. The variety and complexity of biological materials and the optical systems formed should inspire us.

  10. Biological inspiration used for robots motion synthesis.

    Science.gov (United States)

    Zielińska, Teresa

    2009-01-01

    This work presents a biologically inspired method of gait generation. Bipedal gait pattern (for hip and knee joints) was taken into account giving the reference trajectories in a learning task. The four coupled oscillators were taught to generate the outputs similar to those in a human gait. After applying the correction functions the obtained generation method was validated using ZMP criterion. The formula suitable for real-time motion generation taking into account the positioning errors was also formulated. The small real robot prototype was tested to be able walk successfully following the elaborated motion pattern.

  11. Creative design inspired by biological knowledge: Technologies and methods

    Science.gov (United States)

    Tan, Runhua; Liu, Wei; Cao, Guozhong; Shi, Yuan

    2018-05-01

    Biological knowledge is becoming an important source of inspiration for developing creative solutions to engineering design problems and even has a huge potential in formulating ideas that can help firms compete successfully in a dynamic market. To identify the technologies and methods that can facilitate the development of biologically inspired creative designs, this research briefly reviews the existing biological-knowledge-based theories and methods and examines the application of biological-knowledge-inspired designs in various fields. Afterward, this research thoroughly examines the four dimensions of key technologies that underlie the biologically inspired design (BID) process. This research then discusses the future development trends of the BID process before presenting the conclusions.

  12. Modeling biology with HDL languages: a first step toward a genetic design automation tool inspired from microelectronics.

    Science.gov (United States)

    Gendrault, Yves; Madec, Morgan; Lallement, Christophe; Haiech, Jacques

    2014-04-01

    Nowadays, synthetic biology is a hot research topic. Each day, progresses are made to improve the complexity of artificial biological functions in order to tend to complex biodevices and biosystems. Up to now, these systems are handmade by bioengineers, which require strong technical skills and leads to nonreusable development. Besides, scientific fields that share the same design approach, such as microelectronics, have already overcome several issues and designers succeed in building extremely complex systems with many evolved functions. On the other hand, in systems engineering and more specifically in microelectronics, the development of the domain has been promoted by both the improvement of technological processes and electronic design automation tools. The work presented in this paper paves the way for the adaptation of microelectronics design tools to synthetic biology. Considering the similarities and differences between the synthetic biology and microelectronics, the milestones of this adaptation are described. The first one concerns the modeling of biological mechanisms. To do so, a new formalism is proposed, based on an extension of the generalized Kirchhoff laws to biology. This way, a description of all biological mechanisms can be made with languages widely used in microelectronics. Our approach is therefore successfully validated on specific examples drawn from the literature.

  13. Superstring-inspired models

    International Nuclear Information System (INIS)

    Aguila, F. del; Blair, G.; Daniel, M.; Ross, G.G.

    1986-01-01

    We discuss the structure of low-energy groups arising from compactified models based on the heterotic string. Particular regard is paid to the possibility of intermediate scale breaking which may change the low-energy gauge structure and may naturally lead to doublet-triplet splitting and the suppression of proton decay. We present an illustrative example of such a model with a low-energy gauge group structure SU 3 sup(c)xSU 2 sup(L)xSU 2 sup(R)xU 1 sup(B-L) which may be compatible with low-energy phenomena including limits on neutrino masses and sin 2 thetasub(W). Mechanisms leading to the minimal SU 3 sup(c)xSU 2 sup(L)xU 1 sup(Y) low-energy gauge group are also presented. (orig.)

  14. Synthetic biology, inspired by synthetic chemistry.

    Science.gov (United States)

    Malinova, V; Nallani, M; Meier, W P; Sinner, E K

    2012-07-16

    The topic synthetic biology appears still as an 'empty basket to be filled'. However, there is already plenty of claims and visions, as well as convincing research strategies about the theme of synthetic biology. First of all, synthetic biology seems to be about the engineering of biology - about bottom-up and top-down approaches, compromising complexity versus stability of artificial architectures, relevant in biology. Synthetic biology accounts for heterogeneous approaches towards minimal and even artificial life, the engineering of biochemical pathways on the organismic level, the modelling of molecular processes and finally, the combination of synthetic with nature-derived materials and architectural concepts, such as a cellular membrane. Still, synthetic biology is a discipline, which embraces interdisciplinary attempts in order to have a profound, scientific base to enable the re-design of nature and to compose architectures and processes with man-made matter. We like to give an overview about the developments in the field of synthetic biology, regarding polymer-based analogs of cellular membranes and what questions can be answered by applying synthetic polymer science towards the smallest unit in life, namely a cell. Copyright © 2012 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

  15. A Biologically Inspired CMOS Image Sensor

    CERN Document Server

    Sarkar, Mukul

    2013-01-01

    Biological systems are a source of inspiration in the development of small autonomous sensor nodes. The two major types of optical vision systems found in nature are the single aperture human eye and the compound eye of insects. The latter are among the most compact and smallest vision sensors. The eye is a compound of individual lenses with their own photoreceptor arrays.  The visual system of insects allows them to fly with a limited intelligence and brain processing power. A CMOS image sensor replicating the perception of vision in insects is discussed and designed in this book for industrial (machine vision) and medical applications. The CMOS metal layer is used to create an embedded micro-polarizer able to sense polarization information. This polarization information is shown to be useful in applications like real time material classification and autonomous agent navigation. Further the sensor is equipped with in pixel analog and digital memories which allow variation of the dynamic range and in-pixel b...

  16. Biologically inspired robots as artificial inspectors

    Science.gov (United States)

    Bar-Cohen, Yoseph

    2002-06-01

    Imagine an inspector conducting an NDE on an aircraft where you notice something is different about him - he is not real but rather he is a robot. Your first reaction would probably be to say 'it's unbelievable but he looks real' just as you would react to an artificial flower that is a good imitation. This science fiction scenario could become a reality at the trend in the development of biologically inspired technologies, and terms like artificial intelligence, artificial muscles, artificial vision and numerous others are increasingly becoming common engineering tools. For many years, the trend has been to automate processes in order to increase the efficiency of performing redundant tasks where various systems have been developed to deal with specific production line requirements. Realizing that some parts are too complex or delicate to handle in small quantities with a simple automatic system, robotic mechanisms were developed. Aircraft inspection has benefitted from this evolving technology where manipulators and crawlers are developed for rapid and reliable inspection. Advancement in robotics towards making them autonomous and possibly look like human, can potentially address the need to inspect structures that are beyond the capability of today's technology with configuration that are not predetermined. The operation of these robots may take place at harsh or hazardous environments that are too dangerous for human presence. Making such robots is becoming increasingly feasible and in this paper the state of the art will be reviewed.

  17. MIAMI cells embedded within a biologically-inspired construct promote recovery in a mouse model of peripheral vascular disease

    Science.gov (United States)

    Grau-Monge, Cristina; Delcroix, Gaëtan J.-R; Bonnin-Marquez, Andrea; Valdes, Mike; Awadallah, Ead Lewis Mazen; Quevedo, Daniel F.; Armour, Maxime R.; Montero, Ramon B.; Schiller, Paul C.; Andreopoulos, Fotios M.; D’Ippolito, Gianluca

    2017-01-01

    Peripheral vascular disease is one of the major vascular complications in individuals suffering from diabetes and in the elderly that is associated with significant burden in terms of morbidity and mortality. Stem cell therapy is being tested as an attractive alternative to traditional surgery to prevent and treat this disorder. The goal of this study was to enhance the protective and reparative potential of marrow-isolated adult multilineage inducible (MIAMI) cells by incorporating them within a bio-inspired construct (BIC) made of 2 layers of gelatin B electrospun nanofibers. We hypothesized that the BIC would enhance MIAMI cell survival and engraftment, ultimately leading to a better functional recovery of the injured limb in our mouse model of critical limb ischemia compared to MIAMI cells used alone. Our study demonstrated that MIAMI cell-seeded BIC resulted in a wide range of positive outcomes with an almost full recovery of blood flow in the injured limb, thereby limiting the extent of ischemia and necrosis. Functional recovery was also the greatest when MIAMI cells were combined with BICs, compared to MIAMI cells alone or BICs in the absence of cells. Histology was performed 28 days after grafting the animals to explore the mechanisms at the source of these positive outcomes. We observed that our critical limb ischemia model induces an extensive loss of muscular fibers that are replaced by intermuscular adipose tissue (IMAT), together with a highly disorganized vascular structure. The use of MIAMI cells-seeded BIC prevented IMAT infiltration with some clear evidence of muscular fibers regeneration. PMID:28211362

  18. A biologically inspired two-species exclusion model: effects of RNA polymerase motor traffic on simultaneous DNA replication

    Science.gov (United States)

    Ghosh, Soumendu; Mishra, Bhavya; Patra, Shubhadeep; Schadschneider, Andreas; Chowdhury, Debashish

    2018-04-01

    We introduce a two-species exclusion model to describe the key features of the conflict between the RNA polymerase (RNAP) motor traffic, engaged in the transcription of a segment of DNA, concomitant with the progress of two DNA replication forks on the same DNA segment. One of the species of particles (P) represents RNAP motors while the other (R) represents the replication forks. Motivated by the biological phenomena that this model is intended to capture, a maximum of two R particles only are allowed to enter the lattice from two opposite ends whereas the unrestricted number of P particles constitutes a totally asymmetric simple exclusion process (TASEP) in a segment in the middle of the lattice. The model captures three distinct pathways for resolving the co-directional as well as head-on collision between the P and R particles. Using Monte Carlo simulations and heuristic analytical arguments that combine exact results for the TASEP with mean-field approximations, we predict the possible outcomes of the conflict between the traffic of RNAP motors (P particles engaged in transcription) and the replication forks (R particles). In principle, the model can be adapted to experimental conditions to account for the data quantitatively.

  19. Complex biological and bio-inspired systems

    Energy Technology Data Exchange (ETDEWEB)

    Ecke, Robert E [Los Alamos National Laboratory

    2009-01-01

    The understanding and characterization ofthe fundamental processes of the function of biological systems underpins many of the important challenges facing American society, from the pathology of infectious disease and the efficacy ofvaccines, to the development of materials that mimic biological functionality and deliver exceptional and novel structural and dynamic properties. These problems are fundamentally complex, involving many interacting components and poorly understood bio-chemical kinetics. We use the basic science of statistical physics, kinetic theory, cellular bio-chemistry, soft-matter physics, and information science to develop cell level models and explore the use ofbiomimetic materials. This project seeks to determine how cell level processes, such as response to mechanical stresses, chemical constituents and related gradients, and other cell signaling mechanisms, integrate and combine to create a functioning organism. The research focuses on the basic physical processes that take place at different levels ofthe biological organism: the basic role of molecular and chemical interactions are investigated, the dynamics of the DNA-molecule and its phylogenetic role are examined and the regulatory networks of complex biochemical processes are modeled. These efforts may lead to early warning algorithms ofpathogen outbreaks, new bio-sensors to detect hazards from pathomic viruses to chemical contaminants. Other potential applications include the development of efficient bio-fuel alternative-energy processes and the exploration ofnovel materials for energy usages. Finally, we use the notion of 'coarse-graining,' which is a method for averaging over less important degrees of freedom to develop computational models to predict cell function and systems-level response to disease, chemical stress, or biological pathomic agents. This project supports Energy Security, Threat Reduction, and the missions of the DOE Office of Science through its efforts to

  20. Kirigami artificial muscles with complex biologically inspired morphologies

    International Nuclear Information System (INIS)

    Sareh, Sina; Rossiter, Jonathan

    2013-01-01

    In this paper we present bio-inspired smart structures which exploit the actuation of flexible ionic polymer composites and the kirigami design principle. Kirigami design is used to convert planar actuators into active 3D structures capable of large out-of-plane displacement and that replicate biological mechanisms. Here we present the burstbot, a fluid control and propulsion mechanism based on the atrioventricular cuspid valve, and the vortibot, a spiral actuator based on Vorticella campanula, a ciliate protozoa. Models derived from biological counterparts are used as a platform for design optimization and actuator performance measurement. The symmetric and asymmetric fluid interactions of the burstbot are investigated and the effectiveness in fluid transport applications is demonstrated. The vortibot actuator is geometrically optimized as a camera positioner capable of 360° scanning. Experimental results for a one-turn spiral actuator show complex actuation derived from a single degree of freedom control signal. (paper)

  1. Biologically inspired technologies using artificial muscles

    Science.gov (United States)

    Bar-Cohen, Yoseph

    2005-01-01

    After billions of years of evolution, nature developed inventions that work, which are appropriate for the intended tasks and that last. The evolution of nature led to the introduction of highly effective and power efficient biological mechanisms that are scalable from micron to many meters in size. Imitating these mechanisms offers enormous potentials for the improvement of our life and the tools we use. Humans have always made efforts to imitate nature and we are increasingly reaching levels of advancement where it becomes significantly easier to imitate, copy, and adapt biological methods, processes and systems. Some of the biomimetic technologies that have emerged include artificial muscles, artificial intelligence, and artificial vision to which significant advances in materials science, mechanics, electronics, and computer science have contributed greatly. One of the newest fields of biomimetics is the electroactive polymers (EAP) that are also known as artificial muscles. To take advantage of these materials, efforts are made worldwide to establish a strong infrastructure addressing the need for comprehensive analytical modeling of their operation mechanism and develop effective processing and characterization techniques. The field is still in its emerging state and robust materials are not readily available however in recent years significant progress has been made and commercial products have already started to appear. This paper covers the state-of-the-art and challenges to making artificial muscles and their potential biomimetic applications.

  2. Holarchical Systems and Emotional Holons : Biologically-Inspired System Designs for Control of Autonomous Aerial Vehicles

    Science.gov (United States)

    Ippolito, Corey; Plice, Laura; Pisanich, Greg

    2003-01-01

    The BEES (Bio-inspired Engineering for Exploration Systems) for Mars project at NASA Ames Research Center has the goal of developing bio-inspired flight control strategies to enable aerial explorers for Mars scientific investigations. This paper presents a summary of our ongoing research into biologically inspired system designs for control of unmanned autonomous aerial vehicle communities for Mars exploration. First, we present cooperative design considerations for robotic explorers based on the holarchical nature of biological systems and communities. Second, an outline of an architecture for cognitive decision making and control of individual robotic explorers is presented, modeled after the emotional nervous system of cognitive biological systems. Keywords: Holarchy, Biologically Inspired, Emotional UAV Flight Control

  3. Deep ART Neural Model for Biologically Inspired Episodic Memory and Its Application to Task Performance of Robots.

    Science.gov (United States)

    Park, Gyeong-Moon; Yoo, Yong-Ho; Kim, Deok-Hwa; Kim, Jong-Hwan

    2017-06-26

    Robots are expected to perform smart services and to undertake various troublesome or difficult tasks in the place of humans. Since these human-scale tasks consist of a temporal sequence of events, robots need episodic memory to store and retrieve the sequences to perform the tasks autonomously in similar situations. As episodic memory, in this paper we propose a novel Deep adaptive resonance theory (ART) neural model and apply it to the task performance of the humanoid robot, Mybot, developed in the Robot Intelligence Technology Laboratory at KAIST. Deep ART has a deep structure to learn events, episodes, and even more like daily episodes. Moreover, it can retrieve the correct episode from partial input cues robustly. To demonstrate the effectiveness and applicability of the proposed Deep ART, experiments are conducted with the humanoid robot, Mybot, for performing the three tasks of arranging toys, making cereal, and disposing of garbage.

  4. Numerical simulations of odorant detection by biologically inspired sensor arrays

    International Nuclear Information System (INIS)

    Schuech, R; Stacey, M T; Barad, M F; Koehl, M A R

    2012-01-01

    The antennules of many marine crustaceans enable them to rapidly locate sources of odorant in turbulent environmental flows and may provide biological inspiration for engineered plume sampling systems. A substantial gap in knowledge concerns how the physical interaction between a sensing device and the chemical filaments forming a turbulent plume affects odorant detection and filters the information content of the plume. We modeled biological arrays of chemosensory hairs as infinite arrays of odorant flux-detecting cylinders and simulated the fluid flow around and odorant flux into the hair-like sensors as they intercepted a single odorant filament. As array geometry and sampling kinematics were varied, we quantified distortion of the flux time series relative to the spatial shape of the original odorant filament as well as flux metrics that may be important to both organisms and engineered systems attempting to measure plume structure and/or identify chemical composition. The most important predictor of signal distortion is the ratio of sensor diameter to odorant filament width. Achieving high peak properties (e.g. sharpness) of the flux time series and maximizing the total number of odorant molecules detected appear to be mutually exclusive design goals. Sensor arrays inspired specifically by the spiny lobster Panulirus argus and mantis shrimp Gonodactylaceus falcatus introduce little signal distortion but these species' neural systems may not be able to resolve plume structure at the level of individual filaments via temporal properties of the odorant flux. Current chemical sensors are similarly constrained. Our results suggest either that the spatial distribution of flux across the aesthetasc array is utilized by P. argus and G. falcatus, or that such high spatiotemporal resolution is unnecessary for effective plume tracking.

  5. A Project-Based Biologically-Inspired Robotics Module

    Science.gov (United States)

    Crowder, R. M.; Zauner, K.-P.

    2013-01-01

    The design of any robotic system requires input from engineers from a variety of technical fields. This paper describes a project-based module, "Biologically-Inspired Robotics," that is offered to Electronics and Computer Science students at the University of Southampton, U.K. The overall objective of the module is for student groups to…

  6. Handwritten-word spotting using biologically inspired features

    NARCIS (Netherlands)

    van der Zant, Tijn; Schomaker, Lambert; Haak, Koen

    For quick access to new handwritten collections, current handwriting recognition methods are too cumbersome. They cannot deal with the lack of labeled data and would require extensive laboratory training for each individual script, style, language, and collection. We propose a biologically inspired

  7. Biologically inspired collision avoidance system for unmanned vehicles

    Science.gov (United States)

    Ortiz, Fernando E.; Graham, Brett; Spagnoli, Kyle; Kelmelis, Eric J.

    2009-05-01

    In this project, we collaborate with researchers in the neuroscience department at the University of Delaware to develop an Field Programmable Gate Array (FPGA)-based embedded computer, inspired by the brains of small vertebrates (fish). The mechanisms of object detection and avoidance in fish have been extensively studied by our Delaware collaborators. The midbrain optic tectum is a biological multimodal navigation controller capable of processing input from all senses that convey spatial information, including vision, audition, touch, and lateral-line (water current sensing in fish). Unfortunately, computational complexity makes these models too slow for use in real-time applications. These simulations are run offline on state-of-the-art desktop computers, presenting a gap between the application and the target platform: a low-power embedded device. EM Photonics has expertise in developing of high-performance computers based on commodity platforms such as graphic cards (GPUs) and FPGAs. FPGAs offer (1) high computational power, low power consumption and small footprint (in line with typical autonomous vehicle constraints), and (2) the ability to implement massively-parallel computational architectures, which can be leveraged to closely emulate biological systems. Combining UD's brain modeling algorithms and the power of FPGAs, this computer enables autonomous navigation in complex environments, and further types of onboard neural processing in future applications.

  8. Music Information Retrieval Using Biologically Inspired Techniques

    NARCIS (Netherlands)

    Bountouridis, D.

    2018-01-01

    The computational modeling of our perception of music similarity is an intricate, unsolved problem with various practical applications. Many of the current approaches aim at solving it by employing heuristics, such as expert intuition or music theory, which limit their application to narrow

  9. Trusted computation through biologically inspired processes

    Science.gov (United States)

    Anderson, Gustave W.

    2013-05-01

    Due to supply chain threats it is no longer a reasonable assumption that traditional protections alone will provide sufficient security for enterprise systems. The proposed cognitive trust model architecture extends the state-of-the-art in enterprise anti-exploitation technologies by providing collective immunity through backup and cross-checking, proactive health monitoring and adaptive/autonomic threat response, and network resource diversity.

  10. Biologically inspired technologies using artificial muscles

    Science.gov (United States)

    Bar-Cohen, Yoseph

    2005-01-01

    One of the newest fields of biomimetics is the electroactive polymers (EAP) that are also known as artificial muscles. To take advantage of these materials, efforts are made worldwide to establish a strong infrastructure addressing the need for comprehensive analytical modeling of their response mechanism and develop effective processing and characterization techniques. The field is still in its emerging state and robust materials are still not readily available however in recent years significant progress has been made and commercial products have already started to appear. This paper covers the current state of- the-art and challenges to making artificial muscles and their potential biomimetic applications.

  11. Biologically inspired rate control of chaos.

    Science.gov (United States)

    Olde Scheper, Tjeerd V

    2017-10-01

    The overall intention of chaotic control is to eliminate chaos and to force the system to become stable in the classical sense. In this paper, I demonstrate a more subtle method that does not eliminate all traces of chaotic behaviour; yet it consistently, and reliably, can provide control as intended. The Rate Control of Chaos (RCC) method is derived from metabolic control processes and has several remarkable properties. RCC can control complex systems continuously, and unsupervised, it can also maintain control across bifurcations, and in the presence of significant systemic noise. Specifically, I show that RCC can control a typical set of chaotic models, including the 3 and 4 dimensional chaotic Lorenz systems, in all modes. Furthermore, it is capable of controlling spatiotemporal chaos without supervision and maintains control of the system across bifurcations. This property of RCC allows a dynamic system to operate in parameter spaces that are difficult to control otherwise. This may be particularly interesting for the control of forced systems or dynamic systems that are chaotically perturbed. These control properties of RCC are applicable to a range of dynamic systems, thereby appearing to have far-reaching effects beyond just controlling chaos. RCC may also point to the existence of a biochemical control function of an enzyme, to stabilise the dynamics of the reaction cascade.

  12. Semiconductor Devices Inspired By and Integrated With Biology

    Energy Technology Data Exchange (ETDEWEB)

    Rogers, John [University of Illinois

    2012-04-25

    Biology is curved, soft and elastic; silicon wafers are not. Semiconductor technologies that can bridge this gap in form and mechanics will create new opportunities in devices that adopt biologically inspired designs or require intimate integration with the human body. This talk describes the development of ideas for electronics that offer the performance of state-of-the-art, wafer- based systems but with the mechanical properties of a rubber band. We explain the underlying materials science and mechanics of these approaches, and illustrate their use in (1) bio- integrated, ‘tissue-like’ electronics with unique capabilities for mapping cardiac and neural electrophysiology, and (2) bio-inspired, ‘eyeball’ cameras with exceptional imaging properties enabled by curvilinear, Petzval designs.

  13. Artificial heartbeat: design and fabrication of a biologically inspired pump

    International Nuclear Information System (INIS)

    Walters, Peter; Stephenson, Robert; Lewis, Amy; Stinchcombe, Andrew; Ieropoulos, Ioannis

    2013-01-01

    We present a biologically inspired actuator exhibiting a novel pumping action. The design of the ‘artificial heartbeat’ actuator is inspired by physical principles derived from the structure and function of the human heart. The actuator employs NiTi artificial muscles and is powered by electrical energy generated by microbial fuel cells (MFCs). We describe the design and fabrication of the actuator and report the results of tests conducted to characterize its performance. This is the first artificial muscle-driven pump to be powered by MFCs fed on human urine. Results are presented in terms of the peak pumping pressure generated by the actuator, as well as for the volume of fluid transferred, when the actuator was powered by energy stored in a capacitor bank, which was charged by 24 MFCs fed on urine. The results demonstrate the potential for the artificial heartbeat actuator to be employed as a fluid circulation pump in future generations of MFC-powered robots (‘EcoBots’) that extract energy from organic waste. We also envisage that the actuator could in the future form part of a bio-robotic artwork or ‘bio-automaton’ that could help increase public awareness of research in robotics, bio-energy and biologically inspired design. (paper)

  14. 7th World Congress on Nature and Biologically Inspired Computing

    CERN Document Server

    Engelbrecht, Andries; Abraham, Ajith; Plessis, Mathys; Snášel, Václav; Muda, Azah

    2016-01-01

    World Congress on Nature and Biologically Inspired Computing (NaBIC) is organized to discuss the state-of-the-art as well as to address various issues with respect to Nurturing Intelligent Computing Towards Advancement of Machine Intelligence. This Volume contains the papers presented in the Seventh World Congress (NaBIC’15) held in Pietermaritzburg, South Africa during December 01-03, 2015. The 39 papers presented in this Volume were carefully reviewed and selected. The Volume would be a valuable reference to researchers, students and practitioners in the computational intelligence field.

  15. Biologically-inspired Learning in Pulsed Neural Networks

    DEFF Research Database (Denmark)

    Lehmann, Torsten; Woodburn, Robin

    1999-01-01

    Self-learning chips to implement many popular ANN (artificial neural network) algorithms are very difficult to design. We explain why this is so and say what lessons previous work teaches us in the design of self-learning systems. We offer a contribution to the `biologically-inspired' approach......, explaining what we mean by this term and providing an example of a robust, self-learning design that can solve simple classical-conditioning tasks. We give details of the design of individual circuits to perform component functions, which can then be combined into a network to solve the task. We argue...

  16. Superstring inspired models and phenomenology

    International Nuclear Information System (INIS)

    Ross, G.G.

    1987-01-01

    An investigation of the effective low-energy theory resulting from the superstring is given. The possible light gauge and chiral super-multiplet structure is considered and a specific model leading to a SU(3)xSU(2)xU(1) gauge group is presented. Phenomenological implications for such models are briefly discussed

  17. Biologically-Inspired Control Architecture for Musical Performance Robots

    Directory of Open Access Journals (Sweden)

    Jorge Solis

    2014-10-01

    Full Text Available At Waseda University, since 1990, the authors have been developing anthropomorphic musical performance robots as a means for understanding human control, introducing novel ways of interaction between musical partners and robots, and proposing applications for humanoid robots. In this paper, the design of a biologically-inspired control architecture for both an anthropomorphic flutist robot and a saxophone playing robot are described. As for the flutist robot, the authors have focused on implementing an auditory feedback system to improve the calibration procedure for the robot in order to play all the notes correctly during a performance. In particular, the proposed auditory feedback system is composed of three main modules: an Expressive Music Generator, a Feed Forward Air Pressure Control System and a Pitch Evaluation System. As for the saxophone-playing robot, a pressure-pitch controller (based on the feedback error learning to improve the sound produced by the robot during a musical performance was proposed and implemented. In both cases studied, a set of experiments are described to verify the improvements achieved while considering biologically-inspired control approaches.

  18. Spatial Modeling Tools for Cell Biology

    National Research Council Canada - National Science Library

    Przekwas, Andrzej; Friend, Tom; Teixeira, Rodrigo; Chen, Z. J; Wilkerson, Patrick

    2006-01-01

    .... Scientific potentials and military relevance of computational biology and bioinformatics have inspired DARPA/IPTO's visionary BioSPICE project to develop computational framework and modeling tools for cell biology...

  19. Adaptive Fuzzy-Lyapunov Controller Using Biologically Inspired Swarm Intelligence

    Directory of Open Access Journals (Sweden)

    Alejandro Carrasco Elizalde

    2008-01-01

    Full Text Available The collective behaviour of swarms produces smarter actions than those achieved by a single individual. Colonies of ants, flocks of birds and fish schools are examples of swarms interacting with their environment to achieve a common goal. This cooperative biological intelligence is the inspiration for an adaptive fuzzy controller developed in this paper. Swarm intelligence is used to adjust the parameters of the membership functions used in the adaptive fuzzy controller. The rules of the controller are designed using a computing-with-words approach called Fuzzy-Lyapunov synthesis to improve the stability and robustness of an adaptive fuzzy controller. Computing-with-words provides a powerful tool to manipulate numbers and symbols, like words in a natural language.

  20. Biologically inspired control of humanoid robot arms robust and adaptive approaches

    CERN Document Server

    Spiers, Adam; Herrmann, Guido

    2016-01-01

    This book investigates a biologically inspired method of robot arm control, developed with the objective of synthesising human-like motion dynamically, using nonlinear, robust and adaptive control techniques in practical robot systems. The control method caters to a rising interest in humanoid robots and the need for appropriate control schemes to match these systems. Unlike the classic kinematic schemes used in industrial manipulators, the dynamic approaches proposed here promote human-like motion with better exploitation of the robot’s physical structure. This also benefits human-robot interaction. The control schemes proposed in this book are inspired by a wealth of human-motion literature that indicates the drivers of motion to be dynamic, model-based and optimal. Such considerations lend themselves nicely to achievement via nonlinear control techniques without the necessity for extensive and complex biological models. The operational-space method of robot control forms the basis of many of the techniqu...

  1. Marrow-isolated adult multilineage inducible cells embedded within a biologically-inspired construct promote recovery in a mouse model of peripheral vascular disease.

    Science.gov (United States)

    Grau-Monge, Cristina; Delcroix, Gaëtan J-R; Bonnin-Marquez, Andrea; Valdes, Mike; Awadallah, Ead Lewis Mazen; Quevedo, Daniel F; Armour, Maxime R; Montero, Ramon B; Schiller, Paul C; Andreopoulos, Fotios M; D'Ippolito, Gianluca

    2017-02-17

    Peripheral vascular disease is one of the major vascular complications in individuals suffering from diabetes and in the elderly that is associated with significant burden in terms of morbidity and mortality. Stem cell therapy is being tested as an attractive alternative to traditional surgery to prevent and treat this disorder. The goal of this study was to enhance the protective and reparative potential of marrow-isolated adult multilineage inducible (MIAMI) cells by incorporating them within a bio-inspired construct (BIC) made of two layers of gelatin B electrospun nanofibers. We hypothesized that the BIC would enhance MIAMI cell survival and engraftment, ultimately leading to a better functional recovery of the injured limb in our mouse model of critical limb ischemia compared to MIAMI cells used alone. Our study demonstrated that MIAMI cell-seeded BIC resulted in a wide range of positive outcomes with an almost full recovery of blood flow in the injured limb, thereby limiting the extent of ischemia and necrosis. Functional recovery was also the greatest when MIAMI cells were combined with BICs, compared to MIAMI cells alone or BICs in the absence of cells. Histology was performed 28 days after grafting the animals to explore the mechanisms at the source of these positive outcomes. We observed that our critical limb ischemia model induces an extensive loss of muscular fibers that are replaced by intermuscular adipose tissue (IMAT), together with a highly disorganized vascular structure. The use of MIAMI cells-seeded BIC prevented IMAT infiltration with some clear evidence of muscular fibers regeneration.

  2. Progress and Opportunities in Soft Photonics and Biologically Inspired Optics.

    Science.gov (United States)

    Kolle, Mathias; Lee, Seungwoo

    2018-01-01

    Optical components made fully or partially from reconfigurable, stimuli-responsive, soft solids or fluids-collectively referred to as soft photonics-are poised to form the platform for tunable optical devices with unprecedented functionality and performance characteristics. Currently, however, soft solid and fluid material systems still represent an underutilized class of materials in the optical engineers' toolbox. This is in part due to challenges in fabrication, integration, and structural control on the nano- and microscale associated with the application of soft components in optics. These challenges might be addressed with the help of a resourceful ally: nature. Organisms from many different phyla have evolved an impressive arsenal of light manipulation strategies that rely on the ability to generate and dynamically reconfigure hierarchically structured, complex optical material designs, often involving soft or fluid components. A comprehensive understanding of design concepts, structure formation principles, material integration, and control mechanisms employed in biological photonic systems will allow this study to challenge current paradigms in optical technology. This review provides an overview of recent developments in the fields of soft photonics and biologically inspired optics, emphasizes the ties between the two fields, and outlines future opportunities that result from advancements in soft and bioinspired photonics. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  3. Brain-inspired Stochastic Models and Implementations

    KAUST Repository

    Al-Shedivat, Maruan

    2015-05-12

    One of the approaches to building artificial intelligence (AI) is to decipher the princi- ples of the brain function and to employ similar mechanisms for solving cognitive tasks, such as visual perception or natural language understanding, using machines. The recent breakthrough, named deep learning, demonstrated that large multi-layer networks of arti- ficial neural-like computing units attain remarkable performance on some of these tasks. Nevertheless, such artificial networks remain to be very loosely inspired by the brain, which rich structures and mechanisms may further suggest new algorithms or even new paradigms of computation. In this thesis, we explore brain-inspired probabilistic mechanisms, such as neural and synaptic stochasticity, in the context of generative models. The two questions we ask here are: (i) what kind of models can describe a neural learning system built of stochastic components? and (ii) how can we implement such systems e ̆ciently? To give specific answers, we consider two well known models and the corresponding neural architectures: the Naive Bayes model implemented with a winner-take-all spiking neural network and the Boltzmann machine implemented in a spiking or non-spiking fashion. We propose and analyze an e ̆cient neuromorphic implementation of the stochastic neu- ral firing mechanism and study the e ̄ects of synaptic unreliability on learning generative energy-based models implemented with neural networks.

  4. Biologically Inspired Target Recognition in Radar Sensor Networks

    Directory of Open Access Journals (Sweden)

    Liang Qilian

    2010-01-01

    Full Text Available One of the great mysteries of the brain is cognitive control. How can the interactions between millions of neurons result in behavior that is coordinated and appears willful and voluntary? There is consensus that it depends on the prefrontal cortex (PFC. Many PFC areas receive converging inputs from at least two sensory modalities. Inspired by human's innate ability to process and integrate information from disparate, network-based sources, we apply human-inspired information integration mechanisms to target detection in cognitive radar sensor network. Humans' information integration mechanisms have been modelled using maximum-likelihood estimation (MLE or soft-max approaches. In this paper, we apply these two algorithms to cognitive radar sensor networks target detection. Discrete-cosine-transform (DCT is used to process the integrated data from MLE or soft-max. We apply fuzzy logic system (FLS to automatic target detection based on the AC power values from DCT. Simulation results show that our MLE-DCT-FLS and soft-max-DCT-FLS approaches perform very well in the radar sensor network target detection, whereas the existing 2D construction algorithm does not work in this study.

  5. Biologically inspired EM image alignment and neural reconstruction.

    Science.gov (United States)

    Knowles-Barley, Seymour; Butcher, Nancy J; Meinertzhagen, Ian A; Armstrong, J Douglas

    2011-08-15

    Three-dimensional reconstruction of consecutive serial-section transmission electron microscopy (ssTEM) images of neural tissue currently requires many hours of manual tracing and annotation. Several computational techniques have already been applied to ssTEM images to facilitate 3D reconstruction and ease this burden. Here, we present an alternative computational approach for ssTEM image analysis. We have used biologically inspired receptive fields as a basis for a ridge detection algorithm to identify cell membranes, synaptic contacts and mitochondria. Detected line segments are used to improve alignment between consecutive images and we have joined small segments of membrane into cell surfaces using a dynamic programming algorithm similar to the Needleman-Wunsch and Smith-Waterman DNA sequence alignment procedures. A shortest path-based approach has been used to close edges and achieve image segmentation. Partial reconstructions were automatically generated and used as a basis for semi-automatic reconstruction of neural tissue. The accuracy of partial reconstructions was evaluated and 96% of membrane could be identified at the cost of 13% false positive detections. An open-source reference implementation is available in the Supplementary information. seymour.kb@ed.ac.uk; douglas.armstrong@ed.ac.uk Supplementary data are available at Bioinformatics online.

  6. Supersymmetric SO(10) models inspired by deconstruction

    International Nuclear Information System (INIS)

    Huang Chaoshang; Jiang Jing; Li Tianjun

    2004-01-01

    We consider 4-dimensional N=1 supersymmetric SO(10) models inspired by deconstruction of 5-dimensional N=1 supersymmetric orbifold SO(10) models and high-dimensional non-supersymmetric SO(10) models with Wilson line gauge symmetry breaking. We discuss the SO(10)xSO(10) models with bi-fundamental link fields where the gauge symmetry can be broken down to the Pati-Salam, SU(5)xU(1), flipped SU(5)xU(1)' or the Standard Model like gauge symmetry. We also propose an SO(10)xSO(6)xSO(4) model with bi-fundamental link fields where the gauge symmetry is broken down to the Pati-Salam gauge symmetry, and an SO(10)xSO(10) model with bi-spinor link fields where the gauge symmetry is broken down to the flipped SU(5)xU(1)' gauge symmetry. In these two models, the Pati-Salam and flipped SU(5)xU(1)' gauge symmetry can be further broken down to the Standard Model gauge symmetry, the doublet-triplet splittings can be obtained by the missing partner mechanism, and the proton decay problem can be solved. We also study the gauge coupling unification. We briefly comment on the interesting variation models with gauge groups SO(10)xSO(6) and SO(10)xflippedSU(5)xU(1)' in which the proton decay problem can be solved

  7. Geo-inspired model: Agents vectors naturals inspired by the environmental management (AVNG of water tributaries

    Directory of Open Access Journals (Sweden)

    Edwin Eduardo Millán Rojas

    2018-02-01

    Full Text Available Context: Management to care for the environment and the Earth (geo can be source of inspiration for developing models that allow addressing complexity issues; the objective of this research was to develop an additional aspect of the inspired models. The geoinspired model has two features, the first covering aspects related to environmental management and the behavior of natural resources, and the second has a component of spatial location associated with existing objects on the Earth's surface. Method: The approach developed in the research is descriptive and its main objective is the representation or characterization of a case study within a particular context. Results: The result was the design of a model to emulate the natural behavior of the water tributaries of the Amazon foothills, in order to extend the application of the inspired models and allow the use of elements such as geo-referencing and environmental management. The proposed geoinspired model is called “natural vectors agents inspired in environmental management”. Conclusions: The agents vectors naturals inspired by the environmental are polyform elements that can assume the behavior of environmental entities, which makes it possible to achieve progress in other fields of environmental management (use of soil, climate, flora, fauna, and link environmental issues with the structure of the proposed model.

  8. Biologically Inspired Object Localization for a Modular Mobile Robotic System

    Directory of Open Access Journals (Sweden)

    Zlatogor Minchev

    2005-12-01

    Full Text Available The paper considers a general model of real biological creatures' antennae, which is practically implemented and tested, over a real element of a mobile modular robotic system - the robot MR1. The last could be utilized in solving of the most classical problem in Robotics - Object Localization. The functionality of the represented sensor system is described in a new and original manner by utilizing the tool of Generalized Nets - a new likelihood for description, modelling and simulation of different objects from the Artificial Intelligence area including Robotics.

  9. Biomimetics as a Model for Inspiring Human Innovation

    Science.gov (United States)

    Bar-Cohen, Yoseph

    2006-01-01

    Electroactive polymers (EAP) are human made actuators that are the closest to mimic biological muscles. Technology was advanced to the level that biologically inspired robots are taking increasing roles in the world around us and making science fiction ideas a closer engineering reality. Artificial technologies (AI, AM, and others) are increasingly becoming practical tools for making biologically inspired devices and instruments with enormous potential for space applications. Polymer materials are used to produce figures that resemble human and animals. These materials are widely employed by the movie industry for making acting figures and by the orthopedic industry to construct cyborg components. There are still many challenges ahead that are critical to making such possibilities practical. The annual armwrestling contest is providing an exciting measure of how well advances in EAP are implemented to address the field challenges. There is a need to document natures inventions in an engineering form to possibly inspire new capabilities.

  10. Soft Robotics: Biological Inspiration, State of the Art, and Future Research

    Directory of Open Access Journals (Sweden)

    Deepak Trivedi

    2008-01-01

    Full Text Available Traditional robots have rigid underlying structures that limit their ability to interact with their environment. For example, conventional robot manipulators have rigid links and can manipulate objects using only their specialised end effectors. These robots often encounter difficulties operating in unstructured and highly congested environments. A variety of animals and plants exhibit complex movement with soft structures devoid of rigid components. Muscular hydrostats (e.g. octopus arms and elephant trunks are almost entirely composed of muscle and connective tissue and plant cells can change shape when pressurised by osmosis. Researchers have been inspired by biology to design and build soft robots. With a soft structure and redundant degrees of freedom, these robots can be used for delicate tasks in cluttered and/or unstructured environments. This paper discusses the novel capabilities of soft robots, describes examples from nature that provide biological inspiration, surveys the state of the art and outlines existing challenges in soft robot design, modelling, fabrication and control.

  11. Cellular automaton model of crowd evacuation inspired by slime mould

    Science.gov (United States)

    Kalogeiton, V. S.; Papadopoulos, D. P.; Georgilas, I. P.; Sirakoulis, G. Ch.; Adamatzky, A. I.

    2015-04-01

    In all the living organisms, the self-preservation behaviour is almost universal. Even the most simple of living organisms, like slime mould, is typically under intense selective pressure to evolve a response to ensure their evolution and safety in the best possible way. On the other hand, evacuation of a place can be easily characterized as one of the most stressful situations for the individuals taking part on it. Taking inspiration from the slime mould behaviour, we are introducing a computational bio-inspired model crowd evacuation model. Cellular Automata (CA) were selected as a fully parallel advanced computation tool able to mimic the Physarum's behaviour. In particular, the proposed CA model takes into account while mimicking the Physarum foraging process, the food diffusion, the organism's growth, the creation of tubes for each organism, the selection of optimum tube for each human in correspondence to the crowd evacuation under study and finally, the movement of all humans at each time step towards near exit. To test the model's efficiency and robustness, several simulation scenarios were proposed both in virtual and real-life indoor environments (namely, the first floor of office building B of the Department of Electrical and Computer Engineering of Democritus University of Thrace). The proposed model is further evaluated in a purely quantitative way by comparing the simulation results with the corresponding ones from the bibliography taken by real data. The examined fundamental diagrams of velocity-density and flow-density are found in full agreement with many of the already published corresponding results proving the adequacy, the fitness and the resulting dynamics of the model. Finally, several real Physarum experiments were conducted in an archetype of the aforementioned real-life environment proving at last that the proposed model succeeded in reproducing sufficiently the Physarum's recorded behaviour derived from observation of the aforementioned

  12. First controlled vertical flight of a biologically inspired microrobot

    Energy Technology Data Exchange (ETDEWEB)

    Perez-Arancibia, Nestor O; Ma, Kevin Y; Greenberg, Jack D; Wood, Robert J [School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138 (United States); Galloway, Kevin C, E-mail: nperez@seas.harvard.edu, E-mail: kevinma@seas.harvard.edu, E-mail: kevin.galloway@wyss.harvard.edu, E-mail: jdgreenb@seas.harvard.edu, E-mail: rjwood@eecs.harvard.edu [Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02115 (United States)

    2011-09-15

    In this paper, we present experimental results on altitude control of a flying microrobot. The problem is approached in two stages. In the first stage, system identification of two relevant subsystems composing the microrobot is performed, using a static flapping experimental setup. In the second stage, the information gathered through the static flapping experiments is employed to design the controller used in vertical flight. The design of the proposed controller relies on the idea of treating an exciting signal as a subsystem of the microrobot. The methods and results presented here are a key step toward achieving total autonomy of bio-inspired flying microrobots.

  13. First controlled vertical flight of a biologically inspired microrobot

    International Nuclear Information System (INIS)

    Perez-Arancibia, Nestor O; Ma, Kevin Y; Greenberg, Jack D; Wood, Robert J; Galloway, Kevin C

    2011-01-01

    In this paper, we present experimental results on altitude control of a flying microrobot. The problem is approached in two stages. In the first stage, system identification of two relevant subsystems composing the microrobot is performed, using a static flapping experimental setup. In the second stage, the information gathered through the static flapping experiments is employed to design the controller used in vertical flight. The design of the proposed controller relies on the idea of treating an exciting signal as a subsystem of the microrobot. The methods and results presented here are a key step toward achieving total autonomy of bio-inspired flying microrobots.

  14. Quantum and classical dynamics in biologically inspired systems

    International Nuclear Information System (INIS)

    Guerreschi, G.

    2012-01-01

    Quantum biology is an emerging field in which traditional believes and paradigms are under examination. Typically, quantum effects are witnessed inside quantum optics or atomic physics laboratories in systems which are kept under control and isolated from any noise source by means of very advanced technology. Biological systems exhibit opposite characteristics: They are usually constituted of macromolecules continuously exposed to a warm and wet environment, well beyond our control; but at the same time, they operate far away from equilibrium. Recently, the experimental observation of excitonic coherence in photosynthetic complexes has con firmed that, in non-equilibrium scenarios, quantum phenomena can survive even in presence of a noisy environment. The challenge faced by the ongoing research is twofold: On one side, considering biological molecules as effective nanomachines, one has to address questions of principle regarding their design and functioning; on the other side, one has to investigate real systems which are experimentally accessible and identify such features in these concrete scenarios. The present thesis contributes to both of these aspects. In Part I, we demonstrate how entanglement can be persistently generated even under unfavorable environmental conditions. The physical mechanism is modeled after the idea of conformational changes, and it relies on the interplay of classical oscillations of large structures with the quantum dynamics of a few interacting degrees of freedom. In a similar context, we show that the transfer of an excitation through a linear chain of sites can be enhanced when the inter-site distances oscillate periodically. This enhancement is present even in comparison with the static con figuration which is optimal in the classical case and, therefore, it constitutes a clear signature of the underlying quantum dynamics. In Part II of this thesis, we study the radical pair mechanism from the perspective of quantum control and

  15. Review: Biological and Molecular Differences between Tail Regeneration and Limb Scarring in Lizard: An Inspiring Model Addressing Limb Regeneration in Amniotes.

    Science.gov (United States)

    Alibardi, Lorenzo

    2017-09-01

    Tissue regeneration in lizards represents a unique model of regeneration and scarring in amniotes. The tail and limb contain putative stem cells but also dedifferentiating cells contribute to regeneration. Following tail amputation, inflammation is low and cell proliferation high, leading to regeneration while the intense inflammation in the limb leads to low proliferation and scarring. FGFs stimulate tail and limb regeneration and are present in the wound epidermis and blastema while they disappear in the limb wound epidermis 2-3 weeks postamputation in the scarring outgrowth. FGFs localize in the tail blastema and the apical epidermal peg (AEP), an epidermal microregion that allows tail growth but is absent in the limb. Inflammatory cells invade the limb blastema and wound epidermis, impeding the formation of an AEP. An embryonic program of growth is activated in the tail, dominated by Wnt-positive and -negative regulators of cell proliferation and noncoding RNAs, that represent the key regenerative genes. The balanced actions of these regulators likely impede the formation of a tumor in the tail tip. Genes for FACIT and fibrillar collagens, protease inhibitors, and embryonic keratins are upregulated in the regenerating tail blastema. A strong downregulation of genes for both B and T-lymphocyte activation suggests the regenerating tail blastema is a temporal immune-tolerated organ, whereas a scarring program is activated in the limb. Wnt inhibitors, pro-inflammatory genes, negative regulators of cell proliferation, downregulation of myogenic genes, proteases, and oxidases favoring scarring are upregulated. The evolution of an efficient immune system may be the main limiting barrier for organ regeneration in amniotes, and the poor regeneration of mammals and birds is associated with the efficiency of their mature immune system. This does not tolerate embryonic antigens formed in reprogrammed embryonic cells (as for neoplastic cells) that are consequently

  16. Perceptron-like computation based on biologically-inspired neurons with heterosynaptic mechanisms

    Science.gov (United States)

    Kaluza, Pablo; Urdapilleta, Eugenio

    2014-10-01

    Perceptrons are one of the fundamental paradigms in artificial neural networks and a key processing scheme in supervised classification tasks. However, the algorithm they provide is given in terms of unrealistically simple processing units and connections and therefore, its implementation in real neural networks is hard to be fulfilled. In this work, we present a neural circuit able to perform perceptron's computation based on realistic models of neurons and synapses. The model uses Wang-Buzsáki neurons with coupling provided by axodendritic and axoaxonic synapses (heterosynapsis). The main characteristics of the feedforward perceptron operation are conserved, which allows to combine both approaches: whereas the classical artificial system can be used to learn a particular problem, its solution can be directly implemented in this neural circuit. As a result, we propose a biologically-inspired system able to work appropriately in a wide range of frequencies and system parameters, while keeping robust to noise and error.

  17. Energy-based control for a biologically inspired hexapod robot with rolling locomotion

    Directory of Open Access Journals (Sweden)

    Takuma Nemoto

    2015-04-01

    Full Text Available This paper presents an approach to control rolling locomotion on the level ground with a biologically inspired hexapod robot. For controlling rolling locomotion, a controller which can compensate energy loss with rolling locomotion of the hexapod robot is designed based on its dynamic model. The dynamic model describes the rolling locomotion which is limited to planar one by an assumption that the hexapod robot does not fall down while rolling and influences due to collision and contact with the ground, and it is applied for computing the mechanical energy of the hexapod robot and a plant for a numerical simulation. The numerical simulation of the rolling locomotion on the level ground verifies the effectiveness of the proposed controller. The simulation results show that the hexapod robot can perform the rolling locomotion with the proposed controller. In conclusion, it is shown that the proposed control approach is effective in achieving the rolling locomotion on the level ground.

  18. Seeding-inspired chemotaxis genetic algorithm for the inference of biological systems.

    Science.gov (United States)

    Wu, Shinq-Jen; Wu, Cheng-Tao

    2014-09-18

    A large challenge in the post-genomic era is to obtain the quantitatively dynamic interactive information of the important constitutes of underlying systems. The S-system is a dynamic and structurally rich model that determines the net strength of interactions between genes and/or proteins. Good generation characteristics without the need for prior information have allowed S-systems to become one of the most promising canonical models. Various evolutionary computation technologies have recently been developed for the identification of system parameters and skeletal-network structures. However, the gaps between the truncated and preserved terms remain too small. Additionally, current research methods fail to identify the structures of high dimensional systems (e.g., 30 genes with 1800 connections). Optimization technologies should converge fast and have the ability to adaptively adjust the search. In this study, we propose a seeding-inspired chemotaxis genetic algorithm (SCGA) that can force evolution to adjust the population movement to identify a favorable location. The seeding-inspired training strategy is a method to achieve optimal results with limited resources. SCGA introduces seeding-inspired genetic operations to allow a population to possess competitive power (exploitation and exploration) and a winner-chemotaxis-induced population migration to force a population to repeatedly tumble away from an attractor and swim toward another attractor. SCGA was tested on several canonical biological systems. SCGA not only learned the correct structure within only one to three pruning steps but also ensures pruning safety. The values of the truncated terms were all smaller than 10 -14 , even for a thirty-gene system. Copyright © 2014 Elsevier Ltd. All rights reserved.

  19. A biologically inspired meta-control navigation system for the Psikharpax rat robot

    International Nuclear Information System (INIS)

    Caluwaerts, K; Staffa, M; N’Guyen, S; Grand, C; Dollé, L; Favre-Félix, A; Girard, B; Khamassi, M

    2012-01-01

    A biologically inspired navigation system for the mobile rat-like robot named Psikharpax is presented, allowing for self-localization and autonomous navigation in an initially unknown environment. The ability of parts of the model (e.g. the strategy selection mechanism) to reproduce rat behavioral data in various maze tasks has been validated before in simulations. But the capacity of the model to work on a real robot platform had not been tested. This paper presents our work on the implementation on the Psikharpax robot of two independent navigation strategies (a place-based planning strategy and a cue-guided taxon strategy) and a strategy selection meta-controller. We show how our robot can memorize which was the optimal strategy in each situation, by means of a reinforcement learning algorithm. Moreover, a context detector enables the controller to quickly adapt to changes in the environment—recognized as new contexts—and to restore previously acquired strategy preferences when a previously experienced context is recognized. This produces adaptivity closer to rat behavioral performance and constitutes a computational proposition of the role of the rat prefrontal cortex in strategy shifting. Moreover, such a brain-inspired meta-controller may provide an advancement for learning architectures in robotics. (paper)

  20. Mechanization and Control Concepts for Biologically Inspired Micro Aerial Vehicles

    Science.gov (United States)

    Raney, David L.; Slominski, Eric C.

    2003-01-01

    It is possible that MAV designs of the future will exploit flapping flight in order to perform missions that require extreme agility, such as rapid flight beneath a forest canopy or within the confines of a building. Many of nature's most agile flyers generate flapping motions through resonant excitation of an aeroelastically tailored structure: muscle tissue is used to excite a vibratory mode of their flexible wing structure that creates propulsion and lift. A number of MAV concepts have been proposed that would operate in a similar fashion. This paper describes an ongoing research activity in which mechanization and control concepts with application to resonant flapping MAVs are being explored. Structural approaches, mechanical design, sensing and wingbeat control concepts inspired by hummingbirds, bats and insects are examined. Experimental results from a testbed capable of generating vibratory wingbeat patterns that approximately match those exhibited by hummingbirds in hover, cruise, and reverse flight are presented.

  1. Color encoding in biologically-inspired convolutional neural networks.

    Science.gov (United States)

    Rafegas, Ivet; Vanrell, Maria

    2018-05-11

    Convolutional Neural Networks have been proposed as suitable frameworks to model biological vision. Some of these artificial networks showed representational properties that rival primate performances in object recognition. In this paper we explore how color is encoded in a trained artificial network. It is performed by estimating a color selectivity index for each neuron, which allows us to describe the neuron activity to a color input stimuli. The index allows us to classify whether they are color selective or not and if they are of a single or double color. We have determined that all five convolutional layers of the network have a large number of color selective neurons. Color opponency clearly emerges in the first layer, presenting 4 main axes (Black-White, Red-Cyan, Blue-Yellow and Magenta-Green), but this is reduced and rotated as we go deeper into the network. In layer 2 we find a denser hue sampling of color neurons and opponency is reduced almost to one new main axis, the Bluish-Orangish coinciding with the dataset bias. In layers 3, 4 and 5 color neurons are similar amongst themselves, presenting different type of neurons that detect specific colored objects (e.g., orangish faces), specific surrounds (e.g., blue sky) or specific colored or contrasted object-surround configurations (e.g. blue blob in a green surround). Overall, our work concludes that color and shape representation are successively entangled through all the layers of the studied network, revealing certain parallelisms with the reported evidences in primate brains that can provide useful insight into intermediate hierarchical spatio-chromatic representations. Copyright © 2018 Elsevier Ltd. All rights reserved.

  2. Maneuvering control and configuration adaptation of a biologically inspired morphing aircraft

    Science.gov (United States)

    Abdulrahim, Mujahid

    Natural flight as a source of inspiration for aircraft design was prominent with early aircraft but became marginalized as aircraft became larger and faster. With recent interest in small unmanned air vehicles, biological inspiration is a possible technology to enhance mission performance of aircraft that are dimensionally similar to gliding birds. Serial wing joints, loosely modeling the avian skeletal structure, are used in the current study to allow significant reconfiguration of the wing shape. The wings are reconfigured to optimize aerodynamic performance and maneuvering metrics related to specific mission tasks. Wing shapes for each mission are determined and related to the seagulls, falcons, albatrosses, and non-migratory African swallows on which the aircraft are based. Variable wing geometry changes the vehicle dynamics, affording versatility in flight behavior but also requiring appropriate compensation to maintain stability and controllability. Time-varying compensation is in the form of a baseline controller which adapts to both the variable vehicle dynamics and to the changing mission requirements. Wing shape is adapted in flight to minimize a cost function which represents energy, temporal, and spatial efficiency. An optimal control architecture unifies the control and adaptation tasks.

  3. Propulsion of swimming microrobots inspired by metachronal waves in ciliates: from biology to material specifications

    International Nuclear Information System (INIS)

    Palagi, Stefano; Mazzolai, Barbara; Beccai, Lucia; Jager, Edwin WH

    2013-01-01

    The quest for swimming microrobots originates from possible applications in medicine, especially involving navigation in bodily fluids. Swimming microorganisms have become a source of inspiration because their propulsion mechanisms are effective in the low-Reynolds number regime. In this study, we address a propulsion mechanism inspired by metachronal waves, i.e. the spontaneous coordination of cilia leading to the fast swimming of ciliates. We analyse the biological mechanism (referring to its particular embodiment in Paramecium caudatum), and we investigate the contribution of its main features to the swimming performance, through a three-dimensional finite-elements model, in order to develop a simplified, yet effective artificial design. We propose a bioinspired propulsion mechanism for a swimming microrobot based on a continuous cylindrical electroactive surface exhibiting perpendicular wave deformations travelling longitudinally along its main axis. The simplified propulsion mechanism is conceived specifically for microrobots that embed a micro-actuation system capable of executing the bioinspired propulsion (self-propelled microrobots). Among the available electroactive polymers, we select polypyrrole as the possible actuation material and we assess it for this particular embodiment. The results are used to appoint target performance specifications for the development of improved or new electroactive materials to attain metachronal-waves-like propulsion. (paper)

  4. Propulsion of swimming microrobots inspired by metachronal waves in ciliates: from biology to material specifications.

    Science.gov (United States)

    Palagi, Stefano; Jager, Edwin W H; Mazzolai, Barbara; Beccai, Lucia

    2013-12-01

    The quest for swimming microrobots originates from possible applications in medicine, especially involving navigation in bodily fluids. Swimming microorganisms have become a source of inspiration because their propulsion mechanisms are effective in the low-Reynolds number regime. In this study, we address a propulsion mechanism inspired by metachronal waves, i.e. the spontaneous coordination of cilia leading to the fast swimming of ciliates. We analyse the biological mechanism (referring to its particular embodiment in Paramecium caudatum), and we investigate the contribution of its main features to the swimming performance, through a three-dimensional finite-elements model, in order to develop a simplified, yet effective artificial design. We propose a bioinspired propulsion mechanism for a swimming microrobot based on a continuous cylindrical electroactive surface exhibiting perpendicular wave deformations travelling longitudinally along its main axis. The simplified propulsion mechanism is conceived specifically for microrobots that embed a micro-actuation system capable of executing the bioinspired propulsion (self-propelled microrobots). Among the available electroactive polymers, we select polypyrrole as the possible actuation material and we assess it for this particular embodiment. The results are used to appoint target performance specifications for the development of improved or new electroactive materials to attain metachronal-waves-like propulsion.

  5. Biologically-Inspired Adaptive Obstacle Negotiation Behavior of Hexapod Robots

    Directory of Open Access Journals (Sweden)

    Dennis eGoldschmidt

    2014-01-01

    Full Text Available Neurobiological studies have shown that insects are able to adapt leg movements and posture for obstacle negotiation in changing environments. Moreover, the distance to an obstacle where an insect begins to climb is found to be a major parameter for successful obstacle negotiation. Inspired by these findings, we present an adaptive neural control mechanism for obstacle negotiation behavior in hexapod robots. It combines locomotion control, backbone joint control, local leg reflexes, and neural learning. While the first three components generate locomotion including walking and climbing, the neural learning mechanism allows the robot to adapt its behavior for obstacle negotiation with respect to changing conditions, e.g., variable obstacle heights and different walking gaits. By successfully learning the association of an early, predictive signal (conditioned stimulus, CS and a late, reflex signal (unconditioned stimulus, UCS, both provided by ultrasonic sensors at the front of the robot, the robot can autonomously find an appropriate distance from an obstacle to initiate climbing. The adaptive neural control was developed and tested first on a physical robot simulation, and was then successfully transferred to a real hexapod robot, called AMOS II. The results show that the robot can efficiently negotiate obstacles with a height up to 85% of the robot's leg length in simulation and 75% in a real environment.

