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Sample records for biologically inspired model

  1. A biologically inspired model for pattern recognition*

    OpenAIRE

    Gonzalez, Eduardo; Liljenström, Hans; Ruiz, Yusely; Li, Guang

    2010-01-01

    In this paper, a novel bionic model and its performance in pattern recognition are presented and discussed. The model is constructed from a bulb model and a three-layered cortical model, mimicking the main features of the olfactory system. The olfactory bulb and cortex models are connected by feedforward and feedback fibers with distributed delays. The Breast Cancer Wisconsin dataset consisting of data from 683 patients divided into benign and malignant classes is used to demonstrate the capa...

  2. Biologically inspired optics: analog semiconductor model of the beetle exoskeleton

    Science.gov (United States)

    Buhl, Kaia; Roth, Zachary; Srinivasan, Pradeep; Rumpf, Raymond; Johnson, Eric

    2008-08-01

    Evolution in nature has produced through adaptation a wide variety of distinctive optical structures in many life forms. For example, pigment differs greatly from the observed color of most beetles because their exoskeletons contain multilayer coatings. The green beetle is disguised in a surrounding leaf by having a comparable reflection spectrum as the leaves. The Manuka and June beetle have a concave structure where light incident at any angle on the concave structures produce matching reflection spectra. In this work, semiconductor processing methods were used to duplicate the structure of the beetle exoskeleton. This was achieved by combining analog lithography with a multilayer deposition process. The artificial exoskeleton, 3D concave multilayer structure, demonstrates a wide field of view with a unique spectral response. Studying and replicating these biologically inspired nanostructures may lead to new knowledge for fabrication and design of new and novel nano-photonic devices, as well as provide valuable insight to how such phenomenon is exploited.

  3. A Biologically Inspired Classifier

    CERN Document Server

    Bagnoli, Franco

    2007-01-01

    We present a method for measuring the distance among records based on the correlations of data stored in the corresponding database entries. The original method (F. Bagnoli, A. Berrones and F. Franci. Physica A 332 (2004) 509-518) was formulated in the context of opinion formation. The opinions expressed over a set of topic originate a ``knowledge network'' among individuals, where two individuals are nearer the more similar their expressed opinions are. Assuming that individuals' opinions are stored in a database, the authors show that it is possible to anticipate an opinion using the correlations in the database. This corresponds to approximating the overlap between the tastes of two individuals with the correlations of their expressed opinions. In this paper we extend this model to nonlinear matching functions, inspired by biological problems such as microarray (probe-sample pairing). We investigate numerically the error between the correlation and the overlap matrix for eight sequences of reference with r...

  4. A new shoulder model with a biologically inspired glenohumeral joint.

    Science.gov (United States)

    Quental, C; Folgado, J; Ambrósio, J; Monteiro, J

    2016-09-01

    Kinematically unconstrained biomechanical models of the glenohumeral (GH) joint are needed to study the GH joint function, especially the mechanisms of joint stability. The purpose of this study is to develop a large-scale multibody model of the upper limb that simulates the 6 degrees of freedom (DOF) of the GH joint and to propose a novel inverse dynamics procedure that allows the evaluation of not only the muscle and joint reaction forces of the upper limb but also the GH joint translations. The biomechanical model developed is composed of 7 rigid bodies, constrained by 6 anatomical joints, and acted upon by 21 muscles. The GH joint is described as a spherical joint with clearance. Assuming that the GH joint translates according to the muscle load distribution, the redundant muscle load sharing problem is formulated considering as design variables the 3 translational coordinates associated with the GH joint translations, the joint reaction forces associated with the remaining kinematic constraints, and the muscle activations. For the abduction motion in the frontal plane analysed, the muscle and joint reaction forces estimated by the new biomechanical model proposed are similar to those estimated by a model in which the GH joint is modeled as an ideal spherical joint. Even though this result supports the assumption of an ideal GH joint to study the muscle load sharing problem, only a 6 DOF model of the GH joint, as the one proposed here, provides information regarding the joint translations. In this study, the biomechanical model developed predicts an initial upward and posterior migration of the humeral head, followed by an inferior and anterior movement, which is in good agreement with the literature. PMID:27381499

  5. Robust Models for Optic Flow Coding in Natural Scenes Inspired by Insect Biology

    OpenAIRE

    Russell S A Brinkworth; David C O'Carroll

    2009-01-01

    The extraction of accurate self-motion information from the visual world is a difficult problem that has been solved very efficiently by biological organisms utilizing non-linear processing. Previous bio-inspired models for motion detection based on a correlation mechanism have been dogged by issues that arise from their sensitivity to undesired properties of the image, such as contrast, which vary widely between images. Here we present a model with multiple levels of non-linear dynamic adapt...

  6. Biologically-inspired machine vision

    OpenAIRE

    Tsitiridis, A

    2013-01-01

    This thesis summarises research on the improved design, integration and expansion of past cortex-like computer vision models, following biologically-inspired methodologies. By adopting early theories and algorithms as a building block, particular interest has been shown for algorithmic parameterisation, feature extraction, invariance properties and classification. Overall, the major original contributions of this thesis have been: 1. The incorporation of a salient feature-based method for sem...

  7. Biologically Inspired Model for Inference of 3D Shape from Texture.

    Science.gov (United States)

    Gomez, Olman; Neumann, Heiko

    2016-01-01

    A biologically inspired model architecture for inferring 3D shape from texture is proposed. The model is hierarchically organized into modules roughly corresponding to visual cortical areas in the ventral stream. Initial orientation selective filtering decomposes the input into low-level orientation and spatial frequency representations. Grouping of spatially anisotropic orientation responses builds sketch-like representations of surface shape. Gradients in orientation fields and subsequent integration infers local surface geometry and globally consistent 3D depth. From the distributions in orientation responses summed in frequency, an estimate of the tilt and slant of the local surface can be obtained. The model suggests how 3D shape can be inferred from texture patterns and their image appearance in a hierarchically organized processing cascade along the cortical ventral stream. The proposed model integrates oriented texture gradient information that is encoded in distributed maps of orientation-frequency representations. The texture energy gradient information is defined by changes in the grouped summed normalized orientation-frequency response activity extracted from the textured object image. This activity is integrated by directed fields to generate a 3D shape representation of a complex object with depth ordering proportional to the fields output, with higher activity denoting larger distance in relative depth away from the viewer.

  8. Biologically Inspired Model for Inference of 3D Shape from Texture.

    Science.gov (United States)

    Gomez, Olman; Neumann, Heiko

    2016-01-01

    A biologically inspired model architecture for inferring 3D shape from texture is proposed. The model is hierarchically organized into modules roughly corresponding to visual cortical areas in the ventral stream. Initial orientation selective filtering decomposes the input into low-level orientation and spatial frequency representations. Grouping of spatially anisotropic orientation responses builds sketch-like representations of surface shape. Gradients in orientation fields and subsequent integration infers local surface geometry and globally consistent 3D depth. From the distributions in orientation responses summed in frequency, an estimate of the tilt and slant of the local surface can be obtained. The model suggests how 3D shape can be inferred from texture patterns and their image appearance in a hierarchically organized processing cascade along the cortical ventral stream. The proposed model integrates oriented texture gradient information that is encoded in distributed maps of orientation-frequency representations. The texture energy gradient information is defined by changes in the grouped summed normalized orientation-frequency response activity extracted from the textured object image. This activity is integrated by directed fields to generate a 3D shape representation of a complex object with depth ordering proportional to the fields output, with higher activity denoting larger distance in relative depth away from the viewer. PMID:27649387

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

    Science.gov (United States)

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

    2014-03-01

    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. PMID:24451164

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

    International Nuclear Information System (INIS)

    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)

  11. 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

  12. 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. PMID:21527730

  13. 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.

  14. 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.

  15. A Biologically Inspired Model of Distributed Online Communication Supporting Efficient Search and Diffusion of Innovation

    Directory of Open Access Journals (Sweden)

    Soumya Baneerjee

    2016-01-01

    Full Text Available We inhabit a world that is not only “small” but supports efficient decentralized search – an individual using local information can establish a line of communication with another completely unknown individual. Here we augment a hierarchical social network model with communication between and within communities. We argue that organization into communities would decrease overall decentralized search times. We take inspiration from the biological immune system which organizes search for pathogens in a hybrid modular strategy. Our strategy has relevance in search for rare amounts of information in online social networks and could have implications for massively distributed search challenges. Our work also has implications for design of efficient online networks that could have an impact on networks of human collaboration, scientific collaboration and networks used in targeted manhunts. Real world systems, like online social networks, have high associated delays for long-distance links, since they are built on top of physical networks. Such systems have been shown to densify i.e. the average number of neighbours that an individual has increases with time. Hence such networks will have a communication cost due to space and the requirement of building and maintaining and increasing number of connections. We have incorporated such a non-spatial cost to communication in order to introduce the realism of individuals communicating within communities, which we call participation cost. We introduce the notion of a community size that increases with the size of the system, which is shown to reduce the time to search for information in networks. Our final strategy balances search times and participation costs and is shown to decrease time to find information in decentralized search in online social networks. Our strategy also balances strong-ties (within communities and weak-ties over long distances (between communities that bring in diverse ideas and

  16. 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

  17. Biological Inspiration in Human Centred Robotics

    Institute of Scientific and Technical Information of China (English)

    HUHuo-sheng; LIUJin-dong; CalderonCarlosA

    2004-01-01

    Human centred robotics (HCR) concerns with the development of various kinds of intelligent systems and robots that will be used in environments coexisting with humans. These systems and robots will be interactive and useful assistants/companions for people in different ages, situations, activities and environments in order to improve the quality of life. This paper presents the autors' current research work toward the development of advanced theory and technologies for HCR applications, based on inspiration from biological systems. More specifically, both bio-mimetic system modelling and robot learning by imitation are discussed respectively, and some preliminary results are demonstrated.

  18. 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.

  19. 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.

  20. 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. PMID:26196087

  1. Biologically Inspired Mushroom-Shaped Adhesive Microstructures

    Science.gov (United States)

    Heepe, Lars; Gorb, Stanislav N.

    2014-07-01

    Adhesion is a fundamental phenomenon with great importance in technology, in our everyday life, and in nature. In this article, we review physical interactions that resist the separation of two solids in contact. By using examples of biological attachment systems, we summarize and categorize various principles that contribute to the so-called gecko effect. Emphasis is placed on the contact geometry and in particular on the mushroom-shaped geometry, which is observed in long-term biological adhesive systems. Furthermore, we report on artificial model systems with this bio-inspired geometry and demonstrate that surface microstructures with this geometry are promising candidates for technical applications, in which repeatable, reversible, and residue-free adhesion under different environmental conditions—such as air, fluid, and vacuum—is required. Various applications in robotic systems and in industrial pick-and-place processes are discussed.

  2. How can selection of biologically inspired features improve the performance of a robust object recognition model?

    Directory of Open Access Journals (Sweden)

    Masoud Ghodrati

    Full Text Available Humans can effectively and swiftly recognize objects in complex natural scenes. This outstanding ability has motivated many computational object recognition models. Most of these models try to emulate the behavior of this remarkable system. The human visual system hierarchically recognizes objects in several processing stages. Along these stages a set of features with increasing complexity is extracted by different parts of visual system. Elementary features like bars and edges are processed in earlier levels of visual pathway and as far as one goes upper in this pathway more complex features will be spotted. It is an important interrogation in the field of visual processing to see which features of an object are selected and represented by the visual cortex. To address this issue, we extended a hierarchical model, which is motivated by biology, for different object recognition tasks. In this model, a set of object parts, named patches, extracted in the intermediate stages. These object parts are used for training procedure in the model and have an important role in object recognition. These patches are selected indiscriminately from different positions of an image and this can lead to the extraction of non-discriminating patches which eventually may reduce the performance. In the proposed model we used an evolutionary algorithm approach to select a set of informative patches. Our reported results indicate that these patches are more informative than usual random patches. We demonstrate the strength of the proposed model on a range of object recognition tasks. The proposed model outperforms the original model in diverse object recognition tasks. It can be seen from the experiments that selected features are generally particular parts of target images. Our results suggest that selected features which are parts of target objects provide an efficient set for robust object recognition.

  3. 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.

  4. Biologically inspired emotion recognition from speech

    Science.gov (United States)

    Caponetti, Laura; Buscicchio, Cosimo Alessandro; Castellano, Giovanna

    2011-12-01

    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.

  5. 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.

  6. Biologically inspired self-organizing networks

    Institute of Scientific and Technical Information of China (English)

    Naoki WAKAMIYA; Kenji LEIBNITZ; Masayuki MURATA

    2009-01-01

    Information networks are becoming more and more complex to accommodate a continuously increasing amount of traffic and networked devices, as well as having to cope with a growing diversity of operating environments and applications. Therefore, it is foreseeable that future information networks will frequently face unexpected problems, some of which could lead to the complete collapse of a network. To tackle this problem, recent attempts have been made to design novel network architectures which achieve a high level of scalability, adaptability, and robustness by taking inspiration from self-organizing biological systems. The objective of this paper is to discuss biologically inspired networking technologies.

  7. How physics can inspire biology

    Science.gov (United States)

    Kornyshev, Alexei

    2009-07-01

    In July 1997 Adrian Parsegian, a biophysicist at the National Institutes of Health in the US and a former president of the Biophysical Society, published an article in Physics Today in which he outlined his thoughts about the main obstacles to a happy marriage between physics and biology. Parsegian started his article with a joke about a physicist talking to his biology-trained friend.

  8. A biologically inspired MANET architecture

    Science.gov (United States)

    Kershenbaum, Aaron; Pappas, Vasileios; Lee, Kang-Won; Lio, Pietro; Sadler, Brian; Verma, Dinesh

    2008-04-01

    Mobile Ad-Hoc Networks (MANETs), that do not rely on pre-existing infrastructure and that can adapt rapidly to changes in their environment, are coming into increasingly wide use in military applications. At the same time, the large computing power and memory available today even for small, mobile devices, allows us to build extremely large, sophisticated and complex networks. Such networks, however, and the software controlling them are potentially vulnerable to catastrophic failures because of their size and complexity. Biological networks have many of these same characteristics and are potentially subject to the same problems. But in successful organisms, these biological networks do in fact function well so that the organism can survive. In this paper, we present a MANET architecture developed based on a feature, called homeostasis, widely observed in biological networks but not ordinarily seen in computer networks. This feature allows the network to switch to an alternate mode of operation under stress or attack and then return to the original mode of operation after the problem has been resolved. We explore the potential benefits such an architecture has, principally in terms of the ability to survive radical changes in its environment using an illustrative example.

  9. 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

  10. Additive manufacturing of biologically-inspired materials.

    Science.gov (United States)

    Studart, André R

    2016-01-21

    Additive manufacturing (AM) technologies offer an attractive pathway towards the fabrication of functional materials featuring complex heterogeneous architectures inspired by biological systems. In this paper, recent research on the use of AM approaches to program the local chemical composition, structure and properties of biologically-inspired materials is reviewed. A variety of structural motifs found in biological composites have been successfully emulated in synthetic systems using inkjet-based, direct-writing, stereolithography and slip casting technologies. The replication in synthetic systems of design principles underlying such structural motifs has enabled the fabrication of lightweight cellular materials, strong and tough composites, soft robots and autonomously shaping structures with unprecedented properties and functionalities. Pushing the current limits of AM technologies in future research should bring us closer to the manufacturing capabilities of living organisms, opening the way for the digital fabrication of advanced materials with superior performance, lower environmental impact and new functionalities. PMID:26750617

  11. Mathematical modeling and simulation of biologically inspired hair receptor arrays in laminar unsteady flow separation

    Science.gov (United States)

    Dickinson, B. T.; Singler, J. R.; Batten, B. A.

    2012-02-01

    Bats possess arrays of distributed flow-sensitive hair-like mechanoreceptors on their dorsal and ventral wing surfaces. Bat wing hair receptors are known to play a significant role in flight maneuverability and are directionally most sensitive to reversed flow over the wing. In this work, we consider the mechanics of flexible hair-like structures for the time accurate detection and visualization of hydrodynamic images associated with unsteady near surface flow phenomena. A nonlinear viscoelastic model of a hair-like structure coupled to an unsteady nonuniform flow is proposed. Writing the hair model in nondimensional form, we identify five dimensionless groups that govern hair behavior. An order of magnitude analysis of the physical forces involved in the fluid-structure hair response is performed. Through the choice of hair material properties, we show how a local measure of near surface flow velocity may be obtained from hair tip displacement and resultant moment. When hair structures are placed into an array, time and space accurate hydrodynamic images may be obtained. We illustrate the imaging of reversed flow that occurs during a laminar unsteady flow separation with an array of hair-like structures.

  12. Biologically inspired intelligent decision making

    OpenAIRE

    Manning, Timmy; Sleator, Roy D.; Walsh, Paul

    2013-01-01

    Artificial neural networks (ANNs) are a class of powerful machine learning models for classification and function approximation which have analogs in nature. An ANN learns to map stimuli to responses through repeated evaluation of exemplars of the mapping. This learning approach results in networks which are recognized for their noise tolerance and ability to generalize meaningful responses for novel stimuli. It is these properties of ANNs which make them appealing for applications to bioinfo...

  13. Biologically Inspired Organic Light-Emitting Diodes.

    Science.gov (United States)

    Kim, Jae-Jun; Lee, Jaeho; Yang, Sung-Pyo; Kim, Ha Gon; Kweon, Hee-Seok; Yoo, Seunghyup; Jeong, Ki-Hun

    2016-05-11

    Many animal species employ highly conspicuous traits as courtship signals for successful mating. Fireflies utilize their bioluminescent light as visual courtship signals. In addition to efficient bioluminescent light emission, the structural components of the firefly lantern also contribute to the enhancement of conspicuous optical signaling. Recently, these firefly lantern ultrastructures have attracted much interest and inspired highly efficient light management approaches. Here we report on the unique optical function of the hierarchical ultrastructures found in a firefly (Pyrocoelia rufa) and their biological inspiration of highly efficient organic light-emitting diode (OLED) applications. The hierarchical structures are comprised of longitudinal nanostructures and asymmetric microstructures, which were successfully replicated using geometry-guided resist reflow, replica molding, and polydimethylsiloxane (PDMS) oxidation. The external quantum efficiency (EQE) of the bioinspired OLEDs was enhanced by up to 61%. The bioinspired OLEDs clearly showed side-enhanced super-Lambertian emission with a wide-viewing angle. The highly efficient light extraction and wide-angle illumination suggest how the hierarchical structures likely improve the recognition of firefly optical courtship signals over a wide-angle range. At the same time, the biologically inspired designs provide a new paradigm for designing functional optical surfaces for lighting or display applications. PMID:27014918

  14. Biologically Inspired Optimization of Building District Heating Networks

    OpenAIRE

    Leiming Shang; Xiaomin Zhao

    2013-01-01

    In this paper we show that a biologically inspired model can be successfully applied to problems of building optimal district heating network. The model is based on physiological observations of the true slime mold Physarumpolycephalum, but can also be used for path-finding in the complicated networks of mazes and road maps. A strategy of optimally building heating distribution network was guided by the model and a well-tuned ant colony algorithm and genetic algorithm. The results indicate th...

  15. Biologically Inspired Optimization of Building District Heating Networks

    Directory of Open Access Journals (Sweden)

    Leiming Shang

    2013-07-01

    Full Text Available In this paper we show that a biologically inspired model can be successfully applied to problems of building optimal district heating network. The model is based on physiological observations of the true slime mold Physarumpolycephalum, but can also be used for path-finding in the complicated networks of mazes and road maps. A strategy of optimally building heating distribution network was guided by the model and a well-tuned ant colony algorithm and genetic algorithm. The results indicate that although there are not large-scale efficiency savings to be made, the biologically inspired amoeboid movement model is capable of finding results of equal or better optimality than a comparable ant colony algorithm and genetic algorithm.

  16. Bio-Inspired Computer Vision: Towards a Synergistic Approach of Artificial and Biological Vision

    OpenAIRE

    Medathati, N. V. Kartheek; Neumann, Heiko; Masson, Guillaume,; Kornprobst, Pierre

    2016-01-01

    International audience Studies in biological vision have always been a great source of inspiration for design of computer vision algorithms. In the past, several successful methods were designed with varying degrees of correspondence with biological vision studies, ranging from purely functional inspiration to methods that utilise models that were primarily developed for explaining biological observations. Even though it seems well recognised that computational models of biological vision ...

  17. Biologically Inspired Purification and Dispersion of SWCNTs

    Science.gov (United States)

    Feeback, Daniel L.; Clarke, Mark S.; Nikolaev, Pavel

    2009-01-01

    A biologically inspired method has been developed for (1) separating single-wall carbon nanotubes (SWCNTs) from other materials (principally, amorphous carbon and metal catalysts) in raw production batches and (2) dispersing the SWCNTs as individual particles (in contradistinction to ropes and bundles) in suspension, as required for a number of applications. Prior methods of purification and dispersal of SWCNTs involve, variously, harsh physical processes (e.g., sonication) or harsh chemical processes (e.g., acid reflux). These processes do not completely remove the undesired materials and do not disperse bundles and ropes into individual suspended SWCNTs. Moreover, these processes cut long SWCNTs into shorter pieces, yielding typical nanotube lengths between 150 and 250 nm. In contrast, the present method does not involve harsh physical or chemical processes. The method involves the use of biologically derived dispersal agents (BDDAs) in an aqueous solution that is mechanically homogenized (but not sonicated) and centrifuged. The dense solid material remaining after centrifugation is resuspended by vortexing in distilled water, yielding an aqueous suspension of individual, separated SWCNTs having lengths from about 10 to about 15 microns.

  18. 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.

  19. 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...

  20. Biologically-Inspired Water Propulsion System

    Institute of Scientific and Technical Information of China (English)

    Andrzej Sioma

    2013-01-01

    Most propulsion systems of vehicles travelling in the aquatic environment are equipped with propellers.Observations of nature,however,show that the absolute majority of organisms travel through water using wave motion,paddling or using water jet power.Inspired by these observations of nature,an innovative propulsion system working in aquatic environment was developed.This paper presents the design of the water propulsion system.Particular attention was paid to the use of paddling techniques and water jet power.A group of organisms that use those mechanisms to travel through water was selected and analysed.The results of research were used in the design of a propulsion system modelled simultaneously on two methods of movement in the aquatic environment.A method for modelling a propulsion system using a combination of the two solutions and the result were described.A conceptual design and a prototype constructed based on the solution were presented.With respect to the solution developed,studies and analyses of selected parameters of the prototype were described.

  1. Biologically Inspired Flagella-Templated Silica Nanotubes

    Science.gov (United States)

    Jo, Wonjin

    The desire and need for various types of nanostructures have been met with challenges of feasibility, reproducibility, and long fabrication time. To work towards improved bottom-up methods of nanofabrication, bacterial flagella are particularly attractive bio-templates for nanotubes due to their tubular structures and small inner and outer diameters. In this work, flagella isolated from Salmonella typhimurium are used as bio-templates to fabricate silica mineralized nanotubes. The process involves as well-controlled hydrolysis and condensation reaction with aminopropyltriethoxysilane (APTES), followed by the addition of tetraethoxysilane (TEOS). By controlling the concentration of TEOS and the reaction time, a simple and precise method is developed for creating silica-mineralized flagella nanotubes (SMFNs) with various thicknesses of the silica layer. In addition, the SMFNs are further modified to multifunctional nanotubes by coating metal nanoparticles (NPs) or metal oxide NPs such as gold, palladium, and iron oxide. The metallized SMFNs are achieved through reactions including reductive metallization or oxidative hydrolysis. The results from these studies provide evidence for the complete coating of SMFNs with uniform metal NP sizes and high surface area coverage. The metallized SMFNs are found to be electrically conductive along their network structures. The current-voltage characteristics show remarkably improved electrical conductivities depending on the types of metal NPs loading and SMFN networks concentration. The biologically inspired SMFNs with metal loading will allow have controlled electrical properties that can lead to the potential of creating unique and precise nanoelectronic materials. Lastly, the randomly entangled SMFNs are characterized to demonstrate their capabilities for hydrophilic and hydrophobic surface applications.

  2. 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

  3. Biologically inspired highly efficient buoyancy engine

    Science.gov (United States)

    Akle, Barbar; Habchi, Wassim; Abdelnour, Rita; Blottman, John, III; Leo, Donald

    2012-04-01

    Undersea distributed networked sensor systems require a miniaturization of platforms and a means of both spatial and temporal persistence. One aspect of this system is the necessity to modulate sensor depth for optimal positioning and station-keeping. Current approaches involve pneumatic bladders or electrolysis; both require mechanical subsystems and consume significant power. These are not suitable for the miniaturization of sensor platforms. Presented in this study is a novel biologically inspired method that relies on ionic motion and osmotic pressures to displace a volume of water from the ocean into and out of the proposed buoyancy engine. At a constant device volume, the displaced water will alter buoyancy leading to either sinking or floating. The engine is composed of an enclosure sided on the ocean's end by a Nafion ionomer and by a flexible membrane separating the water from a gas enclosure. Two electrodes are placed one inside the enclosure and the other attached to the engine on the outside. The semi-permeable membrane Nafion allows water motion in and out of the enclosure while blocking anions from being transferred. The two electrodes generate local concentration changes of ions upon the application of an electrical field; these changes lead to osmotic pressures and hence the transfer of water through the semi-permeable membrane. Some aquatic organisms such as pelagic crustacean perform this buoyancy control using an exchange of ions through their tissue to modulate its density relative to the ambient sea water. In this paper, the authors provide an experimental proof of concept of this buoyancy engine. The efficiency of changing the engine's buoyancy is calculated and optimized as a function of electrode surface area. For example electrodes made of a 3mm diameter Ag/AgCl proved to transfer approximately 4mm3 of water consuming 4 Joules of electrical energy. The speed of displacement is optimized as a function of the surface area of the Nafion

  4. Synthetic biology, inspired by synthetic chemistry

    OpenAIRE

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

    2012-01-01

    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 an...

  5. An efficient biologically-inspired photocell enhanced by quantum coherence

    CERN Document Server

    Creatore, C; Emmott, S; Chin, A W

    2013-01-01

    Artificially reproducing the biological light reactions responsible for the remarkably efficient photon-to-charge conversion in photosynthetic complexes represents a new direction for the future development of photovoltaic devices. Here, we develop such a paradigm and present a model photocell based on the nanoscale architecture of photosynthetic reaction centres that explicitly harnesses the quantum mechanical effects recently discovered in photosynthetic complexes. Quantum interference of photon absorption/emission induced by the dipole-dipole interaction between molecular excited states guarantees an enhanced light-to-current conversion and power generation for a wide range of realistic parameters, opening a promising new route for designing artificial light-harvesting devices inspired by biological photosynthesis and quantum technologies.

  6. Invariant facial feature extraction using biologically inspired strategies

    Science.gov (United States)

    Du, Xing; Gong, Weiguo

    2011-12-01

    In this paper, a feature extraction model for face recognition is proposed. This model is constructed by implementing three biologically inspired strategies, namely a hierarchical network, a learning mechanism of the V1 simple cells, and a data-driven attention mechanism. The hierarchical network emulates the functions of the V1 cortex to progressively extract facial features invariant to illumination, expression, slight pose change, and variations caused by local transformation of facial parts. In the network, filters that account for the local structures of the face are derived through the learning mechanism and used for the invariant feature extraction. The attention mechanism computes a saliency map for the face, and enhances the salient regions of the invariant features to further improve the performance. Experiments on the FERET and AR face databases show that the proposed model boosts the recognition accuracy effectively.

  7. 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

  8. Biologically Inspired Execution Framework for Vulnerable Workflow Systems

    CERN Document Server

    Safdar, Sohail; Qureshi, Muhammad Aasim; Akbar, Rehan

    2009-01-01

    The main objective of the research is to introduce a biologically inspired execution framework for workflow systems under threat due to some intrusion attack. Usually vulnerable systems need to be stop and put into wait state, hence to insure the data security and privacy while being recovered. This research ensures the availability of services and data to the end user by keeping the data security, privacy and integrity intact. To achieve the specified goals, the behavior of chameleons and concept of hibernation has been considered in combination. Hence the workflow systems become more robust using biologically inspired methods and remain available to the business consumers safely even in a vulnerable state.

  9. Patented Biologically-inspired Technological Innovations: A Twenty Year View

    Institute of Scientific and Technical Information of China (English)

    Richard H. C. Bonser

    2006-01-01

    Publication rate of patents can be a useful measure of innovation and productivity in fields of science and technology. To assess the growth in industrially-important research, I conducted an appraisal of patents published between 1985 and 2005 on online databases using keywords chosen to select technologies arising as a result of biological inspiration. Whilst the total number of patents increased over the period examined, those with biomimetic content had increased faster as a proportion of total patent publications. Logistic regression analysis reveals that we may be a little over half way through an initial innovation cycle inspired by biological systems.

  10. Biologically inspired LED lens from cuticular nanostructures of firefly lantern.

    Science.gov (United States)

    Kim, Jae-Jun; Lee, Youngseop; Kim, Ha Gon; Choi, Ki-Ju; Kweon, Hee-Seok; Park, Seongchong; Jeong, Ki-Hun

    2012-11-13

    Cuticular nanostructures found in insects effectively manage light for light polarization, structural color, or optical index matching within an ultrathin natural scale. These nanostructures are mainly dedicated to manage incoming light and recently inspired many imaging and display applications. A bioluminescent organ, such as a firefly lantern, helps to out-couple light from the body in a highly efficient fashion for delivering strong optical signals in sexual communication. However, the cuticular nanostructures, except the light-producing reactions, have not been well investigated for physical principles and engineering biomimetics. Here we report a unique observation of high-transmission nanostructures on a firefly lantern and its biological inspiration for highly efficient LED illumination. Both numerical and experimental results clearly reveal high transmission through the nanostructures inspired from the lantern cuticle. The nanostructures on an LED lens surface were fabricated by using a large-area nanotemplating and reconfigurable nanomolding with heat-induced shear thinning. The biologically inspired LED lens, distinct from a smooth surface lens, substantially increases light transmission over visible ranges, comparable to conventional antireflection coating. This biological inspiration can offer new opportunities for increasing the light extraction efficiency of high-power LED packages.

  11. Nanostructure Control of Biologically Inspired Polymers

    Science.gov (United States)

    Rosales, Adrianne Marie

    Biological polymers, such as polypeptides, are responsible for many of life's most sophisticated functions due to precisely evolved hierarchical structures. These protein structures are the result of monodisperse sequences of amino acids that fold into well-defined chain shapes and tertiary structures. Recently, there has been much interest in the design of such sequence-specific polymers for materials applications in fields ranging from biotechnology to separations membranes. Non-natural polymers offer the stability and robustness necessary for materials applications; however, our ability to control monomer sequence in non-natural polymers has traditionally operated on a much simpler level. In addition, the relationship between monomer sequence and self-assembly is not well understood for biological molecules, much less synthetic polymers. Thus, there is a need to explore self-assembly phase space with sequence using a model system. Polypeptoids are non-natural, sequence-specific polymers that offer the opportunity to probe the effect of sequence on self-assembly. A variety of monomer interactions have an impact on polymer properties, such as chirality, hydrophobicity, and electrostatic interactions. Thus, a necessary starting point for this project was to investigate monomer sequence effects on the bulk properties of polypeptoid homopolymers. It was found that several polypeptoids have experimentally accessible melting transitions that are dependent on the choice of side chains, and it was shown that this transition is tuned by the incorporation of "defects" or a comonomer. The polypeptoid chain shape is also controlled with the choice of monomer and monomer sequence. By using at least 50% monomers with bulky, chiral side chains, the polypeptoid backbone is sterically twisted into a helix, and as found for the first time in this work, the persistence length is increased. However, this persistence length, which is a measure of the stiffness of the polymer, is

  12. Development of a biologically inspired hydrobot tail

    Science.gov (United States)

    Moore, Danielle; Janneh, Alhaji; Philen, Michael

    2014-04-01

    It has been hypothesized that Europa, one of the moons of Jupiter, has a large ocean underneath a thick layer of ice. In order to determine whether life exists, it has been proposed that an underwater glider (hydrobot) capable of propulsion could be sent to explore the vast ocean. In this research, we considered various smart materials to create a propulsion device inspired by dolphin tails. Dolphins are highly efficient and excellent gliders, which makes them the ideal candidate for ocean exploration. In order to select the best dolphin species, we began by reviewing literature and then utilized the Analytical Hierarchy Process (AHP) to compare the different species. Lagenorhynchus obliquidens (Pacific White-Sided Dolphin) was found to be the best choice for creating a bioinspired hydrobot. We then conducted literature review of various smart materials and using this knowledge constructed a hydrobot tail prototype. This prototype demonstrates that smart materials can be fashioned into suitable actuators to control a tail fashioned after a dolphin.

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

    Science.gov (United States)

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

    2012-03-01

    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. PMID:22155966

  14. Handwritten-word spotting using biologically inspired features

    NARCIS (Netherlands)

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

    2008-01-01

    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

  15. 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…

  16. Biologically-Inspired Electronics with Memory Circuit Elements

    OpenAIRE

    Di Ventra, M.; Pershin, Y. V.

    2011-01-01

    Several abilities of biological systems, such as adaptation to natural environment, or of animals to learn patterns when appropriately trained, are features that are extremely useful, if emulated by electronic circuits, in applications ranging from robotics to solution of complex optimization problems, traffic control, etc. In this chapter, we discuss several examples of biologically-inspired circuits that take advantage of memory circuit elements, namely, electronic elements whose resistive,...

  17. 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.

  18. From Cellular Mechanotransduction to Biologically Inspired Engineering

    Science.gov (United States)

    Ingber, Donald E.

    2010-01-01

    This article is based on a lecture I presented as the recipient of the 2009 Pritzker Distinguished Lecturer Award at the Biomedical Engineering Society annual meeting in October 2009. Here, I review more than thirty years of research from my laboratory, beginning with studies designed to test the theory that cells use tensegrity (tensional integrity) architecture to stabilize their shape and sense mechanical signals, which I believed to be critical for control of cell function and tissue development. Although I was trained as a cell biologist, I found that the tools I had at my disposal were insufficient to experimentally test these theories, and thus I ventured into engineering to find critical solutions. This path has been extremely fruitful as it has led to confirmation of the critical role that physical forces play in developmental control, as well as how cells sense and respond to mechanical signals at the molecular level through a process known as cellular mechanotransduction. Many of the predictions of the cellular tensegrity model relating to cell mechanical behaviors have been shown to be valid, and this vision of cell structure led to discovery of the central role that transmembrane adhesion receptors, such as integrins, and the cytoskeleton play in mechanosensing and mechanochemical conversion. In addition, these fundamental studies have led to significant unexpected technology fallout, including development of micromagnetic actuators for non-invasive control of cellular signaling, microfluidic systems as therapeutic extracorporeal devices for sepsis therapy, and new DNA-based nanobiotechnology approaches that permit construction of artificial tensegrities that mimic properties of living materials for applications in tissue engineering and regenerative medicine. PMID:20140519

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

    OpenAIRE

    Alejandro Carrasco Elizalde; Peter Goldsmith

    2008-01-01

    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 cont...

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

    International Nuclear Information System (INIS)

    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)

  1. Editorial:Mechanics of biological and bio-inspired materials%Editorial: Mechanics of biological and bio-inspired materials

    Institute of Scientific and Technical Information of China (English)

    Baohua Jia

    2012-01-01

    The field of mechanics of biological and bio-inspired materials underwent an exciting development over the past several years,which made it stand at the cutting edge of both engineering mechanics and biomechanics.As an intriguing interdisciplinary research field,it aims at elucidating the fundamental principles in nature's design of strong,multi-functional and smart Materials by focusing on the assembly,deformation,stability and failure of the materials.These principles should have wide applications in not only material sciences and mechanical engineering but also biomedical engineering.For instance,the knowledge in Mechanical principles of biological materials is very helpful for addressing some major challenges in material sciences and engineering.They also have the potential to provide quantitative understanding about how forces and deformation affect human being's health,diseases and treatment at tissue,cellular and molecular levels.This special subject on "mechanics of biological and bio-inspired materials" collects a few studies on recent development by leading scientists in this field.The biological materials or systems in these studies include cell,cytoskeleton (e.g.,microtubulus,intermediate filaments),lipid molecules and composite system of lipid and nanoparticle,tissue,and biological attachment systems,etc.

  2. Proceedings Fourth Workshop on Membrane Computing and Biologically Inspired Process Calculi 2010

    CERN Document Server

    Ciobanu, Gabriel; 10.4204/EPTCS.40

    2010-01-01

    The 4th Workshop on Membrane Computing and Biologically Inspired Process Calculi (MeCBIC 2010) is organized in Jena as a satellite event of the Eleventh International Conference on Membrane Computing (CMC11). Biological membranes play a fundamental role in the complex reactions which take place in cells of living organisms. The importance of this role has been considered in two different types of formalisms introduced recently. Membrane systems were introduced as a class of distributed parallel computing devices inspired by the observation that any biological system is a complex hierarchical structure, with a flow of biochemical substances and information that underlies their functioning. The modeling and analysis of biological systems has also attracted considerable interest of the process algebra research community. Thus the notions of membranes and compartments have been explicitly represented in a family of calculi, such as ambients and brane calculi. A cross fertilization of these two research areas has ...