  6. Automated mitosis detection using texture, SIFT features and HMAX biologically inspired approach.

    Science.gov (United States)

    Irshad, Humayun; Jalali, Sepehr; Roux, Ludovic; Racoceanu, Daniel; Hwee, Lim Joo; Naour, Gilles Le; Capron, Frédérique

    2013-01-01

    According to Nottingham grading system, mitosis count in breast cancer histopathology is one of three components required for cancer grading and prognosis. Manual counting of mitosis is tedious and subject to considerable inter- and intra-reader variations. The aim is to investigate the various texture features and Hierarchical Model and X (HMAX) biologically inspired approach for mitosis detection using machine-learning techniques. We propose an approach that assists pathologists in automated mitosis detection and counting. The proposed method, which is based on the most favorable texture features combination, examines the separability between different channels of color space. Blue-ratio channel provides more discriminative information for mitosis detection in histopathological images. Co-occurrence features, run-length features, and Scale-invariant feature transform (SIFT) features were extracted and used in the classification of mitosis. Finally, a classification is performed to put the candidate patch either in the mitosis class or in the non-mitosis class. Three different classifiers have been evaluated: Decision tree, linear kernel Support Vector Machine (SVM), and non-linear kernel SVM. We also evaluate the performance of the proposed framework using the modified biologically inspired model of HMAX and compare the results with other feature extraction methods such as dense SIFT. The proposed method has been tested on Mitosis detection in breast cancer histological images (MITOS) dataset provided for an International Conference on Pattern Recognition (ICPR) 2012 contest. The proposed framework achieved 76% recall, 75% precision and 76% F-measure. Different frameworks for classification have been evaluated for mitosis detection. In future work, instead of regions, we intend to compute features on the results of mitosis contour segmentation and use them to improve detection and classification rate.

  7. Automated mitosis detection using texture, SIFT features and HMAX biologically inspired approach

    Directory of Open Access Journals (Sweden)

    Humayun Irshad

    2013-01-01

    Full Text Available Context: According to Nottingham grading system, mitosis count in breast cancer histopathology is one of three components required for cancer grading and prognosis. Manual counting of mitosis is tedious and subject to considerable inter- and intra-reader variations. Aims: The aim is to investigate the various texture features and Hierarchical Model and X (HMAX biologically inspired approach for mitosis detection using machine-learning techniques. Materials and Methods: We propose an approach that assists pathologists in automated mitosis detection and counting. The proposed method, which is based on the most favorable texture features combination, examines the separability between different channels of color space. Blue-ratio channel provides more discriminative information for mitosis detection in histopathological images. Co-occurrence features, run-length features, and Scale-invariant feature transform (SIFT features were extracted and used in the classification of mitosis. Finally, a classification is performed to put the candidate patch either in the mitosis class or in the non-mitosis class. Three different classifiers have been evaluated: Decision tree, linear kernel Support Vector Machine (SVM, and non-linear kernel SVM. We also evaluate the performance of the proposed framework using the modified biologically inspired model of HMAX and compare the results with other feature extraction methods such as dense SIFT. Results: The proposed method has been tested on Mitosis detection in breast cancer histological images (MITOS dataset provided for an International Conference on Pattern Recognition (ICPR 2012 contest. The proposed framework achieved 76% recall, 75% precision and 76% F-measure. Conclusions: Different frameworks for classification have been evaluated for mitosis detection. In future work, instead of regions, we intend to compute features on the results of mitosis contour segmentation and use them to improve detection and

  8. Variable gearing in a biologically inspired pneumatic actuator array

    International Nuclear Information System (INIS)

    Azizi, Emanuel; Roberts, Thomas J

    2013-01-01

    A fundamental feature of pennate muscles is that muscle fibers are oriented at an angle to the line of action and rotate as they shorten, becoming more oblique throughout a contraction. This change in fiber orientation (pennation angle) can amplify the shortening velocity of a fiber and increase output velocity of the muscle. The velocity advantage resulting from dynamic changes in pennation angle can be characterized as a gear ratio (muscle velocity/fiber velocity). A recent study has shown that a pennate muscle's gear ratio varies automatically depending on the load such that a muscle operates with a high gear during rapid contractions and low gear during forceful contractions. We examined whether this variable gearing behavior can be replicated in a pennate array of artificial muscles. We used McKibben type pneumatic actuators, which shorten in tension when filled with compressed gas. Similar to muscle fibers, the actuators expand radially during shortening, a feature thought to be a critical part of the variable gearing mechanism in pennate muscles. We arranged McKibben actuators in an array oriented to mimic a pennate muscle, and quantified the system's gear ratio during contraction against a range of loads. Video was used to measure the gear ratio during each contraction. We find that similar to pennate muscles, the gear ratio decreases significantly with increasing load and that variable gearing results from load-dependent variation in the amount of actuator rotation. These results support the idea that variable gearing in pennate muscles is mediated by difference is fiber rotation and the direction of muscle bulging. The behavior of our artificial muscle array also highlights the potential benefits of bio-inspired architectures in artificial muscle arrays, including the ability to vary force and speed automatically in response to variable loading conditions. (paper)

  9. Variable gearing in a biologically inspired pneumatic actuator array.

    Science.gov (United States)

    Azizi, Emanuel; Roberts, Thomas J

    2013-06-01

    A fundamental feature of pennate muscles is that muscle fibers are oriented at an angle to the line of action and rotate as they shorten, becoming more oblique throughout a contraction. This change in fiber orientation (pennation angle) can amplify the shortening velocity of a fiber and increase output velocity of the muscle. The velocity advantage resulting from dynamic changes in pennation angle can be characterized as a gear ratio (muscle velocity/fiber velocity). A recent study has shown that a pennate muscle's gear ratio varies automatically depending on the load such that a muscle operates with a high gear during rapid contractions and low gear during forceful contractions. We examined whether this variable gearing behavior can be replicated in a pennate array of artificial muscles. We used McKibben type pneumatic actuators, which shorten in tension when filled with compressed gas. Similar to muscle fibers, the actuators expand radially during shortening, a feature thought to be a critical part of the variable gearing mechanism in pennate muscles. We arranged McKibben actuators in an array oriented to mimic a pennate muscle, and quantified the system's gear ratio during contraction against a range of loads. Video was used to measure the gear ratio during each contraction. We find that similar to pennate muscles, the gear ratio decreases significantly with increasing load and that variable gearing results from load-dependent variation in the amount of actuator rotation. These results support the idea that variable gearing in pennate muscles is mediated by difference is fiber rotation and the direction of muscle bulging. The behavior of our artificial muscle array also highlights the potential benefits of bio-inspired architectures in artificial muscle arrays, including the ability to vary force and speed automatically in response to variable loading conditions.

  10. VARIABLE GEARING IN A BIOLOGICALLY-INSPIRED PNEUMATIC ACTUATOR ARRAY

    Science.gov (United States)

    Azizi, Emanuel; Roberts, Thomas J.

    2013-01-01

    A fundamental feature of pennate muscles is that muscle fibers are oriented at an angle to the line of action and rotate as they shorten, becoming more oblique throughout a contraction. This change in fiber orientation (pennation angle) can amplify the shortening velocity of a fiber and increase output velocity of the muscle. The velocity advantage resulting from dynamic changes in pennation angle can be characterized as a gear ratio (muscle velocity/fiber velocity). A recent study has shown that a pennate muscle’s gear ratio varies automatically depending on the load such that a muscle operates with a high gear during rapid contractions and low gear during forceful contractions. We examined whether this variable gearing behavior can be replicated in a pennate array of artificial muscles. We used McKibben type pneumatic actuators, which shorten in tension when filled with compressed gas. Similar to muscle fibers, the actuators expand radially during shortening, a feature thought to be a critical part of the variable gearing mechanism in pennate muscles. We arranged McKibben actuators in an array oriented to mimic a pennate muscle, and quantified the system’s gear ratio during contraction against a range of loads. Video was used to measure the gear ratio during each contraction. We find that similar to pennate muscles, the gear ratio decreases significantly with increasing load and that variable gearing results from load-dependent variation in the amount of actuator rotation. These results support the idea that variable gearing in pennate muscles is mediated by difference is fiber rotation and the direction of muscle bulging. The behavior of our artificial muscle array also highlights the potential benefits of bio-inspired architectures in artificial muscle arrays, including the ability to vary force and speed automatically in response to variable loading conditions. PMID:23462288

  11. Biologically inspired autonomous structural materials with controlled toughening and healing

    Science.gov (United States)

    Garcia, Michael E.; Sodano, Henry A.

    2010-04-01

    The field of structural health monitoring (SHM) has made significant contributions in the field of prognosis and damage detection in the past decade. The advantageous use of this technology has not been integrated into operational structures to prevent damage from propagating or to heal injured regions under real time loading conditions. Rather, current systems relay this information to a central processor or human operator, who then determines a course of action such as altering the mission or scheduling repair maintenance. Biological systems exhibit advanced sensory and healing traits that can be applied to the design of material systems. For instance, bone is the major structural component in vertebrates; however, unlike modern structural materials, bone has many properties that make it effective for arresting the propagation of cracks and subsequent healing of the fractured area. The foremost goal for the development of future adaptive structures is to mimic biological systems, similar to bone, such that the material system can detect damage and deploy defensive traits to impede damage from propagating, thus preventing catastrophic failure while in operation. After sensing and stalling the propagation of damage, the structure must then be repaired autonomously using self healing mechanisms motivated by biological systems. Here a novel autonomous system is developed using shape memory polymers (SMPs), that employs an optical fiber network as both a damage detection sensor and a network to deliver stimulus to the damage site initiating adaptation and healing. In the presence of damage the fiber optic fractures allowing a high power laser diode to deposit a controlled level of thermal energy at the fractured sight locally reducing the modulus and blunting the crack tip, which significantly slows the crack growth rate. By applying a pre-induced strain field and utilizing the shape memory recovery effect, thermal energy can be deployed to close the crack and return

  12. A biologically inspired neural network controller for ballistic arm movements

    Directory of Open Access Journals (Sweden)

    Schmid Maurizio

    2007-09-01

    Full Text Available Abstract Background In humans, the implementation of multijoint tasks of the arm implies a highly complex integration of sensory information, sensorimotor transformations and motor planning. Computational models can be profitably used to better understand the mechanisms sub-serving motor control, thus providing useful perspectives and investigating different control hypotheses. To this purpose, the use of Artificial Neural Networks has been proposed to represent and interpret the movement of upper limb. In this paper, a neural network approach to the modelling of the motor control of a human arm during planar ballistic movements is presented. Methods The developed system is composed of three main computational blocks: 1 a parallel distributed learning scheme that aims at simulating the internal inverse model in the trajectory formation process; 2 a pulse generator, which is responsible for the creation of muscular synergies; and 3 a limb model based on two joints (two degrees of freedom and six muscle-like actuators, that can accommodate for the biomechanical parameters of the arm. The learning paradigm of the neural controller is based on a pure exploration of the working space with no feedback signal. Kinematics provided by the system have been compared with those obtained in literature from experimental data of humans. Results The model reproduces kinematics of arm movements, with bell-shaped wrist velocity profiles and approximately straight trajectories, and gives rise to the generation of synergies for the execution of movements. The model allows achieving amplitude and direction errors of respectively 0.52 cm and 0.2 radians. Curvature values are similar to those encountered in experimental measures with humans. The neural controller also manages environmental modifications such as the insertion of different force fields acting on the end-effector. Conclusion The proposed system has been shown to properly simulate the development of

  13. A Comparative Study of Biologically Inspired Walking Gaits through Waypoint Navigation

    Directory of Open Access Journals (Sweden)

    Umar Asif

    2011-01-01

    Full Text Available This paper investigates the locomotion of a walking robot by delivering a comparative study of three different biologically inspired walking gaits, namely: tripod, ripple, and wave, in terms of ground slippage they experience while walking. The objective of this study is to identify the gait model which experiences the minimum slippage while walking on a ground with a specific coefficient of friction. To accomplish this feat, the robot is steered over a reference path using a waypoint navigation algorithm, and the divergence of the robot from the reference path is investigated in terms of slip errors. Experiments are conducted through closed-loop simulations using an open dynamics engine which emphasizes the fact that due to uneven and unsymmetrical distribution of payload in tripod and ripple gait models, the robot experiences comparatively larger drift in these gaits than when using the wave gait model in which the distribution of payload is even and symmetrical on both sides of the robot body. The paper investigates this phenomenon on the basis of force distribution of supporting legs in each gait model.

  14. A computational model of conditioning inspired by Drosophila olfactory system.

    Science.gov (United States)

    Faghihi, Faramarz; Moustafa, Ahmed A; Heinrich, Ralf; Wörgötter, Florentin

    2017-03-01

    Recent studies have demonstrated that Drosophila melanogaster (briefly Drosophila) can successfully perform higher cognitive processes including second order olfactory conditioning. Understanding the neural mechanism of this behavior can help neuroscientists to unravel the principles of information processing in complex neural systems (e.g. the human brain) and to create efficient and robust robotic systems. In this work, we have developed a biologically-inspired spiking neural network which is able to execute both first and second order conditioning. Experimental studies demonstrated that volume signaling (e.g. by the gaseous transmitter nitric oxide) contributes to memory formation in vertebrates and invertebrates including insects. Based on the existing knowledge of odor encoding in Drosophila, the role of retrograde signaling in memory function, and the integration of synaptic and non-synaptic neural signaling, a neural system is implemented as Simulated fly. Simulated fly navigates in a two-dimensional environment in which it receives odors and electric shocks as sensory stimuli. The model suggests some experimental research on retrograde signaling to investigate neural mechanisms of conditioning in insects and other animals. Moreover, it illustrates a simple strategy to implement higher cognitive capabilities in machines including robots. Copyright © 2016 Elsevier Ltd. All rights reserved.

  15. Force sensitive carbon nanotube arrays for biologically inspired airflow sensing

    Science.gov (United States)

    Maschmann, Matthew R.; Dickinson, Ben; Ehlert, Gregory J.; Baur, Jeffery W.

    2012-09-01

    The compressive electromechanical response of aligned carbon nanotube (CNT) arrays is evaluated for use as an artificial hair sensor (AHS) transduction element. CNT arrays with heights of 12, 75, and 225 µm are examined. The quasi-static and dynamic sensitivity to force, response time, and signal drift are examined within the range of applied stresses predicted by a mechanical model applicable to the conceptual CNT array-based AHS (0-1 kPa). Each array is highly sensitive to compressive loading, with a maximum observed gauge factor of 114. The arrays demonstrate a repeatable response to dynamic cycling after a break-in period of approximately 50 cycles. Utilizing a four-wire measurement electrode configuration, the change in contact resistance between the array and the electrodes is observed to dominate the electromechanical response of the arrays. The response time of the CNT arrays is of the order of 10 ms. When the arrays are subjected to constant stress, mechanical creep is observed that results in a signal drift that generally diminishes the responsiveness of the arrays, particularly at stress approaching 1 kPa. The results of this study serve as a preliminary proof of concept for utilizing CNT arrays as a transduction mechanism for a proposed artificial hair sensor. Such a low profile and light-weight flow sensor is expected to have application in a number of applications including navigation and state awareness of small air vehicles, similar in function to natural hair cell receptors utilized by insects and bats.

  16. Biologically-inspired data decorrelation for hyper-spectral imaging

    Directory of Open Access Journals (Sweden)

    Ghita Ovidiu

    2011-01-01

    Full Text Available Abstract Hyper-spectral data allows the construction of more robust statistical models to sample the material properties than the standard tri-chromatic color representation. However, because of the large dimensionality and complexity of the hyper-spectral data, the extraction of robust features (image descriptors is not a trivial issue. Thus, to facilitate efficient feature extraction, decorrelation techniques are commonly applied to reduce the dimensionality of the hyper-spectral data with the aim of generating compact and highly discriminative image descriptors. Current methodologies for data decorrelation such as principal component analysis (PCA, linear discriminant analysis (LDA, wavelet decomposition (WD, or band selection methods require complex and subjective training procedures and in addition the compressed spectral information is not directly related to the physical (spectral characteristics associated with the analyzed materials. The major objective of this article is to introduce and evaluate a new data decorrelation methodology using an approach that closely emulates the human vision. The proposed data decorrelation scheme has been employed to optimally minimize the amount of redundant information contained in the highly correlated hyper-spectral bands and has been comprehensively evaluated in the context of non-ferrous material classification

  17. Force sensitive carbon nanotube arrays for biologically inspired airflow sensing

    International Nuclear Information System (INIS)

    Maschmann, Matthew R; Ehlert, Gregory J; Baur, Jeffery W; Dickinson, Ben

    2012-01-01

    The compressive electromechanical response of aligned carbon nanotube (CNT) arrays is evaluated for use as an artificial hair sensor (AHS) transduction element. CNT arrays with heights of 12, 75, and 225 µm are examined. The quasi-static and dynamic sensitivity to force, response time, and signal drift are examined within the range of applied stresses predicted by a mechanical model applicable to the conceptual CNT array-based AHS (0–1 kPa). Each array is highly sensitive to compressive loading, with a maximum observed gauge factor of 114. The arrays demonstrate a repeatable response to dynamic cycling after a break-in period of approximately 50 cycles. Utilizing a four-wire measurement electrode configuration, the change in contact resistance between the array and the electrodes is observed to dominate the electromechanical response of the arrays. The response time of the CNT arrays is of the order of 10 ms. When the arrays are subjected to constant stress, mechanical creep is observed that results in a signal drift that generally diminishes the responsiveness of the arrays, particularly at stress approaching 1 kPa. The results of this study serve as a preliminary proof of concept for utilizing CNT arrays as a transduction mechanism for a proposed artificial hair sensor. Such a low profile and light-weight flow sensor is expected to have application in a number of applications including navigation and state awareness of small air vehicles, similar in function to natural hair cell receptors utilized by insects and bats. (paper)

  18. Astrophysical constraints on unparticle-inspired models of gravity

    International Nuclear Information System (INIS)

    Bertolami, O.; Paramos, J.; Santos, P.

    2009-01-01

    We use stellar dynamics arguments to constrain the relevant parameters of unparticle-inspired models of gravity. We show that resulting bounds do constrain the parameters of the theory of unparticles, as far as its energy scale satisfies the condition Λ U ≥1 TeV and d U is close to unity.

  19. Design of a biologically inspired lower limb exoskeleton for human gait rehabilitation.

    Science.gov (United States)

    Lyu, Mingxing; Chen, Weihai; Ding, Xilun; Wang, Jianhua; Bai, Shaoping; Ren, Huichao

    2016-10-01

    This paper proposes a novel bionic model of the human leg according to the theory of physiology. Based on this model, we present a biologically inspired 3-degree of freedom (DOF) lower limb exoskeleton for human gait rehabilitation, showing that the lower limb exoskeleton is fully compatible with the human knee joint. The exoskeleton has a hybrid serial-parallel kinematic structure consisting of a 1-DOF hip joint module and a 2-DOF knee joint module in the sagittal plane. A planar 2-DOF parallel mechanism is introduced in the design to fully accommodate the motion of the human knee joint, which features not only rotation but also relative sliding. Therefore, the design is consistent with the requirements of bionics. The forward and inverse kinematic analysis is studied and the workspace of the exoskeleton is analyzed. The structural parameters are optimized to obtain a larger workspace. The results using MATLAB-ADAMS co-simulation are shown in this paper to demonstrate the feasibility of our design. A prototype of the exoskeleton is also developed and an experiment performed to verify the kinematic analysis. Compared with existing lower limb exoskeletons, the designed mechanism has a large workspace, while allowing knee joint rotation and small amount of sliding.

  20. Design of a biologically inspired lower limb exoskeleton for human gait rehabilitation

    Science.gov (United States)

    Lyu, Mingxing; Chen, Weihai; Ding, Xilun; Wang, Jianhua; Bai, Shaoping; Ren, Huichao

    2016-10-01

    This paper proposes a novel bionic model of the human leg according to the theory of physiology. Based on this model, we present a biologically inspired 3-degree of freedom (DOF) lower limb exoskeleton for human gait rehabilitation, showing that the lower limb exoskeleton is fully compatible with the human knee joint. The exoskeleton has a hybrid serial-parallel kinematic structure consisting of a 1-DOF hip joint module and a 2-DOF knee joint module in the sagittal plane. A planar 2-DOF parallel mechanism is introduced in the design to fully accommodate the motion of the human knee joint, which features not only rotation but also relative sliding. Therefore, the design is consistent with the requirements of bionics. The forward and inverse kinematic analysis is studied and the workspace of the exoskeleton is analyzed. The structural parameters are optimized to obtain a larger workspace. The results using MATLAB-ADAMS co-simulation are shown in this paper to demonstrate the feasibility of our design. A prototype of the exoskeleton is also developed and an experiment performed to verify the kinematic analysis. Compared with existing lower limb exoskeletons, the designed mechanism has a large workspace, while allowing knee joint rotation and small amount of sliding.

  1. Can the superstring inspire the standard model

    Energy Technology Data Exchange (ETDEWEB)

    Ellis, J.; Enqvist, K.; Nanopoulos, D.V.; Olive, K.A.

    1988-02-01

    We discuss general features of models in which the E/sub 8/xE'/sub 8/ heterotic superstring is compactified on a specific Calabi-Yau manifold. The gauge group of rank-6 in four dimensions is supposed to be broken down at an intermediate scale m/sub I/ to the standard model group SU(3)/sub C/ x SU(2)/sub L/ x U(1)/sub Y/, as a result of two neutral scalar fields acquiring large vacuum expectations (vev's) in one of many flat directions of the effective potential. We find that it is difficult to generate such an intermediate scale by radiative symmetry breaking, whilst such models have prima facie problems with baryon decay mediated by massive particles and with non-perturbative behaviour of the gauge couplings, unless m/sub I/ > or approx. 10/sup 16/ GeV. Rapid baryon decay mediated by light particles, large neutrino masses, other ..delta..L not = 0 processes and flavour-changing neutral currents are generic features of these models. We illustrate these observations with explicit calculations in a number of different models given by vev's in different flat directions.

  2. Can the superstring inspire the standard model?

    International Nuclear Information System (INIS)

    Ellis, J.; Enqvist, K.; Nanopoulos, D.V.; Olive, K.A.

    1988-01-01

    We discuss general features of models in which the E 8 xE' 8 heterotic superstring is compactified on a specific Calabi-Yau manifold. The gauge group of rank-6 in four dimensions is supposed to be broken down at an intermediate scale m I to the standard model group SU(3) C x SU(2) L x U(1) Y , as a result of two neutral scalar fields acquiring large vacuum expectations (vev's) in one of many flat directions of the effective potential. We find that it is difficult to generate such an intermediate scale by radiative symmetry breaking, whilst such models have prima facie problems with baryon decay mediated by massive particles and with non-perturbative behaviour of the gauge couplings, unless m I > or approx. 10 16 GeV. Rapid baryon decay mediated by light particles, large neutrino masses, other ΔL ≠ 0 processes and flavour-changing neutral currents are generic features of these models. We illustrate these observations with explicit calculations in a number of different models given by vev's in different flat directions. (orig.)

  3. A Bio-Inspired QoS-Oriented Handover Model in Heterogeneous Wireless Networks

    Directory of Open Access Journals (Sweden)

    Daxin Tian

    2014-01-01

    Full Text Available We propose a bio-inspired model for making handover decision in heterogeneous wireless networks. It is based on an extended attractor selection model, which is biologically inspired by the self-adaptability and robustness of cellular response to the changes in dynamic environments. The goal of the proposed model is to guarantee multiple terminals’ satisfaction by meeting the QoS requirements of those terminals’ applications, and this model also attempts to ensure the fairness of network resources allocation, in the meanwhile, to enable the QoS-oriented handover decision adaptive to dynamic wireless environments. Some numerical simulations are preformed to validate our proposed bio-inspired model in terms of adaptive attractor selection in different noisy environments. And the results of some other simulations prove that the proposed handover scheme can adapt terminals’ network selection to the varying wireless environment and benefits the QoS of multiple terminal applications simultaneously and automatically. Furthermore, the comparative analysis also shows that the bio-inspired model outperforms the utility function based handover decision scheme in terms of ensuring a better QoS satisfaction and a better fairness of network resources allocation in dynamic heterogeneous wireless networks.

  4. QCD inspired bag model of quarkonium

    International Nuclear Information System (INIS)

    Hasenfratz, P.; Horgan, R.R.; Kuti, J.; Richard, J.M.

    1981-01-01

    The QCD motivated bag model is applied to heavy quark-antiquark systems. The effect of colored glue in the model is shown to explain the rapid cross-over of the static QQ potential from the asymptotically free Coulomb region into the linear confinement regime. The spin-dependent force between static quarks is derived in Coulomb gauge from the exchange of a confined transverse gluon. The dimensional bag parameter Λ/sub B/ = 235 MeV and the quark-gluon coupling constant α = 0.38 as defined at r/sub QQ/approx.0.2 fermi are determined from a good fit of the cc-bar and bb-bar spectra. The fit is in serious disagreement with the widely accepted MIT parameters. As an important test of our model, we calculate the rich spectrum of QQ glue states. In UPSILON particle spectroscopy we predict a narrow QQ glue state with exotic quantum numbers J/sup PC/ = 1 -+ below the BB threshold. Its experimental confirmation would be the first direct evidence for colored glue in the hadron spectrum

  5. QCD inspired bag model of quarkonium

    CERN Document Server

    Hasenfratz, Peter; Kuti, Julius; Richard, J M

    1981-01-01

    The QCD motivated bag model is applied to heavy quark-antiquark systems. The effect of colored glue in the model is shown to explain the rapid cross-over of the static QQ potential from the asymptotically free Coulomb region into the linear confinement regime. The spin-dependent force between static quarks is derived in Coulomb gauge from the exchange of a confined transverse gluon. The dimensional bag parameter Lambda /sub B/=235 MeV and the quark-gluon coupling constant alpha =0.38 as defined at r/sub QQ/ approximately 0.2 fermi are determined from a good fit of the cc and bb spectra. The fit is in serious disagreement with the widely accepted MIT parameters. As an important test of their model, the authors calculate the rich spectrum of QQ glue states. In Upsilon particle spectroscopy they predict a narrow QQglue state with exotic quantum numbers J/sup PC/=1/sup -+/ below the BB threshold. Its experimental confirmation would be the first direct evidence for colored glue in the hadron spectrum. (3 refs).

  6. Methodology for designing and manufacturing complex biologically inspired soft robotic fluidic actuators: prosthetic hand case study.

    Science.gov (United States)

    Thompson-Bean, E; Das, R; McDaid, A

    2016-10-31

    We present a novel methodology for the design and manufacture of complex biologically inspired soft robotic fluidic actuators. The methodology is applied to the design and manufacture of a prosthetic for the hand. Real human hands are scanned to produce a 3D model of a finger, and pneumatic networks are implemented within it to produce a biomimetic bending motion. The finger is then partitioned into material sections, and a genetic algorithm based optimization, using finite element analysis, is employed to discover the optimal material for each section. This is based on two biomimetic performance criteria. Two sets of optimizations using two material sets are performed. Promising optimized material arrangements are fabricated using two techniques to validate the optimization routine, and the fabricated and simulated results are compared. We find that the optimization is successful in producing biomimetic soft robotic fingers and that fabrication of the fingers is possible. Limitations and paths for development are discussed. This methodology can be applied for other fluidic soft robotic devices.

  7. A biologically inspired controller to solve the coverage problem in robotics.

    Science.gov (United States)

    Rañó, Iñaki; Santos, José A

    2017-06-05

    The coverage problem consists on computing a path or trajectory for a robot to pass over all the points in some free area and has applications ranging from floor cleaning to demining. Coverage is solved as a planning problem-providing theoretical validation of the solution-or through heuristic techniques which rely on experimental validation. Through a combination of theoretical results and simulations, this paper presents a novel solution to the coverage problem that exploits the chaotic behaviour of a simple biologically inspired motion controller, the Braitenberg vehicle 2b. Although chaos has been used for coverage, our approach has much less restrictive assumptions about the environment and can be implemented using on-board sensors. First, we prove theoretically that this vehicle-a well known model of animal tropotaxis-behaves as a charge in an electro-magnetic field. The motion equations can be reduced to a Hamiltonian system, and, therefore the vehicle follows quasi-periodic or chaotic trajectories, which pass arbitrarily close to any point in the work-space, i.e. it solves the coverage problem. Secondly, through a set of extensive simulations, we show that the trajectories cover regions of bounded workspaces, and full coverage is achieved when the perceptual range of the vehicle is short. We compare the performance of this new approach with different types of random motion controllers in the same bounded environments.

  8. BiLBIQ A Biologically Inspired Robot with Walking and Rolling Locomotion

    CERN Document Server

    King, Ralf Simon

    2013-01-01

    The book ‘BiLBIQ: A biologically inspired Robot with walking and rolling locomotion’ deals with implementing a locomotion behavior observed in the biological archetype Cebrennus villosus to a robot prototype whose structural design needs to be developed.   The biological sample is investigated as far as possible and compared to other evolutional solutions within the framework of nature’s inventions. Current achievements in robotics are examined and evaluated for their relation and relevance to the robot prototype in question. An overview of what is state of the art in actuation ensures the choice of the hardware available and most suitable for this project. Through a constant consideration of the achievement of two fundamentally different ways of locomotion with one and the same structure, a robot design is developed and constructed taking hardware constraints into account. The development of a special leg structure that needs to resemble and replace body elements of the biological archetype is a speci...

  9. An Immune-inspired Adaptive Automated Intrusion Response System Model

    Directory of Open Access Journals (Sweden)

    Ling-xi Peng

    2012-09-01

    Full Text Available An immune-inspired adaptive automated intrusion response system model, named as , is proposed. The descriptions of self, non-self, immunocyte, memory detector, mature detector and immature detector of the network transactions, and the realtime network danger evaluation equations are given. Then, the automated response polices are adaptively performed or adjusted according to the realtime network danger. Thus, not only accurately evaluates the network attacks, but also greatly reduces the response times and response costs.

  10. Superstring-inspired SO(10) GUT model with intermediate scale

    Science.gov (United States)

    Sasaki, Ken

    1987-12-01

    A new mechanism is proposed for the mixing of Weinberg-Salam Higgs fields in superstring-inspired SO(10) models with no SO(10) singlet fields. The higher-dimensional terms in the superpotential can generate both Higgs field mixing and a small mass for the physical neutrino. I would like to thank Professor C. Iso for hospitality extended to me at the Tokyo Institute of Technology.

  11. Comparing novelty of designs from biological-inspiration with those from brainstorming

    DEFF Research Database (Denmark)

    Keshwani, Sonal; Lenau, Torben Anker; Ahmed-Kristensen, Saeema

    2017-01-01

    This research aims to understand the significance of biological-analogies in fostering novelty by comparing biological-analogies with other design methods for idea generation. Among other design methods, brainstorming was chosen here as benchmark. Four studies were conducted to compare: (i......) the levels of abstraction at which concepts were ideated using biological inspiration (represented using biocards) with that using traditional brainstorming; and (ii) the novelty of concepts produced by using these two design methods. Concepts produced in these studies were evaluated for levels...... of abstraction at which they were ideated, average novelty, and proportion of high-novelty concepts. Results suggest that concepts generated using biocards were ideated at higher abstraction levels than those using brainstorming, but neither were at the highest abstraction levels. The average novelty of concepts...

  12. Biologically-inspired On-chip Learning in Pulsed Neural Networks

    DEFF Research Database (Denmark)

    Lehmann, Torsten; Woodburn, Robin

    1999-01-01

    Self-learning chips to implement many popular ANN (artificial neural network) algorithms are very difficult to design. We explain why this is so and say what lessons previous work teaches us in the design of self-learning systems. We offer a contribution to the "biologically-inspired" approach......, explaining what we mean by this term and providing an example of a robust, self-learning design that can solve simple classical-conditioning tasks, We give details of the design of individual circuits to perform component functions, which can then be combined into a network to solve the task. We argue...

  13. Models for synthetic biology.

    Science.gov (United States)

    Kaznessis, Yiannis N

    2007-11-06

    Synthetic biological engineering is emerging from biology as a distinct discipline based on quantification. The technologies propelling synthetic biology are not new, nor is the concept of designing novel biological molecules. What is new is the emphasis on system behavior. The objective is the design and construction of new biological devices and systems to deliver useful applications. Numerous synthetic gene circuits have been created in the past decade, including bistable switches, oscillators, and logic gates, and possible applications abound, including biofuels, detectors for biochemical and chemical weapons, disease diagnosis, and gene therapies. More than fifty years after the discovery of the molecular structure of DNA, molecular biology is mature enough for real quantification that is useful for biological engineering applications, similar to the revolution in modeling in chemistry in the 1950s. With the excitement that synthetic biology is generating, the engineering and biological science communities appear remarkably willing to cross disciplinary boundaries toward a common goal.

  14. Adaptation of sensor morphology: an integrative view of perception from biologically inspired robotics perspective

    Science.gov (United States)

    Nurzaman, Surya G.

    2016-01-01

    Sensor morphology, the morphology of a sensing mechanism which plays a role of shaping the desired response from physical stimuli from surroundings to generate signals usable as sensory information, is one of the key common aspects of sensing processes. This paper presents a structured review of researches on bioinspired sensor morphology implemented in robotic systems, and discusses the fundamental design principles. Based on literature review, we propose two key arguments: first, owing to its synthetic nature, biologically inspired robotics approach is a unique and powerful methodology to understand the role of sensor morphology and how it can evolve and adapt to its task and environment. Second, a consideration of an integrative view of perception by looking into multidisciplinary and overarching mechanisms of sensor morphology adaptation across biology and engineering enables us to extract relevant design principles that are important to extend our understanding of the unfinished concepts in sensing and perception. PMID:27499843

  15. Biology and Architecture: Two Buildings Inspired by the Anatomy of the Visual System.

    Science.gov (United States)

    Maro Kiris, Irem

    2018-05-04

    Architectural production has been influenced by a variety of sources. Forms derived from nature, biology and live organisms, had often been utilised in art and architecture. Certain features of the human anatomy had been reflected in design process in various ways, as imitations, abstractions, interpretations of the reality. The correlation of ideal proportions had been investigated throughout centuries. Scholars, art historians starting with Vitruvius from the world of ancient Roman architecture, described the human figure as being the principal source of proportion among the classical orders of architecture. This study aims to investigate two contemporary buildings, namely Kiasma Museum in Helsinki and Eye Museum in Amsterdam, inspired directly from the anatomy of visual system. Morover the author discussed the relationship of biology and architecture through these two special buildings by viewing the eye and chiasma as metaphors for elements of architecture.

  16. Laboratory of Biological Modeling

    Data.gov (United States)

    Federal Laboratory Consortium — The Laboratory of Biological Modeling is defined by both its methodologies and its areas of application. We use mathematical modeling in many forms and apply it to a...

  17. Design and Dynamic Model of a Frog-inspired Swimming Robot Powered by Pneumatic Muscles

    Science.gov (United States)

    Fan, Ji-Zhuang; Zhang, Wei; Kong, Peng-Cheng; Cai, He-Gao; Liu, Gang-Feng

    2017-09-01

    Pneumatic muscles with similar characteristics to biological muscles have been widely used in robots, and thus are promising drivers for frog inspired robots. However, the application and nonlinearity of the pneumatic system limit the advance. On the basis of the swimming mechanism of the frog, a frog-inspired robot based on pneumatic muscles is developed. To realize the independent tasks by the robot, a pneumatic system with internal chambers, micro air pump, and valves is implemented. The micro pump is used to maintain the pressure difference between the source and exhaust chambers. The pneumatic muscles are controlled by high-speed switch valves which can reduce the robot cost, volume, and mass. A dynamic model of the pneumatic system is established for the simulation to estimate the system, including the chamber, muscle, and pneumatic circuit models. The robot design is verified by the robot swimming experiments and the dynamic model is verified through the experiments and simulations of the pneumatic system. The simulation results are compared to analyze the functions of the source pressure, internal volume of the muscle, and circuit flow rate which is proved the main factor that limits the response of muscle pressure. The proposed research provides the application of the pneumatic muscles in the frog inspired robot and the pneumatic model to study muscle controller.

  18. Dark matter in a constrained E6 inspired SUSY model

    International Nuclear Information System (INIS)

    Athron, P.; Harries, D.; Nevzorov, R.; Williams, A.G.

    2016-01-01

    We investigate dark matter in a constrained E 6 inspired supersymmetric model with an exact custodial symmetry and compare with the CMSSM. The breakdown of E 6 leads to an additional U(1) N symmetry and a discrete matter parity. The custodial and matter symmetries imply there are two stable dark matter candidates, though one may be extremely light and contribute negligibly to the relic density. We demonstrate that a predominantly Higgsino, or mixed bino-Higgsino, neutralino can account for all of the relic abundance of dark matter, while fitting a 125 GeV SM-like Higgs and evading LHC limits on new states. However we show that the recent LUX 2016 limit on direct detection places severe constraints on the mixed bino-Higgsino scenarios that explain all of the dark matter. Nonetheless we still reveal interesting scenarios where the gluino, neutralino and chargino are light and discoverable at the LHC, but the full relic abundance is not accounted for. At the same time we also show that there is a huge volume of parameter space, with a predominantly Higgsino dark matter candidate that explains all the relic abundance, that will be discoverable with XENON1T. Finally we demonstrate that for the E 6 inspired model the exotic leptoquarks could still be light and within range of future LHC searches.

  19. Thermo-fluidic devices and materials inspired from mass and energy transport phenomena in biological system

    Institute of Scientific and Technical Information of China (English)

    Jian XIAO; Jing LIU

    2009-01-01

    Mass and energy transport consists of one of the most significant physiological processes in nature, which guarantees many amazing biological phenomena and activ-ities. Borrowing such idea, many state-of-the-art thermo-fluidic devices and materials such as artificial kidneys, carrier erythrocyte, blood substitutes and so on have been successfully invented. Besides, new emerging technologies are still being developed. This paper is dedicated to present-ing a relatively complete review of the typical devices and materials in clinical use inspired by biological mass and energy transport mechanisms. Particularly, these artificial thermo-fluidic devices and materials will be categorized into organ transplantation, drug delivery, nutrient transport, micro operation, and power supply. Potential approaches for innovating conventional technologies were discussed, corresponding biological phenomena and physical mechan-isms were interpreted, future promising mass-and-energy-transport-based bionic devices were suggested, and prospects along this direction were pointed out. It is expected that many artificial devices based on biological mass and energy transport principle will appear to better improve vari-ous fields related to human life in the near future.

  20. A new landing impact attenuation seat in manned spacecraft biologically-inspired by felids

    Directory of Open Access Journals (Sweden)

    Yu Hui

    2015-04-01

    Full Text Available When manned spacecraft comes back to the earth, it relies on the impact attenuation seat to protect astronauts from injuries during landing phase. Hence, the seat needs to transfer impact load, as small as possible, to the crew. However, there is little room left for traditional seat to improve further. Herein, a new seat system biologically-inspired by felids’ landing is proposed. Firstly, a series of experiments was carried out on cats and tigers, in which they were trained to jump down voluntarily from different heights. Based on the ground reaction forces combined with kinematics, the experiment indicated that felids’ landing after self-initial jump was a multi-step impact attenuation process and the new seat was inspired by this. Then the construction and work process of new seat were redesigned to realize the multi-step impact attenuation. The dynamic response of traditional and new seat is analyzed under the identical conditions and the results show that the new concept seat can significantly weaken the occupant overload in two directions compared with that of traditional seat. As a consequence, the risk of injury evaluated for spinal and head is also lowered, meaning a higher level of protection which is especially beneficial to the debilitated astronaut.

  1. Actions, Observations, and Decision-Making: Biologically Inspired Strategies for Autonomous Aerial Vehicles

    Science.gov (United States)

    Pisanich, Greg; Ippolito, Corey; Plice, Laura; Young, Larry A.; Lau, Benton

    2003-01-01

    This paper details the development and demonstration of an autonomous aerial vehicle embodying search and find mission planning and execution srrategies inspired by foraging behaviors found in biology. It begins by describing key characteristics required by an aeria! explorer to support science and planetary exploration goals, and illustrates these through a hypothetical mission profile. It next outlines a conceptual bio- inspired search and find autonomy architecture that implements observations, decisions, and actions through an "ecology" of producer, consumer, and decomposer agents. Moving from concepts to development activities, it then presents the results of mission representative UAV aerial surveys at a Mars analog site. It next describes hardware and software enhancements made to a commercial small fixed-wing UAV system, which inc!nde a ncw dpvelopnent architecture that also provides hardware in the loop simulation capability. After presenting the results of simulated and actual flights of bioinspired flight algorithms, it concludes with a discussion of future development to include an expansion of system capabilities and field science support.

  2. Soft robotic arm inspired by the octopus: I. From biological functions to artificial requirements

    International Nuclear Information System (INIS)

    Margheri, L; Laschi, C; Mazzolai, B

    2012-01-01

    Octopuses are molluscs that belong to the group Cephalopoda. They lack joints and rigid links, and as a result, their arms possess virtually limitless freedom of movement. These flexible appendages exhibit peculiar biomechanical features such as stiffness control, compliance, and high flexibility and dexterity. Studying the capabilities of the octopus arm is a complex task that presents a challenge for both biologists and roboticists, the latter of whom draw inspiration from the octopus in designing novel technologies within soft robotics. With this idea in mind, in this study, we used new, purposively developed methods of analysing the octopus arm in vivo to create new biologically inspired design concepts. Our measurements showed that the octopus arm can elongate by 70% in tandem with a 23% diameter reduction and exhibits an average pulling force of 40 N. The arm also exhibited a 20% mean shortening at a rate of 17.1 mm s −1 and a longitudinal stiffening rate as high as 2 N (mm s) −1 . Using histology and ultrasounds, we investigated the functional morphology of the internal tissues, including the sinusoidal arrangement of the nerve cord and the local insertion points of the longitudinal and transverse muscle fibres. The resulting information was used to create novel design principles and specifications that can in turn be used in developing a new soft robotic arm. (paper)

  3. Soft robotic arm inspired by the octopus: I. From biological functions to artificial requirements.

    Science.gov (United States)

    Margheri, L; Laschi, C; Mazzolai, B

    2012-06-01

    Octopuses are molluscs that belong to the group Cephalopoda. They lack joints and rigid links, and as a result, their arms possess virtually limitless freedom of movement. These flexible appendages exhibit peculiar biomechanical features such as stiffness control, compliance, and high flexibility and dexterity. Studying the capabilities of the octopus arm is a complex task that presents a challenge for both biologists and roboticists, the latter of whom draw inspiration from the octopus in designing novel technologies within soft robotics. With this idea in mind, in this study, we used new, purposively developed methods of analysing the octopus arm in vivo to create new biologically inspired design concepts. Our measurements showed that the octopus arm can elongate by 70% in tandem with a 23% diameter reduction and exhibits an average pulling force of 40 N. The arm also exhibited a 20% mean shortening at a rate of 17.1 mm s(-1) and a longitudinal stiffening rate as high as 2 N (mm s)(-1). Using histology and ultrasounds, we investigated the functional morphology of the internal tissues, including the sinusoidal arrangement of the nerve cord and the local insertion points of the longitudinal and transverse muscle fibres. The resulting information was used to create novel design principles and specifications that can in turn be used in developing a new soft robotic arm.

  4. Biologically-Inspired Concepts for Autonomic Self-Protection in Multiagent Systems

    Science.gov (United States)

    Sterritt, Roy; Hinchey, Mike

    2006-01-01

    Biologically-inspired autonomous and autonomic systems (AAS) are essentially concerned with creating self-directed and self-managing systems based on metaphors &om nature and the human body, such as the autonomic nervous system. Agent technologies have been identified as a key enabler for engineering autonomy and autonomicity in systems, both in terms of retrofitting into legacy systems and in designing new systems. Handing over responsibility to systems themselves raises concerns for humans with regard to safety and security. This paper reports on the continued investigation into a strand of research on how to engineer self-protection mechanisms into systems to assist in encouraging confidence regarding security when utilizing autonomy and autonomicity. This includes utilizing the apoptosis and quiescence metaphors to potentially provide a self-destruct or self-sleep signal between autonomic agents when needed, and an ALice signal to facilitate self-identification and self-certification between anonymous autonomous agents and systems.

  5. Computational intelligence in multi-feature visual pattern recognition hand posture and face recognition using biologically inspired approaches

    CERN Document Server

    Pisharady, Pramod Kumar; Poh, Loh Ai

    2014-01-01

    This book presents a collection of computational intelligence algorithms that addresses issues in visual pattern recognition such as high computational complexity, abundance of pattern features, sensitivity to size and shape variations and poor performance against complex backgrounds. The book has 3 parts. Part 1 describes various research issues in the field with a survey of the related literature. Part 2 presents computational intelligence based algorithms for feature selection and classification. The algorithms are discriminative and fast. The main application area considered is hand posture recognition. The book also discusses utility of these algorithms in other visual as well as non-visual pattern recognition tasks including face recognition, general object recognition and cancer / tumor classification. Part 3 presents biologically inspired algorithms for feature extraction. The visual cortex model based features discussed have invariance with respect to appearance and size of the hand, and provide good...

  6. A biologically inspired neural net for trajectory formation and obstacle avoidance.

    Science.gov (United States)

    Glasius, R; Komoda, A; Gielen, S C

    1996-06-01

    In this paper we present a biologically inspired two-layered neural network for trajectory formation and obstacle avoidance. The two topographically ordered neural maps consist of analog neurons having continuous dynamics. The first layer, the sensory map, receives sensory information and builds up an activity pattern which contains the optimal solution (i.e. shortest path without collisions) for any given set of current position, target positions and obstacle positions. Targets and obstacles are allowed to move, in which case the activity pattern in the sensory map will change accordingly. The time evolution of the neural activity in the second layer, the motor map, results in a moving cluster of activity, which can be interpreted as a population vector. Through the feedforward connections between the two layers, input of the sensory map directs the movement of the cluster along the optimal path from the current position of the cluster to the target position. The smooth trajectory is the result of the intrinsic dynamics of the network only. No supervisor is required. The output of the motor map can be used for direct control of an autonomous system in a cluttered environment or for control of the actuators of a biological limb or robot manipulator. The system is able to reach a target even in the presence of an external perturbation. Computer simulations of a point robot and a multi-joint manipulator illustrate the theory.

  7. Biologically-inspired approaches for self-organization, adaptation, and collaboration of heterogeneous autonomous systems

    Science.gov (United States)

    Steinberg, Marc

    2011-06-01

    This paper presents a selective survey of theoretical and experimental progress in the development of biologicallyinspired approaches for complex surveillance and reconnaissance problems with multiple, heterogeneous autonomous systems. The focus is on approaches that may address ISR problems that can quickly become mathematically intractable or otherwise impractical to implement using traditional optimization techniques as the size and complexity of the problem is increased. These problems require dealing with complex spatiotemporal objectives and constraints at a variety of levels from motion planning to task allocation. There is also a need to ensure solutions are reliable and robust to uncertainty and communications limitations. First, the paper will provide a short introduction to the current state of relevant biological research as relates to collective animal behavior. Second, the paper will describe research on largely decentralized, reactive, or swarm approaches that have been inspired by biological phenomena such as schools of fish, flocks of birds, ant colonies, and insect swarms. Next, the paper will discuss approaches towards more complex organizational and cooperative mechanisms in team and coalition behaviors in order to provide mission coverage of large, complex areas. Relevant team behavior may be derived from recent advances in understanding of the social and cooperative behaviors used for collaboration by tens of animals with higher-level cognitive abilities such as mammals and birds. Finally, the paper will briefly discuss challenges involved in user interaction with these types of systems.

  8. A bio-inspired memory model for structural health monitoring

    Science.gov (United States)

    Zheng, Wei; Zhu, Yong

    2009-04-01

    Long-term structural health monitoring (SHM) systems need intelligent management of the monitoring data. By analogy with the way the human brain processes memories, we present a bio-inspired memory model (BIMM) that does not require prior knowledge of the structure parameters. The model contains three time-domain areas: a sensory memory area, a short-term memory area and a long-term memory area. First, the initial parameters of the structural state are specified to establish safety criteria. Then the large amount of monitoring data that falls within the safety limits is filtered while the data outside the safety limits are captured instantly in the sensory memory area. Second, disturbance signals are distinguished from danger signals in the short-term memory area. Finally, the stable data of the structural balance state are preserved in the long-term memory area. A strategy for priority scheduling via fuzzy c-means for the proposed model is then introduced. An experiment on bridge tower deformation demonstrates that the proposed model can be applied for real-time acquisition, limited-space storage and intelligent mining of the monitoring data in a long-term SHM system.

  9. A bio-inspired memory model for structural health monitoring

    International Nuclear Information System (INIS)

    Zheng, Wei; Zhu, Yong

    2009-01-01

    Long-term structural health monitoring (SHM) systems need intelligent management of the monitoring data. By analogy with the way the human brain processes memories, we present a bio-inspired memory model (BIMM) that does not require prior knowledge of the structure parameters. The model contains three time-domain areas: a sensory memory area, a short-term memory area and a long-term memory area. First, the initial parameters of the structural state are specified to establish safety criteria. Then the large amount of monitoring data that falls within the safety limits is filtered while the data outside the safety limits are captured instantly in the sensory memory area. Second, disturbance signals are distinguished from danger signals in the short-term memory area. Finally, the stable data of the structural balance state are preserved in the long-term memory area. A strategy for priority scheduling via fuzzy c-means for the proposed model is then introduced. An experiment on bridge tower deformation demonstrates that the proposed model can be applied for real-time acquisition, limited-space storage and intelligent mining of the monitoring data in a long-term SHM system

  10. Utilization and viability of biologically-inspired algorithms in a dynamic multiagent camera surveillance system

    Science.gov (United States)

    Mundhenk, Terrell N.; Dhavale, Nitin; Marmol, Salvador; Calleja, Elizabeth; Navalpakkam, Vidhya; Bellman, Kirstie; Landauer, Chris; Arbib, Michael A.; Itti, Laurent

    2003-10-01

    computational resources. The system demonstrates the viability of biologically inspired systems in a real time tracking. In future work we plan on implementing additional biological mechanisms for cooperative management of both the sensor and processing resources in this system that include top down biasing for target specificity as well as novelty and the activity of the tracked object in relation to sensitive features of the environment.

  11. A biologically inspired artificial fish using flexible matrix composite actuators: analysis and experiment

    International Nuclear Information System (INIS)

    Zhang, Zhiye; Philen, Michael; Neu, Wayne

    2010-01-01

    A bio-inspired prototype fish using the flexible matrix composite (FMC) muscle technology for fin and body actuation is developed. FMC actuators are pressure driven muscle-like actuators capable of large displacements as well as large blocking forces. An analytical model of the artificial fish using FMC actuators is developed and analysis results are presented. An experimental prototype of the artificial fish having FMC artificial muscles has been completed and tested. Constant mean thrusts have been achieved in the laboratory for a stationary fish for different undulation frequencies around 1 Hz. The experimental results demonstrate that a nearly constant thrust can be achieved through tuning of excitation frequency for given body stiffness. Free swimming results show that the prototype can swim at approximately 0.3 m s −1

  12. Biologically inspired robotic inspectors: the engineering reality and future outlook (Keynote address)

    Science.gov (United States)

    Bar-Cohen, Yoseph

    2005-04-01

    Human errors have long been recognized as a major factor in the reliability of nondestructive evaluation results. To minimize such errors, there is an increasing reliance on automatic inspection tools that allow faster and consistent tests. Crawlers and various manipulation devices are commonly used to perform variety of inspection procedures that include C-scan with contour following capability to rapidly inspect complex structures. The emergence of robots has been the result of the need to deal with parts that are too complex to handle by a simple automatic system. Economical factors are continuing to hamper the wide use of robotics for inspection applications however technology advances are increasingly changing this paradigm. Autonomous robots, which may look like human, can potentially address the need to inspect structures with configuration that are not predetermined. The operation of such robots that mimic biology may take place at harsh or hazardous environments that are too dangerous for human presence. Biomimetic technologies such as artificial intelligence, artificial muscles, artificial vision and numerous others are increasingly becoming common engineering tools. Inspired by science fiction, making biomimetic robots is increasingly becoming an engineering reality and in this paper the state-of-the-art will be reviewed and the outlook for the future will be discussed.

  13. A Synthetic-Biology-Inspired Therapeutic Strategy for Targeting and Treating Hepatogenous Diabetes.

    Science.gov (United States)

    Xue, Shuai; Yin, Jianli; Shao, Jiawei; Yu, Yuanhuan; Yang, Linfeng; Wang, Yidan; Xie, Mingqi; Fussenegger, Martin; Ye, Haifeng

    2017-02-01

    Hepatogenous diabetes is a complex disease that is typified by the simultaneous presence of type 2 diabetes and many forms of liver disease. The chief pathogenic determinant in this pathophysiological network is insulin resistance (IR), an asymptomatic disease state in which impaired insulin signaling in target tissues initiates a variety of organ dysfunctions. However, pharmacotherapies targeting IR remain limited and are generally inapplicable for liver disease patients. Oleanolic acid (OA) is a plant-derived triterpenoid that is frequently used in Chinese medicine as a safe but slow-acting treatment in many liver disorders. Here, we utilized the congruent pharmacological activities of OA and glucagon-like-peptide 1 (GLP-1) in relieving IR and improving liver and pancreas functions and used a synthetic-biology-inspired design principle to engineer a therapeutic gene circuit that enables a concerted action of both drugs. In particular, OA-triggered short human GLP-1 (shGLP-1) expression in hepatogenous diabetic mice rapidly and simultaneously attenuated many disease-specific metabolic failures, whereas OA or shGLP-1 monotherapy failed to achieve corresponding therapeutic effects. Collectively, this work shows that rationally engineered synthetic gene circuits are capable of treating multifactorial diseases in a synergistic manner by multiplexing the targeting efficacies of single therapeutics. Copyright © 2017 The American Society of Gene and Cell Therapy. Published by Elsevier Inc. All rights reserved.

  14. Biologically inspired multi-layered synthetic skin for tactile feedback in prosthetic limbs.

    Science.gov (United States)

    Osborn, Luke; Nguyen, Harrison; Betthauser, Joseph; Kaliki, Rahul; Thakor, Nitish

    2016-08-01

    The human body offers a template for many state-of-the-art prosthetic devices and sensors. In this work, we present a novel, sensorized synthetic skin that mimics the natural multi-layered nature of mechanoreceptors found in healthy glabrous skin to provide tactile information. The multi-layered sensor is made up of flexible piezoresistive textiles that act as force sensitive resistors (FSRs) to convey tactile information, which are embedded within a silicone rubber to resemble the compliant nature of human skin. The top layer of the synthetic skin is capable of detecting small loads less than 5 N whereas the bottom sensing layer responds reliably to loads over 7 N. Finite element analysis (FEA) of a simplified human fingertip and the synthetic skin was performed. Results suggest similarities in behavior during loading. A natural tactile event is simulated by loading the synthetic skin on a prosthetic limb. Results show the sensors' ability to detect applied loads as well as the ability to simulate neural spiking activity based on the derivative and temporal differences of the sensor response. During the tactile loading, the top sensing layer responded 0.24 s faster than the bottom sensing layer. A synthetic biologically-inspired skin such as this will be useful for enhancing the functionality of prosthetic limbs through tactile feedback.

  15. A Biologically Inspired Approach to Frequency Domain Feature Extraction for EEG Classification

    Directory of Open Access Journals (Sweden)

    Nurhan Gursel Ozmen

    2018-01-01

    Full Text Available Classification of electroencephalogram (EEG signal is important in mental decoding for brain-computer interfaces (BCI. We introduced a feature extraction approach based on frequency domain analysis to improve the classification performance on different mental tasks using single-channel EEG. This biologically inspired method extracts the most discriminative spectral features from power spectral densities (PSDs of the EEG signals. We applied our method on a dataset of six subjects who performed five different imagination tasks: (i resting state, (ii mental arithmetic, (iii imagination of left hand movement, (iv imagination of right hand movement, and (v imagination of letter “A.” Pairwise and multiclass classifications were performed in single EEG channel using Linear Discriminant Analysis and Support Vector Machines. Our method produced results (mean classification accuracy of 83.06% for binary classification and 91.85% for multiclassification that are on par with the state-of-the-art methods, using single-channel EEG with low computational cost. Among all task pairs, mental arithmetic versus letter imagination yielded the best result (mean classification accuracy of 90.29%, indicating that this task pair could be the most suitable pair for a binary class BCI. This study contributes to the development of single-channel BCI, as well as finding the best task pair for user defined applications.

  16. 16th International Conference on Hybrid Intelligent Systems and the 8th World Congress on Nature and Biologically Inspired Computing

    CERN Document Server

    Haqiq, Abdelkrim; Alimi, Adel; Mezzour, Ghita; Rokbani, Nizar; Muda, Azah

    2017-01-01

    This book presents the latest research in hybrid intelligent systems. It includes 57 carefully selected papers from the 16th International Conference on Hybrid Intelligent Systems (HIS 2016) and the 8th World Congress on Nature and Biologically Inspired Computing (NaBIC 2016), held on November 21–23, 2016 in Marrakech, Morocco. HIS - NaBIC 2016 was jointly organized by the Machine Intelligence Research Labs (MIR Labs), USA; Hassan 1st University, Settat, Morocco and University of Sfax, Tunisia. Hybridization of intelligent systems is a promising research field in modern artificial/computational intelligence and is concerned with the development of the next generation of intelligent systems. The conference’s main aim is to inspire further exploration of the intriguing potential of hybrid intelligent systems and bio-inspired computing. As such, the book is a valuable resource for practicing engineers /scientists and researchers working in the field of computational intelligence and artificial intelligence.

  17. A Probabilistic Recommendation Method Inspired by Latent Dirichlet Allocation Model

    Directory of Open Access Journals (Sweden)

    WenBo Xie

    2014-01-01

    Full Text Available The recent decade has witnessed an increasing popularity of recommendation systems, which help users acquire relevant knowledge, commodities, and services from an overwhelming information ocean on the Internet. Latent Dirichlet Allocation (LDA, originally presented as a graphical model for text topic discovery, now has found its application in many other disciplines. In this paper, we propose an LDA-inspired probabilistic recommendation method by taking the user-item collecting behavior as a two-step process: every user first becomes a member of one latent user-group at a certain probability and each user-group will then collect various items with different probabilities. Gibbs sampling is employed to approximate all the probabilities in the two-step process. The experiment results on three real-world data sets MovieLens, Netflix, and Last.fm show that our method exhibits a competitive performance on precision, coverage, and diversity in comparison with the other four typical recommendation methods. Moreover, we present an approximate strategy to reduce the computing complexity of our method with a slight degradation of the performance.

  18. A biological inspired fuzzy adaptive window median filter (FAWMF) for enhancing DNA signal processing.

    Science.gov (United States)

    Ahmad, Muneer; Jung, Low Tan; Bhuiyan, Al-Amin

    2017-10-01

    Digital signal processing techniques commonly employ fixed length window filters to process the signal contents. DNA signals differ in characteristics from common digital signals since they carry nucleotides as contents. The nucleotides own genetic code context and fuzzy behaviors due to their special structure and order in DNA strand. Employing conventional fixed length window filters for DNA signal processing produce spectral leakage and hence results in signal noise. A biological context aware adaptive window filter is required to process the DNA signals. This paper introduces a biological inspired fuzzy adaptive window median filter (FAWMF) which computes the fuzzy membership strength of nucleotides in each slide of window and filters nucleotides based on median filtering with a combination of s-shaped and z-shaped filters. Since coding regions cause 3-base periodicity by an unbalanced nucleotides' distribution producing a relatively high bias for nucleotides' usage, such fundamental characteristic of nucleotides has been exploited in FAWMF to suppress the signal noise. Along with adaptive response of FAWMF, a strong correlation between median nucleotides and the Π shaped filter was observed which produced enhanced discrimination between coding and non-coding regions contrary to fixed length conventional window filters. The proposed FAWMF attains a significant enhancement in coding regions identification i.e. 40% to 125% as compared to other conventional window filters tested over more than 250 benchmarked and randomly taken DNA datasets of different organisms. This study proves that conventional fixed length window filters applied to DNA signals do not achieve significant results since the nucleotides carry genetic code context. The proposed FAWMF algorithm is adaptive and outperforms significantly to process DNA signal contents. The algorithm applied to variety of DNA datasets produced noteworthy discrimination between coding and non-coding regions contrary

  19. Bio-inspired networking

    CERN Document Server

    Câmara, Daniel

    2015-01-01

    Bio-inspired techniques are based on principles, or models, of biological systems. In general, natural systems present remarkable capabilities of resilience and adaptability. In this book, we explore how bio-inspired methods can solve different problems linked to computer networks. Future networks are expected to be autonomous, scalable and adaptive. During millions of years of evolution, nature has developed a number of different systems that present these and other characteristics required for the next generation networks. Indeed, a series of bio-inspired methods have been successfully used to solve the most diverse problems linked to computer networks. This book presents some of these techniques from a theoretical and practical point of view. Discusses the key concepts of bio-inspired networking to aid you in finding efficient networking solutions Delivers examples of techniques both in theoretical concepts and practical applications Helps you apply nature's dynamic resource and task management to your co...

  20. Workshop Introduction: Systems Biology and Biological Models

    Science.gov (United States)

    As we consider the future of toxicity testing, the importance of applying biological models to this problem is clear. Modeling efforts exist along a continuum with respect to the level of organization (e.g. cell, tissue, organism) linked to the resolution of the model. Generally,...

  1. Bio-Inspired Neural Model for Learning Dynamic Models

    Science.gov (United States)

    Duong, Tuan; Duong, Vu; Suri, Ronald

    2009-01-01

    A neural-network mathematical model that, relative to prior such models, places greater emphasis on some of the temporal aspects of real neural physical processes, has been proposed as a basis for massively parallel, distributed algorithms that learn dynamic models of possibly complex external processes by means of learning rules that are local in space and time. The algorithms could be made to perform such functions as recognition and prediction of words in speech and of objects depicted in video images. The approach embodied in this model is said to be "hardware-friendly" in the following sense: The algorithms would be amenable to execution by special-purpose computers implemented as very-large-scale integrated (VLSI) circuits that would operate at relatively high speeds and low power demands.

  2. A biologically inspired artificial muscle based on fiber-reinforced and electropneumatic dielectric elastomers

    Science.gov (United States)

    Liu, Lei; Zhang, Chi; Luo, Meng; Chen, Xi; Li, Dichen; Chen, Hualing

    2017-08-01

    Dielectric elastomers (DEs) have great potential for use as artificial muscles because of the following characteristics: electrical activity, fast and large deformation under stimuli, and softness as natural muscles. Inspired by the traditional McKibben actuators, in this study, we developed a cylindrical soft fiber-reinforced and electropneumatic DE artificial muscle (DEAM) by mimicking the spindle shape of natural muscles. Based on continuum mechanics and variation principle, the inhomogeneous actuation of DEAMs was theoretically modeled and calculated. Prototypes of DEAMs were prepared to validate the design concept and theoretical model. The theoretical predictions are consistent with the experimental results; they successfully predicted the evolutions of the contours of DEAMs with voltage. A pneumatically supported high prestretch in the hoop direction was achieved by our DEAM prototype without buckling the soft fibers sandwiched by the DE films. Besides, a continuously tunable prestretch in the actuation direction was achieved by varying the supporting pressure. Using the theoretical model, the failure modes, maximum actuations, and critical voltages were analyzed; they were highly dependent on the structural parameters, i.e., the cylinder aspect ratio, prestretch level, and supporting pressure. The effects of structural parameters and supporting pressure on the actuation performance were also investigated to optimize the DEAMs.

  3. Training mechanical engineering students to utilize biological inspiration during product development.

    Science.gov (United States)

    Bruck, Hugh A; Gershon, Alan L; Golden, Ira; Gupta, Satyandra K; Gyger, Lawrence S; Magrab, Edward B; Spranklin, Brent W

    2007-12-01

    The use of bio-inspiration for the development of new products and devices requires new educational tools for students consisting of appropriate design and manufacturing technologies, as well as curriculum. At the University of Maryland, new educational tools have been developed that introduce bio-inspired product realization to undergraduate mechanical engineering students. These tools include the development of a bio-inspired design repository, a concurrent fabrication and assembly manufacturing technology, a series of undergraduate curriculum modules and a new senior elective in the bio-inspired robotics area. This paper first presents an overview of the two new design and manufacturing technologies that enable students to realize bio-inspired products, and describes how these technologies are integrated into the undergraduate educational experience. Then, the undergraduate curriculum modules are presented, which provide students with the fundamental design and manufacturing principles needed to support bio-inspired product and device development. Finally, an elective bio-inspired robotics project course is present, which provides undergraduates with the opportunity to demonstrate the application of the knowledge acquired through the curriculum modules in their senior year using the new design and manufacturing technologies.

  4. Dynamics Analysis of Fluid-Structure Interaction for a Biologically-Inspired Biped Robot Running on Water

    Directory of Open Access Journals (Sweden)

    Linsen Xu

    2013-10-01

    Full Text Available A kinematics analysis of a biologically-inspired biped robot is carried out, and the trajectory of the robot foot is understood. For calculating the pressure distribution across a robot foot before touching the surface of water, the compression flow of air and the depression motion of the water surface are considered. The pressure model after touching the water surface has been built according to the theory of rigid body planar motion. The multi-material ALE algorithm is applied to emulate the course of the foot slapping water. The simulation results indicate that the model of the bionic robot can satisfy the water-running function. The real prototype of the robot is manufactured to test its function of running on water. When the biped robot is running on water, the average force generated by the propulsion mechanism is about 1.3N. The experimental results show that the propulsion system can satisfy the requirement of biped robot running on water.

  5. Integrating biologically inspired nanomaterials and table-top stereolithography for 3D printed biomimetic osteochondral scaffolds

    Science.gov (United States)

    Castro, Nathan J.; O'Brien, Joseph; Zhang, Lijie Grace

    2015-08-01

    The osteochondral interface of an arthritic joint is notoriously difficult to regenerate due to its extremely poor regenerative capacity and complex stratified architecture. Native osteochondral tissue extracellular matrix is composed of numerous nanoscale organic and inorganic constituents. Although various tissue engineering strategies exist in addressing osteochondral defects, limitations persist with regards to tissue scaffolding which exhibit biomimetic cues at the nano to micro scale. In an effort to address this, the current work focused on 3D printing biomimetic nanocomposite scaffolds for improved osteochondral tissue regeneration. For this purpose, two biologically-inspired nanomaterials have been synthesized consisting of (1) osteoconductive nanocrystalline hydroxyapatite (nHA) (primary inorganic component of bone) and (2) core-shell poly(lactic-co-glycolic) acid (PLGA) nanospheres encapsulated with chondrogenic transforming growth-factor β1 (TGF-β1) for sustained delivery. Then, a novel table-top stereolithography 3D printer and the nano-ink (i.e., nHA + nanosphere + hydrogel) were employed to fabricate a porous and highly interconnected osteochondral scaffold with hierarchical nano-to-micro structure and spatiotemporal bioactive factor gradients. Our results showed that human bone marrow-derived mesenchymal stem cell adhesion, proliferation, and osteochondral differentiation were greatly improved in the biomimetic graded 3D printed osteochondral construct in vitro. The current work served to illustrate the efficacy of the nano-ink and current 3D printing technology for efficient fabrication of a novel nanocomposite hydrogel scaffold. In addition, tissue-specific growth factors illustrated a synergistic effect leading to increased cell adhesion and directed stem cell differentiation.

  6. Novel biologically-inspired rosette nanotube PLLA scaffolds for improving human mesenchymal stem cell chondrogenic differentiation

    International Nuclear Information System (INIS)

    Childs, Allie; Castro, Nathan J; Zhang, Lijie Grace; Hemraz, Usha D; Fenniri, Hicham

    2013-01-01

    Cartilage defects are a persistent issue in orthopedic tissue engineering where acute and chronic tissue damage stemming from osteoarthritis, trauma, and sport injuries, present a common and serious clinical problem. Unlike bone, cartilage repair continues to be largely intractable due to the tissue's inherently poor regenerative capacity. Thus, the objective of this study is to design a novel tissue engineered nanostructured cartilage scaffold via biologically-inspired self-assembling rosette nanotubes (RNTs) and biocompatible non-woven poly (l-lactic acid) (PLLA) for enhanced human bone marrow mesenchymal stem cell (hMSC) chondrogenic differentiation. Specifically, RNTs are a new class of biomimetic supramolecular nanomaterial obtained through the self-assembly of low-molecular-weight modified guanine/cytosine DNA base hybrids (the G∧C motif) in an aqueous environment. In this study, we synthesized a novel twin G∧C-based RNT (TB-RGDSK) functionalized with cell-favorable arginine–glycine–aspartic acid–serine–lysine (RGDSK) integrin binding peptide and a twin G∧C based RNT with an aminobutane linker molecule (TBL). hMSC adhesion, proliferation and chondrogenic differentiation were evaluated in vitro in scaffold groups consisting of biocompatible PLLA with TBL, 1:9 TB-RGDSK:TBL, and TB-RGDSK, respectively. Our results show that RNTs can remarkably increase total glycosaminoglycan, collagen, and protein production when compared to PLLA controls without nanotubes. Furthermore, the TB-RGDSK with 100% well-organized RGDSK peptides achieved the highest chondrogenic differentiation of hMSCs. The current in vitro study illustrated that RNT nanotopography and surface chemistry played an important role in enhancing hMSC chondrogenic differentiation thus making them promising for cartilage regeneration. (paper)

  7. Social Fingerprinting: detection of spambot groups through DNA-inspired behavioral modeling

    DEFF Research Database (Denmark)

    Cresci, Stefano; Di Pietro, Roberto; Petrocchi, Marinella

    2017-01-01

    Spambot detection in online social networks is a long-lasting challenge involving the study and design of detection techniques capable of efficiently identifying ever-evolving spammers. Recently, a new wave of social spambots has emerged, with advanced human-like characteristics that allow them...... to go undetected even by current state-of-the-art algorithms. In this paper, we show that efficient spambots detection can be achieved via an in-depth analysis of their collective behaviors exploiting the digital DNA technique for modeling the behaviors of social network users. Inspired by its...... biological counterpart, in the digital DNA representation the behavioral lifetime of a digital account is encoded in a sequence of characters. Then, we define a similarity measure for such digital DNA sequences. We build upon digital DNA and the similarity between groups of users to characterize both genuine...

  8. A high-throughput screening approach to discovering good forms of biologically inspired visual representation.

    Directory of Open Access Journals (Sweden)

    Nicolas Pinto

    2009-11-01

    Full Text Available While many models of biological object recognition share a common set of "broad-stroke" properties, the performance of any one model depends strongly on the choice of parameters in a particular instantiation of that model--e.g., the number of units per layer, the size of pooling kernels, exponents in normalization operations, etc. Since the number of such parameters (explicit or implicit is typically large and the computational cost of evaluating one particular parameter set is high, the space of possible model instantiations goes largely unexplored. Thus, when a model fails to approach the abilities of biological visual systems, we are left uncertain whether this failure is because we are missing a fundamental idea or because the correct "parts" have not been tuned correctly, assembled at sufficient scale, or provided with enough training. Here, we present a high-throughput approach to the exploration of such parameter sets, leveraging recent advances in stream processing hardware (high-end NVIDIA graphic cards and the PlayStation 3's IBM Cell Processor. In analogy to high-throughput screening approaches in molecular biology and genetics, we explored thousands of potential network architectures and parameter instantiations, screening those that show promising object recognition performance for further analysis. We show that this approach can yield significant, reproducible gains in performance across an array of basic object recognition tasks, consistently outperforming a variety of state-of-the-art purpose-built vision systems from the literature. As the scale of available computational power continues to expand, we argue that this approach has the potential to greatly accelerate progress in both artificial vision and our understanding of the computational underpinning of biological vision.

  9. A high-throughput screening approach to discovering good forms of biologically inspired visual representation.

    Science.gov (United States)

    Pinto, Nicolas; Doukhan, David; DiCarlo, James J; Cox, David D

    2009-11-01

    While many models of biological object recognition share a common set of "broad-stroke" properties, the performance of any one model depends strongly on the choice of parameters in a particular instantiation of that model--e.g., the number of units per layer, the size of pooling kernels, exponents in normalization operations, etc. Since the number of such parameters (explicit or implicit) is typically large and the computational cost of evaluating one particular parameter set is high, the space of possible model instantiations goes largely unexplored. Thus, when a model fails to approach the abilities of biological visual systems, we are left uncertain whether this failure is because we are missing a fundamental idea or because the correct "parts" have not been tuned correctly, assembled at sufficient scale, or provided with enough training. Here, we present a high-throughput approach to the exploration of such parameter sets, leveraging recent advances in stream processing hardware (high-end NVIDIA graphic cards and the PlayStation 3's IBM Cell Processor). In analogy to high-throughput screening approaches in molecular biology and genetics, we explored thousands of potential network architectures and parameter instantiations, screening those that show promising object recognition performance for further analysis. We show that this approach can yield significant, reproducible gains in performance across an array of basic object recognition tasks, consistently outperforming a variety of state-of-the-art purpose-built vision systems from the literature. As the scale of available computational power continues to expand, we argue that this approach has the potential to greatly accelerate progress in both artificial vision and our understanding of the computational underpinning of biological vision.

  10. Comparative study between a QCD inspired model and a multiple diffraction model

    International Nuclear Information System (INIS)

    Luna, E.G.S.; Martini, A.F.; Menon, M.J.

    2003-01-01

    A comparative study between a QCD Inspired Model (QCDIM) and a Multiple Diffraction Model (MDM) is presented, with focus on the results for pp differential cross section at √s = 52.8 GeV. It is shown that the MDM predictions are in agreement with experimental data, except for the dip region and that the QCDIM describes only the diffraction peak region. Interpretations in terms of the corresponding eikonals are also discussed. (author)

  11. Biologically-Inspired Spike-Based Automatic Speech Recognition of Isolated Digits Over a Reproducing Kernel Hilbert Space

    Directory of Open Access Journals (Sweden)

    Kan Li

    2018-04-01

    Full Text Available This paper presents a novel real-time dynamic framework for quantifying time-series structure in spoken words using spikes. Audio signals are converted into multi-channel spike trains using a biologically-inspired leaky integrate-and-fire (LIF spike generator. These spike trains are mapped into a function space of infinite dimension, i.e., a Reproducing Kernel Hilbert Space (RKHS using point-process kernels, where a state-space model learns the dynamics of the multidimensional spike input using gradient descent learning. This kernelized recurrent system is very parsimonious and achieves the necessary memory depth via feedback of its internal states when trained discriminatively, utilizing the full context of the phoneme sequence. A main advantage of modeling nonlinear dynamics using state-space trajectories in the RKHS is that it imposes no restriction on the relationship between the exogenous input and its internal state. We are free to choose the input representation with an appropriate kernel, and changing the kernel does not impact the system nor the learning algorithm. Moreover, we show that this novel framework can outperform both traditional hidden Markov model (HMM speech processing as well as neuromorphic implementations based on spiking neural network (SNN, yielding accurate and ultra-low power word spotters. As a proof of concept, we demonstrate its capabilities using the benchmark TI-46 digit corpus for isolated-word automatic speech recognition (ASR or keyword spotting. Compared to HMM using Mel-frequency cepstral coefficient (MFCC front-end without time-derivatives, our MFCC-KAARMA offered improved performance. For spike-train front-end, spike-KAARMA also outperformed state-of-the-art SNN solutions. Furthermore, compared to MFCCs, spike trains provided enhanced noise robustness in certain low signal-to-noise ratio (SNR regime.

  12. Biologically-Inspired Spike-Based Automatic Speech Recognition of Isolated Digits Over a Reproducing Kernel Hilbert Space.

    Science.gov (United States)

    Li, Kan; Príncipe, José C

    2018-01-01

    This paper presents a novel real-time dynamic framework for quantifying time-series structure in spoken words using spikes. Audio signals are converted into multi-channel spike trains using a biologically-inspired leaky integrate-and-fire (LIF) spike generator. These spike trains are mapped into a function space of infinite dimension, i.e., a Reproducing Kernel Hilbert Space (RKHS) using point-process kernels, where a state-space model learns the dynamics of the multidimensional spike input using gradient descent learning. This kernelized recurrent system is very parsimonious and achieves the necessary memory depth via feedback of its internal states when trained discriminatively, utilizing the full context of the phoneme sequence. A main advantage of modeling nonlinear dynamics using state-space trajectories in the RKHS is that it imposes no restriction on the relationship between the exogenous input and its internal state. We are free to choose the input representation with an appropriate kernel, and changing the kernel does not impact the system nor the learning algorithm. Moreover, we show that this novel framework can outperform both traditional hidden Markov model (HMM) speech processing as well as neuromorphic implementations based on spiking neural network (SNN), yielding accurate and ultra-low power word spotters. As a proof of concept, we demonstrate its capabilities using the benchmark TI-46 digit corpus for isolated-word automatic speech recognition (ASR) or keyword spotting. Compared to HMM using Mel-frequency cepstral coefficient (MFCC) front-end without time-derivatives, our MFCC-KAARMA offered improved performance. For spike-train front-end, spike-KAARMA also outperformed state-of-the-art SNN solutions. Furthermore, compared to MFCCs, spike trains provided enhanced noise robustness in certain low signal-to-noise ratio (SNR) regime.

  13. Switching Adaptability in Human-Inspired Sidesteps: A Minimal Model.

    Science.gov (United States)

    Fujii, Keisuke; Yoshihara, Yuki; Tanabe, Hiroko; Yamamoto, Yuji

    2017-01-01

    Humans can adapt to abruptly changing situations by coordinating redundant components, even in bipedality. Conventional adaptability has been reproduced by various computational approaches, such as optimal control, neural oscillator, and reinforcement learning; however, the adaptability in bipedal locomotion necessary for biological and social activities, such as unpredicted direction change in chase-and-escape, is unknown due to the dynamically unstable multi-link closed-loop system. Here we propose a switching adaptation model for performing bipedal locomotion by improving autonomous distributed control, where autonomous actuators interact without central control and switch the roles for propulsion, balancing, and leg swing. Our switching mobility model achieved direction change at any time using only three actuators, although it showed higher motor costs than comparable models without direction change. Our method of evaluating such adaptation at any time should be utilized as a prerequisite for understanding universal motor control. The proposed algorithm may simply explain and predict the adaptation mechanism in human bipedality to coordinate the actuator functions within and between limbs.

  14. Issues in Biological Shape Modelling

    DEFF Research Database (Denmark)

    Hilger, Klaus Baggesen

    This talk reflects parts of the current research at informatics and Mathematical Modelling at the Technical University of Denmark within biological shape modelling. We illustrate a series of generalizations, modifications, and applications of the elements of constructing models of shape or appear......This talk reflects parts of the current research at informatics and Mathematical Modelling at the Technical University of Denmark within biological shape modelling. We illustrate a series of generalizations, modifications, and applications of the elements of constructing models of shape...

  15. Biomimetics: using nature as an inspiring model for human innovation

    Science.gov (United States)

    Bar-Cohen, Yoseph

    2006-01-01

    The evolution of nature over 3.8 billion years led to the highly effective and power efficient biological mechanisms. Imitating these mechanisms offers enormous potentials for the improvement of our life and the tools we use.

  16. The effect of shape on drag: a physics exercise inspired by biology

    Science.gov (United States)

    Fingerut, Jonathan; Johnson, Nicholas; Mongeau, Eric; Habdas, Piotr

    2017-07-01

    As part of a biomechanics course aimed at upper-division biology and physics majors, but applicable to a range of student learning levels, this laboratory exercise provides an insight into the effect of shape on hydrodynamic performance, as well an introduction to computer aided design (CAD) and 3D printing. Students use hydrodynamic modeling software and simple CAD programs to design a shape with the least amount of drag based on strategies gleaned from the study of natural forms. Students then print the shapes using a 3D printer and test their shapes against their classmates in a friendly competition. From this exercise, students gain a more intuitive sense of the challenges that organisms face when moving through fluid environments, the physical phenomena involved in moving through fluids at high Reynolds numbers and observe how and why certain morphologies, such as streamlining, are common answers to the challenge of swimming at high speeds.

  17. Biology-inspired Microphysiological System Approaches to Solve the Prediction Dilemma of Substance Testing

    Science.gov (United States)

    Marx, Uwe; Andersson, Tommy B.; Bahinski, Anthony; Beilmann, Mario; Beken, Sonja; Cassee, Flemming R.; Cirit, Murat; Daneshian, Mardas; Fitzpatrick, Susan; Frey, Olivier; Gaertner, Claudia; Giese, Christoph; Griffith, Linda; Hartung, Thomas; Heringa, Minne B.; Hoeng, Julia; de Jong, Wim H.; Kojima, Hajime; Kuehnl, Jochen; Luch, Andreas; Maschmeyer, Ilka; Sakharov, Dmitry; Sips, Adrienne J. A. M.; Steger-Hartmann, Thomas; Tagle, Danilo A.; Tonevitsky, Alexander; Tralau, Tewes; Tsyb, Sergej; van de Stolpe, Anja; Vandebriel, Rob; Vulto, Paul; Wang, Jufeng; Wiest, Joachim; Rodenburg, Marleen; Roth, Adrian

    2017-01-01

    Summary The recent advent of microphysiological systems – microfluidic biomimetic devices that aspire to emulate the biology of human tissues, organs and circulation in vitro – is envisaged to enable a global paradigm shift in drug development. An extraordinary US governmental initiative and various dedicated research programs in Europe and Asia have led recently to the first cutting-edge achievements of human single-organ and multi-organ engineering based on microphysiological systems. The expectation is that test systems established on this basis would model various disease stages, and predict toxicity, immunogenicity, ADME profiles and treatment efficacy prior to clinical testing. Consequently, this technology could significantly affect the way drug substances are developed in the future. Furthermore, microphysiological system-based assays may revolutionize our current global programs of prioritization of hazard characterization for any new substances to be used, for example, in agriculture, food, ecosystems or cosmetics, thus, replacing laboratory animal models used currently. Thirty-five experts from academia, industry and regulatory bodies present here the results of an intensive workshop (held in June 2015, Berlin, Germany). They review the status quo of microphysiological systems available today against industry needs, and assess the broad variety of approaches with fit-for-purpose potential in the drug development cycle. Feasible technical solutions to reach the next levels of human biology in vitro are proposed. Furthermore, key organ-on-a-chip case studies, as well as various national and international programs are highlighted. Finally, a roadmap into the future is outlined, to allow for more predictive and regulatory-accepted substance testing on a global scale. PMID:27180100

  18. A Biologically-Inspired Power Control Algorithm for Energy-Efficient Cellular Networks

    Directory of Open Access Journals (Sweden)

    Hyun-Ho Choi

    2016-03-01

    Full Text Available Most of the energy used to operate a cellular network is consumed by a base station (BS, and reducing the transmission power of a BS can therefore afford a substantial reduction in the amount of energy used in a network. In this paper, we propose a distributed transmit power control (TPC algorithm inspired by bird flocking behavior as a means of improving the energy efficiency of a cellular network. Just as each bird in a flock attempts to match its velocity with the average velocity of adjacent birds, in the proposed algorithm, each mobile station (MS in a cell matches its rate with the average rate of the co-channel MSs in adjacent cells by controlling the transmit power of its serving BS. We verify that this bio-inspired TPC algorithm using a local rate-average process achieves an exponential convergence and maximizes the minimum rate of the MSs concerned. Simulation results show that the proposed TPC algorithm follows the same convergence properties as the flocking algorithm and also effectively reduces the power consumption at the BSs while maintaining a low outage probability as the inter-cell interference increases; in so doing, it significantly improves the energy efficiency of a cellular network.

  19. An FEA study on impact resistance of bio-inspired CAD models

    OpenAIRE

    Page, T; Thorsteinsson, G

    2017-01-01

    The purpose of this paper is to explore the use of biomimetic methods in the design of armour systems. It focusses on biological structures found in nature that feature both rigid and flexible armours, analysing their structures and determining which are the most widely successful. A study was conducted on three bio-inspired structures built in Creo Parametric and tested using Finite Element Analysis (FEA) software to determine which structure had the best impact resistance. The study was con...

  20. DNA-Inspired Online Behavioral Modeling and Its Application to Spambot Detection

    DEFF Research Database (Denmark)

    Cresci, Stefano; Di Pietro, Roberto; Petrocchi, Marinella

    2016-01-01

    A novel, simple, and effective approach to modeling online user behavior extracts and analyzes digital DNA sequences from user online actions and uses Twitter as a benchmark to test the proposal. Specifically, the model obtains an incisive and compact DNA-inspired characterization of user actions...... methodology is platform and technology agnostic, paving the way for diverse behavioral characterization tasks....

  1. Handbook of nature-inspired and innovative computing integrating classical models with emerging technologies

    CERN Document Server

    2006-01-01

    As computing devices proliferate, demand increases for an understanding of emerging computing paradigms and models based on natural phenomena. This handbook explores the connection between nature-inspired and traditional computational paradigms. It presents computing paradigms and models based on natural phenomena.

  2. Mathematical modeling of biological processes

    CERN Document Server

    Friedman, Avner

    2014-01-01

    This book on mathematical modeling of biological processes includes a wide selection of biological topics that demonstrate the power of mathematics and computational codes in setting up biological processes with a rigorous and predictive framework. Topics include: enzyme dynamics, spread of disease, harvesting bacteria, competition among live species, neuronal oscillations, transport of neurofilaments in axon, cancer and cancer therapy, and granulomas. Complete with a description of the biological background and biological question that requires the use of mathematics, this book is developed for graduate students and advanced undergraduate students with only basic knowledge of ordinary differential equations and partial differential equations; background in biology is not required. Students will gain knowledge on how to program with MATLAB without previous programming experience and how to use codes in order to test biological hypothesis.

  3. The role of mechanics in biological and bio-inspired systems.

    Science.gov (United States)

    Egan, Paul; Sinko, Robert; LeDuc, Philip R; Keten, Sinan

    2015-07-06

    Natural systems frequently exploit intricate multiscale and multiphasic structures to achieve functionalities beyond those of man-made systems. Although understanding the chemical make-up of these systems is essential, the passive and active mechanics within biological systems are crucial when considering the many natural systems that achieve advanced properties, such as high strength-to-weight ratios and stimuli-responsive adaptability. Discovering how and why biological systems attain these desirable mechanical functionalities often reveals principles that inform new synthetic designs based on biological systems. Such approaches have traditionally found success in medical applications, and are now informing breakthroughs in diverse frontiers of science and engineering.

  4. Operational Semantics of a Weak Memory Model inspired by Go

    OpenAIRE

    Fava, Daniel Schnetzer; Stolz, Volker; Valle, Stian

    2017-01-01

    A memory model dictates which values may be returned when reading from memory. In a parallel computing setting, the memory model affects how processes communicate through shared memory. The design of a proper memory model is a balancing act. On one hand, memory models must be lax enough to allow common hardware and compiler optimizations. On the other, the more lax the model, the harder it is for developers to reason about their programs. In order to alleviate the burden on programmers, a wea...

  5. Parameter estimation with bio-inspired meta-heuristic optimization: modeling the dynamics of endocytosis

    Directory of Open Access Journals (Sweden)

    Tashkova Katerina

    2011-10-01

    convergence. These results hold for both real and artificial data, for all observability scenarios considered, and for all amounts of noise added to the artificial data. In sum, the meta-heuristic methods considered are suitable for estimating the parameters in the ODE model of the dynamics of endocytosis under a range of conditions: With the model and conditions being representative of parameter estimation tasks in ODE models of biochemical systems, our results clearly highlight the promise of bio-inspired meta-heuristic methods for parameter estimation in dynamic system models within system biology.

  6. Parameter estimation with bio-inspired meta-heuristic optimization: modeling the dynamics of endocytosis.

    Science.gov (United States)

    Tashkova, Katerina; Korošec, Peter; Silc, Jurij; Todorovski, Ljupčo; Džeroski, Sašo

    2011-10-11

    artificial data, for all observability scenarios considered, and for all amounts of noise added to the artificial data. In sum, the meta-heuristic methods considered are suitable for estimating the parameters in the ODE model of the dynamics of endocytosis under a range of conditions: With the model and conditions being representative of parameter estimation tasks in ODE models of biochemical systems, our results clearly highlight the promise of bio-inspired meta-heuristic methods for parameter estimation in dynamic system models within system biology.

  7. Phase-assisted synthesis and DNA unpacking evaluation of biologically inspired metallo nanocomplexes using peptide as unique building block.

    Science.gov (United States)

    Raman, N; Sudharsan, S

    2011-12-01

    The goal of nanomaterials' surface modification using a biomaterial is to preserve the materials' bulk properties while modifying only their surface to possess desired recognition and specificity. Here, we have developed a phase-assisted, modified Brust-Schiffrin methodological synthesis of metallo nanocomplexes anchored by a peptide, N,N'-(1,3-propylene)-bis-hippuricamide. The spectral, thermal and morphological characterizations assure the formation of nanocomplexes. Therapeutic behavior of all the nanocomplexes has been well sighted by evaluating their DNA unpacking skills. In addition, we demonstrate their biological inspiration by targeting few bacterial and fungal strains. The in vitro antimicrobial investigation reports that all the nanocomplexes disrupt microbial cell walls/membranes efficiently and inhibit the growth of microbes. These sorts of nanocomplexes synthesized in large quantities and at low cost, deliver versatile biomedical applications, and can be used to treat various diseases which may often cause high mortality. Copyright © 2011 Elsevier Inc. All rights reserved.

  8. Stress in adolescents with a chronically ill parent: inspiration from Rolland's Family Systems-Illness model

    NARCIS (Netherlands)

    Sieh, D.S.; Dikkers, A.L.C.; Visser-Meily, J.M.A.; Meijer, A.M.

    2012-01-01

    This article was inspired by Rolland’s Family Systems-Illness (FSI) model, aiming to predict adolescent stress as a function of parental illness type. Ninety-nine parents with a chronic medical condition, 82 partners, and 158 adolescent children (51 % girls; mean age = 15.1 years) participated in

  9. Isgur–Wise function in a QCD-inspired potential model with WKB ...

    Indian Academy of Sciences (India)

    2017-02-28

    Feb 28, 2017 ... DOI 10.1007/s12043-016-1357-9. Isgur–Wise function in a QCD-inspired potential model with WKB approximation. BHASKAR JYOTI HAZARIKA1,∗ and D K CHOUDHURY1,2. 1Centre for Theoretical Studies, Pandu College, Guwahati 781 012, India. 2Physics Academy of North East, Gauhati University, ...

  10. Archive Design Based on Planets Inspired Logical Object Model

    DEFF Research Database (Denmark)

    Zierau, Eld; Johansen, Anders

    2008-01-01

    We describe a proposal for a logical data model based on preliminary work the Planets project In OAIS terms the main areas discussed are related to the introduction of a logical data model for representing the past, present and future versions of the digital object associated with the Archival St...... Storage Package for the publications deposited by our client repositories....

  11. Mesoscopic models of biological membranes

    DEFF Research Database (Denmark)

    Venturoli, M.; Sperotto, Maria Maddalena; Kranenburg, M.

    2006-01-01

    Phospholipids are the main components of biological membranes and dissolved in water these molecules self-assemble into closed structures, of which bilayers are the most relevant from a biological point of view. Lipid bilayers are often used, both in experimental and by theoretical investigations...... to coarse grain a biological membrane. The conclusion of this comparison is that there can be many valid different strategies, but that the results obtained by the various mesoscopic models are surprisingly consistent. A second objective of this review is to illustrate how mesoscopic models can be used...

  12. Enhanced chondrocyte culture and growth on biologically inspired nanofibrous cell culture dishes.

    Science.gov (United States)

    Bhardwaj, Garima; Webster, Thomas J

    2016-01-01

    Chondral and osteochondral defects affect a large number of people in which treatment options are currently limited. Due to its ability to mimic the natural nanofibrous structure of cartilage, this current in vitro study aimed at introducing a new scaffold, called XanoMatrix™, for cartilage regeneration. In addition, this same scaffold is introduced here as a new substrate onto which to study chondrocyte functions. Current studies on chondrocyte functions are limited due to nonbiologically inspired cell culture substrates. With its polyethylene terephthalate and cellulose acetate composition, good mechanical properties and nanofibrous structure resembling an extracellular matrix, XanoMatrix offers an ideal surface for chondrocyte growth and proliferation. This current study demonstrated that the XanoMatrix scaffolds promote chondrocyte growth and proliferation as compared with the Corning and Falcon surfaces normally used for chondrocyte cell culture. The XanoMatrix scaffolds also have greater hydrophobicity, three-dimensional surface area, and greater tensile strength, making them ideal candidates for alternative treatment options for chondral and osteochondral defects as well as cell culture substrates to study chondrocyte functions.

  13. RNA synthetic biology inspired from bacteria: construction of transcription attenuators under antisense regulation.

    Science.gov (United States)

    Dawid, Alexandre; Cayrol, Bastien; Isambert, Hervé

    2009-07-01

    Among all biopolymers, ribonucleic acids or RNA have unique functional versatility, which led to the early suggestion that RNA alone (or a closely related biopolymer) might have once sustained a primitive form of life based on a single type of biopolymer. This has been supported by the demonstration of processive RNA-based replication and the discovery of 'riboswitches' or RNA switches, which directly sense their metabolic environment. In this paper, we further explore the plausibility of this 'RNA world' scenario and show, through synthetic molecular design guided by advanced RNA simulations, that RNA can also perform elementary regulation tasks on its own. We demonstrate that RNA synthetic regulatory modules directly inspired from bacterial transcription attenuators can efficiently activate or repress the expression of other RNA by merely controlling their folding paths 'on the fly' during transcription through simple RNA-RNA antisense interaction. Factors, such as NTP concentration and RNA synthesis rate, affecting the efficiency of this kinetic regulation mechanism are also studied and discussed in the light of evolutionary constraints. Overall, this suggests that direct coupling among synthesis, folding and regulation of RNAs may have enabled the early emergence of autonomous RNA-based regulation networks in absence of both DNA and protein partners.

  14. RNA synthetic biology inspired from bacteria: construction of transcription attenuators under antisense regulation

    International Nuclear Information System (INIS)

    Dawid, Alexandre; Cayrol, Bastien; Isambert, Hervé

    2009-01-01

    Among all biopolymers, ribonucleic acids or RNA have unique functional versatility, which led to the early suggestion that RNA alone (or a closely related biopolymer) might have once sustained a primitive form of life based on a single type of biopolymer. This has been supported by the demonstration of processive RNA-based replication and the discovery of 'riboswitches' or RNA switches, which directly sense their metabolic environment. In this paper, we further explore the plausibility of this 'RNA world' scenario and show, through synthetic molecular design guided by advanced RNA simulations, that RNA can also perform elementary regulation tasks on its own. We demonstrate that RNA synthetic regulatory modules directly inspired from bacterial transcription attenuators can efficiently activate or repress the expression of other RNA by merely controlling their folding paths 'on the fly' during transcription through simple RNA–RNA antisense interaction. Factors, such as NTP concentration and RNA synthesis rate, affecting the efficiency of this kinetic regulation mechanism are also studied and discussed in the light of evolutionary constraints. Overall, this suggests that direct coupling among synthesis, folding and regulation of RNAs may have enabled the early emergence of autonomous RNA-based regulation networks in absence of both DNA and protein partners

  15. A Markov Process Inspired Cellular Automata Model of Road Traffic

    OpenAIRE

    Wang, Fa; Li, Li; Hu, Jianming; Ji, Yan; Yao, Danya; Zhang, Yi; Jin, Xuexiang; Su, Yuelong; Wei, Zheng

    2008-01-01

    To provide a more accurate description of the driving behaviors in vehicle queues, a namely Markov-Gap cellular automata model is proposed in this paper. It views the variation of the gap between two consequent vehicles as a Markov process whose stationary distribution corresponds to the observed distribution of practical gaps. The multiformity of this Markov process provides the model enough flexibility to describe various driving behaviors. Two examples are given to show how to specialize i...

  16. Biological armors under impact—effect of keratin coating, and synthetic bio-inspired analogues

    International Nuclear Information System (INIS)

    Achrai, B; Wagner, H D; Bar-On, B

    2015-01-01

    A number of biological armors, such as turtle shells, consist of a strong exoskeleton covered with a thin keratin coating. The mechanical role upon impact of this keratin coating has surprisingly not been investigated thus far. Low-velocity impact tests on the turtle shell reveal a unique toughening phenomenon attributed to the thin covering keratin layer, the presence of which noticeably improves the fracture energy and shell integrity. Synthetic substrate/coating analogues were subsequently prepared and exhibit an impact behavior similar to the biological ones. The results of the present study may improve our understanding, and even future designs, of impact-tolerant structures. (paper)

  17. An Approach for Calculating Land Valuation by Using Inspire Data Models

    Science.gov (United States)

    Aydinoglu, A. C.; Bovkir, R.

    2017-11-01

    Land valuation is a highly important concept for societies and governments have always emphasis on the process especially for taxation, expropriation, market capitalization and economic activity purposes. To success an interoperable and standardised land valuation, INSPIRE data models can be very practical and effective. If data used in land valuation process produced in compliance with INSPIRE specifications, a reliable and effective land valuation process can be performed. In this study, possibility of the performing land valuation process with using the INSPIRE data models was analysed and with the help of Geographic Information Systems (GIS) a case study in Pendik was implemented. For this purpose, firstly data analysis and gathering was performed. After, different data structures were transformed according to the INSPIRE data model requirements. For each data set necessary ETL (Extract-Transform-Load) tools were produced and all data transformed according to the target data requirements. With the availability and practicability of spatial analysis tools of GIS software, land valuation calculations were performed for study area.

  18. An experimental study of double-peeling mechanism inspired by biological adhesive systems

    DEFF Research Database (Denmark)

    Heepe, Lars; Raguseo, Saverio; Gorb, Stanislav N.

    2017-01-01

    Double- (or multiple-) peeling systems consist of two (or numerous) tapes adhering to a substrate and having a common hinge, where the pulling force is applied. Biological systems, consisting of tape-like (or spatula-like) contact elements, are widely observed in adhesive pads of flies, beetles...

  19. Biology-inspired microphysiological system approaches to solve the prediction dilemma of substance testing

    NARCIS (Netherlands)

    Marx, Uwe; Andersson, Tommy B; Bahinski, Anthony; Beilmann, Mario; Beken, Sonja; Cassee, Flemming R; Cirit, Murat; Daneshian, Mardas; Fitzpatrick, Susan; Frey, Olivier; Gaertner, Claudia; Giese, Christoph; Griffith, Linda; Hartung, Thomas; Heringa, Minne B; Hoeng, Julia; de Jong, Wim H; Kojima, Hajime; Kuehnl, Jochen; Leist, Marcel; Luch, Andreas; Maschmeyer, Ilka; Sakharov, Dmitry; Sips, Adrienne J A M; Steger-Hartmann, Thomas; Tagle, Danilo A; Tonevitsky, Alexander; Tralau, Tewes; Tsyb, Sergej; van de Stolpe, Anja; Vandebriel, Rob; Vulto, Paul; Wang, Jufeng; Wiest, Joachim; Rodenburg, Marleen; Roth, Adrian

    2016-01-01

    The recent advent of microphysiological systems - microfluidic biomimetic devices that aspire to emulate the biology of human tissues, organs and circulation in vitro - is envisaged to enable a global paradigm shift in drug development. An extraordinary US governmental initiative and various

  20. Female Leaders: Injurious or Inspiring Role Models for Women?

    Science.gov (United States)

    Hoyt, Crystal L.; Simon, Stefanie

    2011-01-01

    The impact of female role models on women's leadership aspirations and self-perceptions after a leadership task were assessed across two laboratory studies. These studies tested the prediction that upward social comparisons to high-level female leaders will have a relatively detrimental impact on women's self-perceptions and leadership aspirations…

  1. Matrix models with Penner interaction inspired by interacting ...

    Indian Academy of Sciences (India)

    distribution of structure with temperature calculated from the NL model .... where φi are the random Hermitian matrices of size (N × N) placed at each base position ..... PB thanks UGC for research fellowships and ND thanks CSIR Project No.

  2. Silkworm cocoons inspire models for random fiber and particulate composites

    Energy Technology Data Exchange (ETDEWEB)

    Fujia, Chen; Porter, David; Vollrath, Fritz [Department of Zoology, University of Oxford, Oxford OX1 3PS (United Kingdom)

    2010-10-15

    The bioengineering design principles evolved in silkworm cocoons make them ideal natural prototypes and models for structural composites. Cocoons depend for their stiffness and strength on the connectivity of bonding between their constituent materials of silk fibers and sericin binder. Strain-activated mechanisms for loss of bonding connectivity in cocoons can be translated directly into a surprisingly simple yet universal set of physically realistic as well as predictive quantitative structure-property relations for a wide range of technologically important fiber and particulate composite materials.

  3. Mechanical Behavior of Bio-inspired Model Suture Joints

    Science.gov (United States)

    Li, Yaning; Lin, Erica; Ortiz, Christine; Boyce, Mary

    2012-02-01

    Suture joints of varying degrees of geometric complexity are prevalent throughout nature as a means of joining structural elements while providing locally tailored mechanical performance. Here, micromechanical models of general trapezoidal waveforms of varying hierarchy are formulated to reveal the role of geometric complexity in governing stiffness, strength, toughness and corresponding deformation and failure mechanisms. Physical constructs of model composite suture systems are fabricated via multi-material 3D printing (Object Connex500). Tensile tests are conducted on samples covering a range in geometry, thus providing quantitative measures of stiffness, strength, and failure. The experiments include direct visualization of the deformation and failure mechanisms and their progression, as well as their dependence on suture geometry, showing the interplay between shear and tension/compression of the interfacial layers and tension of the skeletal teeth and the transition in failure modes with geometry. The results provide quantitative guidelines for the design and tailoring of suture geometry to achieve the desired mechanical properties and also facilitate understanding of suture growth and fusion, and evolutionary phenotype.

  4. Biologically-inspired synthetic dry adhesives for wall-climbing robots

    Science.gov (United States)

    Murphy, Michael P.

    Animals such as insects, spiders, and lizards are capable of clinging to and climbing on a variety of surfaces, from rough stone to smooth silicon. Hairy microscale arrays of structures on their feet conform to surface roughness to create millions of points of contact, creating a large overall contact area. Weak intermolecular forces (van der Waals forces) between each fiber tip and the surface sum to large overall forces due to the high number of contacts. In this work we present the fabrication, characterization, and demonstration of synthetic polyurethane fibrillar adhesives inspired by these animals. Angled polymer micro-fiber arrays are fabricated and characterized. A tip modification technique is presented which enables fabrication of fibers with flat mushroom shaped tips which greatly increase the adhesion of the fibers, up to 5N/cm 2 (normal direction), and with a magnitude within the range of geckos (10 N/cm2) in the shear direction on smooth surfaces. We present a fabrication technique to create fibers with angled flat mushroom-shaped tips which replicate the directional characteristics of geckos, gripping in one direction (within the range of gecko adhesion) and releasing easily in the other. Multilevel hierarchical structures with specialized tips for roughness adaptation are also presented. Fiber hierarchies from the millimeter scale to the sub-micron scale are demonstrated, including three-level fiber fabrication with specialized tips. Hierarchical structures demonstrate up to 5 times the adhesion of an unstructured sample, and requiring up to 10 times the detachment energy. Finally, an agile, wireless, palm-sized wall climbing robot which uses the synthetic fibrillar dry adhesives to climb is presented. Waalbot , named after the van der Waals forces it uses to climb, exploits the attachment and detachment characteristics of the developed dry adhesives, capabilities include climbing smooth surfaces such as glass in any orientation on any surface slope

  5. IIR Filter Modeling Using an Algorithm Inspired on Electromagnetism

    Directory of Open Access Journals (Sweden)

    Cuevas-Jiménez E.

    2013-01-01

    Full Text Available Infinite-impulse-response (IIR filtering provides a powerful approach for solving a variety of problems. However, its design represents a very complicated task, since the error surface of IIR filters is generally multimodal, global optimization techniques are required in order to avoid local minima. In this paper, a new method based on the Electromagnetism-Like Optimization Algorithm (EMO is proposed for IIR filter modeling. EMO originates from the electro-magnetism theory of physics by assuming potential solutions as electrically charged particles which spread around the solution space. The charge of each particle depends on its objective function value. This algorithm employs a collective attraction-repulsion mechanism to move the particles towards optimality. The experimental results confirm the high performance of the proposed method in solving various benchmark identification problems.

  6. Ergonomics-inspired Reshaping and Exploration of Collections of Models

    KAUST Repository

    Zheng, Youyi

    2015-06-22

    This paper examines the following question: given a collection of man-made shapes, e.g., chairs, can we effectively explore and rank the shapes with respect to a given human body – in terms of how well a candidate shape fits the specified human body? Answering this question requires identifying which shapes are more suitable for a prescribed body, and how to alter the input geometry to better fit the shapes to a given human body. The problem links physical proportions of the human body and its interaction with object geometry, which is often expressed as ergonomics guidelines. We present an interactive system that allows users to explore shapes using different avatar poses, while, at the same time providing interactive previews of how to alter the shapes to fit the user-specified body and pose. We achieve this by first constructing a fuzzy shape-to-body map from the ergonomic guidelines to multi-contacts geometric constraints; and then, proposing a novel contact-preserving deformation paradigm to realize a reshaping to adapt the input shape. We evaluate our method on collections of models from different categories and validate the results through a user study.

  7. Inspiration from role models and advice for moving forward.

    Science.gov (United States)

    Newman, Michelle G; McGinn, Lata K

    2012-12-01

    This Behavior Therapy series on overcoming the glass ceiling followed from a highly attended panel at ABCT on the same topic. The current paper summarizes the common themes across the various papers in this series with respect to obstacles prominent women have faced, and how we can learn from their stories to help inform the future. These themes include the importance of role models, messages from a supportive environment, difficulties balancing careers with children, coordinating careers with family, importance of taking charge of one's career, moving forward despite negative internal and external messages, and questions about whether things have changed substantially. In addition, this paper contains a summary of the helpful advice from accomplished women in academia for navigating the academic waters. It is our aspiration that going forward this series will stimulate other conversations as well as increase thought, behavior, solidarity, and awareness about this topic so that we can continue to work toward a future when things will continue to improve for women. Copyright © 2012. Published by Elsevier Ltd.

  8. Biologically Inspired Modular Neural Control for a Leg-Wheel Hybrid Robot

    DEFF Research Database (Denmark)

    Manoonpong, Poramate; Wörgötter, Florentin; Laksanacharoen, Pudit

    2014-01-01

    In this article we present modular neural control for a leg-wheel hybrid robot consisting of three legs with omnidirectional wheels. This neural control has four main modules having their functional origin in biological neural systems. A minimal recurrent control (MRC) module is for sensory signal...... processing and state memorization. Its outputs drive two front wheels while the rear wheel is controlled through a velocity regulating network (VRN) module. In parallel, a neural oscillator network module serves as a central pattern generator (CPG) controls leg movements for sidestepping. Stepping directions...... or they can serve as useful modules for other module-based neural control applications....

  9. On-chip visual perception of motion: a bio-inspired connectionist model on FPGA.

    Science.gov (United States)

    Torres-Huitzil, César; Girau, Bernard; Castellanos-Sánchez, Claudio

    2005-01-01

    Visual motion provides useful information to understand the dynamics of a scene to allow intelligent systems interact with their environment. Motion computation is usually restricted by real time requirements that need the design and implementation of specific hardware architectures. In this paper, the design of hardware architecture for a bio-inspired neural model for motion estimation is presented. The motion estimation is based on a strongly localized bio-inspired connectionist model with a particular adaptation of spatio-temporal Gabor-like filtering. The architecture is constituted by three main modules that perform spatial, temporal, and excitatory-inhibitory connectionist processing. The biomimetic architecture is modeled, simulated and validated in VHDL. The synthesis results on a Field Programmable Gate Array (FPGA) device show the potential achievement of real-time performance at an affordable silicon area.

  10. Polarization Calculation and Underwater Target Detection Inspired by Biological Visual Imaging

    Directory of Open Access Journals (Sweden)

    Jie Shen

    2014-04-01

    Full Text Available In challenging underwater environments, the polarization parameter maps calculated by the Stokes model are characterized by the high noise and error, harassing the underwater target detection tasks. In order to solve this problem, this paper proposes a novel bionic polarization calculation and underwater target detection method by modeling the visual system of mantis shrimps. This system includes many operators including a polarization-opposition calculation, a factor optimization and a visual neural network model. A calibration learning method is proposed to search the optimal value of the factors in the linear subtraction model. Finally, a six-channel visual neural network model is proposed to detect the underwater targets. Experimental results proved that the maps produced by the polarization-opposition parameter is more accurate and have lower noise than that produced by the Stokes parameter, achieving better performance in underwater target detection tasks.

  11. Dynamical analysis and development of a biologically inspired SMA caterpillar robot.

    Science.gov (United States)

    Daily-Diamond, Christopher A; Novelia, Alyssa; O'Reilly, Oliver M

    2017-09-26

    With the goal of robustly designing and fabricating a soft robot based on a caterpillar featuring shape memory alloy (SMA) actuators, analytical and numerical models for a soft robot were created based on the forward crawling motion of the Manduca sexta caterpillar. The analytical model features a rod theory and the mechanics of undulation were analyzed using a motion pattern based on the 'Witch of Agnesi' curve. Complementing these models, experiments on a SMA actuator sample were performed in order to determine its flexural rigidity and curvature as a function of the actuation voltage. A series of these actuators can be modeled as a system of rigid bodies connected by torsional springs. As these bodies are actuated according to the motion pattern based on the individual caterpillar segments, ground contact forces are calculated and analyzed to determine the requirements of successful forward locomotion. The energetics of the analytical and numerical models are then compared and discussed.

  12. A biologically inspired scale-space for illumination invariant feature detection

    International Nuclear Information System (INIS)

    Vonikakis, Vasillios; Chrysostomou, Dimitrios; Kouskouridas, Rigas; Gasteratos, Antonios

    2013-01-01

    This paper presents a new illumination invariant operator, combining the nonlinear characteristics of biological center-surround cells with the classic difference of Gaussians operator. It specifically targets the underexposed image regions, exhibiting increased sensitivity to low contrast, while not affecting performance in the correctly exposed ones. The proposed operator can be used to create a scale-space, which in turn can be a part of a SIFT-based detector module. The main advantage of this illumination invariant scale-space is that, using just one global threshold, keypoints can be detected in both dark and bright image regions. In order to evaluate the degree of illumination invariance that the proposed, as well as other, existing, operators exhibit, a new benchmark dataset is introduced. It features a greater variety of imaging conditions, compared to existing databases, containing real scenes under various degrees and combinations of uniform and non-uniform illumination. Experimental results show that the proposed detector extracts a greater number of features, with a high level of repeatability, compared to other approaches, for both uniform and non-uniform illumination. This, along with its simple implementation, renders the proposed feature detector particularly appropriate for outdoor vision systems, working in environments under uncontrolled illumination conditions. (paper)

  13. Mathematical models in biological discovery

    CERN Document Server

    Walter, Charles

    1977-01-01

    When I was asked to help organize an American Association for the Advancement of Science symposium about how mathematical models have con­ tributed to biology, I agreed immediately. The subject is of immense importance and wide-spread interest. However, too often it is discussed in biologically sterile environments by "mutual admiration society" groups of "theoreticians", many of whom have never seen, and most of whom have never done, an original scientific experiment with the biolog­ ical materials they attempt to describe in abstract (and often prejudiced) terms. The opportunity to address the topic during an annual meeting of the AAAS was irresistable. In order to try to maintain the integrity ;,f the original intent of the symposium, it was entitled, "Contributions of Mathematical Models to Biological Discovery". This symposium was organized by Daniel Solomon and myself, held during the 141st annual meeting of the AAAS in New York during January, 1975, sponsored by sections G and N (Biological and Medic...

  14. A Mathematical Model of a Novel 3D Fractal-Inspired Piezoelectric Ultrasonic Transducer.

    Science.gov (United States)

    Canning, Sara; Walker, Alan J; Roach, Paul A

    2016-12-17

    Piezoelectric ultrasonic transducers have the potential to operate as both a sensor and as an actuator of ultrasonic waves. Currently, manufactured transducers operate effectively over narrow bandwidths as a result of their regular structures which incorporate a single length scale. To increase the operational bandwidth of these devices, consideration has been given in the literature to the implementation of designs which contain a range of length scales. In this paper, a mathematical model of a novel Sierpinski tetrix fractal-inspired transducer for sensor applications is presented. To accompany the growing body of research based on fractal-inspired transducers, this paper offers the first sensor design based on a three-dimensional fractal. The three-dimensional model reduces to an effective one-dimensional model by allowing for a number of assumptions of the propagating wave in the fractal lattice. The reception sensitivity of the sensor is investigated. Comparisons of reception force response (RFR) are performed between this novel design along with a previously investigated Sierpinski gasket-inspired device and standard Euclidean design. The results indicate that the proposed device surpasses traditional design sensors.

  15. Seeing by touch: evaluation of a soft biologically-inspired artificial fingertip in real-time active touch.

    Science.gov (United States)

    Assaf, Tareq; Roke, Calum; Rossiter, Jonathan; Pipe, Tony; Melhuish, Chris

    2014-02-07

    Effective tactile sensing for artificial platforms remains an open issue in robotics. This study investigates the performance of a soft biologically-inspired artificial fingertip in active exploration tasks. The fingertip sensor replicates the mechanisms within human skin and offers a robust solution that can be used both for tactile sensing and gripping/manipulating objects. The softness of the optical sensor's contact surface also allows safer interactions with objects. High-level tactile features such as edges are extrapolated from the sensor's output and the information is used to generate a tactile image. The work presented in this paper aims to investigate and evaluate this artificial fingertip for 2D shape reconstruction. The sensor was mounted on a robot arm to allow autonomous exploration of different objects. The sensor and a number of human participants were then tested for their abilities to track the raised perimeters of different planar objects and compared. By observing the technique and accuracy of the human subjects, simple but effective parameters were determined in order to evaluate the artificial system's performance. The results prove the capability of the sensor in such active exploration tasks, with a comparable performance to the human subjects despite it using tactile data alone whereas the human participants were also able to use proprioceptive cues.

  16. Biologically inspired flexible quasi-single-mode random laser: An integration of Pieris canidia butterfly wing and semiconductors

    Science.gov (United States)

    Wang, Cih-Su; Chang, Tsung-Yuan; Lin, Tai-Yuan; Chen, Yang-Fang

    2014-10-01

    Quasi-periodic structures of natural biomaterial membranes have great potentials to serve as resonance cavities to generate ecological friendly optoelectronic devices with low cost. To achieve the first attempt for the illustration of the underlying principle, the Pieris canidia butterfly wing was embedded with ZnO nanoparticles. Quite interestingly, it is found that the bio-inspired quasi-single-mode random laser can be achieved by the assistance of the skeleton of the membrane, in which ZnO nanoparticles act as emitting gain media. Such unique characteristics can be interpreted well by the Fabry-Perot resonance existing in the window-like quasi-periodic structure of butterfly wing. Due to the inherently promising flexibility of butterfly wing membrane, the laser action can still be maintained during the bending process. Our demonstrated approach not only indicates that the natural biological structures can provide effective scattering feedbacks but also pave a new avenue towards designing bio-controlled photonic devices.

  17. Biologically inspired flexible quasi-single-mode random laser: an integration of Pieris canidia butterfly wing and semiconductors.

    Science.gov (United States)

    Wang, Cih-Su; Chang, Tsung-Yuan; Lin, Tai-Yuan; Chen, Yang-Fang

    2014-10-23

    Quasi-periodic structures of natural biomaterial membranes have great potentials to serve as resonance cavities to generate ecological friendly optoelectronic devices with low cost. To achieve the first attempt for the illustration of the underlying principle, the Pieris canidia butterfly wing was embedded with ZnO nanoparticles. Quite interestingly, it is found that the bio-inspired quasi-single-mode random laser can be achieved by the assistance of the skeleton of the membrane, in which ZnO nanoparticles act as emitting gain media. Such unique characteristics can be interpreted well by the Fabry-Perot resonance existing in the window-like quasi-periodic structure of butterfly wing. Due to the inherently promising flexibility of butterfly wing membrane, the laser action can still be maintained during the bending process. Our demonstrated approach not only indicates that the natural biological structures can provide effective scattering feedbacks but also pave a new avenue towards designing bio-controlled photonic devices.

  18. A Digital Liquid State Machine With Biologically Inspired Learning and Its Application to Speech Recognition.

    Science.gov (United States)

    Zhang, Yong; Li, Peng; Jin, Yingyezhe; Choe, Yoonsuck

    2015-11-01

    This paper presents a bioinspired digital liquid-state machine (LSM) for low-power very-large-scale-integration (VLSI)-based machine learning applications. To the best of the authors' knowledge, this is the first work that employs a bioinspired spike-based learning algorithm for the LSM. With the proposed online learning, the LSM extracts information from input patterns on the fly without needing intermediate data storage as required in offline learning methods such as ridge regression. The proposed learning rule is local such that each synaptic weight update is based only upon the firing activities of the corresponding presynaptic and postsynaptic neurons without incurring global communications across the neural network. Compared with the backpropagation-based learning, the locality of computation in the proposed approach lends itself to efficient parallel VLSI implementation. We use subsets of the TI46 speech corpus to benchmark the bioinspired digital LSM. To reduce the complexity of the spiking neural network model without performance degradation for speech recognition, we study the impacts of synaptic models on the fading memory of the reservoir and hence the network performance. Moreover, we examine the tradeoffs between synaptic weight resolution, reservoir size, and recognition performance and present techniques to further reduce the overhead of hardware implementation. Our simulation results show that in terms of isolated word recognition evaluated using the TI46 speech corpus, the proposed digital LSM rivals the state-of-the-art hidden Markov-model-based recognizer Sphinx-4 and outperforms all other reported recognizers including the ones that are based upon the LSM or neural networks.

  19. Brain Inspired Cognitive Model with Attention for Self-Driving Cars

    OpenAIRE

    Chen, Shitao; Zhang, Songyi; Shang, Jinghao; Chen, Badong; Zheng, Nanning

    2017-01-01

    Perception-driven approach and end-to-end system are two major vision-based frameworks for self-driving cars. However, it is difficult to introduce attention and historical information of autonomous driving process, which are the essential factors for achieving human-like driving into these two methods. In this paper, we propose a novel model for self-driving cars named brain-inspired cognitive model with attention (CMA). This model consists of three parts: a convolutional neural network for ...