  3. 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.

  4. 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...

  5. Biologically Inspired Robotic Arm Control Using an Artificial Neural Oscillator

    Directory of Open Access Journals (Sweden)

    Woosung Yang

    2010-01-01

    Full Text Available We address a neural-oscillator-based control scheme to achieve biologically inspired motion generation. In general, it is known that humans or animals exhibit novel adaptive behaviors regardless of their kinematic configurations against unexpected disturbances or environment changes. This is caused by the entrainment property of the neural oscillator which plays a key role to adapt their nervous system to the natural frequency of the interacted environments. Thus we focus on a self-adapting robot arm control to attain natural adaptive motions as a controller employing neural oscillators. To demonstrate the excellence of entrainment, we implement the proposed control scheme to a single pendulum coupled with the neural oscillator in simulation and experiment. Then this work shows the performance of the robot arm coupled to neural oscillators through various tasks that the arm traces a trajectory. With these, the real-time closed-loop system allowing sensory feedback of the neural oscillator for the entrainment property is proposed. In particular, we verify an impressive capability of biologically inspired self-adaptation behaviors that enables the robot arm to make adaptive motions corresponding to an unexpected environmental variety.

  6. 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...

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

    OpenAIRE

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

    2013-01-01

    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...

  8. 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.

  9. Color image quality assessment with biologically inspired feature and machine learning

    Science.gov (United States)

    Deng, Cheng; Tao, Dacheng

    2010-07-01

    In this paper, we present a new no-reference quality assessment metric for color images by using biologically inspired features (BIFs) and machine learning. In this metric, we first adopt a biologically inspired model to mimic the visual cortex and represent a color image based on BIFs which unifies color units, intensity units and C1 units. Then, in order to reduce the complexity and benefit the classification, the high dimensional features are projected to a low dimensional representation with manifold learning. Finally, a multiclass classification process is performed on this new low dimensional representation of the image and the quality assessment is based on the learned classification result in order to respect the one of the human observers. Instead of computing a final note, our method classifies the quality according to the quality scale recommended by the ITU. The preliminary results show that the developed metric can achieve good quality evaluation performance.

  10. 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.

  11. 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.

  12. Biologically Inspired Photocatalytically Active Membranes for Water Treatment

    Science.gov (United States)

    Kinsinger, Nichola M.

    There is an alarming increase of a variety of new chemicals that are now being discharged into the wastewater system causing increased concern for public health and safety because many are not removed by typical wastewater treatment practices. Titanium Dioxide (TiO2) is a heterogeneous photocatalytic material that rapidly and completely mineralizing organics without harmful byproducts. TiO2 is synthesized by various methods, which lack the necessary control of crystal size, phase, and morphological features that yield optimized semiconductor materials. Mineralizing organisms demonstrate how nature can produce elegant structures at room temperature through controlled organic-mineral interactions. Here, we utilize biologically-inspired scaffolds to template the nucleation and growth of inorganic materials such as TiO2, which aid in controlling the size and phase of these particles and ultimately, their properties. Nanosized rutile and anatase particles were synthesized under solution conditions at relatively low temperatures and mild pH conditions. The effects of reaction conditions on phase and grain size were investigated and discussed from coordination chemistry and coarsening mechanisms. Photocatalytic characterization of TiO2 phase mixtures was performed to investigate their synergistic effect. The suspension conditions of these catalytic nanomaterials were modulated to optimize the degradation rate of organic analytes. Through the addition of an organic scaffold during the synthesis reaction, a mechanically robust (elastic) composite material containing TiO2 nanoparticles was produced. This composite was subsequently heat-treated to produce a porous, high surface area TiO2 nanoparticulate membrane. Processing conditions were investigated to characterize the growth and phase transformation of TiO2, which ultimately impacts photocatalytic performance. These bulk porous TiO2 structures can be fabricated and tailored to act as stand-alone photocatalytic membranes

  13. E6 inspired composite Higgs model

    CERN Document Server

    Nevzorov, R

    2015-01-01

    We consider a composite Higgs model embedded into a Grand Unified Theory(GUT) based on the E_6 gauge group. The phenomenological viability of this E_6 inspired composite Higgs model (E6CHM) implies that standard model (SM) elementary fermions with different baryon or lepton number should stem from different 27 representations of E_6. We present a six-dimensional orbifold GUT model in which the E_6 gauge symmetry is broken to the SM gauge group so that the appropriate splitting of the bulk 27-plets takes place. In this model the strongly coupled sector is localised on one of the branes and possesses an SU(6) global symmetry that contains the SU(3)_C\\times SU(2)_W\\times U(1)_Y subgroup. In this case the approximate gauge coupling unification can be attained if the right-handed top quark is a composite state and the elementary sector involves extra exotic matter beyond the SM which ensures anomaly cancellation. The breakdown of the approximate SU(6) symmetry at low energies in this model results in a set of the ...

  14. A design methodology for biologically inspired dry fibrillar adhesives

    Science.gov (United States)

    Aksak, Burak

    Realization of the unique aspects of gecko adhesion and incorporating these aspects into a comprehensive design methodology is essential to enable fabrication of application oriented gecko-inspired dry fibrillar adhesives. To address the need for such a design methodology, we propose a fibrillar adhesion model that evaluates the effect of fiber dimensions and material on adhesive performance of fiber arrays. A fibrillar adhesion model is developed to predict the adhesive characteristics of an array of fibrillar structures, and quantify the effect of fiber length, radius, spacing, and material. Photolithography techniques were utilized to fabricate elastomer microfiber arrays. Fibers that are fabricated from stiff SU-8 photoresist are used to fabricate a flexible negative mold that facilitates fabrication of fiber arrays from various elastomers with high yield. The tips of the cylindrical fibers are modified to mushroom-like tip shapes. Adhesive strengths in excess of 100 kPa is obtained with mushroom tipped elastomer microfibers. Vertically aligned carbon nanofibers (VACNFs) are utilized as enhanced friction materials by partially embedding inside soft polyurethanes. Friction coefficients up to 1 were repeatedly obtained from the resulting VACNF composite structures. A novel fabrication method is used to attach Poly(n-butyl acrylate) (PBA) molecular brush-like structures on the surface of polydimethylsiloxane (PDMS). These brushes are grown on unstructured PDMS and PDMS fibers with mushroom tips. Pull-off force is enhanced by up to 7 times with PBA brush grafted micro-fiber arrays over unstructured PDMS substrate. Adhesion model, initially developed for curved smooth surfaces, is extended to self-affine fractal surfaces to better reflect the adhesion performance of fiber arrays on natural surfaces. Developed adhesion model for fiber arrays is used in an optimization scheme which estimates optimal design parameters to obtain maximum adhesive strength on a given

  15. Recent Developments in the Application of Biologically Inspired Computation to Chemical Sensing

    Science.gov (United States)

    Marco, S.; Gutierrez-Gálvez, A.

    2009-05-01

    Biological olfaction outperforms chemical instrumentation in specificity, response time, detection limit, coding capacity, time stability, robustness, size, power consumption, and portability. This biological function provides outstanding performance due, to a large extent, to the unique architecture of the olfactory pathway, which combines a high degree of redundancy, an efficient combinatorial coding along with unmatched chemical information processing mechanisms. The last decade has witnessed important advances in the understanding of the computational primitives underlying the functioning of the olfactory system. In this work, the state of the art concerning biologically inspired computation for chemical sensing will be reviewed. Instead of reviewing the whole body of computational neuroscience of olfaction, we restrict this review to the application of models to the processing of real chemical sensor data.

  16. String field theory inspired phantom model

    International Nuclear Information System (INIS)

    An exact solution to the Friedmann equations with a stringy inspired phantom field is constructed. The Universe is considered as a slowly decaying D3-brane, which is described in the string field theory framework. The notable features of the concerned exactly solvable stringy dark energy (DE) model are a ghost sign of the kinetic term and a special polynomial form of the effective tachyon potential. Cosmological consequences of adding the cold dark matter (CDM) to this model are investigated as well. Solutions with large initial value of the CDM energy density attracted by the exact solution without the CDM are constructed numerically. In contrast to the ACDM model the Hubble parameter in our model is not a monotonic function of time. For specific initial data the DE state parameter UJDE is also not monotonic function of time. For these cases there are two separate domains of time where U'DE being less than - 1 is close to - 1. Stability conditions, under which the constructed solution is stable with respect to small fluctuations of the initial conditions, including the CDM energy density, are found. Keywords: string field theory, cosmology, tachyon, phantom, dark energy, cold dark matter, Big Rip (authors)

  17. Biologically inspired LED lens from cuticular nanostructures of firefly lantern

    OpenAIRE

    Kim, Jae-Jun; Lee, Youngseop; Kim, Ha Gon; Choi, Ki-Ju; Kweon, Hee-Seok; Park, Seongchong; Jeong, Ki-Hun

    2012-01-01

    Cuticular nanostructures found in insects effectively manage light for light polarization, structural color, or optical index matching within an ultrathin natural scale. These nanostructures are mainly dedicated to manage incoming light and recently inspired many imaging and display applications. A bioluminescent organ, such as a firefly lantern, helps to out-couple light from the body in a highly efficient fashion for delivering strong optical signals in sexual communication. However, the cu...

  18. 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.

  19. 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

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

    OpenAIRE

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

    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 i...

  1. Biologically inspired large scale chemical sensor arrays and embedded data processing

    Science.gov (United States)

    Marco, S.; Gutiérrez-Gálvez, A.; Lansner, A.; Martinez, D.; Rospars, J. P.; Beccherelli, R.; Perera, A.; Pearce, T.; Vershure, P.; Persaud, K.

    2013-05-01

    Biological olfaction outperforms chemical instrumentation in specificity, response time, detection limit, coding capacity, time stability, robustness, size, power consumption, and portability. This biological function provides outstanding performance due, to a large extent, to the unique architecture of the olfactory pathway, which combines a high degree of redundancy, an efficient combinatorial coding along with unmatched chemical information processing mechanisms. The last decade has witnessed important advances in the understanding of the computational primitives underlying the functioning of the olfactory system. EU Funded Project NEUROCHEM (Bio-ICT-FET- 216916) has developed novel computing paradigms and biologically motivated artefacts for chemical sensing taking inspiration from the biological olfactory pathway. To demonstrate this approach, a biomimetic demonstrator has been built featuring a large scale sensor array (65K elements) in conducting polymer technology mimicking the olfactory receptor neuron layer, and abstracted biomimetic algorithms have been implemented in an embedded system that interfaces the chemical sensors. The embedded system integrates computational models of the main anatomic building blocks in the olfactory pathway: the olfactory bulb, and olfactory cortex in vertebrates (alternatively, antennal lobe and mushroom bodies in the insect). For implementation in the embedded processor an abstraction phase has been carried out in which their processing capabilities are captured by algorithmic solutions. Finally, the algorithmic models are tested with an odour robot with navigation capabilities in mixed chemical plumes

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

    International Nuclear Information System (INIS)

    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)

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

    Science.gov (United States)

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

    2012-06-01

    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.

  4. A Biologically Inspired Cooperative Multi-Robot Control Architecture

    Science.gov (United States)

    Howsman, Tom; Craft, Mike; ONeil, Daniel; Howell, Joe T. (Technical Monitor)

    2002-01-01

    A prototype cooperative multi-robot control architecture suitable for the eventual construction of large space structures has been developed. In nature, there are numerous examples of complex architectures constructed by relatively simple insects, such as termites and wasps, which cooperatively assemble their nests. The prototype control architecture emulates this biological model. Actions of each of the autonomous robotic construction agents are only indirectly coordinated, thus mimicking the distributed construction processes of various social insects. The robotic construction agents perform their primary duties stigmergically i.e., without direct inter-agent communication and without a preprogrammed global blueprint of the final design. Communication and coordination between individual agents occurs indirectly through the sensed modifications that each agent makes to the structure. The global stigmergic building algorithm prototyped during the initial research assumes that the robotic builders only perceive the current state of the structure under construction. Simulation studies have established that an idealized form of the proposed architecture was indeed capable of producing representative large space structures with autonomous robots. This paper will explore the construction simulations in order to illustrate the multi-robot control architecture.

  5. 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.

  6. 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.

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

    International Nuclear Information System (INIS)

    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)

  8. Biologically inspired force enhancement for maritime propulsion and maneuvering

    CERN Document Server

    Weymouth, G D

    2016-01-01

    The move to high performance applications greatly increases the demand to produce large instantaneous fluid forces for high-speed maneuvering and improved power efficiency for sustained propulsion. Animals achieve remarkable feats of maneuvering and efficiency by changing their body shape to generate unsteady fluid forces. Inspired by this, we have studied a range of immersed bodies which drastically change their shape to produce fluid forces. These include relatively simple shape- changes, such as quickly changing the angle of attack of a foil to induce emergency stops and the use of tandem flapping foils to generate three times the average propulsive force of a single flapping foil. They also include more unconventional shape-changes such as high-speed retracting foil sections to power roll and dive maneuvers and the use of soft robotics to rapidly shrink the frontal area of an ellipsoid to power 68% efficient fast-start maneuvers or even completely cancel the drag force with 91% quasi-propulsive efficiency...

  9. 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.

  10. White dwarfs in an ungravity-inspired model

    Science.gov (United States)

    Bertolami, Orfeu; Mariji, Hodjat

    2016-05-01

    An ungravity-inspired model is employed to examine the astrophysical parameters of white dwarf stars (WDs) using polytropic and degenerate gas approaches. Based on the observed properties such as mass, radius, and luminosity of selected WDs, namely, Sirius B and ɛ Reticulum, bounds on the characteristic length and scaling dimension of the ungravity (UG) model are estimated. The UG effect on the Chandrasekhar limit for WDs is shown. The UG model is examined in the study of ultramassive WDs, e.g., EUVE J1746-706. The UG-inspired model implies that a new location for some WDs on the Hertzsprung-Russell diagram is found.

  11. White dwarfs in an ungravity-inspired model

    CERN Document Server

    Bertolami, Orfeu

    2016-01-01

    An ungravity-inspired model is employed to examine the astrophysical parameters of white dwarf stars (WDs) using polytropic and degenerate gas approaches. Based on the observed properties such as mass, radius, and luminosity of selected WDs, namely, Sirius B and $\\epsilon$ Reticulum, bounds on the characteristic length and scaling dimension of the ungravity (UG) model are estimated. The UG effect on the Chandrasekhar limit for WDs is shown. The UG model is examined in the study of ultra-massive WDs, e.g., EUVE J1746-706. In the contact of UG inspired model, a new location for some WDs on the Hertzsprung-Russell diagram is found.

  12. Biologically-inspired Microfluidic Platforms and Aptamer-based Nanobiosensors

    OpenAIRE

    Cho, Hansang

    2010-01-01

    Recent advances in micro/nano- technologies have shown high potentials in the field of quantitative biology, biomedical science, and analytical chemistry. However, micro/nano fluidics still requires multi-layered structures, complex plumbing/tubing, and external equipments for large-scale applications and nanotechnology-based sensors demand high cost. Interestingly, nature has much simpler and more effective solutions. The goal of this dissertation is to develop novel microfluidic platforms a...

  13. Biological inspiration in optics and photonics: harnessing nature's light manipulation strategies for multifunctional optical materials (Conference Presentation)

    Science.gov (United States)

    Kolle, Mathias; Sandt, Joseph D.; Nagelberg, Sara N.; Zarzar, Lauren D.; Kreysing, Moritz; Vukusic, Peter

    2016-03-01

    The precise control of light-matter interactions is crucial for the majority of known biological organisms in their struggle to survive. Many species have evolved unique methods to manipulate light in their environment using a variety of physical effects including pigment-induced, spectrally selective absorption or light interference in photonic structures that consist of micro- and nano-periodic material morphologies. In their optical performance, many of the known biological photonic systems are subject to selection criteria not unlike the requirements faced in the development of novel optical technology. For this reason, biological light manipulation strategies provide inspiration for the creation of tunable, stimuli-responsive, adaptive material platforms that will contribute to the development of multifunctional surfaces and innovative optical technology. Biomimetic and bio-inspired approaches for the manufacture of photonic systems rely on self-assembly and bottom-up growth techniques often combined with conventional top-down manufacturing. In this regard, we can benefit in several ways from highly sophisticated material solutions that have convergently evolved in various organisms. We explore design concepts found in biological photonic architectures, seek to understand the mechanisms underlying morphogenesis of bio-optical systems, aim to devise viable manufacturing strategies that can benefit from insight in biological formation processes and the use of established synthetic routines alike, and ultimately strive to realize new photonic materials with tailor-made optical properties. This talk is focused on the identification of biological role model photonic architectures, a brief discussion of recently developed bio-inspired photonic structures, including mechano-sensitive color-tunable photonic fibers and reconfigurable fluid micro-lenses. Potentially, early-stage results in studying and harnessing the structure-forming capabilities of living cells that

  14. From Here to Autonomicity: Self-Managing Agents and the Biological Metaphors that Inspire Them

    Science.gov (United States)

    Sterritt, Roy; Hinchey, Mike

    2005-01-01

    We seek inspiration for self-managing systems from (obviously, pre-existing) biological mechanisms. Autonomic Computing (AC), a self-managing systems initiative based on the biological metaphor of the autonomic nervous system, is increasingly gaining momentum as the way forward for integrating and designing reliable systems, while agent technologies have been identified as a key enabler for engineering autonomicity in systems. This paper looks at other biological metaphors such as reflex and healing, heart- beat monitors, pulse monitors and apoptosis for assisting in the realization of autonomicity.

  15. Controlled flight of a biologically inspired, insect-scale robot.

    Science.gov (United States)

    Ma, Kevin Y; Chirarattananon, Pakpong; Fuller, Sawyer B; Wood, Robert J

    2013-05-01

    Flies are among the most agile flying creatures on Earth. To mimic this aerial prowess in a similarly sized robot requires tiny, high-efficiency mechanical components that pose miniaturization challenges governed by force-scaling laws, suggesting unconventional solutions for propulsion, actuation, and manufacturing. To this end, we developed high-power-density piezoelectric flight muscles and a manufacturing methodology capable of rapidly prototyping articulated, flexure-based sub-millimeter mechanisms. We built an 80-milligram, insect-scale, flapping-wing robot modeled loosely on the morphology of flies. Using a modular approach to flight control that relies on limited information about the robot's dynamics, we demonstrated tethered but unconstrained stable hovering and basic controlled flight maneuvers. The result validates a sufficient suite of innovations for achieving artificial, insect-like flight. PMID:23641114

  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. 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.

  18. SelSta - A Biologically Inspired Approach for Self-Stabilizing Humanoid Robot Walking

    OpenAIRE

    Jakimovski, Bojan; Kotke, Michael; Hörenz, Martin; Maehle, Erik

    2010-01-01

    International audience In this paper we elaborate a study on self-stabilizing humanoid robot that achieves run-time self-stabilization and energy optimized walking gait pattern parameters on different kinds of flat surfaces. The algorithmic approach named SelSta uses biologically inspired notions that introduce robustness into the self-stabilizing functionality of the humanoid robot. The approach has been practically tested on our S2-HuRo humanoid robot and the results from the tests demon...

  19. Bio-inspired design of dental multilayers: experiments and model.

    Science.gov (United States)

    Niu, Xinrui; Rahbar, Nima; Farias, Stephen; Soboyejo, Wole

    2009-12-01

    This paper combines experiments, simulations and analytical modeling that are inspired by the stress reductions associated with the functionally graded structures of the dentin-enamel-junctions (DEJs) in natural teeth. Unlike conventional crown structures in which ceramic crowns are bonded to the bottom layer with an adhesive layer, real teeth do not have a distinct "adhesive layer" between the enamel and the dentin layers. Instead, there is a graded transition from enamel to dentin within a approximately 10 to 100 microm thick regime that is called the Dentin Enamel Junction (DEJ). In this paper, a micro-scale, bio-inspired functionally graded structure is used to bond the top ceramic layer (zirconia) to a dentin-like ceramic-filled polymer substrate. The bio-inspired functionally graded material (FGM) is shown to exhibit higher critical loads over a wide range of loading rates. The measured critical loads are predicted using a rate dependent slow crack growth (RDEASCG) model. The implications of the results are then discussed for the design of bio-inspired dental multilayers. PMID:19716103

  20. Evolving Transport Networks With Cellular Automata Models Inspired by Slime Mould.

    Science.gov (United States)

    Tsompanas, Michail-Antisthenis I; Sirakoulis, Georgios Ch; Adamatzky, Andrew I

    2015-09-01

    Man-made transport networks and their design are closely related to the shortest path problem and considered amongst the most debated problems of computational intelligence. Apart from using conventional or bio-inspired computer algorithms, many researchers tried to solve this kind of problem using biological computing substrates, gas-discharge solvers, prototypes of a mobile droplet, and hot ice computers. In this aspect, another example of biological computer is the plasmodium of acellular slime mould Physarum polycephalum (P. polycephalum), which is a large single cell visible by an unaided eye and has been proven as a reliable living substrate for implementing biological computing devices for computational geometry, graph-theoretical problems, and optimization and imitation of transport networks. Although P. polycephalum is easy to experiment with, computing devices built with the living slime mould are extremely slow; it takes slime mould days to execute a computation. Consequently, mapping key computing mechanisms of the slime mould onto silicon would allow us to produce efficient bio-inspired computing devices to tackle with hard to solve computational intelligence problems like the aforementioned. Toward this direction, a cellular automaton (CA)-based, Physarum-inspired, network designing model is proposed. This novel CA-based model is inspired by the propagating strategy, the formation of tubular networks, and the computing abilities of the plasmodium of P. polycephalum. The results delivered by the CA model demonstrate a good match with several previously published results of experimental laboratory studies on imitation of man-made transport networks with P. polycephalum. Consequently, the proposed CA model can be used as a virtual, easy-to-access, and biomimicking laboratory emulator that will economize large time periods needed for biological experiments while producing networks almost identical to the tubular networks of the real-slime mould. PMID

  1. Computing with Biologically Inspired Neural Oscillators: Application to Colour Image Segmentation

    Directory of Open Access Journals (Sweden)

    Ammar Belatreche

    2010-01-01

    Full Text Available This paper investigates the computing capabilities and potential applications of neural oscillators, a biologically inspired neural model, to grey scale and colour image segmentation, an important task in image understanding and object recognition. A proposed neural system that exploits the synergy between neural oscillators and Kohonen self-organising maps (SOMs is presented. It consists of a two-dimensional grid of neural oscillators which are locally connected through excitatory connections and globally connected to a common inhibitor. Each neuron is mapped to a pixel of the input image and existing objects, represented by homogenous areas, are temporally segmented through synchronisation of the activity of neural oscillators that are mapped to pixels of the same object. Self-organising maps form the basis of a colour reduction system whose output is fed to a 2D grid of neural oscillators for temporal correlation-based object segmentation. Both chromatic and local spatial features are used. The system is simulated in Matlab and its demonstration on real world colour images shows promising results and the emergence of a new bioinspired approach for colour image segmentation. The paper concludes with a discussion of the performance of the proposed system and its comparison with traditional image segmentation approaches.

  2. Task-Oriented Parameter Tuning Based on Priority Condition for Biologically Inspired Robot Application

    Directory of Open Access Journals (Sweden)

    Jaesung Kwon

    2015-01-01

    Full Text Available This work gives a biologically inspired control scheme for controlling a robotic system. Novel adaptive behaviors are observed from humans or animals even in unexpected disturbances or environment changes. This is why they have neural oscillator networks in the spinal cord to yield rhythmic-motor primitives robustly under a changing task. Hence, this work focuses on rhythmic arm movements that can be accomplished in terms of employing a control approach based on an artificial neural oscillator model. The main challenge is to determine various parameters for applying a neural feedback to robotic systems with performing a desired behavior and self-maintaining the entrainment effect. Hence, this work proposes a task-oriented parameter tuning algorithm based on the simulated annealing (SA. This work also illustrates how to technically implement the proposed control scheme exploiting a virtual force and neural feedback. With parameters tuned, it is verified in simulations that a 3-DOF planar robotic arm traces a given trajectory precisely, adapting to uneven external disturbances.

  3. Biologically inspired design framework for Robot in Dynamic Environments using Framsticks

    CERN Document Server

    S., Raja Mohamed

    2012-01-01

    Robot design complexity is increasing day by day especially in automated industries. In this paper we propose biologically inspired design framework for robots in dynamic world on the basis of Co-Evolution, Virtual Ecology, Life time learning which are derived from biological creatures. We have created a virtual khepera robot in Framsticks and tested its operational credibility in terms hardware and software components by applying the above suggested techniques. Monitoring complex and non complex behaviors in different environments and obtaining the parameters that influence software and hardware design of the robot that influence anticipated and unanticipated failures, control programs of robot generation are the major concerns of our techniques.

  4. Brane-inspired Four-neutrino Models

    CERN Document Server

    Ioannisian, A N

    1999-01-01

    We propose a four-neutrino model which can reconcile the existing data coming from underground experiments in terms of neutrino oscillations, together with the hint from the LSND experiment and a possible neutrino contribution to the hot dark matter of the Universe. It applies the idea that extra compact dimensions, probed only by gravity and possibly gauge-singlet fields, can lower the fundamental scales such as the Planck, string or unification scales. Our fourth light neutrino $\

  5. Bio-inspired color image enhancement model

    Science.gov (United States)

    Zheng, Yufeng

    2009-05-01

    Human being can perceive natural scenes very well under various illumination conditions. Partial reasons are due to the contrast enhancement of center/surround networks and opponent analysis on the human retina. In this paper, we propose an image enhancement model to simulate the color processes in the human retina. Specifically, there are two center/surround layers, bipolar/horizontal and ganglion/amacrine; and four color opponents, red (R), green (G), blue (B), and yellow (Y). The central cell (bipolar or ganglion) takes the surrounding information from one or several horizontal or amacrine cells; and bipolar and ganglion both have ON and OFF sub-types. For example, a +R/-G bipolar (red-center- ON/green-surround-OFF) will be excited if only the center is illuminated, or inhibited if only the surroundings (bipolars) are illuminated, or stay neutral if both center and surroundings are illuminated. Likewise, other two color opponents with ON-center/OFF-surround, +G/-R and +B/-Y, follow the same rules. The yellow (Y) channel can be obtained by averaging red and green channels. On the other hand, OFF-center/ON-surround bipolars (i.e., -R/+G and -G/+R, but no - B/+Y) are inhibited when the center is illuminated. An ON-bipolar (or OFF-bipolar) only transfers signals to an ONganglion (or OFF-ganglion), where amacrines provide surrounding information. Ganglion cells have strong spatiotemporal responses to moving objects. In our proposed enhancement model, the surrounding information is obtained using weighted average of neighborhood; excited or inhibited can be implemented with pixel intensity increase or decrease according to a linear or nonlinear response; and center/surround excitations are decided by comparing their intensities. A difference of Gaussian (DOG) model is used to simulate the ganglion differential response. Experimental results using natural scenery pictures proved that, the proposed image enhancement model by simulating the two-layer center

  6. 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...

  7. Recovery Management in All Optical Networks Using Biologically-Inspired Complex Adaptive System

    Directory of Open Access Journals (Sweden)

    Inadyuti Dutt

    2013-01-01

    Full Text Available All-Optical Networks have the ability to display varied advantages like performance efficiency, throughput etc but their efficiency depends on their survivability as they are attack prone. These attacks can be categorised as active or passive because they try to access information within the network or alter the information in the network. The attack once detected has to be recovered by formulating back-up or alternative paths. The proposed heuristic uses biologically inspired Complex Adaptive System, inspired by Natural Immune System. The study shows that natural immune system exhibit unique behaviour of detecting foreign bodies in our body and removing them on their first occurrences. This phenomenon is being utilised in the proposed heuristic for recovery management in All-optical Network

  8. Inert scalar dark matter in an extra dimension inspired model

    Energy Technology Data Exchange (ETDEWEB)

    Lineros, R.A.; Santos, F.A. Pereira dos, E-mail: rlineros@ific.uv.es, E-mail: fabio.alex@fis.puc-rio.br [Instituto de Física Corpuscular – CSIC/U. Valencia, Parc Científic, calle Catedrático José Beltrán 2, E-46980 Paterna (Spain)

    2014-10-01

    In this paper we analyze a dark matter model inspired by theories with extra dimensions. The dark matter candidate corresponds to the first Kaluza–Klein mode of an real scalar added to the Standard Model. The tower of new particles enriches the calculation of the relic abundance. For large mass splitting, the model converges to the predictions of the inert singlet dark matter model. For nearly degenerate mass spectrum, coannihilations increase the cross-sections used for direct and indirect dark matter searches. Moreover, the Kaluza–Klein zero mode can mix with the SM higgs and further constraints can be applied.

  9. Inert scalar dark matter in an extra dimension inspired model

    International Nuclear Information System (INIS)

    In this paper we analyze a dark matter model inspired by theories with extra dimensions. The dark matter candidate corresponds to the first Kaluza–Klein mode of an real scalar added to the Standard Model. The tower of new particles enriches the calculation of the relic abundance. For large mass splitting, the model converges to the predictions of the inert singlet dark matter model. For nearly degenerate mass spectrum, coannihilations increase the cross-sections used for direct and indirect dark matter searches. Moreover, the Kaluza–Klein zero mode can mix with the SM higgs and further constraints can be applied

  10. 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...

  11. 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...

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

    Science.gov (United States)

    Iida, Fumiya; Nurzaman, Surya G

    2016-08-01

    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

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

    Science.gov (United States)

    Iida, Fumiya; Nurzaman, Surya G

    2016-08-01

    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.

  14. 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.

  15. Visual Attention: from Bio-Inspired Modeling to Real-Time Implementation

    OpenAIRE

    Ouerhani, Nabil; Hügli, Heinz

    2004-01-01

    Visual Attention: From Bio-Inspired Modeling to Visual attention is the ability of a vision system, be it biological or artificial, to rapidly select the most salient and thus the most relevant data about the environment in which the system is operating. The main goal of this visual mechanism is to drastically reduce the amount of visual information that must be processed by high level and thus complex tasks, such as object recognition, which leads to a considerable speed up of the entire vis...

  16. 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.

  17. 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.

  18. 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.

  19. Survey of locomotion control of legged robots inspired by biological concept

    Institute of Scientific and Technical Information of China (English)

    WU QiDi; LIU ChengJu; ZHANG JiaQi; CHEN QiJun

    2009-01-01

    Compared with wheeled mobile robots, legged robots can easily step over obstacles and walk through rugged ground. They have more flexible bodies and therefore, can deal with complex environment. Nev-ertheless, some other issues make the locomotion control of legged robots a much complicated task, such as the redundant degree of freedoms and balance keeping. From literatures, locomotion control has been solved mainly based on programming mechanism. To use this method, walking trajectories for each leg and the gaits have to be designed, and the adaptability to an unknown environment cannot be guaranteed. From another aspect, studying and simulating animals' walking mechanism for engi-neering application is an efficient way to break the bottleneck of locomotion control for legged robots. This has attracted more and more attentions. Inspired by central pattern generator (CPG), a control method has been proved to be a successful attempt within this scope. In this paper, we will review the biological mechanism, the existence evidences, and the network properties of CPG. From the en-gineering perspective, we will introduce the engineering simulation of CPG, the property analysis, and the research progress of CPG inspired control method in locomotion control of legged robots. Then, in our research, we will further discuss on existing problems, hot issues, and future research directions in this field.

  20. 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...

  1. Adhesion and sliding response of a biologically inspired fibrillar surface: experimental observations.

    Science.gov (United States)

    Yao, H; Rocca, G Della; Guduru, P R; Gao, H

    2008-07-01

    Inspired by the adhesion mechanisms of several animal species such as geckos, beetles and flies, several efforts in designing and fabricating surface engineering strategies have been made recently to mimic the adhesive and frictional behaviour of biological foot pads. An important feature of such biological adhesion systems is the ability to switch between strong attachment and easy detachment, which is crucial for animal locomotion. Recent investigations have suggested that such a 'switching' mechanism can be achieved by the elastic anisotropy of the attachment pad, which renders the magnitude of the detachment force to be direction dependent. This suggestion is supported by the observations that the fibres of the foot pads in geckos and insects are oriented at an angle to the base and that geckos curl their toes backwards (digital hyperextension) while detaching from a surface. One of the promising bio-inspired architectures developed recently is a film-terminated fibrillar PDMS surface; this structure was demonstrated to result in superior detachment force and energy dissipation compared with a bulk PDMS surface. In this investigation, the film-terminated fibrillar architecture is modified by tilting the fibres to make the surface vertically more compliant and elastically anisotropic. The directional detachment and the sliding resistance between the tilted fibrillar surfaces and a spherical glass lens are measured: both show significant directional anisotropy. It is argued that the anisotropy introduced by the tilted fibres and the deformation-induced change in the compliance of the fibre layer are responsible for the observed anisotropy in the detachment force. PMID:17971321

  2. Mechanism Interpretation of the Biological Brain Cooling and Its Inspiration on Bionic Engineering

    Institute of Scientific and Technical Information of China (English)

    Xu Xue; Jing Liu

    2011-01-01

    The brain is one of the most important organs in a biological body which can only work in a relatively stable temperature range. However, many environmental factors in biosphere would cause cerebral temperature fluctuations. To sustain and regulate the brain temperature, many mechanisms of biological brain cooling have been evolved, including Selective Brain Cooling (SBC), cooling through surface water evaporation, respiration, behavior response and using special anatomical appendages. This article is dedicated to present a summarization and systematic interpretation on brain cooling strategies developed in animals by classifying and comparatively analyzing each typical biological brain cooling mechanism from the perspective of bio-heat transfer. Meanwhile, inspirations from such cooling in nature were proposed for developing advanced bionic engineering technologies especially with two focuses on therapeutic hypothermia and computer chip cooling areas. It is expected that many innovations can be achieved along this way to find out new cooling methodologies for a wide variety of industrial applications which will be highly efficient, energy saving, flexible or even intelligent.

  3. Biologically Inspired Electronic, Photovoltaic and Microfluidic Devices Based on Aqueous Soft Matter

    Science.gov (United States)

    Koo, Hyung Jun

    Hydrogels are a water-based soft material where three dimensional networks of hydrophilic polymer retain large amounts of water. We developed hydrogel based devices with new functionalities inspired by materials, structures and processes in nature. The advantages, such as softness, biocompatibility and high ionic conductivity, could enable hydrogels to be novel materials for biomimetic devices operated by ionic current. Moreover, microfluidic patterns are easily embedded in moldable hydrogels and allow for unique convective/diffusive transport mechanism in porous gel to be used for uniform delivery of reagent solution. We first developed and characterized a device with unidirectional ionic current flow across a SiO2/Gel junction, which showed highly efficient rectification of the ionic current by non-linear conductivity of SiO2 films. Addition of polyelectrolytes and salt to the gel layer significantly improved the performance of the new diode device because of the enhanced gel conductance. A soft matter based diode composed of hydrogel and liquid metal (eutectic gallium indium, EGaIn) was also presented. The ability to control the thickness, and thus resistivity, of an insulating oxide skin on the metal enables the current rectification. The effect of ionic conductivity and pH on the formation of the insulating oxide was investigated in a simple model system with liquid metal/electrolyte solution or hydrogel/Pt interfaces. Finally, we present a diode composed entirely of soft materials by replacing the platinum electrode with a second liquid metal electrode. A new type of hydrogel-based photovoltaic systems (HGPVs) was constructed. Two photosensitive ionized molecules embedded in aqueous gel served as photoactive species. The HGPVs showed performance comparable with or higher than those of some other biomimetic or ionic photovoltaic systems reported recently. We suggest a provisional mechanism of the device operation, based on a synergetic effect of the two dye

  4. A Bio-inspired Collision Avoidance Model Based on Spatial Information Derived from Motion Detectors Leads to Common Routes

    OpenAIRE

    Bertrand, Olivier J. N.; Lindemann, Jens P.; Martin Egelhaaf

    2015-01-01

    Avoiding collisions is one of the most basic needs of any mobile agent, both biological and technical, when searching around or aiming toward a goal. We propose a model of collision avoidance inspired by behavioral experiments on insects and by properties of optic flow on a spherical eye experienced during translation, and test the interaction of this model with goal-driven behavior. Insects, such as flies and bees, actively separate the rotational and translational optic flow components via ...

  5. Lagrangians for biological models

    CERN Document Server

    Nucci, M C

    2011-01-01

    We show that a method presented in [S.L. Trubatch and A. Franco, Canonical Procedures for Population Dynamics, J. Theor. Biol. 48 (1974), 299-324] and later in [G.H. Paine, The development of Lagrangians for biological models, Bull. Math. Biol. 44 (1982) 749-760] for finding Lagrangians of classic models in biology, is actually based on finding the Jacobi Last Multiplier of such models. Using known properties of Jacobi Last Multiplier we show how to obtain linear Lagrangians of those first-order systems and nonlinear Lagrangian of the corresponding single second-order equations that can be derived from them, even in the case where those authors failed such as the host-parasite model.