  20. Writing Inspired

    Science.gov (United States)

    Tischhauser, Karen

    2015-01-01

    Students need inspiration to write. Assigning is not teaching. In order to inspire students to write fiction worth reading, teachers must take them through the process of writing. Physical objects inspire good writing with depth. In this article, the reader will be taken through the process of inspiring young writers through the use of boxes.…

  1. Behavior-based obstacle avoidance capability for biologically inspired eight-legged walking robot

    International Nuclear Information System (INIS)

    Izzeldin Ibrahim Mohd; Shamsudin M Amin; Adel Ali Syed Al-Jumaily

    1999-01-01

    Behavior-based approach has proven to be useful in making mobile robot working in real world situations. Since the behaviors are responsible for managing the interaction between the robots and its environment, observing their use can be exploited to model these interactions. A real-time obstacle avoidance algorithm has been developed and implemented. This algorithm permits the detection of unknown obstacle simultaneously with the steering of the mobile robot to avoid collisions and advance toward the target. In our approach the robot is initially given a set of behavior-producing modules to choose from, and the algorithm provides a memory-based approach to dynamically adapt the selection of the behaviors according to the history of their use. We developed a set of algorithms, which uses Subsumption Architecture (SA) for controlling an eight-legged walking robot operating in closed vicinity. This paper describes a successful application of these algorithms to Oct-Ib robot and experimental results of the robot navigating in complex environment. (Author)

  2. Adhesive behaviour of gecko-inspired nanofibrillar arrays: combination of experiments and finite element modelling

    International Nuclear Information System (INIS)

    Wang Zhengzhi; Xu Yun; Gu Ping

    2012-01-01

    A polypropylene nanofibrillar array was successfully fabricated by template-assisted nanofabrication strategy. Adhesion properties of this gecko-inspired structure were studied through two parallel and independent approaches: experiments and finite element simulations. Experimental results show relatively good normal adhesion, but accompanied by high preloads. The interfacial adhesion was modelled by effective spring elements with piecewise-linear constitution. The effective elasticity of the fibre-array system was originally calculated from our measured elasticity of single nanowire. Comparisons of the experimental and simulative results reveal quantitative agreement except for some explainable deviations, which suggests the potential applicability of the present models and applied theories. (fast track communication)

  3. Manufacturing and Evaluation of a Biologically Inspired Engineered MAV Wing Compared to the Manduca Sexta Wing Under Simulated Flapping Conditions

    Science.gov (United States)

    2011-03-24

    and tested under simplified flapping conditions by analyzing ‘frozen’ digital images of the de - formed wing by methods of photogrammetry. This... Rocker System to Biological Flapping Mechanism . . . . . . . . . . . . . . 49 2.6 PhotoModeler Methods . . . . . . . . . . . . . . . . . . 55 2.7 A Word on...126 4.5.3 Residual Calculation . . . . . . . . . . . . . . . 127 4.5.4 Orientation Angle Determination (Torsional De

  4. A Physics-Inspired Mechanistic Model of Migratory Movement Patterns in Birds.

    Science.gov (United States)

    Revell, Christopher; Somveille, Marius

    2017-08-29

    In this paper, we introduce a mechanistic model of migratory movement patterns in birds, inspired by ideas and methods from physics. Previous studies have shed light on the factors influencing bird migration but have mainly relied on statistical correlative analysis of tracking data. Our novel method offers a bottom up explanation of population-level migratory movement patterns. It differs from previous mechanistic models of animal migration and enables predictions of pathways and destinations from a given starting location. We define an environmental potential landscape from environmental data and simulate bird movement within this landscape based on simple decision rules drawn from statistical mechanics. We explore the capacity of the model by qualitatively comparing simulation results to the non-breeding migration patterns of a seabird species, the Black-browed Albatross (Thalassarche melanophris). This minimal, two-parameter model was able to capture remarkably well the previously documented migration patterns of the Black-browed Albatross, with the best combination of parameter values conserved across multiple geographically separate populations. Our physics-inspired mechanistic model could be applied to other bird and highly-mobile species, improving our understanding of the relative importance of various factors driving migration and making predictions that could be useful for conservation.

  5. Time lags in biological models

    CERN Document Server

    MacDonald, Norman

    1978-01-01

    In many biological models it is necessary to allow the rates of change of the variables to depend on the past history, rather than only the current values, of the variables. The models may require discrete lags, with the use of delay-differential equations, or distributed lags, with the use of integro-differential equations. In these lecture notes I discuss the reasons for including lags, especially distributed lags, in biological models. These reasons may be inherent in the system studied, or may be the result of simplifying assumptions made in the model used. I examine some of the techniques available for studying the solution of the equations. A large proportion of the material presented relates to a special method that can be applied to a particular class of distributed lags. This method uses an extended set of ordinary differential equations. I examine the local stability of equilibrium points, and the existence and frequency of periodic solutions. I discuss the qualitative effects of lags, and how these...

  6. Template model inspired leg force feedback based control can assist human walking.

    Science.gov (United States)

    Zhao, Guoping; Sharbafi, Maziar; Vlutters, Mark; van Asseldonk, Edwin; Seyfarth, Andre

    2017-07-01

    We present a novel control approach for assistive lower-extremity exoskeletons. In particular, we implement a virtual pivot point (VPP) template model inspired leg force feedback based controller on a lower-extremity powered exoskeleton (LOPES II) and demonstrate that it can effectively assist humans during walking. It has been shown that the VPP template model is capable of stabilizing the trunk and reproduce a human-like hip torque during the stance phase of walking. With leg force and joint angle feedback inspired by the VPP template model, our controller provides hip and knee torque assistance during the stance phase. A pilot experiment was conducted with four healthy subjects. Joint kinematics, leg muscle electromyography (EMG), and metabolic cost were measured during walking with and without assistance. Results show that, for 0.6 m/s walking, our controller can reduce leg muscle activations, especially for the medial gastrocnemius (about 16.0%), while hip and knee joint kinematics remain similar to the condition without the controller. Besides, the controller also reduces 10% of the net metabolic cost during walking. This paper demonstrates walking assistance benefits of the VPP template model for the first time. The support of human walking is achieved by a force feedback of leg force applied to the control of hip and knee joints. It can help us to provide a framework for investigating walking assistance control in the future.

  7. A SUSY inspired simplified model for the 750 GeV diphoton excess

    Energy Technology Data Exchange (ETDEWEB)

    Gabrielli, E. [Dipart. di Fisica Teorica, Università di Trieste, Strada Costiera 11, I-34151 Trieste (Italy); INFN, Sezione di Trieste, Via Valerio 2, I-34127 Trieste (Italy); NICPB, Rävala 10, Tallinn 10143 (Estonia); Kannike, K., E-mail: kannike@cern.ch [NICPB, Rävala 10, Tallinn 10143 (Estonia); Mele, B. [INFN, Sezione di Roma, c/o Dipart. di Fisica, Università di Roma “La Sapienza”, Piazzale Aldo Moro 2, I-00185 Rome (Italy); Raidal, M. [NICPB, Rävala 10, Tallinn 10143 (Estonia); Institute of Physics, University of Tartu (Estonia); Spethmann, C.; Veermäe, H. [NICPB, Rävala 10, Tallinn 10143 (Estonia)

    2016-05-10

    The evidence for a new neutral scalar particle from the 750 GeV diphoton excess, and the absence of any other signal of new physics at the LHC so far, suggests the existence of new coloured scalars. To study this possibility, we propose a supersymmetry inspired simplified model, extending the Standard Model with a singlet scalar and with heavy scalar fields carrying both colour and electric charges – new scalar quarks. To allow the latter to decay, and to generate the dark matter of the Universe, we also add a neutral fermion to the particle content. We show that this model provides a two-parameter fit to the observed diphoton excess consistently with cosmology, while the allowed parameter space is bounded by the consistency of the model. In the context of our simplified model this implies the existence of other supersymmetric particles accessible at the LHC, rendering this scenario falsifiable.

  8. Deep Neural Networks: A New Framework for Modeling Biological Vision and Brain Information Processing.

    Science.gov (United States)

    Kriegeskorte, Nikolaus

    2015-11-24

    Recent advances in neural network modeling have enabled major strides in computer vision and other artificial intelligence applications. Human-level visual recognition abilities are coming within reach of artificial systems. Artificial neural networks are inspired by the brain, and their computations could be implemented in biological neurons. Convolutional feedforward networks, which now dominate computer vision, take further inspiration from the architecture of the primate visual hierarchy. However, the current models are designed with engineering goals, not to model brain computations. Nevertheless, initial studies comparing internal representations between these models and primate brains find surprisingly similar representational spaces. With human-level performance no longer out of reach, we are entering an exciting new era, in which we will be able to build biologically faithful feedforward and recurrent computational models of how biological brains perform high-level feats of intelligence, including vision.

  9. Biological transportation networks: Modeling and simulation

    KAUST Repository

    Albi, Giacomo; Artina, Marco; Foransier, Massimo; Markowich, Peter A.

    2015-01-01

    We present a model for biological network formation originally introduced by Cai and Hu [Adaptation and optimization of biological transport networks, Phys. Rev. Lett. 111 (2013) 138701]. The modeling of fluid transportation (e.g., leaf venation

  10. Inspired Responses

    Science.gov (United States)

    Steele, Carol Frederick

    2011-01-01

    In terms of teacher quality, Steele believes the best teachers have reached a stage she terms inspired, and that teachers move progressively through the stages of unaware, aware, and capable until the most reflective teachers finally reach the inspired level. Inspired teachers have a wide repertoire of teaching and class management techniques and…

  11. Modelling air quality according to INSPIRE data specifications, ISO standards and national regulations

    Directory of Open Access Journals (Sweden)

    Pachelski Wojciech

    2017-12-01

    Full Text Available Protection of the environment is an activity of many institutions, organizations and communities from global to regional and local scales. Any activity in this area needs structured database records, using advanced methodology, given, among others, in INSPIRE documents, ISO standards of 19100 series, and national regulations. The goal of this paper is to analyse both the legal provisions related to the air quality and also data sources associated with the prevention of air pollution. Furthermore, the UML application schema of the spatial data related to the air protection is proposed, for the use by urban planners. Also, the overview of the methodology of geographic information is given, including the Unified Modelling Language (UML, as well as the basic concepts of conceptual models within the INSPIRE project. The study is based on the relevant literature and documents, as well as on the expert knowledge gained through urban planning practice, as well as on the analysis of the spatial planning regulations. The UML application schema for different aspects related to the air protection, as presented in this paper, is an example of how to use the methodology also in other fields of the environment protection. Spatial planners know how to improve the air quality, but in the present state of law they often suffer from the lack of planning tools for real actions. In the spatial planners work an important issue are data that allow a thorough analysis of the area.

  12. Fermion Mass Textures in an M-Inspired Flipped SU(5) Model Derived from String

    CERN Document Server

    Ellis, Jonathan Richard; Lola, S; Nanopoulos, Dimitri V

    1998-01-01

    We are inspired by the facts that M-theory may reconcile the supersymmetric GUT scale with that of quantum gravity, and that it provides new avenues for low-energy supersymmetry breaking, to re-examine a flipped SU(5) model that has been derived from string and may possess an elevation to a fully-fledged M-phenomenological model. Using a complete analysis of all superpotential terms through the sixth order, we explore in this model a new flat potential direction that provides a pair of light Higgs doublets, yields realistic textures for the fermion mass matrices, and is free of R-violating interactions and dimension-five proton decay operators.

  13. Human Inspired Self-developmental Model of Neural Network (HIM): Introducing Content/Form Computing

    Science.gov (United States)

    Krajíček, Jiří

    This paper presents cross-disciplinary research between medical/psychological evidence on human abilities and informatics needs to update current models in computer science to support alternative methods for computation and communication. In [10] we have already proposed hypothesis introducing concept of human information model (HIM) as cooperative system. Here we continue on HIM design in detail. In our design, first we introduce Content/Form computing system which is new principle of present methods in evolutionary computing (genetic algorithms, genetic programming). Then we apply this system on HIM (type of artificial neural network) model as basic network self-developmental paradigm. Main inspiration of our natural/human design comes from well known concept of artificial neural networks, medical/psychological evidence and Sheldrake theory of "Nature as Alive" [22].

  14. Track structure in biological models.

    Science.gov (United States)

    Curtis, S B

    1986-01-01

    High-energy heavy ions in the galactic cosmic radiation (HZE particles) may pose a special risk during long term manned space flights outside the sheltering confines of the earth's geomagnetic field. These particles are highly ionizing, and they and their nuclear secondaries can penetrate many centimeters of body tissue. The three dimensional patterns of ionizations they create as they lose energy are referred to as their track structure. Several models of biological action on mammalian cells attempt to treat track structure or related quantities in their formulation. The methods by which they do this are reviewed. The proximity function is introduced in connection with the theory of Dual Radiation Action (DRA). The ion-gamma kill (IGK) model introduces the radial energy-density distribution, which is a smooth function characterizing both the magnitude and extension of a charged particle track. The lethal, potentially lethal (LPL) model introduces lambda, the mean distance between relevant ion clusters or biochemical species along the track. Since very localized energy depositions (within approximately 10 nm) are emphasized, the proximity function as defined in the DRA model is not of utility in characterizing track structure in the LPL formulation.

  15. Integrating systems biology models and biomedical ontologies.

    Science.gov (United States)

    Hoehndorf, Robert; Dumontier, Michel; Gennari, John H; Wimalaratne, Sarala; de Bono, Bernard; Cook, Daniel L; Gkoutos, Georgios V

    2011-08-11

    Systems biology is an approach to biology that emphasizes the structure and dynamic behavior of biological systems and the interactions that occur within them. To succeed, systems biology crucially depends on the accessibility and integration of data across domains and levels of granularity. Biomedical ontologies were developed to facilitate such an integration of data and are often used to annotate biosimulation models in systems biology. We provide a framework to integrate representations of in silico systems biology with those of in vivo biology as described by biomedical ontologies and demonstrate this framework using the Systems Biology Markup Language. We developed the SBML Harvester software that automatically converts annotated SBML models into OWL and we apply our software to those biosimulation models that are contained in the BioModels Database. We utilize the resulting knowledge base for complex biological queries that can bridge levels of granularity, verify models based on the biological phenomenon they represent and provide a means to establish a basic qualitative layer on which to express the semantics of biosimulation models. We establish an information flow between biomedical ontologies and biosimulation models and we demonstrate that the integration of annotated biosimulation models and biomedical ontologies enables the verification of models as well as expressive queries. Establishing a bi-directional information flow between systems biology and biomedical ontologies has the potential to enable large-scale analyses of biological systems that span levels of granularity from molecules to organisms.

  16. A Reconfigurable and Biologically Inspired Paradigm for Computation Using Network-On-Chip and Spiking Neural Networks

    Directory of Open Access Journals (Sweden)

    Jim Harkin

    2009-01-01

    Full Text Available FPGA devices have emerged as a popular platform for the rapid prototyping of biological Spiking Neural Networks (SNNs applications, offering the key requirement of reconfigurability. However, FPGAs do not efficiently realise the biologically plausible neuron and synaptic models of SNNs, and current FPGA routing structures cannot accommodate the high levels of interneuron connectivity inherent in complex SNNs. This paper highlights and discusses the current challenges of implementing scalable SNNs on reconfigurable FPGAs. The paper proposes a novel field programmable neural network architecture (EMBRACE, incorporating low-power analogue spiking neurons, interconnected using a Network-on-Chip architecture. Results on the evaluation of the EMBRACE architecture using the XOR benchmark problem are presented, and the performance of the architecture is discussed. The paper also discusses the adaptability of the EMBRACE architecture in supporting fault tolerant computing.

  17. Low-energy consequences of superstring-inspired models with intermediate-mass scales

    International Nuclear Information System (INIS)

    Gabbiani, F.

    1987-01-01

    The phenomenological consequences of implementing intermediate-mass scales in E 6 superstring-inspired models are discussed. Starting from a suitable Calabi-Yau compactification with b 1,1 >1, one gets, after Hosotani breaking, the rank r=5 gauge group SU(3) C x SU(2) L x U(1) Y x U(1) E , that is broken at an intermediate-mass scale down to the standard-model group. The analysis of both the intermediate and the electroweak breaking is performed in the two cases Λ c = M x and Λ c x , where Λ c is the scale at which the hidden sector gauginos condensate. It is performed quantitatively the minimization of the low-energy effective potential and the renormalization group analysis, yielding a viable set of mass spectra and confirming the reliability of the intermediate-breaking scheme

  18. Synchronization of multi-phase oscillators: an Axelrod-inspired model

    Science.gov (United States)

    Kuperman, M. N.; Zanette, D. H.

    2009-07-01

    Inspired by Axelrod’s model of culture dissemination, we introduce and analyze a model for a population of coupled oscillators where different levels of synchronization can be assimilated to different degrees of cultural organization. The state of each oscillator is represented by a set of phases, and the interaction - which occurs between homologous phases - is weighted by a decreasing function of the distance between individual states. Both ordered arrays and random networks are considered. We find that the transition between synchronization and incoherent behaviour is mediated by a clustering regime with rich organizational structure, where any two oscillators can be synchronized in some of their phases, while their remain unsynchronized in the others.

  19. Aerodynamic robustness in owl-inspired leading-edge serrations: a computational wind-gust model.

    Science.gov (United States)

    Rao, Chen; Liu, Hao

    2018-06-08

    Owls are a master to achieve silent flight in gliding and flapping flights under natural turbulent environments owing to their unique wing morphologies. While the leading-edge serrations are recently revealed, as a passive flow control micro-device, to play a crucial role in aerodynamic force production and sound suppression [25], the characteristics of wind-gust rejection associated with leading-edge serrations remain unclear. Here we address a large-eddy simulation (LES)-based study of aerodynamic robustness in owl-inspired leading-edge serrations, which is conducted with clean and serrated wing models through mimicking wind-gusts under a longitudinal fluctuation in free-stream inflow and a lateral fluctuation in pitch angle over a broad range of angles of attack (AoAs) over 0° ≤ Φ ≤ 20°. Our results show that the leading-edge serration-based passive flow control mechanisms associated with laminar-turbulent transition work effectively under fluctuated inflow and wing pitch, indicating that the leading-edge serrations are of potential gust fluctuation rejection or robustness in aerodynamic performance. Moreover, it is revealed that the tradeoff between turbulent flow control (i.e., aero-acoustic suppression) and force production in the serrated model holds independently to the wind-gust environments: poor at lower AoAs but capable of achieving equivalent aerodynamic performance at higher AoAs > 15o compared to the clean model. Our results reveal that the owl-inspired leading-edge serrations can be a robust micro-device for aero-acoustic control coping with unsteady and complex wind environments in biomimetic rotor designs for various fluid machineries. © 2018 IOP Publishing Ltd.

  20. Network model of chemical-sensing system inspired by mouse taste buds.

    Science.gov (United States)

    Tateno, Katsumi; Igarashi, Jun; Ohtubo, Yoshitaka; Nakada, Kazuki; Miki, Tsutomu; Yoshii, Kiyonori

    2011-07-01

    Taste buds endure extreme changes in temperature, pH, osmolarity, so on. Even though taste bud cells are replaced in a short span, they contribute to consistent taste reception. Each taste bud consists of about 50 cells whose networks are assumed to process taste information, at least preliminarily. In this article, we describe a neural network model inspired by the taste bud cells of mice. It consists of two layers. In the first layer, the chemical stimulus is transduced into an irregular spike train. The synchronization of the output impulses is induced by the irregular spike train at the second layer. These results show that the intensity of the chemical stimulus is encoded as the degree of the synchronization of output impulses. The present algorithms for signal processing result in a robust chemical-sensing system.

  1. Inspiration from drones, Lidar measurements and 3D models in undergraduate teaching

    Science.gov (United States)

    Blenkinsop, Thomas; Ellis, Jennifer

    2017-04-01

    Three-dimensional models, photogrammetry and remote sensing are increasingly common techniques used in structural analysis. We have found that using drones and Lidar on undergraduate field trips has piqued interest in fieldwork, provided data for follow-up laboratory exercises, and inspired undergraduates to attempt 3D modelling in independent mapping projects. The scale of structures visible in cliff and sea shore exposures in South Wales is ideal for using drones to capture images for 3D models. Fault scarps in the South Wales coalfield were scanned by Lidar and drone. Our experience suggests that the drone data were much easier to acquire and process than the Lidar data, and adequate for most teaching purposes. In the lab, we used the models to show the structure in 3D, and as the basis for an introduction to geological modelling software. Now that tools for photogrammetry, drones, and processing software are widely available and affordable, they can be readily integrated into teaching. An additional benefit from the images and models is that they may be used for exercises that can be substituted for fieldwork to achieve some (but not all) of the learning outcomes in the case that field access is prevented.

  2. Dynamics of underwater legged locomotion: modeling and experiments on an octopus-inspired robot.

    Science.gov (United States)

    Calisti, M; Corucci, F; Arienti, A; Laschi, C

    2015-07-30

    This paper studies underwater legged locomotion (ULL) by means of a robotic octopus-inspired prototype and its associated model. Two different types of propulsive actions are embedded into the robot model: reaction forces due to leg contact with the ground and hydrodynamic forces such as the drag arising from the sculling motion of the legs. Dynamic parameters of the model are estimated by means of evolutionary techniques and subsequently the model is exploited to highlight some distinctive features of ULL. Specifically, the separation between the center of buoyancy (CoB)/center of mass and density affect the stability and speed of the robot, whereas the sculling movements contribute to propelling the robot even when its legs are detached from the ground. The relevance of these effects is demonstrated through robotic experiments and model simulations; moreover, by slightly changing the position of the CoB in the presence of the same feed-forward activation, a number of different behaviors (i.e. forward and backward locomotion at different speeds) are achieved.

  3. Retina-Inspired Filter.

    Science.gov (United States)

    Doutsi, Effrosyni; Fillatre, Lionel; Antonini, Marc; Gaulmin, Julien

    2018-07-01

    This paper introduces a novel filter, which is inspired by the human retina. The human retina consists of three different layers: the Outer Plexiform Layer (OPL), the inner plexiform layer, and the ganglionic layer. Our inspiration is the linear transform which takes place in the OPL and has been mathematically described by the neuroscientific model "virtual retina." This model is the cornerstone to derive the non-separable spatio-temporal OPL retina-inspired filter, briefly renamed retina-inspired filter, studied in this paper. This filter is connected to the dynamic behavior of the retina, which enables the retina to increase the sharpness of the visual stimulus during filtering before its transmission to the brain. We establish that this retina-inspired transform forms a group of spatio-temporal Weighted Difference of Gaussian (WDoG) filters when it is applied to a still image visible for a given time. We analyze the spatial frequency bandwidth of the retina-inspired filter with respect to time. It is shown that the WDoG spectrum varies from a lowpass filter to a bandpass filter. Therefore, while time increases, the retina-inspired filter enables to extract different kinds of information from the input image. Finally, we discuss the benefits of using the retina-inspired filter in image processing applications such as edge detection and compression.

  4. A biological compression model and its applications.

    Science.gov (United States)

    Cao, Minh Duc; Dix, Trevor I; Allison, Lloyd

    2011-01-01

    A biological compression model, expert model, is presented which is superior to existing compression algorithms in both compression performance and speed. The model is able to compress whole eukaryotic genomes. Most importantly, the model provides a framework for knowledge discovery from biological data. It can be used for repeat element discovery, sequence alignment and phylogenetic analysis. We demonstrate that the model can handle statistically biased sequences and distantly related sequences where conventional knowledge discovery tools often fail.

  5. Neurobiologically inspired mobile robot navigation and planning

    Directory of Open Access Journals (Sweden)

    Mathias Quoy

    2007-11-01

    Full Text Available After a short review of biologically inspired navigation architectures, mainly relying on modeling the hippocampal anatomy, or at least some of its functions, we present a navigation and planning model for mobile robots. This architecture is based on a model of the hippocampal and prefrontal interactions. In particular, the system relies on the definition of a new cell type “transition cells” that encompasses traditional “place cells”.

  6. Continuum Modeling of Biological Network Formation

    KAUST Repository

    Albi, Giacomo; Burger, Martin; Haskovec, Jan; Markowich, Peter A.; Schlottbom, Matthias

    2017-01-01

    We present an overview of recent analytical and numerical results for the elliptic–parabolic system of partial differential equations proposed by Hu and Cai, which models the formation of biological transportation networks. The model describes

  7. Fast prediction and evaluation of eccentric inspirals using reduced-order models

    Science.gov (United States)

    Barta, Dániel; Vasúth, Mátyás

    2018-06-01

    A large number of theoretically predicted waveforms are required by matched-filtering searches for the gravitational-wave signals produced by compact binary coalescence. In order to substantially alleviate the computational burden in gravitational-wave searches and parameter estimation without degrading the signal detectability, we propose a novel reduced-order-model (ROM) approach with applications to adiabatic 3PN-accurate inspiral waveforms of nonspinning sources that evolve on either highly or slightly eccentric orbits. We provide a singular-value decomposition-based reduced-basis method in the frequency domain to generate reduced-order approximations of any gravitational waves with acceptable accuracy and precision within the parameter range of the model. We construct efficient reduced bases comprised of a relatively small number of the most relevant waveforms over three-dimensional parameter-space covered by the template bank (total mass 2.15 M⊙≤M ≤215 M⊙ , mass ratio 0.01 ≤q ≤1 , and initial orbital eccentricity 0 ≤e0≤0.95 ). The ROM is designed to predict signals in the frequency band from 10 Hz to 2 kHz for aLIGO and aVirgo design sensitivity. Beside moderating the data reduction, finer sampling of fiducial templates improves the accuracy of surrogates. Considerable increase in the speedup from several hundreds to thousands can be achieved by evaluating surrogates for low-mass systems especially when combined with high-eccentricity.

  8. LHC Phenomenology and Cosmology of String-Inspired Intersecting D-Brane Models

    CERN Document Server

    Anchordoqui, Luis A.; Goldberg, Haim; Huang, Xing; Lust, Dieter; Taylor, Tomasz R.; Vlcek, Brian

    2012-01-01

    We discuss the phenomenology and cosmology of a Standard-like Model inspired by string theory, in which the gauge fields are localized on D-branes wrapping certain compact cycles on an underlying geometry, whose intersection can give rise to chiral fermions. The energy scale associated with string physics is assumed to be near the Planck mass. To develop our program in the simplest way, we work within the construct of a minimal model with gauge-extended sector U (3)_B \\times Sp (1)_L \\times U (1)_{I_R} \\times U (1)_L. The resulting U (1) content gauges the baryon number B, the lepton number L, and a third additional abelian charge I_R which acts as the third isospin component of an SU(2)_R. All mixing angles and gauge couplings are fixed by rotation of the U(1) gauge fields to a basis diagonal in hypercharge Y and in an anomaly free linear combination of I_R and B-L. The anomalous $Z'$ gauge boson obtains a string scale St\\"uckelberg mass via a 4D version of the Green-Schwarz mechanism. To keep the realizatio...

  9. Accelerating Inspire

    CERN Document Server

    AUTHOR|(CDS)2266999

    2017-01-01

    CERN has been involved in the dissemination of scientific results since its early days and has continuously updated the distribution channels. Currently, Inspire hosts catalogues of articles, authors, institutions, conferences, jobs, experiments, journals and more. Successful orientation among this amount of data requires comprehensive linking between the content. Inspire has lacked a system for linking experiments and articles together based on which accelerator they were conducted at. The purpose of this project has been to create such a system. Records for 156 accelerators were created and all 2913 experiments on Inspire were given corresponding MARC tags. Records of 18404 accelerator physics related bibliographic entries were also tagged with corresponding accelerator tags. Finally, as a part of the endeavour to broaden CERN's presence on Wikipedia, existing Wikipedia articles of accelerators were updated with short descriptions and links to Inspire. In total, 86 Wikipedia articles were updated. This repo...

  10. A physiologically-inspired model of numerical classification based on graded stimulus coding

    Directory of Open Access Journals (Sweden)

    John Pearson

    2010-01-01

    Full Text Available In most natural decision contexts, the process of selecting among competing actions takes place in the presence of informative, but potentially ambiguous, stimuli. Decisions about magnitudes—quantities like time, length, and brightness that are linearly ordered—constitute an important subclass of such decisions. It has long been known that perceptual judgments about such quantities obey Weber’s Law, wherein the just-noticeable difference in a magnitude is proportional to the magnitude itself. Current physiologically inspired models of numerical classification assume discriminations are made via a labeled line code of neurons selectively tuned for numerosity, a pattern observed in the firing rates of neurons in the ventral intraparietal area (VIP of the macaque. By contrast, neurons in the contiguous lateral intraparietal area (LIP signal numerosity in a graded fashion, suggesting the possibility that numerical classification could be achieved in the absence of neurons tuned for number. Here, we consider the performance of a decision model based on this analog coding scheme in a paradigmatic discrimination task—numerosity bisection. We demonstrate that a basic two-neuron classifier model, derived from experimentally measured monotonic responses of LIP neurons, is sufficient to reproduce the numerosity bisection behavior of monkeys, and that the threshold of the classifier can be set by reward maximization via a simple learning rule. In addition, our model predicts deviations from Weber Law scaling of choice behavior at high numerosity. Together, these results suggest both a generic neuronal framework for magnitude-based decisions and a role for reward contingency in the classification of such stimuli.

  11. Thermal impact of migrating birds' wing color on their flight performance: Possibility of new generation of biologically inspired drones.

    Science.gov (United States)

    Hassanalian, M; Abdelmoula, H; Ben Ayed, S; Abdelkefi, A

    2017-05-01

    The thermal impact of the birds' color on their flight performance are investigated. In most of the large migrating birds, the top of their wings is black. Considering this natural phenomenon in the migrating birds, such as albatross, a thermal analysis of the boundary layer of their wings is performed during the year depending on the solar insulation. It is shown that the temperature difference between the bright and dark colored top wing surface is around 10°C. The dark color on the top of the wing increases the temperature of the boundary layer over the wing which consequently reduces the skin drag force over the wing. This reduction in the drag force can be considered as one of the effective factors for long endurance of these migrating birds. This research should lead to improved designs of the drones by applying the inspired colors which can help drones increase their endurance. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. Squid-inspired vehicle design using coupled fluid-solid analytical modeling

    Science.gov (United States)

    Giorgio-Serchi, Francesco; Weymouth, Gabriel

    2017-11-01

    The need for enhanced automation in the marine and maritime fields is fostering research into robust and highly maneuverable autonomous underwater vehicles. To address these needs we develop design principles for a new generation of soft-bodied aquatic vehicles similar to octopi and squids. In particular, we consider the capability of pulsed-jetting bodies to boost thrust by actively modifying their external body-shape and in this way benefit of the contribution from added-mass variation. We present an analytical formulation of the coupled fluid-structure interaction between the elastic body and the ambient fluid. The model incorporates a number of new salient contributions to the soft-body dynamics. We highlight the role of added-mass variation effects of the external fluid in enhancing thrust and assess how the shape-changing actuation is impeded by a confinement-related unsteady inertial term and by an external shape-dependent fluid stiffness contribution. We show how the analysis of these combined terms has guided us to the design of a new prototype of a squid-inspired vehicle tuning of the natural frequency of the coupled fluid-solid system with the purpose of optimizing its actuation routine.

  13. Bianchi Type I Cosmological Models in Eddington-inspired Born–Infeld Gravity

    Directory of Open Access Journals (Sweden)

    Tiberiu Harko

    2014-10-01

    Full Text Available We consider the dynamics of a barotropic cosmological fluid in an anisotropic, Bianchi type I space-time in Eddington-inspired Born–Infeld (EiBI gravity. By assuming isotropic pressure distribution, we obtain the general solution of the field equations in an exact parametric form. The behavior of the geometric and thermodynamic parameters of the Bianchi type I Universe is studied, by using both analytical and numerical methods, for some classes of high density matter, described by the stiff causal, radiation, and pressureless fluid equations of state. In all cases the study of the models with different equations of state can be reduced to the integration of a highly nonlinear second order ordinary differential equation for the energy density. The time evolution of the anisotropic Bianchi type I Universe strongly depends on the initial values of the energy density and of the Hubble function. An important observational parameter, the mean anisotropy parameter, is also studied in detail, and we show that for the dust filled Universe the cosmological evolution always ends into isotropic phase, while for high density matter filled universes the isotropization of Bianchi type I universes is essentially determined by the initial conditions of the energy density.

  14. Inspiration from nature: dynamic modelling of the musculoskeletal structure of the seahorse tail.

    Science.gov (United States)

    Praet, Tomas; Adriaens, Dominique; Van Cauter, Sofie; Masschaele, Bert; De Beule, Matthieu; Verhegghe, Benedict

    2012-10-01

    Technological advances are often inspired by nature, considering that engineering is frequently faced by the same challenges as organisms in nature. One such interesting challenge is creating a structure that is at the same time stiff in a certain direction, yet flexible in another. The seahorse tail combines both radial stiffness and bending flexibility in a particularly elegant way: even though the tail is covered in a protective armour, it still shows sufficient flexibility to fully function as a prehensile organ. We therefore study the complex mechanics and dynamics of the musculoskeletal system of the seahorse tail from an engineering point of view. The seahorse tail derives its combination of flexibility and resilience from a chain of articulating skeletal segments. A versatile dynamic model of those segments was constructed, on the basis of automatic recognition of joint positions and muscle attachments. Both muscle structures that are thought to be responsible for ventral and ventral-lateral tail bending, namely the median ventral muscles and the hypaxial myomere muscles, were included in the model. Simulations on the model consist mainly of dynamic multi-body simulations. The results show that the sequential structure of uniformly shaped bony segments can remain flexible because of gliding joints that connect the corners of the segments. Radial stiffness on the other hand is obtained through the support that the central vertebra provides to the tail plating. Such insights could help in designing biomedical instruments that specifically require both high bending flexibility and radial stiffness (e.g. flexible stents and steerable catheters). Copyright © 2012 John Wiley & Sons, Ltd.

  15. Piecewise deterministic processes in biological models

    CERN Document Server

    Rudnicki, Ryszard

    2017-01-01

    This book presents a concise introduction to piecewise deterministic Markov processes (PDMPs), with particular emphasis on their applications to biological models. Further, it presents examples of biological phenomena, such as gene activity and population growth, where different types of PDMPs appear: continuous time Markov chains, deterministic processes with jumps, processes with switching dynamics, and point processes. Subsequent chapters present the necessary tools from the theory of stochastic processes and semigroups of linear operators, as well as theoretical results concerning the long-time behaviour of stochastic semigroups induced by PDMPs and their applications to biological models. As such, the book offers a valuable resource for mathematicians and biologists alike. The first group will find new biological models that lead to interesting and often new mathematical questions, while the second can observe how to include seemingly disparate biological processes into a unified mathematical theory, and...

  16. Bio-inspired vision

    International Nuclear Information System (INIS)

    Posch, C

    2012-01-01

    Nature still outperforms the most powerful computers in routine functions involving perception, sensing and actuation like vision, audition, and motion control, and is, most strikingly, orders of magnitude more energy-efficient than its artificial competitors. The reasons for the superior performance of biological systems are subject to diverse investigations, but it is clear that the form of hardware and the style of computation in nervous systems are fundamentally different from what is used in artificial synchronous information processing systems. Very generally speaking, biological neural systems rely on a large number of relatively simple, slow and unreliable processing elements and obtain performance and robustness from a massively parallel principle of operation and a high level of redundancy where the failure of single elements usually does not induce any observable system performance degradation. In the late 1980's, Carver Mead demonstrated that silicon VLSI technology can be employed in implementing ''neuromorphic'' circuits that mimic neural functions and fabricating building blocks that work like their biological role models. Neuromorphic systems, as the biological systems they model, are adaptive, fault-tolerant and scalable, and process information using energy-efficient, asynchronous, event-driven methods. In this paper, some basics of neuromorphic electronic engineering and its impact on recent developments in optical sensing and artificial vision are presented. It is demonstrated that bio-inspired vision systems have the potential to outperform conventional, frame-based vision acquisition and processing systems in many application fields and to establish new benchmarks in terms of redundancy suppression/data compression, dynamic range, temporal resolution and power efficiency to realize advanced functionality like 3D vision, object tracking, motor control, visual feedback loops, etc. in real-time. It is argued that future artificial vision systems

  17. Toward synthesizing executable models in biology.

    Science.gov (United States)

    Fisher, Jasmin; Piterman, Nir; Bodik, Rastislav

    2014-01-01

    Over the last decade, executable models of biological behaviors have repeatedly provided new scientific discoveries, uncovered novel insights, and directed new experimental avenues. These models are computer programs whose execution mechanistically simulates aspects of the cell's behaviors. If the observed behavior of the program agrees with the observed biological behavior, then the program explains the phenomena. This approach has proven beneficial for gaining new biological insights and directing new experimental avenues. One advantage of this approach is that techniques for analysis of computer programs can be applied to the analysis of executable models. For example, one can confirm that a model agrees with experiments for all possible executions of the model (corresponding to all environmental conditions), even if there are a huge number of executions. Various formal methods have been adapted for this context, for example, model checking or symbolic analysis of state spaces. To avoid manual construction of executable models, one can apply synthesis, a method to produce programs automatically from high-level specifications. In the context of biological modeling, synthesis would correspond to extracting executable models from experimental data. We survey recent results about the usage of the techniques underlying synthesis of computer programs for the inference of biological models from experimental data. We describe synthesis of biological models from curated mutation experiment data, inferring network connectivity models from phosphoproteomic data, and synthesis of Boolean networks from gene expression data. While much work has been done on automated analysis of similar datasets using machine learning and artificial intelligence, using synthesis techniques provides new opportunities such as efficient computation of disambiguating experiments, as well as the ability to produce different kinds of models automatically from biological data.

  18. Towards Synthesizing Executable Models in Biology

    Directory of Open Access Journals (Sweden)

    Jasmin eFisher

    2014-12-01

    Full Text Available Over the last decade, executable models of biological behaviors have repeatedly provided new scientific discoveries, uncovered novel insights, and directed new experimental avenues. These models are computer programs whose execution mechanistically simulates aspects of the cell’s behaviors. If the observed behavior of the program agrees with the observed biological behavior, then the program explains the phenomena. This approach has proven beneficial for gaining new biological insights and directing new experimental avenues. One advantage of this approach is that techniques for analysis of computer programs can be applied to the analysis of executable models. For example, one can confirm that a model agrees with experiments for all possible executions of the model (corresponding to all environmental conditions, even if there are a huge number of executions. Various formal methods have been adapted for this context, for example, model checking or symbolic analysis of state spaces. To avoid manual construction of executable models, one can apply synthesis, a method to produce programs automatically from high-level specifications. In the context of biological modelling, synthesis would correspond to extracting executable models from experimental data. We survey recent results about the usage of the techniques underlying synthesis of computer programs for the inference of biological models from experimental data. We describe synthesis of biological models from curated mutation experiment data, inferring network connectivity models from phosphoproteomic data, and synthesis of Boolean networks from gene expression data. While much work has been done on automated analysis of similar datasets using machine learning and artificial intelligence, using synthesis techniques provides new opportunities such as efficient computation of disambiguating experiments, as well as the ability to produce different kinds of models automatically from biological data.

  19. Integrating interactive computational modeling in biology curricula.

    Directory of Open Access Journals (Sweden)

    Tomáš Helikar

    2015-03-01

    Full Text Available While the use of computer tools to simulate complex processes such as computer circuits is normal practice in fields like engineering, the majority of life sciences/biological sciences courses continue to rely on the traditional textbook and memorization approach. To address this issue, we explored the use of the Cell Collective platform as a novel, interactive, and evolving pedagogical tool to foster student engagement, creativity, and higher-level thinking. Cell Collective is a Web-based platform used to create and simulate dynamical models of various biological processes. Students can create models of cells, diseases, or pathways themselves or explore existing models. This technology was implemented in both undergraduate and graduate courses as a pilot study to determine the feasibility of such software at the university level. First, a new (In Silico Biology class was developed to enable students to learn biology by "building and breaking it" via computer models and their simulations. This class and technology also provide a non-intimidating way to incorporate mathematical and computational concepts into a class with students who have a limited mathematical background. Second, we used the technology to mediate the use of simulations and modeling modules as a learning tool for traditional biological concepts, such as T cell differentiation or cell cycle regulation, in existing biology courses. Results of this pilot application suggest that there is promise in the use of computational modeling and software tools such as Cell Collective to provide new teaching methods in biology and contribute to the implementation of the "Vision and Change" call to action in undergraduate biology education by providing a hands-on approach to biology.

  20. Integrating interactive computational modeling in biology curricula.

    Science.gov (United States)

    Helikar, Tomáš; Cutucache, Christine E; Dahlquist, Lauren M; Herek, Tyler A; Larson, Joshua J; Rogers, Jim A

    2015-03-01

    While the use of computer tools to simulate complex processes such as computer circuits is normal practice in fields like engineering, the majority of life sciences/biological sciences courses continue to rely on the traditional textbook and memorization approach. To address this issue, we explored the use of the Cell Collective platform as a novel, interactive, and evolving pedagogical tool to foster student engagement, creativity, and higher-level thinking. Cell Collective is a Web-based platform used to create and simulate dynamical models of various biological processes. Students can create models of cells, diseases, or pathways themselves or explore existing models. This technology was implemented in both undergraduate and graduate courses as a pilot study to determine the feasibility of such software at the university level. First, a new (In Silico Biology) class was developed to enable students to learn biology by "building and breaking it" via computer models and their simulations. This class and technology also provide a non-intimidating way to incorporate mathematical and computational concepts into a class with students who have a limited mathematical background. Second, we used the technology to mediate the use of simulations and modeling modules as a learning tool for traditional biological concepts, such as T cell differentiation or cell cycle regulation, in existing biology courses. Results of this pilot application suggest that there is promise in the use of computational modeling and software tools such as Cell Collective to provide new teaching methods in biology and contribute to the implementation of the "Vision and Change" call to action in undergraduate biology education by providing a hands-on approach to biology.

  1. On Biblical Hebrew and Computer Science: Inspiration, Models, Tools, And Cross-fertilization

    DEFF Research Database (Denmark)

    Sandborg-Petersen, Ulrik

    2011-01-01

    Eep Talstra's work has been an inspiration to maby researchers, both within and outside of the field of Old Testament scholarship. Among others, Crist-Jan Doedens and the present author have been heavily influenced by Talstra in their own work within the field of computer science. The present...... of the present author. In addition, the tools surrounding Emdros, including SESB, Libronis, and the Emdros Query Tool, are described. Ecamples Biblical Hebrew scholar. Thus the inspiration of Talstra comes full-circle: from Biblical Hebrew databases to computer science and back into Biblical Hebrew scholarship....

  2. Isotropic LQC and LQC-inspired models with a massless scalar field as generalised Brans-Dicke theories

    Science.gov (United States)

    Rama, S. Kalyana

    2018-06-01

    We explore whether generalised Brans-Dicke theories, which have a scalar field Φ and a function ω (Φ ), can be the effective actions leading to the effective equations of motion of the LQC and the LQC-inspired models, which have a massless scalar field σ and a function f( m). We find that this is possible for isotropic cosmology. We relate the pairs (σ , f) and (Φ , ω ) and, using examples, illustrate these relations. We find that near the bounce of the LQC evolutions for which f(m) = sin m, the corresponding field Φ → 0 and the function ω (Φ ) ∝ Φ ^2. We also find that the class of generalised Brans-Dicke theories, which we had found earlier to lead to non singular isotropic evolutions, may be written as an LQC-inspired model. The relations found here in the isotropic cases do not apply to the anisotropic cases, which perhaps require more general effective actions.

  3. A Simple Mathematical Model Inspired by the Purkinje Cells: From Delayed Travelling Waves to Fractional Diffusion.

    Science.gov (United States)

    Dipierro, Serena; Valdinoci, Enrico

    2018-07-01

    Recently, several experiments have demonstrated the existence of fractional diffusion in the neuronal transmission occurring in the Purkinje cells, whose malfunctioning is known to be related to the lack of voluntary coordination and the appearance of tremors. Also, a classical mathematical feature is that (fractional) parabolic equations possess smoothing effects, in contrast with the case of hyperbolic equations, which typically exhibit shocks and discontinuities. In this paper, we show how a simple toy-model of a highly ramified structure, somehow inspired by that of the Purkinje cells, may produce a fractional diffusion via the superposition of travelling waves that solve a hyperbolic equation. This could suggest that the high ramification of the Purkinje cells might have provided an evolutionary advantage of "smoothing" the transmission of signals and avoiding shock propagations (at the price of slowing a bit such transmission). Although an experimental confirmation of the possibility of such evolutionary advantage goes well beyond the goals of this paper, we think that it is intriguing, as a mathematical counterpart, to consider the time fractional diffusion as arising from the superposition of delayed travelling waves in highly ramified transmission media. The case of a travelling concave parabola with sufficiently small curvature is explicitly computed. The new link that we propose between time fractional diffusion and hyperbolic equation also provides a novelty with respect to the usual paradigm relating time fractional diffusion with parabolic equations in the limit. This paper is written in such a way as to be of interest to both biologists and mathematician alike. In order to accomplish this aim, both complete explanations of the objects considered and detailed lists of references are provided.

  4. A bio-inspired spatial patterning circuit.

    Science.gov (United States)

    Chen, Kai-Yuan; Joe, Danial J; Shealy, James B; Land, Bruce R; Shen, Xiling

    2014-01-01

    Lateral Inhibition (LI) is a widely conserved patterning mechanism in biological systems across species. Distinct from better-known Turing patterns, LI depend on cell-cell contact rather than diffusion. We built an in silico genetic circuit model to analyze the dynamic properties of LI. The model revealed that LI amplifies differences between neighboring cells to push them into opposite states, hence forming stable 2-D patterns. Inspired by this insight, we designed and implemented an electronic circuit that recapitulates LI patterning dynamics. This biomimetic system serve as a physical model to elucidate the design principle of generating robust patterning through spatial feedback, regardless of the underlying devices being biological or electrical.

  5. Setting Parameters for Biological Models With ANIMO

    NARCIS (Netherlands)

    Schivo, Stefano; Scholma, Jetse; Karperien, Hermanus Bernardus Johannes; Post, Janine Nicole; van de Pol, Jan Cornelis; Langerak, Romanus; André, Étienne; Frehse, Goran

    2014-01-01

    ANIMO (Analysis of Networks with Interactive MOdeling) is a software for modeling biological networks, such as e.g. signaling, metabolic or gene networks. An ANIMO model is essentially the sum of a network topology and a number of interaction parameters. The topology describes the interactions

  6. Toward computational cumulative biology by combining models of biological datasets.

    Science.gov (United States)

    Faisal, Ali; Peltonen, Jaakko; Georgii, Elisabeth; Rung, Johan; Kaski, Samuel

    2014-01-01

    A main challenge of data-driven sciences is how to make maximal use of the progressively expanding databases of experimental datasets in order to keep research cumulative. We introduce the idea of a modeling-based dataset retrieval engine designed for relating a researcher's experimental dataset to earlier work in the field. The search is (i) data-driven to enable new findings, going beyond the state of the art of keyword searches in annotations, (ii) modeling-driven, to include both biological knowledge and insights learned from data, and (iii) scalable, as it is accomplished without building one unified grand model of all data. Assuming each dataset has been modeled beforehand, by the researchers or automatically by database managers, we apply a rapidly computable and optimizable combination model to decompose a new dataset into contributions from earlier relevant models. By using the data-driven decomposition, we identify a network of interrelated datasets from a large annotated human gene expression atlas. While tissue type and disease were major driving forces for determining relevant datasets, the found relationships were richer, and the model-based search was more accurate than the keyword search; moreover, it recovered biologically meaningful relationships that are not straightforwardly visible from annotations-for instance, between cells in different developmental stages such as thymocytes and T-cells. Data-driven links and citations matched to a large extent; the data-driven links even uncovered corrections to the publication data, as two of the most linked datasets were not highly cited and turned out to have wrong publication entries in the database.

  7. Phenomenology of a left-right-symmetric model inspired by the trinification model

    Energy Technology Data Exchange (ETDEWEB)

    Hetzel, Jamil

    2015-02-04

    The trinification model is an interesting extension of the Standard Model based on the gauge group SU(3){sub C} x SU(3){sub L} x SU(3){sub R}. It naturally explains parity violation as a result of spontaneous symmetry breaking, and the observed fermion masses and mixings can be reproduced using only a few parameters. We study the low-energy phenomenology of the trinification model in order to compare its predictions to experiment. To this end, we construct a low-energy effective field theory, thereby reducing the number of particles and free parameters that need to be studied. We constrain the model parameters using limits from new-particle searches as well as precision measurements. The scalar sector of the model allows for various phenomenological scenarios, such as the presence of a light fermiophobic scalar in addition to a Standard-Model-like Higgs, or a degenerate (twin) Higgs state at 126 GeV. We show how a measurement of the Higgs couplings can be used to distinguish such scenarios from the Standard Model. We find that the trinification model predicts that several new scalar particles have masses in the O(100 GeV) range. Moreover, large regions of the parameter space lead to measurable deviations from Standard-Model predictions of the Higgs couplings. Hence the trinification model awaits crucial tests at the Large Hadron Collider in the coming years.

  8. Biological transportation networks: Modeling and simulation

    KAUST Repository

    Albi, Giacomo

    2015-09-15

    We present a model for biological network formation originally introduced by Cai and Hu [Adaptation and optimization of biological transport networks, Phys. Rev. Lett. 111 (2013) 138701]. The modeling of fluid transportation (e.g., leaf venation and angiogenesis) and ion transportation networks (e.g., neural networks) is explained in detail and basic analytical features like the gradient flow structure of the fluid transportation network model and the impact of the model parameters on the geometry and topology of network formation are analyzed. We also present a numerical finite-element based discretization scheme and discuss sample cases of network formation simulations.

  9. Modeling biology using relational databases.

    Science.gov (United States)

    Peitzsch, Robert M

    2003-02-01

    There are several different methodologies that can be used for designing a database schema; no one is the best for all occasions. This unit demonstrates two different techniques for designing relational tables and discusses when each should be used. These two techniques presented are (1) traditional Entity-Relationship (E-R) modeling and (2) a hybrid method that combines aspects of data warehousing and E-R modeling. The method of choice depends on (1) how well the information and all its inherent relationships are understood, (2) what types of questions will be asked, (3) how many different types of data will be included, and (4) how much data exists.

  10. Structured population models in biology and epidemiology

    CERN Document Server

    Ruan, Shigui

    2008-01-01

    This book consists of six chapters written by leading researchers in mathematical biology. These chapters present recent and important developments in the study of structured population models in biology and epidemiology. Topics include population models structured by age, size, and spatial position; size-structured models for metapopulations, macroparasitc diseases, and prion proliferation; models for transmission of microparasites between host populations living on non-coincident spatial domains; spatiotemporal patterns of disease spread; method of aggregation of variables in population dynamics; and biofilm models. It is suitable as a textbook for a mathematical biology course or a summer school at the advanced undergraduate and graduate level. It can also serve as a reference book for researchers looking for either interesting and specific problems to work on or useful techniques and discussions of some particular problems.

  11. Unified data model for biological data

    International Nuclear Information System (INIS)

    Idrees, M.

    2014-01-01

    A data model empowers us to store, retrieve and manipulate data in a unified way. We consider the biological data consists of DNA (De-Oxyribonucleic Acid), RNA (Ribonucleic Acid) and protein structures. In our Bioinformatics Lab (Bioinformatics Lab, Alkhawarizmi Institute of Computer Science, University of Engineering and Technology, Lahore, Pakistan), we have already proposed two data models for DNA and protein structures individually. In this paper, we propose a unified data model by using the data models of TOS (Temporal Object Oriented System) after making some necessary modifications to this data model and our already proposed the two data models. This proposed unified data model can be used for the modeling and maintaining the biological data (i.e. DNA, RNA and protein structures), in a single unified way. (author)

  12. Laser interaction with biological material mathematical modeling

    CERN Document Server

    Kulikov, Kirill

    2014-01-01

    This book covers the principles of laser interaction with biological cells and tissues of varying degrees of organization. The problems of biomedical diagnostics are considered. Scattering of laser irradiation of blood cells is modeled for biological structures (dermis, epidermis, vascular plexus). An analytic theory is provided which is based on solving the wave equation for the electromagnetic field. It allows the accurate analysis of interference effects arising from the partial superposition of scattered waves. Treated topics of mathematical modeling are: optical characterization of biological tissue with large-scale and small-scale inhomogeneities in the layers, heating blood vessel under laser irradiation incident on the outer surface of the skin and thermo-chemical denaturation of biological structures at the example of human skin.

  13. Improved Lighthill fish swimming model for bio-inspired robots - Modelling, computational aspects and experimental comparisons.

    OpenAIRE

    Porez , Mathieu; Boyer , Frédéric; Ijspeert , Auke

    2014-01-01

    International audience; The best known analytical model of swimming was originally developed by Lighthill and is known as large amplitude elongated body theory (LAEBT). Recently, this theory has been improved and adapted to robotics through a series of studies [Boyer et al., 2008, 2010; Candelier et al., 2011] ranging from hydrodynamic modelling to mobile multibody system dynamics. This article marks a further step towards the Lighthill theory. The LAEBT is ap- plied to one of the best bio-in...

  14. Ranked retrieval of Computational Biology models.

    Science.gov (United States)

    Henkel, Ron; Endler, Lukas; Peters, Andre; Le Novère, Nicolas; Waltemath, Dagmar

    2010-08-11

    The study of biological systems demands computational support. If targeting a biological problem, the reuse of existing computational models can save time and effort. Deciding for potentially suitable models, however, becomes more challenging with the increasing number of computational models available, and even more when considering the models' growing complexity. Firstly, among a set of potential model candidates it is difficult to decide for the model that best suits ones needs. Secondly, it is hard to grasp the nature of an unknown model listed in a search result set, and to judge how well it fits for the particular problem one has in mind. Here we present an improved search approach for computational models of biological processes. It is based on existing retrieval and ranking methods from Information Retrieval. The approach incorporates annotations suggested by MIRIAM, and additional meta-information. It is now part of the search engine of BioModels Database, a standard repository for computational models. The introduced concept and implementation are, to our knowledge, the first application of Information Retrieval techniques on model search in Computational Systems Biology. Using the example of BioModels Database, it was shown that the approach is feasible and extends the current possibilities to search for relevant models. The advantages of our system over existing solutions are that we incorporate a rich set of meta-information, and that we provide the user with a relevance ranking of the models found for a query. Better search capabilities in model databases are expected to have a positive effect on the reuse of existing models.

  15. Combining Bio-inspired Sensing with Bio-inspired Locomotion

    DEFF Research Database (Denmark)

    Shaikh, Danish; Hallam, John; Christensen-Dalsgaard, Jakob

    In this paper we present a preliminary Braitenberg vehicle–like approach to combine bio-inspired audition with bio-inspired quadruped locomotion in simulation. Locomotion gaits of the salamander–like robot Salamandra robotica are modified by a lizard’s peripheral auditory system model that modula......In this paper we present a preliminary Braitenberg vehicle–like approach to combine bio-inspired audition with bio-inspired quadruped locomotion in simulation. Locomotion gaits of the salamander–like robot Salamandra robotica are modified by a lizard’s peripheral auditory system model...

  16. The Strategies of Modeling in Biology Education

    Science.gov (United States)

    Svoboda, Julia; Passmore, Cynthia

    2013-01-01

    Modeling, like inquiry more generally, is not a single method, but rather a complex suite of strategies. Philosophers of biology, citing the diverse aims, interests, and disciplinary cultures of biologists, argue that modeling is best understood in the context of its epistemic aims and cognitive payoffs. In the science education literature,…

  17. Introduction to stochastic models in biology

    DEFF Research Database (Denmark)

    Ditlevsen, Susanne; Samson, Adeline

    2013-01-01

    This chapter is concerned with continuous time processes, which are often modeled as a system of ordinary differential equations (ODEs). These models assume that the observed dynamics are driven exclusively by internal, deterministic mechanisms. However, real biological systems will always be exp...

  18. A 3D steady-state model of a tendon-driven continuum soft manipulator inspired by the octopus arm

    International Nuclear Information System (INIS)

    Renda, F; Cianchetti, M; Giorelli, M; Arienti, A; Laschi, C

    2012-01-01

    Control and modelling of continuum robots are challenging tasks for robotic researchers. Most works on modelling are limited to piecewise constant curvature. In many cases they neglect to model the actuators or avoid a continuum approach. In particular, in the latter case this leads to a complex model hardly implemented. In this work, a geometrically exact steady-state model of a tendon-driven manipulator inspired by the octopus arm is presented. It takes a continuum approach, fast enough to be implemented in the control law, and includes a model of the actuation system. The model was experimentally validated and the results are reported. In conclusion, the model presented can be used as a tool for mechanical design of continuum tendon-driven manipulators, for planning control strategies or as internal model in an embedded system. (paper)

  19. Notions of similarity for computational biology models

    KAUST Repository

    Waltemath, Dagmar

    2016-03-21

    Computational models used in biology are rapidly increasing in complexity, size, and numbers. To build such large models, researchers need to rely on software tools for model retrieval, model combination, and version control. These tools need to be able to quantify the differences and similarities between computational models. However, depending on the specific application, the notion of similarity may greatly vary. A general notion of model similarity, applicable to various types of models, is still missing. Here, we introduce a general notion of quantitative model similarities, survey the use of existing model comparison methods in model building and management, and discuss potential applications of model comparison. To frame model comparison as a general problem, we describe a theoretical approach to defining and computing similarities based on different model aspects. Potentially relevant aspects of a model comprise its references to biological entities, network structure, mathematical equations and parameters, and dynamic behaviour. Future similarity measures could combine these model aspects in flexible, problem-specific ways in order to mimic users\\' intuition about model similarity, and to support complex model searches in databases.

  20. Notions of similarity for computational biology models

    KAUST Repository

    Waltemath, Dagmar; Henkel, Ron; Hoehndorf, Robert; Kacprowski, Tim; Knuepfer, Christian; Liebermeister, Wolfram

    2016-01-01

    Computational models used in biology are rapidly increasing in complexity, size, and numbers. To build such large models, researchers need to rely on software tools for model retrieval, model combination, and version control. These tools need to be able to quantify the differences and similarities between computational models. However, depending on the specific application, the notion of similarity may greatly vary. A general notion of model similarity, applicable to various types of models, is still missing. Here, we introduce a general notion of quantitative model similarities, survey the use of existing model comparison methods in model building and management, and discuss potential applications of model comparison. To frame model comparison as a general problem, we describe a theoretical approach to defining and computing similarities based on different model aspects. Potentially relevant aspects of a model comprise its references to biological entities, network structure, mathematical equations and parameters, and dynamic behaviour. Future similarity measures could combine these model aspects in flexible, problem-specific ways in order to mimic users' intuition about model similarity, and to support complex model searches in databases.

  1. Bio-inspired Artificial Intelligence: А Generalized Net Model of the Regularization Process in MLP

    Directory of Open Access Journals (Sweden)

    Stanimir Surchev

    2013-10-01

    Full Text Available Many objects and processes inspired by the nature have been recreated by the scientists. The inspiration to create a Multilayer Neural Network came from human brain as member of the group. It possesses complicated structure and it is difficult to recreate, because of the existence of too many processes that require different solving methods. The aim of the following paper is to describe one of the methods that improve learning process of Artificial Neural Network. The proposed generalized net method presents Regularization process in Multilayer Neural Network. The purpose of verification is to protect the neural network from overfitting. The regularization is commonly used in neural network training process. Many methods of verification are present, the subject of interest is the one known as Regularization. It contains function in order to set weights and biases with smaller values to protect from overfitting.

  2. Fabrication, testing and modeling of a new flexible armor inspired from natural fish scales and osteoderms

    International Nuclear Information System (INIS)

    Chintapalli, Ravi Kiran; Mirkhalaf, Mohammad; Dastjerdi, Ahmad Khayer; Barthelat, Francois

    2014-01-01

    Crocodiles, armadillo, turtles, fish and many other animal species have evolved flexible armored skins in the form of hard scales or osteoderms, which can be described as hard plates of finite size embedded in softer tissues. The individual hard segments provide protection from predators, while the relative motion of these segments provides the flexibility required for efficient locomotion. In this work, we duplicated these broad concepts in a bio-inspired segmented armor. Hexagonal segments of well-defined size and shape were carved within a thin glass plate using laser engraving. The engraved plate was then placed on a soft substrate which simulated soft tissues, and then punctured with a sharp needle mounted on a miniature loading stage. The resistance of our segmented armor was significantly higher when smaller hexagons were used, and our bio-inspired segmented glass displayed an increase in puncture resistance of up to 70% compared to a continuous plate of glass of the same thickness. Detailed structural analyses aided by finite elements revealed that this extraordinary improvement is due to the reduced span of individual segments, which decreases flexural stresses and delays fracture. This effect can however only be achieved if the plates are at least 1000 stiffer than the underlying substrate, which is the case for natural armor systems. Our bio-inspired system also displayed many of the attributes of natural armors: flexible, robust with ‘multi-hit’ capabilities. This new segmented glass therefore suggests interesting bio-inspired strategies and mechanisms which could be systematically exploited in high-performance flexible armors. This study also provides new insights and a better understanding of the mechanics of natural armors such as scales and osteoderms. (paper)

  3. Functional model of biological neural networks.

    Science.gov (United States)

    Lo, James Ting-Ho

    2010-12-01

    A functional model of biological neural networks, called temporal hierarchical probabilistic associative memory (THPAM), is proposed in this paper. THPAM comprises functional models of dendritic trees for encoding inputs to neurons, a first type of neuron for generating spike trains, a second type of neuron for generating graded signals to modulate neurons of the first type, supervised and unsupervised Hebbian learning mechanisms for easy learning and retrieving, an arrangement of dendritic trees for maximizing generalization, hardwiring for rotation-translation-scaling invariance, and feedback connections with different delay durations for neurons to make full use of present and past informations generated by neurons in the same and higher layers. These functional models and their processing operations have many functions of biological neural networks that have not been achieved by other models in the open literature and provide logically coherent answers to many long-standing neuroscientific questions. However, biological justifications of these functional models and their processing operations are required for THPAM to qualify as a macroscopic model (or low-order approximate) of biological neural networks.

  4. A biologically-inspired multi-joint soft exosuit that can reduce the energy cost of loaded walking.

    Science.gov (United States)

    Panizzolo, Fausto A; Galiana, Ignacio; Asbeck, Alan T; Siviy, Christopher; Schmidt, Kai; Holt, Kenneth G; Walsh, Conor J

    2016-05-12

    Carrying load alters normal walking, imposes additional stress to the musculoskeletal system, and results in an increase in energy consumption and a consequent earlier onset of fatigue. This phenomenon is largely due to increased work requirements in lower extremity joints, in turn requiring higher muscle activation. The aim of this work was to assess the biomechanical and physiological effects of a multi-joint soft exosuit that applies assistive torques to the biological hip and ankle joints during loaded walking. The exosuit was evaluated under three conditions: powered (EXO_ON), unpowered (EXO_OFF) and unpowered removing the equivalent mass of the device (EXO_OFF_EMR). Seven participants walked on an instrumented split-belt treadmill and carried a load equivalent to 30 % their body mass. We assessed their metabolic cost of walking, kinetics, kinematics, and lower limb muscle activation using a portable gas analysis system, motion capture system, and surface electromyography. Our results showed that the exosuit could deliver controlled forces to a wearer. Net metabolic power in the EXO_ON condition (7.5 ± 0.6 W kg(-1)) was 7.3 ± 5.0 % and 14.2 ± 6.1 % lower than in the EXO_OFF_EMR condition (7.9 ± 0.8 W kg(-1); p = 0.027) and in the EXO_OFF condition (8.5 ± 0.9 W kg(-1); p = 0.005), respectively. The exosuit also reduced the total joint positive biological work (sum of hip, knee and ankle) when comparing the EXO_ON condition (1.06 ± 0.16 J kg(-1)) with respect to the EXO_OFF condition (1.28 ± 0.26 J kg(-1); p = 0.020) and to the EXO_OFF_EMR condition (1.22 ± 0.21 J kg(-1); p = 0.007). The results of the present work demonstrate for the first time that a soft wearable robot can improve walking economy. These findings pave the way for future assistive devices that may enhance or restore gait in other applications.

  5. An online model composition tool for system biology models.

    Science.gov (United States)

    Coskun, Sarp A; Cicek, A Ercument; Lai, Nicola; Dash, Ranjan K; Ozsoyoglu, Z Meral; Ozsoyoglu, Gultekin

    2013-09-05

    There are multiple representation formats for Systems Biology computational models, and the Systems Biology Markup Language (SBML) is one of the most widely used. SBML is used to capture, store, and distribute computational models by Systems Biology data sources (e.g., the BioModels Database) and researchers. Therefore, there is a need for all-in-one web-based solutions that support advance SBML functionalities such as uploading, editing, composing, visualizing, simulating, querying, and browsing computational models. We present the design and implementation of the Model Composition Tool (Interface) within the PathCase-SB (PathCase Systems Biology) web portal. The tool helps users compose systems biology models to facilitate the complex process of merging systems biology models. We also present three tools that support the model composition tool, namely, (1) Model Simulation Interface that generates a visual plot of the simulation according to user's input, (2) iModel Tool as a platform for users to upload their own models to compose, and (3) SimCom Tool that provides a side by side comparison of models being composed in the same pathway. Finally, we provide a web site that hosts BioModels Database models and a separate web site that hosts SBML Test Suite models. Model composition tool (and the other three tools) can be used with little or no knowledge of the SBML document structure. For this reason, students or anyone who wants to learn about systems biology will benefit from the described functionalities. SBML Test Suite models will be a nice starting point for beginners. And, for more advanced purposes, users will able to access and employ models of the BioModels Database as well.

  6. A quantum inspired model of radar range and range-rate measurements with applications to weak value measurements

    Science.gov (United States)

    Escalante, George

    2017-05-01

    Weak Value Measurements (WVMs) with pre- and post-selected quantum mechanical ensembles were proposed by Aharonov, Albert, and Vaidman in 1988 and have found numerous applications in both theoretical and applied physics. In the field of precision metrology, WVM techniques have been demonstrated and proven valuable as a means to shift, amplify, and detect signals and to make precise measurements of small effects in both quantum and classical systems, including: particle spin, the Spin-Hall effect of light, optical beam deflections, frequency shifts, field gradients, and many others. In principal, WVM amplification techniques are also possible in radar and could be a valuable tool for precision measurements. However, relatively limited research has been done in this area. This article presents a quantum-inspired model of radar range and range-rate measurements of arbitrary strength, including standard and pre- and post-selected measurements. The model is used to extend WVM amplification theory to radar, with the receive filter performing the post-selection role. It is shown that the description of range and range-rate measurements based on the quantum-mechanical measurement model and formalism produces the same results as the conventional approach used in radar based on signal processing and filtering of the reflected signal at the radar receiver. Numerical simulation results using simple point scatterrer configurations are presented, applying the quantum-inspired model of radar range and range-rate measurements that occur in the weak measurement regime. Potential applications and benefits of the quantum inspired approach to radar measurements are presented, including improved range and Doppler measurement resolution.

  7. Notions of similarity for systems biology models.

    Science.gov (United States)

    Henkel, Ron; Hoehndorf, Robert; Kacprowski, Tim; Knüpfer, Christian; Liebermeister, Wolfram; Waltemath, Dagmar

    2018-01-01

    Systems biology models are rapidly increasing in complexity, size and numbers. When building large models, researchers rely on software tools for the retrieval, comparison, combination and merging of models, as well as for version control. These tools need to be able to quantify the differences and similarities between computational models. However, depending on the specific application, the notion of 'similarity' may greatly vary. A general notion of model similarity, applicable to various types of models, is still missing. Here we survey existing methods for the comparison of models, introduce quantitative measures for model similarity, and discuss potential applications of combined similarity measures. To frame model comparison as a general problem, we describe a theoretical approach to defining and computing similarities based on a combination of different model aspects. The six aspects that we define as potentially relevant for similarity are underlying encoding, references to biological entities, quantitative behaviour, qualitative behaviour, mathematical equations and parameters and network structure. We argue that future similarity measures will benefit from combining these model aspects in flexible, problem-specific ways to mimic users' intuition about model similarity, and to support complex model searches in databases. © The Author 2016. Published by Oxford University Press.

  8. Bio-inspired ``jigsaw''-like interlocking sutures: Modeling, optimization, 3D printing and testing

    Science.gov (United States)

    Malik, I. A.; Mirkhalaf, M.; Barthelat, F.

    2017-05-01

    Structural biological materials such as bone, teeth or mollusk shells draw their remarkable performance from a sophisticated interplay of architectures and weak interfaces. Pushed to the extreme, this concept leads to sutured materials, which contain thin lines with complex geometries. Sutured materials are prominent in nature, and have recently served as bioinspiration for toughened ceramics and glasses. Sutures can generate large deformations, toughness and damping in otherwise all brittle systems and materials. In this study we examine the design and optimization of sutures with a jigsaw puzzle-like geometry, focusing on the non-linear traction behavior generated by the frictional pullout of the jigsaw tabs. We present analytical models which accurately predict the entire pullout response. Pullout strength and energy absorption increase with higher interlocking angles and for higher coefficients of friction, but the associated high stresses in the solid may fracture the tabs. Systematic optimization reveals a counter-intuitive result: the best pullout performance is achieved with interfaces with low coefficient of friction and high interlocking angle. We finally use 3D printing and mechanical testing to verify the accuracy of the models and of the optimization. The models and guidelines we present here can be extended to other types of geometries and sutured materials subjected to other loading/boundary conditions. The nonlinear responses of sutures are particularly attractive to augment the properties and functionalities of inherently brittle materials such as ceramics and glasses.

  9. Molecular plasma deposition: biologically inspired nanohydroxyapatite coatings on anodized nanotubular titanium for improving osteoblast density

    Directory of Open Access Journals (Sweden)

    Balasundaram G

    2015-01-01

    Full Text Available Ganesan Balasundaram,1 Daniel M Storey,1 Thomas J Webster2,3 1Chameleon Scientific, Longmont, CO, USA; 2Department of Chemical Engineering, Northeastern University, Boston, MA, USA; 3Center of Excellence for Advanced Materials Research, King Abdulaziz University, Jeddah, Saudi Arabia Abstract: In order to begin to prepare a novel orthopedic implant that mimics the natural bone environment, the objective of this in vitro study was to synthesize nanocrystalline hydroxyapatite (NHA and coat it on titanium (Ti using molecular plasma deposition (MPD. NHA was synthesized through a wet chemical process followed by a hydrothermal treatment. NHA and micron sized hydroxyapatite (MHA were prepared by processing NHA coatings at 500°C and 900°C, respectively. The coatings were characterized before and after sintering using scanning electron microscopy, atomic force microscopy, and X-ray diffraction. The results revealed that the post-MPD heat treatment of up to 500°C effectively restored the structural and topographical integrity of NHA. In order to determine the in vitro biological responses of the MPD-coated surfaces, the attachment and spreading of osteoblasts (bone-forming cells on the uncoated, NHA-coated, and MHA-coated anodized Ti were investigated. Most importantly, the NHA-coated substrates supported a larger number of adherent cells than the MHA-coated and uncoated substrates. The morphology of these cells was assessed by scanning electron microscopy and the observed shapes were different for each substrate type. The present results are the first reports using MPD in the framework of hydroxyapatite coatings on Ti to enhance osteoblast responses and encourage further studies on MPD-based hydroxyapatite coatings on Ti for improved orthopedic applications. Keywords: hydroxyapatite, anodization, nanotechnology

  10. Biology-Inspired Robust Dive Plane Control of Non-Linear AUV Using Pectoral-Like Fins

    Directory of Open Access Journals (Sweden)

    Subramanian Ramasamy

    2010-01-01

    Full Text Available The development of a control system for the dive plane control of non-linear biorobotic autonomous underwater vehicles, equipped with pectoral-like fins, is the subject of this paper. Marine animals use pectoral fins for swimming smoothly. The fins are assumed to be oscillating with a combined pitch and heave motion and therefore produce unsteady control forces. The objective is to control the depth of the vehicle. The mean angle of pitch motion of the fin is used as a control variable. A computational-fluid-dynamics-based parameterisation of the fin forces is used for control system design. A robust servo regulator for the control of the depth of the vehicle, based on the non-linear internal model principle, is derived. For the control law derivation, an exosystem of third order is introduced, and the non-linear time-varying biorobotic autonomous underwater vehicle model, including the fin forces, is represented as a non-linear autonomous system in an extended state space. The control system includes the internal model of a k-fold exosystem, where k is a positive integer chosen by the designer. It is shown that in the closed-loop system, all the harmonic components of order up to k of the tracking error are suppressed. Simulation results are presented which show that the servo regulator accomplishes accurate depth control despite uncertainties in the model parameters.

  11. Ultrafast spectroscopy of model biological membranes

    NARCIS (Netherlands)

    Ghosh, Avishek

    2009-01-01

    In this PhD thesis, I have described the novel time-resolved sum-frequency generation (TR-SFG) spectroscopic technique that I developed during the course of my PhD research and used it study the ultrafast vibrational, structural and orientational dynamics of water molecules at model biological

  12. Prospective Tests on Biological Models of Acupuncture

    Directory of Open Access Journals (Sweden)

    Charles Shang

    2009-01-01

    Full Text Available The biological effects of acupuncture include the regulation of a variety of neurohumoral factors and growth control factors. In science, models or hypotheses with confirmed predictions are considered more convincing than models solely based on retrospective explanations. Literature review showed that two biological models of acupuncture have been prospectively tested with independently confirmed predictions: The neurophysiology model on the long-term effects of acupuncture emphasizes the trophic and anti-inflammatory effects of acupuncture. Its prediction on the peripheral effect of endorphin in acupuncture has been confirmed. The growth control model encompasses the neurophysiology model and suggests that a macroscopic growth control system originates from a network of organizers in embryogenesis. The activity of the growth control system is important in the formation, maintenance and regulation of all the physiological systems. Several phenomena of acupuncture such as the distribution of auricular acupuncture points, the long-term effects of acupuncture and the effect of multimodal non-specific stimulation at acupuncture points are consistent with the growth control model. The following predictions of the growth control model have been independently confirmed by research results in both acupuncture and conventional biomedical sciences: (i Acupuncture has extensive growth control effects. (ii Singular point and separatrix exist in morphogenesis. (iii Organizers have high electric conductance, high current density and high density of gap junctions. (iv A high density of gap junctions is distributed as separatrices or boundaries at body surface after early embryogenesis. (v Many acupuncture points are located at transition points or boundaries between different body domains or muscles, coinciding with the connective tissue planes. (vi Some morphogens and organizers continue to function after embryogenesis. Current acupuncture research suggests a

  13. Agent-based modelling in synthetic biology.

    Science.gov (United States)

    Gorochowski, Thomas E

    2016-11-30

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

  14. From Biology to Mathematical Models and Back: Teaching Modeling to Biology Students, and Biology to Math and Engineering Students

    Science.gov (United States)

    Chiel, Hillel J.; McManus, Jeffrey M.; Shaw, Kendrick M.

    2010-01-01

    We describe the development of a course to teach modeling and mathematical analysis skills to students of biology and to teach biology to students with strong backgrounds in mathematics, physics, or engineering. The two groups of students have different ways of learning material and often have strong negative feelings toward the area of knowledge…

  15. Modeling and additive manufacturing of bio-inspired composites with tunable fracture mechanical properties.

    Science.gov (United States)

    Dimas, Leon S; Buehler, Markus J

    2014-07-07

    Flaws, imperfections and cracks are ubiquitous in material systems and are commonly the catalysts of catastrophic material failure. As stresses and strains tend to concentrate around cracks and imperfections, structures tend to fail far before large regions of material have ever been subjected to significant loading. Therefore, a major challenge in material design is to engineer systems that perform on par with pristine structures despite the presence of imperfections. In this work we integrate knowledge of biological systems with computational modeling and state of the art additive manufacturing to synthesize advanced composites with tunable fracture mechanical properties. Supported by extensive mesoscale computer simulations, we demonstrate the design and manufacturing of composites that exhibit deformation mechanisms characteristic of pristine systems, featuring flaw-tolerant properties. We analyze the results by directly comparing strain fields for the synthesized composites, obtained through digital image correlation (DIC), and the computationally tested composites. Moreover, we plot Ashby diagrams for the range of simulated and experimental composites. Our findings show good agreement between simulation and experiment, confirming that the proposed mechanisms have a significant potential for vastly improving the fracture response of composite materials. We elucidate the role of stiffness ratio variations of composite constituents as an important feature in determining the composite properties. Moreover, our work validates the predictive ability of our models, presenting them as useful tools for guiding further material design. This work enables the tailored design and manufacturing of composites assembled from inferior building blocks, that obtain optimal combinations of stiffness and toughness.

  16. Structural Identifiability of Dynamic Systems Biology Models.

    Science.gov (United States)

    Villaverde, Alejandro F; Barreiro, Antonio; Papachristodoulou, Antonis

    2016-10-01

    A powerful way of gaining insight into biological systems is by creating a nonlinear differential equation model, which usually contains many unknown parameters. Such a model is called structurally identifiable if it is possible to determine the values of its parameters from measurements of the model outputs. Structural identifiability is a prerequisite for parameter estimation, and should be assessed before exploiting a model. However, this analysis is seldom performed due to the high computational cost involved in the necessary symbolic calculations, which quickly becomes prohibitive as the problem size increases. In this paper we show how to analyse the structural identifiability of a very general class of nonlinear models by extending methods originally developed for studying observability. We present results about models whose identifiability had not been previously determined, report unidentifiabilities that had not been found before, and show how to modify those unidentifiable models to make them identifiable. This method helps prevent problems caused by lack of identifiability analysis, which can compromise the success of tasks such as experiment design, parameter estimation, and model-based optimization. The procedure is called STRIKE-GOLDD (STRuctural Identifiability taKen as Extended-Generalized Observability with Lie Derivatives and Decomposition), and it is implemented in a MATLAB toolbox which is available as open source software. The broad applicability of this approach facilitates the analysis of the increasingly complex models used in systems biology and other areas.

  17. Institute for Multiscale Modeling of Biological Interactions

    Energy Technology Data Exchange (ETDEWEB)

    Paulaitis, Michael E; Garcia-Moreno, Bertrand; Lenhoff, Abraham

    2009-12-26

    The Institute for Multiscale Modeling of Biological Interactions (IMMBI) has two primary goals: Foster interdisciplinary collaborations among faculty and their research laboratories that will lead to novel applications of multiscale simulation and modeling methods in the biological sciences and engineering; and Building on the unique biophysical/biology-based engineering foundations of the participating faculty, train scientists and engineers to apply computational methods that collectively span multiple time and length scales of biological organization. The success of IMMBI will be defined by the following: Size and quality of the applicant pool for pre-doctoral and post-doctoral fellows; Academic performance; Quality of the pre-doctoral and post-doctoral research; Impact of the research broadly and to the DOE (ASCR program) mission; Distinction of the next career step for pre-doctoral and post-doctoral fellows; and Faculty collaborations that result from IMMBI activities. Specific details about accomplishments during the three years of DOE support for IMMBI have been documented in Annual Progress Reports (April 2005, June 2006, and March 2007) and a Report for a National Academy of Sciences Review (October 2005) that were submitted to DOE on the dates indicated. An overview of these accomplishments is provided.

  18. Extensive Investigations on Bio-Inspired Trust and Reputation Model over Hops Coefficient Factor in Distributed Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Vinod Kumar Verma

    2014-08-01

    Full Text Available Resource utilization requires a substantial consideration for a trust and reputation model to be deployed within a wireless sensor network (WSN. In the evaluation, our attention is focused on the effect of hops coefficient factor estimation on WSN with bio-inspired trust and reputation model (BTRM. We present the state-of-the-art system level evaluation of accuracy and path length of sensor node operations for their current and average scenarios. Additionally, we emphasized over the energy consumption evaluation for static, dynamic and oscillatory modes of BTRM-WSN model. The performance of the hops coefficient factor for our proposed framework is evaluated via analytic bounds and numerical simulations.

  19. A soft body as a reservoir: case studies in a dynamic model of octopus-inspired soft robotic arm

    Science.gov (United States)

    Nakajima, Kohei; Hauser, Helmut; Kang, Rongjie; Guglielmino, Emanuele; Caldwell, Darwin G.; Pfeifer, Rolf

    2013-01-01

    The behaviors of the animals or embodied agents are characterized by the dynamic coupling between the brain, the body, and the environment. This implies that control, which is conventionally thought to be handled by the brain or a controller, can partially be outsourced to the physical body and the interaction with the environment. This idea has been demonstrated in a number of recently constructed robots, in particular from the field of “soft robotics”. Soft robots are made of a soft material introducing high-dimensionality, non-linearity, and elasticity, which often makes the robots difficult to control. Biological systems such as the octopus are mastering their complex bodies in highly sophisticated manners by capitalizing on their body dynamics. We will demonstrate that the structure of the octopus arm cannot only be exploited for generating behavior but also, in a sense, as a computational resource. By using a soft robotic arm inspired by the octopus we show in a number of experiments how control is partially incorporated into the physical arm's dynamics and how the arm's dynamics can be exploited to approximate non-linear dynamical systems and embed non-linear limit cycles. Future application scenarios as well as the implications of the results for the octopus biology are also discussed. PMID:23847526

  20. A Soft Body as a Reservoir: Case Studies in a Dynamic Model of Octopus-Inspired Soft Robotic Arm

    Directory of Open Access Journals (Sweden)

    Kohei eNakajima

    2013-07-01

    Full Text Available The behaviors of the animals or embodied agents are characterized by the dynamic coupling between the brain, the body, and the environment. This implies that control, which is conventionally thought to be handled by the brain or a controller, can partially be outsourced to the physical body and the interaction with the environment. This idea has been demonstrated in a number of recently constructed robots, in particular from the field of soft robotics. Soft robots are made of a soft material introducing high-dimensionality, nonlinearity, and elasticity, which often makes the robots difficult to control. Biological systems such as the octopus are mastering their complex bodies in highly sophisticated manners by capitalizing on their body dynamics. We will demonstrate that the structure of the octopus arm cannot only be exploited for generating behavior but also, in a sense, as a computational resource. By using a soft robotic arm inspired by the octopus we show in a number of experiments how control is partially incorporated into the physical arm’s dynamics and how the arm’s dynamics can be exploited to approximate nonlinear dynamical systems and embed nonlinear limit cycles. Future application scenarios as well as the implications of the results for the octopus biology are also discussed.

  1. Guard Cell and Tropomyosin Inspired Chemical Sensor

    Directory of Open Access Journals (Sweden)

    Jacquelyn K.S. Nagel

    2013-10-01

    Full Text Available Sensors are an integral part of many engineered products and systems. Biological inspiration has the potential to improve current sensor designs as well as inspire innovative ones. This paper presents the design of an innovative, biologically-inspired chemical sensor that performs “up-front” processing through mechanical means. Inspiration from the physiology (function of the guard cell coupled with the morphology (form and physiology of tropomyosin resulted in two concept variants for the chemical sensor. Applications of the sensor design include environmental monitoring of harmful gases, and a non-invasive approach to detect illnesses including diabetes, liver disease, and cancer on the breath.

  2. BIOLOGICALLY INSPIRED HARDWARE CELL ARCHITECTURE

    DEFF Research Database (Denmark)

    2010-01-01

    Disclosed is a system comprising: - a reconfigurable hardware platform; - a plurality of hardware units defined as cells adapted to be programmed to provide self-organization and self-maintenance of the system by means of implementing a program expressed in a programming language defined as DNA...... language, where each cell is adapted to communicate with one or more other cells in the system, and where the system further comprises a converter program adapted to convert keywords from the DNA language to a binary DNA code; where the self-organisation comprises that the DNA code is transmitted to one...... or more of the cells, and each of the one or more cells is adapted to determine its function in the system; where if a fault occurs in a first cell and the first cell ceases to perform its function, self-maintenance is performed by that the system transmits information to the cells that the first cell has...

  3. From biology to mathematical models and back: teaching modeling to biology students, and biology to math and engineering students.

    Science.gov (United States)

    Chiel, Hillel J; McManus, Jeffrey M; Shaw, Kendrick M

    2010-01-01

    We describe the development of a course to teach modeling and mathematical analysis skills to students of biology and to teach biology to students with strong backgrounds in mathematics, physics, or engineering. The two groups of students have different ways of learning material and often have strong negative feelings toward the area of knowledge that they find difficult. To give students a sense of mastery in each area, several complementary approaches are used in the course: 1) a "live" textbook that allows students to explore models and mathematical processes interactively; 2) benchmark problems providing key skills on which students make continuous progress; 3) assignment of students to teams of two throughout the semester; 4) regular one-on-one interactions with instructors throughout the semester; and 5) a term project in which students reconstruct, analyze, extend, and then write in detail about a recently published biological model. Based on student evaluations and comments, an attitude survey, and the quality of the students' term papers, the course has significantly increased the ability and willingness of biology students to use mathematical concepts and modeling tools to understand biological systems, and it has significantly enhanced engineering students' appreciation of biology.

  4. From Biology to Mathematical Models and Back: Teaching Modeling to Biology Students, and Biology to Math and Engineering Students

    Science.gov (United States)

    McManus, Jeffrey M.; Shaw, Kendrick M.

    2010-01-01

    We describe the development of a course to teach modeling and mathematical analysis skills to students of biology and to teach biology to students with strong backgrounds in mathematics, physics, or engineering. The two groups of students have different ways of learning material and often have strong negative feelings toward the area of knowledge that they find difficult. To give students a sense of mastery in each area, several complementary approaches are used in the course: 1) a “live” textbook that allows students to explore models and mathematical processes interactively; 2) benchmark problems providing key skills on which students make continuous progress; 3) assignment of students to teams of two throughout the semester; 4) regular one-on-one interactions with instructors throughout the semester; and 5) a term project in which students reconstruct, analyze, extend, and then write in detail about a recently published biological model. Based on student evaluations and comments, an attitude survey, and the quality of the students' term papers, the course has significantly increased the ability and willingness of biology students to use mathematical concepts and modeling tools to understand biological systems, and it has significantly enhanced engineering students' appreciation of biology. PMID:20810957

  5. Modeling the Biological Diversity of Pig Carcasses

    DEFF Research Database (Denmark)

    Erbou, Søren Gylling Hemmingsen

    This thesis applies methods from medical image analysis for modeling the biological diversity of pig carcasses. The Danish meat industry is very focused on improving product quality and productivity by optimizing the use of the carcasses and increasing productivity in the abattoirs. In order...... equipment is investigated, without the need for a calibration against a less accurate manual dissection. The rest of the contributions regard the construction and use of point distribution models (PDM). PDM’s are able to capture the shape variation of a population of shapes, in this case a 3D surface...

  6. Biologic Constraints on Modelling Virus Assembly

    Directory of Open Access Journals (Sweden)

    Robert L. Garcea

    2008-01-01

    Full Text Available The mathematic modelling of icosahedral virus assembly has drawn increasing interest because of the symmetric geometry of the outer shell structures. Many models involve equilibrium expressions of subunit binding, with reversible subunit additions forming various intermediate structures. The underlying assumption is that a final lowest energy state drives the equilibrium toward assembly. In their simplest forms, these models have explained why high subunit protein concentrations and strong subunit association constants can result in kinetic traps forming off pathway partial and aberrant structures. However, the cell biology of virus assembly is exceedingly complex. The biochemistry and biology of polyoma and papillomavirus assembly described here illustrates many of these specific issues. Variables include the use of cellular ‘chaperone’ proteins as mediators of assembly fidelity, the coupling of assembly to encapsidation of a specific nucleic acid genome, the use of cellular structures as ‘workbenches’ upon which assembly occurs, and the underlying problem of making a capsid structure that is metastable and capable of rapid disassembly upon infection. Although formidable to model, incorporating these considerations could advance the relevance of mathematical models of virus assembly to the real world.

  7. Bounds on the slope and curvature of Isgur-Wise function in a QCD-inspired quark model

    Energy Technology Data Exchange (ETDEWEB)

    Hazarika, Bhaskar Jyoti [Department of Physics, Pandu College, Guwahati (India); Choudhury, D.K. [Department of Physics, Gauhati University, Guwahati (India)

    2011-09-15

    The quantum chromodynamics-inspired potential model pursued by us earlier has been recently modified to incorporate an additional factor 'c' in the linear cum Coulomb potential. While it felicitates the inclusion of standard confinement parameter b = 0.183 GeV{sup 2} unlike in previous work, it still falls short of explaining the Isgur-Wise function for the B mesons without ad hoc adjustment of the strong coupling constant. In this work, we determine the factor 'c' from the experimental values of decay constants and masses and show that the reality constraint on 'c' yields bounds on the strong coupling constant as well as on slope and curvature of Isgur-Wise function allowing more flexibility to the model. (author)

  8. Mathematical modeling in biology: A critical assessment

    Energy Technology Data Exchange (ETDEWEB)

    Buiatti, M. [Florence, Univ. (Italy). Dipt. di Biologia Animale e Genetica

    1998-01-01

    The molecular revolution and the development of biology-derived industry have led in the last fifty years to an unprecedented `lead forward` of life sciences in terms of experimental data. Less success has been achieved in the organisation of such data and in the consequent development of adequate explanatory and predictive theories and models. After a brief historical excursus inborn difficulties of mathematisation of biological objects and processes derived from the complex dynamics of life are discussed along with the logical tools (simplifications, choice of observation points etc.) used to overcome them. `Autistic`, monodisciplinary attitudes towards biological modeling of mathematicians, physicists, biologists aimed in each case at the use of the tools of other disciplines to solve `selfish` problems are also taken into account and a warning against derived dangers (reification of mono disciplinary metaphors, lack of falsification etc.) is given. Finally `top.down` (deductive) and `bottom up` (inductive) heuristic interactive approaches to mathematisation are critically discussed with the help of serie of examples.

  9. Mathematical modeling in biology: A critical assessment

    International Nuclear Information System (INIS)

    Buiatti, M.

    1998-01-01

    The molecular revolution and the development of biology-derived industry have led in the last fifty years to an unprecedented 'lead forward' of life sciences in terms of experimental data. Less success has been achieved in the organisation of such data and in the consequent development of adequate explanatory and predictive theories and models. After a brief historical excursus inborn difficulties of mathematisation of biological objects and processes derived from the complex dynamics of life are discussed along with the logical tools (simplifications, choice of observation points etc.) used to overcome them. 'Autistic', monodisciplinary attitudes towards biological modeling of mathematicians, physicists, biologists aimed in each case at the use of the tools of other disciplines to solve 'selfish' problems are also taken into account and a warning against derived dangers (reification of mono disciplinary metaphors, lack of falsification etc.) is given. Finally 'top.down' (deductive) and 'bottom up' (inductive) heuristic interactive approaches to mathematisation are critically discussed with the help of serie of examples

  10. Continuum Modeling of Biological Network Formation

    KAUST Repository

    Albi, Giacomo

    2017-04-10

    We present an overview of recent analytical and numerical results for the elliptic–parabolic system of partial differential equations proposed by Hu and Cai, which models the formation of biological transportation networks. The model describes the pressure field using a Darcy type equation and the dynamics of the conductance network under pressure force effects. Randomness in the material structure is represented by a linear diffusion term and conductance relaxation by an algebraic decay term. We first introduce micro- and mesoscopic models and show how they are connected to the macroscopic PDE system. Then, we provide an overview of analytical results for the PDE model, focusing mainly on the existence of weak and mild solutions and analysis of the steady states. The analytical part is complemented by extensive numerical simulations. We propose a discretization based on finite elements and study the qualitative properties of network structures for various parameter values.

  11. A String-Inspired Model for the Low-$\\ell$ CMB

    CERN Document Server

    Kitazawa, N.

    2015-07-09

    We present a semi--analytic exploration of some low--$\\ell$ angular power spectra inspired by "Brane Supersymmetry Breaking". This mechanism splits Bose and Fermi excitations in String Theory, leaving behind an exponential potential that is just too steep for the inflaton to emerge from the initial singularity while descending it. As a result, the scalar generically bounces against the exponential wall, which typically introduces an infrared depression and a pre--inflationary peak in the power spectrum of scalar perturbations. We elaborate on a possible link between this phenomenon and the low--$\\ell$ CMB. For the first 32 multipoles, combining the hard exponential with a milder one leading to $n_s\\simeq 0.96$ and with a small gaussian bump we have attained a reduction of $\\chi^{\\,2}$ to about 46% of the standard $\\Lambda$CDM setting, with both WMAP9 and PLANCK 2013 data. This result corresponds to a $\\chi^{\\,2}/DOF$ of about 0.45, to be compared with a $\\Lambda$CDM value of about 0.85. The preferred choices ...

  12. Unit testing, model validation, and biological simulation.

    Science.gov (United States)

    Sarma, Gopal P; Jacobs, Travis W; Watts, Mark D; Ghayoomie, S Vahid; Larson, Stephen D; Gerkin, Richard C

    2016-01-01

    The growth of the software industry has gone hand in hand with the development of tools and cultural practices for ensuring the reliability of complex pieces of software. These tools and practices are now acknowledged to be essential to the management of modern software. As computational models and methods have become increasingly common in the biological sciences, it is important to examine how these practices can accelerate biological software development and improve research quality. In this article, we give a focused case study of our experience with the practices of unit testing and test-driven development in OpenWorm, an open-science project aimed at modeling Caenorhabditis elegans. We identify and discuss the challenges of incorporating test-driven development into a heterogeneous, data-driven project, as well as the role of model validation tests, a category of tests unique to software which expresses scientific models.

  13. Evaluation of biological models using Spacelab

    Science.gov (United States)

    Tollinger, D.; Williams, B. A.

    1980-01-01

    Biological models of hypogravity effects are described, including the cardiovascular-fluid shift, musculoskeletal, embryological and space sickness models. These models predict such effects as loss of extracellular fluid and electrolytes, decrease in red blood cell mass, and the loss of muscle and bone mass in weight-bearing portions of the body. Experimentation in Spacelab by the use of implanted electromagnetic flow probes, by fertilizing frog eggs in hypogravity and fixing the eggs at various stages of early development and by assessing the role of the vestibulocular reflex arc in space sickness is suggested. It is concluded that the use of small animals eliminates the uncertainties caused by corrective or preventive measures employed with human subjects.

  14. Molecular descriptor subset selection in theoretical peptide quantitative structure-retention relationship model development using nature-inspired optimization algorithms.

    Science.gov (United States)

    Žuvela, Petar; Liu, J Jay; Macur, Katarzyna; Bączek, Tomasz

    2015-10-06

    In this work, performance of five nature-inspired optimization algorithms, genetic algorithm (GA), particle swarm optimization (PSO), artificial bee colony (ABC), firefly algorithm (FA), and flower pollination algorithm (FPA), was compared in molecular descriptor selection for development of quantitative structure-retention relationship (QSRR) models for 83 peptides that originate from eight model proteins. The matrix with 423 descriptors was used as input, and QSRR models based on selected descriptors were built using partial least squares (PLS), whereas root mean square error of prediction (RMSEP) was used as a fitness function for their selection. Three performance criteria, prediction accuracy, computational cost, and the number of selected descriptors, were used to evaluate the developed QSRR models. The results show that all five variable selection methods outperform interval PLS (iPLS), sparse PLS (sPLS), and the full PLS model, whereas GA is superior because of its lowest computational cost and higher accuracy (RMSEP of 5.534%) with a smaller number of variables (nine descriptors). The GA-QSRR model was validated initially through Y-randomization. In addition, it was successfully validated with an external testing set out of 102 peptides originating from Bacillus subtilis proteomes (RMSEP of 22.030%). Its applicability domain was defined, from which it was evident that the developed GA-QSRR exhibited strong robustness. All the sources of the model's error were identified, thus allowing for further application of the developed methodology in proteomics.

  15. Form factors and charge radii in a quantum chromodynamics-inspired potential model using variationally improved perturbation theory

    International Nuclear Information System (INIS)

    Hazarika, Bhaskar Jyoti; Choudhury, D.K.

    2015-01-01

    We use variationally improved perturbation theory (VIPT) for calculating the elastic form factors and charge radii of D, D s , B, B s and B c mesons in a quantum chromodynamics (QCD)-inspired potential model. For that, we use linear-cum-Coulombic potential and opt the Coulombic part first as parent and then the linear part as parent. The results show that charge radii and form factors are quite small for the Coulombic parent compared to the linear parent. Also, the analysis leads to a lower as well as upper bounds on the four-momentum transfer Q 2 , hinting at a workable range of Q 2 within this approach, which may be useful in future experimental analyses. Comparison of both the options shows that the linear parent is the better option. (author)

  16. Modeling biological pathway dynamics with timed automata.

    Science.gov (United States)

    Schivo, Stefano; Scholma, Jetse; Wanders, Brend; Urquidi Camacho, Ricardo A; van der Vet, Paul E; Karperien, Marcel; Langerak, Rom; van de Pol, Jaco; Post, Janine N

    2014-05-01

    Living cells are constantly subjected to a plethora of environmental stimuli that require integration into an appropriate cellular response. This integration takes place through signal transduction events that form tightly interconnected networks. The understanding of these networks requires capturing their dynamics through computational support and models. ANIMO (analysis of Networks with Interactive Modeling) is a tool that enables the construction and exploration of executable models of biological networks, helping to derive hypotheses and to plan wet-lab experiments. The tool is based on the formalism of Timed Automata, which can be analyzed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signaling networks. This enforces precision and uniformity in the definition of signaling pathways, contributing to the integration of isolated signaling events into complex network models. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic behavior of the network of interest. A user-friendly interface hides the use of Timed Automata from the user, while keeping the expressive power intact. Abstraction to single-parameter kinetics speeds up construction of models that remain faithful enough to provide meaningful insight. The resulting dynamic behavior of the network components is displayed graphically, allowing for an intuitive and interactive modeling experience.

  17. A Theoretical Characterization of Curvature Controlled Adhesive Properties of Bio-Inspired Membranes

    DEFF Research Database (Denmark)

    Afferante, Luciano; Heepe, Lars; Casdorff, Kirstin

    2016-01-01

    Some biological systems, such as the tree frog, Litoria caerulea, and the bush-cricket, Tettigonia viridissima, have developed the ability to control adhesion by changing the curvature of their pads. Active control systems of adhesion inspired by these biological models can be very attractive...

  18. Spherical Cancer Models in Tumor Biology

    Directory of Open Access Journals (Sweden)

    Louis-Bastien Weiswald

    2015-01-01

    Full Text Available Three-dimensional (3D in vitro models have been used in cancer research as an intermediate model between in vitro cancer cell line cultures and in vivo tumor. Spherical cancer models represent major 3D in vitro models that have been described over the past 4 decades. These models have gained popularity in cancer stem cell research using tumorospheres. Thus, it is crucial to define and clarify the different spherical cancer models thus far described. Here, we focus on in vitro multicellular spheres used in cancer research. All these spherelike structures are characterized by their well-rounded shape, the presence of cancer cells, and their capacity to be maintained as free-floating cultures. We propose a rational classification of the four most commonly used spherical cancer models in cancer research based on culture methods for obtaining them and on subsequent differences in sphere biology: the multicellular tumor spheroid model, first described in the early 70s and obtained by culture of cancer cell lines under nonadherent conditions; tumorospheres, a model of cancer stem cell expansion established in a serum-free medium supplemented with growth factors; tissue-derived tumor spheres and organotypic multicellular spheroids, obtained by tumor tissue mechanical dissociation and cutting. In addition, we describe their applications to and interest in cancer research; in particular, we describe their contribution to chemoresistance, radioresistance, tumorigenicity, and invasion and migration studies. Although these models share a common 3D conformation, each displays its own intrinsic properties. Therefore, the most relevant spherical cancer model must be carefully selected, as a function of the study aim and cancer type.

  19. A Bio-Inspired Model-Based Approach for Context-Aware Post-WIMP Tele-Rehabilitation

    Directory of Open Access Journals (Sweden)

    Víctor López-Jaquero

    2016-10-01

    Full Text Available Tele-rehabilitation is one of the main domains where Information and Communication Technologies (ICT have been proven useful to move healthcare from care centers to patients’ home. Moreover, patients, especially those carrying out a physical therapy, cannot use a traditional Window, Icon, Menu, Pointer (WIMP system, but they need to interact in a natural way, that is, there is a need to move from WIMP systems to Post-WIMP ones. Moreover, tele-rehabilitation systems should be developed following the context-aware approach, so that they are able to adapt to the patients’ context to provide them with usable and effective therapies. In this work a model-based approach is presented to assist stakeholders in the development of context-aware Post-WIMP tele-rehabilitation systems. It entails three different models: (i a task model for designing the rehabilitation tasks; (ii a context model to facilitate the adaptation of these tasks to the context; and (iii a bio-inspired presentation model to specify thoroughly how such tasks should be performed by the patients. Our proposal overcomes one of the limitations of the model-based approach for the development of context-aware systems supporting the specification of non-functional requirements. Finally, a case study is used to illustrate how this proposal can be put into practice to design a real world rehabilitation task.

  20. ACTIVE AND PARTICIPATORY METHODS IN BIOLOGY: MODELING

    Directory of Open Access Journals (Sweden)

    Brînduşa-Antonela SBÎRCEA

    2011-01-01

    Full Text Available By using active and participatory methods it is hoped that pupils will not only come to a deeper understanding of the issues involved, but also that their motivation will be heightened. Pupil involvement in their learning is essential. Moreover, by using a variety of teaching techniques, we can help students make sense of the world in different ways, increasing the likelihood that they will develop a conceptual understanding. The teacher must be a good facilitator, monitoring and supporting group dynamics. Modeling is an instructional strategy in which the teacher demonstrates a new concept or approach to learning and pupils learn by observing. In the teaching of biology the didactic materials are fundamental tools in the teaching-learning process. Reading about scientific concepts or having a teacher explain them is not enough. Research has shown that modeling can be used across disciplines and in all grade and ability level classrooms. Using this type of instruction, teachers encourage learning.

  1. Documentation of TRU biological transport model (BIOTRAN)

    Energy Technology Data Exchange (ETDEWEB)

    Gallegos, A.F.; Garcia, B.J.; Sutton, C.M.

    1980-01-01

    Inclusive of Appendices, this document describes the purpose, rationale, construction, and operation of a biological transport model (BIOTRAN). This model is used to predict the flow of transuranic elements (TRU) through specified plant and animal environments using biomass as a vector. The appendices are: (A) Flows of moisture, biomass, and TRU; (B) Intermediate variables affecting flows; (C) Mnemonic equivalents (code) for variables; (D) Variable library (code); (E) BIOTRAN code (Fortran); (F) Plants simulated; (G) BIOTRAN code documentation; (H) Operating instructions for BIOTRAN code. The main text is presented with a specific format which uses a minimum of space, yet is adequate for tracking most relationships from their first appearance to their formulation in the code. Because relationships are treated individually in this manner, and rely heavily on Appendix material for understanding, it is advised that the reader familiarize himself with these materials before proceeding with the main text.

  2. Documentation of TRU biological transport model (BIOTRAN)

    International Nuclear Information System (INIS)

    Gallegos, A.F.; Garcia, B.J.; Sutton, C.M.

    1980-01-01

    Inclusive of Appendices, this document describes the purpose, rationale, construction, and operation of a biological transport model (BIOTRAN). This model is used to predict the flow of transuranic elements (TRU) through specified plant and animal environments using biomass as a vector. The appendices are: (A) Flows of moisture, biomass, and TRU; (B) Intermediate variables affecting flows; (C) Mnemonic equivalents (code) for variables; (D) Variable library (code); (E) BIOTRAN code (Fortran); (F) Plants simulated; (G) BIOTRAN code documentation; (H) Operating instructions for BIOTRAN code. The main text is presented with a specific format which uses a minimum of space, yet is adequate for tracking most relationships from their first appearance to their formulation in the code. Because relationships are treated individually in this manner, and rely heavily on Appendix material for understanding, it is advised that the reader familiarize himself with these materials before proceeding with the main text

  3. Righting and turning in mid-air using appendage inertia: reptile tails, analytical models and bio-inspired robots

    International Nuclear Information System (INIS)

    Jusufi, A; Full, R J; Kawano, D T; Libby, T

    2010-01-01

    Unlike the falling cat, lizards can right themselves in mid-air by a swing of their large tails in one direction causing the body to rotate in the other. Here, we developed a new three-dimensional analytical model to investigate the effectiveness of tails as inertial appendages that change body orientation. We anchored our model using the morphological parameters of the flat-tailed house gecko Hemidactylus platyurus. The degree of roll in air righting and the amount of yaw in mid-air turning directly measured in house geckos matched the model's results. Our model predicted an increase in body roll and turning as tails increase in length relative to the body. Tails that swung from a near orthogonal plane relative to the body (i.e. 0-30 0 from vertical) were the most effective at generating body roll, whereas tails operating at steeper angles (i.e. 45-60 0 ) produced only half the rotation. To further test our analytical model's predictions, we built a bio-inspired robot prototype. The robot reinforced how effective attitude control can be attained with simple movements of an inertial appendage.

  4. Righting and turning in mid-air using appendage inertia: reptile tails, analytical models and bio-inspired robots

    Energy Technology Data Exchange (ETDEWEB)

    Jusufi, A; Full, R J [Department of Integrative Biology, University of California, Berkeley, CA 94720-3140 (United States); Kawano, D T [Department of Mechanical Engineering, University of California, Berkeley, CA 94720-1740 (United States); Libby, T, E-mail: ardianj@berkeley.ed [Center for Interdisciplinary Bio-inspiration in Education and Research, University of California, Berkeley, CA 94720-3140 (United States)

    2010-12-15

    Unlike the falling cat, lizards can right themselves in mid-air by a swing of their large tails in one direction causing the body to rotate in the other. Here, we developed a new three-dimensional analytical model to investigate the effectiveness of tails as inertial appendages that change body orientation. We anchored our model using the morphological parameters of the flat-tailed house gecko Hemidactylus platyurus. The degree of roll in air righting and the amount of yaw in mid-air turning directly measured in house geckos matched the model's results. Our model predicted an increase in body roll and turning as tails increase in length relative to the body. Tails that swung from a near orthogonal plane relative to the body (i.e. 0-30{sup 0} from vertical) were the most effective at generating body roll, whereas tails operating at steeper angles (i.e. 45-60{sup 0}) produced only half the rotation. To further test our analytical model's predictions, we built a bio-inspired robot prototype. The robot reinforced how effective attitude control can be attained with simple movements of an inertial appendage.

  5. A two-dimensional iterative panel method and boundary layer model for bio-inspired multi-body wings

    Science.gov (United States)

    Blower, Christopher J.; Dhruv, Akash; Wickenheiser, Adam M.

    2014-03-01

    The increased use of Unmanned Aerial Vehicles (UAVs) has created a continuous demand for improved flight capabilities and range of use. During the last decade, engineers have turned to bio-inspiration for new and innovative flow control methods for gust alleviation, maneuverability, and stability improvement using morphing aircraft wings. The bio-inspired wing design considered in this study mimics the flow manipulation techniques performed by birds to extend the operating envelope of UAVs through the installation of an array of feather-like panels across the airfoil's upper and lower surfaces while replacing the trailing edge flap. Each flap has the ability to deflect into both the airfoil and the inbound airflow using hinge points with a single degree-of-freedom, situated at 20%, 40%, 60% and 80% of the chord. The installation of the surface flaps offers configurations that enable advantageous maneuvers while alleviating gust disturbances. Due to the number of possible permutations available for the flap configurations, an iterative constant-strength doublet/source panel method has been developed with an integrated boundary layer model to calculate the pressure distribution and viscous drag over the wing's surface. As a result, the lift, drag and moment coefficients for each airfoil configuration can be calculated. The flight coefficients of this numerical method are validated using experimental data from a low speed suction wind tunnel operating at a Reynolds Number 300,000. This method enables the aerodynamic assessment of a morphing wing profile to be performed accurately and efficiently in comparison to Computational Fluid Dynamics methods and experiments as discussed herein.

  6. At the biological modeling and simulation frontier.

    Science.gov (United States)

    Hunt, C Anthony; Ropella, Glen E P; Lam, Tai Ning; Tang, Jonathan; Kim, Sean H J; Engelberg, Jesse A; Sheikh-Bahaei, Shahab

    2009-11-01

    We provide a rationale for and describe examples of synthetic modeling and simulation (M&S) of biological systems. We explain how synthetic methods are distinct from familiar inductive methods. Synthetic M&S is a means to better understand the mechanisms that generate normal and disease-related phenomena observed in research, and how compounds of interest interact with them to alter phenomena. An objective is to build better, working hypotheses of plausible mechanisms. A synthetic model is an extant hypothesis: execution produces an observable mechanism and phenomena. Mobile objects representing compounds carry information enabling components to distinguish between them and react accordingly when different compounds are studied simultaneously. We argue that the familiar inductive approaches contribute to the general inefficiencies being experienced by pharmaceutical R&D, and that use of synthetic approaches accelerates and improves R&D decision-making and thus the drug development process. A reason is that synthetic models encourage and facilitate abductive scientific reasoning, a primary means of knowledge creation and creative cognition. When synthetic models are executed, we observe different aspects of knowledge in action from different perspectives. These models can be tuned to reflect differences in experimental conditions and individuals, making translational research more concrete while moving us closer to personalized medicine.

  7. Perceptually-Inspired Computing

    Directory of Open Access Journals (Sweden)

    Ming Lin

    2015-08-01

    Full Text Available Human sensory systems allow individuals to see, hear, touch, and interact with the surrounding physical environment. Understanding human perception and its limit enables us to better exploit the psychophysics of human perceptual systems to design more efficient, adaptive algorithms and develop perceptually-inspired computational models. In this talk, I will survey some of recent efforts on perceptually-inspired computing with applications to crowd simulation and multimodal interaction. In particular, I will present data-driven personality modeling based on the results of user studies, example-guided physics-based sound synthesis using auditory perception, as well as perceptually-inspired simplification for multimodal interaction. These perceptually guided principles can be used to accelerating multi-modal interaction and visual computing, thereby creating more natural human-computer interaction and providing more immersive experiences. I will also present their use in interactive applications for entertainment, such as video games, computer animation, and shared social experience. I will conclude by discussing possible future research directions.

  8. Nonlinear Rheology in a Model Biological Tissue

    Science.gov (United States)

    Matoz-Fernandez, D. A.; Agoritsas, Elisabeth; Barrat, Jean-Louis; Bertin, Eric; Martens, Kirsten

    2017-04-01

    The rheological response of dense active matter is a topic of fundamental importance for many processes in nature such as the mechanics of biological tissues. One prominent way to probe mechanical properties of tissues is to study their response to externally applied forces. Using a particle-based model featuring random apoptosis and environment-dependent division rates, we evidence a crossover from linear flow to a shear-thinning regime with an increasing shear rate. To rationalize this nonlinear flow we derive a theoretical mean-field scenario that accounts for the interplay of mechanical and active noise in local stresses. These noises are, respectively, generated by the elastic response of the cell matrix to cell rearrangements and by the internal activity.

  9. Data specifications for INSPIRE

    Science.gov (United States)

    Portele, Clemens; Woolf, Andrew; Cox, Simon

    2010-05-01

    In Europe a major recent development has been the entering in force of the INSPIRE Directive in May 2007, establishing an infrastructure for spatial information in Europe to support Community environmental policies, and policies or activities which may have an impact on the environment. INSPIRE is based on the infrastructures for spatial information established and operated by the 27 Member States of the European Union. The Directive addresses 34 spatial data themes needed for environmental applications, with key components specified through technical implementing rules. This makes INSPIRE a unique example of a legislative "regional" approach. One of the requirements of the INSPIRE Directive is to make existing spatial data sets with relevance for one of the spatial data themes available in an interoperable way, i.e. where the spatial data from different sources in Europe can be combined to a coherent result. Since INSPIRE covers a wide range of spatial data themes, the first step has been the development of a modelling framework that provides a common foundation for all themes. This framework is largely based on the ISO 19100 series of standards. The use of common generic spatial modelling concepts across all themes is an important enabler for interoperability. As a second step, data specifications for the first set of themes has been developed based on the modelling framework. The themes include addresses, transport networks, protected sites, hydrography, administrative areas and others. The data specifications were developed by selected experts nominated by stakeholders from all over Europe. For each theme a working group was established in early 2008 working on their specific theme and collaborating with the other working groups on cross-theme issues. After a public review of the draft specifications starting in December 2008, an open testing process and thorough comment resolution process, the draft technical implementing rules for these themes have been

  10. Detecting variability in MATLAB/Simulink models : an industry-inspired technique and its evaluation

    NARCIS (Netherlands)

    Schlie, A.; Wille, D.; Schulze, S.; Cleophas, L.G.W.A.; Schaefer, I.

    2017-01-01

    Model-based languages such as MATLAB/Simulink play an essential role in the model-driven development of software systems. To comply with new requirements, it is common practice to create new variants by copying existing systems and modifying them. Commonly referred to as clone-and-own, severe

  11. Using a hybrid neuron in physiologically inspired models of the basal ganglia

    Directory of Open Access Journals (Sweden)

    Corey Michael Thibeault

    2013-07-01

    Full Text Available Our current understanding of the basal ganglia has facilitated the creation of computational models that have contributed novel theories, explored new functional anatomy and demonstrated results complementing physiological experiments. However, the utility of these models extends beyond these applications. Particularly in neuromorphic engineering, where the basal ganglia's role in computation is important for applications such as power efficient autonomous agents and model-based control strategies. The neurons used in existing computational models of the basal ganglia however, are not amenable for many low-power hardware implementations. Motivated by a need for more hardware accessible networks, we replicate four published models of the basal ganglia, spanning single neuron and small networks, replacing the more computationally expensive neuron models with an Izhikevich hybrid neuron. This begins with a network modeling action-selection, where the basal activity levels and the ability to appropriately select the most salient input is reproduced. A Parkinson's disease model is then explored under normal conditions, Parkinsonian conditions and during subthalamic nucleus deep brain stimulation. The resulting network is capable of replicating the loss of thalamic relay capabilities in the Parkinsonian state and its return under deep brain stimulation. This is also demonstrated using a network capable of action-selection. Finally, a study of correlation transfer under different patterns of Parkinsonian activity is presented. These networks successfully captured the significant results of the originals studies. This not only creates a foundation for neuromorphic hardware implementations but may also support the development of large-scale biophysical models. The former potentially providing a way of improving the efficacy of deep brain stimulation and the latter allowing for the efficient simulation of larger more comprehensive networks.

  12. A methodology and supply chain management inspired reference ontology for modeling healthcare teams.

    Science.gov (United States)

    Kuziemsky, Craig E; Yazdi, Sara

    2011-01-01

    Numerous studies and strategic plans are advocating more team based healthcare delivery that is facilitated by information and communication technologies (ICTs). However before we can design ICTs to support teams we need a solid conceptual model of team processes and a methodology for using such a model in healthcare settings. This paper draws upon success in the supply chain management domain to develop a reference ontology of healthcare teams and a methodology for modeling teams to instantiate the ontology in specific settings. This research can help us understand how teams function and how we can design ICTs to support teams.

  13. Computational Modeling of Biological Systems From Molecules to Pathways

    CERN Document Server

    2012-01-01

    Computational modeling is emerging as a powerful new approach for studying and manipulating biological systems. Many diverse methods have been developed to model, visualize, and rationally alter these systems at various length scales, from atomic resolution to the level of cellular pathways. Processes taking place at larger time and length scales, such as molecular evolution, have also greatly benefited from new breeds of computational approaches. Computational Modeling of Biological Systems: From Molecules to Pathways provides an overview of established computational methods for the modeling of biologically and medically relevant systems. It is suitable for researchers and professionals working in the fields of biophysics, computational biology, systems biology, and molecular medicine.

  14. Towards Bio-Inspired Chromatic Behaviours in Surveillance Robots

    Directory of Open Access Journals (Sweden)

    Sampath Kumar Karutaa Gnaniar

    2016-09-01

    Full Text Available The field of Robotics is ever growing at the same time as posing enormous challenges. Numerous works has been done in biologically inspired robotics emulating models, systems and elements of nature for the purpose of solving traditional robotics problems. Chromatic behaviours are abundant in nature across a variety of living species to achieve camouflage, signaling, and temperature regulation. The ability of these creatures to successfully blend in with their environment and communicate by changing their colour is the fundamental inspiration for our research work. In this paper, we present dwarf chameleon inspired chromatic behaviour in the context of an autonomous surveillance robot, “PACHONDHI”. In our experiments, we successfully validated the ability of the robot to autonomously change its colour in relation to the terrain that it is traversing for maximizing detectability to friendly security agents and minimizing exposure to hostile agents, as well as to communicate with fellow cooperating robots.

  15. Non-thermal transitions in a model inspired by moral decisions

    International Nuclear Information System (INIS)

    Alamino, Roberto C

    2016-01-01

    This work introduces a model in which agents of a network act upon one another according to three different kinds of moral decisions. These decisions are based on an increasing level of sophistication in the empathy capacity of the agent, a hierarchy which we name Piaget ’ s ladder . The decision strategy of the agents is non-rational, in the sense they are arbitrarily fixed, and the model presents quenched disorder given by the distribution of its defining parameters. An analytical solution for this model is obtained in the large system limit as well as a leading order correction for finite-size systems which shows that typical realisations of the model develop a phase structure with both continuous and discontinuous non-thermal transitions. (paper)

  16. An insect-inspired model for visual binding I: learning objects and their characteristics.

    Science.gov (United States)

    Northcutt, Brandon D; Dyhr, Jonathan P; Higgins, Charles M

    2017-04-01

    Visual binding is the process of associating the responses of visual interneurons in different visual submodalities all of which are responding to the same object in the visual field. Recently identified neuropils in the insect brain termed optic glomeruli reside just downstream of the optic lobes and have an internal organization that could support visual binding. Working from anatomical similarities between optic and olfactory glomeruli, we have developed a model of visual binding based on common temporal fluctuations among signals of independent visual submodalities. Here we describe and demonstrate a neural network model capable both of refining selectivity of visual information in a given visual submodality, and of associating visual signals produced by different objects in the visual field by developing inhibitory neural synaptic weights representing the visual scene. We also show that this model is consistent with initial physiological data from optic glomeruli. Further, we discuss how this neural network model may be implemented in optic glomeruli at a neuronal level.

  17. Bio-inspired modeling and implementation of the ocelli visual system of flying insects.

    Science.gov (United States)

    Gremillion, Gregory; Humbert, J Sean; Krapp, Holger G

    2014-12-01

    Two visual sensing modalities in insects, the ocelli and compound eyes, provide signals used for flight stabilization and navigation. In this article, a generalized model of the ocellar visual system is developed for a 3-D visual simulation environment based on behavioral, anatomical, and electrophysiological data from several species. A linear measurement model is estimated from Monte Carlo simulation in a cluttered urban environment relating state changes of the vehicle to the outputs of the ocellar model. A fully analog-printed circuit board sensor based on this model is designed and fabricated. Open-loop characterization of the sensor to visual stimuli induced by self motion is performed. Closed-loop stabilizing feedback of the sensor in combination with optic flow sensors is implemented onboard a quadrotor micro-air vehicle and its impulse response is characterized.

  18. On the limitations of standard statistical modeling in biological systems: a full Bayesian approach for biology.

    Science.gov (United States)

    Gomez-Ramirez, Jaime; Sanz, Ricardo

    2013-09-01

    One of the most important scientific challenges today is the quantitative and predictive understanding of biological function. Classical mathematical and computational approaches have been enormously successful in modeling inert matter, but they may be inadequate to address inherent features of biological systems. We address the conceptual and methodological obstacles that lie in the inverse problem in biological systems modeling. We introduce a full Bayesian approach (FBA), a theoretical framework to study biological function, in which probability distributions are conditional on biophysical information that physically resides in the biological system that is studied by the scientist. Copyright © 2013 Elsevier Ltd. All rights reserved.