  6. Biologically inspired hexapedal robot using field-effect electroactive elastomer artificial muscles

    Science.gov (United States)

    Eckerle, Joseph; Stanford, Scott; Marlow, John; Schmidt, Roger; Oh, Seajin; Low, Thomas; Shastri, Subramanian V.

    2001-06-01

    Small, autonomous mobile robots are needed for applications such as reconnaissance over difficult terrain or internal inspection of large industrial systems. Previous work in experimental biology and with legged robots has revealed the advantages of using leg actuators with inherent compliance for robust, autonomous locomotion over uneven terrain. Recently developed field-effect electroactive elastomer artificial muscle actuators offer such compliance as well as attractive performance parameters such as force/weight and efficiency, so we developed a small (670 g) six-legged robot, FLEX, using AM actuators. Electrically, AM actuators are a capacitive, high-impedance load similar to piezoelectrics, which makes them difficult to rive optimally with conventional circuitry. Still, we were able to devise a modular, microprocessor-based control system capable of driving 12 muscles with up to 5,000 V, operating form an on- board battery. The artificial muscle actuators had excellent compliance and peak performance, but suffered from poor uniformity and degradation over time. FLEX is the first robot of its kind. While there is room for improvement in some of the robot systems such as actuators and their drivers, this work has validated the idea of using artificial muscle actuators in biologically inspired walking robots.

  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 data model for Cultural Heritage within INSPIRE.

    OpenAIRE

    Farjas Abadía, Mercedes; Fernández Freire, Carlos; Parcero-Oubiña, César; Uriarte González, Antonio

    2014-01-01

    Esta monografía presenta los fundamentos, contexto y detalles técnicos de un Esquema de Aplicación para la incorporación de datos espaciales relativos al patrimonio cultural en el marco definido por la directiva europea INSPIRE sobre información geográfica. Abstract: This monograph presents the background, context and technical details of an Application Schema for the inclusion of cultural heritage spatial data into the INSPIRE framework. Nowadays, INSPIRE provides the most relevant frame...

  9. 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.

  10. Robot Cognitive Control with a Neurophysiologically Inspired Reinforcement Learning Model

    Science.gov (United States)

    Khamassi, Mehdi; Lallée, Stéphane; Enel, Pierre; Procyk, Emmanuel; Dominey, Peter F.

    2011-01-01

    A major challenge in modern robotics is to liberate robots from controlled industrial settings, and allow them to interact with humans and changing environments in the real-world. The current research attempts to determine if a neurophysiologically motivated model of cortical function in the primate can help to address this challenge. Primates are endowed with cognitive systems that allow them to maximize the feedback from their environment by learning the values of actions in diverse situations and by adjusting their behavioral parameters (i.e., cognitive control) to accommodate unexpected events. In such contexts uncertainty can arise from at least two distinct sources – expected uncertainty resulting from noise during sensory-motor interaction in a known context, and unexpected uncertainty resulting from the changing probabilistic structure of the environment. However, it is not clear how neurophysiological mechanisms of reinforcement learning and cognitive control integrate in the brain to produce efficient behavior. Based on primate neuroanatomy and neurophysiology, we propose a novel computational model for the interaction between lateral prefrontal and anterior cingulate cortex reconciling previous models dedicated to these two functions. We deployed the model in two robots and demonstrate that, based on adaptive regulation of a meta-parameter β that controls the exploration rate, the model can robustly deal with the two kinds of uncertainties in the real-world. In addition the model could reproduce monkey behavioral performance and neurophysiological data in two problem-solving tasks. A last experiment extends this to human–robot interaction with the iCub humanoid, and novel sources of uncertainty corresponding to “cheating” by the human. The combined results provide concrete evidence for the ability of neurophysiologically inspired cognitive systems to control advanced robots in the real-world. PMID:21808619

  11. New holographic dark energy model inspired by the DGP braneworld

    Science.gov (United States)

    Sheykhi, A.; Dehghani, M. H.; Ghaffari, S.

    2016-11-01

    The energy density of the holographic dark energy (HDE) is based on the area law of entropy, and thus any modification of the area law leads to a modified holographic energy density. Inspired by the entropy expression associated with the apparent horizon of a Friedmann-Robertson-Walker (FRW) universe in DGP braneworld, we propose a new model for the HDE in the framework of DGP brane cosmology. We investigate the cosmological consequences of this new model and calculate the equation of state (EoS) parameter by choosing the Hubble radius, L = H-1, as the system’s IR cutoff. Our study show that, due to the effects of the extra dimension (bulk), the identification of IR cutoff with Hubble radius, can reproduce the present acceleration of the universe expansion. This is in contrast to the ordinary HDE in standard cosmology which leads to the zero EoS parameter in the case of choosing the Hubble radius as system’s IR cutoff in the absence of interaction between dark matter (DM) and dark energy (DE).

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

    International Nuclear Information System (INIS)

    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

  13. Learning slow features with reservoir computing for biologically-inspired robot localization.

    Science.gov (United States)

    Antonelo, Eric; Schrauwen, Benjamin

    2012-01-01

    This work proposes a hierarchical biologically-inspired architecture for learning sensor-based spatial representations of a robot environment in an unsupervised way. The first layer is comprised of a fixed randomly generated recurrent neural network, the reservoir, which projects the input into a high-dimensional, dynamic space. The second layer learns instantaneous slowly-varying signals from the reservoir states using Slow Feature Analysis (SFA), whereas the third layer learns a sparse coding on the SFA layer using Independent Component Analysis (ICA). While the SFA layer generates non-localized activations in space, the ICA layer presents high place selectivity, forming a localized spatial activation, characteristic of place cells found in the hippocampus area of the rodent's brain. We show that, using a limited number of noisy short-range distance sensors as input, the proposed system learns a spatial representation of the environment which can be used to predict the actual location of simulated and real robots, without the use of odometry. The results confirm that the reservoir layer is essential for learning spatial representations from low-dimensional input such as distance sensors. The main reason is that the reservoir state reflects the recent history of the input stream. Thus, this fading memory is essential for detecting locations, mainly when locations are ambiguous and characterized by similar sensor readings.

  14. 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.

  15. Bio-empirical mode decomposition: visible and infrared fusion using biologically inspired empirical mode decomposition

    Science.gov (United States)

    Sissinto, Paterne; Ladeji-Osias, Jumoke

    2013-07-01

    Bio-EMD, a biologically inspired fusion of visible and infrared (IR) images based on empirical mode decomposition (EMD) and color opponent processing, is introduced. First, registered visible and IR captures of the same scene are decomposed into intrinsic mode functions (IMFs) through EMD. The fused image is then generated by an intuitive opponent processing the source IMFs. The resulting image is evaluated based on the amount of information transferred from the two input images, the clarity of details, the vividness of depictions, and range of meaningful differences in lightness and chromaticity. We show that this opponent processing-based technique outperformed other algorithms based on pixel intensity and multiscale techniques. Additionally, Bio-EMD transferred twice the information to the fused image compared to other methods, providing a higher level of sharpness, more natural-looking colors, and similar contrast levels. These results were obtained prior to optimization of color opponent processing filters. The Bio-EMD algorithm has potential applicability in multisensor fusion covering visible bands, forensics, medical imaging, remote sensing, natural resources management, etc.

  16. Biologically inspired, haltere, angular-rate sensors for micro-autonomous systems

    Science.gov (United States)

    Smith, G. L.; Bedair, S. S.; Schuster, B. E.; Nothwang, W. D.; Pulskamp, J. S.; Meyer, C. D.; Polcawich, R. G.

    2012-06-01

    Small autonomous aerial systems require the ability to detect roll, pitch, and yaw to enable stable flight. Existing inertial measurement units (IMUs) are incapable of accurately measuring roll-pitch-yaw within the size, weight, and power requirements of at-scale insect-inspired aerial autonomous systems. To overcome this, we have designed novel IMUs based on the biological haltere system in a microelectromechanical system (MEMS). MEMS haltere sensors were successfully simulated, designed, and fabricated with a control scheme that enables simple, straightforward decoupling of the signals. Passive mechanical logic was designed to facilitate the decoupling of the forces acting on the sensor. The control scheme was developed that efficiently and accurately decouples the three component parts from the haltere sensors. Individual, coupled, and arrayed halteres were fabricated. A series of static electrical tests and dynamic device tests were conducted, in addition to in-situ bend tests, to validate the simulation results, and these, taken as a whole, indicate that the MEMS haltere sensors will be inherently sensitive to the Coriolis forces caused by changes in angular rate. The successful fabrication of a micro-angular rate sensor represents a substantial breakthrough and is an enabling technology for a number of Army applications, including micro air vehicles (MAVs).

  17. Dark Matter in a Constrained $E_6$ Inspired SUSY Model

    CERN Document Server

    Athron, P; 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 volu...

  18. 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.

  19. 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.

  20. Visual Cortex Inspired CNN Model for Feature Construction in Text Analysis

    Science.gov (United States)

    Fu, Hongping; Niu, Zhendong; Zhang, Chunxia; Ma, Jing; Chen, Jie

    2016-01-01

    Recently, biologically inspired models are gradually proposed to solve the problem in text analysis. Convolutional neural networks (CNN) are hierarchical artificial neural networks, which include a various of multilayer perceptrons. According to biological research, CNN can be improved by bringing in the attention modulation and memory processing of primate visual cortex. In this paper, we employ the above properties of primate visual cortex to improve CNN and propose a biological-mechanism-driven-feature-construction based answer recommendation method (BMFC-ARM), which is used to recommend the best answer for the corresponding given questions in community question answering. BMFC-ARM is an improved CNN with four channels respectively representing questions, answers, asker information and answerer information, and mainly contains two stages: biological mechanism driven feature construction (BMFC) and answer ranking. BMFC imitates the attention modulation property by introducing the asker information and answerer information of given questions and the similarity between them, and imitates the memory processing property through bringing in the user reputation information for answerers. Then the feature vector for answer ranking is constructed by fusing the asker-answerer similarities, answerer's reputation and the corresponding vectors of question, answer, asker, and answerer. Finally, the Softmax is used at the stage of answer ranking to get best answers by the feature vector. The experimental results of answer recommendation on the Stackexchange dataset show that BMFC-ARM exhibits better performance. PMID:27471460

  1. Visual cortex inspired CNN model for feature construction in text analysis

    Directory of Open Access Journals (Sweden)

    Hongping Fu

    2016-07-01

    Full Text Available Recently, biologically inspired models are gradually proposed to solve the problem in text analysis. Convolutional neural networks (CNN are hierarchical artificial neural networks, which include a various of multilayer perceptrons. According to biological research, CNN can be improved by bringing in the attention modulation and memory processing of primate visual cortex. In this paper, we employ the above properties of primate visual cortex to improve CNN and propose a biological-mechanism-driven-feature-construction based answer recommendation method (BMFC-ARM, which is used to recommend the best answer for the corresponding given questions in community question answering. BMFC-ARM is an improved CNN with four channels respectively representing questions, answers, asker information and answerer information, and mainly contains two stages: biological mechanism driven feature construction (BMFC and answer ranking. BMFC imitates the attention modulation property by introducing the asker information and answerer information of given questions and the similarity between them, and imitates the memory processing property through bringing in the user reputation information for answerers. Then the feature vector for answer ranking is constructed by fusing the asker-answerer similarities, answerer's reputation and the corresponding vectors of question, answer, asker and answerer. Finally, the Softmax is used at the stage of answer ranking to get best answers by the feature vector. The experimental results of answer recommendation on the Stackexchange dataset show that BMFC-ARM exhibits better performance.

  2. 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.

  3. ECO-BIOLOGICAL SYSTEM MODELING

    Directory of Open Access Journals (Sweden)

    T. I. Burak

    2015-01-01

    Full Text Available The methodology for computer modeling of complex eco-biological models is presented in this paper. It is based on system approach of J. Forrester. Developed methodology is universal for complex ecological and biological systems. Modeling algorithm considers specialties of eco-biological systems and shows adequate and accurate results in practice. 

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

    Science.gov (United States)

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

    2013-12-01

    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. PMID:24225196

  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

    2015-09-01

    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)

    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. 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

    2015-09-01

    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. PMID:26234364

  8. 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.

  9. Fixed-wing MAV attitude stability in atmospheric turbulence-Part 2: Investigating biologically-inspired sensors

    Science.gov (United States)

    Mohamed, A.; Watkins, S.; Clothier, R.; Abdulrahim, M.; Massey, K.; Sabatini, R.

    2014-11-01

    Challenges associated with flight control of agile fixed-wing Micro Air Vehicles (MAVs) operating in complex environments is significantly different to any larger scale vehicle. The micro-scale of MAVs can make them particularly sensitive to atmospheric disturbances thus limiting their operation. As described in Part 1, current conventional reactive attitude sensing systems lack the necessary response times for attitude control in high turbulence environments. This paper reviews in greater detail novel and emerging biologically inspired sensors, which can sense the disturbances before a perturbation is induced. A number of biological mechanoreceptors used by flying animals are explored for their utility in MAVs. Man-made attempts of replicating mechanoreceptors have thus been reviewed. Bio-inspired flow and pressure-based sensors were found to be the most promising for complementing or replacing current inertial-based reactive attitude sensors. Achieving practical implementations that meet the size, weight and power constraints of MAVs remains a significant challenge. Biological systems were found to rely on multiple sensors, potentially implying a number of research opportunities in the exploration of heterogeneous bio-inspired sensing solutions.

  10. A biologically inspired modular structure to control the sit-to-stand transfer of a biped robot.

    Science.gov (United States)

    Andani, M Emadi; Bahrami, F; Maralani, P Jabedar

    2007-01-01

    In this study, a biologically inspired control structure to control the sit-to-stand (STS) transfer from a chair is developed and simulated. STS movement is consisted of two main phases. First phase of the movement is before leaving the seat (seat-off moment). In this phase seat reactions forces act on the body parts which are in contact with the seat. The second phase is after seat-off, where the only external forces acting on the body are ground reaction forces. A proper control algorithm of the STS transfer needs to consider switching between these two phases, which correspond to two different dynamical structures. The control structure developed and discussed in this work is based on the MOSAIC structure, proposed first by Wolpert and Kawato [1]. Original MOSAIC structure has a modular architecture which is based on multiple pairs of forward and inverse models of the dynamical system to be controlled, and each module is trained separately to learn one part of a given task. The number of effective modules is predetermined. We have developed a new method to train all modules simultaneously. This method is based on reinforcement and cooperative competitive learning, and the number of effective modules is determined automatically. In this study, the simulation was begun with four modules. Our results showed that only two modules out of four were selected to control the STS task. Responsibility of controlling the task was switched between the two modules around the seat-off moment.

  11. Real-Time Illumination Invariant Face Detection Using Biologically Inspired Feature Set and BP Neural Network

    Directory of Open Access Journals (Sweden)

    Reza Azad

    2014-06-01

    Full Text Available In recent years, face detection has been thoroughly studied due to its wide potential applications, including face recognition, human-computer interaction, video surveillance, etc.In this paper, a new and illumination invariant face detection method, based on features inspired by the human's visual cortexand applying BP neural network on the extracted featureset is proposed.A feature set is extracted from face and non-face images, by means of a feed-forward model, which contains a view and illumination invariant C2 features from all images in the dataset. Then, these C2 feature vector which derived from a cortex-like mechanism passed to a BP neural network. In the result part, the proposed approach is applied on FEI and Wild face detection databases and high accuracy rate is achieved. In addition, experimental results have demonstrated our proposed face detector outperforms the most of the successful face detection algorithms in the literature and gives the first best result on all tested challenging face detection databases.

  12. Pose-Independent Face Recognition Using Biologically Inspired Feature Set and Mixture of Experts

    Directory of Open Access Journals (Sweden)

    Reza Azad

    2014-08-01

    Full Text Available Automatic face recognition system has received significant attention during the last decades due to its wide range of applications, such as security, human-computer interaction, visual surveillance, and so on. In this paper, a new and efficient face recognition method, based on features inspired by the human’s visual cortex and applying mixture of experts’ architecture on the extracted feature set is proposed. A feature set is extracted by means of a feed-forward model, which contains a view and illumination invariant C2 features from all images in the data set. Then, these C2 feature vector which derived from a cortex-like mechanism passed to a mixture of multilayer perceptron neural networks. In the result part, the proposed approach is applied on ORL and Yale databases and the accuracy rate achieved 99.75% and 100% respectively. In addition, experimental results have demonstrated our method robust in successful recognition of human faces even with variant lighting and poses.

  13. 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.

  14. Biologically inspired survival analysis based on integrating gene expression as mediator with genomic variants.

    Science.gov (United States)

    Youssef, Ibrahim; Clarke, Robert; Shih, Ie-Ming; Wang, Yue; Yu, Guoqiang

    2016-10-01

    Accurately linking cancer molecular profiling with survival can lead to improvements in the clinical management of cancer. However, existing survival analysis relies on statistical evidence from a single level of data, without paying much attention to the integration of interacting multi-level data and the underlying biology. Advances in genomic techniques provide unprecedented power of characterizing the cancer tissue in a more complete manner than before, offering the opportunity to design biologically informed and integrative approaches for survival data analysis. Human cancer is characterized by somatic copy number alternation and unique gene expression profiles. However, it remains largely unclear how to integrate the gene expression and genetic variant data to achieve a better prediction of patient survival and an improved understanding of disease progression. Consistent with the biological hierarchy from DNA to RNA, we prioritize each survival-relevant feature with two separate scores, predictive and mechanistic. For mRNA expression levels, predictive features are those mRNAs whose variation in expression levels is associated with survival outcome, and mechanistic features are those mRNAs whose variation in expression levels is associated with genomic variants. Further, we simultaneously integrate information from both the predictive model and the mechanistic model through our new approach, GEMPS (Gene Expression as a Mediator for Predicting Survival). Applied on two cancer types (ovarian and glioblastoma multiforme), our method achieved better prediction power (p-value: 6.18E-03-5.15E-11) than peer methods (GE.CNAs and GE.CNAs. Lasso). Gene set enrichment analysis confirms that the genes utilized for the final survival analysis are biologically important and relevant. PMID:27619193

  15. Biologically inspired crack delocalization in a high strain-rate environment.

    Science.gov (United States)

    Knipprath, Christian; Bond, Ian P; Trask, Richard S

    2012-04-01

    Biological materials possess unique and desirable energy-absorbing mechanisms and structural characteristics worthy of consideration by engineers. For example, high levels of energy dissipation at low strain rates via triggering of crack delocalization combined with interfacial hardening by platelet interlocking are observed in brittle materials such as nacre, the iridescent material in seashells. Such behaviours find no analogy in current engineering materials. The potential to mimic such toughening mechanisms on different length scales now exists, but the question concerning their suitability under dynamic loading conditions and whether these mechanisms retain their energy-absorbing potential is unclear. This paper investigates the kinematic behaviour of an 'engineered' nacre-like structure within a high strain-rate environment. A finite-element (FE) model was developed which incorporates the pertinent biological design features. A parametric study was carried out focusing on (i) the use of an overlapping discontinuous tile arrangement for crack delocalization and (ii) application of tile waviness (interfacial hardening) for improved post-damage behaviour. With respect to the material properties, the model allows the permutation and combination of a variety of different material datasets. The advantage of such a discontinuous material shows notable improvements in sustaining high strain-rate deformation relative to an equivalent continuous morphology. In the case of the continuous material, the shockwaves propagating through the material lead to localized failure while complex shockwave patterns are observed in the discontinuous flat tile arrangement, arising from platelet interlocking. The influence of the matrix properties on impact performance is investigated by varying the dominant material parameters. The results indicate a deceleration of the impactor velocity, thus delaying back face nodal displacement. A final series of FE models considered the

  16. Design and Implementation of a Biologically Inspired Flying Robot - An EPS@ISEP 2014 Spring Project

    OpenAIRE

    Caramin, Bénédicte Anki; Dunn, Iain; Ney, Rauno; Klawikowski, Yvonne; Malheiro, Benedita; Ribeiro, Maria Cristina; Silva, Manuel; Caetano, Nídia de Sá; Ferreira, Paulo; Guedes, Pedro

    2015-01-01

    The goal of this EPS@ISEP project proposed in the Spring of 2014 was to develop a flapping wing flying robot. The project was embraced by a multinational team composed of four students from different countries and fields of study. The team designed and implemented a robot inspired by a biplane design, constructed from lightweight materials and battery powered. The prototype, called MyBird, was built with a 250 € budget, reuse existing materials as well as low cost solutio...

  17. 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.

  18. Biologically Inspired Design Principles for Scalable, Robust, Adaptive, Decentralized Search and Automated Response (RADAR)

    CERN Document Server

    Moses, Melanie

    2010-01-01

    Distributed search problems are ubiquitous in Artificial Life (ALife). Many distributed search problems require identifying a rare and previously unseen event and producing a rapid response. This challenge amounts to finding and removing an unknown needle in a very large haystack. Traditional computational search models are unlikely to find, nonetheless, appropriately respond to, novel events, particularly given data distributed across multiple platforms in a variety of formats and sources with variable and unknown reliability. Biological systems have evolved solutions to distributed search and response under uncertainty. Immune systems and ant colonies efficiently scale up massively parallel search with automated response in highly dynamic environments, and both do so using distributed coordination without centralized control. These properties are relevant to ALife, where distributed, autonomous, robust and adaptive control is needed to design robot swarms, mobile computing networks, computer security system...

  19. 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; 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 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-six 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

  20. 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.

  1. A cognitive-inspired model for self-organizing networks

    CERN Document Server

    Borkmann, Daniel; Massaro, Emanuele; Rudolph, Stefan

    2012-01-01

    In this work, we propose a computational scheme inspired by the workings of human cognition in order to embed some fundamental aspects of the human cognitive system such as the minimization of the computational resources, and the evolution of a dynamic knowledge network over time into computer networks. Such algorithm is capable of generating suitable strategies to explore networks like the Internet, which are too large and too dynamic to be ever perfectly known. The algorithm equips each node with a local information about the possible hubs which are present in its environment. Such information can be used by a node to change its connections whenever its fitness is not satisfying some given requirements. Finally, we compare our algorithm with a randomized approach within an ecological scenario for the ICT domain, where a network of nodes carries a certain set of objects, and each node retrieves a subset at a certain time, constrained with limited resources in terms of energy and bandwidth. We show that a cog...

  2. Modelling coordination in biological systems

    OpenAIRE

    Clarke, David; Oliveira Costa, de, David; Arbab, Farhad

    2004-01-01

    We present an application of the Reo coordination paradigm to provide a compositional formal model for describing and reasoning about the behaviour of biological systems, such as regulatory gene networks. Reo governs the interaction and flow of data between components by allowing the construction of connector circuits which have a precise formal semantics. When applied to systems biology, the result is a graphical model, which is comprehensible, mathematically precise, and flexible

  3. MEMBRANE COMPUTING AS THE PARADIGM FOR MODELING SYSTEMS BIOLOGY

    Directory of Open Access Journals (Sweden)

    Ravie Chandren Muniyandi

    2013-01-01

    Full Text Available Membrane computing is a field in computer science that is inspired from the structure and the processes of living cells and is being considered as an alternative in solving the limitations in conventional mathematical approaches by taking into consideration its essential features that are of interest for research in systems biology. Advancements in computability make it feasible to handle huge volumes of data in biology and propose a new and better approach using a discreet computer science model, such as membrane computing. In this respect, membrane-computing abilities, to enhance the understanding of the system level of biological systems, have been explored. This study discusses experiences in applying membrane computing in modeling biological systems as well as possibilities of incorporating membrane computing into other computer science paradigms to enhance the use of membrane computing in systems biology. Experiences in modeling aspects of systems biology with membrane computing demonstrate additional advantages and possibilities compared with conventional methods. However, they are not yet used widely to model or simulate biological processes or systems. A general framework of modeling and verifying biological systems using membrane computing is essential as a guideline for biologists in their research in systems biology.

  4. Performance improvement of IPMC flow sensors with a biologically-inspired cupula structure

    Science.gov (United States)

    Lei, Hong; Sharif, Montassar Aidi; Paley, Derek A.; McHenry, Matthew J.; Tan, Xiaobo

    2016-04-01

    Ionic polymer-metal composites (IPMCs) have inherent underwater sensing and actuation properties. They can be used as sensors to collect flow information. Inspired by the hair-cell mediated receptor in the lateral line system of fish, the impact of a flexible, cupula-like structure on the performance of IPMC flow sensors is experimentally explored. The fabrication method to create a silicone-capped IPMC sensor is reported. Experiments are conducted to compare the sensing performance of the IPMC flow sensor before and after the PDMS coating under the periodic flow stimulus generated by a dipole source in still water and the laminar flow stimulus generated in a flow tank. Experimental results show that the performance of IPMC flow sensors is significantly improved under the stimulus of both periodic flow and laminar flow by the proposed silicone-capping.

  5. A method for fast pavement cracking detection based on the biological inspired model%一种快速的基于生物启发模型的路面裂缝特征提取与识别方法

    Institute of Scientific and Technical Information of China (English)

    徐奕奕; 唐培和; 倪志平

    2012-01-01

    路面裂缝形态复杂、表观差异较大,难以用明确的特征来表示,而通常的wavelet、Gabor变换及其函数都是预定义的,不能适应路面裂缝图像的特点,为此提出一种新颖的基于生物启发模型(BIM)特征的弹性领域联合最大化处理识别算法,采用弹性邻域,先对相邻四邻域或八邻域进行图像分割,并在每一区域引入Adaboost分类器选择,保留关键信息,去掉无用或负面信息.该算法获得的特征向量全面反映了原图像信息,且计算复杂度低,有利于实时应用.实验结果表明:本文所提出的方法在路面裂缝的总体识别率高达99.13%,且响应时间快,充分显示了本方法的有效性.%Due to the complexity of shape and apparent differences of pavement cracks, it is difficult to characterize them with definite features. The wavelet, Gabor transform and its functions are usually predefined and cannot adapt to the characteristics of the pavement crack images. This paper proposes a novel joint maximization recognition algorithm in the resilient area, which is based on the characteristics of biologically inspired model (BIM). The algorithm uses the elastic neighborhood, the first adjacent neighbors domain or eight neighborhood image segmentation. Adaboost classifier is introduced in each region to select and retain key information, get rid of unwanted or negative information. Its eigenvectors can reflect the information in the original image comprehensively and its low computational complexity is helpful in real-time applications. The experimental results show that the overall recognition rate of the proposed method in pavement cracks is up to 99.13%, and its fast response time fully demonstrate the effectiveness of this method.

  6. 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.

  7. A nonlinear mechanics model of bio-inspired hierarchical lattice materials consisting of horseshoe microstructures

    Science.gov (United States)

    Ma, Qiang; Cheng, Huanyu; Jang, Kyung-In; Luan, Haiwen; Hwang, Keh-Chih; Rogers, John A.; Huang, Yonggang; Zhang, Yihui

    2016-05-01

    Development of advanced synthetic materials that can mimic the mechanical properties of non-mineralized soft biological materials has important implications in a wide range of technologies. Hierarchical lattice materials constructed with horseshoe microstructures belong to this class of bio-inspired synthetic materials, where the mechanical responses can be tailored to match the nonlinear J-shaped stress-strain curves of human skins. The underlying relations between the J-shaped stress-strain curves and their microstructure geometry are essential in designing such systems for targeted applications. Here, a theoretical model of this type of hierarchical lattice material is developed by combining a finite deformation constitutive relation of the building block (i.e., horseshoe microstructure), with the analyses of equilibrium and deformation compatibility in the periodical lattices. The nonlinear J-shaped stress-strain curves and Poisson ratios predicted by this model agree very well with results of finite element analyses (FEA) and experiment. Based on this model, analytic solutions were obtained for some key mechanical quantities, e.g., elastic modulus, Poisson ratio, peak modulus, and critical strain around which the tangent modulus increases rapidly. A negative Poisson effect is revealed in the hierarchical lattice with triangular topology, as opposed to a positive Poisson effect in hierarchical lattices with Kagome and honeycomb topologies. The lattice topology is also found to have a strong influence on the stress-strain curve. For the three isotropic lattice topologies (triangular, Kagome and honeycomb), the hierarchical triangular lattice material renders the sharpest transition in the stress-strain curve and relative high stretchability, given the same porosity and arc angle of horseshoe microstructure. Furthermore, a demonstrative example illustrates the utility of the developed model in the rapid optimization of hierarchical lattice materials for

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

    NARCIS (Netherlands)

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

    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 th

  9. The pion electromagnetic form-factor in a QCD-inspired model

    CERN Document Server

    Pacheco-Bicudo-Cabral de Melo, J; Pace, E; Salmè, G

    2004-01-01

    We present detailed numerical results for the pion space-like electromagnetic form factor obtained within a recently proposed model of the pion electromagnetic current in a confining light-front QCD-inspired model. The model incorporates the vector meson dominance mechanism at the quark level, where the dressed photon with $q^+>0$ decay in an interacting quark-antiquark pair,wich absorbs the initial pion and produces the pion in the final state.

  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...

  11. LHC signatures and cosmological implications of the E6 inspired SUSY models

    CERN Document Server

    Nevzorov, R

    2015-01-01

    The phenomenological implications of the E6 inspired supersymmetric models based on the Standard Model gauge group together with extra U(1)_N gauge symmetry under which right-handed neutrinos have zero charge are examined. In these models single discrete symmetry forbids the tree-level flavour changing processes and the most dangerous operators that violate baryon and lepton numbers. The two-loop renormalisation group flow of the gauge and Yukawa couplings is explored and the qualitative pattern of the Higgs spectrum in the case of the quasi-fixed point scenario is discussed. These E6 inspired models contain two dark-matter candidates. The presence of exotic states in these models gives rise to the nonstandard decays of the lightest Higgs boson which are also considered.

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

    International Nuclear Information System (INIS)

    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

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

    International Nuclear Information System (INIS)

    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)

  14. [Biological mutualism, concepts and models].

    Science.gov (United States)

    Perru, Olivier

    2011-01-01

    Mutualism is a biological association for a mutual benefit between two different species. In this paper, firstly, we examine the history and signification of mutualism in relation to symbiosis. Then, we consider the link between concepts and models of mutualism. Models of mutualism depend on different concepts we use: If mutualism is situated at populations' level, it will be expressed by Lotka-Volterra models, concerning exclusively populations' size. If mutualism is considered as a resources' exchange or a biological market increasing the fitness of these organisms, it will be described at an individual level by a cost-benefit model. Our analysis will be limited to the history and epistemology of Lotka-Volterra models and we hypothesize that these models are adapted at first to translate dynamic evolutions of mutualism. They render stability or variations of size and assume that there are clear distinctions and a state of equilibrium between populations of different species. Italian mathematician Vito Volterra demonstrated that biological associations consist in a constant relation between some species. In 1931 and 1935, Volterra described the general form of antagonistic or mutualistic biological associations by the same differential equations. We recognize that these equations have been more used to model competition or prey-predator interactions, but a simple sign change allows describing mutualism. The epistemological problem is the following: Volterra's equations help us to conceptualize a global phenomenon. However, mutualistic interactions may have stronger effects away from equilibrium and these effects may be better understood at individual level. We conclude that, between 1985 and 2000, some researchers carried on working and converting Lotka-Volterra models but this description appeared as insufficient. So, other researchers adopted an economical viewpoint, considering mutualism as a biological market. PMID:22288336

  15. [Biological mutualism, concepts and models].

    Science.gov (United States)

    Perru, Olivier

    2011-01-01

    Mutualism is a biological association for a mutual benefit between two different species. In this paper, firstly, we examine the history and signification of mutualism in relation to symbiosis. Then, we consider the link between concepts and models of mutualism. Models of mutualism depend on different concepts we use: If mutualism is situated at populations' level, it will be expressed by Lotka-Volterra models, concerning exclusively populations' size. If mutualism is considered as a resources' exchange or a biological market increasing the fitness of these organisms, it will be described at an individual level by a cost-benefit model. Our analysis will be limited to the history and epistemology of Lotka-Volterra models and we hypothesize that these models are adapted at first to translate dynamic evolutions of mutualism. They render stability or variations of size and assume that there are clear distinctions and a state of equilibrium between populations of different species. Italian mathematician Vito Volterra demonstrated that biological associations consist in a constant relation between some species. In 1931 and 1935, Volterra described the general form of antagonistic or mutualistic biological associations by the same differential equations. We recognize that these equations have been more used to model competition or prey-predator interactions, but a simple sign change allows describing mutualism. The epistemological problem is the following: Volterra's equations help us to conceptualize a global phenomenon. However, mutualistic interactions may have stronger effects away from equilibrium and these effects may be better understood at individual level. We conclude that, between 1985 and 2000, some researchers carried on working and converting Lotka-Volterra models but this description appeared as insufficient. So, other researchers adopted an economical viewpoint, considering mutualism as a biological market.

  16. Using parallel evolutionary development for a biologically-inspired computer vision system for mobile robots.

    Science.gov (United States)

    Wright, Cameron H G; Barrett, Steven F; Pack, Daniel J

    2005-01-01

    We describe a new approach to attacking the problem of robust computer vision for mobile robots. The overall strategy is to mimic the biological evolution of animal vision systems. Our basic imaging sensor is based upon the eye of the common house fly, Musca domestica. The computational algorithms are a mix of traditional image processing, subspace techniques, and multilayer neural networks.

  17. Scalar dark matter in an extra dimension inspired model

    CERN Document Server

    Lineros, Roberto

    2016-01-01

    In this work we consider a singlet scalar propagating in a flat large extra dimension. The first Kaluza-Klein mode associated to this singlet scalar will be a viable dark matter candidate. The tower of new particles enriches the calculation of the relic density due effect of coannihilation. For large mass splitting, the model converges to the predictions of the singlet dark matter model. For nearly degenerate mass spectrum, coannihilations increase the cross sections used for direct and indirect dark matter searches. We investigate the impact of the Kaluza-Klein tower associated to singlet scalar for indirect and direct detection of dark matter.

  18. Scalar dark matter in an extra dimension inspired model

    Science.gov (United States)

    Lineros, Roberto; Pereira dos Santos, Fabio

    2016-05-01

    In this work we consider a singlet scalar propagating in a flat large extra dimension. The first Kaluza-Klein mode associated to this singlet scalar will be a viable dark matter candidate. The tower of new particles enriches the calculation of the relic density due effect of coannihilation. For large mass splitting, the model converges to the predictions of the singlet dark matter model. For nearly degenerate mass spectrum, coannihilations increase the cross-sections used for direct and indirect dark matter searches. We investigate the impact of the Kaluza-Klein tower associated to singlet scalar for indirect and direct detection of dark matter.

  19. Kinetic Modeling of Biological Systems

    Energy Technology Data Exchange (ETDEWEB)

    Resat, Haluk; Petzold, Linda; Pettigrew, Michel F.

    2009-04-21

    The dynamics of how its constituent components interact define the spatio-temporal response of a natural system to stimuli. Modeling the kinetics of the processes that represent a biophysical system has long been pursued with the aim of improving our understanding of the studied system. Due to the unique properties of biological systems, in addition to the usual difficulties faced in modeling the dynamics of physical or chemical systems, biological simulations encounter difficulties that result from intrinsic multiscale and stochastic nature of the biological processes. This chapter discusses the implications for simulation of models involving interacting species with very low copy numbers, which often occur in biological systems and give rise to significant relative fluctuations. The conditions necessitating the use of stochastic kinetic simulation methods and the mathematical foundations of the stochastic simulation algorithms are presented. How the well-organized structural hierarchies often seen in biological systems can lead to multiscale problems, and possible ways to address the encountered computational difficulties are discussed. We present the details of the existing kinetic simulation methods, and discuss their strengths and shortcomings. A list of the publicly available kinetic simulation tools and our reflections for future prospects are also provided.

  20. Closed Field Coronal Heating Models Inspired by Wave Turbulence

    Science.gov (United States)

    Downs, C.; Lionello, R.; Mikic, Z.; Linker, J.; Velli, M. M.

    2013-12-01

    To simulate the energy balance of coronal plasmas on macroscopic scales, we often require the specification of the coronal heating mechanism in some functional form. To go beyond empirical formulations and to build a more physically motivated heating function, we investigate the wave-turbulence dissipation (WTD) phenomenology for the heating of closed coronal loops. To do so, we employ an implementation of non-WKB equations designed to capture the large-scale propagation, reflection, and dissipation of wave turbulence along a loop. The parameter space of this model is explored by solving the coupled WTD and hydrodynamic equations in 1D for an idealized loop, and the relevance to a range of solar conditions is established by computing solutions for several hundred loops extracted from a realistic 3D coronal field. Due to the implicit dependence of the WTD heating model on loop geometry and plasma properties along the loop and at the footpoints, we find that this model can significantly reduce the number of free parameters when compared to traditional empirical heating models, and still robustly describe a broad range of quiet-sun and active region conditions. The importance of the self-reflection term in producing realistic heating scale heights and thermal non-equilibrium cycles is discussed, and preliminary 3D thermodynamic MHD simulations using this formulation are presented. Research supported by NASA and NSF.