  19. One-Class FMRI-Inspired EEG Model for Self-Regulation Training.

    Directory of Open Access Journals (Sweden)

    Yehudit Meir-Hasson

    Full Text Available Recent evidence suggests that learned self-regulation of localized brain activity in deep limbic areas such as the amygdala, may alleviate symptoms of affective disturbances. Thus far self-regulation of amygdala activity could be obtained only via fMRI guided neurofeedback, an expensive and immobile procedure. EEG on the other hand is relatively inexpensive and can be easily implemented in any location. However the clinical utility of EEG neurofeedback for affective disturbances remains limited due to low spatial resolution, which hampers the targeting of deep limbic areas such as the amygdala. We introduce an EEG prediction model of amygdala activity from a single electrode. The gold standard used for training is the fMRI-BOLD signal in the amygdala during simultaneous EEG/fMRI recording. The suggested model is based on a time/frequency representation of the EEG data with varying time-delay. Previous work has shown a strong inhomogeneity among subjects as is reflected by the models created to predict the amygdala BOLD response from EEG data. In that work, different models were constructed for different subjects. In this work, we carefully analyzed the inhomogeneity among subjects and were able to construct a single model for the majority of the subjects. We introduce a method for inhomogeneity assessment. This enables us to demonstrate a choice of subjects for which a single model could be derived. We further demonstrate the ability to modulate brain-activity in a neurofeedback setting using feedback generated by the model. We tested the effect of the neurofeedback training by showing that new subjects can learn to down-regulate the signal amplitude compared to a sham group, which received a feedback obtained by a different participant. This EEG based model can overcome substantial limitations of fMRI-NF. It can enable investigation of NF training using multiple sessions and large samples in various locations.

  20. Biologically based multistage modeling of radiation effects

    Energy Technology Data Exchange (ETDEWEB)

    William Hazelton; Suresh Moolgavkar; E. Georg Luebeck

    2005-08-30

    This past year we have made substantial progress in modeling the contribution of homeostatic regulation to low-dose radiation effects and carcinogenesis. We have worked to refine and apply our multistage carcinogenesis models to explicitly incorporate cell cycle states, simple and complex damage, checkpoint delay, slow and fast repair, differentiation, and apoptosis to study the effects of low-dose ionizing radiation in mouse intestinal crypts, as well as in other tissues. We have one paper accepted for publication in ''Advances in Space Research'', and another manuscript in preparation describing this work. I also wrote a chapter describing our combined cell-cycle and multistage carcinogenesis model that will be published in a book on stochastic carcinogenesis models edited by Wei-Yuan Tan. In addition, we organized and held a workshop on ''Biologically Based Modeling of Human Health Effects of Low dose Ionizing Radiation'', July 28-29, 2005 at Fred Hutchinson Cancer Research Center in Seattle, Washington. We had over 20 participants, including Mary Helen Barcellos-Hoff as keynote speaker, talks by most of the low-dose modelers in the DOE low-dose program, experimentalists including Les Redpath (and Mary Helen), Noelle Metting from DOE, and Tony Brooks. It appears that homeostatic regulation may be central to understanding low-dose radiation phenomena. The primary effects of ionizing radiation (IR) are cell killing, delayed cell cycling, and induction of mutations. However, homeostatic regulation causes cells that are killed or damaged by IR to eventually be replaced. Cells with an initiating mutation may have a replacement advantage, leading to clonal expansion of these initiated cells. Thus we have focused particularly on modeling effects that disturb homeostatic regulation as early steps in the carcinogenic process. There are two primary considerations that support our focus on homeostatic regulation. First, a number of

  1. Leptogenesis as an origin of hot dark matter and baryon asymmetry in the E6 inspired SUSY models

    Science.gov (United States)

    Nevzorov, R.

    2018-04-01

    We explore leptogenesis within the E6 inspired U (1) extension of the MSSM in which exact custodial symmetry forbids tree-level flavour-changing transitions and the most dangerous baryon and lepton number violating operators. This supersymmetric (SUSY) model involves extra exotic matter beyond the MSSM. In the simplest phenomenologically viable scenarios the lightest exotic fermions are neutral and stable. These states should be substantially lighter than 1eV forming hot dark matter in the Universe. The low-energy effective Lagrangian of the SUSY model under consideration possesses an approximate global U(1)E symmetry associated with the exotic states. The U(1)E symmetry is explicitly broken because of the interactions between the right-handed neutrino superfields and exotic matter supermultiplets. As a consequence the decays of the lightest right-handed neutrino/sneutrino give rise to both U(1)E and U(1) B - L asymmetries. When all right-handed neutrino/sneutrino are relatively light ∼106-107GeV the appropriate amount of the baryon asymmetry can be induced via these decays if the Yukawa couplings of the lightest right-handed neutrino superfields to the exotic matter supermultiplets vary between ∼10-4-10-3.

  2. Multispecies exclusion process with fusion and fission of rods: A model inspired by intraflagellar transport

    Science.gov (United States)

    Patra, Swayamshree; Chowdhury, Debashish

    2018-01-01

    We introduce a multispecies exclusion model where length-conserving probabilistic fusion and fission of the hard rods are allowed. Although all rods enter the system with the same initial length ℓ =1 , their length can keep changing, because of fusion and fission, as they move in a step-by-step manner towards the exit. Two neighboring hard rods of lengths ℓ1 and ℓ2 can fuse into a single rod of longer length ℓ =ℓ1+ℓ2 provided ℓ ≤N . Similarly, length-conserving fission of a rod of length ℓ'≤N results in two shorter daughter rods. Based on the extremum current hypothesis, we plot the phase diagram of the model under open boundary conditions utilizing the results derived for the same model under periodic boundary condition using mean-field approximation. The density profile and the flux profile of rods are in excellent agreement with computer simulations. Although the fusion and fission of the rods are motivated by similar phenomena observed in intraflagellar transport (IFT) in eukaryotic flagella, this exclusion model is too simple to account for the quantitative experimental data for any specific organism. Nevertheless, the concepts of "flux profile" and "transition zone" that emerge from the interplay of fusion and fission in this model are likely to have important implications for IFT and for other similar transport phenomena in long cell protrusions.

  3. A Light Sail Inspired Model to Harness Casimir Forces for Propellantless Propulsion

    International Nuclear Information System (INIS)

    DeBiase, R. L.

    2010-01-01

    The model used to calculate Casimir forces for variously shaped conducting plates in this paper assumes the vacuum energy pervades all space and that photons randomly pop into and out of existence. While they exist, they possess energy and momentum that can be transferred by reflection as in a light sail. Quantum mechanics in the model is entirely bound up in the Casimir equation of force per unit area. This model is compared with two different experiments: that of Chen and Mohideen demonstrating lateral Casimir forces for sinusoidally corrugated spherical and flat plates and Lamoreaux demonstrating normal Casimir forces between a conducting sphere and flat plate. The calculated forces using this model were compared to the forces obtained in these experiments as well as with calculations using the proximity force approximation. In both cases the results (when compared to the actual plates measured and calculated using non-corrected equations) were less than a few parts per thousand different for the range of separation distances used. When the model was used to calculate forces on the opposite plates, different force magnitudes were obtained seemingly indicating prospects for propellentless propulsion but requiring skeptical verification.

  4. Model checking biological systems described using ambient calculus

    DEFF Research Database (Denmark)

    Mardare, Radu Iulian; Priami, Corrado; Qualia, Paola

    2005-01-01

    Model checking biological systems described using ambient calculus. In Proc. of the second International Workshop on Computational Methods in Systems Biology (CMSB04), Lecture Notes in Bioinformatics 3082:85-103, Springer, 2005.......Model checking biological systems described using ambient calculus. In Proc. of the second International Workshop on Computational Methods in Systems Biology (CMSB04), Lecture Notes in Bioinformatics 3082:85-103, Springer, 2005....

  5. Bio-inspired computational heuristics to study Lane-Emden systems arising in astrophysics model.

    Science.gov (United States)

    Ahmad, Iftikhar; Raja, Muhammad Asif Zahoor; Bilal, Muhammad; Ashraf, Farooq

    2016-01-01

    This study reports novel hybrid computational methods for the solutions of nonlinear singular Lane-Emden type differential equation arising in astrophysics models by exploiting the strength of unsupervised neural network models and stochastic optimization techniques. In the scheme the neural network, sub-part of large field called soft computing, is exploited for modelling of the equation in an unsupervised manner. The proposed approximated solutions of higher order ordinary differential equation are calculated with the weights of neural networks trained with genetic algorithm, and pattern search hybrid with sequential quadratic programming for rapid local convergence. The results of proposed solvers for solving the nonlinear singular systems are in good agreements with the standard solutions. Accuracy and convergence the design schemes are demonstrated by the results of statistical performance measures based on the sufficient large number of independent runs.

  6. Anisotropic flow fluctuations in hydro-inspired freeze-out model for relativistic heavy ion collisions

    CERN Document Server

    Bravina, L V; Korotkikh, V L; Lokhtin, I P; Malinina, L V; Nazarova, E N; Petrushanko, S V; Snigirev, A M; Zabrodin, E E

    2015-01-01

    The possible mechanisms contributing to anisotropic flow fluctuations in relativistic heavy ion collisions are discussed. The LHC data on event-by-event harmonic flow coefficients measured in PbPb collisions at center-of-mass energy 2.76 TeV per nucleon pair are analyzed and interpreted within the HYDJET++ model. To compare the model results with the experimental data the unfolding procedure is employed. It is shown that HYDJET++ correctly reproduces dynamical fluctuations of elliptic and triangular flows and related to it eccentricity fluctuations of the initial state.

  7. A Comprehensive Piezoelectric Bending-Beam Model Inspired by Microaerial Vehicle Applications

    Science.gov (United States)

    Szabo, Peter Andras Kovacs

    Microaerial vehicles are an up-and-coming area of robotics which is fuelled by modern understanding of the unsteady aerodynamics of insect flight and the development of new actuation technologies. In the past two decades computer simulations have aided in uncovering the lift mechanisms which flying insects use to stay aloft. Using these details, roboticists had begun using lightweight structures and high power density actuators to mimic the physical parameters and flapping kinematics of flying insects with the intent to recreate the dynamics of insect flight. One of the most important aspects of flapping-wing microaerial vehicles is the actuation method. Piezoelectric bending-beam actuators have been scaled up from MEMS technology for use in microaerial vehicle applications owing to their high power density and performance at low mass. The initial development toward the UTIAS Robotic Dragonfly, a microaerial vehicle platform using a piezoelectric-based actuator, is outlined. The components are fabricated from lightweight materials such as a carbon fibre frame, polymide film joints, and polyester film wings while the actuator is a piezoelectric bending-beam which was designed using existing mathematical models. The design and fabrication of the wings, actuator, transmission, and power supply are detailed. The prototypes are measured for lift generation using custom lift sensors which had undergone static and dynamic calibration for low-force, high-bandwidth measurement. Although the resulting lift curves qualitatively correspond with the literature, it was determined that more power was needed for lift-off to be achieved and existing piezoelectric models do not fully account for maximizing the force-deflection relationship. An extension to the existing Ballas model of piezoelectric bending-beam devices is derived. This modified Ballas model incorporates devices beyond constant width. Actuator performance limitations highlighted the need for a more comprehensive

  8. Mathematical toy model inspired by the problem of the adaptive origins of the sexual orientation continuum

    Science.gov (United States)

    Skinner, Brian

    2016-09-01

    Same-sex sexual behaviour is ubiquitous in the animal kingdom, but its adaptive origins remain a prominent puzzle. Here, I suggest the possibility that same-sex sexual behaviour arises as a consequence of the competition between an evolutionary drive for a wide diversity in traits, which improves the adaptability of a population, and a drive for sexual dichotomization of traits, which promotes opposite-sex attraction and increases the rate of reproduction. This trade-off is explored via a simple mathematical `toy model'. The model exhibits a number of interesting features and suggests a simple mathematical form for describing the sexual orientation continuum.

  9. Dynamic response and transfer function of social systems: A neuro-inspired model of collective human activity patterns.

    Science.gov (United States)

    Lymperopoulos, Ilias N

    2017-10-01

    The interaction of social networks with the external environment gives rise to non-stationary activity patterns reflecting the temporal structure and strength of exogenous influences that drive social dynamical processes far from an equilibrium state. Following a neuro-inspired approach, based on the dynamics of a passive neuronal membrane, and the firing rate dynamics of single neurons and neuronal populations, we build a state-of-the-art model of the collective social response to exogenous interventions. In this regard, we analyze online activity patterns with a view to determining the transfer function of social systems, that is, the dynamic relationship between external influences and the resulting activity. To this end, first we estimate the impulse response (Green's function) of collective activity, and then we show that the convolution of the impulse response with a time-varying external influence field accurately reproduces empirical activity patterns. To capture the dynamics of collective activity when the generating process is in a state of statistical equilibrium, we incorporate into the model a noisy input convolved with the impulse response function, thus precisely reproducing the fluctuations of stationary collective activity around a resting value. The outstanding goodness-of-fit of the model results to empirical observations, indicates that the model explains human activity patterns generated by time-dependent external influences in various socio-economic contexts. The proposed model can be used for inferring the temporal structure and strength of external influences, as well as the inertia of collective social activity. Furthermore, it can potentially predict social activity patterns. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Modeling of nonlinear biological phenomena modeled by S-systems.

    Science.gov (United States)

    Mansouri, Majdi M; Nounou, Hazem N; Nounou, Mohamed N; Datta, Aniruddha A

    2014-03-01

    A central challenge in computational modeling of biological systems is the determination of the model parameters. In such cases, estimating these variables or parameters from other easily obtained measurements can be extremely useful. For example, time-series dynamic genomic data can be used to develop models representing dynamic genetic regulatory networks, which can be used to design intervention strategies to cure major diseases and to better understand the behavior of biological systems. Unfortunately, biological measurements are usually highly infected by errors that hide the important characteristics in the data. Therefore, these noisy measurements need to be filtered to enhance their usefulness in practice. This paper addresses the problem of state and parameter estimation of biological phenomena modeled by S-systems using Bayesian approaches, where the nonlinear observed system is assumed to progress according to a probabilistic state space model. The performances of various conventional and state-of-the-art state estimation techniques are compared. These techniques include the extended Kalman filter (EKF), unscented Kalman filter (UKF), particle filter (PF), and the developed variational Bayesian filter (VBF). Specifically, two comparative studies are performed. In the first comparative study, the state variables (the enzyme CadA, the model cadBA, the cadaverine Cadav and the lysine Lys for a model of the Cad System in Escherichia coli (CSEC)) are estimated from noisy measurements of these variables, and the various estimation techniques are compared by computing the estimation root mean square error (RMSE) with respect to the noise-free data. In the second comparative study, the state variables as well as the model parameters are simultaneously estimated. In this case, in addition to comparing the performances of the various state estimation techniques, the effect of the number of estimated model parameters on the accuracy and convergence of these

  11. Study of the meson mass spectroscopy with a potential model inspired in the quantum chromodynamics

    International Nuclear Information System (INIS)

    Bernardini, Alex Eduardo de

    2001-01-01

    Since the discovery of QCD (Quantum Chromodynamics), there have been remarkable technical achievements in perturbative calculations applied to hadrons. However, it is difficult to use QCD directly to compute hadronic properties. In this context, phenomenological potential models have provided extremely satisfactory results on description of ordinary hadrons, more specifically about quark-antiquark bound states (mesons). In this work we propose and study the main aspects in the construction of a potential model and search a generalized description of meson spectroscopy, with emphasis in heavy quark bound states. We analyze important aspects in the choice of the treatment in good agreement with the dynamics of interacting particles, attempting to relativistic aspects as well as to the possibilities of nonrelativistic approximation analysis. Initially the 'soft QCD' is employed to determine effective potential terms establishing the asymptotic Coulomb term from one gluon exchange approximation. At the same time, a linear confinement term is introduced in accordance with QCD and phenomenological prescription. We perform the calculations of mass spectroscopy for particular sets of mesons and we verify whether the potential model could be extended to calculating the electronic transition rate (Γ(q q-bar → e - e + )). Finishing, we discuss the real physical possibilities of development of a generalized potential model (all quark flavors), its possible advantages relative to experimental parametrization, complexity in numerical calculations and in the description of physical reality in agreement with a quantum field theory (QCD). (author)

  12. A Neurocomputational Model of Goal-Directed Navigation in Insect-Inspired Artificial Agents

    DEFF Research Database (Denmark)

    Goldschmidt, Dennis; Manoonpong, Poramate; Dasgupta, Sakyasingha

    2017-01-01

    in artificial agents. The model consists of a path integration mechanism, reward-modulated global learning, random search, and action selection. The path integration mechanism integrates compass and odometric cues to compute a vectorial representation of the agent's current location as neural activity patterns...

  13. Generating Systems Biology Markup Language Models from the Synthetic Biology Open Language.

    Science.gov (United States)

    Roehner, Nicholas; Zhang, Zhen; Nguyen, Tramy; Myers, Chris J

    2015-08-21

    In the context of synthetic biology, model generation is the automated process of constructing biochemical models based on genetic designs. This paper discusses the use cases for model generation in genetic design automation (GDA) software tools and introduces the foundational concepts of standards and model annotation that make this process useful. Finally, this paper presents an implementation of model generation in the GDA software tool iBioSim and provides an example of generating a Systems Biology Markup Language (SBML) model from a design of a 4-input AND sensor written in the Synthetic Biology Open Language (SBOL).

  14. Minkowski space pion model inspired by lattice QCD running quark mass

    Energy Technology Data Exchange (ETDEWEB)

    Mello, Clayton S. [Instituto Tecnológico de Aeronáutica, DCTA, 12.228-900 São José dos Campos, SP (Brazil); Melo, J.P.B.C. de [Laboratório de Física Teórica e Computacional – LFTC, Universidade Cruzeiro do Sul, 01506-000 São Paulo, SP (Brazil); Frederico, T., E-mail: tobias@ita.br [Instituto Tecnológico de Aeronáutica, DCTA, 12.228-900 São José dos Campos, SP (Brazil)

    2017-03-10

    The pion structure in Minkowski space is described in terms of an analytic model of the Bethe–Salpeter amplitude combined with Euclidean Lattice QCD results. The model is physically motivated to take into account the running quark mass, which is fitted to Lattice QCD data. The pion pseudoscalar vertex is associated to the quark mass function, as dictated by dynamical chiral symmetry breaking requirements in the limit of vanishing current quark mass. The quark propagator is analyzed in terms of a spectral representation, and it shows a violation of the positivity constraints. The integral representation of the pion Bethe–Salpeter amplitude is also built. The pion space-like electromagnetic form factor is calculated with a quark electromagnetic current, which satisfies the Ward–Takahashi identity to ensure current conservation. The results for the form factor and weak decay constant are found to be consistent with the experimental data.

  15. Minkowski space pion model inspired by lattice QCD running quark mass

    Directory of Open Access Journals (Sweden)

    Clayton S. Mello

    2017-03-01

    Full Text Available The pion structure in Minkowski space is described in terms of an analytic model of the Bethe–Salpeter amplitude combined with Euclidean Lattice QCD results. The model is physically motivated to take into account the running quark mass, which is fitted to Lattice QCD data. The pion pseudoscalar vertex is associated to the quark mass function, as dictated by dynamical chiral symmetry breaking requirements in the limit of vanishing current quark mass. The quark propagator is analyzed in terms of a spectral representation, and it shows a violation of the positivity constraints. The integral representation of the pion Bethe–Salpeter amplitude is also built. The pion space-like electromagnetic form factor is calculated with a quark electromagnetic current, which satisfies the Ward–Takahashi identity to ensure current conservation. The results for the form factor and weak decay constant are found to be consistent with the experimental data.

  16. A Neurocomputational Model of Goal-Directed Navigation in Insect-Inspired Artificial Agents.

    Science.gov (United States)

    Goldschmidt, Dennis; Manoonpong, Poramate; Dasgupta, Sakyasingha

    2017-01-01

    Despite their small size, insect brains are able to produce robust and efficient navigation in complex environments. Specifically in social insects, such as ants and bees, these navigational capabilities are guided by orientation directing vectors generated by a process called path integration. During this process, they integrate compass and odometric cues to estimate their current location as a vector, called the home vector for guiding them back home on a straight path. They further acquire and retrieve path integration-based vector memories globally to the nest or based on visual landmarks. Although existing computational models reproduced similar behaviors, a neurocomputational model of vector navigation including the acquisition of vector representations has not been described before. Here we present a model of neural mechanisms in a modular closed-loop control-enabling vector navigation in artificial agents. The model consists of a path integration mechanism, reward-modulated global learning, random search, and action selection. The path integration mechanism integrates compass and odometric cues to compute a vectorial representation of the agent's current location as neural activity patterns in circular arrays. A reward-modulated learning rule enables the acquisition of vector memories by associating the local food reward with the path integration state. A motor output is computed based on the combination of vector memories and random exploration. In simulation, we show that the neural mechanisms enable robust homing and localization, even in the presence of external sensory noise. The proposed learning rules lead to goal-directed navigation and route formation performed under realistic conditions. Consequently, we provide a novel approach for vector learning and navigation in a simulated, situated agent linking behavioral observations to their possible underlying neural substrates.

  17. Cortex Inspired Model for Inverse Kinematics Computation for a Humanoid Robotic Finger

    Science.gov (United States)

    Gentili, Rodolphe J.; Oh, Hyuk; Molina, Javier; Reggia, James A.; Contreras-Vidal, José L.

    2013-01-01

    In order to approach human hand performance levels, artificial anthropomorphic hands/fingers have increasingly incorporated human biomechanical features. However, the performance of finger reaching movements to visual targets involving the complex kinematics of multi-jointed, anthropomorphic actuators is a difficult problem. This is because the relationship between sensory and motor coordinates is highly nonlinear, and also often includes mechanical coupling of the two last joints. Recently, we developed a cortical model that learns the inverse kinematics of a simulated anthropomorphic finger. Here, we expand this previous work by assessing if this cortical model is able to learn the inverse kinematics for an actual anthropomorphic humanoid finger having its two last joints coupled and controlled by pneumatic muscles. The findings revealed that single 3D reaching movements, as well as more complex patterns of motion of the humanoid finger, were accurately and robustly performed by this cortical model while producing kinematics comparable to those of humans. This work contributes to the development of a bioinspired controller providing adaptive, robust and flexible control of dexterous robotic and prosthetic hands. PMID:23366569

  18. [NiFe] hydrogenase structural and functional models: new bio-inspired catalysts for hydrogen evolution

    International Nuclear Information System (INIS)

    Oudart, Y.

    2006-09-01

    Hydrogenase enzymes reversibly catalyze the oxidation and production of hydrogen in a range close to the thermodynamic potential. The [NiFe] hydrogenase active site contains an iron-cyano-carbonyl moiety linked to a nickel atom which is in an all sulphur environment. Both the active site originality and the potential development of an hydrogen economy make the synthesis of functional and structural models worthy. To take up this challenge, we have synthesised mononuclear ruthenium models and more importantly, nickel-ruthenium complexes, mimicking some structural features of the [NiFe] hydrogenase active site. Ruthenium is indeed isoelectronic to iron and some of its complexes are well-known to bear hydrides. The compounds described in this study have been well characterised and their activity in proton reduction has been successfully tested. Most of them are able to catalyze this reaction though their electrocatalytic potentials remain much more negative compared to which of platinum. The studied parameters point out the importance of the complexes electron richness, especially of the nickel environment. Furthermore, the proton reduction activity is stable for several hours at good rates. The ruthenium environment seems important for this stability. Altogether, these compounds represent the very first catalytically active [NiFe] hydrogenase models. Important additional results of this study are the synergetic behaviour of the two metals in protons reduction and the evidence of a protonation step as the limiting step of the catalytic cycle. We have also shown that a basic site close to ruthenium improves the electrocatalytic potential of the complexes. (author)

  19. Organization model for Mobile Wireless Sensor Networks inspired in Artificial Bee Colony

    International Nuclear Information System (INIS)

    Julio de Mesquita Filho, Sao Jose do Rio Preto, SP (Brazil))" data-affiliation=" (Sao Paulo State Univerity Julio de Mesquita Filho, Sao Jose do Rio Preto, SP (Brazil))" >Roberto, Guilherme Freire; Julio de Mesquita Filho, Sao Jose do Rio Preto, SP (Brazil))" data-affiliation=" (Sao Paulo State Univerity Julio de Mesquita Filho, Sao Jose do Rio Preto, SP (Brazil))" >Neves, Leandro Alves; Maschi, Luis Fernando Castilho; Pigatto, Daniel Fernando; Branco, Kalinka Regina Lucas Jaquie Castelo; Montez, Carlos; Pinto, Alex Sandro Roschildt

    2015-01-01

    The purpose of this study is to find a self-organizing model for MWSN based on bee colonies in order to reduce the number of messages transmitted among nodes, and thus reduce the overall consumption energy while maintaining the efficiency of message delivery. The results obtained in this article are originated from simulations carried out with SINALGO software, which demonstrates the effectiveness of the proposed approach. The BeeAODV (Bee Ad-Hoc On Demand Distance Vector) proposed in this paper allows to considerably reduce message exchanges whether compared to AODV (Ad-Hoc On Demand Distance Vector)

  20. Creating a business model from the traditional to global fashion: the regional Vianesa costume as inspiration

    Science.gov (United States)

    Broega, A. C.; Gonçalves, E.; Ribeiro, R.

    2017-10-01

    The great challenge of this century is the creation of new models of fashion business with sustainable principles. Therefore, it is intend to present in this paper the process that gave rise to a set of differentiated designs for fashion accessories. This paper presents the relationship of a set of concepts more or less interconnected, which brings together sustainability principles of social and cultural, besides the environmental dimension, exploring the cultural and intangible heritage of the Vianesa Costume. The Vianesa Costume reflects the culture of a people and has a high potential for innovation, from both technical and aesthetic point of view, in the sense of a more contemporary reading.

  1. A universal optimization strategy for ant colony optimization algorithms based on the Physarum-inspired mathematical model

    International Nuclear Information System (INIS)

    Zhang, Zili; Gao, Chao; Liu, Yuxin; Qian, Tao

    2014-01-01

    Ant colony optimization (ACO) algorithms often fall into the local optimal solution and have lower search efficiency for solving the travelling salesman problem (TSP). According to these shortcomings, this paper proposes a universal optimization strategy for updating the pheromone matrix in the ACO algorithms. The new optimization strategy takes advantages of the unique feature of critical paths reserved in the process of evolving adaptive networks of the Physarum-inspired mathematical model (PMM). The optimized algorithms, denoted as PMACO algorithms, can enhance the amount of pheromone in the critical paths and promote the exploitation of the optimal solution. Experimental results in synthetic and real networks show that the PMACO algorithms are more efficient and robust than the traditional ACO algorithms, which are adaptable to solve the TSP with single or multiple objectives. Meanwhile, we further analyse the influence of parameters on the performance of the PMACO algorithms. Based on these analyses, the best values of these parameters are worked out for the TSP. (paper)

  2. Physically Inspired Models for the Synthesis of Stiff Strings with Dispersive Waveguides

    Directory of Open Access Journals (Sweden)

    Testa I

    2004-01-01

    Full Text Available We review the derivation and design of digital waveguides from physical models of stiff systems, useful for the synthesis of sounds from strings, rods, and similar objects. A transform method approach is proposed to solve the classic fourth-order equations of stiff systems in order to reduce it to two second-order equations. By introducing scattering boundary matrices, the eigenfrequencies are determined and their dependency is discussed for the clamped, hinged, and intermediate cases. On the basis of the frequency-domain physical model, the numerical discretization is carried out, showing how the insertion of an all-pass delay line generalizes the Karplus-Strong algorithm for the synthesis of ideally flexible vibrating strings. Knowing the physical parameters, the synthesis can proceed using the generalized structure. Another point of view is offered by Laguerre expansions and frequency warping, which are introduced in order to show that a stiff system can be treated as a nonstiff one, provided that the solutions are warped. A method to compute the all-pass chain coefficients and the optimum warping curves from sound samples is discussed. Once the optimum warping characteristic is found, the length of the dispersive delay line to be employed in the simulation is simply determined from the requirement of matching the desired fundamental frequency. The regularization of the dispersion curves by means of optimum unwarping is experimentally evaluated.

  3. INTERVAL OBSERVER FOR A BIOLOGICAL REACTOR MODEL

    Directory of Open Access Journals (Sweden)

    T. A. Kharkovskaia

    2014-05-01

    Full Text Available The method of an interval observer design for nonlinear systems with parametric uncertainties is considered. The interval observer synthesis problem for systems with varying parameters consists in the following. If there is the uncertainty restraint for the state values of the system, limiting the initial conditions of the system and the set of admissible values for the vector of unknown parameters and inputs, the interval existence condition for the estimations of the system state variables, containing the actual state at a given time, needs to be held valid over the whole considered time segment as well. Conditions of the interval observers design for the considered class of systems are shown. They are: limitation of the input and state, the existence of a majorizing function defining the uncertainty vector for the system, Lipschitz continuity or finiteness of this function, the existence of an observer gain with the suitable Lyapunov matrix. The main condition for design of such a device is cooperativity of the interval estimation error dynamics. An individual observer gain matrix selection problem is considered. In order to ensure the property of cooperativity for interval estimation error dynamics, a static transformation of coordinates is proposed. The proposed algorithm is demonstrated by computer modeling of the biological reactor. Possible applications of these interval estimation systems are the spheres of robust control, where the presence of various types of uncertainties in the system dynamics is assumed, biotechnology and environmental systems and processes, mechatronics and robotics, etc.

  4. Toward University Modeling Instruction—Biology: Adapting Curricular Frameworks from Physics to Biology

    Science.gov (United States)

    Manthey, Seth; Brewe, Eric

    2013-01-01

    University Modeling Instruction (UMI) is an approach to curriculum and pedagogy that focuses instruction on engaging students in building, validating, and deploying scientific models. Modeling Instruction has been successfully implemented in both high school and university physics courses. Studies within the physics education research (PER) community have identified UMI's positive impacts on learning gains, equity, attitudinal shifts, and self-efficacy. While the success of this pedagogical approach has been recognized within the physics community, the use of models and modeling practices is still being developed for biology. Drawing from the existing research on UMI in physics, we describe the theoretical foundations of UMI and how UMI can be adapted to include an emphasis on models and modeling for undergraduate introductory biology courses. In particular, we discuss our ongoing work to develop a framework for the first semester of a two-semester introductory biology course sequence by identifying the essential basic models for an introductory biology course sequence. PMID:23737628

  5. Toward university modeling instruction--biology: adapting curricular frameworks from physics to biology.

    Science.gov (United States)

    Manthey, Seth; Brewe, Eric

    2013-06-01

    University Modeling Instruction (UMI) is an approach to curriculum and pedagogy that focuses instruction on engaging students in building, validating, and deploying scientific models. Modeling Instruction has been successfully implemented in both high school and university physics courses. Studies within the physics education research (PER) community have identified UMI's positive impacts on learning gains, equity, attitudinal shifts, and self-efficacy. While the success of this pedagogical approach has been recognized within the physics community, the use of models and modeling practices is still being developed for biology. Drawing from the existing research on UMI in physics, we describe the theoretical foundations of UMI and how UMI can be adapted to include an emphasis on models and modeling for undergraduate introductory biology courses. In particular, we discuss our ongoing work to develop a framework for the first semester of a two-semester introductory biology course sequence by identifying the essential basic models for an introductory biology course sequence.

  6. Physical models of biological information and adaptation.

    Science.gov (United States)

    Stuart, C I

    1985-04-07

    The bio-informational equivalence asserts that biological processes reduce to processes of information transfer. In this paper, that equivalence is treated as a metaphor with deeply anthropomorphic content of a sort that resists constitutive-analytical definition, including formulation within mathematical theories of information. It is argued that continuance of the metaphor, as a quasi-theoretical perspective in biology, must entail a methodological dislocation between biological and physical science. It is proposed that a general class of functions, drawn from classical physics, can serve to eliminate the anthropomorphism. Further considerations indicate that the concept of biological adaptation is central to the general applicability of the informational idea in biology; a non-anthropomorphic treatment of adaptive phenomena is suggested in terms of variational principles.

  7. Oscillation and stability of delay models in biology

    CERN Document Server

    Agarwal, Ravi P; Saker, Samir H

    2014-01-01

    Environmental variation plays an important role in many biological and ecological dynamical systems. This monograph focuses on the study of oscillation and the stability of delay models occurring in biology. The book presents recent research results on the qualitative behavior of mathematical models under different physical and environmental conditions, covering dynamics including the distribution and consumption of food. Researchers in the fields of mathematical modeling, mathematical biology, and population dynamics will be particularly interested in this material.

  8. Thermodynamics of a solvable quark model inspired by the Gribov-Zwanziger theory

    International Nuclear Information System (INIS)

    Mintz, B.W.; Guimaraes, M.S.

    2013-01-01

    Full text: In an attempt to solve the problem of spurious gauge copies in the path integral approach to gauge theories, V. N. Gribov proposed in 1978 a method to restrict the integration domain of the path integral to only one gauge field representative of each physical field configuration. As a result, the quadratic part of the gluon propagator is modified in the infrared, so that it acquires complex poles, i.e., complex m asses . This implies the absence of gluons in the physical spectrum, which is a necessary condition for confinement. An analogous reasoning may be applied to quark fields coupled to the gauge fields. As a consequence, the quark propagator also gets modified in the infrared, giving rise to unphysical propagators (i.e., with complex poles) at small momenta. Such a property is understood as a sign of both quark confinement and of the breaking of chiral symmetry in the vacuum. In this work, we study the thermodynamics of this model by exactly calculating the partition function using standard methods of finite-temperature quantum field theory. We find that the infrared behavior of the quark propagator leads to a highly nontrivial pressure as a function of the temperature, which is qualitatively close to the results from lattice QCD at finite temperature. (author)

  9. Bending, force recovery, and D-cones in origami inspired model geometries

    Science.gov (United States)

    Eldar, Theresa; Rozairo, Damith; Croll, Andrew B.

    The need for materials with advanced functionality has driven a considerable amount of modern materials science. One idea that has gained significant traction is combining of the ideas Origami and Kirigami with existing materials to build in advanced functionality. In most origami damage is induced in order to trap areas of high curvature in desirable locations in a material. However, the long term and dynamic consequences of local failure are largely unknown. In order to gauge the complex interplay of material properties, relaxation and failure in a set of model thin films, a series of bending and force recovery experiments were carried out. We focus on three materials; polydimethylsiloxane (PDMS), polycarbonate (PC), and polystyrene (PS) chosen for their varying responses to stress. We first measured the load bearing capacity of a single bend in each material, examining the force recovery of bends at various curvatures. Next we examined a doubly folded system in which a single developable cone was created in a similar manner. While the D-cone clearly has massive local consequences for each system, it plays an insignificant role in the system's overall behavior. Finally, we considered higher order combinations of d-cones, ridges and bends. AFOSR under the Young Investigator Program (FA9550-15-1-0168).

  10. Trophallaxis-inspired model for distributed transport between randomly interacting agents

    Science.gov (United States)

    Gräwer, Johannes; Ronellenfitsch, Henrik; Mazza, Marco G.; Katifori, Eleni

    2017-08-01

    Trophallaxis, the regurgitation and mouth to mouth transfer of liquid food between members of eusocial insect societies, is an important process that allows the fast and efficient dissemination of food in the colony. Trophallactic systems are typically treated as a network of agent interactions. This approach, though valuable, does not easily lend itself to analytic predictions. In this work we consider a simple trophallactic system of randomly interacting agents with finite carrying capacity, and calculate analytically and via a series of simulations the global food intake rate for the whole colony as well as observables describing how uniformly the food is distributed within the nest. Our model and predictions provide a useful benchmark to assess to what level the observed food uptake rates and efficiency in food distribution is due to stochastic effects or specific trophallactic strategies by the ant colony. Our work also serves as a stepping stone to describing the collective properties of more complex trophallactic systems, such as those including division of labor between foragers and workers.

  11. Parametrization of Hydrodynamics of Mangrove Root-Inspired Model for Coastline Protection & Energy Harvesting

    Science.gov (United States)

    Feliciano, Julio Lebron; Kazemi, Amirkhosro; Carbajal, Gerardo; Tutkun, Murat; Bocanegra Evans, Humberto; Curet, Oscar; Castillo, Luciano

    2017-11-01

    Mangroves are tropical and subtropical trees that aid in protecting coastlines by dissipating the energy carried by tidal flows. These trees attenuate the devastating effects of powerful natural disasters such as hurricanes. Their roots form complex networks extending out of the water's surface and interacting with the tidal flow in estuaries, deltas, and other inter-tidal areas. This study focuses on the parametrization of the hydrodynamics of mangrove root-like geometries and the effect of the mangrove patch porosity and flexural stiffness. A multivariable non-dimensional empirical correlation is proposed to obtain a self-similar solution that describes the hydrodynamics. We introduced an effective-diameter length scale based on the wake signature of the mangrove root models. It was found that in this new dimensionless parameter, based on the Reynolds number and porosity, was able to characterize the drag coefficient. This analysis is complemented with high-resolution PIV experiments performed in a water tank under various flow and porosity conditions. Furthermore, we analyzed the Vortex-Induced Vibrations (VIVs) of the flexible mangrove patch that produce oscillating energy as a potential source for energy harvesting.

  12. Computerised modelling for developmental biology : an exploration with case studies

    NARCIS (Netherlands)

    Bertens, Laura M.F.

    2012-01-01

    Many studies in developmental biology rely on the construction and analysis of models. This research presents a broad view of modelling approaches for developmental biology, with a focus on computational methods. An overview of modelling techniques is given, followed by several case studies. Using

  13. Morphogenesis and pattern formation in biological systems experiments and models

    CERN Document Server

    Noji, Sumihare; Ueno, Naoto; Maini, Philip

    2003-01-01

    A central goal of current biology is to decode the mechanisms that underlie the processes of morphogenesis and pattern formation. Concerned with the analysis of those phenomena, this book covers a broad range of research fields, including developmental biology, molecular biology, plant morphogenesis, ecology, epidemiology, medicine, paleontology, evolutionary biology, mathematical biology, and computational biology. In Morphogenesis and Pattern Formation in Biological Systems: Experiments and Models, experimental and theoretical aspects of biology are integrated for the construction and investigation of models of complex processes. This collection of articles on the latest advances by leading researchers not only brings together work from a wide spectrum of disciplines, but also provides a stepping-stone to the creation of new areas of discovery.

  14. Genome-scale biological models for industrial microbial systems.

    Science.gov (United States)

    Xu, Nan; Ye, Chao; Liu, Liming

    2018-04-01

    The primary aims and challenges associated with microbial fermentation include achieving faster cell growth, higher productivity, and more robust production processes. Genome-scale biological models, predicting the formation of an interaction among genetic materials, enzymes, and metabolites, constitute a systematic and comprehensive platform to analyze and optimize the microbial growth and production of biological products. Genome-scale biological models can help optimize microbial growth-associated traits by simulating biomass formation, predicting growth rates, and identifying the requirements for cell growth. With regard to microbial product biosynthesis, genome-scale biological models can be used to design product biosynthetic pathways, accelerate production efficiency, and reduce metabolic side effects, leading to improved production performance. The present review discusses the development of microbial genome-scale biological models since their emergence and emphasizes their pertinent application in improving industrial microbial fermentation of biological products.

  15. OFFl Models: Novel Schema for Dynamical Modeling of Biological Systems.

    Science.gov (United States)

    Ogbunugafor, C Brandon; Robinson, Sean P

    2016-01-01

    Flow diagrams are a common tool used to help build and interpret models of dynamical systems, often in biological contexts such as consumer-resource models and similar compartmental models. Typically, their usage is intuitive and informal. Here, we present a formalized version of flow diagrams as a kind of weighted directed graph which follow a strict grammar, which translate into a system of ordinary differential equations (ODEs) by a single unambiguous rule, and which have an equivalent representation as a relational database. (We abbreviate this schema of "ODEs and formalized flow diagrams" as OFFL.) Drawing a diagram within this strict grammar encourages a mental discipline on the part of the modeler in which all dynamical processes of a system are thought of as interactions between dynamical species that draw parcels from one or more source species and deposit them into target species according to a set of transformation rules. From these rules, the net rate of change for each species can be derived. The modeling schema can therefore be understood as both an epistemic and practical heuristic for modeling, serving both as an organizational framework for the model building process and as a mechanism for deriving ODEs. All steps of the schema beyond the initial scientific (intuitive, creative) abstraction of natural observations into model variables are algorithmic and easily carried out by a computer, thus enabling the future development of a dedicated software implementation. Such tools would empower the modeler to consider significantly more complex models than practical limitations might have otherwise proscribed, since the modeling framework itself manages that complexity on the modeler's behalf. In this report, we describe the chief motivations for OFFL, carefully outline its implementation, and utilize a range of classic examples from ecology and epidemiology to showcase its features.

  16. OFFl Models: Novel Schema for Dynamical Modeling of Biological Systems.

    Directory of Open Access Journals (Sweden)

    C Brandon Ogbunugafor

    Full Text Available Flow diagrams are a common tool used to help build and interpret models of dynamical systems, often in biological contexts such as consumer-resource models and similar compartmental models. Typically, their usage is intuitive and informal. Here, we present a formalized version of flow diagrams as a kind of weighted directed graph which follow a strict grammar, which translate into a system of ordinary differential equations (ODEs by a single unambiguous rule, and which have an equivalent representation as a relational database. (We abbreviate this schema of "ODEs and formalized flow diagrams" as OFFL. Drawing a diagram within this strict grammar encourages a mental discipline on the part of the modeler in which all dynamical processes of a system are thought of as interactions between dynamical species that draw parcels from one or more source species and deposit them into target species according to a set of transformation rules. From these rules, the net rate of change for each species can be derived. The modeling schema can therefore be understood as both an epistemic and practical heuristic for modeling, serving both as an organizational framework for the model building process and as a mechanism for deriving ODEs. All steps of the schema beyond the initial scientific (intuitive, creative abstraction of natural observations into model variables are algorithmic and easily carried out by a computer, thus enabling the future development of a dedicated software implementation. Such tools would empower the modeler to consider significantly more complex models than practical limitations might have otherwise proscribed, since the modeling framework itself manages that complexity on the modeler's behalf. In this report, we describe the chief motivations for OFFL, carefully outline its implementation, and utilize a range of classic examples from ecology and epidemiology to showcase its features.

  17. Social insects inspire human design

    Science.gov (United States)

    Holbrook, C. Tate; Clark, Rebecca M.; Moore, Dani; Overson, Rick P.; Penick, Clint A.; Smith, Adrian A.

    2010-01-01

    The international conference ‘Social Biomimicry: Insect Societies and Human Design’, hosted by Arizona State University, USA, 18–20 February 2010, explored how the collective behaviour and nest architecture of social insects can inspire innovative and effective solutions to human design challenges. It brought together biologists, designers, engineers, computer scientists, architects and businesspeople, with the dual aims of enriching biology and advancing biomimetic design. PMID:20392721

  18. Preservice Biology Teachers' Conceptions about the Tentative Nature of Theories and Models in Biology

    Science.gov (United States)

    Reinisch, Bianca; Krüger, Dirk

    2018-01-01

    In research on the nature of science, there is a need to investigate the role and status of different scientific knowledge forms. Theories and models are two of the most important knowledge forms within biology and are the focus of this study. During interviews, preservice biology teachers (N = 10) were asked about their understanding of theories…

  19. Biochemical Space: A Framework for Systemic Annotation of Biological Models

    Czech Academy of Sciences Publication Activity Database

    Klement, M.; Děd, T.; Šafránek, D.; Červený, Jan; Müller, Stefan; Steuer, Ralf

    2014-01-01

    Roč. 306, JUL (2014), s. 31-44 ISSN 1571-0661 R&D Projects: GA MŠk(CZ) EE2.3.20.0256 Institutional support: RVO:67179843 Keywords : biological models * model annotation * systems biology * cyanobacteria Subject RIV: EH - Ecology, Behaviour

  20. Review of "Stochastic Modelling for Systems Biology" by Darren Wilkinson

    Directory of Open Access Journals (Sweden)

    Bullinger Eric

    2006-12-01

    Full Text Available Abstract "Stochastic Modelling for Systems Biology" by Darren Wilkinson introduces the peculiarities of stochastic modelling in biology. This book is particularly suited to as a textbook or for self-study, and for readers with a theoretical background.

  1. 3D printed, bio-inspired prototypes and analytical models for structured suture interfaces with geometrically-tuned deformation and failure behavior

    Science.gov (United States)

    Lin, Erica; Li, Yaning; Ortiz, Christine; Boyce, Mary C.

    2014-12-01

    Geometrically structured interfaces in nature possess enhanced, and often surprising, mechanical properties, and provide inspiration for materials design. This paper investigates the mechanics of deformation and failure mechanisms of suture interface designs through analytical models and experiments on 3D printed polymer physical prototypes. Suture waveforms with generalized trapezoidal geometries (trapezoidal, rectangular, anti-trapezoidal, and triangular) are studied and characterized by several important geometric parameters: the presence or absence of a bonded tip region, the tip angle, and the geometry. It is shown that a wide range (in some cases as great as an order of magnitude) in stiffness, strength, and toughness is achievable dependent on tip bonding, tip angle, and geometry. Suture interfaces with a bonded tip region exhibit a higher initial stiffness due to the greater load bearing by the skeletal teeth, a double peak in the stress-strain curve corresponding to the failure of the bonded tip and the failure of the slanted interface region or tooth, respectively, and an additional failure and toughening mechanism due to the failure of the bonded tip. Anti-trapezoidal geometries promote the greatest amplification of properties for suture interfaces with a bonded tip due the large tip interface area. The tip angle and geometry govern the stress distributions in the teeth and the ratio of normal to shear stresses in the interfacial layers, which together determine the failure mechanism of the interface and/or the teeth. Rectangular suture interfaces fail by simple shearing of the interfaces. Trapezoidal and triangular suture interfaces fail by a combination of shear and tensile normal stresses in the interface, leading to plastic deformation, cavitation events, and subsequent stretching of interface ligaments with mostly elastic deformation in the teeth. Anti-trapezoidal suture interfaces with small tip angles have high stress concentrations in the teeth

  2. Computer Models and Automata Theory in Biology and Medicine

    CERN Document Server

    Baianu, I C

    2004-01-01

    The applications of computers to biological and biomedical problem solving goes back to the very beginnings of computer science, automata theory [1], and mathematical biology [2]. With the advent of more versatile and powerful computers, biological and biomedical applications of computers have proliferated so rapidly that it would be virtually impossible to compile a comprehensive review of all developments in this field. Limitations of computer simulations in biology have also come under close scrutiny, and claims have been made that biological systems have limited information processing power [3]. Such general conjectures do not, however, deter biologists and biomedical researchers from developing new computer applications in biology and medicine. Microprocessors are being widely employed in biological laboratories both for automatic data acquisition/processing and modeling; one particular area, which is of great biomedical interest, involves fast digital image processing and is already established for rout...

  3. Sensitivity analysis approaches applied to systems biology models.

    Science.gov (United States)

    Zi, Z

    2011-11-01

    With the rising application of systems biology, sensitivity analysis methods have been widely applied to study the biological systems, including metabolic networks, signalling pathways and genetic circuits. Sensitivity analysis can provide valuable insights about how robust the biological responses are with respect to the changes of biological parameters and which model inputs are the key factors that affect the model outputs. In addition, sensitivity analysis is valuable for guiding experimental analysis, model reduction and parameter estimation. Local and global sensitivity analysis approaches are the two types of sensitivity analysis that are commonly applied in systems biology. Local sensitivity analysis is a classic method that studies the impact of small perturbations on the model outputs. On the other hand, global sensitivity analysis approaches have been applied to understand how the model outputs are affected by large variations of the model input parameters. In this review, the author introduces the basic concepts of sensitivity analysis approaches applied to systems biology models. Moreover, the author discusses the advantages and disadvantages of different sensitivity analysis methods, how to choose a proper sensitivity analysis approach, the available sensitivity analysis tools for systems biology models and the caveats in the interpretation of sensitivity analysis results.

  4. Cellular potts models multiscale extensions and biological applications

    CERN Document Server

    Scianna, Marco

    2013-01-01

    A flexible, cell-level, and lattice-based technique, the cellular Potts model accurately describes the phenomenological mechanisms involved in many biological processes. Cellular Potts Models: Multiscale Extensions and Biological Applications gives an interdisciplinary, accessible treatment of these models, from the original methodologies to the latest developments. The book first explains the biophysical bases, main merits, and limitations of the cellular Potts model. It then proposes several innovative extensions, focusing on ways to integrate and interface the basic cellular Potts model at the mesoscopic scale with approaches that accurately model microscopic dynamics. These extensions are designed to create a nested and hybrid environment, where the evolution of a biological system is realistically driven by the constant interplay and flux of information between the different levels of description. Through several biological examples, the authors demonstrate a qualitative and quantitative agreement with t...

  5. Learning (from) the errors of a systems biology model.

    Science.gov (United States)

    Engelhardt, Benjamin; Frőhlich, Holger; Kschischo, Maik

    2016-02-11

    Mathematical modelling is a labour intensive process involving several iterations of testing on real data and manual model modifications. In biology, the domain knowledge guiding model development is in many cases itself incomplete and uncertain. A major problem in this context is that biological systems are open. Missed or unknown external influences as well as erroneous interactions in the model could thus lead to severely misleading results. Here we introduce the dynamic elastic-net, a data driven mathematical method which automatically detects such model errors in ordinary differential equation (ODE) models. We demonstrate for real and simulated data, how the dynamic elastic-net approach can be used to automatically (i) reconstruct the error signal, (ii) identify the target variables of model error, and (iii) reconstruct the true system state even for incomplete or preliminary models. Our work provides a systematic computational method facilitating modelling of open biological systems under uncertain knowledge.

  6. Structured, Physically Inspired (Gray Box) Models Versus Black Box Modeling for Forecasting the Output Power of Photovoltaic Plants

    Czech Academy of Sciences Publication Activity Database

    Paulescu, M.; Brabec, Marek; Boata, R.; Badescu, V.

    2017-01-01

    Roč. 121, 15 February (2017), s. 792-802 ISSN 0360-5442 Grant - others:European Cooperation in Science and Technology(XE) COST ES1002 Institutional support: RVO:67985807 Keywords : photovoltaic plant * output power * forecasting * fuzzy model * generalized additive model Subject RIV: BB - Applied Statistics, Operational Research OBOR OECD: Statistics and probability Impact factor: 4.520, year: 2016

  7. Uncertainty in biology a computational modeling approach

    CERN Document Server

    Gomez-Cabrero, David

    2016-01-01

    Computational modeling of biomedical processes is gaining more and more weight in the current research into the etiology of biomedical problems and potential treatment strategies.  Computational modeling allows to reduce, refine and replace animal experimentation as well as to translate findings obtained in these experiments to the human background. However these biomedical problems are inherently complex with a myriad of influencing factors, which strongly complicates the model building and validation process.  This book wants to address four main issues related to the building and validation of computational models of biomedical processes: Modeling establishment under uncertainty Model selection and parameter fitting Sensitivity analysis and model adaptation Model predictions under uncertainty In each of the abovementioned areas, the book discusses a number of key-techniques by means of a general theoretical description followed by one or more practical examples.  This book is intended for graduate stude...

  8. Mathematical manipulative models: in defense of "beanbag biology".

    Science.gov (United States)

    Jungck, John R; Gaff, Holly; Weisstein, Anton E

    2010-01-01

    Mathematical manipulative models have had a long history of influence in biological research and in secondary school education, but they are frequently neglected in undergraduate biology education. By linking mathematical manipulative models in a four-step process-1) use of physical manipulatives, 2) interactive exploration of computer simulations, 3) derivation of mathematical relationships from core principles, and 4) analysis of real data sets-we demonstrate a process that we have shared in biological faculty development workshops led by staff from the BioQUEST Curriculum Consortium over the past 24 yr. We built this approach based upon a broad survey of literature in mathematical educational research that has convincingly demonstrated the utility of multiple models that involve physical, kinesthetic learning to actual data and interactive simulations. Two projects that use this approach are introduced: The Biological Excel Simulations and Tools in Exploratory, Experiential Mathematics (ESTEEM) Project (http://bioquest.org/esteem) and Numerical Undergraduate Mathematical Biology Education (NUMB3R5 COUNT; http://bioquest.org/numberscount). Examples here emphasize genetics, ecology, population biology, photosynthesis, cancer, and epidemiology. Mathematical manipulative models help learners break through prior fears to develop an appreciation for how mathematical reasoning informs problem solving, inference, and precise communication in biology and enhance the diversity of quantitative biology education.

  9. Development of a Value Inquiry Model in Biology Education.

    Science.gov (United States)

    Jeong, Eun-Young; Kim, Young-Soo

    2000-01-01

    Points out the rapid advances in biology, increasing bioethical issues, and how students need to make rational decisions. Introduces a value inquiry model development that includes identifying and clarifying value problems; understanding biological knowledge related to conflict situations; considering, selecting, and evaluating each alternative;…

  10. SEEK: a systems biology data and model management platform.

    NARCIS (Netherlands)

    Wolstencroft, K.J.; Owen, S.; Krebs, O.; Nguyen, Q.; Stanford, N.J.; Golebiewski, M.; Weidemann, A.; Bittkowski, M.; An, L.; Shockley, D.; Snoep, J.L.; Mueller, W.; Goble, C.

    2015-01-01

    Background: Systems biology research typically involves the integration and analysis of heterogeneous data types in order to model and predict biological processes. Researchers therefore require tools and resources to facilitate the sharing and integration of data, and for linking of data to systems

  11. Unified Deep Learning Architecture for Modeling Biology Sequence.

    Science.gov (United States)

    Wu, Hongjie; Cao, Chengyuan; Xia, Xiaoyan; Lu, Qiang

    2017-10-09

    Prediction of the spatial structure or function of biological macromolecules based on their sequence remains an important challenge in bioinformatics. When modeling biological sequences using traditional sequencing models, characteristics, such as long-range interactions between basic units, the complicated and variable output of labeled structures, and the variable length of biological sequences, usually lead to different solutions on a case-by-case basis. This study proposed the use of bidirectional recurrent neural networks based on long short-term memory or a gated recurrent unit to capture long-range interactions by designing the optional reshape operator to adapt to the diversity of the output labels and implementing a training algorithm to support the training of sequence models capable of processing variable-length sequences. Additionally, the merge and pooling operators enhanced the ability to capture short-range interactions between basic units of biological sequences. The proposed deep-learning model and its training algorithm might be capable of solving currently known biological sequence-modeling problems through the use of a unified framework. We validated our model on one of the most difficult biological sequence-modeling problems currently known, with our results indicating the ability of the model to obtain predictions of protein residue interactions that exceeded the accuracy of current popular approaches by 10% based on multiple benchmarks.

  12. Genome Scale Modeling in Systems Biology: Algorithms and Resources

    Science.gov (United States)

    Najafi, Ali; Bidkhori, Gholamreza; Bozorgmehr, Joseph H.; Koch, Ina; Masoudi-Nejad, Ali

    2014-01-01

    In recent years, in silico studies and trial simulations have complemented experimental procedures. A model is a description of a system, and a system is any collection of interrelated objects; an object, moreover, is some elemental unit upon which observations can be made but whose internal structure either does not exist or is ignored. Therefore, any network analysis approach is critical for successful quantitative modeling of biological systems. This review highlights some of most popular and important modeling algorithms, tools, and emerging standards for representing, simulating and analyzing cellular networks in five sections. Also, we try to show these concepts by means of simple example and proper images and graphs. Overall, systems biology aims for a holistic description and understanding of biological processes by an integration of analytical experimental approaches along with synthetic computational models. In fact, biological networks have been developed as a platform for integrating information from high to low-throughput experiments for the analysis of biological systems. We provide an overview of all processes used in modeling and simulating biological networks in such a way that they can become easily understandable for researchers with both biological and mathematical backgrounds. Consequently, given the complexity of generated experimental data and cellular networks, it is no surprise that researchers have turned to computer simulation and the development of more theory-based approaches to augment and assist in the development of a fully quantitative understanding of cellular dynamics. PMID:24822031

  13. Biomineralization-inspired synthesis of chitosan/hydroxyapatite biocomposites based on a novel bilayer rate-controlling model.

    Science.gov (United States)

    Hu, Jing-Xiao; Ran, Jia-Bing; Chen, Si; Shen, Xin-Yu; Tong, Hua

    2015-12-01

    In order to prepare sophisticated biomaterials using a biomimetic approach, a deeper understanding of biomineralization is needed. Of particular importance is the control and regulation of the mineralization process. In this study, a novel bilayer rate-controlling model was designed to investigate the factors potentially influencing mineralization. In the absence of a rate-controlling layer, nano-scale hydroxyapatite (HA) crystallites exhibited a spherical morphology, whereas, in the presence of a rate-controlling layer, HA crystallites were homogeneously dispersed and spindle-like in structure. The mineralization rate had a significant effect on controlling the morphology of crystals. Furthermore, in vitro tests demonstrated that the reaction layer containing spindle-like HA crystallites possessed superior biological properties. These results suggest that a slow mineralization rate is required for controlling the morphology of inorganic crystallites, and consumption by the rate-controlling layer ensured that the ammonia concentration remained low. This study demonstrates that a biomimetic approach can be used to prepare novel biomaterials containing HA crystallites that have different morphologies and biological properties. Copyright © 2015 Elsevier B.V. All rights reserved.

  14. Theoretical Biology and Medical Modelling: ensuring continued growth and future leadership.

    Science.gov (United States)

    Nishiura, Hiroshi; Rietman, Edward A; Wu, Rongling

    2013-07-11

    Theoretical biology encompasses a broad range of biological disciplines ranging from mathematical biology and biomathematics to philosophy of biology. Adopting a broad definition of "biology", Theoretical Biology and Medical Modelling, an open access journal, considers original research studies that focus on theoretical ideas and models associated with developments in biology and medicine.

  15. Development of a kinetic model for biological sulphate reduction ...

    African Journals Online (AJOL)

    A two-phase (aqueous/gas) physical, biological and chemical processes ... Additionally, the background weak acid/base chemistry for water, carbonate, ... in the UCTADM1 model, and hence the physical gas exchange for sulphide is included.

  16. Mathematical models in biology bringing mathematics to life

    CERN Document Server

    Ferraro, Maria; Guarracino, Mario

    2015-01-01

    This book presents an exciting collection of contributions based on the workshop “Bringing Maths to Life” held October 27-29, 2014 in Naples, Italy.  The state-of-the art research in biology and the statistical and analytical challenges facing huge masses of data collection are treated in this Work. Specific topics explored in depth surround the sessions and special invited sessions of the workshop and include genetic variability via differential expression, molecular dynamics and modeling, complex biological systems viewed from quantitative models, and microscopy images processing, to name several. In depth discussions of the mathematical analysis required to extract insights from complex bodies of biological datasets, to aid development in the field novel algorithms, methods and software tools for genetic variability, molecular dynamics, and complex biological systems are presented in this book. Researchers and graduate students in biology, life science, and mathematics/statistics will find the content...

  17. Modeling dynamics of biological and chemical components of aquatic ecosystems

    International Nuclear Information System (INIS)

    Lassiter, R.R.

    1975-05-01

    To provide capability to model aquatic ecosystems or their subsystems as needed for particular research goals, a modeling strategy was developed. Submodels of several processes common to aquatic ecosystems were developed or adapted from previously existing ones. Included are submodels for photosynthesis as a function of light and depth, biological growth rates as a function of temperature, dynamic chemical equilibrium, feeding and growth, and various types of losses to biological populations. These submodels may be used as modules in the construction of models of subsystems or ecosystems. A preliminary model for the nitrogen cycle subsystem was developed using the modeling strategy and applicable submodels. (U.S.)