  1. 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…

  2. Identification of a Non-Linear Landing Gear Model Using Nature-Inspired Optimization

    OpenAIRE

    Felipe A.C. Viana; Valder Steffen Jr.; Marcelo A.X. Zanini; Sandro A. Magalhães; Góes, Luiz C.S.

    2008-01-01

    This work deals with the application of a nature-inspired optimization technique to solve an inverse problem represented by the identification of an aircraft landing gear model. The model is described in terms of the landing gear geometry, internal volumes and areas, shock absorber travel, tire type, and gas and oil characteristics of the shock absorber. The solution to this inverse problem can be obtained by using classical gradient-based optimization methods. However, this is a difficult ta...

  3. Aspects Of The Phenomenology Of String-inspired Supergravity Models

    CERN Document Server

    Nelson, B D

    2001-01-01

    In this dissertation we calculate the one loop quantum contributions to soft supersymmetry breaking terms in the scalar potential as well as gaugino masses in supergravity theories regulated à la Pauli- Villars. We find “universal” contributions, independent of the regulator masses and tree level soft supersymmetry breaking, that contribute gaugino masses and A-terms equal to the “anomaly mediated” contributions found in analyses using spurion techniques, as well as a scalar mass term not identified in those analyses. The universal terms are in general modified—and in some cases canceled—by model- dependent terms. We emphasize the model dependence of loop-induced soft terms in the potential, which are much more sensitive to the details of Planck scale physics then are the one loop contributions to gaugino masses. Next, a systematic analysis of soft supersymmetry breaking terms at the one loop level is performed in a large class of string e...

  4. Matrix models with Penner interaction inspired by interacting ribonucleic acid

    Indian Academy of Sciences (India)

    Pradeep Bhadola; N Deo

    2015-02-01

    The Penner interaction known in studies of moduli space of punctured Riemann surfaces is introduced and studied in the context of random matrix model of homo RNA. An analytic derivation of the generating function is given and the corresponding partition function is derived numerically. An additional dependence of the structure combinatorics factor on (related to the size of the matrix and the interaction strength) is obtained. This factor has a strong effect on the structure combinatorics in the low regime. Databases are scanned for real ribonucleic acid (RNA) structures and pairing information for these RNA structures is computationally extracted. Then the genus is calculated for every structure and plotted as a function of length. The genus distribution function is compared with the prediction from the nonlinear (NL) model. The specific heat and distribution of structure with temperature calculated from the NL model shows that the NL inter-action is biased towards planar structures. The second derivative of specific heat changes phase from a double peaked function for small to a single peak for large . Detailed analysis reveals the presence of the double peak only for genus 0 structures, the higher genii behave normally with . Comparable behaviour is found in studies involving interactions of RNA with osmolytes and monovalent cations in unfolding experiments.

  5. Biologically inspired kinematic synergies enable linear balance control of a humanoid robot

    OpenAIRE

    Hauser, Helmut; Neumann, Gerhard; Ijspeert, Auke J.; Maass, Wolfgang

    2011-01-01

    Despite many efforts, balance control of humanoid robots in the presence of unforeseen external or internal forces has remained an unsolved problem. The difficulty of this problem is a consequence of the high dimensionality of the action space of a humanoid robot, due to its large number of degrees of freedom (joints), and of non-linearities in its kinematic chains. Biped biological organisms face similar difficulties, but have nevertheless solved this problem. Experimental data reveal that m...

  6. A Fluid-solid Numerical Model for the Analysis of Bio-inspired UUV

    Science.gov (United States)

    Mitra, Santanu; Krishnamurthy, Nagendra; Tafti, Danesh; Priya, Shashank

    2012-11-01

    This research will describe how a biology-inspired approach to engineering has placed jellyfish at the center of efforts to build next-generation underwater vehicles. In order to swim, jellyfish contract the circular muscles that line the undersurface of their bell. The motion of the bell from the relaxed position to the fully contracted position results in the mesoglea interacting with the surrounding water in such a way that causes the jellyfish to move forward. The present method uses two-dimensional fluid elements and plain strain hyperelastic structural elements for the numerical simulation of the problem. The equations of motion of the fluid are expressed as full N-S equation. A new type of bio-inspired boundary condition has been proposed. A prototype of the jellyfish setup has been developed for the experimental validation of the simulation results. The solution of the coupled system is accomplished by solving the two systems separately with the interaction effects using immersed boundary method. This study will be useful in accurate calculation of pressure distribution, maximum blocking stress, strain rate and actuator system for submerged autonomous vehicle. This study will also help in designing efficient propulsion and thruster mechanism for unmanned underwater vehicle. It is believed that the research presented in this paper advances the understanding of the dynamic behavior of bio-inspired UUV.

  7. Modelling coordination in biological systems

    NARCIS (Netherlands)

    Clarke, D.G.; Oliveira Costa, D.F. de; Arbab, F.

    2004-01-01

    We present an application of the Reo coordination paradigm to provide a compositional formal model for describing and reasoning about the behaviour of biological systems, such as regulatory gene networks. Reo governs the interaction and flow of data between components by allowing the construction of

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

    Science.gov (United States)

    Chen, Fujia; Porter, David; Vollrath, Fritz

    2010-10-01

    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.

  9. 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...

  10. 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

  11. Immune-Inspired Self-Protection Model for Securing Grid

    Directory of Open Access Journals (Sweden)

    Inderpreet Chopra

    2016-03-01

    Full Text Available —The application of human immunology in solving security problems in Grid Computing seems to be a thought-provoking research area. Grid involves large number of dynamic heterogeneous resources. Manually managing the security for such dynamic system is always fault prone. This paper presents the simple immune based model for self-protection (SIMS of grid environment from various attacks like DoS, DDoS, Probing, etc. Like human body helps to identify and respond to harmful pathogens that it doesn't recognize as “self”, in the same manner SIMS incorporates the immunological concepts and principles for safeguarding the grid from various security breaches.

  12. 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.

  13. 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.

  14. Modelling cephalopod-inspired pulsed-jet locomotion for underwater soft robots.

    Science.gov (United States)

    Renda, F; Giorgio-Serchi, F; Boyer, F; Laschi, C

    2015-10-01

    Cephalopods (i.e., octopuses and squids) are being looked upon as a source of inspiration for the development of unmanned underwater vehicles. One kind of cephalopod-inspired soft-bodied vehicle developed by the authors entails a hollow, elastic shell capable of performing a routine of recursive ingestion and expulsion of discrete slugs of fluids which enable the vehicle to propel itself in water. The vehicle performances were found to depend largely on the elastic response of the shell to the actuation cycle, thus motivating the development of a coupled propulsion-elastodynamics model of such vehicles. The model is developed and validated against a set of experimental results performed with the existing cephalopod-inspired prototypes. A metric of the efficiency of the propulsion routine which accounts for the elastic energy contribution during the ingestion/expulsion phases of the actuation is formulated. Demonstration on the use of this model to estimate the efficiency of the propulsion routine for various pulsation frequencies and for different morphologies of the vehicles are provided. This metric of efficiency, employed in association with the present elastodynamics model, provides a useful tool for performing a priori energetic analysis which encompass both the design specifications and the actuation pattern of this new kind of underwater vehicle. PMID:26414068

  15. Bio-Inspired Prototype-Based Models and Applied Gompertzian Dynamics in Cluster Analysis

    OpenAIRE

    Pastorek, Lukáš

    2010-01-01

    The thesis deals with the analysis of the clustering and mapping techniques derived from the principles of the neural and statistical learning and growth theory. The selected branch of the unsupervised bio-inspired prototype-based models is described in terms of the proposed logical framework, which highlights the continuity of these methods with the classical "pure" statistical methods. Moreover, as those methods are broadly understood as the "black boxes" with the unpredictable, unclear and...

  16. 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...... is developed and tested using a physics simulation environment. This study verifies that the neural modules can serve a general purpose regardless of the robot’s specific embodiment. We also believe that our neural modules can be important components for locomotion generation in other complex robotic systems...

  17. Seeing by Touch: Evaluation of a Soft Biologically-Inspired Artificial Fingertip in Real-Time Active Touch

    Directory of Open Access Journals (Sweden)

    Tareq Assaf

    2014-02-01

    Full Text Available 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.

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

    OpenAIRE

    Jim Harkin; Fearghal Morgan; Liam McDaid; Steve Hall; Brian McGinley; Seamus Cawley

    2009-01-01

    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...

  19. GPU Implementation of Real-Time Biologically Inspired Face Detection using CUDA

    Directory of Open Access Journals (Sweden)

    Elham Askary

    2013-07-01

    Full Text Available In this paper massively parallel real-time face detection based on a visual attention and cortex-like mechanism of cognitive vision system is presented. As a first step, we use saliency map model to select salient face regions and HMAX C1 model to extract features from salient input image and then apply mixture of expert neural network to classify multi-view faces from nonface images. The saliency map model is a complex concept for bottom-up attention selection that includes many processes to find face regions in a visual science. Parallel real-time implementation on Graphics Processing Unit (GPU provides a solution for this kind of computationally intensive image processing. By implementing saliency map and HMAX C1 model on a multi-GPU platform using CUDA programming with memory bandwidth, we achieve good performance compared to recent CPU. Running on NVIDIA Geforce 8800 (GTX graphics card at resolution 640×480 detection rate of 97% is achieved. In addition, we evaluate our results using a height speed camera with other parallel methods on face detection application.

  20. Biologically Inspired Design Principles for Scalable, Robust, Adaptive, Decentralized Search and Automated Response (RADAR)

    OpenAIRE

    Moses, Melanie; Banerjee, Soumya

    2010-01-01

    Distributed search problems are ubiquitous in Artificial Life (ALife). Many distributed search problems require identifying a rare and previously unseen event and producing a rapid response. This challenge amounts to finding and removing an unknown needle in a very large haystack. Traditional computational search models are unlikely to find, nonetheless, appropriately respond to, novel events, particularly given data distributed across multiple platforms in a variety of formats and sources wi...

  1. 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.…

  2. 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...

  3. Biologically inspired intelligent decision making: a commentary on the use of artificial neural networks in bioinformatics.

    Science.gov (United States)

    Manning, Timmy; Sleator, Roy D; Walsh, Paul

    2014-01-01

    Artificial neural networks (ANNs) are a class of powerful machine learning models for classification and function approximation which have analogs in nature. An ANN learns to map stimuli to responses through repeated evaluation of exemplars of the mapping. This learning approach results in networks which are recognized for their noise tolerance and ability to generalize meaningful responses for novel stimuli. It is these properties of ANNs which make them appealing for applications to bioinformatics problems where interpretation of data may not always be obvious, and where the domain knowledge required for deductive techniques is incomplete or can cause a combinatorial explosion of rules. In this paper, we provide an introduction to artificial neural network theory and review some interesting recent applications to bioinformatics problems. PMID:24335433

  4. TeV-scale pseudo-Dirac seesaw mechanisms in an E6 inspired model

    Science.gov (United States)

    Cai, Yi; Clarke, Jackson D.; Volkas, Raymond R.; Yanagida, Tsutomu T.

    2016-08-01

    TeV-scale seesaw mechanisms are interesting due to their potential testability at existing collider experiments. Herein we propose an E6 -inspired model allowing a TeV-scale pseudo-Dirac singlet neutrino seesaw mechanism with naturally sizeable Yukawa couplings of O (10-2). The model also contains new U(1) gauge interactions (and associated Z' bosons with which the singlet neutrinos can be produced at colliders), typically long-lived color triplet fermions, SU(2) doublet fermions, and a complex scalar—potentially all at the TeV scale. Additionally we identify three possible explanations for the 750 GeV diphoton excess.

  5. Biologically inspired molecular machines driven by light. Optimal control of a unidirectional rotor

    International Nuclear Information System (INIS)

    We investigate the extent to which unidirectional intramolecular torsional motion can be created in an oriented bicyclic model system driven solely by laser light. We apply the machinery of quantum control via specifically tailored laser pulses to induce such motion, eliminating the need for the thermally constrained steps conventionally used in molecular motor systems. Our approach does not rely on specific details of the potential surfaces to create a preferred direction. Rather, we use matter-field interaction and the tools of coherent optimal control to create a wave packet with nonzero angular momentum among unbound torsional states on an excited electronic surface. Analysis of the results of the control algorithm provides general insight into when and how optimal control theory can find solutions that could not be generated through simple intuitive schemes. We find that, under constrained polarization, the control algorithm reduces to a simple intuitive coherent control strategy wherein a first IR pulse creates a non-stationary wave packet on the ground surface and a subsequent UV pulse transfers it to the excited state. Allowing for polarization shaping, however, we find new control routes that go beyond the intuitive scheme.

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

    International Nuclear Information System (INIS)

    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)

  7. A Bio-inspired Collision Avoidance Model Based on Spatial Information Derived from Motion Detectors Leads to Common Routes.

    Science.gov (United States)

    Bertrand, Olivier J N; Lindemann, Jens P; Egelhaaf, Martin

    2015-11-01

    Avoiding collisions is one of the most basic needs of any mobile agent, both biological and technical, when searching around or aiming toward a goal. We propose a model of collision avoidance inspired by behavioral experiments on insects and by properties of optic flow on a spherical eye experienced during translation, and test the interaction of this model with goal-driven behavior. Insects, such as flies and bees, actively separate the rotational and translational optic flow components via behavior, i.e. by employing a saccadic strategy of flight and gaze control. Optic flow experienced during translation, i.e. during intersaccadic phases, contains information on the depth-structure of the environment, but this information is entangled with that on self-motion. Here, we propose a simple model to extract the depth structure from translational optic flow by using local properties of a spherical eye. On this basis, a motion direction of the agent is computed that ensures collision avoidance. Flying insects are thought to measure optic flow by correlation-type elementary motion detectors. Their responses depend, in addition to velocity, on the texture and contrast of objects and, thus, do not measure the velocity of objects veridically. Therefore, we initially used geometrically determined optic flow as input to a collision avoidance algorithm to show that depth information inferred from optic flow is sufficient to account for collision avoidance under closed-loop conditions. Then, the collision avoidance algorithm was tested with bio-inspired correlation-type elementary motion detectors in its input. Even then, the algorithm led successfully to collision avoidance and, in addition, replicated the characteristics of collision avoidance behavior of insects. Finally, the collision avoidance algorithm was combined with a goal direction and tested in cluttered environments. The simulated agent then showed goal-directed behavior reminiscent of components of the navigation

  8. Identification of a Non-Linear Landing Gear Model Using Nature-Inspired Optimization

    Directory of Open Access Journals (Sweden)

    Felipe A.C. Viana

    2008-01-01

    Full Text Available This work deals with the application of a nature-inspired optimization technique to solve an inverse problem represented by the identification of an aircraft landing gear model. The model is described in terms of the landing gear geometry, internal volumes and areas, shock absorber travel, tire type, and gas and oil characteristics of the shock absorber. The solution to this inverse problem can be obtained by using classical gradient-based optimization methods. However, this is a difficult task due to the existence of local minima in the design space and the requirement of an initial guess. These aspects have motivated the authors to explore a nature-inspired approach using a method known as LifeCycle Model. In the present formulation two nature-based methods, namely the Genetic Algorithms and the Particle Swarm Optimization were used. An optimization problem is formulated in which the objective function represents the difference between the measured characteristics of the system and its model counterpart. The polytropic coefficient of the gas and the damping parameter of the shock absorber are assumed as being unknown: they are considered as design variables. As an illustration, experimental drop test data, obtained under zero horizontal speed, were used in the non-linear landing gear model updating of a small aircraft.

  9. Retina-inspired Filter

    OpenAIRE

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

    2016-01-01

    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 spatiotemporal OPL retina-inspired filter, briefly renamed retina- insp...

  10. Energy Aware Model for Sensor Network : A Nature Inspired Algorithm Approach

    Directory of Open Access Journals (Sweden)

    Doreswamy

    2014-08-01

    Full Text Available In this paper we are proposing to develop energy aw are model for sensor network. In our approach, firs t we used DBSCAN clustering technique to exploit the spatiotemporal correlation among the sensors, then we identified subset of sensors called representati ve sensors which represent the entire network state . And finally we used nature inspired algorithms such as Ant Colony Optimization, Bees Colony Optimization, and Simulated Annealing to find the optimal transmi ssion path for data transmission. We have conducted our experiment on publicly available Intel Berkeley Research Lab dataset and the experimental results shows that consumption of energy can be reduced

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

    Directory of Open Access Journals (Sweden)

    E. Gabrielli

    2016-05-01

    Full Text Available 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.

  12. Integrating systems biology models and biomedical ontologies

    Directory of Open Access Journals (Sweden)

    de Bono Bernard

    2011-08-01

    Full Text Available Abstract Background 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. Results 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. Conclusions 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.

  13. 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.

  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. PMID:11537218

  15. Modeling biological systems with Answer Set Programming

    OpenAIRE

    Thiele, Sven

    2012-01-01

    Biology has made great progress in identifying and measuring the building blocks of life. The availability of high-throughput methods in molecular biology has dramatically accelerated the growth of biological knowledge for various organisms. The advancements in genomic, proteomic and metabolomic technologies allow for constructing complex models of biological systems. An increasing number of biological repositories is available on the web, incorporating thousands of biochemical reactions and ...

  16. Diffractive deep inelastic scattering in an AdS/CFT inspired model: A phenomenological study

    International Nuclear Information System (INIS)

    The analytical treatment of the nonperturbative QCD dynamics is one of the main open questions of the strong interactions. Currently, it is only possible to get some qualitative information about this regime considering other QCD-like theories, as, for example, the N=4 super Yang-Mills theory, where one can perform calculations in the nonperturbative limit of large 't Hooft coupling using the anti-de Sitter space/conformal field theory (AdS/CFT). Recently, the high energy scattering amplitude was calculated in the AdS/CFT approach, applied to deep-inelastic scattering and confronted with the F2 HERA data. In this work we extend the nonperturbative AdS/CFT inspired model for diffractive processes and compare its predictions with a perturbative approach based on the Balitsky-Kovchegov equation. We demonstrate that the AdS/CFT inspired model is not able to describe the current F2D(3) HERA data and predicts a similar behavior to that from the Balitsky-Kovchegov equation in the range 10-7 P -4. At smaller values of xP the diffractive structure function is predicted to be energy independent.

  17. 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].

  18. A physiologically inspired model of auditory stream segregation based on a temporal coherence analysis

    DEFF Research Database (Denmark)

    Christiansen, Simon Krogholt; Jepsen, Morten Løve; Dau, Torsten

    2012-01-01

    The ability to perceptually separate acoustic sources and focus one’s attention on a single source at a time is essential for our ability to use acoustic information. In this study, a physiologically inspired model of human auditory processing [M. L. Jepsen and T. Dau, J. Acoust. Soc. Am. 124, 422...... activity across frequency. Using this approach, the described model is able to quantitatively account for classical streaming phenomena relying on frequency separation and tone presentation rate, such as the temporal coherence boundary and the fission boundary [L. P. A. S. van Noorden, doctoral...... dissertation, Institute for Perception Research, Eindhoven, NL, (1975)]. The same model also accounts for the perceptual grouping of distant spectral components in the case of synchronous presentation. The most essential components of the front-end and back-end processing in the framework of the presented...

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

    Energy Technology Data Exchange (ETDEWEB)

    Bravina, L.V. [University of Oslo, Department of Physics, Oslo (Norway); Fotina, E.S.; Korotkikh, V.L.; Lokhtin, I.P.; Malinina, L.V.; Nazarova, E.N.; Petrushanko, S.V.; Snigirev, A.M. [Lomonosov Moscow State University, Skobeltsyn Institute of Nuclear Physics, Moscow (Russian Federation); Zabrodin, E.E. [Lomonosov Moscow State University, Skobeltsyn Institute of Nuclear Physics, Moscow (Russian Federation); University of Oslo, Department of Physics, Oslo (Norway)

    2015-12-15

    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. The essentially dynamical origin of the flow fluctuations in hydro-inspired freeze-out approach has been established. It is shown that the simple modification of the model via introducing the distribution over spatial anisotropy parameters permits HYDJET++ to reproduce both elliptic and triangular flow fluctuations and related to it eccentricity fluctuations of the initial state at the LHC energy. (orig.)

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

    Energy Technology Data Exchange (ETDEWEB)

    Bravina, L. V. [Department of Physics, University of Oslo, Oslo (Norway); Fotina, E. S.; Korotkikh, V. L.; Lokhtin, I. P., E-mail: igor@lav01.sinp.msu.ru; Malinina, L. V.; Nazarova, E. N.; Petrushanko, S. V.; Snigirev, A. M. [Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow (Russian Federation); Zabrodin, E. E. [Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow (Russian Federation); Department of Physics, University of Oslo, Oslo (Norway)

    2015-12-12

    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. The essentially dynamical origin of the flow fluctuations in hydro-inspired freeze-out approach has been established. It is shown that the simple modification of the model via introducing the distribution over spatial anisotropy parameters permits HYDJET++ to reproduce both elliptic and triangular flow fluctuations and related to it eccentricity fluctuations of the initial state at the LHC energy.

  1. 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.

  2. Action selection performance of a reconfigurable Basal Ganglia inspired model with Hebbian-Bayesian Go-NoGo connectivity

    Directory of Open Access Journals (Sweden)

    Pierre eBerthet

    2012-10-01

    Full Text Available Several studies have shown a strong involvement of the basal ganglia (BG in action selection and dopamine dependent learning. The dopaminergic signal to striatum, the input stage of the BG, has been commonly described as coding a reward prediction error (RPE, i.e. the difference between the predicted and actual reward. The RPE has been hypothesized to be critical in the modulation of the synaptic plasticity in cortico-striatal synapses in the direct and indirect pathway. We developed an abstract computational model of the BG, with a dual pathway structure functionally corresponding to the direct and indirect pathways, and compared its behaviour to biological data as well as other reinforcement learning models. The computations in our model are inspired by Bayesian inference, and the synaptic plasticity changes depend on a three factor Hebbian-Bayesian learning rule based on co-activation of pre- and post-synaptic units and on the value of the RPE. The model builds on a modified Actor-Critic architecture and implements the direct (Go and the indirect (NoGo pathway, as well as the reward prediction (RP system, acting in a complementary fashion. We investigated the performance of the model system when different configurations of the Go, NoGo and RP system were utilized, e.g. using only the Go, NoGo, or RP system, or combinations of those. Learning performance was investigated in several types of learning paradigms, such as learning-relearning, successive learning, stochastic learning, reversal learning and a two-choice task. The RPE and the activity of the model during learning were similar to monkey electrophysiological and behavioural data. Our results, however, show that there is not a unique best way to configure this BG model to handle well all the learning paradigms tested. We thus suggest that an agent might dynamically configure its action selection mode, possibly depending on task characteristics and also on how much time is available.

  3. Action selection performance of a reconfigurable basal ganglia inspired model with Hebbian-Bayesian Go-NoGo connectivity.

    Science.gov (United States)

    Berthet, Pierre; Hellgren-Kotaleski, Jeanette; Lansner, Anders

    2012-01-01

    Several studies have shown a strong involvement of the basal ganglia (BG) in action selection and dopamine dependent learning. The dopaminergic signal to striatum, the input stage of the BG, has been commonly described as coding a reward prediction error (RPE), i.e., the difference between the predicted and actual reward. The RPE has been hypothesized to be critical in the modulation of the synaptic plasticity in cortico-striatal synapses in the direct and indirect pathway. We developed an abstract computational model of the BG, with a dual pathway structure functionally corresponding to the direct and indirect pathways, and compared its behavior to biological data as well as other reinforcement learning models. The computations in our model are inspired by Bayesian inference, and the synaptic plasticity changes depend on a three factor Hebbian-Bayesian learning rule based on co-activation of pre- and post-synaptic units and on the value of the RPE. The model builds on a modified Actor-Critic architecture and implements the direct (Go) and the indirect (NoGo) pathway, as well as the reward prediction (RP) system, acting in a complementary fashion. We investigated the performance of the model system when different configurations of the Go, NoGo, and RP system were utilized, e.g., using only the Go, NoGo, or RP system, or combinations of those. Learning performance was investigated in several types of learning paradigms, such as learning-relearning, successive learning, stochastic learning, reversal learning and a two-choice task. The RPE and the activity of the model during learning were similar to monkey electrophysiological and behavioral data. Our results, however, show that there is not a unique best way to configure this BG model to handle well all the learning paradigms tested. We thus suggest that an agent might dynamically configure its action selection mode, possibly depending on task characteristics and also on how much time is available. PMID:23060764

  4. A trophallaxis inspired model for distributed transport between randomly interacting agents

    CERN Document Server

    Gräwer, Johannes; Mazza, Marco G; Katifori, Eleni

    2016-01-01

    A trophallaxis inspired model for distributed transport between randomly interacting agents 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 work 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.

  5. A Class of LQC--inspired Models for Homogeneous, Anisotropic Cosmology in Higher Dimensional Early Universe

    CERN Document Server

    Rama, S Kalyana

    2016-01-01

    The dynamics of a (3 + 1) dimensional homogeneous anisotropic universe is modified by Loop Quantum Cosmology and, consequently, it has generically a big bounce in the past instead of a big-bang singularity. This modified dynamics can be well described by effective equations of motion. We generalise these effective equations of motion empirically to (d + 1) dimensions. The generalised equations involve two functions and may be considered as a class of LQC -- inspired models for (d + 1) dimensional early universe cosmology. As a special case, one can now obtain a universe which has neither a big bang singularity nor a big bounce but approaches asymptotically a `Hagedorn like' phase in the past where its density and volume remain constant. In a few special cases, we also obtain explicit solutions.

  6. Bottomonium states versus recent experimental observations in the QCD-inspired potential model

    Institute of Scientific and Technical Information of China (English)

    TIAN Wei-Zhao; CAO Lu; YANG You-Chang; CHEN Hong

    2013-01-01

    In the QCD-inspired potential model where the quark-antiquark interaction consists of the usual onegluon-exchange and the mixture of long-range scalar and vector linear confining potentials with the lowest order relativistic correction,we investigate the mass spectra and electromagnetic processes of a bottomonium system by using the Gaussian expansion method.It reveals that the vector component of the mixing confinement is anticonfining and takes around 18.51% of the confining potential.Combining the new experimental data released by Belle,BaBar and LHC,we systematically discuss the energy levels of the bottomonium states and make the predictions of the electromagnetic decays for further experiments.

  7. A biologically inspired attachable, self-standing nanofibrous membrane for versatile use in oil-water separation

    Science.gov (United States)

    Tenjimbayashi, Mizuki; Sasaki, Kaichi; Matsubayashi, Takeshi; Abe, Jyunichiro; Manabe, Kengo; Nishioka, Sachiko; Shiratori, Seimei

    2016-05-01

    Uloborus walckenaerius spider webs provided the inspiration for attachable, self-standing nanofibre sheets. The developed product adds selective wettability against oil-water mixtures to both 2D and 3D materials by attaching or covering them, leading to successful separation through a facile, scalable and low-cost process.Uloborus walckenaerius spider webs provided the inspiration for attachable, self-standing nanofibre sheets. The developed product adds selective wettability against oil-water mixtures to both 2D and 3D materials by attaching or covering them, leading to successful separation through a facile, scalable and low-cost process. Electronic supplementary information (ESI) available: Experimental section, designing procedure, cost, cross sectional SEM, influence of NFs-S components to wettability, thickness, fibre diameter and flexibility, surface tension vs. contact angle, SEM images after extraction of oil, characteristics of testing oil, large scale-fabrication of NFs-S. See DOI: 10.1039/c6nr03349k

  8. 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.

  9. Modeling and optimization of shark-inspired riblet geometries for low drag applications.

    Science.gov (United States)

    Martin, Samuel; Bhushan, Bharat

    2016-07-15

    Fast-swimming sharks have scales with microgrooves called riblets aligned in the direction of fluid flow. Riblets result in water moving efficiently over the surface. In previous experimental and modeling studies, it has been shown that riblets provide drag reduction by lifting vortices formed in turbulent flow decreasing overall shear stresses. Riblets have shown drag reductions on the order of 10% when compared to a flat surface. Modeling data of blade riblets exist showing the role of drag and vortex structures. However, various other geometries have not been modeled. To optimize riblet geometries for low drag, three different geometries were modeled and their drag properties and vortex structures were compared. In addition, a shark-inspired geometry with riblets arranged in a scale pattern was modeled to compare shark scales to these riblet geometries. Through this work, optimal riblet geometries and dimensions were determined. A better understanding of riblet design for drag allows for the fabrication of drag-reducing surfaces in transportation, medical, and industrial applications. Riblet features in the designs can range from the micro- to nanoscale dependent upon the scale of the components. PMID:27131153

  10. 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

    2015-08-01

    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. PMID:26226238

  11. 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”.

  12. Neurobiologically inspired mobile robot navigation and planning

    OpenAIRE

    Mathias Quoy

    2007-01-01

    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”.

  13. Neurobiologically Inspired Mobile Robot Navigation and Planning

    OpenAIRE

    Cuperlier, Nicolas; Quoy, Mathias; Gaussier, Philippe

    2007-01-01

    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”.

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

    OpenAIRE

    Tashkova Katerina; Korošec Peter; Šilc Jurij; Todorovski Ljupčo; Džeroski Sašo

    2011-01-01

    Abstract Background We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs) from measured data, where the models are typically non-linear and have many parameters, the measurements are imperfect due to noise, and the studied system can often be only partially observed. A representative task is to estimate the parameters in a model of the dynamics of endocytosis, i.e., endosome maturation, reflected in a cut-ou...

  15. E6 inspired composite Higgs model and 750 GeV diphoton excess

    CERN Document Server

    Nevzorov, R

    2016-01-01

    In the E6 inspired composite Higgs model (E6CHM) the strongly interacting sector possesses an SU(6)\\times U(1)_B\\times U(1)_L global symmetry. Near scale f\\gtrsim 10 TeV the SU(6) symmetry is broken down to its SU(5) subgroup, that involves the standard model (SM) gauge group. This breakdown of SU(6) leads to a set of pseudo--Nambu--Goldstone bosons (pNGBs) including a SM--like Higgs and a SM singlet pseudoscalar A. Because of the interactions between A and exotic fermions, which ensure the approximate unification of the SM gauge couplings and anomaly cancellation in this model, the couplings of the pseudoscalar A to gauge bosons get induced. As a result, the SM singlet pNGB state A with mass around 750 GeV may give rise to sufficiently large cross section of pp\\to \\gamma\\gamma that can be identified with the recently observed diphoton excess.

  16. Asmparts: assembly of biological model parts.

    Science.gov (United States)

    Rodrigo, Guillermo; Carrera, Javier; Jaramillo, Alfonso

    2007-12-01

    We propose a new computational tool to produce models of biological systems by assembling models from biological parts. Our software not only takes advantage of modularity, but it also enforces standardisation in part characterisation by considering a model of each part. We have used model parts in SBML to design transcriptional networks. Our software is open source, it works in linux and windows platforms, and it could be used to automatically produce models in a server. Our tool not only facilitates model design, but it will also help to promote the establishment of a registry of model parts.

  17. Biomechanically inspired modelling of pedestrian-induced forces on laterally oscillating structures

    Science.gov (United States)

    Bocian, M.; Macdonald, J. H. G.; Burn, J. F.

    2012-07-01

    Despite considerable interest among engineers and scientists, bi-directional interaction between walking pedestrians and lively bridges has still not been well understood. In an attempt to bridge this gap a biomechanically inspired model of the human response to lateral bridge motion is presented and explored. The simple inverted pendulum model captures the key features of pedestrian lateral balance and the resulting forces on the structure. The forces include self-excited components that can be effectively modelled as frequency-dependent added damping and mass to the structure. The results of numerical simulations are in reasonable agreement with recent experimental measurements of humans walking on a laterally oscillating treadmill, and in very good agreement with measurements on full-scale bridges. In contrast to many other models of lateral pedestrian loading, synchronisation with the bridge motion is not involved. A parametric study of the model is conducted, revealing that as pedestrians slow down as a crowd becomes more dense, their resulting lower pacing rates generate larger self-excited forces. For typical pedestrian parameters, the potential to generate negative damping arises for any lateral bridge vibration frequency above 0.43 Hz, depending on the walking frequency. Stability boundaries of the combined pedestrian-structure system are presented in terms of the structural damping ratio and pedestrian-to-bridge mass ratio, revealing complex relations between damping demand and bridge and pedestrian frequencies, due to the added mass effect. Finally it is demonstrated that the model can produce simultaneous self-excited forces on multiple structural modes, and a realistic full simulation of a large number of pedestrians, walking randomly and interacting with a bridge, produces structural behaviour in very good agreement with site observations.

  18. Collective behavior and predation success in a predator-prey model inspired by hunting bats

    Science.gov (United States)

    Lin, Yuan; Abaid, Nicole

    2013-12-01

    We establish an agent-based model to study the impact of prey behavior on the hunting success of predators. The predators and prey are modeled as self-propelled particles moving in a three-dimensional domain and subject to specific sensing abilities and behavioral rules inspired by bat hunting. The predators randomly search for prey. The prey either align velocity directions with peers, defined as "interacting" prey, or swarm "independently" of peer presence; both types of prey are subject to additive noise. In a simulation study, we find that interacting prey using low noise have the maximum predation avoidance because they form localized large groups, while they suffer high predation as noise increases due to the formation of broadly dispersed small groups. Independent prey, which are likely to be uniformly distributed in the domain, have higher predation risk under a low noise regime as they traverse larger spatial extents. These effects are enhanced in large prey populations, which exhibit more ordered collective behavior or more uniform spatial distribution as they are interacting or independent, respectively.

  19. Improved analytic extreme-mass-ratio inspiral model for scoping out eLISA data analysis

    CERN Document Server

    Chua, Alvin J K

    2015-01-01

    The space-based gravitational-wave detector eLISA has been selected as the ESA L3 mission, and the mission design will be finalised by the end of this decade. To prepare for mission formulation over the next few years, several outstanding and urgent questions in data analysis will be addressed using mock data challenges, informed by instrument measurements from the LISA Pathfinder satellite launching at the end of 2015. These data challenges will require accurate and computationally affordable waveform models for anticipated sources such as the extreme-mass-ratio inspirals (EMRIs) of stellar-mass compact objects into massive black holes. Previous data challenges have made use of the well-known analytic EMRI waveforms of Barack and Cutler, which are extremely quick to generate but dephase relative to more accurate waveforms within hours, due to their mismatched radial, polar and azimuthal frequencies. In this paper, we describe an augmented Barack-Cutler model that uses a frequency map to the correct Kerr freq...

  20. 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...

  1. A self-adjoint arrival time operator inspired by measurement models

    International Nuclear Information System (INIS)

    Highlights: • Construction of a self-adjoint arrival time operator inspired by measurements. • Agreement with the strong measurement formula in the low momentum regime. • Review of self-adjoint and non-self-adjoint arrival time operators. • Discussion of the momentum operator on the half-line. • Discussion of the intuitive reasons obstructing self-adjointness. - Abstract: We introduce an arrival time operator which is self-adjoint and, unlike previously proposed arrival time operators, has a close link to simple measurement models. Its spectrum leads to an arrival time distribution which is a variant of the Kijowski distribution (a re-ordering of the current) in the large momentum regime but is proportional to the kinetic energy density in the small momentum regime, in agreement with measurement models. A brief derivation of the latter distribution is given. We make some simple observations about the physical reasons for self-adjointness, or its absence, in both arrival time operators and the momentum operator on the half-line and we also compare our operator with the dwell time operator

  2. Integer Programming Models for Computational Biology Problems

    Institute of Scientific and Technical Information of China (English)

    Giuseppe Lancia

    2004-01-01

    The recent years have seen an impressive increase in the use of Integer Programming models for the solution of optimization problems originating in Molecular Biology. In this survey, some of the most successful Integer Programming approaches are described, while a broad overview of application areas being is given in modern Computational Molecular Biology.

  3. 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. PMID:25566538

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Quantum Biological Channel Modeling and Capacity Calculation

    Directory of Open Access Journals (Sweden)

    Ivan B. Djordjevic

    2012-12-01

    Full Text Available Quantum mechanics has an important role in photosynthesis, magnetoreception, and evolution. There were many attempts in an effort to explain the structure of genetic code and transfer of information from DNA to protein by using the concepts of quantum mechanics. The existing biological quantum channel models are not sufficiently general to incorporate all relevant contributions responsible for imperfect protein synthesis. Moreover, the problem of determination of quantum biological channel capacity is still an open problem. To solve these problems, we construct the operator-sum representation of biological channel based on codon basekets (basis vectors, and determine the quantum channel model suitable for study of the quantum biological channel capacity and beyond. The transcription process, DNA point mutations, insertions, deletions, and translation are interpreted as the quantum noise processes. The various types of quantum errors are classified into several broad categories: (i storage errors that occur in DNA itself as it represents an imperfect storage of genetic information, (ii replication errors introduced during DNA replication process, (iii transcription errors introduced during DNA to mRNA transcription, and (iv translation errors introduced during the translation process. By using this model, we determine the biological quantum channel capacity and compare it against corresponding classical biological channel capacity. We demonstrate that the quantum biological channel capacity is higher than the classical one, for a coherent quantum channel model, suggesting that quantum effects have an important role in biological systems. The proposed model is of crucial importance towards future study of quantum DNA error correction, developing quantum mechanical model of aging, developing the quantum mechanical models for tumors/cancer, and study of intracellular dynamics in general.

  9. Bio-inspired vision

    Science.gov (United States)

    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

  10. Bio-inspired vision

    International Nuclear Information System (INIS)

    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

  11. From biological membranes to biomimetic model membranes

    Directory of Open Access Journals (Sweden)

    Eeman, M.

    2010-01-01

    Full Text Available Biological membranes play an essential role in the cellular protection as well as in the control and the transport of nutrients. Many mechanisms such as molecular recognition, enzymatic catalysis, cellular adhesion and membrane fusion take place into the biological membranes. In 1972, Singer et al. provided a membrane model, called fluid mosaic model, in which each leaflet of the bilayer is formed by a homogeneous environment of lipids in a fluid state including globular assembling of proteins and glycoproteins. Since its conception in 1972, many developments were brought to this model in terms of composition and molecular organization. The main development of the fluid mosaic model was made by Simons et al. (1997 and Brown et al. (1997 who suggested that membrane lipids are organized into lateral microdomains (or lipid rafts with a specific composition and a molecular dynamic that are different to the composition and the dynamic of the surrounding liquid crystalline phase. The discovery of a phase separation in the plane of the membrane has induced an explosion in the research efforts related to the biology of cell membranes but also in the development of new technologies for the study of these biological systems. Due to the high complexity of biological membranes and in order to investigate the biological processes that occur on the membrane surface or within the membrane lipid bilayer, a large number of studies are performed using biomimicking model membranes. This paper aims at revisiting the fundamental properties of biological membranes in terms of membrane composition, membrane dynamic and molecular organization, as well as at describing the most common biomimicking models that are frequently used for investigating biological processes such as membrane fusion, membrane trafficking, pore formation as well as membrane interactions at a molecular level.

  12. 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.

  13. Bridging Physics and Biology Teaching through Modeling

    CERN Document Server

    Hoskinson, Anne-Marie; Zwickl, Benjamin M; Hinko, Kathleen; Caballero, Marcos D

    2013-01-01

    As the frontiers of biology become increasingly interdisciplinary, the physics education community has engaged in ongoing efforts to make physics classes more relevant to life sciences majors. These efforts are complicated by the many apparent differences between these fields, including the types of systems that each studies, the behavior of those systems, the kinds of measurements that each makes, and the role of mathematics in each field. Nonetheless, physics and biology are both fundamental sciences that rely on observations and measurements to construct models of the natural world. In the present theoretical article, we propose that efforts to bridge the teaching of these two disciplines must emphasize shared scientific practices, particularly scientific modeling. We define modeling using language common to both disciplines and highlight how an understanding of the modeling process can help reconcile apparent differences between physics and biology. We elaborate how models can be used for explanatory, pre...

  14. 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, modeling has been discussed in a variety of ways, but often without explicit reference to the diversity of roles models play in scientific practice. We aim to expand and bring clarity to the myriad uses of models in science by presenting a framework from philosopher of biology Jay Odenbaugh that describes five pragmatic strategies of model use in the biological sciences. We then present illustrative examples of each of these roles from an empirical study of an undergraduate biological modeling curriculum, which highlight how students used models to help them frame their research question, explore ideas, and refine their conceptual understanding in an educational setting. Our aim is to begin to explicate the definition of modeling in science in a way that will allow educators and curriculum developers to make informed choices about how and for what purpose modeling enters science classrooms.

  15. Bridging physics and biology teaching through modeling

    Science.gov (United States)

    Hoskinson, Anne-Marie; Couch, Brian A.; Zwickl, Benjamin M.; Hinko, Kathleen A.; Caballero, Marcos D.

    2014-05-01

    As the frontiers of biology become increasingly interdisciplinary, the physics education community has engaged in ongoing efforts to make physics classes more relevant to life science majors. These efforts are complicated by the many apparent differences between these fields, including the types of systems that each studies, the behavior of those systems, the kinds of measurements that each makes, and the role of mathematics in each field. Nonetheless, physics and biology are both sciences that rely on observations and measurements to construct models of the natural world. In this article, we propose that efforts to bridge the teaching of these two disciplines must emphasize shared scientific practices, particularly scientific modeling. We define modeling using language common to both disciplines and highlight how an understanding of the modeling process can help reconcile apparent differences between the teaching of physics and biology. We elaborate on how models can be used for explanatory, predictive, and functional purposes and present common models from each discipline demonstrating key modeling principles. By framing interdisciplinary teaching in the context of modeling, we aim to bridge physics and biology teaching and to equip students with modeling competencies applicable in any scientific discipline.

  16. Unified data model for biological data

    International Nuclear Information System (INIS)

    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)

  17. 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.

  18. 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....

  19. Building phenomenological models of complex biological processes

    Science.gov (United States)

    Daniels, Bryan; Nemenman, Ilya

    2009-11-01

    A central goal of any modeling effort is to make predictions regarding experimental conditions that have not yet been observed. Overly simple models will not be able to fit the original data well, but overly complex models are likely to overfit the data and thus produce bad predictions. Modern quantitative biology modeling efforts often err on the complexity side of this balance, using myriads of microscopic biochemical reaction processes with a priori unknown kinetic parameters to model relatively simple biological phenomena. In this work, we show how Bayesian model selection (which is mathematically similar to low temperature expansion in statistical physics) can be used to build coarse-grained, phenomenological models of complex dynamical biological processes, which have better predictive powers than microscopically correct, but poorely constrained mechanistic molecular models. We illustrate this on the example of a multiply-modifiable protein molecule, which is a simplified description of multiple biological systems, such as an immune receptors and an RNA polymerase complex. Our approach is similar in spirit to the phenomenological Landau expansion for the free energy in the theory of critical phenomena.

  20. 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...

  1. Mesoscopic models of biological membranes

    DEFF Research Database (Denmark)

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

    2006-01-01

    , as model systems to understand the fundamental properties of biomembranes. The properties of lipid bilayers can be studied at different time and length scales. For some properties it is sufficient to envision a membrane as an elastic sheet, while for others it is important to take into account the details...... of the individual atoms. In this review, we focus on an intermediate level, where groups of atoms are lumped into pseudo-particles to arrive at a coarse-grained, or mesoscopic, description of a bilayer, which is subsequently studied using molecular simulation. The aim of this review is to compare various strategies...

  2. Classifying continuous, real-time e-nose sensor data using a bio-inspired spiking network modelled on the insect olfactory system.

    Science.gov (United States)

    Diamond, A; Schmuker, M; Berna, A Z; Trowell, S; Nowotny, Thomas

    2016-04-01

    In many application domains, conventional e-noses are frequently outperformed in both speed and accuracy by their biological counterparts. Exploring potential bio-inspired improvements, we note a number of neuronal network models have demonstrated some success in classifying static datasets by abstracting the insect olfactory system. However, these designs remain largely unproven in practical settings, where sensor data is real-time, continuous, potentially noisy, lacks a precise onset signal and accurate classification requires the inclusion of temporal aspects into the feature set. This investigation therefore seeks to inform and develop the potential and suitability of biomimetic classifiers for use with typical real-world sensor data. Taking a generic classifier design inspired by the inhibition and competition in the insect antennal lobe, we apply it to identifying 20 individual chemical odours from the timeseries of responses of metal oxide sensors. We show that four out of twelve available sensors and the first 30 s (10%) of the sensors' continuous response are sufficient to deliver 92% accurate classification without access to an odour onset signal. In contrast to previous approaches, once training is complete, sensor signals can be fed continuously into the classifier without requiring discretization. We conclude that for continuous data there may be a conceptual advantage in using spiking networks, in particular where time is an essential component of computation. Classification was achieved in real time using a GPU-accelerated spiking neural network simulator developed in our group. PMID:26891474

  3. A bio-inspired device for drag reduction on a three-dimensional model vehicle.

    Science.gov (United States)

    Kim, Dongri; Lee, Hoon; Yi, Wook; Choi, Haecheon

    2016-04-01

    In this paper, we introduce a bio-mimetic device for the reduction of the drag force on a three-dimensional model vehicle, the Ahmed body (Ahmed et al 1984 SAE Technical Paper 840300). The device, called automatic moving deflector (AMD), is designed inspired by the movement of secondary feathers on bird's wing suction surface: i.e., secondary feathers pop up when massive separation occurs on bird's wing suction surface at high angles of attack, which increases the lift force at landing. The AMD is applied to the rear slanted surface of the Ahmed body to control the flow separation there. The angle of the slanted surface considered is 25° at which the drag coefficient on the Ahmed body is highest. The wind tunnel experiment is conducted at Re H  = 1.0 × 10(5)-3.8 × 10(5), based on the height of the Ahmed body (H) and the free-stream velocity (U ∞). Several AMDs of different sizes and materials are tested by measuring the drag force on the Ahmed body, and showed drag reductions up to 19%. The velocity and surface-pressure measurements show that AMD starts to pop up when the pressure in the thin gap between the slanted surface and AMD is much larger than that on the upper surface of AMD. We also derive an empirical formula that predicts the critical free-stream velocity at which AMD starts to operate. Finally, it is shown that the drag reduction by AMD is mainly attributed to a pressure recovery on the slanted surface by delaying the flow separation and suppressing the strength of the longitudinal vortices emanating from the lateral edges of the slanted surface. PMID:26963693

  4. A bio-inspired device for drag reduction on a three-dimensional model vehicle.

    Science.gov (United States)

    Kim, Dongri; Lee, Hoon; Yi, Wook; Choi, Haecheon

    2016-03-10

    In this paper, we introduce a bio-mimetic device for the reduction of the drag force on a three-dimensional model vehicle, the Ahmed body (Ahmed et al 1984 SAE Technical Paper 840300). The device, called automatic moving deflector (AMD), is designed inspired by the movement of secondary feathers on bird's wing suction surface: i.e., secondary feathers pop up when massive separation occurs on bird's wing suction surface at high angles of attack, which increases the lift force at landing. The AMD is applied to the rear slanted surface of the Ahmed body to control the flow separation there. The angle of the slanted surface considered is 25° at which the drag coefficient on the Ahmed body is highest. The wind tunnel experiment is conducted at Re H  = 1.0 × 10(5)-3.8 × 10(5), based on the height of the Ahmed body (H) and the free-stream velocity (U ∞). Several AMDs of different sizes and materials are tested by measuring the drag force on the Ahmed body, and showed drag reductions up to 19%. The velocity and surface-pressure measurements show that AMD starts to pop up when the pressure in the thin gap between the slanted surface and AMD is much larger than that on the upper surface of AMD. We also derive an empirical formula that predicts the critical free-stream velocity at which AMD starts to operate. Finally, it is shown that the drag reduction by AMD is mainly attributed to a pressure recovery on the slanted surface by delaying the flow separation and suppressing the strength of the longitudinal vortices emanating from the lateral edges of the slanted surface.

  5. On validation and invalidation of biological models

    Directory of Open Access Journals (Sweden)

    Anderson James

    2009-05-01

    Full Text Available Abstract Background Very frequently the same biological system is described by several, sometimes competing mathematical models. This usually creates confusion around their validity, ie, which one is correct. However, this is unnecessary since validity of a model cannot be established; model validation is actually a misnomer. In principle the only statement that one can make about a system model is that it is incorrect, ie, invalid, a fact which can be established given appropriate experimental data. Nonlinear models of high dimension and with many parameters are impossible to invalidate through simulation and as such the invalidation process is often overlooked or ignored. Results We develop different approaches for showing how competing ordinary differential equation (ODE based models of the same biological phenomenon containing nonlinearities and parametric uncertainty can be invalidated using experimental data. We first emphasize the strong interplay between system identification and model invalidation and we describe a method for obtaining a lower bound on the error between candidate model predictions and data. We then turn to model invalidation and formulate a methodology for discrete-time and continuous-time model invalidation. The methodology is algorithmic and uses Semidefinite Programming as the computational tool. It is emphasized that trying to invalidate complex nonlinear models through exhaustive simulation is not only computationally intractable but also inconclusive. Conclusion Biological models derived from experimental data can never be validated. In fact, in order to understand biological function one should try to invalidate models that are incompatible with available data. This work describes a framework for invalidating both continuous and discrete-time ODE models based on convex optimization techniques. The methodology does not require any simulation of the candidate models; the algorithms presented in this paper have a

  6. 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.

  7. Simplified models of biological networks.

    Science.gov (United States)

    Sneppen, Kim; Krishna, Sandeep; Semsey, Szabolcs

    2010-01-01

    The function of living cells is controlled by complex regulatory networks that are built of a wide diversity of interacting molecular components. The sheer size and intricacy of molecular networks of even the simplest organisms are obstacles toward understanding network functionality. This review discusses the achievements and promise of a bottom-up approach that uses well-characterized subnetworks as model systems for understanding larger networks. It highlights the interplay between the structure, logic, and function of various types of small regulatory circuits. The bottom-up approach advocates understanding regulatory networks as a collection of entangled motifs. We therefore emphasize the potential of negative and positive feedback, as well as their combinations, to generate robust homeostasis, epigenetics, and oscillations. PMID:20192769

  8. Networks in Cell Biology = Modelling cell biology with networks

    OpenAIRE

    Buchanan, Mark; Caldarelli, Guido; De Los Rios, Paolo; Rao, Francesco; Vendruscolo, M.

    2010-01-01

    The science of complex biological networks is transforming research in areas ranging from evolutionary biology to medicine. This is the first book on the subject, providing a comprehensive introduction to complex network science and its biological applications. With contributions from key leaders in both network theory and modern cell biology, this book discusses the network science that is increasingly foundational for systems biology and the quantitative understanding of living systems. It ...

  9. 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.

  10. 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...

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

    CERN Document Server

    Hetzel, Jamil

    2015-01-01

    The trinification model is an interesting extension of the Standard Model based on the gauge group $SU(3)_C\\times SU(3)_L\\times SU(3)_R$. 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....

  12. Inferring Biologically Relevant Models: Nested Canalyzing Functions

    CERN Document Server

    Hinkelmann, Franziska

    2010-01-01

    Inferring dynamic biochemical networks is one of the main challenges in systems biology. Given experimental data, the objective is to identify the rules of interaction among the different entities of the network. However, the number of possible models fitting the available data is huge and identifying a biologically relevant model is of great interest. Nested canalyzing functions, where variables in a given order dominate the function, have recently been proposed as a framework for modeling gene regulatory networks. Previously we described this class of functions as an algebraic toric variety. In this paper, we present an algorithm that identifies all nested canalyzing models that fit the given data. We demonstrate our methods using a well-known Boolean model of the cell cycle in budding yeast.

  13. Post-16 Biology--Some Model Approaches?

    Science.gov (United States)

    Lock, Roger

    1997-01-01

    Outlines alternative approaches to the teaching of difficult concepts in A-level biology which may help student learning by making abstract ideas more concrete and accessible. Examples include models, posters, and poems for illustrating meiosis, mitosis, genetic mutations, and protein synthesis. (DDR)

  14. 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 membr

  15. Electromagnetic structure and weak decay of pseudoscalar mesons in a light-front QCD-inspired model

    CERN Document Server

    Salcedo, L A M; Hadj-Michef, D; Frederico, T

    2006-01-01

    We study the scaling of the $^3S_1-^1S_0$ meson mass splitting and the pseudoscalar weak decay constants with the mass of the meson, as seen in the available experimental data. We use an effective light-front QCD-inspired dynamical model regulated at short-distances to describe the valence component of the pseudoscalar mesons. The experimentally known values of the mass splittings, decay constants (from global lattice-QCD averages) and the pion charge form factor up to 4 [GeV/c]$^2$ are reasonably described by the model

  16. 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.

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

    International Nuclear Information System (INIS)

    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)

  18. A stochastic vision-based model inspired by zebrafish collective behaviour in heterogeneous environments.

    Science.gov (United States)

    Collignon, Bertrand; Séguret, Axel; Halloy, José

    2016-01-01

    Collective motion is one of the most ubiquitous behaviours displayed by social organisms and has led to the development of numerous models. Recent advances in the understanding of sensory system and information processing by animals impels one to revise classical assumptions made in decisional algorithms. In this context, we present a model describing the three-dimensional visual sensory system of fish that adjust their trajectory according to their perception field. Furthermore, we introduce a stochastic process based on a probability distribution function to move in targeted directions rather than on a summation of influential vectors as is classically assumed by most models. In parallel, we present experimental results of zebrafish (alone or in group of 10) swimming in both homogeneous and heterogeneous environments. We use these experimental data to set the parameter values of our model and show that this perception-based approach can simulate the collective motion of species showing cohesive behaviour in heterogeneous environments. Finally, we discuss the advances of this multilayer model and its possible outcomes in biological, physical and robotic sciences. PMID:26909173

  19. 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…

  20. Biological Event Modeling for Response Planning

    Science.gov (United States)

    McGowan, Clement; Cecere, Fred; Darneille, Robert; Laverdure, Nate

    People worldwide continue to fear a naturally occurring or terrorist-initiated biological event. Responsible decision makers have begun to prepare for such a biological event, but critical policy and system questions remain: What are the best courses of action to prepare for and react to such an outbreak? Where resources should be stockpiled? How many hospital resources—doctors, nurses, intensive-care beds—will be required? Will quarantine be necessary? Decision analysis tools, particularly modeling and simulation, offer ways to address and help answer these questions.

  1. 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...... timed automata and most recently hybrid systems using the tool Uppaal SMC. In this paper we enable the application of SMC to complex biological systems, by combining Uppaal SMC with ANIMO, a plugin of the tool Cytoscape used by biologists, as well as with SimBiology®, a plugin of Matlab to simulate...

  2. A patient-specific EMG-driven neuromuscular model for the potential use of human-inspired gait rehabilitation robots.

    Science.gov (United States)

    Ma, Ye; Xie, Shengquan; Zhang, Yanxin

    2016-03-01

    A patient-specific electromyography (EMG)-driven neuromuscular model (PENm) is developed for the potential use of human-inspired gait rehabilitation robots. The PENm is modified based on the current EMG-driven models by decreasing the calculation time and ensuring good prediction accuracy. To ensure the calculation efficiency, the PENm is simplified into two EMG channels around one joint with minimal physiological parameters. In addition, a dynamic computation model is developed to achieve real-time calculation. To ensure the calculation accuracy, patient-specific muscle kinematics information, such as the musculotendon lengths and the muscle moment arms during the entire gait cycle, are employed based on the patient-specific musculoskeletal model. Moreover, an improved force-length-velocity relationship is implemented to generate accurate muscle forces. Gait analysis data including kinematics, ground reaction forces, and raw EMG signals from six adolescents at three different speeds were used to evaluate the PENm. The simulation results show that the PENm has the potential to predict accurate joint moment in real-time. The design of advanced human-robot interaction control strategies and human-inspired gait rehabilitation robots can benefit from the application of the human internal state provided by the PENm.

  3. 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.

  4. Stress in Adolescents with a Chronically Ill Parent: Inspiration from Rolland’s Family Systems-Illness Model

    OpenAIRE

    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 this Dutch study. The Dutch Stress Questionnaire for Children was used to measure child report of stress. Ill parents completed the Beck Depression Inventory. Children filled in a scale of the Invent...

  5. Facial expression recognition using biologically inspired features and SVM%基于生物启发特征和SVM的人脸表情识别

    Institute of Scientific and Technical Information of China (English)

    穆国旺; 王阳; 郭蔚

    2014-01-01

    将C1特征应用于静态图像人脸表情识别,提出了一种新的基于生物启发特征和SVM的表情识别算法。提取人脸图像的C1特征,利用PCA+LDA方法对特征进行降维,用SVM进行分类。在JAFFE和Extended Cohn-Kanade(CK+)人脸表情数据库上的实验结果表明,该算法具有较高的识别率,是一种有效的人脸表情识别方法。%C1 features are introduced to facial expression recognition for static images, and a new algorithm for facial expression recognition based on Biologically Inspired Features(BIFs)and SVM is proposed. C1 features of the facial images are extracted, PCA+LDA method is used to reduce the dimensionality of the C1 features, SVM is used for classifi-cation of the expression. The experiments on the JAFFE and Extended Cohn-Kanade(CK+)facial expression data sets show the effectiveness and the good performance of the algorithm.

  6. An Architecture for Alert Correlation Inspired By a Comprehensive Model of Human Immune System

    Directory of Open Access Journals (Sweden)

    Mehdi Bateni

    2014-11-01

    Full Text Available Alert correlation is the process of analyzing, relating and fusing the alerts generated by one or more Intrusion Detection Systems (IDS in order to provide a high-level and comprehensive view of the security situation of the system or network. Different approaches, such as rule-based, prerequisites consequences-based, learning-based and similarity-based approach are used in correlation process. In this paper, a new AIS-inspired architecture is presented for alert correlation. Different aspects of human immune system (HIS are considered to design iCorrelator. Its three-level structure is inspired by three types of responses in human immune system: the innate immune system's response, the adaptive immune system's primary response, and the adaptive immune system's secondary response. iCorrelator also uses the concepts of Danger theory to decrease the computational complexity of the correlation process without considerable accuracy degradation. By considering the importance of signals in Danger theory, a new alert selection policy is introduced. It is named Enhanced Random Directed Time Window (ERDTW and is used to classify time slots to Relevant (Dangerous and Irrelevant (Safe slots based on the context information gathered during previous correlations. iCorrelator is evaluated using the DARPA 2000 dataset and a netForensics honeynet data. Completeness, soundness, false correlation rate and the execution time are investigated. Results show that iCorrelator generates attack graph with an acceptable accuracy that is comparable to the best known solutions. Moreover, inspiring by the Danger theory and using context information, the computational complexity of the correlation process is decreased considerably and makes it more applicable to online correlation.

  7. 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

  8. 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.

  9. Graphical Modelling in Genetics and Systems Biology

    OpenAIRE

    Scutari, Marco

    2012-01-01

    Graphical modelling has a long history in statistics as a tool for the analysis of multivariate data, starting from Wright's path analysis and Gibbs' applications to statistical physics at the beginning of the last century. In its modern form, it was pioneered by Lauritzen and Wermuth and Pearl in the 1980s, and has since found applications in fields as diverse as bioinformatics, customer satisfaction surveys and weather forecasts. Genetics and systems biology are unique among these fields in...

  10. Computational Biology: Modeling Chronic Renal Allograft Injury.

    Science.gov (United States)

    Stegall, Mark D; Borrows, Richard

    2015-01-01

    New approaches are needed to develop more effective interventions to prevent long-term rejection of organ allografts. Computational biology provides a powerful tool to assess the large amount of complex data that is generated in longitudinal studies in this area. This manuscript outlines how our two groups are using mathematical modeling to analyze predictors of graft loss using both clinical and experimental data and how we plan to expand this approach to investigate specific mechanisms of chronic renal allograft injury.

  11. Formulation of Biologically-Inspired Silk-Based Drug Carriers for Pulmonary Delivery Targeted for Lung Cancer

    OpenAIRE

    Sally Yunsun Kim; Deboki Naskar; Kundu, Subhas C.; Bishop, David P.; Doble, Philip A.; Boddy, Alan V.; Hak-Kim Chan; Ivan B. Wall; Wojciech Chrzanowski

    2015-01-01

    The benefits of using silk fibroin, a major protein in silk, are widely established in many biomedical applications including tissue regeneration, bioactive coating and in vitro tissue models. The properties of silk such as biocompatibility and controlled degradation are utilized in this study to formulate for the first time as carriers for pulmonary drug delivery. Silk fibroin particles are spray dried or spray-freeze-dried to enable the delivery to the airways via dry powder inhalers. The a...

  12. Modeling perspectives on echolocation strategies inspired by bats flying in groups.

    Science.gov (United States)

    Lin, Yuan; Abaid, Nicole

    2015-12-21

    Bats navigating with echolocation - which is a type of active sensing achieved by interpreting echoes resulting from self-generated ultrasonic pulses - exhibit unique behaviors during group flight. While bats may benefit from eavesdropping on their peers׳ echolocation, they also potentially suffer from confusion between their own and peers׳ pulses, caused by an effect called frequency jamming. This hardship of group flight is supported by experimental observations of bats simplifying their sound-scape by shifting their pulse frequencies or suppressing echolocation altogether. Here, we investigate eavesdropping and varying pulse emission rate from a modeling perspective to understand these behaviors׳ potential benefits and detriments. We define an agent-based model of echolocating bats avoiding collisions in a three-dimensional tunnel. Through simulation, we show that bats with reasonably accurate eavesdropping can reduce collisions compared to those neglecting information from peers. In large populations, bats minimize frequency jamming by decreasing pulse emission rate, while collision risk increases; conversely, increasing pulse emission rate minimizes collisions by allowing more sensing information generated per bat. These strategies offer benefits for both biological and engineered systems, since frequency jamming is a concern in systems using active sensing. PMID:26386143

  13. Modeling perspectives on echolocation strategies inspired by bats flying in groups.

    Science.gov (United States)

    Lin, Yuan; Abaid, Nicole

    2015-12-21

    Bats navigating with echolocation - which is a type of active sensing achieved by interpreting echoes resulting from self-generated ultrasonic pulses - exhibit unique behaviors during group flight. While bats may benefit from eavesdropping on their peers׳ echolocation, they also potentially suffer from confusion between their own and peers׳ pulses, caused by an effect called frequency jamming. This hardship of group flight is supported by experimental observations of bats simplifying their sound-scape by shifting their pulse frequencies or suppressing echolocation altogether. Here, we investigate eavesdropping and varying pulse emission rate from a modeling perspective to understand these behaviors׳ potential benefits and detriments. We define an agent-based model of echolocating bats avoiding collisions in a three-dimensional tunnel. Through simulation, we show that bats with reasonably accurate eavesdropping can reduce collisions compared to those neglecting information from peers. In large populations, bats minimize frequency jamming by decreasing pulse emission rate, while collision risk increases; conversely, increasing pulse emission rate minimizes collisions by allowing more sensing information generated per bat. These strategies offer benefits for both biological and engineered systems, since frequency jamming is a concern in systems using active sensing.

  14. Explaining the CMS $eejj$ and $e \\slashed {p}_T jj$ Excess and Leptogenesis in Superstring Inspired $E_6$ Models

    CERN Document Server

    Dhuria, Mansi; Rangarajan, Raghavan; Sarkar, Utpal

    2015-01-01

    We show that superstring inspired $E_6$ models can explain both the recently detected excess $eejj$ and $e \\slashed p_T jj$ signals at CMS, and also allow for leptogenesis. Working in a R-parity conserving low energy supersymmetric effective model, we show that the excess CMS events can be produced via the decay of exotic sleptons in alternative left-right symmetric models of $E_6$, which can also accommodate leptogenesis at a high scale. On the other hand, either the $eejj$ excess or the $e \\slashed p_T jj$ excess can be produced via the decays of right handed gauge bosons, but some of these scenarios may not accommodate letptogenesis as there will be strong $B-L$ violation at low energy, which, along with the anomalous fast electroweak $B+L$ violation, will wash out all baryon asymmetry. Baryogenesis below the electroweak scale may then need to be implemented in these models.

  15. Modeling Interactions between Multicomponent Vesicles and Antimicrobial Peptide-Inspired Nanoparticles.

    Science.gov (United States)

    Chu, Xiaolei; Aydin, Fikret; Dutt, Meenakshi

    2016-08-23

    We examine the interaction between peptide-inspired nanoparticles, or nanopins, and multicomponent vesicles using the dissipative particle dynamics simulation technique. We study the role of nanopin architecture and cholesterol concentration on the binding of the nanopins to the lipid bilayer, their insertion, and postembedding self-organization. We find the insertion to be triggered by enthalpically unfavorable interactions between the hydrophilic solvent and the lipophilic components of the nanopins. The nanopins are observed to form aggregates in solution, insert into the bilayer, and disassemble into the individual nanopins following the insertion process. We examine factors that influence the orientation of the nanopins in the host vesicle. We report the length of the hydrophilic segment of the nanopins to regulate their orientation within the clusters before the embedding process and in the bilayer, after the postinsertion disassembly of the aggregates. The orientation angle distribution for a given nanopin architecture is found to be driven by energy minimization. In addition, higher concentration of cholesterol is observed to constrain the orientation of the nanopins. We also report thermal fluctuations to induce transverse diffusion of nanopins with specific architectures. The incidence of transverse diffusion is observed to decrease with the concentration of cholesterol. Our results can provide guidelines for designing peptide-inspired nanoparticles or macromolecules that can interface with living cells to serve as sensors for applications in medicine, sustainability, and energy. PMID:27434532

  16. 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.

  17. Stochasticity in cell biology: Modeling across levels

    Science.gov (United States)

    Pedraza, Juan Manuel

    2009-03-01

    Effective modeling of biological processes requires focusing on a particular level of description, and this requires summarizing de details of lower levels into effective variables and properly accounting for the constrains that other levels impose. In the context of stochasticity in gene expression, I will show how the details of the stochastic process can be characterized by a few effective parameters, which facilitates modeling but complicates interpretation of current experiments. I will show how the resulting noise can provide advantageous or deleterious phenotypic fluctuation and how noise control in the copy number control system of plasmids can change the selective pressures. This system illustrates the direct connection between molecular dynamics and evolutionary dynamics.

  18. Falsifying Oscillation Properties of Parametric Biological Models

    Directory of Open Access Journals (Sweden)

    Thao Dang

    2013-08-01

    Full Text Available We propose an approach to falsification of oscillation properties of parametric biological models, based on the recently developed techniques for testing continuous and hybrid systems. In this approach, an oscillation property can be specified using a hybrid automaton, which is then used to guide the exploration in the state and input spaces to search for the behaviors that do not satisfy the property. We illustrate the approach with the Laub-Loomis model for spontaneous oscillations during the aggregation stage of Dictyostelium.

  19. An Inspire-Konform 3d Building Model of Bavaria Using Cadastre Information, LIDAR and Image Matching

    Science.gov (United States)

    Roschlaub, R.; Batscheider, J.

    2016-06-01

    The federal governments of Germany endeavour to create a harmonized 3D building data set based on a common application schema (the AdV-CityGML-Profile). The Bavarian Agency for Digitisation, High-Speed Internet and Surveying has launched a statewide 3D Building Model with standardized roof shapes for all 8.1 million buildings in Bavaria. For the acquisition of the 3D Building Model LiDAR-data or data from Image Matching are used as basis in addition with the building ground plans of the official cadastral map. The data management of the 3D Building Model is carried out by a central database with the usage of a nationwide standardized CityGML-Profile of the AdV. The update of the 3D Building Model for new buildings is done by terrestrial building measurements within the maintenance process of the cadaster and from image matching. In a joint research project, the Bavarian State Agency for Surveying and Geoinformation and the TUM, Chair of Geoinformatics, transformed an AdV-CityGML-Profilebased test data set of Bavarian LoD2 building models into an INSPIRE-compliant schema. For the purpose of a transformation of such kind, the AdV provides a data specification, a test plan for 3D Building Models and a mapping table. The research project examined whether the transformation rules defined in the mapping table, were unambiguous and sufficient for implementing a transformation of LoD2 data based on the AdV-CityGML-Profile into the INSPIRE schema. The proof of concept was carried out by transforming production data of the Bavarian 3D Building Model in LoD2 into the INSPIRE BU schema. In order to assure the quality of the data to be transformed, the test specifications according to the test plan for 3D Building Models of the AdV were carried out. The AdV mapping table was checked for completeness and correctness and amendments were made accordingly.

  20. Inspirational Journey

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Artists from across Europe and Asia ventured into the remote Chinese countryside to seek inspiration from the Miao Ethnic group "I’ve never been to Asia before and everything is strange and wonderful:supermarkets and shopping mails,even the air- port seemed exotic!"wrote Ula Sickle,a choreographer from Poland on her blog under the name"chopstick diaries."Ula was one of the 18 foreign and domestic artists participating in a cultural exchange project called the Pointe to Point: Asia-Europe Dance Forum.It aims to empower aspiring young artists from Asia and Europe to reflect upon their views of

  1. Fly's proprioception-inspired micromachined strain-sensing structure: idea, design, modeling and simulation, and comparison with experimental results

    International Nuclear Information System (INIS)

    A new strain-sensing structure inspired from insect's (especially the Fly) propricoception sensor is devised. The campaniform sensillum is a strain-sensing microstructure with very high sensitivity despite its small dimension (diameter ∼10 μm in a relatively stiff material of insect's exocuticle (E = ∼109 Pa). Previous work shows that the high sensitivity of this structure towards strain is due to its membrane-in-recess- and strainconcentrating-hole-features. Based on this inspiration, we built similar structure using silicon micromachining technology. Then a simple characterisation setup was devised. Here, we present briefly, finite-element modeling and simulation based on this actual sample preparation for the characterisation. As comparison and also to understand mechanical features responsible for the strain-sensitivity, we performed the modeling on different mechanical structures: bulk chunk, blind-hole, through-hole, surface membrane, and membrane-in-recess. The actual experimental characterisation was performed previously using optical technique to membrane in-recess micromachined Si structure. The FEM simulation results confirm that the bending stress and strain are concentrated in the hole-vicinity. The membrane inside the hole acts as displacement transducer. The FEM is in conformity with previous analytical results, as well as the optical characterisation result. The end goal is to build a new type MEMS strain sensor

  2. Fly's proprioception-inspired micromachined strain-sensing structure: idea, design, modeling and simulation, and comparison with experimental results

    Science.gov (United States)

    Wicaksono, D. H. B.; Zhang, L.-J.; Pandraud, G.; French, P. J.; Vincent, J. F. V.

    2006-04-01

    A new strain-sensing structure inspired from insect's (especially the Fly) propricoception sensor is devised. The campaniform sensillum is a strain-sensing microstructure with very high sensitivity despite its small dimension (diameter ~10 µm in a relatively stiff material of insect's exocuticle (E = ~109 Pa). Previous work shows that the high sensitivity of this structure towards strain is due to its membrane-in-recess- and strainconcentrating- hole- features. Based on this inspiration, we built similar structure using silicon micromachining technology. Then a simple characterisation setup was devised. Here, we present briefly, finite-element modeling and simulation based on this actual sample preparation for the characterisation. As comparison and also to understand mechanical features responsible for the strain-sensitivity, we performed the modeling on different mechanical structures: bulk chunk, blind-hole, thorugh-hole, surface membrane, and membrane-in-recess. The actual experimental characterisation was performed previously using optical technique to membranein- recess micromachined Si structure. The FEM simulation results confirm that the bending stress and strain are concentrated in the hole-vicinity. The membrane inside the hole acts as displacement transducer. The FEM is in conformity with previous analytical results, as well as the optical characterisation result. The end goal is to build a new type MEMS strain sensor.

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

    OpenAIRE

    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” tex...

  4. Mathematical modeling in biology: A critical assessment

    International Nuclear Information System (INIS)

    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

  5. 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.

  6. 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.

  7. From cellular mechanotransduction to biologically inspired engineering: 2009 Pritzker Award Lecture, BMES Annual Meeting October 10, 2009.

    Science.gov (United States)

    Ingber, Donald E

    2010-03-01

    This article is based on a lecture I presented as the recipient of the 2009 Pritzker Distinguished Lecturer Award at the Biomedical Engineering Society annual meeting in October 2009. Here, I review more than thirty years of research from my laboratory, beginning with studies designed to test the theory that cells use tensegrity (tensional integrity) architecture to stabilize their shape and sense mechanical signals, which I believed to be critical for control of cell function and tissue development. Although I was trained as a cell biologist, I found that the tools I had at my disposal were insufficient to experimentally test these theories, and thus I ventured into engineering to find critical solutions. This path has been extremely fruitful as it has led to confirmation of the critical role that physical forces play in developmental control, as well as how cells sense and respond to mechanical signals at the molecular level through a process known as cellular mechanotransduction. Many of the predictions of the cellular tensegrity model relating to cell mechanical behaviors have been shown to be valid, and this vision of cell structure led to discovery of the central role that transmembrane adhesion receptors, such as integrins, and the cytoskeleton play in mechanosensing and mechanochemical conversion. In addition, these fundamental studies have led to significant unexpected technology fallout, including development of micromagnetic actuators for non-invasive control of cellular signaling, microfluidic systems as therapeutic extracorporeal devices for sepsis therapy, and new DNA-based nanobiotechnology approaches that permit construction of artificial tensegrities that mimic properties of living materials for applications in tissue engineering and regenerative medicine. PMID:20140519

  8. Investigation of Fish Caudal Fin Locomotion Using a Bio-inspired Robotic Model

    Directory of Open Access Journals (Sweden)

    Ziyu Ren

    2016-05-01

    Full Text Available Due to its advantages of realizing repeatable experiments, collecting data and isolating key factors, the bio-robotic model is becoming increasingly important in the study of biomechanics. The caudal fin of fish has long been understood to be central to propulsion performance, yet its contribution to manoeuverability, especially for homocercal caudal fin, has not been studied in depth. In the research outlined in this paper, we designed and fabricated a robotic caudal fin to mimic the morphology and the three-dimensional (3D locomotion of the tail of the Bluegill Sunfish (Lepomis macrochirus. We applied heave and pitch motions to the robot to model the movement of the caudal peduncle of its biological counterpart. Force measurements and 2D and 3D digital particle image velocimetry were then conducted under different movement patterns and flow speeds. From the force data, we found the addition of the 3D caudal fin locomotion significantly enhanced the lift force magnitude. The phase difference between the caudal fin ray and peduncle motion was a key factor in simultaneously controlling the thrust and lift. The increased flow speed had a negative impact on the generation of lift force. From the average 2D velocity field, we observed that the vortex wake directed water both axially and vertically, and formed a jet like structure with notable wake velocity. The 3D instantaneous velocity field at 0.6 T indicated the 3D motion of the caudal fin may result in asymmetry wake flow patterns relative to the mid-sagittal plane and change the heading direction of the shedding vortexes. Based on these results, we hypothesized that live fish may actively tune the movement between the caudal fin rays and the peduncle to change the wake structure behind the tail and hence obtain different thrust and lift forces, which contributes to its high manoeuvrability.