  18. Systematic integration of experimental data and models in systems biology.

    Science.gov (United States)

    Li, Peter; Dada, Joseph O; Jameson, Daniel; Spasic, Irena; Swainston, Neil; Carroll, Kathleen; Dunn, Warwick; Khan, Farid; Malys, Naglis; Messiha, Hanan L; Simeonidis, Evangelos; Weichart, Dieter; Winder, Catherine; Wishart, Jill; Broomhead, David S; Goble, Carole A; Gaskell, Simon J; Kell, Douglas B; Westerhoff, Hans V; Mendes, Pedro; Paton, Norman W

    2010-11-29

    The behaviour of biological systems can be deduced from their mathematical models. However, multiple sources of data in diverse forms are required in the construction of a model in order to define its components and their biochemical reactions, and corresponding parameters. Automating the assembly and use of systems biology models is dependent upon data integration processes involving the interoperation of data and analytical resources. Taverna workflows have been developed for the automated assembly of quantitative parameterised metabolic networks in the Systems Biology Markup Language (SBML). A SBML model is built in a systematic fashion by the workflows which starts with the construction of a qualitative network using data from a MIRIAM-compliant genome-scale model of yeast metabolism. This is followed by parameterisation of the SBML model with experimental data from two repositories, the SABIO-RK enzyme kinetics database and a database of quantitative experimental results. The models are then calibrated and simulated in workflows that call out to COPASIWS, the web service interface to the COPASI software application for analysing biochemical networks. These systems biology workflows were evaluated for their ability to construct a parameterised model of yeast glycolysis. Distributed information about metabolic reactions that have been described to MIRIAM standards enables the automated assembly of quantitative systems biology models of metabolic networks based on user-defined criteria. Such data integration processes can be implemented as Taverna workflows to provide a rapid overview of the components and their relationships within a biochemical system.

  19. How computational models can help unlock biological systems.

    Science.gov (United States)

    Brodland, G Wayne

    2015-12-01

    With computation models playing an ever increasing role in the advancement of science, it is important that researchers understand what it means to model something; recognize the implications of the conceptual, mathematical and algorithmic steps of model construction; and comprehend what models can and cannot do. Here, we use examples to show that models can serve a wide variety of roles, including hypothesis testing, generating new insights, deepening understanding, suggesting and interpreting experiments, tracing chains of causation, doing sensitivity analyses, integrating knowledge, and inspiring new approaches. We show that models can bring together information of different kinds and do so across a range of length scales, as they do in multi-scale, multi-faceted embryogenesis models, some of which connect gene expression, the cytoskeleton, cell properties, tissue mechanics, morphogenetic movements and phenotypes. Models cannot replace experiments nor can they prove that particular mechanisms are at work in a given situation. But they can demonstrate whether or not a proposed mechanism is sufficient to produce an observed phenomenon. Although the examples in this article are taken primarily from the field of embryo mechanics, most of the arguments and discussion are applicable to any form of computational modelling. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

  20. Some Issues of Biological Shape Modelling with Applications

    DEFF Research Database (Denmark)

    Larsen, Rasmus; Hilger, Klaus Baggesen; Skoglund, Karl

    2003-01-01

    This paper illustrates current research at Informatics and Mathematical Modelling at the Technical University of Denmark within biological shape modelling. We illustrate a series of generalizations to, modifications to, and applications of the elements of constructing models of shape or appearance...

  1. Clay Bells: Edo Inspiration

    Science.gov (United States)

    Wagner, Tom

    2010-01-01

    The ceremonial copper and iron bells at the Smithsonian's National Museum of African Art were the author's inspiration for an interdisciplinary unit with a focus on the contributions various cultures make toward the richness of a community. The author of this article describes an Edo bell-inspired ceramic project incorporating slab-building…

  2. Inspiration from britain?

    DEFF Research Database (Denmark)

    Vagnby, Bo

    2008-01-01

    Danish housing policy needs a dose of renewed social concern - and could find new inspiration in Britain's housing and urban planning policies, says Bo Vagnby. Udgivelsesdato: November......Danish housing policy needs a dose of renewed social concern - and could find new inspiration in Britain's housing and urban planning policies, says Bo Vagnby. Udgivelsesdato: November...

  3. Biocellion: accelerating computer simulation of multicellular biological system models.

    Science.gov (United States)

    Kang, Seunghwa; Kahan, Simon; McDermott, Jason; Flann, Nicholas; Shmulevich, Ilya

    2014-11-01

    Biological system behaviors are often the outcome of complex interactions among a large number of cells and their biotic and abiotic environment. Computational biologists attempt to understand, predict and manipulate biological system behavior through mathematical modeling and computer simulation. Discrete agent-based modeling (in combination with high-resolution grids to model the extracellular environment) is a popular approach for building biological system models. However, the computational complexity of this approach forces computational biologists to resort to coarser resolution approaches to simulate large biological systems. High-performance parallel computers have the potential to address the computing challenge, but writing efficient software for parallel computers is difficult and time-consuming. We have developed Biocellion, a high-performance software framework, to solve this computing challenge using parallel computers. To support a wide range of multicellular biological system models, Biocellion asks users to provide their model specifics by filling the function body of pre-defined model routines. Using Biocellion, modelers without parallel computing expertise can efficiently exploit parallel computers with less effort than writing sequential programs from scratch. We simulate cell sorting, microbial patterning and a bacterial system in soil aggregate as case studies. Biocellion runs on x86 compatible systems with the 64 bit Linux operating system and is freely available for academic use. Visit http://biocellion.com for additional information. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  4. Multiscale modeling of emergent materials: biological and soft matter

    DEFF Research Database (Denmark)

    Murtola, Teemu; Bunker, Alex; Vattulainen, Ilpo

    2009-01-01

    In this review, we focus on four current related issues in multiscale modeling of soft and biological matter. First, we discuss how to use structural information from detailed models (or experiments) to construct coarse-grained ones in a hierarchical and systematic way. This is discussed in the c......In this review, we focus on four current related issues in multiscale modeling of soft and biological matter. First, we discuss how to use structural information from detailed models (or experiments) to construct coarse-grained ones in a hierarchical and systematic way. This is discussed...

  5. Statistical Model Checking for Biological Systems

    DEFF Research Database (Denmark)

    David, Alexandre; Larsen, Kim Guldstrand; Legay, Axel

    2014-01-01

    Statistical Model Checking (SMC) is a highly scalable simulation-based verification approach for testing and estimating the probability that a stochastic system satisfies a given linear temporal property. The technique has been applied to (discrete and continuous time) Markov chains, stochastic...

  6. Nematodes: Model Organisms in High School Biology

    Science.gov (United States)

    Bliss, TJ; Anderson, Margery; Dillman, Adler; Yourick, Debra; Jett, Marti; Adams, Byron J.; Russell, RevaBeth

    2007-01-01

    In a collaborative effort between university researchers and high school science teachers, an inquiry-based laboratory module was designed using two species of insecticidal nematodes to help students apply scientific inquiry and elements of thoughtful experimental design. The learning experience and model are described in this article. (Contains 4…

  7. Structure, function, and behaviour of computational models in systems biology.

    Science.gov (United States)

    Knüpfer, Christian; Beckstein, Clemens; Dittrich, Peter; Le Novère, Nicolas

    2013-05-31

    Systems Biology develops computational models in order to understand biological phenomena. The increasing number and complexity of such "bio-models" necessitate computer support for the overall modelling task. Computer-aided modelling has to be based on a formal semantic description of bio-models. But, even if computational bio-models themselves are represented precisely in terms of mathematical expressions their full meaning is not yet formally specified and only described in natural language. We present a conceptual framework - the meaning facets - which can be used to rigorously specify the semantics of bio-models. A bio-model has a dual interpretation: On the one hand it is a mathematical expression which can be used in computational simulations (intrinsic meaning). On the other hand the model is related to the biological reality (extrinsic meaning). We show that in both cases this interpretation should be performed from three perspectives: the meaning of the model's components (structure), the meaning of the model's intended use (function), and the meaning of the model's dynamics (behaviour). In order to demonstrate the strengths of the meaning facets framework we apply it to two semantically related models of the cell cycle. Thereby, we make use of existing approaches for computer representation of bio-models as much as possible and sketch the missing pieces. The meaning facets framework provides a systematic in-depth approach to the semantics of bio-models. It can serve two important purposes: First, it specifies and structures the information which biologists have to take into account if they build, use and exchange models. Secondly, because it can be formalised, the framework is a solid foundation for any sort of computer support in bio-modelling. The proposed conceptual framework establishes a new methodology for modelling in Systems Biology and constitutes a basis for computer-aided collaborative research.

  8. Neuroscience-Inspired Artificial Intelligence.

    Science.gov (United States)

    Hassabis, Demis; Kumaran, Dharshan; Summerfield, Christopher; Botvinick, Matthew

    2017-07-19

    The fields of neuroscience and artificial intelligence (AI) have a long and intertwined history. In more recent times, however, communication and collaboration between the two fields has become less commonplace. In this article, we argue that better understanding biological brains could play a vital role in building intelligent machines. We survey historical interactions between the AI and neuroscience fields and emphasize current advances in AI that have been inspired by the study of neural computation in humans and other animals. We conclude by highlighting shared themes that may be key for advancing future research in both fields. Copyright © 2017. Published by Elsevier Inc.

  9. Polynomial algebra of discrete models in systems biology.

    Science.gov (United States)

    Veliz-Cuba, Alan; Jarrah, Abdul Salam; Laubenbacher, Reinhard

    2010-07-01

    An increasing number of discrete mathematical models are being published in Systems Biology, ranging from Boolean network models to logical models and Petri nets. They are used to model a variety of biochemical networks, such as metabolic networks, gene regulatory networks and signal transduction networks. There is increasing evidence that such models can capture key dynamic features of biological networks and can be used successfully for hypothesis generation. This article provides a unified framework that can aid the mathematical analysis of Boolean network models, logical models and Petri nets. They can be represented as polynomial dynamical systems, which allows the use of a variety of mathematical tools from computer algebra for their analysis. Algorithms are presented for the translation into polynomial dynamical systems. Examples are given of how polynomial algebra can be used for the model analysis. alanavc@vt.edu Supplementary data are available at Bioinformatics online.

  10. SEEK: a systems biology data and model management platform.

    Science.gov (United States)

    Wolstencroft, Katherine; Owen, Stuart; Krebs, Olga; Nguyen, Quyen; Stanford, Natalie J; Golebiewski, Martin; Weidemann, Andreas; Bittkowski, Meik; An, Lihua; Shockley, David; Snoep, Jacky L; Mueller, Wolfgang; Goble, Carole

    2015-07-11

    Systems biology research typically involves the integration and analysis of heterogeneous data types in order to model and predict biological processes. Researchers therefore require tools and resources to facilitate the sharing and integration of data, and for linking of data to systems biology models. There are a large number of public repositories for storing biological data of a particular type, for example transcriptomics or proteomics, and there are several model repositories. However, this silo-type storage of data and models is not conducive to systems biology investigations. Interdependencies between multiple omics datasets and between datasets and models are essential. Researchers require an environment that will allow the management and sharing of heterogeneous data and models in the context of the experiments which created them. The SEEK is a suite of tools to support the management, sharing and exploration of data and models in systems biology. The SEEK platform provides an access-controlled, web-based environment for scientists to share and exchange data and models for day-to-day collaboration and for public dissemination. A plug-in architecture allows the linking of experiments, their protocols, data, models and results in a configurable system that is available 'off the shelf'. Tools to run model simulations, plot experimental data and assist with data annotation and standardisation combine to produce a collection of resources that support analysis as well as sharing. Underlying semantic web resources additionally extract and serve SEEK metadata in RDF (Resource Description Format). SEEK RDF enables rich semantic queries, both within SEEK and between related resources in the web of Linked Open Data. The SEEK platform has been adopted by many systems biology consortia across Europe. It is a data management environment that has a low barrier of uptake and provides rich resources for collaboration. This paper provides an update on the functions and

  11. Biological-Mathematical Modeling of Chronic Toxicity.

    Science.gov (United States)

    1981-07-22

    34Mathematical Model of Uptake and Distribution," Uptake and Distribution of Anesthetic Agents, E. M. Papper and R. J. Kitz (Editors, McGraw-Hill Book Co., Inc...distribution, In: Papper , E.M. and Kltz, R.J.(eds.) Uptake and distribution of anesthetic agents, McGraw- Hill, New York, p. 72 3. Plpleson, W.W...1963) Quantitative prediction of anesthetic concentrations. In: Papper , E.M. and Kitz, R.J. (eds.) Uptake and distribution of anesthetic agents, McGraw

  12. Wireless synapses in bio-inspired neural networks

    Science.gov (United States)

    Jannson, Tomasz; Forrester, Thomas; Degrood, Kevin

    2009-05-01

    Wireless (virtual) synapses represent a novel approach to bio-inspired neural networks that follow the infrastructure of the biological brain, except that biological (physical) synapses are replaced by virtual ones based on cellular telephony modeling. Such synapses are of two types: intracluster synapses are based on IR wireless ones, while intercluster synapses are based on RF wireless ones. Such synapses have three unique features, atypical of conventional artificial ones: very high parallelism (close to that of the human brain), very high reconfigurability (easy to kill and to create), and very high plasticity (easy to modify or upgrade). In this paper we analyze the general concept of wireless synapses with special emphasis on RF wireless synapses. Also, biological mammalian (vertebrate) neural models are discussed for comparison, and a novel neural lensing effect is discussed in detail.

  13. Modeling life the mathematics of biological systems

    CERN Document Server

    Garfinkel, Alan; Guo, Yina

    2017-01-01

    From predator-prey populations in an ecosystem, to hormone regulation within the body, the natural world abounds in dynamical systems that affect us profoundly. This book develops the mathematical tools essential for students in the life sciences to describe these interacting systems and to understand and predict their behavior. Complex feedback relations and counter-intuitive responses are common in dynamical systems in nature; this book develops the quantitative skills needed to explore these interactions. Differential equations are the natural mathematical tool for quantifying change, and are the driving force throughout this book. The use of Euler’s method makes nonlinear examples tractable and accessible to a broad spectrum of early-stage undergraduates, thus providing a practical alternative to the procedural approach of a traditional Calculus curriculum. Tools are developed within numerous, relevant examples, with an emphasis on the construction, evaluation, and interpretation of mathematical models ...

  14. Profiling the biological activity of oxide nanomaterials with mechanistic models

    NARCIS (Netherlands)

    Burello, E.

    2013-01-01

    In this study we present three mechanistic models for profiling the potential biological and toxicological effects of oxide nanomaterials. The models attempt to describe the reactivity, protein adsorption and membrane adhesion processes of a large range of oxide materials and are based on properties

  15. Building executable biological pathway models automatically from BioPAX

    NARCIS (Netherlands)

    Willemsen, Timo; Feenstra, Anton; Groth, Paul

    2013-01-01

    The amount of biological data exposed in semantic formats is steadily increasing. In particular, pathway information (a model of how molecules interact within a cell) from databases such as KEGG and WikiPathways are available in a standard RDF-based format BioPAX. However, these models are

  16. Multi-level and hybrid modelling approaches for systems biology.

    Science.gov (United States)

    Bardini, R; Politano, G; Benso, A; Di Carlo, S

    2017-01-01

    During the last decades, high-throughput techniques allowed for the extraction of a huge amount of data from biological systems, unveiling more of their underling complexity. Biological systems encompass a wide range of space and time scales, functioning according to flexible hierarchies of mechanisms making an intertwined and dynamic interplay of regulations. This becomes particularly evident in processes such as ontogenesis, where regulative assets change according to process context and timing, making structural phenotype and architectural complexities emerge from a single cell, through local interactions. The information collected from biological systems are naturally organized according to the functional levels composing the system itself. In systems biology, biological information often comes from overlapping but different scientific domains, each one having its own way of representing phenomena under study. That is, the different parts of the system to be modelled may be described with different formalisms. For a model to have improved accuracy and capability for making a good knowledge base, it is good to comprise different system levels, suitably handling the relative formalisms. Models which are both multi-level and hybrid satisfy both these requirements, making a very useful tool in computational systems biology. This paper reviews some of the main contributions in this field.

  17. Predictive modelling of complex agronomic and biological systems.

    Science.gov (United States)

    Keurentjes, Joost J B; Molenaar, Jaap; Zwaan, Bas J

    2013-09-01

    Biological systems are tremendously complex in their functioning and regulation. Studying the multifaceted behaviour and describing the performance of such complexity has challenged the scientific community for years. The reduction of real-world intricacy into simple descriptive models has therefore convinced many researchers of the usefulness of introducing mathematics into biological sciences. Predictive modelling takes such an approach another step further in that it takes advantage of existing knowledge to project the performance of a system in alternating scenarios. The ever growing amounts of available data generated by assessing biological systems at increasingly higher detail provide unique opportunities for future modelling and experiment design. Here we aim to provide an overview of the progress made in modelling over time and the currently prevalent approaches for iterative modelling cycles in modern biology. We will further argue for the importance of versatility in modelling approaches, including parameter estimation, model reduction and network reconstruction. Finally, we will discuss the difficulties in overcoming the mathematical interpretation of in vivo complexity and address some of the future challenges lying ahead. © 2013 John Wiley & Sons Ltd.

  18. Physicists get INSPIREd

    CERN Multimedia

    CERN Bulletin

    2010-01-01

    Particle physicists thrive on information. They first create information by performing experiments or elaborating theoretical conjectures and then they share it through publications and various web tools. The INSPIRE service, just released, will bring state of the art information retrieval to the fingertips of researchers.   Keeping track of the information shared within the particle physics community has long been the task of libraries at the larger labs, such as CERN, DESY, Fermilab and SLAC, as well as the focus of indispensible services like arXiv and those of the Particle Data Group. In 2007, many providers of information in the field came together for a summit at SLAC to see how physics information resources could be enhanced, and the INSPIRE project emerged from that meeting. The vision behind INSPIRE was built by a survey launched by the four labs to evaluate the real needs of the community. INSPIRE responds to these directives from the community by combining the most successful aspe...

  19. A distributed approach for parameters estimation in System Biology models

    International Nuclear Information System (INIS)

    Mosca, E.; Merelli, I.; Alfieri, R.; Milanesi, L.

    2009-01-01

    Due to the lack of experimental measurements, biological variability and experimental errors, the value of many parameters of the systems biology mathematical models is yet unknown or uncertain. A possible computational solution is the parameter estimation, that is the identification of the parameter values that determine the best model fitting respect to experimental data. We have developed an environment to distribute each run of the parameter estimation algorithm on a different computational resource. The key feature of the implementation is a relational database that allows the user to swap the candidate solutions among the working nodes during the computations. The comparison of the distributed implementation with the parallel one showed that the presented approach enables a faster and better parameter estimation of systems biology models.

  20. Genetic coding and united-hypercomplex systems in the models of algebraic biology.

    Science.gov (United States)

    Petoukhov, Sergey V

    2017-08-01

    Structured alphabets of DNA and RNA in their matrix form of representations are connected with Walsh functions and a new type of systems of multidimensional numbers. This type generalizes systems of complex numbers and hypercomplex numbers, which serve as the basis of mathematical natural sciences and many technologies. The new systems of multi-dimensional numbers have interesting mathematical properties and are called in a general case as "systems of united-hypercomplex numbers" (or briefly "U-hypercomplex numbers"). They can be widely used in models of multi-parametrical systems in the field of algebraic biology, artificial life, devices of biological inspired artificial intelligence, etc. In particular, an application of U-hypercomplex numbers reveals hidden properties of genetic alphabets under cyclic permutations in their doublets and triplets. A special attention is devoted to the author's hypothesis about a multi-linguistic in DNA-sequences in a relation with an ensemble of U-numerical sub-alphabets. Genetic multi-linguistic is considered as an important factor to provide noise-immunity properties of the multi-channel genetic coding. Our results attest to the conformity of the algebraic properties of the U-numerical systems with phenomenological properties of the DNA-alphabets and with the complementary device of the double DNA-helix. It seems that in the modeling field of algebraic biology the genetic-informational organization of living bodies can be considered as a set of united-hypercomplex numbers in some association with the famous slogan of Pythagoras "the numbers rule the world". Copyright © 2017 Elsevier B.V. All rights reserved.

  1. Synthetic biology between challenges and risks: suggestions for a model of governance and a regulatory framework, based on fundamental rights.

    Science.gov (United States)

    Colussi, Ilaria Anna

    2013-01-01

    This paper deals with the emerging synthetic biology, its challenges and risks, and tries to design a model for the governance and regulation of the field. The model is called of "prudent vigilance" (inspired by the report about synthetic biology, drafted by the U.S. Presidential Commission on Bioethics, 2010), and it entails (a) an ongoing and periodically revised process of assessment and management of all the risks and concerns, and (b) the adoption of policies - taken through "hard law" and "soft law" sources - that are based on the principle of proportionality (among benefits and risks), on a reasonable balancing between different interests and rights at stake, and are oriented by a constitutional frame, which is represented by the protection of fundamental human rights emerging in the field of synthetic biology (right to life, right to health, dignity, freedom of scientific research, right to environment). After the theoretical explanation of the model, its operability is "checked", by considering its application with reference to only one specific risk brought up by synthetic biology - biosecurity risk, i.e. the risk of bioterrorism.

  2. Preservice Biology Teachers' Conceptions About the Tentative Nature of Theories and Models in Biology

    Science.gov (United States)

    Reinisch, Bianca; Krüger, Dirk

    2018-02-01

    In research on the nature of science, there is a need to investigate the role and status of different scientific knowledge forms. Theories and models are two of the most important knowledge forms within biology and are the focus of this study. During interviews, preservice biology teachers ( N = 10) were asked about their understanding of theories and models. They were requested to give reasons why they see theories and models as either tentative or certain constructs. Their conceptions were then compared to philosophers' positions (e.g., Popper, Giere). A category system was developed from the qualitative content analysis of the interviews. These categories include 16 conceptions for theories ( n tentative = 11; n certai n = 5) and 18 conceptions for models ( n tentative = 10; n certain = 8). The analysis of the interviews showed that the preservice teachers gave reasons for the tentativeness or certainty of theories and models either due to their understanding of the terms or due to their understanding of the generation or evaluation of theories and models. Therefore, a variety of different terminology, from different sources, should be used in learning-teaching situations. Additionally, an understanding of which processes lead to the generation, evaluation, and refinement or rejection of theories and models should be discussed with preservice teachers. Within philosophy of science, there has been a shift from theories to models. This should be transferred to educational contexts by firstly highlighting the role of models and also their connections to theories.

  3. Buckling Pneumatic Linear Actuators Inspired by Muscle

    OpenAIRE

    Yang, Dian; Verma, Mohit Singh; So, Ju-Hee; Mosadegh, Bobak; Keplinger, Christoph; Lee, Benjamin; Khashai, Fatemeh; Lossner, Elton Garret; Suo, Zhigang; Whitesides, George McClelland

    2016-01-01

    The mechanical features of biological muscles are difficult to reproduce completely in synthetic systems. A new class of soft pneumatic structures (vacuum-actuated muscle-inspired pneumatic structures) is described that combines actuation by negative pressure (vacuum), with cooperative buckling of beams fabricated in a slab of elastomer, to achieve motion and demonstrate many features that are similar to that of mammalian muscle.

  4. Yeast as a Model System to Study Tau Biology

    Directory of Open Access Journals (Sweden)

    Ann De Vos

    2011-01-01

    Full Text Available Hyperphosphorylated and aggregated human protein tau constitutes a hallmark of a multitude of neurodegenerative diseases called tauopathies, exemplified by Alzheimer's disease. In spite of an enormous amount of research performed on tau biology, several crucial questions concerning the mechanisms of tau toxicity remain unanswered. In this paper we will highlight some of the processes involved in tau biology and pathology, focusing on tau phosphorylation and the interplay with oxidative stress. In addition, we will introduce the development of a human tau-expressing yeast model, and discuss some crucial results obtained in this model, highlighting its potential in the elucidation of cellular processes leading to tau toxicity.

  5. BayesMD: flexible biological modeling for motif discovery

    DEFF Research Database (Denmark)

    Tang, Man-Hung Eric; Krogh, Anders; Winther, Ole

    2008-01-01

    We present BayesMD, a Bayesian Motif Discovery model with several new features. Three different types of biological a priori knowledge are built into the framework in a modular fashion. A mixture of Dirichlets is used as prior over nucleotide probabilities in binding sites. It is trained on trans......We present BayesMD, a Bayesian Motif Discovery model with several new features. Three different types of biological a priori knowledge are built into the framework in a modular fashion. A mixture of Dirichlets is used as prior over nucleotide probabilities in binding sites. It is trained...

  6. Biology and therapy of inherited retinal degenerative disease: insights from mouse models

    Science.gov (United States)

    Veleri, Shobi; Lazar, Csilla H.; Chang, Bo; Sieving, Paul A.; Banin, Eyal; Swaroop, Anand

    2015-01-01

    Retinal neurodegeneration associated with the dysfunction or death of photoreceptors is a major cause of incurable vision loss. Tremendous progress has been made over the last two decades in discovering genes and genetic defects that lead to retinal diseases. The primary focus has now shifted to uncovering disease mechanisms and designing treatment strategies, especially inspired by the successful application of gene therapy in some forms of congenital blindness in humans. Both spontaneous and laboratory-generated mouse mutants have been valuable for providing fundamental insights into normal retinal development and for deciphering disease pathology. Here, we provide a review of mouse models of human retinal degeneration, with a primary focus on diseases affecting photoreceptor function. We also describe models associated with retinal pigment epithelium dysfunction or synaptic abnormalities. Furthermore, we highlight the crucial role of mouse models in elucidating retinal and photoreceptor biology in health and disease, and in the assessment of novel therapeutic modalities, including gene- and stem-cell-based therapies, for retinal degenerative diseases. PMID:25650393

  7. Biology and therapy of inherited retinal degenerative disease: insights from mouse models

    Directory of Open Access Journals (Sweden)

    Shobi Veleri

    2015-02-01

    Full Text Available Retinal neurodegeneration associated with the dysfunction or death of photoreceptors is a major cause of incurable vision loss. Tremendous progress has been made over the last two decades in discovering genes and genetic defects that lead to retinal diseases. The primary focus has now shifted to uncovering disease mechanisms and designing treatment strategies, especially inspired by the successful application of gene therapy in some forms of congenital blindness in humans. Both spontaneous and laboratory-generated mouse mutants have been valuable for providing fundamental insights into normal retinal development and for deciphering disease pathology. Here, we provide a review of mouse models of human retinal degeneration, with a primary focus on diseases affecting photoreceptor function. We also describe models associated with retinal pigment epithelium dysfunction or synaptic abnormalities. Furthermore, we highlight the crucial role of mouse models in elucidating retinal and photoreceptor biology in health and disease, and in the assessment of novel therapeutic modalities, including gene- and stem-cell-based therapies, for retinal degenerative diseases.

  8. Biology learning evaluation model in Senior High Schools

    Directory of Open Access Journals (Sweden)

    Sri Utari

    2017-06-01

    Full Text Available The study was to develop a Biology learning evaluation model in senior high schools that referred to the research and development model by Borg & Gall and the logic model. The evaluation model included the components of input, activities, output and outcomes. The developing procedures involved a preliminary study in the form of observation and theoretical review regarding the Biology learning evaluation in senior high schools. The product development was carried out by designing an evaluation model, designing an instrument, performing instrument experiment and performing implementation. The instrument experiment involved teachers and Students from Grade XII in senior high schools located in the City of Yogyakarta. For the data gathering technique and instrument, the researchers implemented observation sheet, questionnaire and test. The questionnaire was applied in order to attain information regarding teacher performance, learning performance, classroom atmosphere and scientific attitude; on the other hand, test was applied in order to attain information regarding Biology concept mastery. Then, for the analysis of instrument construct, the researchers performed confirmatory factor analysis by means of Lisrel 0.80 software and the results of this analysis showed that the evaluation instrument valid and reliable. The construct validity was between 0.43-0.79 while the reliability of measurement model was between 0.88-0.94. Last but not the least, the model feasibility test showed that the theoretical model had been supported by the empirical data.

  9. Modeling of biological intelligence for SCM system optimization.

    Science.gov (United States)

    Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang

    2012-01-01

    This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms.

  10. Modeling of Biological Intelligence for SCM System Optimization

    Directory of Open Access Journals (Sweden)

    Shengyong Chen

    2012-01-01

    Full Text Available This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms.

  11. Modeling of Biological Intelligence for SCM System Optimization

    Science.gov (United States)

    Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang

    2012-01-01

    This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms. PMID:22162724

  12. Boolean Models of Biological Processes Explain Cascade-Like Behavior.

    Science.gov (United States)

    Chen, Hao; Wang, Guanyu; Simha, Rahul; Du, Chenghang; Zeng, Chen

    2016-01-29

    Biological networks play a key role in determining biological function and therefore, an understanding of their structure and dynamics is of central interest in systems biology. In Boolean models of such networks, the status of each molecule is either "on" or "off" and along with the molecules interact with each other, their individual status changes from "on" to "off" or vice-versa and the system of molecules in the network collectively go through a sequence of changes in state. This sequence of changes is termed a biological process. In this paper, we examine the common perception that events in biomolecular networks occur sequentially, in a cascade-like manner, and ask whether this is likely to be an inherent property. In further investigations of the budding and fission yeast cell-cycle, we identify two generic dynamical rules. A Boolean system that complies with these rules will automatically have a certain robustness. By considering the biological requirements in robustness and designability, we show that those Boolean dynamical systems, compared to an arbitrary dynamical system, statistically present the characteristics of cascadeness and sequentiality, as observed in the budding and fission yeast cell- cycle. These results suggest that cascade-like behavior might be an intrinsic property of biological processes.

  13. Generative models versus underlying symmetries to explain biological pattern.

    Science.gov (United States)

    Frank, S A

    2014-06-01

    Mathematical models play an increasingly important role in the interpretation of biological experiments. Studies often present a model that generates the observations, connecting hypothesized process to an observed pattern. Such generative models confirm the plausibility of an explanation and make testable hypotheses for further experiments. However, studies rarely consider the broad family of alternative models that match the same observed pattern. The symmetries that define the broad class of matching models are in fact the only aspects of information truly revealed by observed pattern. Commonly observed patterns derive from simple underlying symmetries. This article illustrates the problem by showing the symmetry associated with the observed rate of increase in fitness in a constant environment. That underlying symmetry reveals how each particular generative model defines a single example within the broad class of matching models. Further progress on the relation between pattern and process requires deeper consideration of the underlying symmetries. © 2014 The Author. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

  14. A framework to establish credibility of computational models in biology.

    Science.gov (United States)

    Patterson, Eann A; Whelan, Maurice P

    2017-10-01

    Computational models in biology and biomedical science are often constructed to aid people's understanding of phenomena or to inform decisions with socioeconomic consequences. Model credibility is the willingness of people to trust a model's predictions and is often difficult to establish for computational biology models. A 3 × 3 matrix has been proposed to allow such models to be categorised with respect to their testability and epistemic foundation in order to guide the selection of an appropriate process of validation to supply evidence to establish credibility. Three approaches to validation are identified that can be deployed depending on whether a model is deemed untestable, testable or lies somewhere in between. In the latter two cases, the validation process involves the quantification of uncertainty which is a key output. The issues arising due to the complexity and inherent variability of biological systems are discussed and the creation of 'digital twins' proposed as a means to alleviate the issues and provide a more robust, transparent and traceable route to model credibility and acceptance. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  15. A methodology to annotate systems biology markup language models with the synthetic biology open language.

    Science.gov (United States)

    Roehner, Nicholas; Myers, Chris J

    2014-02-21

    Recently, we have begun to witness the potential of synthetic biology, noted here in the form of bacteria and yeast that have been genetically engineered to produce biofuels, manufacture drug precursors, and even invade tumor cells. The success of these projects, however, has often failed in translation and application to new projects, a problem exacerbated by a lack of engineering standards that combine descriptions of the structure and function of DNA. To address this need, this paper describes a methodology to connect the systems biology markup language (SBML) to the synthetic biology open language (SBOL), existing standards that describe biochemical models and DNA components, respectively. Our methodology involves first annotating SBML model elements such as species and reactions with SBOL DNA components. A graph is then constructed from the model, with vertices corresponding to elements within the model and edges corresponding to the cause-and-effect relationships between these elements. Lastly, the graph is traversed to assemble the annotating DNA components into a composite DNA component, which is used to annotate the model itself and can be referenced by other composite models and DNA components. In this way, our methodology can be used to build up a hierarchical library of models annotated with DNA components. Such a library is a useful input to any future genetic technology mapping algorithm that would automate the process of composing DNA components to satisfy a behavioral specification. Our methodology for SBML-to-SBOL annotation is implemented in the latest version of our genetic design automation (GDA) software tool, iBioSim.

  16. Natural crayfish clone as emerging model for various biological ...

    Indian Academy of Sciences (India)

    Home; Journals; Journal of Biosciences; Volume 36; Issue 2. Marmorkrebs: Natural crayfish clone as emerging model for various biological disciplines. Günter Vogt. Mini-review Volume 36 Issue 2 June 2011 pp 377-382. Fulltext. Click here to view fulltext PDF. Permanent link:

  17. Learning through Creating Robotic Models of Biological Systems

    Science.gov (United States)

    Cuperman, Dan; Verner, Igor M.

    2013-01-01

    This paper considers an approach to studying issues in technology and science, which integrates design and inquiry activities towards creating and exploring technological models of scientific phenomena. We implemented this approach in a context where the learner inquires into a biological phenomenon and develops its representation in the form of a…

  18. Model calculations of nuclear data for biologically-important elements

    International Nuclear Information System (INIS)

    Chadwick, M.B.; Blann, M.; Reffo, G.; Young, P.G.

    1994-05-01

    We describe calculations of neutron-induced reactions on carbon and oxygen for incident energies up to 70 MeV, the relevant clinical energy in radiation neutron therapy. Our calculations using the FKK-GNASH, GNASH, and ALICE codes are compared with experimental measurements, and their usefulness for modeling reactions on biologically-important elements is assessed

  19. A Calculus for Modelling, Simulating and Analysing Compartmentalized Biological Systems

    DEFF Research Database (Denmark)

    Mardare, Radu Iulian; Ihekwaba, Adoha

    2007-01-01

    A. Ihekwaba, R. Mardare. A Calculus for Modelling, Simulating and Analysing Compartmentalized Biological Systems. Case study: NFkB system. In Proc. of International Conference of Computational Methods in Sciences and Engineering (ICCMSE), American Institute of Physics, AIP Proceedings, N 2...

  20. Part 6: Modelling of simultaneous chemical-biological P removal ...

    African Journals Online (AJOL)

    drinie

    approaches taken in modelling the chemical P removal processes. In the literature .... to 2 mgP/l) for an iron dose of ~1 to 10 mg/l as Fe - refer to dashed line in Fig. 1). ...... systems exhibiting biological enhanced phosphate removal. Part 3:.

  1. Universally sloppy parameter sensitivities in systems biology models.

    Directory of Open Access Journals (Sweden)

    Ryan N Gutenkunst

    2007-10-01

    Full Text Available Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a "sloppy" spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.

  2. Universally sloppy parameter sensitivities in systems biology models.

    Science.gov (United States)

    Gutenkunst, Ryan N; Waterfall, Joshua J; Casey, Fergal P; Brown, Kevin S; Myers, Christopher R; Sethna, James P

    2007-10-01

    Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a "sloppy" spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.

  3. Guidelines for Reproducibly Building and Simulating Systems Biology Models.

    Science.gov (United States)

    Medley, J Kyle; Goldberg, Arthur P; Karr, Jonathan R

    2016-10-01

    Reproducibility is the cornerstone of the scientific method. However, currently, many systems biology models cannot easily be reproduced. This paper presents methods that address this problem. We analyzed the recent Mycoplasma genitalium whole-cell (WC) model to determine the requirements for reproducible modeling. We determined that reproducible modeling requires both repeatable model building and repeatable simulation. New standards and simulation software tools are needed to enhance and verify the reproducibility of modeling. New standards are needed to explicitly document every data source and assumption, and new deterministic parallel simulation tools are needed to quickly simulate large, complex models. We anticipate that these new standards and software will enable researchers to reproducibly build and simulate more complex models, including WC models.

  4. Inspiration, anyone? (Editorial

    Directory of Open Access Journals (Sweden)

    Lindsay Glynn

    2006-09-01

    Full Text Available I have to admit that writing an editorial for this issue was a struggle. Trying to sit down and write when the sun was shining outside and most of my colleagues were on vacation was, to say the least, difficult. Add to that research projects and conferences…let’s just say that I found myself less than inspired. A pitiful plea for ideas to a colleague resulted in the reintroduction to a few recent evidence based papers and resources which inspired further searching and reading. Though I generally find myself surrounded (more like buried in research papers and EBLIP literature, somehow I had missed the great strides that have been made of late in the world of evidence based library and information practice. I realize now that I am inspired by the researchers, authors and innovators who are putting EBLIP on the proverbial map. My biggest beef with library literature in general has been the plethora of articles highlighting what we should be doing. Take a close look at the evidence based practitioners in the information professions: these are some of the people who are actively practicing what has been preached for the past few years. Take, for example, the about‐to‐be released Libraries using Evidence Toolkit by Northern Sydney Central Coast Health and The University of Newcastle, Australia (see their announcement in this issue. An impressive advisory group is responsible for maintaining the currency and relevancy of the site as well as promoting the site and acting as a steering committee for related projects. This group is certainly doing more than “talking the talk”: they took their experience at the 3rd International Evidence Based Librarianship Conference and did something with the information they obtained by implementing solutions that worked in their environment. The result? The creation of a collection of tools for all of us to use. This toolkit is just what EBLIP needs: a portal to resources aimed at supporting the information

  5. Computer modeling in developmental biology: growing today, essential tomorrow.

    Science.gov (United States)

    Sharpe, James

    2017-12-01

    D'Arcy Thompson was a true pioneer, applying mathematical concepts and analyses to the question of morphogenesis over 100 years ago. The centenary of his famous book, On Growth and Form , is therefore a great occasion on which to review the types of computer modeling now being pursued to understand the development of organs and organisms. Here, I present some of the latest modeling projects in the field, covering a wide range of developmental biology concepts, from molecular patterning to tissue morphogenesis. Rather than classifying them according to scientific question, or scale of problem, I focus instead on the different ways that modeling contributes to the scientific process and discuss the likely future of modeling in developmental biology. © 2017. Published by The Company of Biologists Ltd.

  6. Evaluation of radiobiological effects in 3 distinct biological models

    International Nuclear Information System (INIS)

    Lemos, J.; Costa, P.; Cunha, L.; Metello, L.F.; Carvalho, A.P.; Vasconcelos, V.; Genesio, P.; Ponte, F.; Costa, P.S.; Crespo, P.

    2015-01-01

    Full text of publication follows. The present work aims at sharing the process of development of advanced biological models to study radiobiological effects. Recognizing several known limitations and difficulties of the current monolayer cellular models, as well as the increasing difficulties to use advanced biological models, our group has been developing advanced biological alternative models, namely three-dimensional cell cultures and a less explored animal model (the Zebra fish - Danio rerio - which allows the access to inter-generational data, while characterized by a great genetic homology towards the humans). These 3 models (monolayer cellular model, three-dimensional cell cultures and zebra fish) were externally irradiated with 100 mGy, 500 mGy or 1 Gy. The consequences of that irradiation were studied using cellular and molecular tests. Our previous experimental studies with 100 mGy external gamma irradiation of HepG2 monolayer cells showed a slight increase in the proliferation rate 24 h, 48 h and 72 h post irradiation. These results also pointed into the presence of certain bystander effects 72 h post irradiation, constituting the starting point for the need of a more accurate analysis realized with this work. At this stage, we continue focused on the acute biological effects. Obtained results, namely MTT and clonogenic assays for evaluating cellular metabolic activity and proliferation in the in vitro models, as well as proteomics for the evaluation of in vivo effects will be presented, discussed and explained. Several hypotheses will be presented and defended based on the facts previously demonstrated. This work aims at sharing the actual state and the results already available from this medium-term project, building the proof of the added value on applying these advanced models, while demonstrating the strongest and weakest points from all of them (so allowing the comparison between them and to base the subsequent choice for research groups starting

  7. Modeling drug- and chemical- induced hepatotoxicity with systems biology approaches

    Directory of Open Access Journals (Sweden)

    Sudin eBhattacharya

    2012-12-01

    Full Text Available We provide an overview of computational systems biology approaches as applied to the study of chemical- and drug-induced toxicity. The concept of ‘toxicity pathways’ is described in the context of the 2007 US National Academies of Science report, Toxicity testing in the 21st Century: A Vision and A Strategy. Pathway mapping and modeling based on network biology concepts are a key component of the vision laid out in this report for a more biologically-based analysis of dose-response behavior and the safety of chemicals and drugs. We focus on toxicity of the liver (hepatotoxicity – a complex phenotypic response with contributions from a number of different cell types and biological processes. We describe three case studies of complementary multi-scale computational modeling approaches to understand perturbation of toxicity pathways in the human liver as a result of exposure to environmental contaminants and specific drugs. One approach involves development of a spatial, multicellular virtual tissue model of the liver lobule that combines molecular circuits in individual hepatocytes with cell-cell interactions and blood-mediated transport of toxicants through hepatic sinusoids, to enable quantitative, mechanistic prediction of hepatic dose-response for activation of the AhR toxicity pathway. Simultaneously, methods are being developing to extract quantitative maps of intracellular signaling and transcriptional regulatory networks perturbed by environmental contaminants, using a combination of gene expression and genome-wide protein-DNA interaction data. A predictive physiological model (DILIsymTM to understand drug-induced liver injury (DILI, the most common adverse event leading to termination of clinical development programs and regulatory actions on drugs, is also described. The model initially focuses on reactive metabolite-induced DILI in response to administration of acetaminophen, and spans multiple biological scales.

  8. Biologically based modelling and simulation of carcinogenesis at low doses

    International Nuclear Information System (INIS)

    Ouchi, Noriyuki B.

    2003-01-01

    The process of the carcinogenesis is studied by computer simulation. In general, we need a large number of experimental samples to detect mutations at low doses, but in practice it is difficult to get such a large number of data. To satisfy the requirements of the situation at low doses, it is good to study the process of carcinogenesis using biologically based mathematical model. We have mainly studied it by using as known as 'multi-stage model'; the model seems to get complicated, as we adopt the recent new findings of molecular biological experiments. Moreover, the basic idea of the multi-stage model is based on the epidemiologic data of log-log variation of cancer incidence with age, it seems to be difficult to compare with experimental data of irradiated cell culture system, which has been increasing in recent years. Taking above into consideration, we concluded that we had better make new model with following features: 1) a unit of the target system is a cell, 2) the new information of the molecular biology can be easily introduced, 3) having spatial coordinates for checking a colony formation or tumorigenesis. In this presentation, we will show the detail of the model and some simulation results about the carcinogenesis. (author)

  9. Methods and models in mathematical biology deterministic and stochastic approaches

    CERN Document Server

    Müller, Johannes

    2015-01-01

    This book developed from classes in mathematical biology taught by the authors over several years at the Technische Universität München. The main themes are modeling principles, mathematical principles for the analysis of these models, and model-based analysis of data. The key topics of modern biomathematics are covered: ecology, epidemiology, biochemistry, regulatory networks, neuronal networks, and population genetics. A variety of mathematical methods are introduced, ranging from ordinary and partial differential equations to stochastic graph theory and  branching processes. A special emphasis is placed on the interplay between stochastic and deterministic models.

  10. Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species

    OpenAIRE

    Matthew P. Adams; Catherine J. Collier; Sven Uthicke; Yan X. Ow; Lucas Langlois; Katherine R. O’Brien

    2017-01-01

    When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluat...

  11. Multi-Objective Ant Colony Optimization Based on the Physarum-Inspired Mathematical Model for Bi-Objective Traveling Salesman Problems.

    Directory of Open Access Journals (Sweden)

    Zili Zhang

    Full Text Available Bi-objective Traveling Salesman Problem (bTSP is an important field in the operations research, its solutions can be widely applied in the real world. Many researches of Multi-objective Ant Colony Optimization (MOACOs have been proposed to solve bTSPs. However, most of MOACOs suffer premature convergence. This paper proposes an optimization strategy for MOACOs by optimizing the initialization of pheromone matrix with the prior knowledge of Physarum-inspired Mathematical Model (PMM. PMM can find the shortest route between two nodes based on the positive feedback mechanism. The optimized algorithms, named as iPM-MOACOs, can enhance the pheromone in the short paths and promote the search ability of ants. A series of experiments are conducted and experimental results show that the proposed strategy can achieve a better compromise solution than the original MOACOs for solving bTSPs.

  12. Green Algae as Model Organisms for Biological Fluid Dynamics

    Science.gov (United States)

    Goldstein, Raymond E.

    2015-01-01

    In the past decade, the volvocine green algae, spanning from the unicellular Chlamydomonas to multicellular Volvox, have emerged as model organisms for a number of problems in biological fluid dynamics. These include flagellar propulsion, nutrient uptake by swimming organisms, hydrodynamic interactions mediated by walls, collective dynamics and transport within suspensions of microswimmers, the mechanism of phototaxis, and the stochastic dynamics of flagellar synchronization. Green algae are well suited to the study of such problems because of their range of sizes (from 10 μm to several millimeters), their geometric regularity, the ease with which they can be cultured, and the availability of many mutants that allow for connections between molecular details and organism-level behavior. This review summarizes these recent developments and highlights promising future directions in the study of biological fluid dynamics, especially in the context of evolutionary biology, that can take advantage of these remarkable organisms.

  13. Dynamics of mathematical models in biology bringing mathematics to life

    CERN Document Server

    Zazzu, Valeria; Guarracino, Mario

    2016-01-01

    This volume focuses on contributions from both the mathematics and life science community surrounding the concepts of time and dynamicity of nature, two significant elements which are often overlooked in modeling process to avoid exponential computations. The book is divided into three distinct parts: dynamics of genomes and genetic variation, dynamics of motifs, and dynamics of biological networks. Chapters included in dynamics of genomes and genetic variation analyze the molecular mechanisms and evolutionary processes that shape the structure and function of genomes and those that govern genome dynamics. The dynamics of motifs portion of the volume provides an overview of current methods for motif searching in DNA, RNA and proteins, a key process to discover emergent properties of cells, tissues, and organisms. The part devoted to the dynamics of biological networks covers networks aptly discusses networks in complex biological functions and activities that interpret processes in cells. Moreover, chapters i...

  14. Biological parameters for lung cancer in mathematical models of carcinogenesis

    International Nuclear Information System (INIS)

    Jacob, P.; Jacob, V.

    2003-01-01

    Applications of the two-step model of carcinogenesis with clonal expansion (TSCE) to lung cancer data are reviewed, including those on atomic bomb survivors from Hiroshima and Nagasaki, British doctors, Colorado Plateau miners, and Chinese tin miners. Different sets of identifiable model parameters are used in the literature. The parameter set which could be determined with the lowest uncertainty consists of the net proliferation rate gamma of intermediate cells, the hazard h 55 at an intermediate age, and the hazard H? at an asymptotically large age. Also, the values of these three parameters obtained in the various studies are more consistent than other identifiable combinations of the biological parameters. Based on representative results for these three parameters, implications for the biological parameters in the TSCE model are derived. (author)

  15. Multiway modeling and analysis in stem cell systems biology

    Directory of Open Access Journals (Sweden)

    Vandenberg Scott L

    2008-07-01

    Full Text Available Abstract Background Systems biology refers to multidisciplinary approaches designed to uncover emergent properties of biological systems. Stem cells are an attractive target for this analysis, due to their broad therapeutic potential. A central theme of systems biology is the use of computational modeling to reconstruct complex systems from a wealth of reductionist, molecular data (e.g., gene/protein expression, signal transduction activity, metabolic activity, etc.. A number of deterministic, probabilistic, and statistical learning models are used to understand sophisticated cellular behaviors such as protein expression during cellular differentiation and the activity of signaling networks. However, many of these models are bimodal i.e., they only consider row-column relationships. In contrast, multiway modeling techniques (also known as tensor models can analyze multimodal data, which capture much more information about complex behaviors such as cell differentiation. In particular, tensors can be very powerful tools for modeling the dynamic activity of biological networks over time. Here, we review the application of systems biology to stem cells and illustrate application of tensor analysis to model collagen-induced osteogenic differentiation of human mesenchymal stem cells. Results We applied Tucker1, Tucker3, and Parallel Factor Analysis (PARAFAC models to identify protein/gene expression patterns during extracellular matrix-induced osteogenic differentiation of human mesenchymal stem cells. In one case, we organized our data into a tensor of type protein/gene locus link × gene ontology category × osteogenic stimulant, and found that our cells expressed two distinct, stimulus-dependent sets of functionally related genes as they underwent osteogenic differentiation. In a second case, we organized DNA microarray data in a three-way tensor of gene IDs × osteogenic stimulus × replicates, and found that application of tensile strain to a

  16. Programming biological models in Python using PySB.

    Science.gov (United States)

    Lopez, Carlos F; Muhlich, Jeremy L; Bachman, John A; Sorger, Peter K

    2013-01-01

    Mathematical equations are fundamental to modeling biological networks, but as networks get large and revisions frequent, it becomes difficult to manage equations directly or to combine previously developed models. Multiple simultaneous efforts to create graphical standards, rule-based languages, and integrated software workbenches aim to simplify biological modeling but none fully meets the need for transparent, extensible, and reusable models. In this paper we describe PySB, an approach in which models are not only created using programs, they are programs. PySB draws on programmatic modeling concepts from little b and ProMot, the rule-based languages BioNetGen and Kappa and the growing library of Python numerical tools. Central to PySB is a library of macros encoding familiar biochemical actions such as binding, catalysis, and polymerization, making it possible to use a high-level, action-oriented vocabulary to construct detailed models. As Python programs, PySB models leverage tools and practices from the open-source software community, substantially advancing our ability to distribute and manage the work of testing biochemical hypotheses. We illustrate these ideas using new and previously published models of apoptosis.

  17. Inspiration or deflation? Feeling similar or dissimilar to slim and plus-size models affects self-evaluation of restrained eaters.

    Science.gov (United States)

    Papies, Esther K; Nicolaije, Kim A H

    2012-01-01

    The present studies examined the effect of perceiving images of slim and plus-size models on restrained eaters' self-evaluation. While previous research has found that such images can lead to either inspiration or deflation, we argue that these inconsistencies can be explained by differences in perceived similarity with the presented model. The results of two studies (ns=52 and 99) confirmed this and revealed that restrained eaters with high (low) perceived similarity to the model showed more positive (negative) self-evaluations when they viewed a slim model, compared to a plus-size model. In addition, Study 2 showed that inducing in participants a similarities mindset led to more positive self-evaluations after viewing a slim compared to a plus-size model, but only among restrained eaters with a relatively high BMI. These results are discussed in the context of research on social comparison processes and with regard to interventions for protection against the possible detrimental effects of media images. Copyright © 2011 Elsevier Ltd. All rights reserved.

  18. Learning from nature: Nature-inspired algorithms

    DEFF Research Database (Denmark)

    Albeanu, Grigore; Madsen, Henrik; Popentiu-Vladicescu, Florin

    2016-01-01

    .), genetic and evolutionary strategies, artificial immune systems etc. Well-known examples of applications include: aircraft wing design, wind turbine design, bionic car, bullet train, optimal decisions related to traffic, appropriate strategies to survive under a well-adapted immune system etc. Based......During last decade, the nature has inspired researchers to develop new algorithms. The largest collection of nature-inspired algorithms is biology-inspired: swarm intelligence (particle swarm optimization, ant colony optimization, cuckoo search, bees' algorithm, bat algorithm, firefly algorithm etc...... on collective social behaviour of organisms, researchers have developed optimization strategies taking into account not only the individuals, but also groups and environment. However, learning from nature, new classes of approaches can be identified, tested and compared against already available algorithms...

  19. The impact of realistic models of mass segregation on the event rate of extreme-mass ratio inspirals and cusp re-growth

    International Nuclear Information System (INIS)

    Amaro-Seoane, Pau; Preto, Miguel

    2011-01-01

    One of the most interesting sources of gravitational waves (GWs) for LISA is the inspiral of compact objects on to a massive black hole (MBH), commonly referred to as an 'extreme-mass ratio inspiral' (EMRI). The small object, typically a stellar black hole, emits significant amounts of GW along each orbit in the detector bandwidth. The slowly, adiabatic inspiral of these sources will allow us to map spacetime around MBHs in detail, as well as to test our current conception of gravitation in the strong regime. The event rate of this kind of source has been addressed many times in the literature and the numbers reported fluctuate by orders of magnitude. On the other hand, recent observations of the Galactic centre revealed a dearth of giant stars inside the inner parsec relative to the numbers theoretically expected for a fully relaxed stellar cusp. The possibility of unrelaxed nuclei (or, equivalently, with no or only a very shallow cusp, or core) adds substantial uncertainty to the estimates. Having this timely question in mind, we run a significant number of direct-summation N-body simulations with up to half a million particles to calibrate a much faster orbit-averaged Fokker-Planck code. We show that, under quite generic initial conditions, the time required for the growth of a relaxed, mass segregated stellar cusp is shorter than a Hubble time for MBHs with M . ∼ 6 M o-dot (i.e. nuclei in the range of LISA). We then investigate the regime of strong mass segregation (SMS) for models with two different stellar mass components. Given the most recent stellar mass normalization for the inner parsec of the Galactic centre, SMS has the significant impact of boosting the EMRI rates by a factor of ∼10 in comparison to what would result from a 7/4-Bahcall and Wolf cusp resulting in ∼250 events per Gyr per Milky Way type galaxy. Such an intrinsic rate should translate roughly into ∼10 2 -7 x 10 2 sbh's (EMRIs detected by LISA over a mission lifetime of 2 or 5

  20. Echinococcus as a model system: biology and epidemiology.

    Science.gov (United States)

    Thompson, R C A; Jenkins, D J

    2014-10-15

    The introduction of Echinococcus to Australia over 200 years ago and its establishment in sheep rearing areas of the country inflicted a serious medical and economic burden on the country. This resulted in an investment in both basic and applied research aimed at learning more about the biology and life cycle of Echinococcus. This research served to illustrate the uniqueness of the parasite in terms of developmental biology and ecology, and the value of Echinococcus as a model system in a broad range of research, from fundamental biology to theoretical control systems. These studies formed the foundation for an international, diverse and ongoing research effort on the hydatid organisms encompassing stem cell biology, gene regulation, strain variation, wildlife diseases and models of transmission dynamics. We describe the development, nature and diversity of this research, and how it was initiated in Australia but subsequently has stimulated much international and collaborative research on Echinococcus. Copyright © 2014 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.

  1. Synthesis, Biological Evaluation, and Molecular Modeling Studies of New Oxadiazole-Stilbene Hybrids against Phytopathogenic Fungi

    Science.gov (United States)

    Jian, Weilin; He, Daohang; Song, Shaoyun

    2016-08-01

    Natural stilbenes (especially resveratrol) play important roles in plant protection by acting as both constitutive and inducible defenses. However, their exogenous applications on crops as fungicidal agents are challenged by their oxidative degradation and limited availability. In this study, a new class of resveratrol-inspired oxadiazole-stilbene hybrids was synthesized via Wittig-Horner reaction. Bioassay results indicated that some of the compounds exhibited potent fungicidal activity against Botrytis cinerea in vitro. Among these stilbene hybrids, compounds 11 showed promising inhibitory activity with the EC50 value of 144.6 μg/mL, which was superior to that of resveratrol (315.6 μg/mL). Remarkably, the considerably abnormal mycelial morphology was observed in the presence of compound 11. The inhibitory profile was further proposed by homology modeling and molecular docking studies, which showed the possible interaction of resveratrol and oxadiazole-stilbene hybrids with the cytochrome P450-dependent sterol 14α-demethylase from B. cinerea (BcCYP51) for the first time. Taken together, these results would provide new insights into the fungicidal mechanism of stilbenes, as well as an important clue for biology-oriented synthesis of stilbene hybrids with improved bioactivity against plant pathogenic fungi in crop protection.

  2. On the synthesis of a bio-inspired dual-cellular fluidic flexible matrix composite adaptive structure based on a non-dimensional dynamics model

    International Nuclear Information System (INIS)

    Li, Suyi; Wang, K W

    2013-01-01

    A recent study investigated the dynamic characteristics of an adaptive structure concept featuring dual fluidic flexible matrix composite (F 2 MC) cells inspired by the configuration of plant cells and cell walls. This novel bio-inspired system consists of two F 2 MC cells with different fiber angles connected through internal fluid circuits. It was discovered that the dual F 2 MC cellular structure can be characterized as a two degree of freedom damped mass–spring oscillator, and can be utilized as a vibration absorber or an enhanced actuator under different operation conditions. These results demonstrated that the concept is promising and further investigations are needed to develop methodologies for synthesizing future multi-cellular F 2 MC structural systems. While interesting, the previous study focused on specific case studies and analysis. That is, the outcome did not provide insight that could be generalized, or tools for synthesizing a multiple F 2 MC cellular structure. This paper attempts to address this important issue by developing a non-dimensional dynamic model, which reveals good physical insights as well as identifying crucial constitutive parameters for F 2 MC cellular design. Working with these parameters, rather than physical variables, can greatly simplify the mathematics involved in the study. A synthesis tool is then developed for the dual-cellular structure, and it is found that for each set of achievable target poles and zero, there exist multiple F 2 MC cellular designs, forming a design space. The presented physical insights and synthesis tool for the dual-cellular structure will be the building blocks for future investigation on cellular structures with a larger number of cells. (paper)

  3. Evolving cell models for systems and synthetic biology.

    Science.gov (United States)

    Cao, Hongqing; Romero-Campero, Francisco J; Heeb, Stephan; Cámara, Miguel; Krasnogor, Natalio

    2010-03-01

    This paper proposes a new methodology for the automated design of cell models for systems and synthetic biology. Our modelling framework is based on P systems, a discrete, stochastic and modular formal modelling language. The automated design of biological models comprising the optimization of the model structure and its stochastic kinetic constants is performed using an evolutionary algorithm. The evolutionary algorithm evolves model structures by combining different modules taken from a predefined module library and then it fine-tunes the associated stochastic kinetic constants. We investigate four alternative objective functions for the fitness calculation within the evolutionary algorithm: (1) equally weighted sum method, (2) normalization method, (3) randomly weighted sum method, and (4) equally weighted product method. The effectiveness of the methodology is tested on four case studies of increasing complexity including negative and positive autoregulation as well as two gene networks implementing a pulse generator and a bandwidth detector. We provide a systematic analysis of the evolutionary algorithm's results as well as of the resulting evolved cell models.

  4. Inspirations in medical genetics.

    Science.gov (United States)

    Asadollahi, Reza

    2016-02-01

    There are abundant instances in the history of genetics and medical genetics to illustrate how curiosity, charisma of mentors, nature, art, the saving of lives and many other matters have inspired great discoveries. These achievements from deciphering genetic concepts to characterizing genetic disorders have been crucial for management of the patients. There remains, however, a long pathway ahead. © The Author(s) 2014.