  9. 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. PMID:27635225

  10. Unit testing, model validation, and biological simulation

    Science.gov (United States)

    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.

  11. Unit testing, model validation, and biological simulation

    Science.gov (United States)

    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. PMID:27635225

  12. 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.

  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. An electrostatic model for biological cell division

    CERN Document Server

    Faraggi, Eshel

    2010-01-01

    Probably the most fundamental processes for biological systems is their ability to create themselves through the use of cell division and cell differentiation. In this work a simple physical model is proposed for biological cell division. The model consists of a positive ionic gradient across the cell membrane, and concentration of charge at the nodes of the spindle and on the chromosomes. A simple calculation, based on Coulomb's Law, shows that under such circumstances a chromosome will tend to break up to its constituent chromatids and that the chromatids will be separated by a distance that is an order of thirty percent of the distance between the spindle nodes. Further repulsion between the nodes will tend to stretch the cell and eventually break the cell membrane between the separated chromatids, leading to cell division. The importance of this work is in continuing the understanding of the electromagnetic basis of cell division and providing it with an analytical model. A central implication of this and...

  15. A Fly-Inspired Mushroom Bodies Model for Sensory-Motor Control Through Sequence and Subsequence Learning.

    Science.gov (United States)

    Arena, Paolo; Calí, Marco; Patané, Luca; Portera, Agnese; Strauss, Roland

    2016-09-01

    Classification and sequence learning are relevant capabilities used by living beings to extract complex information from the environment for behavioral control. The insect world is full of examples where the presentation time of specific stimuli shapes the behavioral response. On the basis of previously developed neural models, inspired by Drosophila melanogaster, a new architecture for classification and sequence learning is here presented under the perspective of the Neural Reuse theory. Classification of relevant input stimuli is performed through resonant neurons, activated by the complex dynamics generated in a lattice of recurrent spiking neurons modeling the insect Mushroom Bodies neuropile. The network devoted to context formation is able to reconstruct the learned sequence and also to trace the subsequences present in the provided input. A sensitivity analysis to parameter variation and noise is reported. Experiments on a roving robot are reported to show the capabilities of the architecture used as a neural controller. PMID:27354193

  16. 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 for...

  17. 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...

  18. Multiscale mechanical modeling of soft biological tissues

    Science.gov (United States)

    Stylianopoulos, Triantafyllos

    2008-10-01

    Soft biological tissues include both native and artificial tissues. In the human body, tissues like the articular cartilage, arterial wall, and heart valve leaflets are examples of structures composed of an underlying network of collagen fibers, cells, proteins and molecules. Artificial tissues are less complex than native tissues and mainly consist of a fiber polymer network with the intent of replacing lost or damaged tissue. Understanding of the mechanical function of these materials is essential for many clinical treatments (e.g. arterial clamping, angioplasty), diseases (e.g. arteriosclerosis) and tissue engineering applications (e.g. engineered blood vessels or heart valves). This thesis presents the derivation and application of a multiscale methodology to describe the macroscopic mechanical function of soft biological tissues incorporating directly their structural architecture. The model, which is based on volume averaging theory, accounts for structural parameters such as the network volume fraction and orientation, the realignment of the fibers in response to strain, the interactions among the fibers and the interactions between the fibers and the interstitial fluid in order to predict the overall tissue behavior. Therefore, instead of using a constitutive equation to relate strain to stress, the tissue microstructure is modeled within a representative volume element (RVE) and the macroscopic response at any point in the tissue is determined by solving a micromechanics problem in the RVE. The model was applied successfully to acellular collagen gels, native blood vessels, and electrospun polyurethane scaffolds and provided accurate predictions for permeability calculations in isotropic and oriented fiber networks. The agreement of model predictions with experimentally determined mechanical properties provided insights into the mechanics of tissues and tissue constructs, while discrepancies revealed limitations of the model framework.

  19. Experimental models to study cholangiocyte biology

    Institute of Scientific and Technical Information of China (English)

    Pamela S. Tietz; Xian-Ming Chen; Ai-Yu Gong; Robert C. Huebert; Anatoliy Masyuk; Tatyana Masyuk; Patrick L. Splinter; Nicholas F. LaRusso

    2002-01-01

    Cholangiocytes-the epithelial cells which line the bileducts-are increasingly recognized as importanttransporting epithelia actively involved in the absorptionand secretion of water, ions, and solutes. Thisrecognition is due in part to the recent development ofnew experimental models. New biologic concepts haveemerged including the identification and topography ofreceptors and flux proteins on the apical and/orbasolateral membrane which are involved in the molecularmechanisms of ductal bile secretion. Individually isolatedand/or perfused bile duct units from livers of rats andmice serve as new, physiologically relevant in vitromodels to study cholangiocyte transport. Biliary treedimensions and novel insights into anatomic remodeling ofproliferating bile ducts have emerged from three-dimensional reconstruction using CT scanning andsophisticated software. Moreover, new pathologicconcepts have arisen regarding the interaction ofcholangiocytes with pathogens such as Cryptosporidiumparvum. These concepts and associated methodologiesmay provide the framework to develop new therapies for the cholangiopathies, a group of important hepatobiliarydiseases in which cholangiocytes are the target cell.Tietz PS, Chen XM, Gong AY, Huebert RC, Masyuk A, MasyukT, Splinter PL, LaRusso NF. Experimental models to studycoholangiocyte biology.

  20. Model Checking the Biological Model of Membrane Computing with Probabilistic Symbolic Model Checker by Using Two Biological Systems

    Directory of Open Access Journals (Sweden)

    Ravie c. Muniyandi

    2010-01-01

    Full Text Available Problem statement: Membrane computing formalism has provided better modeling capabilities for biological systems in comparison to conventional mathematical models. Model checking could be used to reason about the biological system in detail and with precision by verifying formally whether membrane computing model meets the properties of the system. Approach: This study was carried to investigate the preservation of properties of two biological systems that had been modeled and simulated in membrane computing by a method of model checking using PRISM. The two biological systems were prey-predator population and signal processing in the legend-receptor networks of protein TGF-ß. Results: The model checking of membrane computing model of the biological systems with five different properties showed that the properties of the biological systems could be preserved in the membrane computing model. Conclusion: Membrane computing model not only provides a better approach in representing and simulating a biological system but also able to sustain the basic properties of the system.

  1. 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.

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

    CERN Document Server

    Kitazawa, N

    2015-01-01

    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 ...

  3. 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

    2015-10-01

    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. PMID:26346190

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

    International Nuclear Information System (INIS)

    We use variationally improved perturbation theory (VIPT) for calculating the elastic form factors and charge radii of D, Ds, B, Bs and Bc 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 Q2, hinting at a workable range of Q2 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)

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

    Indian Academy of Sciences (India)

    Bhaskar Jyoti Hazarika; D K choudhury

    2015-01-01

    We use variationally improved perturbation theory (VIPT) for calculating the elastic form factors and charge radii of , $D_{s}$, $B$, $B_{s}$ 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 2, hinting at a workable range of 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.

  6. 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.

  7. Computational Biology: A Programming Perspective

    DEFF Research Database (Denmark)

    Hartmann, Lars; Jones, Neil; Simonsen, Jakob Grue;

    2011-01-01

    identify some strengths and shortcomings from a programming perspective. To show concretely what one could see as programming in biocomputing, we outline (from recent work) a computation model and a small programming language that are biologically more plausible than existing silicon-inspired models....... Whether or not the model is biologically plausible in an absolute sense, we believe it sets a standard for a biological device that can be both universal and programmable....

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

    International Nuclear Information System (INIS)

    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. 0-300 from vertical) were the most effective at generating body roll, whereas tails operating at steeper angles (i.e. 45-600) 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.

  9. Inspiral into Gargantua

    CERN Document Server

    Gralla, Samuel E; Warburton, Niels

    2016-01-01

    We model the inspiral of a compact object into a more massive black hole rotating very near the theoretical maximum. We find that once the body enters the near-horizon regime the gravitational radiation is characterized by a constant frequency, equal to (twice) the horizon frequency, with an exponentially damped profile. This contrasts with the usual "chirping" behavior and, if detected, would constitute a "smoking gun" for a near-extremal black hole in nature.

  10. 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.

  11. Towards a Brain-inspired Information Processing System: Modelling and Analysis of Synaptic Dynamics

    OpenAIRE

    El-Laithy, Karim

    2012-01-01

    Biological neural systems (BNS) in general and the central nervous system (CNS) specifically exhibit a strikingly efficient computational power along with an extreme flexible and adaptive basis for acquiring and integrating new knowledge. Acquiring more insights into the actual mechanisms of information processing within the BNS and their computational capabilities is a core objective of modern computer science, computational sciences and neuroscience. Among the main reasons of...

  12. Evaluation models for contaminated sites – biological system at risk

    OpenAIRE

    Golomeova, Mirjana; Krstev, Boris; Golomeov, Blagoj; Zendelska, Afrodita; Krstev, Aleksandar

    2009-01-01

    The paper presents the different methods that can be used correspond to three types of approaches, testing, monitoring, and modeling: experimental models, in situ indicators and mathematical models, and choice of model for contaminated sites – biological system at risk.

  13. Summing up dynamics: modelling biological processes in variable temperature scenarios

    NARCIS (Netherlands)

    Tijskens, L.M.M.; Verdenius, F.

    2000-01-01

    The interest of modelling biological processes with dynamically changing external conditions (temperature, relative humidity, gas conditions) increases. Several modelling approaches are currently available. Among them are approaches like modelling under standard conditions, temperature sum models an

  14. 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.

  15. A unified biological modeling and simulation system for analyzing biological reaction networks

    Science.gov (United States)

    Yu, Seok Jong; Tung, Thai Quang; Park, Junho; Lim, Jongtae; Yoo, Jaesoo

    2013-12-01

    In order to understand the biological response in a cell, a researcher has to create a biological network and design an experiment to prove it. Although biological knowledge has been accumulated, we still don't have enough biological models to explain complex biological phenomena. If a new biological network is to be created, integrated modeling software supporting various biological models is required. In this research, we design and implement a unified biological modeling and simulation system, called ezBioNet, for analyzing biological reaction networks. ezBioNet designs kinetic and Boolean network models and simulates the biological networks using a server-side simulation system with Object Oriented Parallel Accelerator Library framework. The main advantage of ezBioNet is that a user can create a biological network by using unified modeling canvas of kinetic and Boolean models and perform massive simulations, including Ordinary Differential Equation analyses, sensitivity analyses, parameter estimates and Boolean network analysis. ezBioNet integrates useful biological databases, including the BioModels database, by connecting European Bioinformatics Institute servers through Web services Application Programming Interfaces. In addition, we employ Eclipse Rich Client Platform, which is a powerful modularity framework to allow various functional expansions. ezBioNet is intended to be an easy-to-use modeling tool and a simulation system for understanding the control mechanism by monitoring the change of each component in a biological network. The simulation result can be managed and visualized on ezBioNet, which is available free of charge at http://ezbionet.sourceforge.net or http://ezbionet.cbnu.ac.kr.

  16. 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....

  17. A prototype effective-one-body model for non-precessing spinning inspiral-merger-ringdown waveforms

    CERN Document Server

    Taracchini, Andrea; Buonanno, Alessandra; Barausse, Enrico; Boyle, Michael; Chu, Tony; Lovelace, Geoffrey; Pfeiffer, Harald P; Scheel, Mark A

    2012-01-01

    We first use five non-spinning and two mildly spinning (chi_i \\simeq -0.44, +0.44) numerical-relativity waveforms of black-hole binaries and calibrate an effective-one-body (EOB) model for non-precessing spinning binaries, notably its dynamics and the dominant (2,2) gravitational-wave mode. Then, we combine the above results with recent outcomes of small-mass-ratio simulations produced by the Teukolsky equation and build a prototype EOB model for detection purposes, which is capable of generating inspiral-merger-ringdown waveforms for non-precessing spinning black-hole binaries with any mass ratio and individual black-hole spins -1 \\leq chi_i \\lesssim 0.7. We compare the prototype EOB model to two equal-mass highly spinning numerical-relativity waveforms of black holes with spins chi_i = -0.95, +0.97, which were not available at the time the EOB model was calibrated. In the case of Advanced LIGO we find that the mismatch between prototype-EOB and numerical-relativity waveforms is always smaller than 0.003 for...

  18. Diphoton Excess at 750 GeV in leptophobic U(1)$^\\prime$ model inspired by $E_6$ GUT

    CERN Document Server

    Ko, P; Yu, Chaehyun

    2016-01-01

    We discuss the 750 GeV diphoton excess at the LHC@13TeV in the framework of leptophobic U(1)$^\\prime$ model inspired by the $E_6$ grand unified theory (GUT). In this model, the Standard Model (SM) chiral fermions carry charges under extra U(1)$^\\prime$ gauge symmetry which is spontaneously broken by a U(1)$^\\prime$-charged singlet scalar ($\\Phi$). In addition, extra quarks and leptons are introduced to achieve the anomaly-free conditions, which is a natural consequence of the assumed $E_6$ GUT. These new fermions are vectorlike under the SM gauge group but chiral under new U(1)$^\\prime$, and their masses come entirely from the nonzero vacuum expectation value of $\\Phi$ through the Yukawa interactions. Then, the CP-even scalar $h_\\Phi$ from $\\Phi$ can be produced at the LHC by the gluon fusion and decay to the diphoton via the one-loop diagram involving the extra quarks and leptons, and can be identified as the origin of diphoton excess at 750 GeV. In this model, $h_\\Phi$ can decay into a pair of dark matter p...

  19. 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

  20. 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.

  1. 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

  2. Evaluating Vocational Educators' Training Programs: A Kirkpatrick-Inspired Evaluation Model

    Science.gov (United States)

    Ravicchio, Fabrizio; Trentin, Guglielmo

    2015-01-01

    The aim of the article is to describe the assessment model adopted by the SCINTILLA Project, a project in Italy aimed at the online vocational training of young, seriously-disabled subjects and their subsequent work inclusion in smart-work mode. It will thus describe the model worked out for evaluation of the training program conceived for the…

  3. Biological Optimisation for Nurse Scheduling

    CERN Document Server

    Twycross, Jamie

    2010-01-01

    Artificial immune systems (AISs) to date have generally been inspired by naive biological metaphors. This has limited the effectiveness of these systems. In this position paper two ways in which AISs could be made more biologically realistic are discussed. We propose that AISs should draw their inspiration from organisms which possess only innate immune systems, and that AISs should employ systemic models of the immune system to structure their overall design. An outline of plant and invertebrate immune systems is presented, and a number of contemporary research that more biologically-realistic AISs could have is also discussed.

  4. 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.

  5. SPAM Detection Server Model Inspired by the Dionaea Muscipula Closure Mechanism: An Alternative Approach for Natural Computing Challenges

    Science.gov (United States)

    de Souza Pereira Lopes, Rodrigo Arthur; Carrari R. Lopes, Lia; Mustaro, Pollyana Notargiacomo

    Natural computing has been an increasingly evolving field in the last few years. Focusing on the interesting behaviours offered by nature and biological processes, this work intends to apply the metaphor of the carnivorous plant "Dionaea muscipula" as a complementary defence system against a recurring problem regarding internet and e-mails: spam. The metaphor model presents relevant aspects for further implementation and debate.

  6. 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.

  7. 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.

  8. 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.

  9. 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. PMID:21893841

  10. 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.

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

    Science.gov (United States)

    Alamino, Roberto C.

    2016-08-01

    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.

  12. Quantum-Inspired Maximizer

    Science.gov (United States)

    Zak, Michail

    2008-01-01

    A report discusses an algorithm for a new kind of dynamics based on a quantum- classical hybrid-quantum-inspired maximizer. The model is represented by a modified Madelung equation in which the quantum potential is replaced by different, specially chosen 'computational' potential. As a result, the dynamics attains both quantum and classical properties: it preserves superposition and entanglement of random solutions, while allowing one to measure its state variables, using classical methods. Such optimal combination of characteristics is a perfect match for quantum-inspired computing. As an application, an algorithm for global maximum of an arbitrary integrable function is proposed. The idea of the proposed algorithm is very simple: based upon the Quantum-inspired Maximizer (QIM), introduce a positive function to be maximized as the probability density to which the solution is attracted. Then the larger value of this function will have the higher probability to appear. Special attention is paid to simulation of integer programming and NP-complete problems. It is demonstrated that the problem of global maximum of an integrable function can be found in polynomial time by using the proposed quantum- classical hybrid. The result is extended to a constrained maximum with applications to integer programming and TSP (Traveling Salesman Problem).

  13. 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.

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

    Science.gov (United States)

    Kinreich, Sivan; Jackont, Gilan; Cohen, Avihay; Podlipsky-Klovatch, Ilana; Hendler, Talma; Intrator, Nathan

    2016-01-01

    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. PMID:27163677

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

    Science.gov (United States)

    Meir-Hasson, Yehudit; Keynan, Jackob N; Kinreich, Sivan; Jackont, Gilan; Cohen, Avihay; Podlipsky-Klovatch, Ilana; Hendler, Talma; Intrator, Nathan

    2016-01-01

    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. PMID:27163677

  16. Characteristics of ant-inspired traffic flow: Applying the social insect metaphor to traffic models

    OpenAIRE

    John, Alexander; Schadschneider, Andreas; Chowdhury, Debashish; Nishinari, Katsuhiro

    2009-01-01

    We investigate the organization of traffic flow on preexisting uni- and bidirectional ant trails. Our investigations comprise a theoretical as well as an empirical part. We propose minimal models of uni- and bi-directional traffic flow implemented as cellular automata. Using these models, the spatio-temporal organization of ants on the trail is studied. Based on this, some unusual flow characteristics which differ from those known from other traffic systems, like vehicular traffic or pedestri...

  17. Self-forced evolutions of an implicit rotating source: a natural framework to model comparable and intermediate mass-ratio systems from inspiral through ringdown

    CERN Document Server

    Huerta, E A; Gair, Jonathan R; McWilliams, Sean T

    2014-01-01

    We develop a waveform model to describe the inspiral, merger and ringdown of binary systems with comparable and intermediate mass-ratios. This model incorporates first-order conservative self-force corrections to the energy and angular momentum, which are valid in the strong-field regime [1]. We model the radiative part of the self-force by deriving second-order radiative corrections to the energy flux. These corrections are obtained by minimizing the phase discrepancy between our self-force model and the effective one body model [2, 3] for a variety of mass-ratios. We show that our model performs substantially better than post-Newtonian approximants currently used to model neutron star-black hole mergers from early inspiral to the innermost stable circular orbit. In order to match the late inspiral evolution onto the plunge regime, we extend the 'transition phase' developed by Ori and Thorne [4] by including finite mass-ratio corrections and modelling the orbital phase evolution using an implicit rotating so...

  18. A bio-inspired auditory perception model for amplitude-frequency clustering (keynote Paper)

    Science.gov (United States)

    Arena, Paolo; Fortuna, Luigi; Frasca, Mattia; Ganci, Gaetana; Patane, Luca

    2005-06-01

    In this paper a model for auditory perception is introduced. This model is based on a network of integrate-and-fire and resonate-and-fire neurons and is aimed to control the phonotaxis behavior of a roving robot. The starting point is the model of phonotaxis in Gryllus Bimaculatus: the model consists of four integrate-and-fire neurons and is able of discriminating the calling song of male cricket and orienting the robot towards the sound source. This paper aims to extend the model to include an amplitude-frequency clustering. The proposed spiking network shows different behaviors associated with different characteristics of the input signals (amplitude and frequency). The behavior implemented on the robot is similar to the cricket behavior, where some frequencies are associated with the calling song of male crickets, while other ones indicate the presence of predators. Therefore, the whole model for auditory perception is devoted to control different responses (attractive or repulsive) depending on the input characteristics. The performance of the control system has been evaluated with several experiments carried out on a roving robot.

  19. A modelling study of regional deposition of inspired aerosols with reference to dosimetric assessments

    Energy Technology Data Exchange (ETDEWEB)

    Egan, M.J.; Nixon, W. (UKAEA Safety and Reliability Directorate, Culcheth (UK))

    1988-01-01

    An improved lung deposition model, agreeing well with a wide range of total and regional deposition data, was used to investigate some assumptions embodied in current ICRP recommendations. Following a comparison between predictions of the new model and the original ICRP Task Group deposition model, the possible influence upon dosimetric calculations caused by various different effects were investigated. Some significant differences between regional deposition predictions of the new model and the current ICRP recommendations embodied in Publication 30 were found, up to a factor of approx 4 in some cases. The impact of improved modelling, aerosol polydispersity, the possibility of mouth as compared to nose breathing and exercise level (especially if there is transition from nose to mouth breathing at high work rates) were observed to be the most important. The impact of different breathing patterns was found to be less significant while the effect of different particle densities could be relatively successfully accounted for via a suitable transition from geometric to aerodynamic diameter. (author).

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

    International Nuclear Information System (INIS)

    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)

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

    Science.gov (United States)

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

    2014-09-01

    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. PMID:24613939

  2. Equivalent model for the phase dynamics of a metamaterial inspired patch antenna

    Science.gov (United States)

    Papari, Gianpaolo; Andreone, Antonello

    2016-02-01

    We present a simple model for a patch antenna based on metamaterial concepts operating in the microwave region with a bandwidth of 1.9-2.6 GHz. The small size and the relatively large operational band make this device exploitable for electromagnetic energy harvesting in urban environments. Describing the antenna by an equivalent circuit composed of a transmission line having right/left hand properties with a RC load, we can properly account for the phase dynamics in correspondence of resonances characterized by a specific handedness. The model is validated measuring the response of the reflection scattering parameter S1,1 for a copper prototype fabricated on a FR4 printed circuit board.

  3. Toward Affordable, Theory-and-Simulation-Inspired, Models for Realistic Wind Turbine Aerodynamics and Noise

    Science.gov (United States)

    Ladeinde, Foluso; Alabi, Ken; Li, Wenhai

    2015-11-01

    The problem of generating design data for the operation of a farm of wind turbines for clean energy production is quite complicated, if properly done. Potential flow theories provide some models, but these are not suitable for the massive aerodynamic separation and turbulence that characterize many realistic wind turbine applications. Procedures, such as computational fluid dynamics (CFD), which can potentially resolve some of the accuracy problems with the purely theoretical approach, are quite expensive to use, and often prohibit real-time design and control. In our work, we seek affordable and acceptably-accurate models derived from the foregoing approaches. The simulation used in our study is based on high-fidelity CFD, meaning that we use high-order (compact-scheme based), mostly large-eddy simulation methods, with due regards for the proper treatment of the stochastic inflow turbulence data. Progress on the project described herein will be presented.

  4. Weak decay constant of pseudscalar meson in a QCD-inspired model

    CERN Document Server

    Salcedo, L A M; Hadj-Michef, D; Frederico, T

    2003-01-01

    We show that a linear scaling between the weak decay constants of pseudoscalar and the vector mesons masses is supported by the available experimental data. The decay constant scale as $f_m/f_{pi}=M_V/M_{\\rho}$ (f_m is decay constant and M_V vector meson ground state mass). This simple form is justified within a renormalized light-front QCD-inpired model for quark-antiquark bound states.

  5. Modelling biological complexity: a physical scientist's perspective

    OpenAIRE

    Coveney, Peter V.; Fowler, Philip W.

    2005-01-01

    We discuss the modern approaches of complexity and self-organization to understanding dynamical systems and how these concepts can inform current interest in systems biology. From the perspective of a physical scientist, it is especially interesting to examine how the differing weights given to philosophies of science in the physical and biological sciences impact the application of the study of complexity. We briefly describe how the dynamics of the heart and circadian rhythms, canonical exa...

  6. Bridging Physics and Biology Teaching through Modeling

    OpenAIRE

    Hoskinson, Anne-Marie; Couch, Brian A.; Zwickl, Benjamin M.; Hinko, Kathleen; Caballero, Marcos D.

    2013-01-01

    As the frontiers of biology become increasingly interdisciplinary, the physics education community has engaged in ongoing efforts to make physics classes more relevant to life sciences majors. These efforts are complicated by the many apparent differences between these fields, including the types of systems that each studies, the behavior of those systems, the kinds of measurements that each makes, and the role of mathematics in each field. Nonetheless, physics and biology are both sciences t...

  7. Inflation at the maxima of the potential inspired by brane models

    CERN Document Server

    Germán, G

    2003-01-01

    We construct a two-stage inflationary model which can accommodate early inflation at a scale $\\Lambda_1$ as well as a second stage of inflation (quintessence) at $\\Lambda_2$ with a single scalar field $\\phi$. We use a symmetric potential, valid in a frictionless world, in which the two inflationary periods have exactly the same scale, i.e. $\\Lambda_1=\\Lambda_2$. However, we see today $\\Lambda_1 \\gg \\Lambda_2$ due to the friction terms (expansion of the universe and interaction with matter). These type of models can be motivated from brane or supergravity models. Inflation occurs close to the maxima of the potential. As a consequence both inflations are necessarily finite. This opens the interesting possibility that the second inflation has already or is about to end. A first inflation is produced when fluctuations displace the inflaton field from its higher maximum rolling down the potential as in new inflation. Instead of rolling towards a global minimum the inflaton approaches a lower maximum where a second...

  8. Path planning versus cue responding: a bio-inspired model of switching between navigation strategies.

    Science.gov (United States)

    Dollé, Laurent; Sheynikhovich, Denis; Girard, Benoît; Chavarriaga, Ricardo; Guillot, Agnès

    2010-10-01

    In this article, we describe a new computational model of switching between path-planning and cue-guided navigation strategies. It is based on three main assumptions: (i) the strategies are mediated by separate memory systems that learn independently and in parallel; (ii) the learning algorithms are different in the two memory systems-the cue-guided strategy uses a temporal-difference (TD) learning rule to approach a visible goal, whereas the path-planning strategy relies on a place-cell-based graph-search algorithm to learn the location of a hidden goal; (iii) a strategy selection mechanism uses TD-learning rule to choose the most successful strategy based on past experience. We propose a novel criterion for strategy selection based on the directions of goal-oriented movements suggested by the different strategies. We show that the selection criterion based on this "common currency" is capable of choosing the best among TD-learning and planning strategies and can be used to solve navigational tasks in continuous state and action spaces. The model has been successfully applied to reproduce rat behavior in two water-maze tasks in which the two strategies were shown to interact. The model was used to analyze competitive and cooperative interactions between different strategies during these tasks as well as relative influence of different types of sensory cues. PMID:20617443

  9. 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. PMID:27270918

  10. 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.

  11. 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.

  12. Neurospora as a model fungus for studies in cytogenetics and sexual biology at Stanford

    Indian Academy of Sciences (India)

    Namboori B Raju

    2009-03-01

    Dodge’s early work (1927–1940) on Neurospora genetics and sexual biology inspired Beadle and Tatum at Stanford to use N. crassa for their landmark discovery that genes specify enzymes. Neurospora has since become a model organism for numerous genetic, cytogenetic, biochemical, molecular and population biology studies. Neurospora is haploid in the vegetative phase with a transient diploid sexual phase. Its meiotic cells (asci) are large, allowing easy examination of dividing nuclei and chromosomes under a light microscope. The haploid meiotic products are themselves the sexual progeny that grow into vegetative cultures, thus avoiding the cumbersome testcrosses and complex dominance–recessive relationships, as in diploid organisms. The Perkins’ laboratory at Stanford (1949–2007) played a pivotal role in advancing our knowledge of Neurospora genetics, sexual biology, cytogenetics and population biology. Since 1974, I have taken advantage of various chromosome-staining methods to examine ascus and ascospore development in wild type and in numerous mutant strains. In addition, I have used GFP-tagged genes to visualize the expression or silencing of unpaired genes in a post-transcriptional gene silencing process (meiotic silencing by unpaired DNA) that operates specifically during meiosis. The genome of N. crassa contains over 10 000 protein-coding genes. Gene knockouts or mutations in specific sequences may now be readily correlated with the observed cytological defects in the sexual stage, thus advancing our molecular understanding of complex processes during ascus and ascospore development.

  13. Dynamics and kinetics of model biological systems

    Science.gov (United States)

    Mirigian, Stephen

    In this work we study three systems of biological interest: the translocation of a heterogeneously charged polymer through an infinitely thin pore, the wrapped of a rigid particle by a soft vesicle and the modification of the dynamical properties of a gel due to the presence of rigid inclusions. We study the kinetics of translocation for a heterogeneously charged polyelectrolyte through an infinitely narrow pore using the Fokker-Planck formalism to compute mean first passage times, the probability of successful translocation, and the mean successful translocation time for a diblock copolymer. We find, in contrast to the homopolymer result, that details of the boundary conditions lead to qualitatively different behavior. Under experimentally relevant conditions for a diblock copolymer we find that there is a threshold length of the charged block, beyond which the probability of successful translocation is independent of charge fraction. Additionally, we find that mean successful translocation time exhibits non-monotonic behavior with increasing length of the charged fraction; there is an optimum length of the charged block where the mean successful translocation time is slowest and there can be a substantial range of charge fraction where it is slower than a minimally charged chain. For a fixed total charge on the chain, we find that finer distributions of the charge along the chain leads to a significant reduction in mean translocation time compared to the diblock distribution. Endocytosis is modeled using a simple geometrical model from the literature. We map the process of wrapping a rigid spherical bead onto a one-dimensional stochastic process described by the Fokker-Planck equation to compute uptake rates as a function of membrane properties and system geometry. We find that simple geometrical considerations pick an optimal particle size for uptake and a corresponding maximal uptake rate, which can be controlled by altering the material properties of the

  14. Energy-dependent dipole form factor in a QCD-inspired model

    CERN Document Server

    Bahia, C A S; Luna, E G S

    2015-01-01

    We consider the effect of an energy-dependent dipole form factor in the high-energy behavior of the forward amplitude. The connection between the semihard parton-level dynamics and the hadron-hadron scattering is established by an eikonal QCD-based model. Our results for the proton-proton ($pp$) and antiproton-proton ($\\bar{p}p$) total cross sections, $\\sigma_{tot}^{pp,\\bar{p}p}(s)$, obtained using the CTEQ6L1 parton distribution function, are consistent with the recent data from the TOTEM experiment.

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

    International Nuclear Information System (INIS)

    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)

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

    Science.gov (United States)

    Freire Roberto, Guilherme; Castilho Maschi, Luis Fernando; Pigatto, Daniel Fernando; Jaquie Castelo Branco, Kalinka Regina Lucas; Alves Neves, Leandro; Montez, Carlos; Sandro Roschildt Pinto, Alex

    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).

  17. 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.

  18. Structure formation in a string-inspired modification of the cold dark matter model

    CERN Document Server

    Gubser, S S; Gubser, Steven S.

    2004-01-01

    Motivated in part by string theory, we consider the idea that the standard LambdaCDM cosmological model might be modified by the effect of a long-range scalar dark matter interaction. The variant of this widely-discussed notion considered here is suggested by the Brandenberger-Vafa picture for why we perceive three spatial dimensions. In this picture there may be at least two species of dark matter particles, with scalar ``charges'' such that the scalar interaction attracts particles with like sign and repels unlike signs. The net charge vanishes. Under this condition the evolution of the mass distribution in linear perturbation theory is the same as in the LambdaCDM cosmology, and both models therefore can equally well pass the available cosmological tests. The physics can be very different on small scales, however: if the scalar interaction has the strength suggested by simple versions of the string scenario, nonlinear mass concentrations are unstable against separation into charged halos with properties un...

  19. Structure combinatorics and thermodynamics of a matrix model with Penner interaction inspired by interacting RNA

    Energy Technology Data Exchange (ETDEWEB)

    Bhadola, P.; Garg, I. [Department of Physics and Astrophysics, University of Delhi, Delhi 110007 (India); Deo, N., E-mail: ndeo@physics.du.ac.in [Department of Physics and Astrophysics, University of Delhi, Delhi 110007 (India)

    2013-05-11

    In this manuscript, we study the logarithmic Penner type nonlinear interaction in the random matrix model for interacting RNA folding and structure combinatorics. The Penner interaction originally appeared in the studies of moduli space of punctured surfaces and has been applied here in the context of RNA folding for the first time. An exact analytic formula for the generating function is derived using the orthogonal polynomial method. The partition function for a given length L of the RNA chain, derived from the generating function enumerates all possible topological structures as well as the pairings. The partition function and the asymptotic large length distribution functions are found and show a change in the critical exponent of the secondary structure contribution from L{sup −3/2} for large N (size of matrix, N>L) to L{sup −1/2} for small N (N≪L). The exact analytic results calculated in the proposed model allow evaluation of the specific heat versus T curve for large interaction strength. In particular, the second derivative of specific heat shows a striking behavior, changing from single peaked function for large N to a double peak for small N.

  20. Geophysics in INSPIRE

    Science.gov (United States)

    Sőrés, László

    2013-04-01

    INSPIRE is a European directive to harmonize spatial data in Europe. Its' aim is to establish a transparent, multidisciplinary network of environmental information by using international standards and OGC web services. Spatial data themes defined in the annex of the directive cover 34 domains that are closely bundled to environment and spatial information. According to the INSPIRE roadmap all data providers must setup discovery, viewing and download services and restructure data stores to provide spatial data as defined by the underlying specifications by 2014 December 1. More than 3000 institutions are going to be involved in the progress. During the data specification process geophysics as an inevitable source of geo information was introduced to Annex II Geology. Within the Geology theme Geophysics is divided into core and extended model. The core model contains specifications for legally binding data provisioning and is going to be part of the Implementation Rules of the INSPIRE directives. To minimize the work load of obligatory data transformations the scope of the core model is very limited and simple. It covers the most essential geophysical feature types that are relevant in economic and environmental context. To fully support the use cases identified by the stake holders the extended model was developed. It contains a wide range of spatial object types for geophysical measurements, processed and interpreted results, and wrapper classes to help data providers in using the Observation and Measurements (O&M) standard for geophysical data exchange. Instead of introducing the traditional concept of "geophysical methods" at a high structural level the data model classifies measurements and geophysical models based on their spatial characteristics. Measurements are classified as geophysical station (point), geophysical profile (curve) and geophysical swath (surface). Generic classes for processing results and interpretation models are curve model (1D), surface

  1. 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…

  2. MIT bag model inspired partonic transverse momentum distribution for prompt photon production in pp collisions

    CERN Document Server

    Diakonos, F K; Maintas, X N; 10.1103/PhysRevD.78.054023

    2010-01-01

    We consider the prompt photon production in pp collisions using, within the framework of perturbative QCD, a non-Gaussian distribution for the transverse momentum distribution of the partons inside the proton. Our description adopts the widely used in the literature factorization of the partonic momentum distribution into longitudinal and transverse components. It is argued that the non-Gaussian distribution of the intrinsic transverse momenta of the partons is dictated by the asymptotic freedom as well as the 3D confinement of the partons in the proton. To make this association more transparent we use the MIT bag model, which plainly incorporates both properties (asymptotic freedom, confinement), in order to determine in a simplified way the partonic transverse momentum distribution. A large set of data from six different experiments have been fitted with this simple description using as a single free parameter the mean partonic transverse momentum . Surprisingly enough, a perfect fit of the experimental dat...