  5. Nature as Inspiration

    Science.gov (United States)

    Tank, Kristina; Moore, Tamara; Strnat, Meg

    2015-01-01

    This article describes the final lesson within a seven-day STEM and literacy unit that is part of the Picture STEM curriculum (pictureSTEM. org) and uses engineering to integrate science and mathematics learning in a meaningful way (Tank and Moore 2013). For this engineering challenge, students used nature as a source of inspiration for designs to…

  6. Ndebele Inspired Houses

    Science.gov (United States)

    Rice, Nicole

    2012-01-01

    The house paintings of the South African Ndebele people are more than just an attempt to improve the aesthetics of a community; they are a source of identity and significance for Ndebele women. In this article, the author describes an art project wherein students use the tradition of Ndebele house painting as inspiration for creating their own…

  7. Bifurcations of a class of singular biological economic models

    International Nuclear Information System (INIS)

    Zhang Xue; Zhang Qingling; Zhang Yue

    2009-01-01

    This paper studies systematically a prey-predator singular biological economic model with time delay. It shows that this model exhibits two bifurcation phenomena when the economic profit is zero. One is transcritical bifurcation which changes the stability of the system, and the other is singular induced bifurcation which indicates that zero economic profit brings impulse, i.e., rapid expansion of the population in biological explanation. On the other hand, if the economic profit is positive, at a critical value of bifurcation parameter, the system undergoes a Hopf bifurcation, i.e., the increase of delay destabilizes the system and bifurcates into small amplitude periodic solution. Finally, by using Matlab software, numerical simulations illustrate the effectiveness of the results obtained here. In addition, we study numerically that the system undergoes a saddle-node bifurcation when the bifurcation parameter goes through critical value of positive economic profit.

  8. Enterococcus infection biology: lessons from invertebrate host models.

    Science.gov (United States)

    Yuen, Grace J; Ausubel, Frederick M

    2014-03-01

    The enterococci are commensals of the gastrointestinal tract of many metazoans, from insects to humans. While they normally do not cause disease in the intestine, they can become pathogenic when they infect sites outside of the gut. Recently, the enterococci have become important nosocomial pathogens, with the majority of human enterococcal infections caused by two species, Enterococcus faecalis and Enterococcus faecium. Studies using invertebrate infection models have revealed insights into the biology of enterococcal infections, as well as general principles underlying host innate immune defense. This review highlights recent findings on Enterococcus infection biology from two invertebrate infection models, the greater wax moth Galleria mellonella and the free-living bacteriovorous nematode Caenorhabditis elegans.

  9. Biological Inspiration for Agile Autonomous Air Vehicles

    National Research Council Canada - National Science Library

    Evers, Johnny H

    2007-01-01

    .... Flying animals exhibit capabilities for aerial acrobatics, insensitivity to wind gusts, avoiding collision with or intercepting fixed and moving objects, landing and take off from small perches...

  10. A Biologically Inspired Learning to Grasp System

    Science.gov (United States)

    2001-10-25

    possible extensive discussions of data on the premotor cortex and monkey grasping circuit with Giacomo Rizzolatti , Vittorio Gallese, to whom we express...premotor specialisation for the different types of grasps that Rizzolatti group [3] has found be formed at this age yet. Infants will need to...our gratitude. REFERENCES [1] M. Jeannerod, M.A. Arbib, G. Rizzolatti , H. Sakata, “Grasping objects: the cortical mechanisms of visuomotor

  11. Project Summary: Biology-Inspired Autonomous Control

    Science.gov (United States)

    2011-02-01

    pp. 644–650, 2005. [4] L. Dugatkin, Cheating monkeys and citizen bees : the nature of cooperation in animals and humans. Simon and Shuster, 1999. [5] L...varied behavioral American Institute of Aeronautics and Astronautics 7 repertoires. Many of the animal extinctions of the past few centuries

  12. Learning from nature : Biologically-inspired sensors

    NARCIS (Netherlands)

    Wicaksono, D.H.B.

    2008-01-01

    New emerging sensing applications demand novel sensors in micro-/nano-scale to enable integration and embedding into higher level structures or systems. Downsizing the structure will usually decrease the sensitivity of the sensors, since the sensitivity is a function of geometrical parameters, e.g.

  13. Biologically inspired hairy surfaces for liquid repellency

    Science.gov (United States)

    Hsu, Shu-Hau

    Owing to remarkable features, such as self-cleaning, anti-biofouling and drag reduction, interest on rendering surfaces water-repellent has significantly grown within this decade. Attempts on making surfaces "superhydrophobic", where high water contact angle (θc >150°) accompanied with only few degrees of roll-off angle, have been extensively demonstrated through the mimicking of the surface chemistry and morphology of lotus leaves. This appealing phenomenon also exists on another structure from nature: surfaces comprising soft hairs. Although the role of this piliferous integument has long been recognized for providing life, arthropods in particular, waterrepellency, the synthetic superhydrophobic surfaces based on this structure are still very limited. In this study, the goal was to develop a novel liquid-repellent surface by mimicking the hairy exterior of species. The artificial hairy surfaces were prepared by means of pressurized membrane casting, in which thermoplastic sheets were forced to flow into porous membranes at elevated temperature. The G-shaped pillars on the membrane cast polypropylene substrate are particularly similar to the conformation of natural hairs. The principle of this fabrication technique is relatively accessible and is expected to be compatible with large-area fabrication of superhydrophobic interfaces. The artificial hairy surface features perfectly hydrophobic response where no contact angle hysteresis was observed from video assessment. Thus the artificial hairy surface of the current work appears to be the first report to have such extreme hydrophobicity with only structural modification from the original substrate. This ultralow adhesion to water droplet is believed to be attributed to the hydrophobic methyl groups and the mechanical response of the artificial hairs. Liquid repellency of the hairy surfaces was further enhanced by coating with fluorocarbon (CF) layers via deep reactive ion etching (DRIE). The contact angle of water-methanol mixture (gamma < 35.2 mN/m) was raised from 60° to around 140°. The surface energy of coated samples, however, was still not low enough to repel non-polar liquids. Moreover, the hairy structure is not favorable for maintaining the low surface tension liquid in Cassie-Baxter state.

  14. Biologically inspired optimization methods an introduction

    CERN Document Server

    Wahde, M

    2008-01-01

    The advent of rapid, reliable and cheap computing power over the last decades has transformed many, if not most, fields of science and engineering. The multidisciplinary field of optimization is no exception. First of all, with fast computers, researchers and engineers can apply classical optimization methods to problems of larger and larger size. In addition, however, researchers have developed a host of new optimization algorithms that operate in a rather different way than the classical ones, and that allow practitioners to attack optimization problems where the classical methods are either not applicable or simply too costly (in terms of time and other resources) to apply.This book is intended as a course book for introductory courses in stochastic optimization algorithms (in this book, the terms optimization method and optimization algorithm will be used interchangeably), and it has grown from a set of lectures notes used in courses, taught by the author, at the international master programme Complex Ada...

  15. A specialized face-processing model inspired by the organization of monkey face patches explains several face-specific phenomena observed in humans.

    Science.gov (United States)

    Farzmahdi, Amirhossein; Rajaei, Karim; Ghodrati, Masoud; Ebrahimpour, Reza; Khaligh-Razavi, Seyed-Mahdi

    2016-04-26

    Converging reports indicate that face images are processed through specialized neural networks in the brain -i.e. face patches in monkeys and the fusiform face area (FFA) in humans. These studies were designed to find out how faces are processed in visual system compared to other objects. Yet, the underlying mechanism of face processing is not completely revealed. Here, we show that a hierarchical computational model, inspired by electrophysiological evidence on face processing in primates, is able to generate representational properties similar to those observed in monkey face patches (posterior, middle and anterior patches). Since the most important goal of sensory neuroscience is linking the neural responses with behavioral outputs, we test whether the proposed model, which is designed to account for neural responses in monkey face patches, is also able to predict well-documented behavioral face phenomena observed in humans. We show that the proposed model satisfies several cognitive face effects such as: composite face effect and the idea of canonical face views. Our model provides insights about the underlying computations that transfer visual information from posterior to anterior face patches.

  16. Dynamic models in research and management of biological invasions.

    Science.gov (United States)

    Buchadas, Ana; Vaz, Ana Sofia; Honrado, João P; Alagador, Diogo; Bastos, Rita; Cabral, João A; Santos, Mário; Vicente, Joana R

    2017-07-01

    Invasive species are increasing in number, extent and impact worldwide. Effective invasion management has thus become a core socio-ecological challenge. To tackle this challenge, integrating spatial-temporal dynamics of invasion processes with modelling approaches is a promising approach. The inclusion of dynamic processes in such modelling frameworks (i.e. dynamic or hybrid models, here defined as models that integrate both dynamic and static approaches) adds an explicit temporal dimension to the study and management of invasions, enabling the prediction of invasions and optimisation of multi-scale management and governance. However, the extent to which dynamic approaches have been used for that purpose is under-investigated. Based on a literature review, we examined the extent to which dynamic modelling has been used to address invasions worldwide. We then evaluated how the use of dynamic modelling has evolved through time in the scope of invasive species management. The results suggest that modelling, in particular dynamic modelling, has been increasingly applied to biological invasions, especially to support management decisions at local scales. Also, the combination of dynamic and static modelling approaches (hybrid models with a spatially explicit output) can be especially effective, not only to support management at early invasion stages (from prevention to early detection), but also to improve the monitoring of invasion processes and impact assessment. Further development and testing of such hybrid models may well be regarded as a priority for future research aiming to improve the management of invasions across scales. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. The University – a Rational-Biologic Model

    Directory of Open Access Journals (Sweden)

    Ion Gh. Rosca

    2008-05-01

    Full Text Available The article advances the extension of the biologic rational model for the organizations, which are reprocessing and living in a turbulent environment. The current “tree” type organizations are not able to satisfy the requirements of the socio-economical environment and are not able to provide the organizational perpetuation and development. Thus, an innovative performing model for both the top and down management areas is presented, with the following recommendations: dividing the organization into departments using neuronal connections, focusing on the formatting processes and not on the activities, rethinking the system of a new organizational culture.

  18. Biological profiling and dose-response modeling tools ...

    Science.gov (United States)

    Through its ToxCast project, the U.S. EPA has developed a battery of in vitro high throughput screening (HTS) assays designed to assess the potential toxicity of environmental chemicals. At present, over 1800 chemicals have been tested in up to 600 assays, yielding a large number of concentration-response data sets. Standard processing of these data sets involves finding a best fitting mathematical model and set of model parameters that specify this model. The model parameters include quantities such as the half-maximal activity concentration (or “AC50”) that have biological significance and can be used to inform the efficacy or potency of a given chemical with respect to a given assay. All of this data is processed and stored in an online-accessible database and website: http://actor.epa.gov/dashboard2. Results from these in vitro assays are used in a multitude of ways. New pathways and targets can be identified and incorporated into new or existing adverse outcome pathways (AOPs). Pharmacokinetic models such as those implemented EPA’s HTTK R package can be used to translate an in vitro concentration into an in vivo dose; i.e., one can predict the oral equivalent dose that might be expected to activate a specific biological pathway. Such predicted values can then be compared with estimated actual human exposures prioritize chemicals for further testing.Any quantitative examination should be accompanied by estimation of uncertainty. We are developing met

  19. Mouse models for gastric cancer: Matching models to biological questions

    Science.gov (United States)

    Poh, Ashleigh R; O'Donoghue, Robert J J

    2016-01-01

    Abstract Gastric cancer is the third leading cause of cancer‐related mortality worldwide. This is in part due to the asymptomatic nature of the disease, which often results in late‐stage diagnosis, at which point there are limited treatment options. Even when treated successfully, gastric cancer patients have a high risk of tumor recurrence and acquired drug resistance. It is vital to gain a better understanding of the molecular mechanisms underlying gastric cancer pathogenesis to facilitate the design of new‐targeted therapies that may improve patient survival. A number of chemically and genetically engineered mouse models of gastric cancer have provided significant insight into the contribution of genetic and environmental factors to disease onset and progression. This review outlines the strengths and limitations of current mouse models of gastric cancer and their relevance to the pre‐clinical development of new therapeutics. PMID:26809278

  20. Caenorhabditis elegans, a Biological Model for Research in Toxicology.

    Science.gov (United States)

    Tejeda-Benitez, Lesly; Olivero-Verbel, Jesus

    2016-01-01

    Caenorhabditis elegans is a nematode of microscopic size which, due to its biological characteristics, has been used since the 1970s as a model for research in molecular biology, medicine, pharmacology, and toxicology. It was the first animal whose genome was completely sequenced and has played a key role in the understanding of apoptosis and RNA interference. The transparency of its body, short lifespan, ability to self-fertilize and ease of culture are advantages that make it ideal as a model in toxicology. Due to the fact that some of its biochemical pathways are similar to those of humans, it has been employed in research in several fields. C. elegans' use as a biological model in environmental toxicological assessments allows the determination of multiple endpoints. Some of these utilize the effects on the biological functions of the nematode and others use molecular markers. Endpoints such as lethality, growth, reproduction, and locomotion are the most studied, and usually employ the wild type Bristol N2 strain. Other endpoints use reporter genes, such as green fluorescence protein, driven by regulatory sequences from other genes related to different mechanisms of toxicity, such as heat shock, oxidative stress, CYP system, and metallothioneins among others, allowing the study of gene expression in a manner both rapid and easy. These transgenic strains of C. elegans represent a powerful tool to assess toxicity pathways for mixtures and environmental samples, and their numbers are growing in diversity and selectivity. However, other molecular biology techniques, including DNA microarrays and MicroRNAs have been explored to assess the effects of different toxicants and samples. C. elegans has allowed the assessment of neurotoxic effects for heavy metals and pesticides, among those more frequently studied, as the nematode has a very well defined nervous system. More recently, nanoparticles are emergent pollutants whose toxicity can be explored using this nematode

  1. Wave basin model tests of technical-biological bank protection

    Science.gov (United States)

    Eisenmann, J.

    2012-04-01

    Sloped embankments of inland waterways are usually protected from erosion and other negative im-pacts of ship-induced hydraulic loads by technical revetments consisting of riprap. Concerning the dimensioning of such bank protection there are several design rules available, e.g. the "Principles for the Design of Bank and Bottom Protection for Inland Waterways" or the Code of Practice "Use of Standard Construction Methods for Bank and Bottom Protection on Waterways" issued by the BAW (Federal Waterways Engineering and Research Institute). Since the European Water Framework Directive has been put into action special emphasis was put on natural banks. Therefore the application of technical-biological bank protection is favoured. Currently design principles for technical-biological bank protection on inland waterways are missing. The existing experiences mainly refer to flowing waters with no or low ship-induced hydraulic loads on the banks. Since 2004 the Federal Waterways Engineering and Research Institute has been tracking the re-search and development project "Alternative Technical-Biological Bank Protection on Inland Water-ways" in company with the Federal Institute of Hydrology. The investigation to date includes the ex-amination of waterway sections where technical- biological bank protection is applied locally. For the development of design rules for technical-biological bank protection investigations shall be carried out in a next step, considering the mechanics and resilience of technical-biological bank protection with special attention to ship-induced hydraulic loads. The presentation gives a short introduction into hydraulic loads at inland waterways and their bank protection. More in detail model tests of a willow brush mattress as a technical-biological bank protec-tion in a wave basin are explained. Within the scope of these tests the brush mattresses were ex-posed to wave impacts to determine their resilience towards hydraulic loads. Since the

  2. Modeling Cancer Metastasis using Global, Quantitative and Integrative Network Biology

    DEFF Research Database (Denmark)

    Schoof, Erwin; Erler, Janine

    understanding of molecular processes which are fundamental to tumorigenesis. In Article 1, we propose a novel framework for how cancer mutations can be studied by taking into account their effect at the protein network level. In Article 2, we demonstrate how global, quantitative data on phosphorylation dynamics...... can be generated using MS, and how this can be modeled using a computational framework for deciphering kinase-substrate dynamics. This framework is described in depth in Article 3, and covers the design of KinomeXplorer, which allows the prediction of kinases responsible for modulating observed...... phosphorylation dynamics in a given biological sample. In Chapter III, we move into Integrative Network Biology, where, by combining two fundamental technologies (MS & NGS), we can obtain more in-depth insights into the links between cellular phenotype and genotype. Article 4 describes the proof...

  3. Agent-Based Modeling in Molecular Systems Biology.

    Science.gov (United States)

    Soheilypour, Mohammad; Mofrad, Mohammad R K

    2018-06-08

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

  4. Estimating confidence intervals in predicted responses for oscillatory biological models.

    Science.gov (United States)

    St John, Peter C; Doyle, Francis J

    2013-07-29

    The dynamics of gene regulation play a crucial role in a cellular control: allowing the cell to express the right proteins to meet changing needs. Some needs, such as correctly anticipating the day-night cycle, require complicated oscillatory features. In the analysis of gene regulatory networks, mathematical models are frequently used to understand how a network's structure enables it to respond appropriately to external inputs. These models typically consist of a set of ordinary differential equations, describing a network of biochemical reactions, and unknown kinetic parameters, chosen such that the model best captures experimental data. However, since a model's parameter values are uncertain, and since dynamic responses to inputs are highly parameter-dependent, it is difficult to assess the confidence associated with these in silico predictions. In particular, models with complex dynamics - such as oscillations - must be fit with computationally expensive global optimization routines, and cannot take advantage of existing measures of identifiability. Despite their difficulty to model mathematically, limit cycle oscillations play a key role in many biological processes, including cell cycling, metabolism, neuron firing, and circadian rhythms. In this study, we employ an efficient parameter estimation technique to enable a bootstrap uncertainty analysis for limit cycle models. Since the primary role of systems biology models is the insight they provide on responses to rate perturbations, we extend our uncertainty analysis to include first order sensitivity coefficients. Using a literature model of circadian rhythms, we show how predictive precision is degraded with decreasing sample points and increasing relative error. Additionally, we show how this method can be used for model discrimination by comparing the output identifiability of two candidate model structures to published literature data. Our method permits modellers of oscillatory systems to confidently

  5. Quantum field inspired model of decision making: Asymptotic stabilization of belief state via interaction with surrounding mental environment

    OpenAIRE

    Bagarello, Fabio; Basieva, Irina; Khrennikov, Andrei

    2017-01-01

    This paper is devoted to justification of quantum-like models of the process of decision making based on the theory of open quantum systems, i.e. decision making is considered as decoherence. This process is modeled as interaction of a decision maker, Alice, with a mental (information) environment ${\\cal R}$ surrounding her. Such an interaction generates "dissipation of uncertainty" from Alice's belief-state $\\rho(t)$ into ${\\cal R}$ and asymptotic stabilization of $\\rho(t)$ to a steady belie...

  6. Analysis and logical modeling of biological signaling transduction networks

    Science.gov (United States)

    Sun, Zhongyao

    The study of network theory and its application span across a multitude of seemingly disparate fields of science and technology: computer science, biology, social science, linguistics, etc. It is the intrinsic similarities embedded in the entities and the way they interact with one another in these systems that link them together. In this dissertation, I present from both the aspect of theoretical analysis and the aspect of application three projects, which primarily focus on signal transduction networks in biology. In these projects, I assembled a network model through extensively perusing literature, performed model-based simulations and validation, analyzed network topology, and proposed a novel network measure. The application of network modeling to the system of stomatal opening in plants revealed a fundamental question about the process that has been left unanswered in decades. The novel measure of the redundancy of signal transduction networks with Boolean dynamics by calculating its maximum node-independent elementary signaling mode set accurately predicts the effect of single node knockout in such signaling processes. The three projects as an organic whole advance the understanding of a real system as well as the behavior of such network models, giving me an opportunity to take a glimpse at the dazzling facets of the immense world of network science.

  7. Inspiring a generation

    CERN Multimedia

    2012-01-01

    The motto of the 2012 Olympic and Paralympic Games is ‘Inspire a generation’ so it was particularly pleasing to see science, the LHC and Higgs bosons featuring so strongly in the opening ceremony of the Paralympics last week.   It’s a sign of just how far our field has come that such a high-profile event featured particle physics so strongly, and we can certainly add our support to that motto. If the legacy of London 2012 is a generation inspired by science as well as sport, then the games will have more than fulfilled their mission. Particle physics has truly inspiring stories to tell, going well beyond Higgs and the LHC, and the entire community has played its part in bringing the excitement of frontier research in particle physics to a wide audience. Nevertheless, we cannot rest on our laurels: maintaining the kind of enthusiasm for science we witnessed at the Paralympic opening ceremony will require constant vigilance, and creative thinking about ways to rea...

  8. [NiFe] hydrogenase structural and functional models: new bio-inspired catalysts for hydrogen evolution; Modeles structuraux et fonctionnels du site actif des hydrogenases [NiFe]: de nouveaux catalyseurs bio-inspires pour la production d'hydrogene

    Energy Technology Data Exchange (ETDEWEB)

    Oudart, Y

    2006-09-15

    Hydrogenase enzymes reversibly catalyze the oxidation and production of hydrogen in a range close to the thermodynamic potential. The [NiFe] hydrogenase active site contains an iron-cyano-carbonyl moiety linked to a nickel atom which is in an all sulphur environment. Both the active site originality and the potential development of an hydrogen economy make the synthesis of functional and structural models worthy. To take up this challenge, we have synthesised mononuclear ruthenium models and more importantly, nickel-ruthenium complexes, mimicking some structural features of the [NiFe] hydrogenase active site. Ruthenium is indeed isoelectronic to iron and some of its complexes are well-known to bear hydrides. The compounds described in this study have been well characterised and their activity in proton reduction has been successfully tested. Most of them are able to catalyze this reaction though their electrocatalytic potentials remain much more negative compared to which of platinum. The studied parameters point out the importance of the complexes electron richness, especially of the nickel environment. Furthermore, the proton reduction activity is stable for several hours at good rates. The ruthenium environment seems important for this stability. Altogether, these compounds represent the very first catalytically active [NiFe] hydrogenase models. Important additional results of this study are the synergetic behaviour of the two metals in protons reduction and the evidence of a protonation step as the limiting step of the catalytic cycle. We have also shown that a basic site close to ruthenium improves the electrocatalytic potential of the complexes. (author)

  9. Revision history aware repositories of computational models of biological systems.

    Science.gov (United States)

    Miller, Andrew K; Yu, Tommy; Britten, Randall; Cooling, Mike T; Lawson, James; Cowan, Dougal; Garny, Alan; Halstead, Matt D B; Hunter, Peter J; Nickerson, David P; Nunns, Geo; Wimalaratne, Sarala M; Nielsen, Poul M F

    2011-01-14

    Building repositories of computational models of biological systems ensures that published models are available for both education and further research, and can provide a source of smaller, previously verified models to integrate into a larger model. One problem with earlier repositories has been the limitations in facilities to record the revision history of models. Often, these facilities are limited to a linear series of versions which were deposited in the repository. This is problematic for several reasons. Firstly, there are many instances in the history of biological systems modelling where an 'ancestral' model is modified by different groups to create many different models. With a linear series of versions, if the changes made to one model are merged into another model, the merge appears as a single item in the history. This hides useful revision history information, and also makes further merges much more difficult, as there is no record of which changes have or have not already been merged. In addition, a long series of individual changes made outside of the repository are also all merged into a single revision when they are put back into the repository, making it difficult to separate out individual changes. Furthermore, many earlier repositories only retain the revision history of individual files, rather than of a group of files. This is an important limitation to overcome, because some types of models, such as CellML 1.1 models, can be developed as a collection of modules, each in a separate file. The need for revision history is widely recognised for computer software, and a lot of work has gone into developing version control systems and distributed version control systems (DVCSs) for tracking the revision history. However, to date, there has been no published research on how DVCSs can be applied to repositories of computational models of biological systems. We have extended the Physiome Model Repository software to be fully revision history aware

  10. Revision history aware repositories of computational models of biological systems

    Directory of Open Access Journals (Sweden)

    Nickerson David P

    2011-01-01

    Full Text Available Abstract Background Building repositories of computational models of biological systems ensures that published models are available for both education and further research, and can provide a source of smaller, previously verified models to integrate into a larger model. One problem with earlier repositories has been the limitations in facilities to record the revision history of models. Often, these facilities are limited to a linear series of versions which were deposited in the repository. This is problematic for several reasons. Firstly, there are many instances in the history of biological systems modelling where an 'ancestral' model is modified by different groups to create many different models. With a linear series of versions, if the changes made to one model are merged into another model, the merge appears as a single item in the history. This hides useful revision history information, and also makes further merges much more difficult, as there is no record of which changes have or have not already been merged. In addition, a long series of individual changes made outside of the repository are also all merged into a single revision when they are put back into the repository, making it difficult to separate out individual changes. Furthermore, many earlier repositories only retain the revision history of individual files, rather than of a group of files. This is an important limitation to overcome, because some types of models, such as CellML 1.1 models, can be developed as a collection of modules, each in a separate file. The need for revision history is widely recognised for computer software, and a lot of work has gone into developing version control systems and distributed version control systems (DVCSs for tracking the revision history. However, to date, there has been no published research on how DVCSs can be applied to repositories of computational models of biological systems. Results We have extended the Physiome Model

  11. In silico biology of bone modelling and remodelling: adaptation.

    Science.gov (United States)

    Gerhard, Friederike A; Webster, Duncan J; van Lenthe, G Harry; Müller, Ralph

    2009-05-28

    Modelling and remodelling are the processes by which bone adapts its shape and internal structure to external influences. However, the cellular mechanisms triggering osteoclastic resorption and osteoblastic formation are still unknown. In order to investigate current biological theories, in silico models can be applied. In the past, most of these models were based on the continuum assumption, but some questions related to bone adaptation can be addressed better by models incorporating the trabecular microstructure. In this paper, existing simulation models are reviewed and one of the microstructural models is extended to test the hypothesis that bone adaptation can be simulated without particular knowledge of the local strain distribution in the bone. Validation using an experimental murine loading model showed that this is possible. Furthermore, the experimental model revealed that bone formation cannot be attributed only to an increase in trabecular thickness but also to structural reorganization including the growth of new trabeculae. How these new trabeculae arise is still an unresolved issue and might be better addressed by incorporating other levels of hierarchy, especially the cellular level. The cellular level sheds light on the activity and interplay between the different cell types, leading to the effective change in the whole bone. For this reason, hierarchical multi-scale simulations might help in the future to better understand the biomathematical laws behind bone adaptation.

  12. Biomimetics inspired surfaces for drag reduction and oleophobicity/philicity

    Directory of Open Access Journals (Sweden)

    Bharat Bhushan

    2011-02-01

    Full Text Available The emerging field of biomimetics allows one to mimic biology or nature to develop nanomaterials, nanodevices, and processes which provide desirable properties. Hierarchical structures with dimensions of features ranging from the macroscale to the nanoscale are extremely common in nature and possess properties of interest. There are a large number of objects including bacteria, plants, land and aquatic animals, and seashells with properties of commercial interest. Certain plant leaves, such as lotus (Nelumbo nucifera leaves, are known to be superhydrophobic and self-cleaning due to the hierarchical surface roughness and presence of a wax layer. In addition to a self-cleaning effect, these surfaces with a high contact angle and low contact angle hysteresis also exhibit low adhesion and drag reduction for fluid flow. An aquatic animal, such as a shark, is another model from nature for the reduction of drag in fluid flow. The artificial surfaces inspired from the shark skin and lotus leaf have been created, and in this article the influence of structure on drag reduction efficiency is reviewed. Biomimetic-inspired oleophobic surfaces can be used to prevent contamination of the underwater parts of ships by biological and organic contaminants, including oil. The article also reviews the wetting behavior of oil droplets on various superoleophobic surfaces created in the lab.

  13. Numerical simulation of humidification and heating during inspiration in nose models with three different located septal perforations.

    Science.gov (United States)

    Lindemann, Jörg; Reichert, Michael; Kröger, Ralf; Schuler, Patrick; Hoffmann, Thomas; Sommer, Fabian

    2016-07-01

    Nasal septum perforations (SP) are characterized by nasal obstruction, bleeding and crusting. The disturbed heating and humidification of the inhaled air are important factors, which cause these symptoms due to a disturbed airflow. Numerical simulations offer a great potential to avoid these limitations and to provide valid data. The aim of the study was to simulate the humidification and heating of the inhaled air in digital nose models with three different SPs and without SP. Four realistic bilateral nose models based on a multi-slice CT scan were created. The SP were located anterior caudal, anterior cranial and posterior caudal. One model was without SP. A numerical simulation was performed. Boundary conditions were based on previous in vivo measurements. Heating and humidification of the inhaled air were displayed, analyzed in each model and compared to each other. Anterior caudal SPs cause a disturbed decrease of temperature and humidity of the inhaled air. The reduced temperature and humidity values can still be shown in the posterior nose. The anterior cranial and the posterior caudal perforation have only a minor influence on heating and humidification. A reduced humidification and heating of the air can be shown by numerical simulations due to SP depending on their localization. The anterior caudal SP representing a typical localization after previous surgery has the biggest influence on heating and humidification. The results explain the typical symptoms such as crusting by drying-out the nasal mucosa. The size and the localization of the SP are essential for the symptoms.

  14. Human pluripotent stem cells: an emerging model in developmental biology.

    Science.gov (United States)

    Zhu, Zengrong; Huangfu, Danwei

    2013-02-01

    Developmental biology has long benefited from studies of classic model organisms. Recently, human pluripotent stem cells (hPSCs), including human embryonic stem cells and human induced pluripotent stem cells, have emerged as a new model system that offers unique advantages for developmental studies. Here, we discuss how studies of hPSCs can complement classic approaches using model organisms, and how hPSCs can be used to recapitulate aspects of human embryonic development 'in a dish'. We also summarize some of the recently developed genetic tools that greatly facilitate the interrogation of gene function during hPSC differentiation. With the development of high-throughput screening technologies, hPSCs have the potential to revolutionize gene discovery in mammalian development.

  15. Experimental, statistical, and biological models of radon carcinogenesis

    International Nuclear Information System (INIS)

    Cross, F.T.

    1991-09-01

    Risk models developed for underground miners have not been consistently validated in studies of populations exposed to indoor radon. Imprecision in risk estimates results principally from differences between exposures in mines as compared to domestic environments and from uncertainties about the interaction between cigarette-smoking and exposure to radon decay products. Uncertainties in extrapolating miner data to domestic exposures can be reduced by means of a broad-based health effects research program that addresses the interrelated issues of exposure, respiratory tract dose, carcinogenesis (molecular/cellular and animal studies, plus developing biological and statistical models), and the relationship of radon to smoking and other copollutant exposures. This article reviews experimental animal data on radon carcinogenesis observed primarily in rats at Pacific Northwest Laboratory. Recent experimental and mechanistic carcinogenesis models of exposures to radon, uranium ore dust, and cigarette smoke are presented with statistical analyses of animal data. 20 refs., 1 fig

  16. Nostalgia-Evoked Inspiration: Mediating Mechanisms and Motivational Implications.

    Science.gov (United States)

    Stephan, Elena; Sedikides, Constantine; Wildschut, Tim; Cheung, Wing-Yee; Routledge, Clay; Arndt, Jamie

    2015-10-01

    Six studies examined the nostalgia-inspiration link and its motivational implications. In Study 1, nostalgia proneness was positively associated with inspiration frequency and intensity. In Studies 2 and 3, the recollection of nostalgic (vs. ordinary) experiences increased both general inspiration and specific inspiration to engage in exploratory activities. In Study 4, serial mediational analyses supported a model in which nostalgia increases social connectedness, which subsequently fosters self-esteem, which then boosts inspiration. In Study 5, a rigorous evaluation of this serial mediational model (with a novel nostalgia induction controlling for positive affect) reinforced the idea that nostalgia-elicited social connectedness increases self-esteem, which then heightens inspiration. Study 6 extended the serial mediational model by demonstrating that nostalgia-evoked inspiration predicts goal pursuit (intentions to pursue an important goal). Nostalgia spawns inspiration via social connectedness and attendant self-esteem. In turn, nostalgia-evoked inspiration bolsters motivation. © 2015 by the Society for Personality and Social Psychology, Inc.

  17. Bridging Mechanistic and Phenomenological Models of Complex Biological Systems.

    Science.gov (United States)

    Transtrum, Mark K; Qiu, Peng

    2016-05-01

    The inherent complexity of biological systems gives rise to complicated mechanistic models with a large number of parameters. On the other hand, the collective behavior of these systems can often be characterized by a relatively small number of phenomenological parameters. We use the Manifold Boundary Approximation Method (MBAM) as a tool for deriving simple phenomenological models from complicated mechanistic models. The resulting models are not black boxes, but remain expressed in terms of the microscopic parameters. In this way, we explicitly connect the macroscopic and microscopic descriptions, characterize the equivalence class of distinct systems exhibiting the same range of collective behavior, and identify the combinations of components that function as tunable control knobs for the behavior. We demonstrate the procedure for adaptation behavior exhibited by the EGFR pathway. From a 48 parameter mechanistic model, the system can be effectively described by a single adaptation parameter τ characterizing the ratio of time scales for the initial response and recovery time of the system which can in turn be expressed as a combination of microscopic reaction rates, Michaelis-Menten constants, and biochemical concentrations. The situation is not unlike modeling in physics in which microscopically complex processes can often be renormalized into simple phenomenological models with only a few effective parameters. The proposed method additionally provides a mechanistic explanation for non-universal features of the behavior.

  18. A framework for modeling information propagation of biological systems at critical states.

    Science.gov (United States)

    Hu, Feng; Yang, Fang

    2016-03-01

    We explore the dynamics of information propagation at the critical state of a biologically inspired system by an individual-based computer model. "Quorum response", a type of social interaction which has been recognized taxonomically in animal groups, is applied as the sole interaction rule among individuals. In the model, we assume a truncated Gaussian distribution to depict the distribution of the individuals' vigilance level. Each individual can assume either a naïve state or an alarmed one and only switches from the former state to the latter one. If an individual has turned into an alarmed state, it stays in the state during the process of information propagation. Initially, each individual is set to be at the naïve state and information is tapped into the system by perturbing an individual at the boundaries (alerting it to the alarmed state). The system evolves as individuals turn into the alarmed state, according to the quorum response rules, consecutively. We find that by fine-tuning the parameters of the mean and the standard deviation of the Gaussian distribution, the system is poised at a critical state. We present the phase diagrams to exhibit that the parameter space is divided into a super-critical and a sub-critical zone, in which the dynamics of information propagation varies largely. We then investigate the effects of the individuals' mobility on the critical state, and allow a proportion of randomly chosen individuals to exchange their positions at each time step. We find that mobility breaks down criticality of the system. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  19. WORKSHOP ON APPLICATION OF STATISTICAL METHODS TO BIOLOGICALLY-BASED PHARMACOKINETIC MODELING FOR RISK ASSESSMENT

    Science.gov (United States)

    Biologically-based pharmacokinetic models are being increasingly used in the risk assessment of environmental chemicals. These models are based on biological, mathematical, statistical and engineering principles. Their potential uses in risk assessment include extrapolation betwe...

  20. Switchable bio-inspired adhesives

    Science.gov (United States)

    Kroner, Elmar

    2015-03-01

    Geckos have astonishing climbing abilities. They can adhere to almost any surface and can run on walls and even stick to ceilings. The extraordinary adhesion performance is caused by a combination of a complex surface pattern on their toes and the biomechanics of its movement. These biological dry adhesives have been intensely investigated during recent years because of the unique combination of adhesive properties. They provide high adhesion, allow for easy detachment, can be removed residue-free, and have self-cleaning properties. Many aspects have been successfully mimicked, leading to artificial, bio-inspired, patterned dry adhesives, and were addressed and in some aspects they even outperform the adhesion capabilities of geckos. However, designing artificial patterned adhesion systems with switchable adhesion remains a big challenge; the gecko's adhesion system is based on a complex hierarchical surface structure and on advanced biomechanics, which are both difficult to mimic. In this paper, two approaches are presented to achieve switchable adhesion. The first approach is based on a patterned polydimethylsiloxane (PDMS) polymer, where adhesion can be switched on and off by applying a low and a high compressive preload. The switch in adhesion is caused by a reversible mechanical instability of the adhesive silicone structures. The second approach is based on a composite material consisting of a Nickel- Titanium (NiTi) shape memory alloy and a patterned adhesive PDMS layer. The NiTi alloy is trained to change its surface topography as a function of temperature, which results in a change of the contact area and of alignment of the adhesive pattern towards a substrate, leading to switchable adhesion. These examples show that the unique properties of bio-inspired adhesives can be greatly improved by new concepts such as mechanical instability or by the use of active materials which react to external stimuli.

  1. Neural network models for biological waste-gas treatment systems.

    Science.gov (United States)

    Rene, Eldon R; Estefanía López, M; Veiga, María C; Kennes, Christian

    2011-12-15

    This paper outlines the procedure for developing artificial neural network (ANN) based models for three bioreactor configurations used for waste-gas treatment. The three bioreactor configurations chosen for this modelling work were: biofilter (BF), continuous stirred tank bioreactor (CSTB) and monolith bioreactor (MB). Using styrene as the model pollutant, this paper also serves as a general database of information pertaining to the bioreactor operation and important factors affecting gas-phase styrene removal in these biological systems. Biological waste-gas treatment systems are considered to be both advantageous and economically effective in treating a stream of polluted air containing low to moderate concentrations of the target contaminant, over a rather wide range of gas-flow rates. The bioreactors were inoculated with the fungus Sporothrix variecibatus, and their performances were evaluated at different empty bed residence times (EBRT), and at different inlet styrene concentrations (C(i)). The experimental data from these bioreactors were modelled to predict the bioreactors performance in terms of their removal efficiency (RE, %), by adequate training and testing of a three-layered back propagation neural network (input layer-hidden layer-output layer). Two models (BIOF1 and BIOF2) were developed for the BF with different combinations of easily measurable BF parameters as the inputs, that is concentration (gm(-3)), unit flow (h(-1)) and pressure drop (cm of H(2)O). The model developed for the CSTB used two inputs (concentration and unit flow), while the model for the MB had three inputs (concentration, G/L (gas/liquid) ratio, and pressure drop). Sensitivity analysis in the form of absolute average sensitivity (AAS) was performed for all the developed ANN models to ascertain the importance of the different input parameters, and to assess their direct effect on the bioreactors performance. The performance of the models was estimated by the regression

  2. Regulatory Impact Analysis Practice in New Zealand in the Light of Models of Evaluation Use – Inspiration for the Polish Government

    Directory of Open Access Journals (Sweden)

    Tomasz Kupiec

    2015-06-01

    Full Text Available Purpose: The paper describes the functioning of the RIA system in New Zealand using the analogy of RIA and the evaluation of public interventions. Presented solutions can provide nspiration for the Polish government in the process of improving the quality and extent of the use of RIA. Methodology: The analysis is based on a review of government documents and literature, as well as individual interviews and correspondence with representatives of the government of NZ. Conclusions: The RIA system in NZ is not error-free and its shortcomings include inter alia the lack of solutions with respect to ex-post analysis and insufficiently rigorous methodological approach. At the same time, a number of solutions can be regarded as good practice, e.g.: regular external quality reviews of RIS, obligation to supplement each RIS with ‘quality assessment’ and a ‘disclosure statement’ outlining their credibility and utility. Practical implications: The presented strengths of the RIA system in NZ may serve as an inspiration for modifying the RIA system in Poland. Originality: The RIA system is presented through the prism of the model of evaluation use, which is a related tool of collecting information about non-regulatory interventions.

  3. Continuous time Boolean modeling for biological signaling: application of Gillespie algorithm.

    OpenAIRE

    Stoll, Gautier; Viara, Eric; Barillot, Emmanuel; Calzone, Laurence

    2012-01-01

    Abstract Mathematical modeling is used as a Systems Biology tool to answer biological questions, and more precisely, to validate a network that describes biological observations and predict the effect of perturbations. This article presents an algorithm for modeling biological networks in a discrete framework with continuous time. Background There exist two major types of mathematical modeling approaches: (1) quantitative modeling, representing various chemical species concentrations by real...

  4. Modeling human risk: Cell & molecular biology in context

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-06-01

    It is anticipated that early in the next century manned missions into outer space will occur, with a mission to Mars scheduled between 2015 and 2020. However, before such missions can be undertaken, a realistic estimation of the potential risks to the flight crews is required. One of the uncertainties remaining in this risk estimation is that posed by the effects of exposure to the radiation environment of outer space. Although the composition of this environment is fairly well understood, the biological effects arising from exposure to it are not. The reasons for this are three-fold: (1) A small but highly significant component of the radiation spectrum in outer space consists of highly charged, high energy (HZE) particles which are not routinely experienced on earth, and for which there are insufficient data on biological effects; (2) Most studies on the biological effects of radiation to date have been high-dose, high dose-rate, whereas in space, with the exception of solar particle events, radiation exposures will be low-dose, low dose-rate; (3) Although it has been established that the virtual absence of gravity in space has a profound effect on human physiology, it is not clear whether these effects will act synergistically with those of radiation exposure. A select panel will evaluate the utilizing experiments and models to accurately predict the risks associated with exposure to HZE particles. Topics of research include cellular and tissue response, health effects associated with radiation damage, model animal systems, and critical markers of Radiation response.

  5. Modeling human risk: Cell ampersand molecular biology in context

    International Nuclear Information System (INIS)

    1997-06-01

    It is anticipated that early in the next century manned missions into outer space will occur, with a mission to Mars scheduled between 2015 and 2020. However, before such missions can be undertaken, a realistic estimation of the potential risks to the flight crews is required. One of the uncertainties remaining in this risk estimation is that posed by the effects of exposure to the radiation environment of outer space. Although the composition of this environment is fairly well understood, the biological effects arising from exposure to it are not. The reasons for this are three-fold: (1) A small but highly significant component of the radiation spectrum in outer space consists of highly charged, high energy (HZE) particles which are not routinely experienced on earth, and for which there are insufficient data on biological effects; (2) Most studies on the biological effects of radiation to date have been high-dose, high dose-rate, whereas in space, with the exception of solar particle events, radiation exposures will be low-dose, low dose-rate; (3) Although it has been established that the virtual absence of gravity in space has a profound effect on human physiology, it is not clear whether these effects will act synergistically with those of radiation exposure. A select panel will evaluate the utilizing experiments and models to accurately predict the risks associated with exposure to HZE particles. Topics of research include cellular and tissue response, health effects associated with radiation damage, model animal systems, and critical markers of Radiation response

  6. Fluctuating Nonlinear Spring Model of Mechanical Deformation of Biological Particles.

    Directory of Open Access Journals (Sweden)

    Olga Kononova

    2016-01-01

    Full Text Available The mechanical properties of virus capsids correlate with local conformational dynamics in the capsid structure. They also reflect the required stability needed to withstand high internal pressures generated upon genome loading and contribute to the success of important events in viral infectivity, such as capsid maturation, genome uncoating and receptor binding. The mechanical properties of biological nanoparticles are often determined from monitoring their dynamic deformations in Atomic Force Microscopy nanoindentation experiments; but a comprehensive theory describing the full range of observed deformation behaviors has not previously been described. We present a new theory for modeling dynamic deformations of biological nanoparticles, which considers the non-linear Hertzian deformation, resulting from an indenter-particle physical contact, and the bending of curved elements (beams modeling the particle structure. The beams' deformation beyond the critical point triggers a dynamic transition of the particle to the collapsed state. This extreme event is accompanied by a catastrophic force drop as observed in the experimental or simulated force (F-deformation (X spectra. The theory interprets fine features of the spectra, including the nonlinear components of the FX-curves, in terms of the Young's moduli for Hertzian and bending deformations, and the structural damage dependent beams' survival probability, in terms of the maximum strength and the cooperativity parameter. The theory is exemplified by successfully describing the deformation dynamics of natural nanoparticles through comparing theoretical curves with experimental force-deformation spectra for several virus particles. This approach provides a comprehensive description of the dynamic structural transitions in biological and artificial nanoparticles, which is essential for their optimal use in nanotechnology and nanomedicine applications.

  7. Precise generation of systems biology models from KEGG pathways.

    Science.gov (United States)

    Wrzodek, Clemens; Büchel, Finja; Ruff, Manuel; Dräger, Andreas; Zell, Andreas

    2013-02-21

    The KEGG PATHWAY database provides a plethora of pathways for a diversity of organisms. All pathway components are directly linked to other KEGG databases, such as KEGG COMPOUND or KEGG REACTION. Therefore, the pathways can be extended with an enormous amount of information and provide a foundation for initial structural modeling approaches. As a drawback, KGML-formatted KEGG pathways are primarily designed for visualization purposes and often omit important details for the sake of a clear arrangement of its entries. Thus, a direct conversion into systems biology models would produce incomplete and erroneous models. Here, we present a precise method for processing and converting KEGG pathways into initial metabolic and signaling models encoded in the standardized community pathway formats SBML (Levels 2 and 3) and BioPAX (Levels 2 and 3). This method involves correcting invalid or incomplete KGML content, creating complete and valid stoichiometric reactions, translating relations to signaling models and augmenting the pathway content with various information, such as cross-references to Entrez Gene, OMIM, UniProt ChEBI, and many more.Finally, we compare several existing conversion tools for KEGG pathways and show that the conversion from KEGG to BioPAX does not involve a loss of information, whilst lossless translations to SBML can only be performed using SBML Level 3, including its recently proposed qualitative models and groups extension packages. Building correct BioPAX and SBML signaling models from the KEGG database is a unique characteristic of the proposed method. Further, there is no other approach that is able to appropriately construct metabolic models from KEGG pathways, including correct reactions with stoichiometry. The resulting initial models, which contain valid and comprehensive SBML or BioPAX code and a multitude of cross-references, lay the foundation to facilitate further modeling steps.

  8. Automated parameter estimation for biological models using Bayesian statistical model checking.

    Science.gov (United States)

    Hussain, Faraz; Langmead, Christopher J; Mi, Qi; Dutta-Moscato, Joyeeta; Vodovotz, Yoram; Jha, Sumit K

    2015-01-01

    Probabilistic models have gained widespread acceptance in the systems biology community as a useful way to represent complex biological systems. Such models are developed using existing knowledge of the structure and dynamics of the system, experimental observations, and inferences drawn from statistical analysis of empirical data. A key bottleneck in building such models is that some system variables cannot be measured experimentally. These variables are incorporated into the model as numerical parameters. Determining values of these parameters that justify existing experiments and provide reliable predictions when model simulations are performed is a key research problem. Using an agent-based model of the dynamics of acute inflammation, we demonstrate a novel parameter estimation algorithm by discovering the amount and schedule of doses of bacterial lipopolysaccharide that guarantee a set of observed clinical outcomes with high probability. We synthesized values of twenty-eight unknown parameters such that the parameterized model instantiated with these parameter values satisfies four specifications describing the dynamic behavior of the model. We have developed a new algorithmic technique for discovering parameters in complex stochastic models of biological systems given behavioral specifications written in a formal mathematical logic. Our algorithm uses Bayesian model checking, sequential hypothesis testing, and stochastic optimization to automatically synthesize parameters of probabilistic biological models.

  9. Bayesian Network Webserver: a comprehensive tool for biological network modeling.

    Science.gov (United States)

    Ziebarth, Jesse D; Bhattacharya, Anindya; Cui, Yan

    2013-11-01

    The Bayesian Network Webserver (BNW) is a platform for comprehensive network modeling of systems genetics and other biological datasets. It allows users to quickly and seamlessly upload a dataset, learn the structure of the network model that best explains the data and use the model to understand relationships between network variables. Many datasets, including those used to create genetic network models, contain both discrete (e.g. genotype) and continuous (e.g. gene expression traits) variables, and BNW allows for modeling hybrid datasets. Users of BNW can incorporate prior knowledge during structure learning through an easy-to-use structural constraint interface. After structure learning, users are immediately presented with an interactive network model, which can be used to make testable hypotheses about network relationships. BNW, including a downloadable structure learning package, is available at http://compbio.uthsc.edu/BNW. (The BNW interface for adding structural constraints uses HTML5 features that are not supported by current version of Internet Explorer. We suggest using other browsers (e.g. Google Chrome or Mozilla Firefox) when accessing BNW). ycui2@uthsc.edu. Supplementary data are available at Bioinformatics online.

  10. Chimeric animal models in human stem cell biology.

    Science.gov (United States)

    Glover, Joel C; Boulland, Jean-Luc; Halasi, Gabor; Kasumacic, Nedim

    2009-01-01

    The clinical use of stem cells for regenerative medicine is critically dependent on preclinical studies in animal models. In this review we examine some of the key issues and challenges in the use of animal models to study human stem cell biology-experimental standardization, body size, immunological barriers, cell survival factors, fusion of host and donor cells, and in vivo imaging and tracking. We focus particular attention on the various imaging modalities that can be used to track cells in living animals, comparing their strengths and weaknesses and describing technical developments that are likely to lead to new opportunities for the dynamic assessment of stem cell behavior in vivo. We then provide an overview of some of the most commonly used animal models, their advantages and disadvantages, and examples of their use for xenotypic transplantation of human stem cells, with separate reviews of models involving rodents, ungulates, nonhuman primates, and the chicken embryo. As the use of human somatic, embryonic, and induced pluripotent stem cells increases, so too will the range of applications for these animal models. It is likely that increasingly sophisticated uses of human/animal chimeric models will be developed through advances in genetic manipulation, cell delivery, and in vivo imaging.

  11. Naumovozyma castellii: an alternative model for budding yeast molecular biology.

    Science.gov (United States)

    Karademir Andersson, Ahu; Cohn, Marita

    2017-03-01

    Naumovozyma castellii (Saccharomyces castellii) is a member of the budding yeast family Saccharomycetaceae. It has been extensively used as a model organism for telomere biology research and has gained increasing interest as a budding yeast model for functional analyses owing to its amenability to genetic modifications. Owing to the suitable phylogenetic distance to S. cerevisiae, the whole genome sequence of N. castellii has provided unique data for comparative genomic studies, and it played a key role in the establishment of the timing of the whole genome duplication and the evolutionary events that took place in the subsequent genomic evolution of the Saccharomyces lineage. Here we summarize the historical background of its establishment as a laboratory yeast species, and the development of genetic and molecular tools and strains. We review the research performed on N. castellii, focusing on areas where it has significantly contributed to the discovery of new features of molecular biology and to the advancement of our understanding of molecular evolution. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  12. Nature as an engineer: one simple concept of a bio-inspired functional artificial muscle

    International Nuclear Information System (INIS)

    Schmitt, S; Haeufle, D F B; Günther, M; Blickhan, R

    2012-01-01

    The biological muscle is a powerful, flexible and versatile actuator. Its intrinsic characteristics determine the way how movements are generated and controlled. Robotic and prosthetic applications expect to profit from relying on bio-inspired actuators which exhibit natural (muscle-like) characteristics. As of today, when constructing a technical actuator, it is not possible to copy the exact molecular structure of a biological muscle. Alternatively, the question may be put how its characteristics can be realized with known mechanical components. Recently, a mechanical construct for an artificial muscle was proposed, which exhibits hyperbolic force–velocity characteristics. In this paper, we promote the constructing concept which is made by substantiating the mechanical design of biological muscle by a simple model, proving the feasibility of its real-world implementation, and checking their output both for mutual consistency and agreement with biological measurements. In particular, the relations of force, enthalpy rate and mechanical efficiency versus contraction velocity of both the construct’s technical implementation and its numerical model were determined in quick-release experiments. All model predictions for these relations and the hardware results are now in good agreement with the biological literature. We conclude that the construct represents a mechanical concept of natural actuation, which is suitable for laying down some useful suggestions when designing bio-inspired actuators. (paper)

  13. Nature as an engineer: one simple concept of a bio-inspired functional artificial muscle.

    Science.gov (United States)

    Schmitt, S; Haeufle, D F B; Blickhan, R; Günther, M

    2012-09-01

    The biological muscle is a powerful, flexible and versatile actuator. Its intrinsic characteristics determine the way how movements are generated and controlled. Robotic and prosthetic applications expect to profit from relying on bio-inspired actuators which exhibit natural (muscle-like) characteristics. As of today, when constructing a technical actuator, it is not possible to copy the exact molecular structure of a biological muscle. Alternatively, the question may be put how its characteristics can be realized with known mechanical components. Recently, a mechanical construct for an artificial muscle was proposed, which exhibits hyperbolic force-velocity characteristics. In this paper, we promote the constructing concept which is made by substantiating the mechanical design of biological muscle by a simple model, proving the feasibility of its real-world implementation, and checking their output both for mutual consistency and agreement with biological measurements. In particular, the relations of force, enthalpy rate and mechanical efficiency versus contraction velocity of both the construct's technical implementation and its numerical model were determined in quick-release experiments. All model predictions for these relations and the hardware results are now in good agreement with the biological literature. We conclude that the construct represents a mechanical concept of natural actuation, which is suitable for laying down some useful suggestions when designing bio-inspired actuators.

  14. A teaching skills assessment tool inspired by the Calgary-Cambridge model and the patient-centered approach.

    Science.gov (United States)

    Sommer, Johanna; Lanier, Cédric; Perron, Noelle Junod; Nendaz, Mathieu; Clavet, Diane; Audétat, Marie-Claude

    2016-04-01

    The aim of this study was to develop a descriptive tool for peer review of clinical teaching skills. Two analogies framed our research: (1) between the patient-centered and the learner-centered approach; (2) between the structures of clinical encounters (Calgary-Cambridge communication model) and teaching sessions. During the course of one year, each step of the action research was carried out in collaboration with twelve clinical teachers from an outpatient general internal medicine clinic and with three experts in medical education. The content validation consisted of a literature review, expert opinion and the participatory research process. Interrater reliability was evaluated by three clinical teachers coding thirty audiotaped standardized learner-teacher interactions. This tool contains sixteen items covering the process and content of clinical supervisions. Descriptors define the expected teaching behaviors for three levels of competence. Interrater reliability was significant for eleven items (Kendall's coefficient pteaching skills. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  15. An inequality relating gauge group coupling constants and the number of generations in a string inspired model

    International Nuclear Information System (INIS)

    Nielsen, H.B.; Bennett, D.L.

    1987-12-01

    Using a model with a regularized (e.g. latticized) Kaluza-Klein space-time at the fundamental scale with Yang-Mills fields in the compactified dimensions, we examine the β-function for a dimensionless expression for the coupling constants g in D-dimensions. In going from the Planck scale of D > 4 down in energy to the scale where D goes from D > 4 to D = 4, it is argued that couplings are weakened by a factor roughly equal to the number of fundamental string regions that can be accommadated in the volume of the compactification space. Subsequently this factor is claimed to be greater than the number of generations by using an argument reminiscent of that often encountered in string model T.O.E. in which various quark and lepton generations are said to correspond to various zero modes of a Weyl operator in the compactifying space. Finally, it is argued that the inequality, which can be shown to be more saturated the larger the gauge group, is already near saturation for the group factors of the SMG. This fact leads to several conclusions: 1. there is not room for many more than 3 generations; 2. G.U.T. can be accommadated only at scales very close to the fundamental scale; 3. No new blossoms are expected to be found in the desert; 4. the compactifying space should not be 'larger than necessary'; 5. at the fundamental scale, couplings are expected to be close to (but not suspiciousely close to) β crit. . (orig./HSI)

  16. Mass balances for a biological life support system simulation model

    Science.gov (United States)

    Volk, Tyler; Rummel, John D.

    1987-01-01

    Design decisions to aid the development of future space based biological life support systems (BLSS) can be made with simulation models. The biochemistry stoichiometry was developed for: (1) protein, carbohydrate, fat, fiber, and lignin production in the edible and inedible parts of plants; (2) food consumption and production of organic solids in urine, feces, and wash water by the humans; and (3) operation of the waste processor. Flux values for all components are derived for a steady state system with wheat as the sole food source. The large scale dynamics of a materially closed (BLSS) computer model is described in a companion paper. An extension of this methodology can explore multifood systems and more complex biochemical dynamics while maintaining whole system closure as a focus.

  17. Introduction to mathematical biology modeling, analysis, and simulations

    CERN Document Server

    Chou, Ching Shan

    2016-01-01

    This book is based on a one semester course that the authors have been teaching for several years, and includes two sets of case studies. The first includes chemostat models, predator-prey interaction, competition among species, the spread of infectious diseases, and oscillations arising from bifurcations. In developing these topics, readers will also be introduced to the basic theory of ordinary differential equations, and how to work with MATLAB without having any prior programming experience. The second set of case studies were adapted from recent and current research papers to the level of the students. Topics have been selected based on public health interest. This includes the risk of atherosclerosis associated with high cholesterol levels, cancer and immune interactions, cancer therapy, and tuberculosis. Readers will experience how mathematical models and their numerical simulations can provide explanations that guide biological and biomedical research. Considered to be the undergraduate companion to t...

  18. #IWD2016 Academic Inspiration

    DEFF Research Database (Denmark)

    Meier, Ninna

    2016-01-01

    What academics or books have inspired you in your writing and research, or helped to make sense of the world around you? In this feature essay, Ninna Meier returns to her experience of reading Hannah Arendt as she sought to understand work and how it relates to value production in capitalist...... economies. Meier recounts how Arendt’s book On Revolution (1963) forged connective threads between the ‘smallest parts’ and the ‘largest wholes’ and showed how academic work is never fully relegated to the past, but can return in new iterations across time....

  19. Thermodynamic modeling of transcription: sensitivity analysis differentiates biological mechanism from mathematical model-induced effects.

    Science.gov (United States)

    Dresch, Jacqueline M; Liu, Xiaozhou; Arnosti, David N; Ay, Ahmet

    2010-10-24

    Quantitative models of gene expression generate parameter values that can shed light on biological features such as transcription factor activity, cooperativity, and local effects of repressors. An important element in such investigations is sensitivity analysis, which determines how strongly a model's output reacts to variations in parameter values. Parameters of low sensitivity may not be accurately estimated, leading to unwarranted conclusions. Low sensitivity may reflect the nature of the biological data, or it may be a result of the model structure. Here, we focus on the analysis of thermodynamic models, which have been used extensively to analyze gene transcription. Extracted parameter values have been interpreted biologically, but until now little attention has been given to parameter sensitivity in this context. We apply local and global sensitivity analyses to two recent transcriptional models to determine the sensitivity of individual parameters. We show that in one case, values for repressor efficiencies are very sensitive, while values for protein cooperativities are not, and provide insights on why these differential sensitivities stem from both biological effects and the structure of the applied models. In a second case, we demonstrate that parameters that were thought to prove the system's dependence on activator-activator cooperativity are relatively insensitive. We show that there are numerous parameter sets that do not satisfy the relationships proferred as the optimal solutions, indicating that structural differences between the two types of transcriptional enhancers analyzed may not be as simple as altered activator cooperativity. Our results emphasize the need for sensitivity analysis to examine model construction and forms of biological data used for modeling transcriptional processes, in order to determine the significance of estimated parameter values for thermodynamic models. Knowledge of parameter sensitivities can provide the necessary

  20. A Color-Opponency Based Biological Model for Color Constancy

    Directory of Open Access Journals (Sweden)

    Yongjie Li

    2011-05-01

    Full Text Available Color constancy is the ability of the human visual system to adaptively correct color-biased scenes under different illuminants. Most of the existing color constancy models are nonphysiologically plausible. Among the limited biological models, the great majority is Retinex and its variations, and only two or three models directly simulate the feature of color-opponency, but only of the very earliest stages of visual pathway, i.e., the single-opponent mechanisms involved at the levels of retinal ganglion cells and lateral geniculate nucleus (LGN neurons. Considering the extensive physiological evidences supporting that both the single-opponent cells in retina and LGN and the double-opponent neurons in primary visual cortex (V1 are the building blocks for color constancy, in this study we construct a color-opponency based color constancy model by simulating the opponent fashions of both the single-opponent and double-opponent cells in a forward manner. As for the spatial structure of the receptive fields (RF, both the classical RF (CRF center and the nonclassical RF (nCRF surround are taken into account for all the cells. The proposed model was tested on several typical image databases commonly used for performance evaluation of color constancy methods, and exciting results were achieved.