  3. The Observed Diphoton Excess in F-theory Inspired Heterotic String-Derived Model

    CERN Document Server

    Ashfaque, Johar M

    2016-01-01

    The production and the subsequent decay of the SM singlet via heavy vector--like colour triplets and electroweak doublets in one--loop diagrams can shed light on the recent observation of diphoton excess at the LHC. In this paper, the $E_6$ GUT is considered in the F-theory setting where the $E_6$ is broken by making use of the spectral cover construction and by turning on the hypercharge gauge flux. This paper is based on the results presented in \\cite{Athanasopoulos:2014bba, Faraggi:2016xnm, Ashfaque:2016jha} which will be reviewed briefly. Here, by following the F-theory approach, akin to \\cite{Karozas:2016hcp, Leontaris:2016wsy, Das:2016xuc}, we present a study of the flipped $SO(10)$ model embedded completely in the $E_{6}$ GUT but with a different accommodation of the SM representations in the ${\\bf{27}}$ of $E_{6}$.

  4. Modeling Co-evolution of Speech and Biology.

    Science.gov (United States)

    de Boer, Bart

    2016-04-01

    Two computer simulations are investigated that model interaction of cultural evolution of language and biological evolution of adaptations to language. Both are agent-based models in which a population of agents imitates each other using realistic vowels. The agents evolve under selective pressure for good imitation. In one model, the evolution of the vocal tract is modeled; in the other, a cognitive mechanism for perceiving speech accurately is modeled. In both cases, biological adaptations to using and learning speech evolve, even though the system of speech sounds itself changes at a more rapid time scale than biological evolution. However, the fact that the available acoustic space is used maximally (a self-organized result of cultural evolution) is constant, and therefore biological evolution does have a stable target. This work shows that when cultural and biological traits are continuous, their co-evolution may lead to cognitive adaptations that are strong enough to detect empirically.

  5. Analytic modelling of tidal effects in the relativistic inspiral of binary neutron stars

    CERN Document Server

    Baiotti, Luca; Giacomazzo, Bruno; Nagar, Alessandro; Rezzolla, Luciano

    2010-01-01

    To detect the gravitational-wave signal from binary neutron stars and extract information about the equation of state of matter at nuclear density, it is necessary to match the signal with a bank of accurate templates. We have performed the longest (to date) general-relativistic simulations of binary neutron stars with different compactnesses and used them to constrain a tidal extension of the effective-one-body model so that it reproduces the numerical waveforms accurately and essentially up to the merger. The typical errors in the phase over the $\\simeq 22$ gravitational-wave cycles are $\\Delta \\phi\\simeq \\pm 0.24$ rad, thus with relative phase errors $\\Delta \\phi/\\phi \\simeq 0.2%$. We also show that with a single choice of parameters, the effective-one-body approach is able to reproduce all of the numerically-computed phase evolutions, in contrast with what found when adopting a tidally corrected post-Newtonian Taylor-T4 expansion.

  6. Grazing incidence modeling of a metamaterial-inspired dual-resonance acoustic liner

    Science.gov (United States)

    Beck, Benjamin S.

    2014-03-01

    To reduce the noise emitted by commercial aircraft turbofan engines, the inlet and aft nacelle ducts are lined with acoustic absorbing structures called acoustic liners. Traditionally, these structures consist of a perforated facesheet bonded on top of a honeycomb core. These traditional perforate over honeycomb core (POHC) liners create an absorption spectra where the maximum absorption occurs at a frequency that is dictated by the depth of the honeycomb core; which acts as a quarter-wave resonator. Recent advances in turbofan engine design have increased the need for thin acoustic liners that are effective at low frequencies. One design that has been developed uses an acoustic metamaterial architecture to improve the low frequency absorption. Specifically, the liner consists of an array of Helmholtz resonators separated by quarter-wave volumes to create a dual-resonance acoustic liner. While previous work investigated the acoustic behavior under normal incidence, this paper outlines the modeling and predicted transmission loss and absorption of a dual-resonance acoustic metamaterial when subjected to grazing incidence sound.

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

    OpenAIRE

    Benjamin Engelhardt; Holger Frőhlich; Maik Kschischo

    2016-01-01

    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 dat...

  8. Modelling the structure and dynamics of biological pathways

    OpenAIRE

    O'Hara, Laura; Livigni, Alessandra; Theocharidis, Thanos; Boyer, Benjamin; Angus, Tim; Wright, Derek; Chen, Sz-Hau; Raza, Sobia; Barnett, Mark; Digard, Paul; Smith, Lee; Freeman, Thomas

    2016-01-01

    There is a need for formalised diagrams that both summarise current biological pathway knowledge and support modelling approaches that explain and predict their behaviour. Here we present a new, freely-available modelling framework that includes: a biologist-friendly pathway modelling language (mEPN); a simple but sophisticated method to support model parameterisation using accessible biological information, a stochastic flow algorithm that simulates the dynamics of pathway activity, and a 3D...

  9. Issues in Applying Bio-Inspiration, Cognitive Critical Mass and Developmental-Inspired Principles to Advanced Intelligent Systems

    Science.gov (United States)

    Berg-Cross, Gary; Samsonovich, Alexei V.

    This Chapter summarizes ideas presented at the special PerMIS 2008 session on Biological Inspiration for Intelligent Systems. Bio-inspired principles of development and evolution are a special part of the bio-models and principles that can be used to improve intelligent systems and related artifacts. Such principles are not always explicit. They represent an alternative to incremental engineering expansion using new technology to replicate human intelligent capabilities. They are more evident in efforts to replicate and produce a “critical mass” of higher cognitive functions of the human mind or their emergence through cognitive developmental robotics (DR) and self-regulated learning (SRL). DR approaches takes inspiration from natural processes, so that intelligently engineered systems may create solutions to problems in ways similar to what we hypothesize is occurring with biologics in their natural environment. This Chapter discusses how an SRL-based approach to bootstrap a “critical mass” can be assessed by a set of cognitive tests. It also uses a three-level bio-inspired framework to illustrate methodological issues in DR research. The approach stresses the importance of using bio-realistic developmental principles to guide and constrain research. Of particular importance is keeping models and implementation separate to avoid the possible of falling into a Ptolemaic paradigm that may lead to endless tweaking of models. Several of Lungarella's design principles [36] for developmental robotics are discussed as constraints on intelligence as it emerges from an ecologically balanced, three-way interaction between an agents' control systems, physical embodiment, and the external environment. The direction proposed herein is to explore such principles to avoid slavish following of superficial bio-inspiration. Rather we should proceed with a mature and informed developmental approach using developmental principles based on our incremental understanding of how

  10. Isgur-Wise function in a QCD inspired potential model with confinement as parent in the Variationally Improved Perturbation Theory (VIPT)

    CERN Document Server

    Hazarika, B J

    2011-01-01

    We have recently reported the calculation of slope and curvature of Isgur-Wise function based on Variationally Improved Perturbation Theory (VIPT) in a QCD inspired potential model. In that work, Coulombic potential was taken as the parent while the linear one as the perturbation.In this work, we choose the linear one as the parent with Coulombic one as the perturbation and see the consequences. Keywords: VIPT,Isgur-Wise function, charge radii and convexity pa- rameter.

  11. A specialized face-processing model inspired by the organization of monkey face patches explains several face-specific phenomena observed in humans

    OpenAIRE

    Amirhossein Farzmahdi; Karim Rajaei; Masoud Ghodrati; Reza Ebrahimpour; Seyed-Mahdi Khaligh-Razavi

    2016-01-01

    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, i...

  12. 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...

  13. A guide to numerical modelling in systems biology

    CERN Document Server

    Deuflhard, Peter

    2015-01-01

    This book is intended for students of computational systems biology with only a limited background in mathematics. Typical books on systems biology merely mention algorithmic approaches, but without offering a deeper understanding. On the other hand, mathematical books are typically unreadable for computational biologists. The authors of the present book have worked hard to fill this gap. The result is not a book on systems biology, but on computational methods in systems biology. This book originated from courses taught by the authors at Freie Universität Berlin. The guiding idea of the courses was to convey those mathematical insights that are indispensable for systems biology, teaching the necessary mathematical prerequisites by means of many illustrative examples and without any theorems. The three chapters cover the mathematical modelling of biochemical and physiological processes, numerical simulation of the dynamics of biological networks, and identification of model parameters by means of comparisons...

  14. Parallel representation of stimulus identity and intensity in a dual pathway model inspired by the olfactory system of the honeybee

    Directory of Open Access Journals (Sweden)

    Michael eSchmuker

    2011-12-01

    Full Text Available The honeybee Apis mellifera has a remarkable ability to detect and locate food sources during foraging, and to associate odor cues with food rewards. In the honeybee’s olfactory system, sensory input is first processed in the antennal lobe (AL network. Uniglomerular projection neurons (PNs convey the sensory code from the AL to higher brain regions via two parallel but anatomically distinct pathways, the lateral and the medial antenno-cerebral tract (l- and m-ACT. Neurons innervating either tract show characteristic differences in odor selectivity, concentration dependence, and representation of mixtures. It is still unknown how this differential stimulus representation is achieved within the AL network. In this contribution, we use a computational network model to demonstrate that the experimentally observed features of odor coding in PNs can be reproduced by varying lateral inhibition and gain control in an otherwise unchanged AL network. We show that odor coding in the l-ACT supports detection and accurate identification of weak odor traces at the expense of concentration sensitivity, while odor coding in the m-ACT provides the basis for the computation and following of concentration gradients but provides weaker discrimination power. Both coding strategies are mutually exclusive, which creates a tradeoff between detection accuracy and sensitivity. The development of two parallel systems may thus reflect an evolutionary solution to this problem that enables honeybees to achieve both tasks during bee foraging in their natural environment, and which could inspire the development of artificial chemosensory devices for odor-guided navigation in robots.

  15. Mechanistic modeling confronts the complexity of molecular cell biology

    OpenAIRE

    Phair, Robert D.

    2014-01-01

    Mechanistic modeling has the potential to transform how cell biologists contend with the inescapable complexity of modern biology. I am a physiologist–electrical engineer–systems biologist who has been working at the level of cell biology for the past 24 years. This perspective aims 1) to convey why we build models, 2) to enumerate the major approaches to modeling and their philosophical differences, 3) to address some recurrent concerns raised by experimentalists, and then 4) to imagine a fu...

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

    Science.gov (United States)

    Engelhardt, Benjamin; Frőhlich, Holger; Kschischo, Maik

    2016-02-01

    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.

  17. Mechanistic modeling confronts the complexity of molecular cell biology.

    Science.gov (United States)

    Phair, Robert D

    2014-11-01

    Mechanistic modeling has the potential to transform how cell biologists contend with the inescapable complexity of modern biology. I am a physiologist-electrical engineer-systems biologist who has been working at the level of cell biology for the past 24 years. This perspective aims 1) to convey why we build models, 2) to enumerate the major approaches to modeling and their philosophical differences, 3) to address some recurrent concerns raised by experimentalists, and then 4) to imagine a future in which teams of experimentalists and modelers build-and subject to exhaustive experimental tests-models covering the entire spectrum from molecular cell biology to human pathophysiology. There is, in my view, no technical obstacle to this future, but it will require some plasticity in the biological research mind-set.

  18. Mathematics in the Biology Classroom: A Model of Interdisciplinary Education

    Science.gov (United States)

    Hodgson, Ted; Keck, Robert; Patterson, Richard; Maki, Dan

    2005-01-01

    This article describes an interdisciplinary course that develops essential mathematical modeling skills within an introductory biology setting. The course embodies recent recommendations regarding the need for interdisciplinary, inquiry-based mathematical preparation of undergraduates in the biological sciences. Evaluation indicates that the…

  19. 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...

  20. Completing and adapting models of biological processes

    OpenAIRE

    Margaria, Tiziana; Hinchey, Michael G.; Raffelt, Harald; Rash, James L.; Rouff, Christopher A.; Steffen, Bernhard

    2006-01-01

    We present a learning-based method for model completion and adaptation, which is based on the combination of two approaches: 1) R2D2C, a technique for mechanically transforming system requirements via provably equivalent models to running code, and 2) automata learning-based model extrapolation. The intended impact of this new combination is to make model completion and adaptation accessible to experts of the field, like biologists or engineers. The principle is briefly illustrated by gene...

  1. Neural networks and neuroscience-inspired computer vision.

    Science.gov (United States)

    Cox, David Daniel; Dean, Thomas

    2014-09-22

    Brains are, at a fundamental level, biological computing machines. They transform a torrent of complex and ambiguous sensory information into coherent thought and action, allowing an organism to perceive and model its environment, synthesize and make decisions from disparate streams of information, and adapt to a changing environment. Against this backdrop, it is perhaps not surprising that computer science, the science of building artificial computational systems, has long looked to biology for inspiration. However, while the opportunities for cross-pollination between neuroscience and computer science are great, the road to achieving brain-like algorithms has been long and rocky. Here, we review the historical connections between neuroscience and computer science, and we look forward to a new era of potential collaboration, enabled by recent rapid advances in both biologically-inspired computer vision and in experimental neuroscience methods. In particular, we explore where neuroscience-inspired algorithms have succeeded, where they still fail, and we identify areas where deeper connections are likely to be fruitful.

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

    OpenAIRE

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

    2013-01-01

    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.

  3. Recent Applications of Hidden Markov Models in Computational Biology

    Institute of Scientific and Technical Information of China (English)

    Khar Heng Choo; Joo Chuan Tong; Louxin Zhang

    2004-01-01

    This paper examines recent developments and applications of Hidden Markov Models (HMMs) to various problems in computational biology, including multiple sequence alignment, homology detection, protein sequences classification, and genomic annotation.

  4. Computational Modeling, Formal Analysis, and Tools for Systems Biology.

    Directory of Open Access Journals (Sweden)

    Ezio Bartocci

    2016-01-01

    Full Text Available As the amount of biological data in the public domain grows, so does the range of modeling and analysis techniques employed in systems biology. In recent years, a number of theoretical computer science developments have enabled modeling methodology to keep pace. The growing interest in systems biology in executable models and their analysis has necessitated the borrowing of terms and methods from computer science, such as formal analysis, model checking, static analysis, and runtime verification. Here, we discuss the most important and exciting computational methods and tools currently available to systems biologists. We believe that a deeper understanding of the concepts and theory highlighted in this review will produce better software practice, improved investigation of complex biological processes, and even new ideas and better feedback into computer science.

  5. Modeling human liver biology using stem cell-derived hepatocytes

    OpenAIRE

    Sun, Pingnan; Zhou, XiaoLing; Farnworth, Sarah; Arvind H Patel; Hay, David C.

    2013-01-01

    Stem cell-derived hepatocytes represent promising models to study human liver biology and disease. This concise review discusses the recent progresses in the field, with a focus on human liver disease, drug metabolism and virus infection.

  6. Modeling Human Liver Biology Using Stem Cell-Derived Hepatocytes

    OpenAIRE

    Arvind H Patel; Hay, David C.; Farnworth, Sarah L.; Pingnan Sun; Xiaoling Zhou

    2013-01-01

    Stem cell-derived hepatocytes represent promising models to study human liver biology and disease. This concise review discusses the recent progresses in the field, with a focus on human liver disease, drug metabolism and virus infection.

  7. Computational Modeling, Formal Analysis, and Tools for Systems Biology.

    Science.gov (United States)

    Bartocci, Ezio; Lió, Pietro

    2016-01-01

    As the amount of biological data in the public domain grows, so does the range of modeling and analysis techniques employed in systems biology. In recent years, a number of theoretical computer science developments have enabled modeling methodology to keep pace. The growing interest in systems biology in executable models and their analysis has necessitated the borrowing of terms and methods from computer science, such as formal analysis, model checking, static analysis, and runtime verification. Here, we discuss the most important and exciting computational methods and tools currently available to systems biologists. We believe that a deeper understanding of the concepts and theory highlighted in this review will produce better software practice, improved investigation of complex biological processes, and even new ideas and better feedback into computer science.

  8. Mathematical modeling of the evolution of a simple biological system

    Digital Repository Service at National Institute of Oceanography (India)

    Gonsalves, M.J.B.D.; Neetu, S.; Krishnan, K.P.; Attri, K.; LokaBharathi, P.A.

    physical system, where a model usually can be developed from well established fundamental principles, in case of biological systems such principles are not always available offering an opportunity for innovation. The success of the innovation, of course...

  9. 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...

  10. Prediction of postharvest firmness of apple using biological switch model.

    Science.gov (United States)

    van der Sman, R G M; Sanders, M

    2012-10-01

    In this paper we present a model that predicts the softening of apple during ripening in the postharvest phase. Apple ripening starts with an autocatalytic production of ethylene, which triggers a multitude of biochemical processes like the degradation of cell wall material. This triggering of the ripening process has been modelled as a biological switch-using the activator-depleted substrate model, which is proposed earlier by Meinhardt in the field of developmental biology. The model has been calibrated using storage experiments using various apple cultivars. Furthermore, the model is proven to be valid using independent experimental data of Elstar apple under dynamic storage conditions.

  11. Uncertainty in biology: a computational modeling approach

    OpenAIRE

    2015-01-01

    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...

  12. Modeling Small Oscillating Biological Networks in Analog VLSI

    OpenAIRE

    Ryckebusch, Sylvie; Bower, James M.; Mead, Carver

    1989-01-01

    We have used analog VLSI technology to model a class of small oscillating biological neural circuits known as central pattern generators (CPG). These circuits generate rhythmic patterns of activity which drive locomotor behaviour in the animal. We have designed, fabricated, and tested a model neuron circuit which relies on many of the same mechanisms as a biological central pattern generator neuron, such as delays and internal feedback. We show that this neuron can be use...

  13. Biological models for active vision: Towards a unified architecture

    OpenAIRE

    Terzic K.; Lobato D.; Saleiro M.; Martins J; Farrajota M.; Rodrigues J.M.F.; Du Buf J.M.H.

    2013-01-01

    Building a general-purpose, real-time active vision system completely based on biological models is a great challenge. We apply a number of biologically plausible algorithms which address different aspects of vision, such as edge and keypoint detection, feature extraction,optical flow and disparity, shape detection, object recognition and scene modelling into a complete system. We present some of the experiments from our ongoing work, where our system leverages a combination of algorithms to ...

  14. SBMLSimulator: A Java Tool for Model Simulation and Parameter Estimation in Systems Biology

    Directory of Open Access Journals (Sweden)

    Alexander Dörr

    2014-12-01

    Full Text Available The identification of suitable model parameters for biochemical reactions has been recognized as a quite difficult endeavor. Parameter values from literature or experiments can often not directly be combined in complex reaction systems. Nature-inspired optimization techniques can find appropriate sets of parameters that calibrate a model to experimentally obtained time series data. We present SBMLsimulator, a tool that combines the Systems Biology Simulation Core Library for dynamic simulation of biochemical models with the heuristic optimization framework EvA2. SBMLsimulator provides an intuitive graphical user interface with various options as well as a fully-featured command-line interface for large-scale and script-based model simulation and calibration. In a parameter estimation study based on a published model and artificial data we demonstrate the capability of SBMLsimulator to identify parameters. SBMLsimulator is useful for both, the interactive simulation and exploration of the parameter space and for the large-scale model calibration and estimation of uncertain parameter values.

  15. 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.

  16. Modeling the Biological Diversity of Pig Carcasses

    DEFF Research Database (Denmark)

    Erbou, Søren Gylling Hemmingsen

    extracting and modeling meaningful information from the vast amount of information available from non-invasive imaging data. The lean meat percentage (LMP) is a common standard for measuring the quality of pig carcasses. Measuring the LMP using CT and using this as a reference for calibration of online...... 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 of a...... specific bone structure in the ham. These models can assist developers of robotic tools by enabling population based testing before actual construction of the tools. Sparse models are compared to the standard PCA based model and a method for fitting PDM’s to sparse data is proposed. The former provides...

  17. Extra light fermions in $E_6$-inspired models and the 3.5 keV X-ray line signal

    CERN Document Server

    Nakayama, Kazunori; Yanagida, Tsutomu T

    2014-01-01

    We propose a scenario in which extra light fermions in an $E_6$-inspired U(1) extension of the standard model constitute the dark matter, as a simple variation of our model for dark radiation presented in 2010. Interestingly, for the light fermions of mass about 7 keV, they radiatively decay into active neutrinos and photons with a lifetime in the range of $10^{27}-10^{28}$ seconds, which naturally explains the recently discovered 3.5 keV X-ray line signal.

  18. Bayesian parameter estimation for nonlinear modelling of biological pathways

    Directory of Open Access Journals (Sweden)

    Ghasemi Omid

    2011-12-01

    Full Text Available Abstract Background The availability of temporal measurements on biological experiments has significantly promoted research areas in systems biology. To gain insight into the interaction and regulation of biological systems, mathematical frameworks such as ordinary differential equations have been widely applied to model biological pathways and interpret the temporal data. Hill equations are the preferred formats to represent the reaction rate in differential equation frameworks, due to their simple structures and their capabilities for easy fitting to saturated experimental measurements. However, Hill equations are highly nonlinearly parameterized functions, and parameters in these functions cannot be measured easily. Additionally, because of its high nonlinearity, adaptive parameter estimation algorithms developed for linear parameterized differential equations cannot be applied. Therefore, parameter estimation in nonlinearly parameterized differential equation models for biological pathways is both challenging and rewarding. In this study, we propose a Bayesian parameter estimation algorithm to estimate parameters in nonlinear mathematical models for biological pathways using time series data. Results We used the Runge-Kutta method to transform differential equations to difference equations assuming a known structure of the differential equations. This transformation allowed us to generate predictions dependent on previous states and to apply a Bayesian approach, namely, the Markov chain Monte Carlo (MCMC method. We applied this approach to the biological pathways involved in the left ventricle (LV response to myocardial infarction (MI and verified our algorithm by estimating two parameters in a Hill equation embedded in the nonlinear model. We further evaluated our estimation performance with different parameter settings and signal to noise ratios. Our results demonstrated the effectiveness of the algorithm for both linearly and nonlinearly

  19. Bionics: Biological insight into mechanical design

    OpenAIRE

    Dickinson, Michael H

    1999-01-01

    When pressed with an engineering problem, humans often draw guidance and inspiration from the natural world (1). Through the process of evolution, organisms have experimented with form and function for at least 3 billion years before the first human manipulations of stone, bone, and antler. Although we cannot know for sure the extent to which biological models inspired our early ancestors, more recent examples of biomimetic designs are well documented. For example, birds and bats played a cen...

  20. In Vivo Models to Study Chemokine Biology.

    Science.gov (United States)

    Amaral, F A; Boff, D; Teixeira, M M

    2016-01-01

    Chemokines are essential mediators of leukocyte movement in vivo. In vitro assays of leukocyte migration cannot mimic the complex interactions with other cell types and matrix needed for cells to extravasate and migrate into tissues. Therefore, in vivo strategies to study the effects and potential relevance of chemokines for the migration of particular leukocyte subsets are necessary. Here, we describe methods to study the effects and endogenous role of chemokine in mice. Advantages and pitfalls of particular models are discussed and we focus on description in model's joint and pleural cavity inflammation and the effects and relevance of CXCR2 and CCR2 ligands on cell migration.

  1. 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…

  2. MODEL ORGANISMS USED IN MOLECULAR BIOLOGY OR MEDICAL RESEARCH

    OpenAIRE

    Pandey Govind

    2011-01-01

    A model organism is a non-human species that is studied to understand specific biological phenomena with the expectation that investigations made in the organism model will provide insight into the workings of other organisms. The model organisms are widely used to explore potential causes and treatments for human as well as animal diseases when experiments on animals or humans would be unfeasible or considered less ethical. Studying model organisms may be informative, but care must be taken ...

  3. Predictive modeling of nanomaterial exposure effects in biological systems

    OpenAIRE

    Liu X; Tang K.; Harper S.; Harper B; Steevens JA; Xu R

    2013-01-01

    Xiong Liu,1 Kaizhi Tang,1 Stacey Harper,2 Bryan Harper,2 Jeffery A Steevens,3 Roger Xu1 1Intelligent Automation, Inc., Rockville, MD, USA; 2Department of Environmental and Molecular Toxicology, School of Chemical, Biological, and Environmental Engineering, Oregon State University, Corvallis, OR, USA; 3ERDC Environmental Laboratory, Vicksburg, MS, USA Background: Predictive modeling of the biological effects of nanomaterials is critical for industry and policymakers to assess the potential ha...

  4. Nature-inspired computing for control systems

    CERN Document Server

    2016-01-01

    The book presents recent advances in nature-inspired computing, giving a special emphasis to control systems applications. It reviews different techniques used for simulating physical, chemical, biological or social phenomena at the purpose of designing robust, predictive and adaptive control strategies. The book is a collection of several contributions, covering either more general approaches in control systems, or methodologies for control tuning and adaptive controllers, as well as exciting applications of nature-inspired techniques in robotics. On one side, the book is expected to motivate readers with a background in conventional control systems to try out these powerful techniques inspired by nature. On the other side, the book provides advanced readers with a deeper understanding of the field and a broad spectrum of different methods and techniques. All in all, the book is an outstanding, practice-oriented reference guide to nature-inspired computing addressing graduate students, researchers and practi...

  5. Flicker Noise in a Model of Coevolving Biological Populations

    OpenAIRE

    Rikvold, Per Arne; Zia, R. K. P.

    2003-01-01

    We present long Monte Carlo simulations of a simple model of biological macroevolution in which births, deaths, and mutational changes in the genome take place at the level of individual organisms. The model displays punctuated equilibria and flicker noise with a 1/f-like power spectrum, consistent with some current theories of evolutionary dynamics.

  6. Design considerations for an underwater soft-robot inspired from marine invertebrates.

    Science.gov (United States)

    Krieg, Michael; Sledge, Isaac; Mohseni, Kamran

    2015-12-01

    This article serves as an overview of the unique challenges and opportunities made possible by a soft, jellyfish inspired, underwater robot. We include a description of internal pressure modeling as it relates to propulsive performance, leading to a desired energy-minimizing volume flux program. Strategies for determining optimal actuator placement derived from biological body motions are presented. In addition a feedback mechanism inspired by the epidermal line sensory system of cephalopods is presented, whereby internal pressure distribution can be used to determine pertinent deformation parameters. PMID:26513603

  7. Gas uptake in a three-generation model geometry with a flat inlet velocity during steady inspiration: comparison of axisymmetric and three-dimensional models.

    Science.gov (United States)

    Madasu, Srinath; Borhan, Ali; Ultman, James

    2007-05-01

    Mass transfer coefficients were predicted and compared for uptake of reactive gas system using an axisymmetric single-path model (ASPM) with experimentally predicted values in a two-generation geometry and with a three-dimensional computational fluid dynamics model (CFDM) in a three-generation model geometry at steady inspiratory flow with a flat inlet velocity profile. The flow and concentration fields in the ASPM were solved using Galerkin's finite element method and in the CFDM using a commercial finite element software FIDAP. ASPM predicted average gas phase mass transfer coefficients within 25% of the experimental values. Numerical results in terms of overall mass transfer coefficients from the two models within each bifurcation unit were compared for two different inlet flow rates, wall mass transfer coefficients, and bifurcation angles. The overall mass transfer coefficients variation with bifurcation unit from the ASPM and CFDM compared qualitatively and quantitatively closely at lower wall mass transfer coefficients for both 40 degree and 70 degree bifurcation angles. But at higher wall mass transfer coefficients, quantitatively they were off in the range of 2-10% for 40 degree bifurcation angle and in the range of 4-15% for 70 degree bifurcation angle. Both CFDM and ASPM predict the same trends of increase in mass transfer coefficients with inlet flow, wall mass transfer coefficients, and during inspiration compared to expiration. Higher mass transfer coefficients were obtained with a flat velocity profile compared to a parabolic velocity profile using ASPM. These results validate the simplified ASPM and the complex CFDM.

  8. A Comparative Analysis of Nature-Inspired Optimization Approaches to 2D Geometric Modelling for Turbomachinery Applications

    Directory of Open Access Journals (Sweden)

    Amir Safari

    2013-01-01

    Full Text Available A vast variety of population-based optimization techniques have been formulated in recent years for use in different engineering applications, most of which are inspired by natural processes taking place in our environment. However, the mathematical and statistical analysis of these algorithms is still lacking. This paper addresses a comparative performance analysis on some of the most important nature-inspired optimization algorithms with a different basis for the complex high-dimensional curve/surface fitting problems. As a case study, the point cloud of an in-hand gas turbine compressor blade measured by touch trigger probes is optimally fitted using B-spline curves. In order to determine the optimum number/location of a set of Bezier/NURBS control points for all segments of the airfoil profiles, five dissimilar population-based evolutionary and swarm optimization techniques are employed. To comprehensively peruse and to fairly compare the obtained results, parametric and nonparametric statistical evaluations as the mathematical study are presented before designing an experiment. Results illuminate a number of advantages/disadvantages of each optimization method for such complex geometries’ parameterization from several different points of view. In terms of application, the final appropriate parametric representation of geometries is an essential, significant component of aerodynamic profile optimization processes as well as reverse engineering purposes.

  9. 3D Modelling of Biological Systems for Biomimetics

    Institute of Scientific and Technical Information of China (English)

    Shujun Zhang; Kevin Hapeshi; Ashok K. Bhattacharya

    2004-01-01

    With the advanced development of computer-based enabling technologies, many engineering, medical, biology,chemistry, physics and food science etc have developed to the unprecedented levels, which lead to many research and development interests in various multi-discipline areas. Among them, biomimetics is one of the most promising and attractive branches of study. Biomimetics is a branch of study that uses biological systems as a model to develop synthetic systems.To learn from nature, one of the fundamental issues is to understand the natural systems such animals, insects, plants and human beings etc. The geometrical characterization and representation of natural systems is an important fundamental work for biomimetics research. 3D modeling plays a key role in the geometrical characterization and representation, especially in computer graphical visualization. This paper firstly presents the typical procedure of 3D modelling methods and then reviews the previous work of 3D geometrical modelling techniques and systems developed for industrial, medical and animation applications. Especially the paper discusses the problems associated with the existing techniques and systems when they are applied to 3D modelling of biological systems. Based upon the discussions, the paper proposes some areas of research interests in 3D modelling of biological systems and for Biomimetics.

  10. Self-organized Critical Model Of Biological Evolution

    OpenAIRE

    Chau, H. F.; Mak, L; Kwok, P. K.

    1994-01-01

    A punctuated equilibrium model of biological evolution with relative fitness between different species being the fundamental driving force of evolution is introduced. Mutation is modeled as a fitness updating cellular automaton process where the change in fitness after mutation follows a Gaussian distribution with mean $x>0$ and standard deviation $\\sigma$. Scaling behaviors are observed in our numerical simulation, indicating that the model is self-organized critical. Besides, the numerical ...

  11. Nutritional systems biology modeling: from molecular mechanisms to physiology.

    OpenAIRE

    de Graaf, Albert A.; Freidig, Andreas P.; Baukje De Roos; Neema Jamshidi; Matthias Heinemann; Rullmann, Johan A.C.; Hall, Kevin D.; Martin Adiels; Ben van Ommen

    2009-01-01

    The use of computational modeling and simulation has increased in many biological fields, but despite their potential these techniques are only marginally applied in nutritional sciences. Nevertheless, recent applications of modeling have been instrumental in answering important nutritional questions from the cellular up to the physiological levels. Capturing the complexity of today's important nutritional research questions poses a challenge for modeling to become truly integrative in the co...

  12. Nutritional Systems Biology Modeling: From Molecular Mechanisms to Physiology

    OpenAIRE

    de Graaf, A A; Freidig, A.P.; Roos, B.; Jamshidi, N.; M. Heinemann; Rullmann, J.A.C.; Hall, K. D.; Adiels, M.; Ommen, B. van

    2009-01-01

    The use of computational modeling and simulation has increased in many biological fields, but despite their potential these techniques are only marginally applied in nutritional sciences. Nevertheless, recent applications of modeling have been instrumental in answering important nutritional questions from the cellular up to the physiological levels. Capturing the complexity of today's important nutritional research questions poses a challenge for modeling to become truly integrative in the co...

  13. Nutritional Systems Biology Modeling: From Molecular Mechanisms to Physiology

    OpenAIRE

    de Graaf, Albert A.; Freidig, Andreas P.; de Roos, Baukje; Jamshidi, Neema; Heinemann, Matthias; Rullmann, Johan A.C.; Hall, Kevin D.; Adiels, Martin; van Ommen, Ben; Bourne, Philip E.

    2009-01-01

    The use of computational modeling and simulation has increased in many biological fields, but despite their potential these techniques are only marginally applied in nutritional sciences. Nevertheless, recent applications of modeling have been instrumental in answering important nutritional questions from the cellular up to the physiological levels. Capturing the complexity of today’s important nutritional research questions poses a challenge for modeling to become truly integrative in the co...

  14. Human pluripotent stem cells: an emerging model in developmental biology

    OpenAIRE

    Zhu, Zengrong; Huangfu, Danwei

    2013-01-01

    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...

  15. Modeling Biology Spanning Different Scales: An Open Challenge

    Directory of Open Access Journals (Sweden)

    Filippo Castiglione

    2014-01-01

    Full Text Available It is coming nowadays more clear that in order to obtain a unified description of the different mechanisms governing the behavior and causality relations among the various parts of a living system, the development of comprehensive computational and mathematical models at different space and time scales is required. This is one of the most formidable challenges of modern biology characterized by the availability of huge amount of high throughput measurements. In this paper we draw attention to the importance of multiscale modeling in the framework of studies of biological systems in general and of the immune system in particular.

  16. Fly's proprioception-inspired micromachined strain-sensing structure: idea, design, modeling and simulation, and comparison with experimental results

    Energy Technology Data Exchange (ETDEWEB)

    Wicaksono, D H B [Department of Microelectronics, Delft University of Technology, Mekelweg 4, Delft, Zuid-Holland 2628CD (Netherlands); Zhang, L-J [Department of Microelectronics, Delft University of Technology, Mekelweg 4, Delft, Zuid-Holland 2628CD (Netherlands); Pandraud, G [Department of Microelectronics, Delft University of Technology, Mekelweg 4, Delft, Zuid-Holland 2628CD (Netherlands); French, P J [Department of Microelectronics, Delft University of Technology, Mekelweg 4, Delft, Zuid-Holland 2628CD (Netherlands); Vincent, J F V [Department of Mech. Engineering, Bath University Bath, BA2 7AY (United Kingdom)

    2006-04-01

    A new strain-sensing structure inspired from insect's (especially the Fly) propricoception sensor is devised. The campaniform sensillum is a strain-sensing microstructure with very high sensitivity despite its small dimension (diameter {approx}10 {mu}m in a relatively stiff material of insect's exocuticle (E = {approx}10{sup 9} Pa). Previous work shows that the high sensitivity of this structure towards strain is due to its membrane-in-recess- and strainconcentrating-hole-features. Based on this inspiration, we built similar structure using silicon micromachining technology. Then a simple characterisation setup was devised. Here, we present briefly, finite-element modeling and simulation based on this actual sample preparation for the characterisation. As comparison and also to understand mechanical features responsible for the strain-sensitivity, we performed the modeling on different mechanical structures: bulk chunk, blind-hole, through-hole, surface membrane, and membrane-in-recess. The actual experimental characterisation was performed previously using optical technique to membrane in-recess micromachined Si structure. The FEM simulation results confirm that the bending stress and strain are concentrated in the hole-vicinity. The membrane inside the hole acts as displacement transducer. The FEM is in conformity with previous analytical results, as well as the optical characterisation result. The end goal is to build a new type MEMS strain sensor.

  17. Biological implications of the Weibull and Gompertz models of aging.

    Science.gov (United States)

    Ricklefs, Robert E; Scheuerlein, Alex

    2002-02-01

    Gompertz and Weibull functions imply contrasting biological causes of demographic aging. The terms describing increasing mortality with age are multiplicative and additive, respectively, which could result from an increase in the vulnerability of individuals to extrinsic causes in the Gompertz model and the predominance of intrinsic causes at older ages in the Weibull model. Experiments that manipulate extrinsic mortality can distinguish these biological models. To facilitate analyses of experimental data, we defined a single index for the rate of aging (omega) for the Weibull and Gompertz functions. Each function described the increase in aging-related mortality in simulated ages at death reasonably well. However, in contrast to the Weibull omega(W), the Gompertz omega(G) was sensitive to variation in the initial mortality rate independently of aging-related mortality. Comparisons between wild and captive populations appear to support the intrinsic-causes model for birds, but give mixed support for both models in mammals.

  18. A neuro-inspired model-based closed-loop neuroprosthesis for the substitution of a cerebellar learning function in anesthetized rats

    Science.gov (United States)

    Hogri, Roni; Bamford, Simeon A.; Taub, Aryeh H.; Magal, Ari; Giudice, Paolo Del; Mintz, Matti

    2015-02-01

    Neuroprostheses could potentially recover functions lost due to neural damage. Typical neuroprostheses connect an intact brain with the external environment, thus replacing damaged sensory or motor pathways. Recently, closed-loop neuroprostheses, bidirectionally interfaced with the brain, have begun to emerge, offering an opportunity to substitute malfunctioning brain structures. In this proof-of-concept study, we demonstrate a neuro-inspired model-based approach to neuroprostheses. A VLSI chip was designed to implement essential cerebellar synaptic plasticity rules, and was interfaced with cerebellar input and output nuclei in real time, thus reproducing cerebellum-dependent learning in anesthetized rats. Such a model-based approach does not require prior system identification, allowing for de novo experience-based learning in the brain-chip hybrid, with potential clinical advantages and limitations when compared to existing parametric ``black box'' models.

  19. 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.

  20. Bio-inspired flapping UAV design: a university perspective

    Science.gov (United States)

    Han, Jae-Hung; Lee, Jun-Seong; Kim, Dae-Kwan

    2009-03-01

    Bio-inspired design to make artificial flappers fly does not just imitate biological systems as closely as possible, but also transferring the flappers' own functionalities to engineering solutions. This paper summarizes some key technical issues and the states-of-art of bio-inspired design of flapping UAVs with an introduction to authors' recent research results in this field.

  1. Decrypting $SO(10)$-inspired leptogenesis

    CERN Document Server

    Di Bari, Pasquale; Fiorentin, Michele Re

    2014-01-01

    Encouraged by the recent results from neutrino oscillation experiments, we perform an analytical study of $SO(10)$-inspired models and leptogenesis with hierarchical right-handed (RH) neutrino spectrum. Under the approximation of negligible misalignment between the neutrino Yukawa basis and the charged lepton basis, we find an analytical expression for the final asymmetry directly in terms of the low energy neutrino parameters that fully reproduces previous numerical results. This expression also shows that is possible to identify an effective leptogenesis phase for these models. When we also impose the wash-out of a large pre-existing asymmetry $N^{\\rm p,i}_{B-L}$, the strong thermal (ST) condition, we derive analytically all those constraints on the low energy neutrino parameters that characterise the {\\rm ST}-$SO(10)$-inspired leptogenesis solution, confirming previous numerical results. In particular we show why, though neutrino masses have to be necessarily normally ordered, the solution implies an analy...

  2. Boolean Models of Biological Processes Explain Cascade-Like Behavior.

    Science.gov (United States)

    Chen, Hao; Wang, Guanyu; Simha, Rahul; Du, Chenghang; Zeng, Chen

    2016-01-01

    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.

  3. Boolean Models of Biological Processes Explain Cascade-Like Behavior.

    Science.gov (United States)

    Chen, Hao; Wang, Guanyu; Simha, Rahul; Du, Chenghang; Zeng, Chen

    2016-01-01

    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. PMID:26821940

  4. Nature inspired algorithms and artificial intelligence

    OpenAIRE

    Elisa Valentina Onet; Ecaterina Vladu

    2008-01-01

    Artificial intelligence has been very muchinterested in studying the characteristics ofintelligent agent, mainly planning, learning,reasoning (making decisions) and perception.Biological processes and methods have beeninfluencing science from many decades. Naturalsystems have many properties that inspiredapplications - self-organisation, simplicity of basicelements, dynamics, flexibility. This paper is a surveyof nature inspired algorithms, like Particle SwarmOptimization (PSO), Ant Colony Op...

  5. 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…

  6. Modeling Radial Holoblastic Cleavage: A Laboratory Activity for Developmental Biology.

    Science.gov (United States)

    Ellis, Linda K.

    2000-01-01

    Introduces a laboratory activity designed for an undergraduate developmental biology course. Uses Play-Doh (plastic modeling clay) to build a multicellular embryo in order to provide a 3-D demonstration of cleavage. Includes notes for the instructor and student directions. (YDS)

  7. 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...

  8. Minimizing Human Intervention in the Development of Basal Ganglia-Inspired Robot Control

    OpenAIRE

    F. Montes-Gonzalez; Prescott, T.J; Negrete-Martinez, J.

    2007-01-01

    A biologically inspired mechanism for robot action selection, based on the vertebrate basal ganglia, has been previously presented (Prescott et al. 2006, Montes Gonzalez et al. 2000). In this model the task confronting the robot is decomposed into distinct behavioural modules that integrate information from multiple sensors and internal state to form ‘salience’ signals. These signals are provided as inputs to a computational model of the basal ganglia whose intrinsic processes cause the selec...

  9. Simple model of self-organized biological evolution

    Energy Technology Data Exchange (ETDEWEB)

    de Boer, J.; Derrida, B.; Flyvbjerg, H.; Jackson, A.D.; Wettig, T. (Department of Physics, State University of New York at Stony Brook, Stony Brook, New York 11794-3800 (United States) The Isaac Newton Institute for Mathematical Sciences, 20 Clarkson Road, Cambridge, CB4 0EH (United Kingdom) Laboratoire de Physique Statistique, Ecole Normale Superieure, 24 rue Lhomond, F-75005 Paris (France) Service de Physique Theorique, Centre de Etudes Nucleaires de Saclay, F-91191, Gif-Sur-Yvette (France) CONNECT, The Niels Bohr Institute, Blegdamsvej 17, DK-2100 Copenhagen (Denmark))

    1994-08-08

    We give an exact solution of a recently proposed self-organized critical model of biological evolution. We show that the model has a power law distribution of durations of coevolutionary avalanches'' with a mean field exponent 3/2. We also calculate analytically the finite size effects which cut off this power law at times of the order of the system size.

  10. Kinetic hierarchy and propagation of chaos in biological swarm models

    OpenAIRE

    Carlen, Eric; Chatelin, Robin; Degond, Pierre; Wennberg, Bernt

    2011-01-01

    We consider two models of biological swarm behavior. In these models, pairs of particles interact to adjust their velocities one to each other. In the first process, called 'BDG', they join their average velocity up to some noise. In the second process, called 'CL', one of the two particles tries to join the other one's velocity. This paper establishes the master equations and BBGKY hierarchies of these two processes. It investigates the infinite particle limit of the hierarchies at large tim...

  11. Evaluation of radiobiological effects in 3 distinct biological models

    International Nuclear Information System (INIS)

    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

  12. 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.

  13. 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...

  14. 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.

  15. An Intuitive Automated Modelling Interface for Systems Biology

    Directory of Open Access Journals (Sweden)

    Ozan Kahramanoğulları

    2009-11-01

    Full Text Available We introduce a natural language interface for building stochastic pi calculus models of biological systems. In this language, complex constructs describing biochemical events are built from basic primitives of association, dissociation and transformation. This language thus allows us to model biochemical systems modularly by describing their dynamics in a narrative-style language, while making amendments, refinements and extensions on the models easy. We demonstrate the language on a model of Fc-gamma receptor phosphorylation during phagocytosis. We provide a tool implementation of the translation into a stochastic pi calculus language, Microsoft Research's SPiM.

  16. Modeling and Simulation Tools: From Systems Biology to Systems Medicine.

    Science.gov (United States)

    Olivier, Brett G; Swat, Maciej J; Moné, Martijn J

    2016-01-01

    Modeling is an integral component of modern biology. In this chapter we look into the role of the model, as it pertains to Systems Medicine, and the software that is required to instantiate and run it. We do this by comparing the development, implementation, and characteristics of tools that have been developed to work with two divergent methodologies: Systems Biology and Pharmacometrics. From the Systems Biology perspective we consider the concept of "Software as a Medical Device" and what this may imply for the migration of research-oriented, simulation software into the domain of human health.In our second perspective, we see how in practice hundreds of computational tools already accompany drug discovery and development at every stage of the process. Standardized exchange formats are required to streamline the model exchange between tools, which would minimize translation errors and reduce the required time. With the emergence, almost 15 years ago, of the SBML standard, a large part of the domain of interest is already covered and models can be shared and passed from software to software without recoding them. Until recently the last stage of the process, the pharmacometric analysis used in clinical studies carried out on subject populations, lacked such an exchange medium. We describe a new emerging exchange format in Pharmacometrics which covers the non-linear mixed effects models, the standard statistical model type used in this area. By interfacing these two formats the entire domain can be covered by complementary standards and subsequently the according tools.

  17. Childhood trauma and personality disorder: toward a biological model.

    Science.gov (United States)

    Lee, Royce

    2006-02-01

    Cross-sectional and prospective associations of personality disorder with childhood trauma provide an important clue regarding the biological mechanism of personality disorder. In this review, empirical literature from several domains is summarized. These include relevant findings from behavioral genetics, preclinical models of early life parental care, and clinical translational studies of personality disorder. Identification of the biological mechanism by which childhood trauma exerts an effect on personality disorder may require modification of the conceptualization of personality disorder, either as a set of categories or dimensions.

  18. Predictive modeling of nanomaterial exposure effects in biological systems

    Directory of Open Access Journals (Sweden)

    Liu X

    2013-09-01

    Full Text Available Xiong Liu,1 Kaizhi Tang,1 Stacey Harper,2 Bryan Harper,2 Jeffery A Steevens,3 Roger Xu1 1Intelligent Automation, Inc., Rockville, MD, USA; 2Department of Environmental and Molecular Toxicology, School of Chemical, Biological, and Environmental Engineering, Oregon State University, Corvallis, OR, USA; 3ERDC Environmental Laboratory, Vicksburg, MS, USA Background: Predictive modeling of the biological effects of nanomaterials is critical for industry and policymakers to assess the potential hazards resulting from the application of engineered nanomaterials. Methods: We generated an experimental dataset on the toxic effects experienced by embryonic zebrafish due to exposure to nanomaterials. Several nanomaterials were studied, such as metal nanoparticles, dendrimer, metal oxide, and polymeric materials. The embryonic zebrafish metric (EZ Metric was used as a screening-level measurement representative of adverse effects. Using the dataset, we developed a data mining approach to model the toxic endpoints and the overall biological impact of nanomaterials. Data mining techniques, such as numerical prediction, can assist analysts in developing risk assessment models for nanomaterials. Results: We found several important attributes that contribute to the 24 hours post-fertilization (hpf mortality, such as dosage concentration, shell composition, and surface charge. These findings concur with previous studies on nanomaterial toxicity using embryonic zebrafish. We conducted case studies on modeling the overall effect/impact of nanomaterials and the specific toxic endpoints such as mortality, delayed development, and morphological malformations. The results show that we can achieve high prediction accuracy for certain biological effects, such as 24 hpf mortality, 120 hpf mortality, and 120 hpf heart malformation. The results also show that the weighting scheme for individual biological effects has a significant influence on modeling the overall impact of

  19. Biomechanical model of batoid (skates and rays) pectoral fins predicts the influence of skeletal structure on fin kinematics: implications for bio-inspired design.

    Science.gov (United States)

    Russo, R S; Blemker, S S; Fish, F E; Bart-Smith, H

    2015-06-16

    Growing interest in the development of bio-inspired autonomous underwater vehicles (AUVs) has motivated research in understanding the mechanisms behind the propulsion systems of marine animals. For example, the locomotive behavior of rays (Batoidea) by movement of the pectoral fins is of particular interest due to their superior performance characteristics over contemporary AUV propulsion systems. To better understand the mechanics of pectoral fin propulsion, this paper introduces a biomechanical model that simulates how batoid skeletal structures function to achieve the swimming locomotion observed in nature. Two rays were studied, Dasyatis sabina (Atlantic ray), and Rhinoptera bonasus (cownose ray). These species were selected because they exhibit very different swimming styles (undulation versus oscillation), but all use primarily their pectoral fins for propulsion (unlike electric rays or guitarfishes). Computerized tomography scans of each species were taken to image the underlying structure, which reveal a complex system of cartilaginous joints and linkages. Data collected from these images were used to quantify the complete skeletal morphometry of each batoid fin. Morphological differences were identified in the internal cartilage arrangement between each species including variations in the orientation of the skeletal elements, or radials, and the joint patterns between them, called the inter-radial joint pattern. These data were used as the primary input into the biomechanical model to couple a given ray skeletal structure with various swimming motions. A key output of the model is an estimation of the uniaxial strain that develops in the skeletal connective tissue in order for the structure to achieve motions observed during swimming. Tensile load tests of this connective tissue were conducted to further investigate the implications of the material strain predictions. The model also demonstrates that changes in the skeletal architecture (e.g., joint

  20. 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.

  1. 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

  2. Biological exposure models for oil spill impact analysis

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    The oil spill impact analysis (OSIA) software system has been developed to supply a tool for comprehensive, quantitative environmental impact assessments resulting from oil spills. In the system, a biological component evaluates potential effects on exposed organisms based on results from a physico-chemieal fates component, including the extent and characteristics of the surface slick, and dissolved and total concentrations of hydrocarbons in the water column. The component includes a particle-based exposure model for migratory adult fish populations, a particle-based exposure model for spawning planktonic organisms (eggs and larvae), and an exposure model for wildlife species (sea birds or marine mammals). The exposure model for migratory adult fish populations simulates the migration behaviors of fish populations migrating to or staying in their feeding areas, over-wintering areas or spawning areas, and determines the acute effects (mortality) and chronic accumulation (body burdens) from the dissolved contaminant. The exposure model for spawning planktonic organisms simulates the release of eggs and larvae, also as particles, from specific spawning areas during the spawning period, and determines their potential exposure to contaminants in the water or sediment. The exposure model for wild species calculates the exposure to surrace oil of wildlife (bird and marine mammal ) categories inhabiting the contaminated area. Compared with the earlier models in which all kinds of organisms are assumed evenly and randomly distributed, the updated biological exposure models can more realistically estimate potential effects on marine ecological system from oil spill pollution events.

  3. Nutritional Systems Biology Modeling: From Molecular Mechanisms to Physiology

    Science.gov (United States)

    de Graaf, Albert A.; Freidig, Andreas P.; De Roos, Baukje; Jamshidi, Neema; Heinemann, Matthias; Rullmann, Johan A.C.; Hall, Kevin D.; Adiels, Martin; van Ommen, Ben

    2009-01-01

    The use of computational modeling and simulation has increased in many biological fields, but despite their potential these techniques are only marginally applied in nutritional sciences. Nevertheless, recent applications of modeling have been instrumental in answering important nutritional questions from the cellular up to the physiological levels. Capturing the complexity of today's important nutritional research questions poses a challenge for modeling to become truly integrative in the consideration and interpretation of experimental data at widely differing scales of space and time. In this review, we discuss a selection of available modeling approaches and applications relevant for nutrition. We then put these models into perspective by categorizing them according to their space and time domain. Through this categorization process, we identified a dearth of models that consider processes occurring between the microscopic and macroscopic scale. We propose a “middle-out” strategy to develop the required full-scale, multilevel computational models. Exhaustive and accurate phenotyping, the use of the virtual patient concept, and the development of biomarkers from “-omics” signatures are identified as key elements of a successful systems biology modeling approach in nutrition research—one that integrates physiological mechanisms and data at multiple space and time scales. PMID:19956660

  4. Nutritional systems biology modeling: from molecular mechanisms to physiology.

    Directory of Open Access Journals (Sweden)

    Albert A de Graaf

    2009-11-01

    Full Text Available The use of computational modeling and simulation has increased in many biological fields, but despite their potential these techniques are only marginally applied in nutritional sciences. Nevertheless, recent applications of modeling have been instrumental in answering important nutritional questions from the cellular up to the physiological levels. Capturing the complexity of today's important nutritional research questions poses a challenge for modeling to become truly integrative in the consideration and interpretation of experimental data at widely differing scales of space and time. In this review, we discuss a selection of available modeling approaches and applications relevant for nutrition. We then put these models into perspective by categorizing them according to their space and time domain. Through this categorization process, we identified a dearth of models that consider processes occurring between the microscopic and macroscopic scale. We propose a "middle-out" strategy to develop the required full-scale, multilevel computational models. Exhaustive and accurate phenotyping, the use of the virtual patient concept, and the development of biomarkers from "-omics" signatures are identified as key elements of a successful systems biology modeling approach in nutrition research--one that integrates physiological mechanisms and data at multiple space and time scales.

  5. 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.

  6. Integrative biological systems modeling:challenges and opportunities

    Institute of Scientific and Technical Information of China (English)

    Jialiang WU; Eberhard VOIT

    2009-01-01

    Most biological systems are by nature hybrids consist of interacting discrete and continuous components,which may even operate on different time scales. Therefore," it is desirable to establish modeling frameworks that are capable of combining deterministic and stochastic, discrete and continuous, as well as multi-timescale features. In the context of molecular systems biology, an example for the need of such a combination is the investigation of integrated biological pathways that contain gene regulatory, metabolic and signaling components, which may operate on different time scales and involve on-off switches as well as stochastic effects. The implementation of integrated hybrid systems is not trivial because most software is limited to one or the other of the dichotomies above. In this study, we first review the motivation for hybrid modeling. Secondly, by using the example of a toggle switch model, we illustrate a recently developed modeling framework that is based on the combination of biochemical systems theory (BST) and hybrid functional Petri nets (HFPN). Finally, we discuss remaining challenges and future opportunities.

  7. Towards Modelling and Simulation of Crowded Environments in Cell Biology

    Science.gov (United States)

    Bittig, Arne T.; Jeschke, Matthias; Uhrmacher, Adelinde M.

    2010-09-01

    In modelling and simulation of cell biological processes, spatial homogeneity in the distribution of components is a common but not always valid assumption. Spatial simulation methods differ in computational effort and accuracy, and usually rely on tool-specific input formats for model specification. A clear separation between modelling and simulation allows a declarative model specification thereby facilitating reuse of models and exploiting different simulators. We outline a modelling formalism covering both stochastic spatial simulation at the population level and simulation of individual entities moving in continuous space as well as the combination thereof. A multi-level spatial simulator is presented that combines populations of small particles simulated according to the Next Subvolume Method with individually represented large particles following Brownian motion. This approach entails several challenges that need to be overcome, but nicely balances between calculation effort and required levels of detail.

  8. An Abstraction Theory for Qualitative Models of Biological Systems

    CERN Document Server

    Banks, Richard; 10.4204/EPTCS.40.3

    2010-01-01

    Multi-valued network models are an important qualitative modelling approach used widely by the biological community. In this paper we consider developing an abstraction theory for multi-valued network models that allows the state space of a model to be reduced while preserving key properties of the model. This is important as it aids the analysis and comparison of multi-valued networks and in particular, helps address the well-known problem of state space explosion associated with such analysis. We also consider developing techniques for efficiently identifying abstractions and so provide a basis for the automation of this task. We illustrate the theory and techniques developed by investigating the identification of abstractions for two published MVN models of the lysis-lysogeny switch in the bacteriophage lambda.

  9. Multi-Objective Ant Colony Optimization Based on the Physarum-Inspired Mathematical Model for Bi-Objective Traveling Salesman Problems.

    Science.gov (United States)

    Zhang, Zili; Gao, Chao; Lu, Yuxiao; Liu, Yuxin; Liang, Mingxin

    2016-01-01

    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. PMID:26751562

  10. 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. PMID:24585051

  11. Modeling Cancer Metastasis using Global, Quantitative and Integrative Network Biology

    DEFF Research Database (Denmark)

    Schoof, Erwin; Erler, Janine

    cancer networks using Network Biology. Technologies key to this, such as Mass Spectrometry (MS), Next-Generation Sequencing (NGS) and High-Content Screening (HCS) are briefly described. In Chapter II, we cover how signaling networks and mutational data can be modeled in order to gain a better...... number of biological aspects that would need to be understood to enable comprehensive treatment regimens specific to each patient (i.e. personalized medicine). However, in the approaches outlined in this thesis, we chose metastasis as a key process for interrogating the clinical potential of targeting...... 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...

  12. Cellular systems biology profiling applied to cellular models of disease.

    Science.gov (United States)

    Giuliano, Kenneth A; Premkumar, Daniel R; Strock, Christopher J; Johnston, Patricia; Taylor, Lansing

    2009-11-01

    Building cellular models of disease based on the approach of Cellular Systems Biology (CSB) has the potential to improve the process of creating drugs as part of the continuum from early drug discovery through drug development and clinical trials and diagnostics. This paper focuses on the application of CSB to early drug discovery. We discuss the integration of protein-protein interaction biosensors with other multiplexed, functional biomarkers as an example in using CSB to optimize the identification of quality lead series compounds.

  13. Homotopy Analysis Method for Solving Biological Population Model

    Institute of Scientific and Technical Information of China (English)

    A.M. Arafa; S,Z. Rida; H. Mohamed

    2011-01-01

    In this paper, the homotopy analysis method (HAM) is applied to solve generalized biological population models. The fractional derivatives are described by Caputo's sense. The method introduces a significant improvement in this field over existing techniques. Results obtained using the scheme presented here agree well with the analytical solutions and the numerical results presented in Ref [6]. However, the fundamental solutions of these equations still exhibit useful scaling properties that make them attractive for applications.

  14. Thermal model of local ultrasound heating of biological tissue

    Science.gov (United States)

    Nedogovor, V. A.; Sigal, V. L.; Popsuev, E. I.

    1996-09-01

    Possibilities of creation of controlled temperature fields in deep-seated biological tissue with the use of an endocavity ultrasound applicator with surface cooling are considered. Mathematical models are proposed and calculated that make it possible to construct acoustic and thermal fields in biotissues depending on the thermophysical and ultrasound characteristics of the medium being irradiated and to reveal situations and effects that are important for solving problems of practical medicine in the field of local ultrasound hyperthermia and thermotherapy of tissue.

  15. A nude mouse model of endometriosis and its biological behaviors

    Institute of Scientific and Technical Information of China (English)

    WANG Dan-bo; ZHANG Shu-lan; NIU Hui-yan; LU Jing-ming

    2005-01-01

    @@ Endometriosis (EM) as a common and intractable gynecological disease is characterized by unknown etiology and complex pathologic changes. Many factors of the disease are uncertain at the molecular level and it is difficult to study clinically. In this study, we attempted to establish a nude mice model of EM for dynamical observation of the genesis and development of the disease, morphological changes in tissue, and biological behaviors.

  16. Inspiration is "Mission Critical"

    Science.gov (United States)

    McCarthy, D. W.; DeVore, E.; Lebofsky, L.

    2014-07-01

    In spring 2013, the President's budget proposal restructured the nation's approach to STEM education, eliminating ˜$50M of NASA Science Mission Directorate (SMD) funding with the intent of transferring it to the Dept. of Education, National Science Foundation, and Smithsonian Institution. As a result, Education and Public Outreach (EPO) would no longer be a NASA mission requirement and funds that had already been competed, awarded, and productively utilized were lost. Since 1994, partnerships of scientists, engineers, and education specialists were required to create innovative approaches to EPO, providing a direct source of inspiration for today's youth that may now be lost. Although seldom discussed or evaluated, "inspiration" is the beginning of lasting education. For decades, NASA's crewed and robotic missions have motivated students of all ages and have demonstrated a high degree of leverage in society. Through personal experiences we discuss (1) the importance of inspiration in education, (2) how NASA plays a vital role in STEM education, (3) examples of high-leverage educational materials showing why NASA should continue embedding EPO specialists within mission teams, and (4) how we can document the role of inspiration. We believe that personal histories are an important means of assessing the success of EPO. We hope this discussion will lead other people to document similar stories of educational success and perhaps to undertake longitudinal studies of the impact of inspiration.

  17. Mathematical and Statistical Modeling in Cancer Systems Biology

    Directory of Open Access Journals (Sweden)

    Rachael eHageman Blair

    2012-06-01

    Full Text Available Cancer is a major health problem with high mortality rates. In the post-genome era, investigators have access to massive amounts of rapidly accumulating high-throughput data in publicly available databases, some of which are exclusively devoted to housing Cancer data. However, data interpretation efforts have not kept pace with data collection, and gained knowledge is not necessarily translating into better diagnoses and treatments. A fundamental problem is to integrate and interpret data to further our understanding in Cancer Systems Biology. Viewing cancer as a network provides insights into the complex mechanisms underlying the disease. Mathematical and statistical models provide an avenue for cancer network modeling. In this article, we review two widely used modeling paradigms: deterministic metabolic models and statistical graphical models. The strength of these approaches lies in their flexibility and predictive power. Once a model has been validated, it can be used to make predictions and generate hypotheses. We describe a number of diverse applications to Cancer Biology, including, the system-wide effects of drug-treatments, disease prognosis, tumor classification, forecasting treatment outcomes, and survival predictions.

  18. Biological Jumping Mechanism Analysis and Modeling for Frog Robot

    Institute of Scientific and Technical Information of China (English)

    Meng Wang; Xi-zhe Zang; Ji-zhuang Fan; Jie Zhao

    2008-01-01

    This paper presents a mechanical model of jumping robot based on the biological mechanism analysis of frog. By biological observation and kinematic analysis the frog jump is divided into take-off phase, aerial phase and landing phase. We find the similar trajectories of hindlimb joints during jump, the important effect of foot during take-off and the role of forelimb in supporting the body. Based on the observation, the frog jump is simplified and a mechanical model is put forward. The robot leg is represented by a 4-bar spring/linkage mechanism model, which has three Degrees of Freedom (DOF) at hip joint and one DOF (passive) at tarsometatarsal joint on the foot. The shoulder and elbow joints each has one DOF for the balancing function of arm.The ground reaction force of the model is analyzed and compared with that of frog during take-off. The results show that the model has the same advantages of low likelihood of premature lift-off and high efficiency as the frog. Analysis results and the model can be employed to develop and control a robot capable of mimicking the jumping behavior of flog.

  19. Automated parameter estimation for biological models using Bayesian statistical model checking

    OpenAIRE

    Hussain, Faraz; Langmead, Christopher J.; Mi, Qi; Dutta-Moscato, Joyeeta; Vodovotz, Yoram; Jha, Sumit K.

    2015-01-01

    Background 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 mode...

  20. 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)

    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 Mo-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 ∼102-7 x 102 sbh's (EMRIs detected by LISA over a mission lifetime of 2 or 5 years

  1. Cooperativity to increase Turing pattern space for synthetic biology

    OpenAIRE

    Diambra, Luis; Senthivel, Vivek Raj; Menendez, Diego Barcena; Isalan, Mark

    2015-01-01

    It is hard to bridge the gap between mathematical formulations and biological implementations of Turing patterns, yet this is necessary for both understanding and engineering these networks with synthetic biology approaches. Here, we model a reaction–diffusion system with two morphogens in a monostable regime, inspired by components that we recently described in a synthetic biology study in mammalian cells.1 The model employs a single promoter to express both the activator and inhibitor genes...

  2. String and string-inspired phenomenology

    CERN Document Server

    López, J L

    1994-01-01

    In these lectures I review the progress made over the last few years in the subject of string and string-inspired phenomenology. I take a practical approach, thereby concentrating more on explicit examples rather than on formal developments. Topics covered include: introduction to string theory the free-fermionic formulation and its general features, generic conformal field theory properties, SU(5)\\times U(1) GUT and string model-building, supersymmetry breaking, the bottom-up approach to string-inspired models, radiative electroweak symmetry breaking, the determination of the allowed parameter space of supergravity models and the experimental constraints on this class of models, and prospects for direct and indirect tests of string-inspired models. (Lectures delivered at the XXII ITEP International Winter School of Physics, Moscow, Russia, February 22 -- March 2, 1994)

  3. Continuous Modeling of Calcium Transport Through Biological Membranes

    Science.gov (United States)

    Jasielec, J. J.; Filipek, R.; Szyszkiewicz, K.; Sokalski, T.; Lewenstam, A.

    2016-08-01

    In this work an approach to the modeling of the biological membranes where a membrane is treated as a continuous medium is presented. The Nernst-Planck-Poisson model including Poisson equation for electric potential is used to describe transport of ions in the mitochondrial membrane—the interface which joins mitochondrial matrix with cellular cytosis. The transport of calcium ions is considered. Concentration of calcium inside the mitochondrion is not known accurately because different analytical methods give dramatically different results. We explain mathematically these differences assuming the complexing reaction inside mitochondrion and the existence of the calcium set-point (concentration of calcium in cytosis below which calcium stops entering the mitochondrion).

  4. Mass Extinction in a Simple Mathematical Biological Model

    CERN Document Server

    Tokita, K; Tokita, Kei; Yasutomi, Ayumu

    1997-01-01

    Introducing the effect of extinction into the so-called replicator equations in mathematical biology, we construct a general model of ecosystems. The present model shows mass extinction by its own extinction dynamics when the system initially has a large number of species ( diversity). The extinction dynamics shows several significant features such as a power law in basin size distribution, induction time, etc. The present theory can be a mathematical foundation of the species-area effect in the paleontologic theory for mass extinction.

  5. 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

  6. Exogenous control of biological and ecological systems through evolutionary modelling

    Directory of Open Access Journals (Sweden)

    Alessandro Ferrarini

    2013-09-01

    Full Text Available The controllability of network-like systems is a topical issue in ecology and biology. It relies on the ability to lead a system's behaviour towards the desired state through the appropriate handling of input variables. Up to now, controllability of networks is based on the permanent control of a set of driver nodes that can guide the system's dynamics. This assumption seems motivated by real-world networks observation, where a decentralized control is often applied only to part of the nodes. While in a previous paper I showed that ecological and biological networks can be efficaciously controlled from the inside, here I further introduce a new framework for network controllability based on the employment of exogenous controllers and evolutionary modelling, and provide an exemplification of its application.

  7. 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

    2016-01-01

    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. PMID:27113635

  8. Accuracy and precision of gravitational-wave models of inspiraling neutron star -- black hole binaries with spin: comparison with numerical relativity in the low-frequency regime

    CERN Document Server

    Kumar, Prayush; Bhagwat, Swetha; Afshari, Nousha; Brown, Duncan A; Lovelace, Geoffrey; Scheel, Mark A; Szilágyi, Béla

    2015-01-01

    Coalescing binaries of neutron stars (NS) and black holes (BH) are one of the most important sources of gravitational waves for the upcoming network of ground based detectors. Detection and extraction of astrophysical information from gravitational-wave signals requires accurate waveform models. The Effective-One-Body and other phenomenological models interpolate between analytic results and $10-30$ orbit numerical relativity (NR) merger simulations. In this paper we study the accuracy of these models using new NR simulations that span $36-88$ orbits, with mass-ratios and black hole spins $(q,\\chi_{BH}) = (7, \\pm 0.4), (7, \\pm 0.6)$, and $(5, -0.9)$. We find that: (i) the recently published SEOBNRv1 and SEOBNRv2 models of the Effective-One-Body family disagree with each other (mismatches of a few percent) for black hole spins $\\geq 0.5$ or $\\leq -0.3$, with waveform mismatch accumulating during early inspiral; (ii) comparison with numerical waveforms indicate that this disagreement is due to phasing errors of...

  9. 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

    2016-01-01

    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. PMID:27113635

  10. Coupled model of physical and biological processes affecting maize pollination

    Science.gov (United States)

    Arritt, R.; Westgate, M.; Riese, J.; Falk, M.; Takle, E.

    2003-04-01

    Controversy over the use of genetically modified (GM) crops has led to increased interest in evaluating and controlling the potential for inadvertent outcrossing in open-pollinated crops such as maize. In response to this problem we have developed a Lagrangian model of pollen dispersion as a component of a coupled end-to-end (anther to ear) physical-biological model of maize pollination. The Lagrangian method is adopted because of its generality and flexibility: first, the method readily accommodates flow fields of arbitrary complexity; second, each element of the material being transported can be identified by its source, time of release, or other properties of interest. The latter allows pollen viability to be estimated as a function of such factors as travel time, temperature, and relative humidity, so that the physical effects of airflow and turbulence on pollen dispersion can be considered together with the biological aspects of pollen release and viability. Predicted dispersion of pollen compares well both to observations and to results from a simpler Gaussian plume model. Ability of the Lagrangian model to handle complex air flows is demonstrated by application to pollen dispersion in the vicinity of an agricultural shelter belt. We also show results indicating that pollen viability can be quantified by an "aging function" that accounts for temperature, humidity, and time of exposure.

  11. Highly eccentric inspirals into a black hole

    CERN Document Server

    Osburn, Thomas; Evans, Charles R

    2015-01-01

    We model the inspiral of a compact stellar-mass object into a massive non-rotating black hole including all dissipative and conservative first-order-in-the-mass-ratio effects on the orbital motion. The techniques we develop allow inspirals with initial eccentricities as high as $e\\sim0.8$ and initial separations as large as $\\sim 100M$ to be evolved through many thousands of orbits up to the onset of the plunge into the black hole. The inspiral is computed using an osculating elements scheme driven by a hybridized self-force model, which combines Lorenz-gauge self-force results with highly accurate flux data from a Regge-Wheeler-Zerilli code. The high accuracy of our hybrid self-force model allows the orbital phase of the inspirals to be tracked to within $\\sim0.1$ radians or better. The difference between self-force models and inspirals computed in the radiative approximation is quantified.

  12. 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

  13. 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…

  14. 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…

  15. An Ark of Inspiration.

    Science.gov (United States)

    King, Steve

    2001-01-01

    Describes an art project suitable for middle and high school students in which they either combine identifiable parts from different animals to create one creature or take one animal and creatively distort it. Explains that this lesson enables students to be satisfied with their animal-inspired artwork. (CMK)

  16. MODEL ORGANISMS USED IN MOLECULAR BIOLOGY OR MEDICAL RESEARCH

    Directory of Open Access Journals (Sweden)

    Pandey Govind

    2011-11-01

    Full Text Available A model organism is a non-human species that is studied to understand specific biological phenomena with the expectation that investigations made in the organism model will provide insight into the workings of other organisms. The model organisms are widely used to explore potential causes and treatments for human as well as animal diseases when experiments on animals or humans would be unfeasible or considered less ethical. Studying model organisms may be informative, but care must be taken when generalizing from one organism to another. Often, model organisms are chosen on the basis that they are amenable to experimental manipulation. When researchers look for an organism to use in their studies, they look for several traits. Among these are size, generation time, accessibility, manipulation, genetics, conservation of mechanisms and potential economic benefit. As comparative molecular biology has become more common, some researchers have sought model organisms from a wider assortment of lineages on the tree of life. There are many model organisms, such as viruses (e.g., Phage lambda virus, Tobacco mosaic virus, etc., bacteria (e.g., Bacillus subtilis, Escherichia coli, Pseudomonas fluorescens, Vibrio fischeri, etc., algae (e.g., Chlamydomonas reinhardtii, Emiliania huxleyi, etc., molds (e.g., Aspergillus nidulans, Neurospora crassa, etc., yeasts (e.g., Saccharomyces cerevisiae, Ustilago maydis, etc., higher plants (e.g., Arabidopsis thaliana, Lemna gibba, Lotus japonicus, Nicotiana tabaccum, Oryza sativa, Physcomitrella patens, Zea mays, etc. and animals (e.g., Caenorhabditis elegans, guinea pig, hamster, mouse, rat, cat, chicken, dog, frog, Hydra, Drosophila melanogaster fruit fly, fish, etc..

  17. Lessons learned from quantitative dynamical modeling in systems biology.

    Directory of Open Access Journals (Sweden)

    Andreas Raue

    Full Text Available Due to the high complexity of biological data it is difficult to disentangle cellular processes relying only on intuitive interpretation of measurements. A Systems Biology approach that combines quantitative experimental data with dynamic mathematical modeling promises to yield deeper insights into these processes. Nevertheless, with growing complexity and increasing amount of quantitative experimental data, building realistic and reliable mathematical models can become a challenging task: the quality of experimental data has to be assessed objectively, unknown model parameters need to be estimated from the experimental data, and numerical calculations need to be precise and efficient. Here, we discuss, compare and characterize the performance of computational methods throughout the process of quantitative dynamic modeling using two previously established examples, for which quantitative, dose- and time-resolved experimental data are available. In particular, we present an approach that allows to determine the quality of experimental data in an efficient, objective and automated manner. Using this approach data generated by different measurement techniques and even in single replicates can be reliably used for mathematical modeling. For the estimation of unknown model parameters, the performance of different optimization algorithms was compared systematically. Our results show that deterministic derivative-based optimization employing the sensitivity equations in combination with a multi-start strategy based on latin hypercube sampling outperforms the other methods by orders of magnitude in accuracy and speed. Finally, we investigated transformations that yield a more efficient parameterization of the model and therefore lead to a further enhancement in optimization performance. We provide a freely available open source software package that implements the algorithms and examples compared here.

  18. 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

  19. Ants as Fluids: Physics-Inspired Biology

    CERN Document Server

    Streiff, Micah; Shinotsuka, Sho; Alexeev, Alex; Hu, David

    2010-01-01

    Fire ants use their claws to grip diverse surfaces, including each other. As a result of their mutual adhesion and large numbers, ant colonies flow like inanimate fluids. In this sequence of films, we demonstrate how ants behave similarly to the spreading of drops, the capillary rise of menisci, and gravity-driven flow down a wall. By emulating the flow of fluids, ant colonies can remain united under stressful conditions.

  20. Biologically Inspired Vision for Indoor Robot Navigation

    OpenAIRE

    Saleiro, Mário; Tersic, K.; Lobato, D.; Rodrigues, J. M. F.; du Buf, J. M. H.

    2014-01-01

    Ultrasonic, infrared, laser and other sensors are being applied in robotics. Although combinations of these have allowed robots to navigate, they are only suited for specific scenarios, depending on their limitations. Recent advances in computer vision are turning cameras into useful low-cost sensors that can operate in most types of environments. Cameras enable robots to detect obstacles, recognize objects, obtain visual odometry, detect and recognize people and gestures, a...